Receptor model-based approach to estimate urban road dust pollution by heavy metal(loid)s exposed to desert dust storms in a rapid-growing city of Iran

To assess the application of a receptor model on the identification of urban road dust pollution and associated human health risks by six heavy metal(loid)s (i.e., As, Cr, Cu, Ni, Pb, and Zn), the present study was carried out in Yazd City, a major city in Iran, that commonly experiences severe desert dust storms. The results indicate that, except for Ni, the mean concentration of all metal(loid)s was found to be higher than corresponding values in the upper continental crust with the highest ratio for Pb (3.8). Geogenic sources (i.e., dust storms and mining activities), vehicular emissions, and industrial emissions (iron, steel, tile, and ceramic factories) are responsible for heavy metal(loid)s pollution in urban road dust from the study area. According to the results of the PMF receptor model, geogenic sources are mainly characterized by Ni (65.8%), As (51.1%), and Zn (45.1%), whereas vehicular emissions are chiefly dominated by Pb (69.9%). With the contribution of 75.6% and 43.2%, Cr and As are the principal heavy metal(loid)s that originate from industrial emissions, respectively. Receptor model-based pollution assessment (RMB-MPI) highlighted those industrial emissions, followed by vehicular emissions and geogenic sources, are responsible for severe, high, and moderate pollution, respectively. The mean value of carcinogenic risk for Cr was found to be at the acceptable level for adults, whereas children are predicted to be at substantial risk of developing cancers due to exposure to Cr. Although the receptor model-based approach to estimate children's health risk (RMB-HHRA) due to exposure to Cr showed an acceptable level of risk from geogenic, vehicular, and industrial sources, the cumulative concentrations of Cr from all three source types lead to elevated cancer risk in children.