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作 者:Bin Shi Jing Meng TieyuWang Qianqian Li Qifan Zhang Guijin Su
机构地区:[1]Research Center for Eco-Environmental Sciences,Chinese Academy of Sciences,Beijing 100085,China [2]University of Chinese Academy of Sciences,Beijing 100049,China [3]Guangdong Provincial Key Laboratory of Marine Disaster Prediction and Prevention,Shantou University,Shantou 515063,China
出 处:《Journal of Environmental Sciences》2024年第2期95-109,共15页环境科学学报(英文版)
基 金:supported by the National Key R&D Program of China (No.2018YFC1800300);the National Natural Science Foundation of China (Nos.41877509 and 41807493)。
摘 要:Nowadays,a large number of compounds with different physical and chemical properties have been determined in soil.Environmental behaviors and source identification of pollutants in soil are the foundation of soil pollution control.Identification and quantitative analysis of potential pollution sources are the prerequisites for its prevention and control.Many efforts have made to develop methods for identifying the sources of soil pollutants.These efforts have involved the measurement of source and receptor parameters and the analysis of their relationships via numerical statistics methods.We have comprehensively reviewed the progress made in the development of source apportionment methodologies to date and present our synthesis.The numerical methods,such as spatial geostatistics analysis,receptor models,and machine learning methods are addressed in depth.In most cases,however,the effectiveness of any single approach for source apportionment remains limited.Combining multiple methods to address soil quality problems can reduce uncertainty about the sources of soil pollution.This review also constructively highlights the key strategies of combining mathematical models with the assessment of chemical profiles to provide more accurate source attribution.This review intends to provide a comprehensive summary of source apportionment methodologies to help promote further development.
关 键 词:Soil pollutants Source attribution METHODOLOGIES Chemical profiles Mathematical models
分 类 号:X53[环境科学与工程—环境工程]
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