Source apportionment and heavy metal health risk (HMHR) quantification from sources in a southern city in China, using an ME2-HMHR model

Heavy metals (Cr, Co, Ni, As, Cd, and Pb) can be bound to PM adversely affecting human health. Quantifying the source impacts on heavy metals can provide source-specific estimates of the heavy metal health risk (HMHR) to guide effective development of strategies to reduce such risks from exposure to heavy metals in PM_2.5 (particulate matter (PM) with aerodynamic diameter less than or equal to 2.5 μm). In this study, a method combining Multilinear Engine 2 (ME2) and a risk assessment model is developed to more effectively quantify source contributions to HMHR, including heavy metal non-cancer risk (non-HMCR) and cancer risk (HMCR). The combined model (called ME2-HMHR) has two steps: step1, source contributions to heavy metals are estimated by employing the ME2 model; step2, the source contributions in step 1 are introduced into the risk assessment model to calculate the source contributions to HMHR. The approach was applied to Huzou, China and five significant sources were identified. Soil dust is the largest source of non-HMCR. For HMCR, the source contributions of soil dust, coal combustion, cement dust, vehicle, and secondary sources are 1.0 × 10⁻⁴, 3.7 × 10⁻⁵, 2.7 × 10⁻⁶, 1.6 × 10⁻⁶ and 1.9 × 10⁻⁹, respectively. The soil dust is the largest contributor to HMCR, being driven by the high impact of soil dust on PM_2.5 and the abundance of heavy metals in soil dust. - Highlights: • As a first effort, source contributions to heavy metal health risk was quantified. • A new combined model was developed by combing ME2 and risk assessment model. • Five sources were identified and contribute to the heavy metal health risk. - A novel combined model was applied to identify five sources of heavy metals and quantify their contributions to heavy metal health risk.