Source apportionment of fine particulate matter over a National Park in Central India

PM2.5 mass and chemical constituents were measured over Van Vihar National Park (VVNP), a forested location within Bhopal. Positive Matrix Factorization (USEPA PMF5) was applied to two-year long (2012 and 2013) measurements of PM2.5 chemical species including water-soluble inorganic ions, organic, pyrolitic, and elemental carbon, and trace elements for the quantitative apportionment of PM2.5 mass. The model resolved seven factors. A combination of source profiles, temporal evolution, and potential source locations were used to identify these factors as secondary sulfate, combustion aerosol, re-suspended crustal dust, pyrolysis carbon-rich aerosol, biomass burning aerosol, secondary nitrate, and sea salt with mean contributions of 24.8%, 23.6%, 17.3%, 15.7%, 11%, 4.1%, 0.8%, respectively, to the PM2.5 mass during the study period. Rest of the mass was unapportioned. Inter-annual and seasonal variability of sources contributing to PM2.5 mass were also assessed. Combustion aerosol and pyrolysis carbon-rich aerosol were responsible for several high PM2.5 mass concentration episodes at the sampling location. Re-suspended crustal dust was also found to be contributing to episodic highs in PM2.5 mass. Biomass burning aerosol contribution to PM2.5 mass increased during stubble burning months in central and northern India. Conditional Bivariate Probability Function (CBPF) and Potential Source Contribution Function (PSCF) analyses were used to identify local and regional source locations (and/or preferred transport pathways) of aerosol sources, respectively. It was found that PM2.5 at the study was mostly regionally transported and that the predominant regional source locations were Chhattisgarh, northern and south-eastern parts of Madhya Pradesh, western Uttar Pradesh, Delhi, Haryana, Rajasthan, and the Arabian Sea. The outcomes of this study are expected to strengthen the air quality management plans for both VVNP and the city. Further, it is hoped that the results of this study will provide inputs to validate emissions inventories as well as climate model outputs over the region. (C) 2020 Elsevier B.V. All rights reserved.