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Mass Concentration, Source and Health Risk Assessment of Volatile Organic Compounds in Nine Cities of Northeast China

Author

Listed:
  • Jianwu Shi

    (Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming 650500, China
    National-Regional Engineering Center for Recovery of Waste Gases from Metallurgical and Chemical Industries, Kunming 650500, China)

  • Yuzhai Bao

    (Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming 650500, China
    National-Regional Engineering Center for Recovery of Waste Gases from Metallurgical and Chemical Industries, Kunming 650500, China)

  • Liang Ren

    (Faculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming 650500, China)

  • Yuanqi Chen

    (Faculty of Civil Engineering and Mechanics, Kunming University of Science and Technology, Kunming 650500, China)

  • Zhipeng Bai

    (State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China)

  • Xinyu Han

    (Faculty of Civil Engineering and Mechanics, Kunming University of Science and Technology, Kunming 650500, China)

Abstract

From April 2008 to July 2009, ambient measurements of 58 volatile organic compounds (VOCs), including alkanes, alkenes, and aromatics, were conducted in nine industrial cities (Shenyang, Fushun, Changchun, Jilin, Harbin, Daqing, Huludao, Anshan and Tianjin) of the Northeast Region, China (NRC). Daqing had the highest concentration of VOCs (519.68 ± 309.88 μg/m 3 ), followed by Changchun (345.01 ± 170.52 μg/m 3 ), Harbin (231.14 ± 46.69 μg/m 3 ), Jilin (221.63 ± 34.32 μg/m 3 ), Huludao (195.92 ± 103.26 μg/m 3 ), Fushun (135.43 ± 46.01 μg/m 3 ), Anshan (109.68 ± 23.27 μg/m 3 ), Tianjin (104.31 ± 46.04 μg/m 3 ), Shenyang (75.2 ± 40.09 μg/m 3 ). Alkanes constituted the largest percentage (>40%) in concentrations of the quantified VOCs in NRC, and the exception was Tianjin dominated by aromatics (about 52.34%). Although alkanes were the most abundant VOCs at the cities, the most important VOCs contributing to ozone formation potential (OFP) were alkenes and aromatics. Changchun had the highest OFP (537.3 μg/m 3 ), Tianjin had the lowest OFP (111.7 μg/m 3 ). The main active species contributing to OFP in the nine cities were C2~C6 alkanes, C7~C8 aromatic hydrocarbons, individual cities (Daqing) contained n-hexane, propane and other alkane species. Correlation between individual hydrocarbons, B/T ratio and principal component analysis model (PCA) were deployed to explore the source contributions. The results showed that the source of vehicle exhausts was one of the primary sources of VOCs in all nine cities. Additionally, individual cities, such as Daqing, petrochemical industry was founded to be an important source of VOCs. The results gained from this study provided a large of useful information for better understanding the characteristics and sources of ambient VOCs incities of NRC. The non-carcinogenic risk values of the nine cities were within the safe range recognized by the U.S. Environmental Protection Agency (HQ < 1), and the lifetime carcinogenic risk values of benzene were 3.82 × 10 −5 ~1.28 × 10 −4 , which were higher than the safety range specified by the US Environmental Protection Agency (R < 1.00 × 10 −6 ). The results of risk values indicated that there was a risk of cancer in these cities.

Suggested Citation

  • Jianwu Shi & Yuzhai Bao & Liang Ren & Yuanqi Chen & Zhipeng Bai & Xinyu Han, 2022. "Mass Concentration, Source and Health Risk Assessment of Volatile Organic Compounds in Nine Cities of Northeast China," IJERPH, MDPI, vol. 19(8), pages 1-17, April.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:8:p:4915-:d:796387
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    References listed on IDEAS

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    1. Henry Kaiser, 1958. "The varimax criterion for analytic rotation in factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 23(3), pages 187-200, September.
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