<p>The current study aims to explore the chemical composition and influence of several sources of coarse aerosol fractions (PM<sub>10</sub>) for the industrial regions of Vapi and Ankleshwar from December 2019 to February 2020. PM<sub>10</sub> refers to particulate matter with aerodynamic diameter of 10 micrometres or less. For Ankleshwar and Vapi, the yearly average PM<sub>10</sub> concentration is between 100.98 and 225.47&#xa0;µg/m<sup>3</sup> and 115.88 to 226.5&#xa0;µg/m<sup>3</sup>. The results of the chemical study for Ankleshwar indicated contributions from EC &amp; OC in the range of 44–48%, WSIs in the range of 21–26%, and elements in the range of 29–31% of PM<sub>10</sub> mass. In Vapi, the total carbon constituted 45 to 48% of PM<sub>10</sub> mass, WSIs constituted 22 to 26% and elements contributed 26 to 29% of PM<sub>10</sub> mass. The significant sources for both Ankleshwar and Vapi are then assessed using PMF. For Ankleshwar, source apportionment using PMF showed the contribution from various sources as 27.73% by crustal or soil dust, 22.94% by burning fossil fuels, 17.94% by vehicular emissions, 13.97% by secondary aerosols, 9.10% by biomass burning, and 8.32% by industrial emissions. Using the PMF receptor model for Vapi, the following sources of effect were identified: combustion (25.75%), crustal or soil dust (22.13%), vehicular emissions (16.95%), biomass burning (14.53%), industrial emissions (11.49%), and secondary aerosols (9.16%). According to the backward trajectory model analysis conducted with HYSPLIT, during the study period, the majority of air mass parcels are observed approaching the Ankleshwar site from the northern regions of Gujarat and Madhya Pradesh, whereas, for Vapi, the impending air parcel is conveyed from the northern region of Maharashtra. The results of this analysis will be used to develop methods for mitigating pollution and enhancing the ambient air quality in the study area. Higher PM<sub>10</sub> or PM<sub>2.5</sub> concentrations are reported to be triggered by the combustion of fossil fuels, crustal or oil dust, and vehicle emissions. When developing air pollution control strategies, these sources should be given higher emphasis.</p>

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Elemental characterisation and source identification of PM10 using PMF receptor model for critically polluted industrial areas of Western India

  • Seema Nihalani,
  • Namrata Jariwala,
  • Anjali Khambete

摘要

The current study aims to explore the chemical composition and influence of several sources of coarse aerosol fractions (PM10) for the industrial regions of Vapi and Ankleshwar from December 2019 to February 2020. PM10 refers to particulate matter with aerodynamic diameter of 10 micrometres or less. For Ankleshwar and Vapi, the yearly average PM10 concentration is between 100.98 and 225.47 µg/m3 and 115.88 to 226.5 µg/m3. The results of the chemical study for Ankleshwar indicated contributions from EC & OC in the range of 44–48%, WSIs in the range of 21–26%, and elements in the range of 29–31% of PM10 mass. In Vapi, the total carbon constituted 45 to 48% of PM10 mass, WSIs constituted 22 to 26% and elements contributed 26 to 29% of PM10 mass. The significant sources for both Ankleshwar and Vapi are then assessed using PMF. For Ankleshwar, source apportionment using PMF showed the contribution from various sources as 27.73% by crustal or soil dust, 22.94% by burning fossil fuels, 17.94% by vehicular emissions, 13.97% by secondary aerosols, 9.10% by biomass burning, and 8.32% by industrial emissions. Using the PMF receptor model for Vapi, the following sources of effect were identified: combustion (25.75%), crustal or soil dust (22.13%), vehicular emissions (16.95%), biomass burning (14.53%), industrial emissions (11.49%), and secondary aerosols (9.16%). According to the backward trajectory model analysis conducted with HYSPLIT, during the study period, the majority of air mass parcels are observed approaching the Ankleshwar site from the northern regions of Gujarat and Madhya Pradesh, whereas, for Vapi, the impending air parcel is conveyed from the northern region of Maharashtra. The results of this analysis will be used to develop methods for mitigating pollution and enhancing the ambient air quality in the study area. Higher PM10 or PM2.5 concentrations are reported to be triggered by the combustion of fossil fuels, crustal or oil dust, and vehicle emissions. When developing air pollution control strategies, these sources should be given higher emphasis.