Source identification and ambient trace element concentrations of PM₁₀ using receptor modeling in an urban area of Chhattisgarh, India

Abstract

This study investigated seasonal variation in PM₁₀ aerosols and associated trace metal concentrations in an urban city Raipur, India. PM₁₀ aerosols were monitored at Raipur for the year 2015 to 2019. Eighteen trace elements (Al, Ba, Ca, Cr, As, Mn, Sb, Se, Sr, Cu, Fe, Ga, Mg, Ni, Ti, V, Pb, Zn) and (EC and OC) were analyzed using atomic absorption spectroscopy and thermal optical transmittance technique. A receptor-based positive matrix factorization (PMF) model was used to identify the possible sources with qualitative analysis of crustal enrichment factor, back-trajectory analysis using concentration weighted trajectory (CWT) to predict potential locations of distant sources, and correlation between different species. The average PM₁₀ aerosol mass concentration during the study period was found to be 184.91 ± 114 µg/m³. Seasonally, the average winter–time PM₁₀ concentration (193.49 ± 129.18 µg/m³) was found higher as compared to summer time (176.32 ± 65.80 µg/m³) during the study period. Five sources were identified including the iron and steel industry (30%), biomass and waste combustion (28.7%), vehicular emissions (21%), heavy oil combustion (17.4%), and crustal dust (2.9%). The study provides information on major sources affecting air quality.

Keywords:

• PM₁₀
• heavy metals
• positive matrix factorization
• source apportionment
• HYSPLIT model

Conflict of interest

There are no conflicts of interest to declare.

Data availability statement

The data analyzed during this study are openly available in the data repository figshare at https://figshare.com/s/fc455d849afcfff96228.

Author contributions

P.K. (Ph.D. student) conducted all the experiments and wrote the manuscript. A.A. (Professor) revised the manuscript.