Editing IPCC:AR6/WGIII/Chapter-9 (section)

== 9.5 Non-technological and Behavioural Mitigation Options and Strategies ==

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Non-technological (NT) measures are key for low-carbon buildings, but still attract less attention than technological measures ( [[#Creutzig--2016|Creutzig et al. 2016]] , 2018; [[#Ruparathna--2016|Ruparathna et al. 2016]] ; [[#Mundaca--2019|Mundaca et al. 2019]] ; [[#Vence--2019|Vence and Pereira 2019]] ; [[#Cabeza--2020|Cabeza et al. 2020]] ; [[#Mata--2021b|Mata et al. 2021b]] ). The section is set out to understand, over the building’s lifecycle, NT determinants of buildings’ energy demand and emissions ( [[#9.5.1|Section 9.5.1]] ); to present NT climate mitigation actions ( [[#9.5.2|Section 9.5.2]] ); then, to understand how to get these actions implemented ( [[#9.5.3|Section 9.5.3]] ). The latter is a starting point in the design of policies ( [[#9.9|Section 9.9]] ).

<div id="9.5.1" class="h2-container"></div>

<span id="non-technological-determinants-of-energy-demand-and-carbon-emissions"></span>
=== 9.5.1 Non-technological Determinants of Energy Demand and Carbon Emissions ===

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Buildings climate impact includes CO 2 emissions from operational energy use, carbon footprint, PM 2.5 concentrations and embodied carbon, and is unequivocally driven by GDP, income, population, buildings floor area, energy price, climate, behaviour, and social and physical environment ( [[#Wolske--2020|Wolske et al. 2020]] ; Mata et al. 2021d).

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<span id="climate-and-physical-environment"></span>
==== 9.5.1.1 Climate and Physical Environment ====

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Outdoor temperature, heating and cooling degree days, sunshine hours, rainfall, humidity and wind are highly determinant of energy demand ( [[#Tol--2012|Tol et al. 2012]] ; [[#Rosenberg--2014|Rosenberg 2014]] ; [[#Harold--2015|Harold et al. 2015]] ; [[#Risch--2017|Risch and Salmon 2017]] ; [[#Lindberg--2019|Lindberg et al. 2019]] ). Density, compacity, and spatial effects define the surrounding environment and urban microclimate. Urban residents usually have a relatively affluent lifestyle, but use less energy for heating ( [[#Niu--2012|Niu et al. 2012]] ; [[#Huang--2015|Huang 2015]] ; [[#Rafiee--2019|Rafiee et al. 2019]] ; [[#Ayoub--2019|Ayoub 2019]] ; [[#Oh--2019|Oh and Kim 2019]] ). Urbanisation is discussed in Chapter 8.

Climate variability and extreme events may drastically increase peak and annual energy consumption ( [[#Hong--2013|Hong et al. 2013]] ; [[#Cui--2017|Cui et al. 2017]] ; [[#Mashhoodi--2019|Mashhoodi et al. 2019]] ). Climate change effects on future demand and emissions, are discussed in [[#9.7|Section 9.7]] , and effects of temperature on health and productivity, in [[#9.8|Section 9.8]] .

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<span id="characteristics-of-the-building"></span>
==== 9.5.1.2 Characteristics of the Building ====

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Building typology and floor area (or e.g., number of bedrooms or lot size) are correlated to energy demand ( [[#Manzano-Agugliaro--2015|Manzano-Agugliaro et al. 2015]] ; [[#Moura--2015|Moura et al. 2015]] ; [[#Fosas--2018|Fosas et al. 2018]] ; [[#Morganti--2019|Morganti et al. 2019]] ; [[#Berrill--2021|Berrill et al. 2021]] ). Affluence is embedded in these variables as higher-income households have larger homes and lots. Residential consumption increases with the number of occupants but consumption per capita decreases proportionally to it ( [[#Serrano--2017|Serrano et al. 2017]] ). Construction or renovation year has a negative correlation as recently built buildings must comply with increasingly strict standards ( [[#Brounen--2012|Brounen et al. 2012]] ; [[#Kavousian--2015|Kavousian et al. 2015]] ; [[#Österbring--2016|Österbring et al. 2016]] ). Only for electricity consumption no significant correlation is observed to building age ( [[#Kavousian--2013|Kavousian et al. 2013]] ). Material choices, bioclimatic and circular design discussed in [[#9.4.2|Section 9.4.2]] .

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<span id="socio-demographic-factors"></span>
==== 9.5.1.3 Socio-demographic Factors ====

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Income is positively correlated to energy demand ( [[#Cayla--2011|Cayla et al. 2011]] ; [[#Sreekanth--2011|Sreekanth et al. 2011]] ; [[#Couture--2012|Couture et al. 2012]] ; [[#Moura--2015|Moura et al. 2015]] ; [[#Singh--2017|Singh et al. 2017]] ; [[#Yu--2017|Yu 2017]] ; [[#Bissiri--2019|Bissiri et al. 2019]] ; [[#Mata--2021b|Mata et al. 2021b]] ). High-income households tend to use more efficient appliances and are likely to be more educated and environmentally sensitive, but their higher living standards require more energy ( [[#Harold--2015|Harold et al. 2015]] ; [[#Hidalgo--2018|Hidalgo et al. 2018]] ). Low-income households are in higher risk of fuel poverty ( [[#9.8|Section 9.8]] ).

Mixed effects are found for household size, age, gender, ethnicity, education levels and tenancy status ( [[#Engvall--2014|Engvall et al. 2014]] ; [[#Hansen--2016|Hansen 2016]] ; [[#Lévy--2018|Lévy and Belaïd 2018]] ; [[#Arawomo--2019|Arawomo 2019]] ; [[#Rafiee--2019|Rafiee et al. 2019]] ). Single-parent and elderly households consume more gas and electricity, and gender has no significant effect ( [[#Brounen--2012|Brounen et al. 2012]] ; [[#Harold--2015|Harold et al. 2015]] ; [[#Huang--2015|Huang 2015]] ). Similarly, larger families use less electricity per capita ( [[#Bedir--2013|Bedir et al. 2013]] ; [[#Kavousian--2013|Kavousian et al. 2013]] ). Heating expenditure tends to be higher for owners than for renters, despite the formers tendency to have more efficient appliances ( [[#Gillingham--2012|Gillingham et al. 2012]] ; Davis, 2012; [[#Kavousian--2015|Kavousian et al. 2015]] ).

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<span id="behaviour"></span>
==== 9.5.1.4 Behaviour ====

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Occupants presence and movement, interactions with the building, comfort-driven adaptations and cultural practices determine energy consumption ( [[#Hong--2017|Hong et al. 2017]] ; [[#Yan--2017|Yan et al. 2017]] ; D’Oca et al. 2018; [[#Khosla--2019|Khosla et al. 2019]] ; Li et al. 2019; [[#O’Brien--2020|O’Brien et al. 2020]] ). Households consume more on weekends and public holidays, and households with employed occupants consume less than self-employed occupants, probably because some of the latter jobs are in-house ( [[#Harold--2015|Harold et al. 2015]] ; [[#Hidalgo--2018|Hidalgo et al. 2018]] ). Understanding and accurate modelling of occupant behaviour is crucial to reduce the gap between design and energy performance ( [[#Gunay--2013|Gunay et al. 2013]] ; [[#Yan--2017|Yan et al. 2017]] ), especially for more efficient buildings, which rely on passive design features, human-centred technologies, and occupant engagement ( [[#Grove-Smith--2018|Grove-Smith et al. 2018]] ; [[#Pitts--2017|Pitts 2017]] ).

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<span id="insights-from-non-technological-and-behavioural-interventions"></span>
=== 9.5.2 Insights From Non-technological and Behavioural Interventions ===

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A range of NT actions can substantially reduce buildings energy demand and emissions (Figure 9.14; see Supplementary Material 9.SM.2 for details). The subsections below present insights on the variations depending on the solution, subsector, and region.

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[[File:eb668198025488ca55ed8d8d5e2544e3 IPCC_AR6_WGIII_Figure_9_14.png]]

'''Figure 9.14''' | Energy saving and GHG mitigation potentials for categories of NT interventions for Residential (R) and Non-Residential (NR) buildings, from studies with worldwide coverage. Sources: [[#Roussac--2012|Roussac and Bright (2012)]] ; [[#Van%20Den%20Wymelenberg--2012|Van Den Wymelenberg (2012)]] ; [[#Rupp--2015|Rupp et al. (2015)]] ; [[#Creutzig--2016|Creutzig et al. (2016)]] ; [[#Khosrowpour--2016|Khosrowpour et al. (2016)]] ; Ruparathna et al. (2016b); [[#van%20Sluisveld--2016|van Sluisveld et al. (2016)]] ; [[#Ohueri--2018|Ohueri et al. (2018)]] ; [[#Ahl--2019|Ahl et al. (2019)]] ; [[#Bierwirth--2019b|Bierwirth and Thomas (2019b)]] ; [[#Derungs--2019|Derungs et al. (2019)]] ; [[#Grover--2019|Grover (2019)]] ; [[#Kaminska--2019|Kaminska (2019)]] ; Levesque et al. (2019a); [[#Bavaresco--2020|Bavaresco et al. (2020)]] ; [[#Cantzler--2020|Cantzler et al. (2020)]] ; Ivanova and Büchs (2020b); Wilson et al. (2020b); [[#Harris--2021|Harris et al. (2021)]] .

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<span id="passive-and-active-design-management-and-operation"></span>
==== 9.5.2.1 Passive and Active Design, Management, and Operation ====

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Bioclimatic design and passive strategies for natural heating, cooling and lighting, can greatly reduce buildings’ climate impact, and avoid cooling in developing countries ( [[#Bienvenido-Huertas--2021|Bienvenido-Huertas et al. 2021]] , 2020; [[#Amirifard--2019|Amirifard et al. 2019]] ). Design can provide additional small savings, for example, by placing refrigerator away from the oven, radiators or windows ( [[#Christidou--2014|Christidou et al. 2014]] ). Passive management refers to adjustments in human behaviour such as adapted clothing, allocation of activities in the rooms of the building to minimise the energy use ( [[#Klein--2012|Klein et al. 2012]] ; [[#Rafsanjani--2015|Rafsanjani et al. 2015]] ) or manual operation of the building envelope ( [[#Rijal--2012|Rijal et al. 2012]] ; [[#Volochovic--2012|Volochovic et al. 2012]] ). Quantitative modelling of such measures is most common for non-residential buildings, in which adaptive behaviours are affected by the office space distribution and interior design, amount of occupants, visual comfort, outdoor view, and easy-to-use control mechanisms ( [[#O’Brien--2014|O’Brien and Gunay 2014]] ; [[#Talele--2018|Talele et al. 2018]] ). Socio-demographic factors, personal characteristics and contextual factors also influence occupant behaviour and their interactions with buildings ( [[#D’Oca--2018b|D’Oca et al. 2018b]] ; [[#Hong--2020|Hong et al. 2020]] ).

Active management refers to human control of building energy systems. Efficient lighting practices can effectively reduce summer peak demand ( [[#Dixon--2015|Dixon et al. 2015]] ; [[#Taniguchi--2016|Taniguchi et al. 2016]] ). On the contrary, the application of the daylight-saving time in the US increases up to 7% lighting consumption ( [[#Rakha--2018|Rakha et al. 2018]] ). Efficient cooking practices for cooking, appliance use (e.g., avoid stand-by regime, select eco-mode), or for hot water can save up to 25% ( [[#Peschiera--2012|Peschiera and Taylor 2012]] ; [[#Teng--2012|Teng et al. 2012]] ; [[#Abrahamse--2013|Abrahamse and Steg 2013]] ; [[#Berezan--2013|Berezan et al. 2013]] ; [[#Hsiao--2014|Hsiao et al. 2014]] ; [[#Dixon--2015|Dixon et al. 2015]] ; [[#Reichert--2016|Reichert et al. 2016]] ). High behavioural control is so far proven difficult to achieve ( [[#Ayoub--2014|Ayoub et al. 2014]] ; [[#Sköld--2018|Sköld et al. 2018]] ). Automated controls and technical measures to trigger occupant operations are addressed in [[#9.4|Section 9.4]] .

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<span id="limited-demands-for-services"></span>
==== 9.5.2.2 Limited Demands for Services ====

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Adjustment in the set-point temperature in winter and summer results in savings between 5% and 25% ( [[#Ayoub--2014|Ayoub et al. 2014]] ; [[#Christidou--2014|Christidou et al. 2014]] ; [[#Taniguchi--2016|Taniguchi et al. 2016]] ; [[#Sun--2017|Sun and Hong 2017]] ). As introduced in [[#9.3|Section 9.3]] , a series of recent works study a cap on the living area ( [[#Mata--2021a|Mata et al. 2021a]] ) or an increase in household size ( [[#Berrill--2021|Berrill et al. 2021]] ). These studies are promising but of limited complexity in terms of rebounds, interactions with other measures, and business models, thus require further investigation. Professional assistance and training on these issues is limited ( [[#Maxwell--2018|Maxwell et al. 2018]] ).

Willingness to adopt is found for certain measures (full load to laundry appliances, lid on while cooking, turning lights off, defer electricity usage and HVAC systems, adjust set-point temperature by 1°C) but not for others (appliances on standby, using more clothes, avoid leaving the TV on while doing other things, defer ovens, ironing or heating systems, adjust set-point temperature by 3°C, move to a low energy house or smaller apartment) ( [[#Yohanis--2012|Yohanis 2012]] ; [[#Brown--2013|Brown et al. 2013]] ; [[#Li--2017|Li et al. 2017]] ; [[#Sköld--2018|Sköld et al. 2018]] ). A positive synergy with digitalisation and smart home appliances is identified, driven by a combination of comfort requirements and economic interest, confirmed by a willingness to defer electricity usage in exchange for cost savings ( [[#Ferreira--2018|Ferreira et al. 2018]] ; [[#Mata--2020c|Mata et al. 2020c]] ).

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<span id="flexibility-of-demand-and-comfort-requirements"></span>
==== 9.5.2.3 Flexibility of Demand and Comfort Requirements ====

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In a flexible behaviour, the desired level of service is the same, but it can be shifted over time, typically allowing automated control, for the benefit of the electricity or district heating networks. There are substantial economic, technical, and behavioural benefits from implementing flexibility measures ( [[#Mata--2020c|Mata et al. 2020c]] ), with unknown social impacts.

With demand-side measures (DSM), such as shifting demand a few hours, peak net demand can be reduced by up to 10–20% ( [[#Stötzer--2015|Stötzer et al. 2015]] ); a similar potential is available for short-term load shifting during evening hours ( [[#Aryandoust--2017|Aryandoust and Lilliestam 2017]] ). Although different household types show different consumption patterns and thus an individual availability of DSM capacity during the day (Fischer et al. 2017), there is limited ( [[#Shivakumar--2018|Shivakumar et al. 2018]] ) or inexistent ( [[#Drysdale--2015|Drysdale et al. 2015]] ; [[#Nilsson--2017|Nilsson et al. 2017]] ) information of consumers’ response to time of use pricing, specifically among those living in apartments ( [[#Bartusch--2014|Bartusch and Alvehag 2014]] ). Behavioural benefits are identified in terms of increased level of energy awareness of the users ( [[#Rehm--2018|Rehm et al. 2018]] ), measured deliberate attempts of the consumers to reduce and/or shift their electricity usage ( [[#Bradley--2016|Bradley et al. 2016]] ). Real-time control and behavioural change influence 40% of the electricity use during the operational life of non-residential buildings ( [[#Kamilaris--2014|Kamilaris et al. 2014]] ).

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<span id="circular-and-sharing-economy-cse"></span>
==== 9.5.2.4 Circular and Sharing Economy (CSE) ====

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Non-technological CSE solutions, based on the Regenerate, Share, Optimise, Loop, Virtualise, Exchange (ReSOLVE) framework ( [[#CE100--2016|CE100 2016]] ; [[#ARUP--2018|ARUP 2018]] ) include sharing, virtualising and exchanging. These are less studied than circular materials, with notably less investigation of existing buildings and sharing solutions ( [[#Pomponi--2017|Pomponi and Moncaster 2017]] ; Høibye and Sand 2018; [[#Kyrö--2020|Kyrö 2020]] ; [[#European%20Commission--2020|European Commission 2020]] ).

The sharing economy generates an increased utilisation rate of products or systems by enabling or offering shared use, access or ownership of products and assets that have a low ownership or use rate. Measures include conditioned spaces (accommodation, facility rooms, offices) as well as tools and transfer of ownership (i.e., second-hand or donation) ( [[#Rademaekers--2017|Rademaekers et al. 2017]] ; [[#Mercado--2018|Mercado 2018]] ; [[#Hertwich--2020|Hertwich et al. 2020]] ; [[#Cantzler--2020|Cantzler et al. 2020]] ; [[#Harris--2021|Harris et al. 2021]] ; [[#Mata--2021a|Mata et al. 2021a]] ). The evidence on the link between user behaviour and net environmental impacts of sharing options is still limited ( [[#Laurenti--2019|Laurenti et al. 2019]] ; [[#Mata--2020a|Mata et al. 2020a]] ; [[#Harris--2021|Harris et al. 2021]] ) and even begins to be questioned, due to rebounds that partially or fully offset the benefits ( [[#Agrawal--2017|Agrawal and Bellos 2017]] ; [[#Zink--2017|Zink and Geyer 2017]] ). For example, the costs savings from reduced ownership can be allocated to activities with a higher carbon intensity, or result in increased mobility. Both reduced ownership and other circular consumption habits show no influence on material footprint, other than mildly positive influence in low-income households ( [[#Junnila--2018|Junnila et al. 2018]] ; [[#Ottelin--2020|Ottelin et al. 2020]] ).

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<span id="value-chain-social-and-institutional-innovations"></span>
==== 9.5.2.5 Value-chain, Social and Institutional Innovations ====

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Cooperative efforts are necessary to improve buildings energy efficiency ( [[#Masuda--2014|Masuda and Claridge 2014]] ; [[#Kamilaris--2014|Kamilaris et al. 2014]] ; [[#Ruparathna--2016|Ruparathna et al. 2016]] ). For instance, interdisciplinary understanding of organisational culture, occupant behaviour, and technology adoption is required to set up occupancy/operation best practises ( [[#Janda--2014|Janda 2014]] ). Similarly, close collaboration of all actors along the value chain can reduce by 50% emissions from concrete use ( [[#Habert--2020|Habert et al. 2020]] ); such collaboration can be enhanced in a construction project by transforming the project organisation and delivery contract to reduce costs and environmental impact ( [[#Hall--2021|Hall and Bonanomi 2021]] ). Building commissioning helps to reduce energy consumption by streamlining the systems, but benefits may not persist. Energy communities are discussed later in the chapter.

NT challenges include training and software costs (tailored learning programs, learning-by-doing, human capital mobilisation), client and market demand (service specification, design and provision, market and financial analysis) and legal issues (volatile energy prices, meeting regulation); and partnership, governance and commercialisation. These challenges are identified for Building Information Modelling (BIM) ( [[#Oduyemi--2017|Oduyemi et al. 2017]] ; [[#Rahman--2019|Rahman and Ayer 2019]] ), PV industry ( [[#Triana--2018|Triana et al. 2018]] ), smart living ( [[#Solaimani--2015|Solaimani et al. 2015]] ) or circular economy ( [[#Vence--2019|Vence and Pereira 2019]] ).

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<span id="adoption-of-climate-mitigation-solutions-reasons-and-willingness"></span>
=== 9.5.3 Adoption of Climate Mitigation Solutions – Reasons and Willingness ===

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Mixed effects are found for technical issues, attitudes, and values (Table 9.3). In spite of proven positive environmental attitudes and willingness to adopt mitigation solutions, these are outweighed by financial aspects all over the world ( [[#Mata--2021b|Mata et al. 2021b]] ). Adopters in Developed Countries are more sensitive towards financial issues and comfort disruptions; whereas in other world regions techno-economic concerns prevail. Private consumers seem ready to support stronger governmental action, whereas non-private interventions are hindered by constraints in budgets and profits, institutional barriers and complexities ( [[#Curtis--2017|Curtis et al. 2017]] ; [[#Zuhaib--2017|Zuhaib et al. 2017]] ; [[#Tsoka--2018|Tsoka et al. 2018]] ; [[#Kim--2019|Kim et al. 2019]] ).

A variety of interventions targeted to heterogeneous consumer groups and decision makers is needed to fulfil their diverse needs ( [[#Zhang--2012|Zhang et al. 2012]] ; [[#Haines--2014|Haines and Mitchell 2014]] ; [[#Gram-Hanssen--2014|Gram-Hanssen 2014]] ; [[#Marshall--2015|Marshall et al. 2015]] ; [[#Friege--2016|Friege et al. 2016]] ; [[#Hache--2017|Hache et al. 2017]] ; [[#Liang--2017|Liang et al. 2017]] ; [[#Ketchman--2018|Ketchman et al. 2018]] ; [[#Soland--2018|Soland et al. 2018]] ). Policy reviews for specific market segments and empirical studies investigating investment decisions would benefit from a multidisciplinary approach to energy consumption patterns and market maturity ( [[#Boyd--2016|Boyd 2016]] ; [[#Heiskanen--2017|Heiskanen and Matschoss 2017]] ; [[#Baumhof--2018|Baumhof et al. 2018]] ; [[#Marzano--2018|Marzano et al. 2018]] ; [[#Wilson--2018|Wilson et al. 2018]] ).

'''Table 9.''' '''3 | Reasons for Adoption of Climate Mitigation Solutions.''' The sign represents if the effect is positive (+) or negative (–), and the number of signs represents confidence level (++, many references; +, few references) ( [[#Mata--2021a|Mata et al. 2021a]] ).

{| class="wikitable"
|-
| rowspan="2"|
| colspan="8"| '''Climate mitigation solutions for buildings'''

|-
| '''Building envelope'''

| '''Efficient technical systems'''

| '''On-site renewable energy'''

| '''Behaviour'''

| '''Performance standards'''

| '''Low-carbon materials'''

| '''Digitalisation and flexibility'''

| '''Circular and sharing economy'''

|-
| colspan="9"| Economic

|-
| Subsidies/microloans*

| +

| ++

| ++

| +

| ++

|
| +

|
|-
| Low/high investment costs

| –

| +/––

| ++/––

| +/–

| +/––

| +/–

| –

| –

|-
| Short payback period

| +

| +

| +

| +

| +

| +

| +

|
|-
| High potential savings

| ++

| ++

| ++

| +

| ++

|
| ++

| +

|-
| Market-driven demand

|
| +

| +

|
| +

|
| +

| +

|-
| Higher resale value

| +

| +

| +

|
| +

|
| +

|
|-
| Operating/maintenance costs

| +

| ++/–

| ++/–

| +

| +

| +

| +/–

|
|-
| Split incentives

| –

| –

| –

| –

| –

|
| –

|
|-
| Constrained budgets and profits

| –

| ––

| –

|
| ––

| –

| ––

| ––

|-
| Price competitive (overall)

|
| +

| +

|
| +

| +

| +

| +

|-
| colspan="9"| Information and support

|-
| Governmental support and capacity/lack of

| +/–

| +/–

| ++/–

|
| ++/–

| +

| +/–

| –

|-
| Institutional barriers and complexities

| –

| –

| –

| –

| ––

| –

| –

| –

|-
| Information and labelling/lack of

| +/–

| ++/–

| ++/–

| +

| ++/–

|
| +/–

| –

|-
| Smart metering

|
| +

| +

| +

|
| +

|
|-
| Participative ownership

|
| +

| +

| +

| +

| +

|
|-
| Peer effects

| +

| +

| ++

|
| +

|
| +

|
|-
| Professional advice/lack of

| +/–

| ++/–

| ++/–

| –

| +/––

| –

| +/–

| +/–

|-
| Social norm

| +

| +

| +

| +

| +

|
| +

| +

|-
| Previous experience with solution/lack of

| +/–

| +/–

| +/–

| –

| –

| –

| +/–

| +/–

|-
| colspan="9"| '''Technical'''

|-
| Condition of existing elements

| +

| +

| +

| +

| +

|
| +

|
|-
| Natural resource availability

| +

| +

| ++

| +

|
| +

|
| +

|-
| Performance and maintenance concerns*

| –

| –

| ––

|
| ––

| –

| –

| –

|-
| Low level of control over appliances

|
| –

| –

| –

| –

|
| –

|
|-
| Limited alternatives available

|
| –

| –

|
| –

| –

|
|-
| Not compatible with existing equipment

| –

| –

| –

| –

|
| –

| –

|-
| colspan="9"| Attitudes and values

|-
| Appealing novel technology

| +

| +

| ++

| +

| +

| +

| ++

| +

|-
| Social and egalitarian world views

| +

|
| +

| +

| +

|
| +

|
|-
| Willingness to pay

|
| +

| ++

|
| +

|
| +

|
|-
| Heritage or aesthetic values

| +/–

| ++/–

| +/–

|
| +/–

|
| +/–

|
|-
| Environmental values

| +

| +

| ++

| +

| ++

| +

| ++

| +

|-
| Status and comfort/Lack of

| ++

| ++

| ++

| +

| ++

|
| +

|
|-
| Discomfort during the retrofitting period

| –

| –

| –

|
| –

|
| –

|
|-
| Control, privacy, and security/Lack of*

|
| +/–

| +/–

| –

| –

| –

| +/––

|
|-
| Risk aversion

| –

| –

| –

|
| –

| –

| –

|
|-
| colspan="9"| Social

|-
| Size factors (household, building)

|
| +/–

| ++/–

| +

| +

|
| +

|
|-
| Status (education, income)

| +/–

| ++/–

| +/–

| +/–

| +/–

| +

| +/–

|
|-
| Socio-demographic (age, gender, and ethnicity)

| +/–

| ++/–

| +/–

| +/–

| +/–

|
| +/–

|
|}

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<span id="building-envelope"></span>
==== 9.5.3.1 Building Envelope ====

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In North America and Europe, personal attitudes, values, and existing information and support are the most and equally important reasons for improving the building envelope. Consumers have some economic concerns and little technical concerns, the latter related to the performance and maintenance of the installed solutions ( [[#Mata--2021a|Mata et al. 2021a]] ). In other world regions or climate zones the literature is limited.

Motivations are often triggered by urgent comfort or replacement needs. Maintaining the aesthetic value may as well hinder the installation of insulation if no technical solutions are easily available ( [[#Haines--2014|Haines and Mitchell 2014]] ; [[#Bright--2019|Bright et al. 2019]] ). Local professionals and practitioners can both encourage ( [[#Friege--2016|Friege 2016]] ; [[#Ozarisoy--2017|Ozarisoy and Altan 2017]] ) and discourage the installation of insulation, according to their knowledge and training ( [[#Curtis--2017|Curtis et al. 2017]] ; [[#Zuhaib--2017|Zuhaib et al. 2017]] ; [[#Maxwell--2018|Maxwell et al. 2018]] ; [[#Tsoka--2018|Tsoka et al. 2018]] ). If energy renovations of the buildings envelopes are not normative, cooperative ownership may be a barrier in apartment buildings ( [[#Miezis--2016|Miezis et al. 2016]] ). Similarly, product information and labelling may be helpful or overwhelming ( [[#Ozarisoy--2017|Ozarisoy and Altan 2017]] ; [[#Lilley--2017|Lilley et al. 2017]] ; [[#Bright--2019|Bright et al. 2019]] ). Decisions are correlated to governmental support (Swantje et al. 2015; [[#Tam--2016|Tam et al. 2016]] ) and peer information ( [[#Friege--2016|Friege et al. 2016]] ; [[#Friege--2016|Friege 2016]] ).

The intervention is required to be cost efficient, although value could be placed in the amount of energy saved ( [[#Mortensen--2016|Mortensen et al. 2016]] ; [[#Lilley--2017|Lilley et al. 2017]] ; [[#Howarth--2018|Howarth and Roberts 2018]] ; [[#Kim--2019|Kim et al. 2019]] ) or the short payback period ( [[#Miezis--2016|Miezis et al. 2016]] ). Subsidies have a positive effect ( [[#Swan--2017|Swan et al. 2017]] ).

<div id="9.5.3.2" class="h3-container"></div>

<span id="adoption-of-efficient-hvac-systems-and-appliances"></span>
==== 9.5.3.2 Adoption of Efficient HVAC Systems and Appliances ====

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Mixed willingness is found to adopt efficient technologies. While Developed Countries are positive towards building envelope technologies, appliances such as A-rated equipment or condensing boilers are negatively perceived ( [[#Yohanis--2012|Yohanis 2012]] ). In contrast, adopters in Asia are positive towards energy-saving appliances ( [[#Liao--2020|Liao et al. 2020]] ; [[#Spandagos--2020|Spandagos et al. 2020]] ).

Comfort, economic and ecological aspects, as well as information influence the purchase of a heating system ( [[#Claudy--2011|Claudy et al. 2011]] ; [[#Decker--2015|Decker and Menrad 2015]] ). Information and support from different stakeholders are the most relevant aspects in different geographical contexts ( [[#Hernandez-Roman--2017|Hernandez-Roman et al. 2017]] ; [[#Tumbaz--2018|Tumbaz and Moğulkoç 2018]] ; [[#Curtis--2018|Curtis et al. 2018]] ; [[#Bright--2019|Bright et al. 2019]] ; [[#Chu--2019|Chu and Wang 2019]] ).

Among high-income countries, economy aspects have positive effects, specially reductions in energy bills and financial incentives or subsidies ( [[#Chun--2013|Chun and Jiang 2013]] ; [[#Christidou--2014|Christidou et al. 2014]] ; [[#Mortensen--2016|Mortensen et al. 2016]] ; [[#Clancy--2017|Clancy et al. 2017]] ; [[#Ketchman--2018|Ketchman et al. 2018]] ). Having complementary technologies already in place also has positively affects adoption ( [[#Zografakis--2012|Zografakis et al. 2012]] ; [[#Clancy--2017|Clancy et al. 2017]] ), but performance and maintenance concerns appear as barriers ( [[#Qiu--2014|Qiu et al. 2014]] ). The solutions are positively perceived as high-technology innovative, to enhance status, and are supported by peers and own-environmental values ( [[#Mortensen--2016|Mortensen et al. 2016]] ; [[#Heiskanen--2017|Heiskanen and Matschoss 2017]] ; [[#Ketchman--2018|Ketchman et al. 2018]] ).

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<span id="installation-of-renewable-energy-sources-res"></span>
==== 9.5.3.3 Installation of Renewable Energy Sources (RES) ====

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Although consumers are willing to install distributed RES worldwide, and information has successfully supported their roll out, economic and governmental support is still necessary for their full deployment. Technical issues remain for either very novel technologies or for the integration of RES in the energy system ( [[#Ürge-Vorsatz--2020|Ürge-Vorsatz et al. 2020]] ; [[#Mata--2021a|Mata et al. 2021a]] ). Capacities are to be built by coordinated actions by all stakeholders ( [[#Musonye--2020|Musonye et al. 2020]] ). To this aim, energy communities and demonstrative interventions at local scale are key to address technical, financial, regulatory and structural barriers and document long-term benefits ( [[#von%20Wirth--2018|von Wirth et al. 2018]] ; [[#Shafique--2020|Shafique et al. 2020]] ; [[#Fouladvand--2020|Fouladvand et al. 2020]] ).

Regarding solar technologies, heterogeneous decisions are formed by socio-demographic, economic and technical predictors interwoven with a variety of behavioural traits (Alipour et al. 2020; [[#Khan--2020|Khan 2020]] ). Studies on PV adoption confirm place-specific (various spatial and peer effects), multi-scalar cultural dynamics ( [[#Bollinger--2012|Bollinger and Gillingham 2012]] ; [[#Schaffer--2015|Schaffer and Brun 2015]] ; [[#Graziano--2015|Graziano and Gillingham 2015]] ). Environmental concern and technophilia drive the earliest PV adopters, while later adopters value economic gains (Hampton and Eckermann 2013; [[#Jager-Waldau--2018|Jager-Waldau et al. 2018]] ; [[#Abreu--2019|Abreu et al. 2019]] ; [[#Palm--2020|Palm 2020]] ). Previous experience with similar solutions increases adoption ( [[#Baumhof--2018|Baumhof et al. 2018]] ; Qurashi and Ahmed 2019; [[#Bach--2020|Bach et al. 2020]] ; Reindl and [[#Palm--2020|Palm 2020]] ).

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<span id="low-carbon-materials"></span>
==== 9.5.3.4 Low-carbon Materials ====

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Studies on low-carbon materials tend to focus on wood-based building systems and prefabricated housing construction, mostly in high-income countries, as many sustainable managed forestries and factories for prefabricated housing concentrated in such regions ( [[#Mata--2021a|Mata et al. 2021a]] ). This uneven promotion of wood can lead to its overconsumption ( [[#Pomponi--2020|Pomponi et al. 2020]] ).

Although the solutions are not yet implemented at scale, examples include the adoption of low carbon cement in Cuba motivated by the possibility of supplying the rising demand with low initial investment costs ( [[#Cancio%20Díaz--2017|Cancio Díaz et al. 2017]] ) or adoption of bamboo-based social houses in The Philippines motivated by local job creation and typhoon resistance ( [[#Zea%20Escamilla--2016|Zea Escamilla et al. 2016]] ). More generally, low investment costs and high level decision-making, for example, political will and environmental values of society, increase the adoption rate of low-carbon materials ( [[#Steinhardt--2016|Steinhardt and Manley 2016]] ; [[#Lien--2019|Lien and Lolli 2019]] ; [[#Hertwich--2020|Hertwich et al. 2020]] ). In contrast, observed barriers include lobbying by traditional materials industries, short-term political decision making ( [[#Tozer--2019|Tozer 2019]] ) and concerns over technical performance, risk of damage, and limited alternatives available ( [[#Thomas--2014|Thomas et al. 2014]] ).

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<span id="digitalisation-and-demand-supply-flexibility"></span>
==== 9.5.3.5 Digitalisation and Demand-supply Flexibility ====

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Demand-supply flexibility measures are experimentally being adopted in North America, Europe, and Asia-Pacific Developed regions. Changes in the current regulatory framework would facilitate participation based on trust and transparent communication ( [[#Wolsink--2012|Wolsink 2012]] ; [[#Nyborg--2013|Nyborg and Røpke 2013]] ; [[#Mata--2020b|Mata et al. 2020b]] ). However, consumers expect governments and energy utilities to steer the transition ( [[#Seidl--2019|Seidl et al. 2019]] ).

Economic challenges are observed, as unclear business models, disadvantageous market models and high costs of advanced smart metering. Technical challenges include constraints for HPs and seasonality of space heating demands. Social challenges relate to lack of awareness of real-time price information and inadequate technical understanding. Consumers lack acceptance towards comfort changes (noise, overnight heating) and increased automation ( [[#Drysdale--2015|Drysdale et al. 2015]] ; [[#Bradley--2016|Bradley et al. 2016]] ; [[#Sweetnam--2019|Sweetnam et al. 2019]] ). Risks identified include higher peaks and congestions in low price-hours, difficulties in designing electricity tariffs because of conflicts with CO 2 intensity, and potential instability in the entire electricity system caused by tariffs coupling to wholesale electricity pricing.

Emerging market players are changing customer utility relationships, as the grid is challenged with intermittent loads and integration needs for ICTs, interfering with consumers requirements of autonomy and privacy ( [[#Wolsink--2012|Wolsink 2012]] ; [[#Parag--2016|Parag and Sovacool 2016]] ). Although most private PV owners would make their storage system available as balancing load for the grid operator, the acquisition of new batteries by a majority of consumers requires incentives ( [[#Gährs--2015|Gährs et al. 2015]] ). For distributed energy hubs, social acceptance depends on the amount of local benefits in economic, environmental or social terms (Kalkbrenner and Roosen 2015), and increases around demonstration projects ( [[#von%20Wirth--2018|von Wirth et al. 2018]] ).

<div id="9.5.3.6" class="h3-container"></div>

<span id="circular-and-sharing-economy"></span>
==== 9.5.3.6 Circular and Sharing Economy ====

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The circular and sharing economy begins to be perceived as organisational and technologically innovative, with the potential to provide superior customer value, response to societal trends and positive marketing ( [[#Mercado--2018|Mercado 2018]] ; [[#Cantzler--2020|Cantzler et al. 2020]] ; [[#Nußholz--2020|Nußholz et al. 2020]] ). Although technical and regulatory challenges remain, there are key difficulties around the demonstration of a business case for both consumers and the supply chain ( [[#Pomponi--2017|Pomponi and Moncaster 2017]] ; [[#Hart--2019|Hart et al. 2019]] ).

Government support is needed as an initiator but also to reinforce building retroﬁt targets, promote more stringent energy and material standards for new constructions, and protect consumer interests ( [[#Hongping--2017|Hongping 2017]] ; [[#Fischer--2017|Fischer and Pascucci 2017]] ; Patwa et al. 2020). Taxes clearly incentivise waste reduction and recycling ( [[#Rachel--2011|Rachel and Travis 2011]] ; [[#Ajayi--2015|Ajayi et al. 2015]] ; [[#Volk--2019|Volk et al. 2019]] ). In developing countries, broader, international, market boundaries can allow for a more attractive business model ( [[#Mohit--2020|Mohit et al. 2020]] ). Participative and new ownership models can favour the adoption of prefabricated buildings ( [[#Steinhardt--2016|Steinhardt and Manley 2016]] ). Needs for improvements are observed, in terms of design for flexibility and deconstruction, procurement and prefabrication and off-site construction, standardisation and dimensional coordination, with differences among solutions ( [[#Osmani--2012|Osmani 2012]] ; Coehlo et al.2013; [[#Lu--2013|Lu and Yuan 2013]] ; [[#Cossu--2015|Cossu and Williams 2015]] ; Schiller et al. 2015, 2017; [[#Ajayi--2017|Ajayi et al. 2017]] ; Bakshan et al. 2017).

Although training is a basic requirement, attitude, past experience, and social pressure can also be highly relevant, as illustrated for waste management in a survey to construction site workers ( [[#Amal--2017|Amal et al. 2017]] ). Traditional community practices of reuse of building elements are observed to be replaced by a culture of waste ( [[#Ajayi--2015|Ajayi et al. 2015]] ; [[#Hongping--2017|Hongping 2017]] ).

<div id="9.6" class="h1-container"></div>

<span id="global-and-regional-mitigation-potentials-and-costs"></span>