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Emission sources influencing high particulate air pollution levels and related mortality in India have been studied earlier on country‐wide and sub‐national scales. Here, we use novel data sets of emissions (for 2019) and observations created under the Carbonaceous Aerosol Emissions, Source Apportionment, and Climate Impacts network in India (Venkataraman et al., 2020, https://doi.org/10.1175/bams‐d‐19‐0030.1) in WRF‐Chem simulations to evaluate drivers of high PM2.5levels during episodes and in airsheds with different pollution levels. We identify airsheds in “extreme” (110–140 μg/m3), “severe” (80–110 μg/m3) and “significant” (40–80 μg/m3) exceedance of the Indian annual ambient air quality standard (National Ambient Air Quality Standards [NAAQS]) of 40 μg/m3for PM2.5. We find that primary organic matter and anthropogenic mineral matter (largely coal fly‐ash) drive high PM2.5levels, both annually and during high PM2.5episodes. PM2.5episodes are driven by organic aerosol in north India (Mohali) in wintertime but are additionally influenced by mineral matter and secondary inorganics in central (Bhopal), south India (Mysuru) and eastern India (Shyamnagar). Across airsheds in exceedance of the NAAQS and during high PM2.5episodes, primary PM2.5emissions arise largely from the residential sector (50%–75%). Formal sector emissions (industry, thermal power and transport; 40%–55%) drive airshed and episode scale PM2.5exceedance in northern and eastern India. Agricultural residue burning emissions predominate (50%–75%) on episode scales, both in northern and central India, but not on annual scales. Interestingly, residential sector emissions strongly influence (60%–90%) airsheds in compliance with the NAAQS (annual mean PM2.5< 40 μg/m3), implying the need for modern residential energy transitions for the reduction of ambient air pollution across India. India faces high levels of air pollution, particularly that of breathable pollution particles, exposure to which leads to large public health impacts, in terms of reduced life spans and more frequent illness. In this work we ask questions about which pollutant species and which emission sources largely affect time periods (or episodes) and regions (or airsheds) where high pollution occurs. We find that organic matter from biomass combustion and mineral matter from coal combustion, are associated with high pollution levels. Biomass combustion is related to residential cooking with fuelwood and crop residue stalks traditional stoves, while coal combustion arises in coal‐fired power plants and industry. While agricultural stubble burning has been highlighted in the media, it affects high pollution episodes in some regions, but is less important on annual scales. Importantly, large residential emissions arise both in cleaner and polluted regions across India, making modern residential energy transitions key to reducing air pollution in India. Primary organic matter and anthropogenic mineral matter (coal fly‐ash) drive both high annual and episodic PM2.5levels, across IndiaAgricultural residue burning emissions predominate on episode scales, both in northern and central India, but not on annual scalesResidential energy transitions key to air pollution mitigation as residential sector emissions dominate both cleaner and polluted airsheds Primary organic matter and anthropogenic mineral matter (coal fly‐ash) drive both high annual and episodic PM2.5levels, across India Agricultural residue burning emissions predominate on episode scales, both in northern and central India, but not on annual scales Residential energy transitions key to air pollution mitigation as residential sector emissions dominate both cleaner and polluted airsheds

The Carbonaceous Aerosol Emissions, Source Apportionment and Climate Impacts (COALESCE) is a multi‐institutional Indian network project to better understand carbonaceous aerosol induced air quality and climate effects. This study presents time synchronized measurements of surface PM2.5concentrations made during 2019 at 11 COALESCE sites across India. The network median PM2.5concentration was 42 μg m−3with the highest median value at Rohtak (99 μg m−3) and the lowest median value at Mysuru (26 μg m−3). The influence of six meteorological parameters on PM2.5were evaluated. Causality analysis suggested that temperature, surface pressure, and relative humidity were the most important factors influencing fine PM mass, on an annual as well as seasonal scale. Further, a multivariable linear regression model showed that, on an annual basis, meteorology could explain 16%–41% of PM2.5variability across the network. Concentration Weighted Trajectories (CWT) together with the results of causality analysis revealed common regional sources affecting PM2.5concentrations at multiple regional sites. Further, CWT source locations for all sites across the network correlated with the SMoG‐India emissions inventory at the 95th percentile confidence. Finally, CWT maps in conjunction with emissions inventory were used to obtain quantitative estimates of anthropogenic primary PM2.5sectoral shares from a mass‐meteorology‐emissions reconciliation, for all 11 pan‐India network sites. These estimates can help guide immediate source reduction and mitigation actions at the national level. Surface PM2.5mass causal associations with annual and seasonal meteorology during 2019 across 11 pan‐India COALESCE network locations were examined. Temperature, surface pressure and relative humidity were the most influential factors on fine PM mass concentrations. However, across the country only 16%–41% of fine PM variability was explained by meteorology on an annual basis. A fusion of trajectory ensemble methods with national emissions inventory was used for apportioning anthropogenic primary PM2.5at all 11 locations. Mass‐meteorology‐emissions associations helped identify priority sectors for source control across the country.