Soil heavy metals harm ecological biodiversity and human health, and quantifying the risks more accurately is still obscure. In this study, a network environ analysis was applied to quantify risks between ecological communities based on control allocation and human health risk models to calculate human health exposure risks from soil heavy metals around Greenside coal mining in South Africa. Ecological and human health risks were apportioned using PMF model. Results showed assessed heavy metals (mean) exceeded local background content with a cumulative of moderately polluted using pollution load index (PLI). Total initial risk (Ri), the risk to biological organisms from direct soil exposure, was 0.656 to vegetation and 1.093 to soil microorganisms. Risk enters the food web via vegetation and harms the whole system. Integrated risks (initial, direct, and indirect) to vegetation, herbivores, soil microorganisms, and carnivores were 0.656, 0.125, 1.750, and 0.081, respectively, revealing that soil microorganisms are the most risk receptors. Total Hazard Index (HIT) was <1 for adults (0.574) whereas >1 for children (4.690), signifying severe non-cancer effects to children. Total cancer risk (TCR) to children and adults surpassed the unacceptable limit (1.00E-04). Comparatively, Cr is a high-risk metal accounted for 63.24% (adults) and 65.88% (children) of the HIT and 92.98% (adults) and 91.31% (children) of the TCR. Four sources were apportioned. Contributions to Ri (soil microorganisms and vegetation) from F3 (industrial), F4 (atmospheric), F2 (coal mining), and F1 (natural) were 42.20%, 24.56%, 23.55%, and 9.68%, respectively. The non-cancer risk from F3 (37.67% to adults and 38.40% to children) was dominant, and TCR to children from the sources except F1 surpassed the unacceptable limit. An integrated approach of risk quantification is helpful in managing risks and reducing high-risk pollution sources to better protect the environment and human health.
