Editing IPCC:AR6/WGIII/Chapter-8 (section)

=== 8.1.6 Urban Carbon Footprint ===

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Urban areas concentrate GHG fluxes because of the size of the urban population, the size and nature of the urban economy, the energy and GHGs embodied in the infrastructure (see ‘embodied emissions’ in Glossary), and the goods and services imported and exported to and from cities ( [[#USGCRP--2018|USGCRP 2018]] ).

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==== 8.1.6.1 Urban Carbon Cycle ====

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In cities, carbon cycles through natural (e.g., vegetation and soils) and managed (e.g., reservoirs and anthropogenic – buildings, transportation) pools. The accumulation of carbon in urban pools, such as buildings or landfills, results from the local or global transfer of carbon-containing energy and raw materials used in the city ( [[#Churkina--2008|Churkina 2008]] ; [[#Pichler--2017|Pichler et al. 2017]] ; [[#Chen--2020b|Chen et al. 2020b]] ). Quantitative understanding of these transfers and the resulting emissions and uptake within an urban area is essential for accurate urban carbon accounting ( [[#USGCRP--2018|USGCRP 2018]] ). Currently, urban areas are a net source of carbon because they emit more carbon than they uptake. Thus, urban mitigation strategies require a twofold strategy: reducing urban emissions of carbon into the atmosphere, and enhancing uptake of carbon in urban pools ( [[#Churkina--2012|Churkina 2012]] ) (for a broader definition of ‘carbon cycle’ and related terms such as ‘carbon sink,’ ‘carbon stock,’ ‘carbon neutrality,’ ‘GHG neutrality,’ and others, see Glossary).

Burning fossil fuels to generate energy for buildings, transportation, industry, and other sectors is a major source of urban GHG emissions ( [[#Gurney--2015|Gurney et al. 2015]] ). At the same time, most cities do not generate within their boundaries all of the resources they use, such as electricity, gasoline, cement, water, and food needed for local homes and businesses to function ( [[#Jacobs--1969|Jacobs 1969]] ), requiring consideration of GHG emissions embodied in supply chains serving cities. Furthermore, urban vegetation, soils, and aquatic systems can both emit or remove carbon from the urban atmosphere and are often heavily managed. For example, urban parks, forests, and street trees actively remove carbon from the atmosphere through growing season photosynthesis. They can become a net source of carbon most often during the dormant season or heat waves. Some of the sequestered carbon can be stored in the biomass of urban trees, soils, and aquatic systems. Urban infrastructures containing cement also uptake carbon through the process of carbonation. The uptake of carbon by urban trees is at least two orders of magnitude faster than by cement-containing infrastructures ( [[#Churkina--2012|Churkina 2012]] ) ( [[#8.4.4|Section 8.4.4]] and Figures 8.17 and 8.18).

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==== 8.1.6.2 Urban Emissions Accounting ====

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Urban GHG emissions accounting can determine critical conceptual and quantitative aspects of urban GHG emissions. The accounting framework chosen can therefore predetermine the emissions responsibility, the mitigation options available, and the level of effort required to correctly account for emissions ( [[#Afionis--2017|Afionis et al. 2017]] ).

Two main urban carbon accounting advances have occurred since AR5. The first includes efforts to better understand and clarify how the different urban GHG accounting frameworks that have emerged over the past 15 years are interrelated, require different methodological tools, and reflect differing perspectives on emissions responsibility and quantification effort. The second main advance lies in a series of methodological innovations facilitating practical implementation, emissions verification, and scaling-up of the different GHG accounting approaches. This section provides an overview of the most used GHG urban accounting frameworks followed by a review of the advances since AR5.

Numerous studies have reviewed urban GHG accounting frameworks and methods with somewhat different nomenclatures and categorical divisions ( [[#Lin--2015|Lin et al. 2015]] ; [[#Lombardi--2017|Lombardi et al. 2017]] ; [[#Chen--2019b|Chen et al. 2019b]] ; [[#Arioli--2020|Arioli et al. 2020]] ; [[#Heinonen--2020|Heinonen et al. 2020]] ; [[#Hachaichi--2021|Hachaichi and Baouni 2021]] ; [[#Ramaswami--2021|Ramaswami et al. 2021]] ). Furthermore, accounting frameworks are reflected in multiple protocols used by urban practitioners ( [[#BSI--2013|BSI 2013]] ; [[#Fong--2014|Fong et al. 2014]] ; [[#ICLEI--2019b|ICLEI 2019b]] ). Synthesis of these reviews and protocols, as well as the many individual methodological studies available, point to four general frameworks of urban GHG accounting: (i) territorial accounting (TA); (ii) community-wide infrastructure supply chain footprinting (CIF); and (iii and iv) consumption-based carbon footprint accounting (CBCF; [[#Wiedmann--2008|Wiedmann and Minx 2008]] ). The last, CBCF, can be further divided into accounting with a focus on household or personal consumption (iii: the personal carbon footprint, or PCF); and an approach in which one includes final consumption in an area by all consumers (iv: the areal carbon footprint, or ACF) ( [[#Heinonen--2020|Heinonen et al. 2020]] ). A number of small variations to these general categories are found in the literature ( [[#Lin--2015|Lin et al. 2015]] ; [[#Chen--2020a|Chen et al. 2020a]] ), but these four general frameworks capture the important distinctive (i.e., policy-relevant) features of urban GHG accounting.

All these approaches are foundationally rooted in the concept of urban metabolism, that is, the tracking of material and energy flows into, within, and out of cities ( [[#Wolman--1965|Wolman 1965]] ). These frameworks all aim to quantify urban GHG emissions but reflect different perspectives on where the emission responsibility is allocated in addition to how much and which components of the GHG emissions associated with the import and export of goods and services to and from a city (‘transboundary embedded/embodied GHG emissions’) are included in a given urban emissions account. The four frameworks share some common, overlapping GHG emission quantities and their interrelationships have been defined mathematically ( [[#Chavez--2013|Chavez and Ramaswami 2013]] ).

A key advance since AR5 lies in understanding the different GHG accounting frameworks in terms of what they imply for responsibility – shared or otherwise – and what they imply for the depth and breadth of GHG emission reductions. TA focuses on in-city direct emission of GHGs to the atmosphere (e.g., combustion, net ecosystem exchange, methane (CH 4 ) leakage) within a chosen geographic area ( [[#Sovacool--2010|Sovacool and Brown 2010]] ; [[#Gurney--2019|Gurney et al. 2019]] ). CIF connects essential infrastructure use and demand activities in cities with their production, by combining TA emissions with the transboundary supply chain emissions associated with imported electricity, fuels, food, water, building materials, and waste management services used in cities ( [[#Ramaswami--2008|Ramaswami et al. 2008]] ; [[#Kennedy--2009|Kennedy et al. 2009]] ; [[#Chavez--2013|Chavez and Ramaswami 2013]] ).

CBCF considers not only the supply-chain-related GHG emissions of key infrastructure, but also emissions associated with all goods and services across a city, often removing emissions associated with goods and services exported from a city ( [[#Wiedmann--2016|Wiedmann et al. 2016]] , 2021). The distinction between the PCF and ACF variants of the CBCF is primarily associated with whether the agents responsible for the final demand are confined to only city residents (PCF) or all consumers in a city (ACF), which can include government consumers, capital formation, and other final demand categories ( [[#Heinonen--2020|Heinonen et al. 2020]] ).

A recent synthesis of these frameworks in the context of a net-zero GHG emissions target suggests that the four frameworks contribute to different aspects of decarbonisation policy and can work together to inform the overall process of decarbonisation ( [[#Ramaswami--2021|Ramaswami et al. 2021]] ). Furthermore, the relative magnitude of GHG emissions for a given city resulting from the different frameworks is often a reflection of the city’s economic structure as a ‘consumer’ or ‘producer’ city ( [[#Chavez--2013|Chavez and Ramaswami 2013]] ; [[#Sudmant--2018|Sudmant et al. 2018]] ).

The TA framework is unique in that it can be independently verified through direct measurement of GHGs in the atmosphere, offering a check on the integrity of emission estimates ( [[#Lauvaux--2020|Lauvaux et al. 2020]] ; [[#Mueller--2021|Mueller et al. 2021]] ). It is traditionally simpler to estimate by urban practitioners given the lower data requirements, and it can be relevant to policies aimed specifically at energy consumption and mobility activities within city boundaries. However, it will not reflect electricity imported for use in cities or lifecycle emissions associated with in-city consumption of goods and services.

The CIF framework adds to the TA framework by including GHG emissions associated with electricity imports and the lifecycle GHG emissions associated with key infrastructure provisioning activities in cities, serving all homes, businesses, and industries. This widens both the number of emitting categories and the responsibility for those emissions by including infrastructure-related supply chain emissions. The CIF framework enables individual cities to connect community-wide demand for infrastructure and food with their transboundary production, strategically aligning their net-zero emissions plans with larger-scale net-zero efforts ( [[#Ramaswami--2013|Ramaswami and Chavez 2013]] ; [[#Ramaswami--2021|Ramaswami et al. 2021]] ; [[#Seto--2021|Seto et al. 2021]] ).

The PCF version of the CBCF shifts the focus of the consumption and associated supply chain emissions to only household consumption of goods and services ( [[#Jones--2014|Jones and Kammen 2014]] ). This both reduces the TA emissions considered and the supply chain emissions, excluding all emissions associated with government, capital formation, and exports. The ACF, by contrast, widens the perspective considerably, including the TA and supply chain emissions of all consumers in a city, but often removing emissions associated with exports.

An additional distinction is the ability to sum up accounts from individual cities in a region or country, for example, directly to arrive at a regional or national total. This can only be done for the TA and PCF frameworks. The ACF and CIF frameworks would require adjustment to avoid double-counting emissions ( [[#Chen--2020a|Chen et al. 2020a]] ).

A second major area of advance since AR5 has been in methods to implement, verify and scale up the different GHG footprinting approaches. Advances have been made in six key areas: (i) advancing urban metabolism accounts integrating stocks and flows, and considering biogenic and fossil-fuel-based emissions ( [[#Chen--2020b|Chen et al. 2020b]] ); (ii) improving fine-scale and near-real-time urban use-activity data through new urban data science ( [[#Gately--2017|Gately et al. 2017]] ; [[#Gurney--2019|Gurney et al. 2019]] ; [[#Turner--2020|Turner et al. 2020]] ; [[#Yadav--2021|Yadav et al. 2021]] ); (iii) using atmospheric monitoring from the ground, aircraft, and satellites combined with inverse modelling to independently quantify TA emissions ( [[#Lamb--2016|Lamb et al. 2016]] ; [[#Lauvaux--2016|Lauvaux et al. 2016]] , 2020; [[#Davis--2017|Davis et al. 2017]] ; [[#Mitchell--2018|Mitchell et al. 2018]] ; [[#Sargent--2018|Sargent et al. 2018]] ; [[#Turnbull--2019|Turnbull et al. 2019]] ; [[#Wu--2020a|Wu et al. 2020a]] ); (iv) improving supply chain and input-output modelling, including the use of physically based input-output models ( [[#Wachs--2018|Wachs and Singh 2018]] ); (v) establishing the global multi-region input-output models ( [[#Lenzen--2017|Lenzen et al. 2017]] ; [[#Wiedmann--2021|Wiedmann et al. 2021]] ); and (vi) generating multi-sector use and supply activity data across all cities in a nation, in a manner where data aggregate consistently across city, province, and national scales ( [[#Tong--2021|Tong et al. 2021]] ) ( [[#8.3|Section 8.3]] ).

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