Geochemical Mapping, Risk Assessment, and Source Identification of Heavy Metals in Road Dust Using Positive Matrix Factorization (PMF)

• Main Authors: Muhammad Faisal, Zening Wu, Huiliang Wang, Zafar Hussain, Chenyang Shen
• Format: Article
• Language: English
• Published: MDPI AG 2021-05-01
• Series: Atmosphere
• Subjects: road dust; heavy metals; positive matrix factorization; geochemical mapping; traditional risk assessment
• Online Access: https://www.mdpi.com/2073-4433/12/5/614

Heavy metals in road dust pose a significant threat to human health. This study investigated the concentrations, patterns, and sources of eight hazardous heavy metals (Cr, Ni, Cu, Zn, As, Cd, Pb, and Hg) in the street dust of Zhengzhou city of PR China. Fifty-eight samples of road dust were analyzed based on three methods of risk assessment, i.e., Geo-Accumulation Index (I_geo), Potential Ecological Risk Assessment (RI), and Nemerow Synthetic Pollution Index (PI_N). The results exhibited higher concentrations of Hg and Cd 14 and 7 times higher than their background values, respectively. I_geo showed the risks of contamination in a range of unpolluted (Cr, Ni) to strongly polluted (Hg and Cd) categories. RI came up with the contamination ranges from low (Cr, Ni, Cu, Zn, As, and Pb) to extreme (Cd and Hg) risk of contamination. The risk of contamination based on PI_N was from safe (Cu, As, and Pb) to seriously high (Cd and Hg). The results yielded by PI_N indicated the extreme risk of Cd and Hg in the city. Positive Matrix Factorization was used to identify the sources of contamination. Factor 1 (vehicular exhaust), Factor 2 (coal combustion), Factor 3 (metal industry), and Factor 4 (anthropogenic activities), respectively, contributed 14.63%, 35.34%, 36.14%, and 13.87% of total heavy metal pollution. Metal’s presence in the dust is a direct health risk for humans and warrants immediate and effective pollution control and prevention measures in the city.