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

== 11.5 Industrial Infrastructure, Policy, and Sustainable Development Goal Contexts ==

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=== 11.5.1 Existing Industry Infrastructures ===

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Countries are at different stages of different economic development paths. Some are already industrialised, while developing and emerging economies are on earlier take-off stages or accelerated growth stages and have yet to build the basic infrastructure needed to allow for basic mobility, housing, sanitation, and other services (Section [[#_idTextAnchor013|11.2.3]] ). The available in-use stock of material per capita and in each country therefore differs significantly, and transition pathways will require a different mix of strategies, depending on each country’s material demand to build, maintain, and operate stock of long-lived assets. Industrialised economies have much greater opportunities for reusing and recycling materials, while emerging economies have greater opportunities to avoid carbon lock-in. The IEA projected that more than 90% of the additional 2050 production of key materials will originate in non-OECD countries ( [[#IEA--2017|IEA 2017]] ). As incomes rise in emerging economies, the industry sector will grow in tandem to meet the increased demand for the manufactured goods and raw materials essential for infrastructure development. The energy and feedstocks needed to support this growth are likely to constitute a large portion of the increase in the emerging economies’ GHG emissions in the future unless new low-carbon pathways are identified and promoted.

Emissions are typically categorised by the territory, subsector or group of technologies from which they emanate. An alternative subdivision is that between existing sources that will continue to generate emissions in the future, and those that are yet to be built ( [[#Erickson--2015|Erickson et al. 2015]] ). The rate of emissions from existing assets will eventually tend to zero, but in a timeframe that is relevant to existing climate and energy goals, the cumulative contribution to emissions from existing infrastructure and equipment is likely to be substantial. Aside from the magnitude of the contribution, the distinction between emissions from existing and forthcoming assets is instructive because of the difference in approach to mitigation that may be necessary or desirable in each instance to avoid getting locked into decades of highly carbon-intensive operations ( [[#Lecocq--2014|Lecocq and Shalizi 2014]] ).

Details of the methodologies to assess ‘carbon lock-in’ or ‘committed emissions’ differ across studies but the core components of the approaches adopted are common to each: an account of the existing level of emissions for the scope being assessed is established; this level is projected forward with a stylised decay function that is informed by assessments of the current age and typical lifetimes of the underlying assets. From this, a cumulative emissions estimate is calculated. The future emissions intensity of the operated assets is usually assumed to remain constant, implying that nothing is done to retrofit with mitigating technologies (e.g., carbon capture) or alter the way in which the plant is operated (e.g., switching to an alternative fuel or feedstock). While the quantities of emissions derived are often referred to as ‘committed’ or ‘locked-in’, their occurrence is of course dependent on a suite of economic, technology and policy developments that are highly uncertain.

Data on the current age profile and typical lifetimes of emissions-intensive industrial equipment are difficult to procure and verify and most of the studies conducted in this area contain little detail on the global industrial sector. Two recent studies are exceptions, both of which cover the global energy system, but contain detailed and novel analysis on the industrial sector ( [[#Tong--2019|Tong et al. 2019]] ; [[#IEA--2020a|IEA 2020a]] ). [[#Tong--2019|Tong et al. (2019)]] use unit-level data from China’s Ministry of Ecology and Environment to obtain a more robust estimate of the age profile of existing capacity in the cement and iron and steel sectors in the country. The [[#IEA--2020a|IEA (2020a)]] uses proprietary global capacity datasets for the iron and steel, cement and chemicals sectors, and historic energy consumption data for the remaining industry sectors as a proxy for the rate of historic capacity build-up.

Both studies come to similar estimates on the average age of cement plants and blast furnaces in China of around 10–12 years old, which are the figures for which they have overlapping coverage. Both studies also use the same assumption of the typical lifetime of assets in these sectors of 40 years, whereas the [[#IEA--2020a|IEA (2020a)]] study uses 30 years for chemical sector assets and 25 years for other industrial sectors. The studies come to differing estimates of cumulative emissions by 2050 from the industry sector; 196 GtCO 2 in the [[#IEA--2020a|IEA (2020a)]] study, and 162 GtCO 2 in the [[#Tong--2019|Tong et al. (2019)]] study. This difference is attributable to a differing scope of emissions, with the [[#IEA--2020a|IEA (2020a)]] study including industrial process emissions (which for the cement sector in particular are substantial) in addition to the energy-related emissions quantities accounted for in the [[#Tong--2019|Tong et al. (2019)]] study. After correcting for this difference in scope, the emissions estimates compare favourably.

The [[#IEA--2020a|IEA (2020a)]] study provides supplementary analysis for the industry sector, examining the impact of considering investment cycles alongside the typical lifetimes assumed in its core analysis of emissions from existing industrial assets. For three heavy industry sectors – iron and steel, cement, and chemicals – the decay function applied to emissions from existing assets is re-simulated using a 25-year investment cycle assumption ( [[#_idTextAnchor032|Figure 11.14]] ). This is 15 years shorter than the typical lifetimes assumed for assets in the iron and steel and cement sectors, and five years shorter than that considered for the chemical sector. The shorter timeframe for the investment cycle is a simplified way of representing the intermediate investments that are made to extend the life of a plant, such as the re-lining of a blast furnace, which can occur multiple times during the lifetime of an installation. These investments can often be similar in magnitude to that of replacing the installation, and they represent key points for intervention to reduce emissions. The findings of this supplementary analysis are that around 40%, or 60 GtCO 2 , could be avoided by 2050 if near-zero emissions options are available to replace this capacity, or units are retired, retrofitted or refurbished in a way that significantly mitigates emissions (e.g., retrofitting carbon capture, or fuel or process switching to utilise bioenergy or low-carbon hydrogen).

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[[File:c77205f33b33206645f8eda5cc4d4076 IPCC_AR6_WGIII_Figure_11_14.png]]

'''Figure 11.14 |CO''' 2 '''emissions from existing heavy industrial assets in the NZE.''' Source: International Energy Agency (2021), Net Zero by 2050, IEA, Paris.

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

The cost of retrofitting or retiring a plant before the end of its lifetime depends on plant-specific conditions as well as a range of economic, technology and policy developments. For industrial decarbonisation it may be a greater challenge to accelerate the development and deployment of zero-emission technologies and systems than to handle the economic costs of retiring existing assets before end of life. The ‘lock-in’ also goes beyond the lifetime of key process units, such as blast furnaces and crackers, since they are typically part of large integrated plants or clusters with industrial symbiosis, as well as infrastructures with feedstock storage, ports, and pipelines. Individual industrial plants are often just a small part of a complex network of many facilities in an industrial supply chain. In that sense, current assessments of ‘carbon lock-in’ rely on simplifications due to the high the complexity of industry.

Conditions are also subsector and context specific in terms of mitigation options, industry structures, markets, value chains and geographical location. For example, the hydrogen steel-making joint venture in Sweden involves three different companies headquartered in Sweden (in mining, electricity and steel-making, respectively), two of which are state-owned, with a shared vision and access to iron ore, fossil-free electricity and high-end steel markets ( [[#Kushnir--2020|Kushnir et al. 2020]] ). In contrast, chemical clusters may consist of several organisations that are subsidiaries to large multinational corporations with headquarters across the world, that also compete in different markets. Even in the presence of a local vision for sustainability this makes it difficult to engage in formalised collaboration or get support from headquarters ( [[#Bauer--2019|Bauer and Fuenfschilling 2019]] ).

Furthermore, it is relevant to consider also institutional and behavioural lock-in ( [[#Seto--2016|Seto et al. 2016]] ). On one side, existing high-emitting practices may be favoured through formal and informal institutions (e.g., regulations and social norms or expectations, respectively), for example, around building construction and food packaging. On the other side, mitigation options may face corresponding institutional barriers. Examples include how cars are conventionally scrapped (i.e., crushed, leading to copper contamination of steel) rather than being dismantled, or slow permitting procedures for new infrastructure and industrial installations for reducing emissions.

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=== 11.5.2 Current Industrial and Broader Policy Context ===

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The basic motivation for industrial policy historically has been economic development and wealth creation. Industrial policy can be progressive and promote new developments or be protective to help infant or declining industries. It may also involve the phase-out of industries, including efforts to retrain workers and create new jobs. Industrial policy is not one policy intervention but rather the combined effects of many policy instruments that are coordinated towards an industrial goal. Industrial policies can be classified as being either vertical or horizontal depending on whether singular sectors or technologies are targeted (e.g., through R&amp;D, tariffs and subsidies) or the whole economy (e.g., education, infrastructure, and general tax policies). The horizontal policies are not always thought of as industrial policy, although taking a broad view, including policy coordination and institution building, is important for industrial policy to be effective (see e.g., [[#Andreoni--2019|Andreoni and Chang 2019]] ).

In the past ten years there has been increasing interest and attention to industrial policy. One driver is the desire to retain industry or re-industrialise in regions within Europe and North America where industry has a long record of declining shares of GDP. The need for economic growth and poverty eradication is a key driver in developing countries. An important aspect is the need to meet the ‘dual challenge of creating wealth for a growing population while staying within planetary boundaries’ ( [[#Altenburg--2017|Altenburg and Assman 2017]] ). The need for industrial policy that supports environmental goals and green growth has been analysed by [[#Rodrik--2014|Rodrik (2014)]] ; [[#Aiginger--2014|Aiginger (2014)]] ; [[#Warwick--2013|Warwick (2013)]] ; and [[#Busch--2018|Busch et al. (2018)]] . Similar ideas are taken up in OECD reports on green growth ( [[#OECD--2011|OECD 2011]] ) and system innovation ( [[#OECD--2015|OECD 2015]] ). However, these approaches to green industrial policy and innovation tend to focus on opportunities for manufacturing industries to develop through new markets for cleaner technologies. They rarely include explicit attention to the necessity of zero emissions and the profound changes in production, use and recycling of basic materials that this entails. This may also involve the phase-out or repurposing of industries that currently rely on fossil fuels and feedstock.

The policy implications of zero emissions for heavy industries are relatively unexplored, although some analyses in this direction are available (e.g., [[#Åhman--2017|Åhman et al. 2017]] ; [[#Philibert--2017a|Philibert 2017a]] ; [[#Wesseling--2017|Wesseling et al. 2017]] ; [[#Bataille--2018a|Bataille et al. 2018a]] ; [[#Wyns--2019|Wyns et al. 2019]] ; [[#Bataille--2020a|Bataille 2020a]] ; [[#Fan--2021|Fan and Friedmann 2021]] ). For industry, there has been a long time focus on energy efficiency policies through voluntary and negotiated agreements, energy management and audit schemes, and various programmes targeting industry ( [[#Fischedick--2014|Fischedick et al. 2014]] a). Since AR5, interest in circular economy policies has increased and they have become more prevalent across regions and countries, including the EU, China, USA., Japan and Brazil (e.g., [[#McDowall--2017|McDowall et al. 2017]] ; [[#Ranta--2018|Ranta et al. 2018]] ; [[#Geng--2019|Geng et al. 2019]] ). For electrification and CCUS, efforts are nascent and mainly focused on technology development and demonstrations. Policies for demand reduction and materials efficiency are still relatively unexplored (e.g., [[#Pollitt--2020|Pollitt et al. 2020]] and [[#IEA--2019b|IEA 2019b]] ). Since zero emissions in industry is a new governance challenge it will be important to build awareness and institutional capacity in industrialised as well as developing countries.

In the context of climate change policy, it is fair to say that industry has so far been sheltered from the increasing costs that decarbonisation may entail. This is particularly true for the energy- and emissions-intensive industries where cost increases and lost competitiveness may lead to carbon leakage (i.e., that industry relocates to regions with less stringent climate policies). Heavy industries typically pay no or very low energy taxes and where carbon pricing exists (e.g., in the European Trading Scheme) they are sheltered through free allocation of emission permits and potentially compensated for resulting electricity price increases. For example, [[#Okereke--2012|Okereke and McDaniels (2012)]] show how the European steel industry was successful in avoiding cost increases and how information asymmetry in the policy process was important for that purpose.

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=== 11.5.3 Co-benefits of Mitigation Strategies and Sustainable Development Goals ===

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The deployment of climate change mitigation strategies is primarily influenced by its costs and potential, but also by other broader sustainable development factors such as the Sustainable Development Goals (SDGs). Mitigation actions therefore are to be considered through the prism of impacts on achieving other economic, social and environmental goals. Those impacts are classified as co-benefits when they are positive or as risk when they are negative. Co-benefits can serve as additional drivers, while risks can inhibit the deployment of available mitigation options. Actions taken to mitigate climate change have direct and indirect interactions with SDGs, both positive (synergies) or negative (trade-offs) ( [[#Fuso%20Nerini--2019|Fuso Nerini et al. 2019]] ).

Given the wide range of stakeholders involved in climate actions and their (often contradictory) interests and priorities, the nature of co-benefits and risk can affect decision-making processes and the behaviour of stakeholders ( [[#Labella--2020|Labella et al. 2020]] ). Co-benefits form an important driver supporting the adoption of mitigation strategies, yet are commonly overlooked in policymaking. [[#Karlsson--2020|Karlsson et al. (2020)]] , based on a review of 239 peer-reviewed articles concluded that diverse co-benefit categories, including air, soil and water quality, diet, physical activity, biodiversity, economic performance, and energy security, are prevalent in the literature.

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==== 11.5.3.1 Sustainable Development Goals Co-benefits Through Material Efficiency and Demand Reduction ====

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Material efficiency, an important mitigation option (SDG 13, climate action) for heavy industries, is yet to be fully acknowledged and leveraged ( [[#Gonzalez%20Hernandez--2018a|Gonzalez Hernandez et al. 2018a]] ; [[#Sudmant--2018|Sudmant et al. 2018]] ; [[#Dawkins--2019|Dawkins et al. 2019]] ). Material efficiency directly addresses SDG 12 (responsible production and consumption) but also provides opportunities to reduce the pressures and impacts on environmental systems (SDG 6, clean water and sanitation) ( [[#Olivetti--2018|Olivetti and Cullen 2018]] ). Exploiting material efficiency usually requires new business models and provides potential co-benefits of increased employment and economic opportunities (SDG 8, decent work and economic growth).

Material efficiency also provides co-benefits through infrastructural development (SDG 9, industry, innovation and infrastructure) ( [[#Mathews--2018|Mathews et al. 2018]] ) to support the wide range of potential material efficiency strategies including light-weighting, reusing, remanufacturing, recycling, diverting scrap, extending product lives, using products more intensely, improving process yields, and substituting materials ( [[#Allwood--2011|Allwood et al. 2011]] ). [[#Worrell--2016|Worrell et al. (2016)]] also emphasises how material efficiency improvements, in addition to limiting the impacts of climate change help deliver sustainable production and consumption co-benefits through environmental stewardship. [[#Binder--2017|Binder and Blankenberg (2017)]] and [[#Dhandra--2019|Dhandra (2019)]] show that sustainable consumption is positively related to life satisfaction and subjective well-being (SDG 3), and [[#Guillen-Royo--2019|Guillen-Royo (2019)]] adds positive associations with happiness and life satisfaction.

The reduction in excessive consumption and demand for products and services generates a reduction in post-consumption waste and so enhances clear water and sanitation (SDG 6) ( [[#Govindan--2018|Govindan 2018]] ; [[#Minelgaitė--2019|Minelgaitė and Liobikienė 2019]] ), and reduces waste along product supply chains and lifecycles (SDG 12) ( [[#Genovese--2017|Genovese et al. 2017]] ; UNSD 2020). At the risk side there are possible reductions of employment, incomes, sales taxes from the material extraction and processing activities, considered as excessive for sustainable consumption ( [[#Thomas--2003|Thomas 2003]] ).

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==== 11.5.3.2 Sustainable Development Goals Co-benefits From Circular Economy and Industrial Waste ====

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While the circular economy concept first emerged in the context of waste avoidance, resource depletion, closed-loop recycling, etc., it has now evolved as a tool for a broader systemic national policy due to its potential wider benefits ( [[#Geng--2013|Geng et al. 2013]] ). It represents new circular business models that encourage design for reuse and to improve material recovery and recycling, and so represents a departure from the traditional linear production and consumption systems (with landfilling at the end), with a wide range of potential co-benefits to a wide range of SDGs ( [[#Guo--2016|Guo et al. 2016]] ; [[#Genovese--2017|Genovese et al. 2017]] ; [[#Schroeder--2019|Schroeder et al. 2019]] ; UNSD 2020).

[[#Genovese--2017|Genovese et al. (2017)]] articulates the advantages from an environmental and responsible consumption and production point of view (SDG 12). Many studies have outlined new business models based on the circular economy that foster sustainable economic growth and the generation of new jobs (SDG 8) ( [[#Antikainen--2016|Antikainen and Valkokari 2016]] ), as well as global competitiveness and innovation in business and the industrial sector ( [[#Pieroni--2019|Pieroni et al. 2019]] ), such as its potential synergies with industry 4.0 ( [[#Garcia-Muiña--2018|Garcia-Muiña et al. 2018]] ).

Following a review of the literature, [[#Schroeder--2019|Schroeder et al. (2019)]] identified linkages between circular economy practices and SDGs based on a relationship scoring system, and highlighted that such SDGs as SDG 6 (clean water and sanitation), SDG 7 (affordable and clean energy), SDG 8 (decent work and economic growth), SDG 12 (responsible consumption and production), and SDG 15 (life on land) all strongly benefit from circular economy practices. With the potential to impact on all stages of the value chain (micro, meso and macro level of the economy), circular economy has also been identified as a key industrial strategy to managing waste across sectors.

[[#Chatziaras--2016|Chatziaras et al. (2016)]] highlights the co-benefit to SDG 7 (affordable and clean energy) resulting from waste-derived fuel for the cement industry. Through the management of industrial waste using circular economy practices, studies such as [[#Geng--2012|Geng et al. (2012)]] and [[#Bonato--2017|Bonato and Orsini (2017)]] have pointed out co-benefits to SDGs beyond clear environmental and economic benefits, highlighting how it also benefits SDG 3 and 11 through improved social relations between industrial sectors and local societies, and improved public environmental awareness and public health levels.

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==== 11.5.3.3 Sustainable Development Goals Co-benefits From Energy Efficiency ====

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Beyond the very direct links between energy and climate change, reliable, clean, and affordable energy (SDG 7) presents a cross-cutting issue, central to all SDGs and fundamental to development, and energy efficiency enables its provision by reducing the direct supply and necessary infrastructure required. Energy efficiency improvements can be delivered through multiple technical options and tested policies, delivering energy and resource savings simultaneously with other socio-economic and environmental co-benefits. At the macro level, this includes enhancement of energy security (SDG 16, peace, justice and strong institutions) delivered through clean low-carbon energy systems ( [[#Fankhauser--2018|Fankhauser and Jotzo 2018]] ). Much of the literature, including [[#Sari--2016|Sari and Akkaya (2016)]] , [[#Allan--2017|Allan et al. (2017)]] and [[#Garrett-Peltier--2017|Garrett-Peltier (2017)]] , points out that energy efficiency improvements deliver superior employment opportunities (SDG 8 – decent work and economic growth), while a limited number of studies have reported that it can negatively impact employment in fuel supply sectors ( [[#Costantini--2018|Costantini et al. 2018]] ).

Many studies report that energy efficiency improvements are essential for supporting overall economic growth, contributing to positive changes in multi-factor productivity (SDGs 8 and 9 – decent work and economic growth and industry, innovation, and infrastructure) ( [[#Lambert--2014|Lambert et al. 2014]] ; [[#Bataille--2017|Bataille and Melton 2017]] ; [[#Rajbhandari--2018|Rajbhandari and Zhang 2018]] ; [[#Bashmakov--2019|Bashmakov 2019]] ; [[#Stern--2019|Stern 2019]] ) through industrial innovation (SDG 9) ( [[#Kang--2016|Kang and Lee 2016]] ), with some dissent (e.g., [[#Mahmood--2018|Mahmood and Ahmad 2018]] ). Improved energy efficiency against a background of growing energy prices helps industrial plants stay competitive ( [[#Bashmakov--2018|Bashmakov and Myshak 2018]] ). Energy efficiency allows continued economic growth under strong environmental regulation. Given that energy efficiency measures reduce the combustion of fossil fuels it leads to reduced air pollution at industrial sites ( [[#Williams--2012|Williams et al. 2012]] ) and better indoor comfort at working places.

Since less energy supply infrastructure is needed in cities and less energy is needed to produce materials such as cement and concrete, and metals, energy efficiency indirectly supports ‘sustainable cities and communities’ (SDG 11) ( [[#Di%20Foggia--2018|Di Foggia 2018]] ). In addition, energy efficiency in industry reflects achievements in meeting SDG 12 (responsible consumption and production).

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==== 11.5.3.4 Sustainable Development Goals Co-benefits From Electrification and Fuel Switching ====

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A key, generally underappreciated SDG benefit of electrification is improved urban and indoor air quality (at working places as well) and associated health benefits (SDG 3) from clean electrification (SDG 7) of industrial facilities ( [[#IEA--2016|IEA 2016]] ). With energy being such an important cross-cutting issue to sustainable development, some SDGs, such as SDGs 1, 3, 4 and 5 ( [[#Harmelink--2018|Harmelink et al. 2018]] ) are co-beneficiaries to using electrification and fuel switching as a climate action mitigation option.

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==== 11.5.3.5 Sustainable Development Goals Co-benefits from Carbon Capture and Utilisation, and Carbon Capture and Storage ====

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CCU and CCS have been identified as playing key roles in the transition of industry to net zero. Advancements in the development and deployment of both CCS and CCU foster climate action (SDG 13). Other co-benefits for CCS include control of non-CO 2 pollutants (SDG 3), direct foreign investment and know-how (SDG 9), enhanced oil recovery from existing resources, and diversified employment prospects and skills (SDG 8) ( [[#Bonner--2017|Bonner 2017]] ). For CCU, the main co-benefit related contributions are expected within the context of energy transition processes, and in societal advancements that are linked to technological progress ( [[#Olfe-Kräutlein--2020|Olfe-Kräutlein 2020]] ). Therefore, the expectations are that the deployment of CCU technologies would have least potential for meeting the SDG targets relating to society/people, compared with the anticipated contributions to the pillars of ecology and economy.

These mitigation options carry a large number of risks as well. The high cost of the capture and storage process not only limit the technology penetration, but also make energy and products more expensive (risk to SDG 7), potential leaks from undersea or underground CO 2 storages carries risks for achieving SDGs 6, 14 and 15. While there are economic costs involved with the deployment of CCS and CCU ( [[#Bataille--2018a|Bataille et al. 2018a]] ), there are also significant economic and developmental costs associated with taking no action, because of the potential negative impact of climate change. CCS and CCU have been argued as providing public good ( [[#Bergstrom--2017|Bergstrom and Ty 2017]] ) and co-benefits to key SDGs ( [[#Schipper--2011|Schipper et al. 2011]] ). On the other hand, [[#Fan--2018|Fan et al. (2018)]] among others have noted the potential lock-in of existing energy structures due to CCS. Refer to Table 17.1 for CCS and CCU co-benefits with respect to other sector chapters.

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