IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v15y2018i6p1240-d151976.html
   My bibliography  Save this article

Source Identification and Apportionment of Trace Elements in Soils in the Yangtze River Delta, China

Author

Listed:
  • Shuai Shao

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

  • Bifeng Hu

    (Science du Sol, INRA, 45075 Orléans, France
    Unité InfoSol, INRA, US 1106, 45075 Orléans, France
    Sciences de la Terre et de lthe’Univers, Orléans University, 45067 Orleans, France)

  • Zhiyi Fu

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

  • Jiayu Wang

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

  • Ge Lou

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

  • Yue Zhou

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

Abstract

Trace elements pollution has attracted a lot of attention worldwide. However, it is difficult to identify and apportion the sources of multiple element pollutants over large areas because of the considerable spatial complexity and variability in the distribution of trace elements in soil. In this study, we collected total of 2051 topsoil (0–20 cm) samples, and analyzed the general pollution status of soils from the Yangtze River Delta, Southeast China. We applied principal component analysis (PCA), a finite mixture distribution model (FMDM), and geostatistical tools to identify and quantitatively apportion the sources of seven kinds of trace elements (chromium (Cr), cadmium (Cd), mercury (Hg), copper (Cu), zinc (Zn), nickel (Ni), and arsenic (As)) in soil. The PCA results indicated that the trace elements in soil in the study area were mainly from natural, multi-pollutant and industrial sources. The FMDM also fitted three sub log-normal distributions. The results from the two models were quite similar: Cr, As, and Ni were mainly from natural sources caused by parent material weathering; Cd, Cu, and Zu were mainly from mixed sources, with a considerable portion from anthropogenic activities such as traffic pollutants, domestic garbage, and agricultural inputs, and Hg was mainly from industrial wastes and pollutants.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jijerp:v:15:y:2018:i:6:p:1240-:d:151976
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/15/6/1240/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/15/6/1240/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Chris Fraley & Adrian E. Raftery, 2003. "Enhanced Model-Based Clustering, Density Estimation, and Discriminant Analysis Software: MCLUST," Journal of Classification, Springer;The Classification Society, vol. 20(2), pages 263-286, September.
    3. 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.
    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. 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.
    2. Mark S. Handcock & Adrian E. Raftery & Jeremy M. Tantrum, 2007. "Model‐based clustering for social networks," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(2), pages 301-354, March.
    3. repec:jss:jstsof:14:i12 is not listed on IDEAS
    4. Maugis, C. & Celeux, G. & Martin-Magniette, M.-L., 2011. "Variable selection in model-based discriminant analysis," Journal of Multivariate Analysis, Elsevier, vol. 102(10), pages 1374-1387, November.
    5. Cathy Maugis & Gilles Celeux & Marie-Laure Martin-Magniette, 2009. "Variable Selection for Clustering with Gaussian Mixture Models," Biometrics, The International Biometric Society, vol. 65(3), pages 701-709, September.
    6. Jeffrey Andrews & Paul McNicholas, 2014. "Variable Selection for Clustering and Classification," Journal of Classification, Springer;The Classification Society, vol. 31(2), pages 136-153, July.
    7. repec:jss:jstsof:18:i06 is not listed on IDEAS
    8. Zhang, Ping & Serban, Nicoleta, 2007. "Discovery, visualization and performance analysis of enterprise workflow," Computational Statistics & Data Analysis, Elsevier, vol. 51(5), pages 2670-2687, February.
    9. Hennig, Christian, 2008. "Dissolution point and isolation robustness: Robustness criteria for general cluster analysis methods," Journal of Multivariate Analysis, Elsevier, vol. 99(6), pages 1154-1176, July.
    10. 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.
    11. Hornik, Kurt, 2005. "A CLUE for CLUster Ensembles," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 14(i12).
    12. Salter-Townshend, Michael & Murphy, Thomas Brendan, 2013. "Variational Bayesian inference for the Latent Position Cluster Model for network data," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 661-671.
    13. 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.
    14. McNicholas, P.D. & Murphy, T.B. & McDaid, A.F. & Frost, D., 2010. "Serial and parallel implementations of model-based clustering via parsimonious Gaussian mixture models," Computational Statistics & Data Analysis, Elsevier, vol. 54(3), pages 711-723, March.
    15. Christian Hennig, 2010. "Methods for merging Gaussian mixture components," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 4(1), pages 3-34, April.
    16. 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.
    17. Jorge Paz-Ferreiro & Gabriel Gascó & Ana Méndez & Suzie M. Reichman, 2018. "Soil Pollution and Remediation," IJERPH, MDPI, vol. 15(8), pages 1-3, August.
    18. Hien D. Nguyen & Geoffrey J. McLachlan & Jeremy F. P. Ullmann & Andrew L. Janke, 2016. "Spatial clustering of time series via mixture of autoregressions models and Markov random fields," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(4), pages 414-439, November.
    19. Crowley, Patrick M., 2008. "One money, several cycles? : evaluation of European business cycles using model-based cluster analysis," Research Discussion Papers 3/2008, Bank of Finland.
    20. 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.
    21. 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.
    22. Alex Sharp & Glen Chalatov & Ryan P. Browne, 2023. "A dual subspace parsimonious mixture of matrix normal distributions," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 17(3), pages 801-822, September.

    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:6:p:1240-:d:151976. 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.