Editing IPCC:AR6/WGI/Chapter-6 (section)

==== 6.6.2.5 Source attribution of regional air pollution ====

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The attribution of present-day surface PM <sub>2.5</sub> and ozone concentrations to sectors and regions (Figure 6.17) is based on 2014 CMIP6 emissions used in the TM5-FASST model ( [[#Van%20Dingenen--2018|Van Dingenen et al., 2018]] ) that has been widely applied to analyse air quality in regional and global scenarios (e.g., Van Dingenen et al. , 2009; Rao et al. , 2016, 2017; Vandyck et al. , 2018; Harmsen et al. , 2020b) . Regions with the largest year-2014 population-weighted annual average surface PM <sub>2.5</sub> concentrations are Southern Asia, Eastern Asia and the Middle East. The dominant anthropogenic source of ambient PM <sub>2.5</sub> in Southern Asia are the residential and commercial sectors (biomass and coal fuel-based cooking and heating) with secondary contributions from energy and industry. In Eastern Asia, the main anthropogenic sources of ambient PM <sub>2.5</sub> are energy, industry and residential sources. Natural sources, predominantly dust, are the most important PM <sub>2.5</sub> source in the Middle East, Africa and Eurasia, contributing about 40–70% of ambient annual average concentrations (Figure 6.17). Agriculture is an important contributor to ambient PM <sub>2.5</sub> in Europe and North America, while open biomass burning is a major contributor in South East Asia and Developing Pacific, North America as well as Latin America. These results are consistent with several global and regional studies, where contribution of emissions sources to ambient PM <sub>2.5</sub> or premature mortality was estimated at different scales (e.g., Guttikunda et al. , 2014; [[#Lelieveld--2015b|Lelieveld et al. 2015b]] ,; Amann et al. , 2017; Qiao et al. , 2018; Venkataraman et al. , 2018; Wu et al. , 2018) .

Natural sources contribute more than 50% to surface ozone in all regions except Southern Asia and South East Asia. Southern Asia, Eastern Asia and the Middle East experience the highest surface ozone levels of all regions. For ozone, the anthropogenic sectoral attribution is more uniform across regions than for PM <sub>2.5</sub> , except for Southern and South East Asia, where land transportation plays a larger role, and Eastern Asia, where the most significant contribution is from energy and industry. Land transportation and energy are the most important contributors to ozone across many of the regions, with smaller contributions from agriculture, biomass burning, waste management and industry. Open biomass burning is not a major contributor to surface ozone, except for in Africa, Latin America and South East Asia where its contribution is estimated at about 5–10% of anthropogenic sources. The relative importance of natural and anthropogenic emissions sources on surface ozone has been assessed in several studies ( [[#Uherek--2010|Uherek et al., 2010]] ; [[#Zare--2014|Zare et al., 2014]] ; [[#Mertens--2020|Mertens et al., 2020]] ; [[#Unger--2020|Unger et al., 2020]] ) and the results are comparable with the estimates of the TM5-FASST used here.

Residential and commercial cooking and heating are among the most important anthropogenic sources of ambient PM <sub>2.5</sub> , except in the Middle East and Asia-Pacific Developed ( ''high confidence'' ) and agriculture is the dominant source in Europe and North America ( ''medium confidence'' ). Energy and industry are important PM <sub>2.5</sub> contributors in most regions, except Africa ( ''high confidence'' ). Energy and land transportation are the major anthropogenic sources of ozone across many world regions ( ''medium to high confidence'' ).

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'''Figure 6.16 |''' '''Global mean temperature response 10 and 100 years following one year of present-day (year 2014) emissions.''' The temperature response is broken down by individual species and shown for total anthropogenic emissions (top), sectoral emissions (left) and regional emissions (right). Sectors and regions are sorted by (high-to-low) net temperature effect on the 10-year time scale. Error bars in the top panel show uncertainty (5–95% interval) in net temperature effect due to uncertainty in radiative forcing ''only'' (calculated using a Monte Carlo approach and best estimate uncertainties from the literature – see [[#Lund--2020|Lund et al. (2020)]] for details). CO <sub>2</sub> emissions are excluded from open biomass burning and residential biofuel use due to their unavailability in the Community Emissions Data System (CEDS) and uncertainties around non-sustainable emission fraction. Emissions for 2014 originate from the CEDS ( [[#Hoesly--2018|Hoesly et al., 2018]] ), except for HFCs which are from [[#Purohit--2020|Purohit et al. (2020)]] , open biomass burning from [[#van%20Marle--2017|van Marle et al. (2017)]] , and aviation H <sub>2</sub> O which is from [[#Lee--2021|Lee et al. (2021)]] . The split of fossil fuel production and distribution and combustion for energy and residential and commercial fuel use into fossil fuel and biofuel components is obtained from the GAINS model (ECLIPSE version 6b dataset). Open biomass burning emissions are not included for the regions. Emissions are aggregated into fossil fuel production and distribution (coal mining, oil and gas production, upstream gas flaring and gas distribution networks), agriculture (livestock and crop production), fossil fuel combustion for energy (power plants), industry (combustion and production processes, solvent-use losses from production and end use), residential and commercial (fossil fuel use for cooking and heating as well is HFCs leakage from A/C and refrigeration), waste management (solid waste, including landfills and open trash burning, residential and industrial waste water), transport (road and off-road vehicles, and HFC leakage from A/C and refrigeration equipment), residential and commercial (biofuels use for cooking and heating), open biomass burning (forest, grassland, savanna fires and agricultural waste burning), shipping (including international shipping), and aviation (including international aviation). Further details on data sources and processing are available in the chapter data table (Table 6.SM.3).

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'''Figure 6.17 |''' '''Emissions source-sector attribution of regional population-weighted mean concentrations of PM''' <sub>2.5</sub> '''and ozone for present-day emissions (year 2014).''' Regional concentrations and source apportionment are calculated with the TM5-FASST model ( [[#Van%20Dingenen--2018|Van Dingenen et al., 2018]] ) for the 2014 emissions data from the Community Emissions Data System (CEDS) ( [[#Hoesly--2018|Hoesly et al., 2018]] ) and [[#van%20Marle--2017|van Marle et al. (2017)]] for open-biomass burning. Dust and sea salt contributions to PM 2.5 are monthly mean climatological averages over 2010–2018 from CAMS global reanalysis (EAC4) ( [[#Inness--2019|Inness et al., 2019]] ), generated using Copernicus Climate Change Service information (January 2020). Anthropogenic sectors are similar to those in Figures 6.2 and 6.16, except the grouping of fossil fuel production, distribution and combustion for energy under ‘Energy’ and the grouping of use of fossil fuel and biofuel use for cooking and heating under ‘Residential and Commercial’. Further details on data sources and processing are available in the chapter data table (Table 6.SM.3).

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