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基于环境容量的县域农用地土壤重金属风险概率预警研究
引用本文:吕悦风,谢丽,朱文娟,周宇,孙华. 基于环境容量的县域农用地土壤重金属风险概率预警研究[J]. 长江流域资源与环境, 2020, 29(1): 253-264. DOI: 10.11870/cjlyzyyhj202001023
作者姓名:吕悦风  谢丽  朱文娟  周宇  孙华
作者单位:(1.南京农业大学公共管理学院,江苏 南京 210095; 2.浙江大学公共管理学院, 浙江 杭州 310058)
摘    要:《土壤污染防治法》的正式出台,标志着我国土壤污染防治工作由"现状治理"转向"风险预防",为此开展区域土壤重金属风险预警研究具有一定的理论与现实意义。以太湖沿岸某产粮县为研究对象,以2015年为基准年,运用重金属输入-输出通量模型和土壤环境负载容量法对研究区耕地土壤中的As、Hg、Cr、Cd、Pb 5种重金属15年(2030年)与35年(2050年)后的风险概率进行预警研究。研究结果表明:大气干湿沉降成为除As以外其他4种土壤重金属的主要来源,畜禽粪便、化肥投入与灌溉水也会在一定程度上影响土壤重金属输入;此外,研究区耕层土壤中As、Cr、Pb 3种重金属整体情况较为良好,Hg、Cd污染风险概率较高,主要分布在研究区中部的O镇、P镇。通过GIS技术与区域物质流通量模型的结合能够很好地对不同区域以及不同重金属污染类型的区域进行风险预警,这可以为土壤污染差别化管控策略的制定提供重要思路。


Risk Prediction of Heavy Metals in Farmland Soil Based on Environmental Capacity: Case Study of the County Scale in Northern Zhejiang Province
LV Yue-feng,XIE Li,ZHU Wen-juan,ZHOU Yu,SUN Hua. Risk Prediction of Heavy Metals in Farmland Soil Based on Environmental Capacity: Case Study of the County Scale in Northern Zhejiang Province[J]. Resources and Environment in the Yangtza Basin, 2020, 29(1): 253-264. DOI: 10.11870/cjlyzyyhj202001023
Authors:LV Yue-feng  XIE Li  ZHU Wen-juan  ZHOU Yu  SUN Hua
Affiliation:(1.College of Public Administration,Nanjing Agricultural University,Nanjing 210095, China;2. College of Public Administration,Zhejiang University,Hangzhou 310085,China);
Abstract:The formal promulgation of“the Law on the Prevention and Control of Soil Pollution”marks that the target of prevention soil pollution in China has changed from "current situation control" to “risk early-warning”. Therefore, it is of theoretical and practical significance to carry out regional soil heavy metal risk warning research. Based on the soil survey data of a grain-producing county along the coast of Taihu Lake in 2015, this study use heavy metal input-output flux model and soil environmental capacity method to calculate the risk probability of five heavy metals in 2030 (15 years later) and 2050 (35 years later). The results show that atmospheric dry and wet deposition becomes the main source of four heavy metals apart from As. Livestock manure, fertilizer input and irrigation water will also affect soil heavy metal input to some extent. In addition, the three heavy metals of As, Cr and Pb in the cultivated soil of the study area are relatively good, and the risk of Hg and Cd pollution is slightly high, mainly distributed in O town and town P in the middle of the study area. The combination of GIS technology and regional material flow model can provide a good risk warning for different regions and different heavy metal pollution types, which can provide important ideas for the formulation of soil pollution differentiation management strategy.
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