Deciphering source contributions of trace metal contamination in urban soil, road dust, and foliar dust of Guangzhou, southern China

Trace metal contamination prevails in various compartments of the urban environment. Understanding the roles of various anthropogenic sources in urban trace metal contamination is critical for pollution control and city development. In this study, the source contribution from various contamination sources to trace metal contamination (e.g., Cu, Pb, Zn, Co, Cr and Ni) in different environmental compartments in a typical megacity, Guangzhou, southern China, was investigated using the receptor model (Absolute Principal Component Scores-Multiple Linear Regression, APCS-MLR) coupled with the Kriging technique. Lead isotopic data and APCS-MLR analysis identified industrial and traffic emissions as the major sources of trace metals in surface soil, road dust, and foliar dust in Guangzhou. Lead isotopic compositions of road dust and foliar dust exhibited similar ranges, implying their similar sources and potential metal exchange between them. Re-suspended soil contributed to 0–38% and 25–58% of the trace metals in the road dust and foliar dust, respectively, indicating the transport of the different terrestrial dust. Spatial distribution patterns implied that Cu in the road dust was a good indicator of traffic contamination, particularly with traffic volume and vehicle speed. Lead and Zn in foliar dust indicated mainly industrial contamination, which decreased from the emission source (e.g., a power plant and steel factory) to the surrounding environment. The spatial influence of industry and traffic on the contamination status of road dust/foliar dust was successfully separated from that of other anthropogenic sources. This study demonstrated that anthropogenic inputs of trace metals in various environmental compartments (e.g., urban soil, road dust, and foliar dust) can be evaluated using a combined APCS-MLR receptor model and geostatistical analysis at a megacity scale. The coupled use of APCS-MLR analysis, geostatistics, and Pb isotopes successfully deciphered the spatial influence of the contamination sources in the urban environment matrix, providing some important information for further land remediation and health risk assessment.