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  • Title: Distribution patterns, infiltration and health risk assessment of PM2.5-bound PAHs in indoor and outdoor air in cold zone.
    Author: Mohammed MOA, Song WW, Ma YL, Liu LY, Ma WL, Li WL, Li YF, Wang FY, Qi MY, Lv N, Wang DZ, Khan AU.
    Journal: Chemosphere; 2016 Jul; 155():70-85. PubMed ID: 27108365.
    Abstract:
    In this study we investigated the distribution patterns, infiltration and health risk assessment of PM2.5-bound PAHs in indoor and outdoor air done in Harbin city, northeastern China. Simultaneous indoor and outdoor sampling was done to collect 264 PM2.5 samples from four sites during winter, summer, and spring. Infiltration of PAHs into indoors was estimated using Retene, Benzo [ghi]perylene and Chrysene as reference compounds, where the latter compound was suggested to be a good estimator and subsequently used for further calculation of infiltration factors (IFs). Modeling with positive matrix factorization (PMF5) and estimation of diagnostic isomeric ratios were applied for identifying sources, where coal combustion, crop residues burning and traffic being the major contributors, particularly during winter. Linear discriminant analysis (LDA) has been utilized to show the distribution patterns of individual PAH congeners. LDA showed that, the greatest seasonal variability was attributed to high molecular weight compounds (HMW PAHs). Potential health risk of PAHs exposure was assessed through relative potency factor approach (RPF). The levels of the sum of 16 US EPA priority PAHs during colder months were very high, with average values of 377 ± 228 ng m(-)(3) and 102 ± 75.8 ng m(-)(3), for the outdoors and indoors, respectively. The outdoor levels reported to be 19 times higher than the outdoor concentrations during warmer months (summer + spring), while the indoor concentrations were suggested to be 9 times and 10 times higher than that for indoor summer (average 11.73 ± 4 ng m(-3)) and indoor spring (9.5 ± 3.3 ng m(-3)). During nighttime, outdoor PAHs revealed wider range of values compared to datytime which was likely due to outdoor temperature, a weather parameter with the strongest negative influence on ∑16PAHs compared to low impact of relative humidity and wind speed.
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