Final Government Distribution Chapter 9 IPCC AR6 WGIII
1
2 Table of Contents
3 Chapter 9: Buildings ...................................................................................................................... 9-1
4 Executive summary.......................................................................................................................... 9-4
5 9.1 Introduction .......................................................................................................................... 9-7
6 9.2 Services and components ................................................................................................... 9-10
7 9.2.1 Building types ............................................................................................................ 9-11
8 9.2.2 Building components and construction methods ....................................................... 9-11
9 9.2.3 Building services ........................................................................................................ 9-13
10 9.3 New developments in emission trends and drivers ............................................................ 9-15
11 9.3.1 Past and future emission trends .................................................................................. 9-15
12 9.3.2 Drivers of CO2 emissions and their climate impact ................................................... 9-19
13 9.3.3 Energy demand trends ................................................................................................ 9-25
14 9.4 Mitigation technological options and strategies towards zero carbon buildings................ 9-32
15 9.4.1 Key points from AR5 and special reports .................................................................. 9-32
16 9.4.2 Embodied energy and embodied carbon .................................................................... 9-32
17 9.4.3 Technological developments since AR5 .................................................................... 9-39
18 9.4.4 Case studies ................................................................................................................ 9-43
19 9.4.5 Low- and net zero energy buildings – exemplary buildings ...................................... 9-44
20 9.5 Non-technological and behavioural mitigation options and strategies .............................. 9-47
21 9.5.1 Non-technological determinants of energy demand and carbon emissions ............... 9-47
22 9.5.2 Insights from non-technological and behavioural interventions ................................ 9-48
23 9.5.3 Adoption of climate mitigation solutions– reasons and willingness .......................... 9-50
24 9.6 Global and regional mitigation potentials and costs .......................................................... 9-54
25 9.6.1 Review of literature calculating potentials for different world countries .................. 9-54
26 9.6.2 Assessment of the potentials at regional and global level .......................................... 9-57
27 9.6.3 Assessment of the potential costs............................................................................... 9-59
28 9.6.4 Determinants of the potentials and costs .................................................................... 9-62
29 9.7 Links to adaptation ............................................................................................................. 9-65
30 9.7.1 Climate change impacts and adaptation in buildings ................................................. 9-65
31 9.7.2 Links between mitigation and adaptation in buildings .............................................. 9-67
32 9.8 Links to sustainable development ...................................................................................... 9-68
33 9.8.1 Overview of contribution of mitigation options to sustainable development ............ 9-68
34 9.8.2 Climate mitigation actions in buildings and health impacts ...................................... 9-71
35 9.8.3 Other environmental benefits of mitigation actions ................................................... 9-75
36 9.8.4 Social well-being........................................................................................................ 9-76
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1 9.8.5 Economic implications of mitigation actions ............................................................. 9-77
2 9.9 Sectoral barriers and policies ............................................................................................. 9-79
3 9.9.1 Barriers, feasibility, and acceptance........................................................................... 9-79
4 9.9.2 Rebound effects.......................................................................................................... 9-82
5 9.9.3 Policy packages for the decarbonisation of buildings ................................................ 9-82
6 9.9.4 Financing mechanisms and business models for reducing energy demand ............... 9-89
7 9.9.5 Policies mechanisms for financing for on-site renewable energy generation ............ 9-90
8 9.9.6 Investment in building decarbonisation ..................................................................... 9-93
9 9.9.7 Governance and Institutional Capacity ...................................................................... 9-93
10 9.10 Knowledge Gaps ................................................................................................................ 9-96
11 Frequently Asked Questions .......................................................................................................... 9-97
12 References ...................................................................................................................................... 9-99
13
14
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Final Government Distribution Chapter 9 IPCC AR6 WGIII
1 Executive summary
2 Global Greenhouse Gas (GHG) emissions from buildings were in 2019 at 12 GtCO2eq., equivalent
3 to 21% of global GHG emissions that year, out of which 57% were indirect emissions from offsite
4 generation of electricity and heat, 24% direct emissions produced onsite and 18% were embodied
5 emissions from the use of cement and steel (high evidence, high agreement). More than 95% of
6 emissions from buildings were CO2 emissions, CH4 and N2O represented 0.08%, and emissions from
7 halocarbon contributed by 3% to global GHG emissions from buildings. If only CO2 emissions would
8 be considered, the share of CO2 emissions from buildings out of global CO2 emissions increases to 31%.
9 Global final energy demand from buildings reached 128.8 EJ in 2019, and global electricity demand
10 was slightly above 43 EJ. The former accounted for 31% of global final energy demand and the latter
11 for 18% of global electricity demand. Residential buildings consumed 70% of global final energy
12 demand from buildings. Over the period 1990-2019, global CO2 emissions from buildings increased by
13 50%, global final energy demand grew by 38 and global final electricity demand increased by 161%
14 (high evidence, high agreement) {9.3}.
15 Drivers of GHG emissions in the building sector were assessed using the SER (Sufficiency,
16 Efficiency, Renewable) framework. Sufficiency measures tackle the causes of GHG emissions by
17 avoiding the demand for energy and materials over the lifecycle of buildings and appliances.
18 Sufficiency differs from efficiency in that the latter is about the continuous short-term marginal
19 technological improvements, which allows doing less with more in relative terms without considering
20 the planetary boundaries, while the former is about long-term actions driven by non-technological
21 solutions (i.e., land use management and planning), which consume less in absolute term and are
22 determined by biophysical processes. Sufficiency addresses the issue of a fair consumption of space
23 and resources. The remaining carbon budget, and its normative target for distributional equity, is the
24 upper limit of sufficiency, while requirements for a decent living standard define the minimum level of
25 sufficiency. The SER framework introduces a hierarchical layering which reduces the cost of
26 constructing and using buildings without reducing the level of comfort of the occupant. Sufficiency
27 interventions in buildings include the optimisation of the use of building, repurposing unused existing
28 buildings, prioritising multi-family homes over single-family buildings, and adjusting the size of
29 buildings to the evolving needs of households by downsizing dwellings. Sufficiency measures do not
30 consume energy during the use phase of buildings.
31 In most regions, historical improvements in efficiency have been approximately matched by
32 growth in floor area per capita. Implementing sufficiency measures that limit growth in floor area
33 per capita, particularly in developed regions, reduces the dependence of climate mitigation on
34 technological solutions (medium evidence, medium agreement). At a global level, up to 17% of the
35 mitigation potential could be captured by 2050 through sufficiency interventions (medium evidence,
36 medium agreement). Sufficiency is an opportunity to avoid locking buildings in carbon-intensive
37 solutions. Density, compacity, building typologies, bioclimatic design, multi-functionality of space,
38 circular use of materials, use of the thermal mass of buildings (to store heat for the cold season and to
39 protect occupants from high temperatures (i.e. heatwaves), when designing energy services, moving
40 from ownership to usership of appliances and towards more shared space, are among the sufficiency
41 measures already implemented in the leading municipalities. At the global level, the main drivers of
42 emissions include (i) population growth, especially in developing countries, (ii) increase in floor area
43 per capita, driven by the increase of the size of dwellings while the size of households kept decreasing,
44 especially in developed countries, (iii) the inefficiency of the newly constructed buildings, especially
45 in developing countries, and the low renovation rates and ambition level in developed countries when
46 existing buildings are renovated, iv) the increase in use, number and size of appliances and equipment,
47 especially ICT and cooling, driven by the growing welfare (income), and (v) the continued reliance on
48 fossil fuel based electricity and heat slow decarbonisation of energy supply. These factors taken together
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1 are projected to continue driving GHG emissions in the building sector in the future (high evidence,
2 high agreement) {9.2, 9.3, 9.4, 9.5, 9.6, and 9.9}.
3 Bottom-up studies show a mitigation potential up to 85% in Europe and North America and up
4 to 45% in Asia Pacific Developed compared to the baselines by 2050, even though they sometimes
5 decline (robust evidence, high agreement). In developing countries, bottom-up studies estimate the
6 potential of up to 40-80% in 2050, as compared to their sharply growing baselines (medium
7 evidence, high agreement). The aggregation of results from all these bottom-up studies translates
8 into a global mitigation potential by 2050 of at least 8.2 GtCO2, which is equivalent to 61% of
9 their baseline scenario. The largest mitigation potential (5.4 GtCO2) is available in developing
10 countries while developed countries will be able to mitigate 2.7 GtCO2. These potentials represent the
11 low estimates, and the real potential is likely to be higher. These estimated potentials would be higher
12 if embodied emissions in buildings and those from halocarbons would be included (low evidence, high
13 agreement) {9.3, 9.6,}.
14 The development, since Assessment Report 5 (AR5), of integrated approaches to construction and
15 retrofit of buildings has led to the widespread of zero energy/carbon buildings in all climate zones.
16 The complementarity and the interdependency of measures lead to cost reduction while optimising the
17 mitigation potential grasped and avoiding the lock-in-effect. The growing consideration of integrated
18 approach to construction of new buildings as well as to the renovation of existing buildings results in a
19 lower relevance of the step-by-step approach to renovate buildings and to breaking down the potential
20 into cost categories, as to deliver deep mitigation and cost savings technologies and approaches shall
21 be applied together in an integrated and interdependent manner (medium evidence, high agreement).
22 The potential associated with the sufficiency measures as well as the exchange of appliances,
23 equipment, and lights with efficient ones is at cost below USD0 tCO2-1 (high evidence, high agreement).
24 The construction of high-performance buildings will become by 2050 a business-as-usual technology
25 with costs below USD20 tCO2-1 in developed countries and below USD100 tCO2-1 in developing
26 countries (medium evidence, high agreement). For existing buildings, there have been many examples
27 of deep retrofits where additional costs per CO2 abated are not significantly higher than those of shallow
28 retrofits. However, for the whole stock they tend to be in cost intervals of 0-200USD tCO2-1 and
29 >200USD tCO2-1 (medium evidence, medium agreement) . Literature emphasizes the critical role of the
30 decade between in 2020 and 2030 in accelerating the learning of know-how and skills to reduce the
31 costs and remove feasibility constrains for achieving high efficiency buildings at scale and set the sector
32 at the pathway to realize its full potential (high evidence, high agreement) {9.6, 9.9}.
33 The decarbonisation of buildings is constrained by multiple barriers and obstacles as well as
34 limited flow of finance (robust evidence, high agreement). The lack of institutional capacity,
35 especially in developing countries, and appropriate governance structures slow down the
36 decarbonisation of the global building stock (medium evidence, high agreement). The building
37 sector stands out for its high heterogeneity, with many different building types, sizes, and operational
38 uses. Its segment representing rented property faces principal/agent problems where the tenant benefits
39 from the decarbonisation investment made by the landlord. The organisational context and the
40 governance structure could trigger or hinder the decarbonisation of buildings (high evidence, high
41 agreement). Global investment in the decarbonisation of buildings was estimated at USD164 billion in
42 2020, not enough to close the investment gap (robust evidence, high agreement) {9.9}.
43 Policy packages based on the SER (Sufficiency, Efficiency, Renewables) framework could grasp
44 the full mitigation potential of the global building stock (medium evidence, high agreement). Low
45 ambitious policies will lock buildings in carbon for decades as buildings last for decades if not
46 centuries (high evidence, high agreement). Building energy codes is the main regulatory
47 instrument to reduce emissions from both new and existing buildings (high evidence, high
48 agreement). Most advanced building energy codes include bioclimatic design requirements to capture
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1 the sufficiency potential of buildings, efficiency requirements by using the most efficient technologies
2 and requirements to increase the integration of renewable energy solutions to the building shape. Some
3 announced building energy codes extend these requirements from the use phase to the whole building
4 lifecycle. Building energy codes are proven to be especially effective if compulsory and combined with
5 other regulatory instruments such as minimum energy performance standard for appliances and
6 equipment, especially if the performance level is set at the level of the best available technologies in
7 the market (robust evidence, high agreement). Market-based instruments such as carbon taxes with
8 recycling of the revenues and personal or building carbon allowances also contribute to foster the
9 decarbonisation of the building sector (robust evidence, high agreement) . Requirements to limit the
10 use of land and property taxes are also considered effective policies to limit urban sprawl and to
11 prioritise multi-family buildings over single-family homes (medium evidence, high agreement) {9.9}.
12 Actions are needed to adapt buildings to future climate while ensuring wellbeing for all. The
13 expected heatwaves will inevitably increase cooling needs to limit the health impacts of climate
14 change (medium evidence, high agreement). Global warming will impact cooling and heating needs
15 but also the performance, durability and safety of buildings, especially historical and coastal ones,
16 through changes in temperature, humidity, concentrations of CO2 and chloride, and sea level rise.
17 Adaptation measures to cope with climate change may increase the demand for energy and materials
18 leading to an increase in GHG emissions if not mitigated. Sufficiency measures such as bioclimatic
19 design of buildings, which consider the expected future climate, and includes natural ventilation, white
20 walls and nature-based solutions (i.e., green roofs) will decrease the demand for cooling. Shared cooled
21 spaces with highly efficient cooling solutions are among the mitigation strategies which can limit the
22 effect of the expected heatwaves on people health. Sufficiency, efficiency, and renewable energy can
23 be designed to reduce buildings’ vulnerability to climate change impacts (medium evidence, high
24 agreement) {9.7, 9.8}.
25 Well-designed and effectively implemented mitigation actions in the buildings sector have
26 significant potential for achieving the United Nations Sustainable Development Goals. The
27 impacts of mitigation actions in the building sector go far beyond the goal of climate action (SDG13)
28 and contribute to further meeting fifteen other SDGs. Mitigation actions in the building sector bring
29 health gains through improved indoor air quality and thermal comfort as well as reduced financial
30 stresses in all world regions. Overall decarbonised building stock contribute to wellbeing and has
31 significant macro- and micro-economic effects, such as increased productivity of labour, job creation,
32 reduced poverty, especially energy poverty, and improved energy security that ultimately reduces net
33 costs of mitigation measures in buildings (high evidence, high agreement) {9.8}.
34 COVID-19 emphasised the importance of buildings for human wellbeing. However, the lockdown
35 measures implemented to avoid the spread of the virus have also stressed the inequalities in the
36 access for all to suitable and healthy buildings, which provide natural daylight and clean air to
37 their occupants (low evidence, high agreement). Meeting the new WHO health requirements, has also
38 put an emphasis on indoor air quality, preventive maintenance of centralised mechanical heating,
39 ventilation, and cooling systems. Moreover, the lockdown measures have led to spreading the South
40 Korean concept of officetel (office-hotel) to many countries and to extending it to officetelschool. The
41 projected growth, prior to the COVID-19, of 58% of the global residential floor area by 2050 compared
42 to the 290 billion m²yr-1 in 2019 might well be insufficient. Addressing the new needs for more
43 residential buildings may not, necessarily mean constructing new buildings, especially in the global
44 North. Repurposing existing non-residential buildings, no longer in use due to the expected spread of
45 teleworking triggered by the health crisis and enabled by digitalization, could be the way to overcome
46 the new needs for officetelschool buildings triggered by the health crisis (low evidence, high confidence)
47 {9.1, 9.2}.
48
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1 9.1 Introduction
2 Total GHG emissions in the building sector reached 12 GtCO2eq. in 2019, equivalent to 21% of global
3 GHG emissions that year, of which 57% were indirect CO2 emissions from offsite generation of
4 electricity and heat, followed by 24% of direct CO2 emissions produced on-site and 18% from the
5 production of cement and steel used for construction and/or refurbishment of buildings. If only CO2
6 emissions would be considered, the share of buildings CO2 emissions increases to 31% out of global
7 CO2 emissions. Energy use in residential and non-residential buildings contributed 50% and 32%
8 respectfully, while embodied emissions contributed 18% to global building CO2 emissions. Global final
9 energy demand from buildings reached 128.8 EJ in 2019, equivalent to 31% of global final energy
10 demand. Residential buildings consumed 70% out of global final energy demand from buildings.
11 Electricity demand from buildings was slightly above 43 EJ in 2019, equivalent to more than 18% of
12 global electricity demand. Over the period 1990-2019, global CO2 emissions from buildings increased
13 by 50%, global final energy demand grew by 38%, with 54% increase in non-residential buildings and
14 32% increase in residential ones. Among energy carriers, the growth in global final energy demand was
15 strongest for electricity, which increased by 161%.
16 There is growing scientific evidence about the mitigation potential of the building sector and its
17 contribution to the decarbonisation of global and regional energy systems, and to meeting Paris
18 Agreement goals and Sustainable Development Goals (SDGs) (IPCC, 2018; IEA, 2019b; IEA 2019c).
19 Mitigation interventions in buildings are heterogeneous in many different aspects, from building
20 components (envelope, structure, materials, etc.) to services (shelter, heating, etc.), to building types
21 (residential and non-residential, sometimes also called commercial and public), to building size,
22 function, and climate zone. There are also variations between developed and developing countries in
23 mitigation interventions to implement, as the former is challenged by the renovation of existing
24 buildings while the latter is challenged by the need to accelerate the construction of new buildings.
25 This chapter aims at updating the knowledge on the building sector since the Intergovernmental Panel
26 on Climate Change (IPCC) Fifth Assessment Report (AR5) (Ürge-Vorsatz et al. 2014). Changes since
27 AR5 are reviewed, including: the latest development of building service and components (Section 9.2),
28 findings of new building related GHG emission trends (Section 9.3), latest technological (Section 9.4)
29 and non-technological (Section 9.5) options to mitigate building GHG emissions, potential emission
30 reduction from these measures at global and regional level (Section 9.6), links to adaptation (Section
31 9.7) and sustainable development (Section 9.8), and sectoral barriers and policies (Section 9.9).
32 The chapter introduces the concept of sufficiency, identified in the literature as a mitigation strategy
33 with high potential, and is organised around the Sufficiency-Efficiency-Renewables (SER) framework
34 (Box 9.1).
35
36 START BOX 9.1 HERE
37 Box 9.1 SER (sufficiency-efficiency-renewables) framework
38 The SER framework was introduced, late nineties, by a French NGO (Negawatt) (Negawatt 2017)
39 advocating for a decarbonised energy transition. In 2015, the SER framework was considered in the
40 design of the French energy transition law and the French energy transition agency (ADEME) is
41 developing its 2050 scenario based on the SER framework.
42 The three pillars of the SER framework include (i) sufficiency, which tackles the causes of the
43 environmental impacts of human activities by avoiding the demand for energy and materials over the
44 lifecycle of buildings and goods, (ii) efficiency, which tackles the symptoms of the environmental
45 impacts of human activities by improving energy and material intensities, and (iii) the renewables pillar,
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1 which tackles the consequences of the environmental impacts of human activities by reducing the
2 carbon intensity of energy supply (Box 9.1 Figure 1). The SER framework introduces a hierarchical
3 layering, sufficiency first followed by efficiency and renewable, which reduces the cost of constructing
4 and using buildings without reducing the level of comfort of the occupant.
5
6 Box 9.1 Figure 1 SER framework applied to the building sector
7 Source: Saheb 2021
8 Sufficiency is not a new concept, its root goes back to the Greek word “sôphrosunè”, which was
9 translated in Latin to “sobrietas”, in a sense of “enough” (Cézard and Mourad 2019). The sufficiency
10 concept was introduced to the sustainability policy debate by (Sachs 1993) and to academia by (Princen
11 2003a). Since 1997, Thailand considers sufficiency, which was framed already in 1974 as Sufficiency
12 Economy Philosophy, as a new paradigm for development with the aim of improving human wellbeing
13 for all by shifting development pathways towards sustainability (Mongsawad 2012). The Thai approach
14 is based on three principles (i) moderation, (ii) reasonableness, and (iii) self-immunity. Sufficiency goes
15 beyond the dominant framing of energy demand under efficiency and behaviour. Sufficiency is defined
16 as avoiding the demand for materials, energy, land, water and other natural resources while delivering
17 a decent living standard for all within the planetary boundaries (Saheb 2021b, Princen 2005). Decent
18 living standards are a set of essential material preconditions for human wellbeing which includes
19 shelter, nutrition, basic amenities, health care, transportation, information, education, and public space
20 (Rao and Baer 2012; Rao and Min 2018; Rao et al. 2019). Sufficiency addresses the issue of a fair
21 consumption of space and resources. The remaining carbon budget, and its normative target for
22 distributional equity, is the upper limit of sufficiency, while requirements for a decent living standard
23 define the minimum level of sufficiency. Sufficiency differs from efficiency in that the latter is about
24 the continuous short-term marginal technological improvements which allow doing more with less in
25 relative terms without considering the planetary boundaries, while the former is about long-term actions
26 driven by non-technological solutions (i.e. land use management and planning), which consume less in
27 absolute-term and are determined by the biophysical processes (Princen 2003b).
28 Applying sufficiency principles to buildings requires (i) optimising the use of buildings, (ii) repurposing
29 unused existing ones, (iii) prioritising multi-family homes over single-family buildings, and (iv)
30 adjusting the size of buildings to the evolving needs of households by downsizing dwellings (Box 9.1
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1 Figure 2) (Sandberg 2018) (Stephan et al. 2013)(Duffy 2009)(Fuller and Crawford 2011)(Wilson and
2 Boehland 2005)(McKinlay et al. 2019)(Sandberg 2018)(Huebner and Shipworth 2017)(Ellsworth-
3 Krebs 2020) (Berrill et al. 2021).
4
5 Box 9.1 Figure 2 Sufficiency interventions and policies in the building sector
6 Source: Saheb 2021
7 Downsizing dwellings through cohousing strategies by repurposing existing buildings and clustering
8 apartments when buildings are renovated and by prioritising multi-family buildings over single-family
9 homes in new developments (Sandberg 2018) (Stephan et al. 2013)(Duffy 2009)(Fuller and Crawford
10 2011)(Wilson and Boehland 2005)(McKinlay et al. 2019)(Sandberg 2018)(Huebner and Shipworth
11 2017)(Ellsworth-Krebs 2020) (Ivanova and Büchs 2020) (Berrill and Hertwich 2021) are among the
12 sufficiency measures that avoid the demand for materials in the construction phase and energy demand
13 for heating, cooling and lighting in the use phase, especially if the conditioned volume and window
14 areas are reduced (Duffy 2009) (Heinonen and Junnila 2014). Less space also means less appliances
15 and equipment and changing preferences towards smaller ones (Aro 2020). Cohousing strategies
16 provide users, in both new and existing buildings, a shared space (i.e, for laundry, offices, guest rooms
17 and dining rooms) to complement their private space. Thus, reducing per capita consumption of
18 resources including energy, water and electricity (Klocker et al. 2012)(Natascha Klocker 2017), while
19 offering social benefits such as limiting loneliness of elderly people and single parents (Riedy et al.
20 2019)(Wankiewicz 2015). Senior cooperative housing communities and eco-villages are considered
21 among the cohousing examples to scale-up (Kuhnhenn et al. 2020). Local authorities have an important
22 role to play in the metamorphosis of housing by proposing communal spaces to be shared (J. Williams
23 2008)(Marckmann et al. 2012) through urban planning and land use policies (Duffy 2009)(Newton et
24 al. 2017). Thus, encouraging inter-generational cohousing as well as interactions between people with
25 different social backgrounds (Lietaert 2010)(J. Williams 2008). Progressive tax properties based on a
26 cap in the per-capita floor area are also needed to adapt the size of dwellings to households’ needs
27 (Murphy 2015) (Akenji 2021).
28 Efficiency, and especially energy efficiency and more recently resource efficiency, and the integration
29 of renewable to buildings are widespread concepts since the oil crisis of the seventies, while only most
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1 advanced building energy codes consider sufficiency measures (IEA 2013). Efficiency and renewable
2 technologies and interventions are described in 9.4 and 9.9.
3 A systematic categorisation of policy interventions in the building sector through the SER framework
4 (Box 9.1 Figure 1) enables identification of the policy areas and instruments to consider for the
5 decarbonisation of the building stock, their overlaps as well as their complementarities. It also shows
6 that sufficiency policies go beyond energy and climate policies to include land use and urban planning
7 policies as well as consumer policies suggesting a need for a different governance including local
8 authorities and a bottom-up approach driven by citizen engagement.
9 END BOX 9.1 HERE
10 Compared to AR5, this assessment introduces four novelties (i) the scope of CO 2 emissions has been
11 extended from direct and indirect emissions considered in AR5 to include embodied emissions, (ii)
12 beyond technological efficiency measures to mitigate GHG emissions in buildings, the contribution of
13 non-technological, in particular of sufficiency measures to climate mitigation is also considered, (iii)
14 compared to SR1.5, the link to sustainable development, well-being and decent living standard for all
15 has been further developed and strengthened, and finally (iv) the active role of buildings in the energy
16 system by making passive consumers prosumers is also assessed.
17 COVID-19 emphasised the importance of buildings for human wellbeing, however, the lockdown
18 measures implemented to avoid the spread of the virus has also stressed the inequalities in the access
19 for all to suitable and healthy buildings, which provide natural daylight and clean air to their occupants
20 (see also Cross-Chapter Box 1 in Chapter 1). COVID-19 and the new health recommendations (World
21 Health Organization 2021) emphasised the importance of ventilation and the importance of indoor air
22 quality (Wei et al. 2020)(J. et al. 2011)(Guyot et al. 2018)(William 2013)(Fisk 2015). The health crisis
23 has also put an emphasis on preventive maintenance of centralised mechanical heating, ventilation, and
24 cooling systems. Moreover, the lockdown measures have led to spreading the South Korean concept of
25 officetel (office-hotel) (Gohaud and Baek 2017) to many countries and to extending it to officetelschool.
26 Therefore, the projected growth, prior to the COVID-19, of 58% of the global residential floor area by
27 2050 compared to the 290 billion m² yr-1 in 2019 might well be insufficient. However, addressing the
28 new needs for more residential buildings may not, necessarily mean constructing new buildings. In fact,
29 repurposing existing non-residential buildings, no longer in use due to the expected spread of
30 teleworking triggered by the health crisis and enabled by digitalisation, could be the way to overcome
31 the new needs for officetelschool triggered by the health crisis.
32 The four novelties introduced in this assessment link the building sector to other sectors and call for
33 more sectoral coupling when designing mitigation solutions. Guidelines and methodologies developed
34 in Chapters 1, 2, 3, 4 and 5 are adopted in this chapter. Detailed analysis in building GHG emissions is
35 discussed based on Chapter 2 and scenarios to assess future emissions and mitigation potentials were
36 selected based on Chapters, 3 and 4. There are tight linkages between this chapter and Chapter 6, 7, 8,
37 10 and 11, which are sectoral sectors. This chapter focusses more on individual buildings and building
38 clusters, while Chapter 8 discusses macro topics in urban areas. Findings of this chapter provides
39 contribution to cross-sectoral prospection (Chapter 12), policies (Chapter 13), international cooperation
40 (Chapter 14), investment and finance (Chapter 15), innovation (Chapter 16), and sustainable
41 development (Chapter 17).
42
43 9.2 Services and components
44 This section mainly details the boundaries of the building sector; mitigation potentials are evaluated in
45 the following sections.
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1 9.2.1 Building types
2 Building types and their composition affect the energy consumption for building operation as well as
3 the GHG emissions (Hachem-Vermette and Singh 2019). They also influence the energy cost
4 (MacNaughton et al. 2015) therefore, an identification of building type is required to understand the
5 heterogeneity of this sector. Buildings are classified as residential and non-residential buildings.
6 Residential buildings can be classified as slums, single-family house and multi-family house or
7 apartment/flats building. Single-family house can be divided between single-family detached (including
8 cottages, house barns, etc.) and single-family attached (or terrace house, small multi-family, etc.).
9 Another classification is per ownership: owner-occupiers, landlords, and owners’
10 association/condominiums.
11 Non-residential buildings have a much broader use. They include cultural buildings (which include
12 theatres and performance, museums and exhibits, libraries, and cultural centres), educational buildings
13 (kindergarten, schools, higher education, research centre, and laboratories), sports (recreation and
14 training, and stadiums), healthcare buildings (health, wellbeing, and veterinary), hospitality (hotel,
15 casino, lodging, nightlife buildings, and restaurants and bars), commercial buildings and offices
16 (institutional buildings, markets, office buildings, retail, and shopping centres), public buildings
17 (government buildings, security, and military buildings), religious buildings (including worship and
18 burial buildings), and industrial buildings (factories, energy plants, warehouses, data centres,
19 transportation buildings, and agricultural buildings).
20
21 9.2.2 Building components and construction methods
22 An understanding of the methods for assembling various materials, elements, and components is
23 necessary during both the design and the construction phase of a building. A building can be broadly
24 divided into parts: the substructure which is the underlying structure forming the foundation of a
25 building, and the superstructure, which is the vertical extension of a building above the foundation.
26 There is not a global classification for the building components. Nevertheless, Figure 9.1 tries to
27 summarise the building components found in literature (Asbjørn 2009; Ching 2014; Mañá Reixach
28 2000). The buildings are divided in the substructure and the superstructure. The substructure is the
29 foundation of the building, where the footing, basement, and plinth are found. The superstructure
30 integrates the primary elements (heavyweight walls, columns, floors and ceilings, roofs, sills and lintels,
31 and stairs), the supplementary components (lightweight walls and curtain walls), the completion
32 components (doors and windows), the finishing work (plastering and painting), and the buildings
33 services (detailed in Section 9.3).
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1
2 Figure 9.1 The main building components
3
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1 At a global level, from historical perspective (from the Neolithic to the present), building techniques
2 have evolved to be able to solve increasingly complex problems. Vernacular architecture has evolved
3 over many years to address problems inherent in housing. Through a process of trial and error,
4 populations have found ways to cope with the extremes of the weather. The industrial revolution was
5 the single most important development in human history over the past three centuries. Previously,
6 building materials were restricted to a few manmade materials (lime mortar and concrete) along with
7 those available in nature as timber and stone. Metals were not available in sufficient quantity or
8 consistent quality to be used as anything more than ornamentation. The structure was limited by the
9 capabilities of natural materials; this construction method is called on-site construction which all the
10 work is done sequentially at the buildings site. The Industrial Revolution changed this situation
11 dramatically, new building materials emerged (cast-iron, glass structures, steel-reinforced concrete,
12 steel). Iron, steel and concrete were the most important materials of the nineteenth century (De
13 Villanueva Domínguez 2005; Wright 2000). In that context, prefabricated buildings (prefabrication also
14 known as pre-assembly or modularization) appeared within the so-called off-site construction.
15 Prefabrication has come to mean a method of construction whereby building elements and materials,
16 ranging in size from a single component to a complete building, are manufactured at a distance from
17 the final building location. Prefabricated buildings have been developed rapidly since World War II and
18 are widely used all over the world (Pons 2014; Moradibistouni et al. 2018)
19 Recently, advances in technology have produced new expectations in terms of design possibilities. In
20 that context, 3D printing seems to have arrived. 3D printing may allow in the future to build faster,
21 cheaper and more sustainable (Agustí-Juan et al. 2017; García de Soto et al. 2018). At the same time, it
22 might introduce new aesthetics, new materials, and complex shapes that will be printed at the click of
23 a mouse on our computers. Although 3D printing will not replace architectural construction, it would
24 allow optimization of various production and assembly processes by introducing new sustainable
25 construction processes and tools (De Schutter et al. 2018). Nevertheless, what is clear is that 3D printing
26 is a technology still in development, with a lot of potentials and that it is advancing quite quickly (Hager
27 et al. 2016; Stute et al. 2018; Wang et al. 2020).
28 9.2.3 Building services
29 Building services make buildings more comfortable, functional, efficient, and safe. In a generic point
30 of view, building services include shelter, nutrition, sanitation, thermal, visual, and acoustic comfort,
31 entertainment, communications, elevators, and illumination. In a more holistic view building services
32 are classified as shown in Figure 9.2.
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1
2 Figure 9.2 Classification of building services.
3 The coloured small rectangles to the left of each building service denote to which other classifications that building service may relate to a lesser extent.
4 Source: adapted from Vérez and Cabeza 2021a
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1 A building management system is a system of devices configured to control, monitor, and manage
2 equipment in or around a building or building area and is meant to optimize building operations and
3 reduce cost (Kelsey Carle Schuster, Youngchoon Park 2019). Recent developments include the
4 integration of the system with the renewable energy systems (D.Arnone, V.Croce, G.Paterno 2016),
5 most improved and effective user interface (Rabe et al. 2018), control systems based on artificial
6 intelligence and IoT (Farzaneh et al. 2021).
7 The use of air conditioning systems in buildings will increase with the experienced rise in temperature
8 (Davis and Gertler 2015; De Falco et al. 2016) (Figure 9.8). This can ultimately lead to high energy
9 consumption rates. Therefore, adoption of energy efficient air conditioning is pertinent to balance the
10 provision of comfortable indoor conditions and energy consumption. Some of the new developments
11 that have been done include ice refrigeration (Xu et al. 2017), the use of solar photovoltaic power in the
12 air conditioning process (Burnett et al. 2014), and use of common thermal storage technologies (De
13 Falco et al. 2016) all of which are geared towards minimizing energy consumption and greenhouse gas
14 emissions.
15 Building designs have to consider provision of adequate ventilation. Natural ventilation reduces energy
16 consumption in buildings in warm climates compared to air conditioning systems (Azmi et al. 2017;
17 Taleb 2015). Enhanced ventilation has higher benefits to the public health than the economic costs
18 involved (MacNaughton et al. 2015).
19 On the refrigeration systems, the recent developments include the use of solar thermoelectric cooling
20 technologies as an energy efficient measure (Liu et al. 2015b); use of nanoparticles for energy saving
21 (Azmi et al. 2017) to mention some.
22 (Lambertz et al. 2019) stated that when evaluating the environmental impact of buildings, building
23 services are only considered in a very simplified way. Moreover, it also highlights that the increasing
24 use of new technologies such as Building Information Modelling (BIM) allows for a much more
25 efficient and easier calculation process for building services, thus enabling the use of more robust and
26 complete models. Furthermore, recent studies on building services related to climate change (Vérez and
27 Cabeza 2021a) highlight the importance of embodied energy (Parkin et al. 2019) (see Section 9.4).
28
29 9.3 New developments in emission trends and drivers
30 9.3.1 Past and future emission trends
31 Total GHG emissions in the building sector reached 12 GtCO2eq. in 2019, equivalent to 21% of global
32 GHG emissions that year. 57% of GHG emissions from buildings were indirect CO 2 emissions from
33 generation of electricity and heat off-site, 24% were direct CO2 emissions produced on-site, and 18%
34 were from the production of cement and steel used for construction and refurbishment of buildings
35 (Figure 9.3a) (see Cross-Chapter Box 3 and Cross-Working Group Box 1 in Chapter 3). Halocarbon
36 emissions were equivalent to 3% of global building GHG emissions in 2019. In the absence of the
37 breakdown of halocarbon emissions per end-use sectors, they have been calculated for the purpose of
38 this chapter, by considering that 60% of global halocarbon emissions occur in buildings (Hu et al. 2020).
39 CH4 and N2O emissions were negligible, representing 0.08% each out of the 2019 global building GHG
40 emissions. Therefore, this chapter considers only CO2 emissions from buildings. By limiting the scope
41 of the assessment to CO2 emissions, the share of emissions from buildings increases to 31% of global
42 2019 CO2 emissions. Energy use in residential and non-residential buildings contributed 50% and 32%
43 respectfully, while embodied emissions contributed 18% to global building CO2 emissions.
44
45
46
47
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1 (a) Global
2
3
4 (b) Regional
5
6 Figure 9.3 Building GHG emissions: historical based on IEA data and future emissions based on two IEA
7 scenarios (sustainable development, and net zero emissions), IMAGE Lifestyle-Renewable scenario and
8 Resource Efficiency and Climate Change-Low Energy Demand scenario (RECC-LED). RECC-LED data
9 include only space heating and cooling and water heating in residential buildings. The IEA current
10 policies scenario is included as a baseline scenario (IEA current policies scenario)
11 Over the period 1990-2019, global CO2 emissions from buildings increased by 50%. Global indirect
12 CO2 emissions increased by 92%, driven by the increase of fossil fuels-based electrification, while
13 global direct emissions decreased by 1%. At regional level, emissions in residential buildings decreased
14 in developed countries, except in Asia-Pacific developed, while they increased in developing countries.
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1 The highest decrease was observed in Europe and Eurasia, with 13.6% decrease of direct emissions and
2 33% decrease of indirect emissions, while the highest increase of direct emissions occurred in Middle
3 East, 198%, and the highest increase of indirect emissions occurred in Eastern Asia, 2258%. Indirect
4 emissions from non-residential buildings increased in all regions. The highest increase occurred in
5 Eastern Asia, 1202%, and the lowest increase occurred in Europe and Central Asia, 4%, where direct
6 emissions from non-residential buildings decreased by 51%. Embodied emissions have also increased
7 in all regions. The highest increase occurred in Southern Asia, 334%, while the lowest increase occurred
8 in North America, 4%. (Figure 9.3b).
9 Future emissions were assessed using four global scenarios and their respective baselines (Box 9.2).
10 The selection of the scenarios was based on the features of each scenario, the geographic scope, and the
11 data availability to analyse future building emissions based on the SER framework (Box 9.1).
12
13 START BOX 9.2 HERE
14 Box 9.2 Scenarios used for the purpose of this chapter
15 Three out of the four scenarios selected, and their related baselines, are based on top-down modelling
16 and were submitted to AR6 scenario database, which includes in total 931 scenarios with a building
17 module (Annex III; see also Cross-Chapter Box 3, Box 3.1, and Box 3.2 in Chapter 3). A fourth
18 scenario, not included in AR6 scenario database, and based on a bottom-up modelling approach was
19 added.
20 The main features of these scenarios are shortly described below while the underlying modelling
21 approaches are described in Annex III. Each scenario is assessed compared to its baseline scenario:
22 International Energy Agency (IEA) scenarios:
23 2021 Net Zero Emissions by 2050 Scenario (NZE) is a normative scenario, which sets out a narrow
24 but achievable pathway for the global energy sector to achieve net zero CO 2 emissions by 2050 (IEA
25 2021a)
26 2020 Sustainable Development Scenario (SDS), which integrates the impact of COVID-19 on health
27 outcomes and economies. It is also a normative scenario, working backwards from climate, clean air,
28 and energy access goals. SDS examines what actions would be necessary to achieve these goals. The
29 near-term detail is drawn from the IEA Sustainable Recovery Plan, which boosts economies and
30 employment while building cleaner and more resilient energy systems (IEA 2020a).
31 Analysis of the IEA scenarios above was conducted compared to the 2019 Current Policies Scenario,
32 which shows what happens if the world continues along its present path (IEA 2020a), and considered
33 as a baseline scenario.
34 IMAGE-Lifestyle-Renewable (LiRE) scenario is based on an updated version of the SSP2 baseline,
35 while also meeting the RCP2.6 radiative forcing target using carbon prices, together with the increased
36 adoption of additional lifestyle changes, by limiting the growth in the floor area per capita in developed
37 countries as well as the use of appliances. Regarding energy supply, IMAGE-LiRE assumes increased
38 electrification and increased share of renewable in the energy mix (Detlef Van Vuuren et.al 2021).
39 Resource Efficiency and Climate Change-Low Energy Demand (RECC-LED) scenario is produced
40 by a global bottom-up model, which assesses contributions of resource efficiency to climate change
41 mitigation. RECC-LED estimates the energy and material flows associated with housing stock growth,
42 driven by population and the floor area per capita (Pauliuk et al. 2021). This scenario is informed by
43 the Low Energy Demand Scenario (LED), which seeks convergence between developed and developing
44 countries in the access to decent living standard (Grubler et al. 2018).
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1 For consistency between the four scenarios, aggregation of regions in this chapter differs from the one
2 of the IPCC. Europe and Eurasia have been grouped into one single region.
3 END BOX 9.2 HERE
4
5 The IEA-NZE scenario projects emissions from the global building stock to be lowered to 29 MtCO 2
6 by 2050 against 1.7 GtCO2 in the IEA-SDS and 3.7 GtCO2 in IMAGE-LiRE Scenario. These projections
7 can be compared to IEA-CPS in which global emissions from buildings were projected to be at 13.5
8 GtCO2 in 2050, which is equivalent to the 2018 emissions level (Figure 9.3a). By 2050, direct emissions
9 from residential buildings are projected to be lowered to 108 MtCO2 in the IEA-NZE, this is four times
10 less than the projected direct emissions in RECC-LED scenario, six times less than those under the IEA-
11 SDS and eleven times less than those in the IMAGE-LiRE scenario.
12 In the IEA-NZE scenario, indirect emissions are projected to be below zero by 2050 for both residential
13 and non-residential buildings, while residual indirect emissions from residential buildings are projected
14 to be 125 MtCO2 in RECC-LED, 634 MtCO2 in IEA-SDS, and 842GtCO2 in IMAGE-LiRE. Residual
15 indirect emissions from non-residential buildings are projected to be at 1.7 GtCO2 in IEA SDS and
16 double of this in IMAGE-LiRE scenario (Figure 9.3a). Compared to IEA-SDS, the highest decrease of
17 emissions in IEA-NZE is expected to occur after 2030. Direct emissions from residential buildings in
18 IEA-NZE are projected to be, by 2030, at 1.37 GtCO2, against 1.7 GtCO2 in the three other scenarios.
19 The highest cut in emissions in IEA-NZE and in IMAGE-LiRE occur through the decarbonisation of
20 energy supply.
21 At regional level, by 2050, the lowest emissions are projected to occur in developed Asia and Pacific,
22 with 6.73 MtCO2 under RECC-LED scenario and 12.4 MtCO2 under the IEA-SDS, and the highest
23 emissions are projected to occur in Europe and Eurasia in all three scenarios, with 152 MtCO2 in IEA-
24 SDS, 199 MtCO2 in RECC-LED scenario and 381 MtCO2 in IMAGE-LiRE scenario. Emissions in
25 Africa are projected to decrease to 10 MtCO2 in RECC-LED, this is nine time less than those of 2019,
26 while they are projected to increase by 25% in IEA-SDS compared to those of 2019. Compared to IEA-
27 SDS and IMAGE-LiRE, RECC-LED projects the highest decreases, over the period 2020-2030, of
28 direct emissions in residential buildings in all regions, up to 45% in Asia-Pacific developed and Eastern
29 Asia and the highest decreases of indirect emissions, ranging from 52% in Eastern Asia to 86% in Latin
30 America and Caribbean. Over the same period, the IEA-SDS projects the highest decreases of indirect
31 emissions to occur in Asia Pacific developed and North America. IMAGE-LiRE projects the lowest
32 decreases of emissions over the same decade in almost all regions (Figure 9.3b).
33 Emissions per capita from residential buildings at a global level reached 0.85 tCO2 per person in 2019.
34 The four scenarios assessed projects a decrease of the global per capita emissions by 2050, ranging
35 from 0 tCO2 in IEA NZE 0.21 tCO2 per person in IMAGE-LiRE, a 75% lower than those of 2019
36 (Figure 9.4a). There are great differences in the projected per capita emissions under each scenario
37 different scenarios across the regions (Figure 9.4b). Compared to IEA SDS and IMAGE-LiRE
38 scenarios, RECC-LED projects the lowest emissions per capita in all regions by 2050. Emissions per
39 capita in Europe and Eurasia are projected to be the highest in all scenarios by 2050, ranging from 0.26
40 tCO2 in RECC-LED and 0.31tCO2 in IEA SDS to 0.65 tCO2 in IMAGE-LiRE.
41
42
43
44
45
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1 (a) Global
2
3
4 (b) Regional
5
6
7 Figure 9.4 Per capita emissions: historical based on IEA data and future emissions based on two IEA
8 scenarios (sustainable development, and net zero emissions), IMAGE Lifestyle-Renewable scenario and
9 Resource Efficiency and Climate Change-Low Energy Demand scenario (RECC-LED). RECC-LED data
10 include only space heating and cooling and water heating in residential buildings. The IEA current
11 policies scenario is included as a baseline scenario (IEA current policies scenario)
12 9.3.2 Drivers of CO2 emissions and their climate impact
13 Building specific drivers of GHG emissions in the four scenarios described above are assessed using an
14 index decomposition analysis with building specific identities and reflecting the three pillars of the SER
15 framework (sufficiency, efficiency, renewables). Broad drivers of GHG emissions such as GDP and
16 population are analysed using a Kaya decomposition in Chapter 2. Previous decompositions analysing
17 drivers of global GHG emissions in the building sector have either assessed only the impact of GDP
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1 and population as drivers of GHG emissions (Lamb et al. 2021) or the impact of building specific drivers
2 on energy demand and not on CO2 emissions (Ürge-Vorsatz et al., 2015, IPCC AR5, 2014, IEA, 2020,
3 ODYSSEE, 2020). For this assessment, the decomposition was conducted for energy-related CO2
4 emissions for residential buildings only, due to lack of data for non-residential buildings.
5 The attribution of changes in emissions in the use phase to changes in the drivers of population,
6 sufficiency, efficiency, and carbon intensity of energy supply is calculated using additive log-mean
7 divisia index decomposition analysis (Ang and Zhang 2000). The decomposition of emissions into four
8 driving factors is shown in Eq. 1, where m2 refers to total floor area, EJ refers to final energy demand,
9 and MtCO2 refers to the sum of direct and indirect CO2 emissions in the use phase. The allocation of
10 changes in emissions between two cases k and k-1 to changes in a single driving factor D is shown in
11 Eq. 2. To calculate changes in emissions due to a single driver such as population growth, D will take
12 on the value of population in the two compared cases. The superscript k stands for the case, defined by
13 the time period and scenario of the emissions, e.g., IEA CPS Baseline scenario in 2050. When
14 decomposing emissions between two cases k and k-1, either the time-period, or the scenario remains
15 constant. The decomposition was done at the highest regional resolution available from each model
16 output, and then aggregated to regional or global level. For changes in emissions within a scenario over
17 time, the decomposition is done for every decade, and the total 2020-2050 decomposition is then
18 produced by summing decompositions of changes in emissions each decade.
19 Equation 9.1
𝑚² 𝐸𝐽 𝑀𝑡𝐶𝑂2
20 𝐶𝑂2𝑘𝑡𝑜𝑡𝑎𝑙 = 𝑃𝑜𝑝 × × × = 𝑃𝑜𝑝 × 𝑆𝑢𝑓𝑓 × 𝐸𝑓𝑓 × 𝑅𝑒𝑛
𝑃𝑜𝑝 𝑚² 𝐸𝐽
21 Equation 9.2
𝐶𝑂2 − 𝐶𝑂2𝑘−1 𝑡𝑜𝑡𝑎𝑙 𝐷𝑘
22 ∆𝐶𝑂2𝑘,𝑘−1
,𝐷 = × 𝑙𝑛 ( )
𝑙𝑛(𝐶𝑂2𝑘𝑡𝑜𝑡𝑎𝑙 ) − 𝑙𝑛(𝐶𝑂2𝑘−1
𝑡𝑜𝑡𝑎𝑙 ) 𝐷𝑘−1
23 Over the period 1990-2019, population growth accounted for 28% of the growth in global emissions in
24 residential buildings, the lack of sufficiency policies (growth in floor area per capita) accounted for
25 52% and increasing carbon intensity of the global energy mix accounted for 16%. Efficiency
26 improvement contributed to decreasing global emissions from residential buildings by 49% (
27 a). The sufficiency potential was untapped in all regions over the same period while the decarbonisation
28 of the supply was untapped in developing countries and to some extent in Asia Pacific developed. The
29 highest untapped sufficiency and supply decarbonisation potentials occurred in Southern Asia where
30 the lack of sufficiency measures has led to increasing emissions by 185% and the high carbon intensity
31 of the energy mix has led to increasing emissions by 340%. In developed countries, the highest untapped
32 sufficiency potential occurred in Asia Pacific developed region. Middle East is the only region where
33 efficiency potential remained untapped (Figure 9.5b).
34
35
36
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1 (a) Global
2
3
4
5
6
7
8
9
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1 (b) Regional
2
3
4 Figure 9.5 Decompositions of changes in historical residential energy emissions 1990-2019, changes in emissions projected by baseline scenarios for 2020-2050, and
5 differences between scenarios in 2050 using scenarios from three models: IEA, IMAGE, and RECC. RECC-LED data include only space heating and cooling and
6 water heating in residential buildings (a) Global resolution, and (b) for nine world regions. Emissions are decomposed based on changes in driver variables of
7 population, sufficiency (floor area per capita), efficiency (final energy per floor area), and renewables (GHG emissions per final energy). ‘Renewables’ is a
8 summary term describing changes in GHG intensity of energy supply. Emission projections to 2050, and differences between scenarios in 2050, demonstrate
9 mitigation potentials from the dimensions of the SER framework realised in each model scenario. In most regions, historical improvements in efficiency have been
10 approximately matched by growth in floor area per capita. Implementing sufficiency measures that limit growth in floor area per capita, particularly in developed
11 regions, reduces the dependence of climate mitigation on technological solutions
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1 Scenarios assessed show an increase of the untapped sufficiency potential at the global level over the
2 period 2020-2050. The highest untapped sufficiency potential occurs in IEA scenarios as there are no
3 changes in the floor area per capita across different scenarios. The lack of sufficiency measures in
4 current policies will contribute to increasing emissions by 54%, offsetting the efficiency improvement
5 effect. By setting a cap in the growth of the floor area per capita in developed countries, 5% of emission
6 reductions in IMAGE-LiRE scenario derives from sufficiency. However, compared to 2020, the lack
7 of sufficiency measures in the baseline scenario will contribute to increasing emissions by 31%. RECC-
8 LED scenario shows the highest global sufficiency potential captured compared to its baseline scenario
9 in 2050 as this scenario assumes a reduction in the floor area per capita in developed countries and
10 slower floor area growth in emerging economies. The four scenarios show a higher contribution of the
11 decarbonisation of energy supply to reducing emissions than the reduction of energy demand through
12 sufficiency and efficiency measures (Figure 9.6a). At regional level, the emissions reduction potential
13 from sufficiency is estimated at 25% in North America under both IMAGE-LiRE and RECC-LED
14 scenarios and at 19% in both Eastern Asia and Europe/Eurasia regions (Figure 9.6b). The highest
15 decarbonisation potential due to growth of renewable energy is 75% in Southern Asia under IMAGE-
16 LiRE scenario.
17 There is a growing literature on the decarbonisation of end-use sectors while providing decent living
18 standard for all (Rao and Min 2018)(Rao et al. 2019)(Rao and Pachauri 2017) (Grubler et al. 2018),
19 (Millward-Hopkins et al. 2020). The floor area per capita is among the gaps identified in the
20 convergence between developed and developing countries in the access to decent living (Kikstra et al.
21 2021) while meeting energy needs. In the Low Energy Demand (LED) scenario, 30 m² per capita is the
22 converging figure assumed by 2050 (Grubler et al. 2018) while in the Decent Living with minimum
23 Energy (DLE) scenario, (Millward-Hopkins et al. 2020) assumes 15 m² per capita.
24
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1
2 (a) Global
3
4 (b) Regional
5
6 Figure 9.6 Per capita floor area: historical based on IEA data and future emissions based on two IEA
7 scenarios (sustainable development, and net zero emissions), IMAGE Lifestyle-Renewable scenario and
8 Resource Efficiency and Climate Change-Low Energy Demand scenario (RECC-LED). RECC-LED data
9 include only space heating and cooling and water heating in residential buildings. The IEA current
10 policies scenario is included as a baseline scenario (IEA current policies scenario)
11 Overall, the global residential building stock grew by almost 30% between 2005 and 2019. However,
12 this growth was not distributed equally across regions and three out of the four scenarios assessed do
13 not assume a convergence, by 2050, in the floor area per capita, between developed and developing
14 countries. Only RECC-LED implements some convergence between developed countries and emerging
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1 economies to a range of 20-40 m² per capita. IEA scenarios assume a growth in the floor area per capita
2 in all regions with the highest growth in developed countries, up to 72 m² per capita in North America
3 from 66 m² per capita in 2019. IMAGE-LiRE projects a floor area per capita in Africa at 14 m² per
4 person. This is lower than the one of 2019, which was at 16 m² per capita (Figure 9.6). Beyond capturing
5 the sufficiency potential by limiting the growth in the floor area per capita in developed countries while
6 ensuring decent living standard, the acceptability of the global scenarios by developing countries is
7 getting attraction in academia (Hickel et al. 2021).
8 9.3.3 Energy demand trends
9 Global final energy demand from buildings reached 128.8 EJ in 2019, equivalent to 31% of global final
10 energy demand. The same year, residential buildings consumed 70% out of global final energy demand
11 from buildings. Over the period 1990-2019, global final energy demand from buildings grew by 38%,
12 with 54% increase in non-residential buildings and 32% increase in residential ones. At regional level,
13 the highest increase of final energy demand occurred in Middle East and Africa in residential buildings
14 and in all developing Asia in non-residential ones. By 2050, global final energy demand from buildings
15 is projected to be at 86 EJ in IEA NZE, 111 EJ in IEA SDS and 138 EJ in IMAGE-LiRE. RECC-LED
16 projects the lowest global final energy demand, at 15.7 EJ by 2050, but this refers to water heating,
17 space heating and cooling in residential buildings only (Figure 9.7a).
18
19 (a) Global
20
21
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1
2 (b) Regional
3
4 Figure 9.7 Final energy demand per fuel: historical based on IEA data and future emissions based on two
5 IEA scenarios (sustainable development, and net zero emissions), IMAGE Lifestyle-Renewable scenario
6 and Resource Efficiency and Climate Change-Low Energy Demand scenario (RECC-LED). RECC-LED
7 data include only space heating and cooling and water heating in residential buildings. The IEA current
8 policies scenario is included as a baseline scenario (IEA current policies scenario)
9 Over the period 1990-2019, the use of coal decreased at a global level by 59% in residential buildings
10 and 52% in non-residential ones. Solar thermal experienced the highest increase, followed by
11 geothermal and electricity. However, by 2019, solar thermal and geothermal contributed by only 1%
12 each to global final energy demand, while electricity contributed by 51% in non-residential buildings
13 and 26% in residential ones. The same year, gas contributed by 26% to non-residential final energy
14 demand and 22% to residential final energy demand, which makes gas the second energy carrier used
15 in buildings after electricity. Over the period 1990-2019, the use of gas grew by 75% in residential
16 buildings and by 46% in non-residential ones. By 2050, RECC-LED projects electricity to contribute
17 by 71% to final energy demand in residential buildings, against 62% in IEA-NZE and 59% in IMAGE-
18 LiRE. IEA-NZE is the only scenario to project less than 1% of gas use by 2050 in residential buildings
19 while the contribution of electricity to energy demand of non-residential buildings is above 60% in all
20 scenarios. At regional level, the use of coal in buildings is projected to disappear while the use of
21 electricity is projected to be above 50% in all regions by 2050 (Figure 9.7b).
22 Hydrogen emerged in the policy debate as an important energy carrier for the decarbonisation of the
23 energy system. In the case of the building sector, depending on how hydrogen is sourced (see Box 12.3
24 in Chapter 12), converting gas grids to hydrogen might be an appealing option to decarbonise heat
25 without putting additional stress on the electricity grids. However, according to (Elements energy Ltd
26 2018; Broad et al. 2020; Frazer-Nash Consultancy 2018; Gerhardt et al. 2020) (Strbac et al. 2018) the
27 delivered cost of heat from hydrogen would be much higher than the cost of delivering heat from heat
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1 pumps, which could also be used for cooling. Repurposing gas grids for pure hydrogen networks will
2 also require system modifications such as replacement of piping and replacement of gas boilers and
3 cooking appliances, a factor cost to be considered when developing hydrogen roadmaps for buildings.
4 There are also safety and performance concerns with domestic hydrogen appliances (Frazer-Nash
5 Consultancy 2018). Over the period 1990-2019, hydrogen was not used in the building sector and
6 scenarios assessed show a very modest role for hydrogen in buildings by 2050 (Figure 9.7).
7 In developed countries, biomass is used for generating heat and power leading to reduction of indirect
8 emissions from buildings (Ortwein 2016)(IEA et al. 2020a). However, according to (IEA 2019b) despite
9 the mitigation potential of biomass, if the wood is available locally, its use remains low in developed
10 countries. Biomass is also used for efficient cook stoves and for heating using modern appliances such
11 as pellet-fed central heating boilers. In developing countries, traditional use of biomass is characterised
12 by low efficiency of combustion (due to low temperatures) leading to high levels of pollutants and CO
13 output, as well as low efficiency of heat transfer. The traditional use of biomass is associated with public
14 health risks such as pre mature deaths related to inhaling fumes from cooking (Dixon et al. 2015; Van
15 de Ven et al. 2019; Taylor et al. 2020; IEA 2019b). According to (Hanna et al. 2016) policies failed in
16 improving the use of biomass. Over the period 1990-2019, the traditional use of biomass decreased by
17 1% and all scenarios assessed do not project any traditional use of biomass by 2050. Biomass is also
18 used for the construction of buildings, leading to low embodied emissions compared to concrete
19 (Pauliuk et al. 2021; Hart and Pomponi 2020; Heeren et al. 2015a)
20 Over the period 1990-2019, space heating was the dominant end-use in residential buildings at a global
21 level, followed by water heating, cooking, and connected and small appliances (Figure 9.8a). However,
22 energy demand from connected and small appliances experienced the highest increase, 280%, followed
23 by cooking, 89%, cooling, 75%, water heating, 73% and space heating, around 10%. Space heating
24 energy demand is projected to decline over the period 2020-2050 in all scenarios assessed. RECC-LED
25 projects the highest decrease, 77%, of space heating energy demand, against 68% decrease in the IEA
26 NZE. IMAGE-LiRE projects the lowest decrease of heating energy demand, 21%. To the contrary, all
27 scenarios confirm cooling as a strong emerging trend (Box 9.3) and project an increase of cooling
28 energy demand. IMAGE-LiRE projects the highest increase, 143% against 45% in the IEA-NZE while
29 RECC-LED projects the lowest increase of cooling energy demand, 32%.
30
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1
2 (a) Global
3
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1 (b) Regional
2
3 Figure 9.8 Energy per end use: historical based on IEA data and future emissions based on two IEA scenarios (sustainable development, and net zero emissions),
4 IMAGE Lifestyle-Renewable scenario and Resource Efficiency and Climate Change-Low Energy Demand scenario (RECC-LED). RECC-LED data include only
5 space heating and cooling and water heating. The IEA current policies scenario is included as a baseline scenario (IEA current policies scenario)
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1 There are great differences in the contribution of each end-use to the regional energy demand (Figure
2 9.8b). In 2019, more than 50% of residential energy demand in Europe and Eurasia was used for space
3 heating while there was no demand for space heating in Middle East, reflecting differences in climatic
4 conditions. To the contrary, the share of energy demand from cooking out of total represented 53% in
5 the Middle East against 5% in Europe-Eurasia reflecting societal organisations. The highest
6 contribution of energy demand from connected and small appliances to the regional energy demand was
7 observed in 2019 in the Asia Pacific developed, 24%, followed by the region of Southern Asia,
8 Southeast Asia and Developing Pacific, with 17%. Energy demand from cooling was at 9% out of total
9 energy demand of Southern Asia, Southeast Asia and Developing Pacific and at 8% in both Middle East
10 and North America while it was at 1% in Europe in 2019.
11 The increased cooling demand can be partly explained by the increased ownership of room air-
12 conditioners per dwellings in all regions driven by increased wealth and the increased ambient
13 temperatures due to global warming (Cayla et al. 2011) (Liddle and Huntington 2021) (Box 9.3). The
14 highest increase, 32%, in ownership of room air-conditioners was observed in Southern Asia and
15 Southeast Asia and developing Pacific while Europe, Latin America and Caribbean countries, Eastern
16 Asia and Africa experienced an increase of 21% in households’ ownership of room air-conditioners.
17 The lowest increases in room air-conditioners ownership were observed in the Middle East and North
18 America with 1% and 8% each as these two markets are almost saturated. All scenarios assessed project
19 an increase of ownership of cooling appliances in all regions over the period 2020-2050.
20 Energy demand from connected and small appliances was, at a global level, above 7 EJ in 2019 (Figure
21 9.8a). However, it is likely that global energy demand from connected and small appliances is much
22 higher as reported data do not include all the connected and small appliances used by households and
23 does not capture energy demand from data centres (Box 9.3). Over the period 1990-2019, the highest
24 increase of energy demand from connected and small appliances, 4740%, was observed in Eastern Asia,
25 followed by Southern Asia, 1358% while the lowest increase, 99%, occurred in Asia Pacific developed
26 countries. The increase of energy demand from connected and small appliances is driven by the
27 ownership increase of such appliances all over the world. The highest increase in ownership of
28 connected appliances, 403%, was observed in Eastern Asia and the lowest increase in ownership of
29 connected appliances was observed in North America, 94%. Future energy demand is expected to occur
30 in the developing world given the projected rate of penetration of household appliances and devices
31 (Wolfram et al. 2012). However, (Grubler et al. 2018) projects a lower energy demand from connected
32 and small appliances by assuming an increase of shared appliances and multiple appliances and
33 equipment will be integrated into units delivering multiple services.
34
35 START BOX 9.3 HERE
36 Box 9.3 Emerging energy demand trends in residential buildings
37 Literature assessed points to three major energy demand trends:
38 Cooling energy demand
39 In a warming world (IPCC 2021) with a growing population and expanding middle-class, the demand
40 for cooling is likely to increase leading to increased emissions if cooling solutions implemented are
41 carbon intensive (Kian Jon et al. 2021; Dreyfus et al. 2020b; Santamouris 2016; Sustainable Energy for
42 All 2018; United Nations Environment Programme (UNEP) International Energy Agency (IEA) 2020).
43 Sufficiency measures such as building design and forms, which allow balancing the size of openings,
44 the volume, the wall and window area, the thermal properties, shading, and orientation are all non-cost
45 solutions, which should be considered first to reduce cooling demand. Air conditioning systems using
46 halocarbons are the most common solutions used to cool buildings. Up to 4 billion cooling appliances
47 are already installed and this could increase to up 14 billion by 2050 (Peters 2018; Dreyfus et al. 2020b).
48 Energy efficiency of air conditioning systems is of a paramount importance to ensuring that the
49 increased demand for cooling will be satisfied without contributing to global warming through
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1 halocarbon emissions (Shah et al. 2019, 2015; Campbell 2018; United Nations Environment
2 Programme (UNEP) International Energy Agency (IEA) 2020). The installation of highly efficient
3 technological solutions with low Global Warming Potential (GWP), as part of the implementation of
4 the Kigali amendment to the Montreal Protocol, is the second step towards reducing GHG emissions
5 from cooling. Developing renewable energy solutions integrated to buildings is another track to follow
6 to reduce GHG emissions from cooling.
7 Electricity energy demand
8 Building electricity demand was slightly above 43 EJ in 2019, which is equivalent to more than 18% of
9 global electricity demand. Over the period 1990-2019, electricity demand increased by 161%. The
10 increase of global electricity demand is driven by the combination of rising incomes, income
11 distribution and the S-curve of ownership rates (Wolfram et al. 2012; Gertler et al. 2016). Electricity is
12 used in buildings for plug-in appliances i.e., refrigerators, cleaning appliances, connected and small
13 appliances, and lighting. An important emerging trend in electricity demand is the use of electricity for
14 thermal energy services (cooking, water, and space heating). The increased penetration of heat pumps
15 is the main driver of the use of electricity for heating. Heat pumps used either individually or in
16 conjunction with heat networks can provide heating in cold days and cooling in hot ones. (Lowes et al.
17 2020) suggests electricity is expected to become an important energy vector to decarbonise heating.
18 However, the use of heat pumps will increase halocarbon emissions (United Nations Environment
19 Programme (UNEP) International Energy Agency (IEA) 2020). (Bloess et al. 2018; Barnes and
20 Bhagavathy 2020; Connolly 2017) argue for electrification of heat as a cost-effective decarbonisation
21 measure, if electricity is supplied by renewable energy sources (Ruhnau et al. 2020). The electrification
22 of the heat supplied to buildings is likely to lead to an additional electricity demand and consequently
23 additional investment in new power plants. (Thomaßen et al. 2021) identifies flexibility as a key enabler
24 of larger heat electrification shares. Importantly, heat pumps work at their highest efficiency level in
25 highly efficient buildings and their market uptake is likely to require incentives due to their high up-
26 front cost (Hannon 2015; Heinen et al. 2017).
27 Digitalisation energy demand
28 Energy demand from digitalisation occurs in datacentres, which are dedicated buildings or part of
29 buildings for accommodating large amount of information technologies equipment such as servers, data
30 storage and communication devices, and network devices. Data-centres are responsible for about 2% of
31 global electricity consumption (Diguet and Lopez 2019; Avgerinou et al. 2017). Energy demand from
32 datacentres arises from the densely packed configuration of information technologies, which is up to
33 100 times higher than a standard office accommodation (Chu and Wang 2019). Chillers combined with
34 air handling units are usually used to provide cooling in datacentres. Given the high cooling demand of
35 datacentres, some additional cooling strategies, such as free cooling, liquid cooling, low-grade waste
36 heat recovery, absorption cooling, etc., have been adopted. In addition, heat recovery can provide useful
37 heat for industrial and building applications. More recently, datacentres are being investigated as a
38 potential resource for demand response and load balancing (Zheng et al. 2020; Koronen et al. 2020).
39 Supplying datacentres with renewable energy sources is increasing (Cook et al. 2014) and is expected
40 to continue to increase (Koomey et al. 2011). Estimates of energy demand from digitalisation
41 (connected and small appliances, data centres, and data networks) combined vary from 5% to 12% of
42 global electricity use (Ferreboeuf 2019; Gelenbe and Caseau 2015; Malmodin and Lundén 2018; Diguet
43 and Lopez 2019). According to (Ferreboeuf 2019) the annual increase of energy demand from
44 digitalisation could be limited to 1.5% against the current 4% if sufficiency measures are adopted along
45 the value chain.
46 Digitalisation occurs also at the construction stage. (European Union 2019; Witthoeft and Kosta 2017)
47 identified seven digital technologies already in use in the building sector. These technologies include
48 (i) Building Information Modelling/Management (BIM), (ii) additive manufacturing, also known as 3D
49 printing, (iii) robots, (iv) drones, (v) 3D scanning, (vi) sensors, and (vii) Internet of Things (IoT). BIM
50 supports decision making in the early design stage and allows assessing a variety of design options and
51 their embodied emissions (Röck et al. 2018; Basbagill et al. 2013). 3D printing reduces material waste
52 and the duration of the construction phase as well as labour accidents (Dixit 2019). Coupling 3D printing
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1 and robots allows for increasing productivity through fully automated prefabricated buildings. Drones
2 allow for a better monitoring and inspection of construction projects through real-time comparison
3 between planned and implemented solutions. Coupling drones with 3D scanning allows predicting
4 building heights and energy consumption (Streltsov et al. 2020). Sensors offer a continuous data
5 collection and monitoring of end-use services (i.e., heating, cooling, and lighting), thus allowing for
6 preventive maintenance while providing more comfort to end-users. Coupling sensors with IoT, which
7 connects to the internet household appliances and devices such as thermostats, enable demand-response,
8 and flexibility to reduce peak loads (IEA 2017; Lyons 2019). Overall, connected appliances offer a
9 variety of opportunities for end-users to optimise their energy demand by improving the responsiveness
10 of energy services (Nakicenovic et al. 2019; [IEA] - International Energy Agency 2017) through the
11 use of digital goods and services (Wilson et al., 2020) including peer-to-peer electricity trading
12 (Morstyn et al. 2018).
13 END BOX 9.3 HERE
14
15 9.4 Mitigation technological options and strategies towards zero carbon
16 buildings
17 Literature in this topic is extensive, but unfortunately, most studies and reviews do not relate themselves
18 to climate change mitigation, therefore there is a clear gap in reporting the mitigation potential of the
19 different technologies (Cabeza et al. 2020). It should be highlighted that when assessing the literature,
20 it is clear that a lot of new research is focussed on the improvement of control systems, including the
21 use of artificial intelligence or internet of things (IoT).
22 This section is organised as follow. First, the key points from AR5 and special reports are summarized,
23 following with a summary of the technological developments since AR5, specially focussing on
24 residential buildings.
25 9.4.1 Key points from AR5 and special reports
26 AR5 Chapter 9 on Buildings (Ürge-Vorsatz et al. 2014) presents mitigation technology options and
27 practices to achieve large reductions in building energy use as well as a synthesis of documented
28 examples of large reductions in energy use achieved in real, new, and retrofitted buildings in a variety
29 of different climates and examples of costs at building level. A key point highlighted is the fact that the
30 conventional process of designing and constructing buildings and its systems is largely linear, losing
31 opportunities for the optimization of whole buildings. Several technologies are listed as being able to
32 achieve significant performance improvements and cost potentials (daylighting and electric lighting,
33 household appliances, insulation materials, heat pumps, indirect evaporative cooling, advances in
34 digital building automation and control systems, and smart meters and grids to implement renewable
35 electricity sources).
36 9.4.2 Embodied energy and embodied carbon
37 9.4.2.1 Embodied energy and embodied carbon in building materials
38 As building energy demand is decreased the importance of embodied energy and embodied carbon in
39 building materials increases (Ürge-Vorsatz et al. 2020). Buildings are recognised as built following five
40 building frames: concrete, wood, masonry, steel, and composite frames (International Energy Agency
41 2019a); but other building frames should be considered to include worldwide building construction
42 practice, such as rammed earth and bamboo in vernacular design (Cabeza et al. 2021).
43 The most prominent materials used following these frames classifications are the following. Concrete,
44 a man-made material, is the most widely used building material. Wood has been used for many centuries
45 for the construction of buildings and other structures in the built environment; and it remains as an
46 important construction material today. Steel is the strongest building material; it is mainly used in
47 industrial facilities and in buildings with big glass envelopes. Masonry is a heterogeneous material using
48 bricks, blocks, and others, including the traditional stone. Composite structures are those involving
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1 multiple dissimilar materials. Bamboo is a traditional building material throughout the world tropical
2 and sub-tropical regions. Rammed earth can be considered to be included in masonry construction, but
3 it is a structure very much used in developing countries and it is finding new interest in developed ones
4 (Cabeza et al. 2021).
5 The literature evaluating the embodied energy in building materials is extensive, but that considering
6 embodied carbon is much more scarce (Cabeza et al. 2021). Recently this evaluation is done using the
7 methodology life cycle assessment (LCA), but since the boundaries used in those studies are different,
8 varying for example, in the consideration of cradle to grave, cradle to gate, or cradle to cradle, the
9 comparison is very difficult (Moncaster et al. 2019). A summary of the embodied energy and embodied
10 carbon cradle to gate coefficients reported in the literature are found in Figure 9.9 (Alcorn and Wood
11 1998; Birgisdottir et al. 2017; Cabeza et al. 2013; De Wolf et al. 2016; Symons 2011; Moncaster and
12 Song 2012; Omrany et al. 2020; Pomponi and Moncaster 2016, 2018; Crawford and Treolar 2010;
13 Vukotic et al. 2010; Cabeza et al. 2021). Steel represents the materials with higher embodied energy,
14 32-35 MJ∙kg-1; embodied energy in masonry is higher than in concrete and earth materials, but
15 surprisingly, some type of wood have more embodied energy than expected; there are dispersion values
16 in the literature depending of the ma. On the other hand, earth materials and wood have the lowest
17 embodied carbon, with less than 0.01 kg CO2 per kg of material (Cabeza et al. 2021). The concept of
18 buildings as carbon sinks raise from the idea that wood stores considerable quantities of carbon with a
19 relatively small ratio of carbon emissions to material volume and concrete has substantial embodied
20 carbon emissions with minimal carbon storage capacity (Churkina et al. 2020; Sanjuán et al. 2019).
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1
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1
2 Figure 9.9 Building materials (a) embodied energy and (b) embodied carbon (Cabeza et al. 2021).
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1 9.4.2.2 Embodied emissions
2 Embodied emissions from production of materials are an important component of building sector
3 emissions, and their share is likely to increase as emissions from building energy demand decrease
4 (Röck et al. 2020). Embodied emissions trajectories can be lowered by limiting the amount of new floor
5 area required (Berrill and Hertwich 2021; Fishman et al. 2021), and reducing the quantity and GHG
6 intensity of materials through material efficiency measures such as lightweighting and improved
7 building design, material substitution to lower-carbon alternatives, higher fabrication yields and scrap
8 recovery during material production, and re-use or lifetime extension of building components (Allwood
9 et al. 2011; Pamenter and Myers 2021; Churkina et al. 2020; Heeren et al. 2015b; Pauliuk et al. 2021;
10 Hertwich et al. 2019). Reducing the GHG intensity of energy supply to material production activities
11 also has a large influence on reducing overall embodied emissions. Figure 9.10 shows projections of
12 embodied emissions to 2050 from residential buildings in a baseline scenario (SSP2 Baseline) and a
13 scenario incorporating multiple material efficiency measures and a much faster decarbonization of
14 energy supply (LED and 2°C policy) (Pauliuk et al. 2021). Embodied emissions are projected to be 32%
15 lower in 2050 than 2020 in a baseline scenario, primarily due to a lower growth rate of building floor
16 area per population. This is because the global population growth rate slows over the coming decades,
17 leading to less demand for new floor area relative to total population. Further baseline reductions in
18 embodied emissions between 2020 and 2050 derive from improvements in material production and a
19 gradual decline in GHG intensity of energy supply. In a LED + 2°C policy scenario, 2050 embodied
20 emissions are 86% lower than the Baseline. This reduction of 2050 emissions comes from contributions
21 of comparable magnitude from three sources; slower floor area growth leading to less floor area of new
22 construction per capita (sufficiency), reductions in the mass of materials required for each unit of newly
23 built floor area (material efficiency), and reduction in the GHG intensity of material production, from
24 material substitution to lower carbon materials, and faster transition of energy supply.
25 The attribution of changes in embodied emissions to changes in the drivers of population, sufficiency,
26 material efficiency, and GHG intensity of material production is calculated using additive log-mean
27 divisia index decomposition analysis (Ang and Zhang 2000). The decomposition of emissions into four
28 driving factors is shown in Eq. 9.3, where m2NC refers to floor area of new construction, kgMat refers to
29 mass of materials used for new construction, and kgCO2e refers to embodied GHG emissions in CO2e.
30 The allocation of changes in emissions between two cases k and k-1 to changes in a single driving factor
31 D is shown in Eq. 9.4. For instance, to calculate changes in emissions due to population growth, D will
32 take on the value of population in the two cases being compared. The superscript k stands for the time
33 period and scenario of the emissions, e.g., SSP2 Baseline scenario in 2050. When decomposing
34 emissions between two cases k and k-1, either the time period or the scenario stays constant. The
35 decomposition is done for every region at the highest regional resolution available, and aggregation
36 (e.g., to global level) is then done by summing over regions. For changes in emissions within a scenario
37 over time (e.g., SSP Baseline emissions in 2020 and 2050), the decomposition is made for every decade,
38 and the total 2020-2050 decomposition is then produced by summing decompositions of changes in
39 emissions each decade.
40 Equation 9.3
2
𝑚𝑁𝐶 𝑘𝑔𝑀𝑎𝑡 𝑘𝑔𝐶𝑂2𝑒
41 𝑘
𝐺𝐻𝐺𝑒𝑚𝑏 = 𝑃𝑜𝑝 × × 2 × = 𝑃𝑜𝑝 × 𝑆𝑢𝑓𝑓 × 𝐸𝑓𝑓 × 𝑅𝑒𝑛
𝑃𝑜𝑝 𝑚𝑁𝐶 𝑘𝑔𝑀𝑎𝑡
42 Equation 9.4
𝑘 𝑘−1
𝑘,𝑘−1 𝐺𝐻𝐺𝑒𝑚𝑏 − 𝐺𝐻𝐺𝑒𝑚𝑏 𝐷𝑘
43 ∆𝐺𝐻𝐺𝑒𝑚𝑏,𝐷 = 𝑘 ) 𝑘−1 )
× 𝑙𝑛 ( )
𝑙𝑛(𝐺𝐻𝐺𝑒𝑚𝑏 − 𝑙𝑛(𝐺𝐻𝐺𝑒𝑚𝑏 𝐷𝑘−1
44
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1
2 (a) Global
3
4
5
6
7
8
9 (b) Regional
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1
2 Figure 9.10 Decompositions of changes in residential embodied emissions projected by baseline scenarios for 2020-2050, and differences between scenarios in 2050
3 using two scenarios from the RECC model. (a) Global resolution, and (b) for nine world regions. Emissions are decomposed based on changes in driver variables of
4 population, sufficiency (floor area of new construction per capita), material efficiency (material production per floor area), and renewables (GHG emissions per
5 unit material production). ‘Renewables’ is a summary term describing changes in GHG intensity of energy supply. Emission projections to 2050, and differences
6 between scenarios in 2050, demonstrate mitigation potentials from the dimensions of the SER framework realised in each model scenario.
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1 9.4.3 Technological developments since AR5
2 9.4.3.1 Overview of technological developments
3 There are many technologies that can reduce energy use in buildings (Finnegan et al. 2018; Kockat et
4 al. 2018a), and those have been extensively investigated. Other technologies that can contribute to
5 achieving carbon zero buildings are less present in the literature. Common technologies available to
6 achieve zero energy buildings were summarized in (Cabeza and Chàfer 2020) and are presented in
7 Tables SM9.1 to SM9.3 in detail, where Figure 9.11 shows a summary.
8
9 Figure 9.11 Energy savings potential of technology strategies for climate change mitigation in buildings.
10 Source: Adapted from (Bojić et al. 2014; Bevilacqua et al. 2019; Coma et al. 2017; Djedjig et al. 2015; Chen et
11 al. 2013; Haggag et al. 2014; Khoshbakht et al. 2017; Saffari et al. 2017; Seong and Lim 2013; Radhi 2011;
12 Pomponi et al. 2016; Andjelković et al. 2016; Rosado and Levinson 2019; Costanzo et al. 2016; Spanaki et al.
13 2014; Coma et al. 2016; Yang et al. 2015; Cabeza et al. 2010; Kameni Nematchoua et al. 2020; Annibaldi et al.
14 2020; Varela Luján et al. 2019; Jedidi and Benjeddou 2018; Capozzoli et al. 2013; Asdrubali et al. 2012; Irshad
15 et al. 2019; Luo et al. 2017; Prívara et al. 2011; Sourbron et al. 2013; Ling et al. 2020; Peng et al. 2020; Zhang
16 et al. 2020c; Dong et al. 2020; Harby et al. 2016; Liu et al. 2019; Vakiloroaya et al. 2014; Mahmoud et al. 2020;
17 Romdhane and Louahlia-Gualous 2018; Gong et al. 2019; de Gracia et al. 2013; Navarro et al. 2016; Fallahi et
18 al. 2010; Mujahid Rafique et al. 2015; Soltani et al. 2019; Imanari et al. 1999; Yu et al. 2020; Lee et al. 2018;
19 Sarbu and Sebarchievici 2014; Hohne et al. 2019; Zhang et al. 2019; Omara and Abuelnour 2019; Alam et al.
20 2019; Langevin et al. 2019; Cabeza and Chàfer 2020)
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1 Other opportunities exist, such as building light-weighting or more efficient material production, use
2 and disposal (Hertwich et al. 2020), fast-growing biomass sources such as hemp, straw or flax as
3 insulation in renovation processes (Pittau et al. 2019), bamboo-based construction systems as an
4 alternative to conventional high-impact systems in tropical and subtropical climates (Zea Escamilla et
5 al. 2018). Earth architecture is still limited to a niche (Morel and Charef 2019). See also Cross-Chapter
6 Box 9 in Chapter 13 for carbon dioxide removal and its role in mitigation strategies.
7 9.4.3.2 Appliances and lighting
8 Electrical appliances have a significant contribution to household electricity consumption (Pothitou et
9 al. 2017). Ownership of appliances, the use of appliances, and the power demand of the appliances are
10 key contributors to domestic electricity consumption (Jones et al. 2015). The drivers in energy use of
11 appliances are the appliance type (e.g., refrigerators), number of households, number of appliances per
12 household, and energy used by each appliance (Cabeza et al. 2014)(Chu and Bowman 2006;
13 Spiliotopoulos 2019). At the same time, household energy-related behaviours are also a driver of energy
14 use of appliances (Khosla et al. 2019) (see Section 9.5). Although new technologies such as IoT linked
15 to the appliances increase flexibility to reduce peak loads and reduce energy demand (Berkeley et al.
16 2020), trends show that appliances account for an increasing amount of building energy consumption
17 (Figure 9.8). Appliances used in developed countries consume electricity and not fuels (fossil or
18 renewable), which often have a relatively high carbon footprint. The rapid increase in appliance
19 ownership (Cabeza et al. 2018b) can affect the electricity grid. Moreover, energy intensity improvement
20 in appliances such as refrigerators, washing machines, TVs, and computers has counteracted the
21 substantial increase in ownership and use since the year 2000 (International Energy Agency 2019b).
22 But appliances also are a significant opportunity for energy efficiency improvement. Research on
23 energy efficiency for different appliances worldwide showed that this research focused in different time
24 frames in different countries (Figure 9.12). This figure presents the number of occurrences of a term
25 (the name of a studied appliance) appearing per year and per country, according to the references
26 obtained from a Scopus search. The figure shows that most research carried out was after 2010. And
27 again, this figure shows that research is mostly carried out for refrigerators and for brown appliances
28 such as smart phones. Moreover, the research carried out worldwide is not only devoted to technological
29 aspects, but also to behavioural aspects and quality of service (such as digital television or smart
30 phones).
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1
2 Figure 9.12 Energy efficiency in appliances research. Year and number of occurrences of different appliances in each studied country/territory.
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1
2 Lighting energy accounts for around 19% of global electricity consumption (Attia et al. 2017; Enongene
3 et al. 2017; Baloch et al. 2018). Many studies have reported the correlation between the decrease in
4 energy consumption and the improvement of the energy efficiency of lighting appliances (Table 9.1).
5 Today, the new standards recommend the phase out of incandescent light bulbs, linear fluorescent
6 lamps, and halogen lamps and their substitution by more efficient technologies such as compact
7 fluorescent lighting (CFL) and light-emitting diodes (LEDs) (Figure 9.8). Due to the complexity of
8 these systems, simulation tools are used for the design and study of such systems, which can be
9 summarized in Baloch et al. 2018 (Baloch et al. 2018).
10 Single-phase induction motors are extensively used in residential appliances and other building low-
11 power applications. Conventional motors work with fixed speed regime directly fed from the grid,
12 giving unsatisfactory performance (low efficiency, poor power factor, and poor torque pulsation).
13 Variable speed control techniques improve the performance of such motors (Jannati et al. 2017).
14
15 Table 9.1 Types of domestic lighting devices and their characteristics (Adapted from (Attia et al. 2017))
Type of lighting Code in Lumens per Colour Life span Energy use
device plan watt [lm∙W-1] temperature [K] [h] [W]
Incandescent InC 13.9 2700 1000 60
Candle CnL 14.0 2700 1000 25
incandescent
Halogen Hal 20.0 3000 5000 60
Fluorescent TL 8 FluT8 80.0 3000-6500 20000 30-40
Compact CfL 66.0 2700-6500 10000 20
fluorescent
LED GLS LeD 100.0 2700-5000 45000 10
LED spotlight LeD Pin 83.8 2700-6500 45000 8
Fluorescent T5 FluT5 81.8 2700-6500 50000 22
LED DT8 LeDT8 111.0 2700-6500 50000 15
16
17 Within the control strategies to improve energy efficiency in appliances, energy monitoring for energy
18 management has been extensively researched. Abubakar et al. 2017 (Abubakar et al. 2017) present a
19 review of those methods. The paper distinguishes between intrusive load monitoring (ILM), with
20 distributed sensing, and non-intrusive load monitoring (NILM), based on a single point sensing.
21
22
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1
2 9.4.4 Case studies
3 9.4.4.1 Warehouses
4 Warehouses are major contributors to the rise of greenhouse gas emissions in supply chains (Bartolini
5 et al. 2019). The expanding e-commerce sector and the growing demand for mass customization have
6 even led to an increasing need for warehouse space and buildings, particularly for serving the
7 uninterrupted customer demand in the business-to-consumer market. Although warehouses are not
8 specifically designed to provide their inhabitants with comfort because they are mainly unoccupied, the
9 impact of their activities in the global GHG emissions is remarkable. Warehousing activities contribute
10 roughly 11% of the total GHG emissions generated by the logistics sector across the world. Following
11 this global trend, increasing attention to green and sustainable warehousing processes has led to many
12 new research results regarding management concepts, technologies, and equipment to reduce
13 warehouses carbon footprint, i.e., the total emissions of GHG in carbon equivalents directly caused by
14 warehouses activities.
15 9.4.4.2 Historical and heritage buildings
16 Historical buildings, defined as those built before 1945, are usually low-performance buildings by
17 definition from the space heating point of view and represent almost 30–40% of the whole building
18 stock in European countries (Cabeza et al. 2018a). Historical buildings often contribute to townscape
19 character, they create the urban spaces that are enjoyed by residents and attract tourist visitors. They
20 may be protected by law from alteration not only limited to their visual appearance preservation, but
21 also concerning materials and construction techniques to be integrated into original architectures. On
22 the other hand, a heritage building is a historical building which, for their immense value, is subject to
23 legal preservation. The integration of renewable energy systems in such buildings is more challenging
24 than in other buildings. The review carried out by (Cabeza et al. 2018a) different case studies are
25 presented and discussed, where heat pumps, solar energy and geothermal energy systems are integrated
26 in such buildings, after energy efficiency is considered.
27 9.4.4.3 Positive energy or energy plus buildings
28 The integration of energy generation on-site means further contribution of buildings towards
29 decarbonisation (Ürge-Vorsatz et al. 2020). Integration of renewables in buildings should always come
30 after maximising the reduction in the demand for energy services through sufficiency measures and
31 maximising efficiency improvement to reduce energy consumption, but the inclusion of energy
32 generation would mean a step forward to distributed energy systems with high contribution from
33 buildings, becoming prosumers (Sánchez Ramos et al. 2019). Decrease price of technologies such as
34 PV and the integration of energy storage (de Gracia and Cabeza 2015) are essential to achieve this
35 objective. Other technologies that could be used are photovoltaic/thermal (Sultan and Ervina Efzan
36 2018), solar/biomass hybrid systems (Zhang et al. 2020b), solar thermoelectric (Sarbu and Dorca 2018),
37 solar powered sorption systems for cooling (Shirazi et al. 2018), and on-site renewables with battery
38 storage (Liu et al. 2021).
39 9.4.4.4 District energy networks
40 District heating networks have evolved from systems where heat was produced by coal or waste and
41 storage was in the form of steam, to much higher energy efficiency networks with water or glycol as
42 the energy carrier and fuelled by a wide range of renewable and low carbon fuels. Common low carbon
43 fuels for district energy systems include biomass, other renewables (i.e., geothermal, PV, and large solar
44 thermal), industry surplus heat or power-to-heat concepts, and heat storage including seasonal heat
45 storage (Lund et al. 2018). District energy infrastructure opens opportunities for integration of several
46 heat and power sources and is 'future proof' in the sense that the energy source can easily be converted
47 or upgraded in the future, with heat distributed through the existing district energy network. Latest
48 developments include the inclusion of smart control and AI (Revesz et al. 2020), and low temperature
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Final Government Distribution Chapter 9 IPCC AR6 WGIII
1 thermal energy districts. Authors show carbon emissions reduction up to 80% compared to the use of
2 gas boilers.
3
4 9.4.5 Low- and net zero energy buildings – exemplary buildings
5 Nearly zero energy (NZE) buildings or low-energy buildings are possible in all world relevant climate
6 zones (Mata et al. 2020b; Ürge-Vorsatz et al. 2020) (Figure 9.13). Moreover, they are possible both for
7 new and retrofitted buildings. Different envelope design and technologies are needed, depending on the
8 climate and the building shape and orientation. For example, using the Passive House standard an annual
9 heating and cooling energy demand decrease between 75% and 95% compared to conventional values
10 can be achieved. Table 9.2 lists several exemplary low- and NZE-buildings with some of their feature.
11
12
13
14 Figure 9.13 Regional distribution of documented low-energy buildings.
15 Source: New Building Institute 2019; Ürge-Vorsatz et al. 2020
16
17 Table 9.2 Selected exemplary low- and net zero- energy buildings worldwide (Adapted from (Mørck 2017;
18 Schnieders et al. 2020; Ürge-Vorsatz et al. 2020))
Building name Location Building type Energy efficiency and renewable energy features Measured energy
and organization performance
SDB-10 at the India Software • Hydronic cooling and a district cooling system with a EPI of 74 kWh·m-2, with
software development chilled beam installation an HVAC peak load of
development block 5.2 W·m-2 for a total
company, Infosys • Energy-efficient air conditioning and leveraged load office area of 47,340 m2
diversity across categorized spaces: comfort air and total conditioned area
conditioning (workstations, rooms), critical load of 29,115 m2
conditioning (server, hub, UPS, battery rooms),
ventilated areas (restrooms, electrical, transformer
rooms), and pressurized areas (staircases, lift wells,
lobbies)
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Final Government Distribution Chapter 9 IPCC AR6 WGIII
• BMS to control and monitor the HVAC system,
reduced face velocity across DOAS filters, and coils
that allow for low pressure drop
Y.S. Sun Green Taiwan, University • Low cost and high efficiency are achieved via passive EUI of the whole building
Building by an China research designs, such as large roofs and protruded eaves which is 29.53 kWh·m-2 (82%
electronics green are typical shading designs in hot-humid climates and more energy-saving
manufacturing building could block around 68% of incoming solar radiation compared to the similar
company Delta annually type of buildings)
Electronics Inc.,
• Porous and wind-channelling designs, such as multiple
balconies, windowsills, railings, corridors, and make
use of stack effect natural ventilation to remove warm
indoor air
• Passive cooling techniques that help reduce the annual
air-conditioning load by 30%
BCA Academy Singapore Academy • Passive design features such a green roof, green walls, First net zero energy
Building Building daylighting, and stack effect ventilation retrofitted building in
Southeast Asia
• Active designs such as energy-efficient lighting, air-
conditioning systems, building management system
with sensors and solar panels
• Well-insulated, thermal bridge free building envelope
Energy-Plus Germany School • Highly insulated Passive House standard Off grid building with an
Primary School • Hybrid (combination of natural and controlled EPI of 23 kWh m-2 yr-1
ventilation) ventilation for thermal comfort, air
quality, user acceptance and energy efficiency
• Integrated photovoltaic plant and wood pellet driven
combined heat and power generation
• Classrooms are oriented to the south to enable
efficient solar shading, natural lighting and passive
solar heating
• New and innovative building components including
different types of innovative glazing, electro chromic
glazing, LED lights, filters and control for the
ventilation system
NREL Research USA Office and • The design maximizes passive architectural strategies EPI of 110 kWh m-2 yr-1
Support Facility Research such as building orientation, north and south glazing, with a project area of
Facility daylighting which penetrates deep into the building, 20624.5 m2 to become the
natural ventilation, and a structure which stores then largest the largest
thermal energy commercial net zero
energy building in the
• Radiant heating and cooling with radiant piping country
through all floors, using water as the cooling and
heating medium in the majority of workspaces instead
of forced air
• Roof-mounted photovoltaic system and adjacent
parking structures covered with PV panels
Mohammed Bin United Non- • Exterior walls U-value = 0.08 W m-2 K-1 Cooling and
Rashid Space Arab residential, dehumidification demand
Centre (Schnieders Emirates, offices • Roof U-value = 0.08 W m-2 K-1 = 40 kWh m-2 yr-1
et al. 2020) Dubai • Floor slab U-value = 0.108 W m-2 K-1 sensible cooling +10 kWh
m-2 yr-1 latent cooling
• Windows UW = 0.89 W m-2 K-1
Primary energy demand =
• PVC and aluminium frames, triple solar protective 143 kWh m-2 yr-1
glazing with krypton filling
• Ventilation = MVHR, 89% efficiency
• Heat pump for cooling with recovery of the rejected
heat for DHW and reheating coil
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Final Government Distribution Chapter 9 IPCC AR6 WGIII
Sems Have (Mørck Roskilde, Multi-family • Pre-fabricated, light weight walls Final Energy Use: 24.54
2017) Denmark residential kWh·m-2
(Retrofit) • Low-energy glazed windows, basement insulated with
expanded clay clinkers under concrete Primary energy use: 16.17
kWh·m-2
• Balanced mechanical ventilation with heat recovery
• PV
1
2
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2 9.5 Non-technological and behavioural mitigation options and strategies
3 Non-technological (NT) measures are key for low-carbon buildings, but still attract less attention than
4 technological measures (Ruparathna et al. 2016; Vence and Pereira 2019; Cabeza et al, 2020; Creutzig
5 et al. 2016; Mundaca et al. 2019; Mata et al. 2021b)(Creutzig et al. 2018). The section is set out to
6 understand, over the buildings lifecycle, NT determinants of buildings’ energy demand and emissions
7 (Section 9.5.1); to present NT climate mitigation actions (Section 9.5.2); then, to understand how to get
8 these actions implemented (Section 9.5.3). The latter is a starting point in the design of policies (Section
9 9.9).
10 9.5.1 Non-technological determinants of energy demand and carbon emissions
11 Buildings climate impact includes CO2 emissions from operational energy use, carbon footprint, PM2.5
12 concentrations and embodied carbon, and is unequivocally driven by GDP, income, population,
13 buildings floor area, energy price, climate, behaviour, and social and physical environment (Wolske et
14 al. 2020; Mata et al. 2021d).
15 9.5.1.1 Climate and physical environment
16 Outdoor temperature, Heating and Cooling Degree Days, sunshine hours, rainfall, humidity and wind
17 are highly determinant of energy demand ( Harold et al. 2015; Rosenberg 2014; Lindberg et al. 2019;
18 Risch and Salmon 2017)(Tol et al. 2012). Density, compacity, and spatial effects define the surrounding
19 environment and urban microclimate. Urban residents usually have a relatively affluent lifestyle, but
20 use less energy for heating (Huang 2015; Niu et al. 2012; Rafiee et al. 2019; Ayoub 2019; Oh and Kim
21 2019). Urbanization is discussed in Chapter 8.
22 Climate variability and extreme events may drastically increase peak and annual energy consumption
23 (Mashhoodi et al. 2019; Cui et al. 2017; Hong et al. 2013). Climate change effects on future demand
24 and emissions, are discussed in Section 9.7, and effects of temperature on health and productivity, in
25 Section 9.8.
26 9.5.1.2 Characteristics of the building
27 Building typology and floor area (or e.g. number of bedrooms or lot size) are correlated to energy
28 demand (Fosas et al. 2018; Morganti et al. 2019; Manzano-Agugliaro et al. 2015; Moura et al. 2015;
29 Berrill et al. 2021). Affluence is embedded in these variables as higher-income households have larger
30 homes and lots. Residential consumption increases with the number of occupants but consumption per
31 capita decreases proportionally to it (Serrano et al. 2017). Construction or renovation year has a negative
32 correlation as recently built buildings must comply with increasingly strict standards (Brounen et al.
33 2012; Kavousian et al. 2015; Österbring et al. 2016). Only for electricity consumption no significant
34 correlation is observed to building age (Kavousian et al. 2013). Material choices, bioclimatic and
35 circular design discussed in Section 9.4.2.
36 9.5.1.3 Socio-demographic factors
37 Income is positively correlated to energy demand (Singh et al. 2017; Bissiri et al. 2019; Sreekanth et al.
38 2011; Couture et al. 2012;Yu 2017; Moura et al. 2015; Mata et al. 2021b; Cayla et al. 2011). High-
39 income households tend to use more efficient appliances and are likely to be more educated and
40 environmentally sensitive, but their higher living standards require more energy (Hidalgo et al. 2018;
41 Harold et al. 2015). Low-income households are in higher risk of fuel poverty (Section 9.8).
42 Mixed effects are found for household size, age, gender, ethnicity, education levels and tenancy status
43 (Engvall et al. 2014; Arawomo 2019; Lévy and Belaïd 2018; Hansen 2016; Rafiee et al. 2019). Single-
44 parent and elderly households consume more gas and electricity, and gender has no significant effect
45 (Harold et al. 2015; Brounen et al. 2012; Huang 2015). Similarly, larger families use less electricity per
46 capita (Bedir et al. 2013; Kavousian et al. 2013). Heating expenditure tends to be higher for owners
47 than for renters, despite the formers tendency to have more efficient appliances (Gillingham et al. 2012;
48 Davis, 2012; Kavousian et al. 2015).
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1 9.5.1.4 Behaviour
2 Occupants presence and movement, interactions with the building, comfort-driven adaptations and
3 cultural practices determine energy consumption (Li et al. 2019; Khosla et al. 2019; D’Oca et al. 2018;
4 Hong et al. 2017; O’Brien et al. 2020; Yan et al. 2017). Households consume more on weekends and
5 public holidays, and households with employed occupants consume less than self-employed occupants,
6 probably because some of the latter jobs are in-house (Harold et al. 2015; Hidalgo et al. 2018).
7 Understanding and accurate modelling of occupant behaviour is crucial to reduce the gap between
8 design and energy performance (Gunay et al. 2013; Yan et al. 2017), especially for more efficient
9 buildings, which rely on passive design features, human-centred technologies, and occupant
10 engagement (Grove-Smith et al. 2018; Pitts 2017).
11 9.5.2 Insights from non-technological and behavioural interventions
12 A range of NT actions can substantially reduce buildings energy demand and emissions (Figure 9.14;
13 see Supplementary Material SM9.2 for details). The subsections below present insights on the variations
14 depending on the solution, subsector, and region.
15
16 Figure 9.14 Energy saving and GHG mitigation potentials for categories of NT interventions for
17 Residential (R) and Non-Residential (NR) buildings, from studies with worldwide coverage.
18 Sources: (Ruparathna et al. 2016b; Khosrowpour et al. 2016; Kaminska 2019; Creutzig et al. 2016; Wilson et al.
19 2020b; Derungs et al. 2019; Levesque et al. 2019a; Bierwirth and Thomas 2019b; Roussac and Bright 2012;
20 Ohueri et al. 2018; Bavaresco et al. 2020; Ahl et al. 2019; Van Den Wymelenberg 2012; Cantzler et al. 2020;
21 Ivanova and Büchs 2020b; Harris et al. 2021a; van Sluisveld et al. 2016;Rupp et al. 2015; Grover 2019).
22 9.5.2.1 Passive and active design, management, and operation
23 Bioclimatic design and passive strategies for natural heating, cooling and lighting, can greatly reduce
24 buildings’ climate impact, and avoid cooling in developing countries (Bienvenido-Huertas et al. 2021,
25 2020; Amirifard et al. 2019). Design can provide additional small savings, e.g., by placing refrigerator
26 away from the oven, radiators or windows (Christidou et al. 2014). Passive management refers to
27 adjustments in human behaviour such as adapted clothing, allocation of activities in the rooms of the
28 building to minimize the energy use (Rafsanjani et al. 2015; Klein et al. 2012) or manual operation of
29 the building envelope (Rijal et al. 2012; Volochovic et al. 2012). Quantitative modelling of such
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1 measures is most common for non-residential buildings, in which adaptive behaviours are affected by
2 the office space distribution and interior design, amount of occupants, visual comfort, outdoor view,
3 and ease to use control mechanisms (Talele et al. 2018; O’Brien and Gunay 2014). Socio demographic
4 factors, personal characteristics and contextual factors also influence occupant behaviour and their
5 interactions with buildings (D’Oca et al. 2018b; Hong et al. 2020).
6 Active management refers to human control of building energy systems. Efficient lighting practices can
7 effectively reduce summer peak demand (Dixon et al. 2015; Taniguchi et al. 2016). On the contrary,
8 the application of the Daylight-Saving Time in the US increases up to 7% lighting consumption (Rakha
9 et al. 2018). Efficient cooking practices for cooking, appliance use (e.g. avoid stand-by regime, select
10 eco-mode), or for hot water can save up to 25% (Teng et al. 2012; Berezan et al. 2013; Hsiao et al.
11 2014; Abrahamse and Steg 2013; Peschiera and Taylor 2012; Dixon et al. 2015; Reichert et al. 2016).
12 High behavioural control is so far proven difficult to achieve (Ayoub et al. 2014) (Sköld et al. 2018).
13 Automated controls and technical measures to trigger occupant operations are addressed in Section 9.4.
14 9.5.2.2 Limited demands for services
15 Adjustment in the set-point temperature in winter and summer results in savings between 5% and 25%
16 (Ayoub et al. 2014)(Christidou et al. 2014; Sun and Hong 2017; Taniguchi et al. 2016). As introduced
17 in 9.3, a series of recent works study a cap on the living area (Mata et al. 2021a) or an increase in
18 household size (Berrill et al. 2021). These studies are promising but of limited complexity in terms of
19 rebounds, interactions with other measures, and business models, thus require further investigation.
20 Professional assistance and training on these issues is limited (Maxwell et al. 2018).
21 Willingness to adopt is found for certain measures (full load to laundry appliances, lid on while cooking,
22 turning lights off, defer electricity usage and HVAC systems, adjust set-point temperature by 1°C) but
23 not for others (appliances on standby, using more clothes, avoid leaving the TV on while doing other
24 things, defer ovens, ironing or heating systems, adjust set-point temperature by 3°C, move to a low
25 energy house or smaller apartment) (Brown et al. 2013; Sköld et al. 2018; Yohanis 2012; Li et al. 2017).
26 A positive synergy with digitalization and smart home appliances is identified, driven by a combination
27 of comfort requirements and economic interest, confirmed by a willingness to defer electricity usage in
28 exchange for cost savings (Ferreira et al. 2018; Mata et al. 2020c).
29 9.5.2.3 Flexibility of demand and comfort requirements
30 In a flexible behaviour, the desired level of service is the same, but it can be shifted over time, typically
31 allowing automated control, for the benefit of the electricity or district heating networks. There are
32 substantial economic, technical, and behavioural benefits from implementing flexibility measures
33 (Mata et al. 2020c), with unknown social impacts.
34 With demand side measures (DSM), such as shifting demand a few hours, peak net demand can be
35 reduced up to 10-20% (Stötzer et al. 2015), a similar potential is available for short-term load shifting
36 during evening hours (Aryandoust and Lilliestam 2017). Although different household types show
37 different consumption patterns and thus an individual availability of DSM capacity during the day (
38 Fischer et al. 2017), there is limited (Shivakumar et al. 2018) or inexistent (Nilsson et al. 2017; Drysdale
39 et al. 2015) information of consumers response to Time of Use pricing, specifically among those living
40 in apartments (Bartusch and Alvehag 2014). Behavioural benefits are identified in terms of increased
41 level of energy awareness of the users (Rehm et al. 2018), measured deliberate attempts of the
42 consumers to reduce and/or shift their electricity usage (Bradley et al. 2016). Real-time control and
43 behavioural change influence 40% of the electricity use during operational life of non-residential
44 buildings (Kamilaris et al. 2014).
45 9.5.2.4 Circular and sharing economy (CSE)
46 Non technological CSE solutions, based on the Regenerate, Share, Optimize, Loop, Virtualize,
47 Exchange (ReSOLVE) framework (CE100 2016; ARUP 2018) include sharing, virtualizing and
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1 exchanging. These are less studied than circular materials, with notably less investigation of existing
2 buildings and sharing solutions (Pomponi and Moncaster 2017; Høibye and Sand 2018; Kyrö 2020;
3 European Commission 2020).
4 The sharing economy generates an increased utilization rate of products or systems by enabling or
5 offering shared use, access or ownership of products and assets that have a low ownership or use rate.
6 Measures include conditioned spaces (accommodation, facility rooms, offices) as well as tools and
7 transfer of ownership (i.e., second-hand or donation) (Rademaekers et al. 2017; Harris et al. 2021;
8 Mercado 2018; Hertwich et al. 2020; Cantzler et al. 2020; Mata et al. 2021c). The evidence on the link
9 between user behaviour and net environmental impacts of sharing options is still limited (Laurenti et al.
10 2019; Mata et al. 2020a; Harris et al. 2021b) and even begins to be questioned, due to rebounds that
11 partially or fully offset the benefits (Agrawal and Bellos 2017; Zink and Geyer 2017). E.g., the costs
12 savings from reduced ownership can be allocated to activities with a higher carbon intensity, or result
13 in increased mobility. Both reduced ownership and other circular consumption habits show no influence
14 on material footprint, other than mildly positive influence in low-income households (Junnila et al.
15 2018; Ottelin et al. 2020).
16 9.5.2.5 Value-chain, social and institutional innovations
17 Cooperative efforts are necessary to improve buildings energy efficiency (Masuda and Claridge 2014;
18 Kamilaris et al. 2014; Ruparathna et al. 2016). For instance, inter-disciplinary understanding of
19 organizational culture, occupant behaviour, and technology adoption is required to set up
20 occupancy/operation best practises (Janda 2014). Similarly, close collaboration of all actors along the
21 value chain can reduce by 50% emissions from concrete use (Habert et al. 2020); such collaboration
22 can be enhanced in a construction project by transforming the project organisation and delivery contract
23 to reduce costs and environmental impact (Hall and Bonanomi 2021). Building commissioning helps to
24 reduce energy consumption by streamlining the systems, but benefits may not persistent. Energy
25 communities are discussed later in the chapter.
26 NT challenges include training and software costs (tailored learning programs, learning-by-doing,
27 human capital mobilization), client and market demand (service specification, design and provision;
28 market and financial analysis) and legal issues (volatile energy prices, meeting regulation); and
29 partnership, governance and commercialization. These challenges are identified for Building
30 Information Modelling (Rahman and Ayer 2019; Oduyemi et al. 2017), PV industry (Triana et al. 2018),
31 Smart Living (Solaimani et al. 2015) or circular economy (Vence and Pereira 2019).
32 9.5.3 Adoption of climate mitigation solutions– reasons and willingness
33 Mixed effects are found for technical issues, attitudes, and values (Table 9.3). In spite of proven positive
34 environmental attitudes and willingness to adopt mitigation solutions, these are outweighed by financial
35 aspects all over the world (Mata et al. 2021b). Adopters in developed countries are more sensitive
36 towards financial issues and comfort disruptions; whereas in other world regions techno-economic
37 concerns prevail. Private consumers seem ready to support stronger governmental action, whereas non-
38 private interventions are hindered by constraints in budgets and profits, institutional barriers and
39 complexities (Curtis et al. 2017; Zuhaib et al. 2017; Tsoka et al. 2018; Kim et al. 2019).
40 A variety of interventions targeted to heterogeneous consumer groups and decision makers is needed to
41 fulfil their diverse needs (Zhang et al. 2012; Liang et al. 2017; Soland et al. 2018; Marshall et al. 2015;
42 Haines and Mitchell 2014; Gram-Hanssen 2014; Friege et al. 2016; Hache et al. 2017; Ketchman et al.
43 2018). Policy reviews for specific market segments and empirical studies investigating investment
44 decisions would benefit from a multidisciplinary approach to energy consumption patterns and market
45 maturity (Boyd 2016; Marzano et al. 2018; Heiskanen and Matschoss 2017; Baumhof et al. 2018;
46 Wilson et al. 2018).
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1 Table 9.3 Reasons for adoption of climate mitigation solutions. The sign represents if the effect is positive
2 (+) or negative (-), and the number of signs represents confidence level (++, many references; +, few
3 references) (Mata et al. 2021a)
Climate mitigation solutions for buildings
and
Digitalization and
On-site renewable
Efficient technical
Building envelope
sharing econ.
Performance
Low-carbon
Behaviour
standards
flexibility
materials
Circular
systems
energy
Economic:
Subsidies/microloans* + ++ ++ + ++ +
Low/high investment costs - +/-- ++/-- +/- +/-- +/- - -
Short payback period + + + + + + +
High potential savings ++ ++ ++ + ++ ++ +
Market-driven demand + + + + +
Higher resale value + + + + +
Operating/maintenance costs + ++/- ++/- + + + +/-
Split incentives - - - - - -
Constrained budgets and profits - -- - -- - -- --
Price competitive (overall) + + + + + +
Information and support:
Governmental support and capacity/lack of +/- +/- ++/- ++/- + +/- -
Institutional barriers and complexities - - - - -- - - -
Information and labeling/lack of +/- ++/- ++/- + ++/- +/- -
Smart metering + + + +
Participative ownership + + + + +
Peer effects + + ++ + +
Professional advice/lack of +/- ++/- ++/- - +/-- - +/- +/-
Social norm + + + + + + +
Previous experience with solution/lack of +/- +/- +/- - - - +/- +/-
Technical:
Condition of existing elements + + + + + +
Natural resource availability + + ++ + + +
Performance and maintenance concerns* - - -- -- - - -
Low level of control over appliances - - - - -
Limited alternatives available - - - -
Not compatible with existing equipment - - - - - -
Attitudes and values:
Appealing novel technology + + ++ + + + ++ +
Social and egalitarian world views + + + + +
Willingness to pay + ++ + +
Heritage or aesthetic values +/- ++/- +/- +/- +/-
Environmental values + + ++ + ++ + ++ +
Status and comfort / Lack of ++ ++ ++ + ++ +
Discomfort during the retrofitting period - - - - -
Control, privacy, and security / Lack of* +/- +/- - - - +/--
Risk aversion - - - - - -
Social:
Size factors (household, building) +/- ++/- + + +
Status (education, income) +/- ++/- +/- +/- +/- + +/-
Sociodemographic (age, gender, and ethnicity) +/- ++/- +/- +/- +/- +/-
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1
2 9.5.3.1 Building envelope
3 In North America and Europe, personal attitudes, values, and existing information and support are the
4 most and equally important reasons for improving the building envelope. Consumers have some
5 economic concerns and little technical concerns, the later related to the performance and maintenance
6 of the installed solutions (Mata el al, 2021c). In other world regions or per climate zone the literature is
7 limited.
8 Motivations are often triggered by urgent comfort or replacement needs. Maintaining the aesthetic value
9 may as well hinder the installation of insulation if no technical solutions are easily available (Haines
10 and Mitchell 2014; Bright et al. 2019). Local professionals and practitioners can both encourage
11 (Ozarisoy and Altan 2017; Friege 2016) and discourage the installation of insulation, according to their
12 knowledge and training (Maxwell et al. 2018; Curtis et al. 2017; Zuhaib et al. 2017; Tsoka et al. 2018).
13 If energy renovations of the buildings envelopes are not normative, cooperative ownership may be a
14 barrier in apartment buildings (Miezis et al. 2016). Similarly, product information and labelling may be
15 helpful or overwhelming (Ozarisoy and Altan 2017; Lilley et al. 2017; Bright et al. 2019). Decisions
16 are correlated to governmental support (Tam et al. 2016; Swantje et al. 2015) and peer information
17 (Friege et al. 2016; Friege 2016).
18 The intervention is required to be cost efficient, although value could be placed in the amount of energy
19 saved (Mortensen et al. 2016; Howarth and Roberts 2018; Kim et al. 2019; Lilley et al. 2017) or the
20 short payback period (Miezis et al. 2016). Subsidies have a positive effect (Swan et al. 2017).
21 9.5.3.2 Adoption of efficient HVAC systems and appliances
22 Mixed willingness is found to adopt efficient technologies. While developed countries are positive
23 towards building envelope technologies, appliances such as A-rated equipment or condensing boilers
24 are negatively perceived (Yohanis 2012). In contrast, adopters in Asia are positive towards energy
25 saving appliances (Liao et al. 2020; Spandagos et al. 2020).
26 Comfort, economic and ecological aspects, as well as information influence the purchase of a heating
27 system (Decker and Menrad 2015; Claudy et al. 2011). Information and support from different
28 stakeholders are the most relevant aspects in different geographical contexts (Tumbaz and Moğulkoç
29 2018; Hernandez-Roman et al. 2017; Curtis et al. 2018; Bright et al. 2019; Chu and Wang 2019).
30 Among high-income countries, economy aspects have positive effects, specially reductions in energy
31 bills and financial incentives or subsidies (Mortensen et al. 2016; Clancy et al. 2017; Christidou et al.
32 2014; Chun and Jiang 2013; Ketchman et al. 2018). Having complementary technologies already in
33 place also has positively affects adoption (Zografakis et al. 2012; Clancy et al. 2017), but performance
34 and maintenance concerns appear as barriers (Qiu et al. 2014). The solutions are positively perceived
35 as high-technology innovative, to enhance status, and are supported by peers and own-environmental
36 values (Ketchman et al. 2018; Mortensen et al. 2016; Heiskanen and Matschoss 2017).
37 9.5.3.3 Installation of renewable energy sources (RES)
38 Although consumers are willing to install distributed RES worldwide, and information has successfully
39 supported their roll out, economic and governmental support is still necessary for their full deployment.
40 Technical issues remain for either very novel technologies or for the integration of RES in the energy
41 system (Mata et al. 2021c; Ürge-Vorsatz et al. 2020). Capacities are to be built by coordinated actions
42 by all stakeholders (Musonye et al. 2020). To this aim, energy communities and demonstrative
43 interventions at local scale are key to address technical, financial, regulatory and structural barriers and
44 document long-term benefits (von Wirth et al. 2018; Shafique M Luo J 2020, Fouladvand et al. 2020).
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1 Regarding solar technologies, heterogeneous decisions are formed by sociodemographic, economic and
2 technical predictors interwoven with a variety of behavioural traits (Alipour M Salim RA Sahin, O
3 2020; Khan 2020). Studies on PV adoption confirm place-specific (various spatial and peer effects),
4 multi-scalar cultural dynamics (Schaffer and Brun 2015; Bollinger and Gillingham 2012; Graziano and
5 Gillingham 2015). Environmental concern and technophilia drive the earliest PV adopters , while later
6 adopters value economic gains (Hampton and Eckermann 2013; Jager-Waldau et al. 2018; Abreu et al.
7 2019; Palm 2020). Previous experience with similar solutions increases adoption (Bach et al. 2020; K
8 2018; QURAISHI and AHMED 2019; Reindl and Palm 2020).
9 9.5.3.4 Low-carbon materials
10 Studies on low-carbon materials tend to focus on wood-based building systems and prefabricated
11 housing construction, mostly in high-income countries, as many sustainable managed forestries and
12 factories for prefabricated housing concentrated in such regions (Mata el al, 2021c). This uneven
13 promotion of wood can lead to its overconsumption (Pomponi et al. 2020).
14 Although the solutions are not yet implemented at scale, examples include , the adoption of low carbon
15 cement in Cuba motivated by the possibility of supplying the raising demand with low initial investment
16 costs (Cancio Díaz et al. 2017) or adoption of bamboo based social houses in Philippines motivated by
17 local job creation and Typhoon resistance (Zea Escamilla et al. 2016). More generally, low investment
18 costs and high level decision-making, e.g. political will and environmental values of society, increase
19 the adoption rate of low-carbon materials (Steinhardt and Manley 2016; Lien and Lolli 2019; Hertwich
20 et al. 2020). In contrast, observed barriers include lobbying by traditional materials industries, short-
21 term political decision making (Tozer 2019) and concerns over technical performance, risk of damage,
22 and limited alternatives available (Thomas et al. 2014).
23 9.5.3.5 Digitalization and demand-supply flexibility
24 Demand-supply flexibility measures are experimentally being adopted in North America, Europe, and
25 Asia-Pacific Developed regions. Changes in the current regulatory framework would facilitate
26 participation based on trust and transparent communication (Wolsink 2012; Nyborg and Røpke 2013;
27 Mata et al. 2020b). However, consumers expect governments and energy utilities to steer the transition
28 (Seidl et al. 2019).
29 Economic challenges are observed, as unclear business models, disadvantageous market models and
30 high costs of advanced smart metering. Technical challenges include constraints for HPs and seasonality
31 of space heating demands. Social challenges relate to lack of awareness of real-time price information
32 and inadequate technical understanding. Consumers lack acceptance towards comfort changes (noise,
33 overnight heating) and increased automation (Sweetnam et al. 2019; Bradley et al. 2016; Drysdale et
34 al. 2015). Risks identified include higher peaks and congestions in low price-hours, difficulties in
35 designing electricity tariffs because of conflicts with CO2 intensity, and potential instability in the entire
36 electricity system caused by tariffs coupling to wholesale electricity pricing.
37 Emerging market players are changing customer utility relationships, as the grid is challenged with
38 intermittent loads and integration needs for ICTs, interfering with consumers requirements of autonomy
39 and privacy (Parag and Sovacool 2016; Wolsink 2012). Although most private PV owners would make
40 their storage system available as balancing load for the grid operator, the acquisition of new batteries
41 by a majority of consumers requires incentives (Gährs et al. 2015). For distributed energy hubs, social
42 acceptance depends on the amount of local benefits in economic, environmental or social terms
43 (Kalkbrenner and Roosen 2015), and increases around demonstration projects (von Wirth et al. 2018).
44 9.5.3.6 Circular and sharing economy
45 The circular and sharing economy begins to be perceived as organizational and technologically
46 innovative, with the potential to provide superior customer value, response to societal trends and
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1 positive marketing (Mercado 2018; Cantzler et al. 2020; L.K et al. 2020). Although technical and
2 regulatory challenges remain, there are key difficulties around the demonstration of a business case for
3 both consumers and the supply chain (Pomponi and Moncaster 2017; Hart et al. 2019).
4 Government support is needed an initiator but also to reinforce building retrofit targets, promote more
5 stringent energy and material standards for new constructions, and protect consumer interests
6 (Hongping 2017; Fischer and Pascucci 2017; Patwa et al. 2020). Taxes clearly incentivize waste
7 reduction and recycling (Ajayi et al. 2015; Rachel and Travis 2011; Volk et al. 2019). In developing
8 countries, broader, international, market boundaries can allow for a more attractive business model
9 (Mohit et al. 2020). Participative and new ownership models can favour the adoption of prefabricated
10 buildings (Steinhardt and Manley 2016). Needs for improvements are observed, in terms of design for
11 flexibility and deconstruction, procurement and prefabrication and off-site construction, standardization
12 and dimensional coordination, with differences among solutions (Ajayi et al. 2017)(Schiller et al,
13 2015,2017; Osmani, 2012; Lu and Yuan, 2013; Cossu and Williams, 2015; Bakshan et al 2017; Coehlo
14 et al 2013).
15 Although training is a basic requirement, attitude, past experience, and social pressure can also be highly
16 relevant, as illustrated for waste management in a survey to construction site workers (Amal et al. 2017).
17 Traditional community practices of reuse of building elements are observed to be replaced by a culture
18 of waste (Hongping 2017; Ajayi et al. 2015).
19
20 9.6 Global and regional mitigation potentials and costs
21 9.6.1 Review of literature calculating potentials for different world countries
22 Section 9.4 provides an update on technological options and practices, which allow constructing and
23 retrofitting individual buildings to produce very low emissions during their operation phase. Since AR5,
24 the world has seen a growing number of such buildings in all populated continents, and a growing
25 amount of literature calculates the mitigation potential for different countries if such technologies and
26 practices penetrate at scale. Figure 9.15 synthesizes the results of sixty-seven bottom-up studies, which
27 rely on the bottom-up technology-reach approach and assess the potential of such technologies and
28 practices, aggregated to stock of corresponding products and/or buildings at national level.
29 The studies presented in Figure 9.15 rely on all, the combination, or either of the following mitigation
30 strategies: the construction of new high energy-performance buildings taking the advantage of building
31 design, forms, and passive construction methods; the thermal efficiency improvement of building
32 envelopes of the existing stock; the installation of advanced HVAC systems, equipment and appliances;
33 the exchange of lights, appliances, and office equipment, including ICT, water heating, and cooking
34 with their efficient options; demand side management, most often controlling comfort requirements and
35 demand-side flexibility and digitalization; as well as onsite production and use of renewable energy.
36 Nearly all studies, which assess the technological potential assume such usage of space heating, cooling,
37 water heating, and lighting that does not exceed health, living, and working standards, thus realizing at
38 least a part of the non-technological potential, as presented in Figure 9.14. The results presented in
39 Figure 9.15 relate to measures applied within the boundaries of the building sector, including the
40 reduction in direct and indirect emissions. The results exclude the impact of decarbonisation measures
41 applied within the boundaries of the energy supply sector, i.e., the decarbonisation of grid electricity
42 and district heat.
43 The analysis of Figure 9.15 illustrates that there is a large body of literature attesting to mitigation
44 potential in the countries of Europe and North America of up to 55-85% and in Asia-Pacific Developed
45 of up to 45% in 2050, as compared to their sector baseline emissions, even though they sometimes
46 decline. For developing countries, the literature estimates the potential of up to 40-80% in 2050, as
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1 compared to their sharply growing baselines. The interpretation of these estimates should be cautious
2 because the studies rely on assumptions with uncertainties and feasibility constrains (see Sections 9.6.4,
3 Figure 9.20 and Table SM9.6).
4
5 Figure 9.15 Potential GHG emission reduction in buildings of different world countries grouped by
6 region, as reported by sixty-seven bottom-up studies
7 Sources: North America: Canada (Radpour et al. 2017; Subramanyam et al. 2017a,b; Trottier 2016; Zhang et al.
8 2020a), the Unites States of America (Gagnon, Peter, Margolis, Robert, Melius, Jennifer, Phillips, Saleb, Elmore
9 2016; Nadel 2016; Yeh et al. 2016; Zhang et al. 2020a; Wilson et al. 2017); Europe: Albania (Novikova et al.
10 2020, 2018c), Austria (Ploss et al. 2017), Bulgaria, the Czech Republic, Hungary (Csoknyai et al. 2016), France
11 (Ostermeyer, Y.; Camarasa, C.; Saraf, S.; Naegeli, C.; Jakob, M.; Palacios, A, Catenazzi 2018), the European
12 Union (Roscini et al. 2020; Brugger et al. 2021; Duscha et al. 2019), Germany (Markewitz et al. 2015; Bürger et
13 al. 2019; Ostermeyer et al. 2019b), Greece (Mirasgedis et al. 2017), Italy (Calise et al. 2021; Filippi Oberegger
14 et al. 2020), Lithuania (Toleikyte et al. 2018), Montenegro (Novikova et al. 2018c), Netherlands (Ostermeyer et
15 al. 2018a), Norway (Sandberg et al. 2021), Serbia (Novikova et al. 2018a), Switzerland (Iten et al. 2017;
16 Streicher et al. 2017), Poland (Ostermeyer et al. 2019a), the United Kingdom (Ostermeyer, Y.; Camarasa, C.;
17 Naegeli, C.; Saraf, S.; Jakob, M.; Hamilton, I; Catenazzi 2018a); Eurasia: Armenia, Georgia (Timilsina et al.
18 2016); the Russian Federation (Bashmakov 2017; Zhang et al. 2020a); Asia-Pacific Developed: Australia
19 (Butler et al. 2020; Energetics 2016; Zhang et al. 2020a), Japan (Zhang et al. 2020a; Momonoki et al. 2017;
20 Wakiyama and Kuramochi 2017; Sugyiama et al. 2020; Minami et al. 2019); Africa: Egypt (Pedzi Makumbe,
21 Manuela Mot, Marwa Moustafa Khalil 2017; Calise et al. 2021), Morocco (Merini et al. 2020), Nigeria (Dioha
22 et al. 2019; Kwag et al. 2019; Onyenokporo and Ochedi 2019), Rwanda (Colenbrander et al. 2019), South
23 Africa (Department of Environmental Affairs 2014), Uganda (de la Rue du Can et al. 2018), Algeria, Egypt,
24 Libya, Morocco, Sudan, Tunisia (Krarti 2019); Middle East - Qatar (Krarti et al. 2017; Kamal et al. 2019),
25 Saudi Arabia (Khan et al. 2017; Alaidroos and Krarti 2015), Bahrain, Iraq, Jordan, Kuwait, Lebanon, Oman,
26 Qatar, Saudi Arabia, State of Palestine, Syrian Arab Republic, United Arab Emirates, Yemen (Krarti 2019);
27 Eastern Asia - China (Tan et al. 2018; Xing et al. 2021; Zhou et al. 2018; Zhang et al. 2020); Southern Asia:
28 India (de la Rue du Can et al. 2019; Yu et al. 2018; Zhang et al. 2020); South-East Asia and Developing Pacific:
29 Indonesia (Kusumadewi and Limmeechokchai 2015, 2017), Thailand (Kusumadewi and Limmeechokchai 2015,
30 2017; Chaichaloempreecha et al. 2017), Viet Nam (ADB 2017), respective countries from the Asia-Pacific
31 Economic Cooperation (APEC) (Zhang et al. 2020a); Latin America and Caribbean: Brazil (de Melo and de
32 Martino Jannuzzi 2015; González-Mahecha et al. 2019), Colombia (Prada-hernández et al. 2015), Mexico
33 (Grande-acosta and Islas-samperio 2020; Rosas-Flores and Rosas-Flores 2020).
34 The novelty since AR5 is emerging bottom-up literature, which attempts to account for potential at
35 national and global level from applying the sufficiency approach (see Box 9.1 in Section 9.1and
36 decomposition analysis in Section 9.3.2). In spite of the reducing energy use per unit of floor area at
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1 an average rate of 1.3% per year, the growth of floor area at an average rate of 3% per year causes rising
2 energy demand and GHG emissions because each new square meter must be served with thermal
3 comfort and/or other amenities (International Energy Agency 2017; Ellsworth-Krebs 2020). Nearly all
4 studies reviewed in Figure 9.15 assume the further growth of floor area per capita until 2050, with many
5 studies of developing countries targeting today per capita floor area as in Europe.
6 Table 9.4 reviews the bottom-up literature, which quantifies the potential from reorganization of human
7 activities, efficient design, planning, and use of building space, higher density of building and settlement
8 inhabitancy, redefining and downsizing goods and equipment, limiting their use to health, living, and
9 working standards, and their sharing, recognizing the number of square meters and devices as a
10 determinant of GHG emissions that could be impacted via policies and measures. Nearly all national or
11 regional studies originate from Europe and North America recognizing challenges, developed countries
12 face toward decarbonisation. Thus, (Goldstein et al. 2020) suggested prioritizing the reduction in floor
13 space of wealthier population and more efficient space planning because grid decarbonisation is not
14 enough to meet the U.S. target by 2050 whereas affluent suburbs may have 15 times higher emission
15 footprints than nearby neighbourhoods. (Cabrera Serrenho et al. 2019) argue that reducing the UK floor
16 area is a low cost mitigation option given a low building replacement rate and unreasonably high retrofit
17 costs of existing buildings. (Lorek and Spangenberg 2019) discusses the opportunity of reducing
18 building emissions in Germany fitting better the structure of the dwelling stock to the declined average
19 household size, as most dwellings have 3–4 rooms while most households have only one person.
20 Whereas these studies suggest sufficiency as an important option for developed countries, global studies
21 argue that it is also important for the developing world. This is because it provides the means to address
22 inequality, poverty reduction and social inclusion, ensuring the provision of acceptable living standards
23 for the entire global population given the planetary boundaries. As Figure 9.6 illustrates, the largest
24 share of current construction occurs in developing countries, while these countries follow a similar
25 demographic track of declining household sizes versus increasing dwelling areas. This trajectory
26 translates into the importance of their awareness of the likely similar forthcoming challenges, and the
27 need in early efficient planning of infrastructure and buildings with a focus on space usage and density.
28
29 Table 9.4 Potential GHG emission reduction in the building sector offered by the introduction of
30 sufficiency as a main or additional measure, as reported by bottom-up (or hybrid) literature
Region Reference Scenario and its result Sufficiency for floor space
Globe (Grubler et al. The Low Energy Demand Scenario halves the final energy demand The scenario assumed a reduction in
2018) of buildings by 2050, as compared the WEO Current Policy the residential and non-residential
(International Energy Agency 2019c) by modelling the changes in building floor area to 29 and 11
quantity, types, and energy intensity of services. m2·cap-1 respectively.
Globe (Millward- With the changes in structural and technological intensity, the The scenario assumed a reduction in
Hopkins et al. Decent Living Energy scenario achieved the decent living standard floor area to 15 m2·cap-1 across the
2020) for all whilst reducing the final energy consumption of buildings by world.
factor three, as compared to the WEO Current Policy Scenario
(International Energy Agency 2019c).
Globe (Levesque et Realizing both the technological and sufficiency potential, the Low The Low Scenario limited the
al. 2019) Demand Scenario and the Very Low Demand Scenario calculated a residential and non-residential floor
reduction in global building energy demand by 32% and 45% in area to 70 and 23 m2·cap-1; the Very
2050, as compared to the business-as-usual baseline. Low Scenario - to 45 and 15 m2·cap-
1.
EU (Bierwirth For the EU residential sector, the authors calculated potential A reduction of the residential floor
and Thomas energy savings of 17% and 29% from setting the per capita floor area to 30 m2·cap-1 and 35 m2·cap-1.,
2019b) area limits. respectively.
EU (Roscini et al. With help of technological and non-technological measures, the The scenario assumed 6% decrease
2020) Responsible Policy Scenario for the EU buildings allows achieving in the residential per capita floor
the emission reduction by 60% in 2030, as compared to 2015. area (to max. 44.8 m2·cap-1).
Canada, (Hertwich et The potential reduction in GHG emissions from the production of Via the efficient use of living space,
UK, al. 2020) building materials is 56%-58% in 2050, as compared to these the scenario assumed its 20%
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France, baseline emissions. The reduction in heating and cooling energy reduction, as compared to its
Italy, demand is 9%-10% in 2050, as compared to its baseline. baseline development
Japan,
USA,
Germany
UK (Cabrera The scenario found that the sufficiency measures allowed The scenario assumed a 10%
Serrenho et al. mitigating 30% of baseline emissions of the English building sector reduction in the current floor area
2019) in 2050, without other additional measures. per capita by 2050.
USA (Goldstein et The scenario calculated 16% GHG mitigation potential in 2050, as The scenario assumed a 10%
al. 2020) compared to the baseline, on the top of two other scenarios reduction in per capita floor area and
assuming building retrofits and grid decarbonization already higher penetration of onsite
delivering a 42% emission reduction. renewable energy.
Switzerland (Roca- The Green Lifestyle scenario allows achieving 48% energy savings The scenario assumed a reduction in
Puigròs et al. by 2050, as compared to the baseline, due to sufficiency in the floor residential floor area. from 47 to 41
2020) area among other measures. m2·cap-1.
France (Negawatt The Negawatt scenario assumes that sufficiency behaviour becomes The scenario assumes a limit of the
2017) a mainstream across all sectors. In 2050, the final energy savings residential floor at 42 m2·cap-1 due
are 21% and 28% for the residential and tertiary sectors to apartment sharing and compact
respectively, as compared to their baselines. urban planning.
France (Virage- The authors assessed sufficiency opportunities across all sectors for The scenario assumed sharing
Energie Nord- the Nord-Pas-de-Calais Region of France. Depending on the level spaces, downsizing spaces and
Pas-de- of implementation, sufficiency could reduce the energy sharing equipment from a ‘soft’ to
Calais. 2016) consumption of residential and tertiary buildings by 13-30% in ‘radical’ degree.
2050, as compared to the baseline.
1
2 9.6.2 Assessment of the potentials at regional and global level
3 This section presents an aggregation of bottom-up potential estimates for different countries into
4 regional and then global figures for 2050, based on literature presented in Section 9.6.1. First, national
5 potential estimates reported as a share of baseline emissions in 2050 were aggregated into regional
6 potential estimates. Second, the latter were multiplied with regional baseline emissions to calculate the
7 regional potential in absolute numbers. Third, the global potential in absolute numbers was calculated
8 as a sum of regional absolute potentials. When several bottom-studies were identified for a region, either
9 a rounded average or a rounded median figure was taken, giving the preference to the one that was
10 closest to the potential estimates of countries with very large contribution to regional baseline emissions
11 in 2050 (i.e., to China in Eastern Asia). Furthermore, we preferred studies, which assessed the whole or
12 a large share of sector emissions and considered a comprehensive set of measures. The regional baseline
13 emissions, refer the WEO Current Policy Scenario (International Energy Agency 2019c). The sector
14 mitigation potential reported in Chapter 12 for the year 2030 was estimated in the same manner.
15 Figure 9.16 presents the mitigation potential in the building sector for the world and each region in
16 2050, estimated as a result of this aggregation exercise. The potentials presented in the figure are
17 different from those reported in Section 9.3.3, where they are estimated by IEA and IMAGE hybrid
18 model. The figure provides two breakdowns of the potential, into the reduction of direct and indirect
19 emissions as well as into the reduction of emissions from introducing sufficiency, energy efficiency,
20 and renewable energy measures. The potential estimates rely on the incremental stepwise approach,
21 assembling the measures according to the SER framework (see Box 9.1) and correcting the amount of
22 the potential at each step for the interaction of measures. The sequence of energy efficiency and
23 renewable energy measures follow the conclusion of the IPCC Global warming of 1.5°C Report (Rogelj
24 et al. 2018) that lower energy demand allows more choice of low-carbon energy supply options, and
25 therefore such sequencing is more beneficial and cost-effective.
26 Figure 9.16 argues that it is possible to mitigate 8.2 GtCO2 or 61% of global building emissions in 2050,
27 as compared to their baseline. At least 1.4 GtCO2 or 10% of baseline emissions could be avoided
28 introducing the sufficiency approaches. Further 5.6 GtCO2 or 42% of baseline emissions could be
29 mitigated with the help of energy efficiency technologies and practices. Finally, at least 1.1 GtCO2 or
30 9% of baseline emissions could be reduced through the production and use of onsite renewable energy.
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1 Out of the total potential, the largest share of 5.4 GtCO2 will be available in developing countries; these
2 countries will be able to reduce 59% of their baseline emissions. Developed countries will be able to
3 mitigate 2.7 GtCO2 or 65% of their baseline emissions. Only few potential studies, often with only few
4 mitigation options assessed, were available for the countries of South-East Asia and Developing Pacific,
5 Africa, and Latin America and Caribbean; therefore, the potential estimates represent low estimates,
6 and the real potentials are likely be higher.
7
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1 Note: the baseline refers to the WEO Current Policy Scenario (International Energy Agency 2019c). It may differ from other chapters.
2 Figure 9.16 Global and regional estimates of GHG emissions in the building sector in 2020 and 2050, and
3 their potential reduction in 2050 broken down by measure (sufficiency / energy efficiency / renewable
4 energy) and by emission source (direct / indirect)
5 9.6.3 Assessment of the potential costs
6 The novelty since AR5 is that a growing number of bottom-up studies considers the measures as an
7 integrated package recognising their technological complementarity and interdependence, rather than
8 the linear process of designing and constructing buildings and their systems, or incremental
9 improvements of individual building components and energy-using devices during building retrofits,
10 losing opportunities for the optimisation of whole buildings. Therefore, integrated measures rather than
11 the individual measures are considered for the estimates of costs and potentials. Figure 9.17 presents
12 the indicative breakdown of the potential reported in Figure 9.16 by measure and cost, to the extent that
13 it was possible to disaggregate and align to common characteristics. Whereas the breakdown per
14 measure was solely based on the literature reviewed in Section 9.6.1, the cost estimates additionally
15 relied on the literature presented in this section, Figure 9.20, and Table SM9.6. The literature reviewed
16 reports fragmented and sometimes contradicting cost-effectiveness information. Despite a large number
17 of exemplary buildings achieving very high performance in all parts of the world, there is a lack of
18 mainstream literature or official studies assessing the costs of these buildings at scale (Lovins 2018;
19 Ürge-Vorsatz et al. 2020).
20 Figure 9.17 indicates that a very large share of the potential in developed countries could be realized
21 through the introduction of sufficiency measures (at least 18% of their baseline emissions). Literature
22 identifies many opportunities, which may help operationalize it. These are reorganization of human
23 activities, teleworking, coworking, more efficient space design, planning and use, higher density of
24 building and settlement inhabitancy, flexible space, housing swaps, shared homes and facilities, space
25 and room renting, and others (Bierwirth and Thomas 2019a; Ivanova and Büchs 2020; Ellsworth-Krebs
26 2020). Whereas literature does not provide a robust cost assessment of the sufficiency potential, it
27 indicates that these measures are likely to be at no or very little cost (Cabrera Serrenho et al. 2019).
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1
2 Notes: 1. The baseline refers to the WEO Current Policy Scenario (International Energy Agency 2019c). It may differ from other chapters. 2. The figure merged the results of Eurasia into those of developed countries.
3 Figure 9.17 Indicative breakdown of GHG emission reduction potential of the buildings sector in developed and developing countries into measure and costs in
4 2050, in absolute figures with uncertainty ranges and as a share of their baseline emissions
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1 The exchange of lights, appliances, and office equipment, including ICT, water heating, and cooking
2 technologies could reduce more than 8% and 13% of the total sector baseline emissions in developed
3 and developing countries respectively, typically at negative cost (González-Mahecha et al. 2019;
4 Grande-Acosta and Islas-Samperio 2020; de Melo and de Martino Jannuzzi 2015; Prada-hernández et
5 al. 2015; Subramanyam et al. 2017a,b; Department of Environmental Affairs 2014). This cost-
6 effectiveness is however often reduced by a larger size of appliances and advanced features, which
7 offset a share of positive economic effects (Molenbroek et al. 2015).
8 Advanced HVAC technologies backed-up with demand side management, and onsite integrated
9 renewables backed-up with demand-side flexibility and digitalization measures are typically a part of
10 the retrofit or construction strategy. Among HVAC technologies, heat pumps are very often modelled
11 to become a central heating and cooling technology supplied with renewable electricity. The estimates
12 of HVAC cost-effectiveness, including heat pumps, varies in modelling results from very cost-effective
13 to medium (Hirvonen et al. 2020; Akander et al. 2017; Prada-hernández et al. 2015; Department of
14 Environmental Affairs 2014). Among demand side management, demand-side flexibility and
15 digitalization options, various sensors, controls, and energy consumption feedback devices have
16 typically negative costs, whereas advanced smart management systems as well as thermal and electric
17 storages linked to fluctuating renewables are not yet cost-effective (Uchman 2021; Duman et al. 2021;
18 Nguyen et al. 2015; Huang et al. 2019; Sharda et al. 2021; Rashid et al. 2021; Prada-hernández et al.
19 2015). Several developed countries achieved to make onsite renewable energy production and use
20 profitable for at least a part of the building stock (Fina et al. 2020; Vimpari and Junnila 2019; Akander
21 et al. 2017; Horváth et al. 2016), but this is not yet the case for developing countries (Cruz et al. 2020;
22 Grande-acosta and Islas-samperio 2020; Kwag et al. 2019). Due to characteristics and parameters of
23 different building types, accommodating the cost-optimal renewables at large scale is especially
24 difficult in non-residential buildings and in urban areas, as compared to residential buildings and rural
25 areas (Fina et al. 2020; Horváth et al. 2016).
26 Literature agrees that new advanced buildings, using design, form, and passive building construction
27 equipped with demand side measures, and advanced HVAC technologies can reduce the sector total
28 baseline emissions in developed and developing countries by at least 10% and 25% in 2050,
29 respectively, and renewable energy technologies backed-up with demand-side flexibility and
30 digitalization measures typically installed in new buildings could further reduce these emissions by at
31 least 11% and 7% (see also Cross-Chapter Box 12 in Chapter 16). The literature however provides
32 different and sometimes conflicting information of their cost-effectiveness. (Esser et al. 2019) reported
33 that by 2016, the perceived share of buildings similar or close to nZEB in the new construction was just
34 above 20% across the EU. In this region, additional investment costs were no higher than 15%, as
35 reported for Germany, Italy, Denmark, and Slovenia (Erhorn-Kluttig et al. 2019). Still the European
36 market experiences challenges which relate to capacity and readiness, as revealed by (Architects’
37 Council of Europe (ACE) 2019) recording a decline in the share of architects who are designing
38 buildings to nZEB standards to more than 50% of their time, from 14% in 2016 to 11% in 2018. In
39 contrast, the APEC countries reported additional investment costs of 67% on average (Xu and Zhang
40 2017) that makes them a key barrier to the nZEB penetration in developing countries as of today (Feng
41 et al. 2019). This calls for additional R&D policies and financial incentives to reduce the nZEB costs
42 (Xu and Zhang 2017; Kwag et al. 2019).
43 Thermal efficiency retrofits of existing envelopes followed up by the exchange of HVAC backed up
44 with demand side measures could reduce the sector total baseline emissions in developed and
45 developing countries by at least 18% and 7% respectively in 2050. There have been many individual
46 examples of deep building retrofits, which incremental costs are not significantly higher than those of
47 shallow retrofits. However, literature tends to agree that cost-effective or low cost deep retrofits are not
48 universally applicable for all cases, especially in historic urban areas, indicating a large share of the
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1 potential in the high-cost category (Mata et al. 2019; Semprini et al. 2017; Paduos and Corrado 2017;
2 Subramanyam et al. 2017b; Department of Environmental Affairs 2014; Streicher et al. 2017; Akander
3 et al. 2017). Achieving deep retrofits assumes additional measures on the top of business-as-usual
4 retrofits, therefore high rate of deep retrofits at acceptable costs are not possible in case of low business-
5 as-usual rates (Streicher et al. 2020).
6 For a few studies, which conducted an assessment of the sector transformation aiming at emission
7 reduction of 50–80% in 2050 versus their baseline, the incremental investment need over the modelling
8 period is estimated at 0.4–3.3% of the country annual GDP of the scenario first year (Kotzur et al. 2020;
9 Novikova et al. 2018c; Bashmakov 2017; Markewitz et al. 2015). These estimates represent strictly the
10 incremental share of capital expenditure and sometimes installation costs. Therefore, these figures are
11 not comparable with investment tracked against the regional or national sustainable finance taxonomies,
12 as recently developed in the EU (European Parliament and the Council 2020), Russia (Government of
13 Russian Federation 2021), South Africa (National Treasury of Republic of South Africa 2021), and
14 others, or the growing literature on calculating the recent finance flows (Macquarie et al. 2020; Hainaut
15 et al. 2021; Novikova et al. 2019; Valentova et al. 2019; Kamenders et al. 2019), because they are
16 measured against other methodologies, which are not comparable with the methodologies used to derive
17 the incremental costs by integrated assessment models and bottom-up studies. Therefore, the gap
18 between the investment need and recent investment flows is likely to be higher, than often reported.
19 9.6.4 Determinants of the potentials and costs
20 That fact that the largest share of the global flow area is still to be built offers a large potential for
21 emission reduction that is however only feasible if ambitious building energy codes will be applied to
22 this new stock (see Section 9.9.3 on building codes). The highest demand for additional floor area will
23 occur in developing countries; the building replacement is also the highest in developing countries
24 because their building lifetime could be as short as 30 years (Lixuan et al. 2016; Alaidroos and Krarti
25 2015). Whereas as of 2018, 73 countries had already had building codes or were developing them, only
26 41 had mandatory residential codes and 51 had mandatory non-residential codes (Global Alliance for
27 Buildings and Construction 2019). Therefore, the feasibility of capturing this potential is a subject to
28 greater coverage, adoption, and strength of building codes.
29 Low rates of building retrofits are the major feasibility constrain of building decarbonization in
30 developed countries. Long building lifetime and their slow replacement caused a lock-in of low energy
31 performance in old buildings of developed countries, especially in urban areas. A few studies of
32 developing countries, mostly medium and high-income, also considered building retrofits (Yu et al.
33 2018b; Zhou et al. 2018; Krarti 2019; Kamal et al. 2019; Prada-hernández et al. 2015). The studies in
34 developed countries tend to rely on either of the strategies: very “deep” envelope retrofits followed by
35 the exchange of HVAC with various advanced alternatives (Novikova et al. 2018c,b; Csoknyai et al.
36 2016; Filippi Oberegger et al. 2020; Duscha et al. 2019) or more shallow retrofits followed by switching
37 to low-carbon district heating or by the exchange of current HVAC with heat pumps linked to onsite
38 renewables backed up energy storages (Kotzur et al. 2020; Hirvonen et al. 2020; Yeh et al. 2016). The
39 factors, which impact the feasibility of these strategies therefore are the building retrofit rates and
40 replacement rates of building systems. To achieve the building stock decarbonization by 2050, most
41 studies reviewed in Figure 9.16 assume “deep” retrofit rates between 2.5% and 5%, and even 10% per
42 annum. (Esser et al. 2019) reported that the annual renovation rate in EU28 is around 0.2%, with
43 relatively small variation across individual EU member states. (Sandberg et al. 2016) simulated retrofit
44 rates in eleven European countries and concluded that only minor future increases in the renovation
45 rates of 0.6–1.6% could be expected. Therefore, without strong policies supporting these renovations,
46 the feasibility to achieve such high “deep” retrofit rates is low.
47 Among key factors affecting the costs-effectiveness of achieving high-performance buildings remain
48 low energy prices in many countries worldwide (Alaidroos and Krarti 2015; Akander et al. 2017) and
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1 high discount rates reflecting low access to capital and high barriers. (Copiello et al. 2017) found that
2 the discount rate affects the economic results of retrofits four times higher than the energy price, and
3 therefore the reduction in upfront costs and working out barriers are the feasibility enablers.
4 The good news is that literature expects a significant cost reduction for many technologies, which are
5 relevant for the construction of high energy-performance buildings and deep retrofits. Applying a
6 technology learning curve to the data available for Europe and reviewing dozens of studies available,
7 (Köhler et al. 2018) estimated the cost reduction potential of biomass boilers, heat pumps, ventilation,
8 air-conditioning, thermal storages, electricity storages, solar PVs and solar thermal systems of 14%,
9 20%, 46–52%, 29%, 29%, 65%, 57%, and 43% respectively in 2050; no significant cost reduction
10 potential was found however for established and wide-spread insulation technologies. More investment
11 into RDD to reduce the technology costs and more financial incentives to encourage uptake of the
12 technologies would allow moving along this learning curve.
13 Furthermore, some literature argues that the key to cost-effectiveness is not necessarily a reduction in
14 costs of technologies, but a know-how and skills of their choosing, combining, sequencing, and timing
15 to take the most benefits of their interdependence, complementarity, and synergy as illustrated by many
16 examples (Lovins 2018; Ürge-Vorsatz et al. 2020). However, the scenarios reviewed lack such
17 approaches in their cost assessments. Few indicative examples of cost reduction at scale were provided
18 though not by the scenario literature, but case studies of the application of One-Stop Shop (OSS)
19 approach at scale (see Section 9.9.4). In 2013, the Dutch Energiesprong network brokered a deal
20 between Dutch building contractors and housing associations to reduce the average retrofit costs from
21 EUR 130,000 down to 65,000 for 111,000 homes with building prefabrication systems and project
22 delivery models while targeting energy savings of 45–80% (Ürge-Vorsatz et al. 2020); out of which
23 10,000 retrofits have been realized by 2020. The French Observatory of Low Energy Buildings reported
24 to achieve the cost-effective deep renovations of 818 dwellings and 27 detached houses in France setting
25 a cap for absolute primary energy consumption to achieve after renovation and a cap for the budget to
26 deliver it; the cost-effectiveness was however calculated with grants and public subsidies (Saheb 2018).
27 Literature emphasizes the critical role of the time between in 2020 and 2030 for the building sector
28 decarbonisation (IEA 2020a; Roscini et al. 2020). To set the sector at the pathway to realize its whole
29 mitigation potential, it is critical to exponentially accelerate the learning of this know-how and skills to
30 reduce the costs and remove feasibility constrains to enable the penetration of advanced technologies
31 at speed that the world has not seen before. The World Energy Outlook (IEA 2020a) portraited in the
32 Net Zero Emissions by 2050 Scenario (see Box 9.2) the challenges and commitments the sector will
33 have to address by 2030. These include bringing new buildings and existing buildings to near zero, with
34 a half of existing buildings in developed countries and a third of existing buildings in developing
35 countries being retrofitted by 2030. These also mean banning the sale of new fossil fuel-fired boilers,
36 as well as making heat pumps and very efficient appliances standard technologies. The Net Zero
37 Emissions by 2050 Scenario achieves almost fully to decarbonize the sector by 2050, with such
38 commitments reflected neither in the planning and modelling efforts (Section 9.9) nor in policies and
39 commitments (Section 9.9) of most world countries, with the countries of South-East Asia and
40 Developing Pacific, Southern Asia, Africa, and Latin America and Caribbean having the least research.
41 As discussed in Section 9.6.1, the alternative and low-cost opportunity to reduce the sector emissions
42 in the countries with high floor area per capita and the low stock turnover is offered by the introduction
43 of the sufficiency approach. Section 9.9.3.1 discusses a range of policy instruments, which could
44 support the realization of the sufficiency potential. As the approach is new, the literature does not yet
45 report experiences of these measures. In the framework of project OptiWohn, the German cities of
46 Göttingen, Köln und Tübingen just started testing the sufficiency approach and policy measures for
47 sufficiency (Stadt Göttingen 2020). Therefore, the feasibility of realizing the sufficiency potential
48 depends on its recognition by the energy and climate policy and the introduction of supporting measures
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1 (Samadi et al. 2017; Ellsworth-Krebs 2020; Goldstein et al. 2020). More research is needed to
2 understand which measures will work and which will not.
3 Similar to buildings, the energy consumption and associated emissions of appliances and equipment is
4 driven by the replacement of old appliances and the additional stock due to the increase in penetration
5 and saturation of appliances. The feasibility of appliance stock replacement with efficient options is
6 higher than the feasibility of building stock replacement or retrofit due to their smaller size, shorter
7 lifetime, and cheaper costs (Chu and Bowman 2006; Spiliotopoulos 2019). Some literature argues that
8 once appliances achieve a particular level of efficiency their exchange does not bring benefits from the
9 resource efficiency point of view (Hertwich et al. 2019). Even through the data records a permanent
10 energy efficiency improvement of individual devices (Figure 9.12), their growing offsets energy savings
11 delivered by this improvement. The emerging literature suggests addressing the growing number of
12 energy services and devices as a part of climate and energy policy (Bierwirth and Thomas 2019b).
13 Sections 9.5.2.2 describes measures for limiting demand for these services and Section 9.5.3.6 addresses
14 reducing the number of technologies through their ownership and use patterns. (Grubler et al. 2018)
15 also suggested redefining energy services and aggregating appliances, illustrating the reduction of
16 energy demand by factor 30 to substitute over 15 different end-use devices with one integrated digital
17 platform. More research is needed to understand opportunities to realize this sufficiency potential for
18 appliances, and more research is needed to understand policies which may support these opportunities
19 (Bierwirth and Thomas 2019a).
20 The difference between baselines is among the main reason for difference between the potential
21 estimates in 2030 reported by Chapter 6 on buildings of AR4 (Levine et al. 2017) and the current section
22 of AR6. For developed countries, the sector direct and indirect baseline emissions in AR6 are 43% and
23 28% lower than those in AR4 respectively. For developing countries, the sector direct baseline
24 emissions in AR6 are 47% lower than those in AR4, and the sector indirect baseline emissions are 3%
25 higher than those in AR4. As AR6 is closer to 2030 than AR4 and thus more precise, the likely reason
26 for the difference (besides the fact that some potential was realized) is that AR4 overall overestimated
27 the future baseline emissions, and it underestimated how quickly the fuel switch to electricity from other
28 energy carriers has been happening, especially in developing countries. As illustrated, the baseline is
29 one of determinant of the potential size and hence, all reported estimates shall only be interpreted
30 together with the baseline developments.
31 The potential is a dynamic value, increasing with the technological progress. Most potential studies
32 reviewed in Section 9.6.1 consider today mature commercialised or near to commercialisation
33 technologies with demonstrated characteristics “freezing them” in the potential estimates until the study
34 target year. Until 2050, many of these technologies will further improve, and furthermore new advanced
35 technologies may emerge. Therefore, the potential estimates are likely to be low estimates of the real
36 potential volumes. Furthermore, models apply many other assumptions and they cannot always capture
37 right emerging societal or innovation trends; these trends may also significantly impact the potential
38 size into both directions (Brugger et al. 2021).
39 With the declining amount of emissions during the building operation stage, the share of building
40 embodied emissions in their lifetime emissions will grow, also due to additional building material
41 (Peñaloza et al. 2018; Cabeza et al. 2021). Reviewing 650 life cycle assessment case studies, (Röck et
42 al. 2020) estimated the contribution of embodied emissions to building lifetime emissions up to 45–
43 50% for highly efficient buildings, surpassing 90% in extreme cases.
44 Recently, a significant body of research has been dedicated to studying the impacts of using bio-based
45 solutions (especially timber) for building construction instead of conventional materials, such as
46 concrete and steel, because more carbon is stored in bio-based construction materials than released
47 during their manufacturing. Assuming the aggressive use of timber in mid-rise urban buildings,
48 Churkina et al. (2020) estimated the associated mitigation potential between 0.04-3.7 GtCO2 per year
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1 depending on how fast countries adopt new building practices and floor area per capita. Based on a
2 simplified timber supply-demand model for timber-based new floor area globally by 2050, Pomponi et
3 al. (2020) showed that the global supply of timber can only be 36% of the global demand for it between
4 2020 and 2050; especially much more forest areas will be required in Asian countries, such as China
5 and India and American countries, such as the USA, Mexico, and Argentina. Goswein et al. (2021)
6 conducted a similar detailed analysis for Europe and concluded that current European forest areas and
7 wheat plantations are sufficient to provide timber and straw for the domestic construction sector.
8 The increased use of timber and other bio-based materials in buildings brings not only benefits, but also
9 risks. The increased use of timber can accelerate degradation through poor management and the pressure
10 for deforestation, as already recorded in the Amazon and Siberia forests, and the competition for land
11 and resources (Brancalion et al. 2018; Carrasco et al. 2017; Hart and Pomponi 2020; Pomponi et al.
12 2020). Churkina et al. (2020) emphasized that promoting the use of more timber in buildings requires
13 the parallel strengthening of legislation for sustainable forest management, forest certification
14 instruments, and care for the people and social organizations that live in forests. In tropical and
15 subtropical countries, the use of bamboo and other fibres brings more benefits and less risks than the
16 use of timber (ibid). One of the main barriers associated with the use of bio-based materials in buildings
17 is fire safety, although there is extensive research on this topic (Audebert et al. 2019; Östman et al.
18 2017). This is a particularly important criterion for the design of medium and high-rise buildings, which
19 tend to be the most adequate typologies for denser and more compact cities. Overall, more robust
20 models are needed to assess the interlinkages between the enhanced use of bio-based materials in the
21 building stock and economic and social implications of their larger supply, as well as the associated
22 competition between forest and land-use activities (for food), and ecological aspects. Furthermore, more
23 research is required on how to change forest and building legislation and design a combination of policy
24 instruments for the specific political, economic and cultural county characteristics (Hildebrandt et al.
25 2017). Benefits and risks of enhanced use of wood products in buildings are also discussed in Chapter
26 7, Section 7.4.5.3.
27
28 9.7 Links to adaptation
29 Buildings are capital-intensive and long-lasting assets designed to perform under a wide range of
30 climate conditions (Hallegatte 2009; Pyke et al. 2012). Their long life span means that the building
31 stock will be exposed to future climate (de Wilde and Coley 2012; Wan et al. 2012; Hallegatte 2009)
32 and, as such, adaptation measures will be necessary.
33 The impacts of climate change on buildings can affect building structures, building construction,
34 building material properties, indoor climate and building energy use (Andrić et al. 2019). Many of those
35 impacts and their respective adaptation strategies interact with GHG mitigation in different ways.
36 9.7.1 Climate change impacts and adaptation in buildings
37 A large body of literature on climate impacts on buildings focuses on the impacts of climate change on
38 heating and cooling needs (de Wilde and Coley 2012; Wan et al. 2012; Andrić et al. 2019). The
39 associated impacts on energy consumption are expected to be higher in hot summer and warm winter
40 climates, where cooling needs are more relevant (Li et al. 2012; Wan et al. 2012; Andrić et al. 2019). If
41 not met, this higher demand for thermal comfort can impact health, sleep quality and work productivity,
42 having disproportionate effects on vulnerable populations and exacerbating energy poverty (Falchetta
43 and Mistry 2021; Biardeau et al. 2020; Sun et al. 2020) (see Section 9.8).
44 Increasing temperatures can lead to higher cooling needs and, therefore, energy consumption (Schaeffer
45 et al. 2012; Clarke et al. 2018; International Energy Agency 2018; Wan et al. 2012; Li et al. 2012;
46 Andrić et al. 2019). Higher temperatures increase the number of days/hours in which cooling is required
47 and as outdoor temperatures increase, the cooling load to maintain the same indoor temperature will be
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1 higher (Andrić et al. 2019). These two effects are often measured by cooling degree-days1 (CDD) and
2 there is a vast literature on studies at the global (Atalla et al. 2018; Mistry 2019; Isaac and van Vuuren
3 2009; Biardeau et al. 2020; Clarke et al. 2018) and regional level (Bezerra et al. 2021; Zhou et al. 2014;
4 Falchetta and Mistry 2021). Other studies use statistical econometric analyses to capture the empirical
5 relationship between climate variables and energy consumption (Auffhammer and Mansur 2014; van
6 Ruijven et al. 2019). A third effect is that higher summer temperatures can incentivize the purchase of
7 space cooling equipment (Auffhammer 2014; De Cian et al. 2019; Biardeau et al. 2020), especially in
8 developing countries (Pavanello et al. 2021).
9 The impacts of increased energy demand for cooling can have systemic repercussions (Ralston Fonseca
10 et al. 2019; Ciscar and Dowling 2014), which in turn can affect the provision of other energy services.
11 Space cooling can be an important determinant of peak demand, especially in periods of extreme heat
12 (International Energy Agency 2018). Warmer climates and higher frequency and intensity of heat waves
13 can lead to higher loads (Dirks et al. 2015; Auffhammer et al. 2017), increasing the risk of grid failure
14 and supply interruptions.
15 Although heating demand in cold climate regions can be expected to decrease with climate change and,
16 to a certain extent, outweigh the increase in cooling demand, the effects on total primary energy
17 requirements are uncertain (Wan et al. 2012; Li et al. 2012). Studies have found that increases in
18 buildings energy expenditures for cooling more than compensate the savings from lower heating
19 demands in most regions (Clarke et al. 2018). In addition, climate change may affect the economic
20 feasibility of district heating systems (Andrić et al. 2019).
21 In cold climates, a warming climate can potentially increase the risk of overheating in high-performance
22 buildings with increased insulation and airtightness to reduce heat losses (Gupta and Gregg 2012). In
23 such situations, the need for active cooling technologies may arise, along with higher energy
24 consumption and GHG emissions (Gupta et al. 2015).
25 Changes in cloud formation can affect global solar irradiation and, therefore, the output of solar
26 photovoltaic panels, possibly affecting on-site renewable energy production (Burnett et al. 2014). The
27 efficiency of solar photovoltaic panels and their electrical components decreases with higher
28 temperatures (Simioni and Schaeffer 2019) (Bahaidarah et al. 2013). However, studies have found that
29 such effect can be relatively small (Totschnig et al. 2017), making solar PV a robust option to adapt to
30 climate change (Shen and Lior 2016; Santos and Lucena 2021) (see Section 9.4).
31 Climate change can also affect the performance, durability and safety of buildings and their elements
32 (facades, structure, etc.) through changes in temperature, humidity, wind, and chloride and CO 2
33 concentrations (Bastidas-Arteaga et al. 2010; Bauer et al. 2018; Rodríguez-Rosales et al. 2021; Chen et
34 al. 2021). Historical buildings and coastal areas tend to be more vulnerable to these changes (Huijbregts
35 et al. 2012; Mosoarca et al. 2019; Cavalagli et al. 2019; Rodríguez-Rosales et al. 2021).
36 Temperature variations affect the building envelope, e.g. with cracks and detachment of coatings (Bauer
37 et al. 2016, 2018). Higher humidity (caused by wind-driven rain, snow or floods) hastens deterioration
38 of bio-based materials such as wood and bamboo (Brambilla and Gasparri 2020), also deteriorating
39 indoor air quality and users health (Grynning et al. 2017; Lee et al. 2020; Huijbregts et al. 2012).
40 Climate change can accelerate the degradation of reinforced concrete structures due to the increase of
41 chloride ingress (Bastidas-Arteaga et al. 2010) and the concentration of CO2, which increase the
42 corrosion of the embedded steel (Stewart et al. 2012; Peng and Stewart 2016; Chen et al. 2021).
FOOTNOTE1 CDD can be generally defined as the monthly or annual sum of the difference between an indoor
set point temperature and outdoor air temperature whenever the latter is higher than a given threshold temperature
(Mistry 2019).
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1 Corrosion rates are higher in places with higher humidity and humidity fluctuations (Guo et al. 2019),
2 and degradation could be faster with combined effects of higher temperatures and more frequent and
3 intense precipitations (Bastidas-Arteaga et al. 2010; Chen et al. 2021).
4 Higher frequency and intensity of hurricanes, storm surges and coastal and non-coastal flooding can
5 escalate economic losses to civil infrastructure, especially when associated with population growth and
6 urbanization in hazardous areas (Bjarnadottir et al. 2011; Lee and Ellingwood 2017; Li et al. 2016).
7 Climate change should increase the risk and exposure to damage from flood (de Ruig et al. 2019), sea
8 level rise (Bove et al. 2020; Zanetti et al. 2016; Bosello and De Cian 2014) and more frequent wildfires
9 (Craig et al. 2020; Barkhordarian et al. 2018).
10
11 9.7.2 Links between mitigation and adaptation in buildings
12 Adaptation options interacts with mitigation efforts because measures to cope with climate change
13 impacts can increase energy and material consumption, which may lead to higher GHG emissions
14 (Kalvelage et al. 2014; Davide et al. 2019; Sharifi 2020). Energy consumption is required to adapt to
15 climate change. Mitigation measures, in turn, influence the degree of vulnerability of buildings to future
16 climate and, thus, the adaptation required.
17 Studies have assessed the increases in energy demand to meet indoor thermal comfort under future
18 climate (de Wilde and Coley 2012; Li et al. 2012; Andrić et al. 2019; Clarke et al. 2018). Higher cooling
19 needs may induce increases in energy demand (Wan et al. 2012; Li et al. 2012), which could lead to
20 higher emissions, when electricity is fossil-based (International Energy Agency 2018; Biardeau et al.
21 2020), and generate higher loads and stress on power systems (Auffhammer et al. 2017; Dirks et al.
22 2015). In this regard, increasing energy efficiency of space cooling appliances and adopting dynamic
23 cooling setpoint temperatures, can reduce the energy needs for cooling and limit additional emissions
24 and pressures on power systems (Davide et al. 2019; Bezerra et al. 2021) (Bienvenido-Huertas et al.
25 2020) (see Section 9.4, Figure 9.11 and Tables SM9.1 to SM9.3). This can also be achieved with on-
26 site renewable energy production, especially solar PV for which there can be a timely correlation
27 between power supply and cooling demand, improving load matching (Salom et al. 2014; Grove-Smith
28 et al. 2018).
29 Mitigation alternatives through passive approaches may increase resilience to climate change impacts
30 on thermal comfort and reduce active cooling needs (González Mahecha et al. 2020; Rosse Caldas et
31 al. 2020; van Hooff et al. 2016; Wan et al. 2012; Andrić et al. 2019). Combining passive measures can
32 help counteracting climate change driven increases in energy consumption for achieving thermal
33 comfort (Huang and Hwang 2016).
34 Studies raise the concern that measures aimed at building envelope may increase the risk of overheating
35 in a warming climate (Dodoo and Gustavsson 2016; Fosas et al. 2018) (see Section 9.4). If this is the
36 case, there may be a conflict between mitigation through energy efficiency building regulations and
37 climate change adaptation (Fosas et al. 2018). However, while overheating may occur as a result of
38 poor insulation design, better insulation may actually reduce overheating when properly projected and
39 the overheating risk can be overcome by clever designs (Fosas et al. 2018).
40 Strengthening building structures to increase resilience and reduce exposure to the risk of extreme
41 events, such as draughts, torrential floods, hurricanes and storms, can be partially achieved by
42 improving building standards and retrofitting existing buildings (Bjarnadottir et al. 2011). However,
43 future climate is not yet considered in parameters of existing building energy codes (Steenbergen et al.
44 2012). While enhancing structural resilience would lead to GHG emissions (Liu and Cui 2018), so
45 would disaster recovery and re-building. This adaptation-mitigation trade-off needs to be further
46 assessed.
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1 Since adaptation of the existing building stock may be more expensive and require building retrofit,
2 climate change must be considered in the design of new buildings to ensure performance robustness in
3 both current and future climates, which can have implications for construction costs (de Rubeis et al.
4 2020; Picard et al. 2020; Hallegatte 2009; Pyke et al. 2012; de Wilde and Coley 2012) and emissions
5 (Liu and Cui 2018). Building energy codes and regulations are usually based on cost-effectiveness and
6 historical climate data, which can lead to the poor design of thermal comfort in future climate
7 (Hallegatte 2009; Pyke et al. 2012; de Wilde and Coley 2012) and non-efficient active adaptive
8 measures based on mechanical air conditioning (De Cian et al. 2019) (see Section 9.4, Figure 9.11 and
9 Tables SM9.1 to SM9.3). However, uncertainty about future climate change creates difficulties for
10 projecting parameters for the design of new buildings (Hallegatte 2009; de Wilde and Coley 2012). This
11 can be especially relevant for social housing programs (Rubio-Bellido et al. 2017; González Mahecha
12 et al. 2020; Triana et al. 2018) in developing countries.
13 The impacts on buildings can lead to higher maintenance needs and the consequent embodied
14 environmental impacts related to materials production, transportation and end-of-life, which account
15 for a relevant share of GHG emissions in buildings life cycle (Rasmussen et al. 2018). Climate change
16 induced biodegradation is especially important for bio-based materials such as wood and bamboo
17 (Brambilla and Gasparri 2020) which are important options for reducing emissions imbued in buildings’
18 construction materials (Peñaloza et al. 2016; Churkina et al. 2020; Rosse Caldas et al. 2020).
19 Although there can potentially be conflicts between climate change mitigation and adaptation, these can
20 be dealt with proper planning, actions, and policies. The challenge is to develop multifunctional
21 solutions, technologies and materials that can mitigate GHG emissions while improving buildings
22 adaptive capacity. Solutions and technologies should reduce not only buildings’ operational emissions,
23 but also embodied emissions from manufacturing and processing of building materials (Röck et al.
24 2020). For instance, some building materials, such as bio-concrete, can reduce life cycle emissions of
25 buildings and bring benefits in terms of building thermal comfort in tropical and subtropical climates.
26 Also, energy efficiency, sufficiency and on-site renewable energy production can help to increase
27 building resilience to climate change impacts and reduce pressure on the energy system.
28
29 9.8 Links to sustainable development
30 9.8.1 Overview of contribution of mitigation options to sustainable development
31 A growing body of research acknowledges that mitigation actions in buildings may have substantial
32 social and economic value beyond their direct impact of reducing energy consumption and/or GHG
33 emissions (Ürge-Vorsatz et al. 2016; Deng et al. 2017; Reuter et al. 2017; IEA 2014; US EPA 2018;
34 Kamal et al. 2019; Bleyl et al. 2019) (see also Cross-Chapter Box 6 in Chapter 7). In other words, the
35 implementation of these actions in the residential and non-residential sector holds numerous multiple
36 impacts (co-benefits, adverse side-effects, trade-offs, risks, etc.) for the economy, society and end-users,
37 in both developed and developing economies, which can be categorized into the following types (Nikas
38 et al. 2020; Thema et al. 2017; Ferreira et al. 2017; Reuter et al. 2017; IEA 2014; US EPA 2018; Ürge-
39 Vorsatz et al. 2016): (i) health impacts due to better indoor conditions, energy/fuel poverty alleviation,
40 better ambient air quality and reduction of the heat island effect; (ii) environmental benefits such as
41 reduced local air pollution and the associated impact on ecosystems (acidification, eutrophication, etc.)
42 and infrastructures, reduced sewage production, etc.; (iii) improved resource management including
43 water and energy; (iv) impact on social well-being, including changes in disposable income due to
44 decreased energy expenditures and/or distributional costs of new policies, fuel poverty alleviation and
45 improved access to energy sources, rebound effects, increased productive time for women and children,
46 etc.; (v) microeconomic effects (e.g., productivity gains in non-residential buildings, enhanced asset
47 values of green buildings, fostering innovation); (vi) macroeconomic effects, including impact on GDP
48 driven by energy savings and energy availability, creation of new jobs, decreased employment in the
49 fossil energy sector, long-term reductions in energy prices and possible increases in electricity prices in
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1 the medium run, possible impacts on public budgets, etc.; and (vii) energy security implications (e.g.,
2 access to modern energy resources, reduced import dependency, increase of supplier diversity, smaller
3 reserve requirements, increased sovereignty and resilience).
4 Well-designed and effectively implemented mitigation actions in the sector of buildings have significant
5 potential for achieving the United Nations (UN) Sustainable Development Goals (SDGs). Specifically,
6 the multiple impacts of mitigation policies and measures go far beyond the goal of climate action
7 (SDG13) and contribute to further activating a great variety of other SDGs (Figure 9.18 presents some
8 indicative examples). Table 9.4 reviews and updates the analysis carried out in the context of the Special
9 Report on Global Warming of 1.5°C (Roy et al. 2018) demonstrating that the main categories of GHG
10 emission reduction interventions in buildings, namely the implementation of energy sufficiency and
11 efficiency improvements as well as improved access and fuel switch to modern low carbon energy,
12 contribute to achieving 16 out of a total of 17 SDGs.
13
14 Figure 9.18 Contribution of mitigation policies of the building sector to meeting sustainable development
15 goals.
16 Source: Based on information from (IEA et al. 2020b; IEA 2020b; Mills 2016; European Commission 2016;
17 Rafaj et al. 2018; Mzavanadze 2018a; World Health Organization 2016) and literature review presented in
18 Section 9.8.5.2.
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1 Table 9.4 Aspects of mitigation actions in buildings and their contributions to the 2030 Sustainable
2 Development Goals. S: enhancement of energy sufficiency; E: energy efficiency improvements; R: improved
3 access and fuel switch to lower carbon and renewable energy.
SDG10
SDG11
SDG12
SDG13
SDG14
SDG15
SDG16
SDG17
SDG1
SDG2
SDG3
SDG4
SDG5
SDG6
SDG7
SDG8
SDG9
Level of impact S E R S E R S E R S E R S E R S E R S E R S E R S E R S E R S E R S E R S E R S E R S E R S E R S E R
+3
+2
+1
-1
-2
-3
Dimensions of mitigation actions that impact SDGs
Health impact X X X X
Environmental impact X X X X X
Resource efficienvy X X X X X X X
Impact on social well-being X X X X X X X X X X X X
Microeconomic effects X X X X X
Macroeconomic effects X X X
4 Energy security X X
5 Notes: The strength of interaction between mitigation actions and SDGs is described with a seven-point scale
6 (Nilsson et al., 2016) Also, the symbol X shows the interactions between co-benefits/risk associated with
7 mitigation actions and the SDGs. SDG1: Sufficiency and efficiency measures result in reduced energy
8 expenditures and other financial savings that further lead to poverty reduction. Access to modern energy forms
9 will largely help alleviate poverty in developing countries as the productive time of women and children will
10 increase, new activities can be developed, etc. The distributional costs of some mitigation policies promoting
11 energy efficiency and lower carbon energy may reduce the disposable income of the poor. SDG2: Energy
12 sufficiency and efficiency measures result in lower energy bills and avoiding the “heat or eat” dilemma. Improved
13 cook-stoves provide better food security and reduces the danger of fuel shortages in developing countries; under
14 real-world conditions these impacts may be limited as the households use these stoves irregularly and
15 inappropriately. Green roofs can support food production. Improving energy access enhances agricultural
16 productivity and improves food security; on the other hand, increased bioenergy production may restrict the
17 available land for food production. SDG3: All categories of mitigation action result in health benefits through
18 better indoor air quality, energy/fuel poverty alleviation, better ambient air quality, and reduction of the heat island
19 effect. Efficiency measures with inadequate ventilation may lead to the sick building syndrome symptoms. SDG4:
20 Energy efficiency measures result in reduced school absenteeism due to better indoor environmental conditions.
21 Also, fuel poverty alleviation increases the available space at home for reading. Improved access to electricity and
22 clean fuels enables people living in poor developing countries to read, while it is also associated with greater
23 school attendance by children. SDG5: Efficient cook-stoves and improved access to electricity and clean fuels in
24 developing countries will result in substantial time savings for women and children, thus increasing the time for
25 rest, communication, education and productive activities. SDG6: Reduced energy demand due to sufficiency and
26 efficiency measures as well as an upscaling of RES can lead to reduced water demand for thermal cooling at
27 energy production facilities. Also, water savings result through improved conditions and lower space of dwellings.
28 Improved access to electricity is necessary to treat water at homes. In some situations, the switch to bioenergy
29 could increase water use compared to existing conditions. SDG7: All categories of mitigation action result in
30 energy/fuel poverty alleviation in both developed and developing countries as well as in improving the security
31 of energy supply. SDG8: Positive and negative direct and indirect macroeconomic effects (GDP, employment,
32 public budgets) associated with lower energy prices due to the reduced energy demand, energy efficiency and
33 RES investments, improved energy access and fostering innovation. Also, energy efficient buildings with
34 adequate ventilation, result in productivity gains and improve the competitiveness of the economy. SDG9:
35 Adoption of distributed generation and smart grids helps in infrastructure improvement and expansion. Also, the
36 development of “green buildings” can foster innovation. Reduced energy demand due to sufficiency and
37 efficiency measures as well as an upscaling of RES can lead to early retirement of fossil energy infrastructure.
38 SDG10: Efficient cook-stoves as well as improved access to electricity and clean fuels in developing countries
39 will result in substantial time savings for women and children, thus enhancing education and the development of
40 productive activities. Sufficiency and efficiency measures lead to lower energy expenditures, thus reducing
41 income inequalities. The distributional costs of some mitigation policies promoting energy efficiency and lower
42 carbon energy as well as the need for purchasing more expensive equipment and appliances may reduce the
43 disposable income of the poor and increase inequalities. SDG11: Sufficiency and efficiency measures as well as
44 fuel switching to RES and improvements in energy access would eliminate major sources (both direct and indirect)
45 of poor air quality (indoor and outdoor). Helpful if in-situ production of RES combined with charging electric
46 two, three and four wheelers at home. Buildings with high energy efficiency and/or green features are sold/rented
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1 at higher prices than conventional, low energy efficient houses. SDG12: Energy sufficiency and efficiency
2 measures as well as deployment of RES result in reduced consumption of natural resources, namely fossil fuels,
3 metal ores, minerals, water, etc. Negative impacts on natural resources could be arisen from increased penetration
4 of new efficient appliances and equipment. SDG13: See sections 9.4-9.6. SDG15: Efficient cookstoves and
5 improved access to electricity and clean fuels in developing countries will result in halting deforestation. SDG16:
6 Building retrofits are associated with lower crime. Improved access to electric lighting can improve safety
7 (particularly for women and children). Institutions that are effective, accountable and transparent are needed at all
8 levels of government for providing energy access and promoting modern renewables as well as boosting
9 sufficiency and efficiency. SDG17: The development of zero energy buildings requires among others capacity
10 building, citizen participation as well as monitoring of the achievements.
11 Sources: (Balaban and Puppim de Oliveira 2017; Marmolejo-Duarte and Chen 2019; Barnes and Samad 2018;
12 Bailis et al. 2015; Baimel et al. 2016; Berrueta et al. 2017; Bleyl et al. 2019; Boermans et al. 2015; Brounen and
13 Kok 2011; Burney et al. 2017; Cajias et al. 2019; Camarinha-Matos 2016; Cameron et al. 2016; Cedeño-Laurent
14 et al. 2018; De Ayala et al. 2016; Deng et al. 2012; Fuerst et al. 2015, 2016; Fricko et al. 2016; Galán-Marín et al.
15 2015; Goldemberg et al. 2018; Hanna et al. 2016; Hasegawa et al. 2015; Hejazi et al. 2015; Högberg 2013; Holland
16 et al. 2015; Hyland et al. 2013; Jensen et al. 2016; Jeuland et al. 2018; Kahn and Kok 2014; Koirala et al. 2014;
17 Levy et al. 2016; Liddell and Guiney 2015; Maidment et al. 2014; Markovska et al. 2016; Alawneh et al. 2019;
18 Mastrucci et al. 2019; Mattioli and Moulinos 2015; McCollum et al. 2018; Mehetre et al. 2017; Mirasgedis et al.
19 2014; Mofidi and Akbari 2017; Mzavanadze 2018a; Niemelä et al. 2017; Ortiz et al. 2017; Payne et al. 2015; Rao
20 et al. 2016; Rao and Pachauri 2017; Rosenthal et al. 2018; Saheb et al. 2018b,a; Scott et al. 2014; Smith et al.
21 2016; Steenland et al. 2018; Tajani et al. 2018; Teubler et al. 2020; Thomson et al. 2017a; Tonn et al. 2018; Torero
22 2015; Van de Ven et al. 2020; Venugopal et al. 2018; Wierzbicka et al. 2018; Willand et al. 2015a; Winter et al.
23 2015; Zheng et al. 2012; Liu et al. 2015a; Sola et al. 2016; Song et al. 2016; Zhao et al. 2017; Grubler et al. 2018;
24 Thema et al. 2017; Ürge-Vorsatz et al. 2016; Nikas et al. 2020) (Blair et al. 2021; Batchelor et al. 2019; ESMAP
25 et al. 2020; Walters and Midden 2018) (European Commission 2016) (MacNaughton et al. 2018)
26 A review of a relatively limited number of studies made by (Ürge-Vorsatz et al. 2016) and (Payne et al.
27 2015) showed that the size of multiple benefits of mitigation actions in the sector of buildings may
28 range from 22% up to 7,400% of the corresponding energy cost savings. In 7 out of 11 case studies
29 reviewed, the value of the multiple impacts of mitigation actions was equal or greater than the value of
30 energy savings. Even in these studies, several effects have not been measured and consequently the size
31 of multiple benefits of mitigation actions may be even higher. Quantifying and if possible, monetizing,
32 these wider impacts of climate action would facilitate their inclusion in cost-benefit analysis, strengthen
33 the adoption of ambitious emissions reduction targets, and improve coordination across policy areas
34 reducing costs (Thema et al. 2017) (Smith et al. 2016).
35
36 9.8.2 Climate mitigation actions in buildings and health impacts
37 9.8.2.1 Lack of access to clean energy
38 In 2018, approximately 2.8 billion people worldwide, most of whom live in Asia and Africa, still use
39 polluting fuels, such as fuelwood, charcoal, dried crops, cow dung, etc., in low-efficiency stoves for
40 cooking and heating, generating household air pollution (HAP), which adversely affects the health of
41 the occupants of the dwellings, especially children and women (World Health Organization 2016;
42 Quinn et al. 2018; Rahut et al. 2017; Mehetre et al. 2017; Rosenthal et al. 2018; Das et al. 2018; Xin et
43 al. 2018; Liu et al. 2018) (IEA et al. 2020b). Exposure to HAP from burning these fuels is estimated to
44 have caused 3.8 million deaths from heart diseases, strokes, cancers, acute lower respiratory infections
45 in 2016 (World Health Organization 2018). It is acknowledged that integrated policies are needed to
46 address simultaneously universal energy access, limiting climate change and reducing air pollution
47 (World Health Organization 2016). (Rafaj et al. 2018) showed that a scenario achieving these SDGs in
48 2030 will imply in 2040 two million fewer premature deaths from HAP compared to current levels, and
49 1.5 million fewer premature deaths in relation to a reference scenario, which assumes the continuation
50 of existing and planned policies. The level of incremental investment needed in developing countries
51 to achieve universal access to modern energy was estimated at around USD0.8 trillion cumulatively to
52 2040 in the scenarios examined (Rafaj et al. 2018).
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1 At the core of these policies is the promotion of improved cook-stoves and other modern energy-
2 efficient appliances to cook (for the health benefits of improved cook-stoves see for example (García-
3 Frapolli et al. 2010; Aunan et al. 2013) (Jeuland et al. 2018; Malla et al. 2011)), as well as the use of
4 non-solid fuels by poor households in developing countries (Figure 9.19). Most studies agree that the
5 use of non-solid energy options such as LPG, ethanol, biogas, piped natural gas, and electricity is more
6 effective in reducing the health impacts of HAP compared to improved biomass stoves (see for example
7 (Larsen 2016; Rosenthal et al. 2018; Steenland et al. 2018; Goldemberg et al. 2018). On the other hand,
8 climate change mitigation policies (e.g., carbon pricing) may increase the costs of some of these clean
9 fuels (e.g., LPG, electricity), slowing down their penetration in the poor segment of the population and
10 restricting the associated health benefits (Cameron et al. 2016). In this case, appropriate access policies
11 should be designed to efficiently shield poor households from the burden of carbon taxation (Cameron
12 et al. 2016). The evaluation of the improved biomass burning cook-stoves under real-world conditions
13 has shown that they have lower than expected, and in many cases limited, long-run health and
14 environmental impacts, as the households use these stoves irregularly and inappropriately, fail to
15 maintain them, and their usage decline over time (Wathore et al. 2017; Patange et al. 2015; Aung et al.
16 2016; Hanna et al. 2016). In this context, the various improved cook-stoves programs should consider
17 the mid- and long-term needs of maintenance, repair, or replacement to support their sustained use
18 (Schilmann et al. 2019; Shankar et al. 2014).
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1
2 Figure 9.19 Trends on energy access: historical based on IEA statistics data and scenarios based on IEA WEO data.
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1 Electrification of households in rural or remote areas results also to significant health benefits. For
2 example, in El Salvador, rural electrification of households leads to reduced overnight air pollutants
3 concentration by 63% due to the substitution of kerosene as a lighting source, and 34-44% less acute
4 respiratory infections among children under six (Torero 2015). In addition, the connection of the health
5 centres to the grid leads to improvements in the quality of health care provided (Lenz et al. 2017).
6 9.8.2.2 Energy/fuel poverty, indoor environmental quality and health
7 Living in fuel poverty, and particularly in cold and damp housing is related to excess winter mortality
8 and increased morbidity rates due to respiratory and cardiovascular diseases, arthritic and rheumatic
9 illnesses, asthma, etc. (Camprubí et al. 2016; Wilson et al. 2016; Lacroix and Chaton 2015; Ormandy
10 and Ezratty 2016; Payne et al. 2015; Thema et al. 2017). In addition, lack of affordable warmth can
11 generate stress related to chronic discomfort and high bills, fear of falling into debt, and a sense of
12 lacking control, which are potential drivers of further negative mental health outcomes, such as
13 depression (Howden-Chapman et al. 2012; Payne et al. 2015; Wilson et al. 2016; Liddell and Guiney
14 2015). Health risks from exposure to cold and inadequate indoor environmental quality may be higher
15 for low-income, energy-poor households, and in particular for those with elderly, young children, and
16 members with existing respiratory illness (Payne et al. 2015; Thomson et al. 2017b; Nunes 2019). High
17 temperatures during summer can also be dangerous for people living in buildings with inadequate
18 thermal insulation and inappropriate ventilation (Sanchez-Guevara et al. 2019; Thomson et al. 2019;
19 Ormandy and Ezratty 2016). Summer fuel poverty (or summer overheating risk) may increase
20 significantly in the coming decades under a warming climate (see also Section 9.7), with the poorest,
21 who cannot afford to install air conditioning, and the elderly (Nunes 2020) being the most vulnerable.
22 Improved energy efficiency in buildings contributes in fuel poverty alleviation and brings health gains
23 through improved indoor temperatures and comfort as well as reduced fuel consumption and associated
24 financial stress (Thomson and Thomas 2015; Curl et al. 2015; Poortinga et al. 2018; Lacroix and Chaton
25 2015; Liddell and Guiney 2015) (Willand et al. 2015). On the other hand, households suffering most
26 from fuel poverty experience more barriers for undertaking building retrofits (Camprubí et al. 2016)
27 (Charlier et al. 2018; Braubach and Ferrand 2013), moderating the potential health gains associated
28 with implemented energy efficiency programs. This can be avoided if implemented policies to tackle
29 fuel poverty target the most socially vulnerable households (Lacroix and Chaton 2015; Camprubí et al.
30 2016). (Mzavanadze 2018a) estimated that in EU-28 accelerated energy efficiency policies, reducing
31 the energy demand in residential sector by 333 TWh in 2030 compared to a reference scenario, coupled
32 with strong social policies targeting the most vulnerable households, could deliver additional co-
33 benefits in the year of 2030 of around 24,500 avoided premature deaths due to indoor cold and around
34 22,300 DALYs of avoided asthma due to indoor dampness. The health benefits of these policies amount
35 to €4.8 billion in 2030. The impacts on inhabitants in developing countries would be much greater than
36 those in EU-28 owing to the much higher prevalence of impoverished household.
37 Apart from thermal comfort, the internal environment of buildings impacts public health through a
38 variety of pathways including inadequate ventilation, poor indoor air quality, chemical contaminants
39 from indoor or outdoor sources, outdoor noise, or poor lighting. The implementation of interventions
40 aiming to improve thermal insulation of buildings combined with inadequate ventilation may increase
41 the risk of mould and moisture problems due to reduced air flow rates, leading to indoor environments
42 that are unhealthy, with the occupants suffering from the sick building syndrome symptoms
43 (Wierzbicka et al. 2018; Cedeño-Laurent et al. 2018) (Willand et al. 2015). On the other hand, if the
44 implementation of energy efficiency interventions or the construction of green buildings is accompanied
45 by adequate ventilation, the indoor environmental conditions are improved through less moisture,
46 mould, pollutant concentrations, and allergens, which result in fewer asthma symptoms, respiratory
47 risks, chronic obstructive pulmonary diseases, heart disease risks, headaches, cancer risks, etc. (Cowell
48 2016; Allen et al. 2015; Doll et al. 2016; Wilson et al. 2016; Thomson and Thomas 2015) (Hamilton et
49 al. 2015; Militello-Hourigan and Miller 2018; Underhill et al. 2018; Cedeño-Laurent et al. 2018). (Fisk
50 2018) showed that increased ventilation rates in residential buildings results in health benefits ranging
51 from 20% to several-fold improvements; however, these benefits do not occur consistently, and
52 ventilation should be combined with other exposure control measures. As adequate ventilation imposes
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1 additional costs, the sick building syndrome symptoms are more likely to be seen in low income
2 households (Shrubsole et al. 2016).
3 The health benefits of residents due to mitigation actions in buildings are significant (for a review see
4 (Maidment et al. 2014; Fisk et al. 2020; Thomson and Thomas 2015)), and are higher among low
5 income households and/or vulnerable groups, including children, the elderly and those with pre-existing
6 illnesses (Maidment et al. 2014; IEA 2014; Ortiz et al. 2019). (Tonn et al. 2018) estimated that the
7 health-related benefits attributed to the two weatherization programs implemented in the US in 2008
8 and 2010 exceeds by a factor of 3 the corresponding energy cost savings yield. (IEA 2014) also found
9 that the health benefits attributed to energy efficiency retrofit programs may outweigh their costs by up
10 to a factor of 3. (Ortiz et al. 2019) estimated that the energy retrofit of vulnerable households in Spain
11 requires an investment of around EUR 10.9-12.3 thousands per dwelling and would generate an average
12 saving to the healthcare system of EUR 372 per year and dwelling (due to only better thermal comfort
13 conditions in winter).
14 9.8.2.3 Outdoor air pollution
15 According to (World Health Organization 2018) around 4.2 million premature deaths worldwide (in
16 both cities and rural areas) are attributed to outdoor air pollution. Only in China, the premature
17 mortalities attributed to PM2.5 and O3 emissions exceeded 1.1 million in 2010 (Gu et al. 2018).
18 Mitigation actions in residential and non-residential sectors decrease the amount of fossil fuels burnt
19 either directly in buildings (for heating, cooking, etc.) or indirectly for electricity generation and thereby
20 reduce air pollution (e.g., PM, O3, SO2, NOx), improve ambient air quality and generate significant
21 health benefits through avoiding premature deaths, lung cancers, ischemic heart diseases, hospital
22 admissions, asthma exacerbations, respiratory symptoms, etc. (Karlsson et al. 2020; Balaban and
23 Puppim de Oliveira 2017; MacNaughton et al. 2018; Levy et al. 2016). Several studies have monetized
24 the health benefits attributed to reduced outdoor air pollution due to the implementation of mitigation
25 actions in buildings, and their magnitude expressed as a ratio to the value of energy savings resulting
26 from the implemented interventions in each case, are in the range of 0.08 in EU, 0.18 in Germany, 0.26-
27 0.40 in US, 0.34 in Brazil, 0.47 in Mexico, 0.74 in Turkey, 8.28 in China and 11.67 in India (Diaz-
28 Mendez et al. 2018; Joyce et al. 2013; MacNaughton et al. 2018; Levy et al. 2016). In developed
29 economies, the estimated co-benefits are relatively low due to the fact that the planned interventions
30 influence a quite clean energy source mix (Tuomisto et al. 2015; MacNaughton et al. 2018). On the
31 other hand, the health co-benefits in question are substantially higher in countries and regions with
32 greater dependency on coal for electricity generation and higher baseline morbidity and mortality rates
33 (Kheirbek et al. 2014; MacNaughton et al. 2018).
34 9.8.3 Other environmental benefits of mitigation actions
35 Apart from the health benefits mentioned above, mitigation actions in the buildings sector are also
36 associated with environmental benefits to ecosystems and crops, by avoiding acidification and
37 eutrophication, biodiversity through green roofs and walls, building environment through reduced
38 corrosion of materials, etc. (Mzavanadze 2018b; Thema et al. 2017) (Knapp et al. 2019; Mayrand and
39 Clergeau 2018), while some negative effects cannot be excluded (Dylewski and Adamczyk 2016).
40 Also, very important are the effects of mitigation actions in buildings on the reduction of consumption
41 of natural resources, namely fossil fuels, metal ores, minerals, etc. These comprise savings from the
42 resulting reduced consumption of fuels, electricity and heat and the lifecycle-wide resource demand for
43 their utilities, as well as potential net savings from the substitution of energy technologies used in
44 buildings (production phase extraction) (Thema et al. 2017) (European Commission 2016). (Teubler et
45 al. 2020) found that the implementation of an energy efficiency scenario in European buildings will
46 result in resource savings (considering only those associated with the generation of final energy
47 products) of 406 kg per MWh lower final energy demand in the residential sector, while the
48 corresponding figure for non-residential buildings was estimated at 706 kg per MWh of reduced energy
49 demand. On the other hand, (Smith et al. 2016) claim that a switch to more efficient appliances could
50 result in negative impacts from increased resource use, which can be mitigated by avoiding premature
51 replacement and maximizing recycling of old appliances.
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1 Mitigation actions aiming to reduce the embodied energy of buildings through using local and
2 sustainable building materials can be used to leverage new supply chains (e.g., for forestry products),
3 which in turn bring further environmental and social benefits to local communities (Hashemi et al. 2015;
4 Cheong C and Storey D 2019). Furthermore, improved insulation and the installation of double- or
5 triple-glazed windows result in reduced noise levels. It is worth mentioning that for every 1 dB decrease
6 in excess noise, academic performance in schools and productivity of employees in office buildings
7 increases by 0.7% and 0.3% respectively (Kockat et al. 2018b). (Smith et al. 2016) estimated that in the
8 UK the annual noise benefits associated with energy renovations in residential buildings may reach
9 £400 million in 2030 outweighing the benefits of reduced air pollution.
10 9.8.4 Social well-being
11 9.8.4.1 Energy/fuel poverty alleviation
12 In 2018 almost 0.79 billion people in developing countries did not have access to electricity, while
13 approximately 2.8 billion people relied on polluting fuels and technologies for cooking (IEA et al.
14 2020b). Only in sub-Saharan Africa, about 548 million people (i.e., more than 50% of the population)
15 live without electricity. In developed economies, the EU Energy Poverty Observatory estimated that in
16 EU-28 44.5 million people were unable to keep their homes warm in 2016, 41.5 million had arrears on
17 their utility bills the same year, 16.3% of households faced disproportionately high energy expenditure
18 in 2010, and 19.2% of households reported being uncomfortably hot during summer in 2012 (Thomson
19 and Bouzarovski 2018). (Okushima 2016) using the “expenditure approach” estimated that fuel poverty
20 rates in Japan reached 8.4% in 2013. In the US, in 2015, 17 million households (14.4% of the total)
21 received an energy disconnect/delivery stop notice and 25 million households (21.2% of the total) had
22 to forgo food and medicine to pay energy bills (Bednar and Reames 2020).
23 The implementation of well-designed climate mitigation measures in buildings can help to reduce
24 energy/fuel poverty and improve living conditions with significant benefits for health (see Section
25 9.8.2) and well-being (Smith et al. 2016; Payne et al. 2015; Tonn et al. 2018). The social implications
26 of energy poverty alleviation for the people in low- and middle-income developing countries with no
27 access to clean energy fuels are further discussed in Section 9.8.4.2. In other developing countries and
28 in developed economies as well, the implementation of mitigation measures can improve the ability of
29 households to affordably heat/cool a larger area of the home, thus increasing the space available to a
30 family and providing more private and comfortable spaces for several activities like homework (Payne
31 et al. 2015). By reducing energy expenditures and making energy bills more affordable for households,
32 a “heat or eat” dilemma can be avoided resulting in better nutrition and reductions in the number of low
33 birthweight babies (Payne et al. 2015; Tonn et al. 2018). Also, renovated buildings and the resulting
34 better indoor conditions, can enable residents to avoid social isolation, improve social cohesion, lower
35 crime, etc. (Payne et al. 2015). (European Commission 2016) found that under an ambitious recast of
36 Energy Performance Buildings Directive (EPBD), the number of households that may be lifted from
37 fuel poverty across the EU lies between 5.17 and 8.26 million. To capture these benefits, mitigation
38 policies and particularly energy renovation programmes should target the most vulnerable among the
39 energy-poor households, which very often are ignored by the policy makers. In this context, it is
40 recognized that fuel poverty should be analysed as a multidimensional social problem (Mashhoodi et
41 al. 2019; Thomson et al. 2017b) (Charlier and Legendre 2019; Baker et al. 2018), as it is related to
42 energy efficiency, household composition, age and health status of its members, social conditions
43 (single parent families, existence of unemployed and retired people, etc.), energy prices, disposable
44 income, etc. In addition, the geographical dimension can have a significant impact on the levels of fuel
45 poverty and should be taken into account when formulating response policies (Besagni and Borgarello
46 2019; Mashhoodi et al. 2019).
47 9.8.4.2 Improved access to energy sources, gender equality and time savings
48 In most low- and middle-income developing countries women and children (particularly girls) spend a
49 significant amount of their time for gathering fuels for cooking and heating (World Health Organization
50 2016; Rosenthal et al. 2018). For example, in Africa more than 70% of the children living in households
51 that primarily cook with polluting fuels spend at least 15 hours and, in some countries, more than 30
52 hours per week in collecting wood or water, facing significant safety risks and constraints on their
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1 available time for education and rest (World Health Organization 2016; Mehetre et al. 2017). Also, in
2 several developing countries (e.g., in most African countries but also in India, in rural areas in Latin
3 America and elsewhere) women spend several hours to collect fuel wood and cook, thus limiting their
4 potential for productive activities for income generation or rest ( García-Frapolli et al. 2010; Mehetre
5 et al. 2017; World Health Organization 2016). Expanding access to clean household energy for cooking,
6 heating and lighting will largely help alleviate these burdens (Lewis et al. 2017; World Health
7 Organization 2016; Rosenthal et al. 2018) (Malla et al. 2011). (Jeuland et al. 2018) found that the time
8 savings associated with the adoption of cleaner and more fuel-efficient stoves by low-income
9 households in developing countries are amount to USD 1.3-1.9 per household per month, constituting
10 the 23-43% of the total social benefits attributed to the promotion of clean stoves.
11 Electrification of remote rural areas and other regions that do not have access to electricity enables
12 people living in poor developing countries to read, socialize, and be more productive during the evening,
13 while it is also associated with greater school attendance by children (Torero 2015; Rao et al. 2016;
14 Barnes and Samad 2018). (Chakravorty et al. 2014) found that a grid connection can increase non-
15 agricultural incomes of rural households in India from 9% up to 28.6% (assuming a higher quality of
16 electricity). On the other hand, some studies clearly show that electricity consumption for connected
17 households is extremely low, with limited penetration of electrical appliances (e.g., (Lee et al. 2017;
18 Cameron et al. 2016) and low quality of electricity (Chakravorty et al. 2014). The implementation of
19 appropriate policies to overcome bureaucratic red tape, low reliability, and credit constraints, is
20 necessary for maximizing the social benefits of electrification.
21 9.8.5 Economic implications of mitigation actions
22 9.8.5.1 Buildings-related labour productivity
23 Low-carbon buildings, and particularly well-designed, operated and maintained high-performance
24 buildings with adequate ventilation, may result in productivity gains and improve the competitiveness
25 of the economy through three different pathways (Bleyl et al. 2019; Thema et al. 2017; Niemelä et al.
26 2017; Mofidi and Akbari 2017; MacNaughton et al. 2015) (European Commission 2016): (i) increasing
27 the amount of active time available for productive work by reducing the absenteeism from work due to
28 illness, the presenteeism (i.e., working with illness or working despite being ill), and the inability to
29 work due to chronic diseases caused by the poor indoor environment; (ii) improving the indoor air
30 quality and thermal comfort of non-residential buildings, which can result in better mental well-being
31 of the employees and increased workforce performance; and (iii) reducing the school absenteeism due
32 to better indoor environmental conditions, which may enhance the future earnings ability of the students
33 and restrict the parents absenteeism due to care-taking of sick children.
34 Productivity gains due to increased amount of active time for work is directly related to acute and
35 chronic health benefits attributed to climate mitigation actions in buildings (see Section 9.8.2.2). The
36 bulk of studies quantifying the impact of energy efficiency on productivity focus on acute health effects.
37 Proper ventilation in buildings is of particular importance and can reduce absenteeism due to sick days
38 by 0.6–1.9 days per person per year (MacNaughton et al. 2015)(Ben-David et al. 2017; Thema et al.
39 2017). In a pan-European study, (Chatterjee and Ürge-Vorsatz 2018) showed that deep energy retrofits
40 in residential buildings may increase the number of active days by 1.78-5.27 (with an average of 3.09)
41 per year and person who has actually shifted to a deep retrofitted building. Similarly, the interventions
42 in the non-residential buildings result in increased active days between 0.79 and 2.43 (with an average
43 of 1.4) per year and person shifted to deeply retrofitted non-residential buildings.
44 As regards improvements in workforce performance due to improved indoor conditions (i.e., air quality,
45 thermal comfort, etc.), (Kozusznik et al. 2019) conducted a systematic review on whether the
46 implementation of energy efficient interventions in office buildings influence well-being and job
47 performance of employees. Among the 34 studies included in this review, 31 found neutral to positive
48 effects of green buildings on productivity and only 3 studies indicated detrimental outcomes for office
49 occupants in terms of job performance. Particularly longitudinal studies, which observe and compare
50 the office users’ reactions over time in conventional and green buildings, show that green buildings
51 have neutral to positive effects on occupants well-being and work performance (Thatcher and Milner
52 2016; Candido et al. 2019; Kozusznik et al. 2019). (Bleyl et al. 2019) estimated that deep energy retrofits
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1 in office buildings in Belgium would generate a workforce performance increase of 10.4 to 20.8
2 EUR·m-2 renovated. In Europe every 1°C reduction in overheating during the summer period increases
3 students learning performance by 2.3% and workers performance in office buildings by 3.6% (Kockat
4 et al. 2018b). Considering the latter indicator, it was estimated that by reducing overheating across
5 Europe, the overall performance of the workers in office buildings can increase by 7-12% (Kockat et
6 al. 2018b).
7 9.8.5.2 Enhanced asset values of energy efficient buildings
8 A significant number of studies confirm that homes with high energy efficiency and/or green features
9 are sold at higher prices than conventional, low energy efficient houses. A review of 15 studies from 12
10 different countries showed that energy efficient dwellings have a price premium ranging between 1.5%
11 and 28%, with a median estimated at 7.8%, for the highest energy efficient category examined in each
12 case study compared to reference houses with the same characteristics but lower energy efficiency (the
13 detailed results of this review are presented in Table SM9.55 included in the Supplementary Material).
14 In a given real estate market, the higher the energy efficiency of dwellings compared to conventional
15 housing, the higher their selling prices. However, a number of studies show that this premium is largely
16 realized during resale transactions and is smaller or even negative in some cases immediately after the
17 completion of the construction (Deng and Wu 2014; Yoshida and Sugiura 2015). A relatively lower
18 number of studies (also included in Table SM9.5 of Supplementary Material) show that energy
19 efficiency and green features have also a positive effect on rental prices of dwellings (Cajias et al. 2019;
20 Hyland et al. 2013), but this is weaker compared to sales prices, and in a developing country even
21 negative as green buildings, which incorporate new technologies such as central air conditioning, are
22 associated with higher electricity consumption (Zheng et al. 2012).
23 Regarding non-residential buildings, (European Commission 2016) reviewed a number of studies
24 showing that buildings with high energy efficiency or certified with green certificates present higher
25 sales prices by 5.2-35%, and higher rents by 2.5-11.8%. More recent studies in relation to those included
26 in the review confirm these results (e.g., (Mangialardo et al. 2018; Ott and Hahn 2018)) or project even
27 higher premiums (e.g., (Chegut et al. 2014)) found that green certification in the London office market
28 results in a premium of 19.7% for rents). On the other hand, in Australia, a review study showed mixed
29 evidence regarding price differentials emerged as a function of energy performance of office buildings
30 (Acil Allen Consulting 2015). Other studies have shown that energy efficiency and green certifications
31 have been associated with lower default rates for commercial mortgages (An and Pivo 2020; Wallace
32 et al. 2018; Mathew et al. 2021).
33 More generally, (Giraudet 2020) based on a meta-analysis of several studies, showed that the
34 capitalization of energy efficiency is observed in building sales and rental (even in the absence of energy
35 performance certificates), but the resulting market equilibrium can be considered inefficient as rented
36 dwellings are less energy efficient than owner-occupied ones.
37 9.8.5.3 Macroeconomic effects
38 Investments required for the implementation of mitigation actions, create, mainly in the short-run,
39 increase in the economic output and employment in sectors delivering energy efficiency services and
40 products, which are partially counterbalanced by less investments and lower production in other parts
41 of the economy (Thema et al. 2017; US EPA 2018; Yushchenko and Patel 2016) (European
42 Commission 2016) (see also Cross-Working Group Box 1 in Chapter 3). The magnitude of these
43 impacts depends on the structure of the economy, the extent to which energy saving technologies are
44 produced domestically or imported from abroad, but also from the growth cycle of the economy with
45 the benefits being maximized when the related investments are realized in periods of economic
46 recession ( Mirasgedis et al. 2014; Thema et al. 2017; Yushchenko and Patel 2016). Particularly in
47 developing countries if the mitigation measures and other interventions to improve energy access
48 (Figure 9.19) are carried out by locals, the impact on economy, employment and social well-being will
49 be substantial (Mills 2016; Lehr et al. 2016). As many of these programs are carried out with foreign
50 assistance funds, it is essential that the funds be spent in-country to the full extent possible, while some
51 portion of these funds would need to be devoted to institution building and especially training. (Mills
52 2016) estimated that a market transformation from inefficient and polluting fuel-based lighting to solar-
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1 LED systems to fully serve the 112 million households that currently lack electricity access will create
2 directly 2 million new jobs in these developing countries, while the indirect effects could be even
3 greater. (IEA 2020b) estimated that 9-30 jobs would be generated for every million dollars invested in
4 building retrofits or in construction of new energy efficient buildings (gross direct and indirect
5 employment), with the highest employment intensity rates occurring in developing countries.
6 Correspondingly, 7-16 jobs would be created for every million dollars spent in purchasing highly
7 efficient and connected appliances, while expanding clean cooking through LPG could create 16-75
8 direct local jobs per million dollars invested. Increases in product and employment attributed to energy
9 efficiency investments also affect public budgets by increasing income and business taxation, reducing
10 unemployment benefits, etc. (Thema et al. 2017), thus mitigating the impact on public deficit of
11 subsidizing energy saving measures (Mikulić et al. 2016).
12 Furthermore, energy savings due to the implementation of mitigation actions will result, mainly in the
13 long-run, in increased disposable income for households, which in turn may be spent to buy other goods
14 and services, resulting in economic development, creation of new permanent employment and positive
15 public budget implications (IEA 2014; US EPA 2018; Thema et al. 2017). According to (Anderson et
16 al. 2014), the production of these other goods and services is usually more labour-intensive compared
17 to energy production, resulting in net employment benefits of about 8 jobs per million dollars of
18 consumer bill savings in the US. These effects may again have a positive impact on public budgets.
19 Furthermore, reduced energy consumption on a large scale is likely to have an impact on lower energy
20 prices and hence on reducing the cost of production of various products, improving the productivity of
21 the economy and enhancing security of energy supply (IEA 2014; Thema et al. 2017).
22 9.8.5.4 Energy security
23 GHG emission reduction actions in the sector of buildings affect energy systems by: (i) reducing the
24 overall consumption of energy resources, especially fossil fuels; (ii) promoting the electrification of
25 thermal energy uses; and (iii) enhancing distributed generation through the incorporation of RES and
26 other clean and smart technologies in buildings. Increasing sufficiency, energy efficiency and
27 penetration of RES result in improving the primary energy intensity of the economy and reducing
28 dependence on fossil fuels, which for many countries are imported energy resources (Markovska et al.
29 2016; Thema et al. 2017; Boermans et al. 2015). The electrification of thermal energy uses is expected
30 to increase the demand for electricity in buildings, which in most cases can be reversed (at national or
31 regional level) by promoting nearly zero energy new buildings and a deep renovation of the existing
32 building stock (Couder and Verbruggen 2017; Boermans et al. 2015). In addition, highly efficient
33 buildings can keep the desired room temperature stable over a longer period and consequently they have
34 the capability to shift heating and cooling operation in time (Boermans et al. 2015). These result in
35 reduced peak demand, lower system losses and avoided generation and grid infrastructure investments.
36 As a significant proportion of the global population, particularly in rural and remote locations, still lack
37 access to modern energy sources, renewables can be used to power distributed generation or micro-grid
38 systems that enable peer-to-peer energy exchange, constituting a crucial component to improve energy
39 security for rural populations (Leibrand et al. 2019; Kirchhoff and Strunz 2019). For successful
40 development of peer-to-peer micro-grids, financial incentives to asset owners are critical for ensuring
41 their willingness to share their energy resources, while support measures should be adopted to ensure
42 that also non-asset holders can contribute to investments in energy generation and storage equipment
43 and have the ability to sell electricity to others (Kirchhoff and Strunz 2019).
44
45 9.9 Sectoral barriers and policies
46 9.9.1 Barriers, feasibility, and acceptance
47 Understanding the reasons why cost-effective investment in building energy efficiency are not taking
48 place as expected by rational economic behaviour is critical to design effective policies for decarbonize
49 the buildings (Cattaneo 2019; Cattano et al. 2013). Barriers depend from the actors (owner, tenant,
50 utility, regulators, manufacturers, etc.), their role in energy efficiency project and the market,
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1 technology, financial economic, social, legal, institutional, regulatory and policy structures (Reddy
2 1991; Weber 1997; Sorrell et al. 2000; Reddy 2002; Sorrell et al. 2011: Cagno et al. 2012; Bardhan et
3 al., 2014; Bagaini et al. 2020; Vogel et al. 2015; Khosla et al. 2017; Gupta et al. 2017). Barriers
4 identified for the refurbishment of exiting building or construction of new efficient buildings includes:
5 lack of high-performance products, construction methods, monitoring capacity, investment risks,
6 policies intermittency, information gaps, principal agent problems (both tenant and landlord face
7 disincentives to invest in energy efficiency), skills of the installers, lack of a trained and ready
8 workforce, governance arrangements in collectively owned properties and behavioural anomalies. (Do
9 et al. 2020; Dutt 2020; Gillingham and Palmer 2014;Yang et al., 2019; Song et al. 2020; Buessler et al.
10 2017)). A better understanding of behavioural barriers (Frederiks et al. 2015) is essential to design
11 effective policies to decarbonise the building sector. Energy efficiency in buildings faces one additional
12 problem: the sector is highly heterogeneous, with many different building types, sizes and operational
13 uses. Energy efficiency investments do not take place in isolation but in competition with other priorities
14 and as part of a complex, protracted investment process (Cooremans 2011). Therefore, a focus on
15 overcoming barriers is not enough for effective policy. Organisational context is important because the
16 same barrier might have very different organisational effects and require very different policy responses
17 (Mallaburn 2018). Cross-Chapter Box 2 in Chapter 2 presents a summary of methodologies for
18 estimating the macro-level impact of policies on indices of GHG mitigation.
19 Reaching deep decarbonisation levels throughout the life cycle of buildings depend on
20 multidimensional criteria for assessing the feasibility of mitigation measures, including criteria related
21 to geophysical, environmental-ecological, technological, economic, socio-cultural and institutional
22 dimensions. An assessment of 16 feasibility criteria for mitigation measures in the buildings sector
23 indicates whether a specific factor, within broader dimensions, acts as a barrier or helps enabling such
24 mitigation measures (Figure 9.20, Supplementary material Table SM9.6, Annex II.11). Although
25 mitigation measures are aggregated in the assessment of Figure 9.20 and feasibility results can differ
26 for more specific measures, generally speaking, the barriers to mitigation measures in buildings are few,
27 sometimes including technological and socio-cultural challenges. However, many co-benefits could
28 help enable mitigation in the buildings sector. For instance, many measures can have positive effects
29 on the environment, health and well-being, and distributional potential, all of which can boost their
30 feasibility. The feasibility of mitigation measures varies significantly according to socio-economic
31 differences across and within countries.
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1
2 Figure 9.20 Summary of the extent to which different factors would enable or inhibit the deployment of mitigation options in buildings.
3 Blue bars indicate the extent to which the indicator enables the implementation of the option (E) and orange bars indicate the extent to which an indicator is a
4 barrier (B) to the deployment of the option, relative to the maximum possible barriers and enablers assessed. A X signifies the indicator is not applicable or does
5 not affect the feasibility of the option, while a forward slash / indicates that there is no or limited evidence whether the indicator affects the feasibility of the option.
6 The shading indicates the level of confidence, with darker shading signifying higher levels of confidence. Table SM9.6 provides an overview of the extent to which
7 the feasibility of options may differ across context (e.g., region), time (e.g., 2030 versus 2050), and scale (e.g., small versus large), and includes a line of sight on
8 which the assessment is based. The assessment method is explained in Annex II.11.
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1 9.9.2 Rebound effects
2 In the buildings sector energy efficiency improvements and promotion of cleaner fuels can lead to all
3 types of rebound effects, while sufficiency measures lead only to indirect and secondary effects (Chitnis
4 et al. 2013). The consideration of the rebound effects as a behavioural economic response of the
5 consumers to cheaper energy services can only partially explain the gap between the expected and actual
6 energy savings (Galvin and Sunikka-Blank 2017). The prebound effect, a term used to describe the
7 situation where there is a significant difference between expected and observed energy consumption of
8 non-refurbished buildings, is usually implicated in high rebound effects upon retrofitting (Teli et al.
9 2016; Calì et al. 2016; Galvin and Sunikka-Blank 2017). The access for all to modern energy services
10 such as heating and cooling is one of the wellbeing objectives governments aim for. However, ensuring
11 this access leads to an increase of energy demand which is considered as a rebound effect by (Berger
12 and Höltl 2019; Poon 2015; Seebauer 2018; Sorrell et al. 2018; Orea et al. 2015; Teli et al. 2016; Chitnis
13 et al. 2013). (Aydin et al. 2017) found that in the Netherlands the rebound effect for the lowest wealth
14 quantile is double compared to the highest wealth quantile. Similar, energy access in developing
15 countries leads to an increase consumption compared to very low baselines which is considered by some
16 authors as rebound (Copiello 2017). On the other hand, in households whose members have a higher
17 level of education and/or strong environmental values, the rebound is lower (Seebauer 2018).
18 Rebound effects in the building sector could be a co-benefit, in cases where the mechanisms involved
19 provide faster access to affordable energy and/or contribute to improved social well-being, or a trade-
20 off, to the extent that the external costs of the increased energy consumption exceed the welfare benefits
21 of the increased energy service consumption (Galvin and Sunikka-Blank 2017; Sorrell et al. 2018)
22 (Chan and Gillingham 2015; Borenstein 2015). In cases where rebound effects are undesirable,
23 appropriate policies could be implemented for their mitigation.
24 There is great variation in estimates of the direct and indirect rebound effects, which stems from the
25 end-uses included in the analysis, differences in definitions and methods used to estimate the rebound
26 effects, the quality of the data utilized, the period of analysis and the geographical area in consideration
27 (Gillingham et al. 2016; International Risk Governance Council 2013; Galvin 2014). Several studies
28 examined in the context of this assessment (see Table SM9.7) showed that direct rebound effects for
29 residential energy consumption, which includes heating, are significant and range between -9% and
30 91%, with a median at 35% in Europe, 0-30% with a median at 20% in the US, and 72-127%, with a
31 median at 89% in China. The direct rebound effects for energy services other than heating may be
32 lower (Chen et al. 2018; Sorrell et al. 2018). The rebound effects may be reduced with the time as the
33 occupants learn how to optimally use the systems installed in energy renovated buildings (Calì et al.
34 2016) and seem to be lower in the case of major renovations leading to nZEB (Corrado et al. 2016).
35 The combined direct and indirect or the indirect only rebound effects were found to range between -2%
36 and 80%, with a median at 12% (see Table SM9.7). In non-residential buildings the rebound effects
37 may be smaller, as the commercial sector is characterized by lower price elasticities of energy demand,
38 while the comfort level in commercial buildings before renovation is likely to be better compared to
39 residential buildings (Qiu 2014).
40 9.9.3 Policy packages for the decarbonisation of buildings
41 There is no single energy efficiency policy (Wiese et al. 2018) able to decarbonise the building sector,
42 but a range of polices are needed, often included in a policy package (Kern et al., 2017; Rosenow et al.
43 2017) to enhance robustness against risks and uncertainties in both short and long-term and addressing
44 the different stakeholder perspectives (Forouli et al. 2019; Nikas et al. 2020; Doukas and Nikas 2020).
45 This is due to: the many barriers; the different types of buildings (residential, non-residential, etc.); the
46 different socio-economic groups of the population (social housing, informal settlement, etc.); the
47 country development status; the local climate (cooling and/or heating), ownership structure (tenant or
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1 owner), the age of buildings. Effective policy packages include mandatory standards, codes, the
2 provision of information, carbon pricing, financing, and technical assistance for end-users. Important
3 element related to policy packages is whether the policies reinforce each other or diminish the impact
4 of individual policies, due to policy “overcrowding”. Examples are the EU policy package for efficiency
5 in buildings (Rosenow and Bayer 2017; Economidou et al, 2020; BPIE, 2020) and China goal of 10
6 million m2 NZEB during the 13th Five-Year Plan, presented in the Supplementary Material (Section
7 SM9.4). See also Cross-Chapter Box 10 in Chapter 14 for integrated policymaking for sector transitions.
8 Revisions in tenant and condominium law are necessary for reducing disincentives between landlord
9 and tenant or between multiple owners, these acts alone cannot incentivise them to uptake an energy
10 efficiency upgrade in a property (Economidou and Serrenho, 2019). A package addressing split
11 incentives include regulatory measures, information measures, labels, individual metering rules and
12 financial models designed to distribute costs and benefits to tenants and owners in a transparent and fair
13 way (Bird and Hernández 2012; Economidou and Bertoldi 2015; Castellazi et al. 2017). A more active
14 engagement of building occupants in energy saving practices, the development of agreements
15 benefitting all involved actors, acknowledgement of real energy consumption and establishment of cost
16 recovery models attached to the property instead of the owner are useful measures to address
17 misalignments between actors.
18 In developed countries policy packages are targeted to increase the number and depth of renovations of
19 existing building, while for developing countries policies focus on new construction, including
20 regulatory measures and incentives, while carbon pricing would be more problematic unless there is a
21 strong recycling of the revenues. Building energy codes and labels could be based on LCA emissions,
22 rather than energy consumption during the use phase of buildings, as it is the case in Switzerland and
23 Finland (Kuittinen and Häkkinen 2020).
24 Policy packages should also combine sufficiency, efficiency, and renewable energy instruments for
25 buildings, for example some national building energy codes already include minimum requirements for
26 the use of renewable energy in buildings.
27 9.9.3.1 Sufficiency and efficiency policies
28 Recently the concept of sufficiency complementary to energy efficiency has been introduced in policy
29 making (Saheb 2021; Bertoldi 2020; Hewitt 2018; Brischke et al. 2015; Thomas et al. 2019), see Box
30 9.1. Lorek and Spangenberg (2019b) investigated the limitations of the theories of planned behaviour
31 and social practice and proposed an approach combining both theories resulting in a heuristic
32 sufficiency policy tool. Lorek and Spangenberg (2019b) showed that increased living area per person
33 counteracts efficiency gains in buildings and called for sufficiency policy instruments to efficiency by
34 limit building size. This could be achieved via mandatory and prescriptive measures, e.g., progressive
35 building energy codes (IEA, 2013), or financial penalties in the form of property taxation (e.g., non-
36 linear and progressive taxation), or with mandatory limits on building size per capita. Heindl and
37 Kanschik (2016) suggested that voluntary policies promoting sufficiency and proposed that sufficiency
38 should be "integrated in a more comprehensive normative framework related to welfare and social
39 justice". Alcott highlighted that in sufficiency there is a loss of utility or welfare (Alcott, 2008), Thomas
40 et al. (2019) described some of the possible policies, some based on the sharing economy principles,
41 for examples co-sharing space, public authorities facilitating the exchange house between young and
42 expanding families with elderly people, with reduce need for space. Policies for sufficiency include
43 land-use and urban planning policies. Berril et al, (2021) proposed removing policies, which support
44 supply of larger home typologies, e.g., single-family home or local land-use regulations restricting
45 construction of multifamily buildings. In non-residential building, sufficiency could be implemented
46 through the sharing economy, for example with flexible offices space with hot-desking.
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1 Scholars have identified the "energy efficiency gap" (Hirst and Brown 1990; Jaffe and Stavins 1994;
2 Stadelmann 2017; Gillingham and Palmer 2014; Alcott and Greenstone 2012) and policies to overcome
3 it. (Markandya et al. 2015) and Shen et al. (2016) have classified energy efficiency policies in three
4 broad categories: the command and control (e.g. mandatory building energy codes; mandatory
5 appliances standards, etc.); price instruments (e.g. taxes, subsides, tax deductions, credits, permits and
6 tradable obligations, etc.); and information instruments (e.g. labels, energy audits, smart meters and
7 feed-back, etc.). Based on the EU Energy Efficiency Directive, the MURE and the IEA energy
8 efficiency policy databases (Bertoldi and Mosconi 2020), Bertoldi (2020) proposed six policy
9 categories: regulatory, financial and fiscal; information and awareness; qualification, training and
10 quality assurance; market-based instruments: voluntary action. The categorization of energy efficiency
11 policies used in this chapter is aligned with the taxonomy used in Chapter 13, sub-section 13.5.1
12 (economic or market-based instruments, regulatory instruments, and other policies). However, the
13 classification used here is more granular in order to capture the complexity of end-use energy efficiency
14 and buildings.
15 1. Regulatory instruments
16 Building energy codes
17 Several scholars highlighted the key role of mandatory building energy codes and minimum energy
18 performance requirements for buildings (Enker and Morrison 2017). Wang et al. (2019) finds that
19 "Building energy efficiency standards (BEES) are one of the most effective policies to reduce building
20 energy consumption, especially in the case of the rapid urbanization content in China". Ex-post policy
21 evaluation shows that stringent buildings codes reduce energy consumption in buildings and CO2
22 emissions and are cost-effective (Scott et al. 2015; Aydin and Brounen 2019; (Yu et al. 2017; Yu et al.
23 2018)(Aroonruengsawat 2012; Levinson 2016; Kotchen 2017; Jacobsen and Kotchen 2013).
24 Progressive building energy codes include requirements on efficiency improvement but also on
25 sufficiency and share of renewables (Rosenberg at al., 2017; Clune at al. 2012) and on embodied
26 emissions (Schwarz et al. 2020), for example the 2022 ASHRAE Standard 90.1 includes prescriptive
27 on-site renewable energy requirements for non-residential building. Evans et al. (2017; 2018) calls for
28 strengthen the compliance checks with efficiency requirements or codes when buildings are in operation
29 and highlighted the need for enforcement of building energy codes to achieve the estimate energy and
30 carbon savings recommending actions to improve enforcements, including institutional capacity and
31 adequate resources.
32 Evans et al. (2017; 2018) identified strengthening the compliance checks with codes when buildings
33 are in operation and the need for enforcement of building energy codes in order to achieve the estimate
34 energy and carbon savings, recommending actions to improve enforcements, including institutional
35 capacity and adequate resources. Another important issue to be addressed by policies is the 'Energy
36 Performance Gap' (EPG), i.e., the gap between design and policy intent and actual outcomes.
37 Regulatory and market support regimes are based on predictive models (Cohen and Bordass 2015) with
38 general assumptions about building types, the way they are used and are not covering all energy
39 consumption. In the perspective of moving towards net zero carbon, it is important that policy capture
40 and address the actual in-use performance of buildings (Gupta and Kotopouleas 2018; Gupta et al.
41 2015). Outcome-based codes are increasingly important because overcome some limitations of
42 prescriptive building energy codes, which typically do not regulate all building energy uses or do not
43 regulate measured operational energy use in buildings. Regulating all loads, especially plug and process
44 loads, is important because they account for an increasingly large percentage of total energy use as
45 building envelope and space-conditioning equipment are becoming more efficient (Denniston et al.,
46 2011; Colker, 2012; Enker and Morrison, 2020).
47 Building codes could also foster the usage of wood and timber as a construction in particular for multi-
48 storey buildings and in the long term penalise carbon intensive building materials (Ludwig 2019) with
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1 policies based on environmental performance assessment of buildings and the “wood first”
2 principle (Ludwig, 2019; Ramage et al., 2017).
3 Retro-commissioning is a cost-effective process to periodically check the energy performance of
4 existing building and assure energy savings are maintained overtime (Ssembatya et al., 2021)(Kong et
5 al. 2019).
6 In countries with low rate of new construction, it is important to consider mandatory building energy
7 codes for existing buildings, but this may also be relevant for countries with high new construction, as
8 they will have soon a large existing building stock. The EU has requirements already in place when
9 building undergo a major renovation (Economidou et. al, 2020). Countries considering mandatory
10 regulations for existing buildings include Canada, the U.S. (specific cities), China, Singapore. Policies
11 include mandating energy retrofits for low performances existing buildings, when sold or rented. In
12 countries with increasing building stock, in particular in developing countries, policies are more
13 effective when targeting new buildings (Kamal et al. 2019).
14 NZEBs definitions are proposed by (Marszal et al. 2011; Deng and Wu 2014; Zhang and Zhou 2015;
15 Wells et al. 2018; Williams et al. 2016); ), covering different geographical areas, developing and
16 developed countries, and both existing buildings and new buildings. In 2019, China issued the national
17 standard Technical Standard for Nearly Zero Energy Building (MoHURD, 2019). California has also
18 adopted a building energy code mandating for NZEBs for new residential buildings in 2020 and 2030
19 for commercial buildings (Feng et al. 2019). Several countries have adopted targets, roadmaps or
20 mandatory building energy codes requiring net zero energy buildings (NZEBs) for some classes of new
21 buildings (Feng et al. 2019).
22 Building Labels and Energy Performance Certificates (EPCs)
23 Buildings labels are an important instrument , with some limitations. Li et al. (2019b) reviewed the EU
24 mandatory Energy Performance Certificates for buildings and proposed several measures to make the
25 EPC more effective in driving the markets towards low consumption buildings. Some authors have
26 indicated that the EPC based on the physical properties of the buildings (asset rating) may be misleading
27 due to occupancy behaviour (Cohen and Bordass 2015) and calculation errors (Crawley et al. 2019).
28 Control authorities can have a large impact on the quality of the label (Mallaburn 2018). Labels can
29 also include information on the GHG embedded in building material or be based on LCA.
30 US EPA Energy Star and NABERS (Gui and Gou, 2020) are building performance labels based on
31 performance, not on modelled energy use. Singapore has mandatory building energy labels, as do many
32 cities in the U.S., while India and Brazil have mandatory labels for public buildings.
33 Mandatory energy performance disclosure and benchmarking of building energy consumption is a
34 powerful policy instrument in particular for non-residential buildings (Trencher et al. 2016) and could
35 be more accurate than energy audits. Gabe (2016) showed that mandatory disclosure is more effective
36 than voluntary disclosure. Some US cities (e.g., New York) have adopted Emissions Performance
37 Standards for buildings, capping CO2 emissions. Accurate statistics related to energy use are very
38 important for reducing GHG in building sector. In 2015, the Republic of Korean stablished the National
39 Building Energy Integrated Management System, where building data and energy consumption
40 information are collected for policy development and public information.
41 Energy audits
42 Energy audits, help to overcome the information barriers to efficiency investments, in particular
43 buildings owned or occupied by small companies (Kalantzis and Revoltella, 2019). In the EU energy
44 audits are mandatory for large companies under the Energy Efficiency Directive (Nabitz and Hirzel
45 2019), with some EU Member States having a long experience with energy audits, as part of national
46 voluntary agreements with the private sector (Cornelis 2019; Rezessy and Bertoldi 2011). Singapore
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1 has adopted mandatory audit for buildings (Shen et al, 2016). In the United States, several cities have
2 adopted energy informational policies in recent years, including mandatory buildings audits (Trencher
3 et al. 2016; Kontokosta et al., 2020). The State of New York has in place a subsidized energy audit for
4 residential building since 2010 (Boucher et al. 2018). It is important to assure the training of auditors
5 and the quality of the audit.
6 Minimum Energy Performance Standards (MEPSs)
7 Mandatory minimum efficiency standards for building technical equipment and appliances (e.g.,
8 HVAC, appliances, ICT, lighting, etc.) is a very common, tested and successful policy in most of the
9 OECD countries (e.g. EU, US, Canada, Australia, etc.) for improving energy efficiency (Wu et al.
10 2019; Scott et al. 2015; Sonnenschein et al. 2019). Brucal and Roberts (2019) showed that efficiency
11 standards reduce product price. McNeil et al. (2019) highlighted how efficiency standards will help
12 developing countries in reducing the power peak demand by a factor of two, thus reducing large
13 investment costs in new generation, transmission, and distribution networks. Mandatory standards have
14 been implemented also other large economies, e.g., Russia, Brazil, India, South Africa, China, Ghana,
15 Kenya, Malaysia (Salleh et al., 2019), with an increase in the uptake also in developing countries, e.g.
16 Ghana, Kenya, Tunisia, etc. In Japan, there is a successful voluntary programme the Top Runner, with
17 similar results of mandatory efficiency standards (Inoue and Matsumoto 2019).
18 Appliance energy labelling
19 Mandatory energy labelling schemes for building technical equipment and appliances are very often
20 implemented together with minimum efficiency standards, with the mandatory standard pushing the
21 market towards higher efficiency and the label pulling the market (Bertoldi, 2019). OECD countries,
22 China and many developing countries (for example Ghana, Kenya, India, South Africa, etc.) (Chunekar
23 2014) (Diawuo et al., 2018; Issock Issock et al., 2018) have adopted mandatory energy labelling. Other
24 labelling schemes are of voluntary nature, e.g. the Energy Star programme in the US (Ohler et al., 2020),
25 which covers many different appliances.
26 Information campaign
27 Provision of information (e.g. public campaigns, targeted technical information, etc.) is a common
28 policy instrument to change end-user behaviour. Many authors agree that the effect of both targeted and
29 general advertisement and campaigns have a short lifetime and the effects tend to decrease over time
30 (Simcock et al. 2014; Diffney et al. 2013; Reiss and White 2008). The meta-analysis carried out by
31 (Delmas et al. 2013) showed that energy audits and personal information were the most effective
32 followed by providing individuals with comparisons with their peers’ energy use including "non-
33 monetary, information-based" (Delmas et al. 2013). An effective approach integrates the social norm
34 as the basis for information and awareness measures on energy behaviour (Gifford 2011; Schultz et al.
35 2007). Information is more successful when it inspires and engages people: how people feel about a
36 given situation often has a potent influence on their decisions (Slovic and Peters 2006). The message
37 needs to be carefully selected and kept as simple as possible focusing on the following: entertain,
38 engage, embed and educate (Dewick and Owen 2015).
39 Energy consumption feedback with smart meters, smart billing and dedicated devices and apps is
40 another instrument recently exploited to reduce energy consumption (Zangheri et al. 2019; Karlin et al.
41 2015; Buchanan et al. 2018) very often coupled with contest-based interventions or norm-based
42 interventions (Bergquist et al. 2019). (Hargreaves et al. 2018) proposes five core types of action to
43 reduce energy use: turn it off, use it less, use it more carefully, improve its performance, and replace
44 it/use an alternative. According to (Aydin et al. 2018), technology alone will not be enough to achieve
45 the desired energy savings due to the rebound effect. The lack of interest from household occupants,
46 confusing feedback message and difficulty to relate it to practical intervention, overemphasis on
47 financial savings and the risks of “fallback effects” where energy use returns to previous levels after a
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1 short time or rebound effects has been pointed out (Buchanan et al. 2015) as the main reasons for the
2 failing of traditional feedback. (Labanca and Bertoldi 2018) highlight the current limitations of policies
3 for energy conservation and suggests complementary policy approach based on social practices
4 theories.
5 2. Market-based instruments
6 Carbon allowances
7 A number of authors (Wadud and Chintakayala 2019; Fan et al. 2016; Raux et al. 2015; Marek et al.
8 2018; Li et al. 2015, 2018; Fawcett and Parag 2017) have investigated personal carbon allowances
9 introduced previously (Fleming 1997; Bristow et al. 2010; Fawcett 2010; Starkey 2012; Raux and
10 Marlot 2005; Ayres 1995). Although there is not yet any practical implementation of this policy, it
11 offers an alternative to carbon taxes, although there are some practical issues to be solved before it could
12 be rolled out. Recently the city of Lahti in Finland has introduced a personal carbon allowance in the
13 transport sector (Kuokkanen et al. 2020). Under this policy instrument governments sets allocates (free
14 allocation, but allowances could also be auctioned) allowances to cover the carbon emission for one
15 year, associated with energy consumption. Trade of allowances between people can be organised.
16 Personal carbon allowances can also foster renewable energies (energy consumption without carbon
17 emissions) both in the grid and in buildings (e.g., solar thermal). Personal carbon allowances can make
18 the carbon price more explicit to consumers, allowing them to know from the market value of each
19 allowance (e.g., 1 kg of CO2). This policy instrument will shift the responsibility to the individual. Some
20 categories may have limited ability to change their carbon budget or to be engaged by this policy
21 instruments. In addition, in common with many other environmental policies the distributional effects
22 have to be assessed carefully as this policy instrument may favour well off people able to purchase
23 additional carbon allowances or install technologies that reduce their carbon emissions (Burgess 2016;
24 Wang et al. 2017).
25 The concept of carbon allowances or carbon budget can also be applied to buildings, by assigning a
26 yearly CO2 emissions budget to each building. This policy would be a less complex than personal
27 allowances as buildings have metered or billed energy sources (e.g., gas, electricity, delivered heat,
28 heating oil, etc.). The scheme stimulates investments in energy efficiency and on-site renewable
29 energies and energy savings resulting from behaviour by buildings occupant. For commercial buildings,
30 similar schemes were implemented in the UK CRC Energy Efficiency Scheme (closed in 2019) or the
31 Tokyo Metropolitan Carbon and Trade Scheme (Nishida and Hua 2011)(Bertoldi et al. 2013a). The
32 Republic of Korea implemented since 2015 an Emission Trading Scheme, covering buildings (Park and
33 Hong 2014; Narassimhan et al. 2018; Lee and Yu 2017). More recently under the New York Climate
34 Mobilization Act enacted in 2019 New York City Local Law 97 established "Carbon Allowances" for
35 large buildings (Spiegel-Feld, 2019; Lee, 2020).
36 Public money can be used to reward and give incentives to energy saved, as a result of technology
37 implementation, and/or as a result of energy conservation and sufficiency (Eyre 2013; Bertoldi et al.
38 2013b; Prasanna et al. 2018). This can be seen as a core feature of the Energy Savings Feed-in Tariff
39 (ES-FiT). The ES-FiT is a performance-based subsidy, whereby actions undertaken by end-users – e.g.,
40 investments in energy efficiency technology measures – are awarded based on the real energy savings
41 achieved.
42 Utilities Programmes, Energy Efficiency Resource Standard and Energy Efficiency Obligations
43 Ratepayers funded efficiency programmes, energy efficiency obligations, energy efficiency resource
44 standards and white certificates have been introduced in some EU Member States, in several US States,
45 Australia, South Korea and Brazil (Bertoldi et al. 2013a; Aldrich and Koerner 2018; Wirl 2015; Choi
46 et al. 2018a; Palmer et al. 2013; Brennan and Palmer 2013; Rosenow and Bayer 2017; Fawcett and
47 Darby 2018; Fawcett et al. 2019; Giraudet and Finon, 2015; Goldman et al, 2020; Nadel, 2019; Sliger
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1 and Colburn, 2019). This policy instrument helps in improving energy efficiency in buildings, but there
2 is no evidence that it can foster deep renovations of existing buildings. Recently this policy instrument
3 has been investigated is some non-OECD countries such as Turkey, where white certificates could
4 deliver energy savings with some limitations (Duzgun and Komurgoz 2014) and UAE, as a useful
5 instrument to foster energy efficiency in buildings (Friedrich and Afshari 2015). Another similar market
6 based instrument is the energy saving auction mechanism implemented in some US States, Switzerland,
7 and in Germany (Thomas and Rosenow 2020; Langreder et al. 2019; Rosenow et al. 2019). Energy
8 efficiency projects participate in auctions for energy savings based on the cost of the energy saved and
9 receive a financial incentive, if successful.
10 Energy or carbon taxes
11 Energy and/or carbon taxes are a climate policy, which can help in reducing energy consumption (Sen
12 and Vollebergh 2018) and manage the rebound effect (Peng et al. 2019; Font Vivanco et al. 2016;
13 Freire-González 2020; Bertoldi 2020). The carbon tax has been adopted mainly in OECD countries and
14 in particular in EU Member States (Hájek et al. 2019; Bertoldi 2020; Sen and Vollebergh 2018) . There
15 is high agreement that carbon taxes can effective in reducing CO2 emissions (Andersson 2017; IPCC
16 2018; Hájek et al. 2019). It is hard to define the optimum level of taxation in order to achieve the desired
17 level of energy consumption or CO2 emission reduction (Weisbach et al. 2009). As for other energy
18 efficiency policy distributional effect and equity considerations have to be carefully considered and
19 mitigated (Borozan 2019). High energy prices tend to reduce the energy consumption particularly in
20 less affluent households, and thus attention is needed in order to avoid unintended effects such as energy
21 poverty. Bourgeois et al. (2021) showed that using carbon tax revenue to finance energy efficiency
22 investment reduces fuel poverty and increases cost-effectiveness. (Giraudet et al. 2021)assessed the
23 cost-effectiveness of various energy efficiency policies in France, concluding that a carbon tax is the
24 most effective. In particular, revenues could be invested in frontline services that can provide a range
25 of support - including advising householders on how to improve their homes. Hence, the introduction
26 of a carbon tax can be neutral or even positive to the economy, as investments in clean technologies
27 generate additional revenues. In addition, in the long term, a carbon/energy tax could gradually replace
28 the tax on labour reducing labour cost (e.g., the example of the German Eco-tax), thus helping to create
29 additional jobs in the economy. In literature, this is known as double dividend (Murtagh et al. 2013)
30 (Freire-González and Ho 2019). Urban economic researches (Rafaj et al. 2018; Creutzig 2014; Borck
31 and Brueckner 2018) have highlighted that higher carbon price would translate in incentives for citizens
32 to live closer to the city centre, which often means less floor space, less commuting distance and thus
33 reduced emissions. Xiang and Lawley (2019) indicated that the carbon tax in British Columbia
34 substantially reduced residential natural gas consumption. Saelim (2019) showed that simulated carbon
35 tax on residential consumption in Thailand will have a low impact on welfare and it will be slightly
36 progressive. Lin and Li (2011) indicate that a carbon tax could reduce the energy consumption and
37 boost the uptake of energy efficiency and renewable energies, while at the same time may impact social
38 welfare and the competitiveness of industry. Solaymani (2017) showed that in Malaysia a tax with
39 revenue recycling increases in the welfare of rural and urban households. Van Heerden et al. (2016)
40 explored economic and environmental effects of the CO2 tax in South Africa highlighting the negative
41 impact on GDP. This negative impact of the carbon tax on GDP is however greatly reduced by the
42 manner in which the tax revenue is recycled. National circumstances shall be taken into consideration
43 in introducing energy taxes, considering the local taxation and energy prices context with regard to
44 sustainable development, justice and equity.
45 A policy, which can have similar impact to a carbon tax and is the energy price/subsidy reform, which
46 also involves raising energy prices. Energy price/subsidy reform reduces energy consumption and
47 greenhouse gas emissions and encourages investment in energy efficiency (Aldubyan and Gasim, 2021;
48 Coady et al., 2018). In a similar manner, government revenues from subsidies reforms can be used to
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1 mitigate the distributional impact on vulnerable population groups, including direct cash transfer
2 programmes (Schaffitzel, et al. 2020; Rentschler and Brazilian, 2017).
3 Taxes could also be used to penalise inefficient behaviour and favour the adoption of efficient behaviour
4 and technologies. Taxes are used in some jurisdictions to promote energy efficient appliances with
5 lower VAT. Similarly, the annual building/property tax (and also the purchase tax) could be based on
6 the CO2 emissions of the buildings, rather than on the value of the building. Tax credits are also an
7 important subsidy for the renovation of buildings in France (Giraudet, 2020), Italy (Alberini and
8 Bigano, 2015) and other countries.
9 9.9.4 Financing mechanisms and business models for reducing energy demand
10 Grants and subsidies are traditional financing instruments used by governments when optimal levels of
11 investments cannot be fully supported by the market alone. They can partly help overcoming the upfront
12 cost barrier as they directly fill an immediate financial gap and thus enable a temporary shift in the
13 market (Newell et al. 2019). These forms of support are usually part of policy mixes including further
14 fiscal and financial instruments such as feed-in tariffs and tax breaks (Polzin et al. 2019). Potential
15 issues with subsidies are the limited availability of public financing, the stop and go due to annual
16 budget and the competition with commercial financing.
17 Loans provide liquidity and direct access to capital important in deep renovation projects (Rosenow et
18 al. 2014). There is empirical evidence (Giraudet et al. 2021), that banks make large profits on personal
19 loans for renovation purposes. International financing institutions (IFIs) and national governments
20 provided subsidies in public-private partnerships so that financial institutions can offer customers loans
21 with attractive terms (Olmos et al. 2012). Loan guarantees are effective in reducing intervention
22 borrowing costs (Soumaré and Lai 2016). Combination of grants and subsidised loans financed by IFIs
23 could be an effective instrument together with guarantees. An important role in financing energy
24 efficiency can be played by green banks, which are publicly capitalized entities set up to facilitate
25 private investment in low-carbon, including energy efficiency (Linh and Anh, 2017; Tu and Yen, 2015;
26 Khan, 2018; Bahl, 2012) . Green banks have been established at the national level (e.g., UK, Poland)
27 and in the US at state and city level.
28 Wholesaling of EE of loans and utilities programmes, are other important financing instruments.
29 Another financing mechanism for building efficiency upgrades, mainly implemented so far in the US,
30 is efficiency-as-a-service under an energy services agreement (ESA), where the building owners or
31 tenant pay to the efficiency service provider a charge based on realized energy savings without any
32 upfront cost (Kim et al., 2012; Bertoldi, 2020). ESA providers give performance guarantees assuming
33 the risk that expected savings would occur (Bertoldi, 2020).
34 Energy Performance Contracting (EPC) is an agreement between a building owner and Energy Services
35 Company (ESCO) for energy efficiency improvements. EPC is a common financing vehicle for large
36 buildings and it is well developed in several markets (Nurcahyanto et al, 2020; Stuart et. al, 2018;
37 Carvallo et al, 2015; Ruan et al., 2018; Zheng et al., 2021; Bertoldi and Boza Kiss, 2017). Quality
38 standards are a part of the EPC (Augustins et al. 2018) . Guarantees can facilitate the provision of
39 affordable and sufficient financing for ESCOs (Bullier and Milin 2013). The ESCO guarantees a certain
40 level of energy savings and it shields the client from performance risk. The loan goes on the client's
41 balance sheet and the ESCO assumes full project performance risk (Deng et al. 2015). One of the
42 limitations is on the depth of the energy renovation in existing buildings. According to (Giraudet et al.
43 2018), EPC is effective at reducing information problems between contractors and investors.
44 Energy efficient mortgages are mortgages that credits a home energy efficiency by offering preferential
45 mortgage terms to extend existing mortgages to finance efficiency improvements. There are two types
46 of energy mortgages: (i) the Energy Efficient Mortgages (EEMs), and (ii) the Energy Improvement
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1 Mortgages (EIMs), both can help in overcoming the main barriers to retrofit policies (Miu et al. 2018).
2 The success depends on the improved energy efficiency with a positive impact on property value and
3 on the reduction of energy bills and the income increase in the household. In the EU, the EeMAP
4 Initiative aims to create a standardised energy efficient mortgage template (Bertoldi et al. 2021).
5 On-bill financing is a mechanism that reduces first-cost barriers by linking repayment of energy
6 efficiency investments to the utility bill and thereby allowing customers to pay back part or all costs of
7 energy efficiency investments over time (Brown 2009). On-bill finance programmes can be categorised
8 into: (i) on-bill loans (assignment of the obligation to the property) and (ii) on-bill tariffs (payment off
9 in case of ownership transfer) (Eadson et al. 2013). On-bill finance programmes can be more effective
10 when set up as a service rather than a loan. (Mundaca and Klocke, 2018).
11 Property Assessed Clean Energy (PACE) is a means of financing energy renovations and renewable
12 energy through the use of specific bonds offered by municipal governments to investors (Mills 2016).
13 Municipalities use the funds raised to loan money towards energy renovations in buildings. The loans
14 are repaid over the assigned long term (15-20 years) via an annual assessment on their property tax bill
15 (Kirkpatrick and Bennear 2014). This model has been subject to consumer protection concerns.
16 Residential PACE programmes in California have been shown to increase PV deployment in
17 jurisdictions that adopt these programs (Ameli et al., 2017; Kirkpatrick and Bennear 2014). In US
18 commercial buildings, PACE volumes and programs, however, continue to grow (Lee, 2020).
19 Revolving funds allow reducing investment requirements and enhancing energy efficiency investment
20 impacts by recovering and reinvesting the savings generated (Setyawan 2014). Revolving fund could
21 make retrofit cost-neutral in the long term and could also dramatically increase low carbon investments,
22 including in developing countries (Gouldson et al. 2015).
23 Carbon finance, started under the Kyoto Protocol with the flexible mechanisms and further enhanced
24 under the Paris Agreement (Michaelowa et al. 2019), is an activity based on “carbon emission rights”
25 and its derivatives (Liu et al. 2015a). Carbon finance can promote low-cost emission reductions (Zhou
26 and Li 2019). Under Emission Trading Schemes or other carbon pricing mechanisms, auctioning carbon
27 allowances creates a new revenue stream. Revenues from auctioning could be used to finance energy
28 efficiency projects in buildings with grants, zero interest loans or guarantees (Wiese et al., 2020).
29 Crowdfunding is a new and rapidly growing form of financial intermediation that channels funds from
30 investors to borrowers (individuals or companies) or users of equity capital (companies) without
31 involving traditional financial organizations such as banks (Miller and Carriveau 2018). Typically, it
32 involves internet-based platforms that link savers directly with borrowers (European Union 2015). It
33 can play a significant role at the start of a renewable and sustainable energy projects (Dilger et al. 2017).
34 The One-Stop Shop (OSS) service providers for buildings energy renovations are organizations,
35 consortia, projects, independent experts or advisors that usually cover the whole or large part of the
36 customer renovation journey from information, technical assistance, structuring and provision of
37 financial support, to the monitoring of savings (Mahapatra et al. 2019; Bertoldi 2021b). OSSs are
38 transparent and accessible advisory tools from the client perspective and new, innovative business
39 models from the supplier perspective (Boza-Kiss and Bertoldi 2018).
40 9.9.5 Policies mechanisms for financing for on-site renewable energy generation
41 On-site renewable energy generation is a key component for the building sector decarbonisation,
42 complementing sufficiency and efficiency. Renewable energies (RES) technologies still face barriers
43 due to the upfront investment costs, despite the declining price of some technologies, long pay-back
44 period, unpredictable energy production, policy incertitude, architectural (in particular for built-in PV)
45 and landscape considerations, technical regulations for access to the grid, and future electricity costs
46 (Mah et al. 2018; Agathokleous and Kalogirou 2020).
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1 Several policy instruments for RES have been identified by scholars (Azhgaliyeva et al. 2018; Pitelis
2 et al. 2020; Fouquet 2013): direct investments; feed-in tariffs; grants and subsidies; loans, taxes;
3 (tradable) green certificates or renewable/clean energy portfolio standards; information and education;
4 strategic planning; codes and standards; building codes; priority grid access; research, development and
5 deployment; and voluntary approaches. There are specific policies for renewable heating and cooling.
6 (Connor et al. 2013). In 2011, the UK introduced the Renewable Heat Incentive (RHI) support scheme
7 (Balta-Ozkan et al. 2015; Connor et al. 2015). The RHI guarantee a fixed payment per unit of heat
8 generated by a renewable heat technology for a specific contract duration (Yılmaz Balaman et al. 2019).
9 The most common implemented policy instruments are the feed-in tariffs (FiTs) and the Renewable/
10 Energy Portfolio Standards (RPSs) (Alizada 2018; Xin-gang et al. 2017a; Bergquist et al., 2020), with
11 FiTs more suited for small scale generation. More than 60 countries and regions worldwide have
12 implemented one of the two policies (Sun and Nie 2015). FiT is a price policy guaranteeing the purchase
13 of energy generation at a specific fixed price for a fixed period (Xin-gang et al. 2020; Barbosa et al.
14 2018). RPS is a quantitative policy, which impose mandatory quota of RES generation to power
15 generators (Xin-gang et al. 2020) .
16 A flat rate feed-in tariff (FiT) is a well-tested incentive adopted in many jurisdictions to encourage end-
17 users to generate electricity from RES using rooftop and on-site PV systems (Pacudan 2018). More
18 recently, there has been an increasing interest for dynamic FiTs taking into account electricity costs,
19 hosting capacity, ambient temperature, and time of day (Hayat et al. 2019). Since 2014, EU Member
20 States have been obligated to move from FiT to feed-in premium (FiTP) (Hortay and Rozner 2019);
21 where a FiTP consist in a premium of top of the electricity market price. Lecuyer and Quirion (2019)
22 argued that under uncertainty over electricity prices and renewable production costs a flat FiT results
23 in higher welfare than a FiTP. One of the main concerns with FiT systems is the increasing cost of
24 policies maintenance (Pereira da Silva et al. 2019; Roberts et al. 2019a; Zhang et al. 2018). In Germany,
25 the financial costs, passed on to consumers in the form a levy on the electricity price have increased
26 substantially in recent years (Winter and Schlesewsky 2019) resulting in opposition to the FiT in
27 particular by non-solar customers. A particular set up of the FiT encourage self-consumption through
28 net metering and net billing, which has a lower financial impact on electricity ratepayers compared with
29 traditional FiTs (Roberts et al. 2019b; Vence and Pereira 2019; Pacudan 2018).
30 In some countries, e.g. Australia (Duong et al. 2019), South Korea (Choi et al. 2018a), China (Yi et al.
31 2019), there was a transition from subsidies under the FiT to market-based mechanisms, such as RPSs
32 and tendering. Compared with FiT, RPS (or Renewable Obligations) reduce the subsidy costs (Zhang
33 et al. 2018). A number of scholars (Xin-gang et al. 2017; Li et al. 2019a; Liu et al. 2018a) have
34 highlighted the RPSs effectiveness in promoting the development of renewable energy. Other authors
35 (Requate 2015; An et al. 2015) have presented possible negative impacts of RPSs.
36 Both FiT and RPS can support the development of RES. Scholars compared the effectiveness of RPSs
37 and FiTs with mix results and different opinions, with some scholars indicating the advantages of RPS
38 (Ciarreta et al. 2017, 2014; Xin-gang et al. 2017), while Nicolini and Tavoni (2017) showed that in Italy
39 FiTs are outperforming RPSs and Tradable Green Certificates (TGCs). García-Álvarez et al. (2018)
40 carried out an empirical assessment of FiTs and RPSs for PV systems energy in EU over the period
41 2000–2014 concluding that that FiTs have a significant positive impact on installed PV capacity. This
42 is due to the small size of many rooftop installations and the difficulties in participating in trading
43 schemes for residential end users. Similar conclusions were reached by (Dijkgraaf et al. 2018) assessing
44 30 OECD countries and concluding that there is a “positive effect of the presence of a FiT on the
45 development of a country's added yearly capacity of PV”. Other scholars (Couture and Gagnon 2010;
46 Lewis and Wiser 2007; Lipp 2007; Cory et al. 2009) concluded that FiT can create a stable investment
47 framework and long-term policy certainty and it is better than RPS for industrial development and job
48 creation. Ouyang and Lin (2014) highlighted that RPS has a better implementation effect than FiT in
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1 China, where FiT required very large subsidy. Ford et al. (2007) showed that TGC is a market-based
2 mechanism without the need for government subsidies. Marchenko (2008) and Wȩdzik et al. (2017)
3 indicate that the TGCs provide a source of income for investors. Choi et al. (2018a) analysed the
4 economic efficiency of FiT and RPS in the South Korean, where FiT was implemented from 2002 to
5 2011 followed by an RPS since 2012 (Park and Kim 2018; Choi et al. 2018b). Choi concluded that RPS
6 was more efficient for PV from the government's perspective while from an energy producers’
7 perspective the FiT was more efficient. Some scholars proposed a policy combining FiT and RPS (Cory
8 et al. 2009). Kwon (2015) and del Río et al. (2017) concluded that both FiT and RPS are effective, but
9 policy costs are higher in RPSs than FiTs. RPS, REC trading and FiT subsidy could also be implemented
10 as complementary policies (Zhang et al. 2018).
11 Tenders are a fast spreading and effective instrument to attract and procure new generation capacity
12 from renewable energy sources (Bayer et al. 2018; Bento et al. 2020; Ghazali et al. 2020; Haelg 2020;
13 Batz T. and Musgens 2019). A support scheme based on tenders allows a more precise steering of
14 expansion and lower risk of excessive support (Gephart et al. 2017). Bento et al. (2020) indicated that
15 tendering is more effective in promoting additional renewable capacity comparing to other mechanisms
16 such as FiTs. It is also important to take into account the rebound effect in energy consumption by on-
17 site PV users, which might reduce up to one fifth of the carbon benefit of renewable energy (Deng and
18 Newton 2017).
19 Financing mechanisms for RES are particularly needed in developing countries. Most of the common
20 supporting mechanisms (FiT, RPSs, PPA, auctions, net metering, etc.) have been implemented in some
21 developing countries (Donastorg et al. 2017). Stable policies and an investment-friendly environment
22 are essential to overcome financing barriers and attract investors (Donastorg et al. 2017). Kimura et al.
23 (2016) identified the following elements as essential for fostering RES in developing countries:
24 innovative business models and financial mechanisms/structures; market creation through the
25 implementation of market-based mechanisms; stability of policies and renewable energy legislation;
26 technical assistance to reduce the uncertainty of renewable energy production; electricity market design,
27 which reflects the impact on the grid capacity and grid balancing; improved availability of financial
28 resources, in particular public, and innovative financial instruments, such as carbon financing (Park et
29 al. 2018; Kim and Park 2018; Lim et al. 2013); green bonds; public foreign exchange hedging facility
30 for renewable energy financing, credit lines; grants and guarantees..
31• The end-user will be at the centre as a key participant in the future electricity system (Zepter et al. 2019;
32 Lavrijssen and Carrillo Parra, 2017) providing flexibility, storage, energy productions, peer to peer
33 trading, electric vehicle charging. Zepter indicates that “the current market designs and business models
34 lack incentives and opportunities for electricity consumers to become prosumers and actively participate
35 in the market”. Klein et al. (2019) explore the policy options for aligning prosumers with the electricity
36 wholesale market, through price and scarcity signals. Policies should allow for active markets
37 participation of small prosumers (Brown et al. 2019; Zepter et al. 2019), local energy communities and
38 new energy market actors such as aggregators (Iria and Soares 2019; Brown et al. 2019). Energy
39 Communities are new important players in the energy transition (Sokołowski, 2020; Gjorgievski, et al.,
40 2021). Citizens and local communities can establish local energy communities, providing local RES
41 production to serve the community, alleviate energy poverty and export energy into the grid (DellaValle
42 and Sareen, 2020; Hahnel et al. 2020). Energy Communities have as primary purpose to provide
43 environmental, economic, or social community benefits by engaging in generation, aggregation, energy
44 storage, energy efficiency services and charging services for electric vehicles. Energy communities help
45 in increasing public acceptance and mobilise private funding. Demand response aggregators
46 (Mahmoudi et al., 2017; Henriquez at al., 2018) can aggregate load reductions by a group of consumers,
47 and sell the resulting flexibility to the electricity market (Zancanella P. et al. 2017). Regulatory
48 frameworks for electricity markets should allow demand response to compete on equal footing in energy
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1 markets and encourage new business models for the provision of flexibility to the electricity grid (Shen
2 et al., 2014). Renewable energy and sufficiency requirements could be included in building energy
3 codes and implemented in coordination with each other and with climate policies, e.g. carbon pricing
4 (Oikonomou et al. 2014).
5 9.9.6 Investment in building decarbonisation
6 As Section 9.6.3 points out, the incremental investment cost to decarbonise buildings at national level
7 is up to 3.5% GDP per annum during the next thirty years (the global GDP in 2019 was USD 88 trillion).
8 As the following figures illustrate, only a very small share of it is currently being invested, leaving a
9 very large investment gap still to address. The incremental capital expenditure on energy efficiency in
10 buildings has grown since AR5 to reach the estimated USD 193 billion in 2021; Europe was the largest
11 investing region, followed by the USA and China (Figure 9.21). The incremental capital expenditure
12 on renewable energy heat vice versa declined to reach USD 24 billion in this year; the leading investor
13 was China, followed by Europe (ibid). The total capital expenditure on distributed small-scale (less than
14 1MW) solar systems in 2019 was USD 52.1 billion, down from the peak of USD 71 billion in 2011;
15 most of this capacity is installed in buildings (Frankfurt School - UNEP Centre/BNEF 2020). The US
16 was the largest country market with USD 9.6 billion investment; notably USD 5 billion was deployed
17 in the Middle East and Africa (ibid). (IEA 2021b) provided an estimate of annual average incremental
18 investment needs in building sector decarbonation between 2026 and 2030 of USD 711 billion,
19 including USD 509 billion in building energy efficiency and USD 202 billion in renewable heat for
20 end-use and electrification in buildings. Such investment would allow being on track towards meeting
21 the goals of the WEO Net Zero Emissions Scenario, as presented in Box 9.2. To reach these levels, the
22 respective investment must grow from their average volumes in 2016-2020 factor 3.6 and 4.5
23 respectively. As the investment needs estimated by (IEA 2021b) are significantly lower the investment
24 intervals reported by bottom-up literature (Section 9.6.3), the actual investment gap is likely to be
25 higher.
26
27 Notes: (i) An energy efficiency investment is defined as the incremental spending on new energy-efficient equipment or the full cost of
28 refurbishments that reduce energy use. (ii) Renewable heat for end-use include solar thermal applications (for district, space, and water
29 heating), bioenergy and geothermal energy, as well as heat pumps. (iii) The investment in 2021 is an estimate.
30 Figure 9.21 Incremental capital expenditure on energy efficiency investment (left) and renewable heat in
31 buildings, 2015-2021
32 Source: IEA 2021b
33 9.9.7 Governance and Institutional Capacity
34 9.9.7.1 Governance
35 Multilevel and polycentric governance is essential for implementing sufficiency, energy efficiency and
36 renewable energies policies (IPCC, 2018). Policies can be implemented at different levels of
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1 government and decision making, international, national, regional, and local. Policies for building have
2 be adopted at national level (Enker and Morrison 2017), at state or regional level (Fournier et al. 2019),
3 or at city level (Trencher and van der Heijden 2019). Zhao et al. (2019) find that national policies are
4 instrumental in driving low carbon developments in buildings.
5 International agreements (Kyoto, Montreal/Kigali, Paris, etc.) play an important role in establishing
6 national energy-efficiency and renewable energy policies in several countries (Dhar et al. 2018; Bertoldi
7 2018). Under the Paris Agreement, some NDCs contain emission reduction targets for subsectors, e.g.,
8 buildings, policies for subsectors and energy efficiency and/or renewable targets (see also Cross-
9 Chapter Box 5 in Chapter 4). In the EU since 2007 climate and energy policies are part of a co-ordinated
10 policy package. EU Member States have prepared energy efficiency plans every three years and long
11 term renovation strategies for buildings (Economidou et al. 2020). Under the new Energy and Climate
12 Governance Regulation EU Member States have submitted at the end of 2020 integrated National
13 Energy and Climate Plans, including energy efficiency and renewable plans. (Oberthur, 2019; Schlacke
14 and Knodt, 2019). The integration of energy and climate change policies and their governance has been
15 analysed (von Lüpke and Well, 2020), highlighting the need of reinforcing the institutions,
16 anticipatory governance, the inconsistency of energy policies and the emerging multi-
17 level governance.
18 Some policies are best implemented at international level. Efficiency requirements for traded goods and
19 the associated test methods could be set at global level in order to enlarge the market, avoid technical
20 barriers to trade; reduce the manufacturers design and compliance costs. International standards could
21 be applied to developing countries when specific enabling conditions exist, particularly in regard to
22 technology transfer, assistance for capacity buildings and financial support. This would also reduce the
23 dumping of inefficient equipment in countries with no or lower efficiency requirements. An example is
24 the dumping of new or used inefficient cooling equipment in developing countries, undermining
25 national and local efforts to manage energy, environment, health, and climate goals. Specific regulations
26 can be put in place to avoid such environmental dumping, beginning with the “prior informed consent”
27 as in the Rotterdam Convention and a later stage with the adoption of minimum efficiency requirements
28 for appliances (Andersen et al. 2018; United Nations Environment Programme (UNEP) 2017). Dreyfus
29 et al. (2020a) indicates that global policies to promote best technologies currently available have the
30 potential to reduce climate emissions from air conditionings and refrigeration equipment by 210–460
31 GtCO2-eq by 2060, resulting from the phasing down of HFC and from improved energy efficiency.
32 Another example is the commitment by governments in promoting improvements in energy efficiency
33 of cooling equipment in parallel with the phasedown of HFC refrigerants enshrined in the Biarritz
34 Pledge for Fast Action on Efficient Cooling signed in 2019. The policy development and
35 implementation costs will be reduced as the technical analysis leading to the standard could be shared
36 among governments. However, it is important that local small manufacturing companies in developing
37 countries have the capacity to invest in updating production lines for meeting new stringent international
38 efficiency requirements.
39 Building energy consumption is dependent on local climate and building construction traditions,
40 regional and local government share an important role in promoting energy efficiency in buildings and
41 on-site RES, through local building energy codes, constructions permits and urban planning. In South
42 Korea, there is a green building certification system operated by the government, based on this, Seoul
43 has enacted Seoul's building standard, which includes more stringent requirements. Where it is difficult
44 to retrofit existing buildings, e.g., historical buildings, cities may impose target at district level, where
45 RES could be shared among buildings with energy positive buildings compensating for energy
46 consuming buildings. Local climate and urban plans could also contribute to the integration of the
47 building sector with the local transport, water, and energy sectors, requiring, for example, new
48 constructions in areas served by public transport, close to offices or buildings to be ready for e-mobility.
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1 Buildings GHG emission reduction shall also be considered in greenfield and brownfield developments
2 and urban expansion (Loo et al, 2017; Salviati and Ricciardo Lamonica., 2020), including co-benefis
3 (Zapata-Diomedi et al., 2019).
4 Energy efficiency, sufficiency, and renewable policies and measures will have a large impact on
5 different stakeholders (citizens, construction companies; equipment manufacturers; utilities, etc.),
6 several studies highlighted the importance of stakeholder consultation and active participation in policy
7 making and policy implementation (Vasileiadou and Tuinstra 2013; Ingold et al. 2020), including
8 voluntary commitments and citizen assemblies. In particular, energy users role will be transformed from
9 passive role to an active role, as outlined in the concept of energy citizenship (Campos and Marín-
10 González, 2020). The energy citizens needs and voice should therefore be included in policy processes
11 among traditional business players, such as incumbent centralised power generation companies and
12 utilities (Van Veelen, 2018). Architects and engineers play an important role in the decarbonisation of
13 buildings. The professional bodies can mandate their members support energy efficiency and
14 sufficiency. For example, the US AIA states in their code of ethics that architects must inform clients
15 of climate risks and opportunities for sustainability. The capacity and quality of workforce and building
16 construction, retrofit, and service firms are essential to execute the fast transition in building systems
17 (see also Cross-Chapter Box 12 in Chapter 16).
18 9.9.7.2 Institutional capacity
19 The concept of institutional capacity is increasingly connected with the issue of public governance,
20 emphasising the broad institutional context within which individual policies are adopted. Institutions
21 are durable and are sources of authority (formal or informal) structuring repeated interactions of
22 individuals, companies, civil society groups, governments, and other entities. Thus, institutional
23 capacity also represents a broader “enabling environment” which forms the basis upon which
24 individuals and organisations interact. In general terms, capacity is “the ability to perform functions,
25 solve problems and set and achieve objectives” (Fukuda-Parr et al. 2002). Institutional capacity is an
26 important element for regional sustainable development (Farajirad et al. 2015). The role and importance
27 of institutional capacity is fundamental in implementing the building decarbonisation. Central and local
28 governments, regulatory organisations, financial institutions, standardisation bodies, test laboratories,
29 building construction and design companies, qualified workforce and stakeholders are key players in
30 supporting the implementation of building decarbonisation.
31 Governments (from national to local) planning to introduce efficiency, RES, and sufficiency policies
32 needs technical capacity to set sectoral targets and design policies and introduce effective and
33 enforcement with adequate structure and resources for their implementation. Policies discussed and
34 agreed with stakeholders and based on impartial data and impact assessments, have a higher possibility
35 of success. Public authorities need technical and economics competences to understand complex
36 technical issues and eliminate the knowledge gap in comparison to private sector experts, human and
37 financial resources to design, implement, revise, and evaluate policies. The role of energy efficiency
38 policy evaluation needs to be expanded, including the assessment of the rebound effect (Vine et al.
39 2013). For developing countries international support for institutional capacity for policy development,
40 implementation and evaluation is of key importance for testing laboratory, standards institute,
41 enforcement and compliances technicians and evaluation experts. Thus, in development support,
42 addition to technology transfer, also capacity buildings for national and local authorities should be
43 provides. The Paris Agreement Article 11 aims at enhancing the capacity of decision-making
44 institutions in developing countries to support effective implementation.
45 Enforcement of policies is of key importance. Policies on appliance energy standards needs to establish
46 criteria for random checks and tests of compliance, establish penalties and sanctions for non-
47 compliance. For building code compliance there is the need to verify compliance after construction to
48 verify the consistence with building design (Vine et al. 2017). Often local authorities lack resources and
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1 technical capacity to carry out inspections to check code compliance. This issue is even more pressing
2 in countries and cities with large informal settlements, where buildings may not be respecting building
3 energy codes for safety and health.
4
5 9.10 Knowledge Gaps
6 Insights from regions, sectors, and communities
7 • Due to the dominating amount of literature from developed countries and rapidly developing
8 Asia (China), the evidence and therefore conclusions are limited for the developing world. In
9 particular, there is limited evidence on the potential and costs the countries of South-East Asia
10 and Developing Pacific, Africa, and Latin America and Caribbean.
11 • The contribution of indigenous knowledge in the evolvement of buildings is not well
12 appreciated. There is a need to understand this contribution and provide methodological
13 approaches for incorporation of indigenous knowledge.
14 • Analysis of emissions and energy demand trends in non-residential buildings is limited due to
15 the number of building types included in this category and the scarcity of data for each building
16 type. The use of new data gathering techniques such as machine learning, GIS combined with
17 digital technologies to fill in this data gap was not identified in the literature. Consideration of
18 embodied emissions from building stock growth has only recently entered the global scenario
19 literature, and more development is expected in this area.
20 Measures, potentials, and costs
21 • There is a lack of scientific reporting of case studies of exemplary buildings, specially from
22 developing countries. Also, there is a lack of identification of researchers on technologies with
23 the mitigation potential of such technologies, bringing a lack in quantification of that potential.
24 • There is limited evidence on sufficiency measures including those from behavioural energy
25 saving practices: updated categorisations, current adoption rates and willingness to adopt.
26 • There is limited evidence on circular and shared economy in buildings, including taxonomies,
27 potentials, current adoption rates and willingness to adopt
28 • Most of the literature on climate change impacts on buildings is focused on thermal comfort.
29 There is need for further research on climate change impacts on buildings structure, materials
30 and construction and the energy and emissions associated with those impacts. Also, more
31 studies that assess the role of passive energy efficiency measures as adaptation options are
32 needed. Finally, regional studies leave out in depth analyses of specific regions.
33 Feasibility and policies
34 • Applications of human centred profiles for targeted policy making and considering stages of
35 diffusion of innovation, that is: what works (motivation) for whom (different stakeholders, not
36 only households) and when (stages of market maturity)
37 • The multiple co-benefits of mitigation actions are rarely integrated into decision-making
38 processes. So, there is a need to further develop methodologies to quantify and monetise these
39 externalities as well as indicators to facilitate their incorporation in energy planning.
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1 • Policies for sufficiency have to be further analysed and tested in real situation, including ex
2 ante simulation and ex-post evaluation. The same is also valid for Personable (tradable) Carbon
3 Allowances.
4 Methods and models
5 • There is limited literature on the integration of behavioural measures and lifestyle changes in
6 modelling exercises
7 • Mitigation potential resulting from the implementation of sufficiency measures is not identified
8 in global energy/climate and building scenarios despite the growing literature on sufficiency.
9 At the best, mitigation potential from behaviour change is quantified in energy scenarios;
10 savings from structural changes and resource efficiency are not identified in the literature on
11 global and building energy models.
12 • The actual costs of the potential could be higher to rather optimistic assumptions of the
13 modelling literature, e.g., assuming a 2-3% retrofit rate, and even higher, versus the current 1%.
14 The uncertainty ranges of potential costs are not well understood.
15 • Despite a large number of exemplary buildings achieving very high performance in all parts of
16 the world and a growing amount of modelling literature on the potential, if these will penetrate
17 at scale, there is a lack of modelling literature assessing the costs of respective actions at
18 national, regional, and global level based on comprehensive cost assessments.
19 • There is a lack of peer-reviewed literature on investment gaps, which compares the investment
20 need in the building sector decarbonisation and recent investment flows into it estimated with
21 the same costing methodologies.
22
23 Frequently Asked Questions
24 FAQ 9.1 To which GHG emissions do buildings contribute?
25 There are three categories of GHG emissions from buildings:
26 i. direct emissions which are defined as all on-site fossil fuel or biomass-based combustion
27 activities (i.e., use of biomass for cooking, or gas for heating and hot water) and F-gas emissions
28 (i.e., use of heating and cooling systems, aerosols, fire extinguishers, soundproof)
29 ii. indirect emissions which occur off-site and are related to heat and electricity production
30 iii. embodied emissions which are related to extracting, producing, transforming, transporting, and
31 installing the construction material and goods used in buildings
32 In 2019, global GHG emissions from buildings were at 12 GtCO2-eq out of which 24% were direct
33 emissions, 57% were indirect emissions, and 18% were embodied emissions. More than 95% of
34 emissions from buildings were CO2 emissions, CH4 and N2O represented 0.08% each and emissions
35 from halocarbon contributed by 3% to global GHG emissions from buildings.
36
37 FAQ 9.2 What are the co-benefits and trade-offs of mitigation actions in buildings?
38 Mitigation actions in buildings generate multiple co-benefits (e.g., health benefits due to the improved
39 indoor and outdoor conditions, productivity gains in non-residential buildings, creation of new jobs
40 particularly at local level, improvements in social wellbeing etc.) beyond their direct impact on reducing
41 energy consumption and GHG emissions. Most studies agree that the value of these multiple benefits
42 is greater than the value of energy savings and their inclusion in economic evaluation of mitigation
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1 actions may improve substantially their cost-effectiveness. It is also worth mentioning that in several
2 cases the buildings sector is characterized by strong rebound effects, which could be considered as a
3 co-benefit in cases where the mechanisms involved provide faster access to affordable energy but also
4 a trade-off in cases where the external costs of increased energy consumption exceed the welfare
5 benefits of the increased energy service consumption, thus lowering the economic performance of
6 mitigation actions. The magnitude of these co-benefits and trade-offs are characterized by several
7 uncertainties, which may be even higher in the future as mitigation actions will be implemented in a
8 changing climate, with changing building operation style and occupant behaviour. Mitigation measures
9 influence the degree of vulnerability of buildings to future climate change. For instance, temperature
10 rise can increase energy consumption, which may lead to higher GHG emissions. Also, sea level rise,
11 increased storms and rainfall under future climate may impact building structure, materials and
12 components, resulting in increased energy consumption and household expenditure from producing and
13 installing new components and making renovations. Well-planned energy efficiency, sufficiency and
14 on-site renewable energy production can help to increase building resilience to climate change impacts
15 and reduce adaptation needs.
16
17 FAQ 9.3 Which are the most effective policies and measures to decarbonize the building sector?
18 Several barriers (information, financing, markets, behavioural, etc.) still prevents the decarbonisation
19 of buildings stock, despite the several co-benefits, including large energy savings. Solutions include
20 investments in technological solutions (e.g., insulation, efficient equipment, and low-carbon energies
21 and renewable energies) and lifestyle changes. In addition, the concept of sufficiency is suggested to be
22 promoted and implemented through policies and information, as technological solutions will be not
23 enough to decarbonise the building sector. Due to the different types of buildings, occupants, and
24 development stage there is not a single policy, which alone will reach the building decarbonisation
25 target. A range of policy instruments ranging from regulatory measures such as building energy code
26 for NZEBs and appliance standards, to market-based instruments (carbon tax, personal carbon
27 allowance, renewable portfolio standards, etc.), and information. Financing (grants, loans, performance
28 base incentives, pays as you save, etc.) is another key enabler for energy efficiency technologies and
29 on-site renewables. Finally, effective governance and strong institutional capacity are key to have an
30 effective and successful implementation of policies and financing.
31
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