Introducing Statistical Methods to Identify the Sources of Microplastics in the Aquatic Environment: An Overview

Abstract

Introduction and purpose: Despite recent efforts to identify microplastics in the aquatic environment worldwide, identifying the various sources of its release remains a challenging task. Understanding and identifying the different sources of aquatic pollution and the processes affecting them is essential for a comprehensive description of the quality of water resources. The aim of this study is therefore to introduce statistical methods to determine the sources of microplastics in aquatic environments. Methods: This review article first identifies the pathways of microplastic entry into the aquatic environment, followed by an examination of four commonly used multivariate statistical methods: Principal Component Analysis (PCA), Cluster Analysis (CA), Hierarchical Cluster Analysis (HCA) and Positive Matrix Factorization (PMF). Results: Multivariate statistical analysis can be used to determine different variables such as size, shape, color, and density of microplastics. It can also determine the sources of microplastics (domestic wastewater, industrial effluents, agricultural activities, surface runoff, air currents, etc.). It also identifies which variables have the greatest impact on pollution and suggests the best solutions to reduce pollution. Conclusion: the study of pollution based on multivariate statistical analysis can provide important information on the main sources of microplastic pollution and the relative contribution of different sources in the aquatic environment, which can help to improve environmental management and reduce pollution.

Keywords

• microplastics
• multivariate statistical analysis
• source
• water resources