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Assessing the Spatial Distribution of Soil PAHs and their Relationship with Anthropogenic Activities at a National Scale

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  • Siyan Zeng

    (School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221008, China)

  • Jing Ma

    (Low Carbon Energy Institute, China University of Mining and Technology, Xuzhou 221008, China)

  • Yanhua Ren

    (School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221008, China)

  • Gang-Jun Liu

    (Geospatial Sciences, College of Science, Engineering, and Health, RMIT University, Melbourne 3000, Australia)

  • Qi Zhang

    (School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221008, China)

  • Fu Chen

    (School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221008, China
    Low Carbon Energy Institute, China University of Mining and Technology, Xuzhou 221008, China)

Abstract

Soil polycyclic aromatic hydrocarbon (PAH) pollution is a major concern due to its negative impact on soil quality around the world. In China, accurate data on soil PAHs and information on the relationship with anthropogenic activities are limited. In this study, about 30,800 samples from 1833 soil sample sites were reviewed from 306 published reports to build a soil PAHs database. Based on the data obtained, the results demonstrated that 24.11% of surface soils in China are heavily contaminated. Meanwhile, the concentration of soil PAHs varied, in the order of independent mining and industrial areas (IMIA) > urban areas > suburban areas > rural areas, and the spatial distribution in China demonstrated a descending trend from north to south. Moreover, the characteristic ratio and PCA-MLR (principal component analysis-multiple linear regression) analysis demonstrated that coal combustion and vehicular exhaust emissions were the main sources of soil PAH pollution in China. On the other hand, provincial total Σ 16 PAHs in surface soil were significantly correlated with the per square kilometer GDP (gross domestic product) of industrial land, the per capita GDP, as well as the production and consumption of energy. These results indicate that anthropogenic factors have greatly affected the levels of soil PAHs in China. This study improves our understanding on the status and sources of soil PAH contamination in China, thereby facilitating the implementation of strategies of prevention, control, and remediation of soils.

Suggested Citation

  • Siyan Zeng & Jing Ma & Yanhua Ren & Gang-Jun Liu & Qi Zhang & Fu Chen, 2019. "Assessing the Spatial Distribution of Soil PAHs and their Relationship with Anthropogenic Activities at a National Scale," IJERPH, MDPI, vol. 16(24), pages 1-22, December.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:24:p:4928-:d:294582
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    References listed on IDEAS

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    1. Feng, Taiwen & Sun, Linyan & Zhang, Ying, 2009. "The relationship between energy consumption structure, economic structure and energy intensity in China," Energy Policy, Elsevier, vol. 37(12), pages 5475-5483, December.
    2. Per Ahlgren & Bo Jarneving & Ronald Rousseau, 2003. "Requirements for a cocitation similarity measure, with special reference to Pearson's correlation coefficient," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 54(6), pages 550-560, April.
    3. William W. Hood & Concepción S. Wilson, 2001. "The Literature of Bibliometrics, Scientometrics, and Informetrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 52(2), pages 291-314, October.
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    Cited by:

    1. Dongxiang Chen & Han Zhao & Jun Zhao & Zhenci Xu & Shaohua Wu, 2020. "Mapping the Finer-Scale Carcinogenic Risk of Polycyclic Aromatic Hydrocarbons (PAHs) in Urban Soil—A Case Study of Shenzhen City, China," IJERPH, MDPI, vol. 17(18), pages 1-13, September.
    2. Carmen Otilia Rusănescu & Irina Aura Istrate & Andrei Marian Rusănescu & Gabriel Alexandru Constantin, 2024. "Bioremediation of Soil Contamination with Polycyclic Aromatic Hydrocarbons—A Review," Land, MDPI, vol. 14(1), pages 1-27, December.
    3. Krystyna Ciarkowska & Messias de Carvalho & Florian Gambus, 2022. "Analysis of Polycyclic Aromatic Hydrocarbons (PAHs) Sources and Vertical Distribution in Soils of the Age-Diverse Brownfields of Southern Poland Using Positive Matrix Factorisation and Data Mining Mod," Sustainability, MDPI, vol. 14(21), pages 1-16, October.
    4. Kaywood Elijah Leizou & Gift Cornelius Timighe & Muhammad Aqeel Ashraf, 2022. "Pah Exposition And Carcinogenicity Risk Evaluation In Soils From Niger Delta, Nigeria," Environmental Contaminants Reviews (ECR), Zibeline International Publishing, vol. 5(1), pages 35-39, March.

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