Personal exposure monitoring of fine and coarse particulate matter using exposure assessment models for elderly residents in Hong Kong.

This study investigated the determinants of personal exposures (PE) to coarse (PM) and fine particulate matter (PM) for elderly communities in Hong Kong. The mean PE PM and PM were 23.6 ± 10.8 and 13.5 ± 22.1 μg/m, respectively during the sampling period. Approximately 76% of study subjects presented statistically significant differences between PE and ambient origin for PM compared to approximately 56% for PM, possibly due to the coarse-size particles being more influenced by similar sources (road dust and construction dust emissions) compared to the PM particles. Individual PE to ambient (P/A) ratios for PM all exceeded unity (≥1), suggesting the dominant influences of non-ambient particles contributed towards total PE values. There were about 80% individual P/A ratios (≤1) for PM, implying possible effective infiltration prevention of larger size particulate matter particles leading to dominant influences from the outdoor sources. The higher concentration of NO and SO in PM compared to PM suggests possible heterogeneous reactions of alkaline minerals leading to the formation of NO and SO in PM particles. The PE and ambient OC/EC ratios in PM (8.8 ± 3.3 and 10.4 ± 22.4, respectively) and in PM (6.0 ± 1.9 and 3.0 ± 1.1, respectively) suggest possible secondary formed OC from surrounding rural areas. Heterogeneous distributions (COD >0.2) between the PE and ambient concentrations were found for both the PM and PM samples. The calibration coefficient as the association between personal and surrogate exposure measure of PE to PM (0.84) was higher than PM (0.52). The findings further confirm that local sources were the dominant contributor to the coarse particles and these coefficients can potentially be used to estimate different PE to PM and PM conditions. A comprehensive understanding of the PE to determinants in coarse particles is essential to further reduce potential exposure misclassification.