Final Government Distribution                                    Chapter 11                                                IPCC AR6 WGIII

1    Table of Contents
2    Chapter 11:          Industry .................................................................................................................... 11-1
3      Executive summary........................................................................................................................ 11-4
4      11.1       Introduction and new developments ................................................................................. 11-7
5         11.1.1          About this chapter .................................................................................................... 11-7
6         11.1.2          Approach to understanding industrial emissions ..................................................... 11-7
7      11.2       New trends in emissions and industrial development..................................................... 11-11
8         11.2.1          Major drivers.......................................................................................................... 11-11
9         11.2.2          New trends in emissions ........................................................................................ 11-16
10        11.2.3          Industrial development patterns and supply chains (regional) ............................... 11-22
11     11.3       Technological developments and options....................................................................... 11-23
12        11.3.1          Demand for materials............................................................................................. 11-23
13        11.3.2          Material efficiency ................................................................................................. 11-25
14        11.3.3          Circular economy and industrial waste .................................................................. 11-27
15        11.3.4          Energy Efficiency .................................................................................................. 11-29
16        11.3.5          Electrification and fuel switching .......................................................................... 11-31
17        11.3.6          CCS, CCU, carbon sources, feedstocks, and fuels................................................. 11-35
18        11.3.7          Strategy interactions and integration ..................................................................... 11-38
19     11.4       Sector mitigation pathways and cross sector implications ............................................. 11-43
20        11.4.1          Sector specific mitigation potential and costs ........................................................ 11-43
21        11.4.2          Transformation pathways....................................................................................... 11-59
22        11.4.3          Cross sectorial interactions and societal pressure on industry ............................... 11-75
23        11.4.4          Links to climate change, mitigation, adaptation .................................................... 11-76
24     11.5       Industrial infrastructure, policy, and SDG contexts ....................................................... 11-77
25        11.5.1          Existing industry infrastructures ............................................................................ 11-77
26        11.5.2          Current industrial and broader policy context........................................................ 11-79
27        11.5.3          Co-benefits of Mitigation Strategies and SDGs..................................................... 11-80
28     11.6       Policy approaches and strategies .................................................................................... 11-83
29        11.6.1          GHG Prices and GHG Markets.............................................................................. 11-85
30        11.6.2          Transition pathways planning and strategies ......................................................... 11-87
31        11.6.3          Technological research, development, and innovation .......................................... 11-89
32        11.6.4          Market Pull ............................................................................................................ 11-91
33        11.6.5          Knowledge and capacity ........................................................................................ 11-97
34        11.6.6          Policy coherence and integration ........................................................................... 11-97
35        11.6.7          Roles and responsibilities ...................................................................................... 11-98
36     11.7       Knowledge gaps ........................................................................................................... 11-102

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1     Frequently Asked Questions ...................................................................................................... 11-102
2     References .................................................................................................................................. 11-104

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1    Executive summary
2    The Paris Agreement, the Sustainable Development Goals (SDGs) and the COVID-19 pandemic
3    provide a new context for the evolution of industry and mitigation of industry greenhouse gas
4    (GHG) emissions (high confidence). This chapter is focused on what is new since AR5. It emphasizes
5    the energy and emissions intensive basic materials industries and key strategies for reaching net zero
6    emissions. {11.1.1}
 7   Net zero CO2 emissions from the industrial sector are possible but challenging (high confidence).
 8   Energy efficiency will continue to be important. Reduced materials demand, material efficiency, and
 9   circular economy solutions can reduce the need for primary production. Primary production options
10   include switching to new processes that use low to zero GHG energy carriers and feedstocks (e.g.,
11   electricity, hydrogen, biofuels, and carbon capture and utilization (CCU) for carbon feedstock) and
12   carbon capture and storage (CCS) for remaining CO2 . These options require substantial scaling up of
13   electricity, hydrogen, recycling, CO2, and other infrastructure, as well as phase-out or conversion of
14   existing industrial plants. While improvements in the GHG intensities of major basic materials have
15   nearly stagnated over the last 30 years, analysis of historical technology shifts and newly available
16   technologies indicate these intensities can be reduced to net zero emissions by mid-century. {11.2, 11.3,
17   11.4}
18   Whatever metric is used, industrial emissions have been growing faster since 2000 than emissions
19   in any other sector, driven by increased basic materials extraction and production (high
20   confidence). GHG emissions attributed to the industrial sector originate from fuel combustion, process
21   emissions, product use and waste, which jointly accounted for 14.1 GtCO2-eq or 24% of all direct
22   anthropogenic emissions in 2019, second behind the energy transformation sector. Industry is a leading
23   GHG emitter - 20 GtCO2-eq or 34% of global emissions in 2019 - if indirect emissions from power and
24   heat generation are included. The share of emissions originating from direct fuel combustion is
25   decreasing and was 7 GtCO2-eq, 50% of direct industrial emissions in 2019. {11.2.2}
26   Global material intensity (in-use stock of manufactured capital, in tonnes per unit of GDP is
27   increasing (high confidence). In-use stock of manufactured capital per capita has been growing faster
28   than GDP per capita since 2000. Total global in-use stock of manufactured capital grew by 3.4% yr-1 in
29   2000–2019. At the same time, per capita material stocks in several developed countries have stopped
30   growing, showing a decoupling from GDP per capita. {11.2.1, 11.3.1}
31   Plastic is the material for which demand has been growing the strongest since 1970 (high
32   confidence). The current >99% reliance on fossil feedstock, very low recycling, and high emissions
33   from petrochemical processes is a challenge for reaching net zero emissions. At the same time, plastics
34   are important for reducing emissions elsewhere, for example, light-weighting vehicles. There are as yet
35   no shared visions for fossil-free plastics, but several possibilities. {}
36   Scenario analyses show that significant cuts in global GHG emissions and even close to net zero
37   emissions from GHG intensive industry (e.g., steel, plastics, ammonia, and cement) can be
38   achieved by 2050 by deploying multiple available and emerging options (medium confidence).
39   Cutting industry emissions significantly requires a reorientation from the historic focus on important
40   but incremental improvements (e.g., energy efficiency) to transformational changes in energy and
41   feedstock sourcing, materials efficiency, and more circular material flows. {11.3, 11.4}
42   Key climate mitigation options such as materials efficiency, circular material flows and emerging
43   primary processes, are not well represented in climate change scenario modelling and integrated
44   assessment models, albeit with some progress in recent years (high confidence). The character of
45   these interventions (e.g., appearing in many forms across complex value chains, making cost estimates
46   difficult) combined with the limited data on new fossil free primary processes help explain why they

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1    are less represented in models than, for example, CCS. As a result, overall mitigation costs and the need
2    for CCS may be overestimated. {}
3    Electrification is emerging as a key mitigation option for industry (high confidence). Electricity is
4    a versatile energy carrier, potentially produced from abundant renewable energy sources or other low
5    carbon options; regional resources and preferences will vary. Using electricity directly, or indirectly via
6    hydrogen from electrolysis for high temperature and chemical feedstock requirements, offers many
7    options to reduce emissions. It also can provide substantial grid balancing services, for example through
8    electrolysis and storage of hydrogen for chemical process use or demand response. {11.3.5}
 9   Carbon is a key building block in organic chemicals, fuels and materials and will remain
10   important (high confidence). In order to reach net zero CO2 emissions for the carbon needed in society
11   (e.g., plastics, wood, aviation fuels, solvents, etc.), it is important to close the use loops for carbon and
12   carbon dioxide through increased circularity with mechanical and chemical recycling, more efficient
13   use of biomass feedstock with addition of low GHG hydrogen to increase product yields (e.g., for
14   biomethane and methanol), and potentially direct air capture of CO2 as a new carbon source. {11.3,
15   11.4.1}
16   Production costs for very low to zero emissions basic materials may be high but the cost for final
17   consumers and the general economy will be low (medium confidence). Costs and emissions reductions
18   potential in industry, and especially heavy industry, are highly contingent on innovation,
19   commercialization, and market uptake policy. Technologies exist to take all industry sectors to very low
20   or zero emissions, but require 5–15 years of intensive innovation, commercialization, and policy to
21   ensure uptake. Mitigation costs are in the rough range of 50–150 USD· tCO2-eq-1, with wide variation
22   within and outside this band. This affects competitiveness and requires supporting policy. Although
23   production cost increases can be significant, they translate to very small increases in the costs for final
24   products, typically less than a few percent depending on product, assumptions, and system boundaries.
25   {}
26   There are several technological options for very low to zero emissions steel, but their uptake will
27   require integrated material efficiency, recycling, and production decarbonisation policies (high
28   confidence). Material efficiency can potentially reduce steel demand by up to 40% based on design for
29   less steel use, long life, reuse, constructability, and low contamination recycling. Secondary production
30   through high quality recycling must be maximized. Production decarbonisation will also be required,
31   starting with the retrofitting of existing facilities for partial fuel switching (e.g., to biomass or hydrogen),
32   CCU and CCS, followed by very low and zero emissions production based on high-capture CCS or
33   direct hydrogen, or electrolytic iron ore reduction followed by an electric arc furnace. {11.3.2,}
34   There are several current and near horizon options to greatly reduce cement and concrete
35   emissions. Producer, user, and regulator education, as well as innovation and commercialization
36   policy are needed (medium confidence). Cement and concrete are currently overused because they are
37   inexpensive, durable, and ubiquitous, and consumption decisions typically do not give weight to their
38   production emissions. Basic material efficiency efforts to use only well-made concrete thoughtfully and
39   only where needed (e.g., using right-sized, prefabricated components) could reduce emissions by 24–
40   50% through lower demand for clinker. Cementitious material substitution with various materials (e.g.,
41   ground limestone and calcined clays) can reduce process calcination emissions by up to 50% and
42   occasionally much more. Until a very low GHG emissions alternative binder to Portland cement is
43   commercialized, which does not look promising in the near to medium term, CCS will be essential for
44   eliminating the limestone calcination process emissions for making clinker, which currently represent
45   60% of GHG emissions in best available technology plants. {11.3.2, 11.3.6,}
46   While several technological options exist for decarbonizing the main industrial feedstock
47   chemicals and their derivatives, the costs vary widely (high confidence). Fossil fuel-based feedstocks

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1    are inexpensive and still without carbon pricing, and their biomass- and electricity-based replacements
2    will likely be more expensive. The chemical industry consumes large amounts of hydrogen, ammonia,
3    methanol, carbon monoxide, ethylene, propylene, benzene, toluene, and mixed xylenes & aromatics
4    from fossil feedstock, and from these basic chemicals produces tens of thousands of derivative end-use
5    chemicals. Hydrogen, biogenic or air-capture carbon, and collected plastic waste for the primary
6    feedstocks can greatly reduce total emissions. Biogenic carbon feedstock is likely to be limited due to
7    competing land-uses. {}
 8   Light industry and manufacturing can be largely decarbonized through switching to low GHG
 9   fuels (e.g., biofuels and hydrogen) and electricity (e.g., for electrothermal heating and heat pumps)
10   (high confidence). Most of these technologies are already mature, for example for low temperature heat,
11   but a major challenge is the current low cost of fossil methane and coal relative to low and zero GHG
12   electricity, hydrogen, and biofuels. {}
13   The pulp and paper industry has significant biogenic carbon emissions but relatively small fossil
14   carbon emissions. Pulp mills have access to biomass residues and by-products and in paper mills
15   the use of process heat at low to medium temperatures allows for electrification (high confidence).
16   Competition for feedstock will increase if wood substitutes for building materials and petrochemicals
17   feedstock. The pulp and paper industry can also be a source of biogenic carbon dioxide and carbon for
18   organic chemicals feedstock and carbon dioxide removal (CDR) using CCS. {}
19   The geographical distribution of renewable resources has implications for industry (medium
20   confidence). The potential for zero emission electricity and low-cost hydrogen from electrolysis
21   powered by solar and wind, or hydrogen from other very low emission sources, may reshape where
22   currently energy and emissions intensive basic materials production is located, how value chains are
23   organized, trade patterns, and what gets transported in international shipping. Regions with bountiful
24   solar and wind resources, or low fugitive methane co-located with CCS geology, may become exporters
25   of hydrogen or hydrogen carriers such as methanol and ammonia, or home to the production of iron and
26   steel, organic platform chemicals, and other energy intensive basic materials. {11.2; 11.4; Box 11.1}
27   The level of policy maturity and experience varies widely across the mitigation options (high
28   confidence). Energy efficiency is a well-established policy field with decades of experience from
29   voluntary and negotiated agreements, regulations, energy auditing and demand side-management
30   (DSM) programs (see AR5). In contrast, materials demand management and efficiency are not well
31   understood and addressed from a policy perspective. Barriers to recycling that policy could address are
32   often specific to the different material loops (e.g., copper contamination for steel and lack of
33   technologies or poor economics for plastics) or waste management systems. For electrification and fuel
34   switching the focus has so far been mainly on innovation and developing technical supply-side solutions
35   rather than creating market demand. {11.5.2, 11.6}
36   Industry has so far largely been sheltered from the impacts of climate policy and carbon pricing
37   due to concerns for competitiveness and carbon leakage (high confidence). New industrial
38   development policy approaches needed for realising a transition to net zero GHG emissions are
39   emerging. The transition requires a clear direction towards net zero, technology development, market
40   demand for low-carbon materials and products, governance capacity and learning, socially inclusive
41   phase-out plans, as well as international coordination of climate and trade policies. It requires
42   comprehensive and sequential industrial policy strategies leading to immediate action as well as
43   preparedness for future decarbonisation, governance at different levels (from international to local) and
44   integration with other policy domains. {11.6}

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1    11.1 Introduction and new developments
2    11.1.1 About this chapter
 3   AR5 was published in 2014. The Paris Agreement and the 17 SDGs were adopted in 2015. An increasing
 4   number of countries have since announced ambitions to be carbon neutral by 2045-2060. The COVID-
 5   19 pandemic shocked the global economy in 2020 and motivated economic stimulus with demands for
 6   green recovery and concerns for economic security. All this has created a new context and a growing
 7   recognition that all industry, including the energy and emissions intensive industries, need to reach net
 8   zero GHG emissions. There is an ongoing mind shift around the opportunities to do so, with
 9   electrification and hydrogen emerging among key mitigation options as a result of renewable electricity
10   costs falling rapidly. On the demand side there has been renewed attention to end-use demand, material
11   efficiency and more and better-quality recycling measures. This chapter takes its starting point in this
12   new context and emphasizes the need for deploying innovative processes and practices in order to limit
13   the global warming to 1.5ºC or 2ºC (IPCC 2018a).
14   The industrial sector includes ores and minerals mining, manufacturing, construction and waste
15   management. It is the largest source of global GHG and CO2 emissions, which include direct and
16   indirect fuel combustion related emissions, emissions from industrial processes and products use, as
17   well as from waste. This chapter is focused on heavy industry - the high temperature heat and process
18   emissions intensive basic materials industries that account for 65% of industrial GHG and over 70% of
19   industrial CO2 emissions (waste excluded), where deployment of near‐zero emissions technologies can
20   be more challenging due to capital intensity and equipment lifetimes compared with other
21   manufacturing industries. The transition of heavy industries to zero emissions requires supplementing
22   the traditional toolkit of energy and process efficiency, fuel switching, electrification, and
23   decarbonisation of power with material end-use demand management and efficiency, circular economy,
24   fossil-free feedstocks, CCU, and CCS. Energy efficiency was extensively treated in AR5 and remains a
25   key mitigation option. This chapter is focused mainly on new options and developments since AR5,
26   highlighting measures along the whole value chains that are required to approach zero emissions in
27   primary materials production.
29   11.1.2 Approach to understanding industrial emissions
30   The Kaya-identity offers a useful tool of decomposing emission sources and their drivers, as well as of
31   weighing the mitigation options. The one presented below (Equation 11.1) builds on the previous
32   assessments (IPCC 2014, 2018b; Hoegh-Guldberg et al. 2018), and reflect a material stock-driven
33   services-oriented vision to better highlight the growing importance of industrial processes (dominated
34   emissions increments in 2010-2019), product use and waste in driving emissions. Services delivery
35   (nutrition, shelter, mobility, education, etc., see chapter 5 for more detail) not only requires energy and
36   materials flows (fuels, food, feed, fertilizers, packaging, etc.), but also material stocks (buildings, roads,
37   vehicles, machinery, etc.), the mass of which has already exceeded 1000 Gtonnes (Krausmann et al.
38   2018). As material efficiency appears to be an important mitigation option, material intensity or
39   productivity (material extraction or consumption versus GDP (Hertwich et al. 2020; Oberle et al. 2019))
40   is reflected in the identity with two dimensions: as material stock intensity of GDP (tonnes per dollar)
41   and material intensity of building and operating accumulated in-use stock.1 For sub-global analysis the
42   ratio of domestically used materials to total material production becomes important to reflect outsourced

     FOOTNOTE1 Accumulated material stock initially was introduced in the analysis of past trends (Krausmann et
     al. 2018; Wiedenhofer et al. 2019), but recently it was incorporated in different forms in the long-term projections
     for the whole economy (Krausmann et al. 2020) and for some sectors (buildings and cars in Hertwich et al. (2020))
     with a steadily improving regional resolution (Krausmann et al. 2020).

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1    materials production and distinguish between territorial and consumption-based emissions. The identity
2    for industry differs significantly from that for sectors with where combustion emissions dominates
3    (Lamb et al. 2021).
4    Recent progress in data availability that allows the integration of major emission sources along with
5    socio-economic metabolism, material flows and stock analysis enriches the identity for industry from a
6    perspective of possible policy interventions (Bashmakov 2021):
                       𝑮𝑫𝑷 𝑴𝑺𝒕𝒐𝒄𝒌 𝑴𝑷𝑹 + 𝑴𝑺𝑬              𝑬        (𝑮𝑯𝑮𝒆𝒅 + 𝑮𝑯𝑮𝒆𝒊𝒏𝒅)    𝑮𝑯𝑮𝒐𝒕𝒉
9      𝑮𝑯𝑮 = 𝑷𝑶𝑷 ∙        ∙      ∙⌊         ∙ 𝑫𝒎 ∙ (            ∙                   +           )⌋
                       𝑷𝑶𝑷 𝑮𝑫𝑷      𝑴𝑺𝒕𝒐𝒄𝒌          (𝑴𝑷𝑹 + 𝑴𝑺𝑬)           𝑬           𝑴𝑷𝑹 + 𝑴𝑺𝑬
10                                                  Equation 11.1
           Variables                             Factors                           Policies and drivers
             𝑷𝑶𝑷            population                                          demographic policies
                            services (expressed via GDP – final consumption
             𝑮𝑫𝑷                                                                sufficiency and demand
                            and investments needed to maintain and expand
             𝑷𝑶𝑷                                                                management (reduction)
                            stock) per capita

                                                                                                              Demand decarbonization
                            material stock (MStock - accumulated in-use
           𝑴𝑺𝒕𝒐𝒄𝒌                                                               material stock efficiency
                            stocks of materials embodied in manufactured
            𝑮𝑫𝑷                                                                 improvement
                            fixed capital) intensity of GDP
                            material inputs (both virgin (primary materials
                                                                                material efficiency,
         𝑴𝑷𝑹 + 𝑴𝑺𝑬          extraction, MPR) and recycled (secondary
                                                                                substitution and circular
          𝑴𝑺𝒕𝒐𝒄𝒌            materials use, MSE)) per unit of in-use material
                                                                                trade policies including
                            share of allocated emissions – consumption versus
                                                                                carbon leakage issues

             𝑫𝒎             production emissions accounting (valid only for
                                                                                (localization versus
                            sub-global levels)*
                            sum of energy use for basic material production     energy efficiency of basic
                            (Em), processing and other operational industrial   materials production and
        (𝑴𝑷𝑹 + 𝑴𝑺𝑬)
                            energy use (Eoind) per unit of material inputs      other industrial processes
                                                                                electrification, fuel         Production decarbonization
                            direct (GHGed) and indirect (GHGeind)
      (𝑮𝑯𝑮𝒆𝒅 + 𝑮𝑯𝑮𝒆𝒊𝒏𝒅)                                                         switching, and energy
                        combustion-related industrial emissions per unit
              𝑬                                                                 decarbonisation (hydrogen,
                            of energy
                                                                                feedstock decarbonisation
                            emissions from industrial processes and product
          𝑮𝑯𝑮𝒐𝒕𝒉                                                                (hydrogen), CCUS-
                            use, waste, F-gases, indirect nitrogen emissions
         𝑴𝑷𝑹 + 𝑴𝑺𝑬                                                              industrial processes, waste
                            per unit of produced materials
                                                                                and F-gases management

13   * Dm=1, when territorial emission is considered, and Dm equals the ratio of domestically used materials
14   to total material production for the consumption-based emission accounting). CBAM – carbon boarder
15   adjustment mechanism
17   Factors in (Equation 11.1) are interconnected by either positive or negative feedbacks: scrap-based
18   production or light weighing improves operational energy efficiency, while growing application of
19   carbon capture, use and storage (CCUS) brings it down and increase material demands (Hertwich et al.
20   2019; IEA 2020a, 2021a). There are different ways to disaggregate Equation 11.1: by industrial
21   subsectors (Bashmakov 2021); by reservoirs of material stock (buildings, infrastructure, vehicles,
22   machinery and appliances, packaging, etc.); by regions and countries (where carbon leakage becomes

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1    relevant); by products and production chains (material extraction, production of basic materials, basic
2    materials processing, production of final industrial products); by traditional and low carbon technologies
3    used; and by stages of products’ lives including recycling.
 4   An industrial transition to net zero emissions is possible when the three last multipliers in Equation 11.1
 5   (in square parentheses) are approaching zero. Contributions from different drivers (energy efficiency,
 6   low carbon electricity and heat, material efficiency, switching to low carbon feedstock and CCUS) to
 7   this evolution vary with time. Energy efficiency dominates in the short- and medium-term and
 8   potentially long-term (in the range of 10-40% by 2050) (Crijns-Graus et al. 2020; IEA 2020a; IPCC
 9   2018a), but for deep decarbonisation trajectories contributions from the other drivers steadily grow, as
10   the share of non-energy sources in industrial emissions rises and new technologies to address mitigation
11   from these sources mature (Material Economics 2019; CEMBUREAU 2020; BPS 2020; Hertwich et al.
12   2020, 2019; IEA 2021a, 2020a; Saygin and Gielen 2021) (Figure 11.1).

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2   Figure 11.1 Stylized composition and contributions from different drivers to the transition of industry to
3                                             net zero emissions


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1    11.2 New trends in emissions and industrial development
2    11.2.1 Major drivers
3    The use of materials is deeply coupled with economic development and growth. For centuries, humanity
4    has been producing and using hundreds of materials (Ashby 2012), the diversity of which skyrocketed
5    in the recent half-century to achieve the desired performance and functionality of multiple products
6    (density; hardness; compressive strength; melting point, resistance to mechanical and thermal shocks
7    and to corrosion; transparency; heat- or electricity conductivity; chemical neutrality or activity, to name
8    a few). New functions drive the growth of material complexity of products; for example, a modern
9    computer chip embodies over 60 different elements (Graedel et al. 2015).
10   Key factors driving up industrial GHG emissions since 1900 include population and per capita GDP,
11     while energy efficiency and non-combustion GHG emissions intensity (from industrial processes and
12   waste) has been pushing it down. Material efficiency factors – material stock intensity of GDP and ratio
13   of extraction, processing and recycling of materials per unit of built capital along with combustion-
14   related emissions intensity factors and electrification – were cyclically switching their contributions
15   with relatively limited overall impact. Growing recycling allowed for replacement of some energy
16   intensive virgin materials and thus contributed to mitigation. In 2014–2019, a combination of these
17   drivers allowed for a slowdown in the growth of industrial GHG emissions to below 1% (Figure 11.2
18   and Table 11.1), while to match a net zero emissions trajectory it should decline by 2% yr-1 in 2020-
19   2030 and by 8.9% yr-1 in 2030–2050 (IEA 2021a).
20   There are two major concepts of material efficiency (ME). The broader one highlights demand
21   reduction via policies promoting more intensive use, assuming sufficient (excl. luxury) living space or
22   car ownership providing appropriate service levels – housing days or miles driven and life-time
23   extension (Hertwich et al. 2019, 2020). This approach focuses on dematerialization of society
24   (Lechtenböhmer and Fischedick 2020), where a “dematerialization multiplier” (Pauliuk et al. 2021)
25   limits both material stock and GDP growth, as progressively fewer materials are required to build and
26   operate the physical in-use stock to deliver sufficient services. According to IRP (2020), reducing floor
27   space demand by 20% via shared and smaller housing compared to the reference scenario would
28   decrease Group of Seven (G7) countries’ GHG emissions from the material-cycle of residential
29   construction up to 70% in 2050. The narrower concept ignores demand and sufficiency aspects and
30   focuses on supply chains considering ME as less basic materials use to produce a certain final product,
31   for example, a car or meter squared of living space (OECD 2019a; IEA 2020a). No matter if the broader
32   or the narrower concept of ME is applied, in 1970-2019 it did not contribute much to the decoupling of
33   industrial emissions from GDP. This is expected to change in the future (Figure 11.2).

     FOOTNOTE2 In 2020 this factor played on the reduction side as the Covid-19 crisis led to a global decline in
     demand for basic materials, respective energy use and emissions by 3-5 % (IEA 2020a).

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 2     Figure 11.2 Average annual growth rates of industrial sector GHG emissions and drivers. 1900–2019.
 3   Before 1970, GHG emission (other) is limited to that from cement production. Waste emission is excluded.
 4       Primary material extraction excludes fuels and biomass. Presented factors correspond directly to
 5                                                 Equation 11.1
 6   Sources: population before 1950 and GDP before 1960: Maddison Project (2018); population from 1950 to
 7       1970: UN (2015); population and GDP for 1960–2020: World Bank (2021); data on material stock,
 8   extraction, and use of secondary materials: Wiedenhofer et al. (2019); data on material extraction: UNEP
 9   and IRP (2020); industrial energy use for 1900–1970: IIASA (2018), for 1971–2019: IEA (2021b); data on
10   industrial GHG emissions for 1900–1970: CDIAC (2017); for 1970–2019: Crippa et al. (2021) and Minx et
11                                                   al., (2021)

13   Material efficiency analysis mostly uses material intensity or productivity indicators, which compare
14   material extraction or consumption with GDP (Oberle et al. 2019; Hertwich et al. 2020). Those
15   indicators are functions of material stock intensity of GDP (tonnes per dollar) and material intensity
16   of building and operating accumulated in-use stock. Coupling services or GDP with the built stock
17   allows for a better evaluation of demand for primary basic materials (Cao et al. 2017; Liu et al. 2013;
18   Liu and Müller 2013; Müller et al. 2011; Pauliuk et al. 2013a; Krausmann et al. 2020; Hertwich et al.
19   2020; Wiedenhofer et al. 2019). Since 1970 material stock growth driven by industrialization and
20   urbanization slightly exceeded that of GDP and there was no decoupling,3 so in Kaya-like identities
21   material stock may effectively replace GDP. There are different methods to estimate the former (see
22   reviews in Pauliuk et al. (2015, 2019) and Wiedenhofer et al. (2019), the results of which are presented
23   for major basic materials with some geographical resolution (Pauliuk et al. 2013a; Liu and Müller 2013)
24   or globally (Graedel et al. 2011; Krausmann et al. 2018; Geyer et al. 2017; International Aluminium
25   Institute 2021a; Pauliuk et al. 2019; Wiedenhofer et al. 2019).

     FOOTNOTE3 This conclusion is also valid separately for developed countries, rest of the world, and for China,
     when adjusted GDP for this country is used (Krausmann et al. 2020).

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 1   For a subset of materials, such as solid wood, paper, plastics, iron/steel, aluminium, copper, other
 2   metals/minerals, concrete, asphalt, bricks, aggregate, and glass, total in-use stock escalated from 36
 3   Gtonnes back in 1900 to 186 Gtonnes in 1970, 572 Gtonnes in 2000, and 960 Gtonnes in 2015, and by
 4   2020 it exceeded 1,100 Gtonnes, or 145 tonnes per capita (Krausmann et al. 2018, 2020; Wiedenhofer
 5   et al. 2019). In 1900–2019, the stock grew 31-fold, which is strongly coupled with GDP growth (36-
 6   fold). As the UK experience shows, material stock intensity of GDP may ultimately decline after
 7   services fully dominate GDP, and this allows for material productivity improvements to achieve
 8   absolute reduction in material use, as stock expansion slows down (Streeck et al. 2020). While the
 9   composition of basic materials within the stock of manufactured capital was evolving significantly,
10   overall stock use associated with a unit of GDP has been evolving over the last half-century in a quite
11   narrow range of 7.7–8.6 t per 1000 USD (2017 PPP) showing neither signs of decoupling from GDP,
12   nor saturation as of yet. Mineral building materials (concrete, asphalt, bricks, aggregate, and glass)
13   dominate the stock volume by mass (94.6% of the whole stock, with the share of concrete alone standing
14   at 43.5%), followed by metals (3.5%) and solid wood (1.4%). The largest part of in-use stock of our
15   ‘cementing societies’ Cao et al. (2017) is constituted by concrete: about 417 Gt in 2015 Krausmann et
16   al. (2018) extrapolated to 478 Gt (65 tonnes per capita) in 2018, which contains about 88 Gt of cement4.
17   The iron and steel stock is assessed at 25-35 Gtonnes (Gielen et al. 2020; Wang et al. 2021; Wiedenhofer
18   et al. 2019), while the plastics stock reached 2.5-3.2 Gtonnes (Geyer et al. 2017; Wiedenhofer et al.
19   2019; Saygin and Gielen 2021) and the aluminium stock approached 1.1 Gtonnes (International
20   Aluminium Institute 2021a), or just 0.1% of the total. In sharp contrast to global energy intensity, which
21   has more than halved since 1900 (Bashmakov 2019), in 2019 material stock intensity (in-use stock of
22   manufactured capital per GDP) was only 14% below the 1900 level, but 15% above the 1970 level. In-
23   use stock per capita has been growing faster than GDP per capita since 2000 (Figure 11.3). The growth
24   rate of total in-use stock of manufactured capital was 3.8% in 1971-2000 and 3.5% in 2000-2019, or
25   32-35 Gt·yr-1, to which concrete and aggregates contributed 88%. Recent demand for stockbuilding
26   materials was 51-54 Gt·yr-1, to which recycled materials recently contributed only about 10% of material
27   input. About 46-49 Gtonnes·yr-1 was virgin inputs, which after accounting for processing waste and
28   short-lived products (over 8 Gtonnes·yr-1) scale up to 54-58 Gtonnes·yr-1 of primary extraction
29   (Krausmann et al. 2017, 2018; UNEP and IRP 2020). The above indicates that we have only begun to
30   exploit the potential for recycling and circularity more broadly.


     FOOTNOTE4 Cement stock for 2014 was estimated at 75 Gtonnes (Cao et al. 2020).

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1      Figure 11.3 Raw natural materials extraction since 1970. In windows: left - growth of population, GDP
2     and basic materials production (1990=100) in 1990-2020; right - production of major basic materials and
3      in-use stock per capita versus income level (1900–2018, brown dots are for 2000–2018). The regressions
4     provided show that for more recent years elasticity of material stock to GDP was greater than unity, comparing
5                                        with the lower unity in preceding years.
6    Source: Developed based on IEA (2020b); Maddison Project (2018); UNEP and IRP (2020); Wiedenhofer et al.
7    (2019); World Steel Association (2021); International Aluminium Institute (2021a); Statista (2021a,b); World
8    Bank (2021); U.S. Geological Survey (2021).

10   Total extraction of all basic materials (including biomass and fuels) in 2017 reached 92 Gtonnes·yr-1,
11   which is 13 times above the 1900 level (Figure 11.3).5 When recycled resources are added, total material
12   inputs exceed 100 Gtonnes (Circle Economy 2020). In Equation 11.1 MPR represents only material
13   inputs to the stock, excluding dissipative use –biomass (food and feed) and combusted fuels. Total
14   extraction of stock building materials (metal ores and non-metallic minerals) in 2017 reached 55
15   Gtonnes·yr-1.6 In 1970–2018, it grew 4.3-fold and the ratio of MPR to accumulated in-use capital has
16   nearly been constant since 1990 along with ratio to GDP (Figure 11.3).
17   End-of-life waste from accumulated stocks along with (re)-manufacturing and construction waste is
18   assessed at 16 Gtonnes·yr-1 in 2014 and can be extrapolated in 2018 to 19 Gtonnes·yr-1 (Krausmann et
19   al. 2018; Wiedenhofer et al. 2019), or 1.8% from stock of manufactured capital. Less than 6 Gtonnes·yr-
20     was recycled and used to build the stock (about 10% of inputs7). While the circularity gap is still large,
21   and limited circularity was engineered into accumulated stocks,8 material recycling mitigated some
22   GHG emissions by replacing energy intensive virgin materials.9 When the stock saturates, in closed
23   material loops the end-of-life materials waste has to be equal to material input, and primary production
24   therefore has to be equal to end-of-life waste multiplied by unity minus recycling rate. When the latter
25   grows, as the linear metabolism is replaced with the circular one, the share of primary materials
26   production in total material input declines.
27   Recycling rates for metals are higher than for other materials: the end-of-life scrap input ratio for 13
28   metals is over 50%, and stays in the range 25–50% for another ten, but even for metals recycling flows
29   fail to match the required inputs (Graedel et al. 2011). Globally, despite overall recycling rates being at
30   85%, the all scrap ratio for steel production in recent years stays close to 35–38% (IEA 2021b; Gielen
31   et al. 2020) ranging from 22% in China (only 10% in 2015) to 69% in the US and to 83% in Turkey
32   (BIR 2020). For end-of-life scrap this ratio declined from 30% in 1995-2010 to 21–25% after 2010
33   (Gielen et al. 2020; Wang et al. 2021).
34   For aluminium, the share of scrap-based production grew from 17% in 1962 to 34% in 2010 and
35   stabilized at this level till 2019, while the share of end-of-life scrap grew from 1.5% in 1962 to nearly
36   20% in 2019 (International Aluminium Institute 2021a). The global recycling (mostly mechanical) rate

     FOOTNOTE5 IRP (2020) estimate 2017 material extraction at 94 Gtonnes·yr-1.
     FOOTNOTE6 It approaches 60 Gtonnes·yr-1 after construction and furniture wood and feedstock fuels are added
     (Krausmann et al. 2018; UNEP and IRP 2020; Wiedenhofer et al. 2019).
     FOOTNOTE7 Mayer et al. (2019) found that in 2010-2014 secondary to primary materials ratio for the EU-28 was
     slightly below 9%,
     FOOTNOTE8 According to Circle Economy (2020) 8.6 Gtonnes·yr-1 or 8.6% of total inputs for all resources.
     FOOTNOTE 9 Environmental impacts of secondary materials are much (up to an order of magnitude) lower
     compared to primary materials (OECD 2019a; Wang et al. 2021; IEA 2021a) , but to enable and mobilize
     circularity benefits it requires social system and industrial designing transformation (Oberle et al. 2019).

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1    for plastics is only 9–10%10 (Geyer et al. 2017; Saygin and Gielen 2021) and that for paper progressed
2    from 34% in 1990 to 44% in 2000 and to over 50% in 2014–2018 (IEA 2020b).
 3   The limited impacts of material efficiency factors on industrial GHG emissions trends reflect the lack
 4   of integration of material efficiency in energy and climate policies which partly results from the
 5   inadequacy of monitored indicators to inform policy debates and set targets;11 lack of high-level political
 6   focus and industrial lobbying; uncoordinated policy across institutions and sequential nature of decision-
 7   making along supply chains; carbon pricing policy lock-in with upstream sectors failing to pass carbon
 8   costs on to downstream sectors (due to compensation mechanisms to reduce carbon leakage) and so
 9   have no incentives to exploit such options as light-weighting, reusing, re-manufacturing, recycling,
10   diverting scrap, extending product lives, using products more intensely, improving process yields, and
11   substituting materials (Skelton and Allwood 2017; Gonzalez Hernandez et al. 2018b; Hilton et al. 2018).
12   Poor progress with material efficiency is part of the reason why industrial GHG emissions are perceived
13   as ‘hard to abate’, and many industrial low-carbon trajectories to 2050 leave up to 40% of emissions in
14   place (Material Economics 2019; IEA 2021a). The importance of this factor activation rises as in-use
15   material stock is expected to scale up by a factor of 2.2–2.7 to reach 2215–2720 Gtonnes by 2050
16   (Krausmann et al. 2020). Material extraction in turn is expected to rise to 140–200 Gtonnes·yr-1 by 2060
17   (Hertwich et al. 2020; OECD 2019a) providing unsustainable pressure on climate and environment and
18   calling for fundamental improvements in material productivity.
19   In 2014–2019, the average annual growth rate (AAGR) of global industrial energy use was 0.4%
20   compared to 3.2% in 2000–2014, following new policies and trends, particularly demonstrated by
21   China12 (IEA 2020b,d). Whatever metric is applied, industry (coal transformation, mining, quarrying,
22   manufacturing and construction) driven mostly by material production, dominates global energy
23   consumption. About two fifths of energy produced globally goes to industry, directly or indirectly.
24   Direct energy use (including energy used in coal transformation) accounts for nearly 30% of total final
25   energy consumption. When supplemented by non-energy use, the share for the post AR5 period (2015–
26   2019) stands on average close to 40% of final energy consumption, and at 28.5% of primary energy
27   use.13 With an account of indirect energy use for the generation of power and centralized heat to be
28   consumed in industry, the latter scales up to 37%. Industrial energy use may be split by: material
29   production and extraction (including coal transformation) 51% on average for 2015-2019, non-energy
30   use (mostly chemical feedstock) 22%14, and other energy use (equipment, machinery, food and tobacco,
31   textile, leather etc.) 27%. Energy use for material production and feedstock15 makes about three quarters
32   (73%) of industrial energy consumption and is responsible for 77% of its increment in 2015-2019 (based
33   on IEA (2021a)).
34   For over a century industrial energy efficiency improvements have partially offset growth in GHG
35   emissions. Industrial energy use per ton of extracted materials (ores and building materials as a proxy

     FOOTNOTE10 IEA (2021a) assesses the global plastics collection ate at 17% for 2020.
     FOOTNOTE11 Significant progress with data and indicators was reached in recent years with the development of
     several global coverage material flows datasets (Oberle et al. 2019).
     FOOTNOTE12 China contributed three forth of global industrial energy use increment in 2000-2014. Since 2014
     China’s share in global industrial energy use slowly declines reaching about a third in 2018 (IEA 2020d).
     FOOTNOTE13 This fits well 28.8% average for 1900-2018 with a slow trend to decline by 0.01% yr-1 in response
     to the growing share of services in global GDP, around which about 60-years-long cycles can be observed.
     FOOTNOTE14 Industry also produce goods traditionally used as feedstock –hydrogen and ammonia – which in
     the coming future may be widely used as energy carriers.
     FOOTNOTE15 Mapping global flows of fuel feedstock allows for better tailoring downstream mitigation options
     for chemical products (Levi and Cullen 2018).

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 1   for materials going through the whole production chain to final products) fell by 20% in 2000–2019 and
 2   by 15% in 2010–2019, accelerated driven by high energy prices to 2.4%·yr-1 in 2014–2019 matching
 3   the values observed back in 1990–2000 (Figure 11.2). Assessed per value added using market exchange
 4   rates, industrial energy intensity globally dropped by 12% in 2010-2018, after its 4% decline in 2000–
 5   2010, resulting in 2000–2018 decline by 15% (IEA 2020b,a). The 2020 COVID crisis slowed down
 6   energy intensity improvements by shifting industrial output towards more energy intensive basic
 7   materials (IEA 2020e). Specific energy consumption per tonne of iron and steel, chemicals and cement
 8   production in 2019 were about 20% below the 2000 level (IEA 2020b,a). This progress is driven by
 9   moving towards best available technologies (BATs) for each product through new and highly efficient
10   production facilities in China, India and elsewhere, and by the contribution from recycled scrap metals,
11   paper and cardboard.
12   Physical energy intensity for the production of materials typically declines and then stabilizes at the
13   BAT level once the market is saturated, unless a transformative new technology enters the market
14   (Gutowski et al. 2013; Crijns-Graus et al. 2020; IEA 2021a) Thus, the energy saving effect of switching
15   to secondary used material comes to the forefront, as energy consumption per tonne for many basic
16   primary materials approach the BATs. This highlights the need to push towards circular economy,
17   materials efficiency, reduced demand, and fundamental process changes (e.g. towards electricity and
18   hydrogen based steel making). Improved recycling rates allow for a substantial reduction in energy use
19   along the whole production chain – material extraction, production, and assembling – which is in great
20   excess of energy used for collection, separation, treatment, and scrap recycling minus energy used for
21   scrap landfilling. IEA (2019b) estimates, that by increasing the recycling content of fabricated metals
22   average specific energy consumption (SEC) for steel and aluminium may be halved by 2060. Focusing
23   on whole systems ‘integrative design’ expands efficiency resource much beyond the sum of potentials
24   for individual technologies. Material efficiency coupled with energy efficiency can deliver much greater
25   savings than energy efficiency alone. Gonzalez Hernandez et al. (2018b) stress that presently about half
26   of steel or aluminium are scrapped in production or oversized for targeted services. They show that
27   resource efficiency expressed in exergy as a single metric for both material and energy efficiency for
28   global iron and steel sector is only 33%, while secondary steelmaking is about twice more efficient
29   (66%), than ore-based production (29%). While shifting globally in ore-based production from average
30   to the best available level can save 6.4 EJ·yr-1, the saving potential of shifting to secondary steelmaking
31   is 8 EJ·yr-1, and limited mostly by scrap availability and steel quality requirements.
33   11.2.2 New trends in emissions
34   GHG emissions attributable to the industrial sector (see chapter 2) in 2019 originate from industrial fuel
35   combustion (7.1 GtCO2-eq direct and about 5.9 Gtonnes indirect from electricity and heat generation16);
36   industrial processes (4.5 GtCO2-eq) and products use (0.2 Gtonnes), as well as from waste (2.3 Gtonnes)
37   (Figure 11.4a-b). Overall industrial direct GHG emission amounts to 14.1 GtCO2-eq, Figure 11.4c and
38   Table 11.1) and scales up to 20 GtCO2-eq after indirect emissions are added,17 putting industry (24%,
39   direct emissions) second after the energy sector in total GHG emissions and lifting it to the leading

     FOOTNOTE16 Indirect emissions are assessed based on EDGAR database (Crippa et al. 2021). IEA database
     reports 6 Gt of CO2 for 2019 (IEA 2020f).
     FOOTNOTE17 Based on Crippa et al. (2021) and Minx et al. (2021). In 2019, industrial CO2 only emissions were
     10.4 GtCO2, which due to wider industrial processes and product use (IPPU) coverage exceeds CO2 emission
     assessed by IEA (2021a) at 8.9 Gt for 2019 and at 8.4-8.5 Gtonnes for 2020.

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1    position after indirect emissions are allocated (34% in 2019)18. The corresponding shares for 1990-2000
2    were 21% for direct emissions and 30% - for both direct and indirect (Crippa et al. 2021; Lamb et al.
3    2021; Minx et al. 2021). As the industrial sector is expected to decarbonize slower than other sectors it
4    will keep this leading position for coming decades (IEA 2021a). In 2000–2010, total industrial emissions
5    have been growing faster (3.8% yr-1), than in any other sector (see chapter 2, mostly due to the dynamics
6    shown by basic materials extraction and production. Industry contributed nearly half (45%) of overall
7    incremental global GHG emissions in the 21st century.
 8   Industrial sector GHG emissions accounting is complicated by carbon storage in products (Levi and
 9   Cullen 2018). About 35% of chemicals’ mass is CO2, which is emitted at use stage - decomposition of
10   fertilizers, or plastic waste incineration (Saygin and Gielen 2021), and sinks. Re-carbonation
11   mineralization of alkaline industrial materials and wastes (aka the “sponge effect”) provide 0.6–1
12   GtCO2·yr-1 uptake by cement containing products19 (Cao et al. 2020; Guo et al. 2021); see section 11.3.6
13   for further discussion in decarbonisation context.
14   In 1970–1990, industrial direct combustion-related emissions were growing modestly, and in 1990–
15   2000 even switched to a slowly declining trend, steadily losing their share in overall industrial
16   emissions. Electrification was the major driver behind both indirect and total industrial emissions in
17   those years. This quiet evolution was interrupted in the beginning of the 21st century, when total
18   emissions increased by 60-68% depending on the metric applied (the fastest growth ever seen). In 2000-
19   2019 iron and steel and cement absolute GHGs increased more than any other period in history
20   (Bashmakov 2021). Emissions froze temporarily in 2014–2016, partly in the wake of the financial crisis,
21   but returned to their growth trajectory 2017–2019 (Figure 11.4a).
22   The largest incremental contributors to industrial emissions 2010–2019 are industrial processes at 40%,
23   then indirect emissions (25%), and only then direct combustion (21%), followed by waste (14%, Figure
24   11.4). Therefore, to stop emission growth and to switch to zero carbon pathway more mitigation efforts
25   should be focused on industrial processes, products use and waste decarbonisation along with the
26   transition to low carbon electrification (Hertwich et al. 2020).
27   Basic materials production dominates both direct industrial GHG emissions (about 62%, waste
28   excluded)20 as well as direct industrial CO2 emissions (70%), led by iron and steel, cement, chemicals,
29   and non-ferrous metals (Figure 11.4e). Basic materials also contribute 60% to indirect emissions. In a
30   zero-carbon power world, with industry lagging behind in the decarbonisation of high-temperature
31   processes and feedstock, it may replace the energy sector as the largest generator of indirect emissions
32   embodied in capital stock21. According to Circle Economy (2020) and Hertwich et al. (2020), GHG
33   emissions embodied in buildings and infrastructure, machinery and transport equipment exceed 50% of
34   their present carbon footprint.

     FOOTNOTE18 According to IEA (2020f) industry fuel combustion CO2 only emissions contributed 24% to total
     combustion emissions, but combined with indirect emission it accounted for 43% in 2018.
     FOOTNOTE 19 There are suggestions to incorporate carbon uptake by cement containing products in IPCC
     methodology for national GHG inventories (Stripple et al. 2018).
     FOOTNOTE 20 Crippa et al. (2021) and IEA (2020a) assess materials related scope 1+2 (direct and indirect
     emissions) correspondingly at 10.3 for 2019 and at 10.7 for 2018. Hertwich (2021) updated estimates for the global
     cradle-to-gate material production related GHG emissions for 2018 at 11.8 Gtonnes (5.1 Gtonnes for metals, 3.7
     Gtonnes for non-metallic minerals, 1.8 Gtonnes for plastics and rubber, 1 Gtonne for wood) –which is about 69%
     of direct and indirect industrial emissions (waste excluded). These assessments are consistent as transportation of
     basic materials contributes around 1 GtCO2-eq. to GHG emissions.
     FOOTNOTE21 According to Hertwich et al. (2020), of 11.5 GtCO2-eq 2015 global materials GHG footprint about
     5 Gt were embodied in buildings and infrastructure, and nearly 3 Gtonnes in machinery, vehicles, and electronics.

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2       (a) Industrial emissions by source (left scale) and emissions structure (right scale). Comb – indicates direct
3             emissions from fuels combustion. IPPU – indicates emissions from industrial processes and product
4            use. Indirect emissions from electricity and heat generation are shown on the top. Shares on the right
5                                                 are shown for direct emissions

         (b) 2019 direct              (c) 2019 emissions split   (d) increments of GHG emissions by sources
             combustion and           by major sources           (direct emissions only)
             process emissions
             split by GHGs

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2                             (e) 2019-2020 emissions by major basic materials production
4                            Figure 11.4 Industrial sector direct global GHG emissions
5    Source: Calculated based on emissions data from Crippa et al., (2021) and Minx et al., (2021). Indirect emissions
6    were assessed using IEA (2021b). For the figure (e): IEA (2020b, 2021a); Cao et al. (2020); Wang et al. (2021);
7    International Aluminium Institute (2021a) and GCCA (2021a).

 9   In 1970–2000, direct GHG emissions per unit of energy showed steady decline interrupted by noticeable
10   growth in 2001–2018 driven by fast expansion of steel and cement production in China (Figure 11.5),
11   where in 2000-2015 on average every month 12 heavy industrial facilities were built (IEA 2021a). Non-
12   energy related GHG emissions per unit of extracted materials decline continuously, as the share of not
13   carbon intensive building materials (aggregates and sand) grows.
14   Wang et al. (2021)’s conclusion that iron and steel carbon intensity stagnated in 1995–2015 due to
15   skyrocketing carbon intensive material production in China and India (Figure 11.5) may be extended to
16   2020 (Bashmakov 2021) and to other basic materials. For aluminium carbon intensity declined in 2010-
17   2019 by only 2% (International Aluminium Institute 2021a). Carbon intensity of cement making since
18   2010 is down by only 4%. In 1990–2019 it fell by 19.5%, mostly due to energy efficiency improvements
19   (by 18.5%) as the carbon intensity of the fuel mix declined only by 3% (GCCA 2021b). Historical
20   analysis shows the carbon intensity of steel production has declined with “stop and go” patterns in 50-
21   60 years cycles, reflective of the major jumps in best available technology. From 1900–1935 and from
22   1960–1990 specific scope 1+2+3 emissions fell by 1.5-2.5 tCO2 per tonne, or as much as needed now
23   to achieve net zero. While historical declines were mostly due to commissioning large capacities with
24   new technologies, with total emissions growing, by 2050 and beyond the decline will likely materialize
25   via new ultra low emission capacity replacements pushing absolute emissions to net zero (Bataille et al.
26   2021b).

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2            Figure 11.5 Industrial sector GHG emissions (direct only) in 10 world regions. 1990-2019
3   Source: Calculated based on emissions data from Crippa et al. (2021). Indirect emissions were assessed using
4   IEA (2021b).


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2                                                                               Table 11.1 Dynamics and structure of industrial GHG emissions

                                                                           Average annual growth rates                        Share in total industrial sector emissions            2019
                                                                           1971-1990    1991-2000    2000-2010    2011-2019   1970       1990        2000       2010       2019     GtCO2-eq
    Direct CO2 emissions form fuel

                                     Mining (excl. fuels), manufacturing
                                                                             0.13%         -0.18%        4.62%      0.77%      45.8%      37.3%       33.2%      36.6%     34.9%       6981
                                     industries and construction
                                     Iron and steel                          0.20%         0.13%         5.62%      2.28%      12.4%      10.2%       9.4%       11.4%     12.4%       2481
                                     Chemical and petrochemical              3.66%         1.54%         3.16%      1.19%      3.0%        4.9%       5.2%        4.9%      4.9%       977
                                     Non-ferrous metals                      2.12%         3.20%         1.12%      1.36%      0.7%        0.8%       1.0%        0.8%      0.8%       163
                                     Non-metallic minerals                   2.91%         1.88%         6.24%     -0.04%      3.3%        4.6%       5.0%        6.5%      5.7%       1148
                                     Paper, pulp and printing                0.78%         2.79%         0.09%     -2.69%      1.4%        1.3%       1.5%        1.1%      0.7%       150

                                     Food and tobacco                        2.55%         1.50%         3.03%     -1.04%      1.3%        1.6%       1.7%        1.6%      1.3%       265
                                     Other                                  -1.55%         -2.89%        4.61%     -0.22%      23.8%      13.8%       9.4%       10.3%      9.0%       1797
    Indirect emissions - electricity                                         2,87%         2.06%         3.00%     -0.87%      17.6%      24.6%       27.3%      25.8%     21.2%       4236
    Indirect emissions – heat                                                2,08%         -3.09%        2.53%      9.83%      5.6%        6.7%       4.5%        4.0%      8.3%       1663

                                     Total                                   1.45%         2.16%         5.00%      1.93%      11.0%      11.6%       13.0%      14.9%     15.7%       3144
                                     Non-metallic minerals                   2.22%         2.36%         5.66%      1.67%      5.7%        7.0%       8.0%        9.7%     10.0%       2008
                                     Chemical and petrochemical              4.51%         2.52%         3.50%      2.01%      1.5%        2.9%       3.4%        3.4%      3.6%       720

                                     Metallurgy                             -3.11%         0.37%         5.16%      3.10%      3.6%        1.5%       1.4%        1.7%      2.0%       391

                                     Other                                   1.55%         2.30%         -1.21%     2.89%      0.1%        0.2%       0.2%        0.1%      0.1%        25
    Industrial product use GHG                                              -0,22%         -0.49%        -1.02%     0.41%      2.7%        2.0%       1.7%        1.1%      1.0%       204
    Other non-CO2 GHG                                                       -0,60%         5.20%         4.29%      3.20%      5.5%        3.9%       5.8%        6.2%      7.3%       1470
    Waste GHG                                                                1,94%         1.35%         1.22%      1.57%      11.9%      13.8%       14.4%      11.4%     11.6%       2327
    Total GHG                                                                1,16%         0.98%         3.61%      1.32%     100.0%      100.0%     100.0%      100.0%    100.0%     20,025
3   Source: Calculated based on Crippa et al. (2021); IEA (2021b) and Minx et al. (2021).

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1    11.2.3 Industrial development patterns and supply chains (regional)
2    The dramatic increase in industrial emissions after 2000 is clearly associated with China’s22 and other
3    non-OECD Asian countries’ economic growth, which dominated both absolute and incremental
4    emissions (Figure 11.5a-b).
5    More recent 2010–2019 trends show that regional contributions to additional emissions are distributed
6    more evenly, while a large part still comes from Asian countries, where both rates of economic growth
7    and the share of industrial emissions much exceed the global average. All other regions also contributed
8    to total industrial GHG emissions. Structural shifts towards emissions from industrial processes and
9    products use are common for many regions (Figure 11.5a).
10   Economic development. Regional differences in emission trends are determined by the differences
11   observed in economic development, trade and supply chain patterns. The major source of industrial
12   emissions is production of energy intensive materials, such as iron and steel, chemical and
13   petrochemicals, non-ferrous metals and non-metallic products. Steel and cement are key inputs to
14   urbanization and infrastructure development (buildings and infrastructure are responsible for about
15   three fourths of the steel stock). Application of a “services-stock-flow-emissions” perspective
16   (Wiedenhofer et al. 2019; Haberl et al. 2021; Bashmakov 2021) shows that relationship patterns
17   between stages of economic development, per capita stocks and flows of materials are not trivial with
18   some clear transition points. Cao et al. (2017) mapped countries by four progressive stages in cement
19   stock per capita S-shape evolution as a function of income and urbanization: initial stage for developing
20   countries with a low level and slow linear growth; take-off stage with accelerated growth; slowdown
21   stage; and finally a shrinking stage (represented by just a few countries with very high incomes
22   exceeding 40k USD 2010 per capita) and urbanization levels above 80%. Bleischwitz et al. (2018) use
23   a similar approach with 5 stages to study material saturation effects for apparent consumption and stocks
24   per capita for steel, cement, aluminium, and copper. This logic may be generalized to other materials
25   from which in-use stock is built. While globally cement in-use stock is about 12 tonnes per capita, in
26   developed countries it is 15-30 tonnes per capita, but order of magnitude lower in developing states
27   with high per capita escalation rates (Cao et al. 2017). When stocks for some materials saturate – per
28   capita stock peaks – the ‘scrap age’ is coming (Pauliuk et al. 2013a). Steel in-use stock has already
29   saturated in advanced economies at 14±2 tonnes per capita due to largely completed urbanization and
30   infrastructure developments and a switch towards services-dominated economy. This saturation level
31   is 3-4 times that of the present global average, which is below 4 tonnes per capita (Pauliuk et al. 2013a;
32   Wiedenhofer et al. 2019; Graedel et al. 2011). China is entering the maturing stage of steel and cement
33   consumption resulting in a moderate projection of additional demand followed by expected industrial
34   emissions peaking in the next 10-15 years (Bleischwitz et al. 2018; Zhou et al. 2013; Wu et al. 2019;
35   OECD 2019a; Zhou et al. 2020). But many developing countries are still urbanizing, and the growing
36   need for infrastructure services results in additional demand for steel and cement. Materials intensity of
37   the global economy is projected by OECD (2019a) to decline at 1.3% yr-1 till 2060, driven by improving
38   resource efficiency and the switch to circular economy, but with a projected tripling of global GDP it
39   means a doubling of projected materials use (OECD 2019a). Under the business-as-usual scenario,
40   India’s demand for steel may more than quadruple over the next 30 years (de la Rue du Can et al. 2019;
41   Dhar et al. 2020). In the IEA (2021a) Net Zero Energy scenario saturation effect along with material
42   efficiency counterbalances activity effects and keeps demand growth for basic materials modest while
43   escalate demand for critical materials (copper, lithium, nickel, graphite, cobalt and others).
44   International trade and supply chain. In Equation 11.1 the share of allocated emissions (Dm) equals
45   unity when territorial emission is considered, and to the ratio of domestically used materials to total

     FOOTNOTE22 In 2020 China accounted for nearly 60% of global steel and cement production (IEA 2021a) and
     in 2015 over than half of the material production associated emissions occurred in China (Hertwich 2021).

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1    material production for consumption-based emission accounting. Tracking consumption-based
2    emissions provides additional insights in the global effectiveness of national climate policies. Carbon
3    emissions embodied in international trade are estimated to account for 20-30% of global carbon
4    emissions (Meng et al. 2018; OECD.Stat 2019) and are the reason for different emissions patterns of
5    OECD versus non-OECD countries (chapter 2).
 6   Based on OECD.Stat (2019) datasets, 2015 CO2 emissions embodied in internationally traded industrial
 7   products (manufacturing and mining excluding fuels) by all countries are assessed at 3 GtCO2, or 30%
 8   of direct CO2 emission in the industrial sector as reported by Crippa et al. (2021). OECD countries
 9   collectively have reduced territorial emissions (shares of basic materials in direct emissions in those
10   regions decline, (Figure 11.5b), but demonstrated no progress in reducing outsourced emissions
11   embedded in imported industrial products (Arto and Dietzenbacher 2014; OECD.Stat 2019).
12   Accounting for net carbon emissions embodied in international trade of only industrial products (1283
13   mln tCO2 in 2015) escalates direct OECD industrial CO2 emissions (1333 mln tCO2 of energy-related
14   and 502 mln tCO2 of industrial processes) 1.7 fold, 2.3-fold for the US, 1.5-fold for the EU, and more
15   than triples it for the UK, while cutting (Dm) by a third for China and Russia (IEA 2020f; OECD.Stat
16   2019). In most OECD economies, the amount of CO2 embodied in net import from non-OECD countries
17   is equal to, or even greater than, the size of their Paris 2030 emissions reduction commitments. In the
18   UK, parliament Committee on Energy and Climate Change requested that a consumption-based
19   inventory be complementarily used to assess the effectiveness of domestic climate policy in delivering
20   absolute global emissions reductions (Barrett et al. 2013; UKCCC 2019a). It should be noted that the
21   other side of the coin is that exports from countries with lower production carbon intensities can lead
22   to overall less emissions than if production took place in countries with high carbon intensities, which
23   may become critical in the global evolution toward lower emissions. The evolution of Dm to the date
24   was driven mostly by factors other than carbon regulation often equipped with carbon leakage
25   prevention tools. Empirical tests have failed to date to detect meaningful “carbon leakage” and impacts
26   of carbon prices on net import, direct foreign investments, volumes of production, value added,
27   employment, profits, and innovation in industry (Acworth et al. 2020; Branger et al. 2016; Carratù et
28   al. 2020; Ellis et al. 2019; Saussay and Sato. 2018; Zachmann and McWilliams 2020; Naegele and
29   Zaklan 2019; Pyrka et al. 2020; Sartor 2013). In the coming years availability of large low-cost
30   renewable electricity potential and cheap hydrogen may become a new driver for relocation of such
31   carbon intensive industries as steel production (Gielen et al. 2020; Bataille 2020a; Bataille et al. 2021a;
32   Saygin and Gielen 2021).

34   11.3 Technological developments and options
35   The following overview of technical developments and mitigation options which relate to the industrial
36   sector is organised in six equally important strategies: (i) demand for materials. (ii) materials efficiency,
37   (iii) circular economy and industrial waste, (iv) energy efficiency, (v) electrification and fuel switching,
38   and (vi) CCUS, feedstock and biogenic carbon. Each strategy is described in detail, followed by a
39   discussion of possible overlaps and interactions between strategies and how conflicts and synergies can
40   be addressed through integration of the approaches.
42   11.3.1 Demand for materials
43   Demand for materials is a key driver of energy consumption and CO2 emissions in the industrial sector.
44   Rapid growth in material demand over the last quarter century has seen demand for key energy-intensive
45   materials increase 2.5– to 3.5–fold (see Figure 11.6), with growth linked to, and often exceeding,
46   population growth and economic development. The International Energy Agency explains, “as

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1    economies develop, urbanise, consume more goods and build up their infrastructure, material demand
2    per capita tends to increase considerably. Once industrialised, an economy’s material demand may level
3    off and perhaps even begin to decline” (IEA 2019b).

 5        Figure 11.6 Growth in global demand for selected key materials and global population, 1990–2019
 6   Notes: Based on global values, shown indexed to 1990 levels (=100). Steel refers to crude steel production.
 7   Aluminium refers to primary aluminium production. Plastic refers to the production of subset of key thermoplastic
 8   resins. Cement and concrete follow similar demand patterns.
 9   Sources: 1990-2018: IEA (2020b). 2019-2020: World Steel Association (2021); International Aluminium Institute
10   (2021a); U.S. Geological Survey (2021); GCCA (2021a); World Bank (2021); Statista (2021b).
12   The Kaya-like identity presented earlier in the chapter (Equation 11.1) suggests that material demand
13   can be decoupled from population and economic development by two means: (i) reducing the
14   accumulated material stock (MStock) used to deliver material services; and, (ii) reducing the material
15   (MPR +MSE) required to maintain material stocks (MStock). Such material demand reduction
16   strategies are linked upstream to material efficiency strategies (the delivery of goods and services with
17   less material demand, and thus energy and emissions) and to demand reduction behaviours, through
18   concepts such as sufficiency, sustainable consumption and social practice theory (Spangenberg and
19   Lorek 2019). Materials demand can also be influenced through urban planning, building codes and
20   related socio-cultural norms that shape the overall demand for square meters per capita of floor space,
21   mobility and transport infrastructures (Chapter 5).
22   Modelling suggests that per capita material stocks saturate (level off) in developed countries and
23   decouple from GDP. Pauliuk et al. (2013b) demonstrated this saturation effect in an analysis of in-use
24   steel stocks in 200 countries, showing that per capita steel in stocks in countries with a long industrial
25   history (e.g. US, UK, Germany) had saturation levels between 11 and 16 tonnes. More recently,
26   Bleischwitz et al. (2018) confirmed the occurrence of a saturation effect for four materials (steel,
27   cement, aluminium and copper) in four industrialised countries (Germany, Japan, UK, US) together
28   with China. These findings have led to the revision of some material demand forecasts, which
29   previously had been based solely on population and economic trends.
30   The saturation effect for material stocks is critical for managing material demand in developed
31   countries. Materials are required to meet demand for the creation of new stocks and the maintenance
32   of existing stocks (Gutowski et al. 2017). Once saturation is attained the need for new stocks is
33   minimised, and materials are only required for replacing old stocks and maintenance. Saturation allows
34   material efficiency strategies (such as lightweight design, longer lifetimes, and more intense use) to
35   reduce the required per capita level of material stocks, and material circularity strategies (closing

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1    material loops through remanufacture, reuse, recycling) to lessen the energy and carbon impacts
2    required to maintain the material stock. However, it should be noted that some materials still show little
3    evidence of saturation (i.e., plastics, see Box 11.2). Furthermore, meeting climate change targets in
4    developed countries will require the construction of new low-carbon infrastructures (i.e., renewable
5    energy generation, new energy distribution and storage systems, electric vehicles and building heating
6    systems) which may increase demand for emissions intensive materials (i.e. steel, concrete, glass).
 7   For developing countries, who are still far from saturation levels, strong growth for new products and
 8   the creation of new infrastructure capacity may still drive global material demand. However, there is an
 9   expectation that economic development can be achieved at lower per capita material stock levels, based
10   on the careful deployment of material efficiency and circularity by design (Grubler et al. 2018).
12   11.3.2 Material efficiency
13   ME—the delivery of goods and services with less material—is increasingly seen as an important
14   strategy for reducing GHG emissions in industry (IEA 2017, 2019b). Options to improve ME exist at
15   every stage in the life-cycle of materials and products, as shown in Figure 11.7. This includes: designing
16   products which are lighter, optimising to maintain the end-use service while minimizing material use,
17   designing for circular principles (i.e. longer life, reusability, repairability, and ease of high quality
18   recycling); pushing manufacturing and fabrication process to use materials and energy more efficiently
19   and recover material wastes; increasing the capacity, intensity of use, and lifetimes of product in use;
20   improving the recovery of materials at end-of-life, through improved remanufacturing, reuse and
21   recycling processes. For more specific examples see Allwood et al. (2012); Rissman et al. (2020); Scott
22   et al. (2019); Hertwich et al. (2019) and Lovins (2018).

25                         Figure 11.7 Material efficiency strategies across the value chain
26   Source: derived from strategies in Allwood et al. (2012).

28   ME provides plentiful options to reduce emissions, yet because interventions are dispersed across
29   supply chains and span many different stakeholders, this makes assessing mitigation potentials and
30   costs more challenging. For this reason, ME interventions have traditionally been under-represented in
31   climate change scenario modelling and integrated assessment models (IAMs) (Grubler et al. 2018;
32   Allwood 2018). However, two advances in the modelling of materials flows have underpinned the
33   recent emergence of ME options being included in climate scenario modelling.
34   Firstly, over many years, the academic community has built up detailed global material flow maps of
35   the processing steps involved in making energy-intensive materials. Some prominent recent examples
36   include: steel (Gonzalez Hernandez et al. 2018b), pulp and paper (Van Ewijk et al. 2018),
37   petrochemicals (Levi and Cullen 2018). In addition, material flow maps at the regional and sectoral

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 1   levels have flourished, for example,: steel (Serrenho et al. 2016) and cement (Shanks et al. 2019) in the
 2   UK; automotive sheet-metal (Horton et al. 2019); and steel powder applications (Azevedo et al. 2018).
 3   The detailed and transparent physical mapping of material supply chains in this manner enables ME
 4   interventions to be traced back to where emissions are released, and allows these options to be compared
 5   against decarbonisation and traditional energy efficiency measures (Levi and Cullen 2018). For
 6   example, a recent analysis by Hertwich et al. (2019) makes the link between ME strategies and reducing
 7   greenhouse gas emissions in buildings, vehicles and electronics, while Gonzalez Hernandez et al.
 8   (2018a) examines leveraging ME as a climate strategy in EU policy. Research to explore the combined
 9   analysis of materials and energy, using exergy analysis (for steel, (Gonzalez Hernandez et al. 2018b))
10   allows promising comparisons across industrial sectors.
11   Secondly, many ME interventions result in immediate GHG emissions savings (short-term), for
12   example, light-weighting products, re-using today’s product components, and improving manufacturing
13   yields. Yet, for other ME actions emissions savings are delayed temporally (long-term). For example,
14   designing a product for future reuse, or with a longer-life, only reaps emissions savings at the end of
15   the product life, when emissions for a replacement product are avoided. Many durable products have
16   long life-times (cars >10 years, buildings >40 years) which requires dynamic modelling of material
17   stocks, over time, to enable these actions to be included in scenario modelling activities. Consequently,
18   much effort has been invested recently to model material stocks in use, to estimate their lifetimes, and
19   anticipate the future waste and replenishment materials to maintain existing stocks and grow the
20   material stock base. Dynamic material models have been applied to material and product sectors, at the
21   country and global level. These include, for example: vehicles stocks in the UK (Serrenho et al. 2017;
22   Craglia and Cullen 2020) and in China (Liu et al. 2020); buildings stocks in the UK (Cabrera Serrenho
23   et al. 2019), China (Hong et al. 2016; Cao et al. 2018, 2019) and the European Union (Sandberg et al.
24   2016); electronic equipment in Switzerland (Thiébaud et al. 2017); specific material stocks, such as
25   cement (Cao et al. 2020, 2017), construction materials (Sverdrup et al. 2017; Habert et al. 2020), plastics
26   (Geyer et al. 2017), copper (Daehn et al. 2017), and all metals (Elshkaki et al. 2018); all materials in
27   China (Jiang et al. 2019), Switzerland (Heeren and Hellweg 2019) and the world (Krausmann et al.
28   2017).
29   These two advances in the knowledge base have allowed the initial inclusion of some ME strategies in
30   energy and climate change scenario models. The International Energy Agency (IEA) first created a ME
31   scenario (MES) in 2015, with an estimated 17% reduction in industrial energy demand in 2040 (IEA
32   2015). World energy outlook report includes a dedicated sub-chapter with calculations explicitly on
33   industrial material efficiency (IEA 2019c). They also include ME options in their modelling frameworks
34   and reporting, for example for petrochemicals (IEA 2018a), and in the Material Efficiency in Clean
35   Energy Transitions report (IEA 2019b). In Grubler et al. (2018) 1.5 degree Low Energy Demand (LED)
36   scenario, global material output decreases by 20% from today, by 2050, with one-third due to
37   dematerialisation, and two-thirds due to ME, resulting in significant emissions savings. Material
38   Economics analysis of Industrial Transformation 2050 (Material Economics 2019), found that resource
39   efficiency and circular economy measures (i.e. ME) could almost halve the 530 MtCO2 yr-1emitted by
40   the basic materials sectors in the EU by 2050. Finally, the Emissions gap report, UNEP (2019) includes
41   an assessment of potential material efficiency savings in residential buildings and cars.
42   Clearly, more work is required to fully integrate ME strategies into mainstream climate change models
43   and future scenarios. Efforts are focused on endogenising ME strategies within climate change
44   modelling, assessing the synergies and trade-offs which exist between energy efficiency and ME
45   interventions, and building up data for the assessment emissions saved and the cost of mitigation from
46   real ME actions. This requires analysts to work in cross-disciplinary teams and to engage with
47   stakeholders from across the full breadth of material supply chains. Efforts should be prioritised to
48   foster engagement between the IAM community and emerging ME models based in the Life Cycle

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1    Assessment, Resource Efficiency, and Industrial Ecology communities (see also Sharmina et al.
2    (2021)).
4    11.3.3 Circular economy and industrial waste
 5   Circular economy (CE) is another effective approach to mitigate industrial GHG emissions and has
 6   been widely promoted worldwide since the fourth IPCC assessment report (AR4). From an industrial
 7   point of view, CE focuses on closing the loop for materials and energy flows by incorporating policies
 8   and strategies for more efficient energy, materials and water consumption, while emitting minimal
 9   waste to the environment (Geng et al. 2013). Moving away from a linear mode of production
10   (sometimes referred to as an “extract-produce-use-discard” model), CE promotes the design of durable
11   goods that can be easily repaired, with components that can be reused, remanufactured, and recycled
12   (Wiebe et al. 2019). In particular, since CE promotes reduction, reuse and recycling, a large amount of
13   energy and GHG intense virgin material processing can be reduced, leading to significant carbon
14   emission reductions. For example, in the case of aluminium, the energy efficiency of primary
15   production is relatively close to best available technology (See Figure 11.8) while switching to
16   production using recycled materials requires only about 5% as much energy ( However,
17   careful evaluation is needed from a life cycle perspective since some recycling activities may be energy
18   and emission intensive, for example, chemical recycling of plastics (
19   As one systemic approach, CE can be seen as conducted at different levels, namely, at the micro‐level
20   (within a single company, such as process integration and cleaner production), meso-level (between
21   three or more companies, such as industrial symbiosis or eco‐industrial parks) and macro‐level (cross‐
22   sectoral cooperation, such as urban symbiosis or regional eco‐industrial network). Each level requires
23   different tools and policies, such as CE-oriented incentive and tax policies (macro-level), and eco-
24   design regulations (micro-level). This section is focused on industry and a broader discussion of the CE
25   concept is found in Box 12.2 and section
26   Micro-level: More firms have begun to implement the concept of CE, particularly multi-national
27   companies, since they believe that multiple benefits can be obtained from CE efforts, and it has become
28   common across sectors (D’Amato et al. 2019). Typical CE tools and policies at this level include cleaner
29   production, eco-design, environmental labelling, process synthesis, and green procurement. For
30   instance, leading chemical companies are incorporating CE into their industrial practices, for example,
31   through the design of more recyclable and degradable plastics, a differentiated and market-driven
32   portfolio of resins, films and adhesives that deliver a total package that is more sustainable, cost-
33   efficient and capable of meeting new packaging and plastics preferences. Problematically, at the same
34   time the plastics industry is improving recyclability it has, for example, been expanding into markets
35   without recycling capacity (Mah 2021). Similarly, automakers are pursuing strategies to increase the
36   portion of new vehicles that is fully recyclable when they reach end of life, with increasing ambitions
37   for using recycled material, largely motivated by end-of-life vehicle regulations. This will require
38   networks are available to collect and sort all the materials in vehicles, and policy incentives to do it
39   (Wiebe et al. 2019; Soo et al. 2021).
40   Meso-level: Industrial parks first appeared in Manchester, UK, at the end of the 19 th century and they
41   have been implemented in industrialized countries for maximizing energy and material efficiency,
42   which has also merit for CO2 emissions reduction, as stated well in AR5. Industrial parks reduce the
43   cost of infrastructure and utilities by concentrating industrial activities in planned areas, and are typical
44   founded around large, long term anchor companies. Complementary industries and services provided
45   by industrial parks can entail diversified effects on the surrounding region and stimulate regional
46   development (Huang et al. 2019a). This is crucial for small and medium enterprises (SMEs) because
47   they often lack access to information and funds for sophisticated technologies.

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 1   Typical CE tools and policies at this level include sustainable supply chains and industrial symbiosis.
 2   A common platform for sharing information and enhancing communication among industrial
 3   stakeholders through the application of information and telecommunication technologies is helpful for
 4   facilitating the creation of industrial symbiosis. The main benefit of industrial symbiosis is the overall
 5   reduction of both virgin materials and final wastes, as well as reduced/avoided transportation costs from
 6   byproduct exchanges among tenant companies, which can specifically help small and medium sized
 7   enterprises to improve their growth and competitiveness. From climate perspective, this indicates
 8   significant industrial emission mitigation since the extraction, processing of virgin materials and the
 9   final disposal of industrial wastes are more energy-intensive. Also, careful site selection of such parks
10   can facilitate the use of renewable energy. Due to these advantages, eco-industrial parks have been
11   actively promoted, especially in East Asian countries, such as China, Japan and South Korea, where
12   national indicators and governance exist (Geng et al. 2019). For instance, the successful implementation
13   of industrial symbiosis at Dalian Economic and Technological Development Zone has achieved
14   significant co-benefits, including GHG emission reduction, economic and social benefits and improved
15   ecosystem functions (Liu et al. 2018). Another case at Ulsan industrial park, South Korea, estimated
16   that 60,522 tonnes CO2 were avoided annually through industrial symbiosis between two companies
17   (Kim et al. 2018b). The case of China shows a great potential of implementing these measures,
18   estimating 111 million tonne CO2 equivalent will be reduced in 213 national-level industrial parks in
19   2030 compared with 2015 (Guo et al. 2018). As such, South Korea’s national eco-industrial park project
20   has reduced over 4.7 million tonne CO2 equivalent through their industrial symbiosis efforts (Park et al.
21   2019). Meso-level CE solutions have been identified as essential for industrial decarbonisation (see
22   11.4.3). Moreover, waste prevention as the top of the so-called “waste hierarchy” can be promoted on
23   the meso-level for specific materials or product systems. For instance, the European Environment
24   Agency published a report on plastic waste prevention approaches in all EU 28 member states (Wilts
25   and Bakas 2019). However, challenges exist for industrial symbiosis activities, such as the inter-firm
26   contractual uncertainties, the lack of synergy infrastructure, and the regulations that hamper reuse and
27   recycling. Therefore, necessary legal reforms are needed to address these implementation barriers.
28   Macro-level: The macro- level uses both micro- and meso-level tools within a broader policy strategy,
29   addressing the specific challenge of CE as a cross-cutting policy (Wilts et al. 2016). More synergy
30   opportunities exist beyond the boundary of one industrial park. This indicates the necessity of scaling
31   up industrial symbiosis to urban symbiosis. Urban symbiosis is defined as the use of by-products (waste)
32   from cities as alternative raw materials for energy sources for industrial operations (Sun et al. 2017). It
33   is based on the synergistic opportunity arising from the geographic proximity through the transfer of
34   physical sources (waste materials) for environmental and economic benefits. Japan is the first country
35   to promote urban symbiosis. For instance, the Kawasaki urban symbiosis efforts can save over 114,000
36   tons of CO2 emission annually (Ohnishi et al. 2017). Another simulation study indicates that Shanghai
37   (the largest Chinese city) has a potential of saving up to 16.8 MtCO2 through recycling all the available
38   wastes (Dong et al. 2018). As such, the simulation of urban energy symbiosis networks in Ulsan, South
39   Korea indicates that 243,396 tCO2-1·yr-1 emission and 48 million USD·yr-1 fuel cost can be saved (Kim
40   et al. 2018a). Moreover, Wiebe et al. (2019) estimates that the adoption of the CE can lead to a
41   significantly lower global material extraction compared to a baseline. Their global results range from a
42   decrease of about 27% in metal extraction to 8% in fossil fuel extraction and use, 8% in forestry
43   products, and about 7% in non-metallic minerals, indicating significant climate change benefits. A
44   macro-perspective calculation on the circulation of iron in Japan’s future society shows that CO 2
45   emissions from the steel sector can be reduced by 56% as per the following assumptions: the amount
46   recovered from social stock is the same as the amount of inflow, and all scrap was used domestically,
47   and the export of steel products is halved (LCS 2018). A key challenge is to go beyond ensuring proper
48   waste management to setting metrics, targets and incentives to preserve the incorporated value in
49   specific waste streams. Estimations for Germany have shown that despite recycling rates of 64% for all

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1    solid waste streams, these activities only lead to a resource use reduction of only 18% (Steger et al.
2    2019). In general, the identification of the most appropriate CE method for different countries requires
3    understanding and information exchange on background conditions, local policies and myriad other
4    factors influencing material flows from the local up to the global level (Tapia Carlos et al. 2019). Also,
5    an information platform should be created at the national level so that all the stakeholders can share
6    their CE technologies and expertise, information (such as materials/energy/water consumption data),
7    and identify the potential synergy opportunities.
9    11.3.4 Energy Efficiency
10   Energy efficiency in industry is an important mitigation option and central in keeping 1.5°C within
11   reach (IPCC SR1.5). It has long been recognized as the first mitigation option in industry (Yeen Chan
12   and Kantamaneni 2016; Nadel and Ungar 2019; IEA 2021a). It allows reduction of the necessary scale
13   of deployment for low-carbon energy supplies and associated mitigation costs (Energy Transitions
14   Commission 2018). The efficiency potentials are greatest in the non-energy intensive industries and
15   often relatively limited in energy intensive ones, such as steel (Pardo and Moya 2013; Arens et al. 2017;
16   Kuramochi 2016). Deep decarbonisation in these subsectors requires fundamental process changes but
17   energy efficiency remains important to reduce costs and the need for low-carbon energy supplies.
18   Below, we focus mainly on the technical progress and on new options that are reflected in the literature
19   since AR5 and refer the reader there for a broader and deeper treatment of energy efficiency.
20   Digitalisation and the development of industrial high-temperature heat pumps are two notable
21   technology developments that can facilitate energy efficiency improvements.
22   Industrial energy efficiency can be improved through multiple technologies and practices (Tanaka 2011;
23   Fawkes et al. 2016; Crijns-Graus et al. 2020; IEA 2020a; Lovins 2018). There are two parallel processes
24   in improvement of SEC: progress in energy-efficient BAT, and moving the SEC of industrial plants
25   towards BAT. Both slow down as theoretical thermodynamic minimums are approached (Gutowski et
26   al. 2013). For the last several decades the focus has been on effective spreading of BAT technologies
27   through application of policies for worldwide diffusion of energy-saving technologies (see 11.6). As a
28   result the SEC for many basic primary materials is approaching BAT and there are signs that energy
29   efficiency improvements have been slowing down over recent decades (IEA 2019d, 2020a, 2021a)
30   (Figure 11.8).


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1      Figure 11.8 Energy efficiency indicators for basic material production. Energy accounting is based on
2                    final energy use. Sectoral boundaries for steel are as defined in (IEA 2020c).
3    Sources: Calculated based on (IEA 2017, 2018b; IEA and WBCSD 2018; IEA 2020b; Hasanbeigi et al. 2012;
4    UNIDO 2010; Saygin et al. 2011; WBCSD 2016; Crijns-Graus et al. 2020; Napp et al. 2014; Moya and Pardo
5    2013; International Aluminium Institute 2020; IEA 2019b, 2020c)

7 Heat use energy efficiency improvement
 8   While about 10% of global GHG emissions originate from combustion to produce high temperature
 9   heat for basic material production processes (Sandalow et al. 2019), limited efforts have been made to
10   decarbonize heat production. There is still a large potential for using various grades of waste heat and
11   the development of high-temperature heat pumps facilitates its use. NEDO (2019) applies a ‘Reduce,
12   Reuse, and Recycle’ concept for improved energy efficiency, and we use this frame our discussion of
13   heat efficiency.
14   Reduce refers to reducing heat needs via improved thermal insulation, for example, where porous type
15   insulators have been developed with thermal conductivity half of what is traditionally achieved by heat
16   resistant bricks under conditions of high compressive strength (Fukushima and Yoshizawa 2016). Reuse
17   refers to waste heat recovery. A study for the EU identified a waste heat potential of about 300 TWh·yr-
18     , corresponding to about 10 % of total energy use in industry. About 50% of this was below 200°C,
19   about 25% at temperatures 200–500°C, and 25% at temperatures of 500°C and above (Papapetrou et al.
20   2018). A survey conducted in Japan showed that 9% of the input energy is lost as waste heat, of which
21   heat below 199°C accounts for 68% and that below 149°C was 29% (NEDO 2019). McBrien et al.
22   (2016) identified that in steel sector process heat recovery presently saves 1.8 GJ per tonne of hot rolled
23   steel, while integrated across all production processes heat recovery with conventional heat exchange
24   could save 2.5 GJ per tonne, and it scales up to 3.0 GJ per tonne using an alternative heat exchange that
25   recovers energy from hot steel. High temperature industrial heat pumps represent a new and important
26   development for upgrading waste heat and at the same time the facilitate electrification. One recent
27   example is a high temperature heat pump that can raise temperatures up to 165°C at a coefficient of
28   performance (COP) of 3.5 by recovering heat from unused hot water (35–65°C) (Arpagaus et al. 2018).
29   Commercially available heat pumps can deliver 100–150°C but at least up to 280°C is feasible
30   (Zühlsdorf et al. 2019). Mechanical vapor recompression avoids the loss of latent heat by condensation,
31   then it acts as a highly efficient heat pump with a 5–10 COP (Philibert 2017a).
32   Waste heat to power (WHP), or Recycle in NEDO´s terms, is also an underutilised option. For example,
33   a study for the cement, glass and iron industries in China showed that current technology enables only
34   7–13% of waste heat to be used for power generation. With improved technologies, potentially 40–57%
35   of waste heat with temperatures above 150°C could be used for power generation via heat recovery.
36   Thermal power fluctuations can be a challenge and negatively affect the operation and economic
37   feasibility of heat recovery power systems such as Steam and/or Organic Rankine Cycle. In such cases,
38   latent heat storage technology and intermediate storage units may be applied (Jiménez-Arreola et al.
39   2018). The development of thermoelectric conversion materials that produce power from unused heat
40   and energy harvested from higher temperature environment is also progressing, with several possible
41   applications in industrial processes (Ohta et al. 2018; Jood et al. 2018; Lv et al. 2018; Gayner and Kar
42   2016). A potential early application in industry is to power wireless sensors, a niche that uses microwatts
43   or milliwatts, and avoid power cables (Champier 2017).
45 Smart energy management
46   Energy management systems to reduce energy costs in an integrated and systematic manner were first
47   developed in the 1970s, mainly in low energy resource countries, for example, by establishing energy

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 1   managers and institutionalizing management targets (Tanaka 2011). Strategic energy management has
 2   since then evolved and been promoted through the establishment of dedicated organizational
 3   infrastructures for energy use optimization, such as ISO-50001 which specifies the requirements for
 4   establishing, implementing, maintaining, and improving an energy management system (Biel and Glock
 5   2016; Tunnessen and Macri 2017). Digitalisation, sometimes referred to as Industry 4.0, facilitates
 6   further improvements in process control and optimisation through technology development involving
 7   sensors, communications, analytics, digital twins, machine learning, virtual reality, and other simulation
 8   and computing technologies (Rogers 2018), all of which can improve energy efficiency. One example
 9   is combustion control systems, where big data analysis of factors affecting boiler efficiency, operation
10   optimization and load forecasting have been shown that it can lead to energy savings of 9% (Wang et
11   al. 2017).
12   Smart energy systems with real time monitoring allow for optimization of innovative technologies,
13   energy demand response, balancing of energy supply and demand including that on real time pricing,
14   and product quality management, and prediction and reduction of idle time for workers and robots
15   (Legorburu and Smith 2018; Pusnik et al. 2016; Ferrero et al. 2020; ISO 2018; ERIA 2016; Nimbalkar
16   et al. 2020). IEA estimated that smart manufacturing could deliver 15 EJ in energy savings between
17   2014 and 2030 (IEA 2019d). Smart manufacturing systems that integrate manufacturing intelligence in
18   real time through the entire production operation have not been yet widely spread in the industry.
19   Examples have been demonstrated and integrated in real operation in the electrical appliance assembly
20   industry (Yoshimoto 2016). Combining process controls and automation allows cost optimization and
21   improved productivity (Edgar and Pistikopoulos 2018).
23   11.3.5 Electrification and fuel switching
24   The principle of electrification and fuel switching as a GHG mitigation strategy is that industries, to the
25   extent possible, switch their end uses of energy from a high GHG intensity energy carrier to a lower or
26   zero intensity one, including both its direct and indirect production and end-use GHG emissions. In
27   general, and non-exclusively, this implies a transition from coal (~0.09 tCO2·GJ-1 on combustion),
28   refined petroleum products (~0.07 tCO2·GJ-1), and natural gas (~0.05 tCO2·GJ-1) to biofuels, direct solar
29   heating, electricity, hydrogen, ammonia, or net zero synthetic hydrocarbon fuels. Switching to these
30   energy carriers is not necessarily lower emitting, however; how they are made matters.
31   Fuel switching has already been observed to reduce direct combustion CO2 emissions in many
32   jurisdictions. There are significant debates about the net effect of upstream fossil fuel production and
33   fugitive emissions, but observers have noted that in the case of US power generation it would take a
34   leakage rate of ~2.7% from natural gas production to undo the direct fuel switching from coal mitigation
35   effect, and the value is likely higher in most cases (Alvarez et al. 2012; Hausfather 2015). Coal mine
36   methane emissions are also estimated to be substantially higher than previously assessed (Kholod et al.
37   2020). Alvarez et al. (2018) estimated US fugitive emissions (not including the Permian) at 2.3% of
38   supply, 60% more than previously estimated, while recent Canadian papers indicate fugitive emissions
39   are at least 50% more than reported (Chan et al. 2020; MacKay et al. 2021). However, given the
40   potential for energy supply infrastructure lock-in effects (Tong et al. 2019), purely fossil fuel to fossil
41   fuel switching is a limited and potentially dangerous strategy unless it is used very carefully and in a
42   limited way.
43   Biofuels come in many forms, including ones that are nearly identical to fossil fuels but sourced from
44   biogenic sources. Solid biomass, either from direct from wood chips, lignin or processed pellets are the
45   most commonly used renewable fuel in industry today and are occasionally used in cement kilns and
46   boilers. Biomethane, biomethanol, and bioethanol are all commercially made today using fermentation
47   and anaerobic digestion techniques and are mostly “drop-in” compatible with fossil fuel equivalents. In

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 1   principle they cycle carbon in and out of the atmosphere, but their life cycle GHG intensities are
 2   typically not GHG neutral due to land use changes, soil carbon depletion, fertilizer use, and other
 3   dynamics (Hepburn et al. 2019), and are highly case specific. Most commercial biofuel feedstocks come
 4   from agricultural (e.g. corn) and food waste sources, and the feedstock is limited; to meet higher levels
 5   of biomass use a transition to using higher cellulose feedstocks like straw, switchgrass and wood waste,
 6   available in much larger quantities, must be fully commercialized and deployed. Significant efforts have
 7   been made to make ethanol from cellulosic biomass, which promises much higher quantities, lower
 8   costs, and lower intensities, but commercialization efforts, with a few exceptions, have largely not
 9   succeeded (Padella et al. 2019). The IEA estimates, however, that up to 20% of today’s fossil methane
10   use, including by industry, could be met with biomethane (IEA 2020g) by 2040, using a mixture of
11   feedstocks and production techniques. Biofuel use may also be critical for producing negative emissions
12   when combined with carbon capture and storage, i.e. BECCS. Most production routes for biofuels,
13   biochemicals and biogas generate large side streams of concentrated CO2 which is easily captured, and
14   which could become a source of negative emissions (Sanchez et al. 2018) (See section 11-3511.3.6).
15   Finally, it should be noted that biofuel combustion can, if inadequately controlled, have substantial
16   negative local air quality effects, with implications for SDGs 3, 7 and 11.
17   There is a large identified potential for direct solar heating in industry, especially in regions with strong
18   solar insolation and sectors with lower heat needs (<180C), for example, food and beverage processing,
19   textiles, and pulp and paper (Schoeneberger et al. 2020). The key challenges to adoption are site and
20   use specificity, capital intensity, and a lack of standardized, mass manufacturing for equipment and
21   supply chain to provide them.
22   Switching to electricity for end-uses, or “direct electrification”, is a highly discussed strategy for net
23   zero industrial decarbonisation (Palm et al. 2016; Lechtenböhmer et al. 2016; Davis et al. 2018; Bataille
24   et al. 2018a; UKCCC 2019b; Åhman et al. 2017; Axelson et al. 2018; Material Economics 2019).
25   Electricity is a flexible energy carrier that can be made from many forms of primary energy, with high
26   potential process improvements in terms of end-use efficiency (Eyre 2021), quality and process
27   controllability, digitizability, and no direct local air pollutants (Deason et al. 2018; McMillan et al.
28   2016; Jadun et al. 2017; Mai et al. 2018). The net GHG effect of electrification is contingent on how
29   the electricity is made, and because total output increases can be expected for full effect it should be
30   made with a very low GHG intensity primary sources (i.e. <50 grams CO2·kWh-1: e.g. hydroelectricity,
31   nuclear energy, wind, solar photovoltaics, or fossil fuels with 95+% carbon capture and storage (IPCC
32   2014)). This has strong implications for the electricity sector and its generation mix when the goal is a
33   net zero emissions electricity system. Despite their falling costs, progressively higher mixes of variable
34   wind and solar on a given grid will require support from grid flexibility sources, including demand
35   response, more transmission, storage on multiple time scales, or firm low to negative emissions
36   generation sources (e.g. nuclear energy, hydrogen fuel cells or turbines, biofuels, fossil or biofuels with
37   CCS, geothermal) to moderate costs (Jenkins et al. 2018; Sepulveda et al. 2018; Williams et al. 2021).
38   Regions that may be slower to reduce the GHG intensity of their electricity production will likely need
39   to consider more aggressive use of other measures, like energy and material efficiency or bioenergy.
40   The long-term potential for full process electrification is a very sector by sector and process by process
41   phenomenon, with differing energy and capacity needs, load profiles, stock turnover, capacity for
42   demand response, and characteristics of decision makers. Industrial electrification is most viable in the
43   near term in cases with: minimal retrofitting and rebuild in processes; with relatively low local
44   electricity costs; where the degree of process complexity and process integration is more limited and
45   extensive process re-engineering would not be required; where combined heat and power is not used;
46   where induction heating technologies are viable; and where process heating temperatures are lower
47   (Deason et al. 2018).

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 1   For these reasons, lighter, manufacturing orientated industries are more readily electrifiable than heavier
 2   industry like steel, cement, chemicals and other sectors with high heat and feedstock needs. Steam
 3   boilers, curing, drying and small-scale process heating, with typically lower maximum heat temperature
 4   needs (<200-250C) are readily electrifiable with appropriate fossil fuel to electricity price ratios
 5   (accounting for capital costs and efficiencies), and direct induction and infrared heating are available
 6   for higher temperature needs. These practices are uncommon outside regions with ample hydroelectric
 7   power due to the currently relatively low cost of coal, natural gas and heating oil, and especially when
 8   there is no carbon combustion cost. Madeddu et al. (2020) argue up to 78% of Europe’s industrial
 9   energy requirements are electrifiable through existing commercial technologies. In contrast (Mai et al.
10   2018) saw only a moderate industrial heat supply electrification in their high electrification scenario for
11   the US.
12   Electrification has also been explored in: raw and recycled steel (Fischedick et al. 2014b; Vogl et al.
13   2018); ammonia (Philibert 2017a; Bazzanella and Ausfelder 2017); and chemicals (Palm et al. 2016;
14   Bazzanella and Ausfelder 2017). While most chemical production of feedstock chemicals (e.g. H2, NH3,
15   CO, CH3OH, C2H4, C2H6, C2H5OH ) is done thermo-catalytically today, it is feasible to use direct
16   electrocatalytic production, by itself or in combination with utilization of previously captured carbon
17   sources if a fossil fuel feedstock is used, or well-known bio-catalytic (e.g. fermentation) and thermo-
18   catalytic processes (De Luna et al. 2019; Kätelhön et al. 2019; Bazzanella and Ausfelder 2017). It may
19   even be commercially possible to electrify cement sintering and calcination through plasma or
20   microwave options (Material Economics 2019).
21   Increased electrification of industry will result in increased overall demand for electricity. For example,
22   75 TWh of electricity was used by steel in the EU in 2015 (out of 1000 TWh total used by industry),
23   Material Economics (2019), varying between their new process, circularity and CCUS scenarios,
24   projects increased demand to 355 (+373%), 214 (+185%) and 238 (+217%) TWh. These values are
25   consistent with (Vogl et al. 2018), which projects a tripling of electricity demand in the German or
26   Swedish steel industries if hydrogen direct reduced iron and electric arc furnace steel making (DRI
27   EAFs) replaces BF-BOFs. Material Economics (2019) was conservative with its use of electricity in
28   chemical production, making preferential use of biofeedstocks and some CCUS, and electricity demand
29   still rose from 118 TWh to 510, 395 and 413 TWh in their three scenarios. (Bazzanella and Ausfelder
30   2017), exploring deeper reductions from the chemical sector using more electrochemistry, projected
31   scenarios with higher electricity demands of 960–4900 TWh (140% of projected available clean
32   electricity at the time) with maximum electricity use. In counterpoint, however, with revised wind
33   capabilities and costs, the (IEA 2019e) Offshore Wind Outlook indicates that ten times current EU
34   electricity use could be produced if necessary. Greater use of electro-catalytic versus thermo-catalytic
35   chemistry, as projected by (De Luna et al. 2019), could greatly reduce these electricity needs, but the
36   technology readiness levels are currently low. Finally, the (UKCCC 2019b), which focussed primarily
37   on CCS for industry in its “Further Ambition” scenario (the UK currently consumes about 300 TWh),
38   in its supplementary “Further electrification” scenario projects an additional 300 TWh for general
39   electrolysis needs and another 200 TWh for synthetic fuel production.
40   While it has been demonstrated that almost any heating end use can be directly electrified, this would
41   imply very high instantaneous thermal loads for blast furnace-basic oxygen furnace (BF-BOF) steel
42   production, limestone calcination for cement and lime production, and other end-uses where flame front
43   (1000°C–1700°C) temperatures are currently needed. This indicates a possible need for another energy
44   carrier to minimize instantaneous generation and transmission needs. These needs can be met at varying
45   current and potential future costs using: bioliquids or gases hydrogen, ammonia, or net zero synthetic
46   hydrocarbons or alcohols.
47   Broadly speaking, hydrogen can contribute to a cleaner energy system in two ways. 1) Existing
48   applications of hydrogen (e.g., nitrogen fertilizer production, refinery upgrading) can use hydrogen

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1    produced using alternative, cleaner production methods. 2) New applications can use low GHG
2    hydrogen as an alternative to current fuels and inputs, or as a complement to the greater use of electricity
3    in these applications. In these cases—for example in transport, heating, industry (e.g. hydrogen direct
4    reduced iron steel production) and electricity—hydrogen can be used in its pure form, or be converted
5    to hydrogen-based fuels, including ammonia, or synthetic net zero hydrocarbons & alcohols like
6    methane or methanol (IEA 2019f). The IEA states that hydrogen could be used to help integrate more
7    renewables, including by enhancing storage options and “exporting sunshine & wind” from places with
8    abundant resources; decarbonize steel, chemicals, trucks, ships and planes; and boost energy security
9    by diversifying the fuel mix & providing flexibility to balance grids (IEA 2019f).
10   Around 70 Mtonne·yr-1 of pure hydrogen is produced today, 76% from natural gas and 23% from coal,
11   resulting in emissions of roughly 830 MtCO2·yr-1 in 2016/17 (IEA 2019f), or 4.7% of global industrial
12   direct and indirect emissions (waste excluded, see Table 11.1) . Fuels refining (~410 MtCO2·yr-1) and
13   production of ammonia (420 MtCO2·yr-1) largely dominate its uses. Another 45 Mtonnes hydrogen is
14   being produced along with other gases, on purpose or as by-products, and used as fuel, to make
15   methanol or as a chemical reactant (IEA 2019f). Very low and potentially zero GHG (depending on the
16   energy source) hydrogen can be made via: electrolysis separation of water into hydrogen and oxygen
17   (Glenk and Reichelstein 2019), also known as “green H2”; electrothermal separation of water, as done
18   in some nuclear plants (Bicer and Dincer 2017); partial oxidation of coal or naphtha or steam/auto
19   methane reforming (SMR/ATR) combined with CCS (Leeson et al. 2017), or “blue H2”; methane
20   pyrolysis, where the hydrogen and carbon are separated thermally and the carbon is left as a solid (Ashik
21   et al. 2015; Abbas and Wan Daud 2010), or via biomass gasification (Ericsson 2017) (which could be
22   negative emissions if the CO2 from the gasification process is sequestered). All these processes would
23   in turn need to be run using very low or zero GHG energy carriers for the resulting hydrogen to also be
24   low GHG emissions.
25   Ammonia production, made from hydrogen and nitrogen using the Haber-Bosch process, is the most
26   voluminous chemical produced from fossil fuels, being used as feedstock for nitrogen fertilizers and
27   explosives, as well as a cleanser, refrigerant and for other uses. Most ammonia is made today using
28   methane as the hydrogen feedstock and heat source but has been made using electrolysis-based
29   hydrogen in the past, and there are several announced investments to resume doing so. If ammonia is
30   used as a combustion fuel care must be taken to avoid N2O as a GHG and NOx in general as a local air
31   pollutant.
32   Hydrogen can also be combined with low to zero net GHG carbon (see 11.3.6 and oxygen and made
33   into methane, methanol and other potential net zero synthetic hydrocarbons & alcohol energy
34   carriers using methanation, steam reforming and Fischer-Tropsch processes, all of which can provide
35   higher degrees of storable and shippable high temperature energy using known industrial processes in
36   novel combinations (Davis et al. 2018; Bataille et al. 2018a). If the hydrogen and oxygen is accessed
37   via electrolysis the terms “power-to-fuel” or “e-fuels” are often used (Ueckerdt et al. 2021). Given their
38   carbon content, if used as fuels, their carbon will eventually be oxidized and emitted as CO2 to the
39   atmosphere. This makes their net GHG intensity dependent on the carbon source (Hepburn et al. 2019),
40   with recycled fossil fuels, biocarbon and direct air capture carbon all having very different net CO2
41   impacts - see the next section on CCS and CCU for elaboration.
43   START BOX 11.1 HERE
45                                       Box 11.1 Hydrogen in industry

46   The ”hydrogen economy” is a long-touted vision for the energy and transport sectors, and one that has
47   gone through hype-cycles since the energy crises in the 1970s (Melton et al. 2016). The widely varying

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1    visions of hydrogen futures have mainly been associated with fuel cells in vehicles, small-scale
2    decentralized cogeneration of heat and electricity, and to a certain extent energy storage for electricity
3    (Eames et al. 2006; Syniak and Petrov 2008). However, nearly all hydrogen currently produced is used
4    in industry, mainly for hydrotreating in oil refineries, to produce ammonia, and in other chemical
5    processes, and it is mostly made using fossil fuels.
 6   In the context of net zero emissions new visions are emerging in which hydrogen has a central role to
 7   play in decarbonizing industry. Near-term industrial applications for hydrogen includes feeding it into
 8   ammonia production for fertilizers, while a noveler application would be as a replacement for coal as
 9   the reductant in steelmaking, being piloted by the HYBRIT project in Sweden 2020-2021, and many
10   companies have initiated hydrogen steelmaking projects. As shown in sections 11.3.5 and 11.3.6 there
11   are many other potential applications of hydrogen, some of which are still relatively unexplored.
12   Hydrogen can also be used to produce various lower GHG hydrocarbons and alcohols for fuels and
13   chemical feedstocks using carbon from biogenic sources or direct air capture of CO2 (Ericsson 2017;
14   Huang et al. 2020).
15   The geographical distribution of the potential for hydrogen from electrolysis powered by renewables
16   like solar and wind, nuclear electrothermally produced hydrogen, and hydrogen from fossil gas with
17   CCS may reshape where heavy industry is located, how value chains are organized, and what gets
18   transported in international shipping (Gielen et al. 2020; Bataille et al. 2021a; Saygin and Gielen 2021;
19   Bataille 2020a). Regions with bountiful renewables resources, nuclear, or methane co-located with CCS
20   geology may become exporters of hydrogen or hydrogen carriers such as methanol and ammonia, or
21   home to the production of iron and steel, organic platform chemicals, and other energy intensive basic
22   materials. This in turn may generate new trade patterns and needs for bulk transport.
24   END BOX 11.1 HERE

26   11.3.6 CCS, CCU, carbon sources, feedstocks, and fuels
27   Carbon is an important and highly flexible building block for a wide range of fuels, organic chemicals
28   and materials including methanol, ethanol, olefins, plastics, textiles, and wood and paper products. In
29   this chapter we define CCS as requiring return of CO2 from combustion or process gases or ambient air
30   to the geosphere for geological time periods, i.e. thousands of years (IEA 2009; IPCC 2005; IEA 2019g;
31   Bruhn et al. 2016). CCU is defined as being where carbon (as CO or CO2) is captured from one process
32   and reused for another, reducing emissions from the initial process, but is then potentially but not
33   necessarily released to the atmosphere in following processes (Tanzer and Ramírez 2019; Detz and van
34   der Zwaan 2019; Bruhn et al. 2016). In both cases the net effect on atmospheric emissions depends on
35   the initial source of the carbon, be it from a fossil fuel, from biomass, or from direct air capture (Cuéllar-
36   Franca and Azapagic 2015; Hepburn et al. 2019) and the duration of storage or use, which can vary
37   from days to millennia.
38   While CCS and CCU share common capture technologies, what happens to the CO2 and therefor the
39   strategies that will employ them can be very different. CCS can help maintain near CO2 neutrality for
40   fossil CO2 that passes through the process, with highly varying partially negative emissions if the source
41   is biogenic (Hepburn et al. 2019), and fully negative emissions if the source is air capture, all not
42   considering the energy used to drive the above processes. CCS has been covered in other IPCC
43   publications at length, for example, IPCC (2005), and in most mitigation oriented assessments since,
44   for example, the IEA’s ETP 2020 and Net Zero scenario reports (IEA 2021a, 2020a). The potentials
45   and costs for CCS in industry vary considerably due to the diversity of industrial processes (Leeson et
46   al. 2017), as well as the volume and purity of different flows of carbon dioxide (Naims 2016); Kearns

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1    et al. (2021) provide a recent review. As a general rule it is not possible to capture all the carbon dioxide
2    emissions from an industrial plant. To achieve zero or negative emissions, CCS would need to be
3    combined with some use of sustainably sourced biofuel or -feedstock, or the remaining emissions would
4    need to be offset by CDR elsewhere.
 5   For concentrated CO2 sources (e.g. cleaning of wellhead formation gas to make it suitable for the
 6   pipeline network, hydrogen production using steam methane reforming, ethanol fermentation, or from
 7   combustion of fossil fuels with oxygen in a nitrogen free environment, i.e. “oxycombustion”) CCS is
 8   already amenable to commercial oil and gas reinjection techniques used to eliminate hydrogen sulphide
 9   gas and brines at prices of 10–40 USD·tCO2-eq-1 sequestered (Wilson et al. 2003; Leeson et al. 2017).
10   Most currently operating CCS facilities take advantage of concentrated CO2 flows, for example, from
11   formation gas cleaning on the Snoevit and Sleipner platforms in Norway, from syngas production for
12   the Al Reyadah DRI steel plant in Abu Dhabi, and from SMR hydrogen production on the Quest
13   upgrader in Alberta. Since concentrated process CO2 emissions are often exempted from existing cap
14   and trade systems, these opportunities for CCS have largely gone unexploited. Many existing projects
15   partially owe their existence to the utilization of the captured CO2 for enhanced oil recovery, which in
16   many cases counts as both CCS and CCU because of the permanent nature of the CO2 disposal upon
17   injection if sealed properly (Mac Dowell et al. 2017). There are several industrial CCS strategies and
18   pilot projects working to take advantage of the relative ease of concentrated CO2 disposal (e.g. LEILAC
19   for limestone calcination process emissions from cement production, HISARNA direct oxycombustion
20   smelting for steel) (Bataille 2020a). An emerging option for storing carbon is methane pyrolysis by
21   which methane is split into hydrogen and solid carbon that may subsequently be stored (Schneider et
22   al. 2020).
23   There are several post-combustion CCS projects underway globally (IEA 2019g), generally focussed
24   on energy production and processing rather than industry. Their costs are higher but evolving downward
25   – (Giannaris et al. 2020) suggest 47 USD·tCO2-1 for a follow up 90% capture power generation plant
26   based on learnings from the Saskpower Boundary Dam pilot – but crucially these costs are higher than
27   implicit and explicit carbon prices almost everywhere, resulting in limited investment and learning in
28   these technologies. A key challenge with all CCS strategies, however, is building a gathering and
29   transport network for CO2, especially from dispersed existing sites; hence most pilot are built near
30   EOR/geological storage sites, and the movement towards industrial clustering in the EU and UK
31   (UKCCC 2019b), and as suggested in (IEA 2019f).
32   In the case of CCU, CO and CO2 are captured and subsequently converted into valuable products (e.g.
33   building materials, chemicals, synthetic fuels) (Daggash et al. 2018; Styring et al. 2011; Vreys et al.
34   2019; Artz et al. 2018; Breyer et al. 2019; Brynolf et al. 2018; Bruhn et al. 2016; Kätelhön et al. 2019).
35   CCU has been envisioned as part of the “circular economy” but conflicting expectations on CCU and
36   its association or not with CCS leads to different and contested framings (Palm and Nikoleris 2021).
37   The duration of the CO2 storage in these products varies from days to millennia according to the
38   application, potentially but not necessarily replacing new fossil, biomass or direct air capture
39   feedstocks, before meeting one of several possible fates: permanent burial, decomposition, recycling or
40   combustion, all with differing GHG implications. While the environmental assessment of CCS projects
41   is relatively straight forward, however, this is not the case for CCU technologies. The net GHG
42   mitigation impact of CCU depends on several factors (e.g. the capture rate, the energy requirements,
43   the lifetime of utilization products, the production route that is substituted, and associated room for
44   improvement along the traditional route) and has to be determined by life cycle CO2 or GHG analysis
45   (e.g. Nocito and Dibenedetto (2020) and Bruhn et al. (2016)). For example, steel mill gases containing
46   carbon monoxide and carbon dioxide can be used as feedstock together with hydrogen for producing
47   chemicals. In this way, the carbon originally contained in the coke used in the blast furnace is used
48   again, or cascaded, and emissions reduced but not brought to zero. If fossil sourced CO2 is only reused

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1    once and then emitted, the maximum reduction is 50% (Tanzer and Ramírez 2019). The logic of using
2    steel mill CO and CO2 could equally be applied to gasified biomass, however, with a far lower net GHG
3    footprint, likely negative, which CCU fed by fossil fuels cannot be if end-use combustion is involved.
 4   Partly because of the complexity of the life cycle analysis accounting, the literature on CCU is not
 5   always consistent in terms of the net GHG impacts of strategies. For example, Artz et al. (2018),
 6   focussed not just on GHG mitigation but multi-attribute improvements to chemical processes from
 7   reutilization of CO2, suggests the largest reduction in the absolute amount of GHGs from CO2
 8   reutilization could be achieved by coupling of highly concentrated CO2 sources with carbon-free
 9   hydrogen or electrons from low GHG power in so called “Power-to-fuel” scenarios. From the point of
10   view of maximizing GHG mitigation using surplus “curtailed” renewable power, however, Daggash et
11   al. (2018) instead indicates the best use would be for direct air capture and CCS. These results depend
12   on what system is being measured, and what the objective is.
13   There are several potential crucial transitional roles for synthetic hydrocarbons & alcohols (e.g.
14   methane, methanol, ethanol, ethylene, diesel, jet fuel) constructed using fossil, biomass or direct carbon
15   capture (DAC) and CCU (Fasihi et al. 2017; Sternberg and Bardow 2015; Breyer et al. 2015; Dimitriou
16   et al. 2015; Bataille 2020a; Bataille et al. 2018a). They can allow reductions in the GHG intensity of
17   high value legacy transport, industry and real estate that currently runs on fossil fuels but cannot be
18   easily or readily retrofitted. They can be used by existing long lived energy and feedstock infrastructure,
19   transport and storage, which can compensate for seasonal supply fluctuations and contribute to
20   enhancing energy security (Ampelli et al. 2015). Finally, they can reduce the GHG intensity of end-
21   uses that are very difficult to run on electricity, hydrogen or ammonia (e.g., long haul aviation).
22   However, their equivalent mitigation cost today would be very high (USD 960–1440 tCO2-eq-1), with
23   the potential to fall to USD 24–324 tCO2-eq-1) with commercial economies of scale, with very high
24   uncertainty (Hepburn et al. 2019; Ueckerdt et al. 2021; IEA 2020a).
25   A very large and important uncertainty is the long-term demand for hydrocarbon and alcohol fuels
26   (whether fossil, biomass or DAC based), chemical feedstocks (e.g., methanol and ethylene) and
27   materials, and competition for biomass feedstock with other priorities, including agriculture,
28   biodiversity and other proximate land use needs, as well as need for negative emissions through BECCS.
29   The current global plastics production of around 350 Mt·yr-1 is almost entirely based on petroleum
30   feedstock and recycling rates are very low. If this or future demand were to be 100% biomass based it
31   would require tens of exajoules of biomass feedstock (Meys et al. 2021). If demand can be lowered and
32   recycling increased (mechanical as well as chemical) the demand for biomass feedstock can be much
33   lower (Material Economics 2019). Promising routes in the short term would be to utilise CO2 from
34   anaerobic digestion for biogas and fermentation for ethanol in the production of methane or methanol
35   (Ericsson 2017); methanol can be converted into ethylene and propylene in a methanol-to-olefins
36   process and used in the production of plastics (Box 11.2). New process configurations where hydrogen
37   is integrated into biomass conversion routes to increase yields and utilise all carbon in the feedstock are
38   relatively unexplored (Ericsson 2017; De Luna et al. 2019).
39   There are widely varying estimates of the capacity of CCU to reduce GHG emissions and meet the net-
40   zero objective. According to Hepburn et al. (2019), the estimated potential for the scale of CO2
41   utilisation in fuels varies widely, from 1 to 4.2 GtCO2·yr−1, reflecting uncertainties in potential market
42   penetration, requiring carbon prices of around USD 40 to 80 tCO2-1, increasing over time. The high end
43   represents a future in which synthetic fuels have sizeable market shares, due to cost reductions and
44   policy drivers. The low end—which is itself considerable—represents very modest penetration into the
45   methane and fuels markets, but it could also be an overestimate if CO2-derived products do not become
46   cost competitive with alternative clean energy vectors such as hydrogen or ammonia, or with direct
47   sequestration. Brynolf et al. (2018) indicates that a key cost variable will be the cost of electrolysers for
48   producing hydrogen. Kätelhön et al. (2019) estimate that up to 3.5 GtC·yr−1 could be displaced from

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1    chemical production by 2030 using CCU, but this would require clean electricity equivalent to 55% of
2    estimated global power production, at the same time other sectors’ demand would also be rising. Mac
3    Dowell et al. (2017) suggest that while CCU, and specifically CO2 based enhanced oil recovery, may
4    be an important economic incentive for early CCS projects (up to 4–8% of required mitigation by 2050),
5    it is unlikely the chemical conversion of CO2 for CCU will account for more than 1% of overall
6    mitigation.
 7   Finally, there is another class of CCU activities associated with carbonation of alkaline industrial wastes
 8   (including iron and steel slags, coal fly ash, mining and mineral processing wastes, incinerator residues,
 9   cement and concrete wastes, and pulp and paper mill wastes) using waste or atmospheric CO2. Given
10   the large volume of alkaline wastes produced by industry, capture estimates are as high at 4 GtCO2·yr−1
11   (Pan et al. 2020; Huang et al. 2019c; Kaliyavaradhan and Ling 2017; Cuéllar-Franca and Azapagic
12   2015; Pasquier et al. 2018; Ebrahimi et al. 2017; Zhang et al. 2020) However, as some alkaline wastes
13   are already used directly as supplementary cementious materials to reduce clinker-to-cement ratios, and
14   their abundant availability in the future is questionable (e.g. steel blast furnace slag and coal fly ash),
15   there will be a strong competition between mitigation uses (see 11.4.2), and the potential for direct
16   removal by carbonation is estimated at about 1 GtCO2·yr−1 (Renforth 2019).
17   The above CCU literature has identified that there may be a highly unpredictable competition between
18   fossil, biogenic and direct air capture carbon to provide highly uncertain chemical feedstock, material
19   and fuel needs. Fossil waste carbon will likely initially be plentiful but will add to net atmospheric CO2
20   when released. Biogenic carbon is variably, partially net-negative, but the available stock will be finite
21   and compete with biodiversity and agriculture needs for land. Direct air capture carbon will require
22   significant amounts of low GHG electricity or methane with high capture rate CCS (Keith et al. 2018).
23   There are clearly strong interactive effects between low carbon electrification, switching to biomass,
24   hydrogen, ammonia, synthetic hydrocarbons via CCU, and CCS.
26   11.3.7 Strategy interactions and integration

28              Figure 11.9 Fully interactive, non-sequential strategies for decarbonising industry

30   In this section we conceptually address interactions between service demand, service product intensity,
31   product material efficiency, energy efficiency, electrication and fuel switching, CCU and CCS, and
32   what conflicts and synergies may exist. Post AR5 a substantial literature has emerged, see Rissman et
33   al. (2020), that addresses integrated and interactive technical deep decarbonization pathways for GHG
34   intense industrial sectors, and how they interact with the rest of the economy (Denis-Ryan et al. 2016;
35   Wesseling et al. 2017; Davis et al. 2018; Axelson et al. 2018; Åhman et al. 2017; Bataille et al. 2018a;
36   Bataille 2020a). It is a common finding across this literature and a related scenario literature (Energy
37   Transitions Commission 2018; Material Economics 2019; IEA 2021a; CAT 2020; UKCCC 2019a,b;
38   IEA 2019b, 2020a) that deep decarbonisation of industry requires integrating all available options.
39   There is no ‘silver bullet’ and so all behavioural and technological options have to be mobilized, with
40   more emphasis required on the policy mechanisms necessary to engage a challenging transition in the

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1    coming decades in highly competitive, currently GHG intense, price sensitive sectors with long lived
2    capital stock (Wesseling et al. 2017; Bataille et al. 2018a; Bataille 2020a), discussed in the final section
3    of this chapter.
4    While the strategies are not sequential and interact strongly, we discuss them in the order given.
5    Reduced demand through reduced service demand and product intensity per service unit (van Vuuren
6    et al. 2018; Grubler et al. 2018) reduces the need for the next five strategies. Greater material efficiency
7    (see earlier sections) reduces the need for the next four, and so on – see Figure 11.9 above.
 8   Circular economy introduces itself throughout, but mainly at the front end when designing materials
 9   and processes to be more materially efficient, efficient in use, and easy to recycle, and at the back end,
10   when a material or product’s services life has come to end, and it is time for recycling or sustainable
11   disposal (Korhonen et al. 2018; Murray et al. 2017). The entire chain’s potential will be maximized
12   when these strategies are designed in ahead of time instead of considered on assembly, or as a retrofit
13   (Material Economics 2019; Allwood et al. 2012; Gonzalez Hernandez et al. 2018a; IEA 2019b; Bataille
14   2020a). For example, when designing a building: 1) Is the building shell, interior mass and ducting
15   orientated for passive heating and cooling, and can the shell and roof have building integrated solar PV
16   or added easily, with hard-to-retrofit wiring already incorporated? 2) Are steel and high quality concrete
17   only used where really needed (i.e. for shear, tension and compression strength), can sections be
18   prefabricated off-site, can other materials be substituted, such as wood? 3) Can the interior fittings be
19   built with easy to recycle plastics or other sustainably disposable materials (e.g. wood)? 4) Can this
20   building potentially serve multiple purposes through its anticipated lifetime, are service conduits
21   oversized and easy to access for retrofitting? 5) When it is time to be taken apart, can pieces be reused,
22   and all componnents recycled at high purity levels, for example, can all the copper wiring be easily be
23   found and removed, are the steel beams clearly tagged with their content? The answers to these
24   questions will be very regionally and site specific, and require revision of educational curricula for the
25   entire supply chain, as well as revision of building codes.
26   Energy efficiency is a critical strategy for net zero transitions and enabling clean electrification (IEA
27   2021a). Improving the efficiency of energy services provision reduces the need for material intensive
28   energy supply, energy storage, CCU and CCS infrastructure, and limits generation and transmission
29   expansion to meet an ever-higher power demand, with associated generation, transmission, and
30   distribution losses. Using electricity efficiently can help reduces peak demand and the need for peaking
31   plants (currently often powered by fossil fuels), and energy storage systems.
32   Electrification and final energy efficiency are deeply entangled, because switching to electricity from
33   fossil fuels in most cases improves GJ for GJ end-use energy efficiency: resistance heaters are almost
34   100% efficient, heat pumps can be 300–400% efficient, induction melting can improve mixing and
35   temperature control, and electric vehicle motors typically translate 90-95% of input electricity to motor
36   drive in contrast to 35–45% for a large, modern internal combustion engine. Overall, the combined
37   effect could be 40 % lower global final energy demand assuming renewable electricity is used (Eyre
38   2021).
39   There are potentially complicated physical and market fuel switching relationships between low GHG
40   electricity, bioliquids and gases, hydrogen, ammonia, and synthetic hydrocarbons constructed using
41   CCU, with remaining CO2 potentially being disposed of using CCS. Whether or not they compete for
42   a wide range of end uses and primary demand needs will be regional and whether or not infrastructure
43   is available to supply them. Regions with less than optimal renewable energy resources, or not sufficient
44   to meet growing needs, could potentially indirectly import them as liquid or compressed hydrogen,
45   ammonia or synthetic hydrocarbon feedstocks made in regions with abundant resources (Armijo and
46   Philibert 2020; Bataille 2020a). Large scale CCU and CCS applications needs additional basic materials
47   to build corresponding infrastructure and energy to operate it thus reducing overall material and energy
48   efficiencies.

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1   There are different roles for different actors in relation to the different mitigation strategies (exemplified
2   in Table 11.2), with institutions and supply chains developed to widely varying levels, for example,
3   while energy efficiency is a relatively mature strategy with an established supply chain, material
4   efficiency is not.

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1   Table 11.2 Examples of the potential roles of different actors in relation to different mitigation strategies indicating the importance of engaging a wide set of actors
2                                                                       across all mitigation strategies.

     Sectors          Demand      control      Materials Efficiency    Circular Economy       Energy             Electrification,        CCU                     CCS
                      measures (DM)            (ME)                                           Efficiency         hydrogen and fuel
     Architectural,   Build awareness on       Education          of   Design and build       Maintain high      Support innovation.     Develop allocation      Transparency,
     and              the material demand      designers,              for e.g., repurpose,   expertise,         Share best practice.    rules, monitoring and   monitoring      and
     engineering      implications of e.g.,    architects,             reuse, and recycle.    knowledge          Design for dynamic      transparency.           labelling.
     firms            building codes, urban    engineers, etc.         Improve                sharing,           demand response         Coordination      and   Coordination and
                      planning,         and    Develop        design   transparency     on    transparency,      for grid balancing.     collaboration across    collaboration for
                      infrastructure.          tools. Map material     volumes and flows.     and                                        sectors.                transport       and
                                               flows.                                         benchmarking.                                                      disposal
     Industry and     Digital solutions to     Design for durability   Design for reuse       Maintain energy    Develop and deploy      Develop          new    Plan for CCS
     service sector   reduce office space      and light weight.       and recycling. Use     management         new technologies in     technologies.           where possible and
                      and travel. Service      Minimize industry       recycled feedstock     systems.           production, engage      Engage in new value     phase-out of non-
                      oriented     business    scrap.                  and        develop                        with lead markets.      chains           and    retrofittable plants
                      models for lower                                 industrial                                                        collaborations    for   where necessary.
                      product demand.                                  symbiosis.                                                        sourcing carbon.
     International    Best practice sharing.   Progressivity    in     Transparency and       Maintain efforts   Coordinate              Coordinate       and    Align regulation to
     bodies           Knowledge building       international           regulation around      for sharing good   innovation efforts,     develop accounting      facilitate export,
                      on demand options.       standards     (e.g.,    products,    waste     practice     and   technology transfer,    and        standards.   transport,     and
                                               ISO).                   handling,    trade,    knowledge.         lead markets, and       Ensure transparency.    storage.
                                                                       and recycling.                            trade policies.
     Regional and     Reconsider spatial       Procurement             Regulation      on     Continue energy    R&D              and    Align regulation to     Develop regulation
     national         planning        and      guidelines and better   product     design     efficiency         electricity             facilitate              and          make
     government,      regulation that has      indicators.             (e.g.,   Ecodesign     policies such as   infrastructure.         implementation and      investment viable.
     and cities       demand implications.     Standards        and    directive)             incentives,        Policy strategies for   ensure accountability   Resolve long term
                                               building codes.         Collect    material    standards,         making investment       for emissions.          liabilities.
                                                                       flow data.             labels,      and   viable (including
                                                                                              disclosure         carbon       pricing
                                                                                              requirements.      instruments).

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     Civil society   Information     and   Strengthen    lobby   Engage         in   Monitor          Information      on    Develop standards       Ensure
     and consumer    advocacy related to   efforts         and   standards,          progress.        embodied               and accounting rules.   transparency and
     organizations   social norms.         awareness around      monitoring    and                    emissions. Assess                              accountability
                                           e.g.,       planned   transparency.                        renewable
                                           obsolescence.                                              electricity and grid

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1    11.4 Sector mitigation pathways and cross sector implications
2    This section continues the discussion of the various mitigation options and strategy elements introduced
3    in section 11.3 and makes them explicit for the most relevant industry sectors. For the various sectors
4    11.4.1 concludes with a tabular overview of key technologies and processes, their technology readiness
5    level (TRL), potential timing of market penetration, mitigation potential and assessment of associated
6    mitigation costs.
 7   An integrated sequencing of mature short-term actions and less mature longer-term actions is crucial to
 8   avoid lock-in effects. Temporal implementation and discussion of the general quantitative role of the
 9   different options to achieve net zero emissions in the industrial sectors is core to the second part of the
10   section (11.4.2), where industry wide mitigation pathways are analysed. This comprises the collection
11   and discussion of mitigation scenarios available in the literature with a high technological resolution
12   for the industry sector in addition to a set of illustrative global and national GHG mitigation scenarios
13   selected from chapter 3 and 4 representing different GHG mitigation ambitions and different pathways
14   to achieve certain mitigation targets. Comparing technology focussed sector-based scenarios with more
15   top-down oriented scenario approaches allows for a reciprocal assessment of both perspectives and
16   helps to identify robust elements for the transformation of the sector. Comparison of real-world
17   conditions within the sector (e.g., industry structure and logics, investment cycles, market behaviour,
18   power, and institutional capacity) and the transformative pathways described in the scenarios helps
19   researchers, analysts, governments, and all stakeholders understand the need not only for technological
20   change, but for structural (e.g., new value chains, markets, infrastructures, and sectoral couplings) and
21   behavioural (e.g., design practices and business models) change at multiple levels.
22   When undergoing a transformative process, it is obvious that interactions occur, within the sector but
23   also on a cross-sectoral basis. Relevant interactions are identified and discussed in the third and fourth
24   part of the sub-section. Changes are induced along the whole value chains, i.e., switching to an
25   alternative (climate-friendly, e.g., low GHG hydrogen based) steel making process has substantial
26   impacts on the value chain, associated sub-suppliers, and electricity and coal outputs. In addition, cross-
27   sectoral interactions are discussed. This includes feedback loops with other end-use chapters, for
28   example, higher material demand through market penetration of some GHG mitigation technologies or
29   measures (e.g., insulation materials for buildings, steel for windmills) and lower demand through others
30   (e.g., less steel for fossil fuel extraction, transport and processing), or substantial additional demand of
31   critical materials (e.g., the widely varying demands for copper, lithium, nickel, cobalt and rare earths
32   for producing windmills, solar panels, and batteries). Generally, if consumption (or behaviour) driven
33   additional material demand creates scarcity it becomes important to increase efforts on material
34   efficiency, substitution, recycling/re-use, and sustainable consumption patterns.
36   11.4.1 Sector specific mitigation potential and costs
37   Based on the general discussion of strategies across industry in Section 11.3 this sub-section focuses on
38   the sector perspective and provides insights into the sector specific mitigation technologies and
39   potentials. As industry is comprised of many different sub-sectors, the discussion here has its focus on
40   the most important sources of GHG emissions, that is, steel, cement and concrete, as well as chemicals,
41   before other sectors are discussed.
43 Steel
44   For the period leading up to 2020, in terms of end-use allocation globally, approximately 40% of steel
45   is used for structures, 20% for industrial equipment, 18% for consumer products, 13% for infrastructure,

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 1   and 10% for vehicles (Bataille 2020b). The global production of crude steel increased by 41 % between
 2   2008 and 2020 (World Steel Association 2021) and its GHG emissions depending on the scope covered
 3   is 3.7–4.1 GtCO2-eq. It represented 20% of total global direct industrial emissions in 2019 accounting
 4   for coke oven and blast furnace gases use Figure 11.4 and Table 11.1 (Crippa et al. 2021; Lamb et al.
 5   2021; Minx et al. 2021; Olivier and Peters 2018; World Steel Association 2021; IEA 2020a). Steel
 6   production can be divided into primary production based on iron ore and secondary production based
 7   on steel scrap. The blast furnace to basic oxygen furnace route (BF-BOF) is the main primary steel route
 8   globally, while the electric arc furnace (EAF) is the preferred process for the less energy and emissions-
 9   intensive melting and alloying of recycled steel scrap. The direct reduced iron (DRI) route is a lesser
10   used route that replaces BFs for reducing iron ore, usually followed by an EAF. In 2019, 73% of global
11   crude steel production was produced in BF-BOFs, while 26% was produced in EAFs, a nominal 5.6%
12   of which is DRI (World Steel Association 2021) .
13   An estimated 15% energy efficiency improvement is possible within the BF-BOF process (Figure 11.8).
14   Several options exist for deep GHG emissions reductions in steel production processes (Leeson et al.
15   2017; Axelson et al. 2018; Fan and Friedmann 2021; Fischedick et al. 2014b; Wang et al. 2021; Holappa
16   2020; Bataille 2020a; Vogl et al. 2018; Rissman et al. 2020). Each could reduce specific CO2 emissions
17   of primary steel production by 80% or more relative to today’s dominant BF-BOF route if input streams
18   are based on carbon-free energy and feedstock sources or if they deploy high capture CCS:
19       •   Increasing the share of the secondary route can bring down emissions quickly and potential
20           emissions savings are significant, from a global average 2.3 tCO2-1 per tonne steel in BF-BOFs
21           down to 0.3 (or less) tCO2-1 per tonne steel in EAFs (Pauliuk et al. 2013a; Zhou et al. 2019), the
22           latter depending scrap preheating and electricity GHG intensity. However, realising this
23           potential is dependent on the availability of regional and global scrap supplies and requires
24           careful sorting and scrap management, especially to eliminate copper contamination (Daehn et
25           al. 2017). There is significant uncertainty how much new scrap will be available and usable
26           (IEA 2019b; Xylia et al. 2018; Wang et al. 2021). Most steel is recycled already; the gains are
27           mainly to be made in quality, i.e. separation from contaminants like copper. End of life scrap
28           availability and its contribution to steel production will increase as in use stock saturates in
29           many countries (Xylia et al. 2016).
30       •   BF-BOFs with CCU or CCS. Abdul Quader et al. (2016) and Fan and Friedmann (2021)
31           indicate that it would be difficult to retrofit BF-BOFs beyond 50% capture, which is insufficient
32           for long term emission targets, but may be useful in some cases for avoiding cumulative
33           emissions where other options are not available. However, BF-BOFs need their furnaces relined
34           every 15–25 years (IEA 2021a; Vogl et al. 2021b), at a cost 80–100% of a new build, and this
35           would be an opportunity to build a new facility designed for 90%+ capture (e.g. fewer CO2
36           outlets). This would depend upon access to transport to geology appropriate for CCS.
37       •   Methane based syngas (hydrogen and carbon monoxide) direct reduced iron (DRI) with CCS.
38           Most DRI facilities currently use a methane-based syngas of H2 and CO as both reductant and
39           fuel (some use coal). A syngas DRI-EAF steel making facility has been operating in Abu Dhabi
40           since 2016 that captures carbon emitted from the DRI furnace (where it is a co-reductant with
41           hydrogen) and sends it to a nearby oil field for enhanced oil recovery.
42       •   Hydrogen-based direct reduced iron (H-DRI) is based on the already commercialized DRI
43           technology but using only hydrogen as the reductant; pure hydrogen has already been used
44           commercially by Circored in Trinidad 1999-2008. The reduction process of iron ore is typically
45           followed by an EAF for smelting. During a transitional period, DRI could start with methane
46           or a mixture of methane and hydrogen as some of the methane (<=30% hydrogen can be
47           substituted with green or blue hydrogen without the need to change the process). If the hydrogen
48           is produced based on carbon-free sources, this steel production process can be nearly CO2
49           neutral (Vogl et al. 2018).

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 1       •   In the aqueous electrolysis route (small scale piloted as Siderwin during the EU ULCOS
 2           program), the iron ore is bathed in an electrolyte solution and an electric current is used to
 3           remove the oxygen, followed by an electric arc furnace for melting and alloying. In the molten
 4           oxide electrolysis route, an electric current is used to directly reduce and melt the iron ore using
 5           electrolysis in one step, followed by alloying. These processes both promise a significant
 6           increase in energy efficiency compared with the direct reduced iron and blast furnace routes
 7           (Cavaliere 2019). If the electricity used is based on carbon-free sources, this steel production
 8           process can be nearly CO2 neutral. Both processes would require supplemental carbon, but this
 9           is typically only up to 0.05% per tonne steel, with a maximum of 2.1%. Aqueous electrolysis
10           is possible with today’s electrode technologies, while molten oxide electrolysis would require
11           advances in high temperature electrodes.
12       •   The HIsarna® process is a new type of coal-based smelting reduction process, which allows
13           certain agglomeration stages (coking plant, sintering/pelletizing) to be dispensed with. The iron
14           ore, with a certain amount of steel scrap, is directly reduced to pig iron in a single reactor. This
15           process is suitable to be combined with CCS technology because of its relatively easy to capture
16           and pure CO2 exhaust gas flow. CO2 emission reductions of 80% are believed to be realisable
17           relative to the conventional blast furnace route (Abdul Quader et al. 2016). The total GHG
18           balance also depends on the further processing in a basic oxygen furnace or in an EAF. The
19           HIsarna process was small scale piloted under the EU ULCOS program.
20       •   Hydrogen co-firing in BF-BOFs can potentially reduce emission by 30-40%, referring to
21           experimental work by the Course50 projects and Thyssen Krupp, but coke is required to
22           maintain stack integrity beyond that.
23   Reflecting the different conditions at existing and potential future plant sites, when choosing one of the
24   above options a combination of different measures and structural changes (including electricity,
25   hydrogen and CCU or CCS infrastructure needs) will likely be necessary in the future to achieve deep
26   reductions in CO2 emissions of steel production.
27   In addition, increases in material efficiency (e.g., more targeted steel use per vehicle, building or piece
28   of infrastructure) and increases in the intensity of product use (e.g. sharing cars instead of owning them)
29   can contribute significantly to reduce emissions by reducing the need for steel production. The IEA
30   (2019b) suggested that up to 24% of cement and 40% of steel demand could be plausibly reduced
31   through strong material efficiency efforts by 2060. Potential material efficiency contribution for the EU
32   is estimated to be much higher—48% (Material Economics 2019). Recycling would cut the average
33   CO2 emissions per tonne of steel produced by 60% (Material Economics 2019), but globally by 2050
34   secondary steel production is limited to 40–56% in various scenarios (IEA 2019b), with 46% in the IEA
35   (2021a) and up to 56% in 2050 in Xylia et al. (2016). It may scale up to 68% by 2070 (Xylia et al.
36   2016). CCU and more directly CCS are other options to reduce GHG emissions but depend on the full
37   life cycle net GHGs that can be allocated to the process (see 11.3.6). Bio-based fuels can also substitute
38   for some of the coal input, but due to other demands for biomass this strategy is likely to be limited to
39   specific cases.
40   Abatement costs for these strategies vary considerably from case to case and for each a plausible cost
41   range is difficult to establish; cf. Table 11.3 (Leeson et al. 2017; Axelson et al. 2018; Fischedick et al.
42   2014b; Wang et al. 2021; Vogl et al. 2018; Fan and Friedmann 2021). A key point is that while cost of
43   production increases are significant, the effect on final end-uses is typically very small (Rootzén and
44   Johnsson 2016), with significant policy consequences (See Section 11.6 on public and private lead
45   markets for cleaner materials).

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1 Cement and concrete
 2   The cement sector is regarded as a sector where mitigation options are especially narrow (Energy
 3   Transitions Commission 2018; Habert et al. 2020). Cement is used as the glue to hold together sand,
 4   gravel and stone aggregates to make concrete, the most consumed manufactured substance globally.
 5   The production of cement has been increasing faster than the global population since the middle of the
 6   last century (Scrivener et al. 2018). Despite significant improvements in energy efficiency over the last
 7   couple of decades (e.g. a systematic move from wet to dry kilns with calciner preheaters feeding off the
 8   kilns) the direct emissions of cement production (sum of energy and process emissions) are estimated
 9   to be 2.1–2.5 GtCO2-eq in 2019 or 14–17% of total global direct industrial GHG emissions (Figure
10   11.4) (Crippa et al. 2021; Lehne and Preston 2018; Hertwich 2021; Sanjuán et al. 2020; Lamb et al.
11   2021; Bataille 2020a). Typically, about 40% of these direct emissions originates from process heating
12   (e.g. for calcium carbonate (limestone) decomposition into calcium oxide at 850°C or higher, directly
13   followed by combination with cementious materials at about 1,450°C to make clinker), while 60% are
14   process CO2 emissions from the calcium carbonate decomposition (Kajaste and Hurme 2016; IEA and
15   WBCSD 2018; Andrew 2019). Some of the CO2 is reabsorbed into concrete products and can be seen
16   as avoided during the decades long life of the products; estimates of this flux vary between 15 and 30%
17   of the direct emissions (Schneider 2019; Stripple et al. 2018; Andersson et al. 2019; GCCA 2021a; Cao
18   et al. 2020). Some companies are mixing CO2 into hardening concrete, both to dispose of the CO2 and
19   more importantly reduce the need for binder (Lim et al. 2019).
20   One of the simplest and most effective ways to reduce cement and concrete emissions is to make
21   stronger concrete through better mixing and aggregate sizing and dispersal; poorly and well-made
22   concrete can vary in strength by a factor of 4 for a given volume (Fechner and Kray 2012; Habert et al.
23   2020). This argues for a refocus of the market away from “one size fits all”, often bagged, cements to
24   professionally mixed clinker, cementious material and filler mixtures appropriate to the needs of the
25   end use.
26   Architects, engineers and contractors also tend to overbuild with cement because it is cheap as well as
27   corrosion and water resistant. Buildings and infrastructure can be purposefully designed to minimize
28   cement use to its essential uses (e.g. compression strength and corrosion resistance), and replace its use
29   with other materials (e.g. wood, stone, other fibres) for non-essential uses. This could reduce cement
30   use by 20–30% (D’Alessandro et al. 2016; Imbabi et al. 2012; Brinkerhoff and GLDNV 2015; Lehne
31   and Preston 2018; Shanks et al. 2019; IEA 2019b; Habert et al. 2020).
32   Because so much of the emissions from concrete come from the limestone calcination to make clinker,
33   anything that reduces use of clinker for a given amount of concrete reduces it GHG intensity. While
34   95% Portland cement is common in some markets, it is typically not necessary for all end-use
35   applications, and many markets will add blast furnace slag, coal fly ash, or natural pozzolanic materials
36   to replace cement as supplementary cementious materials; 71% was the global average clinker content
37   of cement in 2019 (IEA 2020a). All these materials are limited in volume, but combination of roughly
38   2–3 parts ground limestone and one part specially selected, calcined clays can also be used to replace
39   clinker (Fechner and Kray 2012; Lehne and Preston 2018; Habert et al. 2020). Local building codes
40   determine what mixes of cementious materials are allowed for given uses, and would need to be
41   modified to allow these alternative mixtures where appropriate.
42   Ordinary Portland cement process CO2 emissions cannot be avoided or reduced through the use of non-
43   fossil energy sources. For this reason, CCS technology, which could capture just the process emissions
44   (e.g. the EU LEILAC project, which concentrates the process emissions from the limestone calciner,
45   see following paragraph) or both the energy and process-related CO2 emissions, is often mentioned as
46   a potentially important element of an ambitious mitigation strategy in the cement sector. Different types
47   of CCS processes can be deployed, including post-combustion technologies such as amine scrubbing
48   and membrane-assisted CO2-liquefation, oxycombustion in a low to zero nitrogen environment (full or

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1    partial) to produce a concentrated CO2 stream for capture and disposal, or calcium-looping (Dean et al.
2    2011). The IEA puts cement CCS technologies at the TRL 6-8 level (IEA 2020h). These approaches
3    have different strengths and weaknesses concerning emission abatement potential, primary energy
4    consumption, costs and retrofittability (Voldsund et al. 2019; Gardarsdottir et al. 2019; Hills et al. 2016).
5    Use of biomass energy combined with CCS has the possibility of generating partial negative emissions,
6    with the caveats introduced in 11.3.6 (Hepburn et al. 2019).
 7   The energy-related emissions of cement production can also be reduced by using bioenergy solids,
 8   liquids or gases (TRL 9) (IEA and WBCSD 2018), hydrogen or electricity (TRL 4 according to (IEA
 9   2020h)) for generating the high-temperature heat at the calciner – hydrogen and bioenergy co-burning
10   could be complementary due to their respective fast vs slow combustion characteristics. In an approach
11   pursued by the LEILAC research project, the calcination process step is carried out in a steel vessel that
12   is heated indirectly using natural gas (Hills et al. 2017). The LEILAC approach makes it possible to
13   capture the process-related emissions in a comparatively pure CO2 stream, which reduces the energy
14   required for CO2 capture and purification. This technology (LEILAC in combination with CCS) could
15   reduce total furnace emissions by up to 85% compared with an unabated, fossil fuelled cement plant,
16   depending on the type of energy sources used for heating (Hills et al. 2017). In principle, the LEILAC
17   approach allows the eventual potential electrification of the calciner by electrically heating the steel
18   enclosure instead of using fossil burners.
19   In the long run, if some combination of material efficiency, better mixing and aggregate sizing,
20   cementious material substitution and 90%+ capture CCS with supplemental bioenergy are not feasible
21   in some regions or at all to achieve near zero emissions, alternatives to limestone based ordinary
22   Portland cement may be needed. There are several highly regional alternative chemistries in use that
23   provide partial reductions (Fechner and Kray 2012; Lehne and Preston 2018; Habert et al. 2020), for
24   example, carbonatable calcium silicate clinkers, and there have been pilot projects with magnesium
25   oxide based cements, which could be negative emissions. Lower carbon cement chemistries are not
26   nearly as widely available as limestone deposits (Material Economics 2019), and would require new
27   materials testing protocols, codes, pilots and demonstrations.
28   Any substantial changes in cement and concrete material efficiency or production decarbonisation,
29   however, will require comprehensive education and continuing re-education for cement producers,
30   architects, engineers, contractors and small, non-professional users of cements. It will also require
31   changes to building codes, standards, certification, labeling, procurement, incentives, and a range of
32   polices to help create the market will be needed, as well as those for information disclosure, and
33   certification for quality. Even an end-of-pipe solution like CCS will require infrastructure for transport
34   and disposal. Abatement costs for these strategies vary considerably from case to case and for each a
35   plausible cost range is difficult to establish but are summarized in Table 11.3 from the following
36   literature and other sources (Moore 2017; Fechner and Kray 2012; Leeson et al. 2017; IEA 2019f;
37   Wilson et al. 2003; Lehne and Preston 2018; Habert et al. 2020).
39 Chemicals
40   The chemical industry produces a broad range of products that are used in a wide variety of applications.
41   The products range from plastics and rubbers to fertilisers, solvents, and specialty chemicals such as
42   food additives and pharmaceuticals. The industry is the largest industrial energy user and its direct
43   emissions were about 1.1–1.7 GtCO2-eq or about 10% of total global direct industrial emissions in 2019
44   (Figure 11.4 and Table 11.1) (Crippa et al. 2021; Lamb et al. 2021; Olivier and Peters 2018; IEA 2019f;
45   Minx et al. 2021). With regard to energy requirements and CO2 emissions, ammonia, methanol, olefins,
46   and chlorine production are of great importance (Boulamanti and Moya Rivera 2017). Ammonia is

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1    primarily used for nitrogen fertilisers, methanol for adhesives, resins, and fuels, whereas olefins and
2    chlorine are mainly used for the production of polymers, which are the main components of plastics.
 3   Technologies and process changes that enable the decarbonisation of chemicals production are specific
 4   to individual processes. Although energy efficiency in the sector has steadily improved over the past
 5   decades (Figure 11.8; (Boulamanti and Moya Rivera 2017; IEA 2018a) a significant share of the
 6   emissions is caused by the need for heat and steam in the production of primary chemicals (Box 11.2)
 7   (Bazzanella and Ausfelder 2017). This energy is currently supplied almost exclusively through fossil
 8   fuels which could be substituted with bioenergy, hydrogen, or low or zero carbon electricity, for
 9   example, using electric boilers or high-temperature heat pumps (Thunman et al. 2019; Bazzanella and
10   Ausfelder 2017; Saygin and Gielen 2021). The chemical industry has among the largest potentials for
11   industrial energy demand to be electrified with existing technologies, indicating the possibility for a
12   rapid reduction of energy related emissions (Madeddu et al. 2020).
13   The production of ammonia causes most CO2 emissions in the chemical industry, about 30% according
14   to IEA (2018a) and nearly one third according to (Crippa et al. 2021; Lamb et al. 2021; Minx et al.
15   2021). Ammonia is produced in a catalytic reaction between nitrogen and hydrogen – the latter most
16   often produced through natural gas reforming (Stork et al. 2018; Material Economics 2019) and in some
17   regions through coal gasification, which has several times higher associated CO2 emissions. Future low-
18   carbon options include hydrogen from electrolysis using on low or zero-carbon energy sources
19   (Philibert 2017a), natural gas reforming with CCS, or methane pyrolysis, a process in which methane
20   is transformed into hydrogen and solid carbon (Material Economics 2019; Bazzanella and Ausfelder
21   2017) (see also Section 11.3.5 and Box 11.1). Electrifying ammonia production would lead to a decrease
22   in total primary energy demand compared to conventional production, but a significant efficiency
23   improvement potential remains in novel synthesis processes (Wang et al. 2018; Faria 2021). Combining
24   renewable energy sources and flexibility measures in the production process could allow for low-carbon
25   ammonia production on all continents (Fasihi et al. 2021). Steam cracking of naphtha and natural gas
26   liquids for the production of olefins, i.e. ethylene, propylene and butylene, and other high value
27   chemicals is the second most CO2 emitting process in the chemical industry, accounting for another
28   almost 20% of the emissions from the subsector (IEA 2018a). Future lower-carbon options include
29   electrifying the heat supply in the steam cracker as described above, although this will not remove the
30   associated process emissions from the cracking reaction itself or from the combustion of the by-
31   products. Further in the future, electrocatalysis of carbon monoxide, methanol, ethanol, ethylene and
32   formic acid could allow direct electric recombination of waste chemical products into new intermediate
33   products (De Luna et al. 2019).
34   A ranking of key emerging technologies with likely deployment dates from the present to 2025 relevant
35   for the chemical industry identified different carbon capture processes together with electrolytic
36   hydrogen production as being of very high importance to reach net zero emissions (IEA 2020a).
37   Methane pyrolysis, electrified steam cracking, and the biomass based routes for ethanol-to-ethylene and
38   lignin-to-BTX were ranked as being of medium importance. While macro-level analyses show that
39   large-scale use of carbon circulation through CCU is possible in the chemical industry as primary
40   strategy, it would be very energy intensive and the climate impact depend significantly on the source of
41   and process for capturing the CO2 (Kätelhön et al. 2019; Müller et al. 2020; Artz et al. 2018). Significant
42   synergies can be found when combining circular CCU approaches with virgin carbon feedstocks from
43   biomass (Bachmann et al. 2021; Meys et al. 2021).
44   In a net zero world carbon will still be needed for many chemical products, but the sector must also
45   address the life-cycle emissions of its products which arise in the use phase, for example, CO2 released
46   from urea fertilisers, or at the end-of-life, for example, incineration of waste plastics which was
47   estimated to emit 100 Mt globally in 2015 (Zheng and Suh 2019). Reducing life-cycle emissions can
48   partly be achieved by closing the material cycles starting with material and product design planning for

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 1   re-use, re-manufacturing, and recycling of products – ending up with chemical recycling which yields
 2   recycled feedstock that substitutes virgin feedstocks for various chemical processes (Smet and Linder
 3   2019; Rahimi and García 2017). However, the chemical recycling processes which are most well
 4   studied are pyrolytic processes which are energy intensive and have significant losses of carbon to off-
 5   gases and solid residues (Dogu et al. 2021; Davidson et al. 2021). They are thus associated with
 6   significant CO2 emissions, which can even be larger in systems with chemical recycling than energy
 7   recovery (Meys et al. 2020). Further, the products from many pyrolytic chemical recycling processes
 8   are primarily fuels, which then in their subsequent use will emit all contained carbon as CO2 (Vollmer
 9   et al. 2020). Achieving carbon neutrality would thus require this CO2 either to be recirculated through
10   energy-consuming synthesis routes or to be captured and stored (Lopez et al. 2018; Material Economics
11   2019; Geyer et al. 2017; Thunman et al. 2019). As all chemical products are unlikely to fit into chemical
12   recycling systems, CCS can be used to capture and store a large share of their end-of-life emissions
13   when combined with waste combustion plants or heat-demanding facilities like cement kilns (Tang and
14   You 2018; Leeson et al. 2017).
15   Reducing emissions involves demand-side measures, for example, efficient end-use, materials
16   efficiency and slowing demand growth, as well as recycling where possible to reduce the need for
17   primary production. The following strategies for primary production of organic chemicals which will
18   continue to need a carbon source are key in avoiding the GHG emissions of chemical products
19   throughout their life cycles:
20       •   Recycled feedstocks: chemical recycling of plastics unsuitable for mechanical recycling was
21           already mentioned. Through pyrolysis of old plastics, both gas and a naphtha-like pyrolysis oil
22           can be generated, a share of which could replace fossil naphtha as a feedstock in the steam
23           cracker (Honus et al. 2018a,b). Alternatively, waste plastics could be gasified and combined
24           with low-carbon hydrogen to a syngas, for example, the production and methanol and
25           derivatives (Stork et al. 2018; Lopez et al. 2018). Other chemical recycling options include
26           polymer selective chemolysis, catalytic cracking, and hydrocracking (Ragaert et al. 2017).
27           Carbon losses and process emissions must be minimized and it may thus be necessary to
28           combine chemical recycling with CCS to reach near-zero emissions (Smet and Linder 2019;
29           Thunman et al. 2019; Meys et al. 2021).
30       •   Biomass feedstocks: Substituting fossil carbon at the inception of a product life-cycle for
31           carbon from renewable sources processed in designated biotechnological processes (Hatti-Kaul
32           et al. 2020; Lee et al. 2019) using specific biomass resources (Isikgor and Becer 2015) or
33           residual streams already available (Abdelaziz et al. 2016). Routes with thermochemical and
34           catalytic processes, such as pyrolysis and subsequent catalytic upgrading, are also available
35           (Jing et al. 2019).
36       •   Synthetic feedstocks: carbon captured with direct air capture or from point sources (bioenergy,
37           chemical recycling, or during a transition period from industrial processes emitting fossil CO2)
38           can be combined with low-GHG hydrogen into a syngas for further valorisation (Kätelhön et
39           al. 2019). Thus, low-carbon methanol can be produced and used in methanol-to-
40           olefins/aromatics (MTO/MTA) processes, substituting the steam cracker (Gogate 2019) or a
41           Fischer-Tropsch processes could produce synthetic hydrocarbons.
42   Reflecting the diversity of the sector the listed options can only be illustrative. The above listed
43   strategies all rely on low-carbon energy to reach near zero emissions. In considering mitigation
44   strategies for the sector it will be key to focus on those for which there is a clear path towards (close to)
45   zero emissions, with high (carbon) yields over the full product value chain and minimal fossil resource
46   use for both energy and feedstocks (Saygin and Gielen 2021), with CCU and CCS employed for all
47   remnant carbon flows. The necessity of combining mitigation approaches in the chemicals industry with
48   low-carbon energy was recently highlighted in an analysis (see Figure 11.10) which showed how the

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 1   combined use of different recycling options, carbon capture, and biomass feedstocks was most effective
 2   at reducing global life-cycle emissions from plastics (Meys et al. 2021). While most of the chemical
 3   processes for doing all the above are well-known and have been used commercially at least partly, they
 4   have not been used at large scale and in an integrated way. In the past external conditions (e.g.
 5   availability and price of fossil feedstocks) have not set the necessary incentives to implement alternative
 6   routes and to avoid emitting combustion and process related CO2 emissions to atmosphere. Most of
 7   these processes will very likely be more costly than using fossil fuels and full scale commercialisation
 8   would require significant policy support and the implementation of dedicated lead markets (Wyns et al.
 9   2019; Material Economics 2019; Wesseling et al. 2017; Bataille et al. 2018a). As in other sub-sectors
10   abatement costs for the various strategies vary considerably across regions and products making it
11   difficult to establish a plausible cost range for each (Philibert 2017b; Bazzanella and Ausfelder 2017;
12   Philibert 2017a; Axelson et al. 2018; IEA 2018a; Saygin and Gielen 2021; De Luna et al. 2019).

16      Figure 11.10 Feedstock supply and waste treatment in a scenario with a combination of mitigation
17                      measures in a pathway for low-carbon plastics (Meys et al. 2021)

19   START BOX 11.2 HERE
21                                    Box 11.2 Plastics and climate change

22   The global production of plastics has increased rapidly over the past 70 years, with a compound annual
23   growth rate (CAGR) of 8.4 %, about 2.5 times the growth rate for global GDP (Geyer et al. 2017) and
24   higher than other materials since 1970 (IEA 2019b). Global production of plastics is now more than

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 1   400 million tonnes, including synthetic fibres (ibid.) The per capita use of plastics is still up to 20 times
 2   higher in developed countries than in developing countries with low signs of saturation and the potential
 3   for an increased use is thus still very large (IEA 2018a). Plastics is the largest output category from the
 4   petrochemical industry, which as a whole currently uses about 14 % of petroleum and 8 % of natural
 5   gas (IEA 2018a). Forecasts for plastic production assuming continued growth at recent rates of about
 6   3.5% point towards a doubled production by 2035, following record-breaking investments in new and
 7   increased production capacity based on petroleum and gas in recent years (CIEL 2017; Bauer and
 8   Fontenit 2021). IEA forecasts show that even in a world where transport demand for oil falls
 9   considerably by 2050 from the current ~100 mbpd, feedstock demand for chemicals will rise from ~12
10   mbpd to 15–18 mbpd (IEA 2019b). Projections for increasing plastic production as well as petroleum
11   use together with the lack of investments in break-through low-emission technologies do not align with
12   necessary emission reductions.
13   About half of the petroleum that goes into the chemical industry is used for producing plastics, and a
14   significant share of this is combusted or lost in the energy intensive production processes, primarily the
15   steam cracker. GHG emissions from plastic production depend on the feedstock used (ethane based
16   production is associated with lower emissions than naphtha based), the type of plastic produced
17   (production of simple polyolefins is associated with lower emissions than more complex plastics such
18   as polystyrene), and the contextual energy system (e.g. the GHG intensity of the electricity used) but
19   weighted averages have been estimated to be 1.8 tCO2-eq·t-1 for North American production (Daniel
20   Posen et al. 2017) and 2.3 tCO2-eq·t-1 for European production (Material Economics 2019). In regions
21   more dependent on coal electricity production the numbers are likely to be higher, and several times
22   higher for chemical production using coal as a feedstock - coal-based MTO has 7 times higher emissions
23   than olefins from steam cracking (Xiang et al. 2014). Coal-based plastic and chemicals production has
24   over the past decade been developed and deployed primarily in China (Yang et al. 2019). The
25   production of plastics was thus conservatively estimated to emit 1085 MtCO2-eq·yr-1 in 2015 (Zheng
26   and Suh 2019). Downstream compounding and conversion of plastics was estimated to emit another
27   535 MtCO2-eq·yr-1, while end-of-life treatment added 161 MtCO2-eq·yr-1. While incineration of plastic
28   waste was the cause of only 5% of global plastic life cycle emissions, in regions with waste-to-energy
29   infrastructures this share is significantly larger, for example, 13% of life cycle emissions in Europe (Ive
30   Vanderreydt et al. 2021). The effective recycling rate of plastics remains low relating to a wide range
31   of issues such as insufficient collection systems, sorting capacity, contaminants and quality deficiencies
32   in recycled plastics, design of plastics integrated in complex products such as electronics and vehicles,
33   heterogenous plastics used in packaging, and illegal international trade.
35   END BOX 11.2 HERE
37 Other industry sectors
38   The other big sources of direct global industrial combustion and process CO2 emissions are light
39   manufacturing and industry (9.7% in 2016), non-ferrous metals like aluminium (3.1%), pulp and paper
40   (1.1%), and food and tobacco (1.9%) (Bataille 2020a; Crippa et al. 2021; Lamb et al. 2021).
41   Light manufacturing and industry
42   Light manufacturing and industry represent a very diverse sector in terms of energy service needs (e.g.,
43   motive power, ventilation, drying, heating, compressed air, etc.) and it comprises both small and large
44   plants in different geographical contexts. Most of the direct fossil fuel use is for heating and drying, and
45   it can be replaced with low GHG electricity, through direct resistance, high temperature heat pumps
46   and mechanical vapour recompression, induction, infrared, or other electrothermal processes
47   (Bamigbetan et al. 2017; Lechtenböhmer et al. 2016). Madeddu et al. (2020) argue up to 78% of

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1    Europe’s industrial energy requirements are electrifiable through existing commercial technologies and
2    99% with addition of new technologies currently under development. Direct solar heating is possible
3    for low temperature needs (<100°C) and concentrating solar for higher temperatures. Commercially
4    available heat pumps can deliver 100-150°C but at least up to 280°C is feasible (Zühlsdorf et al. 2019).
5    Plasma torches using electricity can be used where high temperatures (>1000°C) are required, but
6    hydrogen, biogenic or synthetic combustible hydrocarbons (methane, methanol, ethanol, LPG, etc.) can
7    also be used (Bataille et al. 2018a).
 8   There is also a large potential for energy savings through cascading in industrial clusters similar to the
 9   one at Kalundborg, Denmark. Waste heat can be passed at lower and lower temperatures from facility
10   to facility or circulated as low-grade steam or hot water, and boosted as necessary using heat pumps
11   and direct heating. Such geographic clusters would also enable lower cost infrastructure for hydrogen
12   production and storage as well as CO2 gathering, transport and disposal (IEA 2019f).
13   Aluminium and other non-ferrous metals
14   Demand for aluminium comes from a variety of end-uses where a reasonable cost, light-weight metal
15   is desirable. It has historically been used in aircraft, window frames, strollers, and beverage containers.
16   As fuel economy has become more desirable and design improvements have allowed crush bodies made
17   of aluminium instead of steel, aluminium has become progressively more attractive for cars. Primary
18   aluminium demand is total demand (100 Mtonnes·yr-1 in 2020) net of manufacturing waste reuse (14%
19   of virgin and recycled input) and end-of-life recycling (about 20% of what reaches market). Primary
20   aluminium consumption rose from under 20 Mtonnes·yr-1 in 1995 to over 66 Mtonnes primary ingot
21   production in 2020 (International Aluminium Institute 2021). International Aluminium Institute (2021a)
22   expects total aluminium consumption to reach 150–290 Mtonnes·yr-1 by 2050 with primary aluminium
23   contributing 69–170 Mtonnes and secondary recycled 91–120 Mtonnes (as in-use stock triples or
24   quadruples). OECD forecasts increases in demand by 2060 for primary aluminium to 139 Mt·yr-1 and
25   for secondary aluminium to 71 Mtonnes (OECD 2019a). Primary (as opposed to recycled) aluminium
26   is generally made in a two-stage process, often geographically separated. In the first stage aluminium
27   oxide is extracted from bauxite ore (often with other trace elements) using the Bayer hydrometallurgical
28   process, which requires up to 200°C heat when sodium hydroxide is used to leach the aluminium oxide,
29   and up to 1000°C for kilning. This is followed by electrolytic separation of the oxygen from the
30   elemental aluminium using the Hall-Héroult process, by far the most energy intense part of making
31   aluminium. This process has large potential emissions from the electricity used (12.5 MWh per tonne
32   aluminium BAT, 14–15 MWh per tonne average). From bauxite mine to aluminium ingot, reported
33   total global average emissions are between 12 and 17.6 tCO2-eq per tonnes of aluminium, depending
34   on estimates and assumptions made23 (Saevarsdottir et al. 2020). About 10 % of this, 1.5 tonnes of direct
35   CO2 per tonne aluminium are currently emitted as the graphite electrodes are depleted and combine
36   with oxygen, and if less than optimal conditions are maintained perfluorocarbons can be emitted with
37   widely varying GHG intensity, up to the equivalent of 2 tCO2-eq.per tonne aluminium. PFC emissions,
38   however, have been greatly reduced globally and almost eliminated in well-run facilities. Aluminium,
39   if is not contaminated, is highly recyclable and requires 1/20 of the energy required to produce virgin
40   aluminium; increasing aluminium recycling rates from the 20–25% global average is a key emissions
41   reduction strategy (Haraldsson and Johansson 2018).
42   The use of low and zero GHG electricity (e.g. historically from hydropower) can reduce the indirect
43   emissions associated with making aluminium. A public-private partnership with financial support from
44   the province of Québec and the Canadian federal government has recently announced a fundamental

     FOOTNOTE23 According to International Aluminium Institute (2021b), scope 3 (cradle to gate) emissions from
     aluminium industry in 2018 reached 1.127 GtCO2-eq or 17.6 tCO2-eq per tonne of primary aluminium. In Low
     carbon B2DS it expected to be reduced to 2.5 tCO2-eq per tonne.

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1    modification to the Hall-Héroult process by which the graphite electrode process emissions can be
2    eliminated by substitution of inert electrodes. This technology is slated to be available in 2024 and is
3    potentially retrofittable to existing facilities (Saevarsdottir et al. 2020).
 4   Smelting and otherwise processing of other non-ferrous metals like nickel, zinc, copper, magnesium
 5   and titanium with less overall emissions have relatively similar emissions reduction strategies (Bataille
 6   and Stiebert 2018): 1) Increase material efficiency. 2) Increase recycling of existing stock. 3) Pursue
 7   ore extraction processes (e.g. hydro- and electro-metallurgy) that allow more use of low carbon
 8   electricity as opposed to pyrometallurgy, which uses heat to melt and separate the ore after it has been
 9   crushed. These processes have been used occasionally in the past but have generally not been used due
10   to the relatively inexpensive nature of fossil fuels.
11   Pulp and Paper
12   The pulp and paper industry is a small net-emitter of CO2, assuming the feedstock is sustainably sourced
13   (see Chapter 7), but it has large emissions of biogenic CO2 from feedstock (700–800 Mtonne·yr-1
14   (Tanzer et al. 2021). It includes pulp mills, integrated pulp and paper mills and paper mills using virgin
15   pulpwood and other fibre sources, residues and co-products from wood products manufacturing, and
16   recycled paper as feedstock. Pulp mills typically have access to bioenergy in the chemical pulping
17   processes to cover most or all of heat and electricity needs, for example, through chemicals recovery
18   boilers and steam turbines in the kraft process. Mechanical pulping mainly uses electricity for energy;
19   decarbonisation thus depends on grid emission factors. With the exception of the lime kiln in kraft pulp
20   mills, process temperature needs are typically less than or equal to 150ºC to 200ºC, mainly steam for
21   heating and drying. This means that this sector can be relatively easily decarbonised through continued
22   energy efficiency, fuel switching and electrification, including use of high temperature heat pumps
23   (Ericsson and Nilsson 2018). Electrification of pulp mills could, in the longer term, make bio-residues
24   currently used internally for energy available as a carbon source for chemicals (Meys et al. 2021). The
25   PPI also has the capabilities, resources and knowledge, to implement these changes. Inertia is mainly
26   caused by equipment turn-over rates, relative fuel and electricity prices, and the profitability of
27   investments.
28   A larger and more challenging issue is how the forestry industry can contribute to the decarbonisation
29   of other sectors and how biogenic carbon will be used in a fossil-free society, for example, through
30   developing the forest based bioeconomy (Bauer 2018; Pülzl et al. 2014). In recent years the concept of
31   biorefineries has gained increasing traction. Most examples involve innovations for taking by-products
32   or diverting small streams to produce fuels, chemicals and bio-composites that can replace fossil-based
33   products, but there is little common vision on what really constitutes a biorefinery (Bauer et al. 2017).
34   Some of these options have limited scalability and the cellulose fibre remains the core product even in
35   the relatively large shift from paper production to textiles fibre production.
36   Pulp mills have been identified as promising candidates for post-combustion capture and CCS
37   (Onarheim et al. 2017), which could allow some degree of net negative emissions. For deep
38   decarbonisation across all sectors, notably switching to biomass feedstock for fuels, organic chemicals
39   and plastics, the availability of biogenic carbon (in biomass or as biogenic CO2, Chapter 7) becomes an
40   issue. A scenario where biogenic carbon is CCU as feedstock implies large demands for hydrogen,
41   completely new value chains and more closed carbon loops, all areas which are as yet largely
42   unexplored (Ericsson 2017; Meys et al. 2021).

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1 Overview of estimates of specific mitigation potential and abatement costs of key technologies
2    and processes for main industry sectors
 3   Climate policy related literature focusing on deep industrial emission reductions has expanded rapidly
 4   since AR 5. An increasing body of research proposes deep decarbonisation pathways for energy
 5   intensive industries (Figure 11.13). (Bataille et al. 2018a) address the question of whether it is possible
 6   to reduce GHG emissions to very low, zero, or negative levels, and identifies preliminary technological
 7   and policy elements that may allow the transition, including the use of policy to drive technological
 8   innovation and uptake. Material Economics (2019); IEA (2019b), Energy Transitions Commission
 9   (2018) and Climate Action Tracker CAT (2020) take steps to identify pathways integrating energy
10   efficiency, material efficiency, circular economy and innovative technologies options to cut GHG
11   emissions across basic materials and value chains. The key conclusion is that net zero CO2 emissions
12   from the largest sources (steel, plastics, ammonia, and cement) could be achieved by 2050 by deploying
13   already available multiple options packaged in different ways (Material Economics 2019; UKCCC
14   2019b; Davis et al. 2018). The studies assume that for those technologies that have a kind of
15   breakthrough technology status further technological development and significant cost reduction can
16   be expected.
17   Table 11.3, modified from Bataille (2020a) and built from (Material Economics 2019; Bazzanella and
18   Ausfelder 2017; Axelson et al. 2018; McMillan et al. 2016; Wesseling et al. 2017; UKCCC 2019b;
19   Energy Transitions Commission 2018; Philibert 2017a; Davis et al. 2018; IEA 2019f, 2020c; Bataille
20   et al. 2018a), presents carbon intensities that could be achieved by implementing mitigation options in
21   major basic material industries, mitigation potential, estimates for mitigation costs, TRL and potential
22   year of market introduction (see also Figure 11.13).
23   Table 11.3 acknowledges that for many carbon intensive products a large variety of novel processes,
24   inputs and practices capable of providing very deep emission reductions are already available and
25   emerging. However, their application is subject to different economic and structural limitations,
26   therefore in the scenarios assuming deep decarbonisation by 2050–2060 different technological mixes
27   can be observed (section 11.4.2).

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 Table 11.3 Technological potentials and costs for deep decarbonisation of basic industries. Percentages of maximum reduction are multiplicative,
 not additive

                                                                                                                             Cost per tonne CO2-eq
                                                                                              Potential                                                        available
                                                                   Current Intensity                           NASA       (2019 USD tCO2-eq-1 for % of
                            Sector                                                              GHG                                                            assuming
                                                                     (tCO2-eq t-1)                              TRL                emissions)
                                                                                              reduction                                                          policy
                                                                                                                                 ? = Unknown
 Iron and Steel
      Current intensity – all steel (Worldsteel)                  1.83
      Current intensity – ~BF-BOF/ Best BF-BOF & NG-DRI           2.3/1.8 & 0.7
      (with near zero GHG electricity)
      Current intensity – EAF (depends on electricity intensity   >=0                  Up to 99%
      & pre-heating fuel)
      Material efficiency (IEA 2019 “Material Efficiency…”)                            Up to 40%               9      Subject to supply chain building codes   Today
                                                                                                                      and education
    More recycling; depends on available stock, recycling                              Highly      regional,   9      Subject to logistical, transport,        Today
    network, quality of scrap, availability of DRI for                                 growing with time              sorting, & recycling equipment costs
    BF-BOF w/ top gas recirculation & CCU/Si                                           60%                     6–7    70–130 USD/t                             2025-‘30
    Syngas (H2 & CO) DRI EAF with concentrated flow                                    90%+                    9      >=40 USD/t                               Today
    Hisarna with concentrated CO2 captureii                                            80–90%                  7      40–70 USD/t                              2025
    Hydrogen DRI EAFiii - Fossil hydrogen with CCS is in                               Up to 99%               7      34–68            EUR/t              &    2025
    operation, electrolysis based hydrogen scheduled for                                                              40 EUR/MWh
    Aqueous (e.g. SIDERWIN) or Molten Oxide (e.g.                                      Up to 99%               3–5    ?                                        2035-‘40
    Boston Metals) Electrolysisiv
 Cement & Concrete
    Current intensity, about 60% is limestone calcination         0.55
    Building design to minimize concrete (IEA 2019b,                                   Up to 24%               9      Low, education, design and logistics     2025
    2020a)                                                                                                            related
    Alternative lower GHG fuels, e.g. waste (biofuels and                              40%                     9      Cost of alt. fuels                       Today
    hydrogen see above)

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     CCUS for process heating & CaCO3 calcination CO2                                     99% calc., <=90%       5–7   <=40            USD/t         calc.    2025
     (e.g. LEILAC, possible retrofit)v                                                    heat                         <=120 USD/t heat
     Clinker substitution (e.g. limestone + calcined clays)vi                             40–50%                 9     Near zero, education,     logistics,   Today
                                                                                                                       building code revisions
    Use of multi sized and well dispersed aggregatesvi                                    Up to 75%              9     Near zero                              Today
    Magnesium or ultramafic cementsvi                                                     Negative?              1–4   ?                                      2040
 Aluminium & other non-ferrous
    Current Al intensity, from hydro to coal based electricity   1.5 t/t + electricity
    production. 1.5 tonne CO2 are produced by graphite           req.,             i.e.
    electrode decay                                              10/t (NG) to 18 t/t
    Inert electrodes + green electricityvii                                               100%                   6–7   Relatively low                         2024
    Hydro/Electrolytic smelting (w/CO2 CCUS if                                            Up to 99%              3–9   Ore specific                           <2030
 Chemicals (see also crosscutting feedstocks above)viii
    Catalysis of ammonia from low/zero GHG hydrogen H2           1.6 (NG), 2.5            <=99%                  9     Cost of H2                             Today
                                                                 (naptha) 3.8 (coal)
     Electrocatalysis: CH4, CH3OH, C2H5OH, CO, olefinsix                                  Up to 99%              3     Cost: Elec., H2, COx                   2030
     Catalysis of olefins from: (m)ethanol; H2 & COx directly                             9%                     9,3   Cost: H2 & COx                         <2030
     End-use plastics, mainly CCUS and recycling                 1.3–4.2, about 2.4       94%                    5–6   150–240 USD/t                          2030?
 Pulp & Paper
     Full biomass firing, inc. lime kilns                                                 60-75%                 9     About 50 USD/t                         Today
 Other manufacturing
     Electrification using current tech (boilers, 90°C–140°C                              99%                    9     Cost: Elec. vs. NG                     2025
     heat pumps
     " using new tech (induction, plasma heating)                                         99%                    3–6                                          2025
 Cross-cutting (CCUS, H2, net zero CoOxHy fuels/feedstocks)
     CCUS of post-combustion CO2 diluted in nitrogenv                                     Up to 90%              6–7   <=120 USD/t                            2025
     CCUS of concentrated CO2v                                                            99%                    9     <=40 USD/t                             Today
     H2 prod: Steam or auto-thermal CH4 reforming w/ CCSv                                 SMR<=90%               6*,   56% @<=40 USD/t chem**, <=120          <=2025
                                                                                          ATR >90%               9**   USD heat*,+20%/kg
     H2 prod: coal with CCUSv                                                             <=90%                  6     “,+25-50%/kg                           <=2025

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         H2 prod: Alkaline or PEM Electrolysisx                                           99%                     9          about 50 USD/t or <20-30 USD/MWh         Today
         H2 prod: Reversible solid oxide fuel electrolysisx                               99%                     6–8        about 40 USD/t or <40 USD/MWh            2025
         H2 prod: CH4 pyrolysis or catalytic crackingxi                                   99%                     5          ?                                        2030?
         Hydrogen as CH4 replacement                                                      <=10%                   9          See above                                Today
         Biogas or liquid replacement hydrocarbons                                        60–90%                  9          Biomass USD/GJ; >=50 USD/t,              Today
         Anaerobic digestion/fermentation: CH4, CH3OH,                                    Up to -99%              9          Biomass cost                             Today
         Methane or methanol from H2 & COx (CCUS for                                      50–99%                  6–9        Cost: H2 & COx                           Today
         excess). Maximum -50% reduction if C source is FF
         850°C woody biomass gasification w/ CCS for excess                               Could be negative       7–8        about 50–75 USD/t, uncertain             Today
         carbon: CO, CO2, H2, H2O, CH4, C2H4 & C6H6xiii
         Direct air capture for short and long chain CoOxHyxiv                            Up to 99%               3          Cost: E, H2, COx about 94–232 USD/t      <=2030
      Data for CCS costs for steel making: Birat (2012); Axelson et al. (2018) and Leeson et al. (2017);
       Data for Hisarna: Axelson et al. (2018);
    iii Data for hydrogen DRI electric arc furnaces: Fischedick et al. (2014b) and Vogl et al. (2018);
        Data for molten oxide electrolysis (also known as SIDERWIN): (Axelson et al. 2018; Fischedick et al. 2014b). The TRLs differ by source, the value provided is from Axelson
    et al. (2018) based on UCLOS SIDERWIN;
       Data for making hydrogen from SMR and ATR with CCUS: Moore (2017), Leeson et al. (2017) and IEA (2019f). The cost of CCS disposal of concentrated sources of CO 2
    at 15–40 USD·tCO2-eq-1 is well established as commercial for direct or EOR purposes and is based on the long standing practise of disposing of hydrogen sulfide and oil brines
    underground: Wilson et al. (2003) and Leeson et al. (2017). There is a wide variance, however, in estimated tCO2-eq-1 breakeven prices for industrial post-combustion capture
    of CO2 from sources highly diluted in nitrogen (e.g. Leeson et al. (2017) at 60–170 USD·tCO2-eq-1), but most fall under 120 USD·tCO2-eq-1;
        Data for clinker substitution and use of well mixed and multi sized aggregates: (Fechner and Kray 2012; Lehne and Preston 2018; Habert et al. 2020);
         Rio Tinto, Alcoa and Apple have partnered with the governments of Québec and Canada to formed a coalition to commercialize inert as opposed to sacrificial graphite
    electrodes by 2024, thereby making the standard Hall Heroult process very low emissions if low carbon electricity is used;
         Data and other information: Bazzanella and Ausfelder (2017); Axelson et al. (2018); IEA (2018a); De Luna et al. (2019) and Philibert (2017b,a);
        See De Luna et al. (2019) for a state of the art review of electrocatalysis, or direct recombination of organic molecules using electricity and catalysts;
       Data for hydrogen production from electrolysis: Bazzanella and Ausfelder (2017); Philibert (2017a); Armijo and Philibert (2020); IEA (2019f); Philibert (2017b);
    xi Data for methane pyrolysis to make hydrogen: Abbas and Wan Daud (2010). Data for hydrogen production from methane catalytic cracking: Amin et al. (2011) and Ashik
    et al. (2015);
         Data for anaerobic digestion or fermentation for the production of methane, methanol and ethanol: De Luna et al. (2019);
         Data for woody biomass gasification: Li et al. (2019) and van der Meijden et al. (2011);
         Data on direct air capture of CO2: Keith et al. (2018) and Fasihi et al. (2019).

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 1   While deep GHG emissions reduction potential is assessed for various regions, assessment of associated
 2   costs is limited to only a few regions; nevertheless those analyses may be illustrative at the global scale.
 3   UKCCC (2019b) provides costs assessments for different industrial subsectors (see Table 11.3) for the
 4   UK. They provide three ranges: core, more ambitious and when energy and material efficiency are
 5   limited. The core options range from 2–85 GBP 2019 tCO2-eq-1 (e.g., reduction in GHG emissions by
 6   about 50% by 2050 applying energy efficiency (EE), ME, CCS, biomass and electrification). The more
 7   ambitious options are estimate at 32–119 GBP 2019 tCO2-eq-1 (e.g., 90% emissions reduction via
 8   widespread deployment of hydrogen, electrification or bioenergy for stationary industrial
 9   heat/combustion). Finally, costs range from 33–299 GBP tCO2-eq-1 when energy and material
10   efficiency are limited.
11   In Material Economics (2019) costs are provided for separate technologies and subsectors, and also by
12   pathways, each including new industrial processes, circular economy and CCS components in different
13   proportions allowing for the transition to net zero industrial emission in the EU by 2050. That means
14   that the study provides information about the three main mid- to long-term options which could enable
15   a widely abatement of GHG emissions. Given different electricity price scenarios, average abatement
16   costs associated with the circular economy-dominated pathway are 12–75 EUR 2019 tCO2-eq-1, for the
17   carbon capture-dominated pathway 79 euro 2019 tCO2-eq-1, and for the new processes dominated
18   scenario 91 euro 2019 tCO2-eq-1. Consequently, net zero emission pathways are about 3–25% costlier
19   compared to the baseline (Material Economics 2019). According to Energy Transitions Commission
20   (2018), cement decarbonisation would cost on average 110–130 USD tCO2-1 depending on the cost
21   scenario. Rootzén and Johnsson (2016) state that CO2 avoidance costs for the cement industry vary
22   from 25 to 110 EUR·tCO2-1, depending on the capture option considered and on the assumptions made
23   with respect to the different cost items involved. According to Energy Transitions Commission (2018),
24   steel can be decarbonised on average at 60 USD tCO2-1, with highly varying costs depending on low
25   carbon electricity prices..
26   For customers of final products, information on the potential impact of supply side decarbonization on
27   final prices may be more useful than that of CO2 abatement costs. A different approach has been
28   developed to assess the costs of mitigation by estimating the potential impacts of supply-side
29   decarbonization on final products prices. Material Economics (2019) shows that with deep
30   decarbonization, depending on the pathway, steel costs grow by 20–30%; plastics by 20–45%; ammonia
31   by 15–60% and cement (not concrete) by 70–115%. While these are large and problematic costs
32   increases for material producers working with low margins in a competitive market, final end-use
33   product price increases are far less, for example, a car becomes 0.5% more expensive, supported by
34   both Rootzén and Johnsson (2016) and Energy Transitions Commission (2018). For comparison,
35   Rootzén and Johnsson (2017) found that decarbonizing cement making, while doubling the cost of
36   cement, would add <1% to the costs of a residential building; the Energy Transitions Commission
37   (2018) found concrete would be 10-30% more expensive, adding 15,000 USD or 3% to the price of a
38   house includign land value. Finally, IEA (2020a) estimated the impact on end-use prices are rather
39   small, even in a net zero scenario; they find price increases of 0.2% for a car and 0.6% for a house based
40   on higher costs for steel and cement respectively.
41   Thus, the price impact scales down going across the value chain and might be acceptable for a
42   significant share of customers. However, it has to be reflected that the cumulative price increase could
43   be more significant if several different zero-carbon materials (e.g., steel, plastics, aluminium) in the
44   production process of a certain product have to be combined, indicating the importance of material
45   efficiency being applied along with production decarbonisation.

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1    11.4.2 Transformation pathways
 2   To discuss the general role and temporal implementation of the different options for achieving a net-
 3   zero GHG emissions industry, mitigation pathways will be analyzed. This starts with showing the
 4   results of IAM based scenarios followed by specific studies which provide much higher technological
 5   resolution and allow a much deeper look into the interplay of different mitigation strategies. The
 6   comparison of more technology-focused sector-based scenarios with top-down oriented scenarios
 7   provides the opportunity for a reciprocal assessment across different modelling philosophies and helps
 8   to identify robust elements for the transformation of the sector. Only some of the scenarios available in
 9   the literature allow for at least rough estimates of the necessary investments and give direction about
10   relevant investment cycles and potential risks of stranded or depreciated assets. In some specific cases
11   cost comparisons can be translated into expected difference costs not only for the overall sector, but
12   also for relevant materials or even consumer products.
14 Central results from (top down) scenarios analysis and illustrative mitigation pathways
15            discussion
16   Chapter 3 conducted a comprehensive analysis of scenarios based on IAMs. The resulting database
17   comprises more than 1000 model-based scenarios published in the literature. The scenarios span a broad
18   range along temperature categories from rather baseline like scenarios to the description of pathways
19   that are compatible with the 1.5°C target. Comparative discussion of scenarios allows some insights
20   with regard to the relevance of mitigation strategies for the industry sector (Figure 11.11).

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3   Figure 11.11 Industrial final energy (top left), CO2 emissions (top right), energy intensity (middle left), carbon intensity (middle right), share of electricity (bottom
4                                                                  left), and share of gases (bottom right)).

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1     Energy intensity is final energy per unit of GDP. Carbon intensity is CO 2 emissions per EJ of final energy. The first four indicators are indexed to 2019, where
2   values less than 1 indicate a reduction. Industrial sector CO 2 emissions include fuel combustion emissions only. Boxes indicate the interquartile range, the median is
3                                              shown with a horizontal black line, while vertical lines show the 5 to 95% interval.
4   Source: Data is from the AR6 database; only scenarios that pass the vetting criteria are included (see Section 3.2).

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2    The main results from the Chapter 3 analysis from an industry perspective are:
3        •   While all scenarios show a decline in energy and carbon intensity over time final energy
4            demand and associated industry related CO2 emissions increase in many scenarios. Only
5            ambitious scenarios (category C1) show significant reduction in final energy demand in 2030,
6            more or less constant demand in 2050, but increasing demand in 2100, driven by growing
7            material use throughout the 21st century. While carbon intensity shrinks over time energy
8            related CO2-emissions decline after 2030 even in less ambitious scenarios, but particularly in
9            those pursuing a temperature increase below 2°C.
10       •   Reduction of CO2-emissions in the sector are achieved through a combination of technologies
11           which includes nearly all options that have been discussed in this chapter (Section 11.3 and
12           11.4.1). However, there are big differences with regard to the intensity the scenarios implement
13           the various options. This is particularly true for CCS for industrial applications and material
14           efficiency and material demand management (i.e., service demand, service product intensity).
15           The latter options are still underrepresented in many global IAMs.
16       •   There are only a few scenarios which allow net-negative CO2-emissions for the industry for the
17           second half of the century while most scenarios assessed (including the majority of 1.5°C
18           scenarios) end up with still significant positive CO2-emissions. In comparison to the whole
19           system most scenarios expect a slower decrease of industry related emissions.
20       •   There is a great - up to a factor of two - difference in assumptions about the GHG mitigation
21           potential associated with different carbon cost levels between IAMs and sector specific industry
22           models. Consequently, IAMs pick up mitigation options slower or later (or not at all) than
23           models which are more technologically detailed. Due to their top-down perspective IAMs to
24           date have not been able to represent the high complexity of industries in terms of the broad
25           variety of technologies and processes (particularly circularity aspects) and to fully reflect the
26           dynamics of the sector. In addition, as energy and carbon price elasticities are still not
27           completely understood, primarily cost driven models have their limitations. However, there are
28           several ongoing activities to bring in more engineering knowledge and technological details
29           into the IAM models (Kermeli et al. 2021).
30   In addition to the more aggregated discussion, the IAMs illustrative mitigation pathways (IMPs) allow
31   a deeper look into the transformation pathways related to the scenarios. For the illustrative mitigation
32   pathways (IMPs) approach sets of scenarios have been selected which represent different levels of GHG
33   mitigation ambitions, scenarios which rely on different key strategies or even exclude some mitigation
34   options, represent delayed actions or SDG oriented pathways. For more detailed information about the
35   selection see Chapter 3.3.2. Figure 11.12 compares for a selected number of key variables the results of
36   IMPs and puts them in the context of the whole sample of IAMs scenario results for three temperature
37   categories.

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3     Figure 11.12 Comparison of industry sector related CO2-emissions (including process emissions), final energy demand, share of electricity and hydrogen in the
4   final energy mix, and industrial CCS for different mitigation scenarios representing illustrative mitigation pathways and the full sample of IAM scenario results for
5      three temperature categories (figure based on scenario data base). Indicators in the Illustrative Mitigation Pathways (lines) and the 5-95% range of Reference,
6     1.5°C and 2°C scenarios (shaded areas). The selected IMPs reflect the following characteristics: opportunities for reducing demand (IMP-LD; low demand), the
7     role of deep renewable energy penetration and electrification (IMP-Ren; renewables), extensive use of CDR in the industry and the energy sectors to achieve net
8   negative emissions (IMP-Neg), insights how shifting development can lead to deep emission reductions and achieve sustainable development goals (IMP-SP; shifting
9           pathways), and insights how slower short term emissions reductions can be compensated by very fast emission reductions later on (IMP-GS; gradual

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1     strengthening). Furthermore, two scenarios were selected to illustrate the consequences of current policies and pledges; these are CurPol (Current Policies) and
2                                       ModAct (Moderate Action) and are referred to as Pathways Illustrative of Higher Emissions
3   Source: Data is from the AR6 database; only scenarios that pass the vetting criteria are included (see Section 3.2).

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 2   With growing mitigation ambition final energy demand is significantly lower in comparison of a current
 3   policy pathway (CurPol) and a scenario that explores the impact of further moderate actions (ModAct).
 4   Based on the underlying assumptions, scenarios IMP-SP and IMP-LD are characterized by the lowest
 5   final energy demand, triggered by high energy efficiency improvement rates as well as additional
 6   demand side measures while a scenario with extensive use of CDR in the industry and the energy sectors
 7   to achieve net negative emissions (IMP-Neg) leads to a significant increase in final energy demand.
 8   Scenario IMP-GS represents a pathway where mitigation action is gradually strengthened by 2030
 9   compared to pre-COP 26 NDCs shows the lowest final energy demand. All ambitious IMPs show
10   substantially increasing contributions from electricity, with electricity’s end-use share more than
11   doubling for some of them by 2050 and more than tripling by 2100. The share of hydrogen shows a
12   flatter curve for many scenarios, reaching 5% (IMP-Ren) in 2050 and up to 20% in 2100 for some
13   scenarios (Ren, LD). Those scenarios that have a strong focus on renewable energy electrification show
14   high shares of hydrogen in the sector. In comparison to sector specific and national studies which show
15   typically a range between 5 and 15% by 2050, many IAM IMPs expect hydrogen to play a less important
16   role. Results for industrial CCS show a broad variety of contributions, with the GS scenario (where
17   hydrogen is not relevant as mitigation option) representing the upper bound to 2050, with almost 2
18   GtCO2·yr-1 captured and stored by 2050. Beyond 2050 the upper bound is associated with scenario IMP-
19   Neg associated with extensive use of CDR in the industry and energy sectors to achieve net negative
20   emissions in the second half of the century - more than 6 GtCO2·yr-1 is captured and stored in 2100
21   (this represents roughly 60% of 2018 direct CO2 emissions of the sector).
23 In-depth discussion and “reality” check of pathways from specific sector scenarios
24   Since AR5 a number of studies providing a high technological level of detail for the industry sector
25   have been released which describe how the industry sector can significantly reduce its GHG emissions
26   until the middle of the century. Many of these studies try to specifically reflect the particular industry
27   sector characteristics and barriers that hinder industry to follow an optimal transformation pathway.
28   They vary in respect to different characteristics. In respect to their geographical scope, some studies
29   analyse the prospects for industry sector decarbonisation on a global level (Tchung-Ming et al. 2018;
30   IEA 2017a; Grubler et al. 2018; Energy Transitions Commission 2018; IEA 2020a, 2019b, 2020c);
31   regional level, for example, European Commission (2018); Material Economics (2019), or country level
32   - studies for China, from where most industry related emissions come, (e.g. Zhou et al. (2019)).24 In
33   regard sectoral scope, some studies include the entire industry sector, while others focus on selected
34   GHG emission intensive sectors, such as steel, chemicals and/or concrete. Most of the scenarios focus
35   solely on CO2 emissions, that is non-CO2 emissions of the industrial sector are neglected.25
36   Industry sector mitigation studies also differ in regard to whether they develop coherent scenarios or
37   whether they focus on discussing and analysing selected key mitigation strategies, without deriving full

     FOOTNOTE 24 In addition, there are many other studies available which have developed country-specific,
     technologically detailed scenarios for industry decarbonisation e.g. (Gerbert et al. 2018) and a few which have
     investigated the decarbonisation prospects of individual industrial clusters (Schneider 2019), but these types of
     studies are not discussed here.
     FOOTNOTE25 Most of the global mitigation scenarios solely focus on CO2 emissions. Non-CO2 emissions make
     up only a small share of the industry sector’s current CO 2-eq. emissions and include N2O emissions (e.g. from
     nitric and adipic acid production), CH4 emissions (e.g. from chemical production and iron and steel production)
     and various F-gases (such as perfluorocarbons from primary aluminium production and semiconductor
     manufacturing) (Gambhir et al. 2017; USEPA and ICF 2012). Mitigation options for these non-CO2 emissions are
     discussed in (Gambhir et al. 2017).

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1    energy and emission scenarios. Coherent scenarios are developed in (IEA 2017; Energy Transitions
2    Commission 2018; Tchung-Ming et al. 2018; Grubler et al. 2018; IEA 2021a; IRENA 2021; IEA 2019b,
3    2020a,c) on the global level and in Climact (2018); European Commission (2018); Material Economics
4    (2019) on the European level. Recent literature analysing selected key mitigation strategies, for example
5    IEA (2019b) and Material Economics (2019) has focused either exclusively or to a large extent on
6    analysing the potential of materials efficiency and circular economy measures to reduce the need for
7    primary raw materials relative to a business-as-usual development. IEA (2021a, 2020a) also provides
8    deep insides in single mitigation strategies for the industry sector, particularly the role of CCS.
 9   The following discussion mainly concentrates on scenarios from IEA. It has to be acknowledged that
10   they only represent a small segment of the huge scenario family (cf. scenario data base in chapter 3),
11   but this approach enables to show the chronological evolution of scenarios coming from the same
12   institution, using the same modelling approach (which allows a technology-rich analytical backcasting
13   approach), but reflect additional requests that emerge over time (Table 11.5). In the 2DS scenario from
14   the “Energy Technology Perspectives (ETP)” study (IEA 2017), which intends to describe in great
15   technological detail how the global energy system could transform by 2060 so as to be in line with
16   limiting global warming to below 2°C, total CO2 emission are 74 % lower in 2060 than in 2014, while
17   only 39% lower in the industry sector. The B2DS scenario of the same study intends to show how far
18   known clean energy technologies (including those that lead to negative emissions) could go if pushed
19   to their practical limits, allowing the future temperature increase to be limited to “well below” 2°C and
20   lowering total CO2 emissions by 100% by 2060 and by 75% relative to 2014 in the industry sector.
21   Technologies penetration assumed in the CTS scenario by 2060 allows for an industrial emission cut of
22   45% from 2017 level and a 50% cut against projected 2060 emissions in the Reference Technology
23   Scenario (RTS) from the same study (IEA 2019b) similar to IEA’s 2DS scenario. Energy efficiency
24   improvements and deployment of BATs contribute 46% to cumulative emission reduction in 2018–
25   2060, while fuel switch (15%), material efficiency (19%) and deployment of innovative processes
26   (20%) provide the rest. IEA (2020a,c) which continuous the Energy Technology Perspectives series
27   include the new Sustainable Development Scenario (SDS) to describe a trajectory for emissions
28   consistent with reaching global “net zero” CO2 emissions by around 2070.26 In 2070 the net zero balance
29   is reached through a compensation of the remaining CO2-emissions (fossil fuel combustion and
30   industrial processes still lead to around 3 GtCO2) by a combination of BECCS and to a lesser degree
31   Direct Air Capture and storage. In IEA (2020c) the Faster Innovation Case (FIC) shows a possibility to
32   reach net zero emissions level globally already in 2050, assuming that technology development and
33   market penetration can be significantly accelerated. Innovation plays a major role in this scenario as
34   almost half of all the additional emissions reductions in 2050 relative to the reference case would be
35   from technologies that are in an early stage of development and have not yet reached the market today
36   (IEA 2020c). The most ambitious IEA scenario NZE2050 (IEA 2021a) describes a pathway reaching
37   net zero emissions at system level by 2050. With 0.52 GtCO2 industry related CO2-emissions (including
38   process emissions) it ends up 94% below 2018 level in 2050. Remaining emissions in the industry sector
39   have to be compensated by negative emissions (e.g. via DAC).

     FOOTNOTE26 Following the description of IEA SDS 2020 would limit the global temperature rise to below 1.8°C
     with a 66% probability if CO2 emissions remain at net zero after 2070. If CO2 emissions were to fall below net
     zero after 2070, then this would increase the possibility of reaching 1.5°C by the end of the century (IEA 2020c).

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1                                 Table 11.4 Perspectives on industrial sector mitigation potential (comparison of different IEA scenarios)

                                                                                        IEA (2017, 2020c,i, 2021a)            IEA (2019b)         IEA (2020a,c)
      Reduction of direct
                            Scenario assumptionsi
      CO2 emissions
                                                                                        2030             2050                 2060                2050            2070

      Baseline direct emissions from industrial sector
                            Industry sector improvements in energy consumption
                            and CO2 emissions are incremental, in line with
      Technology                                                                        9.8 GtCO2        10.4 GtCO2           9.7 GtCO2
                            currently implemented and announced policies and
      Scenario (RTS)
      Emission reduction potential

                            Assumes the decoupling of production in industry
                            from CO2 emissions growth across the sector that            -7% vs 2014ii    -39% vs 2014ii
      2°C Scenario (2DS)
                            would be compatible with limiting the rise in global        -20% vs RTSii    -50% vs RTSii
                            mean temperature to 2°C by 2100.

                            Pushes the available CO2 abatement options in
      Beyond        2°C                                                                 -28% vs 2014     -75% vs 2014
                            industry to their feasible limits in order to aim for the
      Scenario (B2DS)                                                                   -38% vs RTS      -80% vs RTS
                            “well below 2°C” target.
                            Strong focus on clean technologies. Energy efficiency
                                                                                                                              5 Gt CO2 or -45%
                            and deployment of BATs contribute 46% to
      Clean Technology                                                                                                        vs 2017 level and
                            cumulative emission reduction in 2018–2060; fuel
      Scenario (CTS)                                                                                                          -50% from 2060
                            switch -15%; material efficiency -19%; deployment of
                                                                                                                              RTS level
                            innovative processes -20%.
                            Leads to net zero emissions globally by 2070.
                            Remaining emissions in some sectors (including
                            industry) in 2070 will be compensated by negative                                                                     ~ 4.0           ~ 0.6
      Scenario 2020
                            emissions in other areas (e.g. through BECCS and
      (SDS 2020)
                                                                                        -94% (i.e. 8.4   Net-zero
      Net-zero emissions
                            -23% (i.e. 2.1 GtCO2) vs. 2018                              GtCO2)     vs.   emissions
      across all sectors
                                                                                        2018             across         all

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                                                                                     IEA (2017, 2020c,i, 2021a)          IEA (2019b)         IEA (2020a,c)
        Reduction of direct
                              Scenario assumptionsi
        CO2 emissions
                                                                                     2030             2050               2060                2050             2070
        are reached already                                                                           sectors     are
        by 2050.                                                                                      reached already
                                                                                                      by 2050.
                              Achieves net zero emissions status already by 2050                                                             0.8 Gt CO2
        Faster Innovation     based on accelerated development and market                                                                    (mainly steel
        Case (FIC)            penetration of technologies which have currently not                                                           and chemical
                              yet reached the market.                                                                                        industry)

       Based on bottom-up technology modelling of five energy-intensive industry subsectors (cement, iron and steel, chemicals and petrochemicals, aluminium and pulp and
       Industrial direct CO2 emissions reached 8.3 GtCO2 in 2014, 24% of global CO2 emissions.
2   Source: IEA (2017, 2020c,i, 2021a, 2019b, 2020a).

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1    Two studies complement the discussion of the IEA scenarios and are related to IEA data base.27 The
2    ETC Supply Side scenario builds on the ETP 2017 study, investigating additional emission reduction
3    potentials in the emissions intensive sectors such as heavy industry and heavy-duty transport so as to
4    be able to reach net zero emission by the middle of the century. The LED scenario (Grubler et al. 2018)
5    also builds on the ETP 2017 study, but focuses on the possible potential of very far-reaching efforts to
6    reduce future material demand.
 7   A comparison of the different mitigation scenarios shows that they depend on how individual mitigation
 8   strategies in the industry sector (see Figure 11.13) are assessed, . The use of CCS for example is in many
 9   scenarios assessed as very important, while other scenarios indicate that ambitious mitigation level can
10   be achieved without CCS in the industry sector. CCS plays a major role in the B2DS scenario (3.2
11   GtCO2 in 2050), the ETC Supply Side scenario (5.4 GtCO2 in 2050) and the IEA (2020a), IEA (2021a)
12   scenarios (e.g. 2.8 Gt CO2 in NZE2050 in 2050, roughly one halve of the captured CO2 is related to
13   cement production), while it is explicitly excluded in the LED scenario. In the latter scenario, on the
14   other hand, considerable emission reductions are assumed to be achieved by far-reaching reductions in
15   material demand relative to a baseline development. In other words, the analysed scenarios also suggest
16   that to reach very strong emission reductions from the industry sector either CCS needs to be deployed
17   to a great extent or considerable material demand reductions will need to be realised. Such demand
18   reductions only play a minor role in the 2DS scenario and no role in the ETC Supply Side scenario. The
19   SDS described in IEA (2020a) provides a pathway where both CCS and material efficiency contribute
20   significantly. In SDS material efficiency is a relevant factor in several parts of industry, explicitly steel,
21   cement, and chemicals. Combining the different material efficiency options including to a substantial
22   part lifetime extension (particularly of buildings) leads to 29% less steel production by 2070, 26% less
23   cement production, and 25% less chemicals production respectively in comparison to the reference line
24   used in the study (Stated Policy Scenario: STEPS). Sector or sub-sector specific analysis support the
25   growing role of material efficiency. For the global chemical and petrochemical sector (Saygin and
26   Gielen 2021) point out that circular economy (including recycling) has to cover 16% of the necessary
27   reduction that is need for the implementation of a 1.5°C scenario.
28   In all scenarios, the relevance of biomass and electricity in industrial final energy demand increases,
29   especially in the more ambitious scenarios NZE2050, SDS, ETC Supply Side and LED. While in all
30   scenarios, electrification becomes more and more important hydrogen or hydrogen-derived fuels, on
31   the other hand, do not contribute to industrial final energy demand by the middle of the century in 2DS
32   and B2DS, while LED (1% final energy share in 2050) and particularly ETC supply side (25% final
33   energy share in 2050) consider hydrogen or hydrogen-derived fuels as a significant option. In the
34   updated IEA scenarios hydrogen and hydrogen-based fuels already play a more important role. In the
35   SDS share in industry final energy is around 10% (IEA 2020a) and in the Faster Innovation Case around
36   12% (IEA 2020c) in 2050. In the latter case this is based on the assumption that by 2050 on average
37   each year 22 hydrogen-based steel plants come into operation (IEA 2020c). In SDS around 60% of the
38   hydrogen is produced onsite via water electrolysis while the remaining 40% is generated in fossil fuel
39   plants (methane reforming) coupled with CCS facilities. In the NZE2050 scenario biomass/biomethane
40   (13%/3%), hydrogen (3%), natural gas with CCUS (4%) and coal with CCUS (4%) are responsible for
41   27% of the final energy demand of the sector. This is much more than in 2018, starting here from
42   roughly 6% (only biomass). Direct use of electricity still plays a bigger role in the analysis, as share of

     FOOTNOTE27 Several other two global mitigation scenarios (e.g. from Tchung-Ming et al. (2018), Shell Sky
     Scenario from Shell (2018)) are not included in the following scenario comparison as the study’s energy and
     emission base year data on the industry sector deviates considerably from the other three studies included in the
     comparison, which all use IEA data. Furthermore, unlike the other studies, Tchung-Ming et al. (2018) do not
     provide detailed information on the steel, chemicals and concrete sub-sectors. Not included here but worth to be
     mentioned are many other sector specific studies, for example Napp et al. (2019, 2014), which consider more
     technologically advanced decarbonisation routes for the sector.

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1    electricity increases in NZE2050 from 22% in 2018 to 28% in 2030 and 46% in 2050 (in 2050 with
2    15% a part of the electricity is used to produce hydrogen). This is reflecting the effect that since
3    publication of older IEA reports more direct electric applications for the sector become available. In
4    NZE2050 approx. 25% of total heat used in the sector is electrified directly with heat pumps or
5    indirectly with synthetic fuels already by 2030.
 6   For B2DS it is assumed that most of the available abatement options in the industry sector are pushed
 7   to their feasible limits. That leads to cumulative direct CO2 emissions reductions compared to 2DS
 8   which come from: energy efficiency improvements and BAT deployment (42%), innovative processes
 9   and CCS (37%), switching to lower carbon fuels and feedstocks (13%) and material efficiency strategies
10   in manufacturing processes (8%). Energy efficiency improvements are particular important in the first
11   time period.
12   IEA World Energy Oulook indicates energy efficiency improvement in the 2020-2030 period as major
13   basis to switch from STEPS (stated policies) to the SDS (net zero emissions by 2070) pathway (IEA
14   2020i, 2021c). For many energy-intensive industries annual efficiency gains have to be almost doubled
15   (e.g., from 0.6% yr-1 to 1.0 % yr-1 for cement production) to contribute sufficiently to the overall goal.
16   If net zero CO2-emissions should be achieved already by 2050 as pursued in the NZE2050 scenario IEA
17   (2020i) and (2021c) further accelerating energy efficiency improvements are necessary (e.g., for cement
18   annual efficiency gains of 1.75%) leading to the effect, that in 2030 many processes are implemented
19   closely to their technological limits. In total, sector final energy demand can be held nearly constant at
20   2018 level until 2050 and decoupled from product demand growth
21   The comparative analysis leads to the point that the relevance of individual mitigation strategies in
22   different scenarios depends not only on a scenario’s level of ambition. Instead, implicit or explicit
23   assumptions about: a) the costs associated with each strategy, b) future technological progress and
24   availability of individual technologies and c) the future public or political acceptance of individual
25   strategies are likely to be main reasons for the observed differences between the analysed scenarios. For
26   many energy-intensive products technologies capable of deep emission cuts are already available. Their
27   application is subject to different economic and resources constrains (incremental investments needs,
28   products prices escalation, requirements for escalation of new low carbon power generation). To fully
29   exploit potential availability of carbon-free energy sources (e.g., electricity or hydrogen and related
30   derivates) is a fundamental prerequisite and marks the strong interdependencies between the industry
31   and the energy sector.
32   Assessment of the scenario literature allows to conclude that under specific conditions strong CO2
33   emission reductions in the industry sector by 2050–2070 and even net zero emission pathways are
34   possible. However, there is no consensus on the most plausible or most desirable mix of key mitigation
35   strategies to be pursued. In addition it has to be stressed that suitable pathways are very country-specific
36   and depend on the economic structure, resource potentials, technological competences, and political
37   preferences and processes of the country or region in question (Bataille 2020a).
38   There is a consensus among the scenarios that a significant shift is needed from a transition process in
39   the past mainly based on marginal (incremental) changes (with a strong focus on energy efficiency
40   efforts) to a one based on transformational change. To limit the barriers that are associated with
41   transformational change, besides overcoming the valley of death for technologies or processes with
42   breakthrough character, it is required to carefully identify structural change processes which are
43   connected with substantial changes of the existing system (including the whole process chain). This has
44   to be done at an early stage and has to be linked with considerations about preparatory measures which
45   are able to flank the changes and to foster the establishment of new structures (Section 11.6). The right
46   sequencing of the various mitigation options and building appropriate bridges between the different
47   strategies are important. Rissman et al. (2020) proposes three phases of technologies deployment for
48   the industry sector: (1) energy/material efficiency improvement (mainly incremental) and electrification

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1    in combination with demonstration projects for new technologies potentially important in subsequent
2    phases (2020-2035), (2) structural shifts based on technologies which reach maturity in phase (1) such
3    as CCS and alternative materials (2035-2050) (3) widespread deployment for technologies that are
4    nascent today like molten oxide electrolysis based steel making. There are no strong boundaries
5    between the different phases and all phases have to be accompanied by effective policies like R&D
6    programs and market pull incentives.
 7   Taking the steel sector as an illustrative example, sector specific scenarios examining the possibility to
 8   reach GHG reduction beyond 80% (CAT 2020; IEA 2021a; Vogl et al. 2021b; Bataille et al. 2021b)
 9   indicate that robust measures comprise direct reduction of iron (DRI) with hydrogen in combination
10   with efforts to further close the loops and increase availability of scrap metal (reducing the demand for
11   primary steel). As hydrogen based DRI might not be a fully mature technology before 2030 (depending
12   on further developments of the policy framework and technological progress), risk of path dependencies
13   has to be taken into consideration when reinvestments in existing production capacities will be required
14   in the coming years. For existing plants, implementation of energy efficiency measures (e.g. utilization
15   of waste heat, improvement of high temperature pumps) could build a bridge for further mitigation
16   measures, but have only limited unexhausted potential. As many GHG mitigation measures are
17   associated with high investment costs and missing operating experience, a step by step implementing
18   process might be an appropriate strategy to avoid investment leakage (given the mostly long operation
19   times, investment cycles have to be used so as not to miss opportunities) and to gain experience. In the
20   case of steel, companies can start with the integration of a natural gas based direct reduced iron furnace
21   feeding the reduced iron to an existing blast furnace, blending and later replacing the natural gas by
22   hydrogen in a second stage, and later transitioning to a full hydrogen DRI EAF or molten oxide
23   electrolysis EAF, all without disturbing the local upstream and downstream supply chains.
24   It is worth mentioning the flexibility of implementing transformational changes not the least depends
25   on the age profile and projected longevity of existing capital stock, especially the willingness to accept
26   the intentional or market-based stranding of high GHG intensity investments. This is a relevant aspect
27   in all producing countries, but particularly in those countries with a rather young industry structure (i.e.
28   comparative low age of existing facilities on average). Tong et al. (2019) suggest that in China using
29   the survival rate as a proxy less than 10% of existing cement or steel production facilities will reach
30   their end of operation time by 2050. Vogl et al. (2021b) argue that the mean blast furnace campaign is
31   considerably shorter than used in Tong et al (2019), at only 17 years between furnace relining, which
32   suggests there is more room for retrofitting with clean steel major process technologies than generally
33   assumed. Bataille et al. (2021b) found if very low carbon intensity processes were mandatory starting
34   in 2025, given the lifetimes of existing facilities, major steel process lifetimes of up to 27 years would
35   still make a full retrofit cycle with low carbon processes possible.
36   In general, early adoption of new technologies plays a major role. Considering the long operation time
37   (lifetime) of industrial facilities (e.g., steel mills, cement kilns) early adoption of new technologies is
38   needed to avoid lock-in. For the SDS 2020 scenario, IEA (2020h) calculated the potential cumulative
39   reduction of CO2-emissions from the steel, cement and chemicals sector to be around 57 GtCO2 if
40   production technology is changed at its first mandatory retrofit, typically 25 years, rather than at 40
41   years (typical retrofitted lifetime) (Figure 11.13). Net zero pathways require that the new facilities are
42   based on zero- or near zero emissions technologies from 2030 onwards (IEA 2021c).
43   Another important finding is that material efficiency and demand management are still not well
44   represented in the scenario literature. Besides IEA (2020a) two of the few exceptions are Material
45   Economics (2019) for the EU and Zhou et al. (2019) for China. Zhou et al. (2019) describe a consistent
46   mitigation pathway (Reinventing Fire scenario) for China where in 2050 CO2-emissions are at a level
47   42% below 2010 emissions. Around 13% of the reduction is related to less material demand, mainly
48   based on extension of building and infrastructure lifetime as well as reduction of material losses in the

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1    production process and application of higher quality materials particularly high-quality cement (Zhou
2    et al. 2019). For buildings and cars, Pauliuk et al. (2021) analyzed the potential role of material
3    efficiency and demand management strategies on material demand to be covered by the industry sector.
 4   For the three most important sub-sectors in industry Table 11.5 shows results from Material Economics
 5   (2019) for the EU. The combination of circularity, material and energy efficiency, fossil and waste fuels
 6   mix, electrification, hydrogen, and biomass use varies from scenario to scenario with no of these options
 7   ignored. On the contrary, for CCS the authors set a strong default - in all scenarios CCS is not included
 8   as a mitigation option. Scenario studies for Germany Samadi and Barthel (2020) support the Material
 9   Economics (2019) findings and show deep mitigation s and even net zero emissions can be reached
10   without application of CCS and with limited contribution of synthetic carbon neutral fuels. In those
11   scenarios there are large contributions from material efficiency, circular economy, material substitution
12   as well as life-style changes.
14     Table 11.5 Contribution to emission reduction of different mitigation strategies for net zero emission
15     pathways (range represents three different pathways for the industry sector in Europe; each related
16                                 scenario focus on different key strategies)28

                                                   Steel            Plastics         Ammonia     Cement
                                                   Contribution to emission reduction (%) (range represents the
                                                   three different pathways of the study)
     Circularity                                   5–27             7–27                         10–44
     Energy efficiency                             5–23             2–9                          1–5
     Fossil fuels and waste fuels                  9–41             0–27                         0–51
     Decarbonised electricity                      36–59            16–22                        29–71
     Biomass for fuel or feedstock                 5–9              18–22                        0–9
     End-of-life plastic                                            16–35
                                                   Required electrification level
     Growth of electricity      demand    (times
                                                   3–5             3–4                              2–5
     compared with 2015)
                                                   Investments and production costs escalation
     Investment needs growth (% versus BAU)        25–65          122–199          6–26             22–49
     Cost of production (% versus BAU)             2–20           20–43            15–111           70–115
17   Source: Material Economics (2019).
19   The analysis of net zero emission pathways require significantly higher investments compared to
20   business as usual (BAU), 25% to 65% for steel, 6–26% for Ammonia, 22–49% for cement and with
21   122–199% the highest number for plastics (Material Economics 2019).
22   While sector specific cost analysis are rare in general, there are scenarios indicating that pathways to
23   net zero CO2 emissions in the emissions intensive sectors can be realized with limited additional costs.
24   According to Energy Transitions Commission (2018) deep decarbonization from four major industry
25   subsectors (plastics, steel, aluminium and cement) is achievable on a global level with cumulative
26   incremental capital investments (2015–2050) limited to about 0.1% of aggregate GDP over that period.
27   UKCCC (2019a) assesses that total incremental costs (compared to a theoretical scenario with no
28   climate change policy action at all) for cutting industrial emissions by 90% by 2050 is 0.2% of expected
29   2050 UK GDP (UKCCC 2019a). The additional investment is 0.2% of gross fixed capital formation
30   (Material Economics 2019). The IEA (2020a) indicates the required annual incremental global
31   investment in heavy industry is approximately 40 billion 2019 USD yr-1 moving from (STEPS) to the

     FOOTNOTE28 Note: In the described scenarios CCS was not taken into consideration as a mitigation option by
     the authors.

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1    SDS scenario (2020–2040), rising to 55 billion USD yr-1 (2040–2070), effectively 0.05-0.07% of global
2    annual GDP today.
3    Finally, a new literature is emerging, based on the new sectoral electrification, hydrogen and CCS based
4    technologies listed in previous sections, considering the possibility of rearranging standard supply and
5    process chains using regional and international trade in intermediate materials like primary iron, clinker
6    and chemical feedstocks, to reduce global emissions by moving production of these materials to regions
7    with large and inexpensive renewable energy potential or CCS geology (Gielen et al. 2020; Bataille et
8    al. 2021a; Saygin and Gielen 2021; Bataille 2020a)
 9   In a sequence of sectoral and industry wide figures below (Figure 11.13), it is shown - starting in the
10   present on the left and moving through 2050 to 2070 on the right, how much separate mitigation
11   strategies can contribute and how they are integrated in the literature to reach near zero emissions. For
12   cement, steel and primary chemicals GHG intensities are presented, and for all industry absolute GHG
13   emissions are displayed. Effects of the following mitigation strategies are reflected: energy efficiency,
14   material efficiency, circularity/recycling, feedstock carbon intensity, fuel switching, CCU and CCS.
15   Contributions of technologies split by their readiness for 2050 and 2070 are provided along with ranges
16   of mitigation costs for achieving near zero emissions for each strategy, accompanied by ranges of
17   associated basic materials costs escalations and driven by these final products prices increments.

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2   Figure 11.13 Potentials and costs for zero-carbon mitigation options for industry and basic materials CIEl
3    –carbon intensity of electricity for indirect emissions; EE – energy efficiency; ME – material efficiency;
4     Circularity - material flows (clinker substituted by coal fly ash, blast furnace slag or other by-products

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 1     and waste, steel scrap, plastic recycling, etc.); FeedCI – feedstock carbon intensity (hydrogen, biomass,
 2     novel cement, natural clinker substitutes); FSW+El – fuel switch and processes electrification with low
 3      carbon electricity. Ranges for mitigation options are shown based on bottom-up studies for grouped
 4    technologies packages, not for single technologies. In circles contribution to mitigation from technologies
 5     based on their readiness are shown for 2050 (2040) and 2070. Direct emissions include fuel combustion
 6       and process emissions. Indirect emissions include emissions attributed to consumed electricity and
 7     purchased heat. For basic chemicals only methanol, ammonia and high-value chemicals are considered.
 8      Total for industry doesn’t include emissions from waste. Base values for 2020 for direct and indirect
 9      emissions were calculated using 2019 GHG emission data (Crippa et al. 2021) and data for materials
10     production from World Steel Association (2020a) and IEA (2021d). Negative mitigation costs for come
11                                      options like Circularity are not reflected.
12   Sources: (Fawkes et al. 2016; CEMBUREAU 2020; JULIO Friedmann et al. 2019; CAT 2020; Pauliuk et al.
13   2013a; Material Economics 2019; EUROFER 2019; Gielen et al. 2020; Sandalow et al. 2019; Saygin and Gielen
14   2021; WBCSD 2016; World Steel Association 2020b; Scrivener et al. 2018; Bazzanella and Ausfelder 2017;
15   Habert et al. 2020; Lehne and Preston 2018; Bataille 2020a; GCCA 2021a; IEA 2018a, 2019b,g,h, 2020a,c,
16   2021a).

18   11.4.3 Cross sectorial interactions and societal pressure on industry
19   Mitigation involves greater integration and coupling between sectors. This is widely recognised for
20   example in the case of electrification of transport (see 6.6.2 and 10.3.1) but it has been less explored for
21   industrial decarbonisation. Industry is a complex web of sub-sectors and intersectoral interaction and
22   dependence, with associated mitigation opportunities and co-benefits and costs (OECD 2019b; Mendez-
23   Alva et al. 2021). Implementation of the mitigation options assessed in 11.3 will result in new sectoral
24   couplings, value chains, and business models but also in phasing-out of old ones. Notably,
25   electrification in industry, hydrogen and sourcing of non-fossil carbon involves profound changes to
26   how industry interacts with electricity systems and how industrial sub-sectors interact. For example, the
27   chemicals and forestry industries will become much more coupled if various forms of biogenic carbon
28   become an important feedstock for plastics (Figure 11.10). Clinker substitution with blast furnace slag
29   in the cement industry is well established way of reducing CO2 emissions (Fechner and Kray 2012) but
30   this slag will no longer be available if blast furnaces are phased-out. Furthermore, additional material
31   demand resulting from mitigation in other sectors, as well as adaptation, and the importance of material
32   efficiency improvements are issues that has attracted increasing attention since AR5 (Hertwich et al.
33   2020; IEA 2019b; Bleischwitz 2020). How future material will be affected under different climate
34   scenarios is underexplored and typically not accounted for in modelling (Bataille et al. 2021a).
35   Using industrial waste heat for space heating, via district heating, is an established practice that still has
36   a large potential with large quantities of low-grade heat being wasted (Fang et al. 2015). For Denmark
37   it is estimated that 5.1% of district heating demand could be met with waste heat (Bühler et al. 2017)
38   and for four towns studied in Austria 3-35% of total heat demand could be met (Karner et al. 2016). A
39   European study shows that temporal heat demand flexibility could allow for up to 100% utilization of
40   excess heat from industry (Karner et al. 2018). A study of a Swedish chemicals complex estimated that
41   30-50% of excess heat generated on-site could be recovered with payback periods below 3 years
42   (Eriksson et al. 2018).
43   A European study found that most of the industrial symbiosis or clustering synergies today are in the
44   chemicals sector with shared streams of energy, water, and carbon dioxide (Mendez-Alva et al. 2021).
45   For future mitigation the UKCCC (2019b) finds that industrial clustering may be essential for achieving
46   the necessary efficiencies of scale and to build the infrastructure needed for industrial electrification;
47   carbon capture, transport and disposal; hydrogen production and storage, heat cascading between
48   industries and to other potential heat users (e.g. residential and commercial buildings).

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 1   With increasing shares of renewable electricity production there is a growing interest in industrial
 2   demand response, storage and hybrid solutions with on-site PV and CHP (Schriever and Halstrup 2018;
 3   Scheubel et al. 2017; Shoreh et al. 2016). With future industrial electrification, and in particular with
 4   hydrogen used as reduction agent in ironmaking or as feedstock in the chemicals industry, the level of
 5   interaction between industry and power systems becomes very high. Large amounts of coking coal, or
 6   oil and gas as petrochemical energy and feedstock, are then replaced by electricity. For example, Meys
 7   et al. (2021) estimates a staggering future electricity demand of 10,000 TWh in a scenario for a net zero
 8   emissions plastics production of 1100 Mt in 2050 (see 11.3.5 for other estimates of electricity demand).
 9   Much of this electricity is used to produce hydrogen to allow for CCU and this provides a very large
10   potential flexible demand if electrolysers are combined with hydrogen storage. Vogl et al. (2018)
11   describe how hydrogen DRI and EAF steel plants can be highly flexible in their electricity demand by
12   storing hydrogen or hot-briquetted iron and increasing the share of scrap in EAF. The IEA (2019f)
13   Future of Hydrogen report suggests that hydrogen production and storage networks could be in locations
14   with already existing hydrogen production and storage, for example, chemical industries, and that these
15   could be ideal for system load balancing and demand response, and in case of district heating systems
16   - for heat cascading.
17   The climate awareness that investors, shareholders, and customers demand from companies has been
18   increasing steadily. It is reflected in growing number of environmental management, carbon footprint
19   accounting, benchmarking and reporting schemes (e.g., the Carbon Disclosure Project, Task Force on
20   Climate-Related Financial Disclosures, Environmental Product Declarations and others, e.g., Qian et al.
21   (2018)) requiring companies to disclose both direct and indirect GHG emissions, and creating explicit
22   (for regulatory schemes) as well as implicit GHG liabilities. This requires harmonised and widely
23   accepted methods for environmental and carbon footprint accounting (Bashmakov et al. 2021b). From
24   an investor perspective there are both physical risks (e.g., potential damages from climate change to
25   business) and transition risks (e.g., premature devaluation of assets driven by new policies and
26   technologies deployment and changes in public and private consumer preferences (NGFS 2019a)).
27   Accompanied by reputational risks this leads to increased attention to Sustainable and Responsible
28   Investment (SRI) principles and increased demands from investors, consumers and governments on
29   climate and sustainability reporting and disclosure (NGFS 2019b). For example, Japan's Keidanren
30   promotes a scheme by different each industries to reduce GHG through the global value chain, including
31   material procurement, product use stages, and disposal, regardless of geographical origin, with provided
32   quantitative visualization (Keidanren (Japan Business Federation) 2018). EU adopted a non-financial
33   disclosure Directive in 2014 (Kinderman 2020) and a Taxonomy for Sustainable Finance in 2019 (see
34   also 15.6.1).
36   11.4.4 Links to climate change, mitigation, adaptation
37   Sectors that are particularly vulnerable to climate change include agriculture, forestry, fisheries and
38   aquaculture, and their downstream processing industries (Bezner et al. 2021). Many of the energy
39   intensive industries are located based on access to fresh water (e.g., pulp and paper) or sea transport
40   (e.g., petrochemicals). Risks of major concern for industry include disrupted supply chains and energy
41   supplies due to extreme weather events, as well as risks associated with droughts, floods with dirty
42   water, sea level rise and storm surges (Dodman et al. 2021). Adaptation measures may in turn affect the
43   demand for basic materials (e.g., steel and cement), for example, increased demand to build sea walls
44   and protect infrastructure, but we have not found any estimates of the potential demand. Increased heat
45   stress is unsafe for outdoor labourers and can reduce worker productivity, for example, in outdoor
46   construction, resource extraction and waste handling (Ranasinghe et al. 2021).

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1    11.5 Industrial infrastructure, policy, and SDG contexts
2    11.5.1 Existing industry infrastructures
 3   Countries are at different stages of different economic development paths. Some are already
 4   industrialised, while developing and emerging economies are on earlier take-off stages or accelerated
 5   growth stages and have yet to build the basic infrastructure needed to allow for basic mobility, housing,
 6   sanitation, and other services (see 11.2.3). The available in-use stock of material per capita and in each
 7   country therefore differs significantly, and transition pathways will require a different mix of strategies,
 8   depending on each country’s material demand to build, maintain, and operate stock of long-lived assets.
 9   Industrialised economies have much greater opportunities for reusing and recycling materials, while
10   emerging economies have greater opportunities to avoid carbon lock-in. The IEA projected that more
11   than 90% of the additional 2050 production of key materials will originate in non-OECD countries (IEA
12   2017). As incomes rise in emerging economies, the industry sector will grow in tandem to meet the
13   increased demand for the manufactured goods and raw materials essential for infrastructure
14   development. The energy and feedstocks needed to support this growth is likely to constitute a large
15   portion of the increase in the emerging economies’ GHG emissions in the future unless new low carbon
16   pathways are identified and promoted.
17   Emissions are typically categorised by the territory, sub-sector or group of technologies from which
18   they emanate. An alternative sub-division is that between existing sources that will continue to generate
19   emissions in the future, and those that are yet to be built (Erickson et al. 2015). The rate of emissions
20   from existing assets will eventually tend to zero, but in a timeframe that is relevant to existing climate
21   and energy goals, the cumulative contribution to emissions from existing infrastructure and equipment
22   is likely to be substantial. Aside from the magnitude of the contribution, the distinction between
23   emissions from existing and forthcoming assets is instructive because of the difference in approach to
24   mitigation that may be necessary or desirable in each instance to avoid getting locked into decades of
25   highly carbon-intensive operations (Lecocq and Shalizi 2014).
26   Details of the methodologies to assess ‘carbon lock-in’ or ‘committed emissions’ differ across studies
27   but the core components of the approaches adopted are common to each: an account of the existing
28   level of emissions for the scope being assessed is established; this level is projected forward with a
29   stylised decay function that is informed by assessments of the current age and typical lifetimes of the
30   underlying assets. From this, a cumulative emissions estimate is calculated. The future emissions
31   intensity of the operated assets is usually assumed to remain constant, implying that nothing is done to
32   retrofit with mitigating technologies (e.g., carbon capture) or alter the way in which the plant is operated
33   (e.g. switching to an alternative fuel or feedstock). While the quantities of emissions derived are often
34   referred to as ‘committed’ or ‘locked-in’, their occurrence is of course dependent on a suite of economic,
35   technology and policy developments that are highly uncertain.
36   Data on the current age profile and typical lifetimes of emissions-intensive industrial equipment are
37   difficult to procure and verify and most of the studies conducted in this area contain little detail on the
38   global industrial sector. Two recent studies are exceptions, both of which cover the global energy
39   system, but contain detailed and novel analysis on the industrial sector (Tong et al. 2019; IEA 2020a).
40   Tong et al. (2019) use unpublished unit-level data from China’s Ministry of Ecology and Environment
41   to obtain a more robust estimate of the age profile of existing capacity in the cement and iron and steel
42   sectors in the country. The IEA (2020a) uses proprietary global capacity datasets for the iron and steel,
43   cement and chemicals sectors, and historic energy consumption data for the remaining industry sectors
44   as a proxy for the rate of historic capacity build-up.
45   Both studies come to similar estimates on the average age of cement plants and blast furnaces in China
46   of around 10-12 years old, which are the figures for which they have overlapping coverage. Both studies

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1    also use the same assumption of the typical lifetime of assets in these sectors of 40 years, whereas the
2    IEA (2020a) study uses 30 years for chemical sector assets and 25 years for other industrial sectors. The
3    studies come to differing estimates of cumulative emissions by 2050 from the industry sector; 196
4    GtCO2 in the IEA (2020a) study, and 162 GtCO2 in the Tong et al. (2019) study. This difference is
5    attributable to a differing scope of emissions, with the IEA (2020a) study including industrial process
6    emissions (which for the cement sector in particular are substantial) in addition to the energy-related
7    emissions quantities accounted for in the Tong et al. (2019) study. After correcting for this difference
8    in scope, the emissions estimates compare favourably.
 9   The IEA (2020a) study provides supplementary analysis for the industry sector, examining the impact
10   of considering investment cycles alongside the typical lifetimes assumed in its core analysis of
11   emissions from existing industrial assets. For three heavy industry sectors – iron and steel, cement and
12   chemicals – the decay function applied to emissions from existing assets is re-simulated using a 25-year
13   investment cycle assumption (Figure 11.14). This is 15 years shorter than the typical lifetimes assumed
14   for assets in the iron and steel and cement sectors, and 5 years shorter than that considered for the
15   chemical sector. The shorter timeframe for the investment cycle is a simplified way of representing the
16   intermediate investments that are made to extend the life of a plant, such as the re-lining of a blast
17   furnace, which can occur multiple times during the lifetime of an installation. These investments can
18   often be similar in magnitude to that of replacing the installation, and they represent key points for
19   intervention to reduce emissions. The findings of this supplementary analysis are that around 40%, or
20   60 GtCO2, could be avoided by 2050 if near-zero emissions options are available to replace this
21   capacity, or units are retired, retro-fitted or refurbished in a way that significantly mitigates emissions
22   (e.g. retro-fitting carbon capture, or fuel or process switching to utilise bioenergy or low-carbon
23   hydrogen).

26                  Figure 11.14 CO2 emissions from existing heavy industrial assets in the NZE
27   Source: IEA (2021a).

29   As this review was being finalized several papers were released that somewhat contradict the Tong et
30   al (2010) results (Vogl et al. 2021b; Bataille et al. 2021b). Broadly speaking, these papers argue that
31   while high emitting facilities may last for long time, be difficult to shut down early, and are inherent to
32   local boarder supply chains, individual major processes that are currently highly GHG intense, such as
33   blast furnaces and basic oxygen smelters, could be retired and replaced during major retrofits on much
34   shorter time cycles of 15–25 years.

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 1   The cost of retrofitting or retiring a plant before the end of its lifetime depends on plant specific
 2   conditions as well as a range of economic, technology and policy developments. For industrial
 3   decarbonisation it may be a greater challenge to accelerate the development and deployment of zero
 4   emission technologies and systems than to handle the economic costs of retiring existing assets before
 5   end of life. The ‘lock-in’ also goes beyond the lifetime of key process units, such as blast furnaces and
 6   crackers, since they are typically part of large integrated plants or clusters with industrial symbiosis, as
 7   well as infrastructures with feedstock storage, ports, and pipelines. Individual industrial plants are often
 8   just a small part of a complex network of many facilities in an industrial supply chain. In that sense,
 9   current assessments of ‘carbon lock-in’ rely on simplifications due to the high the complexity of
10   industry.
11   Conditions are also sub-sector and context specific in terms of mitigation options, industry structures,
12   markets, value chains and geographical location. For example, the hydrogen steelmaking joint venture
13   in Sweden involves three different companies headquartered in Sweden (in mining, electricity and
14   steelmaking, respectively), two of which are state owned, with a shared vision and access to iron ore,
15   fossil-free electricity and high-end steel markets (Kushnir et al. 2020). In contrast, chemical clusters
16   may consist of several organisations that are subsidiaries to large multinational corporations with
17   headquarters across the world, that also compete in different markets. Even in the presence of a local
18   vision for sustainability this makes it difficult to engage in formalised collaboration or get support from
19   headquarters (Bauer and Fuenfschilling 2019).
20   Furthermore, it is relevant to consider also institutional and behavioural lock-in (Seto et al. 2016). On
21   one side, existing high-emitting practices may be favoured through formal and informal institutions
22   (e.g., regulations and social norms or expectations, respectively), for example around building
23   construction and food packaging. On the other side, mitigation options may face corresponding
24   institutional barriers. Examples include how cars are conventionally scrapped (i.e., crushed, leading to
25   copper contamination of steel) rather than being dismantled, or slow permitting procedures for new
26   infrastructure and industrial installations for reducing emissions.
28   11.5.2 Current industrial and broader policy context
29   The basic motivation for industrial policy historically has been economic development and wealth
30   creation. Industrial policy can be progressive and promote new developments or be protective to help
31   infant or declining industries. It may also involve the phase-out of industries, including efforts to retrain
32   workers and create new jobs. Industrial policy is not one policy intervention but rather the combined
33   effects of many policy instruments that are coordinated towards an industrial goal. Industrial policies
34   can be classified as being either vertical or horizontal depending on whether singular sectors or
35   technologies are targeted (e.g., through R&D, tariffs and subsidies) or the whole economy (e.g.,
36   education, infrastructure, and general tax policies). The horizontal policies are not always thought of as
37   industrial policy although taking a broad view, including policy coordination and institution building,
38   is important for industrial policy to be effective (see e.g., Andreoni and Chang (2019)).
39   In the past ten years there has been increasing interest and attention to industrial policy. One driver is
40   the desire to retain industry or re-industrialise in regions within Europe and North America where
41   industry has a long record of declining shares of GDP. The need for economic growth and poverty
42   eradication is a key driver in developing countries. An important aspect is the need to meet the “dual
43   challenge of creating wealth for a growing population while staying within planetary boundaries”
44   (Altenburg and Assman 2017). The need for industrial policy that supports environmental goals and
45   green growth has been analysed by Rodrik (2014); Aiginger (2014); Warwick (2013) and Busch et al.
46   2018). Similar ideas are taken up in OECD reports on green growth (OECD 2011) and system
47   innovation (OECD 2015). However, these approaches to green industrial policy and innovation tend to

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1    focus on opportunities for manufacturing industries to develop through new markets for cleaner
2    technologies. They rarely include explicit attention to the necessity of zero emissions and the profound
3    changes in production, use and recycling of basic materials that this entails. This may also involve the
4    phase-out or repurposing of industries that currently rely on fossil fuels and feedstock.
 5   The policy implications of zero emissions for heavy industries are relatively unexplored although some
 6   analyses in this direction are available (e.g., (Wesseling et al. 2017; Philibert 2017a; Wyns et al. 2019;
 7   Fan and Friedmann 2021; Åhman et al. 2017; Bataille 2020a; Bataille et al. 2018a)). For industry, there
 8   has been a long time focus on energy efficiency policies through voluntary and negotiated agreements,
 9   energy management and audit schemes, and various programs targeting industry (Fischedick et al.
10   2014a). Since AR5, interest in circular economy policies has increased and they have become more
11   prevalent across regions and countries, including EU, China, U.S., Japan and Brazil (e.g. (McDowall et
12   al. 2017; Ranta et al. 2018; Geng et al. 2019)). For electrification and CCUS, efforts are nascent and
13   mainly focused on technology development and demonstrations. Policies for demand reduction and
14   materials efficiency are still relatively unexplored (e.g., Pollitt et al. (2020) and IEA (2019b)). Since
15   zero emissions in industry is a new governance challenge it will be important to build awareness and
16   institutional capacity in industrialised as well as developing countries.
17   In the context of climate change policy, it is fair to say that industry has so far been sheltered from the
18   increasing costs that decarbonisation may entail. This is particularly true for the energy and emissions
19   intensive industries where cost increases and lost competitiveness may lead to carbon leakage, i.e., that
20   industry relocates to regions with less stringent climate policies. Heavy industries typically pay no or
21   very low energy taxes and where carbon pricing exists (e.g., in the European Trading Scheme) they are
22   sheltered through free allocation of emission permits and potentially compensated for resulting
23   electricity price increases. For example, Okereke and McDaniels (2012) shows how the European steel
24   industry was successful in avoiding cost increases and how information asymmetry in the policy process
25   was important for that purpose.
27   11.5.3 Co-benefits of Mitigation Strategies and SDGs
28   The deployment of climate change mitigation strategies is primarily influenced by its costs and
29   potential, but also by other broader sustainable development factors such as the SDGs. Mitigation
30   actions therefore are to be considered through the prism of impacts on achieving other economic, social
31   and environmental goals. Those impacts are classified as co-benefits when they are positive or as risk
32   when they are negative. Co-benefits can serve as additional drivers, whiles risks can inhibit the
33   deployment of available mitigation options. Actions taken to mitigate climate change have direct and
34   indirect interactions with SDGs, both positive (synergies) or negative (trade-off) (Fuso Nerini et al.
35   2019).
36   Given the wide range of stakeholders involved in climate actions and their (often contradictory) interests
37   and priorities, the nature of co-benefits and risk can affect decision-making processes and behaviour of
38   stakeholders (Labella et al. 2020). Co-benefits form an important driver supporting the adoption of
39   mitigation strategies, yet are commonly overlooked in policymaking. Karlsson et al. (2020), based on a
40   review of 239 peer-reviewed articles concluded that diverse co-benefit categories, including air, soil
41   and water quality, diet, physical activity, biodiversity, economic performance, and energy security, are
42   prevalent in the literature.
44 SDGs co-Benefits through Material Efficiency and Demand Reduction
45   Material efficiency, an important mitigation option (SDG 13 - Climate action) for heavy industries, is
46   yet to be fully acknowledged and leveraged (Gonzalez Hernandez et al. 2018a; Sudmant et al. 2018;

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1    Dawkins et al. 2019). Material efficiency directly address SDG 12 (Responsible production and
2    consumption) but also provide opportunities to reduce the pressures and impacts on environmental
3    systems (SDG 6 – Clean water and sanitation) (Olivetti and Cullen 2018). Exploiting material efficiency
4    usually requires new business models and provides potential co-benefits of increased employment and
5    economic opportunities (SDG 8 - Decent work and economic growth).
 6   Material efficiency also provides co-benefits through infrastructural development (SDG 9 – Industry,
 7   innovation and infrastructure) (Mathews et al. 2018) to support the wide range of potential material
 8   efficiency strategies including light-weighting, re-using, re-manufacturing, recycling, diverting scrap,
 9   extending product lives, using products more intensely, improving process yields, and substituting
10   materials (Allwood et al. 2011). Worrell et al. (2016) also emphasises how material efficiency
11   improvements, in addition to limiting the impacts of climate change help deliver sustainable production
12   and consumption co-benefits through environmental stewardship. Binder and Blankenberg (2017) and
13   Dhandra (2019) show that sustainable consumption is positively related to life satisfaction and
14   subjective well-being (SDG 3) and Guillen-Royo (2019) adds positive association with happiness and
15   life satisfaction.
16   The reduction in excessive consumption and demand for products and services generates a reduction in
17   post-consumption waste and so enhances clear water and sanitation (SDG 6) (Govindan 2018;
18   Minelgaitė and Liobikienė 2019) and reduces waste along product supply chains and lifecycle (SDG
19   12) (Unstats 2020). Genovese et al. (2017) At the risk side there are possible reduction of employment,
20   incomes, sales taxes from the material extraction and processing activities, considered as excessive for
21   sustainable consumption (Thomas 2003).
23 SDGs co-Benefits from Circular Economy and Industrial Waste
24   While the circular economy concept first emerged in the context of waste avoidance, resource depletion,
25   closed-loop recycling, etc., it has now evolved as a tool for a broader systemic national policy due to
26   its potential wider benefits (Geng et al. 2013). It represents new circular business models that encourage
27   design for re-use and to improve material recovery and recycling, and so represents a departure from
28   the traditional linear production and consumption systems (with landfilling at the end), with a wide
29   range of potential co-benefits to a wide range of SDGs (Genovese et al. 2017; Schroeder et al. 2019;
30   Unstats 2020; Guo et al. 2016).
31   Genovese et al. (2017) articulates the advantages from an environmental and responsible consumption
32   and production point of view (SDG 12). Many studies have outlined new business models based on the
33   circular economy that fosters sustainable economic growth and the generation of new jobs (SDG 8)
34   (Antikainen and Valkokari 2016), as well as global competitiveness and innovation in business and the
35   industrial sector (Pieroni et al. 2019), such as its potential synergies with industry 4.0 (Garcia-Muiña et
36   al. 2018).
37   Following a review of the literature, Schroeder et al. (2019) identified linkages between circular
38   economy practices and SDGs based on a relationship scoring system and highlighted that such SDGs
39   as SDG 6 (Clean Water and Sanitation), SDG 7 (Affordable and Clean Energy), SDG 8 (Decent Work
40   and Economic Growth), SDG 12 (Responsible Consumption and Production), and SDG 15 (Life on
41   Land) all strongly benefit from circular economy practices. With the potential to impact on all stages of
42   the value chain (micro, meso- and macro-level of the economy), circular economy has also been
43   identified as key industrial strategy to managing waste across sectors.
44   Chatziaras et al. (2016) highlights the co-benefit to SDG 7 (Affordable and Clean Energy) resulting
45   from waste derived fuel for the cement industry. Through the management of industrial waste using
46   circular economy practices, studies such as (Geng et al. 2012; Bonato and Orsini 2017) have pointed

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1    out co-benefits to SDGs beyond clear environmental and economic benefits, highlighting how it also
2    benefits SDG 3 and 11 through improved social relations between industrial sectors and local societies,
3    and improved public environmental awareness and public health level.
5 SDG co-Benefits from Energy Efficiency
 6   Beyond the very direct links between energy and climate change, reliable, clean, and affordable energy
 7   (SDG 7) presents a cross-cutting issue, central to all SDGs and fundamental to development, and energy
 8   efficiency enables its provision by reducing the direct supply and necessary infrastructure required.
 9   Energy efficiency improvements can be delivered through multiple technical options and tested
10   policies, delivering energy and resource savings simultaneously with other socio-economic and
11   environmental co-benefits. At the macro-level, this includes enhancement of energy security (SDG 16
12   – Peach, Justice and Strong Institutions) delivered through clean low carbon energy systems
13   (Fankhauser and Jotzo 2018). Much of the literature, including Sari and Akkaya (2016); Garrett-Peltier
14   (2017) and Allan et al. (2017) points out that energy efficiency improvements deliver superior
15   employment opportunities (SDG 8 - Decent Work and Economic Growth), while a limited number of
16   studies have reported that it can negatively impact employment in fuel supply sectors (Costantini et al.
17   2018).
18   Many studies report that energy efficiency improvements are essential for supporting overall economic
19   growth, contributing to positive changes in multi-factor productivity (SDG 8 - Decent Work and
20   Economic Growth & Industry, Innovation, and Infrastructure) (Bashmakov 2019; Bataille and Melton
21   2017; Stern 2019; Lambert et al. 2014; Rajbhandari and Zhang 2018) through industrial innovation
22   (SDG 9) (Kang and Lee 2016), with some dissent e.g., (Mahmood and Ahmad 2018). Improved energy
23   efficiency against a background of growing energy prices helps industrial plants stay competitive
24   (Bashmakov and Myshak 2018). Energy efficiency allows continued economic growth under strong
25   environmental regulation. Given that energy efficiency measures reduce the combustion of fossil fuels
26   it leads to reduced air pollution at industrial sites (Williams et al. 2012) and better indoor comfort at
27   working places.
28   Since less energy supply infrastructure is needed in cities and less energy is needed to produce materials
29   such as cement & concrete, and metals, energy efficiency indirectly supports Sustainable Cities and
30   Communities (SDG 11) (Di Foggia 2018). In addition, energy efficiency in industry reflects
31   achievements in meeting SDG12 (Responsible Consumption and Production.
33 SDGs co-Benefits from Electrification and Fuel Switching
34   A key, generally underappreciated SDG benefit of electrification is improved urban and indoor air
35   quality (at working places as well) and associated health benefits (SDG 3) from clean electrification
36   (SDG 7) of industrial facilities (IEA 2016). With energy being such an important cross-cutting issue to
37   sustainable development, some SDGs, such as SDG 1, 3, 4, 5 (Harmelink et al. 2018) are co-
38   beneficiaries to using electrification and fuel switching as a climate action mitigation option.
40 SDGs co-Benefits from CCU and CCS
41   CCU and CCS have been identified as playing key roles in the transition of industry to net zero.
42   Advancements in the development and deployment of both CCS and CCU foster climate action (SDG
43   13). Other co-benefits for CCS include control of non-CO2 pollutants (SDG 3), direct foreign
44   investment and know-how (SDG 9), enhanced oil recovery from existing resources, and diversified
45   employment prospects and skills (SDG 8) (Bonner 2017). For CCU, the main co-benefit related

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1    contributions are expected within the context of energy transition processes, and in societal
2    advancements that are linked to technological progress (Olfe-Kräutlein 2020). Therefore, the
3    expectations are that the deployment of CCU technologies would have least potential for meeting the
4    SDG targets relating to society/people, compared with the anticipated contributions to the pillars of
5    ecology and economy.
 6   These mitigation options carry a large number of risks as well. The high cost of the capture and storage
 7   process not only limit the technology penetration, but also makes energy and products more expensive
 8   (risk to SDG 7), potential leaks from under see or underground CO2 storages carries risks for achieving
 9   SDG 6, 14 and 15. While there are economic costs involved with the deployment of CCS and CCU
10   (Bataille et al. 2018a), there are also significant economic and developmental costs associated with
11   taking no action, because of the potential negative impact of climate change. CCS and CCU have been
12   argued as providing public good (Bergstrom and Ty 2017) and co-benefits to key SDGs (Schipper et
13   al. 2011). On the other hand, Fan et al. (2018) among others have noted the potential lock-in of existing
14   energy structures due to CCS. Refer to Table 17.1 for CCS and CCU co-benefits with respect to other
15   sector chapters.

17   11.6 Policy approaches and strategies
18   Industrial decarbonisation is technically possible on the mid-century horizon, but requires scale up of
19   technology development and deployment, multi-institutional coordination, and sectoral and national
20   industrial policies with detailed sub-sectoral and regional mitigation pathways and transparent
21   monitoring and evaluation processes (Åhman et al. 2017; Wesseling et al. 2017; Nilsson et al. 2021;
22   Rissman et al. 2020; Bataille et al. 2018a). Transitions of industrial systems entail innovations, plant
23   and technology phase-outs, changes across and within existing value-chains, new sectoral couplings,
24   and large investments in enabling electricity, hydrogen, and other infrastructures. Low carbon
25   transitions are likely to be contested, non-linear and require a multi-level perspective policy approach
26   that addresses a large spectrum of social, political, cultural and technical changes as well as
27   accompanying phase-out policies, and involve a wide range of actors, including civil society groups,
28   local authorities, labour unions, industry associations etc. (Geels et al. 2017; Rogge and Johnstone 2017;
29   Yamada and Tanaka 2019; Koasidis et al. 2020). See also cross chapter Box 12.
30   Deployment of the mitigation options presented in this chapter (see 11.3 and 11.4) needs support from
31   a mix of policy instruments including: GHG pricing coupled with border adjustments or other economic
32   signals for trade exposed industries; robust government support for research, development, and
33   deployment; energy, material and emissions standards; recycling policies; sectoral technology
34   roadmaps; market pull policies; and support for new infrastructure (See Figure 11.15) (Creutzig 2019;
35   Flanagan et al. 2011; Tvinnereim and Mehling 2018; Rogge et al. 2017; Rissman et al. 2020; Bataille
36   2020a; Bataille et al. 2018a). The combination of the above will depend on specific sectoral market
37   barriers, technology maturity, and local political and social acceptance (Rogge and Reichardt 2016;
38   Hoppmann et al. 2013). Industrial decarbonization policies need to be innovative and definitive about
39   net zero CO2 emissions to trigger the level of investment needed for the profound changes in production,
40   use and recycling of basic materials needed (Nilsson et al. 2017). Inclusive and transparent governance
41   that assesses industry decarbonization progress, monitors innovation and accountability, and provides
42   regular recommendations for policy adjustments is also important for progressing (Mathy et al. 2016;
43   Bataille 2020a).
44   The level of policy experience and institutional capacity needed varies widely across the mitigation
45   options. In many countries, energy efficiency is a well-established policy field with decades of
46   experience from voluntary and negotiated agreements, regulations, standards, energy audits, and

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1    demand side management (DSM) programs (see AR5), but there are also many countries where the
2    application of energy-efficiency policy is absent or nascent (See AR5) (García-Quevedo and Jové-
3    Llopis 2021; Tanaka 2011; Saunders et al. 2021; Fischedick et al. 2014a). The application of DSM and
4    load flexibility will also need to grow with electrification and renewable energy integration.
 5   Materials efficiency and circular economy are not well understood from a policy perspective and were
 6   for a long time neglected in low-GHG industry roadmaps although they may represent significant
 7   potential (Allwood et al. 2011; Polverini 2021; Calisto Friant et al. 2021; IEA 2019b; Gonzalez
 8   Hernandez et al. 2018b; IEA 2020a). Material efficiency is also neglected in products design,
 9   architectural and civil engineering education, infrastructure and building codes, and urban planning (see
10   Ch 5.6) (Orr et al. 2019; Braun et al. 2018). For example, the overuse of steel and concrete in
11   construction is well documented but policies or strategies (e.g., design guidelines, or regulation) for
12   improving the situation are lacking (Shanks et al. 2019; Dunant et al. 2018). Various circular economy
13   solutions are gaining interest from policy makers with examples such as regulations and economic
14   incentives for repair and reuse, initiatives to reduce planned obsolescence, and setting targets for
15   recycling. Barriers that policies need to address are often specific to the different material loops (e.g.,
16   copper contamination for steel and lack of technologies or poor economics for plastics).
17   There is also a growing interest from policymakers in electrification and fuel switching but the focus
18   has been mainly on innovation and on developing technical production-side solutions rather than on
19   creating markets for enabling demand for low carbon products, although the concept of green public
20   procurement is gaining traction. The situation is similar for CCU and CCS. Low carbon technologies
21   adoption represent an additional cost to producers, and this must be handled through fiscal incentives
22   like tax benefits, GHG pricing, green subsidies, regulation and permit procedures. For example, the
23   45Q tax credit provides some incentives to reduce investor risk for CCS and attract private investment
24   in the US (Ochu and Friedmann 2021).
25   Since industrial decarbonisation is only recently emerging as a policy field there is little international
26   collaboration on facilitation (Oberthür et al. 2021). Given that most key materials markets are global
27   and competitive, unless there is much greater global governance to contribute to the decarbonisation of
28   GHG intensive industry through intergovernmental and transnational institutions it is questionable that
29   the world will achieve industry decarbonisation by 2050.
30   As GHG pricing, through GHG taxes or cap and trade schemes, has remained a central avenue for
31   climate policy, this section begins with a review of how the industrial sector has been concerned with
32   these instruments. The rest of the section is then structured into five key topics, following insights on
33   key failures that policy must address to enable and support large-scale transformations as well as the
34   need for complementary mixes of policies to achieve this goal (Grillitsch et al. 2019; Weber and
35   Rohracher 2012; Rogge and Reichardt 2016). The section describes how the need to focus on long-term
36   transitions rather than incremental changes can be managed through the planning and strategizing of
37   transition pathways; discusses the role of research, development, and innovation policy; highlights the
38   need for enabling low-carbon demand and market creation; reflects on the necessity of establishing and
39   maintaining a level of knowledge and capacity in the policy domain about the industrial transition
40   challenge; and points to the critical importance of coherence across geographical and policy contexts.
41   The section concludes with a reflection on how different groups of actors needs to take up different
42   parts of the responsibility for mitigating climate change in the industrial sector.

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2     Figure 11.15 Schematic Figure showing the life cycle of materials (green), mitigation options (light blue)
3                                      and policy approaches (dark blue).

5    11.6.1 GHG Prices and GHG Markets
 6   Internalizing the cost of GHG emissions in consumer choices and producer investment decisions has
 7   been a major strategy promoted by economists and considered by policy makers to mitigate emissions
 8   cost-effectively and to incentivize low GHG innovations in a purportedly technology neutral way
 9   (Stiglitz et al. 2017; Boyce 2018a). In the absence of a coordinated effort, individual countries, regions
10   and cities have implemented carbon pricing schemes. As of August 23rd, 2021, 64 carbon schemes have
11   been implemented or are scheduled by law for implementation, covering 22.5% of global GHG
12   emissions (World Bank 2020), 35 of which are carbon taxes, primarily implemented on a national level
13   and 29 of which are emissions trading schemes, spread across national and subnational jurisdictions.
14   Assessments of pricing mechanisms show generally that they lead to reduced emissions, even in sectors
15   that receive free allocation such as industry (Bayer and Aklin 2020; Narassimhan et al. 2018; Martin et
16   al. 2016; Haites et al. 2018; Metcalf 2019). However, questions remain as to whether these schemes
17   can bring emissions down fast enough to reach the Paris Agreement goals (World Bank Group 2019;
18   Tvinnereim and Mehling 2018; Boyce 2018b). Most carbon prices are well below the levels needed to
19   motivate investments in high-cost options that are needed to reach net zero emissions (see Section
20 Among the 64 carbon price schemes implemented worldwide today, only nine have carbon
21   prices above 40 USD (World Bank 2020). These are all based in Europe and include EU Emissions
22   Trading System (ETS) (above 40 USD since March 2021), Switzerland ETS, and seven countries with
23   carbon taxes. Furthermore, emissions-intensive and trade-exposed (EITE) industries are typically
24   allowed exemptions and receive provisions that shelter them from any significant cost increase in

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 1   virtually all pricing schemes (Haites 2018). These provisions have been allocated due to concerns about
 2   loss of competitiveness and carbon leakage which result from relocation and increased imports from
 3   jurisdictions with no, or weak, GHG emission regulations (Branger and Quirion 2014a; Jakob 2021a;
 4   Branger and Quirion 2014b). Embodied emissions in international trade accounts for one quarter of
 5   global CO2 emissions in 2015 (Moran et al. 2018) and has increased significantly over the past few
 6   decades, representing a significant challenge to competitiveness related to climate policy. CBAM, or
 7   CBA) are trade-based mechanisms designed to ‘equalise’ the carbon costs for domestic and foreign
 8   producers. They are increasingly being considered by policy makers to address carbon leakage and
 9   create a level playing field for products produced in jurisdiction with no, or lower, carbon price
10   (Mehling et al. 2019; Markkanen et al. 2021). On 14 July 2021, the European Commission adopted a
11   proposal for a CBAM that requires importers of aluminium, cement, iron and steel, electricity and
12   fertiliser to buy certificates at the ETS price for the emissions embedded in the imported products
13   (European Commission 2021; Mörsdorf 2021). CBAMs should be crafted very carefully, to meet
14   technical and legal challenges (Rocchi et al. 2018; Sakai and Barrett 2016; Jakob et al. 2014; Cosbey et
15   al. 2019; Pyrka et al. 2020; Joltreau and Sommerfeld 2019). Technical challenges arise because
16   estimating the price adjustment requires reliable data on the GHG content of products imported as well
17   as a clear understanding of the climate policies implications from the countries of imports. Application
18   of pricing tools in industry requires standardization (benchmarking) of carbon intensity assessments at
19   products, installations, enterprises, countries, regions, and the global level. The limited number of
20   existing benchmarking systems are not yet harmonizeded and thus not able fulfill this function
21   effectively. This limits the scope of products that can potentially be covered by CBAM type policies
22   (Bashmakov et al. 2021a).
23   Legal challenges arise because CBAM can be perceived as a protectionist measure violating the
24   principle of non-discrimination under the regulations of World Trade Organization (WTO). However
25   the absence of GHG prices can also been perceived as a subsidy for fossil fuel based production (Al
26   Khourdajie and Finus 2020; Stiglitz 2006; Kuusi et al. 2020). Another argument supporting CBAM
27   implementation is the possibility to induce low GHG investment in nonregulated regions (Cosbey et al.
28   2019).
29   Thus far, California is the only jurisdiction that has implemented CBA tariffs applied on electricity
30   imports from neighbouring states and provides insights on how a CBA can work in practice by using
31   “default” GHG emissions intensity benchmarks (Fowlie et al. 2021). CBAM is an approach likely to be
32   applied first to a few selected energy-intensive industries that are at risk of carbon leakage as the EU is
33   considering. The implementation of CBA needs to balance applicability versus fairness of treatment.
34   An option recently proposed is individual adjustment mechanism to give companies exporting to the
35   EU the option to demonstrate their actual carbon intensity (Mehling and Ritz 2020). Any CBAMs will
36   have to comply with multilaterally agreed rules under the WTO Agreements to be implemented.
37   The adoption of CBAM by different countries may evolve into the formation of climate club where
38   countries would align on specific elements of climate regulation (e.g. primary iron or clinker intensity)
39   to facilitate implementation and incentivize countries to join (Nordhaus 2015; Hagen and Schneider
40   2021; Tagliapietra and Wolff 2021a,b). However, not all the countries have the same abilities to report,
41   adapt and transition to low carbon production. The implications of CBAMs on trade relationships
42   should be considered to avoid country divide and separation from a common goal of global
43   decarbonization (Eicke et al. 2021; Banerjee 2021; Bashmakov 2021; Kuusi et al. 2020; Michaelowa et
44   al. 2019).
45   The globalization of markets and the fragmentation of supply chains complicates the assignment of
46   responsibility for greenhouse gas emissions mitigations related to trade (Jakob et al. 2021). Production-
47   based carbon price schemes minimize the incentives for downstream carbon abatement due to the
48   imperfect pass through of carbon costs and therefore overlook demand-side solutions such as material

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 1   efficiency (Skelton and Allwood 2017; Baker 2018). An alternative approach is to set the carbon pricing
 2   downstream on the consumption of carbon intensive materials, whether they are imported or produced
 3   locally (Munnings et al. 2019; Neuhoff et al. 2015, 2019). However, implementation of consumption
 4   based GHG pricing is also challenged by the need of product GHG traceability and enforcement
 5   transaction costs (Munnings et al. 2019; Jakob et al. 2014). Hybrid approaches are also considered
 6   (Neuhoff et al. 2015; Jakob et al. 2021; Bataille et al. 2018a). The efficacy of GHG prices to achieve
 7   major industry decarbonization has been challenged by additional real world implementation problems,
 8   such as highly regionally fragmented GHG markets (Tvinnereim and Mehling 2018; Boyce 2018b) and
 9   the difficult social acceptance of price increases (Raymond 2019; Bailey et al. 2012). The higher GHG
10   prices likely needed to incentivize industry to adopt low GHG solutions pose social equity issues and
11   resistance (Huang et al. 2019b; Wang et al. 2019; Grainger and Kolstad 2010; Bataille et al. 2018b;
12   Hourcade et al. 2018). GHG pricing is also associated with promoting mainly incremental low-cost
13   options and not investments in radical technical change or the transformation of sociotechnical systems
14   (Rosenbloom et al. 2020; Stiglitz 2019; Vogt-Schilb et al. 2018; Grubb 2014). Transparent and strategic
15   management of cap-and-trade proceeds toward inclusive decarbonization transition that support high
16   abatement cost options can contribute toward easing these shortcomings (Raymond 2019; Carl and
17   Fedor 2016). In California, Senate Bill 535 (De León, Statutes of 2012) require that at least a quarter of
18   the proceeds go to projects that provide a benefit to disadvantaged communities (California Climate
19   Investments 2020).
20   Clear and firm emission reduction caps towards 2050 are essential for sending strong signals to
21   businesses. However, many researchers recognize that complementary policies must be developed to
22   set current production and consumption patterns toward a path consistent with achieving the Paris
23   agreement goals as cap and trade or carbon taxes are not enough (Schmalensee and Stavins 2017;
24   Kirchner et al. 2019; Vogt-Schilb and Hallegatte 2017; Bataille et al. 2018b). In this broader policy
25   context, proceeds from pricing schemes can be used to support the deployment of options with near
26   term abatement costs that are too high to be incentivised by the prevailing carbon price, but which show
27   substantial cost reduction potential with scale and learning, and to ensure a just transition (Wang and
28   Lo 2021).
30   11.6.2 Transition pathways planning and strategies
31   Decarbonising the industry sector requires transitioning how material and products are produced and
32   used today to development pathways that include the strategies outlined in Sections 11.3 and 11.4 and
33   Figure 11.15. Such broad approaches require the development of transition planning that assesses the
34   impacts of the different strategies and consider local conditions and social challenges that may result
35   from conflicts with established practices and interests, with planning and strategies directly linked to
36   these challenges.
37   Governments have traditionally used voluntary agreements or mandatory energy or emission reduction
38   targets to achieve emission reduction for specific emission intensive sectors (e.g., UK Climate Change
39   Agreements; India Performance, Achieve and Trade scheme). Sector visions, roadmaps and pathways
40   combined with a larger context of socio-economic goals, with clear objectives and policy direction are
41   needed for every industrial sectors to achieve decarbonisation and at the time of writing they are
42   emerging for some sectors. Grillitsch et al. (2019b) working from the socio-technical transitions
43   literature, focuses on the need for maintaining “directionality” for innovation (e.g. towards net zero
44   transformation), the capacity for iterative technological and policy “experimentation” and learning,
45   “demand articulation” (e.g. engagement of material efficiency and high value circularity), and “policy
46   coordination” as four main framing challenges. Wesseling et al. (2017b) bridges from the socio-
47   technical transitions literature to a world more recognisable by executives and engineers, composed of
48   structural components that include actors (e.g., firms, trade associations, government, research

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1    organisations, consumers, etc.), institutions (e.g., legal structures, norms, values and formal policies or
2    regulations), technologies (e.g. facilities, infrastructure) and system interactions.
 3   Several studies (Åhman et al. 2017; Material Economics 2019; Wyns et al. 2019; Bataille et al. 2018a)
 4   offer detailed transition plans using roughly the same five overarching strategies: 1) policies to
 5   encourage material efficiency and high quality circularity; 2) “supply push” R&D and early
 6   commercialisation as well as “demand pull” to develop niche markets and help emerging technologies
 7   cross “the valley of death”; 3) GHG pricing or regulations with competitiveness provisions to trigger
 8   innovation and systemic GHG reduction; 4) long run, low cost finance mechanisms to enable
 9   investment and reduce risk; 5) infrastructure planning and construction (e.g. CO2 transport and disposal,
10   electricity and hydrogen transmission and storage), and institutional support (e.g. labour market training
11   and transition support; electricity market reform). Wesseling et al. (2017b) and (Bataille et al. 2018a)
12   further add a step to conduct ongoing stakeholder engagements, including stakeholders with effective
13   “veto” power (i.e. firms, unions, government, communities, indigenous groups), to share and gather
14   information, educate, debate, and build consensus for a robust, politically resilient policy package. This
15   engagement of stakeholders can also bring on new supply chain collaborations and bridge the cost pass-
16   through challenge (e.g., the Swedish HYBRIT steel project, or the ELYSIS consortium, with plans to
17   bring fully commercialized inert electrodes for bauxite electrolysis to market by 2024).
18   Detailed sectoral roadmaps that assess the technical, economic, social and political opportunities and
19   provide a clear path to low-GHG development are needed to guide policy designs. For example, the
20   German state of North Rhine Westphalia passed a Climate Process Law that resulted in the adoption of
21   a Climate Protection Plan that set subsector targets through a transparent stakeholder engagement
22   process based on scenario development and identification of low GHG options (Lechtenböhmer et al.
23   2015), see Box 11.3. Another example is the UK set of Industrial Decarbonisation and Energy
24   Efficiency Roadmaps to 2050 as well as the UK Strategic Growth Plan, which are accompanied by
25   Action Plans for each energy intensive subsector.
27   START BOX 11.3 HERE
29        Box 11.3 IN4Climate NRW – Initiative for a climate-friendly industry in North Rhine-
30                                      Westphalia (NRW)

31   IN4Climate NRW ( was launched in September 2019 by the state government of
32   North Rhine-Westphalia (IN4climate.NRW 2019) as a platform for collaboration between
33   representatives from industry, science and politics. IN4climate.NRW offers a common space to develop
34   innovative strategies for a carbon-neutral industrial sector, bringing together different perspectives and
35   competencies.
36   North Rhine-Westphalia is Germany’s industrial heartland. Around 19% of North Rhine-Westphalia’s
37   GHGs have their origin in the industry sector. Consequently, the sector bears a particular responsibility
38   when it comes to climate protection, but the state is also a source of high-quality jobs and export value.
39   The NRW government understands that the state’s current competitive advantage can only be
40   maintained if the regional industry positions itself as a frontrunner for becoming GHG-neutral.
41   In working together across different branches (more than 30 companies representing mainly steel,
42   cement, chemical, aluminium industry, refineries and energy utilities) and enabling a direct interaction
43   between industry and government officials, IN4Climate provides a benefit to the participating
44   companies. People from the different areas are working together in so-called innovation teams and
45   underlying working groups with a self-organized process of setting their milestones and working

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1    schedule while reflecting long-term needs as well as short-term requirements based on political or
2    societal discussions.
3    The innovation teams aim to identify and set concrete impulses for development and implementation
4    of breakthrough technologies, specify necessary infrastructures (e.g., for hydrogen production, storage
5    and transport) and appropriate policy settings (i.e., integrated state, national, European policy mix).
6    They also include an attempt to create a discourse between the public and the industry sectors as a kind
7    of sounding board for the early detection of barriers and obstacles.
 8   The initiative has been successful so far, for example having developed a clear vision for a hydrogen
 9   strategy and an associated policy framework as well as a broader decarbonisation strategy for the whole
10   sector. It is present at the national level as well as at the European level. Being successful and unique
11   IN4Climate is useful as a blueprint for other regions and is often visited by companies and
12   administration staff from other German states.
13   It is particularly the so far missing intensive and dedicated cooperation across industrial sub-sectors that
14   can be seen as success factor. Facing substantial transformation needs associated with structural changes
15   and infrastructure challenges, very often solutions can’t be provided and realised by single sector but
16   need cooperation and coordination. Even more, chicken and egg problems like the construction of new
17   infrastructures (e.g., for hydrogen and CO2 disposal) require cooperation and new modes of
18   collaboration. IN4Climate provides the necessary link for this.
20   END BOX 11.3 HERE
22   11.6.3 Technological research, development, and innovation
23   Policies for research, development, and innovation (RDI) for industry are present in most countries but
24   it is only recently, and mainly in developed countries, that decarbonisation of emissions intensive
25   industries has been prioritised (Nilsson et al. 2021; Åhman et al. 2017). Emission intensive industries
26   are characterised by large dominant actors and mature process technologies with high fixed cost, long
27   payback times and low profit margins on the primary production side of the value chain. Investments
28   in RDI are commonly low and aimed at incremental improvements to processes and products
29   (Wesseling et al. 2017).
31 Applied research
32   Investing in RDI for low-GHG process emissions is risky and uncompetitive in the absence of
33   convincing climate policy. Research investment should be guided by assessing options, technology
34   readiness levels, and roadmaps towards technology demonstration and commercialization. The
35   potential GHG and environmental implications need to be assessed early on to assess the sustainability
36   implications and to direct research needs (Zimmerman et al. 2020; Yao and Masanet 2018). Strategic
37   areas for RDI can be focussed on a set of possible process options for producing basic materials using
38   fossil-free energy and feedstock, or CCU and CCS (11.3.5 and 11.3.6). Policies to enhance RDI include
39   public funding for applied research, technological and business model experimentation, pilot and
40   demonstration projects, as well as support for education and training – which further have the positive
41   side-effect of leading to spill-overs and network effects through labour market mobility and
42   collaboration (Nemet et al. 2018). Innovative business models will not emerge if the transition is not
43   considered along the full value chain with a focus on materials efficiency, circularity, and new roles for
44   industry in a transitioning energy system, including possibly providing demand response for electricity

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1    through designed-in flexibility, for example, by combining electrolysis hydrogen production with
2    substantial storage (Vogl et al. 2018).
3    Fostering collaborative innovation across sectors through the support of knowledge sharing and
4    capabilities building is important as mitigation options involve new or stronger sectoral couplings
5    (Tönjes et al. 2020). One example is linking chemicals to forestry in the upscaling of forest bio-
6    refineries, although it has proven to be difficult to engage a diverse group of actors in such
7    collaborations (Karltorp and Sandén 2012; Bauer et al. 2018). Heterogeneous collaboration and
8    knowledge exchange can be encouraged through conscious design of RDI programs and by supporting
9    network initiatives involving diverse actor groups (Van Rijnsoever et al. 2015; Söderholm et al. 2019).
11 Policy support from demonstration to market
12   Applied research is relatively inexpensive compared to piloting, demonstrations, and early
13   commercialisation, and arguably a lot of it has already been done for the key technologies that need to
14   climb the technology readiness ladder (see Table 11.3). This includes electricity and hydrogen-based
15   processes, electro-thermal technologies, high temperature heat pumps, catalysis, lightweight building
16   construction, low embodied carbon construction materials, etc. Demonstration to market strategies can
17   be particularly successful when the complete supply chain is considered. A prominent example of such
18   an integrated supply chain approach is the UK Offshore Wind Accelerator Project. Coordinated by the
19   UK Carbon Trust and working with wind turbine manufacturers, the project looked across the potential
20   supply chain for floating offshore wind and identified what components manufacturers could innovate
21   and produce by themselves, and where there were gaps beyond the capability of any one firm. This
22   process led to several key areas of work where the government and firms could work together; once the
23   concepts were piloted and proven, the firms went back into a competitive mode. The project illustrates
24   the potential importance of third parties, including government, in creating platforms and opportunities
25   for cross-industry exchange and collaboration (Tönjes et al. 2020).
26   Pilot and demonstration projects funded through public - private partnerships contributes to risk
27   mitigation for industries and helps inform on the feasibility, performance, costs and environmental
28   impacts of decarbonization technologies. Most countries already maintain government research and
29   deployment programs. For example, the Horizon Europe has a total budget of 95.5 billion EUR (117
30   billion USD) for 2021-2027, of which 30% will be directed to green technology research. The EU has
31   conducted several demonstration projects for emission intensive industries, such as the Ultra-Low
32   Carbon Steel (ULCOS) project (Abdul Quader et al. 2016), which lead to several small scale pilot that
33   are now going to larger scale firm pilots (e.g., HISARNA, HYBRIT and SIDERWIN). Supported by
34   the EU, several cement firms are working together on the cement LEILAC project, where a new form
35   of limestone calciner is being developed to concentrate the process CO2 emerging from quicklime
36   production (about 60% of cement emissions) for eventual utilisation or geological storage (as one of
37   many options for cement, see for example, Plaza et al. (2020)). If LEILAC works, it is conceivable that
38   existing cement plants globally that are located near CCS opportunities could have their emissions
39   reduced by 60% with one major retrofit of the kiln.
40   Once a technology has been demonstrated with scale up potential, the next stage is commercialization.
41   This is a very expensive stage, where costs are not yet compensated by revenue (see, e.g., Åhman et al.
42   (2018) and Nemet et al. (2018)). The H-DRI, SIDERWIN and LEILAC examples are all at the stage of
43   scaling up. Given the resource requirement, a diversified portfolio of investors and support is required
44   to share the risk. LEILAC includes several firms, as did the UK Offshore Wind Accelerator.
45   Government funds are also required and could be refunded in the future through an equity position,
46   royalty or tax. Fast growing economies, which are adding new industrial capacity, can provide
47   opportunities to pilot, demonstrate and scale-up new technologies, as shown by the rapid expansion of

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1    electric vehicle and solar panel production in China, which contributed to driving down costs (Nemet
2    2019; Jackson et al. 2021; Hsieh et al. 2020).
3    Finally, large capital flows towards deployment of low GHG solutions will not materialise without a
4    growing demand for low carbon materials and products that allows business opportunities. Policy will
5    thus be needed to support the first niche markets which are essential for refining new decarbonized
6    technologies, trouble shooting, and for building manufacturing economies of scale. Market creation
7    does however go beyond the nurturing, shielding, and empowerment of early niches (Smith and Raven
8    2012; Raven et al. 2016) and must also consider how to significantly re-shape existing markets to create
9    space for decarbonized solutions and crowd out fossil-based ones (Mazzucato 2016).
11   11.6.4 Market Pull
12   The perception of an increasing durable demand for low GHG products induces manufacturers to invest
13   in decarbonisation strategies (Olatunji et al. 2019). Policies can support and accelerate this process by
14   creating niche market, stimulating demand for low carbon products through procurement and financing
15   and by addressing informational and other market barriers.
17 Public Procurement
18   Governments spend a large portion of their budget on the provision of products and material through
19   infrastructure development, general equipment, and miscellaneous goods. The OECD estimates that an
20   average of 30% of general government expenditure goes to public procurements in OECD countries,
21   representing 12.6% of GDP, which makes government a powerful market actor (OECD 2021). Public
22   procurement can therefore create a significant market pull and be used to pursue strategic environmental
23   goals (Ghisetti 2017). Local, regional and national authorities can use their purchasing power to create
24   niche markets and to guarantee demand for low GHG products and material (Wesseling and Edquist
25   2018; Muslemani et al. 2021). In some cases, governments will have to adapt government procurement
26   policies that are not well suited for the procurement of products and services that focus on the
27   decarbonisation benefits and longer-term procurement commitments of emissions reducing
28   technologies and projects (Ghisetti 2017). Implementation can be challenged by the complexity of
29   criteria, the lack of credible information to check GHG intensities and the added time needed for
30   selection (Testa et al. 2012; Cheng et al. 2018; Geng and Doberstein 2008; Zhu et al. 2013; Liu et al.
31   2019b; Bratt et al. 2013; Lundberg et al. 2015). To ease these hurdles, the EU commission has developed
32   environmental criteria that can be directly inserted in tender documents (Igarashi et al. 2015; European
33   Commission 2016). These criteria are voluntary, and the extent of their application varies across public
34   authorities (Bratt et al. 2013; Testa et al. 2016; Michelsen and de Boer 2009). In the Netherlands,
35   companies achieving a desirable certification level under the national CO2 Performance Ladder obtain
36   a competitive advantage in public procurement (Rietbergen and Blok 2013; Rietbergen et al. 2015).
37   Globally, many countries have implemented green product procurement or sustainable procurement
38   following Sustainable Development Goal (SDG) 12 – Responsible consumption and production (UNEP
39   2017). Public procurement is also developing at subnational levels. For example, the state of California
40   in the United States passed the Buy Clean California Act (AB 262) that establishes maximum acceptable
41   global warming potentials for eligible steel and glass construction materials for public procurement
42   (USGBC-LA 2018). See Box 11.4.
44   START BOX 11.4 HERE

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1                                      Box 11.4 Buy Clean California Act

2    In October 2017, California passed Assembly Bill (AB) 262, the Buy Clean California Act, a new law
3    requiring state-funded building projects to consider the global warming potential (GWP) of certain
4    construction materials during procurement. The goal of AB 262 is to use California’s substantial
5    purchasing power to buy low-carbon products. Such low-carbon public procurement will directly
6    reduce emissions by using lower-carbon products, and indirectly by sending a market signal to
7    manufacturers to reduce their emissions in order to stay competitive in California.
 8   The bill requirements are two-pronged: as of January 2020, manufacturers of eligible materials must
 9   submit a facility-specific environmental product declaration (EPD), and the eligible materials must
10   demonstrate (through submitted EPDs) GWP below the product-specific compliance limits defined by
11   the state Department of General Services (DGS), which will regulate policy implementation. The
12   eligible materials include structural steel, carbon steel rebar, flat glass, and mineral wool insulation. In
13   January 2021, the DGS published maximum acceptable GWP limits for each product category set at
14   the industry average of facility specific GWP for each material. Beginning July 1, 2021, awarding
15   authorities were required to verify GWP compliance for all eligible materials (DGS 2020; USGBC-LA
16   2018).
17   Prior to adoption of the Buy Clean California Act, the California Department of Transportation
18   (Caltrans) had been evaluating the use of life-cycle assessment and EPDs in evaluating materials. In
19   addition to the materials specified in Buy Clean California Act (noted above), the Caltrans project
20   includes materials used extensively in transportation (concrete, asphalt, and aggregate). Also, the
21   California High-Speed Rail project had begun using EPDs as part of its procurement process. The High-
22   Speed Rail Sustainability Report states that the construction projects will: 1) require EPDs for
23   construction materials including steel products and concrete mix designs, and 2) require “optimized
24   life-cycle scores for major materials” and include additional strategies to reduce impacts across the life
25   cycle of the project (Simonen et al. 2019).
26   Several other states such as Washington, Minnesota, Oregon, Colorado, New York and New Jersey are
27   developing similar types of Buy Clean regulations (BGA 2020; Simonen et al. 2019).
29   END BOX 11.4 HERE
31 Private Procurement
32   The number of companies producing sustainability reports has increased rapidly over the last decade
33   (Jackson and Belkhir 2018) and so has the number of pledges to carbon neutrality announced. This
34   trend has mainly been driven by consumer concerns, investor requests, and as a business strategy to
35   gain a competitive advantage (Koberg and Longoni 2019; Higgins and Coffey 2016; Ibáñez-Forés et
36   al. 2016). For example, Apple and the governments of Québec and Canada are the financier and lead
37   market maker in the Elysis consortium to bring inert electrodes to market for bauxite smelting to make
38   zero GHG aluminium. Aluminium is a very small fraction of the cost of a laptop or smartphone, so even
39   expensive low emissions aluminium adds to Apple’s brand at very little cost per unit sold. Some
40   countries are also requiring corporate to report their emissions. For example, the French government
41   requires companies with 500 or more employees and financial institutions to report Corporate Social
42   Responsibility (CSR) and disclose publically Scope 1 (direct emissions), Scope 2 (indirect emissions
43   from purchased electricity) and Scope 3 (emissions from supply chain’s 2 impacts and consumer’s
44   usage and end-of-life recycling practices) emissions (Mason et al. 2016).

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 1   The most common climate mitigation strategies used by corporates are to set emissions reduction targets
 2   in line with the Paris Agreement goals through science-based target (SBT) and to develop internal
 3   carbon pricing (Kuo and Chang 2021). The SBT initiative records that 338 SBT companies reduced
 4   their emissions by 302 MtCO2 e between 2015 and 2019 (SBTI 2021). As of August 2021, 858
 5   companies had set SBT and over 2,000 companies across the world currently use internal carbon pricing
 6   with a median internal carbon price of 25 USD per metric ton of CO2-eq (Bartlett et al. 2021). The most
 7   determined companies have developed internal GHG abatement strategies that incorporate their supply
 8   chains’ emissions (Martí et al. 2015; Tost et al. 2020; Gillingham et al. 2017) and design procurement
 9   contracts that encourage or require their suppliers to also improve their product GHG footprint (Liu et
10   al. 2019a). For many corporations, the emissions impact within their supply chain far exceeds their
11   operations direct emissions (CDP 2019). Therefore, the opportunities to reduce emissions through
12   purchasing goods and services from the supply chain (scope 3) have much greater potentials than from
13   direct emissions.
14   However, these trends have to be approached with caution as some of the emissions reductions are not
15   direct emissions reductions from companies’ operations, instead often from offset projects of varying
16   quality (Chrobak 2021). There is a lack of consistency and comparability in the way firms are reporting
17   emissions, which limits the possibilities to assess companies’ actual ambition and progress (Blanco et
18   al. 2016; Liu et al. 2015; Burritt and Schaltegger 2014; Sullivan and Gouldson 2012; Rietbergen et al.
19   2015). More research is needed to assess the current impacts of corporate voluntary climate actions and
20   if these efforts meet the Paris agreement’s goals (Rietbergen et al. 2015; Wang and Sueyoshi 2018). It
21   will be critically important that the international corporate accounting frameworks, standards, and
22   related guidance (e.g., GHG Protocol) be maintained and improved to reflect evolving needs in the
23   global market and to allow for comparison of objectives and progress.
25 GHG content certifications
26   The development of GHG labels corresponds to a growing demand from consumers desiring
27   information about the climate impacts of their consumption (Darnall et al. 2012; Feucht and Zander
28   2018; Tan et al. 2014). GHG labels fill this information gap by empowering consumers’ purchasing
29   decisions and creating higher value for low GHG products and materials (Cohen and Vandenbergh
30   2012; Vanclay et al. 2011). The willingness to pay for lower GHG products has been found to be
31   positive but to depend on socioeconomic consumer characteristics, cultural preferences and the product
32   considered (Li et al. 2017; Shuai et al. 2014; Tait et al. 2016; de-Magistris and Gracia 2016; Feucht and
33   Zander 2018). Companies and governments that favour low GHG products and who are seeking to
34   achieve environmental, social, and governance (ESG) goals also need readily available and reliable
35   information about the GHG content of products and materials they purchase and produce (Munasinghe
36   et al. 2016; Long and Young 2016).
37   Numerous methodologies have been developed by public and private organizations to meet the needs
38   for credible and comparable environmental metrics at the product and organization levels. Most follow
39   life cycle assessment standards as described in ISO 14040 and ISO 14044, ISO 14067 for climate
40   change footprint only and ISO 14025 (2006) for environmental product declarations (EPD) but the way
41   system boundaries are applied in practice varies (Liu et al. 2016; Wu et al. 2014). Adoption has been
42   challenged by the complexity and the profusion of applications which contribute to confuse
43   stakeholders (Guenther et al. 2012; Gadema and Oglethorpe 2011; Brécard 2014). The options of
44   applying different system boundaries and allocation principles involve value judgements that in turn
45   influence the results (McManus et al. 2015; Tanaka 2008; Overland 2019; Finnveden et al. 2009). A
46   more systematic and coordinated international approach based on transparent and reliable data and
47   methodologies is needed to induce global low GHG market development (Pandey et al. 2011; Tan et al.
48   2014; Darnall et al. 2012).

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1    Within the context of GHG content certifications and EPD development, more transparency is needed
2    to increase international comparability and to validate claims to meet consumers demand for low GHG
3    material and products (Rangelov et al. 2021). Greater automation, publicly available reference
4    databases, benchmarking systems and increased stakeholder collaboration can also support the
5    important role of conveying credible emissions information between producers, traders and consumers.
7 Performance Standards and Codes
 8   Policy makers can set minimum performance standards or maximum emission content specifications
 9   through legislation to increase the use of low GHG materials and products by mandating the adoption
10   of low GHG production and construction processes while requiring material and resource efficiency
11   aspects.
12   Construction of buildings represented 11% of energy and process-related carbon dioxide (CO2)
13   emissions globally in 2018 (IEA and UNEP 2019). The share of embodied emissions in construction is
14   increasing as building energy efficiency is improving and energy supply is decarbonized (Chastas et al.
15   2016). As a result, jurisdictions are increasingly considering new requirements in building codes to
16   reduce embodied emissions. This is the case of France’s new building code which is shifting from a
17   thermal regulation (RT 2012) to an environmental regulation (RE 2020) to include embodied GHG
18   LCA metrics for encouraging use of low-GHG building materials (Schwarz et al. 2020; Ministère de la
19   Transition écologique et solidaire 2018). The 2018 International Green Construction Code (IGCC)
20   provides technical requirements that can be adopted by jurisdictions for encouraging low GHG building
21   construction, which also covers minimum longevity and durability of structural, building envelope, and
22   hardscape materials (Art. 1001.3.2.3) (Celadyn 2014). Low GHG Building Rating Systems, such as
23   LEEDs, are voluntary standards which include specific requirements on material resources in their
24   rating scale. Trade-offs between energy performance achievement and material used in building
25   construction needs to be further assessed and considered as low GHG building code requirements
26   develop. Local governments can also lead the way by adopting standards for construction. This is the
27   case of the county of Marin in California which specifies maximum embodied carbon in kgCO2-eq m-3
28   and maximum ordinary Portland cement content in lbs/yd3 for different levels of concrete compressive
29   strength (Marin County 2021).
30   Governments are also turning their attention to developing standards to increase the durability of
31   products and materials by requiring options for maintenance, reparability, reusability, upgradability,
32   recyclability and waste handling. For example, the EU Eco-design directive includes new requirements
33   for manufacturers to make available for a minimum of 7 to 10 years spare parts to repair household
34   equipment (Talens Peiró et al. 2020; Nikolaou and Tsagarakis 2021; Calisto Friant et al. 2021). The
35   European Commission plans to widen the resource efficiency requirements beyond energy-related
36   products to cover products such as textiles, furniture as well as high impact intermediary products such
37   as steel, cement and chemicals in a new sustainable product policy legislative initiative. (Polverini 2021;
38   Domenech and Bahn-Walkowiak 2019; Llorente-González and Vence 2019; European Commission
39   2020).
40   Further research is needed to understand how different international and national frameworks, codes,
41   and standards that focus on emissions can work in unison to amplify their mutually desired outcomes.
42   Building performance and market instrument trading frameworks recognized globally do not always
43   incentivize the same outcomes due to the differences in market approach. LCA metrics are a useful tool
44   to help assess optimal options for ultimate emission reduction objectives (Röck et al. 2020; Shadram et
45   al. 2020).

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1 Financial Incentives
 2   Fossil-free basic materials production will often lead to higher costs of production, for example, 20–
 3   40% more for steel, 70–115% more for cement, and potentially 15–60% for chemicals (Material
 4   Economics 2019). There is a nascent literature on what are effectively material “feed-in-tariffs” to
 5   bridge the commercialization “valley of death” (Wilson and Grubler 2011) of early development of low
 6   GHG materials (Neuhoff et al. 2018; Sartor and Bataille 2019; Wyns et al. 2019; Bataille et al. 2018a).
 7   Renewable electricity support schemes have typically been price-based (e.g., production subsidies and
 8   feed-in-tariffs) or volume-based (e.g., quota obligations and certificate schemes) and both principles
 9   can be applied when thinking about low GHG materials. Auction schemes are typically used for larger
10   scale projects, for example, offshore wind parks.
11   Based on how feed-in-tariffs worked, a contract for difference (CfD) could guarantee a minimum and
12   higher-than-market price for a given volume of early low GHG materials. CfDs could be based on a
13   minimum effective GHG price reflecting parity with the costs of current higher emitting technologies,
14   or directly on the higher base capital and operating costs for a lower GHG material (Richstein 2017;
15   Chiappinelli et al. 2019; Sartor and Bataille 2019; Vogl et al. 2021a). CfDs can also be offered through
16   low GHG material procurement where an agreed price offsets the incremental cost of buying low GHG
17   content product or material. Private firms, by themselves or collectively, can also guarantee a higher
18   than market price for low GHG materials from their supplier for marketing purposes (Bataille 2020a;
19   Bataille et al. 2018a). Reverse auctions (by which the lowest bidder gets the production subsidy) for
20   low GHG materials is also an option but it remains to be analyzed and explored. While these financial
21   incentive schemes have been implemented for renewable energy, their application to incentivize and
22   support low GHG material production have yet to be developed and implemented. The German
23   government is currently developing a draft law which will allow companies that commit to cut GHG
24   emissions by more than half using innovative technologies to bid for 10-year CfDs with a guaranteed
25   price for low-carbon steel, chemical and cement products (Agora Energiewende and Wuppertal Institut
26   2019; BMU 2021).
27   New and innovative financial market contracts for basic materials that represent low-carbon varieties
28   of conventional materials are emerging. This is the case of aluminium for which quantity of low GHG
29   production already exist in countries where hydroelectric power is a common power source. Market
30   developments will allow for low GHG aluminium to trade at a premium rate as demand develops. For
31   example, Harbor Aluminium has launched a green aluminium spot premium at the end of October 2019
32   and the London Metal Exchange has introduced a "green aluminium" spot exchange contract. (LME
33   2020; Das 2021).
35 Extended producer responsibility
36   EPR systems are increasingly used by policy maker to require producers to take responsibility for the
37   end life of their outputs and to cover the cost of recycling of materials or otherwise responsibly
38   managing problematic wastes (Kaza et al. 2018). According to the OECD, there are about 400 EPR
39   systems in operation worldwide, three-quarters of which have been established over the last two
40   decades. One-third of EPR systems cover small consumer electronic equipment, followed by packaging
41   and tyres (each 17%), vehicles, lead-acid batteries and a range of other products (OECD 2016).
42   While the economic value of some discarded materials such as steel, paper and aluminium is generally
43   high enough to justify the cost and efforts of recycling, at current rates of 85% above 60% and 43%
44   respectively (Cullen and Allwood 2013; Graedel et al. 2011), others like plastic or concrete have a much
45   lower re-circularity value (Graedel et al. 2011). Most plastic waste ends up in landfills or dumped in
46   the environment, with 9% recycled and 12% incinerated globally (UNEP 2018; Geyer et al. 2017)).
47   Collected waste plastics from OECD countries were largely exported to China until a ban in 2018

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1    required OECD countries to review their practices (Qu et al. 2019). EPR schemes may thus need to be
2    strengthened to actually achieve a reduced use of virgin, GHG intensive materials. The potential for re-
3    circularity of unreacted cement and aggregates in concrete is increasing as new standards and
4    requirement develops. For example, concrete fines are now standardized as a new cement constituent
5    in the European standardization CEN/TC 51 "cements and construction limes".
7    START BOX 11.5 HERE
9                                       Box 11.5 Circular economy policy

10   The implementation of a circular economy relies on the operationalization of the R-imperatives or
11   strategies which extend from the original 3Rs: Reduce, Reuse and Recycle, with the addition of Refuse,
12   Reduce, Re-sell/Re-use, Repair, Re-furbish, Re-manufacture, Re-purpose, Re-cycle, Recover (energy),
13   Re-mine and more (Reike et al. 2018). The R implementation strategies are diverse across countries
14   (Kalmykova et al. 2018; Ghisellini et al. 2016) but, in practice, the lower forms of retention of materials,
15   such as recycling and recover (energy), often dominate. The lack of policies for higher retention of
16   material use such as Reduce, Reuse, repair, remanufacture is due to institutional failures, lack of
17   coordination and lack of strong advocates (Gonzalez Hernandez et al. 2018a).
18   Policies addressing market barriers to circular business development need to demonstrate that circular
19   products meet quality performance standards, ensure that the full environmental costs are reflected in
20   market prices and foster market opportunities for circular products exchange, notably through industrial
21   symbiosis clusters and trading platforms (Hartley et al. 2020; Hertwich 2020; Kirchherr et al. 2018;
22   OECD 2019a). Policy levels span from micro (such as consumer or company) to meso (eco-industrial
23   parks) and macro (provinces, regions and cities) (Geng et al. 2019). The creation of eco-industry parks
24   (“industrial clusters”) has been encouraged by governments to facilitate waste exchanges between
25   facilities, where by-products from one industry is used as a feedstock to another (Tian et al. 2014;
26   Winans et al. 2017; Jiao and Boons 2014; Shi and Yu 2014; Ding and Hua 2012). Systematic assessment
27   of wastes and resources is carried out to assess possible exchange between different supply chains and
28   identify synergies of waste streams that include metal scraps, waste plastics, water heat, bagasse, paper,
29   wood scraps, ash, sludge and others (Ding and Hua 2012; Shi and Yu 2014).
30   The development of data collection and indicators is nascent and need to ramp up to quantify the impacts
31   and provide evidence to improve circular economy and materials efficiency policies. Policy makers
32   needs to leverage the potential socio-economic opportunities of transitioning to circular economies
33   (Llorente-González and Vence 2020) which shows positive GDP growth and job creation by shifting to
34   more labor-intensive recycling plants and repair services than resource extraction activities (Cambridge
35   Econometrics et al. 2018; WRAP and Alliance Green 2015). The International Labor Organization
36   estimates that worldwide employment would grow by 0.1 per cent by 2030 under a circular economy
37   scenario (ILO 2018). However questions remain if the type of jobs created are concentrated in low-
38   wage labor-intensive circular activities which may need targeted policy instruments to improve working
39   conditions (Llorente-González and Vence 2020).
41   END BOX 11.5 HERE

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1    11.6.5 Knowledge and capacity
 2   It is important that government bodies, academia and other actors strengthen their knowledge and
 3   capacities for the broad transformational changes envisioned for industry. In Japan, the industry has
 4   been voluntarily working on GHG reduction, under the Framework of Keidanren's Commitment to a
 5   Low-carbon Society since 2009. Government and scientific experts regularly review their commitments
 6   and discuss results, monitoring methods, and reconsidering goals. Industry federations/associations can
 7   obtain advice in the follow-up meetings from other industries and academics. The energy and transport
 8   sectors have decades of building institutions and expertise, whereas industrial decarbonisation is largely
 9   a new policy domain. Most countries have experience in energy efficiency policies, some areas of
10   research and innovation, waste management, regulations for operational permits and pollution control,
11   worker safety and perhaps fuel switching. There is less experience with market demand pull policies
12   although low GHG public procurement is increasingly being tested. Circular economy policies are
13   evolving but potential policies for managing material demand growth are less understood. Material
14   efficiency policies through, for example, product standards or regulation against planned obsolescence
15   are nascent but relatively unexplored (Gonzalez Hernandez et al. 2018a).
16   All this argues for active co-oversight, management and assessment by government, firms, sector
17   associations and other actors, in effect the formation of an active industrial policy that includes
18   decarbonisation in its broader mandate of economic and social development (OECD 2019b; Bataille
19   2020a). This could draw from the quadruple helix innovation model, which considers the role of
20   government, universities, the private sector, the natural environment and social systems to foster
21   collaboration in innovation (Durán-Romero et al. 2020; Carayannis and Campbell 2019). Important
22   aspects of governance include mechanisms for monitoring, transparency, and accountability. It may
23   involve the development of new evaluation approaches, including a greater focus on ex-ante evaluations
24   and assessment of, for example, readiness and capacities, rather than ex-post evaluations of outcomes.
25   Such organisational routines for learning have been identified as a key aspect of policy capacity to
26   govern evolutionary processes (Karo and Kattel 2018; Kattel and Mazzucato 2018). Although many
27   governments have adopted ideas of focusing resources on the mission or challenge of climate change
28   mitigation, comparisons between Western and East-Asian contexts show significant differences in the
29   implementation of governance structures (Wanzenböck et al. 2020; Mazzucato et al. 2020; Karo 2018).
30   Overall, improved knowledge and stronger expertise is important also to handle information
31   asymmetries and the risk of regulatory capture.
33   11.6.6 Policy coherence and integration
34   Industrial net zero transitions, while technically feasible, involves not just a shift in production
35   technology but major shifts in demand, material efficiency, circularity, supply chain structure and
36   geographic location, labour training and adaptation, finance, and industrial policy. This transition must
37   also link decarbonisation to larger environmental and social goals (e.g. air and water quality, low GHG
38   growth, poverty alleviation, sustainable development goals) (OECD 2019b).
39   Although there is little evidence of carbon leakage so far it will be ever more important to strive for
40   coherence in climate and trade policies as some countries take the lead in decarbonising internationally
41   traded basic materials (Jakob 2021b). At the time of writing the previously academic debate on this
42   issue is shifting to real policy making through debates and negotiations around carbon border
43   adjustment (see 11.6.1) and sectoral agreements or climate clubs (Nordhaus 2015; Nilsson et al. 2021;
44   Åhman et al. 2017; Jakob 2021a). The climate and trade policy integration should also consider what is
45   sometimes called positive leakage, i.e., that heavy industry production moves to where it is easier to
46   reach zero emissions. As a result, policy should go beyond border measures to include, for example,
47   international technology cooperation and transfer and development of shared lead markets.

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1    Energy intensive production steps may move where clean resources are most abundant and relatively
2    inexpensive (Bataille et al. 2021a; Gielen et al. 2020). For example, steel making has historically located
3    itself near iron ore and coal resources whereas in the future it may be located near iron ore and zero
4    GHG electricity or close to carbon storage sites (Fischedick et al. 2014b; Vogl et al. 2018; Bataille
5    2020a). This indicates large changes in industrial and supply chain structure, with directly associated
6    needs for employment and skills. Some sectors will grow, and some will shrink, with differing skill
7    needs. Each new workforce cohort needs the general specific skill to provide the employment that is
8    needed at each stage in the transition, implicating a need for co-ordination with policies for education
9    and retraining.
10   Depending on what mixes of deep decarbonisation strategies are followed in a given region (e.g.
11   material efficiency, electrification, hydrogen, biomass, CCU, CCS), infrastructure will need to be
12   planned, financed and constructed The UKCCC Net-zero Technical Report describes the infrastructure
13   needs for achieving net zero GHG in the UK by 2050 for every sector of the economy (UKCCC 2019b).
14   Transportation would be facilitated with pipelines or ships to allow transfer of captured CO2 for
15   utilisation and disposal, and associated institutional frameworks (IEAGHG 2021). Electrification will
16   require market design and transmission to support increased generation, transmission, and flexible
17   demand. Hydrogen, CCU, and CCS will require significant new or adapted infrastructure. Hydrogen
18   and CO2 pipelines, and expanded electricity transmission, have natural monopoly characteristics which
19   are normally governed and planned by national and regional grid operators and their regulators.
20   Industrial clustering (a.k.a. eco-parks), such as those planned in Rotterdam and Teeside, UK, would
21   allow more physical and cost-effective sharing of electricity, CCU, CCS, and hydrogen infrastructure
22   but is dependent on physical planning, permitting, and infrastructure policies.
23   Costing analysis (see Chapter 15) indicates an increased upfront need for financial capital which require
24   policies to encourage long term, patient capital that reflects society’s preferences for investment in
25   industrial decarbonisation and the minimum 10 or more years horizon before there are significant new
26   commercially available processes.
27   All the above indicate the need for general industrial policy as part of a coherent general economic,
28   taxation, investment, employment and social policy for climate change mitigation (Wyns et al. 2019;
29   Wesseling et al. 2017; Bataille et al. 2018a; Nilsson et al. 2021).
31   11.6.7 Roles and responsibilities
32   While all climate policy requires topic specific adaptive governance for long term effectiveness (Mathy
33   et al. 2016), deep decarbonisation of heavy industry has special governance challenges, different from
34   those for the electricity, transport or buildings sectors (Åhman et al. 2017; Wesseling et al. 2017;
35   Bataille et al. 2018a). Competition is strong, investments are rare, capital intensive and very “lumpy”.
36   In an atmosphere where transformative innovation is required the process is very capital focussed with
37   non-diversifiable risks unless several companies are involved. There are significant infrastructure needs
38   for electricity, hydrogen, and CCS and CCU. Given there is no “natural” market for low emissions
39   materials, there is a need to manage both the supply and demand sides of the market, especially in early
40   phase through lead supplier and markets. Finally, there is a very high probability of surprises and
41   substantial learning, which could affect policy choice, direction, and stringency.
42   Different types of actors thus have to play different, but coordinated roles and responsibilities in
43   developing, supporting, and implementing policies for an industrial transition. Table 11.6 below shows
44   how the different core parts of integrated policy making for an industrial transition may depend on
45   efforts from different actors groups and highlights the responsibility of these actor groups in developing
46   a progressive and enabling policy context for the transition. This includes policy makers at local,

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1   national, and international arenas as well as civil society organisations, industry firms, and interest
2   organisations.

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   1     Table 11.6 Examples of the potential roles of different actors in key policy and governance areas for a low GHG transition to indicate the importance of
   2                                   agency and wide stakeholder engagement in the governance of industrial decarbonisation

Actors                  Direction:                          Innovation:                      Market creation:           Knowledge and capacity:               Coherence:
                        Planning    and      strategising   RD&D for new technologies        Create and shape           Build institutional capacity across   Establish international and
                        pathways to net zero                and other solutions              demand-pull       for      various actors                        national policy coherence
                                                                                             various solutions
International bodies    More attention to industry in       Include    heavy      industry   International              Support knowledge building and        Align other Conventions and
and      multilateral   NDCs. Monitor progress and          decarbonisation in technology    standards,                 sharing       on      industrial      arenas (e.g., WTO) with
collaboration           identify      gaps.     Develop     cooperation (e.g., Mission       benchmarking               decarbonisation.                      climate targets and include
                        international roadmaps.             Innovation).                     systems, and GHG                                                 heavy industry transitions in
                                                                                             labels. Allow for                                                negotiations.
                                                                                             creation and protection
                                                                                             of lead markets.
Regional         and    Require net zero strategies in      Experimentation            for   Public     procurement     Develop policy expertise for          Support vertical policy
national                permitting. Set targets and         recycling,           materials   for innovation and lead    industrial transformation. Support    coherence (i.e., international,
government,      and    facilitate roadmaps at various      efficiency,     and   demand     markets.         Green     and facilitate materials efficient    national, city level).
cities                  levels. Sunset clauses and phase-   management.         Hydrogen,    infrastructure             and circular solutions through
                        out agreements for polluting        electrification, and other       investments.               design standards, building codes,
                        plants.                             infrastructure.                                             recycling, and waste policy.
Civil society           Monitor and evaluate leaders and    Engage      in   responsible     Progressive labelling,     Engage in policy processes and        Monitor and support policy
                        laggards. Support transparency.     innovation        programs,      standards and criteria     build capacity on industrial          coherence and coordination
                                                            experimentation, and social      for low emissions          decarbonisation.          Support     across policy domains (trade,
                                                            innovation.                      materials and products     consumer      information    and      climate, waste, etc.).
                                                                                             (e.g.,    LCA-based),      knowledge.
                                                                                             including updating.
Industrial   sectors    Adopt net zero emissions targets,   Share        best  practice.     Work across (new)          Education and retraining for          Coordination across policy
and associations        roadmaps, and policy strategies     Coordination            and      value     chains      to   designers, engineers, architects,     domains (trade, climate,
                        for reaching them. Assess whole     collaboration.     Efficient     establish lead markets     etc. Information sharing and          waste, etc.). Explore sectoral
                        value chains, scope 3 emissions     markets for new technology       for low emissions          transparency to reduce information    couplings, new value chains
                        and new business models.            (e.g., licensing).               materials as well as for   asymmetry.                            and location of heavy
                                                                                             materials efficiency                                             industry.
                                                                                             and circularity.

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Corporations   and   Set zero emissions targets and      Lead and participate in R&D,    Marketing           and   Engage in value chains for          MNCs avoid race to the
companies            develop corporate and plant level   pilots, and demonstrations.     procurement of low        increased recycling and materials   bottom, and strategically
                     roadmaps for reaching targets.      Increase and direct R&D         emissions     materials   efficiency. Build knowledge and     account for high carbon price
                                                         efforts at reaching net zero.   and products. Include     capacity for reorientation and      as part of transition strategy.
                                                                                         scope 3 emissions to      transformation.
                                                                                         assess impact and
                                                                                         mitigation strategies.

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1    11.7 Knowledge gaps
2    An increasing body of research proposes deep decarbonisation pathways for energy intensive industries
3    including mitigation options such as materials efficiency, circular economy and new primary processes.
4    These options are underrepresented in climate change scenario modelling and integrated assessment
5    models, some of which do not even reflect evolution of demand for basic materials, which is a key
6    driver behind energy consumption and GHGs emissions in the industrial sector. As a result, no
7    agreement is reached so far between bottom-up and top-down studies on the effectiveness and costs for
8    many promising mitigation options, their respective roles, sequencing and packaging within various
9    mitigation pathways.
10   A significant shift is needed from the transition process of the past mainly based on marginal and
11   incremental changes, with a strong focus on energy efficiency efforts, to one grounded in
12   transformational change where there is limited knowledge of how to implement such change effectively.
13   There is a knowledge gap on comparable, comprehensive, and detailed quantitative information on costs
14   and potentials associated with the mitigation options for deep decarbonisation in industry, as cost
15   estimates are not often comparable due to the regional or country focus, differences in costs metrics,
16   currencies, discount rates, and energy prices across studies and regions.
17   A very large and important uncertainty is the availability of biomass for deep decarbonisation pathways
18   due to competition for biomass feedstock with other priorities and the extent to which electrification
19   can reduce the demand for bioenergy in the industry, transport and energy sectors.
20   CCS and CCU are important mitigation options in industry, for which the potentials and costs vary
21   considerably depending on the diversity of industrial processes, the volume and purity of carbon dioxide
22   flows, the energy requirements, the lifetime of utilisation products and the production route.
23   The effectiveness of mitigation policies in industry is poorly known as so far the sector has largely been
24   sheltered from the impacts of climate policy due to the concerns of competitiveness and carbon leakage.
25   There is a lack of integration of material efficiency and circularity with energy and climate policies
26   which partly results from the inadequacy of monitored indicators to inform policy debates and set
27   targets, a lack of high-level political focus, a history of strong industrial lobbying, uncoordinated policy
28   across subsectors and institutions, and the sequential nature of decision-making along supply chains.
29   Industry as a whole is a very complex web of sectors, sub-sectors and inter-sectoral interactions and
30   dependence, with diverse associated mitigation opportunities and co-benefits and costs. Additional
31   knowledge is needed to understand sectoral interactions in the transformation processes.
32   Industrial climate mitigation policy is supplemental to many other policy instruments developed to
33   reach multiple industrial goals, for the range of stakeholders with their interest and priorities reflecting
34   the assessment of co-benefits and risk and affecting decision-making processes and behaviour of
35   stakeholders. Better knowledge is needed to identify the co-benefits for the adoption of climate change
36   mitigation strategies.

38   Frequently Asked Questions
39   FAQ 11.1         What are the key options to reduce industrial emissions?
40   Industry has a diverse set of GHG emission sources across sub-sectors. To decarbonise industry requires
41   that we pursue several options simultaneously. These include energy efficiency, materials demand
42   management, improving materials efficiency, more circular material flows, electrification, as well as
43   CCU and CCS. Improved materials efficiency and recycling reduces the need for primary resource

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1    extraction and the energy intensive primary processing steps. Future recycling may include chemical
2    recycling of plastics if quality requirements make mechanical recycling difficult. One approach, albeit
3    energy intensive, is to break down waste plastics to produce new monomer building blocks, potentially
4    based on biogenic carbon and hydrogen instead of fossil feedstock. Hydrogen can also be used as a
5    reduction agent instead of coke and coal in ironmaking. Process emissions from cement production can
6    be captured and stored or used as feedstock for chemicals and materials. Electricity and hydrogen needs
7    can be very large but the potential for renewable electricity, possibly in combination with other low
8    carbon options, is not a limiting factor.
10   FAQ 11.2      How costly is industrial decarbonisation and will there be synergies or conflicts
11      with sustainable development?
12   In most cases and in early stages of deployment, decarbonisation through electrification or CCS will
13   make the primary production of basic materials such as cement, steel, or polyethylene more expensive.
14   However, demand management, energy and materials efficiency, and more circular material flows can
15   dampen the effect of such cost increases. In addition, the cost of energy intensive materials is typically
16   a very small part of the total price of products, such as an appliance, a bottle of soda or a building, so
17   the effect on consumers is very small. Getting actors to pay more for zero emission materials is a
18   challenge in supply chains with a strong focus on competitiveness and cutting costs, but it is not a
19   significant problem for the broader economy. Reduced demand for services such as square meters of
20   living space or kilometres of car travel is an option where material living standards are already high. If
21   material living standards are very low, increased material use is often needed for more sustainable
22   development. The options of materials and energy efficiency, and more circular material flows,
23   generally have synergies with sustainable development. Increased use of electricity, hydrogen, CCU
24   and CCS may have both positive and negative implications for sustainable development and thus require
25   careful assessment and implementation for different contexts.
27   FAQ 11.3        What needs to happen for a low carbon industry transition?
28   Broad and sequential policy strategies for industrial development and decarbonisation that pursue
29   several mitigation options at the same time are more likely to result in resource-efficient and cost-
30   effective emission reductions. Industrial decarbonisation is a relatively new field and thus building
31   capacity for industrial transition governance is motivated. For example, policy to support materials
32   efficiency or fundamental technology shifts in primary processes is less developed than energy
33   efficiency policy and carbon pricing. Based on shared visions or pathways for a zero-emission industry,
34   industrial policy needs to support development of new technologies and solutions as well as market
35   creation for low and zero emission materials and products. This implies coordination across several
36   policy domains including research and innovation, waste and recycling, product standards,
37   digitalisation, taxes, regional development, infrastructure, public procurement, permit procedures and
38   more to make the transition to a carbon neutral industry. International competition means that trade
39   rules must be evolved to not conflict with industrial decarbonisation. Some local and regional
40   economies may be disadvantaged from the transition which can motivate re-education and other
41   support.

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