Dataset on heavy metal pollution assessment in freshwater ecosystems.

Abstract

Water quality degradation due to heavy metal contamination poses serious threats to both human health and aquatic ecosystems. The rise in the concentration of heavy metals in aquatic environments is largely attributable to anthropogenic activities. These metals accumulate over time in water bodies, necessitating rigorous monitoring to accurately assess pollution levels. The present study is concerned with the assessment of heavy metal pollution in the Styr River (Ukraine) before and after the discharge of water from a nuclear power plant. The assessment is based on three indices: the Heavy Metal Pollution Index, the Heavy Metal Evaluation Index, and the Degree of Contamination. Therefore, heavy metals, including zinc (Zn), cadmium (Cd), lead (Pb), copper (Cu), nickel (Ni), manganese (Mn), arsenic (As) and chromium (Cr), were analyzed in this study. Water samples were collected at two locations on a monthly basis over the course of five years (2018-2022) and subsequently analysed using inductively coupled plasma optical emission spectroscopy. The results indicates a low contamination level at both sampling sites, indicating stable and uniform concentrations of metals across the study area. Moreover, statistical analysis highlights significant associations between certain metals and pollution indices, supporting the indices' utility in tracking pollution trends and assessing environmental impacts. This dataset underscores the importance of ongoing monitoring for effective water quality management.