Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/152082
Title: Inhalation cancer risk estimation of source-specific personal exposure for particulate matter–bound polycyclic aromatic hydrocarbons based on positive matrix factorization
Authors: Han, Bin
You, Yan
Liu, Yating
Xu, Jia
Zhou, Jian
Zhang, Jiefeng
Niu, Can
Zhang, Nan
He, Fei
Ding, Xiao
Bai, Zhipeng
Keywords: Engineering::Environmental engineering
Issue Date: 2019
Source: Han, B., You, Y., Liu, Y., Xu, J., Zhou, J., Zhang, J., Niu, C., Zhang, N., He, F., Ding, X. & Bai, Z. (2019). Inhalation cancer risk estimation of source-specific personal exposure for particulate matter–bound polycyclic aromatic hydrocarbons based on positive matrix factorization. Environmental Science and Pollution Research, 26(10), 10230-10239. https://dx.doi.org/10.1007/s11356-019-04198-y
Journal: Environmental Science and Pollution Research
Abstract: In previous studies, inhalation cancer risk was estimated using conventional risk assessment method, which was normally based on compound-specific analysis, and cannot provide substantial data for source-specific particulate matter concentrations and pollution control. In the present study, we applied an integrated risk analysis method, which was a synthetic combination of source apportionment receptor model and risk assessment method, to estimate cancer risks associated to individual PAHs coming from specific sources. Personal exposure particulate matter samples referring to an elderly panel were collected in a community of Tianjin, Northern China, in 2009, and 12 PAH compounds were measured using GC-MS. Positive matrix factorization (PMF) was used to extract the potential sources and quantify the source contributions to the PAH mixture. Then, the lung cancer risk of each modeled source was estimated by summing up the cancer risks of all measured PAH species according to the extracted source profile. The final results indicated that the overall cancer risk was 1.12 × 10−5, with the largest contribution from gasoline vehicle emission (44.1%). Unlike other risk estimation studies, this study was successful in combining risk analysis and source apportionment approaches, which allow estimating the potential risk of all source types and provided suitable information to select prior control strategies and mitigate the main air pollution sources that contributing to health risks.
URI: https://hdl.handle.net/10356/152082
ISSN: 0944-1344
DOI: 10.1007/s11356-019-04198-y
Rights: © 2019 Springer-Verlag GmbH Germany, part of Springer Nature. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:ERI@N Journal Articles

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