Editing IPCC:AR6/WGIII/Chapter-11 (section)

== 11.3 Technological Developments and Options ==

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The following overview of technical developments and mitigation options which relate to the industrial sector is organised in six equally important strategies: (i) demand for materials, (ii) materials efficiency, (iii) circular economy and industrial waste, (iv) energy efficiency, (v) electrification and fuel switching, and (vi) CCUS, feedstock and biogenic carbon. Each strategy is described in detail, followed by a discussion of possible overlaps and interactions between strategies and how conflicts and synergies can be addressed through integration of the approaches.

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=== 11.3.1 Demand for Materials ===

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Demand for materials is a key driver of energy consumption and CO 2 emissions in the industrial sector. Rapid growth in material demand over the last quarter century has seen demand for key energy-intensive materials increase 2.5- to 3.5-fold (Figure 11.6), with growth linked to, and often exceeding, population growth and economic development. The International Energy Agency (IEA) explains, ‘as economies develop, urbanise, consume more goods and build up their infrastructure, material demand per capita tends to increase considerably. Once industrialised, an economy’s material demand may level off and perhaps even begin to decline’ ( [[#IEA--2019b|IEA 2019b]] ).

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[[File:c4f683a0e2b8799cba0f35073f914ea7 IPCC_AR6_WGIII_Figure_11_6.png]]

'''Figure 11.6 | Growth in global demand for selected key materials and global population,''' '''1990–2019''' '''.''' Notes: based on global values, shown indexed to 1990 levels (=100). Steel refers to crude steel production. Aluminium refers to primary aluminium production. Plastic refers to the production of a subset of key thermoplastic resins. Cement and concrete follow similar demand patterns. Sources: 1990–2018: [[#IEA--2020b|IEA (2020b)]] . 2019–2020: [[#GCCA--2021a|GCCA (2021a)]] ; [[#International%20Aluminium%20Institute--2021a|International Aluminium Institute (2021a)]] ; [[#Statista--2021b|Statista (2021b)]] ; U.S. Geological Survey (2021); [[#World%20Bank--2021|World Bank (2021)]] ; [[#World%20Steel%20Association--2021|World Steel Association (2021)]] .

The Kaya-like identity presented earlier in the chapter (Equation 11.1) suggests that material demand can be decoupled from population and economic development by two means: (i) reducing the accumulated material stock ( ''MStock'' ) used to deliver material services; and (ii) reducing the material ( ''MPR'' + ''MSE'' ) required to maintain material stocks ( ''MStock'' ). Such material demand reduction strategies are linked upstream to material efficiency strategies (the delivery of goods and services with less material demand, and thus energy and emissions) and to demand reduction behaviours, through concepts such as sufficiency, sustainable consumption and social practice theory ( [[#Spangenberg--2019|Spangenberg and Lorek 2019]] ). Materials demand can also be influenced through urban planning, building codes and related socio-cultural norms that shape the overall demand for square metres per capita of floor space, mobility and transport infrastructures (Chapter 5).

Modelling suggests that per capita material stocks saturate (level off) in developed countries and decouple from GDP. [[#Pauliuk--2013b|Pauliuk et al. (2013b)]] demonstrated this saturation effect in an analysis of in-use steel stocks in 200 countries, showing that per capita steel in stocks in countries with a long industrial history (e.g., USA, UK, Germany) had saturation levels between 11 and 16 tonnes. More recently, [[#Bleischwitz--2018|Bleischwitz et al. (2018)]] confirmed the occurrence of a saturation effect for four materials (steel, cement, aluminium and copper) in four industrialised countries (Germany, Japan, UK and USA) together with China. These findings have led to the revision of some material demand forecasts, which previously had been based solely on population and economic trends.

The saturation effect for material stocks is critical for managing material demand in '''developed countries''' . Materials are required to meet demand for the creation of new stocks and the maintenance of existing stocks ( [[#Gutowski--2017|Gutowski et al. 2017]] ). Once saturation is attained the need for new stocks is minimised, and materials are only required for replacing old stocks and maintenance. Saturation allows material efficiency strategies (such as light-weight design, longer lifetimes, and more intense use) to reduce the required per capita level of material stocks, and material circularity strategies (closing material loops through remanufacture, reuse and recycling) to lessen the energy and carbon impacts required to maintain the material stock. However, it should be noted that some materials still show little evidence of saturation (i.e., plastics, see Box 11.2). Furthermore, meeting climate change targets in developed countries will require the construction of new low-carbon infrastructures (i.e., renewable energy generation, new energy distribution and storage systems, electric vehicles and building heating systems) which may increase demand for emissions intensive materials (i.e., steel, concrete and glass).

For '''developing countries''' , who are still far from saturation levels, strong growth for new products and the creation of new infrastructure capacity may still drive global material demand. However, there is an expectation that economic development can be achieved at lower per capita material stock levels, based on the careful deployment of material efficiency and circularity by design ( [[#Grubler--2018|Grubler et al. 2018]] ).

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=== 11.3.2 Material Efficiency ===

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Material efficiency ( ''ME'' ) – the delivery of goods and services with less material – is increasingly seen as an important strategy for reducing GHG emissions in industry ( [[#IEA--2017|IEA 2017]] , 2019b). Options to improve ''ME'' exist at every stage in the lifecycle of materials and products, as shown in Figure 11.7. This includes: designing products which are lighter, optimising to maintain the end-use service while minimising material use, designing for circular principles (i.e., longer life, reusability, repairability, and ease of high-quality recycling); pushing manufacturing and fabrication process to use materials and energy more efficiently and recover material wastes; increasing the capacity, intensity of use, and lifetimes of product in use; improving the recovery of materials at the end of life, through improved remanufacturing, reuse and recycling processes. For more specific examples see [[#Allwood--2012|Allwood et al. (2012)]] ; [[#Lovins--2018|Lovins (2018)]] ; [[#Hertwich--2019|Hertwich et al. (2019)]] ; [[#Scott--2019|Scott et al. (2019)]] ; and [[#Rissman--2020|Rissman et al. (2020)]] .

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'''Figure 11.7 | Material efficiency (''' ''ME'' ''') strategies across the value chain.''' Source: derived from strategies in [[#Allwood--2012|Allwood et al. (2012)]] .

''ME'' provides plentiful options to reduce emissions, yet because interventions are dispersed across supply chains and span many different stakeholders, this makes assessing mitigation potentials and costs more challenging. For this reason, ''ME'' interventions have traditionally been under-represented in climate change scenario modelling and integrated assessment models (IAMs) ( [[#Grubler--2018|Grubler et al. 2018]] ; [[#Allwood--2018|Allwood 2018]] ). However, two advances in the modelling of materials flows have underpinned the recent emergence of ''ME'' options being included in climate scenario modelling.

Firstly, over many years, the academic community has built up detailed global material-flow maps of the processing steps involved in making energy-intensive materials. Some prominent recent examples include: steel ( [[#Gonzalez%20Hernandez--2018b|Gonzalez Hernandez et al. 2018b]] ), pulp and paper ( [[#Van%20Ewijk--2018|Van Ewijk et al. 2018]] ), petrochemicals ( [[#Levi--2018|Levi and Cullen 2018]] ). In addition, material-flow maps at the regional and sectoral levels have flourished, for example: steel ( [[#Serrenho--2016|Serrenho et al. 2016]] ) and cement ( [[#Shanks--2019|Shanks et al. 2019]] ) in the UK; automotive sheet-metal ( [[#Horton--2019|Horton et al. 2019]] ); and steel-powder applications ( [[#Azevedo--2018|Azevedo et al. 2018]] ). The detailed and transparent physical mapping of material supply chains in this manner enables ''ME'' interventions to be traced back to where emissions are released, and allows these options to be compared against decarbonisation and traditional energy efficiency measures ( [[#Levi--2018|Levi and Cullen 2018]] ). For example, a recent analysis by [[#Hertwich--2019|Hertwich et al. (2019)]] makes the link between ''ME'' strategies and reducing GHG emissions in buildings, vehicles and electronics, while [[#Gonzalez%20Hernandez--2018a|Gonzalez Hernandez et al. (2018a)]] examines leveraging ''ME'' as a climate strategy in European Union (EU) policy. Research to explore the combined analysis of materials and energy, using exergy analysis (for steel: [[#Gonzalez%20Hernandez--2018b|Gonzalez Hernandez et al. 2018b]] ) allows promising comparisons across industrial sectors.

Secondly, many ''ME'' interventions result in immediate GHG emissions savings (short-term), for example, light-weighting products, reusing today’s product components, and improving manufacturing yields. Yet, for other ''ME'' actions emissions savings are delayed temporally (long-term). For example, designing a product for future reuse, or with a longer life, only reaps emissions savings at the end of the product life, when emissions for a replacement product are avoided. Many durable products have long lifetimes (cars &gt;10 years, buildings &gt;40 years) which requires dynamic modelling of material stocks, over time, to enable these actions to be included in scenario modelling activities. Consequently, much effort has been invested recently to model material stocks in use, to estimate their lifetimes, and anticipate the future waste and replenishment materials to maintain existing stocks and grow the material stock base. Dynamic material models have been applied to material and product sectors, at the country and global level. These include, for example: vehicles stocks in the UK ( [[#Serrenho--2017|Serrenho et al. 2017]] ; [[#Craglia--2020|Craglia and Cullen 2020]] ) and in China ( [[#Liu--2020|Liu et al. 2020]] ); buildings stocks in the UK ( [[#Cabrera%20Serrenho--2019|Cabrera Serrenho et al. 2019]] ), China ( [[#Hong--2016|Hong et al. 2016]] ; [[#Cao--2018|Cao et al. 2018]] , 2019) and the European Union ( [[#Sandberg--2016|Sandberg et al. 2016]] ); electronic equipment in Switzerland ( [[#Thiébaud--2017|Thiébaud et al. 2017]] ); specific material stocks, such as cement ( [[#Cao--2020|Cao et al. 2020]] , 2017), construction materials ( [[#Sverdrup--2017|Sverdrup et al. 2017]] ; [[#Habert--2020|Habert et al. 2020]] ), plastics ( [[#Geyer--2017|Geyer et al. 2017]] ), copper ( [[#Daehn--2017|Daehn et al. 2017]] ), and all metals ( [[#Elshkaki--2018|Elshkaki et al. 2018]] ); all materials in China ( [[#Jiang--2019|Jiang et al. 2019]] ), Switzerland ( [[#Heeren--2019|Heeren and Hellweg 2019]] ) and the world ( [[#Krausmann--2017|Krausmann et al. 2017]] ).

These two advances in the knowledge base have allowed the initial inclusion of some ''ME'' strategies in energy and climate change scenario models. The International Energy Agency (IEA) first created a ''ME'' scenario (MES) in 2015, with an estimated 17% reduction in industrial energy demand in 2040 ( [[#IEA--2015|IEA 2015]] ). The World Energy Outlook report includes a dedicated sub-chapter with calculations explicitly on industrial material efficiency ( [[#IEA--2019c|IEA 2019c]] ). They also include ''ME'' options in their modelling frameworks and reporting, for example for petrochemicals ( [[#IEA--2018a|IEA 2018a]] ), and in the Material Efficiency in Clean Energy Transitions report ( [[#IEA--2019b|IEA 2019b]] ). In [[#Grubler--2018|Grubler et al. (2018)]] 1.5°C Low Energy Demand (LED) scenario, global material output decreases by 20% from today, by 2050, with one-third due to dematerialisation, and two-thirds due to ''ME'' , resulting in significant emissions savings. Material Economics’ analysis of Industrial Transformation 2050 ( [[#Material%20Economics--2019|Material Economics 2019]] ), found that resource efficiency and circular economy measures (i.e., ''ME'' ) could almost halve the 530 MtCO 2 yr –1 emitted by the basic materials sectors in the EU by 2050. Finally, the Emissions Gap Report, [[#UNEP--2019|UNEP (2019)]] includes an assessment of potential material efficiency savings in residential buildings and cars.

Clearly, more work is required to fully integrate ''ME'' strategies into mainstream climate change models and future scenarios. Efforts are focused on endogenising ''ME'' strategies within climate change modelling, assessing the synergies and trade-offs which exist between energy efficiency and ''ME'' interventions, and building up data for the assessment of emissions saved and the cost of mitigation from real ''ME'' actions. This requires analysts to work in cross-disciplinary teams and to engage with stakeholders from across the full breadth of material supply chains. Efforts should be prioritised to foster engagement between the IAM community and emerging ''ME'' models based in the Life Cycle Assessment, Resource Efficiency, and Industrial Ecology communities (see also [[#Sharmina--2021|Sharmina et al. 2021]] ).

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=== 11.3.3 Circular Economy and Industrial Waste ===

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Circular economy (CE) is another effective approach to mitigate industrial GHG emissions and has been widely promoted worldwide since the fourth IPCC assessment report (AR4). From an industrial point of view, CE focuses on closing the loop for materials and energy flows by incorporating policies and strategies for more efficient energy, materials and water consumption, while emitting minimal waste to the environment ( [[#Geng--2013|Geng et al. 2013]] ). Moving away from a linear mode of production (sometimes referred to as an ‘extract-produce-use-discard’ model), CE promotes the design of durable goods that can be easily repaired, with components that can be reused, remanufactured, and recycled ( [[#Wiebe--2019|Wiebe et al. 2019]] ). In particular, since CE promotes reduction, reuse and recycling, a large amount of energy and GHG-intense virgin material processing can be reduced, leading to significant carbon emission reductions. For example, in the case of aluminium, the energy efficiency of primary production is relatively close to best available technology (Figure 11.8), while switching to production using recycled materials requires only about 5% as much energy ( [[#11.4.1.4|Section 11.4.1.4]] ). However, careful evaluation is needed from a lifecycle perspective since some recycling activities may be energy- and emission-intensive, for example, the chemical recycling of plastics ( [[#11.4.1.3|Section 11.4.1.3]] ).

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'''Figure 11.8 | Energy efficiency indicators for basic material production.''' Energy accounting is based on final energy use. Sectoral boundaries for steel are as defined in [[#IEA--2020c|IEA (2020c)]] .Sources: calculated based on [[#UNIDO--2010|UNIDO (2010)]] ; [[#Saygin--2011|Saygin et al. (2011)]] ; [[#Hasanbeigi--2012|Hasanbeigi et al. (2012)]] ; [[#Moya--2013|Moya and Pardo (2013)]] ; [[#Napp--2014|Napp et al. (2014)]] ; [[#WBCSD--2016|WBCSD (2016)]] ; IEA (2017, 2018b); [[#IEA%20and%20WBCSD--2018|IEA and WBCSD (2018)]] ; IEA (2019b, 2020c); [[#Crijns-Graus--2020|Crijns-Graus et al. (2020)]] ; [[#IEA--2020b|IEA (2020b)]] ; [[#International%20Aluminium%20Institute--2020|International Aluminium Institute (2020)]] .

As one systemic approach, CE can be seen as conducted at different levels, namely, at the micro level (within a single company, such as process integration and cleaner production), meso level (between three or more companies, such as industrial symbiosis or eco‐industrial parks) and macro level (cross‐sectoral cooperation, such as urban symbiosis or a regional eco‐industrial network). Each level requires different tools and policies, such as CE-oriented incentive and tax policies (macro level), and eco-design regulations (micro level). This section is focused on industry and a broader discussion of the CE concept is found in Box 12.2 and [[IPCC:Wg3:Chapter:Chapter-5#5.3.4.2|Section 5.3.4.2]] .

'''Micro level:''' More firms have begun to implement the concept of CE, particularly multi-national companies, since they believe that multiple benefits can be obtained from CE efforts, and it has become common across sectors ( [[#D’Amato--2019|D’Amato et al. 2019]] ). Typical CE tools and policies at this level include cleaner production, eco-design, environmental labelling, process synthesis, and green procurement. For instance, leading chemical companies are incorporating CE into their industrial practices, for example, through the design of more recyclable plastics, a differentiated and market-driven portfolio of resins, films and adhesives that deliver a total package that is more sustainable, cost-efficient and capable of meeting new packaging and plastics preferences. Problematically, at the same time the plastics industry is improving recyclability, it has, for example, been expanding into markets without recycling capacity ( [[#Mah--2021|Mah 2021]] ). Similarly, automakers are pursuing strategies to increase the portion of new vehicles that are fully recyclable when they reach the end of life, with increasing ambitions for using recycled material, largely motivated by end-of-life vehicle regulations. This will require networks that are available to collect and sort all the materials in vehicles, and policy incentives to do it ( [[#Wiebe--2019|Wiebe et al. 2019]] ; [[#Soo--2021|Soo et al. 2021]] ).

'''Meso level:''' Industrial parks first appeared in Manchester, UK, at the end of the 19th century and they have been implemented in industrialised countries for maximising energy and material efficiency, which also has merit for CO 2 -emissions reduction, as stated in AR5. Industrial parks reduce the cost of infrastructure and utilities by concentrating industrial activities in planned areas, and are typically founded around large, long-term anchor companies. Complementary industries and services provided by industrial parks can entail diversified effects on the surrounding region and stimulate regional development ( [[#Huang--2019a|Huang et al. 2019a]] ). This is crucial for small and medium enterprises (SMEs) because they often lack access to information and funds for sophisticated technologies.

Typical CE tools and policies at this level include sustainable supply chains and industrial symbiosis. A common platform for sharing information and enhancing communication among industrial stakeholders through the application of information and telecommunication technologies is helpful for facilitating the creation of industrial symbiosis. The main benefit of industrial symbiosis is the overall reduction of both virgin materials and final wastes, as well as reduced/avoided transportation costs from by-product exchanges among tenant companies, which can specifically help small- and medium-sized enterprises to improve their growth and competitiveness. From a climate perspective, this indicates significant industrial emission mitigation since the extraction, processing of virgin materials and the final disposal of industrial wastes are more energy intensive. Also, careful site selection of such parks can facilitate the use of renewable energy. Due to these advantages, eco-industrial parks have been actively promoted, especially in East Asian countries, such as China, Japan and the Republic of Korea (South Korea), where national indicators and governance exist ( [[#Geng--2019|Geng et al. 2019]] ). For instance, the successful implementation of industrial symbiosis at Dalian Economic and Technological Development Zone has achieved significant co-benefits, including GHG-emission reduction, economic and social benefits, and improved ecosystem functions ( [[#Liu--2018|Liu et al. 2018]] ). Another case at Ulsan industrial park, South Korea, estimated that 60,522 tonnes of CO 2 were avoided annually through industrial symbiosis between two companies ( [[#Kim--2018b|Kim et al. 2018b]] ). The case of China shows the great potential of implementing these measures, estimating 111 million tonnes of CO 2 equivalent will be reduced in 213 national-level industrial parks in 2030 compared with 2015 ( [[#Guo--2018|Guo et al. 2018]] ). As such, South Korea’s national eco-industrial park project has reduced over 4.7 million tonnes of CO 2 equivalent through their industrial symbiosis efforts ( [[#Park--2019|Park et al. 2019]] ). Meso-level CE solutions have been identified as essential for industrial decarbonisation ( [[#11.4.3|Section 11.4.3]] ). Moreover, waste prevention as the top of the so-called ‘waste hierarchy’ can be promoted on the meso level for specific materials or product systems. For instance, the European Environment Agency published a report on plastic waste prevention approaches in all 28 EU-member states ( [[#Wilts--2019|Wilts and Bakas 2019]] ). However, challenges exist for industrial symbiosis activities, such as inter-firm contractual uncertainties, the lack of synergy infrastructure, and the regulations that hamper reuse and recycling. Therefore, necessary legal reforms are needed to address these implementation barriers.

'''Macro level:''' The macro level uses both micro- and meso-level tools within a broader policy strategy, addressing the specific challenge of CE as a cross-cutting policy ( [[#Wilts--2016|Wilts et al. 2016]] ). More synergy opportunities exist beyond the boundary of one industrial park. This indicates the necessity of scaling up industrial symbiosis to urban symbiosis. Urban symbiosis is defined as the use of by-products (waste) from cities as alternative raw materials for energy sources for industrial operations ( [[#Sun--2017|Sun et al. 2017]] ). It is based on synergistic opportunity arising from geographic proximity through the transfer of physical sources (waste materials) for environmental and economic benefits. Japan is the first country to promote urban symbiosis. For instance, the Kawasaki urban symbiosis efforts can save over 114,000 tonnes of CO 2 emissions annually ( [[#Ohnishi--2017|Ohnishi et al. 2017]] ). Another simulation study indicates that Shanghai (the largest Chinese city) has the potential to save up to 16.8 MtCO 2 through recycling all the available wastes ( [[#Dong--2018|Dong et al. 2018]] ). As such, the simulation of urban-energy-symbiosis networks in Ulsan, South Korea, indicates that 243,396 tCO 2 –1 yr –1 emission and USD48 million yr –1 fuel cost can be saved ( [[#Kim--2018a|Kim et al. 2018a]] ). Moreover, [[#Wiebe--2019|Wiebe et al. (2019)]] estimate that the adoption of the CE can lead to a significantly lower global material extraction compared to a baseline. Their global results range from a decrease of about 27% in metal extraction to 8% in fossil fuel extraction and use, 8% in forestry products, and about 7% in non-metallic minerals, indicating significant climate change benefits. A macro-perspective calculation on the circulation of iron in Japan’s future society shows that CO 2 emissions from the steel sector can be reduced by 56% as per the following assumptions: the amount recovered from social stock is the same as the amount of inflow, and all scrap was used domestically, and the export of steel products is halved ( [[#LCS--2018|LCS 2018]] ). A key challenge is to go beyond ensuring proper waste management to setting metrics, targets and incentives to preserve the incorporated value in specific waste streams. Estimations for Germany have shown that despite recycling rates of 64% for all solid-waste streams, these activities only lead to a resource-use reduction of only 18% ( [[#Steger--2019|Steger et al. 2019]] ). In general, the identification of the most appropriate CE method for different countries requires understanding and information exchange on background conditions, local policies and myriad other factors influencing material flows from the local up to the global level (Tapia Carlos et al. 2019). Also, an information platform should be created at the national level so that all the stakeholders can share their CE technologies and expertise, information (such as materials/energy/water consumption data), and identify the potential synergy opportunities.

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=== 11.3.4 Energy Efficiency ===

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Energy efficiency in industry is an important mitigation option and central in keeping 1.5°C within reach (IPCC SR1.5). It has long been recognised as the first mitigation option in industry (Yeen [[#Chan--2016|Chan and Kantamaneni 2016]] ; [[#Nadel--2019|Nadel and Ungar 2019]] ; [[#IEA--2021a|IEA 2021a]] ). It allows reduction of the necessary scale of deployment for low-carbon energy supplies and associated mitigation costs ( [[#Energy%20Transitions%20Commission--2018|Energy Transitions Commission 2018]] ). The efficiency potentials are greatest in the non-energy-intensive industries and are often relatively limited in energy-intensive ones, such as steel ( [[#Pardo--2013|Pardo and Moya 2013]] ; [[#Kuramochi--2016|Kuramochi 2016]] ; [[#Arens--2017|Arens et al. 2017]] ). Deep decarbonisation in these subsectors requires fundamental process changes but energy efficiency remains important to reduce costs and the need for low-carbon energy supplies.

Below, we focus mainly on the technical progress and on new options that are reflected in the literature since AR5 and refer the reader there for a broader and deeper treatment of energy efficiency. Digitalisation and the development of industrial high-temperature heat pumps are two notable technology developments that can facilitate energy efficiency improvements.

Industrial energy efficiency can be improved through multiple technologies and practices ( [[#Tanaka--2011|Tanaka 2011]] ; [[#Fawkes--2016|Fawkes et al. 2016]] ; [[#Lovins--2018|Lovins 2018]] ; [[#Crijns-Graus--2020|Crijns-Graus et al. 2020]] ; [[#IEA--2020a|IEA 2020a]] ). There are two parallel processes in improvement of specific energy consumption (SEC): progress in energy-efficient BAT and moving the SEC of industrial plants towards BAT. Both slow down as theoretical thermodynamic minimums are approached ( [[#Gutowski--2013|Gutowski et al. 2013]] ). For the last several decades the focus has been on effective spreading of BAT technologies through application of policies for worldwide diffusion of energy-saving technologies ( [[#11.6|Section 11.6]] ). As a result the SEC for many basic primary materials is approaching BAT and there are signs that energy efficiency improvements have been slowing down over recent decades ( [[#IEA--2019d|IEA 2019d]] , 2020a, 2021a) (Figure 11.8).

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==== 11.3.4.1 Heat-use Energy Efficiency Improvement ====

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While about 10% of global GHG emissions originate from combustion to produce high-temperature heat for basic material production processes ( [[#Sandalow--2019|Sandalow et al. 2019]] ), limited efforts have been made to decarbonise heat production. There is still a large potential for using various grades of waste heat and the development of high-temperature heat pumps facilitates its use. [[#NEDO--2019|NEDO (2019)]] applies a ‘Reduce, Reuse, and Recycle’ concept for improved energy efficiency, and we use this frame our discussion of heat efficiency.

''Reduce'' refers to reducing heat needs via improved thermal insulation, for example, where porous type insulators have been developed with thermal conductivity half of what is traditionally achieved by heat-resistant bricks under conditions of high compressive strength (Fukushima and Yoshizawa 2016). ''Reuse'' refers to waste heat recovery. A study for the EU identified a waste heat potential of about 300 TWh yr –1 , corresponding to about 10% of total energy use in industry. About 50% of this was below 200°C, about 25% at temperatures 200°C–500°C, and 25% at temperatures of 500°C and above ( [[#Papapetrou--2018|Papapetrou et al. 2018]] ). A survey conducted in Japan showed that 9% of the input energy is lost as waste heat, of which heat below 199°C accounts for 68% and that below 149°C was 29% ( [[#NEDO--2019|NEDO 2019]] ). [[#McBrien--2016|McBrien et al. (2016)]] identified that in the steel sector process heat recovery presently saves 1.8 GJ per tonne of hot rolled steel, while integrated across all production processes heat recovery with conventional heat exchange could save 2.5 GJ t –1 , and it scales up to 3.0 GJ t –1 using an alternative heat exchange that recovers energy from hot steel. High-temperature industrial heat pumps represent a new and important development for upgrading waste heat and at the same time they facilitate electrification. One recent example is a high-temperature heat pump that can raise temperatures up to 165°C at a coefficient of performance (COP) of 3.5 by recovering heat from unused hot water (35°C–65°C) ( [[#Arpagaus--2018|Arpagaus et al. 2018]] ). Commercially available heat pumps can deliver 100°C–150°C but at least up to 280°C is feasible ( [[#Zühlsdorf--2019|Zühlsdorf et al. 2019]] ). Mechanical vapour recompression avoids the loss of latent heat by condensation, then it acts as a highly efficient heat pump with a 5–10 COP ( [[#Philibert--2017a|Philibert 2017a]] ).

Waste heat to power (WHP), or ''Recycle'' in NEDO’s terms, is also an under-utilised option. For example, a study for the cement, glass and iron industries in China showed that current technology enables only 7–13% of waste heat to be used for power generation. With improved technologies, potentially 40–57% of waste heat with temperatures above 150°C could be used for power generation via heat recovery. Thermal power fluctuations can be a challenge and negatively affect the operation and economic feasibility of heat recovery power systems such as steam and/or organic Rankine cycle. In such cases, latent heat storage technology and intermediate storage units may be applied ( [[#Jiménez-Arreola--2018|Jiménez-Arreola et al. 2018]] ). The development of thermoelectric conversion materials that produce power from unused heat and energy harvested from a higher temperature environment is also progressing, with several possible applications in industrial processes (Gayner and Kar 2016; [[#Jood--2018|Jood et al. 2018]] ; [[#Lv--2018|Lv et al. 2018]] ; [[#Ohta--2018|Ohta et al. 2018]] ). A potential early application in industry is to power wireless sensors, a niche that uses microwatts or milliwatts, and avoid power cables ( [[#Champier--2017|Champier 2017]] ).

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==== 11.3.4.2 Smart Energy Management ====

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Energy management systems to reduce energy costs in an integrated and systematic manner were first developed in the 1970s, mainly in low-energy-resource countries, for example, by establishing energy managers and institutionalising management targets ( [[#Tanaka--2011|Tanaka 2011]] ). Strategic energy management has since then evolved and been promoted through the establishment of dedicated organisational infrastructures for energy-use optimisation, such as ISO-50001 which specifies the requirements for establishing, implementing, maintaining, and improving an energy management system ( [[#Biel--2016|Biel and Glock 2016]] ; [[#Tunnessen--2017|Tunnessen and Macri 2017]] ). Digitalisation, sometimes referred to as Industry 4.0, facilitates further improvements in process control and optimisation through technology development involving sensors, communications, analytics, digital twins, machine learning, virtual reality, and other simulation and computing technologies ( [[#Rogers--2018|Rogers 2018]] ), all of which can improve energy efficiency. One example is combustion control systems, where big data analysis of factors affecting boiler efficiency, operation optimisation and load forecasting have shown that it can lead to energy savings of 9% ( [[#Wang--2017|Wang et al. 2017]] ).

Smart energy systems with real-time monitoring allow for optimisation of innovative technologies, energy demand response, balancing of energy supply and demand including that on real-time pricing, and product quality management, and prediction and reduction of idle time for workers and robots ( [[#ERIA--2016|ERIA 2016]] ; [[#Pusnik--2016|Pusnik et al. 2016]] ; [[#ISO--2018|ISO 2018]] ; [[#Legorburu--2018|Legorburu and Smith 2018]] ; [[#Ferrero--2020|Ferrero et al. 2020]] ; [[#Nimbalkar--2020|Nimbalkar et al. 2020]] ). The IEA estimated that smart manufacturing could deliver 15 EJ in energy savings between 2014 and 2030 ( [[#IEA--2019d|IEA 2019d]] ). Smart manufacturing systems that integrate manufacturing intelligence in real time through the entire production operation have not been yet widely spread in the industry. Examples have been demonstrated and integrated in real operation in the electrical appliance assembly industry ( [[#Yoshimoto--2016|Yoshimoto 2016]] ). Combining process controls and automation allows cost optimisation and improved productivity ( [[#Edgar--2018|Edgar and Pistikopoulos 2018]] ).

<div id="11.3.5" class="h2-container"></div>

<span id="electrification-and-fuel-switching"></span>
=== 11.3.5 Electrification and Fuel Switching ===

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The principle of electrification and fuel switching as a GHG mitigation strategy is that industries, to the extent possible, switch their end uses of energy from a high GHG intensity energy carrier to a lower or zero intensity one, including both its direct and indirect production and end-use GHG emissions. In general, and non-exclusively, this implies a transition from coal (about 0.09 tCO 2 GJ –1 on combustion), refined petroleum products (about 0.07 tCO 2 GJ –1 ), and natural gas (about 0.05 tCO 2 GJ –1 ) to biofuels, direct solar heating, electricity, hydrogen, ammonia, or net zero synthetic hydrocarbon fuels. Switching to these energy carriers is not necessarily lower emitting, however; how they are made matters.

Fuel switching has already been observed to reduce direct combustion CO 2 emissions in many jurisdictions. There are significant debates about the net effect of upstream fossil fuel production and fugitive emissions, but observers have noted that in the case of US power generation it would take a leakage rate of about 2.7% from natural gas production to undo the direct fuel switching from coal mitigation effect, and the value is likely higher in most cases ( [[#Alvarez--2012|Alvarez et al. 2012]] ; [[#Hausfather--2015|Hausfather 2015]] ). Coal mine methane emissions are also estimated to be substantially higher than previously assessed ( [[#Kholod--2020|Kholod et al. 2020]] ). [[#Alvarez--2018|Alvarez et al. (2018)]] estimated US fugitive emissions (not including the Permian) at 2.3% of supply, 60% more than previously estimated, while recent Canadian papers indicate fugitive emissions are at least 50% more than reported ( [[#Chan--2020|Chan et al. 2020]] ; [[#MacKay--2021|MacKay et al. 2021]] ). However, given the potential for energy supply infrastructure lock-in effects ( [[#Tong--2019|Tong et al. 2019]] ), purely fossil fuel to fossil fuel switching is a limited and potentially dangerous strategy unless it is used very carefully and in a limited way.

Biofuels come in many forms, including ones that are nearly identical to fossil fuels but sourced from biogenic sources. Solid biomass, either direct from wood chips, lignin or processed pellets, is the most commonly used renewable fuel in industry today and is occasionally used in cement kilns and boilers. Biomethane, biomethanol, and bioethanol are all commercially made today using fermentation and anaerobic digestion techniques and are mostly ‘drop-in’ compatible with fossil fuel equivalents. In principle they cycle carbon in and out of the atmosphere, but their lifecycle GHG intensities are typically not GHG neutral due to land-use changes, soil carbon depletion, fertiliser use, and other dynamics ( [[#Hepburn--2019|Hepburn et al. 2019]] ), and are highly case specific. Most commercial biofuel feedstocks come from agricultural (e.g., corn) and food waste sources, and the feedstock is limited; to meet higher levels of biomass use a transition to using higher cellulose feedstocks like straw, switchgrass and wood waste, available in much larger quantities, must be fully commercialised and deployed. Significant efforts have been made to make ethanol from cellulosic biomass, which promises much higher quantities, lower costs, and lower intensities, but commercialisation efforts, with a few exceptions, have largely not succeeded ( [[#Padella--2019|Padella et al. 2019]] ). The IEA estimates, however, that up to 20% of today’s fossil methane use, including by industry, could be met with biomethane ( [[#IEA--2020g|IEA 2020g]] ) by 2040, using a mixture of feedstocks and production techniques. Biofuel use may also be critical for producing negative emissions when combined with carbon capture and storage (i.e., bioenergy with carbon capture and storage – BECCS). Most production routes for biofuels, biochemicals and biogas generate large side streams of concentrated CO 2 which is easily captured, and which could become a source of negative emissions ( [[#Sanchez--2018|Sanchez et al. 2018]] ) (Section ). Finally, it should be noted that biofuel combustion can, if inadequately controlled, have substantial negative local air quality effects, with implications for SDGs 3, 7 and 11.

There is a large identified potential for direct solar heating in industry, especially in regions with strong solar insolation and sectors with lower heat needs (&lt;180°C), for example, food and beverage processing, textiles, and pulp and paper ( [[#Schoeneberger--2020|Schoeneberger et al. 2020]] ). The key challenges to adoption are site and use specificity, capital intensity, and a lack of standardised mass manufacturing for equipment and a supply chain to provide them.

Switching to electricity for end uses, or ‘direct electrification’, is a highly discussed strategy for net zero industrial decarbonisation ( [[#Lechtenböhmer--2016|Lechtenböhmer et al. 2016]] ; [[#Palm--2016|Palm et al. 2016]] ; [[#Åhman--2017|Åhman et al. 2017]] ; [[#Axelson--2018|Axelson et al. 2018]] ; [[#Bataille--2018a|Bataille et al. 2018a]] ; [[#Davis--2018|Davis et al. 2018]] ; [[#UKCCC--2019b|UKCCC 2019b]] ; [[#Material%20Economics--2019|Material Economics 2019]] ). Electricity is a flexible energy carrier that can be made from many forms of primary energy, with high potential process improvements in terms of end-use efficiency ( [[#Eyre--2021|Eyre 2021]] ), quality and process controllability, digitisability, and no direct local air pollutants ( [[#McMillan--2016|McMillan et al. 2016]] ; [[#Jadun--2017|Jadun et al. 2017]] ; [[#Deason--2018|Deason et al. 2018]] ; [[#Mai--2018|Mai et al. 2018]] ). The net-GHG effect of electrification is contingent on how the electricity is made, and because total output increases can be expected, for full effect it should be made with a very low GHG intensity primary source (i.e., &lt;50 g CO 2 kWh –1 : e.g., hydroelectricity, nuclear energy, wind, solar photovoltaics, or fossil fuels with 95+% carbon capture and storage ( [[#IPCC--2014|IPCC 2014]] )). This has strong implications for the electricity sector and its generation mix when the goal is a net-zero-emissions electricity system. Despite their falling costs, progressively higher mixes of variable wind and solar on a given grid will require support from grid flexibility sources, including demand response, more transmission, storage on multiple time scales, or firm low-to-negative emissions generation sources (e.g., nuclear energy, hydrogen fuel cells or turbines, biofuels, fossil or biofuels with CCS, and geothermal) to moderate costs ( [[#Jenkins--2018|Jenkins et al. 2018]] ; [[#Sepulveda--2018|Sepulveda et al. 2018]] ; [[#Williams--2021|Williams et al. 2021]] ). Regions that may be slower to reduce the GHG intensity of their electricity production will likely need to consider more aggressive use of other measures, like energy and material efficiency or bioenergy.

The long-term potential for full-process electrification is a very sector-by-sector and process-by-process phenomenon, with differing energy and capacity needs, load profiles, stock turnover, capacity for demand response, and characteristics of decision-makers. Industrial electrification is most viable in the near term in cases with: minimal retrofitting and rebuild in processes; with relatively low local electricity costs; where the degree of process complexity and process integration is more limited and extensive process re-engineering would not be required; where combined heat and power is not used; where induction heating technologies are viable; and where process heating temperatures are lower ( [[#Deason--2018|Deason et al. 2018]] ).

For these reasons, lighter, manufacturing-orientated industries are more readily electrifiable than heavier industry like steel, cement, chemicals and other sectors with high heat and feedstock needs. Steam boilers, curing, drying and small-scale process heating, with typically lower maximum heat temperature needs (&lt;200°C–250°C) are readily electrifiable with appropriate fossil-fuel-to-electricity price ratios (accounting for capital costs and efficiencies), and direct induction and infrared heating are available for higher temperature needs. These practices are uncommon outside regions with ample hydroelectric power due to the currently relatively low cost of coal, natural gas and heating oil, and especially when there is no carbon combustion cost. [[#Madeddu--2020|Madeddu et al. (2020)]] argue up to 78% of Europe’s industrial energy requirements are electrifiable through existing commercial technologies. In contrast, [[#Mai--2018|Mai et al. (2018)]] saw only a moderate industrial heat supply electrification in their high-electrification scenario for the US. Electrification has also been explored in: raw and recycled steel ( [[#Fischedick--2014|Fischedick et al. 2014]] b; [[#Vogl--2018|Vogl et al. 2018]] ); ammonia ( [[#Bazzanella--2017|Bazzanella and Ausfelder 2017]] ; [[#Philibert--2017a|Philibert 2017a]] ); and chemicals ( [[#Palm--2016|Palm et al. 2016]] ; [[#Bazzanella--2017|Bazzanella and Ausfelder 2017]] ). While most chemical production of feedstock chemicals (e.g., H 2 , NH 3 , CO, CH 3 OH, C 2 H 4, C 2 H 6 and C 2 H 5 OH ) is done thermo-catalytically today, it is feasible to use direct electrocatalytic production, by itself or in combination with utilisation of previously captured carbon sources if a fossil fuel feedstock is used, or well-known bio-catalytic (e.g., fermentation) and thermo-catalytic processes ( [[#Bazzanella--2017|Bazzanella and Ausfelder 2017]] ; [[#De%20Luna--2019|De Luna et al. 2019]] ; [[#Kätelhön--2019|Kätelhön et al. 2019]] ). It may even be commercially possible to electrify cement sintering and calcination through plasma or microwave options ( [[#Material%20Economics--2019|Material Economics 2019]] ).

Increased electrification of industry will result in increased overall demand for electricity. For example, 75 TWh of electricity was used by steel in the EU in 2015 (out of the 1000 TWh total used by industry), [[#Material%20Economics--2019|Material Economics (2019)]] , varying between their new process, circularity and CCUS scenarios, projects increased demand to 355 (+373%), 214 (+185%) and 238 (+217%) TWh. These values are consistent with [[#Vogl--2018|Vogl et al. (2018)]] , which projects a tripling of electricity demand in the German or Swedish steel industries if hydrogen-direct reduced iron and electric arc furnace steel-making (DRI EAFs) replaces BF-BOFs. [[#Material%20Economics--2019|Material Economics (2019)]] was conservative with its use of electricity in chemical production, making preferential use of biofeedstocks and some CCUS, and electricity demand still rose from 118 TWh to 510, 395 and 413 TWh in their three scenarios. [[#Bazzanella--2017|Bazzanella and Ausfelder (2017)]] , exploring deeper reductions from the chemical sector using more electrochemistry, projected scenarios with higher electricity demands of 960–4900 TWh (140% of the projected available clean electricity at the time) with maximum electricity use. In counterpoint, however, with revised wind capabilities and costs, the [[#IEA--2019e|IEA (2019e)]] Offshore Wind Outlook indicates that ten times the current EU electricity use could be produced if necessary. Greater use of electro-catalytic versus thermo-catalytic chemistry, as projected by [[#De%20Luna--2019|De Luna et al. (2019)]] , could greatly reduce these electricity needs, but the technology readiness levels are currently low. Finally, the [[#UKCCC--2019b|UKCCC (2019b)]] , which focused primarily on CCS for industry in its ‘Further Ambition’ scenario (the UK currently consumes about 300 TWh), in its supplementary ‘Further Electrification’ scenario projects an additional 300 TWh for general electrolysis needs and another 200 TWh for synthetic fuel production.

While it has been demonstrated that almost any heating end use can be directly electrified, this would imply very high instantaneous thermal loads for blast furnace-basic oxygen furnace (BF-BOF) steel production, limestone calcination for cement and lime production, and other end uses where flame-front (1000°C–1700°C) temperatures are currently needed. This indicates a possible need for another energy carrier to minimise instantaneous generation and transmission needs. These needs can be met at varying current and potential future costs using: bioliquids or gases hydrogen, ammonia, or net zero synthetic hydrocarbons or alcohols.

Broadly speaking, '''hydrogen''' can contribute to a cleaner energy system in two ways: (i) existing applications of hydrogen (e.g., nitrogen fertiliser production, refinery upgrading) can use hydrogen produced using alternative, cleaner production methods; (ii) new applications can use low-GHG hydrogen as an alternative to current fuels and inputs, or as a complement to the greater use of electricity in these applications. In these cases – for example, in transport, heating, industry (e.g., hydrogen-direct reduced iron and steel production) and electricity – hydrogen can be used in its pure form, or be converted to hydrogen-based fuels, including ammonia, or synthetic net zero hydrocarbons and alcohols such as methane or methanol ( [[#IEA--2019f|IEA 2019f]] ). The IEA states that hydrogen could be used to help integrate more renewables, including by enhancing storage options and ‘exporting sunshine and wind’ from places with abundant resources; decarbonise steel, chemicals, trucks, ships and planes; and boost energy security by diversifying the fuel mix and providing flexibility to balance grids ( [[#IEA--2019f|IEA 2019f]] ).

Around 70 Mt yr –1 of pure hydrogen is produced today: 76% from natural gas and 23% from coal, resulting in emissions of roughly 830 MtCO 2 yr –1 in 2016/17 ( [[#IEA--2019f|IEA 2019f]] ), or 4.7% of global industrial direct and indirect emissions (waste excluded; [[#_idTextAnchor023|Table 11.1]] ). Fuels refining (about 410 MtCO 2 yr –1 ) and production of ammonia (420 MtCO 2 yr –1 ) largely dominate its uses. Another 45 Mt hydrogen is being produced along with other gases, on purpose or as by-products, and used as fuel, to make methanol or as a chemical reactant ( [[#IEA--2019f|IEA 2019f]] ). Very low and potentially zero GHG (depending on the energy source) hydrogen can be made via: electrolysis separation of water into hydrogen and oxygen ( [[#Glenk--2019|Glenk and Reichelstein 2019]] ), also known as ‘green H 2 ’; electrothermal separation of water, as done in some nuclear plants ( [[#Bicer--2017|Bicer and Dincer 2017]] ); partial oxidation of coal or naphtha or steam/auto methane reforming (SMR/ATR) combined with CCS ( [[#Leeson--2017|Leeson et al. 2017]] ), or ‘blue H 2 ’; methane pyrolysis, where the hydrogen and carbon are separated thermally and the carbon is left as a solid (Abbas and Wan Daud 2010; [[#Ashik--2015|Ashik et al. 2015]] ), or via biomass gasification ( [[#Ericsson--2017|Ericsson 2017]] ), which could be negative emissions if the CO 2 from the gasification process is sequestered. All these processes would in turn need to be run using very low or zero GHG energy carriers for the resulting hydrogen to also be low in GHG emissions.

'''Ammonia production''' , made from hydrogen and nitrogen using the Haber-Bosch process, is the most voluminous chemical produced from fossil fuels, being used as feedstock for nitrogen fertilisers and explosives, as well as a cleanser, a refrigerant, and for other uses. Most ammonia is made today using methane as the hydrogen feedstock and heat source but has been made using electrolysis-based hydrogen in the past, and there are several announced investments to resume doing so. If ammonia is used as a combustion fuel, care must be taken to avoid N 2 O as a GHG and NO x in general as a local air pollutant.

Hydrogen can also be combined with low-to-zero net GHG carbon (Section ) and oxygen and made into '''methane''' , '''methanol''' and other potential net zero '''synthetic hydrocarbons''' '''and alcohol''' energy carriers using methanation, steam reforming and Fischer-Tropsch processes, all of which can provide higher degrees of storable and shippable high-temperature energy using known industrial processes in novel combinations ( [[#Bataille--2018a|Bataille et al. 2018a]] ; [[#Davis--2018|Davis et al. 2018]] ). If the hydrogen and oxygen is accessed via electrolysis, the terms ‘power-to-fuel’ or ‘e-fuels’ are often used ( [[#Ueckerdt--2021|Ueckerdt et al. 2021]] ). Given their carbon content, if used as fuels, their carbon will eventually be oxidised and emitted as CO 2 to the atmosphere. This makes their net-GHG intensity dependent on the carbon source ( [[#Hepburn--2019|Hepburn et al. 2019]] ), with recycled fossil fuels, biocarbon and direct air capture carbon all having very different net-CO 2 impacts – see section 11.3.6 on CCS and CCU for elaboration.

<div id="Box 11.1 | Hydro" class="h2-container"></div>

<span id="box-11.1-hydro-gen-in-industry"></span>
=== Box 11.1 | Hydrogen in Industry ===

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The‘hydrogen economy’ is a long-touted vision for the energy and transport sectors, and one that has gone through hype-cycles since the energy crises in the 1970s (Melton et al. 2016) . The widely varying visions of hydrogen futures have mainly been associated with fuel cells in vehicles, small-scale decentralised cogeneration of heat and electricity, and to a certain extent energy storage for electricity (Eames et al. 2006; Syniak and Petrov 2008) . However, nearly all hydrogen currently produced is used in industry, mainly for hydrotreating in oil refineries, to produce ammonia, and in other chemical processes, and it is mostly made using fossil fuels.

In the context of net zero emissions, new visions are emerging in which hydrogen has a central role to play in decarbonising industry. Near-term industrial applications for hydrogen include feeding it into ammonia production for fertilisers, while a more novel application would be as a replacement for coal as the reductant in steel-making, being piloted by the HYBRIT project in Sweden 2020–2021, and many companies have initiated hydrogen steel-making projects. As shown in Sections [[#_idTextAnchor014|11.3.5]] and , there are many other potential applications of hydrogen, some of which are still relatively unexplored. Hydrogen can also be used to produce various lower-GHG hydrocarbons and alcohols for fuels and chemical feedstocks using carbon from biogenic sources or direct air capture of CO 2 ( [[#Ericsson--2017|Ericsson 2017]] ; Huan g et al. 2020) .

The geographical distribution of the potential for hydrogen from electrolysis powered by renewables like solar and wind, nuclear electrothermally produced hydrogen, and hydrogen from fossil gas with CCS may reshape where heavy industry is located, how value chains are organised, and what gets transported in international shipping ( [[#Bataille--2020a|Bataille 2020a]] ; [[#Gielen--2020|Gielen et al. 2020]] ; [[#Bataille--2021a|Bataille et al. 2021a]] ; [[#Saygin--2021|Saygin and Gielen 2021]] ). Regions with bountiful renewables resources, nuclear, or methane co-located with CCS geology may become exporters of hydrogen or hydrogen carriers such as methanol and ammonia, or home to the production of iron and steel, organic platform chemicals, and other energy-intensive basic materials. This in turn may generate new trade patterns and needs for bulk transport.

<div id="11.3.6" class="h2-container"></div>

<span id="ccs-ccu-carbon-sources-feedstocks-and-fuels"></span>

=== 11.3.6 CCS, CCU, Carbon Sources, Feedstocks, and Fuels ===

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Carbon is an important and highly flexible building block for a wide range of fuels, organic chemicals and materials including methanol, ethanol, olefins, plastics, textiles, and wood and paper products. In this chapter we define CCS as requiring return of CO 2 from combustion or process gases or ambient air to the geosphere for geological time periods (i.e., thousands of years) ( [[#IPCC--2005|IPCC 2005]] ; [[#IEA--2009|IEA 2009]] ; [[#Bruhn--2016|Bruhn et al. 2016]] ; [[#IEA--2019g|IEA 2019g]] ). CCU is defined as being where carbon (as CO or CO 2 ) is captured from one process and reused for another, reducing emissions from the initial process, but is then potentially but not necessarily released to the atmosphere in following processes ( [[#Bruhn--2016|Bruhn et al. 2016]] ; [[#Detz--2019|Detz and van der Zwaan 2019]] ; [[#Tanzer--2019|Tanzer and Ramírez 2019]] ). In both cases the net effect on atmospheric emissions depends on the initial source of the carbon, be it from a fossil fuel, from biomass, or from direct air capture ( [[#Cuéllar-Franca--2015|Cuéllar-Franca and Azapagic 2015]] ; [[#Hepburn--2019|Hepburn et al. 2019]] ) and the duration of storage or use, which can vary from days to millennia.

While CCS and CCU share common capture technologies, what happens to the CO 2 and therefore the strategies that will employ them can be very different. CCS can help maintain near-CO 2 neutrality for fossil CO 2 that passes through the process, with highly varying partially negative emissions if the source is biogenic ( [[#Hepburn--2019|Hepburn et al. 2019]] ), and fully negative emissions if the source is air capture, all not considering the energy used to drive the above processes. CCS has been covered in other IPCC publications at length, for example, [[#IPCC--2005|IPCC (2005)]] , and in most mitigation-oriented assessments since, for example, the IEA’s Energy Technology Perspectives (ETP) 2020 and Net Zero scenario reports ( [[#IEA--2021a|IEA 2021a]] , 2020a). The potentials and costs for CCS in industry vary considerably due to the diversity of industrial processes ( [[#Leeson--2017|Leeson et al. 2017]] ), as well as the volume and purity of different flows of CO 2 ( [[#Naims--2016|Naims 2016]] ); [[#Kearns--2021|Kearns et al. (2021)]] provide a recent review. As a general rule it is not possible to capture all the CO 2 emissions from an industrial plant. To achieve zero or negative emissions, CCS would need to be combined with some use of sustainably sourced biofuel or feedstock, or the remaining emissions would need to be offset by carbon dioxide removal (CDR) elsewhere.

For concentrated CO 2 sources (e.g., cleaning of wellhead formation gas to make it suitable for the pipeline network, hydrogen production using steam methane reforming, ethanol fermentation, or from combustion of fossil fuels with oxygen in a nitrogen-free environment, i.e., ‘oxycombustion’) CCS is already amenable to commercial oil and gas reinjection techniques used to eliminate hydrogen sulphide gas and brines at prices of USD10–40 tCO 2 -eq –1 sequestered ( [[#Wilson--2003|Wilson et al. 2003]] ; [[#Leeson--2017|Leeson et al. 2017]] ). Most currently operating CCS facilities take advantage of concentrated CO 2 flows, for example, from formation gas cleaning on the Snoevit and Sleipner platforms in Norway, from syngas production for the Al Reyadah DRI steel plant in Abu Dhabi, and from SMR hydrogen production on the Quest upgrader in Alberta. Since concentrated process CO 2 emissions are often exempted from existing cap and trade systems, these opportunities for CCS have largely gone unexploited. Many existing projects partially owe their existence to the utilisation of the captured CO 2 for enhanced oil recovery, which in many cases counts as both CCS and CCU because of the permanent nature of the CO 2 disposal upon injection if sealed properly ( [[#Mac%20Dowell--2017|Mac Dowell et al. 2017]] ). There are several industrial CCS strategies and pilot projects working to take advantage of the relative ease of concentrated CO 2 disposal (e.g., LEILAC for limestone calcination process emissions from cement production, HISARNA direct oxycombustion smelting for steel) ( [[#Bataille--2020a|Bataille 2020a]] ). An emerging option for storing carbon is methane pyrolysis by which methane is split into hydrogen and solid carbon that may subsequently be stored ( [[#Schneider--2020|Schneider et al. 2020]] ).

There are several post-combustion CCS projects underway globally ( [[#IEA--2019g|IEA 2019g]] ), generally focused on energy production and processing rather than industry. Their costs are higher but evolving downward – [[#Giannaris--2020|Giannaris et al. (2020)]] suggest USD47 tCO 2 –1 for a follow-up 90% capture power generation plant based on learnings from the Saskpower Boundary Dam pilot – but crucially these costs are higher than implicit and explicit carbon prices almost everywhere, resulting in limited investment and learning in these technologies. A key challenge with all CCS strategies, however, is building a gathering and transport network for CO 2 , especially from dispersed existing sites; hence most pilot projects are built near EOR/geological storage sites, and the movement towards industrial clustering in the EU and UK ( [[#UKCCC--2019b|UKCCC 2019b]] ), and as suggested in [[#IEA--2019f|IEA (2019f)]] .

In the case of CCU, CO and CO 2 are captured and subsequently converted into valuable products (e.g., building materials, chemicals and synthetic fuels) ( [[#Styring--2011|Styring et al. 2011]] ; [[#Bruhn--2016|Bruhn et al. 2016]] ; [[#Artz--2018|Artz et al. 2018]] ; [[#Brynolf--2018|Brynolf et al. 2018]] ; [[#Daggash--2018|Daggash et al. 2018]] ; [[#Breyer--2019|Breyer et al. 2019]] ; [[#Kätelhön--2019|Kätelhön et al. 2019]] ; [[#Vreys--2019|Vreys et al. 2019]] ). CCU has been envisioned as part of the ‘circular economy’ but conflicting expectations on CCU and its association or not with CCS leads to different and contested framings ( [[#Palm--2021|Palm and Nikoleris 2021]] ). The duration of the CO 2 storage in these products varies from days to millennia according to the application, potentially but not necessarily replacing new fossil, biomass or direct air capture feedstocks, before meeting one of several possible fates: permanent burial, decomposition, recycling or combustion, all with differing GHG implications. While the environmental assessment of CCS projects is relatively straightforward, however, this is not the case for CCU technologies. The net-GHG mitigation impact of CCU depends on several factors (e.g., the capture rate, the energy requirements, the lifetime of utilisation products, the production route that is substituted, and associated room for improvement along the traditional route) and has to be determined by lifecycle CO 2 or GHG analysis (e.g., [[#Nocito--2020|Nocito and Dibenedetto 2020]] ; and [[#Bruhn--2016|Bruhn et al. 2016]] ). For example, steel-mill gases containing carbon monoxide and carbon dioxide can be used as feedstock together with hydrogen for producing chemicals. In this way, the carbon originally contained in the coke used in the blast furnace is used again, or cascaded, and emissions are reduced but not brought to zero. If fossil-sourced CO 2 is only reused once and then emitted, the maximum reduction is 50% ( [[#Tanzer--2019|Tanzer and Ramírez 2019]] ). The logic of using steel-mill CO and CO 2 could equally be applied to gasified biomass, however, with a far lower net-GHG footprint, likely negative, which CCU fed by fossil fuels cannot be if end-use combustion is involved.

Partly because of the complexity of the lifecycle analysis accounting, the literature on CCU is not always consistent in terms of the net-GHG impacts of strategies. For example, [[#Artz--2018|Artz et al. (2018)]] , focused not just on GHG mitigation but multi-attribute improvements to chemical processes from reutilisation of CO 2 , suggests the largest reduction in the absolute amount of GHGs from CO 2 reutilisation could be achieved by the coupling of highly concentrated CO 2 sources with carbon-free hydrogen or electrons from low GHG power in so called ‘power-to-fuel’ scenarios. From the point of view of maximising GHG mitigation using surplus ‘curtailed’ renewable power, however, [[#Daggash--2018|Daggash et al. (2018)]] instead indicates the best use would be for direct air capture and CCS. These results depend on what system is being measured, and what the objective is.

There are several potential crucial transitional roles for synthetic hydrocarbons and alcohols (e.g., methane, methanol, ethanol, ethylene, diesel and jet fuel) constructed using fossil, biomass or direct carbon capture (DAC) and CCU ( [[#Breyer--2015|Breyer et al. 2015]] ; [[#Dimitriou--2015|Dimitriou et al. 2015]] ; [[#Sternberg--2015|Sternberg and Bardow 2015]] ; [[#Fasihi--2017|Fasihi et al. 2017]] ; [[#Bataille--2018a|Bataille et al. 2018a]] ; [[#Bataille--2020a|Bataille 2020a]] ). They can allow reductions in the GHG intensity of high-value legacy transport, industry and real estate that currently runs on fossil fuels but cannot be easily or readily retrofitted. They can be used by existing long-lived energy and feedstock infrastructure, transport and storage, which can compensate for seasonal supply fluctuations and contribute to enhancing energy security ( [[#Ampelli--2015|Ampelli et al. 2015]] ). Finally, they can reduce the GHG intensity of end uses that are very difficult to run on electricity, hydrogen or ammonia (e.g., long-haul aviation). However, their equivalent mitigation cost today would be very high (USD960–1440 tCO 2 -eq –1 ), with the potential to fall to USD24–324 tCO 2 -eq –1 ) with commercial economies of scale, with very high uncertainty ( [[#Hepburn--2019|Hepburn et al. 2019]] ; [[#IEA--2020a|IEA 2020a]] ; [[#Ueckerdt--2021|Ueckerdt et al. 2021]] ).

A very large and important uncertainty is the long-term demand for hydrocarbon and alcohol fuels (whether fossil-, biomass- or DAC-based), chemical feedstocks (e.g., methanol and ethylene) and materials, and competition for biomass feedstock with other priorities, including agriculture, biodiversity and other proximate land-use needs, as well as need for negative emissions through BECCS. The current global plastics production of around 350 Mt yr –1 is almost entirely based on petroleum feedstock and recycling rates are very low. If this or future demand were to be 100% biomass-based it would require tens of exajoules of biomass feedstock ( [[#Meys--2021|Meys et al. 2021]] ). If demand can be lowered and recycling increased (mechanical as well as chemical) the demand for biomass feedstock can be much lower ( [[#Material%20Economics--2019|Material Economics 2019]] ). Promising routes in the short-term would be to utilise CO 2 from anaerobic digestion for biogas and fermentation for ethanol in the production of methane or methanol ( [[#Ericsson--2017|Ericsson 2017]] ); methanol can be converted into ethylene and propylene in a methanol-to-olefins process and used in the production of plastics (Box 11.2). New process configurations where hydrogen is integrated into biomass conversion routes to increase yields and utilise all carbon in the feedstock are relatively unexplored ( [[#Ericsson--2017|Ericsson 2017]] ; [[#De%20Luna--2019|De Luna et al. 2019]] ).

There are widely varying estimates of the capacity of CCU to reduce GHG emissions and meet the net zero objective. According to [[#Hepburn--2019|Hepburn et al. (2019)]] , the estimated potential for the scale of CO 2 utilisation in fuels varies widely, from 1 to 4.2 GtCO 2 yr –1 , reflecting uncertainties in potential market penetration, requiring carbon prices of around USD40 to 80 tCO 2 –1 , increasing over time. The high end represents a future in which synthetic fuels have sizeable market shares, due to cost reductions and policy drivers. The low end – which is itself considerable – represents very modest penetration into the methane and fuels markets, but it could also be an overestimate if CO 2 -derived products do not become cost competitive with alternative clean energy vectors such as hydrogen or ammonia, or with direct sequestration. [[#Brynolf--2018|Brynolf et al. (2018)]] indicates that a key cost variable will be the cost of electrolysers for producing hydrogen. [[#Kätelhön--2019|Kätelhön et al. (2019)]] estimate that up to 3.5 GtC yr –1 could be displaced from chemical production by 2030 using CCU, but this would require clean electricity equivalent to 55% of estimated global power production, at the same time other sectors’ demand would also be rising. [[#Mac%20Dowell--2017|Mac Dowell et al. (2017)]] suggest that while CCU, and specifically CO 2 -based enhanced oil recovery, may be an important economic incentive for early CCS projects (up to 4–8% of required mitigation by 2050), it is unlikely the chemical conversion of CO 2 for CCU will account for more than 1% of overall mitigation.

Finally, there is another class of CCU activities associated with carbonation of alkaline industrial wastes (including iron and steel slags, coal fly ash, mining and mineral processing wastes, incinerator residues, cement and concrete wastes, and pulp and paper mill wastes) using waste or atmospheric CO 2 . Given the large volume of alkaline wastes produced by industry, capture estimates are as high as 4 GtCO 2 yr −1 ( [[#Cuéllar-Franca--2015|Cuéllar-Franca and Azapagic 2015]] ; [[#Ebrahimi--2017|Ebrahimi et al. 2017]] ; [[#Kaliyavaradhan--2017|Kaliyavaradhan and Ling 2017]] ; [[#Pasquier--2018|Pasquier et al. 2018]] ; [[#Huang--2019c|Huang et al. 2019c]] ; [[#Pan--2020|Pan et al. 2020]] ; [[#Zhang--2020|Zhang et al. 2020]] ) However, as some alkaline wastes are already used directly as supplementary cementitious materials to reduce clinker-to-cement ratios, and their abundant availability in the future is questionable (e.g., steel blast furnace slag and coal fly ash), there will be a strong competition between mitigation uses ( [[#11.4.2|Section 11.4.2]] ), and the potential for direct removal by carbonation is estimated at about 1 GtCO 2 yr −1 ( [[#Renforth--2019|Renforth 2019]] ).

The above CCU literature has identified that there may be a highly unpredictable competition between fossil, biogenic and direct air capture carbon to provide highly uncertain chemical feedstock, material and fuel needs. Fossil waste carbon will likely initially be plentiful but will add to net atmospheric CO 2 when released. Biogenic carbon is variably, partially net-negative, but the available stock will be finite and compete with biodiversity and agriculture needs for land. Direct air capture carbon will require significant amounts of low-GHG electricity or methane with high-capture rate CCS ( [[#Keith--2018|Keith et al. 2018]] ). There are clearly strong interactive effects between low-carbon electrification, switching to biomass, hydrogen, ammonia, synthetic hydrocarbons via CCU, and CCS.

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=== 11.3.7 Strategy Interactions and Integration ===

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In this section we conceptually address interactions between service demand, service product intensity, product material efficiency, energy efficiency, electrication and fuel switching, CCU and CCS, and what conflicts and synergies may exist. Post AR5 a substantial literature has emerged, see [[#Rissman--2020|Rissman et al. (2020)]] , that addresses integrated and interactive technical deep decarbonisation pathways for GHG-intense industrial sectors, and how they interact with the rest of the economy ( [[#Denis-Ryan--2016|Denis-Ryan et al. 2016]] ; [[#Åhman--2017|Åhman et al. 2017]] ; [[#Wesseling--2017|Wesseling et al. 2017]] ; [[#Axelson--2018|Axelson et al. 2018]] ; [[#Davis--2018|Davis et al. 2018]] ; [[#Bataille--2018a|Bataille et al. 2018a]] ; [[#Bataille--2020a|Bataille 2020a]] ). It is a common finding across this literature and a related scenario literature ( [[#Energy%20Transitions%20Commission--2018|Energy Transitions Commission 2018]] ; [[#Material%20Economics--2019|Material Economics 2019]] ; [[#UKCCC--2019a|UKCCC 2019a]] ,b; [[#IEA--2019b|IEA 2019b]] , 2020a; [[#CAT--2020|CAT 2020]] ; [[#IEA--2021a|IEA 2021a]] ) that deep decarbonisation of industry requires integrating all available options. There is no ‘silver bullet’ and so all behavioural and technological options have to be mobilised, with more emphasis required on the policy mechanisms necessary to engage a challenging transition in the coming decades in highly competitive, currently GHG-intense, price-sensitive sectors with long-lived capital stock ( [[#Wesseling--2017|Wesseling et al. 2017]] ; [[#Bataille--2018a|Bataille et al. 2018a]] ; [[#Bataille--2020a|Bataille 2020a]] ), discussed in the final section of this chapter.

While the strategies are not sequential and interact strongly, we discuss them in the order given. Reduced demand through reduced service demand and product intensity per service unit ( [[#Grubler--2018|Grubler et al. 2018]] ; [[#van%20Vuuren--2018|van Vuuren et al. 2018]] ) reduces the need for the next six strategies. Greater material efficiency (see earlier sections) reduces the need for the next five, and so on – see above.

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[[File:05f77a882b9df9c9f87fe340e319aa15 IPCC_AR6_WGIII_Figure_11_9.png]]

'''Figure 11.9 | Fully interactive, non-sequential strategies for decarbon''' '''ising industry.'''

Circular economy introduces itself throughout, but mainly at the front end when designing materials and processes to be more materially efficient, efficient in use, and easy to recycle, and at the back end, when a material or product’s services life has come to end, and it is time for recycling or sustainable disposal ( [[#Murray--2017|Murray et al. 2017]] ; [[#Korhonen--2018|Korhonen et al. 2018]] ). The entire chain’s potential will be maximised when these strategies are designed in ahead of time instead of considered on assembly, or as a retrofit ( [[#Allwood--2012|Allwood et al. 2012]] ; [[#Gonzalez%20Hernandez--2018a|Gonzalez Hernandez et al. 2018a]] ; [[#IEA--2019b|IEA 2019b]] ; [[#Material%20Economics--2019|Material Economics 2019]] ; [[#Bataille--2020a|Bataille 2020a]] ). For example, when designing a building: (i) Is the building shell, interior mass and ducting orientated for passive heating and cooling, and can the shell and roof have building-integrated solar PV or added easily, with hard-to-retrofit wiring already incorporated? (ii) Are steel and high-quality concrete only used where really needed (i.e., for shear, tension and compression strength), can sections be prefabricated off-site, can other materials be substituted, such as wood? (iii) Can the interior fittings be built with easy-to-recycle plastics or other sustainably disposable materials (e.g., wood)? (iv) Can this building potentially serve multiple purposes through its anticipated lifetime, are service conduits oversized and easy to access for retrofitting? (v) When it is time to be taken apart, can pieces be reused, and all componnents recycled at high purity levels, for example, can all the copper wiring be easily be found and removed, are the steel beams clearly tagged with their content? The answers to these questions will be very regionally and site specific, and require revision of educational curricula for the entire supply chain, as well as revision of building codes.

Energy efficiency is a critical strategy for net zero transitions and enabling clean electrification ( [[#IEA--2021a|IEA 2021a]] ). Improving the efficiency of energy services provision reduces the need for material intensive energy supply, energy storage, CCU and CCS infrastructure, and limits generation and transmission expansion to reduce an ever-higherdemand, with associated generation, transmission, and distribution losses. Using electricity efficiently can help reduces peak demand and the need for peaking plants (currently often powered by fossil fuels), and energy storage systems.

Electrification and final energy efficiency are deeply entangled, because switching to electricity from fossil fuels in most cases improves GJ for GJ end-use energy efficiency: resistance heaters are almost 100% efficient, heat pumps can be 300–400% efficient, induction melting can improve mixing and temperature control, and electric vehicle motors typically translate 90–95% of input electricity to motor drive in contrast to 35–45% for a large, modern internal combustion engine. Overall, the combined effect could be 40% lower global final energy demand assuming renewable electricity is used ( [[#Eyre--2021|Eyre 2021]] ).

There are potentially complicated physical and market fuel switching relationships between low-GHG electricity, bioliquids and gases, hydrogen, ammonia, and synthetic hydrocarbons constructed using CCU, with remaining CO 2 potentially being disposed of using CCS. Whether or not they compete for a wide range of end uses and primary demand needs will be regional and whether or not infrastructure is available to supply them. Regions with less than optimal renewable energy resources, or not sufficient to meet growing needs, could potentially indirectly import them as liquid or compressed hydrogen, ammonia or synthetic hydrocarbon feedstocks made in regions with abundant resources ( [[#Armijo--2020|Armijo and Philibert 2020]] ; [[#Bataille--2020a|Bataille 2020a]] ). Large-scale CCU and CCS applications need additional basic materials to build corresponding infrastructure and energy to operate it, thus reducing overall material and energy efficiencies.

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

'''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 across all mitigat''' '''ion strategies.'''

{| class="wikitable"
|-
! Sectors

! Demand control measures (DM)

! Materials efficiency (ME)

! Circular economy

! Energy efficiency

! Electrification, hydrogen and fuel switching

! CCU

! CCS

|-
| Architectural and engineering firms

| Build awareness on the material demand implications of e.g., building codes, urban planning and infrastructure.

| Education of designers, architects and engineers, etc.

Develop design tools. Map material flows.

| Design and build for e.g., repurpose, reuse and recycle. Improve transparency on volumes and flows.

| Maintain high expertise, knowledge sharing, transparency, and benchmarking.

| Support innovation.

Share best practice. Design for dynamic demand response for grid balancing.

| Develop allocation rules, monitoring and transparency.

Coordination and collaboration across sectors.

| Transparency, monitoring and labelling.

Coordination and collaboration for transport and disposal infrastructure.

|-
| Industry and service sector

| Digital solutions to reduce office space and travel. Service-oriented business models for lower product demand.

| Design for durability and light weight.

Minimise industry scrap.

| Design for reuse and recycling. Use recycled feedstock and develop industrial symbiosis.

| Maintain energy management systems.

| Develop and deploy new technologies in production, engage with lead markets.

| Develop new technologies.

Engage in new value chains and collaborations for sourcing carbon.

| Plan for CCS where possible and phase-out of non-retrofittable plants where necessary.

|-
| International bodies

| Best practice sharing.

Knowledge building on demand options.

| Progressivity in international standards (e.g., ISO).

| Transparency and regulation around products, waste handling, trade, and recycling.

| Maintain efforts for sharing good practice and knowledge.

| Coordinate innovation efforts, technology transfer, lead markets, and trade policies.

| Coordinate and develop accounting and standards. Ensure transparency.

| Align regulation to facilitate export, transport, and storage.

|-
| Regional and national government, and cities

| Reconsider spatial planning and regulation that has demand implications.

| Procurement guidelines and better indicators. Standards and building codes.

| Regulation on product design (e.g., Ecodesign Directive).

Collect material-flow data.

| Continue energy efficiency policies such as incentives, standards, labels, and disclosure requirements.

| R&amp;D and electricity infrastructure. Policy strategies for making investment viable (including carbon pricing instruments).

| Align regulation to facilitate implementation and ensure accountability for emissions.

| Develop regulation and make investment viable.

Resolve long-term liabilities.

|-
| Civil society and consumer organisations

| Information and advocacy related to social norms.

| Strengthen lobby efforts and awareness around e.g., planned obsolescence.

| Engage in standards, monitoring and transparency.

| Monitor progress.

| Information on embodied emissions. Assess renewable electricity and grid expansion.

| Develop standards and accounting rules.

| Ensure transparency and accountability.

|}

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