IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v15y2018i4p710-d140398.html
   My bibliography  Save this article

Heavy Metal Pollution Delineation Based on Uncertainty in a Coastal Industrial City in the Yangtze River Delta, China

Author

Listed:
  • Bifeng Hu

    (Institute of Agricultural Remote Sensing and Information Technology Application, Zhejiang University, Hangzhou 310058, China
    Unité de Recherche en Science du Sol, INRA, Orléans 45075, France
    InfoSol, INRA, US 1106, Orléans F-4075, France
    Sciences de la Terre et de l’Univers, Orléans University, Orleans 45067, France)

  • Ruiying Zhao

    (Institute of Agricultural Remote Sensing and Information Technology Application, Zhejiang University, Hangzhou 310058, China)

  • Songchao Chen

    (InfoSol, INRA, US 1106, Orléans F-4075, France
    Unité Mixte de Rercherche (UMR) Sol Agro et hydrosystème Spatialisation (SAS), INRA, Agrocampus Ouest, Rennes 35042, France)

  • Yue Zhou

    (Institute of Agricultural Remote Sensing and Information Technology Application, Zhejiang University, Hangzhou 310058, China)

  • Bin Jin

    (Ningbo Agricultural Food Safety Management Station, Ningbo 315000, China)

  • Yan Li

    (Institute of Land Science and Property, School of Public Affairs, Zhejiang University, Hangzhou 310058, China)

  • Zhou Shi

    (Institute of Agricultural Remote Sensing and Information Technology Application, Zhejiang University, Hangzhou 310058, China)

Abstract

Assessing heavy metal pollution and delineating pollution are the bases for evaluating pollution and determining a cost-effective remediation plan. Most existing studies are based on the spatial distribution of pollutants but ignore related uncertainty. In this study, eight heavy-metal concentrations (Cr, Pb, Cd, Hg, Zn, Cu, Ni, and Zn) were collected at 1040 sampling sites in a coastal industrial city in the Yangtze River Delta, China. The single pollution index (PI) and Nemerow integrated pollution index (NIPI) were calculated for every surface sample (0–20 cm) to assess the degree of heavy metal pollution. Ordinary kriging (OK) was used to map the spatial distribution of heavy metals content and NIPI. Then, we delineated composite heavy metal contamination based on the uncertainty produced by indicator kriging (IK). The results showed that mean values of all PIs and NIPIs were at safe levels. Heavy metals were most accumulated in the central portion of the study area. Based on IK, the spatial probability of composite heavy metal pollution was computed. The probability of composite contamination in the central core urban area was highest. A probability of 0.6 was found as the optimum probability threshold to delineate polluted areas from unpolluted areas for integrative heavy metal contamination. Results of pollution delineation based on uncertainty showed the proportion of false negative error areas was 6.34%, while the proportion of false positive error areas was 0.86%. The accuracy of the classification was 92.80%. This indicated the method we developed is a valuable tool for delineating heavy metal pollution.

Suggested Citation

  • Bifeng Hu & Ruiying Zhao & Songchao Chen & Yue Zhou & Bin Jin & Yan Li & Zhou Shi, 2018. "Heavy Metal Pollution Delineation Based on Uncertainty in a Coastal Industrial City in the Yangtze River Delta, China," IJERPH, MDPI, vol. 15(4), pages 1-13, April.
    • Handle: RePEc:gam:jijerp:v:15:y:2018:i:4:p:710-:d:140398
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/15/4/710/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/15/4/710/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bifeng Hu & Songchao Chen & Jie Hu & Fang Xia & Junfeng Xu & Yan Li & Zhou Shi, 2017. "Application of portable XRF and VNIR sensors for rapid assessment of soil heavy metal pollution," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-13, February.
    2. Bifeng Hu & Xiaolin Jia & Jie Hu & Dongyun Xu & Fang Xia & Yan Li, 2017. "Assessment of Heavy Metal Pollution and Health Risks in the Soil-Plant-Human System in the Yangtze River Delta, China," IJERPH, MDPI, vol. 14(9), pages 1-18, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Feng Li & Mingtao Xiang & Shiying Yu & Fang Xia & Yan Li & Zhou Shi, 2022. "Source Identification and Apportionment of Potential Toxic Elements in Soils in an Eastern Industrial City, China," IJERPH, MDPI, vol. 19(10), pages 1-19, May.
    2. Sha Huang & Guofan Shao & Luyan Wang & Lin Wang & Lina Tang, 2018. "Distribution and Health Risk Assessment of Trace Metals in Soils in the Golden Triangle of Southern Fujian Province, China," IJERPH, MDPI, vol. 16(1), pages 1-17, December.
    3. Shudi Zuo & Shaoqing Dai & Yaying Li & Jianfeng Tang & Yin Ren, 2018. "Analysis of Heavy Metal Sources in the Soil of Riverbanks Across an Urbanization Gradient," IJERPH, MDPI, vol. 15(10), pages 1-23, October.
    4. Jorge Paz-Ferreiro & Gabriel Gascó & Ana Méndez & Suzie M. Reichman, 2018. "Soil Pollution and Remediation," IJERPH, MDPI, vol. 15(8), pages 1-3, August.
    5. Zhaolin Du & Dasong Lin & Haifeng Li & Yang Li & Hongan Chen & Weiqiang Dou & Li Qin & Yi An, 2022. "Bibliometric Analysis of the Influencing Factors, Derivation, and Application of Heavy Metal Thresholds in Soil," IJERPH, MDPI, vol. 19(11), pages 1-12, May.
    6. Fang Xia & Bifeng Hu & Shuai Shao & Dongyun Xu & Yue Zhou & Yin Zhou & Mingxiang Huang & Yan Li & Songchao Chen & Zhou Shi, 2019. "Improvement of Spatial Modeling of Cr, Pb, Cd, As and Ni in Soil Based on Portable X-ray Fluorescence (PXRF) and Geostatistics: A Case Study in East China," IJERPH, MDPI, vol. 16(15), pages 1-15, July.
    7. Hua Wang & Wuyan Li & Congmou Zhu & Xiaobo Tang, 2021. "Analysis of Heavy Metal Pollution in Cultivated Land of Different Quality Grades in Yangtze River Delta of China," IJERPH, MDPI, vol. 18(18), pages 1-17, September.
    8. Shuai Shao & Bifeng Hu & Zhiyi Fu & Jiayu Wang & Ge Lou & Yue Zhou & Bin Jin & Yan Li & Zhou Shi, 2018. "Source Identification and Apportionment of Trace Elements in Soils in the Yangtze River Delta, China," IJERPH, MDPI, vol. 15(6), pages 1-14, June.
    9. Zhiping Yang & Rong Zhang & Hongying Li & Xiaoyuan Zhao & Xiaojie Liu, 2022. "Heavy Metal Pollution and Soil Quality Assessment under Different Land Uses in the Red Soil Region, Southern China," IJERPH, MDPI, vol. 19(7), pages 1-15, March.

    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. Fengxu Li & Jiquan Zhang & Tiehua Cao & Sijia Li & Yanan Chen & Xuanhe Liang & Xin Zhao & Junwei Chen, 2018. "Human Health Risk Assessment of Toxic Elements in Farmland Topsoil with Source Identification in Jilin Province, China," IJERPH, MDPI, vol. 15(5), pages 1-15, May.
    2. Zhou Li & Hong Su & Li Wang & Danbiao Hu & Lijun Zhang & Jian Fang & Micong Jin & Samuel Selorm Fiati Kenston & Xin Song & Hongbo Shi & Jinshun Zhao & Guochuan Mao, 2018. "Epidemiological Study on Metal Pollution of Ningbo in China," IJERPH, MDPI, vol. 15(3), pages 1-14, February.
    3. Qiang Liu & Yan Cheng & Chunnan Fan, 2023. "Pollution Characteristics and Health Exposure Risks of Heavy Metals in River Water Affected by Human Activities," Sustainability, MDPI, vol. 15(10), pages 1-14, May.
    4. Shudi Zuo & Shaoqing Dai & Yaying Li & Jianfeng Tang & Yin Ren, 2018. "Analysis of Heavy Metal Sources in the Soil of Riverbanks Across an Urbanization Gradient," IJERPH, MDPI, vol. 15(10), pages 1-23, October.
    5. Yujie Pan & Hongxia Peng & Shuyun Xie & Min Zeng & Changsheng Huang, 2019. "Eight Elements in Soils from a Typical Light Industrial City, China: Spatial Distribution, Ecological Assessment, and the Source Apportionment," IJERPH, MDPI, vol. 16(14), pages 1-17, July.
    6. Bifeng Hu & Xiaolin Jia & Jie Hu & Dongyun Xu & Fang Xia & Yan Li, 2017. "Assessment of Heavy Metal Pollution and Health Risks in the Soil-Plant-Human System in the Yangtze River Delta, China," IJERPH, MDPI, vol. 14(9), pages 1-18, September.
    7. Xiaolin Jia & Yi Fang & Bifeng Hu & Baobao Yu & Yin Zhou, 2023. "Development of Soil Fertility Index Using Machine Learning and Visible-Near-Infrared Spectroscopy," Land, MDPI, vol. 12(12), pages 1-13, December.
    8. Shuai Shao & Bifeng Hu & Zhiyi Fu & Jiayu Wang & Ge Lou & Yue Zhou & Bin Jin & Yan Li & Zhou Shi, 2018. "Source Identification and Apportionment of Trace Elements in Soils in the Yangtze River Delta, China," IJERPH, MDPI, vol. 15(6), pages 1-14, June.
    9. Ioana Andreea Petrean & Valer Micle & Marin Șenilă, 2023. "Investigation of Sterile Mining Dumps Resulting from Ore Exploitation and Processing in Maramures County, Romania," Land, MDPI, vol. 12(2), pages 1-21, February.
    10. Modian Xie & Hongyi Li & Youwei Zhu & Jie Xue & Qihao You & Bin Jin & Zhou Shi, 2021. "Predicting Bioaccumulation of Potentially Toxic Element in Soil–Rice Systems Using Multi-Source Data and Machine Learning Methods: A Case Study of an Industrial City in Southeast China," Land, MDPI, vol. 10(6), pages 1-17, May.
    11. Ioana Andreea Petrean & Valer Micle & Ioana Monica Sur & Marin Șenilă, 2023. "Characterization of Sterile Mining Dumps by the ICP-OES Analytical Method: A Case Study from Baia Mare Mining Area (Maramures, Romania)," Sustainability, MDPI, vol. 15(2), pages 1-14, January.
    12. Fang Xia & Bifeng Hu & Shuai Shao & Dongyun Xu & Yue Zhou & Yin Zhou & Mingxiang Huang & Yan Li & Songchao Chen & Zhou Shi, 2019. "Improvement of Spatial Modeling of Cr, Pb, Cd, As and Ni in Soil Based on Portable X-ray Fluorescence (PXRF) and Geostatistics: A Case Study in East China," IJERPH, MDPI, vol. 16(15), pages 1-15, July.
    13. Yan Zha & Lin Zhao & Tianxin Niu & Erkui Yue & Xianbo Wang & Jiang Shi, 2023. "Multi-Target Element-Based Screening of Maize Varieties with Low Accumulation of Heavy Metals (HMs) and Metalloids: Uptake, Transport, and Health Risks," Agriculture, MDPI, vol. 13(6), pages 1-15, May.
    14. Mohammad Nishat Akhtar & Abdurrahman Javid Shaikh & Ambareen Khan & Habib Awais & Elmi Abu Bakar & Abdul Rahim Othman, 2021. "Smart Sensing with Edge Computing in Precision Agriculture for Soil Assessment and Heavy Metal Monitoring: A Review," Agriculture, MDPI, vol. 11(6), pages 1-37, May.

    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:15:y:2018:i:4:p:710-:d:140398. 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.