Positive matrix factorization-based receptor modelling of particulate matter in northwest India

Abstract

India is facing a dearth in the area of particulate matter (PM) source apportionment studies. Frequent exceedances and unusual high concentrations of PM observed in North India further presses the identification and quantification of particulate pollution sources to plan mitigation measures. But most of the PM source apportionment studies performed here are concentrated in and around Delhi, so this paper sets to explore the sources of PM in an understudied region of North India. The present study employed positive matrix factorization (PMF) 5.0 model developed by the United States Environmental Protection Agency (US EPA) for source characterisation of particulate matter quantified at Mohali in May 2012. Application of US EPA PMF 5.0 to a hybrid dataset of particulate matter and volatile organic compounds identified seven source factors, namingly, dust, wheat residue burning, biofuel use and waste disposal, mixed daytime, cars, two-wheelers) and industrial emissions and solvent use. The contributions of these individual source factors to PM₁₀ and PM_2.5 mass loadings were found to be 48.8%, 20.6%, 15.8%, 7.79%, 2.89%, 2.86%, 1.37% and 33.6%, 22.6%, 29.6%, 4.97%, 2.05%, 4.07% and 3.07% respectively. Dust and biomass burning were the major sources of PM in Mohali that contributed relatively highest average concentrations of PM₁₀ (∼321 μg/m³) and PM_2.5 (∼123 μg/m³) during morning hours (05:00–10:00 LT) in May 2012. This study reaffirmed the need to check anthropogenic activities and calls for strict air quality measures, especially in May to limit PM emissions in northwest India.