基于“源-径-汇”关系的土壤重金属污染风险空间区划研究

构建土壤污染风险管控空间区划体系是对《中华人民共和国土壤污染防治法》“分类分区分阶段管理”思想的深入落实，高分辨率的风险空间区划地图能为划分风险管控优先区和大尺度统筹部署土壤污染防治铺排工作提供科学有效的决策指导。利用正定矩阵因子分析模型（PMF）源解析模型明确了浙江省宁波市某工业集聚区铬、铜、砷、镉、铅、镍、锑和汞等8种重金属的污染源和贡献率，然后基于“源-径-汇”关系和质量平衡理论形成土壤重金属污染风险管控空间区划技术体系。结果表明，土壤重金属的空间分布具有明显异质性，主要排放源包括火力发电燃煤燃烧源（17.08%）、其他工业源（17.94%）、农业活动排放源（26.07%）、自然源（28.61%）和交通排放源（10.31%）等五类；利用构建的空间区划技术体系可将土壤重金属污染风险划分为极高、高、中、低和极低共五个等级，分别占研究区总面积的8.64%、17.28%、18.27%、22.92%和32.89%。区域风险胁迫水平的空间量化表达能有效识别高风险热点，进而采取优先管控措施实现土壤污染精准防治。

Source-Route-Receptor-Based Spatial Zoning Study on Soil Heavy Metals Pollution Risk

【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.