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 (47.6 %) and PAHs (40.2 %), but not always the largest contributor of HHR. Agricultural or urban green-space management activities of HM, and mixed source of PAH, are the largest contributors of non-carcinogenic risk (NCR, 48.7 % and 51.1 %, respectively), while mixed source of HM and traffic emissions of PAH are the largest contributors of carcinogenic risk (CR, 53.9 % and 71.2 %, respectively). The probability of risk exceeding safe threshold levels is < 5.0 % for NCR and > 90.0 % for CR. High-risk hotspots were identified in the mid-west and south of the city, making up 15.0 % of the total Guangzhou area. Risk mechanisms were deduced from the spatial heterogeneity and inter-dependence of emission sources and soil sink, based on source–sink theory. Our findings provide a new framework for precisely identifying risk sources and target areas, thereby alleviating HHR associated with co-occurring HMs and PAHs in urban soil systems.
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