This study aims at exploring size distribution, meteorological influence and uncertainty for source-specific risks of atmospheric particulate matter (PM), which can improve risk-mitigation strategies for health protection. Heavy metals (HMs) and polycyclic aromatic hydrocarbons (PAHs) in PM2.5 and PM10 were detected in a Chinese megacity during 2011?2021. A new method named as PMFBMR, which combines the Positive Matrix Factorization, Bootstrapping, Mote Carlo and Risk assessment model, was developed to estimate uncertainty of source-specific risks. It was found that PAH risks concentrated in fine PM, while HMs showed high risks in both fine and coarse PMs. For PM2.5, HQ (non-cancer risk hazard quotient) of gasoline combustion (GC), diesel and heavy oil combustion (DC), coal combustion (CC), industrial source (IS), resuspended dust (RD) and secondary and transport PM (ST) were 0.6, 1.4, 0.9, 1.6, 0.3, and 0.3. ILCR (lifetime cancer risk) of sources were IS (9.2E-05)?>?DC (2.6E-05)?=?CC (2.6E-05)?>?RD (2.2E-05)?>?GC (1.7E-05)?>?ST (6.4E-06). PM2.5 from GC, DC, CC and IS caused higher risks than coarse PM, while coarse PM from RD caused higher risks. Source-specific risks were influenced not only by emissions, but also by meteorological condition and dominant toxic components. Risks of GC and DC were usually high during stable weather. Some high risks of CC, IS and RD occurred at strong WS due to transport or wind-blown resuspension. GC and DC risks (influenced by both PAHs and HMs) showed strong relationship with T, while IS and RD risks (dominated by HMs) showed weak link with meteorological conditions. For uncertainty of source-specific risks, HQ and ILCR were sensitive for different variables, because they were dominated by components with different uncertainties. When using source-specific risks for risk-mitigation strategies, the focused toxic components, used toxic values, PM sizes and uncertainty are necessary to be considered.

» Author: Yingze Tian, Bin Jia, Peng Zhao, Danlin Song, Fengxia Huang, Yinchang Feng

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