The contamination of rivers by heavy metals is a pressing environmental issue caused by industrial, agricultural, and urban activities. In our latest study, we investigated the Styr River in north-western Ukraine, focusing on the potential impact of discharges from the Nuclear Power Plant, a facility that uses significant water volumes for cooling and subsequently discharges treated water back into the river.

Using a four-year dataset, we measured concentrations of eight heavy metals, including zinc, cadmium, and lead, at two locations: upstream and downstream of the discharge point. This dataset, publicly accessible for further research and analysis, includes raw concentrations of heavy metals, calculated pollution indices, and statistical correlations.

This study aims to assess HM pollution levels in the Styr River by employing three indices—Heavy Metal Pollution Index (HPI), Heavy Metal Evaluation Index (HEI), and Degree of Contamination (DC). Water samples were collected from two strategic locations along the Styr River: upstream (S1) and downstream (S2) of the Rivne NPP discharge point. Sampling occurred monthly from 2018 to 2022, following standardized protocols to ensure consistency.  Heavy metals (HM), including Zn, Cd, Pb, Cu, Ni, Mn, As, and Cr, were quantified using Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES). Qual

The contamination of rivers by heavy metals is a pressing environmental issue caused by industrial, agricultural, and urban activities. In our latest study, we investigated the Styr River in north-western Ukraine, focusing on the potential impact of discharges from the Nuclear Power Plant, a facility that uses significant water volumes for cooling and subsequently discharges treated water back into the river. ity assurance involved calibration with standard solutions and compliance with laboratory standards. Statistical metrics, such as mean, standard deviation, and Pearson correlation, were calculated using JASP software (v0.14.3). 

HM concentrations at both S1 and S2 were consistent across the study period. Zn, Cu, and As exhibited the highest mean concentrations, while Cd and Cr showed the lowest. Statistical analysis revealed minor differences between upstream and downstream sites, indicating limited influence from the NPP discharge.  The study demonstrates that the Rivne NPP has a negligible impact on HM contamination in the Styr River. Despite industrial activities, HM concentrations remain stable, likely due to effective dilution and low discharge volumes. The consistent classification of both sites as exhibiting low pollution levels underscores the utility of the applied indices in capturing spatial and temporal variations. While HMs such as Zn and Cu are moderately correlated with pollution indices, their concentrations remain well below regulatory thresholds, minimizing ecological and health risks. The use of multiple indices provides a comprehensive framework for understanding HM dynamics, offering a robust model for assessing pollution in industrially influenced water bodies. 

Pollution indices corroborated these findings:

• HPI ranged from 0.54 to 0.85 across sites, indicating low pollution levels.
• HEI values consistently fell below the threshold for medium pollution, reflecting minimal contamination.
• DC results confirmed low contamination levels, with slight variability downstream.

Moderate positive correlations were observed between certain HMs (e.g., Zn, Pb, Mn) and indices, suggesting their significant contribution to pollution metrics.

This study provides critical insights into HM pollution in the Styr River, demonstrating minimal environmental impact from the Rivne NPP. The integration of HPI, HEI, and DC indices facilitates a detailed assessment of contamination levels and trends. Findings suggest that current monitoring and discharge management practices effectively mitigate pollution risks. The Styr River’s resilience to current industrial pressures, including discharges from the nuclear power plant, underscores the importance of effective water management practices. However, continuous monitoring is essential to ensure that the ecosystem remains protected. The dataset accompanying this study provides a robust foundation for future research, enabling scientists to analyze pollution patterns and apply these findings to other freshwater ecosystems.

The meticulous methodology employed ensures that findings are not only scientifically robust but also practically applicable. This dual focus enhances the study’s relevance to both academic audiences and the broader community reliant on the river’s health. Behind the scenes, the research reflects a commitment to addressing local concerns through science-based approaches. It was conducted with the input of environmental scientists, engineers, and community representatives, underscoring its collaborative and practical value.  By delving into the behind-the-scenes efforts, including extensive fieldwork and precise laboratory analyses, the research underscores its commitment to community well-being and sustainable resource management. These insights, coupled with their applicability to similar contexts, position the study as a model for environmental monitoring and policy development. Further elaboration on the methods and their adaptation to local conditions ensures that the research resonates with both scientific and community audiences, making it a significant contribution to environmental stewardship.