Early warning of urban heavy metal pollution based on PMF- MeteoInfo model combined with physicochemical properties of dust

Abstract

Heavy metals in dust have been found to be a significant threat to human health, but how dust sources and physicochemical properties influence the distribution of heavy metals has not been fully investigated. Fuzhou, a Chinese subtropical city, was chosen as a case in this study. We collected 51 dust samples from open spaces, in order to serve as an early warning system for heavy metals in urban dust, the risk level of heavy metal pollution was assessed, the physicochemical properties of dust were analyzed, and the sources of heavy metals were examined using a combination of positive matrix factorization (PMF) and backward trajectory model (MeteoInfo). The results showed that the average concentrations of heavy metals were Zn > Pb > Cr > Cu > Ni > As > Cd, with Cd having the highest ecological risk level. All heavy metals are positively correlated, the higher the organic matter and the larger the particle size, the higher the heavy metal concentration. The higher the water content, the higher the Ni and Cu content. The sources of heavy metals in dust are complex and include local anthropogenic sources: traffic, architectural paint, combustion, and mixed sources, as well as the impact of atmospheric motion on dust from northern cities in Fuzhou City and Zhejiang Province. Our study provides a valuable point of reference for early warning of urban heavy metal.

Graphical Abstract

Sources of heavy metals in open space and ways of entering the human body.