A spatial source-oriented and probability-based risk-assessment framework for heavy metal and PAH contamination of urban soils in Guangzhou, China.

The identification and quantification of high-risk hotspots for soils contaminated by heavy metals (HMs) and polycyclic aromatic hydrocarbons (PAHs) remains a challenge due to their various sources and heterogeneous sink properties in urban soil systems. In this study of 221 soil samples from Guangzhou, China, a novel framework combining Bivariate local Moran's I (BLMI), positive matrix factorization (PMF), human health risk (HHR) assessment, Monte Carlo simulation (MCS), and a newly developed spatial risk model were proposed to conduct probabilistic source-oriented HHR assessment, high-risk hotspot quantification, and risk formation mechanism elaboration. Study results indicate that traffic emissions are the largest contributor of HMs (47.