Source Apportionment of PM10 Over Three Tropical Urban Atmospheres at Indo-Gangetic Plain of India: An Approach Using Different Receptor Models

• Published in: Archives of environmental contamination and toxicology 2019-01, Vol.76 (1), p.114-128
• Main Authors: Jain, Srishti, Sharma, Sudhir Kumar, Srivastava, Manoj Kumar, Chaterjee, Abhijit, Singh, Rajeev Kumar, Saxena, Mohit, Mandal, Tuhin Kumar
• Format: Article
• Language: English
• Subjects: Airborne particulates; Atmospheric models; Biomass burning; Burning; Chemical speciation; Combustion; Comparative analysis; Earth and Environmental Science; Ecotoxicology; Environment; Environmental Chemistry; Environmental Health; Fossil fuels; Fuel combustion; Industrial emissions; Magnesium; Monitoring/Environmental Analysis; Organic chemistry; Particulate emissions; Particulate matter; Pollution; Principal components analysis; Sampling; Sodium; Soil Science & Conservation; Sulfates; Temporal variations; Urban atmosphere; Vehicle emissions
• ISSN: 0090-4341; 1432-0703
• DOI: 10.1007/s00244-018-0572-4

The present work is the ensuing part of the study on spatial and temporal variations in chemical characteristics of PM 10 (particulate matter with aerodynamic diameter ≤ 10 μm) over Indo Gangetic Plain (IGP) of India. It focuses on the apportionment of PM 10 sources with the application of different receptor models, i.e., principal component analysis with absolute principal component scores (PCA-APCS), UNMIX, and positive matrix factorization (PMF) on the same chemical species of PM 10 . The main objective of this study is to perform the comparative analysis of the models, obtained mutually validated outputs and more robust results. The average PM 10 concentration during January 2011 to December 2011 at Delhi, Varanasi, and Kolkata were 202.3 ± 74.3, 206.2 ± 77.4, and 171.5 ± 38.5 μg m −3 , respectively. The results provided by the three models revealed quite similar source profile for all the sampling regions, with some disaccords in number of sources as well as their percent contributions. The PMF analysis resolved seven individual sources in Delhi [soil dust (SD), vehicular emissions (VE), secondary aerosols (SA), biomass burning (BB), sodium and magnesium salt (SMS), fossil fuel combustion, and industrial emissions (IE)], Varanasi [SD, VE, SA, BB, SMS, coal combustion, and IE], and Kolkata [secondary sulfate (Ssulf), secondary nitrate, SD, VE, BB, SMS, IE]. However, PCA-APCS and UNMIX models identified less number of sources (besides mixed type sources) than PMF for all the sampling sites. All models identified that VE, SA, BB, and SD were the dominant contributors of PM 10 mass concentration over the IGP region of India.