The main strategies for soil pollution apportionment: A review of the numerical methods
Guijin Su , Bin Shi , Jing Meng , Tieyu Wang , Qianqian Li , Qifan Zhang
DOI:10.1016/j.jes.2022.09.027
Received June 25, 2022,Revised , Accepted September 19, 2022, Available online September 25, 2022
Volume 36,2024,Pages 95-109
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.
