Evaluation of nitrate contamination in well waters by ion chromatography and UV–Vis spectrophotometry

Abstract. Nitrate contamination of groundwater is a growing environmental concern due to its adverse effects on drinking water quality and human health. This study aimed to evaluate nitrate contamination in well waters and to compare the analytical performance of ion chromatography (IC) and UV–Vis spectrophotometry employing an isoabsorptive correction method. Well water samples were collected from various regions of Romania and Hungary during autumn following standard sampling techniques and kept refrigerated until analysis. The average nitrate concentrations determined by IC and UV–Vis spectrophotometry were 16.8 mg/L and 16.6 mg/L, respectively, indicating good agreement between the two methods. One sample exceeded the regulatory limit of 50 mg/L NO₃⁻, likely reflecting the influence of agricultural activities. The nitrite concentrations in all samples were below the limit of detection. Additional analyses of major ions and trace elements revealed that potentially toxic metals, including arsenic, nickel, lead, and cadmium, were below the drinking-water guideline values. Although IC demonstrated superior analytical performance, including lower detection limits, higher precision, and improved calibration linearity, the UV–Vis method provided comparable results for nitrate concentrations between 1 and 100 mg/L, with measurement deviations generally below 10%. Error analysis showed a significant correlation with total organic carbon content, indicating that elevated organic matter may interfere with UV–Vis measurements. These findings demonstrate that UV–Vis spectrophotometry, when combined with an isoabsorptive correction approach, can serve as a practical and cost-effective alternative to IC for routine groundwater nitrate monitoring. The results suggest that UV–Vis spectrophotometry represents a reliable and cost-effective alternative for routine nitrate monitoring in groundwater.

Acknowledgement. This work was supported by the Core Program within the National Research Development and Innovation Plan 2022–2027, with the support of MCID, project PN no. 23 05.