FINAL DRAFT Chapter 9 IPCC WGII Sixth Assessment Report
1
2 Chapter 9: Africa
3
4 Coordinating Lead Authors: Christopher H. Trisos (South Africa), Ibidun O. Adelekan (Nigeria), Edmond
5 Totin (Benin).
6
7 Lead Authors: Ayansina Ayanlade (Nigeria), Jackson Efitre (Uganda), Adugna Gemeda (Ethiopia),
8 Kanungwe Kalaba (Zambia), Christopher Lennard (South Africa), Catherine Masao (Tanzania), Yunus
9 Mgaya (Tanzania), Grace Ngaruiya (Kenya), Daniel Olago (Kenya), Nicholas P. Simpson (Zimbabwe/South
10 Africa), Sumaya Zakieldeen (Sudan).
11
12 Contributing Authors: Philip Antwi-Agyei (Ghana), Aaron Atteridge (Sweden/Australia), Rachel Bezner
13 Kerr (Canada/USA), Max Callaghan (United Kingdom/Germany), Tamma Carleton (USA), Colin Carlson
14 (USA), Hayley Clements (South Africa), Declan Conway (United Kingdom), Sean Cooke (South Africa),
15 Matthew Chersich (South Africa), David Chiawo (Kenya), Joanne Clarke (Australian/United Kingdom),
16 Marlies Craig (South Africa), Olivier Crespo (South Africa), James Cullis (South Africa), Jampel
17 Dell'Angelo (Italy/USA), Luleka Dlamini (South Africa) Hussen Seid Endris (Kenya), Christien Engelbreht
18 (South Africa), Aidan Farrell (Trinidad and Tobago/Ireland), James Franke (USA), Thian Yew Gan
19 (Malaysia/Canada), Christopher Golden (USA), Kerry Grey (South Africa), Toshihiro Hasegawa (Japan),
20 Ryan Hogarth (Canada/United Kingdom), Nadia, Hassan O. Kaya (South Africa), Khalaf (United Kingdom),
21 Mercy Kinyua (Kenya), Scott Kulp (USA), William F. Lamb (United Kingdom/Germany), Charne Lavery
22 (South Africa), Johan Maritz (South Africa), Guy Midgley (South Africa), Danielle Millar (South Africa),
23 Jan Minx (Germany), Glenn Moncrieff (South Africa), Rachid Moussadek (Morocco), Mzime Ndebele-
24 Murisa (Zimbabwe), Emily Nicklin (South Africa), Michelle North (South Africa), Mary Nyasimi (Kenya),
25 Elizabeth Nyboer (Canada), Romaric Odoulami (Benin/South Africa), Andrew Okem (South
26 Africa/Nigeria), Gladys Okemwa (Kenya), Kulthoum Omari (Botswana/South Africa), Esther Onyango
27 (Kenya/Australia), Birgitt Ouweneel (Netherlands/South Africa), Indra 豽erland (Norway), Lorena,
28 Pasquini (South Africa), Belynda Petrie (South Africa), Alex Pigot (United Kingdom), Wilfried Pokam
29 (Cameroon), Bronwen Powell (Canada/USA), Jeff Price (United Kingdom), Heather Randell (USA), Maren
30 Radeny (Kenya), Jonathan Rawlins (South Africa), Kanta Kumari Rigaud (Malaysia/USA), Carla Roncoli
31 (USA), Olivia Rumble (South Africa), Elisa Sainz de Murieta (Spain), Georgia Savvidou (Sweden/Cyprus),
32 Lucia Schlemmer (South Africa), Laura Schmitt Olabisi (USA), Chandni Singh (India), Thomas Smucker
33 (USA), Nicola Stevens (South Africa), Anna Steynor (South Africa), Bamba Sylla (Rwanda/Senegal),
34 Arame Tall (Senegal/USA), Richard Taylor (Canada/United Kingdom), Meryem Tenarhte
35 (Morocco/Germany), Mia Thom (South Africa), Jessica Thorn (Namibia/South Africa), Katharina Waha
36 (Germany/Australia), Hitomi Wakatsuki (Japan), Edna Wangui (Kenya/USA), Portia Adade Williams
37 (Ghana), Kevin Winter (South Africa), Caradee Wright (South Africa), Luckson Zvobgo (Zimbabwe/South
38 Africa).
39
40 Review Editors: Stuart Mark Howden (Australia), Robert (Bob) J. Scholes (South Africa), Pius Yanda
41 (Tanzania).
42
43 Chapter Scientists: Michelle North (South Africa), Luckson Zvobgo (Zimbabwe/South Africa).
44
45 Date of Draft: 1 October 2021
46
47 Notes: TSU Compiled Version
48
49
50 Table of Contents
51
52 Executive Summary..........................................................................................................................................4
53 9.1 Introduction ............................................................................................................................................11
54 9.1.1 Point of Departure ........................................................................................................................11
55 9.1.2 Major Conclusions from Previous Assessments ...........................................................................12
56 9.1.3 What's New on Africa in AR6? .....................................................................................................13
57 9.1.4 Extent of Climate Change Impacts Across Africa.........................................................................13
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1 9.1.5 Extent of Climate Change Data and Research Gaps Across Africa .............................................14
2 9.1.6 Loss and Damage from Climate Change ......................................................................................17
3 9.2 Key Risks for Africa ...............................................................................................................................18
4 9.3 Climate Adaptation Options..................................................................................................................22
5 9.3.1 Adaptation Feasibility and Effectiveness......................................................................................22
6 9.3.2 Adaptation Co-Benefits and Trade-Offs with Mitigation and SDGs ............................................25
7 9.4 Climate Resilient Development .............................................................................................................26
8 9.4.1 Climate Finance............................................................................................................................26
9 9.4.2 Governance ...................................................................................................................................31
10 9.4.3 Cross-Sectoral and Transboundary Solutions ..............................................................................33
11 9.4.4 Climate Change Adaptation Law in Africa...................................................................................35
12 9.4.5 Climate Services, Perception and Literacy...................................................................................38
13 Box 9.1: Vulnerability Synthesis ...................................................................................................................43
14 9.5 Observed and Projected Climate Change ............................................................................................46
15 9.5.1 Climate Hazards in Africa ............................................................................................................46
16 9.5.2 North Africa ..................................................................................................................................51
17 9.5.3 West Africa....................................................................................................................................52
18 9.5.4 Central Africa ...............................................................................................................................53
19 9.5.5 East Africa.....................................................................................................................................54
20 9.5.6 Southern Africa .............................................................................................................................56
21 9.5.7 Tropical cyclones ..........................................................................................................................57
22 9.5.8 Glaciers.........................................................................................................................................57
23 9.5.9 Teleconnections and Large-Scale Drivers of African Climate Variability...................................57
24 9.5.10 African Marine Heatwaves ...........................................................................................................58
25 Box 9.2: Indigenous Knowledge and Local Knowledge ..............................................................................58
26 9.6 Ecosystems...............................................................................................................................................61
27 9.6.1 Observed Impacts of Climate Change on African Biodiversity and Ecosystem Services.............61
28 9.6.2 Projected Risks of Climate Change for African Biodiversity and Ecosystem Services ................64
29 9.6.3 Nature-Based Tourism in Africa ...................................................................................................69
30 9.6.4 Ecosystem-Based Adaptation in Africa.........................................................................................70
31 Box 9.3: Tree Planting in Africa....................................................................................................................72
32 9.7 Water .......................................................................................................................................................74
33 9.7.1 Observed Impacts from Climate Variability and Climate Change ...............................................74
34 Box 9.4: African Cities Facing Water Scarcity ............................................................................................75
35 9.7.2 Projected Risks and Vulnerability.................................................................................................76
36 9.7.3 Water Adaptation Options and their Feasibility...........................................................................79
37 Box 9.5: Water-Energy-Food Nexus .............................................................................................................79
38 9.8 Food Systems...........................................................................................................................................83
39 9.8.1 Vulnerability to Observed and Projected Impacts from Climate Change ....................................83
40 9.8.2 Observed Impacts and Projected Risks to Crops and Livestock...................................................85
41 9.8.3 Adapting to Climate Variability and Change ...............................................................................91
42 9.8.4 Climate Information Services and Insurance for Agriculture Adaptation....................................93
43 9.8.5 Marine and Inland Fisheries.........................................................................................................94
44 9.9 Human Settlements and Infrastructure ...............................................................................................97
45 9.9.1 Urbanisation, Population and Development Trends ....................................................................97
46 9.9.2 Observed Impacts on Human Settlements and Infrastructure ......................................................98
47 9.9.3 Observed Vulnerabilities of Human Settlements to Climate Risks .............................................101
48 9.9.4 Projected Risks for Human Settlements and Infrastructure........................................................101
49 9.9.5 Adaptation in Human Settlements and for Infrastructure...........................................................109
50 9.10 Health.....................................................................................................................................................112
51 9.10.1 The Influence of Social Determinants of Health on the Impacts of Climate Change .................112
52 9.10.2 Observed Impacts and Projected Risks.......................................................................................113
53 Box 9.6: Pandemic Risk in Africa: COVID-19 and Future Threats........................................................116
54 Box 9.7: The Health-Climate Change Nexus in Africa .............................................................................123
55 9.10.3 Adaptation for Health and Well-Being in Africa ........................................................................124
56 9.11 Economy, Poverty and Livelihoods.....................................................................................................130
57 9.11.1 Observed Impacts of Climate Change on African Economies and Livelihoods .........................130
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1 9.11.2 Projected Risks of Climate Change for African economies and livelihoods ..............................132
2 9.11.3 Informality...................................................................................................................................132
3 9.11.4 Climate Change Adaptation to Reduce Vulnerability, Poverty and Inequality ..........................133
4 Box 9.8: Climate Change, Migration and Displacement in Africa ..........................................................136
5 9.11.5 COVID-19 Recovery Stimulus Packages for Climate Action .....................................................140
6 Box 9.9: Climate Change and Security: Interpersonal Violence and Large-scale Civil Conflict .........141
7 9.12 Heritage .................................................................................................................................................142
8 9.12.1 Observed Impacts on Cultural Heritage.....................................................................................142
9 9.12.2 Projected Risks............................................................................................................................143
10 9.12.3 Adaptation...................................................................................................................................144
11 FAQ 9.1: Which climate hazards impact African livelihoods, economies, health and well-being the
12 most? ......................................................................................................................................................147
13 FAQ9.2: What are the limits and benefits of climate change adaptation in Africa? .............................148
14 FAQ 9.3: How can African countries secure enough food in changing climate conditions for their
15 growing populations? ...........................................................................................................................149
16 FAQ9.4: How can African local knowledge serve climate adaptation planning more effectively? ......150
17 References......................................................................................................................................................151
18
19
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FINAL DRAFT Chapter 9 IPCC WGII Sixth Assessment Report
1 Executive Summary
2
3 Overall Key Messages
4
5 Africa has contributed among the least to greenhouse gas emissions, yet key development sectors have
6 already experienced widespread loss and damage attributable to anthropogenic climate change,
7 including biodiversity loss, water shortages, reduced food production, loss of lives and reduced
8 economic growth (high confidence1). {9.1.1, 9.2, 9.6.1, 9.8.2, 9.10.2, 9.11.1; Box 9.4}
9
10 Between 1.5癈 and 2癈 global warming--assuming localised and incremental adaptation--impacts
11 are projected to become widespread and severe for reduced food production, reduced economic
12 growth, increased inequality and poverty, biodiversity loss, increased human morbidity and mortality
13 (high confidence). Limiting global warming to 1.5癈 is expected to substantially reduce damages to
14 African economies and ecosystems (high confidence). {9.2, 9.6.2, 9.8.2, 9.8.5, 9.10.2, 9.11.2}
15
16 Exposure and vulnerability to climate change in Africa are multi-dimensional with socioeconomic,
17 political and environmental factors intersecting (very high confidence). Africans are disproportionately
18 employed in climate-exposed sectors: 55�62% of the sub-Saharan workforce employed is in agriculture and
19 95% of cropland rainfed. In rural Africa, poor and female-headed households face greater livelihood risks
20 from climate hazards. In urban areas, growing informal settlements without basic services increases the
21 vulnerability of large populations to climate hazards, especially women, children and the elderly. {9.8.2,
22 9.9.1, 9.9.3, 9.11.4; Box 9.1}
23
24 Adaptation in Africa has multiple benefits, and most assessed adaptation options have medium
25 effectiveness at reducing risks for present-day global warming, but their efficacy at future warming
26 levels is largely unknown (high confidence). {9.3, 9.6.4, 9.8.3, 9.11.4}
27
28 Enabling Climate-Resilient Development
29
30 Climate-related research in Africa faces severe data constraints, as well as inequities in funding and
31 research leadership that reduce adaptive capacity (very high confidence). Many countries lack regularly
32 reporting weather stations, and data access is often limited. From 1990�2019 research on Africa received just
33 3.8% of climate-related research funding globally: 78% of this funding went to EU and North American
34 institutions and only 14.5% to African institutions. The number of climate research publications with locally-
35 based authors are among the lowest globally and research led by external researchers may focus less on local
36 priorities. Increased funding for African partners, and direct control of research design and resources can
37 provide more actionable insights on climate risks and adaptation options in Africa. {9.1, 9.4.5, 9.5.2}
38
39 Adaptation generally is cost effective, but annual finance flows targeting adaptation for Africa are
40 billions of USD less than the lowest adaptation cost estimates for near-term climate change (high
41 confidence). Finance has not targeted more vulnerable countries. From 2014�2018 more finance
42 commitments were debt than grants and--excluding multilateral development banks--only 46% of
43 commitments were disbursed (compared to 96% for other development projects). {9.4.1}
44
45 Adaptation costs will rise rapidly with global warming (very high confidence). Increasing public and
46 private finance flows by billions of dollars per year, increasing direct access to multilateral funds,
47 strengthening project pipeline development, and shifting finance from readiness activities to project
48 implementation would help realise transformative adaptation in Africa (high confidence). Concessional
49 finance will be required for adaptation in low-income settings. Aligning sovereign debt relief with climate
50 goals could increase finance by redirecting debt-servicing payments to climate resilience. {9.4.1}
51
1
In this Report, the following summary terms are used to describe the available evidence: limited, medium, or robust;
and for the degree of agreement: low, medium, or high. A level of confidence is expressed using five qualifiers: very
low, low, medium, high, and very high, and typeset in italics, e.g., medium confidence. For a given evidence and
agreement statement, different confidence levels can be assigned, but increasing levels of evidence and degrees of
agreement are correlated with increasing confidence.
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FINAL DRAFT Chapter 9 IPCC WGII Sixth Assessment Report
1 Governance for climate resilient development includes: long-term planning, all-of-government
2 approaches, transboundary cooperation and benefit-sharing, development pathways that increase
3 adaptation and mitigation and reduce inequality, and NDC implementation (high confidence). {9.3.2,
4 9.4.2, 9.4.3}
5
6 Cross-sectoral `nexus' approaches provide significant opportunities for large co-benefits and/or
7 avoided damages (very high confidence). For example, climate change adaptation benefits pandemic
8 preparedness; `One Health' approaches benefit human and ecosystem health; and Ecosystem-based
9 Adaptation can deliver adaptation and emissions mitigation (high confidence). {9.4.3, 9.6.4, 9.11.5; Box 9.6}
10
11 Without cross-sectoral, transboundary and long-term planning, response options in one sector can
12 become response risks, exacerbating impacts in other sectors and causing maladaptation (very high
13 confidence). For example, maintaining indigenous forest benefits biodiversity and emissions mitigation, but
14 afforestation--or wrongly targeting ancient grasslands and savannas for reforestation--harms water security
15 and biodiversity, and can increase carbon loss to fire and drought. Planned hydropower projects may
16 increase risk as rainfall changes impact water, energy and food security exacerbating trade-offs between
17 users, including across countries. {9.4.3; Boxes 9.3, 9.5}
18
19 Robust legislative frameworks that develop or amend laws to mainstream climate change into their
20 empowerment and planning provisions will facilitate effective design and implementation of climate
21 change responses (high confidence). {9.4.4}
22
23 Climate information services that are demand-driven and context-specific (e.g., for agriculture or
24 health) combined with climate change literacy can affect the difference between coping and informed,
25 adaptation responses (high confidence). Across 33 African countries, 23�66% of people are aware of
26 anthropogenic climate change--with larger variation at subnational scales (e.g., 5�71% among states in
27 Nigeria). Climate change literacy increases with education level but is undermined by poverty, and rates
28 average 12.8% lower for women than men. 71% of Africans aware of climate change agree it should be
29 stopped. Production of salient climate information in Africa is hindered by limited availability of and access
30 to weather and climate data. {9.4.5, 9.5.1, 9.8.4, 9.10.3}
31
32 Ecosystem-based adaptation can reduce climate risk while providing social, economic and
33 environmental benefits (high confidence). Direct human dependence on ecosystem services in Africa is
34 high. Ecosystem protection and restoration, conservation agriculture practices, sustainable land management,
35 and integrated catchment management can support climate resilience. Ecosystem-based adaptation can cost
36 less than grey infrastructure in human settlements (e.g., using wetlands and mangroves as coastal protection).
37 {9.6.4, 9.7.3, 9.8.3, 9.9.5, 9.12.3; Box 9.7}
38
39 Observed Impacts and Projected Risks
40
41 Climate
42 Increasing mean and extreme temperature trends across Africa are attributable to human-induced
43 climate change (high confidence). {9.5.1, 9.5.2}
44
45 Climate change has increased heat waves (high confidence) and drought (medium confidence) on land,
46 and doubled the probability of marine heatwaves around most of Africa (high confidence). Multi-year
47 droughts have become more frequent in West Africa, and the 2015�2017 Cape Town drought was three
48 times more likely2 due to human-induced climate change. {9.5.3�7, 9.5.10}
49
2
In this Report, the following terms have been used to indicate the assessed likelihood of an outcome or a result:
Virtually certain 99�100% probability, Very likely 90�100%, Likely 66�100%, About as likely as not 33�66%,
Unlikely 0�33%, Very unlikely 0�10%, and Exceptionally unlikely 0�1%. Additional terms (Extremely likely: 95�
100%, More likely than not >50�100%, and Extremely unlikely 0�5%) may also be used when appropriate. Assessed
likelihood is typeset in italics, e.g., very likely). This Report also uses the term `likely range' to indicate that the assessed
likelihood of an outcome lies within the 17-83% probability range.
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FINAL DRAFT Chapter 9 IPCC WGII Sixth Assessment Report
1 Above 2癈 global warming, meteorological drought frequency will increase and duration will double
2 from 2 to 4 months over North Africa, the western Sahel and southern Africa (medium confidence).
3 {9.5.2, 9.5.3, 9.5.6.}
4
5 Frequency and intensity of heavy rainfall events will increase at all levels of global warming (except in
6 North and southwestern Africa), increasing exposure to pluvial and riverine flooding (high confidence).
7 {9.5.3�7, 9.7}
8
9 Glaciers on the Rwenzoris and Mt. Kenya are projected to disappear by 2030, and by 2040 on
10 Kilimanjaro (medium confidence). {9.5.8}
11
12 In East and southern Africa, tropical cyclones making landfall are projected to become less frequent
13 but have more intense rainfall and higher wind speeds at increasing global warming (medium
14 confidence). {9.5.7}
15
16 Heat waves on land, in lakes, and in the ocean will increase considerably in magnitude and duration
17 with increasing global warming (very high confidence). Under a 1.5癈-compatible scenario, children born
18 in Africa in 2020 are likely to be exposed to 4�8 times more heat waves compared to people born in 1960,
19 increasing to 5�10 times for 2.4癈 global warming. The annual number of days above potentially lethal heat
20 thresholds reaches 50�150 in west Africa at 1.6癈 global warming, 100�150 in Central Africa at 2.5癈, and
21 200�300 over tropical Africa for >4癈. {9.5.2, 9.5.3, 9.5.4, 9.5.5, 9.5.6, 9.7.2.1}
22
23 Most African countries will enter unprecedented high temperature climates earlier in this century
24 than generally wealthier, higher latitude countries, emphasising the urgency of adaptation measures in
25 Africa (high confidence). {9.5.1}
26
27 Compound risks
28 Multiple African countries are projected to face compounding risks from: reduced food production
29 across crops, livestock and fisheries; increasing heat-related mortality; heat-related loss of labour
30 productivity; and flooding from sea level rise, especially in West Africa (high confidence). {9.8.2, 9.8.5,
31 9.9.4, 9.10.2, 9.11.2}
32
33 Water
34 Recent extreme variability in rainfall and river discharge (c. -50% to +50% relative to long-term
35 historical means) across Africa have had largely negative and multi-sector impacts across water-
36 dependent sectors (high confidence) {9.7.2, 9.10.2}. Hydrological variability and water scarcity have
37 induced cascading impacts from water-supply provision and/or hydro-electric power production to health,
38 economies, tourism, food, disaster risk response capacity and increased inequality of water access. {Box 9.4}
39
40 Extreme hydrological variability is projected to progressively amplify under all climate scenarios
41 relative to the current baseline, depending on region (high confidence). Projections of numbers of people
42 exposed to water stress by the 2050s vary widely--decreases/increases by hundreds of millions, with higher
43 numbers for increases--with disagreement among global climate models the major factor driving these large
44 ranges. Populations in drylands are projected to more than double. Projected changes present heightened
45 cross-cutting risks to water-dependent sectors, and require planning under deep uncertainty for the wide
46 range of extremes expected in future. {9.7.1, 9.7.2}
47
48 Economy and Livelihoods
49 Climate change has reduced economic growth across Africa, increasing income inequality between
50 African countries and those in temperate, Northern Hemisphere climates (high confidence). One
51 estimate suggests GDP per capita for 1991�2010 in Africa was on average 13.6% lower compared to if
52 climate change had not occurred. Impacts manifest largely through losses in agriculture, as well as tourism,
53 manufacturing, and infrastructure. {9.6.3, 9.11.1}
54
55 Climate variability and change undermine educational attainment (high agreement, medium evidence).
56 High temperatures, low rainfall, and flooding, especially in the growing season, may mean children are
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FINAL DRAFT Chapter 9 IPCC WGII Sixth Assessment Report
1 removed from school to assist income generation. Early life undernutrition associated with low harvests can
2 impair cognitive development. {9.11.1.2}
3
4 Limiting global warming to 1.5癈 is very likely to positively impact GDP per capita across Africa.
5 Increasing economic damage forecasts under high-emissions diverge from low-emissions pathways by 2030.
6 Inequalities between African countries are projected to widen with increased warming. Across nearly all
7 African countries, GDP per capita is projected to be at least 5% higher by 2050 and 10�20% higher by 2100
8 if global warming is held to 1.5癈 versus 2癈. {9.11.2}
9
10 Food systems
11 In Africa, climate change is reducing crop yields and productivity (medium confidence). Agricultural
12 productivity growth has been reduced by 34% since 1961 due to climate change, more than any other region.
13 Maize and wheat yields decreased on average 5.8% and 2.3%, respectively in sub-Saharan Africa due to
14 climate change in the period 1974�2008. Farmers and pastoralists perceive the climate to have changed and
15 over two thirds of Africans perceive climate conditions for agricultural production have worsened over the
16 past ten years. Woody plant encroachment has reduced fodder availability. {9.4.5, 9.6.1, 9.8.2}
17
18 Future warming will negatively affect food systems in Africa by shortening growing seasons and
19 increasing water stress (high confidence). By 1.5癈 global warming, yields are projected to decline for
20 olives (North Africa) and Sorghum (West Africa) with a decline in suitable areas for coffee and tea (East
21 Africa). Although yield declines for some crops may be partially compensated by increasing atmospheric
22 CO2 concentrations, global warming above 2癈 will result in yield reductions for staple crops across most of
23 Africa compared to 2005 yields (e.g., 20�40% decline in West African maize yields), even when considering
24 adaptation options and increasing CO2 (medium confidence). Relative to 1986�2005, global warming of 3癈
25 is projected to reduce labour capacity in agriculture by 30�50% in sub-Saharan Africa. {9.8.2}
26
27 Climate change threatens livestock production across Africa (high agreement, low evidence). Rangeland
28 net primary productivity is projected to decline 42% for west Africa by 2050 at 2oC global warming. Vector-
29 borne livestock diseases and the duration of severe heat stress are both projected to become more prevalent
30 under warming. {9.8.2}
31
32 Climate change poses a significant threat to African marine and freshwater fisheries (high confidence).
33 Fisheries provide the main source of protein for ~30% of Africa's population and support the livelihoods of
34 12.3 million people. At 1.5癈 global warming, marine fish catch potential (MFCP) decreases 3�41% by
35 2081�2100 relative to 1986�2005, increasing to 12�69% at 4.3癈, with the highest declines for tropical
36 countries. Under 1.7癈 global warming, reduced fish harvests could leave 1.2�70 million people vulnerable
37 to iron deficiencies, up to 188 million for vitamin A deficiencies, and 285 million for vitamin B12 and
38 omega-3 fatty acids by mid-century. For inland fisheries, 55�68% of commercially harvested fish species are
39 vulnerable to extinction under 2.5癈 global warming by 2071�2100. {9.8.5}
40
41 Health
42 Climate variability and change already impacts the health of tens of millions of Africans through
43 exposure to non-optimal temperatures and extreme weather, and increased range and transmission of
44 infectious diseases (high confidence). {9.10.1}
45
46 Mortality and morbidity will escalate with further global warming, placing additional strain on health
47 and economic systems (high confidence). At 1.5癈 of global warming, distribution and seasonal
48 transmission of vector-borne diseases is expected to increase, exposing tens of millions more people, mostly
49 in East and Southern Africa (high confidence). Above 1.5癈 risk of heat-related deaths rises sharply (high
50 confidence), with at least 15 additional deaths per 100,000 annually across large parts of Africa. At 2.1癈
51 degrees, thousands to tens of thousands of additional cases of diarrhoeal disease are projected, mainly in
52 Central and East Africa (medium confidence). These changes risk undermining improvements in health from
53 future socio-economic development (high agreement, medium evidence).{9.10.2}
54
55 Human Settlements
56 Exposure of people, assets and infrastructure to climate hazards is increasing in Africa with rapid
57 urbanisation, infrastructure deficit, and growing population in informal settlements (high confidence).
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1 About one-third of African cities with populations over 300,000 are located in areas that are at high risk from
2 climate hazards. Sub-Saharan Africa is the only region that has recorded increasing rates of flood mortality
3 since the 1990s. {9.9.1, 9.9.2}
4
5 High population growth and urbanisation in low-elevation coastal zones will be a major driver of
6 exposure to sea level rise in the next 50 years (high confidence). By 2030, 108�116 million people in
7 Africa will be exposed to sea level rise in Africa (compared to 54 million in 2000), increasing to 190�245
8 million by 2060. {9.9.1, 9.9.4}
9
10 Africa's rapidly growing cities will be hotspots of risks from climate change and climate-induced in-
11 migration, which could amplify pre-existing stresses related to poverty, informality, exclusion and
12 governance (high confidence). Urban population exposure to extreme heat is projected to increase from 2
13 billion person-days per year in 1985�2005 to 45 billion person-days by the 2060s (1.7 global warming
14 with low population growth) and to 95 billion person-days (2.8 global warming with medium-high
15 population growth), with greatest exposure in West Africa. Sensitive populations under 5 and over 64 years
16 old in African cities exposed to heat waves are projected to increase from around 27 million in 2010 to 360
17 million (SSP1) and 440 million (SSP5) by 2100, for global warming of 1.8 and >4, respectively.
18 Compared to 2000, urbanization is projected to increase urban land extent exposed to arid conditions by
19 around 700% and exposure to high-frequency flooding by 2,600% across West, Central and East Africa by
20 2030. {9.9.1, 9.9.2, 9.9.4; Box 9.8}
21
22 Migration
23 Most climate-related migration observed currently is within countries or between neighbouring
24 countries, rather than to distant high-income countries (high confidence). Urbanisation has increased
25 when rural livelihoods were negatively impacted by low rainfall. Over 2.6 million and 3.4 million new
26 weather-related displacements occurred in sub-Saharan Africa in 2018 and 2019. {Box 9.8}
27
28 Climate change is projected to increase migration, especially internal and rural-to-urban migration
29 (high agreement, medium evidence). With 1.7癈 global warming by 2050, 17�40 million people could
30 migrate internally in sub-Saharan Africa, increasing to 56�86 million for 2.5癈 (>60% in West Africa) due
31 to water stress, reduced crop productivity, and sea level rise. This is a lower-bound estimate excluding rapid-
32 onset hazards such as floods and tropical cyclones. {Box 9.8}
33
34 Infrastructure
35 Climate-related infrastructure damage and repairs will be a financially significant burden to countries
36 (high confidence). Without adaptation, aggregate damages from sea level rise and coastal extremes to 12
37 major African coastal cities in 2050 under medium and high emissions scenarios will be USD 65 billion and
38 USD 86.5 billion, respectively. Potential costs of up to USD 183.6 billion may be incurred through 2100 to
39 maintain existing road networks damaged from temperature and precipitation changes due to climate change.
40 Increased rainfall variability is expected to affect electricity prices in countries highly dependent on
41 hydropower. {9.9.4; Boxes 9.4, 9.5}
42
43 Ecosystems
44 Increasing CO2 levels and climate change are destroying marine biodiversity, reducing lake
45 productivity, and changing animal and vegetation distributions (high confidence). Impacts include
46 repeated mass coral bleaching events in east Africa, and uphill (birds) or poleward (marine species) shifts in
47 geographic distributions. For vegetation, the overall observed trend is woody plant expansion, particularly
48 into grasslands and savannas, reducing grazing land and water supplies. {9.6.1}
49
50 The outcome of interacting drivers operating in opposing directions on future biome distributions is
51 highly uncertain. Further increasing CO2 concentrations could increase woody plant cover, but increasing
52 aridity could counteract this, destabilising forest and peatland carbon stores in central Africa (low
53 confidence). {9.6.2.1}
54
55 African biodiversity loss is projected to be widespread and escalating with every 0.5篊 increase above
56 present-day global warming (high confidence). Above 1.5癈, half of assessed species are projected to lose
57 over 30% of their population or area of suitable habitat. At 2癈, 36% of freshwater fish species are
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1 vulnerable to local extinction, 7�18% of species assessed are at risk of extinction, and over 90% of East
2 African coral reefs could be destroyed by bleaching. Above 2癈, risk of sudden and severe biodiversity
3 losses becomes widespread in West, Central and East Africa. Climate change is also projected to change
4 patterns of invasive species spread. {9.6.2}
5
6 Climate security
7 There is increasing evidence linking increased temperatures and drought to conflict risk in Africa
8 (high confidence). Agriculturally dependent and politically excluded groups are especially vulnerable to
9 drought-associated conflict risk. However, climate is one of many interacting risk factors, and may explain a
10 small share of total variation in conflict incidence. Ameliorating ethnic tensions, strengthening political
11 institutions, and investing in economic diversification could mitigate future impacts of climate change on
12 conflict. {Box 9.9}
13
14 Heritage
15 African cultural heritage is already at risk from climate hazards, including sea level rise and coastal
16 erosion. Most African heritage sites are neither prepared for, nor adapted to, future climate change
17 (high confidence). {9.12}
18
19 Adaptation
20
21 With global warming increasing above present-day levels the ability of adaptation responses to offset
22 risk is substantially reduced (high confidence). Crop yield losses, even after adaptation, are projected to
23 rise rapidly above 2癈 global warming. Limits to adaptation are already being reached in coral reef
24 ecosystems. Immigration of species from elsewhere may partly compensate for local extinctions and/or lead
25 to local biodiversity gains in some regions. However, more African regions face net losses than net gains. At
26 1.5癈 global warming, over 46% of localities face net losses in terrestrial vertebrate species richness with net
27 increases projected for under 15% of localities. {9.6.1.4, 9.6.2.2, 9.8.2.1, 9.8.2.2, 9.8.4}
28
29 Technological, institutional, and financing factors are major barriers to climate adaptation feasibility
30 in Africa (high confidence). {9.3, 9.4.1}
31
32 There is limited evidence for economic growth alone reducing climate damages, but under scenarios of
33 inclusive and sustainable development, millions fewer people in Africa will be pushed into extreme
34 poverty by climate change and negative impacts to health and livelihoods can be reduced by 2030
35 (medium confidence). {9.10.3, 9.11.4}
36
37 Gender-sensitive and equity-based adaptation approaches reduce vulnerability for marginalised
38 groups across multiple sectors in Africa, including water, health, food systems and livelihoods (high
39 confidence). {9.7.3, 9.8.3, 9.9.5, 9.10.3, 9.11.4; Boxes 9.1, 9.2}
40
41 Integrating climate adaptation into social protection programs, such as cash transfers, public works
42 programmes and healthcare access, can increase resilience to climate change (high confidence).
43 Nevertheless, social protection programs may increase resilience to climate-related shocks, even if they do
44 not specifically address climate risks. {9.4.2, 9.10.3, 9.11.4}
45
46 The diversity of African indigenous knowledge and local knowledge systems provide a rich foundation
47 for adaptation actions at local scales (high confidence). African indigenous knowledge systems are
48 exceptionally rich in ecosystem-specific knowledge used for management of climate variability. Integration
49 of indigenous knowledge systems within legal frameworks, and promotion of indigenous land tenure rights
50 can reduce vulnerability. {9.4.4; Box 9.1, Box 9.2}
51
52 Early warning systems based on targeted climate services can be effective for disaster risk reduction,
53 social protection programmes, and managing risks to health and food systems (e.g., vector-borne
54 disease and crops) (high confidence). {9.4.5, 9.5.1, Box 9.2, 9.8.4, 9.8.5, 9.10.3, 9.11.4}
55
56 Risk-sensitive infrastructure delivery and equitable provision of basic services can reduce climate
57 risks and provide net financial savings (high confidence). However, there is limited evidence of pro-active
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1 climate adaptation in African cities. Proactive adaptation policy could reduce road repair and maintenance
2 costs by 74% compared to a reactive policy. Adapting roads for increased temperatures and investment in
3 public transport are assessed as `no regret' options. In contrast, hydropower development carries risk of
4 regrets due to damages when a different climate than was expected materializes. Energy costs for cooling
5 demands are projected to accumulate to USD 51.3 billion in 2035 at 2 global warming and to USD 486.5
6 billion in 2076 at 4. {9.8.5}
7
8 Reduced drought and flood risk, and improved water and sanitation access, can be delivered by:
9 water-sensitive and climate scenario planning, monitored groundwater use, waterless on-site
10 sanitation, rainwater harvesting and water reuse, reducing risk to human settlements, food systems,
11 economies, and human health (high confidence). {9.8, 9.9, 9.10, 9.11}
12
13 Water sector adaptation measures show medium social and economic feasibility but low feasibility for
14 most African cities due to technical and institutional restrictions, particularly for large supply dams
15 and centralised distribution systems (medium confidence). {9.3.1, 9.7.3} Use of integrated water
16 management, water supply augmentation, and establishment of decentralised water management systems can
17 reduce risk. Integrated water management measures including sub-national financing, demand management
18 through subsidies, rates and taxes, and sustainable water technologies can reduce water insecurity caused by
19 either drought or floods (medium confidence). {9.7.3; Box 9.4}
20
21 Agricultural and livelihood diversification, agroecological and conservation agriculture practices,
22 aquaculture, on-farm engineering, and agroforestry can increase resilience and sustainability of food
23 systems in Africa under climate change (medium confidence). However, smallholder farmers tend to
24 address short-term shocks or stresses by deploying coping responses rather than transformative adaptations.
25 Climate information services, institutional capacity building, and strategic financial investment can help
26 overcome these barriers to adaptation (medium confidence). {9.4.5, 9.8.3, 9.8.5}
27
28 African countries and communities are inadequately insured against climate risk, but innovative
29 index-based insurance schemes can help transfer risk and aid recovery, including in food systems
30 (medium confidence). Despite their potential, uptake of climate insurance products remains constrained by
31 lack of affordability, awareness and product diversity. {9.4.5, 9.8.4, 9.11.4.1}
32
33 Human migration is a potentially effective adaptation strategy across food systems, water, livelihoods
34 and in climate-induced conflict areas, but can also be maladaptive if vulnerability is increased,
35 particularly for health and human settlements (high confidence). Migration of men from rural areas can
36 aggravate the work burden faced by women. The more agency migrants have (that is, degree of voluntarity
37 and freedom of movement) the greater the potential benefits for sending and receiving areas (high
38 agreement, medium evidence).{9.3, 9.8.3, 9.9.1�3, 9.10.2.2.2; Boxes 9.8, 9.9; Cross-Chapter Box MIGRATE
39 in Chapter 7}
40
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1 9.1 Introduction
2
3 9.1.1 Point of Departure
4
5 This chapter assesses the scientific evidence on observed and projected climate change impacts, vulnerability
6 and adaptation options in Africa. The assessment refers to five African sub-regions � North, West, Central,
7 East and southern � closely following the African Union (AU), but including Mauritania in West Africa and
8 Sudan in North Africa because much of the literature assessed places these countries in these regions (Figure
9 9.1). Madagascar and other island states are addressed in Chapter 15.
10
11 Africa has contributed among the least to historical greenhouse gas emissions (GHG) responsible for
12 anthropogenic climate change and has the lowest per capita GHG emissions of all regions currently (high
13 confidence) (Figure 9.2). Yet Africa has already experienced widespread impacts from anthropogenic
14 climate change (high confidence) (Table 9.1; Figure 9.2).
15
16
17
18 Figure 9.1: The 5 Regions of Africa used in this chapter, also showing estimated population density in 2019. The
19 population of Africa was estimated at 1.312 billion for 2020, which is about 17% of the world population but this is
20 projected to grow to around 40% of world population by 2100 (UNDESA, 2019a). Although 57% of the African
21 population currently live in rural areas (43% urban), Africa is the most rapidly urbanising region globally and is
22 projected to transition to a majority urban population in the 2030s with a 60% urban population by 2050 (UNDESA,
23 2019b). The 2019 Gross Domestic Product (GDP) per capita in constant 2010 averaged USD 2,250 across 43 countries
24 reporting data, ranging from USD 202 (Burundi) to USD 8,840 (Gabon), with 40% of the population of sub-Saharan
25 Africa living below the international poverty line of USD 1,90 per day in 2018 (World Bank, 2018). The highest life
26 expectancy at birth is 67 (Botswana and Senegal) and the lowest is 52 (Central African Republic) (World Bank, 2018).
27 Grid-cell population density data for mapping are from (Tatem, 2017; WorldPop, 2021).
28
29
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1
2 Figure 9.2: Historical greenhouse gas (GHG) emission trends for Africa compared to other world regions: (a) Per
3 person GHG emissions by region and growth from 1990-2018 (circles represent countries, diamonds represent the
4 region average). (b) Total GHG emissions by region since 1990. (c) The total GHG emissions in 1990 and 2018 for the
5 15 highest emitting countries within Africa. (d) Total emissions in Africa since 1990, broken down by GHG (left) and
6 sector (right). Methane and CO2 emissions comprise an almost equal share of greenhouse gas emissions in Africa, with
7 the largest emissions sectors being energy and agriculture (Crippa et al., 2021). Agriculture emissions in panel (d) do
8 not include land use, land use change and forestry (LULUCF CO2). One-hundred-year global warming potentials
9 consistent with WGI estimates are used. Emissions data are from (Crippa et al., 2021), compiled by Chapter 2 of
10 WGIII.
11
12
13 Since AR5, there have been notable policy changes in Africa and globally. The Paris Agreement, 2030
14 Sustainable Development Goals (SDGs), the Sendai Framework and Agenda 2063 emphasise interlinked
15 aims to protect the planet, reduce disaster risk, end poverty and ensure all people enjoy peace and prosperity
16 (AU, 2015; UNFCCC Paris Agreement, 2015; UNISDR Sendai Framework, 2015; United Nations General
17 Assembly, 2015). To match these interlinked ambitions, this chapter assesses risks and response options both
18 for individual sectors and cross-sectorally to assess how risks can compound and cascade across sectors, as
19 well as the potential feasibility and effectiveness, co-benefits and trade-offs and potential for maladaptation
20 from response options (Simpson et al., 2021b; Williams et al., 2021).
21
22 9.1.2 Major Conclusions from Previous Assessments
23
24 Based on an analysis of 1,022 mentions of Africa or African countries across the three AR6 Special Reports,
25 the following main conclusions emerged.
26
27 � Hot days, hot nights and heatwaves have become more frequent; heatwaves have also become longer
28 (high confidence). Drying is projected particularly for West and southwestern Africa (high confidence)
29 (IPCC, 2018c; Shukla et al., 2019).
30 � Climate change is contributing to land degradation, loss of biodiversity, bush encroachment and spread
31 of pests and invasive species (SR1.5, SRCCL, SROCC).
32 � Climate change has already reduced food security through losses in crop yields, rangelands, livestock
33 and fisheries, deterioration in food nutritional quality, access and distribution and price spikes. Risks to
34 crop yields are substantially less at 1.5 compared with 2 of global warming, with a large reduction
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1 in maize cropping areas projected even for 1.5, as well as reduced fisheries catch potential (SR1.5,
2 SRCCL, SROCC).
3 � Increased deaths from undernutrition, malaria, diarrhoea, heat stress and diseases related to exposure to
4 dust, fire smoke and other air pollutants are projected from further warming (IPCC, 2018c; Shukla et al.,
5 2019).
6 � The largest reductions in economic growth for an increase from 1.5 to 2 of global warming are
7 projected for low- and middle-income countries, including in Africa (IPCC, 2018c).
8 � Climate change interacts with multidimensional poverty, among other vulnerabilities. Africa is projected
9 to bear an increasing proportion of the global exposed and vulnerable population at 2 and 3 of
10 global warming (IPCC, 2018c).
11 � Poverty and limited financing continue to undermine adaptive capacity, particularly in rapidly growing
12 African cities (Shukla et al., 2019).
13 � Large-scale afforestation and bioenergy can reduce food availability and ecosystem health (IPCC,
14 2018c) (SRCCL 2019).
15 � Transitioning to renewable energy would reduce reliance on wood fuel and charcoal, especially in urban
16 areas, with co-benefits including reduced deforestation, desertification, fire risk and improved indoor air
17 quality, local development and agricultural yield (Shukla et al., 2019).
18 � Sustainable use of biodiversity, conservation agriculture, reduced deforestation, land and watershed
19 restoration, rainwater harvesting and well-planned reforestation can have multiple benefits for adaptation
20 and mitigation, including water security, food security, biodiversity, soil conservation and local surface
21 cooling (IPBES, 2018; Shukla et al., 2019).
22 � Climate resilience can be enhanced through improvements to early warning systems, insurance,
23 investment in safety nets, secure land tenure, transport infrastructure, communication, access to
24 information and investments in education and strengthened local governance (Shukla et al., 2019).
25 � Scenarios of socio-environmental change are underused in decision-making in Africa (IPBES, 2018).
26 � Africa's rich biodiversity together with a wealth of indigenous knowledge and local knowledge is a key
27 strategic asset for sustainable development (IPBES, 2018).
28
29 9.1.3 What's New on Africa in AR6?
30
31 1. Increased confidence in observed and projected changes in climate hazards, including heat and
32 precipitation.
33 2. Increased regional, national and sub-national observed impacts and projected risks.
34 3. Loss and damage assessment.
35 4. Increased quantification of projected risks at 1.5, 2, 3 and 4 of global warming (Section
36 9.2; Figure 9.6).
37 5. Improved assessment of sea level rise risk (Sections 9.9 and 9.12).
38 6. Increased quantification of risk across all sectors assessed.
39 7. Expanded assessment of adaptation feasibility and effectiveness and limits to adaptation (Figure
40 9.7).
41 8. Assessment of adaptation finance (Section 9.4.1).
42 9. Increased assessment of how climate risk and adaptation and mitigation response options are
43 interlinked across multiple key development sectors (Section 9.4.3; Boxes 9.4 and 9.5).
44
45 9.1.4 Extent of Climate Change Impacts Across Africa
46
47 In many parts of southern, East and West Africa, temperature or precipitation trends since the 1950s are
48 attributable to anthropogenic climate change and several studies document the impacts of these climate
49 trends on human and natural systems (high confidence) (Figure 9.3; Sections 9.5.6 and 9.5.7). Nevertheless,
50 research into attribution of trends to anthropogenic climate change or climate impacts remains scarce for
51 multiple regions, especially in North and Central Africa. This illustrates an `attribution gap' where robust
52 evidence for attributable impacts is twice as prevalent in high compared to low-income countries globally
53 (Callaghan et al., 2021). Most studies on climate impacts in Africa have focused on terrestrial ecosystems or
54 water, with fewer on marine ecosystems, agriculture, migration and health and well-being (Callaghan et al.,
55 2021). Specific factors driving these knowledge gaps include limited data collection, data access and
56 research funding for African researchers (see next section).
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1
2
3
4 Figure 9.3: Climate impacts on human and natural systems are widespread across Africa, as are climate trends
5 attributable to human-induced climate change. This machine-learning-assisted evidence map shows the presence of
6 historical trends in temperature and precipitation attributable to human-induced climate change (pinks vs. greys) and the
7 amount of evidence (intensity of colours) documenting the impacts of these climate trends on human and natural
8 systems (e.g., ecosystems, agriculture, health) across Africa. `Robust' indicates more than 5 studies document impacts
9 per grid cell. A `high' amount of evidence indicates more than 20 studies documented impacts for a grid cell. Climate
10 impact studies from the literature were identified and categorised using machine learning. A language representation
11 model was trained on a set of 2,373 climate impact studies coded by hand. This supervised machine learning model
12 identified 102,160 published studies predicted to be relevant for climate impacts globally; references to places in Africa
13 were found in 5,081 studies (5% of global studies). Temperature trends were calculated from 1951-2018 and
14 precipitation from 1951-2016. Hatching shows regions where trends in both temperature and precipitation are
15 attributable to human-induced climate change. Data from (Callaghan et al., 2021).
16
17
18 9.1.5 Extent of Climate Change Data and Research Gaps Across Africa
19
20 Since AR5, there have been rapid advances in climate impacts research due to increased computing power,
21 data access and new developments in statistical analysis (Carleton and Hsiang, 2016). However, sparse and
22 intermittent weather station data limit attribution of climate trends to anthropogenic climate change for large
23 areas of Africa, especially for precipitation and extreme events, and hinder more accurate climate change
24 projections (Otto et al., 2020) (Section 9.5.2; Figure 9.3). Outside of South Africa and Kenya, digitally
25 accessible data on biodiversity is limited (Meyer et al., 2015). Lack of comprehensive socioeconomic data
26 also limits researchers' ability to predict climate change impacts. Ideally, multiple surveys over time are
27 needed to identify effects of a location's changing climate on changing socioeconomic conditions. Twenty-
28 five African countries conducted only one nationally representative survey that could be used to construct
29 measures of poverty during 2000-2010 and 14 conducted none over this period (Jean et al., 2016). Because
30 of these challenges, much of what is known about climate impacts and risks in Africa relies on evidence
31 from global studies that use data largely from outside Africa (e.g., Zhao et al., 2021). These studies generate
32 estimates of average impacts across the globe, but may not have the statistical power to distinguish whether
33 African nations display differential vulnerability, exposure or adaptive capacity. In sections of this chapter,
34 we have relied when necessary on such studies, as they often provide best available evidence for Africa.
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1 Increasing data coverage and availability would increase the ability to discern important differences in risk
2 both among and within African countries.
3
4 Climate-related research in Africa faces severe funding constraints with unequal funding relationships
5 between countries and with research partners in Europe and North America (high confidence). Based on
6 analysis of over 4 million research grants from 521 funding organisations globally, it is estimated from 1990-
7 2020 USD 1,26 billion funded Africa-related research on climate impacts, mitigation and adaptation. This
8 represents only 3.8% of global funding for climate-related research � a figure incommensurate with Africa's
9 high vulnerability to climate change (Overland et al., 2021) (Box 9.1; Chapter 8). Almost all funding for
10 Africa-related climate research originates outside Africa and goes to research institutions outside Africa
11 (Blicharska et al., 2017; Bendana, 2019; Siders, 2019; Overland et al., 2021). From 1990�2020, 78% of
12 funding for Africa-related climate research flowed to institutions in Europe and the United States � only
13 14.5% flowed to institutions in Africa (Overland et al., 2021) (Figure 9.4). Kenya (2.3% of total funding)
14 and South Africa (2.2%) are the only African countries among the top 10 countries in the world in terms of
15 hosting institutions receiving funding for climate-related research on Africa (Overland et al., 2021).
16
17 These unequal funding relations influence inequalities in climate-related research design, participation, and
18 dissemination between African researchers and researchers from high-income countries outside Africa, in
19 ways that can reduce adaptive capacity in Africa (very high confidence). Those empowered to shape research
20 agendas can shape research answers: climate research agendas, skills gaps and eligible researchers are
21 frequently defined by funding agencies, often from a Global North perspective (Vincent et al., 2020a).
22 Larger funding allocations for research focused on Ghana, South Africa, Kenya, Tanzania and Ethiopia are
23 reflected in higher concentrations of empirical research on impacts and adaptation options in these countries,
24 and there is a general lack of adaptation research for multiple of the most vulnerable countries in Africa
25 (Figure 9.5) (Callaghan et al., 2021; Overland et al., 2021; Sietsma et al., 2021; Vincent and Cundill, 2021).
26 The combination of Northern-led identification of both knowledge and skills gaps can result in projects
27 where African partners are positioned primarily as recipients engaged to support research and/or have their
28 `capacity built' rather than also leading research projects on an equal basis (Vincent et al., 2020a; Trisos et
29 al., 2021). Analysis of >15,000 climate change publications found for over 75% of African countries 60�
30 100% of climate change publications on these countries did not include a single local author, with authorship
31 dominated by researchers from richer countries outside Africa (Pasgaard et al., 2015). This can reduce
32 adaptive capacity in Africa as researchers at Global North institutions may shape research questions and
33 outputs for a Northern audience rather than providing actionable insights on priority issues for African
34 partners (Pasgaard et al., 2015; Nago and Krott, 2020). Moreover, in order to access research publications in
35 a timely manner, many researchers in Africa are forced to use shadow websites bypassing journal paywalls
36 (Bohannon, 2016). Ways to enhance research partnerships to produce actionable insights on climate impacts
37 and solutions in Africa include increased funding from African and non-African sources, projects funded by
38 non-African agencies, increasing direct control of resources for African partners and having African research
39 and user priorities set research questions, identify skills gaps and lead research, open access policies for
40 research outputs (ESPA Directorate, 2018; Vogel et al., 2019; Vincent et al., 2020a; IDRC, 2021; Trisos et
41 al., 2021).
42
43
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1
2
3 Figure 9.4: Climate-related research on Africa receives a small proportion of global climate research funding (a, b),
4 with most funding for climate-related research on Africa flowing to institutions based in the Europe and the USA (d).
5 Major funding countries are the UK, EU, USA, Germany and Sweden (d) . Funding comes mainly from government
6 organisations with private philanthropy providing only around 1% (Overland et al., 2021). Africa-related climate
7 research funding focuses mostly on food systems, ecosystems and freshwater, while security and conflict and urban
8 areas have received the least (e). Research on climate mitigation received only 17% of funding while climate impacts
9 and adaptation each received 40% (f). Since 2010, climate research has made up a larger share (5%) of Africa-related
10 research funding than is the case for research globally (3%) with a greater proportion of this Africa-focused climate
11 funding going to social sciences and humanities (28%) than is the case globally (12%) (Overland et al., 2021). Data are
12 from an analysis of 4,458,719 research grants in the Dimensions database with a combined value of USD 1.51 trillion
13 awarded by 521 funding organisations globally (Overland et al. 2021). The Dimensions database is the world's largest
14 database on research funding flows (Overland et al. 2021). It draws on official data from all major funding
15 organisations in the world, mainly government research councils or similar institutions. Note: The South African
16 National Research Foundation is the only African research funding body that is sufficiently large to be included in
17 Dimensions.
18
19
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1
2 Figure 9.5: Major gaps in climate change research funding, participation and publication exist within Africa, and for
3 Africa compared to the rest of the world. (a) Funding: Amount of climate change research funding focused on African
4 countries 1990-2020 (Overland et al., 2021). Considering population size, research on Egypt and Nigeria stands out as
5 particularly underfinanced (b) Participation: Percentage of climate change papers (impacts and adaptation) published on
6 a given country that also include at least one based in that country (Pasgaard et al. 2015). (c) Number of publications of
7 climate change adaptation research focused on individual countries identified from a global sample of 62,191
8 adaptation-relevant peer-reviewed articles published from 1988-2020 (Sietsma et al., 2021). There is a general lack of
9 adaptation-related research on many vulnerable countries in Africa. Topic biases in adaptation-relevant research also
10 exist where research focuses more on disaster and development-related topics in Southern countries (but published
11 authors from the global North), while Northern countries dominate governance topics (Sietsma et al., 2021).
12
13
14 9.1.6 Loss and Damage from Climate Change
15
16 Assessment of impacts, vulnerability, risks and adaptation highlights climate change is leading to irreversible
17 and existential impacts across Africa which breach current and projected adaptation limits (Table 9.1)
18 (Cross-Chapter Box LOSS in Chapter 17).
19
20
21 Table 9.1: Loss and damage from climate change across sectors covered in this report. Loss and damage arise from
22 adverse climate-related impacts and risks from both sudden-onset events, such as floods and cyclones, and slower-onset
23 processes, including droughts, sea level rise, glacial retreat and desertification and includes both include both economic
24 (e.g., loss of assets and crops) and non-economic types (e.g., loss of biodiversity, heritage and health) (UNFCCC Paris
25 Agreement, 2015; IPCC, 2018a; Mechler et al., 2020). Section marked with * and in bold highlights Loss and Damage
26 attributed to anthropogenic climate change (16.1.3).
Sector Loss and damage from climate change Observed Projected
Ecosystems Local, regional and global extinction 9.6.2 9.6.2
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Reduced ecosystem goods and services 9.6.1; 9.6.2 9.6.2
Declining natural coastal protection and habitats 9.6.1; 9.6.2 9.6.2
Altered ecosystem structure and declining 9.6.1 9.6.2
ecosystem functioning
Water Nature璪ased tourism 9.6.3 9.6.3
Biodiversity loss 9.6.2* 9.7.2
Declining lake and river resources
9.7.1
Reduced hydro-electricity and irrigation 9.7.2; 9.9.1 9.7.2; 9.9.3; Box 9.5
Disappearing glaciers - 9.5.9
9.5.9*; 9.7.1
Reduced groundwater recharge and salinization - 9.7.2
Drought Box 9.4*
Food systems Reduced crop productivity and revenues
9.7.2*, 9.8.1; 9.8.2; 9.8.2; 9.8.3; Box 9.5
9.11.1; Box 9.5
Increased livestock mortality and price shocks 9.8.2 9.8.2
Decreased fodder and pasture availability 9.8.2 9.8.2
Human Reduced fisheries catch and fisher livelihoods 9.6.1; 9.8.5 9.8.5
settlements Loss or damage to formal and informal dwellings 9.9.2 9.9.4
and Damage to transport systems 9.9.2 9.9.4
Infrastructure Damage to energy systems 9.9.2 9.7.2; 9.9.4
Water supply, sanitation, education and health 9.9.2; 9.10; 9.11.1 9.7.3; 9.9.4; 9.10;
infrastructure 9.11.1
Migration 9.9.1; Box 9.8 9.9.4; Box 9.8
Loss of life
Health 9.9.2*; 9.10.2; Box 9.9.4; 9.10.2
9.9
Loss of productivity 9.10.3; 9.11.1 9.10.2; 9.11.2
Economy, Reduced nutrition 9.8.1; 9.10.2 9.10.2
poverty and Loss of livelihoods, jobs and income 9.10.2; 9.11.2
Livelihoods Reduced productive land 9.9.2; 9.10.2; 9.11.1 9.8.2
Reduced economic growth and increased 9.8.2 9.11.2
9.11.1*; Box 9.5
inequality
Community and involuntary displacement 9.9.3; Box 9.8 9.9.4; Box 9.8
Reduced labour productivity and earning potential 9.11.1 9.11.2
Delayed and poorer education progress 9.11.1 9.11.1
Reduced tourism 9.6.3 9.5.9, 9.6.3, 9.12.2
Increased urban in-migration 9.8.1; 9.9.1; Table 9.9.4; Table Box 9.8
Heritage Loss of traditional cultures and ways of life Box 9.8 9.12.2
Box 9.2; 9.12.1
Loss of language and knowledge systems - 9.12.1
Damage to heritage sites 9.12.1 9.12.2
1
2
3 9.2 Key Risks for Africa
4
5 A key risk is defined as a potentially severe risk. In line with AR5, `severity' relates to dangerous
6 anthropogenic interference with the climate system, the prevention of which is the ultimate objective of the
7 UNFCCC as stated in its Article 2 (Oppenheimer et al., 2014). The process for identifying key risks for
8 Africa included reviewing risks from the Africa chapter of AR5, and assessing new evidence on observed
9 impacts and projected risks in this chapter.
10
11 Several key risks were identified for both ecosystems and people including species extinction and ecosystem
12 disruption, loss of food production, reduced economic output and increased poverty, increased disease and
13 loss of human life, increased water and energy insecurity, loss of natural and cultural heritage, and
14 compound extreme events harming human settlements and critical infrastructure (Table 9.2). In order to
15 provide a sector and continent-level perspective, the key risks aggregate across different regions and
16 combine multiple risks within sectors. For detailed assessments of observed impacts and future risks within
17 each sector and each sub-region of Africa, see the sector-specific sections of this chapter (Sections 9.6.1 and
18 9.12.1).
19
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1 Several expert elicitation workshops of lead and contributing authors were held to develop `burning embers'
2 assessing how risk increases with further global warming for a subset of key risks, specifically risk of food
3 production losses, risk of biodiversity loss and risk of mortality and morbidity from heat and infectious
4 disease (Figure 9.6). These key risks were selected in part because of underlying assessment work in the
5 chapter to connect multiple studies to observed impacts and/or risk at increasing global warming levels
6 (Sections 9.6.2, 9.8.2, 9.8.5.2 and 9.10.2).
7
8 All three of these key risks are assessed to have already transitioned completely into moderate risk--that is,
9 negative impacts have been detected and attributed to climate change--before the 2010�2020 level of global
10 warming (1.09癈) (IPCC, 2021), with medium confidence for increased mortality and morbidity and high
11 confidence for losses of food productivity and biodiversity (Figure 9.6). For biodiversity, these impacts
12 include repeated mass die-offs of coral reefs due to marine heat (Section 9.6.1.4), reductions in lake
13 productivity due to warming (Section 9.6.1.3), and woody encroachment of grasslands and savannas due to
14 increased atmospheric CO2 concentrations (Section 9.6.1.1), with negative impacts on livelihoods (Section
15 9.6.1). For food production, climate change impacts include up to 5.8% mean reduction in maize
16 productivity due to increased temperatures in sub-Saharan Africa (Section 9.8.2.1 and 9.8.2.2) and reduced
17 fisheries catches due to increased temperatures, especially in tropical regions (Section 9.8.2). For health,
18 climate change impacts include increased mortality and morbidity from changes in the distribution and
19 incidence of malaria and cholera and the direct effects of increasing temperatures (Section 9.10.2).
20
21 In scenarios with low adaptation (that is largely localised and incremental), the transition to high risk--
22 widespread and severe impacts--has already begun at the current level of global warming for biodiversity
23 loss (high confidence), and begins below 1.5癈 global warming for both food production (medium
24 confidence) and mortality and morbidity from heat and infectious disease (high confidence). Across all risks,
25 the best estimate for the transition to high risk is at 1.5癈 of global warming, with transition to high risk
26 completing before 2癈 (Figure 9.6). Projected impacts considered high risk around 1.5癈 include: across
27 more than 90% of Africa, more than 10% of species are at risk of local extinction (Figure 9.6; Table 9.1); the
28 further expansion of woody plants into grass-dominated biomes (Section 9.6.2.1); 9% declines in maize yield
29 for West Africa and 20�60% decline in wheat yield for southern and northern Africa, as well as declines in
30 coffee and tea in East Africa and sorghum in West Africa (Figures 9.22 and 9.23; Section 9.8.2.1 and
31 9.8.2.2), and >12% decline in marine fisheries catch potential for multiple West African countries,
32 potentially leaving millions at risk of nutritional deficiencies (Figure 9.25; Section 9.8.5); tens of millions
33 more people exposed to vector-borne diseases in East and southern Africa (malaria), and North, East and
34 southern Africa (dengue, zika), increased risk of malnutrition in Central, East and West Africa, and more
35 than 15 additional deaths per 100,000 annually due to heat in parts of West, East and North Africa (Figures
36 9.32 and 9.35; Sections 9.10.2 and 9.9.4.1).
37
38 The transition from high to very high risk--that is severe and widespread impacts with limited ability to
39 adapt--begins either at or just below 2癈 for all three risks (Figure 9.6). The assessed temperature range for
40 the transition to very high risk is wider for food production than for biodiversity and health. Projected
41 impacts for food include: 10�30% decline in marine fisheries catch potential for the Horn of Africa region
42 and southern Africa and more than 30% decline for West Africa at 2癈 global warming, with greater
43 declines at higher levels of warming (Section 9.8.2). Beyond 2癈 global warming, over 50% of
44 commercially important freshwater fish species across Africa are projected to be vulnerable to extinction
45 (Figure 9.26). Between 2 and 4, wheat, maize and rice yields are projected, on average, to be lower than
46 2005 yields across all regions of Africa. From 2 global warming, over 40% losses in rangeland
47 productivity are projected for western Africa. By 3.75癈, severe heat stress may be near year-round for cattle
48 across tropical Africa (Figure 9.24). Multiple countries in West, Central and East Africa are projected to be
49 at risk from simultaneous negative impacts on crops, fisheries and livestock (Thiault et al., 2019) (9.8.2;
50 9.8.5).
51
52 The best estimate for the onset of very high risk for biodiversity and health is at 2.1癈. Projected impacts
53 considered very high risk for biodiversity include potential destabilisation of the African tropical forest
54 carbon sink, risk of local extinction of more than 50% of plants, vertebrate and insect species across one-fifth
55 of Africa, 7�18% of African species at risk of total extinction including, a third of freshwater fish, and more
56 than 90% warm-water coral reefs lost (Section 9.6.2). For health, projected impacts considered high risk
57 include potentially lethal heat exposure for more than 100 days per year in West, Central and East Africa,
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1 with more than 50 additional heat-related deaths per 100,000 annually across large parts of Africa, and
2 hundreds of millions more people exposed to extreme heat in cities (Section 9.5, 9.10.2 and 9.9.4.1; Figure
3 9.35), tens to hundreds of thousands of additional cases of diarrhoeal disease in East, Central and West
4 Africa, and tens of millions more people exposed to mosquito-borne arboviruses like dengue or zika in
5 North, East and southern Africa (Section 9.10.2).
6
7 The feasibility and effectiveness of existing adaptation options under current levels of warming are assessed
8 in Section 9.10.2 and adaptation options considering future levels of warming are assessed in the chapter
9 section for each sector.
10
11
12
13 Figure 9.6: Burning Embers showing increasing risk due to climate change for selected key risks in Africa. Projected
14 increase is assessed for global warming increasing above pre-industrial levels (1850�1900). All three risks are assessed
15 to have already transitioned to moderate risk by the recent level of global warming 2010�2020 (1.09癈). Risks are
16 characterized as undetectable, moderate, high, or very high, and the transition between risk levels as a function of global
17 warming is represented by the colour change of each bar (IPCC, 2021). For range of global warming levels for each risk
18 transition used to make this figure see Supplementary Material Table SM 9.1.
19
20
21 Table 9.2: Key risks from climate change in Africa
Key climate change risk Climate impact driver Vulnerability Chapter section
Local or global extinction Increasing temperatures of Vulnerability highest 9.6
of species and reduction freshwaters, ocean and on among poorly dispersing
or irreversible loss of land; heatwaves; organisms (plants) and
ecosystes and their precipitation changes species with narrow and
services, including (both increases and disappearing niches (e.g.
freshwater, land and decreases); increased mountain endemics), and
ocean ecosystems atmospheric CO2 is exacerbated by non-
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concentrations; sea level climate hazards (e.g.
rise; ocean acidification habitat loss for agriculture
or afforestation projects);
Vulnerability is high for
Protected Areas
surrounded by
transformed land
preventing species'
dispersal and areas with
limited elevational
gradients that reduce their
potential to act as climate
refugia
Loss of food production Increasing temperatures High for low-income 9.8
from crops, livestock and
fisheries and heat waves for coastal and riparian
freshwaters, ocean and on communities whose
land; precipitation livelihood depends on
changes; drought; healthy ocean and
increased atmospheric freshwater ecosystems,
CO2 concentrations and for populations reliant
on fish for protein and
micronutrients.
Vulnerability is high for
many food producers
dependent on rainfall and
temperature conditions,
including subsistence
farmers, the rural poor,
and pastoralists. Lack of
access to climate
information and services
increases vulnerability.
Mortality and morbidity Increasing temperatures; Vulnerability is highest 9.10
from heat and infectious heatwaves; precipitation for the elderly, pregnant
diseases change (both increases women, individuals with
and decreases) underlying conditions,
immune-compromised
individuals (e.g., from
HIV), and young children.
Regions without vector
control programmes in
place or without detection
and treatment regimens.
Inadequate insulation in
housing in informal
settlements in urban heat
islands. Inadequate
improvements in public
health systems.
Inadequate water and
sanitation infrastructure,
especially in rapidly
expanding urban areas and
informal settlements.
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Reduced economic output Increased temperatures; Conditions underlying 9.11
and growth, and increased reduced rainfall; extreme severe risk are lower
inequality and poverty weather events income growth, higher
rates population levels, low
rates of structural
economic change with
more of the labour force
engaged in agriculture and
other more climate-
exposed sectors due in
part to physical labour
outdoors.
Water and energy Heat and drought High reliance on 9.7, 9.9, Box 9.5
insecurity due to shortage hydropower for national
of irrigation and electricity generation,
hydropower. especially East and
Southern African
countries. Planned for
high reliance on irrigated
food production.
Concentrations of
hydropower plants within
river basins experiencing
similar rainfall and run-off
patterns. Limited
electricity trade between
major river basins.
Cascading and Extreme heat; floods; Coastal and low-lying 9.9
compounding risks of loss drought; sea level rise and urban areas and those in
of life, livelihoods and associated coastal dryland regions with
infrastructure in human hazards; compound rapidly growing
settlements. climate hazards (e.g., populations. People living
coinciding heat and in informal settlements.
drought) Increased magnitude of
heat waves due to urban
heat island effects.
Climate-shocks to
municipal revenues (e.g.,
from water). Unaffordable
maintenance of transport
and protective
infrastructure with
increasing climate
impacts. Greater water
resource demand from
urban and non-urban
populations and key
economic sectors
1
2
3 9.3 Climate Adaptation Options
4
5 9.3.1 Adaptation Feasibility and Effectiveness
6
7 Based on a systematic assessment of observed climate adaptation responses in the scientific literature
8 covering 827 adaptation response types in 553 studies (2013�2021), and expert elicitation process, 24
9 categories of adaptation responses in Africa were identified (Williams et al., 2021). This assessment
10 excluded autonomous adaptation in ecosystems, such as migration and evolution of animal and plant species.
11
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1
2
3 Figure 9.7: Assessment of feasibility of observed climate adaptation responses under current climate conditions for 24
4 categories of adaptation responses across regions of Africa. The assessment comprised evaluation of each adaptation
5 category along six feasibility dimensions: economic viability, environmental sustainability, social validity, institutional
6 relevance, technological availability, and potential for risk reduction (considering current climate conditions) (Williams
7 et al., 2021). Fifty-six experts on the African region were consulted using a structured, expert-driven elicitation process
8 to increase the coverage and robustness of the continent-wide adaptation feasibility and effectiveness assessment in
9 Williams et al. (2021). Assessment included both peer-reviewed articles and grey literature.
10
11
12 At the current global warming level, 83% of adaptation response categories assessed showed medium
13 potential for risk reduction (that is, mixed evidence of effectiveness). Bulk water infrastructure (including
14 managed aquifer recharge, dams, pipelines, pump stations, water treatment plants and distribution networks),
15 human migration, financial investment for agricultural intensification, and social infrastructure (including
16 decentralised management, strong community structures and informal support networks) show high potential
17 for risk reduction (high evidence of option's effectiveness) (Sections 9.6.4 and 9.7.3; Boxes 9.8, 9.9, 9.10
18 and 9.11). However, there was limited evidence to assess the continued effectiveness of these options at
19 higher global warming levels (Williams et al., 2021) with some options, such as bulk water infrastructure
20 (particularly large dams), expected to face increasing risk with continued warming with damages cascading
21 to other sectors (see Box 9.5), while others, such as crop irrigation and adjusting planting times, may
22 increasingly reach adaptation limits above 1.5癈 and 2癈 global warming (Sections 9.8.3 and 9.8.4)
23
24 The majority of adaptation studies were in West and East Africa (Ghana, Ethiopia, Kenya and Tanzania),
25 followed by southern Africa, with the least coming from Central and North Africa (Figure 9.7) (Williams et
26 al., 2021). Most studies were on adaptation actions in the food sector, with the least on health (Figure 9.7).
27 The five adaptation response categories with the highest number of reported actions were sustainable water
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1 management (food sector), resilient infrastructure and technologies (health sector), agricultural
2 intensification (food sector), human migration (poverty and livelihoods) and crop management (food sector).
3
4 No adaptation response categories were assessed to have high feasibility of implementation. Technological
5 barriers dominate factors limiting implementation (92% of adaptation categories have low technological
6 feasibility) followed by institutional barriers (71% of adaptation categories have low institutional feasibility).
7 This assessment matches review studies finding institutional responses to be least common in Africa and
8 highlight inadequate institutional capacities as key limits to human adaptation (Berrang-Ford et al., 2021;
9 Thomas et al., 2021) (Cross-Chapter Box FEASIB in Chapter 18). Feasibility is higher for the social
10 dimension of adaptation responses (with moderate feasibility for 88% of categories). The largest evidence
11 gap is for environmental feasibility for which 67% could not be assessed due to insufficient evidence (Figure
12 9.7).
13
14 Sustainable Water Management (SWM) includes rainwater harvesting for irrigation, watershed restoration,
15 water conservation practices (e.g., efficient irrigation) and less water-intensive cropping (also see Section
16 9.8.3), and was the most reported adaptation response in the food sector. SWM was assessed with medium
17 economic and social feasibility and low environmental, institutional and technological feasibility. The
18 feasibility of this adaptation category may depend largely on socioeconomic conditions (Amamou et al.,
19 2018; Harmanny and Malek, 2019; Schilling et al., 2020), as many African farmers cannot afford the cost of
20 sustainable water management facilities (Section 9.8.4).
21
22 Resilient Infrastructure and Technologies (RIT) for health include improved housing to limit exposure to
23 climate hazards (Stringer et al., 2020), and improved water quality, sanitation and hygiene infrastructure
24 (e.g., technology across all sectors to prevent contamination and pollution of water, improved water,
25 sanitation and hygiene (WASH) approaches such as promotion of diverse water sources for water supply,
26 improving health infrastructure) (Section 9.10.3). Overall, RIT had medium social feasibility and low
27 institutional and technological feasibility. Bulk water infrastructure was assessed to have high effectiveness,
28 but low institutional and technological feasibility. Increasing variability in climate and environmental
29 challenges has made sustainable and resilient infrastructure design a key priority (Minsker et al., 2015). RIT
30 is, however, generally new in the African context (Cumming et al., 2017) and that may be why there is
31 limited evidence to assess some of its dimensions (economic and environmental feasibility). Construction of
32 resilient public water infrastructures that include safeguards for sanitation and hygiene are expensive and,
33 across national and local levels, planning for its construction poses multiple challenges (Choko et al., 2019).
34
35 Agricultural intensification (including mixed cropping, mixed farming, no soil disturbance, mulching) in
36 many smallholder farming systems remains a key response option to secure food for the growing African
37 population (Nziguheba et al., 2015; Ritzema et al., 2017). Yet this option faces low environmental,
38 institutional and technological feasibility (Figure 9.7). Social and economic feasibility is higher, but barriers
39 include high cost of farm inputs (land, capital and labour), lack of access to timely weather information and
40 lack of water resources can make this option quite challenging for African smallholder farmers (Kihila,
41 2017; Williams et al., 2019b) (Sections 9.8.1 and 9.11.4).
42
43 Crop management includes adjusting crop choices, planting times, or the size, type and location of planted
44 areas (Altieri et al., 2015; Nyagumbo et al., 2017; Dayamba et al., 2018). This option faces environmental,
45 institutional and technological barriers to feasibility. Social and economic barriers to implementation are
46 fewer. Factors such as tenure and ownership rights, labour requirements, high investment costs and lack of
47 skills and knowledge on how to use the practices are reported to hinder implementation of crop management
48 options by smallholder farmers (Muller and Shackleton, 2013; Nyasimi et al., 2017). For instance, when
49 improved seed varieties are available, high price limits access for rural households (Amare et al., 2018) (see
50 Sections 9.8.3 and 9.8.4).
51
52 Human migration was assessed to have high potential for risk reduction (Rao et al., 2019; Sitati et al., 2021)
53 (Cross-Chapter Box MIGRATE in Chapter 7, Box 9.8). However, it had low feasibility for economic,
54 institutional and technological dimensions, with limited evidence on environmental feasibility. Institutional
55 factors such as the implementation of top-down policies have been reported as limiting options for coping
56 locally, resulting in migration (Brockhaus et al., 2013). Limited financial and technical support for migration
57 limits the extent to which it can make meaningful contributions to climate resilience (Djalante et al., 2013;
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1 Trabacchi and Mazza, 2015). International and domestic remittances are an important resource that can help
2 aid recovery from climate shocks, but inadequate finance and banking infrastructure can limit cash transfers
3 (Box 9.8). Male migration can increase burdens of household and agricultural work, especially for women
4 (Poudel et al., 2020; Rao et al., 2020; Zhou et al., 2020). The more agency migrants have (that is, degree of
5 voluntarity and freedom of movement), the greater the potential benefits for sending and receiving areas
6 (high agreement, medium evidence) (Cross-Chapter Box MIGRATE in Chapter 7, Box 9.8)
7
8 Adaptation options within a number of categories, including sustainable agriculture practices, agricultural
9 intensification, fisheries management, health advisory services and education, social infrastructure,
10 infrastructure and built environment and livelihood diversification were observed to reduce socioeconomic
11 inequalities (Williams et al., 2021). Whether adaptation options reduce inequality can be a key consideration
12 enhancing acceptability of policies and adaptation implementation (Islam and Winkel, 2017) (Box 9.1;
13 Section 9.11.4).
14
15 9.3.2 Adaptation Co-Benefits and Trade-Offs with Mitigation and SDGs
16
17 Synergies between the adaptation and progress towards the Sustainable Development Goals (SDGs) present
18 potential co-benefits for realising multiple objectives towards Climate Resilient Development in Africa,
19 increasing the efficiency and cost-effectiveness of climate actions (Cohen et al., 2021). However, designing
20 adaptation policy under conditions of scarcity, common to many African countries, can inadvertently lead to
21 trade-offs between adaptation options, as well as between adaptation and mitigation options, can reinforce
22 inequality, and fail to address underlying social vulnerabilities (Kuhl, 2021).
23
24 Adaptation options such as access to climate information, provision of climate information services, growing
25 of early maturing varieties, agroforestry systems, agricultural diversification and growing of drought-
26 resistant varieties of crops may deliver co-benefits, providing synergies that result in positive outcomes. For
27 instance, in SSA drylands including northern Ghana and Burkina Faso and large parts of the Sahel, migration
28 as a result of unfavourable environmental conditions closely linked to climate change has often provided
29 opportunities for farmers to earn income (SDG 1) and mitigate the effects of climate-related fluctuations in
30 crop and livestock productivity (SDG 2) (Zampaligr� et al., 2014; Antwi-Agyei et al., 2018; Wiederkehr et
31 al., 2018). Renewable energy can mitigate climate effects (SDG 13), improve air quality (SDG 3), wealth
32 and development (SDGs 1, 2).
33
34 Different types of irrigation including drip and small-scale irrigation can contribute towards increased
35 agricultural productivity (SDG 2), improved income (SDG 1) and food security (SDG 2) and increase
36 resilience to long-term changes in precipitation (SDG 13) (Bjornlund et al., 2020). In Kenya and Tanzania,
37 small-scale irrigation provides employment opportunities and income to both farmers and private businesses
38 (SDGs 8 and 9) (Lefore et al., 2021; Simpson et al., 2021c). Land management practices including the use of
39 fertilizers and mulching have also been highlighted as adaptation options improving soil fertility for better
40 yields (SDG 2) and delivering opportunities to reduce the climate change effects (SDG 13) (Muchuru and
41 Nhamo, 2019).
42
43 Climate smart agriculture (CSA) offers opportunities for smallholder farmers to increase productivity (SDG
44 2), build adaptive capacity whilst reducing the emission of greenhouse gases (SDG 13) from agricultural
45 systems (Lipper et al., 2014; Mutenje et al., 2019). CSA practices including conservation agriculture, access
46 to climate information, agroforestry systems, drip irrigation, planting pits and erosion control techniques
47 (Partey et al., 2018; Antwi-Agyei et al., 2021) can improve soil fertility, increase yield and household food
48 security (Zougmor� et al., 2016; Zougmor� et al., 2018), thereby contributing to the realisation of SDG 2 in
49 Africa (Mbow et al., 2014).
50
51 On the contrary, adaptation actions may induce trade-offs with mitigation objectives, as well as other
52 adaptation and developmental outcomes, delivering negative impacts and compromising the attainment of
53 the SDGs. For example, increased deployment of renewable energy technologies can drive future land use
54 changes (Frank et al., 2021) and threaten important biodiversity areas if poorly deployed (Rehbein et al.,
55 2020). The use of early-maturing or drought-tolerant crop varieties may increase resilience (SDGs 1, 2), but
56 adoption by smallholder farmers can also be hindered by affordability of seed. Cultivation of biodiesel crops
57 also can hinder food security (SDG 2) at local and national levels (Tankari, 2017; Brinkman et al., 2020).
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1 Additionally, the use of fertilizers in intense systems can result in increased environmental degradation
2 (Akinyi et al., 2021). When farmers migrate, it puts pressure on inadequate social services provision and
3 facilities at their destination (SDG 8) and leads to reduced farm labour and a deterioration of the workforce
4 and assets (SDG 2) (Gemenne and Blocher, 2017a), which negatively affects farm operations and non-
5 migrants, particularly women, elderly and children, at the point of origin (Nyantakyi-Frimpong and Bezner-
6 Kerr, 2015; Ahmed et al., 2016; Otto et al., 2017; Eastin, 2018). Farmers may also miss critical periods
7 during the farming season that eventually makes them food insecure (SDG 2) and vulnerable to climate
8 change (SDG 13) (Antwi-Agyei et al., 2018). Migrants should be supported to reduce their overall shocks to
9 climate vulnerability at the points of origin and destination. Small-scale irrigation infrastructure if not
10 managed properly, may lead to negative environmental effects and compromise the integrity of riparian
11 ecosystems (SDG 15) (Loucks and van Beek, 2017) and serve as breeding grounds for malaria-causing
12 mosquitoes (SDG 3) (Attu and Adjei, 2018).
13
14
15 9.4 Climate Resilient Development
16
17 Climate resilient development (CRD) is a process of implementing greenhouse gas mitigation and adaptation
18 measures to support sustainable development for all (Denton et al., 2014; Andrijevic et al., 2020; Owen,
19 2020; Cornforth et al., 2021). It emphasises equity as a core element of sustainable development as well as
20 conditions for inclusive and sustained economic growth, shared prosperity and decent work for all, taking
21 into account different levels of national development and capacities as encoded in the SDGs (Section 9.3.2;
22 Chapter 18, Section 18.1). This chapter section identifies five key dimensions of CRD for Africa: climate
23 finance, governance, cross-sectoral and transboundary solutions, adaptation law and climate services and
24 literacy.
25
26 9.4.1 Climate Finance
27
28 Access to adequate financial resources is crucial for climate change adaptation (Cross-Chapter Box
29 FINANCE in Chapter 17). Since the Copenhagen Accord (UNFCCC, 2009), and then extended by the Paris
30 Agreement (UNFCCC Paris Agreement, 2015 see Article 4.4, and also 4.8, 4.9), developed countries are
31 expected to scale up climate finance for developing countries toward a collective goal of USD 100 billion
32 per year by 2020, with a balanced allocation between adaptation and mitigation.
33
34 9.4.1.1 How Much Adaptation Finance is Needed?
35
36 There is limited research providing quantitative estimates of adaptation costs across Africa. Adaptation costs
37 in Africa have been estimated at USD 7�15 billion per year by 2020 (Schaeffer et al., 2013), corresponding
38 to USD 5�11 per capita per year. The African Development Bank estimates costs of near-term adaptation
39 needs identified in the Intended NDCs (INDCS) of African countries as USD 7.4 billion per year from 2020,
40 recognising INDCs describes only a limited subset of adaptation needs (AfDB, 2019). Many African
41 countries, particularly Least Developed Countries (LDCs), express a stronger demand for adaptation finance
42 � a study of financial demands in INDCs for 16 African countries suggests a ratio around 2:1 for adaptation
43 to mitigation finance with demand for Eritrea and Uganda approximately 80% for adaptation (Zhang and
44 Pan, 2016).
45
46 Adaptation costs in Africa are expected to rise rapidly as global warming increases (high confidence). A
47 meta-analysis of adaptation costs identified in 44 NDCs and NAPs from developing countries estimated a
48 median adaptation cost around USD 17 per capita per year for 2020�2030 (Chapagain et al., 2020).
49 Adaptation cost estimates for Africa increase from USD 20�50 billion per year for RCP2.6 in 2050 (around
50 1.5癈 of warming), to USD18�60 billion per year for just over 2癈, to USD 100�437 billion per year for 4癈
51 of global warming above pre-industrial levels (Schaeffer et al., 2013; UNEP, 2015; Chapagain et al., 2020).
52 Focusing on individual sectors, the average country-level cost is projected to be USD 0.8 billion per year for
53 adapting to temperature-related mortality under 4癈 global warming (Carleton et al., 2018), with cumulative
54 energy costs for cooling demand projected to reach USD 51 billion by 2癈 and USD 486 billion by 4癈
55 global warming (Parkes et al., 2019). Transport infrastructure repair costs are also projected to be substantial
56 (Section 9.8.2) More precise estimates are limited by methodological difficulties and data gaps for costing
57 adaptation, uncertainties about future levels of global warming and associated climate hazards, and ethical
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1 choices such as the desired level of protection achieved (Fankhauser, 2010; Hallegatte et al., 2018;
2 UNFCCC, 2018) (Cross-Chapter Box FINANCE in Chapter 17). As such, existing estimates are expected to
3 substantially underestimate eventual costs with adaptation costs possibly 2�3 times higher than current
4 global estimates by 2030, and 4�5 times higher by 2050 (UNEP, 2016a).
5
6 9.4.1.2 Benefit-Cost Ratios in Adaptation
7
8 Although analysts face challenges related to the nature of climate change impacts (Sussman et al., 2014) and
9 data limitations (Li et al., 2014) when estimating all costs and benefits for adaptation measures in specific
10 contexts, adaptation generally is cost-effective (high confidence). The Global Commission on Adaptation
11 estimated the benefits and costs of five illustrative investments and found benefit-cost ratios ranging from
12 2:1 to 10:1. However, it also noted that `actual returns depend on many factors, such as economic growth
13 and demand, policy context, institutional capacities and condition of assets' (The Global Commission on
14 Adaptation, 2019). A review of ex-ante cost-benefit analyses for 19 adaptation-focused projects in Africa
15 financed by the Green Climate Fund (GCF) shows benefit-cost ratios in a similar range. Using a 10%
16 discount rate, as used by many of GCF's accredited entities, the benefit-cost ratio for individual projects
17 ranges from 0.9:1 to 7.3:1, the median benefit-cost ratio is 1.8:1 and total ratio across all 19 projects is 2.6:1.
18 When using lower discount rates, as some entities do for climate projects, the benefit-cost ratio is even
19 higher, reflecting the front-loaded costs and back-loaded benefits of many adaptation investments. Using a
20 5% discount rate, the overall benefit-cost ratio of the GCF projects is 3.5:1, with a range from 1:1 to 11.5:1
21 and a median ratio of 2.4:1 (Breitbarth, 2020). In addition, many proposals have activities for which further
22 benefits were not estimated due to the difficulty of attributing benefits directly to the intervention. The
23 benefits of adaptation measures for infrastructure and others with clear market impacts are often easier to
24 estimate than for policy interventions and where markets may not exist, such as ecosystem services (Li et al.,
25 2014).
26
27 9.4.1.3 How Much Finance is Being Mobilised?
28
29 The amounts of finance being mobilised internationally to support adaptation in African countries are
30 billions of USD less than adaptation cost estimates, and finance has targeted mitigation more than adaptation
31 (high confidence). The OECD (2020) estimates an average of USD 17.3 billion per year in public finance
32 targeting mitigation and adaptation from developed countries to Africa from 2016-2018, with adaptation
33 expected to be a small share of this amount: Of the global total only 21% in 2018 targeted adaptation (there
34 is no breakdown provided for Africa). Analysis of OECD data that is reported by the funders, covering
35 bilateral and multilateral funding sources, estimated international public finance (grants and concessional
36 lending) committed to Africa for climate change for 2014-2018 at USD 49.9 billion: 61% (30.6 billion) for
37 mitigation, 33% (16.5 billion) for adaptation and 5% (2.7 billion) for both objectives simultaneously
38 (Savvidou and Atteridge, 2021) (Figure 9.8a). This equates to an average of USD 3.8 billion per year
39 targeting adaptation (Savvidou and Atteridge, 2021). In per capita terms, only two countries (Djibouti and
40 Gabon) were supported with more than USD 15 per person per year, most were supported with less than
41 USD 5 per person per year (Savvidou and Atteridge, 2021).
42
43 The multilateral development banks (MDBs) report 43% of their climate-related commitments to sub-
44 Saharan Africa in 2018 targeted adaptation (EBRD et al., 2021). Sources other than international public
45 finance are more difficult to track and there is limited data on Africa (Cross-Chapter Box FINANCE in
46 Chapter 17). Considering a wider range of finance types (including private flows and domestic mobilisation),
47 an estimated annual average of roughly USD 19 billion in climate finance for 2017-2018 went to sub-
48 Saharan Africa, of which only 5% was for adaptation (CPI, 2019; Adhikari and Safaee Chalkasra, 2021). The
49 mobilisation of private finance by developed country governments, through bilateral and multilateral
50 financial support, is lower in Africa relative to other world regions. Globally, in 2016-2018, Africa made up
51 only 17% of mobilised private finance relevant for climate change (OECD, 2020).
52
53 Strong differences exist among African sub-regions. Finance commitments targeting adaptation increased
54 from 2014-2018 for East and West Africa but decreased in Central Africa (Savvidou and Atteridge, 2021)
55 (Figure 9.8b). Climate-related finance was >50% for adaptation in 19 countries, while 26 received >50% for
56 mitigation (Savvidou and Atteridge, 2021).
57
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1 African countries expect grants to play a crucial role in supporting adaptation efforts because loans add to
2 already high debt levels that exacerbate fiscal challenges, especially in light of high sovereign debt levels
3 from the COVID-19 pandemic (Bulow et al., 2020; Estev鉶, 2020). From 2014-2018, more finance
4 commitments targeting adaptation in Africa were debt instruments (57%) than grants (42%) (Savvidou and
5 Atteridge, 2021) (Figure 9.8c).
6
7
8
9 Figure 9.8: Finance targeting climate adaptation by sector and percentages of climate finance commitments that have
10 been disbursed in Africa (2014-2018) as reported to OECD. (a) Flows of committed finance targeting adaptation, (b)
11 trend over time in international development finance commitments targeting adaptation in Africa, and (c) country-level
12 shares of total climate finance that targeted adaptation or mitigation or both simultaneously. Source: (Savvidou and
13 Atteridge, 2021).
14
15
16 For Africa combined, the sectors targeted with most support for adaptation are Agriculture and Water Supply
17 and Sanitation, which account for half of total adaptation finance from 2014-2018 (Figure 9.9a). The sectoral
18 distribution has changed little over these years, suggesting adaptation planners and funders are maintaining a
19 relatively narrow view of where support is needed and how to build climate resilience (Savvidou and
20 Atteridge, 2021).
21
22 However, to understand actual expenditure on adaptation, it is necessary to look at disbursements (that is, the
23 amounts paid out versus committed amounts). Low ratios of disbursements to commitments suggest
24 difficulties in project implementation. Disbursement ratios for climate-related finance from all funders other
25 than MDBs (for which data is not published) in Africa are very low (Savvidou and Atteridge, 2021) (Figure
26 9.9b). Only 46% of 2014�2018 commitments targeting adaptation were dispersed (Savvidou and Atteridge,
27 2021). Regions faring worst are North Africa (15%), Central Africa (33%) and West Africa (33%) (Figure
28 9.9c). These disbursement ratios for adaptation and mitigation finance in Africa are lower than the global
29 average (Savvidou and Atteridge, 2021), which suggests greater capacity problems in implementing climate-
30 related projects and, in turn, means lost opportunities to build resilience and adaptive capacity and a wider
31 gap in adaptation finance for Africa (Omari-Motsumi et al., 2019).
32
33
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1
2 Figure 9.9: (a) Sectoral distribution of adaptation finance commitments to Africa 2014-2018 (Savvidou and Atteridge,
3 2021). Disbursement ratio (disbursements expressed as percentage of commitments) targeting mitigation, adaptation
4 and for total development finance, (b) disbursement ratios for Africa compared to global average, and (c) disbursement
5 ratios for adaptation finance broken down by each African sub-region. 2014-2018 (for all funders reporting to OECD
6 except Multilateral Development Banks). Source: (Savvidou and Atteridge, 2021).
7
8
9 9.4.1.4 What are the Barriers and Enabling Conditions for Adaptation Finance?
10
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1 The present situation reflects not only an insufficient level of finance being mobilised to support African
2 adaptation needs (Section 9.4.1) but also problems in accessing and using funding that is available. The
3 direct access modality introduced by the Adaptation Fund and GCF, whereby national and regional entities
4 from developing countries can be accredited to access funds directly, is aimed at reducing transaction costs
5 for recipient countries, increasing national ownership and agency for adaptation actions, and enhancing
6 decision-making responsibilities by national actors, thereby contributing to strengthening local capacity for
7 sustained and transformational adaptation (CDKN, 2013; Masullo et al., 2015). Indeed, direct-access projects
8 from the Adaptation Fund tend to be more community focussed than indirect-access projects (Manuamorn
9 and Biesbroek, 2020). Country institutions in Africa, however, are struggling to be accredited for direct
10 access because of the complicated, lengthy and bureaucratic processes of accreditation, which requires, for
11 example, strong institutional and fiduciary standards and capacity to be in place (Brown et al., 2013; Omari-
12 Motsumi et al., 2019). As of December 2019, over 80% of all developing countries had no national Direct
13 Access Entities (DAEs) (Asfaw et al., 2019). Capacity to develop fundable projects in Africa is also
14 inadequate. An analysis of proposals submitted to the GCF up to 2017 revealed that, while African countries
15 were able to submit proposals to the GCF, they had the lowest percentage of approvals (39%) compared to
16 all other regions (Fonta et al., 2018). This suggests the quality of proposals and therefore the capacity to
17 develop fundable proposals remains inadequate in the region.
18
19 Even when accredited, some countries experience significant institutional and financial challenges in
20 programming and implementing activities to support concrete adaptation measures (Omari-Motsumi et al.,
21 2019). Low disbursement ratios suggest inadequate capacity to implement projects once they are approved
22 (Savvidou and Atteridge, 2021). Systemic barriers have been highlighted in relation to the multilateral
23 climate funds, including funds not providing full-cost adaptation funding, capacity barriers in the design and
24 implementation of adaptation actions (including the development of fundable project proposals) and barriers
25 in recognising and enabling the involvement of sub-national actors in the delivery and implementation of
26 adaptation action (Omari-Motsumi et al., 2019). As of 2017, most GCF disbursements to Africa (61.9%)
27 were directed to support national stakeholders' engagement with regards to readiness activities, with only
28 11% directed to support DAEs in implementation of concrete projects/pipeline development (Fonta et al.,
29 2018). While supporting readiness activities is important for strengthening country ownership and
30 institutional development, research suggests adaptation finance needs to shift towards implementation of
31 concrete projects and more pipeline development if the goal of transformative and sustained adaptation in
32 Africa is to be realised (Fonta et al., 2018; Omari-Motsumi et al., 2019). The source of these problems needs
33 to be better understood so that the prospects for future climate-related investments can be improved and
34 institutional strengthening and targeted project preparation can be supported (Omari-Motsumi et al., 2019;
35 Doshi and Garschagen, 2020; Savvidou and Atteridge, 2021).
36
37 Some progress has been made in supporting developing countries to enhance their adaptation actions. The
38 process to formulate and implement NAPs was established by parties under the UNFCCC to support
39 developing countries identify their vulnerabilities, and determine their medium- and long-term adaptation
40 needs (UNFCCC Paris Agreement, 2015). NAPs provide a means of developing and implementing strategies
41 and programmes to address those needs. In 2016, the parties agreed for the GCF to fund up to USD 3 million
42 per country for adaptation planning instruments, including NAPs. However, accessing funding through the
43 GCF for NAP formulation is challenging (Fonta et al., 2018) and, as of October 2020, four years after the
44 decision to fund NAPs, only six African countries had completed their NAPs (UNFCCC NAP Central). The
45 next step is to convert adaptation planning documents into programming pipeline projects that are fundable
46 and implementable, which presents a significant barrier to enhanced adaptation action (Omari-Motsumi et
47 al., 2019).
48
49 Adaptation finance has not been targeted more towards more vulnerable countries (Barrett, 2014; Weiler and
50 Sanubi, 2019; Doshi and Garschagen, 2020; Savvidou and Atteridge, 2021). Reasons for this include fast-
51 growing middle-income countries offering larger gains in emission reductions, so finance has favoured
52 mitigation in these economies, even within sub-Saharan Africa, and as more climate finance uses debt
53 instruments, mitigation projects are further preferred because returns are perceived to be more certain (Rai et
54 al., 2016; Lee and Hong, 2018; Carty et al., 2020; Simpson et al., 2021c).
55
56 Many adaptation interventions for most vulnerable countries and communities provide no adequate financial
57 return on investments and can therefore only be funded with concessional public finance (Cross-Chapter Box
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1 FINANCE in Chapter 17). Yet, public funds alone are insufficient to meet rapidly growing adaptation needs.
2 Public mechanisms can help leverage private sector finance for adaptation by reducing regulatory, cost and
3 market barriers through blended finance approaches, public-private partnerships, or innovative financial
4 instruments and structuring in support of private sector requirements for risk and investment returns, such as
5 green bonds (Cross-Chapter Box FINANCE in Chapter 17). Subnational actors can be core agents to
6 conceptualize, drive, and deliver adaptation responses and unlock domestic resources in the implementation
7 of adaptation action (CoM SSA, 2019; Omari-Motsumi et al., 2019), provided they are sufficiently resourced
8 and their participation and agency are supported.
9
10 Many African countries are at high risk of debt distress, especially due to the COVID-19 pandemic, and will
11 need to decrease their debt levels to have the fiscal space to invest in climate resilience (Estev鉶, 2020;
12 Dibley et al., 2021). As of mid-2021, the G20's Debt Service Suspension Initiative is providing temporary
13 relief for repayment of bilateral credit, but this has largely not been taken up by private lenders (Dibley et al.,
14 2021; World Bank, 2021). The total external debt servicing payments combined for 44 African countries in
15 2019 were USD 75 billion (World Bank, 2018), far exceeding discussed levels of near-term climate finance.
16 Aligning debt relief with Paris Agreement goals could provide an important channel for increased financing
17 for climate action, for example, by allowing African countries to use their debt-servicing payments to
18 finance climate change mitigation and adaptation (Fenton et al., 2014). Governments can disclose climate
19 risks when taking on sovereign debt, and debt-for-climate resilience swaps could be used to reduce debt
20 burdens for low-income countries while supporting adaptation and mitigation (Dibley et al., 2021).
21
22 9.4.2 Governance
23
24 9.4.2.1 Governance Barriers
25
26 Overcoming governance barriers is a precondition to ensure successful adaptation and climate-resilient
27 development (Pasquini et al., 2015; Owen, 2020). Despite the ambitious climate targets across African
28 countries and renewed commitments in recent years (Zheng et al., 2019; Ozor and Nyambane, 2020),
29 governance barriers include, among others, slow policy implementation progress (Shackleton et al., 2015;
30 Taylor, 2016), incoherent and fragmented approaches (Zinngrebe et al., 2020; Nemakonde et al., 2021),
31 inadequate governance systems to manage climate finance (Granoff et al., 2016; Banga, 2019), poor
32 stakeholder participation (Sherman and Ford, 2014), gender inequalities (Andrijevic et al., 2020), unaligned
33 development and climate agendas (Musah-Surugu et al., 2019; Robinson, 2020), elite capture of climate
34 governance systems (Kita, 2019), hierarchical and complex state bureaucracy (Meissner and Jacobs, 2016;
35 Biesbroek et al., 2018) and weak, non-existent or fragmented subnational institutions (Paterson et al., 2017;
36 Musah-Surugu et al., 2019). Further, adaptation planning involves cross-cutting themes, multiple actors and
37 institutions with different objectives, jurisdictional authority and levels of power and resources, yet there is
38 often a lack of coordination, clear leadership or governance mandates (Shackleton et al., 2015; Leck and
39 Simon, 2018) and unequal power relations between African countries and developed countries can hinder
40 progress on governance of financial markets, budget allocations and technology transfer to address
41 addressing climate technology gaps in Africa (Rennkamp and Boyd, 2015; Olawuyi, 2018).
42
43 Policy implementation can be slow due to the absence of support mechanisms and dependency on funding by
44 international partners (Leck and Roberts, 2015; Ozor and Nyambane, 2020). In many countries, commitment
45 to climate policy objectives is low (Naess et al., 2015), particularly in light of competing development
46 imperatives and post-COVID-19 recovery efforts (Caetano et al., 2020), although COVID-19 recovery
47 efforts offer significant opportunities for health, economic and climate resilience co-benefits (Sections 9.4.3
48 and 9.11.5; Cross-Chapter Box COVID in Chapter 7). Another challenge relates to long-term planning and
49 decision-making which is hampered by uncertainty related to future socio-economic and GHG emissions
50 scenarios (Coen, 2021), political cycles and short-term political appointment terms (Pasquini et al., 2015).
51
52 Lack of community agency in climate governance affects ability for citizen-led climate interventions in
53 Africa (Antwi-Agyei et al., 2015; Mersha and Van Laerhoven, 2016). This is attributed partly to low civic
54 education, limited participation power of citizens and tokenism due to perceived lack of immediate benefits
55 (Odei Erdiaw-Kwasie et al., 2020), as well as low rates of climate change literacy in many regions (Simpson
56 et al., 2021a) (Section 9.4.3). Participation in climate policy also extends to the private sector, which has
57 been relatively uninvolved in adaptation discussions to date (Crick et al., 2018).
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1
2 Africa requires substantial resources and support to adapt to the unavoidable consequences of climate
3 change, a pertinent climate justice concern for governments. However, the mechanisms needed to redress
4 current power imbalances, structural and systemic inequality are often absent (Saraswat and Kumar, 2016)
5 (see Section 9.11.4) and policies that underpin environmental justice concerns, including distributive justice,
6 participation, recognition and capability (Shi et al., 2016; Chu et al., 2017) are also needed.
7
8 9.4.2.2 Good Governance
9
10 Good governance can contribute to positive climate outcomes and climate-resilient development in Africa
11 through long-term planning, development-focused policy environments, the development of robust and
12 transformational policy architecture, inclusive participation and timely implementation of NDCs (Bataille et
13 al., 2016; Werners et al., 2021) (see Table 9.3 for examples).
14
15
16 Table 9.3: Characteristics and examples of governance that contribute towards climate-resilient development in Africa
Governance Example
characteristic
Long-term Countries are mainstreaming adaptation into their long-term development cycles
development (UNFCCC Adaptation Committee, 2019). For example, Burkina Faso's National
planning Adaptation Plan elaborates its perspective to 2050 and links to its development pathways
(Government of Burkina Faso, 2015). Many African countries are also enhancing the
Climate justice and adaptation components of their long-term low emissions strategies.
inequality-focused Climate policies can be designed to include specific policy mechanisms (e.g., carbon taxes,
policies renewable energy subsidies) to maximise developmental gains while reducing inequality
(Andrijevic et al., 2020). For example, revenues from a carbon tax can be used to increase
social assistance programs that benefit poor people and reduce their vulnerability to
climate change (Hallegatte et al., 2016). Climate risk management can be integrated into
social protection and assistance programs, such as public works programs that increase
Interlinkages climate resilience (9.11)
between adaptation Cross-sectoral and multi-level governance approaches can harness synergies with the
and development SDGs, Paris Agreement and Agenda 2063 aspirations, helping to counter the adaptation
pathways deficit, promote sustainable resource use and contribute to poverty reduction (Niang et al.,
2014; IPBES, 2018; Roy et al., 2018b). Ghana, Namibia, Rwanda and Uganda all link
adaptation with disaster risk reduction in their NDCs (UNFCCC Adaptation Committee,
High-level 2019).
engagement Climate policies, traditionally overseen by environment ministries, are increasingly
receiving priority from finance and planning ministries. Zambia's Climate Change
Secretariat is currently led by the Ministry of Finance (Government of the Republic of
Zambia, 2010), while Tanzania's environmental division sits in the office of the Vice-
All-of-government President (Governmet of the United Republic of Tanzania, 2011).
approach In Kenya, the Climate Change Directorate is the secretariat for the National Climate
Change Commission, serving as an overarching mechanism to coordinate sectoral and
county level action (Government of the Republic of Kenya, 2018). In South Africa, the
National Committee on Climate Change, the Intergovernmental Committee on Climate
Change and the Presidential Climate Change Commission have been established to
enhance intergovernmental and multisectoral coordination on climate action (Climate
Participatory Action Tracker, 2021).
engagement Polycentric, bottom-up and locally implemented approaches are more able to include the
emergence of new actors (e.g., city networks, multinational companies and sub-state
entities), new instruments and levels (soft law instruments or transnational dynamics) and
new guiding principles and values (fairness, transparency and co-participation) (Leal Filho
et al., 2018; Sapiains et al., 2021). Case studies include the community-based,
participatory scenario planning approach used in Malawi to generate information for
farmers from seasonal forecasts, as well as the integration of climate risk into Lusaka's
Strategic Plan through engagement with city planners (Conway and Vincent, 2021;
Vincent and Conway, 2021). Many innovative solutions have been designed to promote
participation, such as Pamoja Voices toolkits in pastoralist communities in Northern
Tanzania (Greene et al., 2020).
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Inclusive and Kenya's Climate Change Directorate has a designated team to integrate gender into its
diverse national climate policies (Murray, 2019), while Seychelles' National Climate Change
stakeholders Council has allocated a seat exclusively for a youth candidate (Government of The
Seychelles, 2020). Tanzanian Climate-Smart Agriculture Alliance supports the integration
of farmers and builds strategic alliances to support climate processes (Nyasimi et al.,
Partnerships 2017).
Ghana, Kenya, Uganda and Zambia are developing anticipatory scenarios for low-carbon
climate-resilient development pathways for the agricultural sector, aimed at informing
input into national climate policy (Bali� et al., 2019). This science to policy to practice
interface is bridged through the inclusion of policymakers, practitioners and academics
(Dinesh et al., 2018). In Lusaka, Durban and other African cities, processes of engagement
and learning have built the trust and capacities needed to inform city-scale, climate-
NDC resilient decisions and associated actions (Taylor et al., 2021a; Taylor et al., 2021b).
implementation Rwanda has developed an indicator-based Monitoring, Reporting and Verification (MRV)
framework for tracking its NDC implementation and associated financial flows
(Government of Republic of Rwanda, 2020). Zambia has also integrated gender indicators
into its NDC implementation plan and is incorporating gender considerations into its MRV
framework (Murray, 2019).
1
2
3 African governments are developing and revising ambitious adaptation policies that are enforceable and
4 aligned with wider societal development goals, including an enabling environment for finance and
5 investment in the jobs and skills development necessary to support a just transition (ILO, 2019) (Section
6 9.4.5). If appropriately designed, such institutions offer the opportunity to foster adaptive governance which
7 is collaborative, multi-level and decentralised, offering integration of policy domains, flexibility and an
8 emphasis on non-coerciveness and adaptation (Ruhl, 2010).
9
10 Coordination across multiple sectors, supported with leadership from the highest levels of government, has
11 shown to improve implementation effectiveness and anticipated scaling up (Rigaud et al., 2018). This high-
12 level engagement promotes the inclusion of climate resilience and adaptation targets in national planning and
13 budgeting. Financial and capacity support is essential (Adenle et al., 2017; UNEP, 2021), as is the tracking
14 of national progress towards development goals (Box 9.6).
15
16 In Africa, climate governance occurs in a context of deep inequality and asymmetric power relations � both
17 within countries and between countries � making adequate mechanisms for multi-stakeholder participation
18 essential (Sapiains et al., 2021). This requires creation of avenues for the voices of marginalised groups in
19 policy processes and enabling policy environments that can catalyse inclusive action and transformational
20 responses to climate change (Totin et al., 2018; Revi et al., 2020; Ziervogel et al., 2021), safeguarding
21 protection against the climate harms of the most vulnerable in society, particularly of women and children
22 (see also Box 9.1). Community-based natural resource management in pastoral communities was observed to
23 improve institutional governance outcomes through involving community members in decision-making,
24 increasing the capacity of these communities to respond to climate change (Reid, 2014).
25
26 Specific indicators can be included in the performance metrics and monitoring frameworks for each sector,
27 policy intervention and budget planning cycle (Wojewska et al., 2021). Many countries in Africa are also
28 revamping their institutional coordination mechanisms to reflect an all-of-government approach and
29 partnership with non-State stakeholders with diverse capabilities and expertise (see examples from Rwanda
30 and Zambia in Table 9.3). This includes Cape Town's drought response in 2017/2018 where non-State actors
31 actively partnered with the state response around water management/savings practices (Simpson et al.,
32 2020a; Simpson et al., 2020b; Cole et al., 2021b).
33
34 9.4.3 Cross-Sectoral and Transboundary Solutions
35
36 Climate change does not present its problems and opportunities conveniently aligned with traditional sectors,
37 so mechanisms are needed to facilitate interactions and collaborations between people working in widely
38 different sectors (Simpson et al., 2021b). Traditional risk assessments typically only consider one climate
39 hazard and one sector at a time, but this can lead to substantial misestimation of risk because multiple climate
40 risks can interact to cause extreme impacts (Zscheischler et al., 2018; Simpson et al., 2021b).
41
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1 Because multiple risks are interlinked and can cascade and amplify risk across sectors, cross-sectoral
2 approaches that consider these interlinkages are essential for climate-resilient development, especially for
3 managing trade-offs and co-benefits between SDGs, mitigation and adaptation responses (Liu et al., 2018a).
4
5 In Africa, placing cross-sectoral approaches at the core of climate-resilient development provides significant
6 opportunities to deliver large benefits and/or avoids damages across multiple sectors including water, health,
7 ecosystems and economies (very high confidence) (Boxes 9.5, 9.6 and 9.7). They can also prevent adaptation
8 or mitigation action in one sector, exacerbating risks in other sectors and resulting in maladaptation, for
9 example, from large-scale dam construction or large-scale re/afforestation (e.g., water-energy-food nexus and
10 large-scale tree planting efforts) (Boxes 9.3 and 9.5).
11
12 Cross-sectoral or `nexus' approaches can improve the ability of decision-makers to foresee and prevent major
13 climate impacts. Barriers to developing nexus approaches arise from rigid sectoral planning, regulatory and
14 implementation procedures, entrenched interests and power structures and established sectoral communication
15 structures. Opportunities for overcoming these barriers include creating a dedicated home for co-development
16 of nexus risk assessment and solutions, promoting co-leadership of projects by multiple sectors, specific
17 budget allocations for nexus projects, facilitating and coordinating services, compiling useful strategies into
18 toolkits, ameliorating inequitable power relations among participants and measuring progress on nexus
19 approaches through metrics (Palmer et al., 2016; Baron et al., 2017).
20
21 Beyond cross-sectoral collaboration, international cooperation is vital to avert dangerous climate change as
22 its impacts reach beyond the jurisdiction of individual states. International good practice and regional
23 agreements, protocols and policies together recognise that regional integration, cooperative governance and
24 benefit-sharing approaches are cornerstones of effective resource security and climate change responses in
25 Africa (Jensen and Lange, 2013; World Bank, 2017a; Dombrowsky and Hensengerth, 2018). Natural
26 resource development, particularly governance of shared river basins, exemplifies opportunities for
27 governance responses for African nations that can be cooperative, regionally integrated and climate-resilient.
28
29 In Africa, climate vulnerability crosses geopolitical divides as regional clusters of fragile and high
30 vulnerability countries exist, emphasising the need for transboundary cooperation (Birkmann et al., 2021;
31 Buhaug and von Uexkull, 2021). Natural resource security is increasingly reliant on transboundary
32 governance, regional integration and cooperation (Namara and Giordano, 2017). There are 60 international
33 or shared river basins on the continent, a function of colonial divides and topography, with some basins
34 shared by four or more countries (UNECA, 2016; Popelka and Smith, 2020). Climate changes which result
35 in impact and risk pathways across country boundaries and regions (although with different levels of impact)
36 accelerate the urgency for integrated approaches to manage and benefit from shared resources and promote
37 their security for populations and economies (Namara and Giordano, 2017; Frame et al., 2018; Carter et al.,
38 2021). At the same time, natural resources such as water generate economic benefits shared across
39 boundaries, such as hydroelectric power generation and regional food security (Dombrowsky and
40 Hensengerth, 2018).
41
42 Poor governance, particularly at the transboundary level, can undermine water security and climate change is
43 likely to add new challenges to pre-existing dynamics, emphasising the necessity of formal transboundary
44 arrangements (Jensen and Lange, 2013; UNECA, 2016). Further, it can constrain access to critical financial
45 resources at a time when it is needed most. This is particularly the case when climate impact pathways
46 manifest at the transboundary level (Challinor et al., 2018; Simpson et al., 2021b), but where the need to
47 protect sovereign interests can block regionally integrated institutional arrangements that are pivotal for
48 accessing the multilateral climate funds for transboundary climate investments that include resilient
49 infrastructure and greater water benefits across Africa's shared river basins (Carter et al., 2021) (Cross-
50 Chapter Box INTEREG in Chapter 16).
51
52 In response, the African Development Bank is supporting two of the most climate-vulnerable and larger
53 African river basins to leverage GCF and GEF funds to finance Programmes for Integrated Development and
54 Adaptation to Climate Change (PIDACC). PIDACC finance is approved at the multinational level in the
55 Niger basin which is shared by 9 West and Central African States (AfDB, 2018c; GCF, 2018a), while a
56 PIDACC proposal is currently under development for the Zambezi basin (Zambezi Watercourse
57 Commission, 2021).
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1
2 Stakeholders across Africa are recognising the scale and severity of transboundary risks to water. Such risks
3 are twofold in nature, arising both from potential impacts due to climate change and from responses to
4 climate change (Simpson et al., 2021b). This awareness amongst stakeholders is leading to increasingly
5 progressive approaches to natural resource development which can also reduce risk across boundaries within
6 regions. For example, river basin organisations (RBOs) in southern Africa such as the Orange-Senqu and the
7 Okavango River Basin Commissions are revising treaties considered to predate the interrelated issues of
8 climate change, growing populations and water scarcity (OKACOM, 2020). In parts of West Africa, where
9 climate change is characterised by reduction of precipitation (Barry et al., 2018), regionally integrated and
10 climate-resilient economic investments for water resource development are enabled by the Senegal River
11 Basin Organisation (OMVS) which emphasises programme and project development, financing and
12 implementation in ensuing work plans (World Bank, 2020e), as does the Nile Basin Initiative (NBI) in North
13 and East Africa (Schmeier, 2017; Blumstein and Petersen-Perlman, 2021).
14
15 Enhanced transboundary governance arrangements suggest that countries are joining forces to coherently
16 manage and protect natural resources (Spalding-Fecher et al., 2014; AfDB, 2021). Underlying governance
17 issues and political economy interests block or advance such transitions to regionally integrated resource
18 management and benefit-sharing, the market drivers of water security (AMCOW, 2012; Soliev et al., 2015).
19 Angola, for example, outlines regional adaptation as a priority and one of its unconditional adaptation
20 strategies (which is already funded) is enhancing resilience in the Benguela fisheries system, a project shared
21 with Namibia and South Africa (GEF and FAO, 2021). Another example is The Great Green Wall for the
22 Sahara and Sahel Initiative which was launched in 2007, with the aim of tackling land degradation in Africa
23 (UNCCD, 2020). This transboundary project, led by the African Union Commission, is being implemented
24 in more than 20 countries across Africa's Sahel region, in cooperation with international partners including
25 UNCCD, GEF and the World Bank among others. Approximately USD 10 billion have been mobilised
26 and/or promised for this initiative (UNCCD, 2020). Such statements demonstrate the increasing
27 identification of transboundary risks and approaches to manage and adapt to them as areas of `common
28 concern' that require cooperative adaptation actions. Accelerating strengthened transboundary water and
29 climate governance needs to integrate these climate drivers of compromised water security. The role of
30 institutions such as OVMS and the NBI have demonstrated they can be played in influencing economic
31 behaviour among riparian countries of shared river basins highlighting that institutions are an integral part of
32 climate governance in evolving economic systems (Hodgson, 2000).
33
34 9.4.4 Climate Change Adaptation Law in Africa
35
36 9.4.4.1 The Rise of Climate Change Adaptation Law
37
38 Robust legislative frameworks, both climate change specific and non-specific, can foster adaptive responses
39 to climate change, particularly in Least Developed Countries (LDCs) (Nachmany et al., 2017). As discussed
40 in Chapter 17, there are multiple reasons for this. The successful implementation of policy objectives across
41 the continent is often contingent upon or at least supported by an underlying legislative framework
42 (Averchenkova and Matikainen, 2017; Scotford et al., 2017). There are also wider systemic and structural
43 reasons for developing climate change legislation, including the promotion of coordination within
44 government, its policy entrenching role, its symbolic value and its potential to support climate finance flows
45 (Nachmany et al., 2017; Scotford and Minas, 2019).
46
47 Legal systems, however, also have the potential to be maladaptive. Laws may be brittle, often assuming and
48 reinforcing a static state, and the boundary of the law may not align to the relevant location, scale or impact
49 (Craig, 2010; Arnold and Gunderson, 2013; Wenta et al., 2019). This necessitates the review and revision of
50 existing laws to remove such barriers and foster adaptive management (Craig, 2010; Ruhl, 2010; Cosens et
51 al., 2017) and, where necessary, the promulgation of new laws.
52
53
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1
2 Figure 9.10: Progress in development of climate change framework law in Africa derived from an analysis of public
3 databases of African laws (author's own map), data drawn from (Government of Niger, 1998; Government of Liberia,
4 2002; Government of Algeria, 2004; Government of Tanzania, 2004; Government of Central African Republic, 2008;
5 Government of Lesotho, 2008; Government of Togo, 2008; Government of Guinea Bissau, 2011; Government of Ivory
6 Coast, 2012; Government of Rwanda, 2012; Government of Sierra Leone, 2012; Government of Cape Verde, 2014;
7 Government of Morocco, 2014; Government of Mozambique, 2014; Government of Madagascar, 2015; Government of
8 the Seychelles, 2015; Government of Gabon, 2016; Government of Kenya, 2016; Government of Mali, 2016;
9 Government of Zambia, 2016; Government of Malawi, 2017; Government of Nigeria, 2017; Government of Benin,
10 2018; Government of Ghana, 2018; Government of South Africa, 2018; Government of Uganda, 2018; Government of
11 Zimbabwe, 2019 sources quoted as of September 2019).
12
13
14 There has been a rise in framework and sectoral climate change laws across Africa, as illustrated in Figure
15 9.10 above. The map illustrates the two framework statutes which have been promulgated in Benin and
16 Kenya, as well as the three framework Bills which have been drafted in Nigeria, South Africa and Uganda.
17 There are also discussions taking place in Zimbabwe and Ghana regarding the potential development of a
18 draft framework Climate Change Bill. A review of the climate change framework laws indicates evidence of
19 cross-pollination in design across African jurisdictions, creating the potential for a unique and regionally
20 appropriate body of law with a strong focus on adaptation responses (Rumble, 2019). As discussed in
21 Chapter 17, however, there remains the need for in-country expert input on how the domestic legal landscape
22 may influence their operation, and for each jurisdiction to independently interrogate its adaptation needs and
23 objectives (Scotford et al., 2017).
24
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1 Numerous African states have also included dedicated climate change-related provisions within various
2 existing statutes which regulate the environment or disaster management. For example, Tanzania's
3 Environmental Management Act 20 of 2004 contains dedicated provisions to address climate change.
4 Rwanda's Law on Environment 48/2018 also contains detailed provisions on mainstreaming climate change
5 into development planning processes, education on climate change, vulnerability assessments and the
6 promotion of measures to enhance adaptive capacity. Some countries have also developed laws dedicated to
7 a specific aspect of adaptation. For example, the Conservation and Climate Adaptation Trust of Seychelles
8 Act 18 of 2015 establishes a trust fund to finance climate change adaptation responses in Seychelles.
9 Similarly, many countries including Algeria, Burkina Faso, Djibouti, Ghana, Namibia, Malawi, Mauritius,
10 Madagascar, Mozambique, Tanzania and South Africa have dedicated disaster management laws. At this
11 stage, it is still too early to determine whether these laws are having any substantive influence in
12 strengthening resilience and reducing vulnerability and, as discussed in Chapter 17, this is identified as a
13 knowledge gap requiring further research.
14
15 9.4.4.2 Common Themes in Framework Laws
16
17 Laws are now being developed to formalise and entrench institutional structures, specifying their mandate,
18 function, membership and related procedures. A useful example of such an approach can be found in the
19 Nigerian Climate Change Bill which establishes the National Climate Council on Climate Change headed
20 and chaired by the Vice-President, with a wide membership of Ministers, the Chairmen of the Governors'
21 Forum and Association of Local Governments, as well as the private sector and non-governmental
22 organisation (NGO) representatives.
23
24 Climate change framework laws can play an instrumental role in achieving mainstreaming by directing
25 relevant actors to integrate adaptation considerations into existing mandates, operations and planning
26 instruments (Rumble, 2019). By way of example, the South African Draft Climate Change Bill contains a
27 general duty to `coordinate and harmonise the policies, plans, programmes and decisions of the national,
28 provincial and local spheres of government' to achieve, among other things, the climate change objectives of
29 the Bill and national adaptation objectives.
30
31 Another common theme is the requirement to develop national climate change adaptation strategies and
32 plans. Many laws further entrench their longevity by requiring them to be subject to strong community
33 participation and consultation, as demonstrated by the Kenyan Climate Change Act and the Nigerian Climate
34 Change Bill.
35
36 9.4.4.3 Local Climate Change Laws and Indigenous Knowledge Systems
37
38 The Paris Agreement acknowledges, in Article 7.5, that adaptation should be based on and guided by, among
39 other things, `traditional knowledge, knowledge of indigenous peoples and local knowledge systems'. The
40 accumulated knowledge within indigenous knowledge systems is particularly important as it can assist
41 governments in determining how the climate is changing, how to characterise these impacts and provide
42 lessons for adaptation (Salick and Ross, 2009). In this context, indigenous knowledge systems can play an
43 important role in the effective design of local laws (Mwanga, 2019) as well as national laws. Doing so can
44 contribute to the success of climate change response strategies, including enhancing local participation and
45 the implementation of community-based and ecosystem-based adaptations (Chanza and de Wit, 2016;
46 Mwanga, 2019). For example, the Makorongo Village Forest Management By-Law in Tanzania codifies
47 local customary practices relating to forest management and sustainable harvesting with associated dual
48 adaptation and mitigation benefits and includes all villagers in the decision-making processes relating to
49 forest management (Mwanga, 2019). The inclusion of beneficial indigenous knowledge systems within local
50 by-laws is contingent on the active involvement of members of the indigenous community and awareness of
51 climate change considerations within the local sphere of government, and a willingness to foster such
52 practices (Mwanga, 2019).
53
54 In addition to the advancement of indigenous knowledge in adaptive responses, it has been suggested that the
55 protection of the rights of indigenous peoples can have adaptive benefits, in particular through the protection
56 of land tenure rights (Ayanlade and Jegede, 2016). It has been argued that doing so will protect indigenous
57 peoples' lands and resources from overconsumption, secure the recognition of their cultural stewardship over
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1 the environment, provide the financial incentive for land stewardship and promote the application of their
2 unique knowledge on the sustainable development of that land and its preservation (Jaksa, 2006; Ayanlade
3 and Jegede, 2016). Not only can a lack of protection of indigenous legal tenure undermine these objectives,
4 but a number of African laws may actively work against them. For example, a review of Tanzanian and
5 Zambian laws highlighted existing provisions that empowered the state to terminate or criminalise the
6 occupation of vacant, undeveloped or fallow lands, which undermined the occupation by indigenous peoples
7 of forests and other uncultivated lands (Ayanlade and Jegede, 2016).
8
9 9.4.5 Climate Services, Perception and Literacy.
10
11 Policy actors across Africa perceive that anthropogenic climate change is already impacting their locales
12 through a range of negative socioeconomic and environmental effects (Pasquini, 2020; Steynor and Pasquini,
13 2020). They are highly concerned about and motivated to address these impacts (Hambira and Saarinen,
14 2015; Pasquini, 2020). Transformative responses to the impacts of climate change facilitate climate-resilient
15 development and are informed by perceptions of climate variability and change and climate change literacy
16 (Figure 9.11).
17
18
19
20 Figure 9.11: The importance of climate services and climate change literacy for more transformative responses to
21 climate change in Africa (adapted from Simpson et al., 2021a). Climate services promote Climate Resilient
22 Development by providing climate information for adaptation decision-making (Street, 2016; Vaughan et al., 2018).
23 However, scalable uptake of climate services relies on climate risk perception of users which is largely driven in Africa
24 by experience and perception of local climate changes (Jacobs and Street, 2020; Steynor et al., 2020b; Steynor and
25 Pasquini, 2020). Perception of climate change in Africa can occur without the knowledge of its anthropogenic causes
26 and its effect on risk, as awareness of the concept of climate change is generally low across Africa (Lee et al., 2015;
27 Alemayehu and Bewket, 2017; Andrews and Smirnov, 2020). This can lead to coping responses to climate change
28 which fall short of adaptation. Climate change literacy can fill this knowledge gap and, together with climate services,
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1 extend responses to climate change to include consideration of future risk through awareness of the anthropogenic cause
2 of climate change and its effect on risk (IPCC, 2019b; Simpson et al., 2021a). Maps a-c: (a) Percentage of times
3 scholarship on Africa record that perception of temperature changes (left), (b) precipitation changes (centre), aligned
4 with available meteorological or climate records for 144 country studies across 33 African countries (Size of bubble
5 indicates number of studies per country for both Panels a and b; Panel b, alignment with temperature changes is
6 indicated for all studies within a country in red, and articles indicating no alignment in orange; while in panel c,
7 alignment with precipitation changes is indicated per country in dark blue and articles indicating no alignment in light
8 blue). Panel c) country-level rates of climate change literacy for 33 African countries (that is, percentage of the
9 population that have heard about climate change and think that human activity is wholly or partly the cause of climate
10 change) (adapted from Simpson et al., 2021a).
11
12
13 9.4.5.1 Climate Information and Services
14
15 Climate services (CS) broadly include the generation, tailoring and provision of climate information for use
16 in decision-making at all levels of society (Street, 2016; Vaughan et al., 2018). There is a range of climate
17 service providers in Africa, including primarily National Meteorological and Hydrological Services (NMHS)
18 and partner institutions, complemented by NGOs, the private sector and research institutions (Snow et al.,
19 2016; Harvey et al., 2019), which offer the potential for public-private partnerships (Winrock, 2018; Harvey
20 et al., 2019).
21
22 International development funding has progressed the provision of climate services and, together with
23 technological advances and capacity-building initiatives, has increased the reliability of climate services
24 across Africa (Vogel et al., 2019). Most CS investments have been towards the agricultural sector, with other
25 focal sectors including pastoralism, health, water, energy and disaster risk reduction having only small CS
26 initiatives directed towards them (Nkiaka et al., 2019; Carr et al., 2020). Despite this focus and investment,
27 however, there remains a mismatch between the supply and uptake of CS in Africa as information is often
28 inaccessible, unaffordable, not relevant to context or scale and is poorly communicated (Singh et al., 2018;
29 Antwi-Agyei et al., 2021) (Table 9.4; Sections 9.4.1.5.1 and 9.13.4.1). Observational data required for
30 effective regional climate services, including trend analyses, seasonal climate assessment, modelling and
31 model evaluation, is sparse and often of poor quality (Figure 9.11) and usually requires payment which
32 renders it unaffordable (Winrock, 2018).
33
34 A number of these challenges may be addressed through the transdisciplinary co-production of climate
35 services (Alexander and Dessai, 2019; Vogel et al., 2019; Carter et al., 2020). Co-production of climate
36 services involves climate information producers, practitioners and stakeholders, and other knowledge holders
37 participating in equitable partnerships and dialogues to collaboratively identify climate-based risk and
38 develop scale-relevant climate information to address this risk (Table 9.4) (Vincent et al., 2018; Carter et al.,
39 2020).
40
41
42 Table 9.4: Challenges and opportunities for Climate Services in Africa for the supply and uptake of climate services.
Challenges Opportunities/Solutions References Examples of Programmes that
address these challenges.
Reproduced from (Carter et al.,
2020) with permission.
Supply of climate services (Winrock, East Africa and the West African
Poor infrastructure (e.g., � International
non-functioning funding for 2018; Harvey et Sahel (ENACTS programme).
observational networks; observation al., 2019) Work with NMHS to provide
limited Internet networks, data (Snow et al., enhanced services by overcoming
bandwidth; lack of rescue and data 2016; World the challenges of data quality,
climate modelling sharing Bank Group, availability and access.
2016; Winrock, Creation of reliable climate
capacity; keeping pace � Regular NMHS
with changing budgets from 2018; Cullmann information suitable for national
technology). governments et al., 2020; and local decision-making using
� Public-private Meque et al., station observations and satellite
partnerships 2021) data to provide greater accuracy in
smaller space and time scales.
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Fragmented delivery of � Greater (Winrock, Rwanda (RCSA programme).
climate services. collaboration 2018; Hansen et improving climate services and
between the NMHS al., 2019a) agricultural risk management at
Mismatch in timescales: � and sector-specific local and national government
short-term information specialists to create (Jones et al., levels in the face of a variable and
more desirable, e.g., a central database of 2015; Vincent changing climate
seasonal predictions as sector-based climate et al., 2018;
opposed to decadal or services Hansen et al., Burkina Faso (BRACED project).
end of century Co-production of CS 2019a; Carr et Strengthening technical and
projections. climate service al., 2020; communication capacities of
products Sultan et al., national meteorological services to
Development funding � 2020) enable partners to jointly develop
Co-production of (Vincent et al., forecasts tailored to support agro-
interventions operate on climate service CS 2018; Vogel et pastoralists.
products al., 2019)
timescales that inhibit or Endogenously (Vincent et al., Burkina Faso (BRACED project).
driven climate 2020a) Actors recognised the need to
restrict effective � services (services ensure continuation of climate
that are developed services post-project. Burkina Faso
adaptation and neglect by regional actors, NMHS (ANAM) and National
not by remote, Council for Emergency Assistance
to build in usually developed and Rehabilitation (CONASUR)
nation actors) budgeted for the continued
considerations for communication of climate services
and training of focal weather
sustainability post the intermediaries. Local radio stations
agreed to continue transmitting
funded intervention. climate services.
Use of climate services (Jones et al., Kenya, Ethiopia, Ghana, Niger and
Insufficient access to � Capacity 2015; Winrock, Malawi (ALP Programme).
2018; Hansen et Co-production of relevant
usable data, including development al., 2019a; information for decision-making
Hansen et al., and planning at seasonal time
station data, and initiatives for CS 2019c; Mercy scales. The methods and media for
Corps, 2019; communication and messages
information suited to the providers, Nkiaka et al., differ between different users.
2019; Carr et Strong emphasis on participation
decision context intermediaries al., 2020; by women.
Cullmann et al.,
(including accessibility (including extension 2020; Gumucio Cities in Zambia, Namibia,
et al., 2020; Mozambique, Zimbabwe,
limitations based on agents, NGO Sultan et al., Botswana, Malawi and South
2020) Africa (FRACTAL programme).
gender and social workers and others) (Figure 9.11) Repeated interactions between
each represented sector to learn
inequalities) and users (Snow et al., and more completely understand
� User needs 2016; Singh et the different contexts of each
al., 2018; represented party and build
assessments Vincent et al., understanding through an ethic of
� Consistent 2018; Nkiaka et collaboration for solving climate-
al., 2019; related problems in each unique
monitoring and Daniels et al., city.
2020)
evaluation of
climate services
Limited capacity of interventions
� Co-production of
users to understand or climate service
request appropriate CS products
products � Capacity
development
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Lack of user trust in the � Co-production of (Vincent et al., Tanzania (ENACTS programme).
information climate service 2018; Nkiaka et Co-production to inform malaria
products al., 2019; decisions systematically and
� Combine scientific Vaughan et al., change relationships, trust, and
and indigenous 2019; Vogel et demand in a manner that had not
forecasts al., 2019; been realised through previous
singular and siloed approaches.
� Demonstrate added Nyadzi et al.,
value of the climate 2021)
Socio-economic, and service (Snow et al.,
� Regular NMHS
institutional barriers budgets from 2016; World
(limited professional governments Bank Group,
mandates, financing � Public-private 2016; Winrock,
limitations, institutional partnerships 2018; Harvey et
al., 2019;
cooperation) � Supportive
institutions, policy Vincent et al.,
frameworks and 2020b)
individual capacity
and agency
1
2
3 However, the effectiveness of co-production processes are hindered by aspects such as inequitable power
4 relationships between different types of knowledge holders (e.g., scientists and practitioners), inequitable
5 distribution of funding between developed country versus African partners that favours developed country
6 partners, an inability to develop sustained trust relationships as a result of short-funding cycles, a lack of
7 flexibility due to product-focused engagements and the scalability of co-production to enable widespread
8 reach across Africa as the process is usually context-specific (high confidence) (Vincent et al., 2018; Vogel
9 et al., 2019; Vincent et al., 2020a).
10
11 Despite these challenges, the inclusive nature of co-production has had a positive influence on the uptake of
12 climate services into decision-making where it has been applied (Vincent et al., 2018; Vogel et al., 2019;
13 Carter et al., 2020; Chiputwa et al., 2020) (Table 9.4; Figure 9.12) (medium confidence), through sustained
14 inter/transdisciplinary relationships and capacity development (Norstr鰉 et al., 2020), strategic financial
15 investment (Section 9.13.4.1), fostering of ownership of resulting products and the combining of scientific
16 and other knowledge systems (Carter et al., 2020; Steynor et al., 2020a). There is high confidence that
17 together with improved institutional capacity building and strategic financial investment, climate services
18 can help African stakeholders adapt to projected climate risks (Section 9.13.4.1; Figure 9.11).
19
20
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1 Figure 9.12: Case studies of co-production programmes, the countries they occurred in, sectors involved (icons � see
2 key) and programmes under which the engagements occurred (numbers). Programmes listed are (1) AMMA-2050, (2,3)
3 BRACED, (4) RCSA, (5) ALP, (6) Climate Risk Narratives, (7) ENACTS, (8) FATHUM, (9) FRACTAL, (10)
4 FONERWA, (11) MHEWS, (12) Resilient Transport Strategic Assessment , (13) RRA, (14) UMFULA, (15) IRRP, (16)
5 PRISE, (17) NMA ENACTS, (18) REACH, (19) DARAJA, (20) ForPAc, (21) HIWAY, (22) HyCRYSTAL, (23)
6 SCIPEA, (24) Weather Wise. See Carter et al. (2020) for details and outcomes of each engagement. Source (Carter et
7 al., 2020).
8
9
10 9.4.5.2 Community Perceptions of Climate Variability and Change
11
12 Perceptions of climate variability and change affect whether and how individuals and institutions act, and
13 thus contribute to the success or failure of adaptation policies related to weather and climate (Silvestri et al.,
14 2012; Arbuckle et al., 2015; Simpson et al., 2021a).
15
16 A recent Afrobarometer study covering 34 African countries found 67% of Africans perceive climate
17 conditions for agricultural production to have worsened over time, and report drought as the main extreme
18 weather event to have worsened in the past decade (Selormey et al., 2019). Of these participants, across all
19 socioeconomic strata, 71% of those who were aware of the concept of climate change agreed that it needs to
20 be stopped, but only 51% expressed confidence about their ability to make a difference. East Africans (63%)
21 were almost twice as likely as North Africans (35%) to report that the weather for growing crops had
22 worsened. Additionally, people engaged in occupations related to agriculture (farming, fishing or forestry)
23 were more likely to report negative weather effects (59%) than those with other livelihoods (45%) (Selormey
24 et al., 2019). Similar perceptions have been reported among a diversity of rural communities in many sub-
25 Saharan African countries (Asiyanbi, 2015; Mahl et al., 2020; Simpson et al., 2021a).
26
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1 Rural communities, particularly farmers, have been the most studied groups for climate change perception.
2 They perceive the climate to be changing, most often reporting changes in rainfall variability, increased dry
3 spells, decreases in rainfall and increased temperatures or temperature extremes, and perceive these changes
4 to bring a range of negative socioeconomic and environmental effects (Alemayehu and Bewket, 2017;
5 Liverpool-Tasie et al., 2020; Simpson et al., 2021a). In some cases, farmers' perceptions of changes in
6 weather and climate frequently match climate records for decreased precipitation totals, increased drought
7 frequency, shorter rainy season and rainy season delay and increased temperatures (Rurinda et al., 2014;
8 Boansi et al., 2017; Ayanlade et al., 2018) (Figure 9.11), but not in all cases or not for all perceived changes,
9 with common discrepancies in perceived lower rainfall totals (Alemayehu and Bewket, 2017; Ayal and Leal
10 Filho, 2017; Simpson et al., 2021a).
11
12 Farming experience, access to extension services and increasing age are the most frequently cited factors
13 positively influencing the perceptions of climate changes (Alemayehu and Bewket, 2017; Oduniyi and
14 Tekana, 2019). Personal experience of climate-related changes and their impacts appears to be an important
15 factor influencing perceptions through shaping negative associations, for example, experience of flash floods
16 (Elshirbiny and Abrahamse, 2020) or direct effect on economic activity, indicating that perception is not
17 restricted to crop farmers (Liverpool-Tasie et al., 2020). However, perception commonly has misconceptions
18 about the causes of climate change which has implications for climate action (Elshirbiny and Abrahamse,
19 2020), highlighting the importance of climate change literacy.
20
21 9.4.5.3 Climate Change Literacy
22
23 Understanding the human cause of climate change has been shown to be a strong predictor of climate change
24 risk perception (Lee et al., 2015) and a critical knowledge foundation that can affect the difference between
25 coping responses and more informed and transformative adaptation (Oladipo, 2015; Mutandwa et al., 2019)
26 (Figure 9.11). At a minimum, climate change literacy includes both having heard of climate change and
27 understanding it is, at least in part, caused by people (Simpson et al., 2021a). However, large inequalities in
28 climate change literacy exist between and within countries and communities across Africa.
29
30 The average national climate change literacy rate in Africa is only 39% (country rates range from 23-66%)
31 (Figure 9.11). Of 394 sub-national regions surveyed by Afrobarometer, 8% (37 regions in 16 countries) have
32 a climate change literacy rate lower than 20%, while only 2% (8 regions) score higher than 80% which is
33 common across European countries (Simpson et al., 2021a). Striking differences exist when comparing sub-
34 national units within countries. Climate change literacy rates in Nigeria range from 71% in Kwara to 5% in
35 Kano, and within Botswana from 69% in Lobatse to only 6% in Kweneng West (Simpson et al., 2021a).
36 Education is the strongest positive predictor of climate change literacy, particularly tertiary education, but
37 poverty decreases climate change literacy and climate change literacy rates average 12.8% lower for women
38 than men (Simpson et al., 2021a).
39
40 As the identified drivers of climate change literacy overlap with broader developmental challenges on the
41 continent, policies targeting these predictors can potentially yield co-benefits for both climate change
42 adaptation as well as progress towards SDGs, particularly education and gender equality (Simpson et al.,
43 2021a). Progress towards greater climate change literacy affords a concrete opportunity to mainstream
44 climate change within core national and sub-national developmental agendas in Africa towards more
45 climate-resilient development pathways. Synergies with climate services can also overcome gendered
46 deficits, for example, although women are generally less climate change aware and more vulnerable to
47 climate change than men in Africa, they are generally more likely to adopt climate-resilient crops when they
48 are climate change aware and have exposure to extension services (Acevedo et al., 2020; Simpson et al.,
49 2021a).
50
51
52 [START BOX 9.1 HERE]
53
54 Box 9.1: Vulnerability Synthesis
55
56 Vulnerability in Africa is socially, culturally and geographically differentiated among climatic regions,
57 countries and local communities, with climate change impacting the health, livelihoods and food security of
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1 different groups to different extents (Gan et al., 2016; Onyango et al., 2016a; Gumucio et al., 2020). This
2 synthesis emphasises intersectional diversity within vulnerable groups as well as their position within
3 dynamic social and cultural contexts (Wisner, 2016; Kuran et al., 2020), and highlights the differential
4 impacts of climate change and restricted adaptation options available to vulnerable groups across African
5 countries (see also Cross-Chapter Box GENDER in Chapter 18).
6
7
8
9 Figure Box 9.1.1: Factors contributing to the progression of vulnerability in African contexts considering their
10 socioeconomic processes, resource access and livelihood changes, and intersectional vulnerability among social groups.
11 Figure reflects a synthesis of vulnerability across sections of this chapter and highlights the compounding interactions
12 of multiple dimensions of vulnerability (Potts, 2008; Nielsen and Reenberg, 2010; Akresh et al., 2011; Eriksen et al.,
13 2011; Beymer-Farris and Bassett, 2012; Davis et al., 2012; Adom, 2014; Akello, 2014; Dickovick, 2014; Headey and
14 Jayne, 2014; Otzelberger, 2014; Conteh, 2015; Huntjens and Nachbar, 2015; Spencer, 2015; Adetula et al., 2016;
15 Djoudi et al., 2016; Kuper et al., 2016; Stark and Landis, 2016; Allard, 2017; Anderson, 2017; Asfaw et al., 2017; Hufe
16 and Heuermann, 2017; Hulme, 2017; Paul and wa Gthnji, 2017; Rao et al., 2017; Serdeczny et al., 2017; Tesfamariam
17 and Zinyengere, 2017; Tierney et al., 2017; Waha et al., 2017; Chihambakwe et al., 2018; Cholo et al., 2018; Jenkins et
18 al., 2018; Keahey, 2018; Lwasa et al., 2018; Makara, 2018; Nyasimi et al., 2018; Petesch et al., 2018; Schuman et al.,
19 2018; Theis et al., 2018; van Baalen and Mobj鰎k, 2018; van der Zwaan et al., 2018; Adepoju, 2019; Adzawla et al.,
20 2019b; Bryceson, 2019; Grasham et al., 2019; Jayne et al., 2019a; Lowe et al., 2019; Lunga et al., 2019; OGAR and
21 Bassey, 2019; Onwutuebe, 2019; Ramutsindela and B黶cher, 2019; Sulieman and Young, 2019; Torabi and Noori,
22 2019; Adeniran and Daniell, 2020; Alexander, 2020; Clay and Zimmerer, 2020; Devonald et al., 2020; Dolislager et al.,
23 2020; Edo et al., 2020; Kaczan and Orgill-Meyer, 2020; Lammers et al., 2020; World Bank, 2020b; Asiama et al., 2021;
24 Azong and Kelso, 2021; Birgen, 2021; Paalo and Issifu, 2021).
25
26
27 Vulnerability and exposure to the impacts of climate change are complex and affected by multiple,
28 interacting non-climatic processes, which together influence risk including socioeconomic processes (Lwasa
29 et al., 2018; UNCTAD, 2020), resource access and livelihood changes (Jayne et al., 2019b), and
30 intersectional vulnerability among social groups (Rao et al., 2020) (Figure Box 9.1.1). Socioeconomic
31 processes encompass broader social, economic and governance trends, such as expanded investment in large
32 energy and transportation infrastructure projects (Adeniran and Daniell, 2020), rising external debt (Edo et
33 al., 2020), changing role of the state in social development (Dickovick, 2014), environmental management
34 (Ramutsindela and B黶cher, 2019) and conflict, as well as those emanating from climate change mitigation
35 and adaptation projects (Beymer-Farris and Bassett, 2012; van Baalen and Mobj鰎k, 2018; Simpson et al.,
36 2021b). These macro trends shape both urban and rural livelihoods, including the growing diversification of
37 rural livelihoods through engagement in the informal sector and other non-farm activities, and are mediated
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1 by complex and intersecting factors like gender, ethnicity, class, age, disability and other dimensions of
2 social status that influence access to resources (Luo et al., 2019). Research increasingly highlights the
3 intersectionality of multiple dimensions of social identity and status that are associated with greater
4 susceptibility to loss and harm (Caparoci Nogueira et al., 2018; Li et al., 2018).
5
6 Arid and semi-arid countries in the Sahelian belt and the greater Horn of Africa are often identified as the
7 most vulnerable regions on the continent (Closset et al., 2017; Serdeczny et al., 2017). Particularly
8 vulnerable groups include pastoralists (Wangui, 2018; Ayanlade and Ojebisi, 2019), fishing communities
9 (Belhabib et al., 2016; Muringai et al., 2019a), small-scale farmers (Ayanlade et al., 2017; Mogomotsi et al.,
10 2020) (see Section 9.8.1) and residents of formal and informal urban settlements (see Section 9.9.2).
11 Research has identified key macro drivers as well as the multiple dimensions of social status that mediate
12 differential vulnerability in different African contexts. For example, the contemporary vulnerability of small-
13 scale rural producers in semi-arid northern Ghana has been shaped by colonial economic transformations
14 (Ahmed et al., 2016), more recent neoliberal reforms reducing state support (Fieldman, 2011) and the
15 disruption of local food systems due to increasing grain imports (Nyantakyi-Frimpong and Bezner-Kerr,
16 2015). Age interacts with other dimensions of social status, shaping differential vulnerability in several
17 ways. Projected increases in mean temperatures and longer and more intense heat waves (Figure Box 9.1.1)
18 may increase health risks for children and elderly populations by increasing risks associated with heat stress
19 (Bangira et al., 2015; Cairncross et al., 2018). Temperature extremes are associated with increased risk of
20 mortality in Ghana, Burkina Faso, Kenya and South Africa, with greatest increases among children and the
21 elderly (Bangira et al., 2015; Amegah et al., 2016; Omonijo, 2017; Wiru et al., 2019) (see Section
22 9.10.2.3.1).
23
24 Rural African women are often disadvantaged by traditional, patriarchal decision-making processes and lack
25 of access to land � issues compounded by kinship systems (that, is matrilineal or patrilineal), migrant status,
26 age, type of household, livelihood orientation and disability in determining their adaptive options (Ahmed et
27 al., 2016) (sees Section 9.8.1 and 9.11.1.2; Box 9.8). Differential agricultural productivity between men and
28 women is about 20�30% or more in dryland regions of Ethiopia and Nigeria (Ghanem, 2011) and challenges
29 women's ability to adapt to climate change. Limited access to agricultural resources and limited benefits
30 from agricultural policies, compounded by other social and cultural factors, make women more vulnerable to
31 climatic risks (Shukla et al., 2021). Kinship systems can contribute to their vulnerability and capacity to
32 adapt. Women in matrilineal systems have greater bargaining power and have access to more resources than
33 those in patrilineal systems (Chigbu, 2019; Robinson and Gottlieb, 2021) (see Sections 9.8.1 and 9.11.1.2).
34
35 Knowledge Gaps and Recommendations
36
37 The differential impacts of climate change on and adaptation options available to vulnerable groups in Africa
38 are a critical knowledge gap. More research is needed to examine the intersection of different dimensions of
39 social status on climate change vulnerability in Africa (Thompson-Hall et al., 2016; Oluwatimilehin and
40 Ayanlade, 2021). More analysis of vulnerability based on gender and other social and cultural factors is
41 needed to fully understand the impacts of climate change, the interaction of divergent adaptive strategies, as
42 well as the development of targeted adaptation and mitigation strategies, for example, for women in
43 patrilineal kinship systems, people living with disabilities, youth, girls and the elderly. Finally, there is an
44 urgent need to build capacity among those conducting vulnerability assessments, so that they are familiar
45 with this intersectionality lens.
46
47 Additional information and capacity development through education and early warning systems could
48 enhance vulnerable groups' ability to cope and adapt their livelihoods (Jaka and Shava, 2018). However,
49 some groups of people may struggle to translate information into actual changes (Makate et al., 2019;
50 McOmber et al., 2019). Lack of access to assets and social networks, for example, among older populations,
51 are critical limitations to locally-driven or autonomous adaptation and limit potential benefits from planned
52 adaptation actions (e.g., adoption of agricultural technologies or effective use of early warning systems).
53 There is an urgent need for societal and political change to realise potential benefits for these vulnerable
54 groups in the long term (Nyasimi et al., 2018). There is a need for gender-sensitive climate change policies
55 in many African countries and gender-responsive policies, implementation plans and budgets for all local-
56 level initiatives (Wrigley-Asante et al., 2019).
57
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1 [END BOX 9.1 HERE]
2
3
4 9.5 Observed and Projected Climate Change
5
6 This section assesses observed and projected climate change over Africa. In Working Group I of the IPCC
7 AR6 (WGI), four chapters make regional assessments of observed and projected climate change (Doblas-
8 Reyes et al., 2021; Guti閞rez et al., 2021; Ranasinghe et al., 2021; Seneviratne et al., 2021), which facilitates
9 a more nuanced assessment in this section of climate and ocean phenomena that impact African systems.
10
11 9.5.1 Climate Hazards in Africa
12
13 Human-caused temperature increases are detected across Africa and many regions have warmed more
14 rapidly than the global average (Figure 9.13a) (Ranasinghe et al., 2021) and a signal of increased annual
15 heatwave frequency has already emerged from the background natural variability over the whole continent
16 (Engdaw et al., 2021) (Figure 9.14). However, detection of statistically significant rainfall trends is evident
17 in only a few regions (Figure 9.13b), and in some regions different observed precipitation datasets disagree
18 on the direction of rainfall trends (Panitz et al., 2013; Sylla et al., 2013; Contractor et al., 2020). The
19 uncertainty of observed rainfall trends results from a number of sources, including high interannual and
20 decadal rainfall variability, different methodologies used in developing rainfall products and a lack of and
21 poor quality of rainfall station data (Figure 9.15) (Guti閞rez et al., 2021).
22
23 With increased greenhouse gas emissions, mean temperature is projected to increase over the whole
24 continent, as are temperature extremes over most of the continent (Figure 9.16a,b). Increased mean annual
25 rainfall is projected over the eastern Sahel, eastern East Africa and Central Africa (Figures 9.16c and 9.14).
26 In contrast, reduced mean annual rainfall and increased drought (meteorological and agricultural) are
27 projected over southwestern Southern Africa and coastal North Africa, with drought in part as a result of
28 increasing atmospheric evaporative demand due to higher temperatures (Figure 9.16e) (Ukkola et al., 2020;
29 Ranasinghe et al., 2021; Seneviratne et al., 2021). The frequency and intensity of heavy precipitation are
30 projected to increase across most of Africa, except northern and southwestern Africa (Figures 9.16d and
31 9.14).
32
33 Most African countries are expected to experience high temperatures unprecedented in their recent history
34 earlier in this century than generally wealthier, higher latitude countries (high confidence). As low latitudes
35 have lower internal climate variability (e.g. low seasonality), low-latitude African countries are projected to
36 have their populations exposed to large increases in frequency of daily temperature extremes (hotter than
37 99.9% of their historical records) earlier in the 21st century compared to generally wealthier nations at
38 higher latitudes (Harrington et al., 2016; Chen et al., 2021; Doblas-Reyes et al., 2021; Guti閞rez et al., 2021).
39 Although higher warming rates are projected over high latitudes during the first half of this century, societies
40 and environments in low-latitude, low-income countries are projected to become exposed to unprecedented
41 climates before those in high latitude, developed countries (Frame et al., 2017; Harrington et al., 2017;
42 Guti閞rez et al., 2021). For example, beyond 2050, in Central Africa and coastal West Africa 10 months of
43 every year will be hotter than any month in the period 1950�2000 under a high emissions scenario (RCP8.5)
44 (Harrington et al., 2017; Guti閞rez et al., 2021). Ambitious, near-term mitigation will provide the largest
45 reductions in exposure to unprecedented high temperatures for populations in low-latitude regions, such as
46 across tropical Africa (Harrington et al., 2016; Frame et al., 2017).
47
48
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1 Figure 9.13: Mean observed trends calculated for the common 1980-2015 period in (a) 2-meter temperature in degrees
2 Celsius per decade and (b) precipitation in millimetres per decade with respect to the climatological mean over this
3 period. The Climate Research Unit Time Series data (CRU TS) are used to compute temperature trends and the Global
4 Precipitation Climatology Centre data (GPCC) precipitation trends. Regions with no `x' hatching indicate statistically
5 significant trends over this period. The figures are derived from (Guti閞rez et al., 2021).
6
7
8 9.5.1.1 Station Data Limitations
9
10 Sustained station observation networks (Figure 9.15) are essential for the long-term analysis of local and
11 regional climate trends, including for temperature and rainfall, the calibration of satellite-derived climate
12 products, development of gridded climate datasets using interpolated and blended station-satellite products
13 that form the baseline from which climate change departures are measured, development and running of
14 early warning systems, climate projection and impact studies and extreme event attribution studies (Harrison
15 et al., 2019; Otto et al., 2020). However, production of salient climate information in Africa is hindered by
16 limited availability of and access to weather and climate data, especially in Central and North Africa (Figure
17 9.15) (Coulibaly et al., 2017; Hansen et al., 2019a). Existing weather infrastructure remains suboptimal for
18 development of reliable early warning systems (Africa Adaptation Initiative, 2018; Krell et al., 2021). For
19 example, it is estimated only 10% of ground-based observation networks are in Africa, and that 54% of
20 Africa's surface weather stations cannot capture data accurately (Africa Adaptation Initiative, 2018; World
21 Bank, 2020d). Some programmes are trying to address this issue, including the trans-African hydro-
22 meteorological observatory (van de Giesen et al., 2014), the West African Science Service Centre on Climate
23 Change and Adaptive Land Management (WASCAL) (Salack et al., 2019), the Southern African Science
24 Service Centre for Climate Change, Adaptive Land Management (SASSCAL) (Kaspar et al., 2015) and
25 AMMA-CATCH (Galle et al., 2018). However, the sustainability of observation networks beyond the life of
26 these programmes is uncertain as many African National Meteorological and Hydrology Services experience
27 structural, financial and technical barriers to maintaining these systems (Section 9.4.5).
28
29
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Heat and Cold Wet and Dry Climatic Impact-Driver Other
Wind Snow and Ice Coastal & Oceanic
Region Mean air temperature
Extreme heat
North Africa (MED)* Cold spell
Sahara (SAH) Frost
Mean precipitation
Western Africa (WAF) River flood
Central Africa (CAF) Heavy precipitation and pluvial flood
North Eastern Africa (NEAF) Landslide
South Eastern Africa (SEAF) Aridity
West Southern Africa (WSAF) Hydrological drought
East Southern Africa (WSAF) Agricultural and ecological drought
Madagascar (MDG) Fire weather
Mean wind speed
Severe wind storm
Tropical cyclone
Sand and dust storm
Snow, glacier and ice sheet
Hail
Relative sea level
Coastal flood
Coastal erosion
Marine heatwave
Ocean acidity
Air pollution weather
Atmospheric CO2 at surface
Radiation at surface
3 4
4
1 1 1 1 4
4
1,2 1 1 1 4
1 1 1 1 3 4
4
3 4,5
3 4,5
1. Contrasted regional signal: drying in western portions and wettening in eastern portions Key
2. Likely increase over the Ethiopian Highlands High confidence of decrease
3. Medium confidence of decrease in frequency and increase in intensity Medium confidence of decrease
4. Along sandy coasts and in the absence of additional sediment sinks/sources or any physical barriers to shoreline retreat. Low confidence in direction of change
5. Substantial parts of the ESAF and MDG coasts are projected to prograde if present-day ambient shoreline change rates continue Medium confidence of increase
* North Africa is not an official region of IPCC AR6, but assessment here is based upon the African portions of the Mediterranean High confidence of increase
Region Not broadly relevant
1 Figure 9.14: Summary of confidence in direction of projected change in climatic impact-drivers (CIDs) in Africa,
2 representing their aggregate characteristic changes for mid-century for medium emission scenarios RCP4.5, SSP3�4.5,
3 SRES A1B, or higher emissions scenarios (e.g., RCP8.5, SSP5璕CP8.5), within each AR6 WGI region (inset map)
4 approximately corresponding to global warming levels between 2癈 and 2.4癈 (for CIDs that are independent of sea-
5 level rise). CIDs are drivers of impacts that are of climatic origin (that is, physical climate system conditions including
6 means and extremes) that affect an element of society or ecosystems. The table also includes the assessment of
7 observed or projected time-of-emergence of the CID change signal from the natural inter-annual variability if found
8 with at least medium confidence (dots). Emergence of a climate change signal or trend refers to when a change in
9 climate (the `signal') becomes larger than the amplitude of natural or internal variations (the `noise'). The figure is a
10 modified version of Table 12.3 in Chapter 12 (Ranasinghe et al., 2021), please see this chapter for definitions of the
11 various climate impact drivers and the basis for confidence levels of the assessment. Please note these WGI regions do
12 not directly correspond to the regionalisation in this chapter nor do we assess climate risks for Madagascar.
13
14
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a b
1 Figure 9.15: Large regions of Africa lack regularly reporting and quality-controlled weather station data. Stations in
2 Africa with quality-controlled station data used in developing the Rainfall Estimates on a Gridded Network (REGEN)
3 interpolated rainfall product (Harrison et al., 2019). Panel (a) provides a spatial representation of stations across the
4 continent since 1950 as black dots and red crosses, where red crosses represent stations that were still active in 2017.
5 Panel (b) demonstrates the decline in operational stations or stations with quality-controlled data since circa 1998,
6 which is largely a function of declining networks in a subset of countries. Figure is derived from (Contractor et al.,
7 2020).
8
9
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1
2 Figure 9.16: Projected changes of climate variables and hazards (relative to 1995�2014 average) at 1.5, 2 and 3
3 of global warming above pre-industrial (1850�1900). Rows are (a) Increase in mean annual temperature; (b) Increase in
4 number of days per year above 35 癈; (c) Change in average annual rainfall (%); (d) Change in heavy precipitation
5 represented by maximum 5-day precipitation (%); (e) Change in drought represented as the six-month standardized
6 precipitation index (%). Negative changes indicate areas where drought frequency, intensity and/or duration is projected
7 to increase. Positive changes show the opposite; (f) Increase in mean annual sea surface temperature (癈). All figures
8 are derived from the WGI Interactive Atlas and show results from between 26 to 33 CMIP6 global climate models,
9 depending on the climate variable. CMIP6 models include improved representations of physical, biological and
10 chemical processes as well as higher spatial resolutions compared to previous CMIP5 models (WGI CH3). Three
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1 categories of trend robustness are shown in the projection figures: (1) No hatching indicates a projected change is robust
2 and likely greater than natural climate variability (that is, 66% of models show change greater than natural variability,
3 and 80% of all models agree on sign of change); (2) Diagonal lines (\) indicate no robust change (<66% of models
4 show change greater than natural variability); (3) Crossed lines (X) indicate conflicting signals where at least 66% of
5 the models show change greater than natural variability, but <80% of all models agree on direction of change (Guti閞rez
6 et al., 2021).
7
8
9 9.5.2 North Africa
10
11 9.5.2.1 Temperature
12
13 Observations
14 Mean and seasonal temperatures have increased at twice the global rate over most regions in North Africa
15 due to anthropogenic climate change (Ranasinghe et al., 2021) (Figures 9.13a and 9.14) (high confidence).
16 Increasing temperature trends are particularly strong since the 1970s (between 0.2癈/decade and
17 0.4癈/decade), especially in the summer (Tanarhte et al., 2012; Donat et al., 2014a; Lelieveld et al., 2016).
18 Similar warming signals have been observed since the mid-1960s over the Sahara and the Sahel (Fontaine et
19 al., 2013; Moron et al., 2016). Trends in mean maximum (TX) and minimum (TN) temperatures range
20 between +2癈 and +3癈 per century over North Africa, and the frequencies of hot days (TX >90th percentile,
21 TX90p) and tropical nights (TN >20癈), as well as the frequencies of warm days and nights, roughly follow
22 these mean TX and TN trends (Fontaine et al., 2013; Moron et al., 2016; Ranasinghe et al., 2021;
23 Seneviratne et al., 2021). Warm spell duration has increased in many North African countries (Donat et al.,
24 2014a; Filahi et al., 2016; Lelieveld et al., 2016; Nashwan et al., 2018) and heatwave magnitude and spatial
25 extent have increased across North Africa since 1980, with an increase in the number of events since 2000
26 that is beyond the level of natural climate variability (Russo et al., 2016; Ceccherini et al., 2017; Engdaw et
27 al., 2021).
28
29 Projections
30 At 1.5癈, 2癈 and 3癈 of global warming above pre-industrial levels, mean annual temperatures in North
31 Africa are projected to be on average, 0.9癈, 1.5癈 and 2.6癈 warmer than the 1994�2005 average
32 respectively (Figure 9.16a). Warming is projected to be stronger in summer than winter (Lelieveld et al.,
33 2016; Dosio, 2017). The number of hot days is likely to increase by up to 90% by the end of the century
34 under RCP8.5 (global warming level [GWL] 4.4癈) (Guti閞rez et al., 2021; Ranasinghe et al., 2021) and hot
35 nights and the duration of warm spells to increase in the first half of the 21st century in both intermediate and
36 high emission scenarios (Patricola and Cook, 2010; Vizy and Cook, 2012; Lelieveld et al., 2016; Dosio,
37 2017; Filahi et al., 2017). Heatwaves are projected to become more frequent and intense even at 1.5癈 of
38 global warming (Guti閞rez et al., 2021; Ranasinghe et al., 2021). Children born in 2020, under a 1.5癈-
39 compatible scenario will be exposed to 4�6 times more heatwaves in their lifetimes compared to people born
40 in 1960; this exposure increases to 9�10 times more heatwaves for emission reduction pledges, limiting
41 global warming to 2.4癈 (Thiery et al., 2021).
42
43 9.5.2.2 Precipitation
44
45 Observations
46 Mean annual precipitation decreased over most of North Africa between 1971�2000 (Donat et al., 2014a;
47 Hertig et al., 2014; Nicholson et al., 2018; Zittis, 2018), with a gradual recovery to normal or wetter
48 conditions in Algeria and Tunisia since 2000 and over Morocco since 2008 (Nouaceur and Murrescu,
49 2016). Since the 1960s days with more than 10 mm of rainfall have decreased and the number of consecutive
50 dry days have increased in the eastern parts of North Africa, while in the western parts of North Africa heavy
51 rainfall and flooding has increased (Donat et al., 2014a). Aridity, the ratio of potential evaporation to
52 precipitation, has increased over the Mediterranean and North Africa due to significant decreases in
53 precipitation (Greve et al., 2019).
54
55 Projections
56 Mean annual precipitation is projected to decrease in North Africa at warming levels of 2癈 and higher (high
57 confidence) with the most pronounced decreases in the northwestern parts (Schilling et al., 2012; Filahi et al.,
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1 2017; Barcikowska et al., 2018; Ranasinghe et al., 2021) (Figures 9.14 and 9.16c). Meteorological drought
2 over Mediterranean North Africa in CMIP5 and CMIP6 models are projected to increase in duration from
3 approximately 2 months during 1950�2014 to approximately 4 months in the period 2050�2100 under
4 RCP8.5 and SSP5-85 (Ukkola et al., 2020). Extreme rainfall (monthly maximum 1-day rainfall � RX1day) in
5 the region is projected to decrease (Donat et al., 2019).
6
7 During 1984�2012, North Africa experienced a decreasing dust trend with North African dust explaining
8 more than 60% of global dust variations (Shao et al., 2013). Dust loadings and related air pollution hazards
9 (from fine particles that affect health) are projected to decrease in many regions of the Sahara as a result of
10 decreased wind speeds (Evan et al., 2016; Ranasinghe et al., 2021).
11
12 9.5.3 West Africa
13
14 9.5.3.1 Temperature
15
16 Observations
17 Observed mean annual and seasonal temperatures have increased 1�3癈 since the mid-1970s with the
18 highest increases in the Sahara and Sahel (Cook and Vizy, 2015; Lelieveld et al., 2016; Dosio, 2017;
19 Nikiema et al., 2017; Guti閞rez et al., 2021; Ranasinghe et al., 2021) (Figure 9.13a) and positive trends in
20 mean annual maximum (TX) and minimum (TN) of 0.16癈 and 0.28癈 per decade, respectively (Mouhamed
21 et al., 2013; Moron et al., 2016; Russo et al., 2016; Barry et al., 2018). The frequency of very hot days
22 (TX>35癈) and tropical nights has increased by 1�9 days and 4�13 nights per decade between 1961�2014
23 (Moron et al 2016), and cold nights have become less frequent (Fontaine et al., 2013; Mouhamed et al.,
24 2013; Barry et al., 2018). In the 21st century, heatwaves have become hotter, longer and more extended
25 compared to the last two decades of the 20th century (Mouhamed et al., 2013; Moron et al., 2016; Russo et
26 al., 2016; Barbier et al., 2018).
27
28 Projections
29 At 1.5癈, 2癈 and 3癈 of global warming above pre-industrial levels, mean annual temperatures in West
30 Africa are projected to be on average, 0.6癈, 1.1癈 and 2.1癈 warmer than the 1994�2005 average
31 respectively (Figure 9.16a). Under mid- and high-emission scenarios end of century summer temperatures
32 are projected to increase by 2癈 and 5癈, respectively (Sylla et al., 2015a; Russo et al., 2016; Dosio, 2017).
33 The annual number of hot days is projected to increase at all global warming levels with larger increases at
34 higher warming levels (Figure 9.16b). By 2060 the frequency of hot nights is projected to be almost double
35 the 1981�2010 average at GWL 2癈 (Dosio, 2017; Bathiany et al., 2018; Guti閞rez et al., 2021; Ranasinghe
36 et al., 2021). Heatwave frequency and intensity are projected to increase under all scenarios, but limiting
37 global warming to 1.5癈 leads to a decreased heatwave magnitude (�35%) and frequency (�37%) compared
38 to 2癈 global warming (Dosio, 2017; Weber et al., 2018; Nangombe et al., 2019). Children born in 2020,
39 under a 1.5癈-compatible scenario will be exposed to 4�6 times more heatwaves in their lifetimes compared
40 to people born in 1960; this exposure increases to 7�9 times more heatwaves at GWL 2.4癈 (Thiery et al.,
41 2021).
42
43 The number of dangerous heat days (TX >40.6) is projected to increase from approximately 60 per year in
44 1985�2005 to approximately 110, 130 and 140 under RCPs 2.6, 4.5 and 8.5, respectively, in the 2060s and to
45 105, 145 and 196 in the 2090s (Rohat et al., 2019). Over tropical West Africa, heat-related mortality risk
46 through increased heat and humidity is 6�9 times higher than the 1950�2005 average at GWL 2, 8�15
47 times at GWL 2.65 and 15�30 times at GWL 4.12 (Ahmadalipour and Moradkhani, 2018) (Coffel et al.,
48 2018). The number of potentially lethal heat days per year is projected to increase from <50 during 1995�
49 2005 to 50�150 at GWL 1.6, 100�250 at GWL 2.5 and 250�350 at GWL 4.4, with highest increases
50 in coastal regions (Mora et al., 2017). Increasing urbanization concentrates this exposure in cities, such as
51 Lagos, Niamey, Kano and Dakar (Coffel et al., 2018; Rohat et al., 2019) (Section 9.9.3.1).
52
53 9.5.3.2 Precipitation
54
55 Observations
56 Negative trends in rainfall accompanied by increased rainfall variability were observed between 1960s�
57 1980s over West Africa (Nicholson et al., 2018; Thomas and Nigam, 2018), caused by a combination of
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1 anthropogenic aerosols and greenhouse gases emitted between 1950s�1980s (Booth et al., 2012; Wang et al.,
2 2016; Giannini and Kaplan, 2019; Douville et al., 2021). Declining rainfall trends ended by 1990 due to the
3 growing influence of greenhouse gasses and reduced cooling effect of aerosol emissions, with a trend to
4 wetter conditions emerging in the mid-1990s accompanied by more intense, but fewer precipitation events
5 (Sanogo et al., 2015; Sylla et al., 2016; Kennedy et al., 2017; Barry et al., 2018; Bichet and Diedhiou, 2018a;
6 Bichet and Diedhiou, 2018b; Thomas and Nigam, 2018). A shift to a later onset and end of the West African
7 monsoon is also reported in West Africa and Sahel (low confidence) (Chen et al., 2021; Ranasinghe et al.,
8 2021). Between 1981�2014 the Gulf of Guinea and the Sahel have experienced more intense precipitation
9 events (Panthou et al., 2014; Bichet and Diedhiou, 2018a; Panthou et al., 2018) and the frequency of
10 mesoscale storms has tripled (Taylor et al., 2017; Callo-Concha, 2018). Extreme heavy precipitation indices
11 show increasing trends from 1981�2010 (Barry et al., 2018), increasing high flow events in large Sahelian
12 rivers as well as small to mesoscale catchments leading to pluvial and riverine flooding (Douville et al.,
13 2021). Meteorological, agricultural and hydrological drought in the region has increased in frequency since
14 the 1950s (medium confidence) (Seneviratne et al., 2021).
15
16 Projections
17 West African rainfall projections show a gradient of precipitation decrease in the west and increase in the
18 east (medium confidence) (Dosio et al., 2021; Guti閞rez et al., 2021; Ranasinghe et al., 2021) (Figure 9.14).
19 This pattern is evident at 1.5 of global warming and the magnitude of change increases at higher warming
20 levels (Schleussner et al., 2016b; Kumi and Abiodun, 2018; Sylla et al., 2018) (Figure 9.16c). A reduction in
21 length of the rainy season is projected over the western Sahel through delayed rainfall onset by 4 to 6 days at
22 global warming levels of 1.5癈 and 2癈 (Kumi and Abiodun, 2018; Douville et al., 2021; Guti閞rez et al.,
23 2021). Although there are uncertainties in rainfall projections over the Sahel (Klutse et al., 2018; Guti閞rez et
24 al., 2021), CMIP6 models project monsoon rainfall amounts to increase by approximately 2.9% per degree
25 of warming (Jin et al., 2020; Wang et al., 2020a), therefore, at higher levels of warming and towards the end
26 of the century, a wetter monsoon is projected in the eastern Sahel (medium confidence).
27
28 The frequency and intensity of extremely heavy precipitation are projected to increase under mid- and high-
29 emission scenarios (Sylla et al., 2015b; Diallo et al., 2016; Akinsanola and Zhou, 2019; Giorgi et al., 2019;
30 Dosio et al., 2021; Li et al., 2021; Seneviratne et al., 2021) (Figure 9.16d). However, heavy rainfall statistics
31 from global and regional climate models may be conservative as very-high-resolution, convection-permitting
32 climate models simulate more intense rainfall than these models (Stratton et al., 2018; Berthou et al., 2019;
33 Han et al., 2019; Kendon et al., 2019).
34
35 At 2癈 global warming, West Africa is projected to experience a drier, more drought-prone and arid climate,
36 especially in the last decades of the 21st century (Sylla et al., 2016; Zhao and Dai, 2016; Klutse et al., 2018).
37 The duration of meteorological drought duration is projected to increase from approximately 2 months
38 during 1950�2014 to approximately 4 months in the period 2050�2100 under RCP8.5 and SSP5�8.5 (Ukkola
39 et al., 2020). Increased intensity of heavy precipitation events combined with increasing drought occurrences
40 will substantially increase the cumulative hydroclimatic stress on populations in West Africa during the late
41 21st century (Giorgi et al., 2019).
42
43 9.5.4 Central Africa
44
45 9.5.4.1 Temperature
46
47 Observations
48 Mean annual temperature across Central Africa has increased by 0.75�1.2癈 since 1960 (Aloysius et al.,
49 2016; Guti閞rez et al., 2021). The number of hot days, heatwaves and heatwave days increased between
50 1979�2016 (Hu et al., 2019) and cold extremes have decreased (Aguilar et al., 2009; Seneviratne et al.,
51 2021) (Figure 9.14). Uncertainties associated with the poor ground-based observation networks in the region
52 and associated observational uncertainties (Section 9.5.1.1) result in an assessment of medium confidence in
53 an increase in the number of heat extremes over the region.
54
55 Projections
56 At 1.5癈, 2癈 and 3癈 of global warming above pre-industrial levels, mean annual temperatures in Central
57 Africa are projected to be on average, 0.6癈, 1.1癈 and 2.1癈 warmer than the 1994�2005 average,
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1 respectively (Figure 9.16a). By the end of the century (2070�2099), warming of 2癈 (RCP4.5 ) to 4癈
2 (RCP8.5) is projected over the region (Aloysius et al., 2016; Fotso-Nguemo et al., 2017; Diedhiou et al.,
3 2018; Mba et al., 2018; Tamoffo et al., 2019) and the number of days with maximum temperature exceeding
4 35癈 is projected to increase by 150 days or more at GWL 4.4癈 (Guti閞rez et al., 2021; Ranasinghe et al.,
5 2021). According to CMIP6 and CORDEX models, the annual average number of days with maximum
6 temperature exceeding 35癈 will increase between 14�27 days at GWL 2癈 and 33�59 days at GWL 3癈
7 above the 61�63 days for 1995�2014 (Guti閞rez et al., 2021; Ranasinghe et al., 2021) (high confidence). The
8 number of heatwave days is projected to increase and extreme heatwave events may last longer than 180
9 days at GWL 4.1癈 (Dosio, 2017; Weber et al., 2018; Spinoni et al., 2019). Children born in 2020, under a
10 1.5癈-compatible scenario will be exposed to 6�8 times more heatwaves in their lifetimes compared to
11 people born in 1960; this exposure increases to 7�9 times more heatwaves at GWL 2.4癈 (Thiery et al.,
12 2021). The number of potentially lethal heat days per year is projected to increase from <50 during 1995�
13 2005 to 50�75 at GWL 1.6, 100�150 at GWL 2.5 and 200�350 at GWL 4.4 (Mora et al., 2017).
14
15 9.5.4.2 Precipitation
16
17 Observations
18 The severe lack of station data over the region leads to large uncertainty in the estimation of observed
19 rainfall trends and low confidence in changes in extreme rainfall (Figure 9.13b) (Creese and Washington,
20 2018; Guti閞rez et al., 2021; Ranasinghe et al., 2021). There is some evidence of drying since the mid-20th
21 century through decreased mean rainfall and increased precipitation deficits (Guti閞rez et al., 2021), as well
22 as increases in meteorological, agricultural and ecological drought (medium confidence) (Seneviratne et al.,
23 2021). However, there is spatial heterogeneity in annual rainfall trends between 1983�2010 ranging from �
24 10 to +39 mm per year (Maidment et al., 2015), with a decline in mean seasonal April璊une precipitation of
25 �69 mm per year in most regions except in the northwest (Zhou et al., 2014; Hua et al., 2016; Klotter et al.,
26 2018; Hu et al., 2019). Southern and eastern Central Africa were identified as drought hotspots between
27 1991�2010 (Spinoni et al., 2014).
28
29 Projections
30 Under low emission scenarios and at GWL 1.5 and GWL 2癈 there is low confidence in projected mean
31 rainfall change over the region (Figure 9.16c). At GWL 3癈 and GWL 4.4癈 an increased mean annual
32 rainfall of 10�25% is projected by regional climate models (Coppola et al., 2014; Pinto et al., 2015) and the
33 intensity of extreme precipitation will increase (high confidence) (Sylla et al., 2015a; Diallo et al., 2016;
34 Dosio et al., 2019; Guti閞rez et al., 2021; Ranasinghe et al., 2021; Seneviratne et al., 2021) (Figure 9.16c,d).
35 This is projected to increase the likelihood of widespread flood occurrences before, during and after the
36 mature monsoon season (Figure 9.14).
37
38 Convection permitting simulations (4.5 km spatial resolution) simulate increased dry spell length not
39 apparent at coarser resolutions, suggesting drying in addition to more intense extreme rainfall (Stratton et al.,
40 2018). Although reduced drought frequency is indicated in Figure 9.16e, the SPI metric does not account for
41 the effect of increased temperature on drought (increased moisture deficit), and metrics that account for this
42 indicate slightly increased drought frequency or no change (Spinoni et al., 2020). Therefore, there is low
43 confidence in projected changes of drought frequency over the region (Figure 9.14).
44
45 9.5.5 East Africa
46
47 9.5.5.1 Temperature
48
49 Observations
50 Mean temperatures over the region have increased by 0.7�1癈 from 1973 to 2013, depending on the
51 season (Ayugi and Tan, 2018; Camberlin, 2018). Increases in TX and TN are evident across the region
52 accompanied by significantly increasing trends of warm nights, warm days and warm spells (Russo et al.,
53 2016; Gebrechorkos et al., 2019; Nashwan and Shahid, 2019). The greatest increases are found in northern
54 and central regions.
55
56 Projections
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1 At 1.5癈, 2癈 and 3癈 of global warming above pre-industrial levels, mean annual temperatures in East
2 Africa are projected to be on average, 0.6癈, 1.1癈 and 2.1癈 warmer than the 1994�2005 average
3 respectively (Figure 9.16a). Highest increases are projected over the northern and central parts of the region
4 and the lowest increase over the coastal regions (Otieno and Anyah, 2013; Dosio, 2017). The magnitude and
5 frequency of hot days are projected to increase from GWL 2癈 and above with larger increases at higher
6 GWLs (Dosio, 2017; Bathiany et al., 2018; Dosio et al., 2018; Kharin et al., 2018) (Figure 9.16a,b). At GWL
7 4.6癈 a number of East African cities are projected to have an up to 2000-fold increase in exposure to
8 dangerous heat (days >40.6 ) compared to 1985�2005 including Blantyre-Limbe, Lusaka and Kampala,
9 (Mora et al., 2017; Rohat et al., 2019). Children born in 2020, under a 1.5癈-compatible scenario will be
10 exposed to 3�5 times more heatwaves in their lifetimes compared to people born in 1960; this exposure
11 increases to 4�9 times more heatwaves at GWL 2.4癈 (Thiery et al., 2021). The number of potentially lethal
12 heat days per year is projected to increase from <50 during 1995�2005 to <50 at GWL 1.6, 50�120 at
13 GWL 2.5 and 150�350 at GWL 4.4 with largest increases at the coast (Mora et al., 2017), highlighting
14 the new emergence of dangerous heat conditions in these areas.
15
16 9.5.5.2 Precipitation
17
18 Observations
19 Over Equatorial East Africa the short rains (October璑ovember璂ecember) have shown a long-term wetting
20 trend from the 1960s until present (Manatsa and Behera, 2013; Nicholson, 2015; Nicholson, 2017), which is
21 linked with western Indian Ocean warming and a steady intensification of Indian Ocean Walker Cell
22 (Liebmann et al., 2014; Nicholson, 2015).
23
24 In contrast, the long rainfall season (March-April-May) has experienced a long-term drying trend between
25 1986 and 2007, with rainfall declines in each of these months and a shortening of the wet season (Rowell et
26 al., 2015; Wainwright et al., 2019). Unlike previous decades, since around 2000 the long rains have exhibited
27 a significant relationship with the El Ni駉-Southern Oscillation (Park et al., 2020), as multiple droughts have
28 occurred during recent La Ni馻 events and when the western to central Pacific SST gradient was La Ni馻-
29 like (Funk et al., 2015; Funk et al., 2018a). Wetter-than-average rainfall years within this long-term drying
30 trend are often associated with a stronger amplitude of the Madden-Julian Oscillation (Vellinga and Milton,
31 2018).
32
33 In the northern, summer rainfall region (June璖eptember), a decline in rainfall occurred in the 1960s and
34 rainfall has remained relatively low, while interannual variability has increased since the late 1980s
35 (Nicholson, 2017); the cause of this drying trend is uncertain.
36
37 Since 2005, drought frequency has doubled from once every six to once every three years and has become
38 more severe during the long and summer rainfall seasons than during the short rainfall season (Ayana et al.,
39 2016; Gebremeskel Haile et al., 2019). Several prolonged droughts have occurred predominantly within the
40 arid and semi-arid parts of the region over the past three decades (Nicholson, 2017).
41
42 Projections
43 Higher mean annual rainfall, particularly in the eastern parts of east Africa are projected at GWL 1.5 and
44 2癈 by 25 CORDEX models (Nikulin et al., 2018; Osima et al., 2018). The additional 0.5癈 of warming
45 from 1.5癈 increases average dry spell duration by between two and four days, except over southern Somalia
46 where this is reduced by between two to three days (Hoegh-Guldberg et al., 2018; Nikulin et al., 2018;
47 Osima et al., 2018; Weber et al., 2018).
48
49 During the short rainy season, a longer rainfall season (Gudoshava et al., 2020) and increased rainfall of up
50 to over 100 mm on average is projected over the eastern horn of Africa and regions of high/complex
51 topography at GWL 4.5癈 (Dunning et al., 2018; Endris et al., 2019; Ogega et al., 2020).
52
53 During the long rainy season, there is low confidence in projected mean rainfall change (Guti閞rez et al.,
54 2021). Although some studies report projected increased end of century rainfall (Otieno and Anyah, 2013;
55 Kent et al., 2015), the mechanisms responsible for this are not well-understood and a recent regional model
56 study has detected no significant change (Cook et al., 2020b). Projected wetting is opposite to the observed
57 drying trends, giving rise to the `East African rainfall paradox' (Rowell et al., 2015; Wainwright et al.,
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1 2019). In other parts of East Africa, no significant trend is evident (Ogega et al., 2020), agreement on the
2 sign of change is low, and in some regions, CMIP5 and CORDEX data show opposite signs of change (Lyon
3 et al., 2017; Lyon and Vigaud, 2017; Osima et al., 2018; Kendon et al., 2019; Ogega et al., 2020).
4
5 Heavy rainfall events are projected to increase over the region at global warming of 2癈 and higher (high
6 confidence) (Nikulin et al., 2018; Finney et al., 2020; Ogega et al., 2020; Li et al., 2021). Drought frequency,
7 duration and intensity are projected to increase in Sudan, South Sudan, Somalia and Tanzania but decrease or
8 not change over Kenya, Uganda and Ethiopian highlands (Liu et al., 2018c; Nguvava et al., 2019; Haile et
9 al., 2020; Spinoni et al., 2020).
10
11 9.5.6 Southern Africa
12
13 9.5.6.1 Temperature
14
15 Observations
16 Mean annual temperatures over the region have increased by between 1.04癈 and 1.44癈 over the period
17 1961�2015 depending on the observational dataset (Guti閞rez et al., 2021) and in northern Botswana and
18 Zimbabwe increasing 1.6癈�1.8癈 between 1961�2010 (Engelbrecht et al 2015). The annual number of hot
19 days have increased in southern Africa over the last four decades (Ceccherini et al., 2017; Kruger and
20 Nxumalo, 2017b; Kruger and Nxumalo, 2017a) and there is increasing evidence of increased heat stress
21 impacting agriculture and human health (Section 9.10.2). The occurrence of cold extremes, including frost
22 days, have decreased (Kruger and Nxumalo, 2017b) (Figure 9.14).
23
24 Projections
25 At 1.5, 2 and 3癈 of global warming above pre-industrial levels, mean annual temperatures in southern
26 Africa are projected to be on average, 1.2, 2.3 and 3.3癈 warmer than the 1994�2005 average
27 respectively (Figure 9.16a). The annual number of heatwaves is projected to increase by between 2�4 (GWL
28 1.5癈), 4�8 (GWL 2癈) and 8�12 (GWL 3癈) and hot and very hot days are virtually certain to increase
29 under 1.5癈 and 2癈 of global warming (Engelbrecht et al., 2015; Russo et al., 2016; Dosio, 2017; Weber et
30 al., 2018; Seneviratne et al., 2021). Cold days and cold extremes are projected to decrease under all emission
31 scenarios with the strongest decreases associated with low mitigation (Iyakaremye et al., 2021). Children
32 born in 2020, under a 1.5癈-compatible scenario will be exposed to 3�4 times more heatwaves in their
33 lifetimes compared to people born in 1960, although in Angola this is 7�8 times; at GWL 2.4癈 this
34 exposure increases to 5�9 times more heatwaves (>10 times in Angola) (Thiery et al., 2021).
35
36 9.5.6.2 Precipitation
37
38 Observations
39 Mean annual rainfall has increased over parts of Namibia, Botswana and southern Angola during 1980�2015
40 by between 128 and 256 mm (Figure 9.13b). Since the 1960s decreasing precipitation trends have been
41 detected over the South African winter rainfall region (high confidence) and the far eastern parts of South
42 Africa (low confidence) (Engelbrecht et al., 2009; Kruger and Nxumalo, 2017b; Burls et al., 2019; Lakhraj-
43 Govender and Grab, 2019; Guti閞rez et al., 2021; Ranasinghe et al., 2021). The frequency of dry spells and
44 agricultural drought in the region has increased over the period 1961�2016 (Yuan et al., 2018; Seneviratne et
45 al., 2021), the frequency of meteorological drought increased by between 2.5�3 events per decade since 1961
46 (Spinoni et al 2019) and the probability of the multi-year drought over the southwestern cape of South Africa
47 increased by a factor of three in response to global warming (Otto et al., 2018). The number and intensity of
48 extreme precipitation events have increased over the last century (Kruger and Nxumalo, 2017b; Ranasinghe
49 et al., 2021; Sun et al., 2021), and in the Karoo region of southern South Africa, long-term station data show
50 an increasing trend in annual rainfall of greater than 5 mm per decade over the period 1921�2015 (Kruger
51 and Nxumalo, 2017b).
52
53 Projections
54 Mean annual rainfall in the summer rainfall region is projected to decrease by 10�20%, accompanied by an
55 increase in the number of consecutive dry days during the rainy season under RCP8.5 (Kusangaya et al.,
56 2014; Engelbrecht et al., 2015; Lazenby et al., 2018; Ma鷕e et al., 2018; Spinoni et al., 2019). The western
57 parts of the region are projected to become drier, with increasing drought frequency, intensity and duration
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1 likely under RCP8.5 (high confidence) (Engelbrecht et al., 2015; Liu et al., 2018b; Liu et al., 2018c; Ukkola
2 et al., 2020) (Figures 9.16c,e and 9.14), including multi-year droughts (Zhao and Dai, 2016; Dosio, 2017).
3
4 Dryness in the summer rainfall region is expected to increase at 1.5癈 and higher levels of global warming
5 (Hoegh-Guldberg et al., 2018) and together with higher temperatures will enhance evaporation from the
6 region's mega-dams and reduce soil-moisture content (Engelbrecht et al., 2015) (Section 9.7.1). Increases in
7 drought frequency and duration are projected over large parts of southern Africa at GWL 1.5癈 (Liu et al.,
8 2018b; Liu et al., 2018c; Seneviratne et al., 2021) and unprecedented extreme droughts (compared to the
9 1981�2010 period) emerge at GWL 2癈 (Spinoni et al., 2021). Meteorological drought duration is projected
10 to increase from approximately 2 months during 1950�2014 to approximately 4 months in the mid-to-late-
11 21st century future under RCP8.5 (Ukkola et al., 2020). Heavy precipitation in the southwestern region is
12 projected to decrease (Donat et al., 2019) and increase in the eastern parts of southern Africa at all warming
13 levels (Li et al., 2021; Seneviratne et al., 2021).
14
15 9.5.7 Tropical cyclones
16
17 There is limited evidence of an increased frequency of Category 5 tropical cyclones in the southwestern
18 Indian Ocean (Fitchett et al., 2016; Ranasinghe et al., 2021; Seneviratne et al., 2021) and more frequent
19 landfall of tropical cyclones over central to northern Mozambique (Malherbe et al., 2013; Muthige et al.,
20 2018). There is a projected decrease in the number of tropical cyclones making landfall in the region at 1,
21 2 and 3 of global warming, however, they are projected to become more intense with higher wind
22 speeds so when they do make landfall the impacts are expected to be high (medium confidence) (Malherbe et
23 al., 2013; Muthige et al., 2018; Ranasinghe et al., 2021).
24
25 9.5.8 Glaciers
26
27 Total glacial area on Mount Kenya decreased by 121�103 m2 (44%) during 2004�2016 (Prinz et al., 2016),
28 Kilimanjaro from 4.8 km2 in 1984 to 1.7 km2 in 2011 (Cullen et al., 2013) and, in the Rwenzori Mountains,
29 from ~2 km2 in 1987 to ~1 km2 in 2003 (Taylor et al., 2006). Declining glacial areas in East Africa are linked
30 to rising air temperatures (Taylor et al., 2006; Hastenrath, 2010; Veettil and Kamp, 2019), and in the case of
31 Kilimanjaro and Mount Kenya, declining precipitation and atmospheric moisture (M鰈g et al., 2009a; M鰈g
32 et al., 2009b; Prinz et al., 2016; Veettil and Kamp, 2019).
33
34 Glacial ice cover is projected to disappear before 2030 on the Rwenzori Mountains (Taylor et al., 2006) and
35 Mount Kenya (Prinz et al., 2018) and by 2040 on Kilimanjaro (Cullen et al., 2013). The loss of glaciers is
36 expected to result in a loss in tourism revenues, especially in mountain tourism (Wang and Zhou, 2019).
37
38 9.5.9 Teleconnections and Large-Scale Drivers of African Climate Variability
39
40 The El Ni駉-Southern Oscillation (ENSO), Indian Ocean dipole (IOD) and southern annular mode (SAM)
41 are the primary large-scale drivers of African seasonal and interannual climate variability. The diurnal
42 temperature range tends to be greater during La Ni馻 than El Ni駉 in northeastern Africa (Hurrell et al.,
43 2003; Donat et al., 2014a), and in southern Africa, the El Ni駉 warming effect has been stronger for more
44 recent times (1979�2016) compared to earlier period (1940�1978) (Lakhraj-Govender and Grab, 2019). In
45 East Africa, ENSO and IOD exert an interannual control on particularly October璑ovember璂ecember
46 (short rains) and June璊uly瑼ugust璖eptember seasons. In southern Africa, El Ni駉 is associated with
47 negative rainfall and positive temperature anomalies with the opposite true for La Ni馻. The SAM exerts
48 control on rainfall in the southwestern parts of the region and a positive SAM mode is often associated with
49 lower seasonal rainfall in the region (Reason and Rouault, 2005). The SAM shows a systematic positive
50 trend over the last five decades (Niang et al., 2014).
51
52 There is no clear indication that climate change will impact the frequencies of ENSO and IOD (Stevenson et
53 al., 2012; Endris et al., 2019), although there is some indication that extreme ENSO events and extreme
54 phases of the IOD, particularly the positive phase, may become more frequent with implications for extreme
55 events associated with these features, such as drought (Collins et al., 2019; Cai et al., 2021; Seneviratne et
56 al., 2021). Under high emission scenarios, a positive trend in SAM is projected to continue through the 21st
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1 century, however, under low emission scenarios, this trend is projected to be weak or even negative given the
2 potential for ozone hole recovery (Arblaster et al., 2011).
3
4 9.5.10 African Marine Heatwaves
5
6 Marine heatwaves are periods of extreme warm sea surface temperature that persist for days to months and
7 can extend up to thousands of kilometres (Hobday et al., 2016; Scannell et al., 2016), negatively impacting
8 marine ecosystems (Section 9.6.1.4).
9
10 The number of marine heatwaves doubled in Mediterranean North Africa and along the Somalian and
11 southern African coastlines from 1982�2016 (Fr鰈icher et al., 2018; Laufk鰐ter et al., 2020) (Oliver et al.,
12 2018), very likely as a result of human-induced climate change (Seneviratne et al., 2021). Marine heatwave
13 intensity has increased along the southern African coastline (Oliver et al., 2018). In the ecologically sensitive
14 region west of southern Madagascar, the longest and most intense marine heatwave in the past 35 years was
15 recorded during the austral summer of 2017 in the region, it lasted 48 days and reached a maximum intensity
16 of 3.44癈 above climatology (Mawren et al., 2021). Satellite-derived measurements of coastal marine
17 heatwaves may under-report their intensity as measured against coastal in situ measurements (Schlegel et al.,
18 2017).
19
20 Sea surface temperatures around Africa are projected to increase 0.5�1.3癈 under GWL1.5 and 1.3�
21 2.0癈 under GWL3 (Figure 9.16f). Globally, 87% of observed MHWs have been attributed to anthropogenic
22 forcing, and at GWL2.0, nearly all MHWs would be attributable to anthropogenic heating (Fr鰈icher et al.,
23 2018; Laufk鰐ter et al., 2020). Increases in frequency, intensity, spatial extent and duration of marine
24 heatwaves are projected for all coastal zones of Africa. At 1癈 and 3.5癈 of global warming, the probability
25 of MHW days is between 4�15 times and 30�60 times higher compared to the preindustrial (1861�1880) 99th
26 percentile probability, with highest increases over equatorial and sub-tropical coastal regions (Fr鰈icher et
27 al., 2018) (Figure 9.16). These events are expected to overwhelm the ability of marine organisms and
28 ecosystems to adapt to these changes (Fr鰈icher et al., 2018) (Sections 9.6.1). Reducing emissions and
29 limiting warming to lower levels reduces risk to these systems (high confidence) (Hoegh-Guldberg et al.,
30 2018).
31
32
33 [START BOX 9.2 HERE]
34
35 Box 9.2: Indigenous Knowledge and Local Knowledge
36
37 This box aims at mapping the diversity of indigenous and local knowledge systems in Africa and highlights
38 the potential of this knowledge to enable sustainability and effective climate adaptation. This box builds on
39 the framing of the IPCC system for which `indigenous knowledge (IK) refers to the understandings, skills
40 and philosophies developed by societies with long histories of interaction with their natural surroundings'
41 (IPCC, 2019b), while `local knowledge (LK) refers to the understandings and skills developed by individuals
42 and populations, specific to the place where they live' (IPCC, 2019b) (Cross-Chapter Box INDIG in Chapter
43 18).
44
45 Early warning systems and indicators of climate variability
46
47 In most African indigenous agrarian systems, local communities integrate IK to anticipate or respond to
48 climate variability (Mafongoya et al., 2017). This holds potential for a more holistic response to climate
49 change, as IK and LK approaches seek solutions that increase resilience to a wide range of shocks and
50 community stresses (IPCC, 2019b). In Africa, IK and LK are exceptionally rich in ecosystem-specific
51 knowledge, with the potential to enhance the management of natural hazards and climate variability (high
52 confidence), but there is uncertainty about IK and LK for adaptation under future climate conditions.
53
54 Common indicators for the quality of the rain season for local communities in Africa include flower and fruit
55 production of local trees (Nkomwa et al., 2014; Jiri et al., 2015; Kagunyu et al., 2016), insect, bird and
56 animal behaviour and occurrence (Jiri et al., 2016; Mwaniki and Stevenson, 2017; Ebhuoma, 2020) and dry
57 season temperatures (Kolawole et al., 2016; Okonya et al., 2017). Fulani herders in West Africa believe that
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1 when `nests hang high on trees, then rains will be heavy; when nests hang low, rains will be scarce' (Roncoli
2 et al., 2002). In South Africa, LK on weather forecasting is based on the hatching of insects, locust swarm
3 movements and the arrival of migratory birds, which has enabled farmers to make adjustments to cropping
4 practices (Muyambo et al., 2017; Tume et al., 2019). Most of these IK indicators apply to specific
5 communities, and are used for short-term forecasting (e.g., event-specific predictions, such as a violent
6 storm, and onset rain predictions) (Zuma-Netshiukhwi et al., 2013; Mutula et al., 2014). There is evidence of
7 communities that rely heavily on IK and LK indicators to forecast seasonal variability across the continent
8 (Kagunyu et al., 2016; Mwaniki and Stevenson, 2017; Tume et al., 2019). However, their accuracy is
9 debatable, with evidence of both accuracy and inaccuracies due to age-old knowledge losing accuracy
10 because of recent changes in weather conditions (Shaffer, 2014; Adjei and Kyerematen, 2018). There are
11 also some limitations in the transferability of IK across geographical scales, as its understanding is framed by
12 traditional beliefs and cultural practices, historical and social conditions of each community, which vary
13 significantly across communities. This has direct implications for the adoption of IK and LK in national
14 policy and planned adaptation by governments. However, in some parts of Africa, evidence of the integration
15 of IK and LK and scientific-based weather forecasting is increasing (Jiri et al., 2016; Mapfumo et al., 2017;
16 Williams et al., 2020).
17
18 IK and LK and climate adaptation
19
20 Communities across Africa have long histories of using IK and LK to cope with climate variability, reduce
21 vulnerability and improve the capacity to cope with climate variability (Iloka Nnamdi, 2016; Mapfumo et al.,
22 2017). The adaptation is mostly incremental, such as customary rainwater harvesting practices and planting
23 ahead of rains (Ajibade and Eche, 2017; Makate, 2019), which are used to address the late-onset rains and
24 rainfall variability. Although IK and LK adaptation practices implemented by African communities are
25 incremental, such practices record higher evidence of climate risk reduction compared to practices
26 influenced by other knowledge types (Williams et al., 2020). African communities have used IK and LK to
27 cope, adapt to and manage climate hazards, mainly floods, wildfires, rainfall variability and droughts (see
28 Table Box 9.2.1) (IPCC, 2018b; IPCC, 2019b).
29
30
31 Table Box 9.2.1: Selected studies where IK and LK have been used to cope with climate variability and climate change
32 impacts in Africa.
Climate Adaptation/Coping Strategy Indigenous Group, Evidence
Hazard Use IK to predict floods (village Community, Country (Fabiyi and Oloukoi, 2013;
Floods elders acted as meteorologists) and use Coastal communities in Hooli, 2016; Lunga and
LK to prepare coping mechanisms (social Nigeria; Oshiwambo Musarurwa, 2016; Bwambale
Wildfires capital); place valuable goods on higher communities in the northern et al., 2018; Tume et al.,
Rainfall ground, raise the floor level; leave the region of Namibia; 2019)
variability field uncultivated when facing Matabeleland and
flood/drought; indigenous earthen walls Mashonaland provinces in (Mugambiwa, 2018;
Droughts to protect homesteads from flooding; Zimbabwe; communities in Humphrey et al., 2021)
planting of culturally flood-immunising Nyamwamba watershed,
indigenous plants. Uganda; subsistent farmers in (Codjoe et al., 2014;
Mount Oku and Mbaw, Nkomwa et al., 2014; Lunga
Early burning to prevent the intensity of Cameroon; Akobo in South and Musarurwa, 2016;
the late-season fires Sudan. Rankoana, 2016b;
Smallholders in Mutoko, Mugambiwa, 2018;
Change crop type (from maize to Zimbabwe; Khwe and Mfitumukiza et al., 2020;
traditional millet and sorghum); no Mbukushu communities in Mogomotsi et al., 2020)
weeding; forecasting, rainwater Namibia
harvesting; women perform rituals Communities in Accra, (Egeru, 2012; Gebresenbet
rainmaking, seed dressing and crop Ghana; small-scale farmers in and Kefale, 2012; Codjoe et
maintenance as adaptation measures; Ngamiland in Botswana; al., 2014; Kamwendo and
mulching Malawi; Zimbabwe; Women
in Dikgale, South Africa,
Traditional drying of food for agropastoral smallholders in
preservation (to consume during short Ntungamo, Kamuli and
Sembabule in Uganda.
Communities in Accra,
Ghana; Malawi; South
Africa, Uganda; Smallholder
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term droughts); harvesting wild fruits and farmers in Mutoko, Kamwendo, 2014; Okoye and
vegetables; herd splitting by pastorals Zimbabwe; Agro-pastoralists Oni, 2017; Mugambiwa,
in Makueni, Kenya; 2018)
Pastoralists in South Omo,
Drought related Traditional rainwater harvesting to Ethiopia (Ncube, 2018)
water scarcity supplement both irrigation and domestic Smallholder farmers in
Beaufort, South Africa
water; indigenous water bottle
technology for irrigation.
1
2
3 IK and LK and coping strategies in Table Box 9.2.1 are supportive measures that communities cannot solely
4 rely upon, but which can be used to complement other adaptation options to increase community resilience.
5
6 African indigenous language and climate change adaptation
7
8 The diversity of African languages is crucial for climate adaptation. Africa has over 30% of the world's
9 indigenous languages (Seti et al., 2016) which are exceptionally rich in ecosystem-specific knowledge on
10 biodiversity, soil systems and water (Oyero, 2007; Mugambiwa, 2018). Taking into consideration the low
11 level of literacy in Africa, especially among women and girls, indigenous languages hold great potential for
12 more effective climate change communication and services that enable climate adaptation (Brooks et al.,
13 2005; Ologeh et al., 2018; IPCC, 2019b). African traditional beliefs and cultural practices place great value
14 on the natural environment, especially land as the dwelling place of the ancestors and source of livelihoods
15 (Tarusarira, 2017) (see Section 9.12).
16
17 Limitations of African IK and LK in climate adaptation
18
19 Studies on IK and LK and climate change adaptation conducted in various African countries and across
20 ecosystems indicate that indigenous environmental knowledge is negatively affected by several factors.
21 Local farmers who depend on this knowledge system for their livelihoods hold the view that African
22 governments do not support and promote it in policy development. Most government agricultural extension
23 workers still consider IK as unscientific and unreliable (Seaman et al., 2014; Mafongoya et al., 2017). At the
24 national level, there is a lack of recognition and inclusion of IK and LK in adaptation planning by African
25 governments, partly because most of the IK and LK in African local communities remains undocumented,
26 but also because IK and LK are inadequately captured in the literature (Ford et al., 2016; IPCC, 2019b). It is
27 predominantly preserved in the memories of the elderly and is handed down orally or by demonstration from
28 generation to generation. It gradually disappears due to memory gaps, and when those holding the
29 knowledge die or refuse to pass it to another generation, the knowledge becomes extinct (Rankoana, 2016a).
30 The way in which IK is transmitted, accessed and shared in most African societies is not smooth (IIED,
31 2015). IK is also threatened by urbanisation, which attracts rural migrants to urban areas where IK and LK
32 use is limited (Fern醤dez-Llamazares et al., 2015). Further, most African societies that use IK were once
33 colonised, whereby the African indigenous ways of knowing were devalued and marginalised (Bolden et al.,
34 2018). There are concerns about the effectiveness of both IK indicators and related adaptation responses by
35 communities to predict and adapt to weather events under future climate conditions (Speranza et al., 2009;
36 Shaffer, 2014; Hooli, 2016).
37
38
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2 Figure Box 9.2.1: Indigenous earth walls (hayit) built by indigenous people in Akobo, Jonglei Region, South Sudan to
3 protect their houses/ infrastructure from the worst flood in 25 years occurred in 2019. The wall is 1�2 m high. Photo
4 credit, Laurent-Charles Levesque.
5
6 [END BOX 9.2 HERE]
7
8
9 9.6 Ecosystems
10
11 9.6.1 Observed Impacts of Climate Change on African Biodiversity and Ecosystem Services
12
13 9.6.1.1 Terrestrial Ecosystems
14
15 The overall continental trend is woody plant expansion, particularly in grasslands and savannas, with woody
16 plant cover increasing at a rate of 2.4% per decade (Stevens et al., 2017; Axelsson and Hanan, 2018) (Figure
17 9.17). There is also increased grass cover in arid regions in southwestern Africa (Masubelele et al., 2014).
18 There is high agreement that this is attributable to increased CO2, warmer and wetter climates, declines in
19 burned area and release from herbivore browsing pressure, but the relative importance of these interacting
20 drivers remains uncertain (O'Connor et al., 2014; Stevens et al., 2016; Garc韆 Criado et al., 2020). Woody
21 encroachment is the dominant trend in the western and central Sahel, occurring over 24% of the region,
22 driven primarily by shifts in rainfall timing and recovery from drought (Anchang et al., 2019; Brandt et al.,
23 2019). Remote sensing studies demonstrate greening in southern Africa and forest expansion into water-
24 limited savannas in Central and West Africa (Baccini et al., 2017; Aleman et al., 2018; Piao et al., 2020),
25 with increases in precipitation and atmospheric CO2 the likely determinants of change (Venter et al., 2018;
26 Brandt et al., 2019; Zhang et al., 2019). These trends of greening and woody plant expansion stand in
27 contrast to the desertification and contraction of vegetated areas highlighted in AR5 (Niang et al., 2014), but
28 are based on multiple studies and longer time series of observations. Reported cases of desertification and
29 vegetation loss, for example, in the Sahel, appear transitory and localised rather than widespread and
30 permanent (Dardel et al., 2014; Pandit et al., 2018; Sterk and Stoorvogel, 2020).
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2 Shifts in demography, geographic ranges and abundance of plants and animals consistent with expected
3 impacts of climate change are evident across Africa. These include uphill contractions of elevational range
4 limits of birds (Neate-Clegg et al., 2021), changes in species distributions previously reported in AR5 (Niang
5 et al., 2014) and the death of many of the oldest and largest African Baobabs (Patrut et al., 2018). An
6 increase in frequency and intensity of hot, dry weather after wildfires led to a long-term decline in plant
7 biodiversity in Fynbos since the 1960s (Slingsby et al., 2017). Increasing temperatures may have contributed
8 to the declining abundance and range size of South African birds (Milne et al., 2015), including Cape Rock-
9 jumper (Chaetops frenatus) and Protea Canary (Serinus leucopterus), from increased risk of reproductive
10 failure (Lee and Barnard, 2016; Oswald et al., 2020). For hot and dry regions (e.g., Kalahari), there is strong
11 evidence increased temperatures are having chronic sublethal impacts, including reduced foraging efficiency
12 and loss of body mass (du Plessis et al., 2012; Conradie et al., 2019), and are approaching species
13 physiological limits, with heat extremes driving mass mortality events in birds and bats (McKechnie et al.,
14 2021). Vegetation change linked to climate change and increasing atmospheric CO2 has had an indirect
15 impact on animals. Increased woody cover has decreased the occurrence of bird, reptile and mammal species
16 that require grassy habitats (P閞on and Altwegg, 2015; McCleery et al., 2018). Decreased fruit production
17 linked to rising temperatures has decreased the body condition of fruit-dependent forest elephants by 11%
18 from 2008�2018 (Bush et al., 2020).
19
20 There is high agreement that land use activities counteract or exacerbate climate-driven vegetation change
21 (Aleman et al., 2017; Timm Hoffman et al., 2019). Decreased woody plant biomass in 11% of sub-Saharan
22 Africa was attributed to land clearing for agriculture (Brandt et al., 2017; Ordway et al., 2017). Localised
23 loss of tree cover in Miombo woodlands and 16.6�0.5 Mha of forest loss in the Congo basin between 2000-
24 2014 was driven largely by forest clearing and drought mortality (McNicol et al., 2018; Tyukavina et al.,
25 2018).
26
27 Vegetation changes interacting with climate and land use change have impacted fire regimes across Africa.
28 The frequency of weather conducive for fire has increased in southern and West Africa and is expected to
29 continue increasing in the 21st century under both RCP2.6 and RCP8.5 (Betts et al., 2015; Abatzoglou et al.,
30 2019). Increased grass cover in arid regions introduced fire into regions where fuel was previously
31 insufficient to allow fire spread, such as the arid Karoo in South Africa (du Toit et al., 2015; Strydom and
32 Savage, 2016). In contrast, shrub encroachment, increased precipitation (Zubkova et al., 2019), vegetation
33 fragmentation and cropland expansion have reduced fire activity in many African grasslands and savannas
34 (Andela and van der Werf, 2014; Probert et al., 2019). These drivers are expected to negate the effect of
35 increasing fire weather and ultimately lead to a reduction in the total burned area under RCP4.5 and RCP8.5
36 (Knorr et al., 2016; Moncrieff et al., 2016; Wu et al., 2016).
37
38 9.6.1.2 Vegetation Resilience
39
40 African ecosystems have a long evolutionary association with fire, large mammal herbivory and drought
41 (Maurin et al., 2014; Charles-Dominique et al., 2016). The maintenance of biodiversity depends on natural
42 disturbance regimes. Natural regrowth of savanna plant biomass in southern Africa compensated for biomass
43 removal through human activities (McNicol et al., 2018), and rapid recovery occurred after the 2014-2016
44 extreme drought (Abbas et al., 2019). During the same drought event, browsing and mixed feeder herbivores
45 were resilient, but grazers declined by approximately 60% and were highly dependent on drought refugia
46 (Abraham et al., 2019). African tropical forests remained a carbon sink through the record drought and
47 temperature experienced in the 2015�2016 El Ni駉, indicating resilience in the face of extreme
48 environmental conditions (Bennett et al., 2021). This is likely due to the presence of drought-tolerant species
49 and floristic and functional shifts in tree species assemblages (Fauset et al., 2012; Aguirre-Guti閞rez et al.,
50 2019). This resilience indicates that there is the capacity to recover from disturbances and short-term change.
51 But resilience has limits and beyond certain points, change can lead to irreversible shifts to different states
52 (Figure 9.18).
53
54
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2 Figure 9.17: Widespread changes to African vegetation have been reported, especially increasing woody plant cover in
3 many savannas and grasslands, with 37% of these changes proposed to be driven by anthropogenic climate change and
4 increased CO2. The warming of lakes and rivers has been detected across Africa and is attributed to climate change.
5 Data on vegetation change was gathered from 156 studies published between 1989 and 2021. Climatic changes, mostly
6 associated with changes in rainfall, are enhancing grass production in arid grasslands and savannas, and causing grass
7 expansion into semi-desert regions with notable increases in the Sahel and southern Africa. Tropical forest expansion
8 into mesic savannas is occurring on the fringes of the central African tropical forest. Interactions between land use,
9 climate change and increasing atmospheric CO2 concentrations are causing a widespread increase in woody plant cover
10 encroachment in tropical savannas and grasslands. Some tree death and woody cover decline associated with climate
11 and land use change have also been recorded across biomes. Of the reported changes to terrestrial vegetation, 24% were
12 explicitly linked to climate change and a further 13% were proposed to be driven by climate change. In 48% of studies,
13 no climate driver was mentioned and in 15% climate change was ruled out as the driver of change. Annual surface
14 water temperatures in African lakes have warmed at a rate of 0.05�0.76 per decade. Both satellite-based measures
15 spanning 1985-2011 and in situ measurements spanning 1927-2014 agree on this warming trend. Other surface waters
16 across Africa warmed from 1979-2018 at a rate of between 0.05 and 0.5 per decade (Woolway and Maberly,
17 2020). Vegetation change data were taken from a larger, global literature survey of existing databases supplemented
18 with newer studies documenting changes in tree, shrub and grass cover linked to climate and land use change in natural
19 and semi-natural areas (for further details 2.4.3.5 and Table 2.S.1 in Chapter 2, and see Supplementary Material Table
20 SM 9.2 for Africa vegetation change data and Table SM 9.3 for studies reporting lake warming data).
21
22
23 9.6.1.3 Freshwater Ecosystems
24
25 Small climatic variations have large impacts on ecosystem function in Africa's freshwaters (Ndebele-Murisa,
26 2014; Ogutu-Ohwayo et al., 2016). Warming of water temperatures from 0.2 to 3.2 occurred in several
27 lakes over 1927�2014 and has been attributed to anthropogenic climate change (Ogutu-Ohwayo et al., 2016);
28 Figure 9.17). Increased temperature, changes in rainfall, and reduced wind speed altered the physical and
29 chemical properties of inland water bodies, affecting water quality and productivity of algae, invertebrates
30 and fish (high confidence). In deeper lakes, warmer surface waters and decreasing wind speeds reduced
31 shallow waters mixing with nutrient-rich deeper waters, reducing biological productivity in the upper sunlit
32 zone (Ndebele-Murisa, 2014; Saulnier-Talbot et al., 2014). In several lakes, climate change was identified as
33 causing changes in insect emergence time (Dallas and Rivers-Moore, 2014) and in loss of fish habitats
34 (Natugonza et al., 2015; Gownaris et al., 2016). This set of changes can harm human livelihoods, for
35 example, from reduced fisheries productivity (Ndebele-Murisa, 2014; Ogutu-Ohwayo et al., 2016) (9.8.5)
36 and reduced water supply and quality (Section 9.7.1).
37
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1 9.6.1.4 Marine Ecosystems
2
3 Anthropogenic climate change is already negatively impacting Africa's marine biodiversity, ecosystem
4 functioning and services by changing physical and chemical properties of seawater (increased temperature,
5 salinity and acidification, and changes in oxygen concentration, ocean currents and vertical stratification)
6 (high confidence) (Hoegh-Guldberg et al., 2014; Hoegh-Guldberg et al., 2018). Coastal ecosystems in West
7 Africa are among the most vulnerable because of extensive low-lying deltas exposed to sea level rise,
8 erosion, saltwater intrusion and flooding (Belhabib et al., 2016; UNEP, 2016b; Kifani et al., 2018). In
9 southern Africa, shifting distributions of anchovy, sardine, hake, rock lobster and seabirds have been partly
10 attributed to climate change (Crawford et al., 2015; van der Lingen and Hampton, 2018; Vizy et al., 2018),
11 including southern shifts of 30 estuarine and marine fish species attributed to increased temperature and
12 changes in water circulation from decreased river inflow (Augustyn et al., 2018). Warming sea surface
13 temperatures inhibiting nutrient mixing reduced phytoplankton biomass in the western Indian Ocean by 20%
14 since the 1960s, potentially reducing tuna catches (Roxy et al., 2016).
15
16 Mangroves, seagrasses and coral reefs support nursery habitats for fish, sequester carbon, trap sediment and
17 provide shoreline protection (Ghermandi et al., 2019). Climate change is compromising these ecosystem
18 services (medium confidence). Marine heatwaves associated with El Ni駉-Southern Oscillation (ENSO)
19 events triggered massive coral bleaching and mortality over the past 20 years (Oliver et al., 2018). Mass
20 coral bleaching in the western Indian Ocean occurred in 1998, 2005, 2010 and 2015/2016 with coral cover
21 just 30�40% of 1998 levels by 2016 (Obura et al., 2017; Moustahfid et al., 2018). The northern Mozambique
22 Channel has served as a refuge from climate change and biological reservoir for the entire coastal East
23 African region (McClanahan et al., 2014; Hoegh-Guldberg et al., 2018). A southern shift of mangrove
24 species has been observed in South Africa (Peer et al., 2018) with loss in total suitable coastal habitats for
25 mangroves and shifts in the distribution of some species of mangroves and a gain for others (Record et al.,
26 2013). Mangrove cover was reduced 48% in Mozambique in 2000 from tropical cyclone Eline, with 100%
27 mortality of seaward mangroves dominated by Rhizophora mucronata (Macamo et al., 2016). Recovery of
28 mangrove species was observed 14 years later in sheltered sites. There is low confidence these cyclone-
29 induced impacts are attributable to climate change owing, in part, to a lack of reliable long-term data sets
30 (Macamo et al., 2016). In West Africa, oil and gas extraction, deforestation, canalisation and de-silting of
31 waterways have been the largest factors in mangrove destruction (Numbere, 2019).
32
33 9.6.2 Projected Risks of Climate Change for African Biodiversity and Ecosystem Services
34
35 9.6.2.1 Projected Biome Distribution
36
37 African biomes are projected to shift due to changes in atmospheric CO2 concentrations and aridity (Figure
38 9.18). Grassland expansion into the desert, woody expansion into grasslands and forest expansion into
39 savannas are projected for areas of reduced aridity, caused by reduced moisture stress from CO2 fertilisation
40 under medium (RCP4.5) and high (SRES A2) emissions scenarios (Heubes et al., 2011; Moncrieff et al.,
41 2016). This greening trend may slow or reverse with continued temperature increase and/or in areas of
42 increased aridity (Berdugo et al., 2020). The net impact of these effects on vegetation is highly uncertain
43 (Trugman et al., 2018; Cook et al., 2020a; Martens et al., 2021). The maintenance or re-establishment of
44 natural fire and large mammal herbivory processes can mitigate projected CO2 and climate-driven changes
45 (Scheiter and Savadogo, 2016; Stevens et al., 2016). Expansion of croplands and pastures will reduce
46 ecosystem carbon storage in Africa, potentially reversing climate- and CO2-driven greening in savannas
47 (Aleman et al., 2018; Quesada et al., 2018).
48
49 Vegetation growth simulated by dynamic vegetation models is often highly sensitive to CO2 fertilisation.
50 These models project the African tropical forest carbon sink to be stable or strengthened under scenarios of
51 future climate change (Huntingford et al., 2013; Martens et al., 2021). In contrast, statistical modelling
52 suggests it has begun to decline and will weaken further, decreasing from current estimates of 0.66 tonnes of
53 carbon removed from the atmosphere per hectare per year to 0.55 tonnes of carbon (Hubau et al., 2020).
54 Increasing rainfall seasonality and aridity over central Africa (Haensler et al., 2013) threatens the massive
55 carbon store in the Congo Basin's Cuvette Centrale peatlands, estimated at 30.6 billion tonnes (Dargie et al.,
56 2019).
57
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1
2
3 Figure 9.18: Increases in atmospheric CO2 and changes in aridity are projected to shift the geographic distribution of
4 major biomes across Africa (high confidence). Arrows in the diagram indicate possible pathways of biome change from
5 current conditions resulting from changes in CO2 and aridity. Changes need not be gradual or linear and may occur
6 rapidly if tipping points are crossed. Currently, widespread greening observed in Africa has been at least partially
7 attributed to increasing atmospheric CO2 concentrations. Future projected increases in aridity are expected to cause
8 desertification in many regions, but it is highly uncertain how this will interact with the greening effect of CO2. Inset
9 maps show the projected geographical extent of changes in CO2 concentrations and aridity. CO2 is projected to increase
10 globally under all future emission scenarios. Aridity index maps show projected change in aridity (calculated as annual
11 precipitation/annual potential evapotranspiration) at around 4 global warming relative to 1850�1900 (RCP8.5 in
12 2070�2099) from 34 CMIP5 models (Scheff et al., 2017). Shaded areas indicate regions where >75 % of models agree
13 on the direction of change.
14
15
16 9.6.2.2 Terrestrial Biodiversity
17
18 Local extinction is when a species is extirpated from a local site. The magnitude and extent of local
19 extinctions predicted across Africa increase substantially under all future global warming levels (high
20 confidence) (Table 9.5; Figure 9.19). Above 2 the risk of sudden disruption or loss of local biodiversity,
21 increases and becomes more widespread, especially in Central, West and East Africa (Trisos et al., 2020).
22
23 Global extinction is when a species is extirpated from all areas. At 2 global warming, 11.6% of African
24 species (mean 11.6%, 95% CI 6.8�18.2%) assessed are at risk of global extinction, placing Africa second
25 only to South America in the magnitude of projected biodiversity losses (Urban, 2015). At >2, 20% of
26 North African mammals may lose all suitable climates (Soultan et al., 2019), and over half of the dwarf
27 succulents in South African Karoo may lose >90% of their suitable habitat (Young et al., 2016). Among the
28 thousands of species at risk, many are species of ecological, cultural and economic importance such as
29 African wild dogs (Woodroffe et al., 2017) and Arabica Coffee (Moat et al., 2019).
30
31 With increasing warming, there is a lower likelihood species can migrate rapidly enough to track shifting
32 climates, increasing global extinction risk and biodiversity loss across more of Africa (high confidence).
33 Immigration of species from elsewhere may partly compensate for local extinctions and lead to local
34 biodiversity gains in some regions (Newbold, 2018; Warren et al., 2018). However, more regions face net
35 losses than net gains. At 1.5 global warming, >46% of localities face net declines in vertebrate species
36 richness of >10%, with net increases projected for less than 15% of localities (Barbet-Massin and Jetz, 2015;
37 Newbold, 2018). At >2癈, 9% of species face complete range loss by 2100, regardless of their dispersal
38 ability (Urban, 2015). With >4癈 global warming, a net loss of >10% of vertebrate species richness is
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1 projected across 85% of Africa (Barbet-Massin and Jetz, 2015; Mokhatla et al., 2015; Newbold, 2018;
2 Warren et al., 2018). Mountain top endemics and species in North and southern Africa are at risk due to
3 disappearing cold climates (Milne et al., 2015; Garcia et al., 2016; Bentley et al., 2018; Soultan et al., 2019).
4 For hot regions such as the Sahara, Congo Basin and Kalahari, no warmer-adapted species are available
5 elsewhere to compensate for local extinctions, so the resilience of local biodiversity will depend entirely on
6 the persistence of species (Burrows et al., 2014; Garcia et al., 2014). The capacity for species to avoid
7 extinction through behavioural thermoregulation, plasticity or evolution is uncertain but will become
8 increasingly unlikely under higher warming scenarios (Conradie et al., 2019).
9
10
11 Table 9.5: Risk of local extinction risk increases across Africa with increasing global warming.
Global Warming Taxa % of species at a Extent across Areas at risk References
Level (relative to site at risk of Africa (% of
1850-1900) local extinction the land area
of Africa)
1.5 Plants, insects, >10% >90% Widespread. Hot Fig. 9.29b
vertebrates and/or arid regions (Newbold, 2018;
especially at risk, Warren et al.,
including Sahara, 2018)
Sahel and Kalahari
>2 Plants, insects, >50% 18% Widespread (Newbold, 2018;
vertebrates
Warren et al.,
2018)
>4 Plants, insects, >50% 45-73% Widespread. Higher Fig. 9.29c
vertebrates uncertainty for (Barbet-Massin
12 central African and Jetz, 2015;
13 tropical forests due Newbold, 2018;
to lower agreement Warren et al.,
between 2018)
biodiversity models
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>1.5癈 >4癈
1.5-2癈 2.6-3.2癈
1
2 Figure 9.19: The loss of African biodiversity under future climate change is projected to be widespread and increasing
3 substantially with every 0.5 above the current (2001�2020) level of global warming (high confidence). (a) Projected
4 biodiversity loss, quantified as percentage change in species abundance, range size or area of suitable habitat increases
5 with increasing global warming levels (relative to 1850�1900). Above 1.5 global warming, half of all assessed
6 species are projected to lose >30% of their population, range size or area of suitable habitat, with losses increasing to
7 >40% for >3. The 2001�2020 level of global warming is around 1 higher than 1850�1900 (IPCC, 2021). Boxplots
8 show the median (horizontal line), 50% quantiles (box), and points are studies of individual species or of multiple
9 species (symbol size indicates the number of species in a study). (b璫) The mean projected local extinction of
10 vertebrates, plants and insects within 100 km grid cells increases in severity and extent under increased global warming
11 (relative to 1850�1900). Local extinction >10% is widespread by 1.5. Pixel colour shows the projected percentage of
12 species undergoing local extinction and the agreement between multiple biodiversity models. (d璭) The mean projected
13 increase in species of freshwater fish vulnerable to local extinction within 10 km grid cells for future global warming.
14 Around a third of fish species are projected to be vulnerable to extinction by 2 global warming. Pixel colour shows
15 the projected percentage of species vulnerable to extinction and agreement between multiple vulnerability models. In
16 (a), data were obtained from 22 peer-reviewed papers published since 2012 investigating the impacts of projected
17 climate change on African biodiversity. When a paper provided impact projections for several time periods, climate
18 change scenarios or for more than one species, each impact was recorded as an individual biodiversity impact
19 projection, resulting in a database of 1,165 biodiversity impact projections. Data were initially collected by Manes et al.
20 (2021) as part of a larger literature review for Cross-Chapter Paper 1 on Biodiversity Hotspots and then expanded to
21 include areas outside of African priority conservation areas (see Supplementary Material Table SM 9.4). The literature
22 review was limited to peer-reviewed publications that reported quantifiable risks to biodiversity, eliminating non-
23 empirical studies. In (b璫), projections are based on intersecting current and future modelled species distributions at ~10
24 km spatial resolution from two recent global assessments of climate change impacts on terrestrial vertebrates (Newbold,
25 2018; Warren et al., 2018). In (d-e) projections are based on intersecting future species vulnerabilities from two recent
26 assessments of climate change vulnerability of freshwater fish species (Nyboer et al., 2019; Barbarossa et al., 2021).
27
28
29 9.6.2.3 Marine Ecosystems
30
31 African coastal and marine ecosystems are highly vulnerable to climate change (high confidence). At 1.5
32 of global warming, mangroves will be exposed to sedimentation and sea level rise, while seagrass
33 ecosystems will be most affected by heat extremes (high confidence) (Hoegh-Guldberg et al., 2018) and
34 turbidity (Wong et al., 2014). These risks will be amplified at 2 and 3 (virtually certain) (Hoegh-
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1 Guldberg et al., 2018). Over 90% of East African coral reefs are projected to be destroyed by bleaching at
2 2 of global warming (very high confidence) (Hoegh-Guldberg et al., 2018). At around 2.5 global
3 warming, an important reef-building coral (Diploastrea heliopora) in the central Red Sea is projected to stop
4 growing altogether (Cantin et al., 2010). By 2.5, suitable habitat of >50% of species are projected to
5 decline for coastal lobster in East and North Africa, with large declines for commercially important J.
6 lalandii in southern Africa (Boavida-Portugal et al., 2018). More generally, tropical regions, especially
7 exclusive economic zones in West Africa, are projected to lose large numbers of marine species and may
8 experience sudden declines with extratropical regions having potential net increases as species track shifting
9 temperatures poleward (Garc韆 Molinos et al., 2016; Trisos et al., 2020).
10
11 9.6.2.4 Freshwater Ecosystems
12
13 Above 2 global warming, the proportion of freshwater fish species vulnerable to climate change increases
14 substantially (high confidence) (Figure 9.19). At 2, 36.4% of fish species are projected to be vulnerable to
15 local or global extinction by 2100, increasing to 56.4% under 4 warming (average of values from (Nyboer
16 et al., 2019; Barbarossa et al., 2021) (Figure 9.19). Global warming reduces available habitat for freshwater
17 species due to reduced precipitation and increased drought leading to increasing water temperatures above
18 optimal physiological limits in floodplains, estuaries, wetlands, ephemeral pools, rivers and lakes (Dalu et
19 al., 2017; Kalacska et al., 2017; Nyboer and Chapman, 2018). Along the Zambezi River, projected flow
20 reductions could cause a 22% reduction in annual spawning habitat and depletion of food resources for fry
21 and juvenile fish that could impede fish migration and reduce stocks (Kangalawe, 2017; Mart韓ez-Capel et
22 al., 2017; Tamatamah and Mwedzi, 2020). More aquatic species will have the capacity to cope with 2
23 compared to 4 global warming, with more negative effects on physiological performance at 4 (Dallas,
24 2016; Pinceel et al., 2016; Zougmor� et al., 2016; Nyboer and Chapman, 2017; Ross-Gillespie et al., 2018).
25 Endemic, specialised fish species will have a lower capacity to adjust to elevated water temperatures
26 compared to hardier generalist fishes (McDonnell and Chapman, 2015; Nyboer and Chapman, 2017;
27 Lapointe et al., 2018; Reizenberg et al., 2019). More work is needed to understand the risk for invertebrates
28 (Dallas and Rivers-Moore, 2014; Cohen et al., 2016), and to understand the potential effects of reduced
29 mixing of water and other climate risks on freshwater biodiversity.
30
31 9.6.2.5 Climate Change & Ecosystem Services
32
33 Direct human dependence on provisioning ecosystem services in Africa is high (Egoh et al., 2012; IPBES,
34 2018). For example, natural forests provided 21% of rural household income across 11 African countries
35 (Angelsen et al., 2014) and wild-harvested foods (including fisheries) provide important nutrition to millions
36 of Africans, including through important micronutrients and increased dietary diversity (Powell et al., 2013;
37 Baudron et al., 2019a) (Sections 9.8.2.3 and 9.8.5)
38
39 Climate change has affected ecosystem services in Africa by reducing fish stocks, crop and livestock
40 productivity and water provisioning due to heat and drought (see Sections 9.8.2.1, 9.8.2.2, 9.8.2.4 and
41 9.8.5.1). Woody encroachment is decreasing cattle production and water supply (Smit and Prins, 2015;
42 Stafford et al., 2017), but can also provide forage for goat production, as well as resins, fuelwood and
43 charcoal (Reed et al., 2015; Stafford et al., 2017; Charis et al., 2019). Local communities perceive climate
44 change to have decreased crop and livestock productivity, reduced wild food availability and reduced forest
45 resources across Africa (Onyekuru and Marchant, 2014) (see Sections 9.8.2.1, 9.8.2.2, 9.8.2.4 and 9.8.2.3).
46
47 With global warming >3, and with high population growth and agricultural expansion (SSP3, 2081�2100),
48 1.2 billion Africans are projected to be negatively affected by pollution of drinking water from reduced water
49 quality regulation by ecosystems and 27 million people affected by reduced coastal protection by ecosystems
50 (Chaplin-Kramer et al., 2019). The number of people affected reduces to 0.4 billion and 22 million under a
51 sustainable development scenario with global warming below 2 (SSP1, 2081�2100). The African tropical
52 forest carbon sink has been more resilient than Amazonia to recent warming but may already have peaked,
53 and this service is predicted to decline with further warming, reducing 14% by the 2030s (Hubau et al., 2020;
54 Sullivan et al., 2020). This declining carbon storage may be offset by CO2 fertilisation (low confidence)
55 (Martens et al., 2021). Climate change is projected to shift the geographic distribution of important human
56 and livestock disease vectors (see Section 9.8.2.4 and 9.10.2). Changes in rainfall seasonality compounded
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1 with land privatisation and population growth may adversely impact nomadic and semi-nomadic pastoralists
2 who follow shifting patterns of greening vegetation (Van Der Ree et al., 2015).
3
4 9.6.2.6 Invasive Species
5
6 Invasive species threaten African ecosystems and livelihoods (Ranasinghe et al., 2021). For instance,
7 economic impacts were estimated at USD 1 billion per year for smallholder maize farmers in East Africa
8 (Pratt et al., 2017). Climate change is projected to change patterns of invasive species spread (high
9 confidence). The area of suitable climate for Lantana camara is projected to contract (Taylor et al., 2012)
10 and to expand for Prosopis juliflora (Sintayehu et al., 2020). Bioclimatic suitability for fall armyworm, a
11 major threat to maize, is projected to decrease in Central Africa but expand in southern and West Africa
12 (Zacarias, 2020), and to expand for coffee berry borer (H. hampei) in Uganda and around Mount Kenya
13 (Jaramillo et al., 2011). Climate suitability for tephritid fruit flies is projected to decrease in central Africa
14 (Hill et al., 2016). Increased water temperature is projected to favour invasive over local freshwater fish
15 populations and shift the range of invasive aquatic plants in South Africa (Hoveka et al., 2016; Shelton et al.,
16 2018). Alterations to lake and river connectivity are predicted to modify invasion pathways in Lake
17 Tanganyika and water hyacinth coverage may increase with warmer waters in Lake Victoria (Masters and
18 Norgrove, 2010; Plisnier et al., 2018).
19
20 9.6.3 Nature-Based Tourism in Africa
21
22 Nature-based tourism is important for African economies and jobs. Tourism contributed 8.5% of Africa's
23 2018 GDP (World Travel and Tourism Council, 2019a) with Wildlife tourism contributing a third of tourism
24 revenue (USD 70.6 billion), supporting 8.8 million jobs (World Travel and Tourism Council, 2019b).
25
26 Climate change is already negatively affecting tourism in Africa (high confidence). The 2015�2018 Cape
27 Town drought caused severe water restrictions, reducing tourist arrivals and spending with associated job
28 losses (Dube et al., 2020). Anthropogenic climate change increased the likelihood of drought by a factor of
29 five to six (Pascale et al., 2020). Extreme heat days have increased across South African national parks since
30 the 1990s (van Wilgen et al., 2016). This reduces animal mobility, decreasing animal viewing opportunities
31 (Dube and Nhamo, 2020). Tourists and employees also fear heat stress (Dube and Nhamo, 2020). Visitors to
32 South Africa's national parks preferred to visit in cool-to-mild temperatures (Coldrey and Turpie, 2020).
33 Extreme weather conditions disrupted tourist activities and damaged infrastructure at Victoria Falls, Hwange
34 National Park, Kruger National Park and the Okavango Delta (Dube et al., 2018; Dube and Nhamo, 2018;
35 Mushawemhuka et al., 2018; Dube and Nhamo, 2020). Rainfall variability and drought alters wildlife
36 migrations, affecting tourist visits to the Serengeti (Kilungu et al., 2017). Reduced tourism decreases revenue
37 for national park management (van Wilgen et al., 2016).
38
39 Future climate change is projected to further negatively affect nature-based tourism. Decreased snow and
40 forest cover may reduce visits to Kilimanjaro National Park (Kilungu et al., 2019). Woody plant expansion
41 in savanna and grasslands reduce tourist's game viewing experience and negatively impact conservation
42 revenues (Gray Emma and Bond William, 2013; Arbieu et al., 2017). Visitation rates to South African
43 national parks, based on mean monthly temperatures, are projected to decline 4% with 2 global warming
44 (Coldrey and Turpie, 2020). Sea level rise and increased intensity of storms is projected to reduce beach
45 tourism due to beach erosion (Grant, 2015; Amusan and Olutola, 2017). Tourism in the Victoria Falls,
46 Okavango and Chobe hydrological systems may be negatively affected by heat and increased variability of
47 rainfall and river flow (Saarinen et al., 2012; Dube and Nhamo, 2019). Increased extreme heat will increase
48 air turbulence and weight restrictions on aircraft, which could make air travel more uncomfortable and
49 expensive to African destinations (Coffel and Horton, 2015; Dube and Nhamo, 2019).
50
51 9.6.3.1 Protected Areas and Climate Change
52
53 African protected areas store around 1.5% of global land ecosystem carbon stocks and support biodiversity
54 (Gray et al., 2016; Melillo et al., 2016; Sala et al., 2018). They also support livelihoods and economies, such
55 as through nature-based tourism and improved fisheries (Brockington and Wilkie, 2015; Mavah et al., 2018;
56 Ban et al., 2019).
57
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1 Climate change and land use change will interact to influence the effectiveness of African protected areas
2 (high confidence). Species representation in the existing African protected area network is projected to
3 decrease due to species range shifts for mammals, bats, birds and amphibians (Hole et al., 2009; Baker et al.,
4 2015; Payne and Bro-J鴕gensen, 2016; Smith et al., 2016; Phipps et al., 2017). Species ability to disperse
5 between areas to track shifting climates is increasingly impaired by land transformation and fencing, which
6 also impact seasonal wildlife migrations (Lovschal et al., 2017; Sloan et al., 2017). On land, only 0.5% of the
7 African protected area network is connected through low-impact landscapes (Ward et al., 2020). Linear
8 transport infrastructure (e.g., roads, railways, pipelines) and fencing from proposed `development corridors'
9 are projected to bisect over 400 protected areas and degrade around 1,800 more (Laurance et al., 2015).
10 Climate change could increase human-wildlife conflict as resultant resource shortages cause communities to
11 move into protected areas for harvesting or livestock grazing, or wildlife to move out of protected areas and
12 into contact with people (Mukeka et al., 2018; Kupika et al., 2019; Hambira et al., 2020). See Section 9.1.4
13 for the role of land and ocean protected areas in climate change adaptation.
14
15 9.6.4 Ecosystem-Based Adaptation in Africa
16
17 Ecosystem-based adaptation (EbA) uses biodiversity and ecosystem services to assist people to adapt to
18 climate change (Swanepoel and Sauka, 2019). Africa's Nationally Determined Contributions (NDCs) show
19 36% of adaptation actions identified by 52 countries are considered to be EbA (Figure 9.20).
20
21 EbA can reduce climate impacts and there is high agreement EbA can be more cost-effective than traditional
22 grey infrastructure when a range of economic, social and environmental benefits are also accounted for
23 (Table 9.6) (Baig et al., 2016; Emerton, 2017; Chausson et al., 2020). This is particularly relevant in Africa
24 where climate vulnerabilities are strongly linked to natural resource-based livelihood practices and existing
25 grey infrastructure levels are low in many regions (Dube et al., 2016; Reid et al., 2019). However, financial
26 constraints limit EbA project implementation (Mumba et al., 2016; Swanepoel and Sauka, 2019).
27
28 Evidence for EbA in Africa is largely case study based and often anecdotal (Reid et al., 2018). There is high
29 agreement that costs, challenges and negative outcomes of EbA interventions are still poorly understood
30 (Reid, 2016; Chaplin-Kramer et al., 2019), despite limited evidence for the efficacy of context-specific
31 applications at different scales (Doswald et al., 2014).
32
33
34
35 Figure 9.20: Over a third (36%) of all adaptation actions identified in the NDCs of 52 African countries are Ecosystem-
36 based Adaptations (EbA). Of these actions � 83% fall within the Agriculture, Land Use/Forestry, Environment and
37 Water sectors. The EbA actions identified from the NDCs span 12 primary sectors and 29 sub-sectors.
38
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1
2 Table 9.6: The beneficial outcomes of Ecosystem-based Adaptation (EbA) actions and assessed confidence in these
3 outcomes. Assessment is provided for EbA options in the four most prevalent EbA sectors identified in the Nationally
4 Determined Contributions of 52 African countries (Figure 9.20). See Chapter 2.6.3 and 3.6.2 of this report for further
5 assessment of EbA approaches in terrestrial, freshwater and marine systems.
Sector EbA Action(s) Outcome(s) Confidence Source(s)
Improved soil and High (Thierfelder et al.,
water conservation 2017)
Conservation Improved (Pittelkow et al.,
agriculture agricultural Medium 2015; Thierfelder et
productivity and al., 2017; Adenle et
Agriculture drought resilience al., 2019)
Improved (Shiferaw et al.,
Diversified crop agricultural High 2014; Tesfaye et al.,
2016; Thierfelder et
varieties productivity and
drought resilience al., 2017)
Carbon sequestration High (Melillo et al., 2016;
and storage Griscom et al., 2017;
FAO, 2018a)
Stepping stones for
species migrating Medium (Beale et al., 2013;
due to climate Roberts et al., 2020)
change
(Anthony et al.,
Ecosystem Increased ecosystem 2015; Sierra-Correa
protection and and Cantera Kintz,
Environment restoration resilience to High 2015; Kroon et al.,
2016; Roberts et al.,
disturbance
2017)
Livelihood (Lunga and
diversification Musarurwa, 2016;
opportunities from Bedelian and Ogutu,
ecotourism, resource Medium 2017; Agyeman,
harvesting, and 2019; Kupika et al.,
rangelands (among 2019; Naidoo et al.,
others) 2019)
Restoration of
Forestry & Other Restoration/ degraded ecosystems High (Mugwedi et al.,
Land Use Reforestation and enhanced carbon Medium 2018)
Sustainable forestry sequestration
and land Reducing pressure (Peprah, 2017;
management on forests for food Zegeye, 2018)
and energy needs
(Bradshaw et al.,
Improved flood High 2007; Mwenge
Kahinda et al., 2016;
attenuation capacity
Rawlins et al., 2018)
Integrated catchment (Ndebele-Murisa,
2014; Natugonza et
Water al., 2015; Lowe et
al., 2019;
management Tamatamah and
Improved resilience
of freshwater High
ecosystems
Mwedzi, 2020)
6
7
8 9.6.4.1 Terrestrial Ecosystems
9
10 Improved ecosystem care and restoration are cost-effective for carbon sequestration while providing multiple
11 environmental, social and economic co-benefits (Griscom et al., 2017; Shukla et al., 2019). Protecting and
12 restoring natural forests and wetlands reduces flood risk across multiple African countries (Bradshaw et al.,
13 2007). In Kenya, enclosures for rangeland regeneration diversified income sources, which could increase the
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1 adaptive capacity of local people (Mureithi et al., 2016; Wairore et al., 2016). Sustainable agroforestry in
2 semi-arid regions provides income sources from fuelwood, fruit and timber and reduces exposure to drought,
3 floods and erosion (Quandt et al., 2017). Forest protection in Zimbabwe maintains honey production during
4 droughts, providing food supply options if crops fail (Lunga and Musarurwa, 2016). Community-based
5 natural resource management in pastoral communities improved institutional governance outcomes through
6 involving community members in decision-making, increasing the capacity of these communities to respond
7 to climate change (Reid, 2014).
8
9 EbA can also increase ecological resilience. Re-introduction of fire and large mammals can restore
10 ecosystem services, enhance adaptive capacity and benefit people by combatting woody encroachment,
11 restoring grazing and increasing streamflow (Asner et al., 2016; Stafford et al., 2017; Cromsigt et al., 2018).
12 Herbivores can also reduce fuel loads in areas facing increased fire risk (Hempson et al., 2017).
13
14 Protected areas can be `stepping stones' that facilitate climate-induced species range shifts (Roberts et al.,
15 2020), preserve medicinal plant diversity despite climate change (Kaky and Gilbert, 2017) and provide
16 livelihood diversification opportunities (Table 9.6). Protecting 30% of sub-Saharan Africa's land area could
17 reduce the proportion of species at risk of extinction by around 60% in both low and high warming scenarios
18 (Hannah et al., 2020). The role of protected areas in EbA can be strengthened by: (i) increasing coverage of
19 diverse environments and high carbon storage ecosystems, (ii) habitat restoration, (iii) maintaining intact
20 habitat, (iv) participatory, equitable conservation and adaptation strategies; (v) cooperation across borders
21 and (vi) adequate monitoring (Gillson et al., 2013; Rannow et al., 2014; Midgley and Bond, 2015; Pecl et al.,
22 2017; Dinerstein et al., 2019; Roberts et al., 2020).
23
24
25 [START BOX 9.3 HERE]
26
27 Box 9.3: Tree Planting in Africa
28
29 Due to widespread deforestation and forest degradation (Malhi et al., 2014), future scenarios to limit global
30 warming include large-scale reforestation and afforestation (Griscom et al., 2017; Bastin et al., 2019). Africa
31 has been targeted through the AFR100 (https://afr100.org) to plant ~1 million km2 of trees by 2030 (Bond et
32 al 2019). Maintaining existing indigenous forest and indigenous forest restoration is a win-win, maximising
33 benefits to biodiversity, adaptation and mitigation (Griscom et al., 2017; Watson et al., 2018; Lewis et al.,
34 2019) (high confidence).
35
36 Yet many areas targeted by AFR100 erroneously mark Africa's open ecosystems (grasslands, savannas,
37 shrublands) as degraded and suitable for afforestation (Figure Box 9.3.1) (Veldman et al., 2015; Bond et al.,
38 2019) (high confidence). These ecosystems are not degraded, they are ancient ecosystems that evolved in the
39 presence of disturbances (fire/herbivory) (Maurin et al., 2014; Bond and Zaloumis, 2016; Charles-
40 Dominique et al., 2016). Afforestation prioritises carbon sequestration at the cost of biodiversity and other
41 ecosystem services (Veldman et al., 2015; Bond et al., 2019). Furthermore, it remains uncertain how much
42 carbon can be sequestered as, compared to grassy ecosystems, afforestation can reduce belowground carbon
43 stores and increase aboveground carbon loss to fire and drought (Yang et al., 2019; Wigley et al., 2020b;
44 Nu馿z et al., 2021). Thus, afforested areas may store less carbon than ecosystems they replace (Dass et al.,
45 2018; Heilmayr et al., 2020). Afforestation would reduce livestock forage, eco-tourism potential and water
46 availability (Gray Emma and Bond William, 2013; Anad髇 et al., 2014; Cao et al., 2016; Stafford et al.,
47 2017; Du et al., 2021), and may reduce albedo thereby increasing warming (Baldocchi and Penuelas, 2019;
48 Bright et al., 2015).
49
50 Exotic tree species are often selected for planting (e.g., Pinus spp or Eucalyptus spp), but in parts of Africa,
51 they have become invasive (Zengeya, 2017; Witt et al., 2018), increasing fire hazards and decreasing
52 biodiversity and water resources (Nu馿z et al., 2021) (high confidence). Negative impacts of afforestation on
53 ecosystems are not restricted to plantations of exotic species; they extend to inappropriate planting of native
54 forest species (Slingsby et al., 2020).
55
56
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1
2 Figure Box 9.3.1: Proposed tree planting plans in Africa are focused on (a) non-forested ecosystems like savannas,
3 grasslands and shrublands which (b) host uniquely adapted biodiversity and (c) offer important ecosystem services like
4 grazing which supports subsistence and commercial agriculture. Figure adapted from (Bond et al., 2019).
5
6 [END BOX 9.3 HERE]
7
8
9 9.6.4.2 Freshwater Ecosystems
10
11 EbA can mitigate flooding and increase the resilience of freshwater ecosystems (Table 9.6). Adaptation in
12 African freshwater ecosystems is heavily influenced by non-climate anthropogenic factors, including land
13 use change, water abstraction and diversion, damming and overfishing (Dodds et al., 2013; Kimirei et al.,
14 2020; UNESCO and UN-Water, 2020). Wetlands and riparian areas support biodiversity, act as natural
15 filtration systems and serve as buffers to changes in the hydrological cycle, thereby increasing the resilience
16 of freshwater ecosystems and the people that rely on them (Ndebele-Murisa, 2014; Musinguzi et al., 2015;
17 Lowe et al., 2019). However, national adaptation programmes of action, national adaptation plans and
18 national communications rarely consider the ecological stability of ecosystems safeguarding the very water
19 resources they seek to preserve (Kolding et al., 2016). Some countries have mandated the protection of
20 riparian zones, but implementation is low (Musinguzi et al., 2015; Muchuru and Nhamo, 2018). Protecting
21 terrestrial areas surrounding Lake Tanganyika benefited fish diversity (Britton et al., 2017). Afforestation
22 reduces water availability but forest restoration and removing invasive plant species can increase water flows
23 in regions facing water insecurity from climate change (Chausson et al., 2020; Le Maitre et al., 2020).
24 Regular, long-term monitoring of African freshwaters would improve understanding of responses to climate
25 change. General principles for this type of monitoring were developed for Lake Tanganyika (Plisnier et al.,
26 2018) and could be applied to develop harmonised, regional monitoring of African lakes, rivers and wetlands
27 (Tamatamah and Mwedzi, 2020)
28
29 9.6.4.3 Marine and Coastal Ecosystems
30
31 Marine and coastal ecosystems such as mangroves, seagrass and coral reefs provide storm protection and
32 food security for coastal communities (high confidence) (IPCC, 2019c). Restoring reef systems reduced
33 wave height in Madagascar (Narayan et al., 2016), but there is limited evidence for the efficacy of coral reef
34 restoration at large scales with increased warming (3.6.3). Populations at risk from storm surge and/or sea
35 level rise coincide with areas of high coastal EbA potential from Mozambique to Somalia, and coastlines of
36 the Gulf of Guinea, Gambia, Guinea-Bissau and Sierra Leone (Jones et al., 2020). Understanding hotspots of
37 EbA potential is particularly important for West Africa with some of the highest levels of human dependence
38 on marine ecosystems at high risk from climate change and large populations vulnerable to sea level rise
39 (Selig et al., 2018; Trisos et al., 2020) (Sections 9.9.3.1 and 9.8.5.2).
40
41 Marine protected areas (MPAs) can yield multiple adaptation benefits, such as buffering species from
42 extinction and increasing fish stocks, as well as storing large amounts of carbon (Edgar et al., 2014; Roberts
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1 et al., 2017; Lovelock and Duarte, 2019). However, this potential of MPAs will reach limits with increased
2 warming (Roberts et al., 2017). For example, MPAs cannot prevent coral bleaching at scale and mass die-
3 offs are well-described from MPAs following climate shocks (Bates et al., 2019; Bruno et al., 2019).
4 Although prioritising MPA coverage of climate refugia, such as the northern Mozambique channel, may
5 offer some increased resilience (McClanahan et al., 2014).
6
7
8 9.7 Water
9
10 Much of Africa experiences very high hydrological variability in all components of the water cycle, with
11 important implications for people and ecosystems. Most of the continent's water is stored in groundwater
12 (660,000 km3), which is 20 times more than the water stored in the lakes and 100 times more than the annual
13 renewable water resources (MacDonald et al., 2012). The accessible volume of groundwater via wells and
14 springs is smaller than these estimates (Xu et al., 2019). Africa has 63 transboundary river basins (UNEP,
15 2010), 72 mapped transboundary aquifers (Nijsten et al., 2018) and 33 transboundary lakes (ILEC and
16 UNEP, 2016), reflecting a highly water-connected and interdependent socio-ecological system across
17 countries, extending also to the coastal areas of the continent (see Section 4.1, Figure 4.1).
18
19 9.7.1 Observed Impacts from Climate Variability and Climate Change
20
21 Climate impacts on water are occurring against a backdrop of increasing temperatures and changes in
22 rainfall, with increased seasonal and interannual variability, droughts in some regions, and increased
23 frequency of heavy rainfall events (see Section 9.5). In West Africa, declines in river flows have been
24 attributed to declining rainfall and increasing temperature, drought frequency and water demand (Biao, 2017;
25 Thompson et al., 2017; Descroix et al., 2018). In Central Africa, the Congo river demonstrates inter-decadal
26 shifts but no long-term trend (Mahe et al., 2013; Alsdorf et al., 2016), however, recently observed falling
27 water levels in its upper and middle reaches are attributed to climate change (von Lossow, 2017).
28
29 A review of river flow and lake level changes in 82 basins in eastern and southern Africa regions for 1970�
30 2010 showed mixed trends: 51% had decreasing trends ranging from 10�49% and 11% increasing trends
31 ranging from 7�60% (Sch鋐er et al., 2015). However, in southern Africa as a whole, river flows have mostly
32 decreased (high confidence) (Dallas and Rivers-Moore, 2014). In East Africa, large rivers such as the Tana
33 show increasing flow (1941�2016) related to increased rainfall in the highlands, with little influence of flow
34 regulation by a series of dams (Langat et al., 2017). The Nile river basin has been experiencing a mainly
35 increasing rainfall trend upstream and decreasing trend downstream (Onyutha et al., 2016). The observed
36 changes are driven by a complex coupling of changes in climate, land use and water demand.
37
38 Observed climate changes in Africa (see Section 9.5) have led to changes in river flow and runoff (Dallas
39 and Rivers-Moore, 2014; Wolski et al., 2014) and high fluctuations in lake levels (high confidence)
40 (Natugonza et al., 2016; Ogutu-Ohwayo et al., 2016; Gownaris et al., 2018). Shallow lakes respond
41 dramatically to hydrological changes, for example, Lake Chilwa has dried up completely nine times in the
42 last century (Wilson, 2014), while Lake Chad shrunk by 90% between 1963 and 2000 (Gao et al., 2011).
43 However, recent analyses indicate that Lake Chad's water levels have been stable since 2000 due to infilling
44 from groundwater resources (Buma et al., 2018; Pham-Duc et al., 2020). Other factors such as deforestation
45 and increased water use in upstream tributaries also contribute to lake shrinking (Mvula et al., 2014). Water
46 levels in Kenya's mostly shallow rift lakes have been rising since 2010, with some exceeding historical
47 record high levels (Schagerl and Renaut, 2016; Olago et al., 2021). The recent 10-year rising trend is partly
48 attributed to increased rainfall and changing land uses (Onywere and John M. Mironga, 2012; Olago et al.,
49 2021). Changes in water level fluctuations of 13 African lakes have been positively correlated with primary
50 and overall production (Gownaris et al., 2018), and will have important consequences for freshwater
51 ecosystems and related ecosystem goods and services (see Sections 9.6.1.3 and 9.8.5). Other effects of
52 observed climate changes in Africa include higher episodic groundwater recharge, particularly in drylands,
53 from heavy rainfall events that are in some cases related to El Ni駉-Southern Oscillation and the Indian
54 Ocean Dipole (Taylor et al., 2013; Fischer and Knutti, 2016; Cuthbert et al., 2019; Kotchoni et al., 2019;
55 Myhre et al., 2019), reduced soil moisture, more frequent and intense floods, more persistent and frequent
56 droughts (Douville et al., 2021) and the steady decline and projected disappearance by 2040 of African
57 tropical glaciers (see Section 9.5.9).
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1
2 The mixed-signal in river flow trends (increase/decrease/no-change) across Africa mirrors the results seen
3 globally for runoff and streamflow (see Section 4.2.3 in Chapter 4). Hydrological extremes are, however, of
4 increasing concern. There has been an increase in drought frequency, severity and spatial extent in recent
5 decades. From 1900�2013, Africa suffered the largest number of drought events globally and registered the
6 second largest number of people affected after Asia (Masih et al., 2014). The likelihood of recent severe
7 climate conditions such as the multi-year Cape Town Drought has increased to due to human-induced
8 climate change (Otto et al., 2018; Pascale et al., 2020) (see Box 9.4), and regional and urban floods (Yuan et
9 al., 2018; Tiitmamer, 2020) and droughts (Funk et al., 2018b; Siderius et al., 2018; Uhe et al., 2018) are
10 expected to increase.
11
12 However, between 2010�2020 more people across Africa have been impacted by floods (e.g., related to
13 Cyclone Idai in March 2019) compared to droughts (Lumbroso, 2020). Coastal cities are vulnerable to floods
14 related to rainfall and sea level rise (Musa et al., 2014), as exemplified by the flood disasters experienced in
15 the Niger delta in 2012 which displaced more than 3 million people and destroyed schools, clinics, markets
16 and electricity installations (Amadi and Ogonor, 2015). From 2000�2015, the proportion of people exposed
17 to floods grew by 20�24%, mostly in Africa and Asia, and these numbers will increase under climate change
18 (Tellman et al., 2021). Sectoral impacts from flooding within Africa and globally are further elaborated on in
19 Sections 9.8.2 and 9.8.5.1, Table 9.3 and Section 4.3 in Chapter 4.
20
21
22 [START BOX 9.4 HERE]
23
24 Box 9.4: African Cities Facing Water Scarcity
25
26 Many African cities will face increasing water scarcity under climate change (Grasham et al., 2019). The
27 Cape Town and Dodoma cases illustrate challenges for both surface and groundwater supply and what
28 adaptation responses have been employed.
29
30 The Cape Town Drought (2015-2018)
31
32 The Cape Town drought illustrates how a highly diverse African city and its citizens responded to protracted
33 and unanticipated water scarcity. Anthropogenic climate change made the drought five to six times more
34 likely (Pascale et al., 2020; Doblas-Reyes et al., 2021). After three consecutive years of low precipitation,
35 Cape Town braced for a `Day Zero' where large portions of the city would lose water supply (Cole et al.,
36 2021a). The risk of day zero was anticipated to cascade to affect risks to health, economic output and
37 security (Simpson et al., 2021b). The case study highlights the importance of communication, budgetary
38 flexibility, robust financial buffers and insurance mechanisms, disaster planning, intergovernmental
39 cooperation, nature-based solutions, infrastructure transformations and equitable access for climate
40 adaptation in African cities facing water scarcity.
41
42 A substantial media campaign was launched to inform residents about the severity of the drought and urge
43 water conservation (Booysen et al., 2019; Hellberg, 2019; Ouweneel et al., 2020). Together with stringent
44 demand management through higher water tariffs, this communication campaign played an important role in
45 reducing consumption from 540 to 280 litres per household per day (Booysen et al., 2019; Simpson et al.,
46 2019a). Revenue from water sales contributes 14% of Cape Town's total revenue, making it the third-largest
47 source of `own' revenue for the city (Simpson et al., 2019b). However, with an unprecedented reduction in
48 water use, the municipal budget was undermined (Simpson et al., 2020b). Collecting less revenue created a
49 financial shock as the city struggled to recover operating finance, even while new capital requirements were
50 needed for the development of expensive new water supply projects (Simpson et al., 2019b). This financial
51 shock was compounded by the economic stress of poor agricultural and tourism performance brought about
52 by the drought (Shepherd, 2019; Simpson et al., 2021b). As wealthy residents invested in private, off-grid
53 water supplies, the risk of reduced municipal revenue collections from newly off-grid households aggregated
54 with the risk of reduced tourism, increasing the risk to the reputation of the incumbent administration
55 (Simpson et al., 2021b). This demonstrates how a population cohort with a high response capability to water
56 scarcity can reduce risk while simultaneously increasing risks to the municipality and its capacity to provide
57 water to vulnerable residents (Simpson et al., 2020b). Given that city populations in Africa pay 5�7 times
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1 more for water than the average price paid in the United States or Europe (Adamu and Ndi, 2017; Lwasa et
2 al., 2018), municipal finance needs to delink operating revenue from potential climate shocks (see Box 8.6 in
3 Chapter 8).
4
5 The drought led the municipality to consider a broader diversity of water supply options, including
6 groundwater (CoCT, 2019), developing city-scale slow-onset disaster planning (Cole et al., 2021a) and
7 building an enhanced `relationship with water' (CoCT, 2019; Madonsela et al., 2019). This shift in approach
8 is displayed in the recognition of nature-based solutions as a priority in water resilience-building efforts
9 (Rodina, 2019) and is signalled in Cape Town's Water Strategy which aims to become a `water sensitive
10 city' that makes `optimal use of stormwater and urban waterways for flood control, aquifer recharge, water
11 reuse and recreation' (CoCT, 2019).
12
13 The drought required cooperation between multiple spheres of government, and the management of a broad
14 range of stakeholders and political entities (Nhamo and Agyepong Adelaide, 2019; Cole et al., 2021a). The
15 case highlights how a lack of coordination between essential organs of state and political entities can reduce
16 response efficacy (Rodina, 2019). Despite significant investments in water security by public and private
17 entities, one-quarter of Cape Town's population remains in persistent conditions of water stress, emphasising
18 the challenge and importance of inclusive solutions that address the persistent social and economic stressors
19 which affect vulnerability to water scarcity (Enqvist and Ziervogel, 2019).
20
21 Sustaining intensive groundwater use in a dryland city under climate change: Dodoma, Tanzania
22
23 Since 1954, the Makutapora wellfield in semi-arid, central Tanzania has supplied safe water to the city of
24 Dodoma. Substantial rises in wellfield pumping and population growth have increased freshwater demand in
25 Dodoma and dependence upon the Makutapora Wellfield, currently the sole perennial source of piped water
26 to the city. Yet, there is high uncertainty of groundwater recharge rates (Nkotagu, 1996; Taylor et al., 2013)
27 which rely on intense seasonal rainfall associated with the El Ni駉-Southern Oscillation (ENSO) and the
28 Indian Ocean Dipole (IOD) modes of climate variability (e.g., 2 to 7 years) to contribute disproportionately
29 to recharge (Taylor et al., 2013; Kolusu et al., 2019).
30
31 Defining a sustainable pumping rate for the Makutapora wellfield is complicated by the variable and
32 episodic nature of groundwater replenishment in this dryland environment. For example, groundwater
33 recharge during the 1997/1998 El Ni駉 event, the strongest El Ni駉 event of the 20th century, accounted for
34 nearly 20% of all of the recharge received from 1955�2010 (Taylor et al., 2013), highlighting the vital role
35 interannual groundwater storage plays in enabling adaptation to climate variability and change in drylands.
36 The disproportionate contribution of intense seasonal rainfalls to the replenishment of the Makutapora
37 wellfield, consistent with observations from across sub-Saharan Africa (Cuthbert et al., 2019), suggests that
38 groundwater in drylands are currently naturally resilient to climate change. However, it remains unclear
39 whether climate change will strengthen or weaken the influence of ENSO and IOD on rainfall (Brown et al.,
40 2020) and thereby affect the predictability of groundwater recharge.
41
42 As freshwater demand in Tanzania's rapidly growing capital is projected to increase substantially in the
43 coming decades, questions remain as to whether the capacity of the Makutapora wellfield can meet some or
44 all of this demand. Nature-based solutions to improve the resilience of wellfield abstraction to increased
45 pumpage and climate change include Managed Aquifer Recharge (MAR). The sharing of general lessons
46 learned from other cities in dryland Africa employing MAR, such as Windhoek in Namibia (Murray et al.,
47 2018), could prove invaluable.
48
49 [END BOX 9.4 HERE]
50
51
52 9.7.2 Projected Risks and Vulnerability
53
54 9.7.2.1 Projected Risks
55
56 By 2050, up to 921 million additional people in Africa could be exposed to climate change-related water
57 stress, while up to 459 million could experience reduced exposure (Dickerson et al., 2021). This large
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1 variance in numbers and direction of change is related to uncertainties in climate models and non-climate
2 factors like population growth and water withdrawals (Dickerson et al., 2021). The baseline for most of the
3 projected risks presented here is 1971�2000.
4
5 In West Africa, significant spatial variability in river flow is projected in the upper reaches of several rivers,
6 with no clear pattern overall (Roudier et al., 2014) and large uncertainties in estimations of change in runoff
7 (Roudier et al., 2014; Bodian et al., 2018). In some higher altitude regions, like the Niger Inland Delta in
8 West Africa, river flows and water levels are expected to increase (medium confidence) (Aich et al., 2014;
9 Thompson et al., 2017). In the Lower Niger Basin, combined average annual rainfall and erosivity for all the
10 climatic models in all scenario shows increasing rainfall amounts are projected to result in an increasing
11 average change in rainfall-runoff erosivity of about 14%, 19% and 24% for the 2030s, 2050s and 2070s, with
12 concomitant increase in soil loss of 12%, 19% and 21% (Amanambu et al., 2019). In the Volta River system,
13 increasing wet season river flows (+36% by 2090s) and Volta lake outflow (+5% by 2090s) are anticipated
14 under RCP8.5 (medium confidence) (Awotwi A et al., 2015; Jin et al., 2018). In the Volta River basin,
15 compared to 1976�2005, drought events are projected to increase by 1.2 events per decade at around 2 to
16 1.6 events per decade at around 2.5 global warming, and drought area extent is projected to increase by
17 24% to 34% (Oguntunde et al., 2017). In Central Africa, runoff in the Congo River system may increase by
18 up to 50% (RCP8.5), especially in the wet season, enhancing flood risks in the entire Congo basin,
19 particularly in the central and western parts (CSC, 2013). Average river flows are expected to increase in
20 most parts of Central Africa, with expected increases in total potential hydropower production (Ludwig et
21 al., 2013).
22
23 In North Africa, in the upper White Nile basin, Olaka et al. (2019) project a 25% and 5 to 10% (RCP4.5)
24 increase in the intensification of future annual rainfall in the eastern and western parts of the Lake Victoria
25 Basin, respectively, with corresponding variability in future river discharge ranging from 5 to 26%. In the
26 upper Blue Nile basin, models also indicate up to 15% increase in runoffs in wet-season and up to -24%
27 decreasing in dry-season 2021�2040 (RCP8.5) (Ayele et al., 2016; Siam and Eltahir, 2017; Meresa and
28 Gatachew, 2018). The increase of precipitation in wet-season indicates a higher possibility of flash floods
29 while decreased runoffs in dry-season further intensify existing shortage of irrigation water demand (Ayele
30 et al., 2016; Siam and Eltahir, 2017; Meresa and Gatachew, 2018). The annual flow and revenues from
31 hydropower production and irrigated agriculture of the Blue Nile River at Khartoum are projected to increase
32 under maximum but are expected to decrease under minimum and median projected changes in streamflow
33 for 2041�2070 and 2071�2100, respectively (Tariku et al., 2021). The Middle Draa valley in Morocco is
34 expected to experience more severe droughts and the estimation of the water balance suggests a lack of
35 supply in the future (Karmaoui et al., 2016).
36
37 In East Africa, Liwenga et al. (2015) show that it will likely be warmer and wetter in the Great Ruaha River
38 region and with increasing seasonal variation and extremes towards the end of the century. A similar
39 observation is made for the River Pangani, with mean river flow being about 10% higher in the 2050s
40 relative to the 1980�1999 period, associated with a 16�18% increase in rainfall in its upper catchment
41 (Kishiwa et al., 2018). However, at more local scales, the projections cover a range of slight declines to
42 significant increases in mean annual rainfall amounts (Gulacha and Mulungu, 2017). In the Tana River basin
43 in Kenya, water yield is projected to increase progressively under RCP4.5 and RCP8.5 relative to the
44 baseline period 1983�2011 but is characterised by distinct spatial heterogeneity (Muthuwatta et al., 2018).
45
46 In southern Africa, reductions in rainfall over the Limpopo and Zambezi river basins under 1.5 and 2
47 global warming could have adverse impacts on hydropower generation, irrigation, tourism, agriculture and
48 ecosystems (Figure Box 9.5.1) (Ma鷕e et al., 2018), although model projections of strong early summer
49 drying trends remain uncertain (Munday and Washington, 2019).
50
51 Changes in the amplitude, timing and frequency of extreme events such as droughts and floods will continue
52 to affect lake levels, rates of river discharge and runoff and groundwater recharge (high confidence)
53 (Gownaris et al., 2016; Darko et al., 2019), but with disparate effects at regional, basin and sub-basin scales,
54 and at seasonal, annual and longer timescales. The increased frequency of extreme rainfall events under
55 climate change (Myhre et al., 2019) is projected to amplify groundwater recharge in drylands (Jasechko and
56 Taylor, 2015; Cuthbert et al., 2019). However, declining trends in rainfall and snowfall in some areas of
57 North Africa (Donat et al., 2014b) are projected to continue in a warming world (Seif-Ennasr et al., 2016),
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1 restricting groundwater recharge from meltwater flows, exacerbating the salinisation and depletion of
2 groundwater (Hamed et al., 2018) and increasing the risk of reduced soil moisture (Petrova et al., 2018) in
3 this region where groundwater abstraction is greatest (Wada et al., 2014).
4
5
6
7 Figure 9.21: Climate change is projected to increase the intensity of lake heatwaves across Africa. Projected increases
8 in average intensity of lake heatwaves () under (a) 1.8 global warming (RCP2.6 in 2070�2099) and (b) 4.2
9 global warming (RCP8.5 in 2070�2099). Each lake is represented by a point. Data were extracted from (Woolway et
10 al., 2021).
11
12
13 Lake surface temperatures across Africa are expected to rise in tandem with increasing global warming. Lake
14 heatwaves, periods of extreme warm lake surface water temperature, are projected to become hotter and
15 longer (Figure 9.21), with heatwaves more than 300 days per year in many lakes for global warming of 4.2
16 (Woolway et al., 2021). Lake warming is expected to have adverse consequences for aquatic biodiversity,
17 habitats, water quality and disruption of current lake physical processes and circulation patterns (Kraemer et
18 al., 2021).
19
20 9.7.2.2 Vulnerability
21
22 Climate change is projected to reduce water availability and increase the extent of water scarcity (Mekonnen
23 and Hoekstra, 2016), particularly in southern and North Africa, while other regions will be more affected by
24 increased hydrological variability over temporally short to interannual timescales (see Section 9.6.2). African
25 countries are considered to be particularly at risk due to their underlying vulnerabilities (IPCC, 2014;
26 UNESCO and UN-Water, 2020), yet the continents' water resources are still inadequately quantified and
27 modelled (M黮ler Schmied et al., 2016; Reinecke et al., 2019), constraining sustainable management
28 practices (Cuthbert et al., 2019; Hughes, 2019).
29
30 Hydrological fluctuations are associated with drought, flood and cyclone events which have had multi-sector
31 impacts (Siderius et al., 2021) (see Sections 4.3 and 4.5 in Chapter 4), including: reduced crop production
32 (D'Odorico et al., 2018), migration and displacement (Siam and Eltahir, 2017; IDMC, 2018), food insecurity
33 and extensive livestock deaths (Nhamo et al., 2018), electricity outages (Gannon et al., 2018), increased
34 incidence of cholera (Olago et al., 2007; Sorensen et al., 2015; Hou閙閚ou et al., 2020) and increased
35 groundwater abstraction amplifying the risk from sea level rise of saline intrusion (Hamed et al., 2018;
36 Ouhamdouch et al., 2019).
37
38 The literature shows significant gender-differentiated vulnerability and intersectional vulnerability to climate
39 change impacts on water in Africa (Fleifel et al., 2019; Grasham et al., 2019; Mackinnon et al., 2019; Dickin
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1 et al., 2020; Lund Schlamovitz and Becker, 2020), although studies are generally lacking in northern Africa
2 (Daoud, 2021). Women and girls are in most cases more impacted than men/boys by customary water
3 practices as adult females are the primary water collectors (46% in Liberia to 90% in Cote d'Ivoire), while
4 more female than male children are associated with water collection (62% compared with 38%, respectively)
5 (Graham et al., 2016). Women and girls face barriers toward accessing basic sanitation and hygiene
6 resources, and 71% of studies reported a negative health outcome, reflecting a water-gender-health nexus
7 (Pouramin et al., 2020). These differential vulnerabilities are crucial for informing adaptation, but are still
8 relatively under-researched, more so for the urban poor than rural communities (Grasham et al., 2019;
9 Mackinnon et al., 2019; Lund Schlamovitz and Becker, 2020).
10
11 9.7.3 Water Adaptation Options and their Feasibility
12
13 9.7.3.1 Reducing Risk through a Systems Approach to Water Resources Planning and Management
14
15 An integrated systems and risk-based approach to the design and management of water resources at scale is
16 generally accepted as a practical and viable way of underpinning the resilience of water systems to climate
17 change and human pressures (Duffy, 2012; Garc韆 et al., 2014). Such approaches confer multiple benefits to
18 nature and society at scale and enhance efficiency gains through technology and management improvements,
19 but their full implementation has not yet been realised (Weinzierl and Schilling, 2013; McDonald et al.,
20 2014; UN Environment, 2019). Drylands are particularly singled out as ignored areas that require Integrated
21 Water Resource Management approaches (Stringer et al., 2021) (Section 9.3.1). Appropriate nature-based
22 solutions that are applicable at scale should be identified and strongly embedded in these approaches to
23 deliver multiple benefits while maintaining the integrity of ecosystems and biodiversity (UN Environment,
24 2019) (see Sections 9.6.4, 9.8.5, and Box 4.6). Furthermore, adaptation options are often influenced or
25 constrained by institutions, regulation, availability, distribution, price and technologies (McCarl et al., 2016).
26 Thus, institutional capacity to manage complex water supply systems under rapidly increasing demand and
27 climate change stress is critical in achieving water security for African cities, particularly as cities become
28 more dependent on alternative and distant water sources (Padowski et al., 2016).
29
30 9.7.3.2 Adopting Nexus Lenses
31
32 The water-energy-food (WEF) nexus explicitly recognises the strong interdependencies of these three sectors
33 and their high levels of exposure to climate change (Zografos et al., 2014; Dottori et al., 2018) (see Box 9.5).
34 With increasing societal demands on more variable water resources under climate change, an intensification
35 of WEF competition and trade-offs are projected (D'Odorico et al., 2018; Dottori et al., 2018). Other
36 interacting factors, for example, the increasing number of transnational investments in land resources can
37 lead to localised increased competition for water resources (Messerli et al., 2014; Breu et al., 2016; Chiarelli
38 et al., 2016). Understanding such nexus inter-linkages can help characterise risks to water resource security,
39 identify co-benefits and clarify the range of multi-sectoral actors involved in and affected by development
40 decisions (Kyriakarakos et al., 2020). Major barriers and entry points for greater integration include
41 coordination of horizontal policy and integration of climate change adaptation actions (England et al., 2018),
42 capturing the scarcity values of water and energy embedded in food/energy products (Allan et al., 2015), and
43 inclusion of community-based organisations such as water resource user associations (Villamayor-Tomas et
44 al., 2015) and agricultural cooperatives (Kyriakarakos et al., 2020).
45
46
47 [START BOX 9.5 HERE]
48
49 Box 9.5: Water-Energy-Food Nexus
50
51 The water-energy-food (WEF) nexus explicitly recognises the strong interdependencies of these three sectors
52 and their high levels of exposure to climate change. Risks can be transmitted from one WEF sector to the
53 other two with cascading risks to human health, cities and infrastructure (Conway et al., 2015; Mpandeli et
54 al., 2018; Nhamo et al., 2018; Yang and Wi, 2018; Ding et al., 2019; Simpson et al., 2021b). For example,
55 increasing demand for water for agricultural and energy production is driving an increasing competition over
56 water resources between food and energy industries which, among other effects, compromises the nutritional
57 needs of local populations (Zografos et al., 2014; Dottori et al., 2018). Drought events, such as in southern
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1 Africa during the 2015/16 El Ni駉, have been associated with major multi-sector impacts on food security
2 (over 40 million food-insecure people and extensive livestock deaths) and reduced energy security through
3 disruption to hydropower generation (associated in Zambia with the lowest rate of real economic growth in
4 over 15 years)(Nhamo et al., 2018). The WEF nexus of the Nile and Zambezi river basins, which include
5 many of Africa's largest existing hydropower dams, have received the most attention. In these two regions
6 where socioeconomic development is already driving up demand, projections indicate that water scarcity
7 may be exacerbated by drying (Munday and Washington, 2019) and increased flow variability (Siam and
8 Eltahir, 2017). However, for Africa more widely, very few studies fully integrate all three WEF nexus
9 sectors and rarely include an explicit focus on climate change.
10
11 In Africa, the climate risks that the water, energy and food sectors will face in the future are heavily
12 influenced by the infrastructure decisions that governments make in the near term. The African Union's
13 Programme for Infrastructure Development (PIDA), along with other national energy plans (jointly referred
14 to as PIDA+), aim to increase hydropower capacity nearly six-fold, irrigation capacity by over 60% and
15 hydropower storage capacity by over 80% in major African river basins (Cervigni et al., 2015). The vast
16 majority of hydropower additions would occur in the Congo, Nile, Zambezi and Niger river basins, and the
17 majority of the irrigation capacity additions would occur in the Niger, Nile and Zambezi River basins
18 (Huber-Lee et al., 2015) (Figure Box 9.5.1).
19
20 Climate change risk to the productivity of this rapidly expanding hydropower and irrigation infrastructure
21 compound the overall WEF nexus risk. Future levels of rainfall, evaporation and runoff will have a
22 substantial impact on hydropower and irrigation production. Climate models disagree on whether climates
23 will become wetter or dryer in each river basin. Cervigni et al. (2015) modelled revenues from the sale of
24 hydroelectricity and irrigated crops in major African river basins under different climate scenarios between
25 2015 and 2050 (Figure Box 9.5.1). The study found that hydropower revenues in the driest climate scenarios
26 could be 58% lower in the Zambezi River basin, 30% lower in the Orange basin and 7% lower in the Congo
27 basin relative to a scenario with current climate conditions. Hydropower revenues in the wettest climate
28 scenario could be more than 20% higher in the Zambezi River basin and 50% higher in the Orange basin.
29 The biggest risk to the production of irrigated crops is in the eastern Nile where irrigation revenue could be
30 34% lower in the driest scenario and 11% higher in the wettest than in a scenario without climate change
31 (Cervigni et al., 2015).
32
33
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1
2 Figure Box 9.5.1: Climate risks to hydropower and irrigation in Africa. The map shows the location and size of
3 existing (blue) and planned (red) hydropower plants in African governments' infrastructure expansion plans, 2015�
4 2050. The bar graphs show the forecast revenues for hydropower and irrigation infrastructure from 2015-2050 in each
5 river basin. Hydropower revenues refer to net present value of hydroelectricity produced in each river basin over the
6 period, and irrigation revenues refer to the crop revenues per hectare for each crop multiplied by the number of hectares
7 of each crop across the basin. Dark blue dots show forecasted revenues from 2015�2050 of existing irrigation and
8 hydropower in major African river basins in a scenario without further climate change (i.e., based on historical data).
9 Red dots show how hydropower and irrigation revenues are expected to increase as new hydropower and irrigation
10 infrastructure is added in a scenario without climate change. Blue and green bars illustrate the range of forecasted
11 revenue from 2015�2050 from new and existing hydropower and irrigation under 121 different climate futures. In river
12 basins with a wide range of potential outcomes, such as the eastern Nile and Zambezi River, there is significant
13 uncertainty around revenue forecasts based on historical trends. All figures are estimates of the net present value of
14 revenues, using a discount rate of 3%, and are in 2012 USD billions. The 121 potential climate futures were derived
15 using different General Circulation Models (GCMs), Representative Concentration Pathways (RCPs), and downscaling
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1 methods. IPCC AR4 and AR5 provided data from 22 and 23 GCMs, respectively. These were evaluated across two or
2 three emissions pathways, including RCP4.5 and RCP8.5. The Bias Corrected Spatial Disaggregation (BCSD) method
3 of downscaling was then used to derive 99 potential climate futures. An additional 22 climate futures (11 GCMs driven
4 by the RCP4.5 and RCP8.5 emissions pathways) were produced using the Empirical Statistical Downscaling Methods
5 developed at the Climate Systems Analysis Group at the University of Cape Town.. Data sourced from (Cervigni et al.,
6 2015).
7
8
9 Studies have used the river basin as a unit of analysis and adopted sophisticated techniques to assess and
10 present trade-offs between competing uses. For example, Yang and Wi (2018) consider the WEF nexus in
11 the Great Ruaha tributary of the Rufiji River in Tanzania motivated by an observed decrease in streamflow
12 during the dry season in the 1990s, but without an explicit focus on climate. Yang and Wi (2018) show
13 sensitivity of water availability for irrigated crop production to warming, and sensitivity of hydropower
14 generation and ecosystem health to changes in precipitation and dam development. Understanding of WEF
15 nexus interlinkages can help characterise risks and identify entry points and the relevant institutional levels
16 for cross-sectoral climate change adaptation actions (England et al., 2018). An integrated response can be
17 enhanced through the inclusion of community-based organisations, such as water resource user associations
18 and the wide range of other multi-sectoral actors involved in and affected by development decisions.
19 Capturing the scarcity values of water and energy embedded in food and other products can help identify the
20 co-benefits and costs of integrated adaptation (Allan et al., 2015).
21
22 [END BOX 9.5 HERE]
23
24
25 9.7.3.3 Climate-Proofing Water Infrastructure
26
27 While natural variability in the hydrological cycle has always been considered by water resources planners
28 and engineers (M黮ler Schmied et al., 2016; Muller, 2018), many countries will have to take into
29 consideration the range of historically unprecedented extremes expected in the future. Increasingly, the
30 provision of urban water security is dependent on the functioning of complex bulk water infrastructure
31 systems consisting of dams, inter-basin transfers, pipelines, pump stations, water treatment plants and
32 distribution networks (McDonald et al., 2014). Risk-based studies on the potential climate change risks for
33 water security show that there are benefits when risks are reduced at the tails of the distribution - floods and
34 droughts--even if there is little benefit in terms of changes in the mean (Arndt et al., 2019). When risk is
35 taken into account in an integrated (national) bulk water infrastructure supply system, the overall impact of
36 climate change on the average availability of water to meet current and future demands is significantly
37 reduced (Cullis et al., 2015). Further, stemming leakages and enhancing efficiency through technology and
38 management improvements is important in building climate-resilient water conveyance systems (UN
39 Environment, 2019). African cities could leap-frog through the development phases to achieve a water
40 sensitive city ideal, reaping benefits such as improved liveability, reduced flooding impacts, safe water and
41 overall lower net energy requirements and avoid making the mistakes developed countries' cities have made
42 (Fisher-Jeffes et al., 2017) (Brodnik et al., 2018). However, the challenge of large proportions of the
43 population lacking access to even basic water supply and sanitation infrastructure (Armitage et al., 2014)
44 must be simultaneously and effectively addressed, particularly in light of other major exacerbating factors
45 like the COVID-19 pandemic (Section 9.11.5).
46
47 9.7.3.4 Decision Support Tools for Managing Complex Water Systems
48
49 Many studies in Africa use the river basin as a unit of analysis at scale and adopt sophisticated model-based
50 techniques to assess climate change impacts on hydrology under different climate and development
51 scenarios, thereby presenting trade-offs between competing uses such as hydropower generation, irrigation
52 and ecosystem requirements (Yang and Wi, 2018; Ahmed, 2020) (Section 9.12.1). However, longer (multi-
53 decadal) hydrological datasets and model improvements are required (Taye et al., 2015), and models should
54 incorporate the quantification of the wider benefits, risks and political opportunities arising from reservoir
55 development to better inform decision-makers to achieve a higher level of (transboundary) cooperation
56 (Digna et al., 2016; Nijsten et al., 2018). Collaboration between scientists and policy-makers to address the
57 complexity of decision-making under uncertainty (Steynor et al., 2016) (Pienaar and Hughes, 2017), coupled
58 with community involvement in participatory scenario development and participatory GIS to aid in
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1 collaborative planning that is context-specific (Muhati et al., 2018; 羖varez Larrain and McCall, 2019) are
2 powerful tools for more beneficial adaptive and resilience building actions.
3
4 9.7.3.5 Other Adaptation Options
5
6 Climate change is projected to increase dependence upon groundwater withdrawals in most parts of Africa as
7 an adaptive strategy to amplified variability in precipitation and surface water resources, highlighting the
8 need for conjunctive surface-groundwater management and rainwater harvesting (Cobbing and Hiller, 2019;
9 Taylor et al., 2019). Alternative water supply options such as desalination, managed aquifer recharge,
10 stormwater harvesting and re-use (direct and indirect, potable and non-potable), all require significant
11 amounts of energy and are complex to operate and maintain. A failure to provide a source of reliable energy
12 and the capacity to implement, maintain, and operate these systems is a significant contributor to water
13 scarcity risks in Africa (Muller and Wright, 2016). Soft adaptation options include increasing water use
14 efficiency, chaning agricultural practices, more appropriate water pricing (Olmstead, 2014) and enhancing
15 capacity to tackle groundwater overexploitation (Kuper et al., 2016), among others (see Section 9.10.2.4;
16 Sections 4.6 and 4.7 in Chapter 4).
17
18 9.7.3.6 Mainstreaming Gender Across all Adaptation Options
19
20 Gender is important in building resilience and adaptation pathways to global environmental change (Ravera
21 et al., 2016). It is well-established that women, in most societies, have accumulated considerable knowledge
22 about water resources, including location, quality and storage methods because they are primarily
23 responsible for the management of water for household water supply, sanitation and health, and for
24 productive uses in subsistence agriculture (UN-Water, 2006). As gender-differentiated relationships are
25 complex, adaptation should take into account intersectional differences such as homeownership, employment
26 and age (Harris et al., 2016), educational, infrastructural and programmatic interventions (Pouramin et al.,
27 2020), aspects of protection and safety (Mackinnon et al., 2019), barriers to adaptation and gendered
28 differences in the choice of adaptation measures (Mersha and Van Laerhoven, 2016), the complex power
29 dynamics of existing social and political relations (Djoudi et al., 2016; Rao et al., 2017) and inclusion and
30 empowerment of women in the management of environmental resources (Makina and Moyo, 2016).
31 Incorporation of gender and water inequities into climate change adaptation would have a significant impact
32 on achieving the SDGs (particularly 1,3,4, 5 and 6), while failure to incorporate gender will undermine
33 adaptation efforts (Bunce and Ford, 2015; Fleifel et al., 2019; Pouramin et al., 2020).
34
35
36 9.8 Food Systems
37
38 Ideally, a systems approach (Ericksen, 2008; Rosenzweig et al., 2020) could be used to assess how global
39 environmental changes affect the food sector in Africa, emphasising the complex interactions that exist
40 within the components of the food supply system, including its enabling socioeconomic and biophysical
41 environment (Ingram, 2011; Foran et al., 2014; Tendall et al., 2015), and how food is connected to other
42 critical systems such as energy, water and transportation (Albrecht et al., 2018) (see Box 9.5). Production
43 will not be the only aspect of food security that is impacted by climate change. Processing, storage,
44 distribution and consumption will also be affected. Access to healthy and adequate food in the face of
45 climate change requires resilience across these components of the food system (Adenle et al., 2017).
46 However, most studies on climate change impacts on food in Africa are heavily focused on production only.
47 A significant knowledge gap, therefore, exists around the complex ways in which climate change will
48 interact with broader components of African food systems, and strategies for making these systems more
49 resilient, particularly in a context of rapid population growth and urbanisation across the continent (Adenle et
50 al., 2017; Schmitt Olabisi et al., 2018).
51
52 9.8.1 Vulnerability to Observed and Projected Impacts from Climate Change
53
54 Agricultural activities are mainly rainfed and subsistence across Africa. The dominant farming system is
55 mixed cereal-livestock (Thornton and Herrero, 2015; Nematchoua et al., 2019), with pastoral systems in East
56 Africa, and commercial livestock and crop systems also representing a significant proportion of the food
57 system in southern Africa (Thornton and Herrero, 2015). Many African regions are vulnerable to food
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1 insecurity, facing dwindling food production, food access, stocks and income due to low adaptive capacity
2 (Evariste et al., 2018; Fuller et al., 2018; Bang et al., 2019; Gebre and Rahut, 2021).
3
4 Across regions with food systems highly vulnerable to climate change, female farmers, cocoa farmers,
5 pastoralists, plantain farmers, coastal zone communities, rural households and forest communities in central
6 Africa indicate higher vulnerability (Chia et al., 2016; Schut et al., 2016; Nematchoua et al., 2019). Their
7 vulnerability is multidimensional and affected by low adaptive capacity, location, livelihood system,
8 socioeconomic status, gender, age and ethnicity (Perez et al., 2015; Weston et al., 2015; Gebre and Rahut,
9 2021) (see also Box 9.1).
10
11 Across Africa, including West Africa, adverse climate conditions for agricultural and pastoral livelihoods
12 have contributed to rural-to-urban migration patterns and migration among African regions (see Box 9.8)
13 (Baudoin et al., 2014; Abbas, 2017; Gemenne and Blocher, 2017b). Rural to urban migration may increase
14 vulnerability of migrants through exposure to additional risks, including food insecurity (Amadi and Ogonor,
15 2015; Abbas, 2017). In general, West African countries are characterised by the poor adaptive capacity of
16 rural households (Douxchamps et al., 2015; Dumenu and Obeng, 2016).
17
18 In North Africa, livelihoods and economies are strongly dependent on agriculture. Pressure on water demand
19 due to climate change and variability is threatening income, development processes and food security in the
20 region (high confidence) (Mohmmed et al., 2018; Khedr, 2019). Increased temperatures and droughts have
21 enhanced the vulnerability of the irrigation sector (Verner et al., 2018; lseven et al., 2019), and the
22 combined effect of these hazards negatively affects crop and animal production (Mohmmed et al., 2018;
23 Verner et al., 2018). For example, dairy farms in Tunisia are experiencing warmer temperatures above the
24 thermoneutral zone of cows for more than 5 months each year, reducing production efficiency and resulting
25 in significant economic losses (Amamou et al., 2018).
26
27 Non-climatic stressors aggravate food insecurity in many parts of the continent, including lack of access to
28 production inputs and land, lack of education and limited income sources, with adverse climate impacts on
29 agriculture reducing education attainment for children (Evariste et al., 2018; Fuller et al., 2018) (Section
30 9.11.1.2). Geographic and social isolation is another type of social vulnerability, especially for pastoralist
31 communities in East and southern Africa (Sonwa et al., 2017; Basupi et al., 2019). Rural communities often
32 have poor transport networks, limited access to markets or information and fewer livelihood alternatives, and
33 are less able to be informed of risks or be assisted in the event of extreme climate events (Sonwa et al., 2017;
34 Basupi et al., 2019).
35
36 Extreme climate events have been key drivers in rising acute food insecurity and malnutrition of millions of
37 people requiring humanitarian assistance in Africa (high confidence). Between 2015 and 2019, an estimated
38 45.1 million people in the Horn of Africa and 62 million people in eastern and southern Africa required
39 humanitarian assistance due to climate-related food emergencies. Children and pregnant women experience
40 disproportionately greater adverse health and nutrition impacts (very high confidence) (Gebremeskel Haile et
41 al., 2019) (see Chapter 7, Section 7.2.4).
42
43 Future climate warming will likely have a substantial impact on food security in Africa and is anticipated to
44 coincide with low adaptive capacity as climate change intensifies anthropogenic stressors, as 85% of Africa's
45 poor live in rural areas and mostly depend on agriculture for their livelihoods (Adams, 2018; Mahmood et
46 al., 2019). This highlights the need to prioritise innovative measures for reducing vulnerabilities in Africa
47 food systems (Fuller et al., 2018; Mahmood et al., 2019).
48
49 Climate change impacts could increase the global number of people at risk of hunger in 2050 by 8 million
50 people under a scenario of sustainable development (SSP1) and 80 million people under a scenario of
51 reduced international cooperation and low environmental protection (SSP3), with populations concentrated
52 in sub-Saharan Africa, South Asia and Central America (see Chapter 5, Sections 5.2.2, 5.4.2 and 5.4.3).
53 Global climate impacts on food availability are expected to lead to higher food prices, increasing the risk of
54 hunger for people in African countries, and slow progress towards eradicating child undernutrition and
55 malnutrition in all its forms (see Chapter 7, Section 7.4).
56
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1 9.8.2 Observed Impacts and Projected Risks to Crops and Livestock
2
3 9.8.2.1 Observed Impacts and Projected Risks for Staple Crops
4
5 Climate change is already negatively impacting crop production and slowing productivity growth in Africa
6 (high confidence) (Iizumi et al., 2018; Ray et al., 2019; Sultan et al., 2019; Ortiz-Bobea et al., 2021). Climate
7 change has reduced total agricultural productivity growth in Africa by 34% since 1961, more than in any
8 other region (Ortiz-Bobea et al., 2021), more than in any other region. Maize yields have decreased 5.8% and
9 wheat yields 2.3%, on average, in sub-Saharan Africa due to climate change in the period 1974�2008 (Ray
10 et al., 2019). Overall, climate change has decreased food total calories across all crops in sub-Saharan Africa
11 by 1.4% on average compared to a no climate change counterfactual since 1970, with up to 10% reductions
12 in Ghana and Zimbabwe (Ray et al., 2019).
13
14 Farmers perceive a wide variety of climate threats to crop production including droughts, precipitation
15 variability, a delayed onset and overall reductions in early growing season rainfall and excess heat
16 (Rankoana, 2016a; Elum et al., 2017; Kichamu et al., 2017; Alvar-Beltr醤 et al., 2020). Farmers attribute
17 these perceived changes as a major driver of yield losses (Ayanlade and Jegede, 2016) (see Section 9.4.5).
18 Over half of surveyed farmers in West Africa perceive increases in crop pests and diseases as due to climate
19 change as the range and seasonality of many pests and diseases change under warming (Callo-Concha,
20 2018),. Pests and diseases contribute between 10�35% yield losses for wheat, rice, maize, potato and
21 soybean in sub-Saharan Africa (Savary et al., 2019). Recent locust outbreaks in 2019 in East Africa have
22 been linked to climate conditions caused in part by ocean warming (Wang et al., 2020b) (see Box 5.8 in
23 Chapter 5).
24
25 Future climate change may increase insect pest-driven losses in Africa for maize, rice and wheat: Compared
26 to 1950�2000, losses may increase by up to 50% at 2癈 of global warming (Deutsch et al., 2018). However,
27 many challenges remain in modelling pest and disease under climate change with additional research needed
28 expanding the range of crops and diseases studied (Newbery et al., 2016).
29
30 Agriculture in Africa is especially vulnerable to future climate change in part because 90�95% of African
31 food production is rainfed (Adams, 2018). Maize, rice, wheat and soybean yields in tropical regions (20S-
32 20N) are projected to decrease approximately 5% per 癈 of global warming in a multi-model ensemble
33 (Rosenzweig et al., 2014; Franke et al., 2020). Dryland agricultural areas are especially sensitive to changes
34 in rainfall. For example, without adaptation, substantial yield declines are projected for staple crops in North
35 Africa (Figure 9.3). A recent meta-analysis of 56 studies indicates that, compared to 1995�2005, economic
36 welfare in the agriculture sector in North Africa is projected to decline 5% for 2 global warming and 20%
37 for 3 global warming, and in sub-Saharan Africa by 5% (2) and 10% (3) (Moore et al., 2017a), both
38 more pessimistic than previous economic estimates.
39
40 A synthesis of projected staple crop impacts across 35 studies for nearly 1040 locations and cases shows on
41 average decreases in crop yields with increasing global warming across staple crops in Africa, including
42 when accounting for CO2 increases and adaptation measures. For example for maize in West Africa,
43 compared to 2005 yield levels, median projected yields decrease 9% at 1.5 global warming and 41% at
44 4, without adaptation (Figure 9.22). However, uncertainties in projected impacts across crops and regions
45 are driven by uncertainties in crop responses to increasing CO2 and adaptation response, especially for maize
46 in East Africa and wheat in North Africa and East Africa (Figure 9.22) (Hasegawa et al., 2021).
47
48 There is also growing evidence that climate change is likely beginning to outpace adaptation in agricultural
49 systems in parts of Africa (Rippke et al., 2016). For example, despite the use of adjusted sowing dates and
50 existing heat-tolerant varieties, Sudan's domestic production share of wheat may decrease from 16.0% to
51 4.5�12.2% by 2050 under RCP8.5 (2.4 global warming) (Iizumi et al., 2021).
52
53
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MAIZE RICE WHEAT
NORTH AFRICA
Yield impact (%)
WEST AFRICA
Yield impact (%)
EAST AFRICA
Yield impact (%)
SOUTHERN AFRICA Without adaptation
With adaptation
Yield impact (%)
1 >1.5oC >2oC >3oC >4oC >1.5oC >2oC >3oC >4oC >1.5oC >2oC >3oC >4oC
2 Figure 9.22: Projected yield changes for major crops in Africa due to climate change (compared to 2005 yield levels).
3 Impacts are binned into global warming levels above pre-industrial global mean temperature (1850�1900). Boxplots
4 show a synthesis of projected staple crop impacts, with and without adaptation measures (e.g. planting date, cultivar,
5 tillage or irrigation). On average crop yields are projected to decrease with increasing global warming across staple
6 crops in Africa. The overall adaptation potential to offset yield losses across Africa for rice, maize and wheat reduces
7 with increasing global warming. On average, in projections including adaptation options and yield losses, in the median
8 case, are reduced from �33% to �10% of 2005 levels at 2 of global warming and from �46% to �23% at 4. Data
9 are a synthesis across 35 studies for nearly 1040 locations and cases of projected impacts for regions of Africa for
10 maize, rice and wheat (Hasegawa et al., 2021) (Supplementary Material Table SM 9.5).
11
12
13 Elevated CO2 concentrations in the atmosphere might mitigate some or all climate-driven losses (Swann et
14 al., 2016; Durand et al., 2018), but there is considerable uncertainty around the CO2 response (Deryng et al.,
15 2016; Toreti et al., 2020), especially when nutrients such as nitrogen and phosphorus are limiting crop
16 growth. Additional Free-Air Carbon dioxide Enrichment (FACE) experiments are needed in the tropics,
17 particularly on the African continent, to better understand the impacts of increased CO2 concentrations on the
18 productivity of crops and cultivars grown in Africa under additional temperature impacts and water and
19 nutrient limitations (Ainsworth and Long, 2021). Warming and elevated CO2 may also change the nutritional
20 content of some crops. By 2050 under RCP8.5 (2.4 global warming), overall wheat yields and grain
21 protein content may decrease by 10% and 15%, respectively, in North and East Africa, and by over 15% in
22 southern Africa (Asseng et al., 2019). See Chapter 5 for more details on CO2 impacts and uncertainties.
23
24 9.8.2.2 Observed Impacts and Projected Risks on Regional Cash Crops and Food Crops
25
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1 Few studies have attributed changes in yields of cash crops and other regionally important food crops in
2 Africa to anthropogenic climate change, but recent research suggests yields of cash crops in Africa have
3 already been impacted by climate change, in both a negative and positive manner (Falco et al., 2012; Traore
4 et al., 2013; Ray et al., 2019). For example, between the period 1974�2008, sugarcane yields decreased on
5 average by 3.9% and 5.1% in sub-Saharan Africa and North Africa, respectively, due to climate change,
6 while sorghum yields increased 0.7%, and cassava yield increased 1.7% in sub-Saharan Africa and 18% in
7 North Africa (Ray et al., 2019).
8
9 There are also limited studies for assessing projected climate change impacts on important cash crops and
10 food crops other than maize, rice and wheat (Jarvis et al., 2012; Schroth et al., 2016; Awoye et al., 2017).
11 These studies often represent changes at specific sites in a country or assess changes in the yield and/or
12 suitability for cultivating a specific crop across a larger geographic area. Climate change is projected to have
13 overall positive impacts on sugarcane and Bambara nuts in southern Africa, oil palm in Nigeria and chickpea
14 in Ethiopia (low confidence) (Figure 9.23).
15
16 Climate change is projected to reduce sorghum yields in West Africa (Figure 9.23). For example, across the
17 West African Sahel savanna sorghum yields are projected to decline on average 2% at 1.5 and 5% at 2
18 global warming (Faye et al., 2018). For coffee and tea in eastern Africa, olives in Algeria and sunflower in
19 Botswana and Morocco, we find studies indicating mostly negative impacts on production systems. For
20 example, in Kenya, compared to 2000, optimal habitat for tea production is projected to decrease in area by
21 27% with yields declining 10% for global warming of 1.8�1.9, although yield declines may be reduced at
22 higher levels of warming (Beringer et al., 2020; Jayasinghe and Kumar, 2020; Rigden et al., 2020). Suitable
23 area for tea production may reduce by half in Uganda (Eitzinger et al., 2011; L鋎erach et al., 2013). In East
24 Africa, the coffee-growing area is projected to shift up in elevation with suitability decreasing 10�30%
25 between 1.5�2 of global warming (Bunn et al., 2015; Ovalle-Rivera et al., 2015).
26
27 For all other crops, there is at least one study that finds low to highly negative impacts for one or several
28 warming levels (Figure 9.23). Mixed results on the direction of change often occur when several contrasting
29 sites with varying baseline climates are studied, and when a study considers the full range of climate
30 scenarios. For example, there are mixed results on the direction of change for impacts of 1.5 global
31 warming on cassava, cotton, cocoa and millet in West Africa (low confidence) (Figure 9.23). In general,
32 there is limited evidence in the direction of change, due to single studies being available for most crop-
33 country combinations (Knox et al., 2010; Chemura et al., 2013; Asaminew et al., 2017; Bouregaa, 2019).
34 Occasionally, two studies agree on the direction and magnitude of change, for example, for potatoes in East
35 Africa, yields are projected to decrease by 11�17% with 3 of warming (Fleisher et al., 2010; Tatsumi et
36 al., 2011).
37
38
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1
2
3 Figure 9.23: Projected risks at increasing global warming levels for regionally important cash and food crops in Africa.
4 Insufficient data (ID) indicates there were limited to no published studies that have quantified projected climate change
5 impacts or adaptation options for specific crops under different warming levels (see Supplementary Material Table SM
6 9.6).
7
8
9 9.8.2.3 Observed Impacts and Projected Risks for Wild-Harvested Food
10
11 Wild-harvested foods (e.g., fruits, vegetables and insects) provide dietary diversification and for many
12 people in Africa, wild-harvested food plants may provide a livelihood and/or nutritional safety net when
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1 other sources of food fail, such as during drought (Sunderland et al., 2013; Shumsky et al., 2014; Wunder et
2 al., 2014; Baudron et al., 2019b). In Zimbabwe, during lean times, consumption of wild fruits increases, as
3 does their sale to generate income for additional food expenses in poor, rural households (Mith鰂er and
4 Waibel, 2004). In Zambia, Mali and Tanzania, household surveys indicate that forest products including wild
5 foods can play an important role in reducing household vulnerability to climate shocks by providing
6 alternative sources of food and income during droughts and floods (Robledo et al., 2012). In the Parklands of
7 West Africa, wild trees are a significant source of wild foods and are thus a place where one might expect
8 wild plant foods to make an important contribution to diets and nutrition (Boedecker et al., 2014; Le適eister
9 et al., 2015). Non-timber forest products are consumed by an estimated 43% of all households in Burkina
10 Faso (FAO, 2019), and wild vegetables accounted for about 50% of total vegetable consumption in
11 southeastern Burkina Faso (Mertz et al., 2001).
12
13 The focus of projected climate change impacts has been almost exclusively on agricultural production, yet
14 climate change could have substantial impacts on the distribution and availability of wild-harvested food
15 plants in Africa (Wessels et al., 2021). Non-cultivated species in Africa are vulnerable to current and future
16 climate changes, with widespread changes in woody plant cover already observed (see Section 9.6.1.1).
17 Evidence about the impacts of climate change on individual wild food species is less consistent.
18 Communities in the Kalahari (Crate and Nuttall, 2016) and Zimbabwe (Sango and Godwell, 2015) report
19 growing scarcity of wild foods (such as wild meat and fruit) perceived to be, at least in part, due to drought
20 and climate change. Shea tree (Vitellaria paradoxa) nuts provide fats and oils for the diets of many rural
21 populations in West Africa. In Burkina Faso, global warming of 3 is projected to reduce area of suitable
22 habitat for the Shea tree by 14% (Dimobe et al., 2020). In southern Africa, 40% of native, wild-harvested
23 food plant species are projected to decrease in geographic range extent at 1.7 global warming with range
24 reductions for 66% of species projected for 3.5 (Wessels et al., 2021).
25
26 9.8.2.4 Observed Impacts and Projected Risks on Livestock
27
28 Livestock systems in Africa are already being affected by changes in climate through increased precipitation
29 variability decreasing fodder availability (Sloat et al., 2018; Stanimirova et al., 2019). More than twice as
30 many countries in Africa have experienced increases in precipitation variability in the last century than
31 decreases (Sloat et al., 2018). Fodder availability is also being impacted by Woody Plant Encroachment--the
32 increase in shrub and tree cover--which has increased by 10% on subsistence grazing lands and 20% on
33 economically important grazing lands in South Africa in the last 60 years (Stevens et al., 2016), and is driven
34 in part by climatic factors (see Section 9.6.1.1). Increased temperature and precipitation have contributed to
35 the expanding range, especially in East and southern Africa, of several ixodid tick species which carry
36 economically important livestock diseases (Nyangiwe et al., 2018).
37
38 Pastoralists in Africa perceive the climate as already changing and report more erratic and reduced rainfall,
39 prolonged and more frequent droughts and a rise in temperature (Sanogo et al., 2017; Kimaro et al., 2018).
40 They also report reduced milk production, increased deaths and disease outbreaks in their herds due to
41 malnutrition and starvation resulting from the shortages in forage and water (Kimaro et al., 2018). Additional
42 research is required to attribute precipitation variability to anthropogenic forcing (see Section 9.3), and to
43 evaluate the relative contributions of climate change and management to disease vector extent.
44
45 Future climate change will have compounding impacts on livestock, including negative impacts on fodder
46 availability and quality, availability of drinking water, direct heat stress and the prevalence of livestock
47 diseases (Nardone et al., 2010; Rojas-Downing et al., 2017; Godde et al., 2021). Climate change is projected
48 to negatively affect fodder availability (Briske, 2017) because overall rangeland net primary productivity
49 (NPP) by 2050 is projected to decrease 42% under RCP4.5 (2 global warming) and 46% under RCP8.5
50 (2.4 global warming) for western sub-Saharan Africa, compared to a 2000 baseline (Boone et al., 2018).
51 NPP is also projected to decline by 37% in southern Africa, 32% in North Africa and 5% in both East Africa
52 and Central Africa by 2050 under RCP8.5 (2.4 global warming) (Boone et al., 2018). For example, in
53 Zimbabwe by 2040�2070, net revenues from livestock production, compared to a 2011 survey, are projected
54 to decline by 8�32% under RCP4.5 for 2 and 11�43% under RCP8.5 for 2.7 global warming due to a
55 decline in fodder availability (Descheemaeker et al., 2018). The available literature does not
56 comprehensively capture the economic implications of climate-related impacts on livestock production
57 across Africa.
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1
2 Fodder quality, critical for animal health and weight gain, is at risk from climate change as increases in
3 temperature, elevated CO2 and water stress have been shown to reduce dry matter digestibility and nitrogen
4 content for C3 grasses (Augustine et al., 2018), tropical C4 grasses (Habermann et al., 2019) and fodder crops
5 such as Lucerne/Alfalfa (Polley et al., 2013; Thivierge et al., 2016).
6
7 Climate change is projected to threaten water availability for livestock. Droughts in Africa have become
8 more intense, frequent and widespread in the last 50 years (Masih et al., 2014), and progressive increase in
9 droughts between three- and twenty-fold under climate change up to 3 of warming are projected for most
10 of Africa (9.5). In the Klela basin in Mali by 2050, groundwater recharge is projected to decline by 49% and
11 groundwater storage by 24% under RCP8.5 (2.4 global warming) compared to the 2006 baseline (Toure et
12 al., 2017). Water availability for livestock during drought is a major concern for many African pastoralists
13 including but not limited to those in Zimbabwe (Dzavo et al., 2019) and Nigeria (Ayanlade and Ojebisi,
14 2019). Increased livestock mortality and livestock price shocks have been associated with droughts in Africa,
15 as well as being a potential pathway for climate-related conflict (Catley et al., 2014; Maystadt and Ecker,
16 2014) (see Box 9.9).
17
18 Heat stress may already be the largest factor impacting livestock production in many regions in Africa (El-
19 Tarabany et al., 2017; Pragna et al., 2018), as the combination of high temperatures and high relative
20 humidity can be dangerous for livestock and has already decreased dairy production in Tunisia (Amamou et
21 al., 2018). Climate change is projected to increase heat stress for all types of livestock, especially in the
22 tropics (Lallo et al., 2018) (Figure 9.24). More studies quantifying the impact of heat stress on other types of
23 livestock production loss are needed in Africa (Rahimi et al., 2021).
24
25
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a Historical Risk (1985-2014) b Historical Exposure (1985-2014)
0 60 120 180 240 300
Annual number of days over threshold
c Global warming 1.5 oC d Global warming 3.75 oC
0 60 120 180 240 300
1 Increase in annual days over threshold
2 Figure 9.24: Severe heat stress duration for cattle in Africa is projected to increase with increased global
3 warming. (a) Number of days per year with severe heat stress in the historical climate (1985-2014). (b) Historical cattle
4 exposure to severe heat. (Cattle density fromGilbert et al., 2018) . (c and d) Increase in the number of days per year with
5 severe heat stress for global warming of 1.5C and 3.75C above pre-industrial levels (1850-2100). Severe heat stress for
6 cattle is projected to become much more extensive in the future in Africa at increased global warming levels. Strong
7 mitigation would substantially limit the spatial extent and the duration of cattle heat stress across Africa. Heat stress is
8 estimated using THI (Temperature Humidity Index) with a value greater than 79 considered the onset of severe heat
9 stress (Livestock Weather Safety Index) (Lallo et al., 2018). Global warming of 1.5 used scenario SSP1�2.6 and
10 global warming of 3.75 used SSP5�8.5, both for 2070�2099 (12 climate models fromO'Neill et al., 2016; Tebaldi et
11 al., 2021) .
12
13
14 Climate change will impact livestock disease prevalence primarily through changes in vector dynamics or
15 range (Abdela and Jilo, 2016; Semenza and Suk, 2018). African Rift Valley Fever (RVF) and
16 Trypanosomiasis are positively associated with extreme climate events (droughts and ENSO) (Bett et al.,
17 2017) and are projected to expand in range under climate change (Kimaro et al., 2017; Mweya et al., 2017).
18 More quantitative estimates of projected risk from diseases are needed.
19
20 9.8.3 Adapting to Climate Variability and Change
21
22 Agricultural and livelihood diversification are strategies used by African households to cope with climate
23 change, enabling them to spread risks and adjust to shifting climate conditions (Thierfelder et al., 2017;
24 Thornton et al., 2018). This includes adjusting cropping choices, planting times, or size, type and location of
25 planted areas (Altieri et al., 2015; Nyagumbo et al., 2017; Dayamba et al., 2018). In southern Africa, changes
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1 in planting dates provide farmers with greater yield stability in uncertain climate conditions (Nyagumbo et
2 al., 2017). In Ghana, farmers are changing planting schedules and using early maturing varieties to cope with
3 late-onset and early cessation of the rainy season (Antwi-Agyei et al., 2014; Bawakyillenuo et al., 2016).
4
5 The use of drought-tolerant crop varieties is another adaptation available to African farmers (Hove and
6 Gweme, 2018; Choko et al., 2019). Adoption, however, is hindered by lack of information and training,
7 availability or affordability of seed, inadequate labelling and packaging size for seed supplies and financial
8 constraints (Fisher et al., 2015). Moreover, drought-tolerant varieties do not address changing temperature
9 regimes (Guan et al., 2017).
10
11 Crop diversification enhances crop productivity and resilience and reduces vulnerability in smallholder
12 farming systems (McCord et al., 2015; Mulwa and Visser, 2020). In Tanzania, diversified crop portfolios are
13 associated with greater food security and dietary quality (Br黶sow et al., 2017). In Kenya, levels of crop
14 diversity are higher in villages affected by frequent droughts, which are the main cause of crop failure
15 (Bozzola and Smale, 2020). They also help control pest outbreaks, which may become more frequent and
16 severe under increased climate variability and extreme events (Schroth and Ruf, 2014). High farming
17 diversity enables households to better meet food needs, but only up to a certain level of diversity (Waha et
18 al., 2018), and the viability of and benefits from mixed-farming are highly context-dependent (Thornton and
19 Herrero, 2015; Weindl et al., 2015).
20
21 Agroecological and conservation agriculture practices, such as intercropping, integration of legumes,
22 mulching and incorporation of crop residues, are associated with household food security and improved
23 health status (Nyantakyi-Frimpong et al., 2017; Shikuku et al., 2017). These practices can enhance the
24 benefits of other adaptations, such as planting drought- and heat-tolerant or improved varieties, although
25 effects vary across soil types, geographical zones and social groups (Makate et al., 2019; Mutenje et al.,
26 2019). Non-climatic variables, such as financial resources, access to information and technology, level of
27 education, land security and gender dynamics affect feasibility and adoption (Makate et al., 2019; Mutenje et
28 al., 2019).
29
30 To mitigate growing water stress, countries like Tanzania, Uganda, Rwanda and Ethiopia are striving to
31 improve irrigation efficiency (McCarl et al., 2015; Connolly-Boutin and Smit, 2016; Herrero et al., 2016).
32 The feasibility and effectiveness of this adaptation depend on biophysical and socioeconomic conditions
33 (Amamou et al., 2018; Harmanny and Malek, 2019; Schilling et al., 2020). Irrigation is unaffordable for
34 many smallholder farmers and only covers a negligible proportion of the total cultivated area. Nonetheless,
35 in some regions of West Africa, small-scale irrigation, including the digging of ditches, holes and
36 depressions to collect rainwater (Makondo and Thomas, 2018), is widely adopted and promoted to support
37 national food security (Dowd-Uribe et al., 2018).
38
39 African farmers are also diversifying their income sources to offset reduced yields or crop losses by shifting
40 labour resources to off-farm work, or by migrating seasonally or longer-term (Kangalawe et al., 2017; Hove
41 and Gweme, 2018). Off-farm activities provide financial resources that rural households need to cope with
42 extreme climate variability (Hamed et al., 2018; Rouabhi et al., 2019). However, in some cases, these off-
43 farm activities can be maladaptive at larger scales, such as when households turn to charcoal production
44 which contributes to deforestation (Egeru, 2016). Whether off-farm activities constitute maladaptation
45 depends on whether resources are available to upgrade skills or support investments that make a new
46 business more lucrative. Without such resources, this option may lead to impoverishment (see Box 5.8 on
47 AFOLU in Chapter 5).
48
49 Smallholder farmers' responses tend to address short-term shocks or stresses by deploying coping responses
50 (e.g., selling labour, reducing consumption and temporary migration), rather than longer-term sustainable
51 adaptations (Ziervogel and Parnell, 2014; Jiri et al., 2017). This is partly due to institutional barriers (e.g.,
52 markets, credit, infrastructure and information) and resource requirements that are unaffordable to
53 smallholder farmers (Pauline et al., 2017). There is a need for policies that strengthen natural, financial,
54 human and social capitals, the latter being key to household and community resilience, especially where
55 government services may be limited (Mutabazi et al., 2015; Alemayehu and Bewket, 2017). There is
56 evidence that collective action, local organizations and climate information are associated with higher food
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1 security, and that institutional interventions are needed to ensure scaling up of adaptations (Thornton et al.,
2 2018).
3
4 A range of options is considered potentially effective in reducing future climate change risk, including plant
5 breeding, crop diversification alongside livestock, mixed planting, intercrops, crop rotation and integrated
6 crop-livestock systems (Thornton and Herrero, 2014; Cunningham et al., 2015; Himanen et al., 2016; Farrell
7 et al., 2018; Snowdon et al., 2021) (Chapter 5, Sections 5.4.4 and 5.14.1). However, adaptation limits for
8 crops in Africa are increasingly reached for global warming above 2 (high confidence), and in tropical
9 Africa may already be reached at current levels of global warming (low confidence).
10
11 Global warming beyond 2 will place nearly all of sub-Saharan Africa cropland substantially outside of its
12 historical Safe Climate Zone (Kummu et al., 2021) and may exponentially increase the cost of adaptation and
13 residual damage for major crops (Iizumi et al., 2020). Without accounting for CO2 increases, global-scale
14 studies employing ensembles of gridded crop models for 2 of global warming find that for adaptation
15 using genetic cultivar change in most of Africa net losses are projected, even with adaptation up to 2 of
16 global warming for rice, maize, soybean, and wheat (Minoli et al., 2019; Zabel et al., 2021), although model
17 uncertainty is still high (M黮ler et al., 2021). In contrast, when accounting for CO2 increases, applying new
18 genetics for rice under warming is projected to fully counteract all climate change-induced losses in Africa
19 up to 3.5 of global warming, except in West Africa (van Oort and Zwart, 2018).
20
21 However, compared to temperate regions, risks of adaptation shortfalls � that is climate change impacts even
22 after adaptation � are generally greater for current agricultural conditions across much of Africa (tropical,
23 arid and semi-arid) (Sun et al., 2019). The overall adaptation potential to offset yield losses across Africa for
24 rice, maize, and wheat wheat reduces with increasing global warming. On average, in projections including
25 adaptation options, yield losses, in the median case, are reduced from �33% to �10% of 2005 levels at 2 of
26 global warming and from �46% to �23% at 4, but estimates vary widely (Hasegawa et al., 2021) (Figure
27 9.22). Across Africa, the risks of no available genetic varieties of maize for growing season adaptation are
28 higher for East Africa and southern Africa than for Central or West Africa (Zabel et al., 2021). To keep pace
29 with expected rates of climate change, crop breeding, development and adoption must accelerate to meet the
30 challenge (Challinor et al., 2016). Regional modelling has shown very little efficacy for late sowing,
31 intensification of seeding density and fertilizers, water harvesting and other measures for cereals in West
32 Africa at 2 of global warming (Sultan and Gaetani, 2016; Guan et al., 2017). Historical climate change
33 adaptation by crop migration has been shown in some cases (Sloat et al., 2020) but poses risks to biodiversity
34 and water resources and this option may be limited for maize in Africa by suitable climate shifting
35 completely across national borders and available land at the edges of the continent (Franke et al., 2021).
36 More research is required to evaluate the potential effectiveness and limits of adaptation options in African
37 agriculture under future climate change (see Chapter 5, Section 5.4.4 for more details)
38
39 9.8.4 Climate Information Services and Insurance for Agriculture Adaptation
40
41 In addition to adaptation in crop, soil and water management, the combination of (i) Climate Information
42 Services (CIS), (ii) institutional capacity building and (iii) strategic financial investment can help African
43 food producers adapt to projected climate risks (Carter et al., 2015; Surminski et al., 2016; Scott et al., 2017;
44 Cinner et al., 2018; Diouf et al., 2019; Hansen et al., 2019a). There is growing evidence of farmers' use of
45 weather and climate information, especially at the short- and medium-time horizon (Carr et al., 2016; Singh
46 et al., 2018). Digital services can contribute to the sustainable intensification of food production globally
47 (Duncombe, 2018; Klerkx et al., 2019). This points to the need for the scientific and development
48 communities to better understand the conditions that enable widespread adoption in Africa.
49
50 Although climate services have the potential to strengthen farmers' resilience, barriers to accessibility,
51 affordability and utilisation remain (Krell et al., 2021). Often the information offered is not consistent with
52 what farmers need to know and how they access and process information (Meadow et al., 2015; Singh et al.,
53 2018). Production of salient and credible climate information is hindered by the limited availability of and
54 access to weather and climate data (Coulibaly et al., 2017; Hansen et al., 2019a). The existing weather
55 infrastructure remains suboptimal to enable the development of reliable early warning systems (Africa
56 Adaptation Initiative, 2018; Krell et al., 2021). Of the 1,017 land-based observational networks in the world,
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1 only 10% are in Africa, and 54% of Africa's surface weather stations cannot capture data accurately (Africa
2 Adaptation Initiative, 2018; World Bank, 2020d).
3
4 Advances in remote sensing and climate analysis tools have allowed the development of weather index
5 insurance products as a potential adaptation option, with Malawi and Ethiopia being early testbeds (Tadesse
6 et al., 2015). These pilot projects were initially sponsored by NGOs, but in the last decade, the private sector
7 has become more active in this sector. The Ghana Agricultural Insurance Pool (GAIP) and Agriculture and
8 Climate Risk Enterprise (ACRE) in Kenya, Tanzania and Rwanda are examples. Despite the potential for
9 weather index insurance, uptake by smallholder farmers in Africa remains constrained by several factors.
10 These include the failure to capture actual crop loss as in traditional crop insurance products, as well as the
11 inability of poor farmers to pay premiums (Elum et al., 2017; Weber, 2019). Weather index insurance could
12 be part of a wider portfolio of risk mitigation services offered to farmers (Tadesse et al., 2015; Weber, 2019).
13 Strategic partnerships between key players (e.g., credit institutions, policymakers, meteorologists, farmer
14 associations, extension services, NGOs) are needed to develop better products and build capacity among
15 smallholder farmers to engage more beneficially with weather index insurance (Singh et al., 2018; Tesfaye et
16 al., 2019).
17
18 9.8.5 Marine and Inland Fisheries
19
20 9.8.5.1 Observed Impacts of Climate Variability and Change on Marine and Inland Fisheries
21
22 Marine and freshwater fisheries provide 19.3% of animal protein intake (Chan et al., 2019) and support the
23 livelihoods of 12.3 million people (de Graaf and Garibaldi, 2015) across Africa. Estimates suggest that fish
24 provides ~30% of the continent's population (approximately 200 million people) with their main source of
25 animal protein and key micronutrients (Obiero et al., 2019). Although marine fisheries account for >50 % of
26 total capture fishery production (Obiero et al., 2019), 2.9 million tonnes of fish are harvested annually from
27 inland water bodies constituting the highest per-capita inland fishery production of any continent (2.56 kg /
28 year / person) (Harrod et al., 2018a; Funge-Smith and Bennett, 2019).
29
30 Climate change poses a significant threat to marine and freshwater fisheries and aquaculture in Africa
31 (Blasiak et al., 2017; Harrod et al., 2018a). Severe (>30%) coral bleaching has impacted ~80% of major reef
32 areas in the western Indian Ocean and Red Sea along Africa's eastern coast (Hughes et al., 2018). Biological
33 effects (e.g., changes in primary production, fish distribution) have also occurred (Hidalgo et al., 2018).
34 Range shifts in marine fish species can exacerbate boundary conflicts among fisher communities (Penney et
35 al., 2017; Belhabib et al., 2019). Changes in fish distribution and reductions in catch across inland fisheries
36 are associated with climatic variability by fishing communities (Okpara et al., 2017b; Lowe et al., 2019;
37 Muringai et al., 2019b). Floods and reduced river flow reduces fish catches (Kolding et al., 2019), which
38 scale positively with discharge rates in rivers across Africa (McIntyre et al., 2016). Warming air and water
39 temperatures have altered water stratification patterns in African lakes causing reductions in or
40 redistirbutions of primary productivity and leading to reduced fish biomass (Section 9.6.1.3). Such changes,
41 partially explain reduced fish catches in Lake Tanganyika (Cohen et al., 2016). In some regions, water
42 scarcity has resulted in conflict within and among food production sectors (pastoralists, fishers and farmers)
43 in this region (Okpara et al., 2017b). Small-scale and artisanal fisher communities are ill-equipped to adapt
44 to climate impacts because there are few financially-accessible alternative livelihoods (Belhabib et al., 2016;
45 Ndhlovu and Saito, 2017).
46
47 9.8.5.2 Projected Risks of Climate Change to Fisheries
48
49 At 4.3癈 global warming, maximum catch potential (MCP) from marine fisheries in African Exclusive
50 Economic Zones (EEZs) would decrease by 12�69% by the end of the 21st century relative to recent decades
51 (1986�2005) whereas maintaining warming levels below 1.6癈 would decrease MCP by 3�41% (Cheung
52 William et al., 2016) (Figure 9.25). However, by mid-century under 2癈 global warming, MCP would
53 decrease by 10 to >30% on the western coast of South Africa, the Horn of Africa and West Africa, indicating
54 these regions could be at risk to declines in MCP earlier in the century than other parts of Africa (Cheung et
55 al., 2016) (Figure 9.25). Declining fish harvests due to sea temperature rise could leave 1.2�70 (median 11.1)
56 million people in Africa vulnerable to deficiencies in iron, and up to 188 million to vitamin A and 285
57 million to vitamin B12 and omega-3 fatty acids by mid-century under 1.7癈 global warming (Golden et al.,
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1 2016). Maire et al. (2021) assessed the nutritional vulnerabilities of African countries to climate change and
2 overfishing, and found that the four most vulnerable countries ranked on a scale from 0 (low vulnerability) to
3 100 (high vulnerability) were Mozambique (87), Madagascar (76), Tanzania (61) and Sierra Leone (58).
4 Coral reef habitat in East Africa is projected to decrease, resulting in negative impacts on demersal fish
5 stocks and invertebrates (Hoegh-Guldberg et al., 2018). Central, West and East Africa appear to be at the
6 greatest nutritional risk from sea temperature rise, leading to reduced catch in coastal waters (Golden et al.,
7 2016) (Figure 9.25). In North Africa, a rise in water temperatures is expected to impact the phenology and
8 migratory patterns of large pelagic species (e.g., bluefin tuna, Thunnus thynnus) (Hidalgo et al., 2018).
9 Increased sea surface temperatures have been associated with increases in spring and summer upwelling
10 intensity reducing the abundance and larval survival of small pelagic fishes and shellfish in West Africa
11 (Bakun et al., 2015; Tiedemann et al., 2017; Atindana et al., 2020). Ocean warming, acidification and
12 hypoxia are predicted to affect the early life history stages of several marine food species, including fish and
13 crustaceans (Kifani et al., 2018). Climate warming is projected to impact water temperature and horizontal
14 and vertical mixing on the southern Benguela ecosystem, with marked negative effects on the biomass of
15 several important fishery resources by 2050 amplified under 2.5癈 compared to 1.7癈 global warming
16 (Ortega-Cisneros et al., 2018).
17
18 For inland fisheries, 55�68% of commercially harvested fish species will be vulnerable to extinction under
19 2.5癈 global warming by the end of the 21st century (2071�2100) compared to 77�97% under 4.4癈 global
20 warming (Figure 9.26). This will increase the number of countries that are at food security risk due to
21 fishery species declines from 10 to 13 (Figure 9.26). Other recent analyses suggest that African countries
22 with the highest inland fisheries production have low- to mid-range projected climate risk (2.4�2.6癈 local
23 temperature increase compared to other regions with 2.7�3.3癈 increase by end of centruy) based on a
24 3.9癈 global warming scenario (Harrod et al., 2018b). In regions where inland fishery production is derived
25 primarily from lakes, there is a lower likelihood of reduced catch, especially where precipitation is projected
26 to increase (e.g., African Great Lakes region) (Harrod et al., 2018b). Regions reliant on rivers and
27 floodplains (e.g., Zambezi and Niger basins) are more likely to experience downturns in catch, as
28 hydrological dynamics may be altered (Harrod et al., 2018b). Projections suggest that opportunistic species
29 that do well in modified systems (Escalera-v醶quez et al., 2017) and small pelagic fishes will remain
30 important components to inland fishery food systems (Kolding et al., 2016; Gownaris et al., 2018; Kolding et
31 al., 2019). Climate adaptation responses that rely on freshwater resources (e.g., hydroelectric power
32 generation, agricultural irrigation) represent threats to inland fisheries (Cowx et al., 2018; Harrod et al.,
33 2018c), by changing flow regimes, reducing water levels, and increasing runoff of pesticides and nutrients
34 (Harrod et al., 2018c).
35
36 For both marine and freshwater fisheries, climate-related extreme weather events and flooding may drive the
37 loss of fishing days, cause damage and loss to fishing gear, endanger the lives of fishers and block
38 transportation from damaged roads (Muringai et al., 2021). Fish processing via weather-dependent
39 techniques such as sun drying may be hampered, causing post-harvest losses (Akintola and Fakoya, 2017;
40 Chan et al., 2019).
41
42 9.8.5.3 Current and Future Adaptation Responses for Fisheries
43
44 Patterns of vulnerability and adaptive capacity are highly context-dependent and vary within and among
45 fishing communities in coastal and riparian areas (Ndhlovu and Saito, 2017; Lowe et al., 2019; D'agata et
46 al., 2020). Interventions that integrate scientific knowledge and fishers' local knowledge while focusing on
47 vulnerable groups are more likely to be more successful (Musinguzi et al., 2018; Muringai et al., 2019b).
48 Infrastructure improvements (e.g., storage facilities, processing technologies, transport systems) could
49 reduce post-harvest losses and improve food safety (Chan et al., 2019). Fisher safety can be aided by early
50 warning of severe weather conditions (Thiery et al., 2017), enhanced through communication via mass
51 media and mobile phones (Thiery et al., 2017; Kiwanuka-Tondo et al., 2019). Although changing fishing
52 gears and shifting target species are important adaptation options for artisanal fishers, many have instead
53 expanded their fishing range or increased effort (Musinguzi et al., 2015; Belhabib et al., 2016). Adapting to
54 the impacts of climate change on marine fisheries productivity requires management reforms accounting for
55 shifting productivity and species distributions, such as increasing marine protected areas, strengthening
56 regional trade networks, and increasing the investment and innovation in climate-resilient aquaculture
57 production (Golden et al., 2021). This could yield higher catch and profits in the future relative to today in
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1 50% of African countries with marine territories under 2癈 global warming and in 35% under 4.3癈 global
2 warming (Free et al., 2020). For inland fisheries, opportunities for adaptation include better integration of
3 inland fisheries into management plans from other sectors (e.g., hydropower and irrigation) (Harrod et al.,
4 2018c; Cowx and Ogutu-Ohwayo, 2019; McCartney et al., 2019). There is growing interest in enhancing the
5 supply of freshwater fishery production from small water bodies and reservoirs in dryland regions of sub-
6 Saharan Africa (Kolding et al., 2016).
7
8
9
10 Figure 9.25: Climate change risk to nutrition and catch potential from Marine Fisheries: Panels comparing countries
11 current percent dependence on marine foods for nutrition compared with projected change in maximum catch potential
12 (MCP) from marine fisheries. (a) The percentage of animal sources foods consumed that originate from a marine
13 environment. Countries with higher dependence are indicated by darker shades of blue (Golden et al., 2016). (b璫)
14 Projected percent change in maximum catch potential (MCP) of marine fisheries under 1.6癈 global warming (b) and
15 >4癈 global warming (c) from recent past (1986�2005) to end of 21st century (2081-2100) in countries' Exclusive
16 Economic Zones (EEZs)(Cheung William et al., 2016). Darker red indicates greater percent reduction [negative values].
17 (d璭) Countries (in green) that have overlap between high nutritional dependence and high reduction in MCP under two
18 warming scenarios.
19
20
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1
2 Figure 9.26: Climate change risk to Freshwater Fisheries: Panels comparing countries current dependence on inland
3 fisheries compared with climate change vulnerability of important fishery species. (a) Countries' reliance on inland
4 fisheries was estimated by catch (total, tonnes) (FAO, 2018b; Fluet-Chouinard et al., 2018), per capita catch
5 (kg/person/year) (FAO, 2018b), percent reliance on fish for micronutrients, and percent consumption per household
6 (Golden et al., 2016). Z-scores of each metric were averaged for each country to create a composite index describing
7 `current dependence on freshwater fish' for each country with darker blue colours indicating higher dependence. (b璫)
8 Projected concentrations (numbers) of vulnerable freshwater fishery species averaged within freshwater ecoregions
9 under >2癈 global warming (b) and >4癈 global warming (c) estimated from recent past (1961�1992) to the end of the
10 21st century (2071 to 2100) (Nyboer et al., 2019). Numbers of vulnerable fish species translate to an average of 55�
11 68% vulnerable at >2癈 and 77�97% vulnerable at <4癈 global warming. Darker reds indicate higher concentrations of
12 vulnerable fish species. (d璭) Countries (in green) that have an overlap between high dependence on freshwater fish and
13 high concentrations of fishery species that are vulnerable to climate change under two warming scenarios
14
15
16 9.9 Human Settlements and Infrastructure
17
18 This section assesses climate impacts, risks and adaptation options for human settlements comprising human
19 populations and infrastructure such as buildings, roads and energy across Africa.
20
21 9.9.1 Urbanisation, Population and Development Trends
22
23 Africa is the most rapidly urbanising region in the world, with an annual urban population growth rate of
24 3.6% for 2005�2015 (UN-Habitat, 2016). About 57% of the population currently lives in rural areas, the
25 proprotion of the population living in urban areas is projectted to exceed 60% by 2050 (UNDESA, 2019b)
26 (UN-Habitat, 2016). Much of the rapid rate of urbanisation has resulted from the growth of small towns and
27 intermediary cities (African Development Bank et al., 2016).
28
29 Approximately 59% of sub-Saharan Africa's urban population resides in informal settlements (in some cities
30 up to 80%), and the population in informal settlements is expected to increase (very high confidence) (Taylor
31 and Peter, 2014; UN-Habitat, 2014; UN-Habitat, 2016; UNDP, 2019). These urbanisation trends are
32 compounding the increasing exposure to climate hazards, particularly floods and heatwaves (high
33 confidence) (Dodman et al., 2015).
34
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1 Globally, the highest rates of population growth and urbanisation are taking place in Africa's coastal zones
2 (high confidence) (Merkens et al., 2016). Coastal urban populations account for 25�29% of the total
3 population in West, North and southern Africa (OECD/SWAC, 2020). Accounting for a continuing young
4 population, stagnant economies and migration to regional growth centres, projections indicate that the low-
5 lying coastal zone population of sub-Saharan Africa could increase by 175% (2030) and 625% (2060)
6 relative to 24 million in 2000 (Neumann et al., 2015).
7
8 Climate-related displacement is widespread in Africa, with increased migration to urban areas in sub-
9 Saharan Africa linked to decreased rainfall in rural areas, increasing urbanisation and affecting household
10 vulnerability (see Box 9.9). Much of this growth can occur in informal settlements which are growing due to
11 both climatic and non-climatic drivers, and which often house temporary migrants, including internally
12 displaced people. Such informal settlements are located in areas exposed to climate change and variability
13 and are exposed to floods, landslides, sea level rise and storm surges in low-lying coastal areas, or alongside
14 rivers that frequently overflow, thereby exacerbating existing vulnerabilities (Satterthwaite et al., 2020).
15
16 Sub-Saharan Africa's large infrastructure deficit (quantity, quality and access) with respect to road transport,
17 electricity, water supply and sanitation places the region at the lowest of all developing regions (AfDB,
18 2018a; Calderon et al., 2018). Adequate infrastructure to support Africa's rapidly growing population is
19 important to raise living standards and productivity in informal settlements (AfDB, 2018b; UN Environment,
20 2019). Yet planned infrastructure developments, including those related to African Union's Programme for
21 Infrastructure Development (PIDA), along with other energy plans, and China's Belt and Road Initiative
22 (BRI), may increase or decrease both climate change mitigation and adaptation depending on whether
23 infrastructure planning integrates current and future climate change risks (Cervigni et al., 2015; Addaney,
24 2020) (see Box 9.5).
25
26 9.9.2 Observed Impacts on Human Settlements and Infrastructure
27
28 African human settlements are particularly exposed to floods (pluvial and fluvial), droughts and heat waves.
29 Other climate hazards are sea level rise and storm surges in coastal areas, tropical cyclones and convective
30 storms. This sub-section provides an assessment of observed impacts and risks from climate hazards in
31 different sub-regions to underscore the relevance of climate-sensitive planning and actions to advance social
32 and economic development, and reduce the loss and damage of property, assets and critical infrastructure.
33
34 9.9.2.1 Observed Impacts on Human Settlements
35
36 The spatial distribution of climate hazards and observed impacts in terms of total people affected (displaced
37 persons and deaths) during 2010�2020 is shown in Figure 9.27. From 2000�2019 , floods and droughts
38 accounted for 80% and 16%, respectively, of the 337 million affected persons, and a further 32% and 46%,
39 respectively, of 46,078 deaths from natural disasters in Africa (CRED, 2019). Flooding is a major hazard
40 across Africa (Kundzewicz et al., 2014; Douglas, 2017) and is increasing (Zevenbergen et al., 2016; Elboshy
41 et al., 2019). An increase in extreme poverty and up to a 35% decrease in consumption has been associated
42 with exposure to flood shocks (Azzarri and Signorelli, 2020). Globally, only sub-Saharan Africa has
43 recorded increasing rates of flood mortality since the 1990s (Tellman et al., 2021). Economic opportunities,
44 transportation of goods and services, and mobility and access to essential services, including health and
45 education, are greatly hindered by flooding (Gannon et al., 2018). Severe impacts from tropical cyclone
46 landfalls have been recorded in East and southeastern Africa (Rapolaki and Reason, 2018; Cambaza et al.,
47 2019; Chatiza, 2019; Hope, 2019). Cyclones Idai and Kenneth in early 2019 caused flooding of districts in
48 Mozambique, Zimbabwe and Malawi, with substantial loss and damage to infrastructure in the energy,
49 transport, water supply, communication services, housing, health and education sectors, particularly in
50 Mozambique (Figure 9.27; see also Cross-Chapter Box DISASTER in Chapter 4) (Warren, 2019; Dube et
51 al., 2021; Phiri et al., 2021).
52
53
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1
2 Figure 9.27: From 2010�2020, over 166 million people were reported to be affected by climate hazards across Africa.
3 Maps show (a) location of all reported climate hazards, (b) people affected by droughts, (c) people affected by
4 convective storms, (d) people affected by floods, (e) total deaths from tropical cyclones, and (f) total deaths from heat
5 waves. Source (EMDAT and CRED, 2020). Note, although extreme weather damage databases under report heatwaves
6 (which is indicated in panel (f) by very few deaths), the region has experienced a number of heatwaves and will be
7 affected disproportionately by them in the future under climate change (Harrington and Otto, 2020).
8
9
10 Table 9.7: Case studies of climate hazard impacts and risks to selected human settlements in Africa
Hazard Country/City Impact on Human Settlement and Infrastructure Source
Sea level Egypt December 2010, January 2011, and October 2015: Storm surge of (Kloos and
rise and (North 1.2 m above MSL (typical of the Nile Delta coast: 0.4�0.5 m). Baumert, 2015;
storm Africa) Coastal flooding and damage to some coastal structures. Moderate Abutaleb et al.,
surge flooding of the Nile Delta lowlands. 2018)
Alexandria city: Flooding generated by heavy rainfall (2015). (Eldeberky Y,
Increased turbidity of water sources affected efficiency of water 2015; Yehia et
treatment plants leading to reduction of water supplies affecting al., 2017)
public health systems. Potable water supply affected by saltwater
intrusion. Coastal erosion and property damage.
Drought Southern El Ni駉 Drought 2015�2016: Western Cape Region Affected 8.6 (Davis-Reddy et
Africa million people. Losses: >USD 2.2 billion. Power generation reduced al., 2017;
by 75% at Kariba dam (Zambia) in 2016, and the Cahora Bassa dam Spalding-Fecher
(Mozambique) reduced to 34% of its capacity with widespread et al., 2017)
impact on electricity supplies across southern Africa. (Brooks, 2019)
Somalia Somalia drought 2016-2017: 926,000 newly displaced persons (Government of
(East Africa) reported (Nov. 2016璒ct. 2017). 40% of total drought-related Somalia, 2018)
displacements accommodated in Mogadishu, Baidoa, Kismayo;
60% hosted in other secondary cities. Increased population density
and overcrowding in Somalia's urban areas. Explosion of new
shelters and tents for displaced persons within and in outskirts of
cities. In Mogadishu, 34% of new settlements developed within six
months.
Flooding Malawi Floods 2019: Approximately 975,600 people affected, 672 injured, (Government of
(East Africa) 60 persons killed, and 86,976 people displaced. 288,371 houses Malawi, 2019)
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damaged. 129 bridges and 68 culverts destroyed. 1841 km of road
network estimated at USD 36.1 million destroyed. Total cost of
damage and losses: housing sector - USD 106.9 million, energy -
USD 3.1 million; water and sanitation - USD 6.4 million; transport -
USD 37.0 million. Total cost of destroyed physical assets � USD
157.7 million. Damage and Losses in Blantyre city: housing sector -
USD 29.87 million, energy sector - USD 0.38 million and transport
sector - USD 1.72 million.
Tropical Mozambique, Cyclones Idai and Kenneth 2019: Severe flooding of districts in (Cambaza et al.,
cyclone Zimbabwe Mozambique, Zimbabwe, and Malawi; 233,900 houses completely 2019; Chatiza,
and Malawi destroyed or damaged in Mozambique. 2019;
(Southern Cyclone Kenneth - about 40,000 houses and 19 health facilities Government of
Africa) destroyed. Mozambique,
Cyclone Idai - destroyed or damaged 1,345 km of transmission 2019; Hope,
lines, 10,216 km of distribution lines, two 90MW generation plants, 2019;
30 sub-stations and 4,000 transformers, resulting in estimated Lequechane et
damage of USD 133.5 million and loss of USD 47.9 million in the al., 2020; Phiri
energy sector in Mozambique. 602 and 299 people killed in et al., 2021)
Mozambique and Zimbabwe respectively; Affected persons - about
1.5 million in Mozambique and 270,000 in Zimbabwe. (Enenkel et al.,
In Beira (Mozambique) - 60% of city was inundated, 70% of houses 2020)
damaged or totally destroyed, mostly in the poorest neighbourhood,
and 90% of the city's power grid affected. Huge losses and damages
to infrastructures in the energy, transport, water supply,
communication services, housing, health and education sector were
also recorded.
Landslide Freetown August 2017: At least 500 persons killed and over 600 persons (Cui et al.,
(West Africa) declared missing, >3,000 residents rendered homeless; 349 houses 2019)
destroyed. Damage to health facilities and educational buildings. (World Bank,
Economic cost of landslide and flood: USD 31.6 million. 2017b)
Uganda Slopes of Mt. Elgon (2010): More than 350 deaths and 500,000 (Croitoru et al.,
(East Africa) persons needed to be relocated 2019)
1
2
3 From 2005�2020, flood-induced damage over Africa was estimated at over USD 4.4 billion, with eastern and
4 western Africa being the most affected regions (EMDAT and CRED, 2020). Total damages in four West
5 African countries (Benin, Cote d'Ivoire, Senegal and Togo) in 2017 were estimated at USD 850 million for
6 pluvial floods and USD 555 million for fluvial floods (Croitoru et al., 2019). Unprecedented economic loss,
7 in terms of goods and properties, estimated by the Nigerian insurance industry at USD 200 million resulted
8 from floods in Lagos in 2011 (Adelekan, 2016). In southern Africa, the highest costs were incurred from
9 flood losses during the period 2000-2015 (UNEP-FI, 2019b; Simpson, 2020).
10
11 Business disruptions from climate impacts have implications for deepening poverty (Adelekan and Fregene,
12 2015). Small and medium enterprises (SMEs) employ 60�90% of workers in many African countries and
13 contribute 40% or more to the GDP in Ghana, Kenya, Nigeria, Zimbabwe, South Africa and Tanzania
14 (Muriithi, 2017). The viability of businesses and economic well-being of large populations employed in
15 SMEs is severely affected by climate hazards as reported for local wind storms in Ibadan (Adelekan, 2012),
16 El Ni駉-related flooding (Nairobi), drought-induced water supply disruption (Gaborone) and power outages
17 (Lusaka) (Gannon et al., 2018). High water demand due to high rates of urbanisation and population growth,
18 coupled with drought, reduce groundwater levels in cities (e.g., Bouake, Harare, Tripoli, Niamey) and
19 increase saltwater intrusion into groundwater in coastal areas, reducing water availability and water security,
20 particularly for poorer populations not connected to municipal water networks (Aswad et al., 2019; Claon et
21 al., 2020).
22
23 Evidence of the impact of heat waves in urban Africa in the current climate is sparse, due in part to low
24 reporting and monitoring (Engelbrecht et al., 2015; Harrington and Otto, 2020). Knowledge is also limited
25 on the interaction of climate change, urban growth and the urban heat island effect in Africa (Chapman et al.,
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1 2017). In North Africa, the present day number of high heat-stress nights is around 10 times larger in urban
2 than rural areas (Fischer et al., 2012).
3
4 9.9.2.2 Observed Impacts to Road and Energy Infrastructure
5
6 The highest transport infrastructure exposures are from floods (Koks et al., 2019), with potentially severe
7 consequences for food security (Fanzo et al., 2018), communication and the economy of affected regions
8 (high confidence) (Koks et al., 2019). Eight of the twenty countries with the highest expected annual
9 damages to road and rail assets, relative to the country's GDP, are located in East, West and Central Africa
10 (Koks et al., 2019). Transport impacts compound climate impacts, such as heat stress and air pollution linked
11 to vehicle emissions in Dar es Salaam (Ndetto and Matzarakis, 2014).
12
13 African economies that rely primarily on hydropower for electricity generation are particularly sensitive to
14 climate variability (Brooks, 2019). This sensitivity was already felt during the 2015/16 El Ni駉, in which
15 Malawi, Tanzania, Zambia and Zimbabwe all experienced widespread and prolonged load shedding due to
16 low rainfall. The impact was felt throughout the economy and reflected in reduced GDP growth in Zambia
17 (Conway et al., 2017).
18
19 9.9.3 Observed Vulnerabilities of Human Settlements to Climate Risks
20
21 Urban vulnerabilities and exposure to climate change are increasing (medium to high confidence) and are
22 influenced by patterns of urban settlement and housing characteristics (Satterthwaite, 2017; Godsmark et al.,
23 2019; Williams et al., 2019a). About 70% of African cities are highly vulnerable to climate shocks of which
24 small- and medium-sized towns and cities are more at risk (Verisk Maplecroft, 2018). Flooding was
25 perceived as the most prominent water risk in 75% of 36 sampled cities across African sub-regions, while
26 drought-related water scarcity was indicated as very important/important in 66.7% of cities (OECD, 2021).
27 Almost one-third of African cities with populations of 300,000 or more are located in areas of high exposure
28 to at least one natural hazard, including floods (12%) and droughts (20�25%) (Gu et al., 2015). The coastal
29 cities of East, West and North Africa are particularly vulnerable to the effects of rising sea levels (Abutaleb
30 et al., 2018; IPCC, 2019a).
31
32 Globally, sub-Saharan Africa has the largest population living in extreme poverty that are exposed to high
33 flood risk (~71 million people or 55% of global total) (Rentschler and Salhab, 2020). Poverty is a significant
34 factor of flood-induced displacement in Africa, where even small flood exposure can lead to high numbers of
35 displacement (Kakinuma et al., 2020). Africa's large population of urban poor and marginalised groups and
36 informal sector workers, further contribute to high vulnerability to extreme weather and climate change in
37 many settlements (high confidence) (Adelekan and Fregene, 2015; IPCC, 2019a; UNDP, 2019).
38
39 Other non-climatic stressors which exacerbate vulnerabilities, especially in urban areas, include poor
40 socioeconomic development, weak municipal governance, poor resource and institutional capacities,
41 together with multi-dimensional, location-specific inequalities (high confidence) (Dodman et al., 2017;
42 Satterthwaite, 2017).
43
44 9.9.4 Projected Risks for Human Settlements and Infrastructure
45
46 9.9.4.1 Projected Risks for Human Settlements
47
48 The extent of urban areas in Africa exposed to climate hazards will increase considerably and cities will be
49 hotspots of climate risks, which could amplify pre-existing stresses related to poverty, exclusion and
50 governance (high confidence) (IPCC, 2018b).
51
52 Flooding
53 Continuing current population and GDP growth trends, the extent of urban land exposed to high-frequency
54 flooding is projected to increase around 270% in North Africa, 800% in southern Africa, and 2600% in mid-
55 latitude Africa by 2030 when compared to 2000, without considering climate change (G黱eralp et al., 2015).
56 In addition, global warming is projected to increase frequency and magnitude of river floods in East, Central
57 and West Africa (Alfieri et al., 2017; Gu et al., 2020; Kam et al., 2021). On average across large African
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1 river basins, the frequency of flood events with a current return period of 100 years is projected to increase to
2 1 in 40 years at 1.5 and 2 global warming, and 1 in 21 years at 4 warming, with Egypt, Nigeria,
3 Sudan and DRC in the top 20 countries globally for projected damages (Alfieri et al., 2017). Compared to
4 population in 2000, human displacement due to river flooding in Sub-Saharan Africa is projected to increase
5 600% by 2066�2096 with moderate-to-high population growth and 2.6 global warming, with risk reducing
6 to a 200% increase for low population growth and 1.6 global warming (Kam et al., 2021).
7
8 Urban population exposure to tropical cyclone hazards in southeastern Africa, in particular Mozambique, is
9 projected to increase due to the intensification of cyclones and their extended duration associated with
10 warmer sea surface temperatures (Fitchett, 2018; Vidya et al., 2020). Urban damage assessment based on a
11 10-year flood protection level for Accra shows that without flood protection, there is a 10% probability of a
12 flood occurring annually which could cause USD 98.5 million urban damage, affect GDP by USD 50.3
13 million and affect 34,000 people (Asumadu-Sarkodie et al., 2015). Many urban households and Africa's
14 growing assets could therefore be exposed to increased flooding (IPCC, 2018b).
15
16
17
18 Figure 9.28: Tens to hundreds of millions of people in Africa are projected to be exposed to sea level rise, with a major
19 risk driver being increased exposure due to population increase in low-lying areas. (a) Population in the low-elevation
20 coastal zone (LECZ) projected for 2030 (+10cm SLR) and 2060 (+21 cm SLR). (b) African countries with highest
21 population in LECZ, and additional population exposed in the 100-year floodplain. Data sourced from (Neumann et al.,
22 2015).
23
24
25 Sea level rise and coastal flooding
26 Africa's low-lying coastal zone population is expected to grow more than any other region from 2000 to
27 2060 (see Figure 9.28) (Neumann et al., 2015). Future rapid coastal development is expected to increase
28 existing high vulnerabilities to sea level rise (SLR) and coastal hazards, particularly in East Africa (high
29 confidence) (Figure 9.29) (Hinkel et al., 2012; Kulp and Strauss, 2019). By 2100, sea levels are projected to
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1 rise at least 40 cm above those in 2000 in a below 2 scenario, and possibly up to 1 m by the end of the
2 century under a 4 warming scenario (Serdeczny et al., 2017) (see also Cross-Chapter Box SLR in Chapter
3 3).
4
5
(a) Dar es Salaam, Bagamoyo and Stonetown (Tanzania)
RCP 2.6
RCP 4.5
RCP 8.5
Built-up area (2014)
50 km
Present Day 2050 2100
(b) Lagos (Nigeria) and Cotonou and Porto-Novo (Benin) (c) Cairo and Alexandria (Egypt)
Present Day Present Day
2050 2050
2100 2100
6
7 Figure 9.29: Selected African cities exposed to sea level rise include (a) Dar es Salaam, Bagamoyo, and Stone Town in
8 Tanzania (East Africa), (b) Lagos in Nigeria, and Cotonou and Porto-Novo in Benin (West Africa), and (c) Cairo and
9 Alexandria in Egypt (North Africa). Orange shows built-up area in 2014. Shades of blue show permanent flooding due
10 to sea level rise by 2050 and 2100 under low (RCP2.6), medium (RCP4.5) and high (RCP8.5) greenhouse gas
11 emissions scenarios. Darker colours for higher emissions scenarios show areas projected to be flooded in addition to
12 those for lower emissions scenarios. The figure assumes failure of coastal defences in 2050 and 2100. Some areas are
13 already below current sea level rise and coastal defences need to be upgraded as sea level rises (e.g., in Egypt), others
14 are just above mean sea levels and they do not necessarily have high protection levels, so these defences need to be built
15 (e.g., Dar Es Salam and Lagos). Blue shading shows permanent inundation surfaces predicted by Coastal DEM and
16 SRTM given the 95th percentile K14/RCP2.6, RCP4.5, and RCP8.5, for present day, 2050, and 2100 sea level
17 projection for permanent inundation (inundation without a storm surge event), and RL10 (10-year return level storm)
18 (Kulp and Strauss, 2019). Low-lying areas isolated from the ocean are removed from the inundation surface using
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1 connected components analysis. Current water bodies are derived from the SRTM Water Body Dataset. Orange areas
2 represent the extent of coastal human settlements in 2014 (Corbane et al., 2018). See Figure CCP4.7 for projections
3 including subsidence and worst-case scenario projections for 2100.
4
5
6 In the absence of any adaptation, Egypt, Mozambique, and Nigeria are projected to be worst affected by SLR
7 in terms of the number of people at risk of flooding annually in a 4 warming scenario (Hinkel et al., 2012).
8 Recent estimates have explored the potential damages due to SLR and coastal extreme events in 12 major
9 African cities using a stochastic approach to account for uncertainty (Abadie et al., 2020). Expected
10 aggregate damages to these cities in 2050 are USD 65 billion for RCP4.5 and USD 86.5 billion for RCP8.5,
11 and USD 137.5 billion under a high-end scenario that incorporates expert opinion on additional ice sheet
12 melting (Table 9.8). When considering low-probability, high-damage events, aggregate damage risks can be
13 more than twice as high, reaching USD 187 billion and USD 206 billion under RCP4.5 and RCP8.5
14 scenarios, respectively, and USD 397 billion under the high-end scenario. City characteristics and exposure
15 play a larger role in expected damages and risk than changes in sea level. The city of Alexandria in North
16 Africa leads the ranking, with aggregate expected damage of USD 36 billion and USD 50 billion under
17 RCP4.5 and RCP8.5 scenarios, respectively, and USD 79.4 billion under the high-end scenario.
18
19
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1 Table 9.8: Regional relative sea level rise and associated damage risks in 12 major African coastal cities under four SLR scenarios. Panel (a) Regional relative sea level rise by 2050
2 and 2100. For SLR, median and 95th percentiles are presented, in centimetres. Panel (b) Probabilistic damage estimations by 2050 include expected average damages (EAD),
3 damages at the 95th percentile (VaR) and the Expected Shortfall (ES), which represents the average damages of the 5% worst cases. Four relative sea level projections were
4 considered under no adaptation: the RCP2.6, 4.5 and 8.5 scenarios from the IPCC AR5, and a high-end RCP8.5 scenario that incorporates expert opinion on additional ice sheet
5 melting. Note that figures are provided in undiscounted millions of US dollars (2005) and have been rounded off to avoid a false sense of precision (Abadie et al., 2020; Abadie et
6 al., 2021).
7
a) Regional relative sea level rise (cm)
City Year RCP2.6 RCP4.5 RCP8.5 High end
Median P95 Median P95 Median P95 Median P95
Abidjan 2050 21 30 22 32 24 34 28 48
2100 44 69 53 86 75 114 86 206
Alexandria 2050 18 26 18 28 21 30 25 43
2100 36 58 46 73 67 102 78 186
Algiers 2050 19 27 19 29 22 31 25 45
2100 39 62 47 76 66 98 78 192
Cape Town 2050 20 30 21 31 23 33 27 48
2100 44 69 53 87 75 117 86 199
Casablanca 2050 19 27 20 29 22 31 26 46
2100 39 63 47 78 65 99 77 198
Dakar 2050 21 31 21 31 23 33 27 48
2100 43 69 53 86 73 111 85 209
Dar-es-Salam 2050 20 29 21 31 24 33 27 47
2100 45 70 54 86 76 117 87 206
Durban 2050 20 30 22 32 25 34 28 49
2100 46 72 55 90 78 119 89 207
Lagos 2050 21 30 22 32 24 34 28 48
2100 44 69 54 86 75 113 86 205
Lome 2050 21 30 22 32 24 34 28 48
2100 44 69 53 86 76 115 87 205
Luanda 2050 21 30 23 32 25 35 29 49
2100 45 70 55 88 78 119 90 205
Maputo 2050 21 31 22 32 24 34 28 49
2100 45 71 55 89 78 120 89 209
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b) Expected damages and risk measures (USD millions)
City RCP2.6 RCP4.5 RCP8.5 High-end scenario
EAD VaR(95%) ES(95%) EAD VaR(95%) ES(95%) EAD VaR(95%) ES(95%) EAD VaR(95%) ES(95%)
Abidjan 14,290 33,910 41,690 16,730 38,230 46,390 20,910 42,140 49,550 32,670 77,750 96,570
Alexandria 32,840 74,100 92,470 36,220 83,700 104,270 49,990 99,500 117,580 79,360 180,090 221,390
Algiers 270 620 760 300 700 870 390 810 960 640 1,540 1,920
Cape Town 110 310 400 130 360 450 170 410 490 300 800 1,010
Casablanca 350 1,150 1,520 420 1,340 1,740 610 1,570 1,930 1,230 3,590 4,630
Dakar 590 1,310 1,590 620 1,390 1,690 760 1,530 1,800 1,180 2,880 3,610
Dar-es-Salam 880 2,100 2,600 1,050 2,440 2,970 1,360 2,760 3,250 2,140 5,120 6,360
Durban 110 370 470 150 420 530 210 490 590 370 970 1,230
Lagos 3,680 6,790 7,950 4,200 7,660 8,930 4,920 8,270 9,420 6,750 13,820 16,730
Lome 3,230 10,480 13,460 4,280 12,580 15,780 5,980 14,430 17,380 10,720 28,580 36,010
Luanda 160 380 470 200 440 530 260 510 600 400 910 1,130
Maputo 650 1,990 2,530 700 2,080 2,620 980 2,410 2,910 1,790 4,830 6,110
Aggregate damage 57,160 133,510 165,910 65,000 151,340 186,770 86,540 174,830 206,460 137,550 320,880 396,700
and risk
1
2
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1 Sea level rise and associated episodic flooding are identified as key drivers of projected net migration of
2 750,000 people out of the East African coastal zone between 2020 and 2050 (IPCC, 2019a). These trends,
3 alongside the emergence of `hotspots' of climate in and out-migration (Box 9.8), will have major
4 implications for climate-sensitive sectors and the adequacy of human settlements, including urban
5 infrastructure and social support systems. Actions which could help reduce the number of people being
6 forced to move in distress, include adoption of inclusive and climate-resilient development policies, together
7 with targeted investments to manage the reality of climate migration; and mainstreaming climate migration
8 in development planning (Box 9.8).
9
10 Drought
11 Although an increase in drought hazard is projected for North and southwest southern Africa with increased
12 global warming (Figure 9.15), Central African countries may have the highest drought risk because of high
13 vulnerability and high population growth (Ahmadalipour et al., 2019). Among continents, Africa contains
14 the second largest population of people living in drylands, which is expected to double by 2050 (IPCC,
15 2019a). Continuing current population and GDP growth trends, the extent of urban land in arid zones is
16 projected to increase around 180% in Southern Africa, 300% in North Africa, and 700% in mid-latitude
17 Africa by 2030 when compared to 2000, without considering climate change (G黱eralp et al., 2015). At
18 1.5 warming, urban populations exposed to severe droughts in West Africa are projected to increase
19 (65�34 million) and increase further at 2 (IPCC, 2018b; Liu et al., 2018b). Risks associated with increases
20 in drought frequency and magnitudes are projected to be substantially larger at 2 than at 1.5 for North
21 Africa and Southern Africa (IPCC, 2018b; Oppenheimer et al., 2019). Dryland populations exposed
22 (vulnerable) to water stress, heat stress, and desertification are projected to reach 951 (178) million at 1.5,
23 1,152 (220) million at 2, and 1,285 (277) million at 3 of global warming (IPCC, 2019a). At global
24 warming of 2 under a scenario of low populaton growth and sustainable development (SSP1), the exposed
25 (vulnerable) dryland population is 974 (35) million and for higher population growth and low environmental
26 protections (SSP3) it is 1.27 billion (522 million), a majority of which is in West Africa (IPCC, 2019a).
27
28 Extreme heat
29 Projections for 173 African cities show that around 25 cities will have over 150 days per year with an
30 apparent temperature above 40.6 for 1.7 global warming, increasing to 35 cities for 2.1 and 65 cities
31 for 4.4 warming, with West African cities most affected (Rohat et al., 2019). Across Africa, urban
32 population exposure to extreme heat is expected to increase from 2 billion person-days per year for 1985�
33 2005 to 45 billion person-days for 1.7 global warming with low population growth (SSP1) and to 95
34 billion person-days for 2.8 and medium-high population growth (SSP4) by the 2060s, with increases of
35 20�52 times 1985�2005 levels by 2080�2100, depending on the scenario (Rohat et al., 2019). West Africa
36 (especially Nigeria) has the highest absolute exposure and Southern Africa the least. Considering the urban
37 heat island effect, the more vulnerable populations under 5 and over 64 exposed to heat waves of >15 days
38 over 42 are projected to increase from 27 million in 2010 to 360 million by 2100 for 1.8 global
39 warming, increasing to 440 million for >4 global warming, with West Africa most affected (Marcotullio et
40 al., 2021). This portends increased vulnerability to risk of heat stress in big cities of Central, East and West
41 Africa (very high confidence) (Gasparrini et al., 2015; Liu et al., 2017; Rohat et al., 2019). Shifting to a low
42 urban population growth pathway is projected to achieve a greater reduction in aggregate exposure to
43 extreme heat for most cities in West Africa whereas limiting warming through lower emissions pathways
44 achieves greater reductions in exposure in Central and East Africa (Rohat et al., 2019).
45
46 The African population exposed to compound climate extremes, such as coincident heat waves and droughts
47 or drought followed immediately by extreme rainfall, is projected to increase 47-fold by 2070�2099
48 compared to 1981�2010 for a scenario with high population growth and 4 global warming (SSP3/RCP8.5)
49 and only 12-fold for low population growth and 1.6 global warming (SSP1/RCP2.6), with West, Central-
50 East, northeastern and southeastern Africa especially exposed (Weber et al., 2020). Coincident heat waves
51 and drought is the compound event to which the most people are projected to be exposed: ~1.9 billion
52 person-events (a 14-fold increase) for SSP1/RCP2.6 and ~7.3 billion person-events (52-fold increase) for
53 SSP3/RCP8.5 (Weber et al., 2020).
54
55 9.9.4.2 Projected Risks to Electricity Generation and Transmission
56
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1 Climate change poses an increased risk to energy security for human settlements in Africa (high confidence).
2 With burgeoning urban populations and growing economies, sub-Saharan Africa's electricity needs are
3 growing. The IEA projects total generation capacity in Africa must grow 2.5 times from 244 GW in 2018 to
4 614 GW by 2040 (IEA, 2019). African nations plan to add significant generation capacity from natural gas,
5 hydropower, wind and solar power. Each of these technologies is associated to a varying degree with climate
6 risk.
7
8 The long lifespan of hydropower dams exposes them to decades of climatic variability. There is a wide range
9 of uncertainty around the future climate of Africa's major river basins, but in several basins, there is the
10 likelihood of increased rainfall variability and a drier climate (see Box 9.5). In countries that rely primarily
11 on hydropower, climate change could have considerable impacts on electricity prices and as a result,
12 consumers' expenditure (Sridharan et al., 2019). With increasing societal demands on limited water
13 resources and future climate change, it is expected that there will be an intensification of water-energy-food
14 competition and trade-offs (high confidence) (Section 9.7; Box 9.5).
15
16 9.9.4.3 Projected Risks to Road Infrastructure
17
18 Climate change and sea level rise will result in high economic costs for road infrastructure in sub-Saharan
19 Africa (medium confidence) (Chinowsky et al., 2015). Across Africa as a whole, potential cumulative costs
20 estimates through 2100 range from USD 183.6 billion (with adaptation) to USD 248.3 billion (no adaptation)
21 to repair and maintain existing roads damaged by temperature and precipitation changes directly related to
22 projected climate change (see Figure 9.30) (Chinowsky et al., 2013). Climate-related road damage and
23 associated repairs will be a significant financial burden to countries, but to varying degrees according to
24 flood risk, existing road asset liability, topography and rural connectivity, among other factors (Chinowsky
25 et al., 2015; Cervigni et al., 2017; Koks et al., 2019). For example, Mozambique is projected to face
26 estimated annual average costs of USD 123 million for maintaining and repairing roads damaged directly by
27 precipitation and temperature changes from climate change through 2050 in a median climate change
28 scenario for a policy that does not consider climate impacts during road design and construction (Chinowsky
29 et al., 2015). Risk of river flooding to bridges in Mozambique under current conditions is estimated to be
30 USD 200 million, equal to 1.5% of its GDP per year, and could rise to USD 400 million per year in the
31 worst-case climate change scenario by 2050 (Schweikert et al., 2015).
32
33
34
35 Figure 9.30: Projected costs for repair and maintenance of pre-2011 road infrastructure in selected African countries as
36 a result of projected climate-change-related damages due directly to precipitation and temperature changes through to
37 2100 (Data sources: (Chinowsky et al., 2013). The analysis was run for 22 SRES climate scenarios and the median, and
38 maximum results of the analyses are represented as proportions of the 2011 GDP of each country.
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1
2
3 9.9.5 Adaptation in Human Settlements and for Infrastructure
4
5 9.9.5.1 Solutions and Residual Risk Observed in Human Settlements
6
7 Autonomous responses to climate impacts in 40 African cities show that excess rainfall is the primary
8 climate driver of adaptation, followed by multi-hazard impacts, with 72% of responses focused on excess
9 rainfall (Hunter et al., 2020). Innovation for adaptation in areas such as home design, social networks,
10 organisations and infrastructure, is evident (Swanepoel and Sauka, 2019). Social learning platforms also
11 increase communities' adaptive capacities and resilience to risk (Thorn et al., 2015).
12
13 There is limited evidence of successful, proactively planned climate change adaptation in African cities
14 (Simon and Leck, 2015), particularly for those countries highly vulnerable to climate change (Ford et al.,
15 2014). Planned adaptation initiatives in African cities since 2006 have been predominantly determined at the
16 national level with negligible participation of lower levels of government (Ford et al., 2014). Adaptation
17 action directed at vulnerable populations is also rare (Ford et al., 2014). There are emerging examples of
18 cities planned climate adaptation measures, such as those advanced by Durban (Roberts, 2010), Cape Town
19 (Taylor et al., 2016) and Lagos (Adelekan, 2016). There are also examples of community-led projects such
20 as those in Maputo (Broto et al., 2015), which have seen meaningful help from a range of policy networks,
21 dialogue forums and urban learning labs (Pasquini and Cowling, 2014; Shackleton et al., 2015). These
22 researched cities can be lighthouses for wider exchange and the basis for a deeper synthesis of evidence
23 (Lindley et al., 2019). However, planned adaptation progress is slow, especially in West and Central Africa
24 (Tiepolo, 2014).
25
26 Nature-based solutions are also being deployed in mitigating and adapting to climate change, with
27 demonstrated long-term health, ecological and social co-benefits (Swanepoel and Sauka, 2019) (Section
28 9.6.4). The cost-benefit analysis of nature-based solutions, compared to purely grey infrastructure initiatives,
29 is discussed in Chapter 6 (Section 6.3.3). Nature-based solutions can also lengthen the life of existing built
30 infrastructure (du Toit et al., 2018). Since 2014, an increasing number of ecosystem-based adaptation
31 projects involving the restoration of mangrove, wetland and riparian ecosystems have been initiated across
32 Africa, a majority of which address water-related climate risks (Table 9.9).
33
34
35 Table 9.9: Examples of ecosystem-based solutions to climate impacts in African cities.
Project City Solution Reference
Green Urban Beira Mitigating against increased flood (IPCC, 2019a; CES
Infrastructure (GUI) (Mozambique) risks through restoration of Consulting Engineers
mangrove and other natural habitats Salzgitter GmbH and Inros
along the Chiveve river and the Lackner SE, 2020) .
development of urban green spaces.
The Msimbazi Dar es Salaam, Enhancing urban resilience to flood (Croitoru et al., 2019)
Opportunity Plan Tanzania risk by reducing flood hazard, and
(MOP) 2019-2024 reducing people, properties and
critical infrastructure exposed to
flood hazard.
Tanzania Ecosystem Dar es Salaam Rehabilitation of over 3,000 (UNEP, 2019)
Based Adaptation and five coastal hectares of climate-resilient
districts, Tanzania mangrove species.
Building Resilience Maputo, Restoration of mangrove and (GEF, 2019)
in the Coastal Zone Mozambique riparian ecosystems for flood
through Ecosystem� control and protection from coastal
based approaches to flooding enhanced water supply.
adaptation
Addressing Urgent Five coastal Restoration of 561 hectares of (UNEP, 2020)
Coastal Adaptation communities in wetland, mangroves and other
Needs and Capacity Angola ecological habitats to promote flood
Gaps in Angola defence and mitigate the threat of
drought.
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Green City Kigali Kigali (Rwanda) 600 hectares planned (SWECO, 2019)
2016- neighbourhood which integrates
green building and design, efficient
and renewable energy, recycling
and inclusive living.
Urban Natural Assets Kampala Preservation of natural buffers to (World Bank, 2015)
for Africa - Rivers for (Uganda) enhance the protective functions
Life offered by natural ecosystems that
support disaster resilience benefit.
1
2
3 For green infrastructure to be successful, however, sustainable landscapes and regions require both
4 stewardship and management at multiple levels of governance and social scales (Brink et al., 2016).
5
6 Currently planned climate change adaptation to coastal hazards in Africa's large coastal cities has mainly
7 been achieved through expensive coastal engineering efforts such as sea walls, revetments, breakwaters,
8 spillways, dikes and groynes. Examples are found in West Africa (Adelekan, 2016; Alves et al., 2020).
9 Beach nourishment efforts have also been undertaken in Egypt, Banjul and Lagos (Frihy et al., 2016; Alves
10 et al., 2020). However, the use of vegetated coastal ecosystems presents greater opportunities for African
11 cities because of the lower costs (Duarte et al., 2013).
12
13 Most (>80%) of Africa's large coastal cities have no adaptation policies and, where available, these are
14 mostly, except for South Africa, dominated by national plans (Olazabal et al., 2019). Coastal adaptation
15 actions minimally consider socioeconomic projections and are not at all aligned with future climate scenarios
16 and risks, which is highly limiting for adaptation planning (Olazabal et al., 2019).
17
18 9.9.5.2 Anticipated Adaptation and Residual Risk for Human Settlements
19
20 Africa's smaller towns and cities have received far less scholarly and policy development attention for
21 adaptation (Clapp and Pillay, 2017; White and Wahba, 2019). Smaller towns also have less ability to partner
22 effectively with private entities for adaptation initiatives (Wisner et al., 2015). Political will to address
23 climate change and information flows between key stakeholders, professional and political decision-makers
24 may be easier to establish in smaller cities than in the megacity context (Wisner et al., 2015).
25
26 Exposure and vulnerability are particularly acute in informal areas, making coordinated adaptation
27 challenging. Yet, there is growing recognition of the potential for bottom-up adaptation that embraces
28 informality in order to more effectively reduce risk (Taylor et al., 2021a) (Figure 9.31). This can provide an
29 opportunity for change towards more risk-sensitive urban development and transformative climate
30 adaptation (Leck et al., 2018). Addressing social vulnerability is particularly important for ensuring the
31 resilience of populations at risk. Improved monitoring, modelling and communication of climate risks is
32 needed to reduce the impacts of climate hazards (Tramblay et al., 2020; Cole et al., 2021a).
33
34
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Climate hazard affecting the highest Actions to reduce Actions to reduce Vulnerability context
number of people per country (2000-2019) Hazards Vulnerability of informal settlements
in Africa
� Ecosystem-based � Comprehensive in situ Currently,
measures to reduce community upgrading � 189 million people (59%)
riparian and coastal � Ameliorate flood desert of urban population live
flooding. conditions in informal settlements
� Mangroves alleviate � Actions to reduce � 72% of non-agricultural
coastal storm energy discrimination employment in the
� Water reservoirs to � High quality health care informal sector.
buffer low-flows and � Insurance � 78% of residential areas
Drought water scarcity � Clarification of land developed between
Extreme temp. tenure 1990 and 2014.
Flood Projected,
Storm � Cost of water, electricity
and transport delays
US$300 million per year
� 3 x urban population by
2050
� 4x physical footprint by
2050
� Africa needs to spend
Adaptation Actions to reduce US$ 130-170 million per
Pathways Risk year on basic
infrastructure delivery
� Pooling (e.g. knowledge, care, � Cooling spaces � 1.2 billion people will live
space, income and labour) during heatwaves in informal settlements
by 2050.
� Diversification of livelihoods � Access to clean
� Mobility and migration drinking water and Limits to Actions to reduce
� Rationing over time / community sanitation Adaptation Exposure
saving schemes � Effective Disaster Physical, ecological, � Risk sensitive land use planning
� Early warning systems
� Intensification (e.g. crop Risk Reduction technological, economic, � Evacuation routes
� Maintained storm surface drains
production) � Access to clean, political, institutional, � Hazard proof housing infrastructure
� Transport infrastructure
� Material and symbolic exchange reliable renewable psychological, and/or
� Innovation and energy socio-cultural.
� Reconfiguration of ideologies � Watershed
1 management
2 Figure 9.31: Key elements of adaptation in informal settlements in Africa. Adapted from (Thorn et al., 2015; Fedele et
3 al., 2019; Satterthwaite et al., 2020)
4
5
6 9.9.5.3 Anticipated Adaptation for Transport Systems in Africa
7
8 Higher costs will be incurred to maintain and repair damages caused to existing roads as a result of climate
9 change for countries with no adaptation policy for transport infrastructure (very high confidence)
10 (Chinowsky et al., 2013; Cervigni et al., 2017; Koks et al., 2019). Countries with a greater percentage of
11 unpaved roads will, however, incur higher economic costs through adaptation policy when compared to no
12 adaptation policy (Cervigni et al., 2017).
13
14 Adaptation measures in the transport sector have focused on the climate resilience of road infrastructure.
15 Modelling suggests that proactive adaptation of road designs to account for temperature increases is a `no
16 regret' option in all cases, but accounting for precipitation increases should be assessed on a case-by-case
17 basis (medium confidence) (Cervigni et al., 2017). African governments will need climate adaptation
18 financing options to meet the higher capital requirements of resilient road infrastructure interventions
19 (Hearn, 2016).
20
21 Under the Nationally Appropriate Mitigation Action (NAMA) programme, investments in public transport
22 and transit-oriented development are highlighted as desired mitigation-adaptation interventions within cities
23 of South Africa, Ethiopia and Burkina Faso (UNFCCC, 2020). These interventions simultaneously reduce
24 the vulnerability of low-income residents to climate shocks, prevent lock-ins into carbon-intensive
25 development pathways and reduce poverty (high confidence) (Hallegatte et al., 2016; Rozenberg et al.,
26 2019). The combined mitigation-adaptation interventions in the land use transport systems of African cities
27 are also expected to have sufficient short-term co-benefits (reducing air pollution, congestion and traffic
28 fatalities) to be `no regret' investments (very high confidence) (Hallegatte et al., 2016; Rozenberg et al.,
29 2019). Only eight African countries have transport-specific adaptation measures in their NDCs (Nwamarah,
30 2018). Five African countries have submitted National Adaptation Plans (NAPs) (Table 9.10).
31
32
33 Table 9.10: Transport sector references in the National Adaptation Plans of five African countries. Source:
34 (Government of Burkina Faso, 2015; Government of Cameroon, 2015; Government of Togo, 2016; Government of
35 Kenya, 2017; Government of Ethiopia, 2019).
Identify Promote Transport-specific adaptation measures
climate transport as a
Country change disaster risk Climate Promote Promote non- Urban land
impacts resilient public motorized use planning
transport transport
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reduction design
measure standards
Burkina Faso X X X X
Cameroon X X
Ethiopia X X X X
Kenya X
Togo X X
1
2
3 9.9.5.4 Projected Adaptation for Electricity Generation and Transmission in Africa
4
5 Most electricity infrastructure in Africa has been designed to account for historical climatic patterns. Failure
6 to take into account future climate scenarios in power system planning increases the climate risk facing
7 infrastructure and supplies. Yet, energy demand for cooling over Africa, for example, is expected to increase,
8 with a potential increase in heat stress, population growth and rapid urbanisation to 1.2% of total final energy
9 demand by 2100 compared to 0.4% in 2005 (Parkes et al., 2019). Integrated energy system costs from
10 increased demand for cooling to mitigate heat stress are projected to accumulate from 2005 to USD 51.3
11 billion by 2035 at 2 and to USD 486.5 billion by 2076 at 4 global warming (Parkes et al., 2019).
12
13 For hydropower, adaptations to different climate conditions can be made at the level of the power plant,
14 turbine size and reservoir storage capacities, and can be adjusted to projected hydrological patterns (Lempert
15 et al., 2015). At the river basin level, integrated water resource management practices can be implemented
16 across sectors that compete for the same water resources (Howells et al., 2013). At the power system level,
17 the energy mix and the protocol through which different power plants are dispatched can be adapted to
18 different climate scenarios (Spalding-Fecher et al., 2017; Sridharan et al., 2019).
19
20 Given the uncertainty around future hydroclimate conditions, hydropower development decisions carry risk
21 of `regrets' (that is, damages or missed opportunities) when a different climate than was expected
22 materialises. `Robust adaptation' refers to an adaptation strategy that balances risks across different climate
23 scenarios (Cervigni et al., 2015) (Cross-Chapter Box DEEP in Chapter 17). Development bank lending
24 principles require consideration of the regional picture and interactions with other developments along a
25 river when they determine the social and environmental impacts of the proposed hydropower project.
26 However, these principles often do not explicitly consider climate change, so the risk of reoccurring drought-
27 induced hydropower shortages could be missed (Box 9.5).
28
29 Lastly, given the degree to which hydropower competes with other sectors and ecosystems for the same
30 water resources, it is critical that hydropower planning and adaptation does not occur in isolation. As
31 discussed in Section 9.7, it must be part of an integrated water management system that balances the needs of
32 different water-reliant sectors with other societal and ecological demands under increasingly variable climate
33 and hydrological conditions (Section 9.7.3).
34
35
36 9.10 Health
37
38 The health section is organised by disease or health outcome, with observed impacts and projected risks
39 described for each condition. All adaptation options are presented at the end of the section, highlighting
40 prevention and preparedness, community engagement and disease-specific adaptation options.
41
42 9.10.1 The Influence of Social Determinants of Health on the Impacts of Climate Change
43
44 The social determinants of health are `the conditions in which people are born, grow, live, work and age' as
45 well as the drivers of these, including the social circumstances which profoundly affect health and drive
46 health disparities (Commission of Social Determinants of Health, 2008; Gurewich et al., 2020). Social
47 features (e.g., health-related behaviours), socioeconomic factors (e.g., income, wealth and education) and
48 environmental determinants (e.g., air or water quality) are critical for shaping health outcomes. These factors
49 are inextricably linked (Schulz and Northridge, 2004; Moore and Diaz, 2015) and are largely outside the
50 domain of the health sector. Climate change is already challenging the health and well-being of African
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1 communities, compounding the effects of underlying inequalities (high confidence). The interlinkage
2 between climate change and social determinants of health are largely discussed at a global level
3 (Commission of Social Determinants of Health, 2008), or for developed countries (Ahdoot et al., 2015; Levy
4 and Patz, 2015; Department of Economic and Social Affairs, 2016), with scant evidence for Africa.
5 Nevertheless, there is robust evidence that the health impacts of climate change disproportionately affect the
6 poorest people and children and, in some situations, can differ by gender and age (St Louis and Hess, 2008;
7 Nyahunda et al., 2020; Ragavan et al., 2020) (see Box 9.1). Unequal access to health care particularly affects
8 rural communities (Falchetta et al., 2020), vulnerable women and children (Wigley et al., 2020a) and
9 challenges the achievement of development priorities such as universal health care access (SDG 3) (Weiss et
10 al., 2020).
11
12 9.10.2 Observed Impacts and Projected Risks
13
14 Climate change is already impacting certain health outcomes in Africa (e.g. temperature-related mortality)
15 and risks for most (but not all) health outcomes are projected to increase with increasing global warming
16 (Figure 9.32), with young children (<5 years old), the elderly (>65 years old), pregnant women, individuals
17 with pre-existing morbidities, physical labourers and people living in poverty or affected by other
18 socioeconomic determinants of health being the most vulnerable (high confidence). Women may be more
19 vulnerable to climate change impacts than men (Chersich et al., 2018; Jaka and Shava, 2018; Adzawla et al.,
20 2019a). Contextualising projected impacts of climate change on health requires an understanding of observed
21 impacts (Figure 9.32). Without management and mitigation, current and projected morbidities and
22 mortalities will put additional strain on health, social and economic systems (Hendrix, 2017; Alonso et al.,
23 2019).
24
25
26
27 Figure 9.32: Observed climate impacts and projected climate change risks across African regions for eight key health
28 outcomes. Increased global warming levels are shown relative to pre-industrial 1850�1900. This list of health impacts
29 and risks is not intended to be exhaustive, but instead focusses on well-documented conditions. This assessment is a
30 synthesis across 58 studies on observed impacts and 29 studies on projected risks for health (see Supplementary
31 Material Table SM 9.7). The category of air pollution-related health outcomes includes health impacts from changing
32 particulate matter concentrations due to climate change.
33
34
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1 9.10.2.1 Vector-Borne Diseases
2
3 9.10.2.1.1 Malaria
4
5 Observed impacts
6 Higher temperatures and shifting patterns of rainfall influence the distribution and incidence of malaria in
7 sub-Saharan Africa (high confidence) (Agusto et al., 2015; Beck-Johnson et al., 2017). Up to 10.9 million
8 km2 of sub-Saharan Africa is optimally suitable for year-round malaria transmission (Mordecai et al., 2013;
9 Ryan et al., 2015). Current climate suitability for endemic malaria transmission is concentrated in the central
10 African region, some areas along the Southern coast of West Africa and the East African coast (Ryan et al.,
11 2020).
12
13 In East Africa, there has been an expansion of the Anopheles vector into higher altitudes (Gone et al., 2014;
14 Carlson et al., 2019) and increasing incidence of infection with P. falciparum with higher temperatures (high
15 confidence) (Alemu et al., 2014; Lyon et al., 2017). Over Southern Africa, changes in temperature and
16 rainfall are increasing malaria transmission (Abiodun et al., 2018). In West Africa, studies show both
17 positive (Adu-Prah and Kofi Tetteh, 2015; Darkoh et al., 2017) and negative (M'Bra et al., 2018)
18 correlations of malaria incidence with increases in mean monthly temperatures, and an abundance of
19 Anopheles gambiae s.s. associated with mean diurnal temperature (Akpan et al., 2018).
20
21 Malaria incidence and outbreaks in East Africa were linked with both moderate monthly rainfall and extreme
22 flooding (Boyce et al., 2016; Amadi et al., 2018; Simple et al., 2018), and increase one to two months after
23 periods of rainfall in Southern and West Africa (Diouf et al., 2017; Ferr鉶 et al., 2017; Adeola et al., 2019).
24 The years following La Ni馻 events (Southern Africa) (Adeola et al., 2017)) and high relative humidity
25 (West Africa) (Adu-Prah and Kofi Tetteh, 2015; Darkoh et al., 2017) have been positively linked with
26 malaria incidence.
27
28 Projected risks
29 Since AR5, significant progress has been made in understanding how changes in climate influence the
30 seasonal and geographical range of malaria vectors, transmission intensity and burden of disease of malaria
31 across Africa. Yet projecting changes remains challenging given the range of factors that influence
32 transmission and disease patterns, and model outputs contain high degrees of uncertainty (Zermoglio et al.,
33 2019; Giesen et al., 2020). Models have limited ability to account for population changes and development
34 trends (Kibret et al., 2015; Kibret et al., 2017), investments in health sectors and interventions (McCord,
35 2016; Colborn et al., 2018; Caminade et al., 2019), and confounders such as age, socioeconomic status,
36 employment and labour migration and climate variability (Bennett et al., 2016; Karuri and Snow, 2016;
37 Byass et al., 2017; Chuang et al., 2017; Colborn et al., 2018). Nevertheless, available models do allow for
38 projections of malaria transmission under different climate change scenarios to be made with high levels of
39 certainty.
40
41 In East and southern Africa and the Sahel, malaria vector hotspots and prevalence are projected to increase
42 under RCP4.5 and RCP8.5 by 2030 (1.5�1.7癈 global warming) (high confidence) (Leedale et al., 2016;
43 Semakula et al., 2017b; Zermoglio et al., 2019), becoming more pronounced later in the century (2.4�
44 3.9癈 global warming) (Ryan et al., 2020). Under RCP4.5, 50.6�62.1 million people in East and Southern
45 Africa will be at risk of malaria by the 2030s (1.5癈 global warming), and 196�198 million by the 2080s
46 (2.4癈 global warming) (Ryan et al., 2020). Northern Angola, Southern DRC, western Tanzania and central
47 Uganda are predicted to be worst impacted in 2030, extending to western Angola, upper Zambezi River
48 Basin, northeastern Zambia and the East African highlands by 2080 (Ryan et al., 2020). Under rising
49 temperatures, by the 2050s, the greatest shifts in suitability for malaria transmission will be seen in East,
50 Southern and Central Africa (2癈 global warming) (Tonnang et al., 2014; Zermoglio et al., 2019; Ryan et al.,
51 2020).
52
53 Conversely, in some regions, changing climatic conditions are projected to reduce malaria hotspots and
54 prevalence. With continued greenhouse gas emissions, these include: West Africa by 2030 (1.7癈 global
55 warming) (high confidence) (Yamana et al., 2016; Semakula et al., 2017b; Ryan et al., 2020), parts of
56 Southern Central Africa and dryland regions in East Africa by 2050 (2.5癈 global warming) (high
57 confidence) (Semakula et al., 2017b; Ryan et al., 2020), and large areas of southern Central Africa and the
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1 western Sahel by 2100 (>4癈 global warming) (Yu et al., 2015; Tourre et al., 2019). These reductions in
2 transmission correspond with decreasing environmental suitability for the malaria vector and parasite in
3 these regions (Ryan et al., 2015; Mordecai et al., 2020). Most areas in Burkina Faso, Cameroon, Ivory Coast,
4 Ghana, Sierra Leone, Niger, Nigeria, Zambia and Zimbabwe will have almost zero malaria transmission
5 under RCP8.5 (Semakula et al., 2017b; Tourre et al., 2019).
6
7 The El Ni駉-Southern Oscillation (ENSO) cycle currently contributes to seasonal epidemic malaria in
8 epidemic-prone areas (high confidence), and is projected to shift the malaria epidemic fringe southward and
9 into higher altitudes by mid- to end-century (high confidence) (Bouma et al., 2016; Semakula et al., 2017b;
10 Caminade et al., 2019). More evidence is needed, however, of climate variability impacts through ENSO
11 cycles in future risk projections, as well as a deeper understanding of how climate change will impact the
12 length of transmission season for mosquitoes, particularly in areas where increases in spring and autumn
13 temperatures may increase suitability for the reproduction of malaria vectors (Ryan et al., 2020). Other gaps
14 in knowledge include a better understanding of mosquito thermal biology and thermal limits for a variety of
15 species, potential adaptations to extreme temperatures and how landscape changes contribute to malaria
16 transmission (Tompkins and Caporaso, 2016).
17
18 9.10.2.1.2 Mosquito-borne viruses
19
20 Observed impacts
21 Climate variability has driven a global intensification of mosquito-borne viruses (e.g., dengue, Zika and Rift
22 Valley Fever), including expansion into areas with higher altitudes (Leedale et al., 2016; Mweya et al., 2016;
23 Messina et al., 2019). Concerns centre on diseases vectored by the yellow fever mosquito (Aedes aegypti),
24 common throughout most of sub-Saharan Africa, and the tiger mosquito (Aedes albopictus), currently largely
25 confined to western Central Africa (Kraemer et al., 2019; Mordecai et al., 2020).
26
27 Although warming temperatures are largely responsible for increasing environmental suitability for mosquito
28 vectors (Mordecai et al., 2019), droughts can augment transmission when open water storage provides
29 breeding sites near human settlements, and when flooding enables mosquitoes to proliferate and spread
30 viruses further (Mweya et al., 2017; Bashir and Hassan, 2019). Within Africa's rapidly growing cities,
31 diseases vectored by urban-adapted Aedes mosquitoes pose a major threat, especially in West Africa
32 (Zahouli et al., 2017; Weetman et al., 2018; Messina et al., 2019). Dengue virus expansion may cause
33 explosive outbreaks but the burden of dengue haemorrhagic fever and associated mortality is higher in areas
34 where transmission is already endemic (Murray et al., 2013).
35
36 Projected risks
37 Populations of Aedes aegypti and Aedes albopictus mosquitoes and epidemics of dengue and yellow fever
38 and other Aedes-borne viruses are expected to increase, including at high altitudes (Weetman et al., 2018;
39 Messina et al., 2019; Ryan et al., 2019; Gaythorpe et al., 2020; Mordecai et al., 2020). Aedes albopictus may
40 expand beyond western Central Africa into Chad, Mali and Burkina Faso by mid-century at >2癈 global
41 warming (Kraemer et al., 2019). Shifts projected in Aedes range due to changing environmental suitability,
42 combined with rapid urbanisation and population growth, suggest that by 2050 populations exposed to these
43 vectors in Africa may double, and by 2080 nearly triple at >2癈 global warming (Kraemer et al., 2019).
44 Southern limits of dengue transmission in Namibia and Botswana, and the western Sahel, may show the
45 greatest expansions in environmental suitability under 1.8�2.6癈 global warming (Messina et al., 2019).
46 In the warmest scenarios (RCP8.5), however, some parts of Central Africa may become too hot for
47 mosquitoes to transmit dengue, and thus at-risk populations may peak at intermediate warming levels (Ryan
48 et al., 2019). Climatic conditions favourable for mosquitoes, combined with the increase of animal trade,
49 may result in the expansion of the geographic range of zoonotic diseases like Rift Valley fever (Martin et al.,
50 2008), a threat for human and animal health with strong socioeconomic impacts (Peyre, 2015).
51
52 9.10.2.2 Diarrhoeal Diseases, HIV and Other Infectious Diseases
53
54 9.10.2.2.1 Diarrhoeal diseases
55 Observed impacts
56 Africa has the highest rates of death due to diarrhoeal diseases in the world (Havelaar et al., 2015; Troeger et
57 al., 2018) and many children have repeated diarrhoeal episodes with impaired growth, stunting, immune
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1 dysfunction and reduced cognitive performance (Squire and Ryan, 2017). High land and sea temperatures
2 (Paz, 2009; Musengimana et al., 2016) and precipitation extremes increase transmission of bacterial and
3 protozoal diarrhoeal disease agents (Boeckmann et al., 2019) through contamination of drinking water and
4 food preparation and preservation practices (Figure 9.33) (Levy et al., 2016; Soneja et al., 2016; Walker,
5 2018).
6
7 Cholera incidence has been shown to increase with temperature (Tr鎟up et al., 2011). Outbreaks, however,
8 are most frequent in East and Southern Africa following tropical cyclones (Moore et al., 2017b; Troeger et
9 al., 2018; Ajayi and Smith, 2019; Cambaza et al., 2019).
10
11 Africa's rapidly urbanising population increases the demand for freshwater and is occurring in places that
12 already have stretched water and sanitation infrastructure (Howard et al., 2016). These conditions, especially
13 during periods of water scarcity, can reduce the frequency and adequacy of hand washing and thereby
14 increase disease transmission.
15
16 Projected risks
17 Disruptions in water availability, such as during droughts or infrastructure breakdown, will jeopardise access
18 to safe water and adequate sanitation, undermine hygiene practices and increase environmental
19 contamination with toxins (Howard et al., 2016; WWF-SA, 2016; Miller and Hutchins, 2017).
20
21 Climate change is projected to cause 20,000�30,000 additional diarrhoeal deaths in children (<15 years old)
22 by mid-century under 1.5�2.1癈 global warming (WHO, 2014), with West Africa most affected, followed
23 by East, Central and southern Africa. Cholera outbreaks are anticipated to impact East Africa most severely
24 during and particularly after ENSO events (Moore et al., 2017b).
25
26
27
28 Figure 9.33: Pathways to impact: diarrhoeal disease. Schematic showing the pathways of impact diarrhoeal disease
29 in Africa as a result of exposure to climate hazards.
30
31
32 [START BOX 9.6 HERE]
33
34 Box 9.6: Pandemic Risk in Africa: COVID-19 and Future Threats
35
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1 Rapid advances in vaccination and other control measures in high-income countries means that the burden of
2 COVID-19 is increasingly concentrated in low- and middle-income countries, including those in Africa. The
3 extent to which the COVID-19 pandemic is influenced by weather or by future changes in climate remains
4 contested (WMO, 2021). In time, COVID-19 may develop seasonal dynamics (Baker et al., 2020; Kissler et
5 al., 2020) similar to other respiratory infections (Carlson et al., 2020b).
6
7 Early work interpreted low-reported cases of COVID-19 in Africa as suggesting evidence of a protective
8 climatic effect, but increasing evidence indicates the role of climate is secondary to the timing of disease
9 introduction, the pace of implementation of non-pharmaceutical interventions, and surveillance gaps (Evans
10 et al., 2020; WMO, 2021). Going forward, testing coverage, reporting, governance, non-pharmaceutical
11 interventions and vaccine distribution and uptake are likely to be far more significant for Africa's COVID-19
12 trajectory than climate change. Compounding risks, where climate hazards and natural disasters impair
13 outbreak responses, may disrupt interventions or cause additional deaths (Phillips et al., 2020; Salas et al.,
14 2020).
15
16 Emerging and future pandemic threats
17 Future influenza pandemics are highly likely, as are regional epidemics and pandemics of novel zoonotic
18 viruses (including coronaviruses and flaviviruses) (high confidence). In the next decades, climate change will
19 reshape the risk landscape for emerging zoonotic threats as wildlife-livestock-human interfaces shift,
20 facilitating the emergence of novel zoonotic threats and spillover of known zoonoses into novel geographies
21 (Carlson et al., 2020a; Mordecai et al., 2020). Characteristics of urban development and level of service
22 provision, for example, crowded living spaces and transport facilities, and access to water and sanitation will
23 influence the transmission of COVID-19 and future disease outbreaks (Wilkinson, 2020). Historically, West
24 and Central Africa were considered especially at risk of outbreaks given their high biodiversity, high
25 intensity of human-wildlife contact including wild meat trade, vulnerable health systems and history of
26 Ebola virus disease outbreaks (Paige et al., 2014; Allen et al., 2017; Pigott et al., 2017). However, as the
27 Middle East respiratory syndrome coronavirus (MERS-CoV) and COVID-19 pandemics have shown, there
28 are multiple hotspots of viruses with pandemic potential globally, many of which are not in Africa. Thus,
29 labelling African rainforests as unique `hotspots' undermines global health work and pandemic
30 preparedness.
31
32 [END BOX 9.6 HERE]
33
34
35 9.10.2.2.2 HIV
36 Observed impacts
37 Although levels of new HIV infections declined sharply during the last decade, still more than a million
38 adults and children become infected each year (UNAIDS, 2020). Climate influences on HIV are
39 predominately indirect such as through heightened migration due to climate variability, or extreme weather
40 events leading to increased transactional sex to replace lost sources of income. Changes in climate affect
41 each of the main drivers of HIV transmission in women, including poverty, inequity and gender-based
42 violence (Burke et al., 2015a; Loevinsohn, 2015; Fiorella et al., 2019).
43
44 Projected risks
45 `Oscillating' or `circular' migration for migrant workers in urban and mining centres drove HIV transmission
46 in the 1990s and 2000s (Lurie, 2006), and climate-related displacement may have similar effects (see Box
47 9.7) (Gray and Mueller, 2012; Loevinsohn, 2015; Low et al., 2019). Food insecurity and nutritional
48 deficiencies, projected to increase with increasingly variable climates, has been shown to increase sexual
49 risk-taking and migration, as well as increase susceptibility to other infections (Lieber et al., 2021). Projected
50 increases in exposure to infectious diseases pose considerable threats to HIV-infected people who may
51 already have compromised immune function. Additionally, reduced lung function in people with HIV from
52 previous tuberculosis infection may put them at high risk for morbidity and death during extreme heat
53 (Abayomi and Cowan, 2014). Moreover, extreme weather events accompanied by damage to health system
54 infrastructure could compromise the continuity of antiretroviral treatment (Weiser et al., 2010; Pozniak et al.,
55 2020).
56
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1 9.10.2.2.3 Other infectious diseases
2 Poor populations in the western Sahel have the highest burden of bacterial meningitis worldwide, with
3 seasonal dynamics driven by the dry Harmattan winds that transport dust long distances across the continent
4 (Agier et al., 2013; Garc韆-Pando et al., 2014). In Nigeria, rising temperatures are projected to increase
5 meningitis cases by about 50% for 1.8癈 global warming (RCP2.6 in 2060�2075), and by almost double for
6 3.4癈 global warming (RCP8.5 in 2060-2075) (Abdussalam et al., 2014). Bilharzia is also highly climate-
7 sensitive, with its distribution influenced by changes in temperature and precipitation, as well as
8 development, such as the introduction of freshwater projects (e.g., canals, hydroelectric dams and irrigation
9 schemes) (Adekiya et al., 2019).
10
11 9.10.2.3 Temperature-Related Impacts
12
13
14
15 Figure 9.34: Pathways to impact: heat-related morbidities. Schematic showing the pathways of impact for heat-related
16 morbidities in Africa as a result of exposure to climate hazards. Numbers in the figure refer to chapter sections of this
17 report. Indirect health impacts of heat are not shown. For example, risk of malnutrition from reduced crop yields or
18 reduced fisheries catches (see Section 9.8.5).
19
20
21 9.10.2.3.1 Mortality and morbidity
22 Observed impacts
23 Emergency department visits and hospital admissions have been shown to increase at moderate to high
24 temperatures (Bishop-Williams et al., 2018; van der Linden et al., 2019), with increased levels of mortality
25 recorded on days with raised temperatures in Burkina Faso (Kynast-Wolf et al., 2010; Diboulo et al., 2012;
26 Bunker et al., 2017), Ghana (Azongo et al., 2012), Kenya (Egondi et al., 2012; Egondi et al., 2015), South
27 Africa (Wichmann, 2017; Scovronick et al., 2018), Tanzania (Mrema et al., 2012) and Tunisia (Bettaieb et
28 al., 2010; Leone et al., 2013). Cause of death most commonly involves cardiovascular diseases (Kynast-Wolf
29 et al., 2010; Scovronick et al., 2018), but increased incidences of respiratory (Scovronick et al., 2018), stroke
30 (Longo-Mbenza et al., 1999) and non-communicable diseases (Bunker et al., 2017) have also been linked
31 with heat.
32
33 Excess death rates from non-optimal temperature in sub-Saharan Africa are estimated to be nearly double the
34 global average, with 24% of the more than 5 million annual deaths associated with non-optimal temperature
35 occurring in Africa (Zhao et al., 2021). The region had the world's highest cold-related excess death ratio
36 and lowest heat-related excess death ratio over the period 2000�2019. However, during this time, cold-
37 related excess deaths declined more rapidly than the increase in heat-related excess deaths, resulting in a net
38 decrease in the excess death ratio from temperature.
39
40 Recent estimates of the burden of mortality associated with the additional heat exposure from recent human-
41 induced warming suggest approximately 43.8% of heat-related mortality in South Africa was attributable to
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1 anthropogenic climate change from 1991�2018 (Vicedo-Cabrera et al., 2021). In many of South Africa's 52
2 districts, this equates to dozens of deaths per year. The elderly and children under five years are most
3 vulnerable to heat exposure (Sewe et al., 2015; Scovronick et al., 2018).
4
5 Projected risks
6 Globally, Africa is predicted to suffer disproportionately higher all-cause mortality risk from higher
7 temperature-related all-cause mortality from global warming, compared to temperate, Northern Hemisphere
8 countries (Carleton et al., 2018). The number of days projected to exceed potentially lethal heat thresholds
9 per year reaches 50�150 days in West Africa at 1.6癈 global warming, up to 200 days in West Africa and
10 100�150 days in Central Africa and parts of coastal East Africa at 2.5癈, and over 200 days for parts of
11 West, Central and East Africa for >4癈 global warming (Mora et al., 2017) (see Sections 9.5.3�7; Figure
12 9.15). Projected rates of heat-related mortality among people in the Middle East and North Africa who are
13 older than 65 years increase by 8�20 fold in 2070�2099, compared with 1951�2005, based on RCP4.5 and
14 RCP8.5 (both at >2癈 global warming) (Ahmadalipour and Moradkhani, 2018).
15
16 Temperature-related mortality across Africa is projected to escalate with global warming, reaching 50�180
17 additional deaths per 100,000 people annually in regions of North, West, and East Africa for 2.5癈 global
18 warming, and increasing to 200-600 per 100,000 people annually for 4.4癈 global warming (Carleton et al.,
19 2018) (Figure 9.35). However, some regions that currently experience cold-related mortality (e.g., Lesotho
20 and Ethiopian highlands) are projected to have reduced temperature-related mortality risk from warming.
21 Greenhouse gas mitigation is projected to save tens of thousands of lives: limiting warming to RCP4.5
22 (2.5癈) rather than RCP8.5 (4.4癈) at the end of the century is projected to avoid on average 71 deaths per
23 100,000 people annually across Africa with larger reductions in risk in North, West, Central and parts of East
24 Africa (Figure 9.35). The cost of mitigating heat stress using energy-intensive cooling methods is expected
25 to be to be unachievable for many African countries (Parkes et al., 2019) (see Section 9.9.4).
26
27
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1
2 Figure 9.35: Temperature-related mortality risk in Africa with increased global warming. Maps showing changes in
3 mortality rates in deaths per 100 000 for global warming in the years 2020�2039, 2040�2059, and 2080�2099 for (a)
4 medium emissions scenario (RCP 4.5); (b) a high emissions scenario (RCP 8.5); and (c) showing avoidable deaths due
5 to increased emissions mitigation to achieve reduced global warming (RCP4.5璕CP8.5). These estimates of climate
6 change impacts on mortality rates include temperature-related impacts only. They account for the benefits of income
7 growth and incremental adaptation to climate change, both of which reduce mortality sensitivity to extreme
8 temperatures. Projections were based on income and demographics from Shared Socioeconomic Pathway 3 (SSP3),
9 with future adaptation based on adaptation actions observed in the global historical record. The estimates do not include
10 the costs of the behaviours and investments required to achieve such adaptation (Carleton et al., 2018). Areas shown in
11 green in c) have fewer deaths due to temperature under RCP8.5 than RCP4.5. This is because cold is currently the
12 greatest driver of temperature-related deaths in these countries, which will be alleviated with increasing levels of global
13 warming (Zhao et al., 2021).
14
15
16 9.10.2.3.2 Heat stress in specific settings
17 Heat stress symptoms are prevalent among people in buildings that are poorly ventilated or insulated, or
18 constructed with unsuitable materials (e.g., corrugated metal sheeting). These features are common to many
19 structures in Africa, including in slums, informal and low-income settlements, as well as schools and
20 healthcare facilities (Bidassey-Manilal et al., 2016; Naicker et al., 2017; Wright et al., 2019). Temperatures
21 inside these structures can exceed outdoor temperatures by 4 or more and have large diurnal fluctuations
22 (Mabuya and Scholes, 2020). Daily wage labourers and residents of urban informal settlements are among
23 the most vulnerable to heat stress because of the urban heat island effect, with congestion, little ventilation,
24 shade, open space and vegetation (Bartlett, 2008) being associated with impacts of both hot and cold
25 conditions on public health (Ramin, 2009), and the number of years lived depending on age, sex and
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1 comorbidities (Egondi et al., 2015). Temperature extremes are likely to result in relatively more deaths in
2 informal settlements than in other settlement types (Scovronick and Armstrong, 2012).
3
4 The urban heat island effect exacerbates current and projected heat stress in Africa's rapidly growing cities
5 (Mitchell, 2016) and is discussed in more detail in Section 9.9.3.
6
7 Escalating temperatures and longer-duration heatwaves are likely to heavily affect workers already exposed
8 to extreme temperatures, e.g., outdoor workers (Kjellstrom et al., 2018) and miners (El-Shafei et al., 2018;
9 Nunfam et al., 2019a; Nunfam et al., 2019b). Vulnerability may also be high for women who cook food for a
10 living, and children who accompany them, due to prolonged exposure to high temperatures (Parmar et al.,
11 2019). Prisons, commonly poorly ventilated and overcrowded, are also high-risk settings (Van Hout and
12 Mhlanga-Gunda, 2019).
13
14 9.10.2.3.3 Maternal and child health
15
16 Exposure to high temperatures during pregnancy has been linked with adverse birth outcomes, including
17 stillbirths or miscarriages (Asamoah et al., 2018) and long-term behavioural and developmental deficiencies
18 (Duchoslav, 2017; MacVicar et al., 2017).
19
20 9.10.2.4 Impacts of Extreme Weather
21
22 During extreme conditions, for example, Cyclone Kenneth (Codjoe et al., 2020) and El Ni駉 2015-2016
23 (WHO, 2016; Pozniak et al., 2020), direct physical injury, loss of life, destruction of property and population
24 displacement can occur. Flooding and landslides are common after extreme rainfall and are the most
25 frequently described impact of climate variability in Africa's cities currently, with residents of poorly
26 serviced or informal settlements most vulnerable (Hunter et al., 2020). Post-traumatic stress disorders in
27 affected individuals are common, including in children (Rother, 2020). In rural areas, the resulting damage to
28 health facilities, access routes and transport services can severely compromise health service delivery
29 (WHO, 2016). The effects of extreme weather on urban health infrastructure depends on the characteristics,
30 location and adaptive capacity of cities (see Section 9.9.4).
31
32 9.10.2.5 Malnutrition
33
34 Observed impacts
35 Africa has experienced the greatest impacts of climate change on acute food insecurity and malnutrition
36 (FAO and ECA, 2018). Adverse climatic conditions exacerbate the impacts of an unstable global economy,
37 conflict and pandemics on food insecurity (AfDB, 2018b; Food Security Information Network (FSIN), 2019;
38 Fore et al., 2020) (see Chapter 5, Section 5.12.4).
39
40 More than 250 million Africans are undernourished, mostly in Central and East Africa (FAO et al., 2020),
41 which increases childhood stunting, affects cognition and has trans-generational sequelae (IFPRI, 2016;
42 UNICEF et al., 2019). Undernutrition is strongly linked with hot climates (Hagos et al., 2014; Tusting et al.,
43 2020). In Burkina Faso, low crop yields resulted in around 110 deaths per 10,000 children under five, with
44 72% of this impact attributable to adverse climate conditions in the growing season (Belesova et al., 2019).
45
46 Increasing incidence and expanded distributions of vector-borne livestock diseases (e.g., bluetongue,
47 trypanosomiasis and Rift Valley Fever) in response to changes in rainfall and increasing temperatures,
48 undermine food security, especially among subsistence farmers (Samy and Peterson, 2016; Caminade et al.,
49 2019). Locust infestations linked with changes in climate (Salih et al., 2020) are a major risk for food
50 security in Africa.
51
52 Projected risks
53 Projected risks for malnutrition in Africa are high (FAO, 2016) (see Section 9.8.1): 433 million people in
54 Africa are anticipated to be undernourished by 2030 (FAO et al., 2020) and, compared to 1961�1990, 1.4
55 million additional African children will suffer from severe stunting by 2050 under 2.1癈 global warming
56 (WHO, 2014). In Burkina Faso, the mortality burden due to low crop yields could double by 2100 with
57 1.5癈 of global warming (Belesova et al., 2019). Drought risks will include crop and livestock failures
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1 (Ahmadalipour et al., 2019). Additionally, increasing concentrations of atmospheric CO2 will affect the
2 nutritional quality of C3 plant staples, lowering levels of protein and minerals like zinc and iron (Myers et al.,
3 2014; Weyant et al., 2018). Declining fish catches due to ocean warming, illegal fishing and poor stock
4 management are projected to increase deficiencies of zinc, iron and vitamin A for millions of people across
5 Mozambique, Angola and multiple West African countries (Golden et al., 2016) (see Section 9.8.5).
6
7 9.10.2.6 Non-Communicable Diseases and Mental Health
8
9 Links between climate change and the environmental risk factors for non-communicable diseases (NCDs)
10 may be direct (e.g., extreme heat exposure in people with cardiovascular disease) or indirect, such as via the
11 global agriculture and food industry (Landrigan et al., 2018). These effects are largely unreported for Africa
12 (Amegah et al., 2016), where the burden of many NCDs is growing rapidly with increasing urbanisation and
13 pollution (Rother, 2020).
14
15 Many urban poor populations have unhealthy dietary practices, which present major risks for obesity, type II
16 diabetes and hypertension. Paradoxically, despite growing levels of undernutrition, the incidence of
17 overweight and obesity continues to rise in Africa, particularly in children under five from the northern and
18 southern parts of the continent (FAO and ECA, 2018). Diabetes is increasingly prevalent and outcomes may
19 worsen if climate change undermines health infrastructure and the range of available foods (Keeling et al.,
20 2012; Kula et al., 2013; Chersich and Wright, 2019).
21
22 The relationship between cancer and climate change is complex and indirect. Changing temperature and
23 humidity may alter the distribution of Aflatoxin-producing fungi, contaminating food (grains, maize) and
24 causing cancer (see Box 5.9 in Chapter 5) (Sserumaga et al., 2020; Valencia-Quintana et al., 2020). Severe
25 storms and flooding may disrupt wastewater treatment or disposal, potentially contaminating drinking water
26 with carcinogenic substances.
27
28 Areas with low service provision (e.g., informal settlements in Africa) suffer from increased infestations of
29 pests such as flies, cockroaches, rats, bedbugs and lice, which may be controlled by chemical pesticides
30 (Rother et al., 2020) and may become more prevalent with a changing climate (Mafongoya et al., 2019).
31 Inappropriate pesticide use and disposal cause endocrine disruption and increased incidences of some
32 cancers (Rother et al., 2020).
33
34 9.10.2.6.1 Mental health and well-being
35 Mental health and well-being are affected by local climate conditions and are therefore sensitive to climate
36 change (Burke et al., 2018b; Obradovich et al., 2018). High temperatures are strongly associated with poor
37 mental health and suicide in South Africa (Kim et al., 2019). Exposure to extreme heat directly influences
38 emotional control, aggression and violent behaviour, escalating rates of interpersonal violence, with
39 homicides rising by as much as 18% in South Africa when temperatures are above 30 compared with
40 temperatures below 20 (Burke et al., 2015a; Chersich et al., 2019b; Gates et al., 2019).
41
42 Extreme weather events are often severely detrimental to mental health (Scheerens et al., 2020), with
43 elevated rates of anxiety, post-traumatic stress disorder and depression in impacted individuals (Schlenker
44 and Lobell, 2010; Nuvey et al., 2020). Youth may be at especially high risk (Barkin et al., 2021).
45
46 Loss of livestock from disease or lack of pastures is strongly linked with poor mental health among farmers
47 (Nuvey et al., 2020). Climate change impacts on mental health among refugees is concerning but remains
48 under-researched (Matlin et al., 2018).
49
50 9.10.2.7 Air Quality-Related Health Impacts
51
52 Links between air quality and climate change are complex (Smith et al., 2014; Szopa et al., 2021). Increases
53 in particulate matter concentrations are driven more by vehicle emissions, solid waste, biomass burning and
54 development (Abera et al., 2021) than by climate change, and these factors vary widely across regions of the
55 continent (West et al., 2013). Women and children who are exposed to high particulate matter concentrations
56 when cooking indoors and HIV-infected people are more vulnerable to the health impacts of air pollution
57 (Abera et al., 2021). Information on the direction of change of air quality in different African regions
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1 attributable to climate change are contradictory (Westervelt et al., 2016; Silva et al., 2017). Additionally,
2 much uncertainty remains about interactions between air quality and climate change and relative impacts of
3 different modes of development and climate change on pollutants. However, increasing temperatures
4 combined with a reduction in rainfall are likely to increase particulate matter concentrations (Abera et al.,
5 2021), particularly in North Africa (Westervelt et al., 2016; Silva et al., 2017).
6
7 Nevertheless, continued dependence on fossil-fuelled power plants will result in tens of thousands of
8 avoidable deaths due to air pollution by 2030 (Marais and Wiedinmyer, 2016), and accelerate climate
9 change. Actions to reduce air pollution can both mitigate climate change and have major co-benefits for
10 health (West et al., 2013; Rao et al., 2016; Markandya et al., 2018; Rauner et al., 2020a; Rauner et al.,
11 2020b) (see also AR6 WGIII, Chapters 3, 4, 8 and 10). Investing in renewable energy resources rather than
12 reliance on the combustion of fossil fuels would mark an important step forward for African population
13 health (Marais et al., 2019). This is especially important in South Africa which emits approximately half the
14 total carbon emissions for Africa, ranking 12th in the world for carbon emissions (Mohsin et al., 2019).
15
16 Dust events in West Africa have severe health impacts (cardiorespiratory and infectious diseases, including
17 meningitis) (Ayanlade et al., 2020) given the proximity of the Sahara, which produces about half of the
18 yearly global mineral dust (de Longueville et al., 2013). Wildfires are projected to become the main source
19 of particulate matter in West, Central and southern Africa under both the lowest and highest future emissions
20 scenarios, whereas, under intermediate scenarios (i.e., SSP3/RCP4.5), anthropogenic sources of particulate
21 matter are projected to exceed that produced by wildfires (Knorr et al., 2017).
22
23
24 [START BOX 9.7 HERE]
25
26 Box 9.7: The Health-Climate Change Nexus in Africa
27
28 The intersections between climate change and human health are involve interactions of numerous systems
29 and sectors (Lindley et al., 2019; Yokohata et al., 2019). This complexity means that holistic,
30 transdisciplinary and cross-sectoral (systems) approaches like One Health, EcoHealth and Planetary Health
31 can improve the long-term effectiveness of responses to health risks (Zinsstag, 2012; Whitmee et al., 2015;
32 Nantima et al., 2019). More research is needed to identify sustainable solutions (Rother et al., 2020), as
33 recently re-emphasised by the Intergovernmental Panel on Biodiversity in its report on the COVID-19
34 pandemic (IPBES, 2020). The close dependency of many Africans on their livestock and surrounding
35 ecosystems forms a context where integrated health approaches are especially critical for addressing climate
36 change risks to health (Figure Box 9.7.1) (Watts et al., 2015; Ciss�, 2019).
37
38
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1
2 Figure Box 9.7.1: Human, ecosystem and animal health are intimately interlinked, and require transdisciplinary
3 approaches such as One Health, EcoHealth and Planetary Health for effective, sustainable, long-term management. This
4 schematic shows some examples of these interlinkages, and how they impact human health, highlighting the complex
5 interactions and the importance of holistic, systems approaches to health interventions, including for climate change
6 adaptation. Supporting literature: 1 (Egoh et al., 2012); 2 (Wangai et al., 2016); 3 (Failler et al., 2018); 4 (Ifejika
7 Speranza, 2010); 5 (Brancalion et al., 2020); 6 (Bloomfield et al., 2020); 7 (Rojas-Downing et al., 2017).
8
9
10 Integrated approaches to health in Africa can deliver multiple benefits for humans and ecosystems For
11 example, rather than addressing micronutrient deficiencies with supplements, which may not be accepted
12 culturally and can be disrupted by stockouts or similar, addressing nutrient deficiencies in staple crops by
13 selecting or breeding more nutritious varieties (e.g., orange-fleshed sweet potatoes or `golden rice' for
14 vitamin A deficiency) may prove to be more sustainable options (Datta et al., 2003; Nair et al., 2016; Laurie
15 et al., 2018; Oduor et al., 2019; Stokstad, 2019). Additionally, some micro- or macronutrient deficiencies and
16 food insecurities may be improved by addressing the depletion of soils through better management,
17 including the incorporation of holistic, sustainable principles, such as those promoted by agroforestry or
18 regenerative agriculture (Rhodes, 2017; Elevitch et al., 2018; LaCanne and Lundgren, 2018) (5.12.4).
19
20 [END BOX 9.7 HERE]
21
22
23 9.10.3 Adaptation for Health and Well-Being in Africa
24
25 In this section, we focus on adaptation actions that are well-documented or shown to have the potential for
26 substantially improving health or well-being. These adaptation options are assessed in Figure 9.36 and Table
27 9.11.
28
29 In Africa, adaptive responses have begun to be implemented by local, national and international entities (Ebi
30 and Otmani Del Barrio, 2017). With strong leadership, these initiatives can be used as an opportunity for
31 comprehensive, transformative change rather than incremental improvements to existing systems. Adaptation
32 responses are necessarily context-specific and can focus on providing services for vulnerable and high-risk
33 populations (Dumenu and Obeng, 2016; Herslund et al., 2016).
34
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1 Adaptation actions in the health sector range from building resilient health systems to preparing responses to
2 health impacts of extreme weather events to reducing effects of increasing temperatures in residential and
3 occupational settings (Kjellstrom et al., 2016; Chersich and Wright, 2019). A climate-resilient health system
4 involves functional and effective health systems (WHO, 2015), national and local policy plans with
5 resources for implementation, and long- and short-term communication strategies to raise awareness around
6 climate change (Nhamo and Muchuru, 2019).
7
8 Many health conditions associated with climate change are not new, and existing evidence-based
9 interventions can be modified to address shifting disease patterns (Ebi and Otmani Del Barrio, 2017).
10 Adaptation options can build on a long tradition of community-based services in Africa (Ebi and Otmani Del
11 Barrio, 2017). Indeed, strengthening many of the services already provided (e.g., childhood vaccinations and
12 vector control) will help curtail emerging burdens of climate-sensitive conditions. However, a
13 disproportionate focus on emerging zoonotic and vector-borne viruses could undermine climate change
14 adaptation efforts in Africa if it shifts the focus away from health system strengthening and leaves few
15 resources for addressing other health impacts of climate change.
16
17 Core components of an adaptation response include rapid impact packages (e.g., mass drug administration
18 for schistosomiasis), education of women and direct poverty alleviation (Bailey et al., 2019). Where droughts
19 are more frequent and rainfall patterns have shifted, adaptation support can be provided for strategies
20 developed by communities, including the adaptation of livelihoods and diversification of crops and livestock
21 (Mbereko et al., 2018; Bailey et al., 2019). Continued efforts through partnerships, blending adaptation and
22 disaster risk reduction, and long-term international financing are needed to bridge humanitarian and
23 sustainable development priorities (Lindley et al., 2019) (Cross-Chapter Box HEALTH in Chapter 7).
24
25 9.10.3.1 Risk Assessment and Warning Systems
26
27 Improved institutional capacity for risk monitoring and early warning systems is key to support emergency
28 preparedness and responsiveness in Africa, as well as shock-responsive and long-term social protection
29 (FAO and ECA, 2018). Climate risk assessments grounded in evidence and locally appropriate technologies
30 are important for identifying priority actions, the scale of intervention needed and high-risk geographical
31 areas and populations. Potential tools include those developed by WHO (Ceccato et al., 2018) and the
32 Strategic Tool for Analysis of Risk (Ario et al., 2019).
33
34 Warning systems that predict seasonal to intra-seasonal climate risks could assist in improving response
35 times to extreme weather events (such as droughts, flooding or heat waves) and shifts in infectious diseases.
36 Weather and other types of forecasting provide an advanced warning � a central tenet of disaster risk
37 reduction (Funk et al., 2017; Okpara et al., 2017a; Lumbroso, 2018). Models encompassing each component
38 of the human-animal-environmental interface, including disease surveillance in humans and animals and
39 remote sensing of vegetation indexes, water and soil can be used to project patterns of zoonose outbreaks
40 (UNDP, 2016; Bashir and Hassan, 2019; Durand et al., 2019). Early warning systems may help better
41 prepare for these and other forms of infectious disease outbreaks (Thomson et al., 2006) but adaptation is
42 possible in the absence of statistical tools through vaccination and surveillance, for example.
43
44 Surveillance systems for diseases and vectors are well-established in many parts of Africa (Ogden, 2017).
45 However, many data gaps remain, especially in monitoring climate-sensitive conditions such as diarrheal-
46 and arbovirus-related diseases, and morbidity and mortality stemming from heat exposure (Ogden, 2017;
47 Buchwald et al., 2020).
48
49 Climate and health adaptation indicators are required for Africa to strengthen institutional capacity for risk
50 monitoring and early warning systems, emergency preparedness and response, vulnerability reduction
51 measures, shock-responsive and long-term social protection and planning and implementing resilience
52 building measures (FAO and ECA, 2018). National-level progress is assessed through the Lancet
53 Countdown indicators (Watts et al., 2018), however, district- and local-level indicators are needed to
54 measure levels of vulnerability and response effectiveness at a local level, and for informing planning local
55 service delivery. Potential indicators include monitoring the number of excess health conditions during
56 extreme heat events. Indoor temperature monitoring in sentinel houses and health facilities is a related
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1 indicator (Ebi and Otmani Del Barrio, 2017), linked with threshold temperature levels at which health
2 impacts occur, and the ability of the built environment to protect against these impacts (e.g., for heatwaves).
3
4 Measuring climate-health linkages is challenging due to the considerable diversity of the exposures, impacts
5 and outcomes, as well as constraints in key technical areas. Increasing our understanding of this diversity and
6 how this is influenced by adaptative changes is a major knowledge gap. This could be facilitated through a
7 pan-African database of climate and other environmental exposures, together with real-time statistical
8 support for analyses of climate and health associations.
9
10 9.10.3.2 Community Engagement
11
12 Increased awareness can facilitate community engagement and action (see Section 9.4.3). In Ghana, for
13 example, local communities understand the climate hazards that drive outbreaks of meningitis and adapt
14 accordingly by improving housing to limit heat and exposure, changing funeral practices during outbreaks,
15 increased vaccination uptake and afforestation (Codjoe and Nabie, 2014). Similarly, participation in
16 community organisations improved child nutrition in vulnerable rural households in Eswatini (Anchang et
17 al., 2019). Interventions specifically targeting women are beneficial for food security, although they may be
18 undermined by harmful gender norms in communities that are patriarchal, led by chiefs or have high rates of
19 gender-based violence (Jaka and Shava, 2018; Kita, 2019; Masson et al., 2019). The BRACED project in
20 Burkina Faso and Ethiopia specifically adopted a gender-transformative approach as an integral part of
21 resilience-building (McOmber et al., 2019). Improving `climate literacy' could empower youth, women and
22 men to be active citizens in promoting adherence of governments to international agreements in climate
23 change (Mudombi et al., 2017; Chersich et al., 2019a).
24
25 9.10.3.3 9.10.3.1Health Financing
26
27 Poor and low-income households often are not able to afford high out-of-pocket costs for medical care, or it
28 consumes a large portion of their income. As a result, without financial aid, peoples' health needs may not be
29 met after a climate shock (Hallegatte and Rozenberg, 2017). Microfinance (the provision of small-scale
30 financial products to low income and otherwise disadvantaged groups by financial institutions) and disaster
31 contingency funds can serve to reduce health risks of climate change for low-income communities
32 (Agrawala and Carraro, 2010; Ozaki, 2016), as can different forms of insurance and disaster relief (Fenton et
33 al., 2015; Dowla, 2018). Unconditional cash transfers in Kenya, Uganda and Zambia assisted vulnerable
34 groups to absorb the negative impacts of climate-related shocks or stress and to prepare for these (Lawlor et
35 al., 2019; Ulrichs et al., 2019). Based on several case studies in Africa, the Food and Agriculture
36 Organization recommends a `Cash+' approach which combines cash transfers with productive assets, inputs
37 or technical training to address the needs of vulnerable households in emergency situations, and enhance
38 livelihoods potential, income generation and food security (FAO, 2017). New economic models have been
39 implemented in North Africa, focused on poor households, youth and women that enable access to credit and
40 support the implementation of policies that balance cash and food crops, social safety nets and social
41 protection (Mumtaz and Whiteford, 2017; Narayanan and Gerber, 2017) (see also Sections 9.4, 9.8 and
42 9.11).
43
44 9.10.3.4 Disease-Specific Adaptations
45
46 Adaptation to prevent malaria
47 Increasing distribution and coverage of long-lasting insecticide-treated bed nets, improved diagnostic tests
48 and increasing health service access could mitigate the impacts of climate change on malaria if aligned with
49 the predicted or actual burden of malaria (medium confidence) (Kienberger and Hagenlocher, 2014; Thwing
50 et al., 2017). Understanding seasonal shifts in malaria transmission suitability as a result of climate change
51 can guide more targeted seasonal public health responses and better planning for different types of
52 management and control interventions based on the impact. For example, an increase in the number of
53 months where climate conditions are suitable for mosquito survival will require public health responses for
54 an extended period of time (Ryan et al., 2020).
55
56 In malaria-endemic areas, repeated malaria infections can provide temporary immunity, which reduces new
57 clinical cases (Laneri et al., 2015; Yamana et al., 2016). Conversely, where people have little or no
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1 immunity, exposure to malaria can lead to epidemics (Semakula et al., 2017a; Ryan et al., 2020). Pregnant
2 women and infants remain at risk for severe malaria, regardless of immunity status. Vector control and case
3 management capacity should be rapidly scaled up in newly affected areas where risks for epidemics are high
4 and populations are especially vulnerable. Poverty-alleviation initiatives underpin malaria control as the
5 malaria burden is strongly tied to socioeconomic status (Huld閚 et al., 2014; Degarege et al., 2019).
6
7 Contextualised risk studies on local drivers of transmission are still lacking and present a major gap in
8 developing appropriate adaptation strategies (high confidence). Progress has been made identifying and
9 ranking vulnerability and exposure indicators (Protopopoff et al., 2009; Onyango et al., 2016a), however,
10 better linking of biophysical and socioeconomic determinants of risk in integrated assessment models are
11 needed (Caminade et al., 2019; Zermoglio et al., 2019), as are applied approaches to develop adaptation
12 strategies for risk management (Leedale et al., 2016; Onyango et al., 2016b; Sadoine et al., 2018).
13
14 Adaptation to reduce diarrhoeal disease
15 Reducing pathogen concentrations in water and across food chains is fundamental for controlling diarrhoeal
16 diseases (van den Berg et al., 2019). Diarrhoea prevention and treatment post-disaster, encompass social
17 mobilisation campaigns, water treatment, enhanced surveillance and vaccination and treatment centres for
18 cholera (Cambaza et al., 2019) and typhoid (Neuzil et al., 2019).
19
20 Improved water, sanitation and hygiene (WASH) requires robust water and sanitation infrastructure
21 (Duncker, 2017; Kohlitz et al., 2017; Venema and Temmer, 2017) and technological adaptations (Gabert,
22 2016; van Wyk et al., 2017), such as waterless on-site sanitation (Sutherland et al., 2021), diversification of
23 water sources (e.g., rainwater harvesting (Lasage and Verburg, 2015) and groundwater abstraction
24 (MacDonald et al., 2012)), and sharing of best practices across the continent (WASH Alliance International,
25 2015; Jack et al., 2016) (see also Section 9.7.3; Chapter 4, Section 4.6.4). Hand hygiene can be improved
26 through the creation of handwashing stations, increased access to soap and simple technologies such as the
27 foot-operated Tippy taps (Coultas and Iyer, 2020; Mbakaya et al., 2020).
28
29 Adaptation to reduce conditions related to heat exposure
30 Reducing morbidity and mortality during extreme heat events requires changes in behaviour and health
31 promotion initiatives, health system interventions and modifications to the built and natural environment.
32 Health promotion initiatives include promoting adequate hydration and simple cooling measures such as
33 drinking cold liquids, water sprays and raising awareness of the symptoms and importance of heat stress,
34 including heatstroke (Aljawabra and Nikolopoulou, 2018). Adaptive measures are especially important for
35 high-risk groups such as outdoor workers, the elderly, pregnant women and infants. Health systems
36 interventions may include early warning systems, heat health regulation, and health workers providing
37 cooling interventions, such as supplying cool water or fans, during heat waves. Changes to the built
38 environment include painting the roofs of houses white and improving ventilation during extreme heat
39 (Codjoe et al., 2020), the use of insulation materials or altering the building materials used for the
40 construction of housing to improve their ability to moderate indoor temperatures (Mathews et al., 1995;
41 Makaka and Meyer, 2006).
42
43 Adaptation to prevent malnutrition
44 Transformative adaptation requires integration of resilience and mitigation across all parts of the food system
45 including production, supply chains, social aspects and dietary choices (IPCC, 2019a). Adaptation to prevent
46 malnutrition goes hand-in-hand with adaptation to prevent food insecurity, as is discussed in Section 9.8.3
47 and Chapter 5, Section 5.12.5.
48
49 Urban agriculture and forestry can improve nutrition and food security, household income and mental health
50 of urban farmers while mitigating against some of the impacts of climate change like flooding and landslides
51 (by stabilising the soil and reducing runoff, for example), heat (by providing shade and through
52 evapotranspiration) and diversifying food sources in case of drought (Zezza and Tasciotti, 2010; Lwasa et
53 al., 2014; Battersby and Hunter-Adams, 2020).
54
55 The health sector needs to collaborate and coordinate adaptation activities with other sectors, as well as civil
56 society and international agencies, to engage communities in health promotion (Irwin et al., 2006;
57 Commission of Social Determinants of Health, 2008; Braveman and Gottlieb, 2014). The importance of
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1 social determinants of health, such as socioeconomic status, education and the physical environment in
2 which people live and work and their consideration during development are highlighted in Chapter 7 (see
3 Sections 7.1.6 and 7.4.2)
4
5
6
7 Figure 9.36: Adaptation options across multiple sectors have potential for reducing risk across multiple health
8 outcomes, considering their potential to reduce vulnerability, and potential barriers to implementation (e.g., lack of
9 social acceptance). Reduced risk for health may result from targeted actions or as a result of co-benefits (see
10 Supplementary Material Table SM9.8 for a full list of references).
11
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1
2
3 Table 9.11: Co-benefits, barriers and enablers of adaptation responses to climate change impacts on human health in
4 Africa (see Supplementary Material Table SM 9.9 for a full list of references).
Inter-sectoral trade-
Response category Co-benefits offs and/or Enablers Barriers
drawbacks
Policies and plans that Willingness of
facilitate service delivery policymakers; political
and guide national and
Policy development international funding; Lack of
decreased number of work support; politically
hours lost; improved work
performance, increased implementation; poor
productivity willing environment;
governance
inter-sectoral
collaboration
Education & Promotion of sustainable Guarantee to sustained
awareness living and circular Lack of
economy
funding; political
implementation;
support; politically
historical and
willing environment;
colonisation-related
increased accessibility
insensitivities
of learning institutions
Health systems & Capacity building in Increased GHG from
primary communities; buffered building; increased
healthcare economic impact of
services outbreaks/ disasters; job Guarantee to sustained Corruption and
creation energy demand;
funding; political fraudulent activities
decreased productivity
support; politically around resource
and increased work
willing environment allocation
hours lost due to
waiting times
Surveillance, risk Evidence to improve Requires effective
assessments, adaptation response; fast institutional
monitoring, & post-disaster recovery;
research increased awareness and May be limited by
disease prevention; arrangements and inter-
improved health system
functioning post-disasters uncertainty in modelled
sectoral collaboration;
predictions and
guarantee to sustained
thresholds
funding; requires skills
development
Improved health system
functioning post-disasters;
capacity building in Guarantee to sustained
communities; promotes Increased GHG from funding; political
economic building; increased support; politically
growth/stability; increases energy demand; willing environment; Corruption and
Resource the tourism potential of increased crowding/ requires effective fraudulent activities
management
the area; increased population density; institutional around resource
accessibility/ mobility of land use; microclimate arrangements and inter- allocation
the community; reduced and ecosystem sectoral collaboration;
land degradation, disruption requires skills
desertification, and bush development
encroachment; food
security; decreased
emissions
Increased GHG;
Decreased mortality; decreased biodiversity; Guarantee to sustained
Vector control & improved work environmental impacts funding; funding and Last-mile access; cost
disease prevention performance; increased of production, resources; future per capita and capacity
productivity; improved packaging, and planning or retrofit for service delivery
mental health delivery; potentially required
detrimental to health
5
6
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1 9.11 Economy, Poverty and Livelihoods
2
3 9.11.1 Observed Impacts of Climate Change on African Economies and Livelihoods
4
5 9.11.1.1 Economic Output and Growth
6
7 Increased average temperatures and lower rainfall have reduced economic output and growth in Africa, with
8 larger negative impacts than other regions of the world (Abidoye and Odusola, 2015; Burke et al., 2015a;
9 Acevedo et al., 2017; Kalkuhl and Wenz, 2020). In one estimate, GDP per capita is on average 13.6% lower
10 for African countries than it would be if anthropogenic warming since 1991 had not occurred (Diffenbaugh
11 and Burke, 2019), although impacts vary substantially across countries (see Figure 9.37). As such, global
12 warming has increased economic inequality between temperate, Northern Hemisphere countries and those in
13 Africa (Diffenbaugh and Burke, 2019). Warming also leads to differential economic damages within Africa
14 (Baarsch et al., 2020). One estimate found a 1 increase in 20-year average temperature reduced GDP
15 growth by 0.67 percentage points, with the greatest impacts in Central African Republic, Democratic
16 Republic of Congo and Zimbabwe (Abidoye and Odusola, 2015). Changes in rainfall patterns also influence
17 individual and national incomes. Had total rainfall not declined between 1960 and 2000, the gap between
18 African GDP and that of the rest of the developing world would be 15�40% smaller than today, with the
19 largest impacts in countries heavily dependent on agriculture and hydropower (Barrios et al., 2010).
20
21 Aggregate macroeconomic impacts manifest through many channels (Carleton et al., 2016). Macroeconomic
22 evidence suggests aggregate impacts occurred largely through losses in agriculture with a smaller role for
23 manufacturing (Barrios et al., 2010; Burke et al., 2015b; Acevedo et al., 2017). Sector-specific analyses
24 confirm that declines in productivity of food crops, commodity crops and overall land productivity
25 contribute to lower macroeconomic performance under rising temperatures (Schlenker and Lobell, 2010;
26 Bezabih et al., 2011; Jaramillo et al., 2011; Lobell et al., 2011; Adhikari et al., 2015). Labour supply and
27 productivity declines in manufacturing, industry, services and daily wage labour have been observed in other
28 regions (Graff Zivin and Neidell, 2014; Somanathan et al., 2015; Day et al., 2019; Nath, 2020) and
29 contribute to aggregate economic declines, countering aggregate poverty reduction strategies and other
30 sustainable development goals (Satterthwaite and Bartlett, 2017; Day et al., 2019). In a case study of a rural
31 town in South Africa, over 80% of businesses (both formal and informal) lost over 50% of employees and
32 revenue due to agricultural drought (Hlalele et al., 2016). Drought and extreme heat events have also reduced
33 tourism revenues in Africa (Section 9.6.3). Infrastructure damage and transport disruptions from adverse
34 climate events reduce access to services and growth opportunities (Chinowsky et al., 2014). In global
35 datasets including Africa, tropical cyclones have been shown to have large and long-lasting negative impacts
36 on GDP growth (Hsiang and Jina, 2014).
37
38
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1
2 Figure 9.37: Observed aggregate economic impacts and projected risks from climate change in Africa. (A) Estimated
3 effect of anthropogenic climate change on GDP per capita for 48 African countries between 1991 and 2010. (B, C)
4 Projected effect on GDP per capita of global warming of ~4癈 by 2100 compared to no global warming after 2010 at
5 country level (B) and averaged across sub-Saharan Africa (C). (D) Benefits to GDP per capita of holding warming to
6 1.5 versus 2癈 above pre-industrial. (E) Probability of realising any economic benefits by holding warming to 1.5癈
7 versus 2癈. Data sources: (Burke et al., 2015b; Burke et al., 2018a; Diffenbaugh and Burke, 2019).
8
9
10 9.11.1.2 Human Capital Development and Education
11
12 Investments in human capital, particularly education, are critical for socioeconomic development and
13 poverty reduction by providing valuable skills and expanding labour market opportunities. Much progress
14 has been made in improving education access, however, in sub-Saharan Africa, 32% of children, adolescents
15 and youth (~97 million people) remain out of school (UNESCO Institute of Statistics, 2018). Climate
16 variability and change can undermine educational attainment with negative impacts on later life earning
17 potential and adaptive capacity to future climate change (Lutz et al., 2014) (Figure 9.11).
18
19 Several studies indicate experiencing low rainfall, warming temperatures or extreme events reduce education
20 attainment and that future climate change may reduce children's school participation, particularly for
21 agriculturally-dependent and poor urban households. In West and Central Africa, experiencing lower-than-
22 average rainfall during early life is associated with up to 1.8 fewer years of completed schooling in
23 adolescence while more rainfall and milder temperatures during the main agricultural season were positively
24 associated with educational attainment for boys and girls in rural Ethiopia (Randell and Gray, 2016; Randell
25 and Gray, 2019). In Uganda, low rainfall reduced primary school enrolment by 5% for girls (Bj鰎kman-
26 Nyqvist, 2013), and in Malawi, in utero drought exposure was associated with delayed school entry among
27 boys (Abiona, 2017). In rural Zimbabwe, experiencing drought conditions during the first few years of life
28 was associated with fewer grades of completed schooling in adolescence, which translates into a 14%
29 reduction in lifetime earnings (Alderman et al., 2006). In Cameroon, warming temperatures have negatively
30 affected plantain yields, which in turn is linked to lower educational attainment (Fuller et al., 2018). One
31 suggested mechanism underlying the relationship between climate and schooling is that adverse climatic
32 conditions can reduce income among farming households, leading them to pull children out of school
33 (Randell and Gray, 2016; Marchetta et al., 2019). Other potential mechanisms are poor harvests from
34 droughts or supply interruptions from extreme weather events leading to undernutrition among young
35 children, negatively affecting cognitive development and schooling potential (Alderman et al., 2006; Bartlett,
36 2008).
37
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1 More research is needed on climate change impacts on education in Africa. This information can help ensure
2 families keep children in school amidst climate-related income shocks. For example, in Mexico, a
3 conditional cash transfer program mitigated the negative effect of natural disasters on school attendance (de
4 Janvry et al., 2006).
5
6 9.11.2 Projected Risks of Climate Change for African economies and livelihoods
7
8 Future warming will have negative consequences for economic growth in Africa, relative to a future without
9 additional climate change and assuming current levels of adaptation (high confidence) (Dell et al., 2012;
10 Burke et al., 2015a; Burke et al., 2015b; Acevedo et al., 2017; Baarsch et al., 2020). Statistically-based
11 empirical analyses project that global warming of 2.3癈 by 2050 could lower GDP per capita across sub-
12 Saharan Africa by 12% (SSP2) (Baarsch et al., 2020) and 80% for warming >4癈 by 2100 (SSP5, 75% for
13 MENA) (Burke et al., 2015b). Depending on the future socioeconomic scenario, this could increase global
14 inequality and leave some African countries poorer than at present (Burke et al., 2015b). Inequalities
15 between African countries are projected to widen under climate change, with negative impacts estimated to
16 be largest in West and East Africa (Baarsch et al., 2020). While negative impacts across African economies
17 are highly likely under climate change, precise magnitudes are debated in the literature. Alternative statistical
18 analyses suggest a 12% reduction of GDP per capita by 2100 under RCP8.5 across African countries relative
19 to a future without climate change (Kahn et al., 2019), while computable general equilibrium models
20 generate smaller damages as well, ranging from 3.8% reduction across sub-Saharan Africa in 2060 under
21 warming of 2.5癈 (Dellink et al., 2019) to 12% across all of Africa in 2100 under warming of 5癈 (SSP4)
22 (Takakura et al., 2019).
23
24 Substantial avoided economic damages to African countries are projected from ambitious, near-term global
25 mitigation limiting global warming well below 2癈 above pre-industrial levels (high confidence). Increased
26 economic damage forecasts for Africa under high emissions scenarios start diverging rapidly from low
27 emissions scenarios by the 2030s (Baarsch et al., 2020). Across nearly all African countries, GDP per capita
28 is projected to be at least 5% higher by 2050 and 10�20% higher by 2100 if global warming is held to 1.5癈
29 versus 2癈 (Burke et al., 2018a; Baarsch et al., 2020) (Figure 9.37). The probability of this positive gain to
30 GDP per capita from achieving 1.5癈 versus 2癈 is reported as close to 100% (Burke et al., 2018a). While
31 these estimates rely on temperature and rainfall-driven damages, sea level rise also poses a risk for Africa.
32 By 2050, damages from sea level rise across sub-Saharan Africa could reach 2�4% of GDP, depending on
33 the socioeconomic, adaptation and emissions scenario (Parrado et al., 2020).
34
35 Heat stress is projected to reduce working hours and work capacity under climate change, with among the
36 largest declines in sub-Saharan Africa and for workers in vulnerable occupation groups, such as those
37 working outdoors (Kjellstrom et al., 2014; Kjellstrom et al., 2016; de Lima et al., 2021) (AR6 WGII, Chapter
38 5). Global warming of 3癈 is projected to reduce labour capacity in agriculture by 30�50% in sub-Saharan
39 Africa (relative to the baseline in 1986�2005) (de Lima et al., 2021). These effects lead to substantial
40 aggregate losses, for example, in West Africa, labour productivity impacts under a 3癈 temperature increase
41 are estimated to cost up to 8% of GDP (Roson and Sartori, 2016). Manufacturing productivity across Africa
42 is projected to decline under RCP8.5 by 0�15% by 2080�2099, with the largest effects in the Democratic
43 Republic of Congo, Ethiopia, Somalia, Mozambique and Malawi (Nath, 2020).
44
45 Large risks to road, rail and water infrastructure are projected from climate change with substantial economic
46 cost implications (see Section 9.9.3; Box 9.5).
47
48 9.11.3 Informality
49
50 Aggregate GDP data capture formal economic activity but informal employment is the main source of
51 employment in Africa, accounting for 85.8% of all employment (71.9%, excluding agriculture), which is
52 21.4% higher than the global average (ILO, 2018b). Estimates of national levels of informal employment
53 range from 30% in South Africa, to 94.6% in Burkina Faso (ILO, 2018b), with high variability within
54 countries such as South Africa and Nigeria (Etim and Daramola, 2020). Informal employment is a greater
55 source of employment for women than for men in sub-Saharan Africa and young and old have especially
56 high rates of informal employment: 94.9% of persons between ages 15 and 24 in employment and 96% of
57 persons aged 65 and older (ILO, 2018b).
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1
2 Informal sector impacts are omitted from GDP-based impacts projections. Yet informal sector activity and
3 small to medium-sized enterprises can be highly exposed to climate extremes, as they are often located in
4 low-lying areas, coastal areas, sloped or other hazardous zones (Thorn et al., 2015; Satterthwaite et al.,
5 2020). Businesses and individuals in the informal sector, including construction workers, domestic workers,
6 street vendors and transport workers, often cannot operate during climate shocks due to interruptions in
7 transportation and commodity flows and, without the ability to insure against risk, struggle to recover assets
8 from extreme events such as flooding, landslides and waterlogging (Chen, 2014; Thorn et al., 2015; Roy et
9 al., 2018a). Women are overrepresented in the more poorly remunerated sections of the informal economy
10 (Satterthwaite et al., 2020).
11
12 There is scope for governments to better harness the role of the informal sector in mitigation and adaptation
13 (Douxchamps et al., 2015; Satterthwaite et al., 2020). Multi-level governance that includes informal service
14 providers, such as informal water and sanitation networks, into planned adaptation programmes can increase
15 climate resilience, in part because these networks can respond with more flexibility than hard infrastructure
16 projects (Satterthwaite et al., 2020; Peirson and Ziervogel, 2021). Climate risk is often concentrated in urban
17 informal settlements (Section 9.9.4). Here, informal land markets influence development patterns and can
18 help ensure adherence to building codes to ensure safety of informally built structures at high risks of
19 landslides and floods and enforce compliance with regulations relating to planning and land use (Thorn et al.,
20 2015; Satterthwaite et al., 2020). Improving land management practices of charcoal producers and artisanal
21 gold miners, combined with appropriate alternative livelihood and energy sources, can reduce emissions and
22 increase resilience (e.g., reduce erosion and sedimentation, increase water infiltration) and benefit health
23 (Atteridge, 2013; Paz et al., 2015; Mach醕ek, 2019; Barenblitt et al., 2021; Eniola, 2021). Providing
24 concessional loans, commercial financing or equity investment to informal brick makers can boost delivery
25 of low emission social housing while the use of crop residues or renewable energy for brick making can
26 replace wood biomass and reduce pressure on forests (Alam, 2006; Paz et al., 2015).
27
28 9.11.4 Climate Change Adaptation to Reduce Vulnerability, Poverty and Inequality
29
30 High temperature-related income losses have been observed in low- and high-income countries, suggesting
31 optimistic economic development trajectories may not substantially reduce climate change impacts on
32 aggregate economic performance in Africa (low confidence) (Burke et al., 2015b; Deryugina and Hsiang,
33 2017; Henseler and Schumacher, 2019). Nevertheless, climate change impacts on poverty in Africa will
34 depend on how socioeconomic development unfolds over the coming decades (medium confidence)
35 (Rozenberg and Hallegatte, 2015; Hallegatte and Rozenberg, 2017; Henseler and Schumacher, 2019).
36 Climate change by 2030 is projected to push 39.7 million Africans into extreme poverty3 under a baseline
37 scenario of delayed and non-inclusive growth, with food prices acting as the dominant channel of impact, but
38 this number is cut roughly in half under an inclusive economic growth scenario (Rozenberg and Hallegatte,
39 2015; Hallegatte and Rozenberg, 2017; Jafino et al., 2020).
40
41 People in Africa are disproportionately employed in highly climate-sensitive sectors: 55�62% of the sub-
42 Saharan African workforce is employed in agriculture and while between 90�95% of cropland is rainfed
43 (Woodhouse et al., 2017; ILO, 2018a; International Institute of Water Management, 2019; World Bank,
44 2020c), there has been an expansion of small-scale `farmer-led irrigation' (Woodhouse et al., 2017).
45 Agricultural GDP also appears more strongly affected by increasing temperatures than non-agricultural
46 GDP, implying livelihood diversification out of agriculture may help minimise future economic damage
47 (Bezabih et al., 2011; Burke et al., 2015b; Acevedo et al., 2017; Deryugina and Hsiang, 2017), although such
48 workforce reallocation requires careful management and planning depending on the overall livelihood
49 portfolios, type of farmer and profitability (Stringer et al., 2020). De-agrarianisation can feed urbanisation,
50 which may exacerbate inequality within and between countries (Stringer et al., 2020).
51
52 Changes in trade patterns may help mitigate projected aggregate economic losses by reallocating agricultural
53 production abroad and encouraging economic diversification toward less affected sectors. Temperature
54 increases have been shown to lower agriculture and manufacturing exports with especially large declines in
3 Extreme poverty is defined using a consumption poverty line at US$1.25 per day, using 2005 purchasing power parity exchange rates.
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1 poor countries (Jones and Olken, 2010; Roberts and Schlenker, 2013). Further, imports of agricultural
2 products are projected to rise across most of Africa by 2080-2099 under a high emissions scenario (RCP8.5),
3 with increases ranging from ~30% of GDP in the Central African Republic to ~5% of GDP in South Africa
4 and Nigeria, although some countries will experience increases in net agricultural exports (Nath, 2020).
5 While these reallocation effects may be large, current evidence is mixed regarding whether such adjustment
6 of production will dampen or amplify overall social costs of climate change in Africa (Costinot et al., 2012;
7 Bren d'Amour et al., 2016; Wenz and Levermann, 2016; Nath, 2020), as food prices are projected to rise by
8 2080-2099 across all African countries under a scenario with high challenges to mitigation and adaptation
9 (SSP3 and RCP8.5), with the largest price effects (up to 120%) experienced in Niger, Chad and Sudan (Nath,
10 2020). Moreover, reallocating production of agriculture abroad could be maladaptive if it leads to decline or
11 replacement of traditional sectors by industrial and service sectors which could lead to land abandonment,
12 food insecurity and loss of traditional practices and cultural heritage (Thorn et al., 2020; Gebre and Rahut,
13 2021; Nyiwul, 2021).
14
15 African countries have high inequality: the average within-country share of income accruing to the top 10%
16 of households was estimated at 50% for 2019 (Robilliard, 2020). However, analysis of INDCs across 54
17 African countries suggests current climate policies do not, on average, target social inequality in energy,
18 water and food security; proposed mitigation and adaptation actions fell about 23% for every 1% rise in
19 social inequality across these sectors (Nyiwul, 2021). In contrast, adaptation actions can be designed in ways
20 that actively work towards reducing inequality, whether gender, income, employment, education or
21 otherwise (Andrijevic et al., 2020).
22
23 In rural Africa, poor and female-headed households face greater livelihood risks from climate hazards (high
24 confidence). Women often constitute a high proportion of the informal workforce and are also more likely to
25 be unemployed than men (ILO, 2018a). These factors leave women, and particularly female-headed
26 households, at greater risk of poverty and food insecurity from climate hazards. Controlling for multiple
27 factors, income of female-headed households in agricultural districts in South Africa is more vulnerable to
28 precipitation variability than those headed by men (Davidson, 2016; Flat� et al., 2017). Across nine countries
29 in East and West Africa women tend to control smaller plots of land that is often of poorer quality, have less
30 access to inputs such as fertilizer, tools and improved seeds, have lower educational attainment and benefit
31 less from extension services, government agencies and non-governmental organisations (Perez et al., 2015).
32 Gender assessments prior to adaptation programmes can identify disparities in division of labour and income
33 and socio-cultural norms, hindering women from holding leadership positions or determining livelihood and
34 resource-use activities, thereby helping ensure equitable benefits from livelihood diversification and
35 improving women's working conditions (ILO, 2018a). Gender-responsive policy instruments can measure
36 success using sex-disaggregated data to monitor impact and meaningful participation in decision-making
37 (GCF, 2018b).
38
39 Exposure to climate hazards can trap poorer households in a cycle of poverty (Dercon and Christiaensen,
40 2011; Sesmero et al., 2018) and poor people in Africa are often more exposed to climate hazards than non-
41 poor people. For example, poor people live in hotter areas in Nigeria and in multiple African countries, poor
42 households are more exposed to flooding (Hallegatte et al., 2016) (Section 9.9.2). Daily wage labourers and
43 residents of urban informal settlements are vulnerable to heat stress because of the urban heat-island effect
44 combined with congestion, little shade and ventilation (Bartlett, 2008). Climate change can negatively affect
45 household poverty through price spikes, destroying assets or ability to invest in new assets and reducing
46 productivity (Hallegatte et al., 2016) with important impact pathways operating through agriculture,
47 ecosystem functioning and health (Sections 9.6, 9.8, 9.10; Chapters 5, 7, 8). Non-poor people can lose more
48 in absolute terms from climate shocks because of having more assets and higher incomes, but in relative
49 terms, poor people often lose more than the non-poor. These relative losses matter most for livelihoods and
50 welfare (Hallegatte et al., 2016).
51
52 In Malawi, wealthier households were able to maintain more diversified livelihoods, buffering them from
53 extreme weather-related income losses (Sesmero et al., 2018). Poorer households have limited access to
54 resources such as savings, credit, irrigation technologies and insurance, which can lead to larger crop and
55 other income losses from climate hazards, preventing investments to improve resilience to future climate
56 shocks (Castells-Quintana et al., 2018). Poor households may reduce risk or aid recovery by cooperating
57 with other households in their community to adapt collectively to climate change, for example, through
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1 informal insurance networks (Paul et al., 2016; Wuepper et al., 2018). Prioritising poor households for
2 interventions including social protection, ecosystem-based adaptation, universal healthcare, climate-smart
3 buildings and agriculture, flexible work hours under extreme heat and early warning systems will increase
4 adaptation to climate shocks (Angula and Menjono, 2014; Moosa and Tuana, 2014; Hallegatte et al., 2016;
5 Day et al., 2019) (Section 9.6.4; Chapter 6). Pro-poor policies that link mitigation and adaptation, such as
6 using renewable energy to increase rural electrification or using revenues from a carbon tax, combined with
7 international financial support to increase social assistance, could support sustainable eradication of poverty
8 under near-term climate change (Hallegatte et al., 2016; Aklin et al., 2018; Simpson et al., 2021c).
9 Integrating urban green infrastructure into adaptation planning in informal settlements can simultaneously
10 unlock pathways for inclusivity and social justice (Tozer et al., 2020; Wijesinghe and Thorn, 2021) (Section
11 9.9.5).
12
13 Social protection has been used for decades, particularly in eastern and southern Africa, to safeguard poor
14 and vulnerable populations from poverty and food insecurity (Ni駉-Zaraz鷄 et al., 2012). Instruments of
15 social protection include public works programs, cash transfers, in-kind transfers, social insurance and
16 microinsurance schemes that assist individuals and households to cope during times of crisis and minimise
17 social inequality. Evidence from Kenya, Ethiopia and Uganda indicates national social protection
18 programmes are effective in improving individual and household resilience to climate-related shocks,
19 regardless of whether they aim specifically to address climate risks (Ulrichs et al., 2019). Strengthening
20 social protection and better integrating climate risk management into design of social protection programs
21 can help build long-term resilience to climate change (Hallegatte et al., 2016; Agrawal et al., 2019). For
22 example, Public Works programs can build climate resilience by targeting soil, water and ecosystem
23 conservation and carbon sequestration, such as South Africa's Working for Water Programme that restores
24 river catchments to reduce fire risk and increase water supplies (Turpie et al., 2008; Norton et al., 2020).
25
26 9.11.4.1 Climate Insurance
27
28 African countries and communities are inadequately insured against climate risk. Insurance penetration is
29 less than 2% of GDP (Swis Re, 2019) and 90% of natural catastrophe losses were uninsured in Africa in
30 2018 (Swis Re, 2019) leaving a large risk protection gap. The cost of reinsurance in Africa's most mature
31 insurance market � South Africa � has increased since 2017 due to climate-related payouts (SAIA, 2018;
32 Simpson, 2020), likely to further reduce the extent of insurance coverage. Emerging trends that seek to
33 address this gap include innovative weather and drought index-based insurance schemes to transfer risk,
34 forward-looking climate data and models to manage risk and insurers transitioning from risk transfer
35 providers to proactive risk managers.
36
37 The most significant area of climate risk insurance innovation has occurred in weather and drought index-
38 based insurance schemes that pay out fixed amounts based on the occurrence of an event instead of full
39 indemnification against assessed losses (Table 9.12). However, despite the relatively low cost, uptake
40 remains low due to affordability constraints, lack of awareness, access to and trust in products, distribution
41 challenges, basis risk, poor transparency, challenges regarding the integration of complementary
42 interventions (e.g., access to improved inputs or informal savings/credit) and poor perceptions/norms of
43 insurance and risk transfer. Lack of data and models further hinders insurers' ability to price risk correctly,
44 which reduces value to clients (Greatrex et al., 2015; Di Marcantonio and Kayitakire, 2017; WEF, 2021).
45 Impact assessments point to potential but remain context-specific (Awondo, 2019; Hansen et al., 2019b;
46 Noritomo and Takahashi, 2020). In addition, there is no comprehensive overview of the number of people
47 covered by such schemes, nor of the value they provide in terms of actual claims payouts. Lastly, donor
48 and/or public funds still play an outsized role in launching and/or sustaining these schemes and schemes
49 beyond weather and drought remain limited (Table 9.12).
50
51 Insurers and their clients are often unaware of their risk exposure, partly due to data and modelling gaps.
52 Climate information services and related collaborations are increasingly helping to address this problem (see
53 Section 9.4.5). Climate change attribution methods to estimate the contribution of anthropogenic climate
54 change to the cost of parametric insurance offers possibilities for a sharing of the premium between the
55 impacted African country and a global climate fund, such as the Green Climate Fund (New et al., 2020).
56 Technology companies and start-ups (including fintechs) are also emerging as solutions to fill risk gaps,
57 leveraging new approaches to data and technology through the use of sensors, drones and satellite imaging to
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1 speak to mainly agricultural risks, but also urban risks such as informal settlement fires, exacerbated by heat
2 and drought (Table 9.12).
3
4 Ten African insurers formally committed to help manage climate risk on the continent through the Nairobi
5 declaration of the UNEP Principles for Sustainable Insurance (PSI) in 2021 (UNEP PSI, 2021). Some early
6 examples of public-private partnerships with municipalities and governments to better manage climate risk
7 are also emerging (Table 9.12).
8
9
10 Table 9.12: Insurance opportunities to mitigate climate risk.
Initiatives Drought/ Flood Cycl Fire Example Policyholders/ Reference
beneficiaries
heatwave one
Index and x x ACRE Africa, Pula, Smallholder (Greatrex et al.,
R4 Rural Resilience farmers 2015; CTA, 2019;
parametric Initiative, KLIP, Global Index
FISP, Ghana Insurance
schemes � Agricultural Facility, 2019;
Insurance Pool, WFP, 2020; Fava
smallholder Oko Crop et al., 2021; OKO
Assurance Finance, 2021;
farmer Pula, 2021; Tsan
et al., 2021)
Index and x x x African Risk Governments (ARC, 2019)
Capacity
parametric
schemes �
sovereign
and sub-
sovereign
Index and x x African and Asian Individuals (Global
Resilience in and Parametrics,
parametric Disaster Insurance smallholder 2018)
Scheme (ARDIS) farmers
schemes �
global
Risk x x x x UNEP PSI Insurers and (Santam, 2018;
reinsurers, Forsyth et al.,
management Santam local 2019; UNEP-FI,
municipalities, 2019a;
and data Tripartite governments InsurResilience,
2020; Simpson,
collaboration Agreement 2020)
FinTech x x x Lumkani, Individuals, (Greatrex et al.,
WorldCover, smallholder 2015; Hunter et
Econet, PlaNet farmers al., 2018; CTA,
Guarantee 2019; UK Space
Agency, 2020;
Tsan et al., 2021)
11
12
13 [START BOX 9.8 HERE]
14
15 Box 9.8: Climate Change, Migration and Displacement in Africa
16
17 Climatic conditions are important drivers of migration and displacement with migration responses to climate
18 hazards strongly influenced by economic, social, political and demographic processes (Cross-Chapter Box
19 MIGRATE in Chapter 7).
20
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1 Most climate-related migration and displacement observed currently is within countries or between
2 neighbouring countries, rather than to more geographically distant high-income countries (Hoffmann et al.,
3 2020; Kaczan and Orgill-Meyer, 2020). Natural-related disaster displacements in sub-Saharan Africa were
4 over 2.6 million in 2018 and 3.4 million in 2019 (13.9% of the global total and one of the highest historical
5 figures for the region), with East (1,437,7000) and West Africa (798,000) being hotspots in 2018
6 (Mastrorillo et al., 2016; IDMC, 2019; IDMC, 2020) (Table Box 9.8.1). Estimates indicate future climate
7 change effects on internal migration in Africa will be considerable (Rigaud et al., 2018) (Table Box 9.8.2).
8
9 Internal migration, displacement and urbanisation
10
11 Climate change can have opposing influences on migration flows. Deteriorating economic conditions caused
12 by climate hazards can encourage out-migration (Wiederkehr et al., 2018). However, these same economic
13 losses undermine household resources needed to migrate (Cattaneo and Peri, 2016). The net effect of these
14 two forces leads to mixed results across study methodologies and contexts (Carleton and Hsiang, 2016;
15 Borderon et al., 2019; Cattaneo et al., 2019; Hoffmann et al., 2020).
16
17 Urbanisation in Africa is affected by climate conditions in rural agricultural areas (high confidence).
18 Urbanisation can increase when reduced moisture availability depresses farm incomes or pastoral livelihoods
19 become unviable (Marchiori et al., 2012; Henderson et al., 2014; Mastrorillo et al., 2016). The influence of
20 rainfall on rural-urban migration increased since decolonisation, possibly due to more lenient legislation on
21 internal mobility, with each 1% reduction in precipitation below a long-term average associated with a
22 0.45% increase in urbanisation (Barrios et al., 2006). Rate of rural-urban migration is anticipated to increase
23 (Neumann et al., 2015) as a result of increasing vulnerability of agricultural livelihoods to climate change
24 (Serdeczny et al., 2017). Nevertheless, rural-urban migration is not a simple one-way process. Peri-urban and
25 rural areas provide developmental feedback loops, helping create a `regional agglomeration' effect, for
26 instance, through growing food demand, family and social connections, and flows back to rural areas of
27 goods and services and financial investments (UN-Habitat, 2016; Dodman et al., 2017).
28
29 Migration is an important and potentially effective climate change adaptation strategy in Africa and must be
30 considered in adaptation planning (high confidence) (Williams et al., 2021). The more agency migrants have
31 (that is, degree of voluntarity and freedom of movement), the greater the potential benefits for sending and
32 receiving areas (high agreement, medium evidence) (Cross-Chapter Box MIGRATE in Chapter 7). In a
33 synthesis of 63 studies covering over 9,700 rural households in dryland sub-Saharan Africa, 23% of
34 households employed migration (primarily temporary economic) to adapt to changes in rainfed agriculture
35 (Wiederkehr et al., 2018). Migration responses to climate change tend to be stronger among wealthier
36 households, as poorer households often lack financial resources necessary to migrate (Kaczan and Orgill-
37 Meyer, 2020).
38
39 International migration
40
41 Studies on propensity to emigrate have uncovered conflicting results. Some findings suggest in low-income
42 countries high temperatures `trap' people at home and lower migration rates abroad, but in middle-income
43 countries, these same high temperatures encourage emigration (Cattaneo and Peri, 2016). However, other
44 research finds in poor and agriculturally-dependent countries, high temperatures encourage international out-
45 migration, particularly to the OECD (Cai et al., 2016). Some evidence indicates people who leave tend to be
46 more educated, possibly leading to `brain drain' (Mbaye, 2017). Recent evidence suggests hotter-than-
47 normal temperatures across 103 countries, including many in Africa, increased asylum applications to the
48 European Union (Missirian and Schlenker, 2017). Assuming no change in present-day vulnerability, asylum
49 applications are projected to increase 34% across Africa (relative to 2000�2014) at 2.2癈 global warming
50 (Missirian and Schlenker, 2017), although this finding has been challenged in the literature (Abel et al.,
51 2019; Boas et al., 2019).
52
53 International remittances are a vital resource for developing countries that can help aid recovery from
54 climate shocks (Hallegatte et al. 2016). Estimated at USD 48 billion in 2019 their importance is expected to
55 grow further due to foreign direct investment declines during the COVID-19 pandemic (World Bank,
56 2020a). Furthermore, domestic remittances from rural-urban migration can help rural households respond to
57 climate risks (KNOMAD, 2016). However, adequate finance and banking infrastructure are essential for
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1 remittances and, on average, cash transfer costs for sub-Saharan African countries remain the highest
2 globally (World Bank, 2020a). Mobile money technologies and regulation that promotes competition in the
3 remittances market can reduce transaction costs (World Bank, 2020a). Governments can further address
4 challenges facing internal and international migrants by including them in health services and other social
5 programmes and protecting them from discrimination (World Bank, 2020a).
6
7
8 Table Box 9.8.1: Reported impacts of climate on migration in Africa (Findings on the linkages between climatic
9 conditions and migration vary greatly across countries in Africa)
Climate driver Country Climate - Migration linkages Reference
Kenya Cool temperatures linked to internal labour migration among males (Gray and
Wise, 2016)
Uganda High temperatures linked to increased non-labour migration among (Gray and
females. Wise, 2016;
Temperature Short hot spells linked to increased temporary migration. Long- Call and Gray,
term heat stress linked to permanent migration through an 2020)
agricultural livelihoods pathway.
Tanzania Temperature-induced income shocks linked to decreased long-term (Hirvonen,
rural-urban migration among men. 2016)
Kenya Increased precipitation linked to decreased rural-urban migration. (Mueller et al.,
2020)
Zambia Increased precipitation linked to increased internal migration. (Mueller et al.,
2020)
Burkina Drier regions linked to increased temporary and permanent (Henry et al.,
Faso
migrations to other rural areas. Short-term precipitation deficits 2004)
linked to increased long-term migration to rural areas and decreased
risk of short-term migration to distant destinations.
Ethiopia Drought linked to men's labour migration from rural to urban areas, (Gray and
Precipitation especially in land-poor households. Mueller, 2012;
Drought linked to decreased marriage-related migration by women. Morrissey,
Precipitation variability and drought linked to labour migration 2013;
from rural to urban areas. Hermans-
Precipitation variability and drought linked to out-migration to Neumann et
communities where precipitation variability and drought probability al., 2017;
are lower. Groth et al.,
High precipitation variability linked to increased migration, either 2021)
through increased non-farm activities, which enable migration
through economic resources or through insufficient agricultural
production, which increase migration needs.
Ghana Increased severity of drought and household insecurity linked to (Adger et al.,
reduced future migration intentions of households. 2021)
Malawi Precipitation shocks linked to rural out-migration to communities (Lewin et al.,
where precipitation variability and drought probability are lower. 2012; Suckall
Precipitation shocks (flood and droughts) linked to longer-term et al., 2015)
urban migration and/or reverse (i.e., urban-rural) migration.
Mali Decreased precipitation linked to overall increase in out-migration (Grace et al.,
� where farming families or individuals from farming communities 2018)
will leave their origin community � and some changes in duration
and destination of trips. These moves can be either permanent or
short-term, domestic or international.
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Niger Drought linked to economically-induced migration of households (Afifi, 2011)
from rural areas to cities. Drought also linked to temporary
international migration.
Burkina High temperatures linked to negative effects on all migration (Gray and
Faso streams including international migration, much of which is to Wise, 2016)
neighbouring countries. International migration also declines with
precipitation.
Senegal No detected linkages between climate and migration. (Gray and
Wise, 2016)
Nigeria No detected linkages between climate and migration. (Gray and
Wise, 2016)
Botswana
Temperature Increased temperatures and precipitation linked to decreased (Mueller et al.,
and South internal migration. 2020)
precipitation Africa
Higher temperatures and precipitation extremes linked to increased (Mastrorillo et
rural out-migration, especially among black and low-income South al., 2016)
Africans.
Senegal Precipitation variability, drought and increased temperatures linked (Hummel,
to seasonal migration from rural to urban areas. 2016)
Zambia Hotter and drier climate linked to inter-district migration of wealthy (Nawrotzki
districts. Poor districts characterised by climate-related immobility. and DeWaard,
2018)
1
2
3 Table Box 9.8.2: Projected numbers and shares of internal climate migrants in 2050 by sub-regions of sub-Saharan
4 Africa. Projections are for internal migration driven by three slow-onset climate hazards (water stress, crop failure, and
5 sea level rise), and excluding rapid-onset hazards such as floods and tropical cyclones. As such, they present a lower-
6 bound estimate of potential climate change impacts on internal migration. Projections are for two warming scenarios:
7 low emissions (RCP2.6) and high emissions (RCP8.5), both coupled with a socioeconomic pathway (SSP4) in which
8 low-income countries have high population growth, high rates of urbanisation, and increasing inequality within and
9 among countries. By 2050, between 17.4 million (RCP2.6) and 85 million (RCP8.5) people (up to 4% of the region's
10 total population) could be moving as a consequence of climate impacts on water stress, crop productivity and sea level
11 rise. More inclusive socioeconomic pathways with lower population growth are projected to reduce these risks. West
12 Africa has the highest levels of climate migrants, potentially reaching more than 50 million, suggesting that climate
13 impacts will have a particularly pronounced impact on future migration in the region. In East Africa, out-migration
14 hotspots include coastal regions of Kenya and Tanzania, western Uganda and parts of the northern highlands of
15 Ethiopia. Kampala, Nairobi and Lilongwe may become hotspots of climate in-migration, coupled with existing rural to
16 urban migration trends, and a high likelihood of movement toward non-climate-related sources of income in cities.
17 Source: (Rigaud et al., 2018).
Region Global warming around 2.5癈 Global warming around 1.7癈
above pre-industrial by 2050 above pre-industrial by 2050
(RCP8.5) (RCP2.6)
East Africa Average number of internal 10.1 6.9
migrants by 2050 (million)
Internal climate migrants as 1.28% 0.87%
percent of population 54.4 17.9
West Africa Average number of internal
migrants by 2050 (million)
Internal climate migrants as 6.87% 2.27%
percent of population
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Central Average number of internal 5.1 2.6
Africa migrants by 2050 (million)
Internal climate migrants as 1.31% 0.66%
percent of population
Southern Average number of internal 1.5 0.9
Africa migrants by 2050 (million)
Sub- Internal climate migrants as 2.31% 1.40%
Saharan percent of population
Africa
Average number of internal 71.1 28.3
migrants by 2050 (million)
Minimum (left) and 56.6 85.7 17.4 39.9
maximum (right) million
Internal climate migrants as 3.49% 1.39%
percent of population
Minimum (left) and 2.71% 4.03% 0.91% 2.04%
maximum (right) percent
1
2
3 [END BOX 9.8 HERE]
4
5
6 9.11.5 COVID-19 Recovery Stimulus Packages for Climate Action
7
8 The COVID-19 pandemic recovery effort includes significant opportunities for African countries to reduce
9 future vulnerability to compound climate, economic and health risks. Fiscal recovery packages could set
10 economies on a pathway towards net-zero emissions, reducing future climate risk or entrench fossil-fuel
11 intensive systems, exacerbating risk (Hepburn et al., 2020; Dibley et al., 2021; IEA, 2021). Investments in
12 renewable energy, building efficiency retrofits, education and training, natural capital (that is, ecosystem
13 restoration and ecosystem-based adaptation), R&D, connectivity infrastructure and sustainable agriculture
14 can help meet both economic recovery and climate goals (Hepburn et al., 2020; Dibley et al., 2021).
15
16 The impacts of the COVID-19 pandemic have been substantially worsened by climate hazards in many
17 places. In others, outbreak response has been disrupted (Phillips et al., 2020; Kruczkiewicz et al., 2021).
18 These vulnerabilities are rooted in insufficient disaster preparedness infrastructure but are almost always
19 worsened by social and economic inequality. Ensuring the most vulnerable populations are properly
20 protected from climate change has co-benefits for recovery from the COVID-19 pandemic (Manzanedo and
21 Manning, 2020). In particular, efforts to reduce syndemic vulnerabilities across key sectors (especially
22 health, livelihoods and food security) will lessen climate change impacts and will also reduce the risk and
23 impacts of future epidemics and pandemics, for example, during the pandemic, water scarcity has been a
24 barrier to a key risk mitigation behaviour (handwashing). In the long-term, development efforts focused on
25 water, sanitation and hygiene (WASH) will reduce this vulnerability and also reduce the health toll of
26 diarrheal disease linked to climate change (Anim and Ofori-Asenso, 2020; Zvobgo and Do, 2020). Spending
27 recovery funds on social safety nets will reduce inequality and protect the most vulnerable communities
28 (especially women and low-income and marginalised communities) from the social and economic impacts of
29 disasters. Key among these safety nets is universal health coverage, including low- or no-cost access to
30 essential medicine, high-quality preventative care, financial protections against medical debt and increased
31 geographic and population coverage for all services (Hallegatte et al., 2016). All of these are key
32 components of climate change adaptation for health and will reduce both the rate at which future outbreaks
33 start and their total scope and impact (Carlson et al., 2021). The co-benefits of multilateral cooperation on
34 the attainment of universal health coverage will be a key determinant of success or failure in both climate
35 change adaptation and pandemic preparedness.
36
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1
2 [START BOX 9.9 HERE]
3
4 Box 9.9: Climate Change and Security: Interpersonal Violence and Large-scale Civil Conflict
5
6 There is substantial evidence that climate variability influences human security across Africa (see Chapter 7
7 WGII Section 7.2.7 and 7.3.3 7). However, the strength and nature of this link depend on socioeconomic and
8 institutional conditions, and climate is just one of many factors influencing violence and civil conflict
9 (Schleussner et al., 2016a; von Uexkull et al., 2016; Linke et al., 2018; Mach et al., 2019; van Weezel, 2019;
10 Ide et al., 2020).
11
12 Projections of security implications of long-run climate change in Africa are uncertain, as they rely on
13 extrapolating observed effects of short-run climate variability (Burke et al., 2014). Lack of detection and
14 attribution studies limit assessment of the impacts of observed anthropogenic climate change on security.
15
16 Interpersonal violent crime
17
18 Evidence from across the globe finds that interpersonal violence, ranging from use of profanity to violent
19 crime, increases with temperature and sometimes low rainfall (Hsiang et al., 2013a; Burke et al., 2014; Gates
20 et al., 2019). The effect of temperature may be driven by a physiological mechanism (Morrison et al., 2008;
21 Seo et al., 2008; Ray et al., 2011), while effects of rainfall may operate through an agricultural yield impacts
22 channel (Burke et al., 2014). While few studies link interpersonal violence to climate in Africa, Gates et al.
23 (2019) documents homicide risks increasing under high temperatures in South Africa, and similarity across
24 diverse study settings suggests temperature-induced violent crime likely generalizes to Africa (Burke et al.,
25 2014).
26
27 Large-scale intergroup conflict
28
29 Climatic conditions also change the risk of large-scale conflicts such as riots, ethnic conflicts and civil war
30 (Burke et al., 2014; Koubi, 2019). The effects of temperature are particularly well-studied in Africa. Risk of
31 violent conflict rises with temperature in Sudan and South Sudan (Maystadt and Ecker, 2014; Maystadt et
32 al., 2014; Scheffran et al., 2014), Kenya (Hsiang et al., 2013b; Scheffran et al., 2014), the East African
33 region (O'Loughlin et al., 2012) and across sub-Saharan Africa (Burke et al., 2009; O'Loughlin et al., 2014;
34 Witmer et al., 2017). Estimates indicate that warming trends since 1980 have elevated conflict risk across
35 sub-Saharan Africa by 11% (Burke et al., 2009; Carleton et al., 2016).
36
37 Periods of low rainfall or flooding also contribute to social instability and upheaval across Africa (Miguel et
38 al., 2004; Ralston, 2015; von Uexkull et al., 2016; Harari and Ferrara, 2018; van Weezel, 2019; Ide et al.,
39 2020). The link between rainfall and conflict appears likely due to crop losses and declines in economic
40 opportunity. One study finds that dry growing seasons increase conflict incidence across 36 African nations,
41 with spillover effects from the location of climate shock to neighbouring communities (Harari and Ferrara,
42 2018). Conflict-inducing impacts of drought have also been uncovered in Somalia (Maystadt and Ecker,
43 2014), Uganda, Sudan, Ethiopia and Kenya (Fjelde and von Uexkull, 2012; Hendrix and Salehyan, 2012;
44 Couttenier and Soubeyran, 2014; Ralston, 2015; Linke et al., 2018; van Weezel, 2019), the Democratic
45 Republic of Congo (von Uexkull et al., 2020) and in a pooled sample of African and Asian countries (von
46 Uexkull et al., 2016). Extremely high rainfall may also incite conflict risk, although results are mixed
47 (Hendrix and Salehyan, 2012; Raleigh and Kniveton, 2012). This uncertainty, combined with large
48 uncertainties in rainfall projections under climate change, render future impacts of anthropogenic emissions
49 on rainfall-induced conflict in Africa highly uncertain.
50
51 While conflict-climate links have been repeatedly identified in Africa, climate is one of many interacting
52 conflict risk factors and appears to explain only a small share of total variation in conflict incidence (von
53 Uexkull et al., 2016; Mach et al., 2019; van Weezel, 2019).
54
55 Opportunities for adaptation
56
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1 Adaptive capacity with respect to climate and conflict remains low in Africa (Sitati et al., 2021). For
2 example, one study finds that relative to each country's optimal annual temperature, realized temperatures
3 across sub-Saharan Africa increase the annual incidence of war by 29.3% on average (Carleton et al., 2016).
4 Another finds that rising temperatures due to climate change may lead to higher levels of violence in sub-
5 Saharan Africa if political rights do not improve from current conditions (Witmer et al., 2017). Available
6 studies on adaptation in conflict-affected areas tend to have a narrow focus, particularly on agriculture-
7 related adaptation in rural contexts and adaptation by low-income actors, with little known beyond these
8 contexts (Sitati et al., 2021). Literature on the gender dimension of climate adaptation in conflict-affected
9 countries is also limited (Sitati et al., 2021).
10
11 Migration is a common response (Sitati et al., 2021) and may be an effective adaptive response to climate-
12 induced conflict. Bosetti et al. (2018) find that countries with high emigration propensity display lower
13 sensitivity of conflict to temperature, with no evidence of detrimental impacts on the destination countries.
14 Indigenous knowledge has also been applied to enable adaptation amidst conflict, for example, in Libya, to
15 deal with erratic rainfall (Biagetti, 2017).
16
17 Other socioeconomic factors have been identified as adaptive opportunities. Rising incomes may mitigate
18 conflict-climate relationships (Carleton et al., 2016), while weak institutions, lack of political freedom,
19 agricultural dependence and exclusion of ethnic groups increase their strength (Schleussner et al., 2016a; von
20 Uexkull et al., 2016; Witmer et al., 2017; Ide et al., 2020). In particular, agriculturally dependent and
21 politically excluded groups in Africa are especially vulnerable to the impact of drought on conflict (von
22 Uexkull et al., 2016; Koubi, 2019). Household-level resilience to economic shocks has been shown to lower
23 support for violence after drought (von Uexkull et al., 2020). Local-level institutions have also been shown
24 to support non-violence under adverse climate conditions (Bogale and Korf, 2007).
25
26 These findings suggest that ameliorating ethnic tensions, improving political institutions, and investing in
27 economic diversification and household resilience could mitigate future impacts of climate change on
28 conflict.
29
30 [END BOX 9.9 HERE]
31
32
33 9.12 Heritage
34
35 Africa is a rich reservoir of heritage resources and indigenous knowledge, showcased by about 96 sites
36 inscribed by UNESCO as World Heritage Sites (UNESCO, 2018b). These include 53 sites specifically
37 denoted as having great cultural importance and 5 sites with mixed heritage values. Unfortunately, valuable
38 cultural heritage in forms of tangible evidence of past human endeavour, and the intangible heritage
39 encapsulated by diverse cultural practices of many communities (Feary et al., 2016), is under great threat
40 from climate change.
41
42 9.12.1 Observed Impacts on Cultural Heritage.
43
44 For more than 10,000 years, Africans recorded over 8,000 painted and engraved images on rock shelters and
45 rock outcroppings across 800 exceptional rock art sites of incalculable value (Hall et al., 2007; di Lernia and
46 Gallinaro, 2011; di Lernia, 2017; Clarke and Brooks, 2018; Barnett, 2019), but which are exceptionally
47 fragile to the elements. Unfortunately, there has been a poor study of direct climate change impacts on rock
48 art across Africa.
49
50 Underwater heritage includes shipwrecks and artefacts lost at sea and extends to prehistoric sites, sunken
51 towns and ancient ports that are now submerged due to climatic or geological changes (Spalding, 2011). Off
52 the shores of Africa, about 111 shipwrecks have been documented, with South Africa having a major share
53 of about 41 sites. The sunken Egyptian city of Thonis-Heracleion and its associated 60+ shipwrecks reflect
54 the richness of Africa's waters. Unfortunately, increased storm surges and violent weather currently threaten
55 the integrity of shipwrecks by accelerating the destruction of wooden parts and other features (Harkin et al.,
56 2020). However, climate change impacts on underwater cultural heritage sites are poorly studied, as it
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1 requires specialist assessment techniques (Feary et al., 2016), and marine archaeology studies are not well-
2 established in Africa.
3
4 Intangible heritage includes instruments, objects, artefacts and cultural spaces associated with communities,
5 and are almost always held orally (UNESCO, 2003). Loss of heritage assets may be a direct consequence of
6 climate change/variability (Markham et al., 2016), or a consequence of indirect factors resulting from
7 climate change, for example, economic instability and poor decision-making in areas of governance. In
8 northern Nigeria, climate change exacerbates the impact of poor land use decisions, reducing the flow of the
9 Yobe River and negatively impacting the Bade fishing festival because the available fish species continue to
10 decline (Oruonye, 2010). Similarly, Lake Sank� in Mali has been degraded by a combination of urban
11 development and poor rainfall, threatening the Sank� mon collective fishing rite (UNESCO, 2018b).
12
13 Migration related to climate change and climatic events could offer openings to women and young people to
14 become de facto family heads (Kaag et al., 2019). However, such societal changes also increase community
15 vulnerability to the loss of cultural knowledge held by village elders. For example, in Mauritius, the Sega
16 tambour Chagos music is at risk, as elders familiar with the landscape pass on (Boswell, 2008).
17
18 Case study: Traditional earthen `green energy' buildings
19 Historically, Africa has had a unique and sustainable architecture (Diop, 2018) characterised by area-
20 specific, traditional earthen materials and associated indigenous technology. Key examples include Ti閎閘�
21 in Burkina Faso, Walata in Mauritania, Akan in Ghana, Ghadames in Libya, Old Towns of Djenn� in Mali
22 (World Heritage Site) and other diverse earthen architecture across sub-Saharan Africa. Adegun and Adedeji
23 (2017) indicate that earthen materials provide advantages in thermal conductivity, resistivity and diffusivity,
24 indoor and outdoor temperature, as well as cooling and heating capacities. Moreover, earthen materials are
25 recyclable and environmentally `cleaner' (Sanya, 2012) because of the absence or small quantity of cement
26 in production, thus reducing carbon emissions. Despite these advantages, the expertise and socio-cultural
27 ceremonies that accompany building and renewal of earthen architecture are disappearing fast (Adegun and
28 Adedeji, 2017). Further, earthen construction is being threatened by extreme climatic variability and
29 changing climate that exacerbates decay (Brimblecombe et al., 2011; Bosman and Van der Westhuizen,
30 2014; Brooks et al., 2020).
31
32 9.12.2 Projected Risks
33
34 Sea level rise and its associated hazards will present increasing climate risk to African heritage in the coming
35 decades (Marzeion and Levermann, 2014; Reimann et al., 2018; Brito and Naia, 2020) (Figure 9.38).
36 Although no continental assessment has quantified climate risk to African heritage and little is known of near
37 term exposure to hazards such as sea level rise and erosion, for a handful of coastal heritage sites included in
38 global or Mediterranean studies, 10 cultural sites are identified to be physically exposed to sea level rise by
39 2100 at high emissions scenarios (RCP8.5) (Marzeion and Levermann, 2014; Reimann et al., 2018), of
40 which, 7 World Heritage Sites in the Mediterranean are also projected to face medium or high risk of erosion
41 (Reimann et al., 2018) (Figure 9.38). Further, Brito and Naia (2020) identify natural heritage sites across 27
42 African countries that will be affected by sea level rise by 2100 (RCP8.5), of which 15 sites covering eight
43 countries demonstrated a high need for proactive management actions because of high levels of biodiversity,
44 international conservation relevance and exposure to sea level rise (Figure 9.38). These nascent studies
45 highlight the potential severity of risk and loss and damage from climate change to African heritage, as well
46 as gaps in knowledge of climate risk to African cultural and natural, particularly concerning bio-cultural
47 heritage.
48
49
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1
2 Figure 9.38: Risk to Africa's cultural and natural coastal heritage sites from sea level rise and erosion by 2100
3 (RCP8.5). Panel (a) Exposed World Heritage sites projected to be affected by sea level rise under a high-end sea level
4 rise scenario (RCP8.5, 2100) (Marzeion and Levermann, 2014; Reimann et al., 2018). Panel a call out) Sites identified
5 to be also exposed to medium and high erosion risk under current and future conditions (2000 and 2100) under a high-
6 end sea level rise scenario (Reimann et al., 2018). Panel (b) The 15 topmost African natural sites (coastal protected
7 areas) identified to be exposed to negative impacts from sea level rise and as priority for conservation (Brito and Naia,
8 2020).
9
10
11 Although climate change is a significant risk to heritage sites (Brito and Naia, 2020), there is little research
12 on how heritage management is adapting to climate change, and particularly, whether the capacity of current
13 heritage management systems can prepare for and deal with consequences of climate change (Phillips, 2015)
14 (see also Cross-Chapter Box SLR in Chapter 3).
15
16 Worsening climate impacts are cumulative and often exacerbate the vulnerability of cultural heritage sites to
17 other existing risks, including conflict, terrorism, poverty, invasive species, competition for natural resources
18 and pollution (Markham et al., 2016). These issues may affect a broad range of tourism segments, including
19 beach vacation sites, safari tourism, cultural tourism and visits to historic cities (UNWTO, 2008). Climate
20 change impacts have the potential to increase tourist safety concerns, especially at sites where increased
21 intensity of extreme weather events or vulnerability to floods and landslides are projected (Markham et al.,
22 2016) (see also Cross-Chapter Box EXTREMES in Chapter 2). There may also be circumstances where
23 interventions required to preserve and protect the resource alter its cultural significance (van Wyk, 2017).
24
25 9.12.3 Adaptation
26
27 Research highlights potential in integrating indigenous knowledge, land use practices, scientific knowledge
28 and heritage values to co-produce tools that refine our understanding of climate change and variability and
29 develop comprehensive heritage adaptation policy (Ekblom et al., 2019) (Table 9.13).
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1 Table 9.13: Examples of responses to climate change impacts to heritage sites.
Heritage Type Example Type of Intervention Focus or Main Intervention State of Materials Final State Literature
Climate Activity Activity of Heritage
Impact
Ancient Historic Ounga Coastal Archaeological Building repairs Mixed. Fort is in good Some (Slim et al.,
buildings Byzantine Fort erosion conservation of fort to outer walls of condition, but other aspects of 2004)
and associated fort but other parts of the site are site well
archaeological archaeological under threat of coastal preserved,
remains, Tunisia areas no erosion, particularly other parts
intervention lesser archaeological damaged
remains of other
periods
Archaeolo Sabratha, Roman Sea level Monitoring of None Loss of archaeological Some (Abdalahh,
gical sites City, Libyan rise, local condition remains into the sea aspects of 2011)
coast flooding and site well
coastal preserved,
erosion other parts
damaged
Living Cities / Lamu Old Town Sea Level Lamu Old Town Draft for National Mangrove forests Continuing (Wanderi,
towns and archipelago, Rise managed by National Policy for provide protection deterioratio 2019)
Museums of Kenya the Disaster
Tangible Kenya impacting from storm surges and n
low lying mangrove forests by Management in coastal erosion.
areas and Community Forest Kenya Changing biodiversity
climate Associations and of mangroves is
variability Forest Conservation threatening mangroves
impacting and Management Act which threaten Lamu
protective of 2016. Changes in Old Town
mangroves biodiversity and
cultural resilience to
climate shocks.
Mud Ti閎閘�, Burkina Climate Local community Improvements to Current and ongoing Stable (Birabi and
buildings Faso variability conservation drainage and land conservation Nawangwe,
causing security, 2011)
flooding, development of
erosion. conservation and
management
plans.
Bio- Rock art Golden Gate Precipitation Monitoring of No known Biodeterioration of Increasing (Viles and
cultural Highlands, South and condition intervention condition of rock loss of Cutler, 2012)
Africa atmospheric surface rock
changes surfaces
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Intangible Language !Xun and Khwe causing Groups (youth) Documentation Non-formal, local and images (Bodunrin,
(indigenou Indigenous luxuriant on the rock 2019)
s) Rituals Youth of South lichen growth Farmer groups, Research, Formal, local surfaces
Africa Climate communities documentation Enhancem
1 Customs variability Formal, non-formal, ent,
& beliefs Indigenous causing Maasai community Identification, local, foreign promotion
Indigenou Language Use in drought and groups documentation, Formal, non-formal,
s Agricultural loss of plants research local Promotion, (Adeyeye et
engineerin Radio Climate Malink閟, Bambara Formal, local transmissio al., 2020)
g systems Programming in variability and Buwa Identification, n
Nigeria increasing communities documentation, Formal, non-formal,
Arts and Enkipaata, frequency of Touat and Tidikelt preservation local, foreign promotion (UNESCO,
crafts Eunoto and drought communities Research, 2018a)
Olng'esherr identification,
Maasai male Climate Residents of oases, documentation promotion (UNESCO,
rites of passage variability groups, communities, 2009)
Sank� mon causing agricultural Research,
fishing festival drought cooperative societies identification, transmissio
in Mali documentation,
Climate preservation, n (Mokadem et
Water measurers variability protection
of the Foggara reducing al., 2018)
irrigation system rainfall
in Algeria Increased Transmissi (UNESCO,
siltation and on, 2003)
Traditional crafts sandstorms promotion, (Shabani et al.,
made from Climate enhanceme 2012)
various parts of variability nt,
the Date Palm in causing revitalizati
Egypt, flooding on
Mauritania, Climate
Morocco, Sudan, variability
Tunisia and causing shift
other countries in plant
outside Africa habitats
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1 Conservation of heritage may require offsetting the impact of loss through partial or total excavation under
2 certain circumstances, like environment instability, or where in situ heritage preservation is exorbitant in cost
3 (Maarleveld and Gu閞in, 2013).
4
5 Although many underwater shipwrecks and ruins of cities are currently preserved better in situ than similar
6 sites on land (Feary et al., 2016), preserving such heritage is often financially prohibitive with many physical
7 and technical challenges. Further, skill capacities of heritage agencies are limited to a few qualified
8 archaeologists in Africa (Maarleveld and Gu閞in, 2013).
9
10 For centuries, Africans have drawn on intangible heritage to enhance their resilience to climatic variability
11 and support adaptation practices. For example, pastoralist communities have historically translated their
12 experiences into memories that can be `translated' into diverse adaptive practices (Oba, 2014). In coastal
13 Kenya, Mijikenda communities rely on indigenous knowledge and practices used in the management of the
14 sacred Kaya Forests to adapt their farming to a changing climate (Wekesa et al., 2015).
15
16 Hence, preservation measures for transforming oral information into written records should ensure viability
17 of intangible cultural heritage by giving due consideration to the confidentiality of culturally sensitive
18 information and intellectual property rights (Feary et al., 2016).
19
20 Inclusion of cultural landscapes and intangible heritage in the landscape approach at the regional scale
21 development planning processes may have significant impacts on protected area management (Feary et al.,
22 2016). For example, at the Domboshava rock art site in Zimbabwe, all management decisions are taken in
23 direct consultation with traditional leaders and other stakeholders from surrounding communities (Chirikure
24 et al., 2010). Such adaptation strategies promote a more open-minded approach to heritage by leveraging
25 local development (UNESCO, 2018b).
26
27 Lack of expertise and resources, together with legislation that privileges certain typologies of heritage, seem
28 to limit implementation of approved policies (Ndoro, 2015). Additionally, cultural heritage has least priority
29 in terms of budgetary allocation, capacity building and inclusion into school curricula. Failure to consider the
30 views of people who attach spiritual significance to places is detrimental to the conservation of heritage
31 places (Bwasiri, 2011). In particular, documented cases of local people having to pay an entrance fee, like
32 tourists, to access burial grounds and places of pilgrimage negate local participation in cultural site
33 management (Ndoro, 2015).
34
35 In the long term, heritage managers and local authorities could shift from planning primarily for disaster
36 response and recovery to strategies that focus on disaster preparedness, reducing the vulnerability of sites
37 and strengthening resilience of local communities (UNFCCC, 2007; Domke and Pretzsch, 2016). This could
38 evolve into innovative approaches that integrate community, government and the research sector in
39 productive cultural heritage management partnerships.
40
41 There is a need for institutions to establish, maintain and update a comprehensive inventory of underwater
42 cultural heritage. This can be done using non-intrusive, detailed mapping of the wreck site and a 3D model
43 from which scientists can reconstruct the site in detail (Maarleveld and Gu閞in, 2013).
44
45
46 [START FAQ9.1 HERE]
47
48 FAQ 9.1: Which climate hazards impact African livelihoods, economies, health and well-being the
49 most?
50
51 Climate extremes, particularly extreme heat, drought, and heavy rainfall events, impact the livelihoods,
52 health, and well-being of millions of Africans. They will also continue to impact African economies, limiting
53 adaptation capacity. Interventions based on resilient infrastructure and technologies can achieve numerous
54 developmental and adaptation co-benefits.
55
56 Rainfall impacts African livelihoods and well-being primarily through drought and heavy rainfall events.
57 Drought frequency, duration and intensity is projected to increase in most parts of Africa, but particularly in
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FINAL DRAFT Chapter 9 IPCC WGII Sixth Assessment Report
1 West Africa and the Sahel. By 2030, about 250 million people may experience high water stress in Africa,
2 with up to 700 million people displaced as a result. In sub-Saharan Africa, floods are expected to displace an
3 average of 2.7 million people in any given year in the future. Changing rainfall distributions together with
4 warming temperatures will alter the distributions of disease vectors like mosquitoes and midges. Malaria
5 vector hotspots and prevalence are projected to increase in East and southern Africa and the Sahel under
6 RCP4.5 by the 2030s, exposing an additional 50.6�62.1 million people to malaria risk.
7
8 Increases in the number of hot days and nights, as well as in heatwave intensity and duration, have had
9 negative impacts on agriculture, human health, water availability, energy demand and livelihoods. By some
10 estimates, African countries' GDP per capita is on average 13.6% lower since 1991 than if anthropogenic
11 warming had not occurred. In the future, high temperatures combined with high humidity exceed the
12 threshold for human and livestock tolerance over larger parts of Africa and with greater frequency. Increased
13 average temperatures and lower rainfall will further reduce economic output and growth in Africa, with
14 larger negative impacts than on other regions of the world.
15
16 Resilient infrastructure and technologies are required to cope with the increasing climate variability and
17 change (Figure FAQ 9.1). These include improving housing to limit heat and exposure, along with
18 improving water and sanitation infrastructure. Such interventions to ensure that the most vulnerable are
19 properly protected from climate change have many co-benefits, including for pandemic recovery and
20 prevention.
21
22
23
24 Figure FAQ9.1.1: A schematic illustration of the interconnectedness of different sectors and impacts that spillover to
25 affect the health and well-being of African people.
26
27 [END FAQ9.1 HERE]
28
29
30 [START FAQ9.2 HERE]
31
32 FAQ9.2: What are the limits and benefits of climate change adaptation in Africa?
33
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1 The capacity for African ecosystems to adapt to changing environmental conditions is limited by a range of
2 factors, from heat tolerance to land availability. Adaptation across human settlements and food systems are
3 further constrained by insufficient planning and affordability. Integrated development planning and
4 increasing finance flows can improve African climate change adaptation.
5
6 Many species will lose all suitable habitats due to increases in temperature by 2100. Coupled with projected
7 losses of Africa's protected areas, higher temperatures will also reduce carbon sinks and other ecosystem
8 services. Many nature-based adaptation measures (e.g., for coral reefs, mangroves, marshes) are no longer
9 effective at 1.5篊 of global warming. Human-based adaptation strategies for ecosystems reach their limits as
10 availability and affordability of land decreases, resulting in migration, displacement and relocation.
11
12 The limits to adaptation for human settlements arise largely from developmental challenges associated with
13 Africa's rapid urbanisation, poor development planning, and increasing numbers of urban poor residing in
14 informal settlements. Further limits arise from insufficient consideration of climate change in adaptation
15 planning and infrastructure investment and insufficient financial resources. There are also limits to
16 adaptation for food production strategies. Increasing climate events � droughts and floods � impose specific
17 adaptation responses which poorer households cannot afford. For instance, the use of early-maturing or
18 drought-tolerant crop varieties may increase resilience, but adoption by smallholder farmers is hindered by
19 the unavailability or unaffordability of seed.
20
21 Adaptation in Africa can reduce risks at current levels of global warming. However, there is very limited
22 evidence for the effectiveness of current adaptation at increased global warming levels. Ambitious, near-term
23 mitigation would yield the largest single contribution to successful adaptation in Africa.
24
25 Current adaptation finance flows are billions of USD less than the needs of African countries and around half
26 of finance commitments to Africa reported by developed countries remain undisbursed. Increasing
27 adaptation finance flows by billions of dollars (including public and private sources), removing barriers to
28 accessing finance and providing targeted country support can improve climate change adaptation across
29 Africa.
30
31 [END FAQ9.2 HERE]
32
33
34 [START FAQ9.3 HERE]
35
36 FAQ 9.3: How can African countries secure enough food in changing climate conditions for their
37 growing populations?
38
39 Climate change is already impacting African food systems and will worsen food insecurity in sub-Saharan
40 Africa in the future. An integrated approach to adaptation planning can serve as a flexible and cost-effective
41 solution for addressing African food security challenges.
42
43 Maize and wheat yields have decreased on average 5.8% and 2.3%, respectively, in Sub-Saharan Africa due
44 to climate change. Among the 135 million acutely food-insecure people in crisis globally, more than half (73
45 million) are in Africa. This is partly due to the growing severity of drought. Adding to these challenges,
46 Africa has the fastest-growing population in the world. Its population is expected to increase by roughly 50%
47 over the next fifteen years, growing from 1.2 billion people to over 1.8 billion by 2035.
48
49 Sustainable agricultural development combined with enabling institutional conditions, such as supportive
50 governance systems and policy, can provide farmers with greater yield stability in uncertain climate
51 conditions. It is also widely acknowledged that an integrated approach for adaptation planning that combines
52 (i) emerging Climate Information Services, (ii) capacity building, (iii) local and indigenous knowledge
53 systems and (iv) strategic financial investment can serve as a flexible and cost-effective solution for
54 addressing African food security challenges (Section 9.4.1.2; Box 9.2).
55
56 [END FAQ9.3 HERE]
57
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1
2 [START FAQ9.4 HERE]
3
4 FAQ9.4: How can African local knowledge serve climate adaptation planning more effectively?
5
6 A strong relationship between scientific knowledge and local knowledge is desirable, especially in
7 developing contexts where technology for prediction and modelling is least accessible.
8
9 In many African settings, farmers use the local knowledge gained over time � through experience and passed
10 on orally from generation to generation � to cope with climate challenges. Indigenous knowledge systems of
11 weather and climate patterns include early warning systems, agroecological farming systems and observation
12 of natural or non-natural climate indicators. For instance, biodiversity and crop diversification are used as a
13 buffer against environmental challenges: if one crop fails, another will survive. Local knowledge of seasons,
14 storms, and wind patterns is used to guide and plan farming and other activities.
15
16 Collaborative partnerships between research, agricultural extension services and local communities would
17 create new avenues for the co-production of knowledge in climate change adaptation to better inform
18 adaptation policies and practices across Africa (Section 9.4.3; Box 9.2).
19
20 [END FAQ9.4 HERE]
21
22
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