Application of Positive Matrix Factorization (PMF) and Multivariate Statistical Techniques in Identifying and Managing Sources of Heavy Metal Pollutants in Sediments

Understanding and identifying various sources of water pollution and the processes affecting them are essential for achieving a comprehensive description of the quality of essential water resources. To this end, implementing a suitable network for monitoring water quality is crucial. Therefore, this study aims to examine the effectiveness of the Positive Matrix Factorization (PMF) model compared to multivariate statistical techniques. Additionally, the combined application of the PMF model with these methods in determining the contribution and management of heavy metal pollutants in aquatic sediments is investigated. Multivariate statistical analysis methods have proven effective in preparing and interpreting data on the quality of aquatic environments and determining the information available in them. However, they have some limitations. Thus, in this research, the application of Positive Matrix Factorization for sediment quality data, especially concerning heavy metals, is compared with multivariate statistical methods. The study also evaluates the status and extent of using this model in various environmental studies worldwide in recent years. Positive Matrix Factorization allows considering uncertain data and provides a positive constraint, leading to an environmentally interpretable result. The results of examining the applications of the PMF model in determining the contribution of various pollutants, including heavy metals, in different environmental sectors over the past two decades, indicate a significant increase in its usage in recent years compared to the past. Recent study results suggest that while Positive Matrix Factorization leads to a stronger understanding of the sources of pollution in the studied system compared to multivariate statistical methods, the combined application of the PMF model with other multivariate statistical methods for determining pollutant sources results in a more accurate and comprehensive analysis of pollutants, including heavy metals.

کلیدواژه ها:

Heavy metal pollutants ، Source apportionment ، Ecosystem management ، Positive Matrix Factorization (PMF) ، Multivariate statistical techniques