This study systemically investigated the ambient PM2.5 (n = 108) with comprehensive analyses of the chemical composition, identification of the potential contributors, and estimation of the resultant respiratory physician visits in the residential regions near energy-consuming and high-polluting industries in central Taiwan. The positive matrix fraction (PMF) model with chemical profiles of trace metals, water-soluble ions, and organic/elemental carbons (OC/EC) was applied to quantify the potential sources of PM2.5. The influences of local sources were also explored using the conditional probability function (CPF). Associations between the daily PM2.5 concentration and the risk of respiratory physician visits for the elderly (≥ 65 years of age) were estimated using time-series analysis. A seasonal variation, with higher concentrations of PM2.5, metals (As, Cd, Sb, and Pb), OC/EC and ions (i.e., NO3 −, SO42 − and NH4+) in the winter than in the spring and summer, was observed. Overall, an increase of 10 μg m− 3 in the same-day PM2.5 was associated with an ~ 2% (95% CI: 1.5%–2.5%) increase in respiratory physician visits. Considering the health benefits of an effective reduction, we suggest that the emission from coal combustion (23.5%), iron ore and steel industry (17.1%), and non-ferrous metallurgy (14.4%), accounting for ~ 70% of the primary PM2.5 in the winter are prioritized to control.
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