Sources and uncertainties of health risks for PM2.5-bound heavy metals based on synchronous online and offline filter-based measurements in a Chinese megacity.

Abstract

Accurate measurements of PM2.5 related heavy metals (HMs) and some components are critical to better understanding the sources and health risks of PM2.5. HMs and other components in PM2.5 were simultaneously measured using online and offline filter-based methods in a Chinese megacity. Online Mn, Pb, Cu, and Zn concentrations exhibited good correspondence with offline results (R2≥0.7, relative biases=-3%-22%). Some differences were observed for Cr, As, Co, and V. The assessment of online and offline probabilistic health risks indicated that non-cancer and total cancer risks were higher than the acceptable limits. Different analytical methods of As may result in different uncertainties in risk analysis. The positive matrix factorization model (PMF) was used to perform online and offline source apportionment. Five sources (coal combustion, vehicle source, industrial source, secondary source, and resuspended dust) were identified. Lower online percentage contribution of resuspended dust (8%) might relate to the lack of Si and Al measurements. The different rate contributions of vehicle source were potentially linked to the different time resolutions of the online and offline data. The assessment of online and offline source-specific health risks revealed that industrial source and coal combustion were the most important sources. Online and offline source-specific risks were not significantly different (P>0.05). This contrastive study not only helps decision makers to manage health risk more effectively, but also provides insights into the applicability of online and offline measurements for quantifying source-specific risks.