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 PM 2.5 concentrations made during 2019 at 11 COALESCE sites across India. The network median PM 2.5 concentration was 42 μg m −3 with 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 PM 2.5 were 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 PM 2.5 variability across the network. Concentration Weighted Trajectories (CWT) together with the results of causality analysis revealed common regional sources affecting PM 2.5 concentrations 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 PM 2.5 sectoral 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.Plain Language Summary Surface PM 2.5 mass 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 PM 2.5 at all 11 locations. Mass-meteorology-emissions associations helped identify priority sectors for source control across the country.

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Objectives: (a) ground-truthing of black and organic aerosol mass simulated by CAMS and MERRA-2, (b) identification of different atmospheric processes that propagated errors in these reanalysis datasets.

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<p>Climatological parameters like wind speed, temperature, boundary layer height facilitate in dispersion and accumulation of aerosols. Stagnant condition of atmosphere promote accumulation while the pollutants are more likely to get dispersed when non stagnation conditions exist. Sparse studies exist to assess the seasonal and episodic impact of stagnant weather conditions on enhancing aerosol formation in the North-East region of India.PM<sub>2.5 </sub>sampling was carried from January to November 2019 at a regional background site in Jorhat,Assam. Meteorological variables like wind speed, surface ambient temperature and relative humidity were obtained at one-minute resolution from a collocated air weather sensor. Ventilation coefficient was calculated from wind speed and Boundary Layer Height (BLH) ( from ERA5 reanalysis dataset)</p><p>Episodic days were identified as those exceeding permissible values of PM<sub>2.5 </sub>(National Ambient Air Quality Standards) i.e, 60µg/m<sup>3</sup>. Average wind speed on polluted and non-polluted days was 0.58±0.08 and 0.77 ± 0.17 m/s respectively. The average BLH was lower for the polluted days (243±73) than the non-polluted days (316±79). Pearson corelation coefficient of PM<sub>2.5 </sub>and wind speeds on polluted days was low (-0.23) compared to the non-polluted days (-0.54).</p><p>Wind rose plots reveal a seasonality trend with winter and summer winds being mostly between North East and South South-West while in monsoon and autumn it lies predominantly between SSW and South South-East (from the Bay of Bengal).  The Pearson correlation coefficients between PM<sub>2.5 </sub>and wind speeds are -0.66, -0.54 and -0.52 (all p <0.01) in winter, summer and autumn, respectively.Low average BLH persists in Winter and autumn . The seasonal maxima of BLH during winter, summer, monsoon and autumn was 847±167m, 932 ± 271m, 871 ±275m and 814 ± 256m, respectively.  Low night-time BLH (≈ 50m) in winter and autumn contributes to higher aerosol loading. The ventilation coefficient reaches its maxima during daytime around noon with summer season having the maximum daytime VC. High VC (≈270m<sup>2</sup>/s) in summer and monsoon  signify the seasonal effect on the pollutant dispersion and consequent high PM<sub>2.5 </sub>loading. Statistically significant negative correlations were obtained between PM<sub>2.5 </sub>and VC in winter and autumn seasons (-0.75 and -0.43).</p><p>Wind speeds have a strong correlation with PM<sub>2.5 </sub>except for the monsoon season and play a major role in aerosol dispersion.During monsoon, weak dependence of PM<sub>2.5 </sub>with wind speed and ventilation coefficient suggest significance of precipitation  which cause sscavenging of aerosols. Low correlations exist in summer for PM<sub>2.5 </sub>and VC due to possible interference due to regional transport of aerosols. 5-day backward trajectory analysis suggest  transport of air masses across the Thar desert and Indo Gangetic Plains to the site during the March(summer) suggesting transport of dust across the region.</p>