Source-Route-Receptor-Based Spatial Zoning Study on Soil Heavy Metals Pollution Risk
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Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences

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Supported by the National Key R&D Program of China (Nos. 2020YFC1807500 and 2021YFC1809103), and the National Natural Science Foundation of China (Nos. 72104231 and 41977146)

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    Abstract:

    【Objective】The establishment of a spatial zoning system of soil pollution risk management indicates the concrete implementation of “classification, division and phased soil environmental management” claimed in Soil Pollution Prevention and Control Law. The high-resolution risk spatial mapping can undoubtedly provide scientific and effective decision-making guidance not only for delineating prior areas for soil pollution risk management but also for facilitating the overall deployment of soil pollution prevention and control works at a large scale.【Method】This study first adopted positive matrix factorization (PMF) model to identify emission sources and the corresponding contribution rate of Cr, Cu, As, Cd, Pb, Ni, Sb and Hg in an industrial agglomeration area in Ningbo City, Zhejiang Province. Then, a spatial zoning technical system for risk management on soil heavy metals pollution was developed based on the source-route-receptor relationship and mass balance theory.【Result】The results showed that: (1) the spatial distribution of soil heavy metals presented a significant heterogeneity and five factors were primarily determined as the emission sources of soil heavy metals including coal-fired power generation source (17.08%), other industrial sources (17.94%), natural source (28.61%), agricultural source (26.07%), and traffic source (10.31%); (2) five risk levels were clustered using the established spatial zoning technical system, including extremely high-, high-, medium-, low- and extremely low-risk accounting for 8.64%, 17.28%, 18.27%, 22.92%, and 32.89% of the total area, respectively. 【Conclusion】The quantification of the regional risk stress levels can effectively map high-risk hotspots to apply prior measures for precise soil pollution management.

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History
  • Received:March 22,2023
  • Revised:June 20,2023
  • Adopted:September 18,2023
  • Online: September 19,2023
  • Published: