IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2020i18p6735-d414161.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/18/6735/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/17/18/6735/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Li Ji & Wenwen Li & Yuan Li & Qiusheng He & Yonghong Bi & Minghua Zhang & Guixiang Zhang & Xinming Wang, 2022. "Spatial Distribution, Potential Sources, and Health Risk of Polycyclic Aromatic Hydrocarbons (PAHs) in the Surface Soils under Different Land-Use Covers of Shanxi Province, North China," IJERPH, MDPI, vol. 19(19), pages 1-14, September.
    2. Chen, Yanguang, 2023. "Demonstration of duality of fractal gravity models by scaling symmetry," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    3. Tranos, Emmanouil & Incera, Andre Carrascal & Willis, George, 2022. "Using the web to predict regional trade flows: data extraction, modelling, and validation," OSF Preprints 9bu5z, Center for Open Science.
    4. Huang, Feihu & Qiao, Shaojie & Peng, Jian & Guo, Bing & Xiong, Xi & Han, Nan, 2019. "A movement model for air passengers based on trip purpose," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 798-808.
    5. Haihua Jiao & Xiaoping Rui & Shanghua Wu & Zhihui Bai & Xuliang Zhuang & Zhanbin Huang, 2015. "Polycyclic Aromatic Hydrocarbons in the Dagang Oilfield (China): Distribution, Sources, and Risk Assessment," IJERPH, MDPI, vol. 12(6), pages 1-17, May.
    6. Varga, Levente & Tóth, Géza & Néda, Zoltán, 2017. "An improved radiation model and its applicability for understanding commuting patterns in Hungary," MPRA Paper 76806, University Library of Munich, Germany.
    7. Sgrignoli, Paolo & Metulini, Rodolfo & Schiavo, Stefano & Riccaboni, Massimo, 2015. "The relation between global migration and trade networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 417(C), pages 245-260.
    8. Chaocan Li & Xiaopeng Zhang & Xuqin Wang & Xinbo Zhang & Shigang Liu & Ting Yuan & Weigui Qu & Youjun Zhang, 2022. "Distribution Characteristics and Potential Risks of Polycyclic Aromatic Hydrocarbon (PAH) Pollution at a Typical Industrial Legacy Site in Tianjin, North China," Land, MDPI, vol. 11(10), pages 1-16, October.
    9. James Truscott & Neil M Ferguson, 2012. "Evaluating the Adequacy of Gravity Models as a Description of Human Mobility for Epidemic Modelling," PLOS Computational Biology, Public Library of Science, vol. 8(10), pages 1-12, October.
    10. Chen, Yong & Geng, Maosi & Zeng, Jiaqi & Yang, Di & Zhang, Lei & Chen, Xiqun (Michael), 2023. "A novel ensemble model with conditional intervening opportunities for ride-hailing travel mobility estimation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 628(C).
    11. Chaogui Kang & Yu Liu & Diansheng Guo & Kun Qin, 2015. "A Generalized Radiation Model for Human Mobility: Spatial Scale, Searching Direction and Trip Constraint," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-11, November.
    12. Luo, Xiaohu & Caron, Justin & Karplus, Valerie J. & Zhang, Da & Zhang, Xiliang, 2016. "Interprovincial migration and the stringency of energy policy in China," Energy Economics, Elsevier, vol. 58(C), pages 164-173.
    13. Mark Thissen & Olga Ivanova & Giovanni Mandras & Trond Husby, 2019. "European NUTS 2 regions: construction of interregional trade-linked Supply and Use tables with consistent transport flows," JRC Working Papers on Territorial Modelling and Analysis 2019-01, Joint Research Centre.
    14. Thompson, C.A. & Saxberg, K. & Lega, J. & Tong, D. & Brown, H.E., 2019. "A cumulative gravity model for inter-urban spatial interaction at different scales," Journal of Transport Geography, Elsevier, vol. 79(C), pages 1-1.
    15. Gonzalo Suarez & Rachata Muneepeerakul, 2022. "Modeling human migration driven by changing mindset, agglomeration, social ties, and the environment," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-11, February.
    16. Rosita De Vincentis & Federico Karagulian & Carlo Liberto & Marialisa Nigro & Vincenza Rosati & Gaetano Valenti, 2022. "A Data-Driven Approach to Analyze Mobility Patterns and the Built Environment: Evidence from Brescia, Catania, and Salerno (Italy)," Sustainability, MDPI, vol. 14(21), pages 1-14, November.
    17. Vinyas Harish & Felipe J. Colón-González & Filipe R. R. Moreira & Rory Gibb & Moritz U. G. Kraemer & Megan Davis & Robert C. Reiner & David M. Pigott & T. Alex Perkins & Daniel J. Weiss & Isaac I. Bog, 2024. "Human movement and environmental barriers shape the emergence of dengue," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    18. Animesh Gain & Vahid Mojtahed & Claudio Biscaro & Stefano Balbi & Carlo Giupponi, 2015. "An integrated approach of flood risk assessment in the eastern part of Dhaka City," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 79(3), pages 1499-1530, December.
    19. Wang, Wenjun & Pan, Lin & Yuan, Ning & Zhang, Sen & Liu, Dong, 2015. "A comparative analysis of intra-city human mobility by taxi," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 420(C), pages 134-147.
    20. Aike Steentoft & Bu-Sung Lee & Markus Schläpfer, 2024. "Quantifying the uncertainty of mobility flow predictions using Gaussian processes," Transportation, Springer, vol. 51(6), pages 2301-2322, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:17:y:2020:i:18:p:6735-:d:414161. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.