Emission source apportionment of the road dust-bound trace and major elements in Najafabad to the west of Isfahan megacity (Iran) based on multivariate receptor-oriented source models of PMF, PCFA and UNMIX.

Research in the source apportionment of trace and major elements for the successful implementation of strategies in environmental management has expanded following growth trends in industrial activities, urban transportation systems, and urbanization in developing countries. This study adopted a novel approach to identify and quantify the contribution of geogenic sources along with other potential sources. Enrichment factor (EF), principal component factor analysis (PCFA), positive matrix factorization (PMF), UNMIX receptor model, and the SPECIATE database were used for source apportionment to determine the role of twenty-four trace and major elements as pollutants in the road dust of Najafabad (Iran). The statistical analyses of the geochemical data were conducted via GraphPad Prism, version 9.0, and SPSS, version 22. According to the results, the concentration levels of all the trace and major elements, except Cd and K, were higher than the background value. The mean EF value for Ce was the highest (10.93), followed by Ba (6.09), Al (5.30), Mg (5.71), Sr (3.63), and Y (3.17), while the other elements were of minimum enrichment in the dust samples (EF < 2). The PCFA results resolved four sources with their respective contributions, namely geogenic (57%), industrial (24%), traffic (12%), and unidentified sources (6%). The PMF and UNMIX models revealed three sources with their respective contributions based on marker species: geogenic (80 and 94%), traffic (13 and 5%), and industrial (1 and 7%). The spatial variation analysis of source contribution by UNMIX and PMF revealed that the contribution of industrial and traffic sources corresponded to the substantial activity of factories and transport by light and heavy vehicles in the study area. Overall, the EF results were in agreement with 43% of the PCFA results, 33% of the UNMIX results, and 23% of the PMF results. The study concluded that the PMF model gave acceptable results, but those of EF, PCFA, and UNMIX were unsatisfactory. [ABSTRACT FROM AUTHOR]

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