Determinants of personal exposure to fine particulate matter (PM₂.₅) in adult subjects in Hong Kong

Abstract

Personal monitoring for fine particulate matter (PM₂.₅) was conducted for adults (48 subjects, 18–63 years of age) in Hong Kong during the summer and winter of 2014–2015. All filters were analyzed for PM₂.₅ mass and constituents (including carbonaceous aerosols, water-soluble ions, and elements). We found that season (p = 0.02) and occupation (p < 0.001) were significant factors affecting the strength of the personal-ambient PM₂.₅ associations. We applied mixed-effects models to investigate the determinants of personal exposure to PM₂.₅ mass and constituents, along with within- and between-individual variance components. Ambient PM₂.₅ was the dominant predictor of (R2 = 0.12–0.59, p < 0.01) and the largest contributor (>37.3%) to personal exposures for PM₂.₅ mass and most components. For all subjects, a one-unit (2.72 μg/m3) increase in ambient PM₂.₅ was associated with a 0.75 μg/m3 (95% CI: 0.59–0.94 μg/m3) increase in personal PM₂.₅ exposure. The adjusted mixed-effects models included information extracted from individual's activity diaries as covariates. The results showed that season, occupation, time indoors at home, in transit, and cleaning were significant determinants for PM₂.₅ components in personal exposure (R2β = 0.06–0.63, p < 0.05), contributing to 3.0–70.4% of the variability. For one-hour extra time spent at home, in transit, and cleaning an average increase of 1.7–3.6% (ammonium, sulfate, nitrate, sulfur), 2.7–12.3% (elemental carbon, ammonium, titanium, iron), and 8.7–19.4% (ammonium, magnesium ions, vanadium) in components of personal PM₂.₅ were observed, respectively. In this research, the within-individual variance component dominated the total variability for all investigated exposure data except PM₂.₅ and EC. Results from this study indicate that performing long-term personal monitoring is needed for examining the associations of mass and constituents of personal PM₂.₅ with health outcomes in epidemiological studies by describing the impacts of individual-specific data on personal exposures.