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Mapping the Finer-Scale Carcinogenic Risk of Polycyclic Aromatic Hydrocarbons (PAHs) in Urban Soil—A Case Study of Shenzhen City, China

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  • Dongxiang Chen

    (Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Land and Resources, Shenzhen 510034, China
    School of Business Administration, Zhejiang University of Finance & Economics Dongfang College, Haining 314408, China)

  • Han Zhao

    (Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Land and Resources, Shenzhen 510034, China)

  • Jun Zhao

    (Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Land and Resources, Shenzhen 510034, China)

  • Zhenci Xu

    (Department of Geography, University of Hong Kong, Hong Kong 999077, China)

  • Shaohua Wu

    (Institute of Land and Urban-rural Development, Zhejiang University of Finance & Economics, Hangzhou 310018, China)

Abstract

The high-precision mapping of urban health risk is a difficult problem due to the high heterogeneity of the urban environment. In this paper, the spatial distribution characteristics of the Polycyclic Aromatic Hydrocarbon (PAH) content in the urban soil of Shenzhen City were analyzed through a field investigation. We propose an approach for improving the accuracy and spatial resolution of PAH carcinogenic risk assessment by integrating the pollutant distribution and Location Based Service (LBS) data. The results showed that the concentration of PAHs in the high-density urban area was 271.67 ng g −1 , which was 27.2% higher than that in the green area. Although the average carcinogenic risk of PAHs in the surface soil of Shenzhen city was less than 10 −6 , the maximum carcinogenic risk at some sample sites exceeded 10 −6 , which indicates a potential health risk. The LBS data were effective for high-precision mapping of the population distribution. According to the combination relationship between the risk threshold of pollutants and the population density, four types of risk zones were proposed. Among them, 6.9% of the areas had a high-risk and high population density and 15.8% of the areas were high-risk with a low population density. These two kinds of zones were the critical areas for controlling risk. The fine-scale risk mapping approach for determining the carcinogenic risk of soil PAHs integrating pollutant distribution and location based service data was demonstrated to be a useful tool for explicit spatial risk management. This tool could provide spatial insights and decision support for urban health-risk management and pollution prevention.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jijerp:v:17:y:2020:i:18:p:6735-:d:414161
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    References listed on IDEAS

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    1. Yihua Xiao & Fuchun Tong & Yuanwen Kuang & Bufeng Chen, 2014. "Distribution and Source Apportionment of Polycyclic Aromatic Hydrocarbons (PAHs) in Forest Soils from Urban to Rural Areas in the Pearl River Delta of Southern China," IJERPH, MDPI, vol. 11(3), pages 1-15, March.
    2. Tekleweini Gereslassie & Ababo Workineh & Xiaoning Liu & Xue Yan & Jun Wang, 2018. "Occurrence and Ecological and Human Health Risk Assessment of Polycyclic Aromatic Hydrocarbons in Soils from Wuhan, Central China," IJERPH, MDPI, vol. 15(12), pages 1-19, December.
    3. 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.
    4. Wei Cao & Liqin Yin & Dan Zhang & Yingying Wang & Jing Yuan & Yi Zhu & Junfeng Dou, 2019. "Contamination, Sources, and Health Risks Associated with Soil PAHs in Rebuilt Land from a Coking Plant, Beijing, China," IJERPH, MDPI, vol. 16(4), pages 1-16, February.
    5. Di Wang & Shilei Zhu & Lijing Wang & Qing Zhen & Fengpeng Han & Xingchang Zhang, 2020. "Distribution, Origins and Hazardous Effects of Polycyclic Aromatic Hydrocarbons in Topsoil Surrounding Oil Fields: A Case Study on the Loess Plateau, China," IJERPH, MDPI, vol. 17(4), pages 1-14, February.
    6. Filippo Simini & Marta C. González & Amos Maritan & Albert-László Barabási, 2012. "A universal model for mobility and migration patterns," Nature, Nature, vol. 484(7392), pages 96-100, April.
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