Fine particulate matter (PM2.5) is a major criteria pollutant affecting the environment, health and climate. In India where ground-based measurements of PM2.5 is scarce, it is important to have a long-term database at a high spatial resolution for an efficient air quality management plan. Here we develop and present a high-resolution (1-km) ambient PM2.5 database spanning two decades (2000–2019) for India. We convert aerosol optical depth from Moderate Resolution Imaging Spectroradiometer (MODIS) retrieved by Multiangle Implementation of Atmospheric Correction (MAIAC) algorithm to surface PM2.5 using a dynamic scaling factor from Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) data. The satellite-derived daily (24-h average) and annual PM2.5 show a R2 of 0.8 and 0.97 and root mean square error of 25.7 and 7.2 μg/m3, respectively against surface measurements from the Central Pollution Control Board India network. Population-weighted 20-year averaged PM2.5 over India is 57.3 μg/m3 (5–95 percentile ranges: 16.8–86.9) with a larger increase observed in the present decade (2010–2019) than in the previous decade (2000 to 2009). Poor air quality across the urban–rural transact suggests that this is a regional scale problem, a fact that is often neglected. The database is freely disseminated through a web portal ‘satellite-based application for air quality monitoring and management at a national scale’ (SAANS) for air quality management, epidemiological research and mass awareness.

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Gaussian-based dispersion models are widely used to estimate local pollution levels. The accuracy of such models depends on stability classification schemes as well as plume rise equations. A general plume dispersion model (GPDM) for a point source emission, based on Gaussian plume dispersion equation, was developed. The program complex was developed using Java and Visual basic tools. It has the flexibility of using five kinds of stability classification schemes, i.e., Lapse Rate, PasquillYGifford (PG), Turner, 'Y and Richardson number. It also has the option of using two types of plume rise formulations Y Briggs and Holland_s. The model, applicable for both rural and urban roughness conditions, uses meteorological and emission data as its input parameters, and calculates concentrations of pollutant at the center of each cell in a predefined grid area with respect to the given source location. Its performance was tested by comparing with 4-h average field data of continuous releases of SO 2 from Dadri thermal power plant (Uttar Pradesh, India). Results showed that the Turner scheme used with Holland_s equation gives the best outcome having a degree of agreement (d) of 0.522.

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The concentrations of twenty five heavy metals adsorbed to fine fraction of particulate matter, PM2.5 (d ≤ 2.5 µm) have been experimentally analysed at a sampling site located at the kerbside along a National Highway in Delhi city, India. The sampling has been carried out for 12-hour using Ecotech Intruments, APM550. The PM2.5 has been collected on PTFE filter papers for the winter season. Later, the filter papers have been analysed for various heavy metal concentrations using ED-XRF. It has been observed that the metals concentrations are in this trend: Si > K > S > Ca = Fe > Zn = Pb > Br. it is observed that Si has high co-relation with Ca, Fe and K, which may be due to crustal origin of all three elements; while S, Br and Pb may be from vehicular exhaust emissions and/or abrasions due to brake and tyre wear. The potential health risks associated with different carcinogenic heavy metals have also been calculated. One of the health risk indicators, the excess cancer risk (ECR), is found to be in the order as As > Cd > Pb > Cr > Ni.