Seasonal and Spatial Assessment of Heavy Metal Contamination in Groundwater in the Republic of Kosovo

Abstract

Groundwater is vital to subsurface ecosystems and to maintaining water supplies for human and environmental needs. Heavy metal pollution of water bodies poses a significant threat to environmental health and human well-being. In this paper, a detailed spatiotemporal analysis of heavy metal pollution at a network of 35 sampling sites is presented for the summer, autumn, and winter seasons. The water samples were analyzed based on the concentration (μg/L) of eight priority metals, such as Lead (Pb), Mercury (Hg), Cadmium (Cd), Arsenic (As), Chromium VI (Cr-VI), Copper (Cu), Zinc (Zn), as well as Iron (Fe). Measuring contamination levels, identifying space hotspots, and explaining seasonal variations were the key tasks. The results show that Fe, Zn, and Cu concentrations are consistently high across seasons, with mean values ranging from 234.3 to 253.2 µg/L (Fe), 163.2 to 175.6 µg/L (Zn), and 107.0 to 109.2 µg/L (Cu), indicating a widespread geogenic or diffuse source. The most significant seasonal deviation was observed in the fall when there were unusually high levels of Cd and Hg, with mean concentrations reaching 0.476 µg/L and 0.312 µg/L, respectively, suggesting a strong seasonal contamination event or mobilization process. The spatial analysis showed that the locations (e.g., L6, L8, L10, L28, L29) exhibited common hotspots for different metals, with maximum concentrations reaching up to 793.3 µg/L (Fe), 602.3 µg/L (Zn), and 508 µg/L (Cu). Principal Component Analysis (PCA) effectively separated seasonal trends and classified metals into anthropogenic (Pb, Cd, Hg, Cr (VI)) and geogenic/diffuse (Fe, Zn, Cu) groups. The health risk assessment indicated no significant non-carcinogenic risk, although children are more vulnerable, while arsenic levels in winter approached the upper acceptable carcinogenic limit (up to 1.1 × 10−4). Overall, the study highlights the importance of multi-seasonal monitoring by capturing temporally abrupt contamination events and provides a novel integrated framework that combines seasonal analysis, spatial hotspot identification, and multivariate techniques, distinguishing it from conventional single-season or non-integrated studies.