Introduction: The present study examines human exposure to Particulate Matter (PM10) and analyses potential health concerns in the industrial zones of Ankleshwar and Vapi in Gujarat. Materials and methods: For Ankleshwar and Vapi, 120 samples were collected, and characterisation was carried out to determine the concentration of NO3, SO4, NH3, K-S, Na, EC, OC, Al, Si, Fe, K, Ti, Ni, Br, Ca, Cl, Mn, Pb, Cr, Zn, S, V, and Cu in PM10 mass. The health risk from exposure to different trace elements, including both carcinogenic and non-carcinogenic, is evaluated for three distinct paths of ingestion, inhalation, and skin contact. Results: The Excess Cancer Risk (ECR) values for Cr and Pb for the ingestion pathway and the carcinogenic risks for Cr, Ni, and Pb for the inhalation pathway are both found to be higher than the minimal permissible threshold (1×10−, 6) for both children and adults for Ankleshwar and Vapi. However, for Ankleshwar and Vapi, the carcinogenic risks from dermal exposure to Cr and Pb are found to be lower than the permissible limit for both adults and children. It is observed that non-carcinogenic Hazard Index (HI) values for the skin contact and ingestion routes are less than 1 for both children and adults for Ankleshwar and Vapi. While the HI value for the inhalation pathway is found to be larger than the tolerable limit of 1 for both adults and children. Conclusion: For the purpose of creating sustainable cities and improving the health of the urban population, this study will provide a fundamental basis and help the governing authorities design mandatory pollution prevention and control methods, restoration plans, and systematic monitoring programmes.

Introduction: Receptor models use the chemical characterisation of particulate matter to distinguish the source and analyse the source contributions. The main aim of this study is to carry out source apportionment of PM10 for industrial locations of Vapi and Ankleshwar in Gujarat, using the Chemical Mass Balance (CMB) receptor model. Materials and methods: At six distinct locations of Ankleshwar and Vapi, respirable dust samplers were used to collect particulate matter on quartz filter sheets for the current study. Filter papers containing PM10 mass were subsequently examined for Water Soluble Ions (WSIs), major and trace elements, elemental and organic carbon followed by source apportionment study. Results: Using CMB, the contributions obtained for Ankleshwar are 27. 85% for crustal or soil dust, 26. 31% for fossil fuel combustion, 21. 06% for vehicle emissions, 14. 20% for secondary aerosols, 9. 30% for biomass, and 1. 20% for industrial emissions. CMB for Vapi revealed the chief source signatures as fossil fuel combustion including industries contributing 35%, crustal or soil dust contributing 22. 90%, biomass burning contributing 19. 12%, vehicular emissions contributing 16. 18%, and secondary aerosols contributing 6. 79%. Conclusion: By applying the CMB model, the primary source is found to be crustal or soil dust followed by burning fossil fuels, vehicular emissions, and secondary aerosols for Ankleshwar and Vapi, respectively. A quantitative assessment of source contributions to particulate matter is required to create emission control measures. The findings of this study will be beneficial for the environmental management of particle concentrations in the study region.

Pollution from atmospheric particulates is a severe environmental problem of universal concern. Fine and ultra-fine particulates harbour the ability to enter the bloodstream and carry with them trace metals like copper, cadmium, iron, lead, and zinc that can cause toxic and carcinogenic effects. This necessitates an increased emphasis on the detailed chemical characterisation of atmospheric particulates. The current study identified six locations in the Vapi industrial area. In these six locations, coarse particulate matter (PM10) samples were collected simultaneously for 20 days to determine the Elemental Carbon (EC), Organic Carbon (OC), Water-soluble ions (WSIs), and major and trace elements. The concentration of PM10 was observed to be in the range of 115. 88 to 226. 5 μg/m3, exceeding the NAAQS standard value of 100 ug/m3. The chemical analysis results suggested contributions from total carbon, water-soluble ions, and elements varied between 45 to 48%, 20 to 23%, and 29 to 33% of PM10 mass, respectively. Chemical mass balance (CMB) and Positive matrix factorisation (PMF) models were employed separately for carrying out source apportionment studies. CMB demonstrated influence from various sources: 35% from fossil fuel combustion that included industries, 22. 90% from crustal or soil dust, 19. 12% from biomass burning, 16. 18% from vehicular emissions, and 6. 79 % from secondary particulates. The PMF receptor model showed the influence from various sources as 25. 75 % from fossil fuel combustion, 22. 13 % from crustal or soil dust, 16. 95% from vehicular emissions, 14. 53% from biomass burning, 11. 49% from industrial emissions, and 9. 16% from secondary aerosols. Thus, this study shall help in formulating pollution abetment strategies.