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

== 8.4 Urban Mitigation Options ==

<div id="h1-5-siblings" class="h1-siblings"></div>

Urban mitigation options can be categorised into three broad strategies: (i) reducing or changing urban energy and material use towards more sustainable production and consumption across all sectors, including through spatial planning and infrastructure; (ii) electrification and switching to net-zero-emissions resources; and (iii) enhancing carbon storage in the urban environment through urban green and blue infrastructure, which can also offer multiple co-benefits. A fourth, socio-behavioural aspects, can shift energy demand and emerge as the result of implementing the strategies. Urban mitigation options covered in this section are organised around these three strategies and can facilitate deep decarbonisation through systemic transformation (see [[#8.6|Section 8.6]] and Figure 8.21 for prioritising mitigation options based on urban form and urban growth typologies).

Urban areas are systems where multiple mitigation options – especially when integrated – have cascading effects across transport, energy, buildings, land use, and behaviour. These cascading effects take place both within and across urban systems (Figure 8.15). Mitigation actions also occur at multiple urban scales, from households and blocks to districts and city regions, and can be implemented as standalone sectoral strategies, such as increasing energy efficiency for appliances, and also as system-wide actions. In reducing emissions locally, urban areas can help lower emissions outside of their administrative boundaries through their use of materials and resources, and by increasing the efficiency of infrastructure and energy use beyond what is possible with individual sectoral strategies. Urban mitigation policies that implement multiple integrated interventions will provide more emissions savings than the sum of individual interventions ( [[#Sethi--2020|Sethi et al. 2020]] ).

<div id="_idContainer00a" class="Basic-Text-Frame"></div>

[[File:5e208c73461e2279fd6aca88e97051ab IPCC_AR6_WGIII_Figure_8_15b.png]] [[File:2871b97d3d5573b609b871f174598ae6 IPCC_AR6_WGIII_Figure_8_15a.png]]

'''Figure 8.15: Urban systems, lock-in, and cascading effects of mitigation strategies.''' Cities are systems of interconnected sectors, activities, and governance structures. Urban-scale mitigation action can have cascading effects across multiple sectors, as shown in panel '''(a)''' , as well as regional, national, and global impacts through supply chains, resource flows, and institutions, as shown in panel '''(b)''' . Mitigation efforts implemented at larger scales of governance or in sectors that transcend urban boundaries, like energy and transportation, can also facilitate and amplify mitigation at the urban scale, as shown by the arrows extending in both directions across layers (a). Because urban areas are connected locally and globally, urban mitigation efforts can also impact other cities and surrounding areas (agriculture, forestry and other land use (AFOLU)). Cities are prone to carbon lock-in due to the numerous reinforcing interactions among urban infrastructures and technologies, institutions, and individual and collective behaviours; see the side arrows extending across the layers in panel (a): the yellow arrow represents the infrastructure and technological lock-in involving user technologies and supporting infrastructure, the blue arrow indicates lock-in of local to international institutions, and the pink arrow represents behavioural lock-in for individuals and society. Urban carbon lock-in is strongly determined by urban form, in particular the layout of streets and land-use mix. The different coloured spatial patterns represent varying levels of co-location of housing and jobs, and mobility options (Figure 8.16). Efforts to break urban carbon lock-in require meta-transformations to break inertia in and among infrastructures, institutions, and behaviours. Source: adapted in part from [[#Seto--2016|Seto et al. (2016)]] .

Integrated action also has a key role in providing benefits for human well-being. Urban mitigation options and strategies that are effective, efficient, and fair can also support broader sustainability goals ( [[#Güneralp--2017|Güneralp et al. 2017]] ; [[#Kona--2018|Kona et al. 2018]] ; [[#Pasimeni--2019|Pasimeni et al. 2019]] ). Due to the complex and intensive interactions in urban systems and the interlinked nature of the SDGs, cities can be important intervention points to harness synergies and co-benefits for achieving emissions reductions along with other SDGs ( [[#Nilsson--2016|Nilsson et al. 2016]] ; [[#Corbett--2017|Corbett and Mellouli 2017]] ) ( [[#8.2|Section 8.2]] and Figure 8.4).

<div id="8.4.1" class="h2-container"></div>

<span id="avoiding-carbon-lock-in"></span>
=== 8.4.1 Avoiding Carbon Lock-in ===

<div id="h2-15-siblings" class="h2-siblings"></div>

Carbon lock-in occurs as the result of interactions between different geographic and administrative scales (institutional lock-in) and across sectors (infrastructural and technological lock-in), which create the conditions for behavioural lock-in covering both individual and social structural behaviours ( [[#Seto--2016|Seto et al. 2016]] ) (see Glossary for a broader definition of ‘lock-in’). The way that urban areas are designed, laid out, and built (i.e., urban form) affects and is affected by the interactions across the different forms of carbon lock-in (Figures 8.15 and 8.16). Cities are especially prone to carbon lock-in because of the multiple interactions of technological, institutional, and behavioural systems, which create inertia and path dependency that are difficult to break. For example, the lock-in of gasoline cars is reinforced by highway and energy infrastructures that are further locked-in by social and cultural preferences for individual mobility options. The dominance of cars and their supporting infrastructures in auto-centric urban forms is further reinforced by zoning and urban development patterns, such as dispersed and low-density housing distantly located from jobs, that create obstacles to creating alternative mobility options ( [[#Seto--2016|Seto et al. 2016]] ; [[#Linton--2021|Linton et al. 2021]] ).

Urban infrastructures and the built environment are long-lived assets, embodying triple carbon lock-ins in terms of their construction, operations, and demolition ( [[#Creutzig--2016b|Creutzig et al. 2016b]] ; [[#Seto--2016|Seto et al. 2016]] ; [[#Ürge-Vorsatz--2018|Ürge-Vorsatz et al. 2018]] ). There is much focus in the climate change literature on the operational lifetimes of the energy sector, especially power plants and the electricity grid, which are between 30 and 60 years ( [[#Rode--2017|Rode et al. 2017]] ). Yet, in reality, the lifespans of urban infrastructures, especially the basic layout of roadways, are often much longer (Reyna and Chester 2015). A number of detailed case studies on the evolution of urban road networks for cities around the world reveal that the current layout of streets grew out of street networks that were established hundreds of years ago ( [[#Strano--2012|Strano et al. 2012]] ; [[#Masucci--2013|Masucci et al. 2013]] ; [[#Mohajeri--2014|Mohajeri and Gudmundsson 2014]] ). Furthermore, there is evidence that urban street layout, population growth, urban development, and automobile ownership co-evolve ( [[#Li--2019a|Li et al. 2019a]] ).

For cities to break out of mutually reinforcing carbon lock-in, it will require systematic transformation and systems-based planning that integrates mitigation strategies across sectors and geopolitical scales. Urban energy demand patterns are locked-in whenever incremental urban design and planning decisions, coupled with investments in long-lasting infrastructure, such as roads and buildings, take place ( [[#Seto--2016|Seto et al. 2016]] ). The fundamental building blocks of cities are based on the layout of the street network, the size of city blocks, and the density of street intersections. If not significantly altered, these three factors will continue to shape and lock-in energy demand for decades after their initial construction, influencing the mitigation potential of urban areas ( [[#8.4.2|Section 8.4.2]] and Figure 8.22).

Avoiding carbon lock-in inherently involves decisions that extend beyond the administrative boundaries of cities. This includes pricing of low-emissions technology or materials, such as electric battery or hydrogen vehicles and buses, although cities can support their development and deployment (Cross-Chapter Box 12 in [[IPCC:Wg3:Chapter:Chapter-16|Chapter 16]] on Transition Dynamics). In contrast, urban governments in most parts of the world do have powers to set building codes that regulate materials and construction standards for buildings, including heating and cooling technologies, and major appliances. Other examples include zoning that determines the location of buildings, land uses, standards for densities, and the inclusion of energy planning in their building standards and public works, including streets, parks, and open spaces ( [[#Blanco--2011|Blanco et al. 2011]] ; [[#Raven--2018|Raven et al. 2018]] ).

<div id="8.4.2" class="h2-container"></div>

<span id="spatial-planning-urban-form-and-infrastructure"></span>
=== 8.4.2 Spatial Planning, Urban Form, and Infrastructure ===

<div id="h2-16-siblings" class="h2-siblings"></div>

Urban form is the resultant pattern and spatial layout of land use, transportation networks, and urban design elements, including the physical urban extent, configuration of streets and building orientation, and the spatial figuration within and throughout cities and towns ( [[#Lynch--1981|Lynch 1981]] ; [[#Handy--1996|Handy 1996]] ). Infrastructure describes the physical structures, social and ecological systems, and corresponding institutional arrangements that provide services and enable urban activity ( [[#Dawson--2018|Dawson et al. 2018]] ; [[#Chester--2019|Chester 2019]] ) and comprises services and built-up structures that support urban functioning, including transportation infrastructure, water and wastewater systems, solid waste systems, telecommunications, and power generation and distribution (Seto et al. 2014).

<div id="8.4.2.1" class="h3-container"></div>

<span id="urban-form"></span>
==== 8.4.2.1 Urban Form ====

<div id="h3-8-siblings" class="h3-siblings"></div>

The AR5 concluded that infrastructure and four dimensions of urban form are especially important for driving urban energy use: density, land-use mix, connectivity, and accessibility. Specifically, low-carbon cities have the following characteristics: (i) co-located medium to high densities of housing, jobs, and commerce; (ii) high mix of land uses; (iii) high connectivity of streets; and (iv) high levels of accessibility, distinguished by relatively low travel distances and travel times that are enabled by multiple modes of transportation. Urban areas with these features tend to have smaller dwelling units, smaller parcel sizes, walking opportunities, high density of intersections, and are highly accessible to shopping. For brevity, we will refer to these characteristics collectively as ‘compact and walkable urban form’ (Figure 8.16). Compact and walkable urban form has many co-benefits, including mental and physical health, lower resource demand, and saving land for AFOLU. In contrast, dispersed and auto-centric urban form is correlated with higher GHG emissions, and characterised by separated land uses, low population and job densities, large block size, and low intersection density.

<div id="_idContainer00b" class="Basic-Text-Frame"></div>

[[File:b4247eb2342c8e469b50e6118aac70db IPCC_AR6_WGIII_Figure_8_16.png]]

'''Figure 8.16: Urban form and implications for GHG emissions.''' Compact and walkable urban form is strongly correlated with low GHG emissions and characterised by co-located medium to high densities of housing and jobs, high street density, small block size, and mixed land use (Seto et al. 2014). Higher population densities at places of origin (e.g., home) and destination (e.g., employment, shopping) concentrate demand and are necessary for achieving the Avoid-Shift-Improve (ASI) approach for sustainable mobility (Chapters 5 and 10). Dispersed and auto-centric urban form is strongly correlated with high GHG emissions, and characterised by separated land uses, especially of housing and jobs, low street density, large block sizes, and low urban densities. Separated and low densities of employment, retail, and housing increase average travel distances for both work and leisure, and make active transport and modal shift a challenge. Since cities are systems, urban form has interacting implications across energy, buildings, transport, land use, and individual behaviour. Compact and walkable urban form enables effective mitigation while dispersed and auto-centric urban form locks-in higher levels of energy use. The colours represent different land uses and indicate varying levels of co-location and mobility options.

Since AR5, a range of studies have been published on the relationships between urban spatial structures, urban form, and GHG emissions. Multiple lines of evidence reaffirm the key findings from AR5, especially regarding the mitigation benefits associated with reducing vehicle miles or kilometres travelled (VMT/VKT) through spatial planning. There are important cascading effects not only for transport but also other key sectors and consumption patterns, such as in buildings, households, and energy. However, these benefits can be attained only when the existing spatial structure of an urban area does not limit locational and mobility options, thereby avoiding carbon lock-in through the interaction of infrastructure and the resulting socio-behavioural aspects.

Modifying the layout of emerging urbanisation to be more compact, walkable, and co-located can reduce future urban energy use by 20–25% in 2050 while providing a corresponding mitigation potential of 23–26% ( [[#Creutzig--2015|Creutzig et al. 2015]] , 2016b; [[#Sethi--2020|Sethi et al. 2020]] ), forming the basis for other urban mitigation options. Cross-Chapter Box 7 in [[IPCC:Wg3:Chapter:Chapter-10|Chapter 10]] provides perspectives on simultaneously reducing urban transport emissions, avoiding infrastructure lock-in, and providing accessible services. The systemic nature of compact urban form and integrated spatial planning influences ‘Avoid-Shift-Improve’ (ASI, see Glossary) options across several sectors simultaneously, including for mobility and shelter (for an in-depth discussion on the integration of service provision solutions within the ASI framework, see [[IPCC:Wg3:Chapter:Chapter-5#5.3|Section 5.3]] ).

<div id="8.4.2.2" class="h3-container"></div>

<span id="co-located-housing-and-jobs-mixed-land-use-and-high-street-connectivity"></span>
==== 8.4.2.2 Co-located Housing and Jobs, Mixed Land Use, and High Street Connectivity ====

<div id="h3-9-siblings" class="h3-siblings"></div>

Integrated spatial planning, co-location of higher residential and job densities, and systemic approaches are widely identified with development that is characterised by the 5Ds of transit-oriented development (TOD) based on density, diversity (mixed land uses), design (street connectivity), destination accessibility, and distance to transit. Spatial strategies that integrate the 5Ds are shown to reduce VMT/VKT, and thereby transport-related GHG emissions through energy savings. The effect of urban form and built environment strategies on VMT per capita varies by a number of factors ( [[#Ewing--2010|Ewing and Cervero 2010]] ; [[#Stevens--2017|Stevens 2017]] ; [[#Blanco--2018|Blanco and Wikstrom 2018]] ). Density and destination accessibility have the highest elasticities, followed by design ( [[#Stevens--2017|Stevens 2017]] ). Population-weighted densities for 121 metropolitan areas have further found that the concentration of population and jobs along mass transit corridors decreases VMT/VKT significantly when compared to more dispersed metropolitan areas. In this sample, elasticity rates were twice as high for dense metropolitan areas located along mass transit lines ( [[#Lee--2020|Lee and Lee 2020]] ).

Meta-analyses of the reduction in VMT and the resulting GHG emissions consider the existing and still dominant use of emitting transportation technology, transportation fleets, and urban form characteristics. Varied historical legacies of transportation and the built environment, which can be utilised to develop more sustainable cities ( [[#Newman--2016|Newman et al. 2016]] , 2017), are often not taken into account directly. Metropolitan policies and spatial planning, as evident in Copenhagen’s Finger Plan, as well as strategic spatial planning in Stockholm and Seoul, have been major tools to restructure urban regions and energy patterns ( [[#Sung--2017|Sung and Choi 2017]] ). Road prices and congestion charges can provide the conditions for urban inhabitants to shift mobility demands and reduce vehicle use ( [[IPCC:Wg3:Chapter:Chapter-5#5.6.2|Section 5.6.2]] ). Surprisingly, even cities with higher population densities and a greater range of land uses can show declines in these important attributes, which can lead to emissions increases, such as found in a study of 323 East and South East Asian cities ( [[#Chen--2020c|Chen et al. 2020c]] ). Conversely, the annual CO 2 emissions reduction of passenger cars in compact versus dispersed urban form scenarios can include at least a 10% reduction by 2030 ( [[#Matsuhashi--2016|Matsuhashi and Ariga 2016]] ). When combined with advances in transport technology, this share increases to 64–70% in 2050 based on compact urban form scenarios for 1727 municipalities ( [[#Kii--2020|Kii 2020]] ).

As a reaffirmation of AR5, population density reduces emissions per capita in the transport, building, and energy sectors ( [[#Baur--2015|Baur et al. 2015]] ; [[#Gudipudi--2016|Gudipudi et al. 2016]] ; [[#Wang--2017|Wang et al. 2017]] ; [[#Yi--2017|Yi et al. 2017]] ) (see also Sections 8.3.1 and 8.3.4 on past trends and forecasts of urban population density and land expansion). Urban compactness tends to reduce emissions per capita in the transport sector, especially for commuting ( [[#Matsuhashi--2016|Matsuhashi and Ariga 2016]] ; [[#Lee--2018|Lee and Lim 2018]] ; [[#Lee--2020|Lee and Lee 2020]] ). The relative accessibility of neighbourhoods to the rest of the region, in addition to the density of individual neighbourhoods, is important ( [[#Ewing--2018|Ewing et al. 2018]] ). Creating higher residential and employment densities, developing smaller block sizes, and increasing housing opportunities in an employment area can significantly reduce household car ownership and car driving, and increase the share of transit, walk, and bicycle commuting ( [[#Ding--2018|Ding et al. 2018]] ). In addition to population density, land-use mix, rail transit accessibility, and street design reduce emissions from transport ( [[#Dou--2016|Dou et al. 2016]] ; [[#Cao--2017|Cao and Yang 2017]] ; [[#Choi--2018|Choi 2018]] ). The impact of population density and urban compactness on emissions per capita in the household or energy sector is also associated with socioeconomic characteristics or lifestyle preferences ( [[#Baiocchi--2015|Baiocchi et al. 2015]] ; [[#Miao--2017|Miao 2017]] ). Changes in the attributes of urban form and spatial structure have influences on overall energy demand across spatial scales, particularly street, block, neighbourhood, and city scales, as well as across the building (housing) and transport (mobility) sectors ( [[#Silva--2017|Silva et al. 2017]] ). Understanding the existing trade-offs (or synergetic links) between urban form variables across major emissions source sectors, and how they impact the size of energy flows within the urban system, is key to prioritising action for energy-efficient spatial planning strategies, which are likely to vary across urban areas.

<div id="8.4.2.3" class="h3-container"></div>

<span id="urban-form-growth-and-sustainable-development"></span>
==== 8.4.2.3 Urban Form, Growth, and Sustainable Development ====

<div id="h3-10-siblings" class="h3-siblings"></div>

Spatial planning for compact urban form is a system-wide intervention ( [[#Sethi--2020|Sethi et al. 2020]] ) and has potential to be combined with sustainable development objectives while pursuing climate mitigation for urban systems ( [[#Große--2016|Große et al. 2016]] ; [[#Cheshmehzangi--2017|Cheshmehzangi and Butters 2017]] ; [[#Facchini--2017|Facchini et al. 2017]] ; [[#Lwasa--2017|Lwasa 2017]] ; [[#Stokes--2019|Stokes and Seto 2019]] ). Compact urban form can enable positive impacts on employment and green growth given that the local economy is decoupled from GHG emissions and related parameters while the concentration of people and activity can increase productivity based on both proximity and efficiency ( [[#Lee--2017|Lee and Erickson 2017]] ; [[#Salat--2017|Salat et al. 2017]] ; [[#Gao--2018|Gao and Newman 2018]] ; [[#Han--2018|Han et al. 2018]] ; [[#Li--2018|Li and Liu 2018]] ; [[#Lall--2021|Lall et al. 2021]] ).

Public acceptance can have a positive impact on integrated spatial planning especially when there is a process of co-design ( [[#Grandin--2018|Grandin et al. 2018]] ; [[#Webb--2018|Webb et al. 2018]] ). The quality of spatial planning can also increase co-benefits for health and well-being, including decisions to balance urban green areas with density ( [[#Li--2016|Li et al. 2016]] ; [[#Sorkin--2018|Sorkin 2018]] ; [[#Pierer--2019|Pierer and Creutzig 2019]] ). The distributional effects of spatial planning can depend on the policy tools that shape the influence of urban densification on affordable housing while evidence for transit-induced gentrification is found to be partial and inconclusive ( [[#Chava--2016|Chava and Newman 2016]] ; [[#Jagarnath--2018|Jagarnath and Thambiran 2018]] ; [[#Padeiro--2019|Padeiro et al. 2019]] ; [[#Debrunner--2020|Debrunner and Hartmann 2020]] ) (Sections 8.2 and 8.4.4).

Reducing GHG emissions across different urban growth typologies (Figure 8.20) depends in part on the ability to integrate opportunities for climate mitigation with co-benefits for health and well-being ( [[#Grandin--2018|Grandin et al. 2018]] ). At the same time, requirements for institutional capacity and governance for cross-sector coordination for integrated urban planning is high given the complex relations between urban mobility, buildings, energy systems, water systems, ecosystem services, other urban sectors, and climate adaptation ( [[#Große--2016|Große et al. 2016]] ; [[#Castán%20Broto--2017a|Castán Broto 2017a]] ; [[#Endo--2017|Endo et al. 2017]] ; [[#Geneletti--2017|Geneletti et al. 2017]] ). The capacity for implementing land-use zoning and regulations in a way that is consistent with supporting spatial planning for compact urban form is not equal across urban areas and depends on different contexts as well as institutional capacities ( [[#Bakır--2018|Bakır et al. 2018]] ; [[#Deng--2018|Deng et al. 2018]] ; [[#Shen--2019|Shen et al. 2019]] ).

Currently, integrating spatial planning, urban form, and infrastructure in urban mitigation strategies remains limited in mainstream practices, including in urban areas targeting an emissions reduction of 36–80% in the next decades ( [[#Asarpota--2020|Asarpota and Nadin 2020]] ). Capacity building for integrated spatial planning for urban mitigation includes increasing collaboration among city departments and with civil society to develop robust mitigation strategies, bringing together civil engineers, architects, urban designers, public policy and spatial planners, and enhancing the education of urban professionals ( [[#Asarpota--2020|Asarpota and Nadin 2020]] ) ( [[#8.5|Section 8.5]] ).

Spatial planning for compact urban form is a prerequisite for efficient urban infrastructure, including district heating and/or cooling networks ( [[#Swilling--2018|Swilling et al. 2018]] ; [[#Möller--2019|Möller et al. 2019]] ; [[#Persson--2019|Persson et al. 2019]] ; [[#UNEP%20IRP--2020|UNEP IRP 2020]] ). District heating and cooling networks benefit from urban design parameters, including density, block area, and elongation that represent the influence of urban density on energy density ( [[#Fonseca--2015|Fonseca and Schlueter 2015]] ; [[#Shi--2020|Shi et al. 2020]] ). Heat- demand density is a function of both population density and heat demand per capita and can be equally present in urban areas with high population density or high heat demand per capita ( [[#Möller--2019|Möller et al. 2019]] ; [[#Persson--2019|Persson et al. 2019]] ). Low-temperature networks that utilise waste heat or renewable energy can provide an option to avoid carbon lock-in to fossil fuels while layout and eco-design principles can further optimise such networks ( [[#Gang--2016|Gang et al. 2016]] ; [[#Buffa--2019|Buffa et al. 2019]] ; [[#Dominković--2019|Dominković and Krajačić 2019]] ). Replacing gas-based heating and cooling with electrified district heating and cooling networks, for instance, provides 65% emissions reductions also involving carbon-aware scheduling for grid power ( [[#De%20Chalendar--2019|De Chalendar et al. 2019]] ). The environmental and ecological benefits increase through the interaction of urban energy and spatial planning ( [[#Tuomisto--2015|Tuomisto et al. 2015]] ; [[#Bartolozzi--2017|Bartolozzi et al. 2017]] ; [[#Dénarié--2018|Dénarié et al. 2018]] ; [[#Zhai--2020|Zhai et al. 2020]] ). These interactions include support for demand-side flexibility, spatial planning using geographic information systems, and access to renewable and urban waste heat sources ( [[#Möller--2018|Möller et al. 2018]] ; [[#REN21--2020|REN21 2020]] ; [[#Sorknæs--2020|Sorknæs et al. 2020]] ; [[#Dorotić--2019|Dorotić et al. 2019]] ) (see Table 8.SM.2 for other references).

<div id="8.4.3" class="h2-container"></div>

<span id="electrification-and-switching-to-net-zero-emissions-resources"></span>
=== 8.4.3 Electrification and Switching to Net-Zero-Emissions Resources ===

<div id="h2-17-siblings" class="h2-siblings"></div>

Pursuing the electrification of mobility, heating, and cooling systems, while decarbonising electricity and energy carriers, and switching to net-zero materials and supply chains, represent important strategies for urban mitigation. Electrification of energy end uses in cities and efficient energy demand for heating, transport, and cooking through multiple options and urban infrastructure, has an estimated mitigation potential of at least 6.9 GtCO 2 -eq by 2030 and 15.3 GtCO 2 -eq by 2050 ( [[#Coalition%20for%20Urban%20Transitions--2019|Coalition for Urban Transitions 2019]] ). Energy efficiency measures in urban areas can be enabled by urban form, building codes, retrofitting and renovation, modal shifts, and other options. Decarbonising electricity supply raises the mitigation potential of efficient buildings and transport in urban areas to about 75% of the total estimate ( [[#Coalition%20for%20Urban%20Transitions--2019|Coalition for Urban Transitions 2019]] ). In addition, relatively higher-density urban areas enable more cost-effective infrastructure investments, including electric public transport and large-scale heat pumps in districts that support electrification. Urban policymakers can play a key role in supporting carbon-neutral energy systems by acting as target setters and planners, demand aggregators, regulators, operators, conveners, and facilitators for coordinated planning and implementation across sectors, urban form, and demand ( [[#IEA--2021a|IEA 2021a]] ; [[#IRENA--2021|IRENA 2021]] ).

<div id="8.4.3.1" class="h3-container"></div>

<span id="electrification-and-decarbonisation-of-the-urban-energy-system"></span>
==== 8.4.3.1 Electrification and Decarbonisation of the Urban Energy System ====

<div id="h3-11-siblings" class="h3-siblings"></div>

Urban energy infrastructures often operate as part of larger energy systems that can be electrified, decarbonised, and become enablers of urban system flexibility through demand-side options. With multiple end-use sectors (e.g., transport, buildings) and their interactions with land use drawing on the same urban energy system(s), increasing electrification is essential for rapid decarbonisation, renewable energy penetration, and demand flexibility ( [[#Kammen--2016|Kammen and Sunter 2016]] ) (see IMPs in Sections 3.2.5 and 8.3.4). The mitigation potential of electrification is ultimately dependent on the carbon intensity of the electricity grid ( [[#Kennedy--2015|Kennedy 2015]] ; [[#Hofmann--2016|Hofmann et al. 2016]] ; [[#Peng--2018|Peng et al. 2018]] ; [[#Zhang--2020|Zhang and Fujimori 2020]] ) and starts providing lifecycle emission savings for carbon intensities below a threshold of 600 tCO 2 -eq GWh –1 ( [[#Kennedy--2019|Kennedy et al. 2019]] ). Integrated systems of roof-top photovoltaics (PVs) and all-electric vehicles (EVs) alone could supply affordable carbon-free electricity to cities and reduce CO 2 emissions by 54–95% ( [[#Brenna--2014|Brenna et al. 2014]] ; [[#Kobashi--2021|Kobashi et al. 2021]] ). Furthermore, electrification and decarbonisation of the urban energy system holds widespread importance for climate change mitigation across different urban growth typologies and urban form ( [[#8.6|Section 8.6]] and Figure 8.21) and leads to a multitude of public health co-benefits (see [[#8.2|Section 8.2]] ).

Strategies that can bring together electrification with reduced energy demand based on walkable and compact urban form can accelerate and amplify decarbonisation. Taking these considerations – across the energy system, sectors, and land use – contributes to avoiding, or breaking out of, carbon lock-in and allows continued emission savings as the energy supply is decarbonised ( [[#Kennedy--2018|Kennedy et al. 2018]] ; [[#Teske--2018|Teske et al. 2018]] ; [[#Seto--2021|Seto et al. 2021]] ). Indeed, electrification is already transforming urban areas and settlements and has the potential to continue transforming urban areas into net-negative electric cities that may sequester more carbon than emitted ( [[#Kennedy--2018|Kennedy et al. 2018]] ; [[#Seto--2021|Seto et al. 2021]] ).

In its simplest form, electrification involves the process of replacing fossil fuel-based technologies with electrified innovations such as electric vehicles, buses, streetcars, and trains (Sections 10.3 and 10.4), heat pumps, PVs ( [[IPCC:Wg3:Chapter:Chapter-6#6.4.2.1|Section 6.4.2.1]] ), electric cook-stoves ( [[IPCC:Wg3:Chapter:Chapter-9#9.8.2.1|Section 9.8.2.1]] ), and other technologies ( [[#Stewart--2018|Stewart et al. 2018]] ). Cost-effective decarbonisation of energy use can be supported by electrification in urban areas if there is also demand-side flexibility for power, heat, mobility, and water with sector coupling ( [[#Guelpa--2019|Guelpa et al. 2019]] ; [[#Pfeifer--2021|Pfeifer et al. 2021]] ). Overall, demand-side flexibility across sectors in urban areas is supported by smart charging, electric mobility, electrified urban rail, power-to-heat, demand side response, and water desalination ( [[#Lund--2015|Lund et al. 2015]] ; [[#Calvillo--2016|Calvillo et al. 2016]] ; [[#Salpakari--2016|Salpakari et al. 2016]] ; [[#Newman--2017|Newman 2017]] ; [[#Meschede--2019|Meschede 2019]] ).

As an enabler, electrification supports integrating net-zero energy sources in urban infrastructure across sectors, especially when there is more flexible energy demand in mobility, heating, and cooling to absorb greater shares of variable renewable energy. In the transport sector, smart charging can reduce electric vehicle impacts on peak demand by 60% ( [[#IEA--2021a|IEA 2021a]] ). Urban areas that connect efficient building clusters with the operation of smart thermal grids in district heating and cooling networks with large-scale heat pumps can support higher penetrations of variable renewable energy in smart energy systems ( [[#Lund--2014|Lund et al. 2014]] , 2017). Higher urban densities provide the advantage of increasing the penetration of renewable power for deep decarbonisation, including mixed-use neighbourhoods for grid balancing and electric public transport ( [[#Hsieh--2017|Hsieh et al. 2017]] ; [[#Tong--2017|Tong et al. 2017]] ; [[#Fichera--2018|Fichera et al. 2018]] ; [[#Kobashi--2020|Kobashi et al. 2020]] ). Based on these opportunities, urban areas that provide low-cost options to energy storage for integrating the power sector with multiple demands reduce investment needs in grid electricity storage capacities ( [[#Mathiesen--2015|Mathiesen et al. 2015]] ; [[#Lund--2018|Lund et al. 2018]] ).

Electrification at the urban scale encompasses strategies to aggregate energy loads for demand response in the urban built environment to reduce the curtailment of variable renewable energy and shifting time-of-use based on smart charging for redistributing energy demands ( [[#O’Dwyer--2019|O’Dwyer et al. 2019]] ). Peak shaving or shifting takes place among frequent interventions at the urban level ( [[#Sethi--2020|Sethi et al. 2020]] ). Business models and utility participation, including municipal level demonstrations, can allow for upscaling ( [[#Gjorgievski--2020|Gjorgievski et al. 2020]] ; [[#Meha--2020|Meha et al. 2020]] ). The urban system can support increasing demand-side flexibility in energy systems, including in contexts of 100% renewable energy systems ( [[#Drysdale--2019|Drysdale et al. 2019]] ; [[#Thellufsen--2020|Thellufsen et al. 2020]] ).

<div id="Smart grids in the urban system" class="h4-container"></div>

<span id="smart-grids-in-the-urban-system"></span>
===== Smart grids in the urban system =====

<div id="h4-1-siblings" class="h4-siblings"></div>

Smart electricity grids enable peak demand reductions, energy conservation, and renewable energy penetration, and are a subset of smart energy systems. GHG emission reductions from smart grids range from 10 to 180 gCO 2 kWh –1 (grams of CO 2 per kilowatt-hour) with a median value of 89 gCO 2 kWh –1 , depending on the electricity mix, penetration of renewable energy, and the system boundary ( [[#Moretti--2017|Moretti et al. 2017]] ). Smart electricity grids are characterised by bi-directional flows of electricity and information between generators and consumers, although some actors can be both as ‘prosumer’ (see Glossary). Two-way power flows can be used to establish peer-to-peer trading (P2P) ( [[#Hansen--2020|Hansen et al. 2020]] ). Business models based on local citizen utilities ( [[#Green--2017|Green and]] [[#Newman--2017|Newman 2017]] ; [[#Green--2020|Green et al. 2020]] ; [[#Syed--2020|Syed et al. 2020]] ) and community batteries ( [[#Mey--2019|Mey and Hicks 2019]] ; [[#Green--2020|Green et al. 2020]] ) can support the realisation of distributed energy and solar energy cities ( [[#Galloway--2014|Galloway and Newman 2014]] ; [[#Byrne--2016|Byrne and Taminiau 2016]] ; [[#Stewart--2018|Stewart et al. 2018]] ; [[#Allan--2020|Allan 2020]] ).

Currently, despite power outages that are costly to local economies, the adoption of smart electricity grids or smart energy systems has been slow in many developing regions, including in Sub-Saharan Africa ( [[#Westphal--2017|Westphal et al. 2017]] ; [[#Kennedy--2019|Kennedy et al. 2019]] ). This is due to a number of different factors, such as unreliable existing infrastructure, fractured fiscal authority, lack of electricity access in urban areas, upfront cost, financial barriers, inefficient pricing of electricity, and low consumer education and engagement ( [[#Venkatachary--2018|Venkatachary et al. 2018]] ; [[#Acakpovi--2019|Acakpovi et al. 2019]] ; [[#Cirolia--2020|Cirolia 2020]] ).

<div id="Pathways and trade-offs of electrification in urban systems" class="h4-container"></div>

<span id="pathways-and-trade-offs-of-electrification-in-urban-systems"></span>
===== Pathways and trade-offs of electrification in urban systems =====

<div id="h4-2-siblings" class="h4-siblings"></div>

Urbanisation and population density are one of the key drivers for enabling access to electricity across the world, with benefits for sustainable development ( [[#Aklin--2018|Aklin et al. 2018]] ). Grid-connected PV systems for urban locations that currently lack electricity access can allow urban areas to leapfrog based on green electrification ( [[#Abid--2021|Abid et al. 2021]] ). In the Global South, the conversion of public transport to electric transport, especially municipal buses (e.g., Bengaluru, India; Jakarta, Indonesia; Medellín, Colombia; Rio de Janeiro, Brazil; Quito, Ecuador) and micro-mobility (e.g., e-trikes in Manila, Philippines) have been quantified based on reductions in GHG and PM 2.5 emissions, avoided premature deaths, and increases in life expectancies ( [[#IEA--2014|IEA 2014]] ; [[#C40%20Cities--2018|C40 Cities 2018]] , 2020b,c,d,e). In 22 Latin American cities, converting 100% of buses and taxis in 2030 to electric was estimated to result in a reduction of 300 MtCO 2 -eq compared to 2017 ( [[#ONU%20Medio%20Ambiente--2017|ONU Medio Ambiente 2017]] ). Yet the scaling up of electric vehicles in cities can be examined within a larger set of possible social objectives, such as reducing congestion and the prioritisation of other forms of mobility.

Electrification requires a layering of policies at the national, state, and local levels. Cities have roles as policy architects, including transit planning (e.g., EV targets and low-emission zones, restrictions on the types of energy use in new buildings), implementers (e.g., building codes and compliance checking, financial incentives to encourage consumer uptake of EVs and heat pumps), and complementary partners to national and state policymaking (e.g., permitting or installation of charging infrastructure) ( [[#Broekhoff--2015|Broekhoff et al. 2015]] ). The number of cities that have instituted e-mobility targets that aim for a certain percentage of EVs sold, in circulation or registered, is increasing ( [[#REN21--2021|REN21 2021]] ). Realising the mitigation potential of electrification will require fiscal and regulatory policies and public investment ( [[#Hall--2017a|Hall et al. 2017a]] ; [[#Deason--2019|Deason and Borgeson 2019]] ; [[#Wappelhorst--2020|Wappelhorst et al. 2020]] ) ( [[#8.5|Section 8.5]] ).

EVs are most rapidly deployed when there has been a suite of policies, including deployment targets, regulations and use incentives (e.g., zero-emission zone mandates, fuel economy standards, building codes), financial incentives (e.g., vehicles, chargers), industrial policies (e.g., subsidies), and fleet procurement ( [[#IEA--2016b|IEA 2016b]] , 2017, 2018, 2020a; [[#Cazzola--2019|Cazzola et al. 2019]] ). The policy mix has included mandates for bus deployment, purchase subsidies, or split ownership of buses and chargers ( [[#IEA--2021b|IEA 2021b]] ) (Chapter 10). Subsidies are often critical to address the often-higher upfront costs of electric devices. In other instances, the uptake of electric induction stoves was increased through government credit and allotment of free electricity ( [[#Martínez--2017|Martínez et al. 2017]] ; [[#Gould--2018|Gould et al. 2018]] ).

Bringing multiple stakeholders together in local decision-making for smart energy systems requires effort beyond usual levels while multi-actor settings can be increased to enable institutional conditions ( [[#Lammers--2019|Lammers and Hoppe 2019]] ). Public participation and community involvement in the planning, design and operation of urban energy projects can be an enabler of decarbonising local energy demands ( [[#Corsini--2019|Corsini et al. 2019]] ). Cooperation across institutions is important for municipalities that are engaged in strategic energy planning and implementation for smart energy systems ( [[#Krog--2019|Krog 2019]] ) ( [[#8.5|Section 8.5]] ).

Electrification technologies can present potential trade-offs that can be minimised through governance strategies, smart grid technologies, circular economy practices, and international cooperation. One consideration is the increase in electricity demand ( [[IPCC:Wg3:Chapter:Chapter-5#5.3.1.1|Section 5.3.1.1]] ). Across 23 megacities in the world (population greater than 10 million people), electrification of the entire gasoline vehicle fleet could increase electricity demand on average by 18% ( [[#Kennedy--2018|Kennedy et al. 2018]] ). How grid capacity will be impacted is dependent on the match between daily electricity loads and supply ( [[#Tarroja--2018|Tarroja et al. 2018]] ). Materials recycling of electrification technologies is also key to minimising potential environmental and social costs ( [[#Church--2018|Church and Crawford 2018]] ; [[#Gaustad--2018|Gaustad et al. 2018]] ; [[#Sovacool--2020|Sovacool et al. 2020]] ) and can ensure electrification reaches its complete mitigation potential. Circular economy strategies are particularly valuable to this goal by creating closed-loop supply chains through recycling, material recovery, repair, and reuse. For instance, the PV CYCLE programme in Europe prevented more than 30,000 metric tonnes of renewable technology from reaching the waste stream ( [[#Sovacool--2020|Sovacool et al. 2020]] ) (Box 10.6 and ‘circular economy’ in Glossary).

<div id="8.4.3.2" class="h3-container"></div>

<span id="switching-to-net-zero-emissions-materials-and-supply-chains"></span>
==== 8.4.3.2 Switching to Net-zero-emissions Materials and Supply Chains ====

<div id="h3-12-siblings" class="h3-siblings"></div>

For the carbon embodied in supply chains to become net-zero, all key infrastructure and provisioning systems will need to be decarbonised, including electricity, mobility, food, water supply, and construction ( [[#Seto--2021|Seto et al. 2021]] ). The growth of global urban populations that is anticipated over the next several decades will create significant demand for buildings and infrastructure. As cities expand in size and density, there is an increase in the production of mineral-based structural materials and enclosure systems that are conventionally associated with mid- and high-rise urban construction morphologies, including concrete, steel, aluminium, and glass. This will create a significant spike in GHG emissions and discharge of CO 2 at the beginning of each building lifecycle, necessitating alternatives ( [[#Churkina--2020|Churkina et al. 2020]] ).

The initial carbon debt incurred in the production stage, even in sustainable buildings, can take decades to offset through operational stage energy efficiencies alone. Increased reduction in the energy demands and GHG emissions associated with the manufacture of mineral-based construction materials will be challenging, as these industries have already optimised their production processes. Among the category of primary structural materials, it is estimated that final energy demand for steel production can be reduced by nearly 30% compared to 2010 levels, with 12% efficiency improvement for cement ( [[#Lechtenböhmer--2016|Lechtenböhmer et al. 2016]] ). Even when industries are decarbonised, residual CO 2 emissions will remain from associated chemical reactions that take place in calcination and use of coke from coking coal to reduce iron oxide ( [[#Davis--2018|Davis et al. 2018]] ). Additionally, carbon sequestration by cement occurs over the course of the building lifecycle in quantities that would offset only a fraction of their production stage carbon spike ( [[#Xi--2016|Xi et al. 2016]] ; [[#Davis--2018|Davis et al. 2018]] ). Moreover, there are collateral effects on the carbon cycle related to modern construction and associated resource extraction. The production of cement, asphalt, and glass requires large amounts of sand extracted from beaches, rivers, and seafloors, disturbing aquatic ecosystems and reducing their capacity to absorb atmospheric carbon. The mining of ore can lead to extensive local deforestation and soil degradation ( [[#Sonter--2017|Sonter et al. 2017]] ). Deforestation significantly weakens the converted land as a carbon sink and in severe cases may even create a net emissions source.

A broad-based substitution of monolithic engineered timber systems for steel and concrete in mid-rise urban buildings offers the opportunity to transform cityscapes from their current status as net sources of GHG emissions into large-scale, human-made carbon sinks. The storage of photosynthetic forest carbon through the substitution of biomass-based structural materials for emissions-intensive steel and concrete is an opportunity for urban infrastructure. The construction of timber buildings for 2.3 billion new urban dwellers from 2020 to 2050 could store between 0.01 and 0.68 GtCO 2 per year depending on the scenario and the average floor area per capita. Over 30 years, wood-based construction can accumulate between 0.25 and 20 GtCO 2 and reduce cumulative emissions from 4 GtCO 2 (range of 7–20 GtCO 2 ) to 2 GtCO 2 (range of 0.3–10 GtCO 2 ) ( ''high confidence'' ) ( [[#Churkina--2020|Churkina et al. 2020]] ).

Figure 8.17 indicates that new and emerging structural assemblies in engineered timber rival the structural capacity of steel and reinforced concrete while offering the benefit of storing significant quantities of atmospheric carbon (see also Figure 8.22). ‘Mass timber’ refers to engineered wood products that are laminated from smaller boards or lamella into larger structural components such as glue-laminated (glulam) beams or cross-laminated timber (CLT) panels. Methods of mass-timber production that include finger-jointing, longitudinal and transverse lamination with both liquid adhesive and mechanical fasteners, have allowed for the reformulation of large structural timbers. The parallel-to-grain strength of mass (engineered) timber is similar to that of reinforced concrete ( [[#Ramage--2017|Ramage et al. 2017]] ). As much as half the weight of a given volume of wood is carbon, sequestered during forest growth as a by-product of photosynthesis ( [[#Martin--2018|Martin et al. 2018]] ). Mass timber is inflammable, but in large sections forms a self-protective charring layer when exposed to fire that will protect the remaining ‘cold wood’ core. This property, formed as massive structural sections, is recognised in the fire safety regulations of building codes in several countries, which allow mid- and high-rise buildings in timber. Ongoing studies have addressed associated concerns about the vulnerability of wood to decay and the capacity of structural timber systems to withstand seismic and storm-related stresses.

<div id="_idContainer00c" class="Basic-Text-Frame"></div>

[[File:e7b335f444ba0f44018ea740d878d3a0 IPCC_AR6_WGIII_Figure_8_17.png]]

'''Figure 8.17: Relative volume of a given weight, its carbon emissions, and carbon storage capacity of primary structural materials comparing one tonne of concrete, steel, and timber.''' Concrete and steel have substantial embodied carbon emissions with minimal carbon storage capacities, while timber stores a considerable quantity of carbon with a relatively small ratio of carbon emissions-to-material volume. The displayed carbon storage of concrete is the theoretical maximum value, which may be achieved after hundreds of years. Cement ratios of 10%, 15%, and 20% are assumed to estimate minimum, mean, and maximum carbon storage in concrete. Carbon storage of steel is not displayed as it is negligible (0.004 tonne C per tonne of steel). The middle-stacked bars represent the mean carbon emission or mean carbon storage values displayed in bold font and underlined. The darker and lighter coloured stacked bars depict the minimum and maximum values. Grey tones represent carbon emissions and green tones are given for storage capacity values. Construction materials have radically different volume-to-weight ratios, as well as material intensity (see representations of structural columns in the upper panel. These differences should be accounted for in the estimations of their carbon storage and emissions (see also Figure 8.22). Source: adapted with permission from [[#Churkina--2020|Churkina et al. (2020)]] .

Transitioning to biomass-based building materials, implemented through the adoption of engineered structural timber products and assemblies, will succeed as a mitigation strategy only if working forests are managed and harvested sustainably ( [[#Churkina--2020|Churkina et al. 2020]] ). Since future urban growth and the construction of timber cities may lead to increased timber demand in regions with low forest cover, it is necessary to systematically analyse timber demand, supply, trade, and potential competition for agricultural land in different regions ( [[#Pomponi--2020|Pomponi et al. 2020]] ). The widespread adoption of biomass-based urban construction materials and techniques will demand more robust forest and urban land governance and management policies, as well as internationally standardised carbon accounting methods to properly value and incentivise forest restoration, afforestation, and sustainable silviculture.

Expansion of agroforestry practices may help to reduce land-use conflicts between forestry and agriculture. Harvesting pressures on forests can be reduced through the reuse and recycling of wooden components from dismantled timber buildings. Potential synergies between the carbon sequestration capacity of forests and the associated carbon storage capacity of dense mid-rise cities built from engineered timber offer the opportunity to construct carbon sinks deployed at the scale of landscapes, sinks that are at least as durable as other buildings ( [[#Churkina--2020|Churkina et al. 2020]] ). Policies and practices promoting design for disassembly and material reuse will increase their durability.

<div id="8.4.4" class="h2-container"></div>

<span id="urban-green-and-blue-infrastructure"></span>
=== 8.4.4 Urban Green and Blue Infrastructure ===

<div id="h2-18-siblings" class="h2-siblings"></div>

The findings of AR6 WGI and WGII have underscored the importance of urban green and blue infrastructure for reducing the total warming in urban areas due to its local cooling effect on temperature and its benefits for climate adaptation ( [[#IPCC--2021|IPCC 2021]] ; Cross-Working Group Box 2 in this chapter). Urban green and blue infrastructure in the context of nature-based solutions (NBS) involves the protection, sustainable management, and restoration of natural or modified ecosystems while simultaneously providing benefits for human well-being and biodiversity ( [[#IUCN--2021|IUCN 2021]] ) (see Glossary for additional definitions). As an umbrella concept, urban NBS integrates established ecosystem-based approaches that provide multiple ecosystem services and are important in the context of societal challenges related to urbanisation, climate change, and reducing GHG emissions through the conservation and expansion of carbon sinks ( [[#Naumann--2014|Naumann et al. 2014]] ; [[#Raymond--2017|Raymond et al. 2017]] ) ( [[#8.1.6.1|Section 8.1.6.1]] ).

Urban green and blue infrastructure includes a wide variety of options, from street trees, parks, and sustainable urban drainage systems ( [[#Davis--2017|Davis and Naumann 2017]] ), to building-related green roofs or green facades, including green walls and vertical forests ( [[#Enzi--2017|Enzi et al. 2017]] ). Figure 8.18 synthesises urban green and blue infrastructure based on urban forests, street trees, green roofs, green walls, blue spaces, greenways, and urban agriculture. Key mitigation benefits, adaptation co-benefits, and SDG linkages are represented by types of green and blue infrastructure. Local implementations of urban green and blue infrastructure can pursue these linkages while progressing toward inclusive sustainable urban planning (SDG 11.3) and the provision of safe, inclusive and accessible green and public spaces for all (SDG 11.7) ( [[#Butcher-Gollach--2018|Butcher-Gollach 2018]] ; [[#Pathak--2018|Pathak and Mahadevia 2018]] ; [[#Rigolon--2018|Rigolon et al. 2018]] ; [[#Anguelovski--2019|Anguelovski et al. 2019]] ; [[#Buyana--2019|Buyana et al. 2019]] ; [[#Azunre--2021|Azunre et al. 2021]] ) ( [[#8.2|Section 8.2]] ).

<div id="_idContainer00d" class="Basic-Text-Frame"></div>

[[File:bf885970b9cf3b74e41a7327b90027fd IPCC_AR6_WGIII_Figure_8_18a.png]] [[File:3e3403f793ff8fece611faae5f68677a IPCC_AR6_WGIII_Figure_8_18b.png]]

'''Figure 8.18: Key mitigation benefits, adaptation co-benefits, and SDG linkages of urban green and blue infrastructure.''' Panel '''(b)''' evaluates those strategies in the context of their mitigation benefits, adaptation co-benefits, and linkages to the SDGs. Urban forests and street trees provide the greatest mitigation benefit because of their ability to sequester and store carbon while simultaneously reducing building energy demand. Moreover, they provide multiple adaptation co-benefits and synergies based on the linkages to the SDGs (Figure 8.4). The assessments of mitigation benefits are dependent on context, scale, and spatial arrangement of each green and blue infrastructure type and their proximity to buildings. Mitigation benefits due to reducing municipal water use are based on reducing wastewater loads that reduce energy use in wastewater treatment plants. The sizes of the bars are illustrative and their relative size is based on the authors’ best understanding and assessment of the literature.

<div id="8.4.4.1" class="h3-container"></div>

<span id="the-mitigation-potential-of-urban-trees-and-associated-co-benefits"></span>
==== 8.4.4.1 The Mitigation Potential of Urban Trees and Associated Co-benefits ====

<div id="h3-13-siblings" class="h3-siblings"></div>

Due to their potential to store relatively high amounts of carbon compared to other types of urban vegetation, as well as their ability to provide many climate mitigation co-benefits ( ''high agreement, robust evidence'' ), natural area protection and natural forest management in urban areas is an important priority for cities looking to mitigate climate change. Globally, urban tree cover averages 26.5%, but varies from an average of 12% in deserts to 30.4% in forested regions ( [[#Nowak--2020|Nowak and Greenfield 2020]] ).

Global urban tree carbon storage is approximately 7.4 billion tonnes (GtC) given 363 million hectares of urban land, 26.5% tree cover, and an average carbon storage density of urban tree cover of 7.69 kgC m –2 (kilograms carbon per square metre) ( [[#Nowak--2013|Nowak et al. 2013]] ; World Bank et al. 2013). Estimated global annual carbon sequestration by urban trees is approximately 217 million tonnes (MtC) given an average carbon sequestration density per unit urban tree cover of 0.226 kgC m –2 ( [[#Nowak--2013|Nowak et al. 2013]] ). With an average plantable (non-tree and non-impervious) space of 48% globally ( [[#Nowak--2020|Nowak and Greenfield 2020]] ), the carbon storage value could nearly triple if all this space is converted to tree cover. In Europe alone, if 35% of the urban surfaces (26,450 km 2 ) were transformed into green surfaces, the mitigation potential based on carbon sequestration would be an estimated 25.9 MtCO 2 yr −1 with the total mitigation benefit being 55.8 MtCO 2 yr −1 , including an energy saving of about 92 TWh yr −1 ( [[#Quaranta--2021|Quaranta et al. 2021]] ). Other co-benefits include reducing urban runoff by about 17.5% and reducing summer temperatures by 2.5°C–6°C ( [[#Quaranta--2021|Quaranta et al. 2021]] ).

Urban tree carbon storage is highly dependent on biome. For example, carbon sequestered by vegetation in Amazonian forests is two to five times higher compared to boreal and temperate forests ( [[#Blais--2005|Blais et al. 2005]] ). At the regional level, the estimated carbon storage density rates of tree cover include a range of 3.14–14.1 kgC m –2 in the United States, 3.85–5.58 kgC m –2 in South Korea, 1.53–9.67 kgC m –2 in Barcelona, Spain, 28.1–28.9 kgC m –2 in Leicester, England, and an estimated 6.82 kgC m –2 in Leipzig, Germany and 4.28 kgC m –2 in Hangzhou, China ( [[#Nowak--2013|Nowak et al. 2013]] ). At the local scale, above- and below-ground tree carbon densities can vary substantially, as with carbon in soils and dead woody materials. The conservation of natural mangroves has been shown to provide urban mitigation benefits through carbon sequestration, as demonstrated in the Philippines ( [[#Abino--2014|Abino et al. 2014]] ). Research on urban carbon densities from the Southern Hemisphere will contribute to better estimates.

On a per-tree basis, urban trees offer the most potential to mitigate climate change through both carbon sequestration and GHG emissions reduction from reduced energy use in buildings ( [[#Nowak--2017|Nowak et al. 2017]] ). Maximum possible street tree planting among 245 world cities could reduce residential electricity use by about 0.9–4.8% annually ( [[#McDonald--2016|McDonald et al. 2016]] ). Urban forests in the United States reduce building energy use by 7.2%, equating to an emissions reduction of 43.8 MtCO 2 annually ( [[#Nowak--2017|Nowak et al. 2017]] ).

Urban trees can also mitigate some of the impacts of climate change by reducing the UHI effect and heat stress, reducing stormwater runoff, improving air quality, and supporting health and well-being in areas where the majority of the world’s population resides ( [[#Nowak--2007|Nowak and Dwyer 2007]] ). Urban forest planning and management can maximise these benefits for present and future generations by sustaining optimal tree cover and health (also see SDG linkages in Figure 8.4). Urban and peri-urban agriculture can also have economic benefits from fruit, ornamental, and medicinal trees ( [[#Gopal--2014|Gopal and Nagendra 2014]] ; [[#Lwasa--2017|Lwasa 2017]] ; [[#Lwasa--2018|Lwasa et al. 2018]] ).

<div id="box-8.2:-urban-carbon-storage:-an-example-from-new-york-city" class="h2-container box-container"></div>

<span id="box-8.2-urban-carbon-storage-an-example-fro-m-new-york-city"></span>
=== Box 8.2: Urban Carbon Storage: An Example from New York City ===

<div id="h2-19-siblings" class="h2-siblings"></div>

The structure, composition, extent, and growing conditions of vegetation in cities has an influence on their potential for mitigating climate change ( [[#Pregitzer--2021|Pregitzer et al. 2021]] ). Urban natural areas, particularly forested natural areas, grow in patches and contain many of the same components as non-urban forests, such as high tree density, down woody material, and regenerating trees (Box 8.2, Figure 1).

<div id="_idContainer00e"></div>

[[File:be07ee82a2555dd5d2b39e1f2e66fe58 IPCC_AR6_WGIII_Box_8_1_Figure_1.png]]

'''Box 8.2, Figure 1: Estimates for carbon storage in natural area forests in New York City.''' '''(a)''' Mean estimated carbon stock per hectare in natural area forests ( [[#Pregitzer--2019a|Pregitzer et al. 2019a]] , 2021); '''(b)''' estimates for carbon stocks vary based on vegetation types; and '''(c)''' estimates of the amount of carbon stock in different forest pools per hectare. The proportion of the total estimated carbon stock per pool is out of the total estimated for the entire city (1.86 TgC). Source: adapted from [[#Pregitzer--2021|Pregitzer et al. (2021)]] .

Urban forested natural areas have unique benefits as they can provide habitat for native plants and animals, protecting local biodiversity in a fragmented landscape ( [[#Di%20Giulio--2009|Di Giulio et al. 2009]] ). Forests can have a greater cooling effect on cities than designed greenspaces, and the bigger the forest the greater the effect ( [[#Jaganmohan--2016|Jaganmohan et al. 2016]] ). In New York City, urban forested natural areas have been found to account for the majority of trees estimated in the city (69%), but are a minority of the total tree canopy (25%, or 5.5% of the total city land area) ( [[#Pregitzer--2019a|Pregitzer et al. 2019a]] ). In New York City, natural areas are estimated to store a mean of 263.5 MgC ha –1 (megagram carbon per hectare), adding up to 1.86 TgC (teragram carbon) across the city, with the majority of carbon (86%) being stored in the trees and soils ( [[#Pregitzer--2021|Pregitzer et al. 2021]] ). These estimates are similar to per-hectare estimates of carbon storage across different pools in non-urban forest types (Table 1), and 1.5 times greater than estimates for carbon stored in just trees across the entire city ( [[#Pregitzer--2021|Pregitzer et al. 2021]] ).

Within urban natural areas, the amount of carbon stored varies widely based on vegetation type, tree density, and the species composition (Box 8.2, Figure 1). The oak-hardwood forest type is one of the most abundant in New York City’s natural areas and is characterised by large and long-lived native hardwood tree species, with relatively dense wood. These forests store an estimated 311.5 MgC ha –1 . However, non-native exotic invasive species can be prevalent in the understory vegetation layer (&lt;1m height), and account for about 50% of cover in New York City ( [[#Pregitzer--2019b|Pregitzer et al. 2019b]] ).

This could lead to a trajectory where exotic understory species, which are often herbaceous, out-compete regenerating trees in the understory layer, alter the soil ( [[#Ward--2020|Ward et al. 2020]] ), and alter the forest canopy ( [[#Matthews--2016|Matthews et al. 2016]] ). A change in New York City’s vegetation structure and composition to a more open vegetation type could reduce the carbon storage by over half (open grassland 120.1 MgC ha –1 ).

When compared to estimates of carbon storage presented in other studies, the components (pools) of the natural area forests in New York City store carbon in similar proportions to other non-urban forests (see Table 1). This might suggest that in other geographies, similar adjacent non-urban forest types may store similar carbon stocks per unit area ( ''medium confidence'' ). However, despite similarities to non-urban forests, the urban context can lead to altered forest function and carbon cycling that should be considered. For example, trees growing in urban areas have been observed to grow at much higher rates due to higher access to light, nutrients, and increased temperatures ( [[#Gregg--2003|Gregg et al. 2003]] ; [[#Reinmann--2020|Reinmann et al. 2020]] ).

Higher growth rates coupled with the UHI effect have also been suggested to yield greater evaporative cooling by urban canopies relative to rural forests ( [[#Winbourne--2020|Winbourne et al. 2020]] ). Based on estimates in New York City, it is likely that the majority of tree biomass, and carbon in trees in cities, could be found in urban natural area forest patches ( ''medium agreement'' , ''limited evidence'' ). More research is needed to map urban natural areas, assess vegetation, and differentiate tree canopy types (natural versus non-natural) at fine scales within many cities and geographies. Accurate maps, as well as greater understanding of definitions of urban canopies and vegetation, could lead to better accounts for carbon stocks and the many other unique benefits they provide ( [[#Raciti--2012|Raciti et al. 2012]] ; [[#Pregitzer--2019a|Pregitzer et al. 2019a]] ).

Despite this potential, natural areas are inherently a minority land-use type in cities and should be viewed along with other types of urban tree canopy that occur in more designed environments that might out-perform natural areas in other ecosystem services. The mosaic of vegetation characteristics and growing conditions will yield different ecosystem services across cities ( [[#Pataki--2011|Pataki et al. 2011]] ) and should be an important consideration in planning, management, and policy in the future.

'''Box 8.2, Table 1: A selection of benchmark reference estimates of different carbon pools sampled and the related urban considerations to contextualise the results from New York City (NYC), United States (USA) natural area carbon stocks.''' The benchmark estimates are intended to provide a point of reference to help contextualise the calculations for carbon pools in NYC’s forests. Forest carbon is highly variable and dependent on microclimatic conditions such as moisture, microbial communities, and nutrient availability, all of which can be impacted by human activity in urban or altered environments. Standard errors and 95% confidence intervals can be found in [[#Pregitzer--2021|Pregitzer et al. (2021)]] . DBH: diameter at breast height; DWM: down woody material; CWM: coarse woody material and FWM: fine woody material. Source: [[#Pregitzer--2021|Pregitzer et al. (2021)]] .

{| class="wikitable"
|-
! Pool considered in NYC natural area

! Published estimates of carbon stock (MgC ha –1 )

! NYC estimated carbon stock (MgC ha –1 )

! Urban considerations

|-
| Live trees: all trees (&gt;2 cm DBH) including above and below ground

| 87.1: northeastern USA ( [[#Smith--2013|Smith et al. 2013]] )

73.3: NYC assuming 100% cover ( [[#Nowak--2013|Nowak et al. 2013]] )

| 135.4

| Lower ozone levels, higher CO 2 , warmer temperatures, and higher nutrient deposition could lead to increased growth rates and annual carbon sequestration. However, pollutants in soil (e.g., heavy metals), increased pests, and GHGs in the atmosphere (e.g., NO X and SO 2 ) could decrease annual tree growth and carbon sequestration ( [[#Gregg--2003|Gregg et al. 2003]] )

|-
| Groundcover: all vegetation growing &lt;1 m height

| 1.8: northeastern USA ( [[#Smith--2013|Smith et al. 2013]] )

| 5.5

| Anthropogenic disturbance creates canopy gaps that accelerate herbaceous growth; invasive vines are prevalent in urban forests that can alter tree survival and growth and soils ( [[#Matthews--2016|Matthews et al. 2016]] ; [[#Ward--2020|Ward et al. 2020]] )

|-
| Standing dead trees

| 5.1: northeastern USA ( [[#Smith--2013|Smith et al. 2013]] )

2.59: Massachusetts ( [[#Liu--2006|Liu et al. 2006]] )

| 5.8

| Removal may occur due to safety considerations

|-
| CWM: coarse (&gt;10 cm) and FWM (&gt;0.1 cm)

| 9.18: CWM – New York state

2.52: CWM – Massachusetts ( [[#Liu--2006|Liu et al. 2006]] )

6.37: FWM – New York ( [[#Woodall--2013|Woodall et al. 2013]] )

3.67: FWM northern hardwood; 0 to 227.94: Northern USA ( [[#Domke--2016|Domke et al. 2016]] )

| 15.25 (added together DWM and FWM)

| Removal may occur due to safety considerations

|-
| Litter and duff: depth measured

| 12: NYC ( [[#Pouyat--2002|Pouyat et al. 2002]] )

9.36: northern hardwood;

0.04: northern USA ( [[#Domke--2016|Domke et al. 2016]] )

| 10.95

| Decomposition increases with temperature ( [[#Hanson--2003|Hanson et al. 2003]] ); decreased ozone levels facilitate litter decay ( [[#Carreiro--2009|Carreiro et al. 2009]] )

|-
| Mineral soil (organic 30 cm)

| 104: to 30 cm depth, NYC ( [[#Cambou--2018|Cambou et al. 2018]] )

50: to 10 cm depth, NYC ( [[#Pouyat--2002|Pouyat et al. 2002]] )

| 105.11(30 cm) and 77.78 (10 cm)

| UHI and pollution alter the litter chemistry, decomposer organisms, conditions, and resources, which all influence respiration rates ( [[#Carreiro--2009|Carreiro et al. 2009]] ); earthworms, prevalent in urban areas, accelerate decay, but some carbon is sequestered in passive pools ( [[#Pouyat--2002|Pouyat et al. 2002]] ). Soil could be compacted.

|}

<div id="8.4.4.2" class="h3-container"></div>

<span id="benefits-of-green-roofs-green-walls-and-greenways"></span>
==== 8.4.4.2 Benefits of Green Roofs, Green Walls, and Greenways ====

<div id="h3-14-siblings" class="h3-siblings"></div>

Green roofs and green walls have potential to mitigate air and surface temperature, improve thermal comfort, and mitigate UHI effects ( [[#Jamei--2021|Jamei et al. 2021]] ; [[#Wong--2021|Wong et al. 2021]] ), while lowering the energy demand of buildings ( [[#Susca--2019|Susca 2019]] ) (Figure 8.18). Green roofs have the highest median cooling effect in dry climates (3°C) and the lowest cooling effect in hot, humid climates (1°C) ( [[#Jamei--2021|Jamei et al. 2021]] ). These mitigation potentials depend on numerous factors and the scale of implementation. The temperature reduction potential for green roofs when compared to conventional roofs can be about 4°C in winter and about 12°C during summer conditions ( [[#Bevilacqua--2016|Bevilacqua et al. 2016]] ). Green roofs can reduce building heating demands by about 10–30% compared to conventional roofs ( [[#Besir--2018|Besir and Cuce 2018]] ), 60–70% compared to black roofs, and 45–60% compared to white roofs ( [[#Silva--2016|Silva et al. 2016]] ). Green walls or facades can provide a temperature difference between air temperature outside and behind a green wall of up to 10°C, with an average difference of 5°C in Mediterranean contexts in Europe ( [[#Perini--2017|Perini et al. 2017]] ). The potential of saving energy for air conditioning by green facades can be around 26% in summer months. Considerations of the spatial context are essential given their dependence on climatic conditions ( [[#Susca--2019|Susca 2019]] ). Cities are diverse and emissions savings potentials depend on several factors, while the implementation of green roofs or facades may be prevented in heritage structures.

Green roofs have been shown to have beneficial effects in stormwater reduction ( [[#Andrés-Doménech--2018|Andrés-Doménech et al. 2018]] ). A global meta-analysis of 75 international studies on the potential of green roofs to mitigate runoff indicate that the runoff retention rate was on average 62% but with a wide range (0–100%) depending on a number of interdependent factors ( [[#Zheng--2021|Zheng et al. 2021]] ). These factors relate to the characteristics of the rainfall event (e.g., intensity) and characteristics of the green roof (e.g., substrate, vegetation type, and size), and of the climate and season type. A hydrologic modelling approach applied to an Italian case demonstrated that implementing green roofs may reduce peak runoff rates and water volumes by up to 35% in a 100% green roof conversion scenario ( [[#Masseroni--2016|Masseroni and Cislaghi 2016]] ).

Greenways support stormwater management to mitigate water runoff and urban floods by reducing the water volume (e.g., through infiltration) and by an attenuation or temporal shift of water discharge ( [[#Fiori--2020|Fiori and Volpi 2020]] ; [[#Pour--2020|Pour et al. 2020]] ). Using green infrastructure delays the time to runoff and reduces water volume but depends on the magnitude of floods ( [[#Qin--2013|Qin et al. 2013]] ). Measures are most effective for flood mitigation at a local scale; however, as the size of the catchment increases, the effectiveness of reducing peak discharge decreases ( [[#Fiori--2020|Fiori and Volpi 2020]] ). Reduction of water volume through infiltration can be more effective with rainfall events on a lower return rate. Overall, the required capacity for piped engineered systems for water runoff attenuation and mitigation can be reduced while lowering flow rates, controlling pollution transport, and increasing the capacity to store stormwater ( [[#Srishantha--2017|Srishantha and Rathnayake 2017]] ). Benefits for flood mitigation require a careful consideration of the spatial context of the urban area, the heterogeneity of the rainfall events, and characteristics of implementation ( [[#Qiu--2021|Qiu et al. 2021]] ). Maintenance costs and stakeholder coordination are other aspects requiring attention ( [[#Mguni--2016|Mguni et al. 2016]] ).

Providing a connected system of greenspace throughout the urban area may promote active transportation ( [[#Nieuwenhuijsen--2016|Nieuwenhuijsen and Khreis 2016]] ), thereby reducing GHG emissions. Soft solutions for improving green infrastructure connectivity for cycling is an urban NBS mitigation measure, although there is ''low evidence'' for emissions reductions. In the city of Lisbon, Portugal, improvements in cycling infrastructure and bike-sharing system resulted in 3.5 times more cyclists within two years ( [[#Félix--2020|Félix et al. 2020]] ). In Copenhagen, the cost of cycling (0.08 EUR km -1 ) is declining and is about six times lower than car driving (Euro 0.50/km) ( [[#Vedel--2017|Vedel et al. 2017]] ). In addition, participants were willing to cycle 1.84 km longer if the route has a designated cycle track and 0.8 km more if there are also green surroundings. Changes in urban landscapes, including through the integration of green infrastructure in sustainable urban and transport planning, can support the transition from private motorised transportation to public and physically active transportation in carbon-neutral, more liveable and healthier cities ( [[#Nieuwenhuijsen--2016|Nieuwenhuijsen and Khreis 2016]] ; [[#Nieuwenhuijsen--2020|Nieuwenhuijsen 2020]] ). Car infrastructure can be also transferred into public open and green space, such as in the Superblock model in Barcelona’s neighbourhoods ( [[#Rueda--2019|Rueda 2019]] ). Health impact assessment models estimated that 681 premature deaths may be prevented annually with this implementation ( [[#Mueller--2020|Mueller et al. 2020]] ) and the creation of greenways in Maanshan, China has stimulated interest in walking or cycling ( [[#Zhang--2020|Zhang et al. 2020]] ).

<div id="8.4.5" class="h2-container"></div>

<span id="socio-behavioural-aspects"></span>

=== 8.4.5 Socio-behavioural Aspects ===

<div id="h2-20-siblings" class="h2-siblings"></div>

Urban systems shape the behaviour and social structures of their residents through urban form, energy systems, and infrastructure – all of which provide a range of options for consumers to make choices about residential location, mobility, energy sources, and the consumption of materials, food, and other resources. The relative availability of options across these sectors has implications on urban emissions through individual behaviour. In turn, urban GHG emissions, as well as emissions from the supply chains of cities, are driven by the behaviour and consumption patterns of residents, with households accounting for over 60% of carbon emissions globally ( [[#Ivanova--2016|Ivanova et al. 2016]] ). The exclusion of consumption-based emissions and emissions that occur outside of city boundaries as a result of urban activities, however, will lead to significant undercounting. For example, a study of 79 major cities found that about 41% of consumption-based carbon footprints (1.8 GtCO 2 -eq of 4.4 GtCO 2 -eq) occurred outside of city boundaries.

Changes in behaviour across all areas (e.g., transport, buildings, food) could reduce an individual’s emissions by 5.6–16.2% relative to the accumulated GHG emissions from 2011 to 2050 in a baseline scenario modelled with the Global Change Assessment Model ( [[#van%20de%20Ven--2018|van de Ven et al. 2018]] ). In other models, behaviour change in transport and residential energy use could reduce emissions by 2 GtCO 2 -eq in 2030 compared to 2019 ( [[#IEA--2020b|IEA 2020b]] ) (Chapter 5). Voluntary behaviour change can support emissions reduction, but behaviours that are not convenient to change are unlikely to shift without changes to policy ( [[#Sköld--2018|Sköld et al. 2018]] ). Cities can increase the capability of citizens to make sustainable choices by making these choices less onerous, through avenues such as changing urban form to increase locational and mobility options and providing feedback mechanisms to support socio-behavioural change.

Transport emissions can be reduced by options including telecommuting (0.3%), taking closer holidays (0.5%), avoiding short flights (0.5%), using public transit (0.7%), cycling (0.6%), car sharing (1.1%), and carpool commuting (1.2%); all reduction estimates reflect cumulative per capita emission savings relative to baseline emissions for the period 2011–2050, and assume immediate adoption of behavioural changes ( [[#van%20de%20Ven--2018|van de Ven et al. 2018]] ). Cities can support voluntary shift to walking, cycling, and transit instead of car use through changes to urban form, such as TOD ( [[#Kamruzzaman--2015|Kamruzzaman et al. 2015]] ), increased density of form with co-location of activities ( [[#Ma--2015|Ma et al. 2015]] ; [[#Ding--2017|Ding et al. 2017]] ; [[#Duranton--2018|Duranton and Turner 2018]] ; [[#Masoumi--2019|Masoumi 2019]] ), and greater intersection density and street integration ( [[#Koohsari--2016|Koohsari et al. 2016]] ). Mechanisms such as providing financial incentives or disincentives for car use can also be effective in reducing emissions ( [[#Wynes--2018|Wynes et al. 2018]] ) ( [[#8.4.2|Section 8.4.2]] ).

Adopting energy efficient practices in buildings could decrease global building energy demand in 2050 by 33–44% compared to a business-as-usual scenario ( [[#Levesque--2019|Levesque et al. 2019]] ). Reductions in home energy use can be achieved by reducing floor area (0.5–3.0%), utilising more efficient appliances and lighting (2.7–5.0%), optimising thermostat settings (8.3–11%), using efficient heating and cooling technologies (6.7–10%), improving building insulation (2.9–4.0%), optimising clothes washing (5.0–5.7%), and optimising dishwashing (1–1.1%) ( [[#Levesque--2019|Levesque et al. 2019]] ). Building standards and mandates could work towards making these options required or more readily available and accessible. Residential appliance use, water heating, and thermostat settings can be influenced by feedback on energy use, particularly when paired with real-time feedback and/or instructions on how to reduce energy use ( [[#Kastner--2015|Kastner and Stern 2015]] ; [[#Stern--2016|Stern et al. 2016]] ; [[#Wynes--2018|Wynes et al. 2018]] ; [[#Tiefenbeck--2019|Tiefenbeck et al. 2019]] ). The energy-saving potentials of changing occupant behaviour can range between 10% and 25% for residential buildings, and between 5% and 30% for commercial buildings ( [[#Zhang--2018|Zhang et al. 2018]] ). Households are more likely to invest in energy-related home technologies if they believe it financially benefits (rather than disadvantages) them, increases comfort, or will benefit the natural environment ( [[#Kastner--2015|Kastner and Stern 2015]] ). Social influences and availability of funding for household energy measures also support behaviour change ( [[#Kastner--2015|Kastner and Stern 2015]] ).

<div id="8.4.5.1" class="h3-container"></div>

<span id="increasing-locational-and-mobility-options"></span>
==== 8.4.5.1 Increasing Locational and Mobility Options ====

<div id="h3-15-siblings" class="h3-siblings"></div>

Spatial planning, urban form, and infrastructure can be utilised to deliberately increase both locational and mobility options for socio-behavioural change in support of urban mitigation. The mitigation impacts of active travel can include a reduction of mobility-related lifecycle CO 2 emissions by about 0.5 tonnes over a year when an average person cycles one trip per day more, and drives one trip per day less, for 200 days a year ( [[#Brand--2021|Brand et al. 2021]] ). Urban areas that develop and implement effective 15/20-minute city programmes are very likely to reduce urban energy use and multiply emission reductions, representing an important cascading effect.

Accessibility as a criterion widens the focus beyond work trips and VKT/VMT, paying attention to a broader set of destinations beyond workplaces, as well as walking and biking trips or active travel. It holds promise for targeting and obtaining greater reductions in GHG emissions in household travel by providing access through walking, biking, and public transit. Accessibility as a criterion for urban form has been embedded in neighbourhood form models since at least the last century and in more recent decades in the ‘urban village’ concept of the New Urbanism ( [[#Duany--1991|Duany and Plater-Zyberck 1991]] ) and TODs ( [[#Calthorpe--1993|Calthorpe 1993]] ). However, accessibility did not gain much traction in urban planning and transportation until the last decade. The experience of cities and metropolitan areas with the COVID-19 pandemic has led to a further resurgence in interest and importance ( [[#Handy--2020|Handy 2020]] ; [[#Hu--2020|Hu et al. 2020]] ), and it is becoming a criterion at the core of the concept of the 15/20-minute city ( [[#Moreno--2021|Moreno et al. 2021]] ; [[#Pozoukidou--2021|Pozoukidou and Chatziyiannaki 2021]] ). Initially, neighbourhoods have been designed to provide quality, reliable services within 15 or 20 minutes of active transport (i.e., walking or cycling), as well as a variety of housing options and open space ( [[#Portland%20Bureau%20of%20Planning%20and%20Sustainability--2012|Portland Bureau of Planning and Sustainability 2012]] ; [[#Pozoukidou--2021|Pozoukidou and Chatziyiannaki 2021]] ; [[#State%20Government%20of%20Victoria--2021|State Government of Victoria 2021]] ). Community life circles strategy for urban areas has also emphasised walking access and health ( [[#Weng--2019|Weng et al. 2019]] ; [[#Wu--2021|Wu et al. 2021]] ). The growing popularity of the 15/20-minute city movement has significant potential for reducing VMT/VKT and associated GHG emissions.

<div id="8.4.5.2" class="h3-container"></div>

<span id="avoiding-minimising-and-recycling-waste"></span>
==== 8.4.5.2 Avoiding, Minimising, and Recycling Waste ====

<div id="h3-16-siblings" class="h3-siblings"></div>

The waste sector is a significant source of GHG emissions, particularly CH 4 ( [[#Gonzalez-Valencia--2016|Gonzalez-Valencia et al. 2016]] ; [[#Nisbet--2019|Nisbet et al. 2019]] ). Currently, the sector remains the largest contributor to urban emissions after the energy sector, even in low-carbon cities ( [[#Lu--2019|Lu and Li 2019]] ). Since waste management systems are usually under the control of municipal authorities, they are a prime target for city-level mitigation efforts with co-benefits ( [[#EC--2015|EC 2015]] , 2020; [[#Gharfalkar--2015|Gharfalkar et al. 2015]] ; [[#Herrero--2018|Herrero and Vilella 2018]] ; [[#Zaman--2019|Zaman and Ahsan 2019]] ). Despite general agreement on mitigation impacts, quantification remains challenging due to differing assumptions for system boundaries and challenges related to measuring avoided waste ( [[#Zaman--2013|Zaman and Lehmann 2013]] ; [[#Bernstad%20Saraiva%20Schott--2015|Bernstad Saraiva Schott and Cánovas 2015]] ; [[#Matsuda--2018|Matsuda et al. 2018]] ).

The implementation of the waste hierarchy from waste prevention onward, as well as the effectiveness of waste separation at source, involves socio-behavioural options in the context of urban infrastructure ( [[#Sun--2018a|Sun et al. 2018a]] ; [[#Hunter--2019|Hunter et al. 2019]] ). Managing and treating waste as close to the point of generation as possible, including distributed waste treatment facilities, can minimise transport-related emissions, congestion, and air pollution. Home composting and compact urban form can also reduce waste transport emissions ( [[#Oliveira--2017|Oliveira et al. 2017]] ). Decentralised waste management can reinforce source-separation behaviour since the resulting benefits can be more visible ( [[#Eisted--2009|Eisted et al. 2009]] ; [[#Hoornweg--2012|Hoornweg and Bhada-Tata 2012]] ; [[#Linzner--2013|Linzner and Lange 2013]] ). Public acceptance for waste management is greatest when system costs for citizens are reduced, there is greater awareness of primary waste separation at source, and there are positive behavioural spill-overs across environmental policies ( [[#Milutinović--2016|Milutinović et al. 2016]] ; [[#Boyer--2017|Boyer and Ramaswami 2017]] ; [[#Díaz-Villavicencio--2017|Díaz-Villavicencio et al. 2017]] ; [[#Slorach--2020|Slorach et al. 2020]] ). In addition to the choice of technology, the costs of waste management options depend on the awareness of system users that can represent time-dependent costs ( [[#Khan--2016|Khan et al. 2016]] ; [[#Chifari--2017|Chifari et al. 2017]] ; [[#Ranieri--2018|Ranieri et al. 2018]] ; [[#Tomić--2020|Tomić and Schneider 2020]] ). Waste management systems and the inclusion of materials from multiple urban sectors for alternative by-products can increase scalability ( [[#Eriksson--2015|Eriksson et al. 2015]] ; [[#Boyer--2017|Boyer and Ramaswami 2017]] ; [[#D’Adamo--2021|D’Adamo et al. 2021]] ). As a broader concept, circular economy approaches can contribute to managing waste (Box 12.8) with varying emissions impacts ( [[IPCC:Wg3:Chapter:Chapter-5#5.3.4|Section 5.3.4]] ).

The generation and composition of waste varies considerably from region to region and city to city. So do the levels of institutional management, infrastructure, and (informal) work in waste disposal activities. Depending on context, policy priorities are directed towards reducing waste generation and transforming waste to energy or other products in a circular economy ( [[#Diaz--2017|Diaz 2017]] ; [[#Ezeudu--2019|Ezeudu and Ezeudu 2019]] ; [[#Joshi--2019|Joshi et al. 2019]] ; [[#Calderón%20Márquez--2020|Calderón Márquez and Rutkowski 2020]] ; [[#Fatimah--2020|Fatimah et al. 2020]] ). Similarly, waste generation, waste collection coverage, recycling, and composting rates, as well as the means of waste disposal and treatment, differ widely, including the logistics of urban waste management systems. Multiple factors influence waste generation, and regions with similar urbanisation rates can generate different levels of waste per capita ( [[#Kaza--2018|Kaza et al. 2018]] ).

Under conventional practices, municipal solid waste is projected to increase by about 1.4 Gt between 2016 and 2050, reaching 3.4 Gt in 2050 ( [[#Kaza--2018|Kaza et al. 2018]] ). Integrated policymaking can increase the energy, material, and emissions benefits in the waste management sector ( [[#Hjalmarsson--2015|Hjalmarsson 2015]] ; [[#Fang--2017|Fang et al. 2017]] ; [[#Jiang--2017|Jiang et al. 2017]] ). Organisational structure and programme administration poses demands for institutional capacity, governance, and cross-sectoral coordination for obtaining the maximum benefit ( [[#Hjalmarsson--2015|Hjalmarsson 2015]] ; [[#Kalmykova--2016|Kalmykova et al. 2016]] ; [[#Conke--2018|Conke 2018]] ; [[#Marino--2018|Marino et al. 2018]] ; [[#Yang--2018|Yang et al. 2018]] ).

The informal sector plays a critical role in waste management, particularly but not exclusively in developing countries ( [[#Linzner--2013|Linzner and Lange 2013]] ; [[#Dias--2016|Dias 2016]] ). Sharing of costs and benefits, and transforming informality of waste recycling activities into programmes, can support distributional effects ( [[#Conke--2018|Conke 2018]] ; [[#Grové--2018|Grové et al. 2018]] ). Balancing centralised and decentralised waste management options along low-carbon objectives can address potential challenges in transforming informality ( [[#de%20Bercegol--2019|de Bercegol and Gowda 2019]] ). Overall, the positive impacts of waste management on employment and economic growth can be increased when informality is transformed to stimulate employment opportunities for value-added products with an estimated 45 million jobs in the waste management sector by 2030 ( [[#Alzate-Arias--2018|Alzate-Arias et al. 2018]] ; [[#Coalition%20for%20Urban%20Transitions--2020|Coalition for Urban Transitions 2020]] ; [[#Soukiazis--2020|Soukiazis and Proença 2020]] ).

<div id="8.4.6" class="h2-container"></div>

<span id="urban-rural-linkages"></span>
=== 8.4.6 Urban-Rural Linkages ===

<div id="h2-21-siblings" class="h2-siblings"></div>

Urban-rural linkages, especially through waste, food, and water, are prominent elements of the urban system, given that cities are open systems that depend on their hinterlands for imports and exports ( [[#Pichler--2017|Pichler et al. 2017]] ), and include resources, products for industrial production or final use ( [[#8.1.6|Section 8.1.6]] ). As supply chains are becoming increasingly global in nature, so are the resource flows with the hinterlands of cities. In addition to measures within the jurisdictional boundaries of cities, cities can influence large upstream emissions through their supply chains, as well as through activities that rely on resources outside city limits. The dual strategy of implementing local actions and taking responsibility for the entire supply chains of imported and exported goods can reduce GHG emissions outside of a city’s administrative boundaries (Figure 8.15).

Waste prevention, minimisation, and management provides the potential of alleviating resource usage and upstream emissions from urban settlements ( [[#Swilling--2018|Swilling et al. 2018]] ; [[#Chen--2020a|Chen et al. 2020a]] ; [[#Harris--2020|Harris et al. 2020]] ). Integrated waste management and zero-waste targets can allow urban areas to maximise the mitigation potential while reducing pressures on land use and the environment. This mitigation option reduces emissions due to (i) avoided emissions upstream in the supply chain of materials based on measures for recycling and the reuse of materials; (ii) avoided emissions due to land-use changes as well as emissions that are released into the atmosphere from waste disposal; and (ii) avoided primary energy (see Glossary) spending and emissions. Socio-behavioural change that reduces waste generation, combined with technology and infrastructure according to the waste hierarchy, can be especially effective. The mitigation potential of waste-to-energy depends on the technological choices that are undertaken (e.g., anaerobic digestion of the organic fraction), the emissions factor of the energy mix that it replaces, and its broader role within integrated municipal solid management practices ( [[#Eriksson--2015|Eriksson et al. 2015]] ; [[#Potdar--2016|Potdar et al. 2016]] ; [[#Yu--2016|Yu and Zhang 2016]] ; [[#Soares--2017|Soares and Martins 2017]] ; [[#Alzate-Arias--2018|Alzate-Arias et al. 2018]] ; [[#Islam--2018|Islam 2018]] ). The climate mitigation potential of anaerobic digestion plants can increase when power, heat and/or cold is co-produced ( [[#Thanopoulos--2020|Thanopoulos et al. 2020]] ).

Urban food systems, as well as city-regional production and distribution of food, factors into supply chains. Reducing food demand from urban hinterlands can have a positive impact on energy and water demand for food production ( [[#Eigenbrod--2015|Eigenbrod and Gruda 2015]] ) (see ‘food system’ in Glossary). Managing food waste in urban areas through recycling or reduction of food waste at source of consumption would require behavioural change ( [[#Gu--2019|Gu et al. 2019]] ). Urban governments could also support shifts towards more climate-friendly diets, including through procurement policies. These strategies have created economic opportunities or have enhanced food security while reducing the emissions that are associated with waste and the transportation of food. Strategies for managing food demand in urban areas would depend on the integration of food systems in urban planning.

Urban and peri-urban agriculture and forestry is pursued by both developing and some developed country cities. There is increasing evidence for economically feasible, socially acceptable, and environmentally supportive urban and peri-urban agricultural enterprises although these differ between cities ( [[#Brown--2015|Brown 2015]] ; [[#Eigenbrod--2015|Eigenbrod and Gruda 2015]] ; [[#Blay-Palmer--2019|Blay-Palmer et al. 2019]] ; [[#De%20la%20Sota--2019|De la Sota et al. 2019]] ). The pathways include integrated crop-livestock systems, urban agroforestry systems, aquaculture-livestock-crop systems, and crop systems ( [[#Lwasa--2015|Lwasa et al. 2015]] ), while the mitigation potential of urban and peri-urban agriculture has ''medium agreement'' and ''low evidence'' . Strategies for urban food production in cities have also relied on recycling nutrients from urban waste and utilisation of harvested rainwater or wastewater.

Systems for water reallocation between rural areas and urban areas will require change by leveraging technological innovations for water capture, water purification, and reducing water wastage either by plugging leakages or changing behaviour in regard to water use ( [[#Eigenbrod--2015|Eigenbrod and Gruda 2015]] ; [[#Prior--2018|Prior et al. 2018]] ). Reducing energy use for urban water systems involves reducing energy requirements for water supply, purification, distribution, and drainage ( [[#Ahmad--2020|Ahmad et al. 2020]] ). Various levels of rainwater harvesting in urban settings for supplying end-use water demands or supporting urban food production can reduce municipal water demands, including by up to 20% or more in Cape Town ( [[#Fisher-Jeffes--2017|Fisher-Jeffes et al. 2017]] ).

<div id="8.4.7" class="h2-container"></div>

<span id="cross-sectoral-integration"></span>
=== 8.4.7 Cross-sectoral Integration ===

<div id="h2-22-siblings" class="h2-siblings"></div>

There are two broad categories of urban mitigation strategies. One is from the perspective of key sectors, including clean energy, sustainable transport, and construction ( [[#Rocha--2017|Rocha et al. 2017]] ; [[#Álvarez%20Fernández--2018|Álvarez Fernández 2018]] ; [[#Magueta--2018|Magueta et al. 2018]] ; [[#Seo--2018|Seo et al. 2018]] ; [[#Waheed--2018|Waheed et al. 2018]] ); the coupling of these sectors can be enabled through electrification ( [[#8.4.3.1|Section 8.4.3.1]] ). The other looks at the needs for emissions through a more systematic or fundamental understanding of urban design, urban form, and urban spatial planning ( [[#Wang--2017|Wang et al. 2017]] ; [[#Privitera--2018|Privitera et al. 2018]] ), and proposes synergistic scenarios for their integration for carbon neutrality ( [[#Ravetz--2020|Ravetz et al. 2020]] ).

Single-sector analysis in low-carbon urban planning examines solutions in supply, demand, operations, and assets management either from technological efficiency or from a system approach. For example, the deployment of renewable energy technologies for urban mitigation can be evaluated in detail and the transition to zero-carbon energy in energy systems and EVs in the transport sector can bring about a broad picture for harvesting substantial low-carbon potentials through urban planning ( ''high agreement'' , ''robust evidence'' ) ( [[#Álvarez%20Fernández--2018|Álvarez Fernández 2018]] ; [[#Tarigan--2018|Tarigan and Sagala 2018]] ).

The effects of urban carbon lock-in on land use, energy demand, and emissions vary depending on national circumstances ( [[#Wang--2017|Wang et al. 2017]] ; [[#Pan--2020|Pan 2020]] ). Systematic consideration of urban spatial planning and urban forms, such as polycentric urban regions and rational urban population density, is essential not only for liveability but also for achieving net-zero GHG emissions as it aims to shorten commuting distances and is able to make use of NBS for energy and resilience ( ''high agreement'' , ''medium evidence'' ). However, crucial knowledge gaps remain in this field. There is a shortage of consistent and comparable GHG emissions data at the city level and a lack of in-depth understanding of how urban renewal and design can contribute to carbon neutrality ( [[#Mi--2019|Mi et al. 2019]] ).

An assessment of opportunities suggests that strategies for material efficiency that cross-cut sectors will have greater impact than those that focus one-dimensionally on a single sector ( [[#UNEP%20IRP--2020|UNEP IRP 2020]] ). In the urban context, this implies using less material by the design of physical infrastructure based on light-weighting and down-sizing, material substitution, prolonged use, as well as enhanced recycling, recovery, remanufacturing, and reuse of materials and related components. For example, light-weight design in residential buildings and passenger vehicles can enable about 20% reductions in lifecycle material-related GHG emissions ( [[#UNEP%20IRP--2020|UNEP IRP 2020]] ).

The context of urban areas as the nexus of both sectors (i.e., energy, and urban form and planning) underlines the role of urban planning and policies in contributing to reductions in material-related GHG emissions while enabling housing and mobility services for the benefit of inhabitants. In addition, combining resource efficiency measures with strategic densification can increase the GHG reduction potential and lower resource impacts. While resource efficiency measures are estimated to reduce GHG emissions, land use, water consumption, and metal use impacts from a lifecycle assessment perspective by 24–47% over a baseline, combining resource efficiency with strategic densification can increase this range to about 36–54% over the baseline for a sample of 84 urban settlements worldwide ( [[#Swilling--2018|Swilling et al. 2018]] ).

Evidence from a systematic scoping of urban solutions further indicates that the GHG abatement potential of integrating measures across urban sectors is greater than the net sum of individual interventions due to the potential of realising synergies when realised in tandem, such as urban energy infrastructure and renewable energy ( [[#Sethi--2020|Sethi et al. 2020]] ). Similarly, system-wide interventions, such as sustainable urban form, are important for increasing the GHG abatement potential of interventions based on individual sectoral projects ( [[#Sethi--2020|Sethi et al. 2020]] ). Overall, the pursuit of inter-linkages among urban interventions is important for accelerating GHG reductions in urban areas ( [[#Sethi--2020|Sethi et al. 2020]] ); this is also important for reducing reliance on carbon capture and storage technologies (CCS) at the global scale (Figures 8.15 and 8.21).

Currently, cross-sectoral integration is one of the main thematic areas of climate policy strategies among the actions that are adopted by signatories to an urban climate and energy network ( [[#Hsu--2020c|Hsu et al. 2020c]] ). Although not as prevalent as those for efficiency, municipal administration, and urban planning measures ( [[#Hsu--2020c|Hsu et al. 2020c]] ), strategies that are cross-cutting in nature across sectors can provide important emission-saving opportunities for accelerating the pace of climate mitigation in urban areas. Cross-sectoral integration also involves mobilising urban actors to increase innovation in energy services and markets beyond individual energy efficiency actions ( [[#Hsu--2020c|Hsu et al. 2020c]] ). Indeed, single-sector versus cross-sector strategies for 637 cities from a developing country can enable an additional 15–36% contribution to the national climate mitigation reduction potential ( [[#Ramaswami--2017a|Ramaswami et al. 2017a]] ). The strategies at the urban level involved those for energy cascading and exchange of materials that connected waste, heat, and electricity strategies ( [[#8.5|Section 8.5]] and Box 8.4).

The feasibility of upscaling multiple response options depends on the urban context as well as the stage of urban development, with certain stages providing additional opportunities over others ( [[#Dienst--2015|Dienst et al. 2015]] ; [[#Maier--2016|Maier 2016]] ; [[#Affolderbach--2017|Affolderbach and Schulz 2017]] ; [[#Roldán-Fontana--2017|Roldán-Fontana et al. 2017]] ; [[#Zhao--2017a|Zhao et al. 2017a]] ; [[#Beygo--2017|Beygo and Yüzer 2017]] ; [[#Lwasa--2017|Lwasa 2017]] ; [[#Pacheco-Torres--2017|Pacheco-Torres et al. 2017]] ; [[#Alhamwi--2018|Alhamwi et al. 2018]] ; [[#Kang--2018|Kang and Cho 2018]] ; [[#Lin--2018|Lin et al. 2018]] ; [[#Collaço--2019|Collaço et al. 2019]] ) (Figures 8.19 and 8.21, and Section 8.SM.2).

<div id="8.5" class="h1-container"></div>

<span id="governance-institutio-ns-and-finance"></span>