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

=== 8.4.5 Socio-behavioural Aspects ===

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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]] ).

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==== 8.4.5.1 Increasing Locational and Mobility Options ====

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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.

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==== 8.4.5.2 Avoiding, Minimising, and Recycling Waste ====

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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]] ).

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