Journal
JOURNAL OF HAZARDOUS MATERIALS
Volume 283, Issue -, Pages 462-468Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jhazmat.2014.09.062
Keywords
Polycyclic aromatic hydrocarbons; Positive matrix factorization; Multilinear Engine 2; Receptor model-incremental lifetime cancer risk; Cancer risk apportionment
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Funding
- National Natural Science Foundation of China [21207070, 41375132]
- Special Funds for Research on Public Welfares of the Ministry of Environmental Protection of China [201409003]
- Tianjin Research Program of Application Foundation and Advanced Technology [13JCZDJC36100]
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PM10 and PM2.5 samples were simultaneously collected during a one-year monitoring period in Chengdu. The concentrations of 16 particle-bound polycyclic aromatic hydrocarbons (Sigma(16)PAHs) were measured. Sigma(15)PAHs concentrations varied from 16.85 to 160.24 ng m(-3) and 14.93 to 111.04 ng m(-3) for PM10 and PM2.5, respectively. Three receptor models (principal component analysis (PCA), positive matrix factorization (PMF), and Multilinear Engine 2 (ME2)) were applied to investigate the sources and contributions of PAHs. The results obtained from the three receptor models were compared. Diesel emissions, gasoline emissions, and coal and wood combustion were the primary sources. Source apportionment results indicated that these models were able to track the Sigma PAHs. For the first time, the cancer risks for each identified source were quantitatively calculated for ingestion and dermal contact routes by combining the incremental lifetime cancer risk (ILCR) values with the estimated source contributions. The results showed that gasoline emissions posed the highest cancer risk, even though it contributed less to Sigma(16)PAHs. The results and method from this work can provide useful information for quantifying the toxicity of source categories and studying human health in the future. (C) 2014 Elsevier B.V. All rights reserved.
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