Abstract
The health effects of PM2.5 associated heavy metals have caused wide public concern. To more accurately assess source-specific health risks of PM2.5-bound heavy metals, and to formulate a cost-effective control strategy to health risk reduction, it is necessary to have a better understanding of the temporal variation of source-specific health risks. For this purpose, hourly PM2.5 and associated heavy metals were measured during four seasons in 2018–2019 in a Chinese megacity. A method integrating positive matrix factorization (PMF) with the health risk assessment model was used to quantify the source-specific health risks. Results showed that the total hazard index (HI) of PM2.5-bound heavy metals was 1.35, higher than the safety level, the sum cancer risks (R) of carcinogenic elements (Cr, Co, Ni and As) were 2.8 × 10−5, implying nonnegligible risks. Industrial source 1 (61.3%), which was related with Mn posed the largest non-cancer risk, while coal combustion (36.1%) and industrial source 1 (34.9%) posed most of the cancer risk, and slightly fluctuated with seasons. Health risks of most resolved sources were higher in autumn and winter than in other seasons. In terms of the diurnal variation, they were the lowest in the afternoon. Besides, the health risks of vehicle source had a peak value in rush hours. Different scenarios were simulated to understand the influences of time resolutions and sampling periods on source-specific risk assessment. The results showed the cancer risks of coal combustion and industrial source 1 calculated from the dataset with reduced sampling periods were different from those calculated from the whole dataset. We conclude that source-specific health risks of heavy metals show seasonal and diurnal variations, which suggests that targeted strategies should be adopted on the basis of seasonal and diurnal cycles to protect public health. In addition, a sufficient sampling period is required to generate representative and reliable results for source-specific health risk assessment.
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