Health risk assessment of groundwater nitrogen pollution in Yinchuan plain

Evaluation and health risk assessment of arsenic and potentially toxic elements pollution in groundwater of Majha Belt, Punjab, India

Concentrations of potentially toxic elements (PTEs) like arsenic, uranium, iron, and nitrate in the groundwater of the Majha Belt (including Tarn Taran, Amritsar, Gurdaspur, and Pathankot districts) in Punjab, India were measured to evaluate the health risks associated with its consumption and daily use. The average concentrations of these elements in some locations exceeded the WHO-recommended values. Arsenic and iron toxicity levels were found to be higher in the Amritsar district, while uranium toxicity was more prevalent in Tarn Taran. The Trace Element Evaluation Index suggests that Amritsar is one of the districts most affected by toxic elements. According to the US Environmental Protection Agency's (USEPA) guidelines, the HQ values of U, Fe, and nitrate were less than one, indicating that there is no non-carcinogenic health risk for adults and children. However, the hazard quotient (HQ) value for arsenic was greater than one, indicating a higher possibility of health risk due to arsenic in the study area. The total hazard index values of 44.10% of samples were greater than four for arsenic, indicating that people in the Majha Belt are at a very high health risk due to the usage of water for drinking and domestic purposes. The cancer risk assessment values for arsenic in children (5.69E + 0) and adults (4.07E + 0) were higher than the accepted limit of USEPA (10-4 to 10-6) in the Majha Belt. The average radiological cancer risk values of U for children and adults were 8.68E-07 and 9.45E-06, respectively, which are well below the permissible limit of 1.67 × 10-4 suggested by the Atomic Energy Regulatory Board of DAE, India. The results of this study confirm that the residents of the Majha Belt who use contaminated groundwater are at a serious risk of exposure to arsenic in the Amritsar district and uranium in Tarn Taran district.

Hydrochemical analysis and groundwater suitability for drinking and irrigation in an arid agricultural area of the Northwest China

Groundwater is the foremost water source in the arid and semiarid regions of Northwest China. Assessing groundwater's drinking and irrigation quality is essential for protecting these valuable groundwater resources. In this study, a total of 24 confined groundwater samples and 54 phreatic groundwater samples were collected in the southern and central Ningxia area for hydrochemical analysis and quality assessment. The hydrochemical results revealed that hydrochemical types of phreatic and confined groundwater consistently belonged to Na-SO4-Cl and Na-Mg-SO4-Cl types. The driving forces of groundwater chemistry were determined by gypsum dissolution, silicate dissolution, and positive cation exchange for phreatic and confined aquifers. The entropy-weighted water quality index (EWQI) and irrigation water quality index (IWQI) showed that the drinking water quality and irrigation quality were better in phreatic groundwater than in confined groundwater due to the Neogene-Paleogene groundwater system recharge and strong evaporation. Measures such as controlling groundwater extraction and optimizing well placement need to be implemented. The achievements would be helpful for groundwater management and protection in agricultural areas under semi-arid and arid climates.

Nitrogen sources and conversion processes in shallow groundwater around a plain lake (Northwest China): Evidenced by multiple isotopes and water chemistry

The groundwater quality is severely impacted by Nitrate (NO₃^--N) pollution worldwide. Effective lake quality management depends on understanding the origin and fate of nitrogen (N) in the groundwater around lakes. This study combined data for multiple stable isotopes (δ²H-H₂O and δ¹⁸O-H₂O, δ¹⁵N-NO₃ and δ¹⁸O-NO₃) and hydrochemistry with the hydrodynamic monitoring profile and a Bayesian isotope mixing (MixSIAR) model to clarify the sources and transformation of N within shallow groundwater around Shahu Lake in the arid area plain of Northwest China. In May 2022, multiple water samples were collected from aquifers (n = 33), drainage water (n = 1), channel water (n = 1), and lake water (n = 7). The results showed that 57% of groundwater samples had high NO₃^--N concentrations exceeding the World Health Organisation threshold for drinking water (10 mg/L). The high variation in δ¹⁵N-NO₃ (from -9.21‰ to +27.57‰) and δ¹⁸O-NO₃ (from -8.32‰ to +19.04‰) revealed multiple N sources and conversion processes. According to nitrate isotopes and the MixSIAR model, N fertilizer, soil organic N and manure, and sewage are the main sources of nitrogen in groundwater and lake water, which account for 40.61%, 35.86%, and 21.55% of groundwater NO₃^--N, respectively, and 35.07%, 34.43%, and 27.49% of lake water NO₃^--N. Hydrodynamic monitoring combined with water isotopes showed that upper groundwater (5-10 m) within 1.22 km of the adjacent lake shore strongly interacted with the lake. In groundwater, nitrification predominated, while local denitrification remained a possibility. In conclusion, this research offers a comprehensive approach to determining the sources and conversion of N in contaminated groundwater.

Hotspot and accumulated hotspot analysis for assessment of groundwater quality and pollution indices using GIS in the arid region of Iran

Because groundwater quality representatives for drinking usage (i.e., Schuler method, Nitrate and Groundwater Quality Index) have been abruptly changing due to extreme events induced by global climate change and over-abstracting, applying an efficient tool for their assessments is vitally important. While hotspot analysis is introduced as an efficient tool concentrating on sharp changes in groundwater quality, it has not been closely examined. Accordingly, this study is an attempt to determine the groundwater quality proxies and assess them through hotspot and accumulated hotspot analyses. To this end, a GIS-based hotspot analysis (HA) applying Getis-Ord Gi* statistics was used. The accumulated hotspot analysis was launched to identify the Groundwater Quality Index (AHA-GQI). Moreover, Schuler method (AHA-SM) was utilized to determine the maximum levels (ML) for the hottest hotspot and the lowest levels (LL) for the coldest cold-spot, and compound levels (CL). The results revealed that a significant correlation (r = 0.8) between GQI and SM was observed. However, the correlation between GQI and nitrate was not significant and the correlation between SM and nitrate was so low (r = 0.298, sig > 0.05). The results also demonstrated that using hotspot analysis on only GQI, the correlation between GQI and SM increased from 0.8 to 0.856, while using hotspot analysis on both GQI and SM increased the correlation to 0.945. Likewise, when GQI was subjected to hotspot analysis and SM underwent accumulated hotspot analysis (i.e., AHA-SM (ML)), the correlation degree increased to the highest extent (i.e., 0.958), indicating the usefulness of including the hotspot analysis and accumulated hotspot analysis in the evaluation of groundwater quality.