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Updated: Mar 10, 2026

An Anaerobic Biosensor Assay for the Detection of Mercury and Cadmium
Published on: December 17, 2018
Source apportionment and heavy metal health risk (HMHR) quantification from sources in a southern city in China,
Xing Peng1, GuoLiang Shi1, GuiRong Liu2
1State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China.
Abstract:
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 PM2.5 (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 PM2.5 and the abundance of heavy metals in soil dust.
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