摘要
离散检测数据的重金属生态风险评估往往受采样数据空间覆盖度有限、检测数据随机波动等问题影响,使评价结果具有较大的不确定性.相对而言,基于地方区域的重金属概率统计以概率的形式解释污染等级的占比,能更有效指导风控方案的制定、污染的修复和场地的管控.本文应用Monte-Carlo模拟结合Hakanson潜在生态风险指数法,对云南省内某小流域土壤中的8种重金属(Cd、Hg、As、Pb、Cr、Cu、Ni和Zn)展开调查,分别从单种金属的污染等级、风险等级,以及整个区域的生态风险三个维度阐述当地的污染状况,系统性评估了当地的生态风险.研究表明Cd是主要污染贡献因子,其生态风险应引起重点关注.本研究证实了Monte-Carlo模拟可有效平衡Hakanson潜在生态风险指数法的随机性,将二者结合可更加全面精确地反映重金属的生态风险.
The ecological risk assessment of heavy metals is often hindered by the limited spatial coverage of the sampling area and fluctuation of the detection data,which resulted in high uncertainty of the evaluation results.The analysis on the statistical characteristics of heavy metal distribution will enable a determination of pollution levels based on probability,which can guide the establishment of effective strategies for risk control,pollution remediation,and site management.In this study,the Monte-Carlo simulation combined with the Hakanson potential ecological risk index method was used to investigate the distributions and risks of heavy metals(Cd,Hg,As,Pb,Cr,Cu,Ni,and Zn)in the soil of a small watershed in Yunnan Province.The results illustrated the pollution and risk levels of individual metals as well as the entire region,and thus the locally ecological risk was systematically assessed.The results showed that Cd is the main pollution contributor and its ecological risk should be concerned in priority.This study confirmed that the Monte-Carlo simulation can effectively reduce the uncertainty of the Hakanson Potential Hazard Index method.The combination of these two methods can comprehensively and accurately describe the ecological risk of heavy metals.
作者
陈莹
吴敏
陈全
牛学奎
和丽萍
王静
王斌
潘波
CHEN Ying;WU Min;CHEN Quan;NIU Xuekui;HE Liping;WANG Jing;WANG Bin;PAN Bo(Yunnan Provincial Key Lab of Soil Carbon Sequestration and Pollution Control,Faculty of Environmental Science and Engineering,Kunming University of Science and Technology,Kunming,650500,China;Yunnan Research Academy of Ecoenvironmental Sciences,Kunming,650034,China;School of Public Health,Peking University,Beijing,100191,China)
出处
《环境化学》
CAS
CSCD
北大核心
2023年第10期3359-3367,共9页
Environmental Chemistry
基金
国家自然科学基金(41977334)
国家自然科学基金中波国际合作项目(41961134002)
云南省土壤科学与生态安全创新团队项目(2019HC008)资助.