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

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 ess...

Full description

Saved in:
Bibliographic Details
Main Authors: Yalda Hashempour (Author), Atefeh Jabari (Author), kosar kouhi (Author), Afsaneh Fendereski (Author)
Format: Book
Published: Mazandaran University of Medical Sciences, 2024-01-01T00:00:00Z.
Subjects:
Online Access:Connect to this object online.
Tags: Add Tag
No Tags, Be the first to tag this record!

MARC

LEADER 00000 am a22000003u 4500
001 doaj_6b582e06fc854c8eab93c4f86fbb120c
042 |a dc 
100 1 0 |a Yalda Hashempour  |e author 
700 1 0 |a Atefeh Jabari  |e author 
700 1 0 |a kosar kouhi  |e author 
700 1 0 |a Afsaneh Fendereski  |e author 
245 0 0 |a Introducing Statistical Methods to Identify the Sources of Microplastics in the Aquatic Environment: An Overview 
260 |b Mazandaran University of Medical Sciences,   |c 2024-01-01T00:00:00Z. 
500 |a 2423-6772 
500 |a 2423-6764 
520 |a 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. 
546 |a FA 
690 |a microplastics 
690 |a multivariate statistical analysis 
690 |a source 
690 |a water resources 
690 |a Medicine 
690 |a R 
690 |a Public aspects of medicine 
690 |a RA1-1270 
655 7 |a article  |2 local 
786 0 |n تحقیقات سلامت در جامعه, Vol 9, Iss 4, Pp 111-120 (2024) 
787 0 |n http://jhc.mazums.ac.ir/article-1-923-en.pdf 
787 0 |n https://doaj.org/toc/2423-6772 
787 0 |n https://doaj.org/toc/2423-6764 
856 4 1 |u https://doaj.org/article/6b582e06fc854c8eab93c4f86fbb120c  |z Connect to this object online.