PM10 aerosols were monitored and analyzed for heavy metal concentration at Raipur city Chhattisgarh, India for possible source identification of pollutants. Sampling of PM10 aerosols was carried out by using respirable dust sampler during the year 2016. Daily PM10 average concentrations varied between 122.033 and 197.854 µg/m3, 91.350 and 133.950 µg/m3 and 112.770 and 480.170 µg/m3 in summer, monsoon and winter respectively. Chemical analysis of PM10 samples was carried out for heavy metal determination. Heavy metal (Fe, Mn, Ni and Pb) were analyzed with the help of atomic absorption spectroscopy (AAS) and found in the range of 2.713-36.862, 0.131-9.129. 0.880-4.195 and 0.015-0.321 µg/m3 for Fe, Mn, Pb and Ni respectively. PM10 concentrations shows distinct seasonal variation being twice in winter season than in summer; winter (mean: 241.820 ± 33.912 µg/m3) > summer (mean: 159.512 ± 14.360 µg/m3) > monsoon (mean: 107.480 ± 9.213 µg/m3). The concentration of heavy metal was different in all the seasons depending on their sources. Identification of possible sources was done by principal component analysis (PCA) illustrating industrial activities, soil (crustal) dust and biomass burning as the major sources in the region. The back trajectory analysis of the air masses depicts that the local anthropogenic activities affect the concentration of pollutants at the source. Correlation analysis between the heavy metal concentrations agreed the results obtained by PCA. The work helped in observing the seasonal trend of particulate matter concentrations and in identification of major sources of air pollution in the city.

Purpose The purpose of this study is to monitor suspended particulate matter (SPM), PM2.5 and source apportionment study for the identification of possible sources during the year 2018–2019 at Raipur, India. Design/methodology/approach Source apportionment study was performed using a multivariate receptor model, positive matrix factorization (PMFv5.0) with a view to identify the various possible sources of particulate matter in the area. Back-trajectory analysis was also performed using NOAA-HYSPLIT model to understand the origin and trans-boundary movement of air mass over the sampling location. Findings Daily average SPM and PM2.5 aerosols mass concentration was found to be 377.19 ± 157.24 µg/m³ and 126.39 ± 37.77 µg/m³ respectively. SPM and PM2.5 mass concentrations showed distinct seasonal cycle; SPM – (Winter ; 377.19 ±157.25 µg/m?) > (Summer; 283.57 ±93.18 µg/m?) > (Monsoon; 33.20 ±16.32 µg/m?) and PM2.5 – (Winter; 126.39±37.77 µg/m³) > (Summer; 75.92±12.28 µg/m³). Source apportionment model (PMF) have been applied and identified five major sources contributing the pollution; steel production and industry (68%), vehicular and re-suspended road dust (10.1%), heavy oil combustion (10.1%), tire wear and brake wear/abrasion (8%) and crustal/Earth crust (3.7%). Industrial activities have been identified as major contributing factor for air quality degradation in the region. Practical implications Chemical characterization of aerosols and identification of possible sources will be helpful in abatement of pollution and framing mitigating strategies. It will also help in standardization of global climate model. Originality/value The findings provide valuable results to be considered for controlling air pollution in the region.

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