A study of surface water quality using organic pollution indices: Comparative characteristics and educational opportunities
Olha Biedunkova, Павло Кузнєцов, Vasyl Korbutiak
Abstract
ABSTRACT This study sets out to examine a variety of approaches to the assessment of organic pollution, and to consider the potential application of the results in the educational process of students specializing in the environment. Water samples from the Styr River were collected and analyzed for physicochemical parameters such as nitrogen, phosphorus, carbon components, and dissolved oxygen from 2018 to 2022. Four equations were used to calculate the Organic Pollution Index (OPI). Statistical analyses included Pearson correlation, multiple linear regression, principal component analysis (PCA), and network analysis (NA). Results indicated variations in OPI levels depending on the methodology, with pollution classifications ranging from ‘pure’ to ‘moderate’. Seasonal trends were observed, with higher pollution levels in summer and lower levels in winter. PCA and NA identified key variables contributing to pollution. Some methods showed stable OPI levels, while others exhibited periodic fluctuations. This study provides a comprehensive comparison of OPI calculation methods and integrates statistical techniques for river water quality assessment. It offers a valuable framework for environmental education, enhancing students' understanding of water quality assessment, data analysis, and statistical applications in environmental science.