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

=== 9.3.2 Drivers of CO 2 Emissions and Their Climate Impact ===

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Building specific drivers of GHG emissions in the four scenarios described above are assessed using an index decomposition analysis with building specific identities and reflecting the three pillars of the Sufficiency, Efficiency, Renewables (SER) framework. Broad drivers of GHG emissions such as GDP and population are analysed using a Kaya decomposition in Chapter 2. Previous decompositions analysing drivers of global GHG emissions in the building sector have either assessed only the impact of GDP and population as drivers of GHG emissions ( [[#Lamb--2021|Lamb et al. 2021]] ) or the impact of building specific drivers on energy demand and not on CO 2 emissions (Lucon et al. 2014; [[#Ürge-Vorsatz--2015|Ürge-Vorsatz et al. 2015]] ; [[#IEA--2020c|IEA 2020c]] ; ODYSSEE 2020). For this assessment, the decomposition was conducted for energy-related CO 2 emissions for residential buildings only, due to lack of data for non-residential buildings.

The attribution of changes in emissions in the use phase to changes in the drivers of population, sufficiency, efficiency, and carbon intensity of energy supply is calculated using additive log-mean divisia index decomposition analysis ( [[#Ang--2000|Ang and Zhang 2000]] ). The decomposition of emissions into four driving factors is shown in Equation 1, where m 2 refers to total floor area, EJ refers to final energy demand, and MtCO 2 refers to the sum of direct and indirect CO 2 emissions in the use phase. The allocation of changes in emissions between two cases ''k'' and ''k'' – ''1'' to changes in a single driving factor D is shown in Equation 2. To calculate changes in emissions due to a single driver such as population growth, D will take on the value of population in the two compared cases. The superscript k stands for the case, defined by the time period and scenario of the emissions, for example, IEA-CPS baseline scenario in 2050. When decomposing emissions between two cases ''k'' and ''k–1'' , either the time-period, or the scenario remains constant. The decomposition was done at the highest regional resolution available from each model output, and then aggregated to regional or global level. For changes in emissions within a scenario over time, the decomposition is done for every decade, and the total 2020–2050 decomposition is then produced by summing decompositions of changes in emissions each decade.

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Over the period 1990–2019, population growth accounted for 28% of the growth in global emissions in residential buildings, the lack of sufficiency policies (growth in floor area per capita) accounted for 52% and increasing carbon intensity of the global energy mix accounted for 16%. Efficiency improvement contributed to decreasing global emissions from residential buildings by 49% (Figure 9.5a). The sufficiency potential was untapped in all regions over the same period while the decarbonisation of the supply was untapped in developing countries and to some extent in Asia-Pacific Developed. The highest untapped sufficiency and supply decarbonisation potentials occurred in Southern Asia where the lack of sufficiency measures has led to increasing emissions by 185% and the high carbon intensity of the energy mix has led to increasing emissions by 340%. In Developed Countries, the highest untapped sufficiency potential occurred in Asia-Pacific Developed region. Middle East is the only region where efficiency potential remained untapped (Figure 9.5b).

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'''Figure 9.5: Decompositions of changes in historical residential energy emissions 1990–2019, changes in emissions projected by baseline scenarios for 2020–2050, and differences between scenarios in 2050 using scenarios from''' '''three models: IEA, IMAGE, and RECC.''' '''RECC-LED data include only space heating and cooling and water heating in residential buildings (a) global resolution, and (b) for nine world regions.''' Emissions are decomposed based on changes in driver variables of population, sufficiency (floor area per capita), efficiency (final energy per floor area), and renewables (GHG emissions per final energy). ‘Renewables’ is a summary term describing changes in GHG intensity of energy supply. Emission projections to 2050, and differences between scenarios in 2050, demonstrate mitigation potentials from the dimensions of the SER framework realised in each model scenario. In most regions, historical improvements in efficiency have been approximately matched by growth in floor area per capita. Implementing sufficiency measures that limit growth in floor area per capita, particularly in developed regions, reduces the dependence of climate mitigation on technological solutions.

Scenarios assessed show an increase of the untapped sufficiency potential at the global level over the period 2020–2050. The highest untapped sufficiency potential occurs in IEA scenarios as there are no changes in the floor area per capita across different scenarios. The lack of sufficiency measures in current policies will contribute to increasing emissions by 54%, offsetting the efficiency improvement effect. By setting a cap in the growth of the floor area per capita in developed countries, 5% of emission reductions in IMAGE-LiRE scenario derives from sufficiency. However, compared to 2020, the lack of sufficiency measures in the baseline scenario will contribute to increasing emissions by 31%. RECC-LED scenario shows the highest global sufficiency potential captured compared to its baseline scenario in 2050 as this scenario assumes a reduction in the floor area per capita in Developed Countries and slower floor area growth in emerging economies. The four scenarios show a higher contribution of the decarbonisation of energy supply to reducing emissions than the reduction of energy demand through sufficiency and efficiency measures (Figure 9.6a). At regional level, the emissions reduction potential from sufficiency is estimated at 25% in North America under both IMAGE-LiRE and RECC-LED scenarios and at 19% in both Eastern Asia and Europe/Eurasia regions (Figure 9.6b). The highest decarbonisation potential due to growth of renewable energy is 75% in Southern Asia under IMAGE-LiRE scenario.

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'''Figure 9.6 | Per capita floor area: historical based on IEA data and future emissions based on two IEA scenarios (sustainable development, and net zero emissions), IMAGE Lifestyle-Renewable scenario and Resource Efficiency and Climate Change-Low Energy Demand scenario (RECC-LED).''' RECC-LED data include only space heating and cooling and water heating in residential buildings. The IEA current policies scenario is included as a baseline scenario (IEA current policies scenario).

There is a growing literature on the decarbonisation of end-use sectors while providing decent living standard for all ( [[#Rao--2017|Rao and Pachauri 2017]] ; [[#Grubler--2018|Grubler et al. 2018]] ; [[#Rao--2018|Rao and Min 2018]] ; [[#Rao--2019|Rao et al. 2019]] ; [[#Millward-Hopkins--2020|Millward-Hopkins et al. 2020]] ). The floor area per capita is among the gaps identified in the convergence between developed and developing countries in the access to decent living ( [[#Kikstra--2021|Kikstra et al. 2021]] ) while meeting energy needs. In the Low Energy Demand (LED) scenario, 30 m² per capita is the converging figure assumed by 2050 ( [[#Grubler--2018|Grubler et al. 2018]] ) while in the Decent Living with minimum Energy (DLE) scenario, ( [[#Millward-Hopkins--2020|Millward-Hopkins et al. 2020]] ) assumes 15 m² per capita.

Overall, the global residential building stock grew by almost 30% between 2005 and 2019. However, this growth was not distributed equally across regions and three out of the four scenarios assessed do not assume a convergence, by 2050, in the floor area per capita, between developed and developing countries. Only RECC-LED implements some convergence between Developed Countries and emerging economies to a range of 20–40 m² per capita. IEA scenarios assume a growth in the floor area per capita in all regions with the highest growth in Developed Countries, up to 72 m² per capita in North America from 66 m² per capita in 2019. IMAGE-LiRE projects a floor area per capita in Africa at 14 m² per person. This is lower than the one of 2019, which was at 16 m² per capita (Figure 9.6). Beyond capturing the sufficiency potential by limiting the growth in the floor area per capita in Developed Countries while ensuring decent living standard, the acceptability of the global scenarios by developing countries is getting attraction in academia ( [[#Hickel--2021|Hickel et al. 2021]] ).

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