Editing IPCC:AR6/WGIII/Chapter-2 (section)

== 2.7 Emissions Associated With Existing and Planned Long-lived Infrastructure ==

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=== 2.7.1 Introduction: Clarification of Concepts ===

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Carbon lock-in can be understood as inertia in a system that limits the rate of transformation by a path-dependent process ( [[#Seto--2016|Seto et al. 2016]] ). For example, long lifetimes of infrastructures such as power plants, roads, buildings or industrial plants may influence the rate of transformation substantially and lock societies into carbon-intensive lifestyles and practices for many decades ( [[#Unruh--2000|Unruh 2000]] , 2002; [[#Unruh--2006|Unruh and Carrillo-Hermosilla 2006]] ; [[#Grubler--2012|Grubler 2012]] ; [[#Seto--2016|Seto et al. 2016]] ; [[#Sovacool--2016|Sovacool 2016]] ). Infrastructure stock evolution depends on technological and economic factors, but also on institutional and behavioural ones that are often mutually reinforcing. That is, physical infrastructure such as the built environment of urban areas can shape people’s behaviour and practices, which in turn change the demand for such infrastructure and lock-in energy demand patterns ( [[#Banister--1997|Banister et al. 1997]] ; [[#Makido--2012|Makido et al. 2012]] ; [[#Creutzig--2016|Creutzig et al. 2016]] ; [[#Seto--2016|Seto et al. 2016]] ; [[#Shove--2018|Shove and Trentmann 2018]] ).

There is a broad literature on carbon lock-in related to infrastructure that has analysed different geographical scales and sectors, with a strong focus on the power sector (Fisch-Romito et al. 2020). Available quantifications differ in the time frames of analysis that can be classified as backward-looking, static for a given year, or forward-looking using scenarios (Fisch-Romito et al. 2020). Quantifications also differ in the indicators used to describe carbon lock-in. Literature has assessed how delays in climate policy affect the evolution of fossil-fuel infrastructure stock in the short term ( [[#Bertram--2015|Bertram et al. 2015]] ; [[#Kefford--2018|Kefford et al. 2018]] ; [[#McGlade--2018|McGlade et al. 2018]] ), overall mitigation costs ( [[#Riahi--2015|Riahi et al. 2015]] ; [[#Luderer--2016|Luderer et al. 2016]] ), or the transition risks from premature retirements or underutilisation of existing assets ( [[#Iyer--2015|Iyer et al. 2015]] ; [[#Johnson--2015|Johnson et al. 2015]] ; [[#Lane--2016|Lane et al. 2016]] ; [[#Luderer--2016|Luderer et al. 2016]] ; [[#Farfan--2017|Farfan and Breyer 2017]] ; [[#van%20Soest--2017|van Soest et al. 2017]] ; [[#Kefford--2018|Kefford et al. 2018]] ; [[#Cui--2019|Cui et al. 2019]] ; [[#Fofrich--2020|Fofrich et al. 2020]] ; [[#Malik--2020|Malik et al. 2020]] ; H. [[#Wang--2020|Wang et al. 2020]] ; [[#Pradhan--2021|Pradhan et al. 2021]] ). Only a few authors have relied on indicators related to institutional factors such as technology scale or employment ( [[#Erickson--2015|Erickson et al. 2015]] ; [[#Spencer--2018|Spencer et al. 2018]] ). Complementary literature has explored how the sheer size of the world’s fossil fuel reserves (and resources) and owners’ financial interests could contribute to supply-side dynamics that sustain the use of fossil fuels ( [[#Jewell--2013|Jewell et al. 2013]] ; Jakob and Hilaire 2015; [[#McGlade--2015|McGlade and Ekins 2015]] ; [[#Bauer--2016|Bauer et al. 2016]] ; [[#Heede--2016|Heede and Oreskes 2016]] ; [[#Welsby--2021|Welsby et al. 2021]] ).

One way of quantifying potential carbon lock-in is to estimate the future CO 2 emissions from existing and planned infrastructure ( [[#Davis--2010|Davis et al. 2010]] ; [[#Davis--2014|Davis and Socolow 2014]] ) based on historic patterns of use and decommissioning. Such estimates focus on CO 2 emissions from operating infrastructure and do not comprise any upstream or downstream emissions across the lifecycle, which are provided elsewhere in the literature ( [[#Müller--2013|Müller et al. 2013]] ; [[#Creutzig--2016|Creutzig et al. 2016]] ; [[#Krausmann--2020|Krausmann et al. 2020]] ; [[#Fisch-Romito--2021|Fisch-Romito 2021]] ). Estimates tend to focus on energy, while other areas, such as the agricultural sector are usually not covered. Another strand of literature quantifies lock-in by estimating fossil-fuel related CO 2 emissions that are hard to avoid in future scenarios using integrated assessment models (IAMs) ( [[#Kriegler--2018b|Kriegler et al. 2018b]] ; [[#Luderer--2018|Luderer et al. 2018]] ). The remainder of this chapter will assess potential carbon lock-in through those two related strands of literature.

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=== 2.7.2 Estimates of Future CO 2 Emissions From Long-lived Infrastructures ===

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Table 2.6 summarises studies that apply an accounting approach based on plant-level data to quantify future CO 2 emissions from long-lived fossil fuel infrastructure ( [[#Davis--2010|Davis et al. 2010]] ; [[#Davis--2014|Davis and Socolow 2014]] ; [[#Rozenberg--2015|Rozenberg et al. 2015]] ; [[#Edenhofer--2018|Edenhofer et al. 2018]] ; [[#Pfeiffer--2018|Pfeiffer et al. 2018]] ; [[#Cui--2019|Cui et al. 2019]] ; [[#Smith--2019|Smith et al. 2019]] ; [[#Tong--2019|Tong et al. 2019]] ; [[#Pradhan--2021|Pradhan et al. 2021]] ). Differences between studies arise in the scope of the infrastructure covered (including resolution), the inclusion of new infrastructure proposals, the exact estimation methodology applied as well as their assessments of uncertainties. Other studies provide analysis with a sectoral focus ( [[#Bullock--2020|Bullock et al. 2020]] ; [[#Vogl--2021|Vogl et al. 2021]] ) or with a regional focus on the power sector ( [[#Shearer--2017|Shearer et al. 2017]] , 2020; [[#González-Mahecha--2019|González-Mahecha et al. 2019]] ; [[#Grubert--2020|Grubert 2020]] ; [[#Tao--2020|Tao et al. 2020]] ).

Assuming variations in historic patterns of use and decommissioning, comprehensive estimates of cumulative future CO 2 emissions from ''current'' fossil fuel infrastructures are 720 (550–910) GtCO 2 ( [[#Smith--2019|Smith et al. 2019]] ) and 660 (460–890) ( ''high confidence'' ) ( [[#Tong--2019|Tong et al. 2019]] ) (Table 2.6 and Figure 2.26). This is about the same size as the overall cumulative net CO 2 emissions until reaching net zero CO 2 of 510 (330–710) Gt in pathways that limit warming to 1.5°C with no or limited overshoot (Chapter 3). About 50% of cumulative future CO 2 emissions from ''current'' fossil fuel infrastructures come from the power sector and 70% of these (or about 40% of the total) are from coal plants only. Like global annual CO 2 emissions ( [[#Friedlingstein--2020|Friedlingstein et al. 2020]] ; [[#Peters--2020|Peters et al. 2020]] ), future CO 2 emissions from fossil fuel infrastructures have increased over time – that is, future CO 2 emissions from fossil fuel infrastructure additions in a given year still outgrow ‘savings’ from infrastructure retirements ( [[#Davis--2014|Davis and Socolow 2014]] ; [[#Tong--2019|Tong et al. 2019]] ). This could add further inertia to the system as it may require more and faster retirement of fossil-fuel based infrastructures later, and lead to higher costs for meeting climate goals (e.g., [[#Bertram--2015|Bertram et al. 2015]] ; [[#Johnson--2015|Johnson et al. 2015]] ).

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[[File:6a59e082f68aa72e46afe7da590c9fff IPCC_AR6_WGIII_Figure_2_26.png]]

'''Figure 2.26''' '''|''' '''Future CO''' 2 '''emissions from existing and currently planned fossil fuel infrastructure in the context of Paris carbon budgets in GtCO''' 2 '''based on historic patterns of infrastructure lifetimes and capacity utilisation.''' Future CO 2 emissions estimates of existing infrastructure for the electricity sector as well as all other sectors (industry, transport, buildings, other fossil fuel infrastructures) and of proposed infrastructures for coal power as well as gas and oil power. Grey bars on the right depict the range (5th–95th percentile) in overall cumulative net CO 2 emissions until reaching net zero CO 2 in pathways that limit warming to 1.5°C with no or limited overshoot (1.5°C scenarios), and in pathways that limit warming to 2°C (&lt;67%) (2°C scenarios). Source: based on [[#Edenhofer--2018|Edenhofer et al. (2018)]] and [[#Tong--2019|Tong et al. (2019)]] .

Estimates of total cumulative future CO 2 commitments from ''proposed infrastructure'' focus only on the power sector due to data availability (Table 2.6 and Figure 2.26). Infrastructure proposals can be at various stages of development involving very different probabilities of implementation. About one-third of the currently proposed projects are more probable as they are already under construction ( [[#Cui--2019|Cui et al. 2019]] ). [[#Pfeiffer--2018|Pfeiffer et al. (2018)]] and [[#Tong--2019|Tong et al. (2019)]] assess the cumulated CO 2 emissions from proposed infrastructure in the entire power sector at 270 GtCO 2 and 190 GtCO 2 respectively. Estimates of CO 2 emissions implications for new coal power infrastructure plans are more frequent ( [[#Edenhofer--2018|Edenhofer et al. 2018]] ; [[#Pfeiffer--2018|Pfeiffer et al. 2018]] ; [[#Cui--2019|Cui et al. 2019]] ; [[#Tong--2019|Tong et al. 2019]] ) ranging between 100 and 210 GtCO 2 . Differences across estimates of future CO 2 emissions from proposed power infrastructure mostly reflect substantial cancellations of coal infrastructure proposals in 2017 and 2018 ( [[#Tong--2019|Tong et al. 2019]] ).

The global estimate of future CO 2 emissions from ''current and planned'' fossil-fuel infrastructures is 850 (600–1100) GtCO 2 ( [[#Tong--2019|Tong et al. 2019]] ). This already exceeds total cumulative net CO 2 emissions in pathways that limit warming to 1.5°C with no or limited overshoot (see above). It is about the same size as the total cumulative net CO 2 emissions of 890 (640–1160) GtCO 2 from pathways that limit warming to 2°C (&lt;67%) (Chapter 3). Hence, cumulative net CO 2 emissions to limit warming to 2°C (&lt;67%) or lower could already be exhausted by current and planned fossil fuel infrastructure ( ''high confidence'' ) even though this estimate only covers a fraction of all infrastructure developments over the 21st century as present in mitigation pathways, does not cover all sectors (e.g., AFOLU) and does not include currently infrastructure development plans in transport, buildings, and industry due to a lack of data.

Hence, the Paris climate goals could move out of reach unless there are dedicated efforts for early decommissioning, and reduced utilisation of existing fossil fuel infrastructures, cancellation of plans for new fossil fuel infrastructures, or compensation efforts by removing some of the CO 2 emissions from the atmosphere ( [[#Cui--2019|Cui et al. 2019]] ; [[#Smith--2019|Smith et al. 2019]] ; [[#Tong--2019|Tong et al. 2019]] ; [[#Pradhan--2021|Pradhan et al. 2021]] ). For example, [[#Fofrich--2020|Fofrich et al. (2020)]] suggest in a multi-model study that coal and gas power infrastructure would need to be retired 30 (19–34) and 24 (21–26) years earlier than the historical averages of 39 and 36 years when following 1.5°C pathways and 23 (11–33) and 19 (11–16) years earlier when following 2°C pathways. [[#Cui--2019|Cui et al. (2019)]] arrive at more conservative estimates for coal power plants, but only consider the existing and currently proposed capacity. Premature retirement of power plants pledged by members of the Powering Past Coal Alliance would cut emissions by 1.6 GtCO 2 , which is 150 times less than future CO 2 emissions from existing coal power plants ( [[#Jewell--2019|Jewell et al. 2019]] ).

Few quantifications of carbon lock-in from urban infrastructure, in particular urban form, have been attempted, in part because they also relate to behaviours that are closely tied to routines and norms that co-evolve with ‘hard infrastructures’ and technologies, as well as ‘soft infrastructure‘ such as social networks and markets ( [[#Seto--2016|Seto et al. 2016]] ). There are some notable exceptions providing early attempts ( [[#Guivarch--2011|Guivarch and Hallegatte 2011]] ; [[#Driscoll--2014|Driscoll 2014]] ; Seto et al.2014; Lucon et al. 2014; [[#Erickson--2015|Erickson and Tempest 2015]] ; [[#Creutzig--2016|Creutzig et al. 2016]] ). [[#Creutzig--2016|Creutzig et al. (2016)]] attempt a synthesis of this literature and estimate the total cumulative future CO 2 emissions from existing urban infrastructure at 210 Gt, and from new infrastructures at 495 Gt for the period 2010–2030.

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=== 2.7.3 Synthesis – Comparison with Estimates of Residual Fossil Fuel CO 2 Emissions ===

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A complementary strand of literature uses IAMs to assess the cumulative gross amount of unabated CO 2 emissions from fossil fuels across decarbonisation pathways that are not removed from the system, even under strong (short- and long-term) climate policy ambitions. Lower bound estimates for such a minimum amount of unabated residual CO 2 emissions across the 21st century that is not removed from the system, even under very ambitious climate policy assumptions, may be around 600–700 GtCO 2 ( [[#Kriegler--2018b|Kriegler et al. 2018b]] ). This range increases to 650–1800 GtCO 2 (Table 2.7) as soon as a broader set of policy assumptions are considered, including delayed action in scenarios that limit warming to 1.5°C and 2°C respectively ( [[#Luderer--2018|Luderer et al. 2018]] ).

Notably, the lower end of residual fossil fuel emissions in IAM scenarios ( [[#Luderer--2018|Luderer et al. 2018]] ) is remarkably similar to global estimates from the accounting studies of the previous section, as shown in Table 2.6. Yet, there are important conceptual and interpretative differences that are also reflected in the very different distribution of reported future CO 2 emissions attached to current and future fossil fuel infrastructures (Table 2.7). Accounting studies start from granular, plant-based data for existing fossil fuel infrastructure and make statements about their future CO 2 emissions, assuming variations of historic patterns of use and decommissioning. Expansions to the future are limited to proposals for new infrastructures that we know of today. Scenario studies quantifying residual fossil fuel emissions start from aggregate infrastructure descriptions, but dynamically update those through new investment decisions in each time step across the 21st century based on the development of energy and energy service demands, as well as technology availability, guided by defined climate policy goals (or their absence).

In accounting studies, estimates of future CO 2 emissions from current fossil fuel infrastructures are dominated by the power sector with its large fossil fuel capacities. In contrast, scenario studies highlight residual emissions from non-electric energy – particularly in the transport and industry sectors. Fossil-fuel infrastructure in the power sector can be much more easily retired than in those sectors, where there are fewer and more costly alternatives. IAMs therefore account for continued investments into fossil-based energy technologies in areas with limited decarbonisation potential, such as some areas of transportation (in particular aviation, shipping and road-based freight) or some industrial processes (such as cement production or feedstocks for chemicals). This explains the key discrepancies observable in Table 2.7. Therefore, our overall assessment of these available lines of evidence strongly emphasises the importance of decommissioning, reduced utilisation of existing power sector infrastructure, as well as continued cancellation of new power sector infrastructures in order to limit warming to well below 2°C ( ''high confidence'' ) ( [[#Kriegler--2018b|Kriegler et al. 2018b]] ; [[#Luderer--2018|Luderer et al. 2018]] ; [[#Chen--2019|Chen et al. 2019]] ; [[#Cui--2019|Cui et al. 2019]] ; [[#Fofrich--2020|Fofrich et al. 2020]] ). This is important as the power sector is comparatively easy to decarbonise (IPCC 2014a; [[#Krey--2014|Krey et al. 2014]] ; [[#Davis--2018|Davis et al. 2018]] ; [[#Méjean--2019|Méjean et al. 2019]] ) and it is crucial to make space for residual emissions from non-electric energy end uses that are more difficult to mitigate ( ''high confidence'' ). Any further delay in climate policy substantially increases carbon lock-in and mitigation challenges as well as a dependence on carbon dioxide removal technologies for meeting the Paris climate goals ( [[#Kriegler--2018b|Kriegler et al. 2018b]] ; [[#Luderer--2018|Luderer et al. 2018]] ).

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