Environmental Exposure of Arsenic in Groundwater Associated to Carcinogenic Risk in Underweight Children Exposed to Fluorides

Designing dynamic groundwater management strategies through a composite groundwater vulnerability model: Integrating human-related parameters into the DRASTIC model using LightGBM regression and SHAP analysis

Groundwater nitrate contamination has emerged as a pressing global concern. Given its potential for long-term impacts on aquifers, protective measures should primarily focus on prevention. Drawing on the theory of groundwater vulnerability (GV), the original DRASTIC model and parameters related to human activities are employed as inputs and integrated with the LightGBM regression algorithm to facilitate nitrate index (NI) prediction tasks. The SHAP analysis is conducted to effectively examine the contribution of parameters to the NI prediction and interpret the issue of parameter interactions. In addition, to mitigate the limitations of the intrinsic GV model, a composite nitrate index (CNI) is developed by linearly combining the DRASTIC index with the NI. The framework presented in this study provides adaptive strategies for managing groundwater resources over different time periods. A representative region for arid and semiarid climates, the Yinchuan region, is studied using the framework. As compared to 2012, the intrinsic GV index has changed spatially in 2022. Human activities have increased the influence of the nitrate concentration as shown by the Pearson correlation coefficient of -0.082 between the DRASTIC index and nitrate concentration. A significant increase in pollution levels was predicted by NI, ranging from -0.116 to 0.968. According to SHAP analysis, the significant increase in NI levels in 2022 was mainly due to high-value industrial and agricultural production. In 2022, 12.02% of the areas had an increase of at least 0.549 in the CNI. 42.1% of the areas were classified as moderate or high CNI levels. The farm was identified as a high-contributing source to nitrate pollution. The small-scale agricultural and livestock activities in non-urban areas also contribute to groundwater pollution. Dynamic groundwater management strategies need to be implemented in high-growth and high-level CNI areas.

Arsenic in waters, soils, sediments, and biota from Mexico: An environmental review

We reviewed over 226 studies dealing with arsenic (As) in water bodies (124 sites or regions; 5,834 samples), soils (44; 2,700), sediments (56; 765), rocks (6; 85), mine waste (25; 582), continental plants (17 (77 species); 571), continental animals (10 (32 species); 3,525) and aquatic organisms (27 (100 species) 2,417) in Mexico. In general, higher As concentrations were associated with specific regions in the states of Hidalgo (21 sites), San Luis Potosi (SLP) (19), Baja California Sur (15), Zacatecas (5), and Morelos (4). High As levels have been detected in drinking water in certain locations of Coahuila (up to 435 μg L^-1) and Sonora (up to 1004 μg L^-1); in continental surficial water in Puebla (up to 780 μg L^-1) and Matehuala, SLP (up to 8684 μg L^-1); in groundwater in SLP (up to 16,000 μg L^-1) and Morelia, Michoacán (up to 1506,000 μg L^-1); in soils in Matehuala, SLP (up to 27,945 μg g^-1) and the Xichú mining area, Guanajuato (up to 62,302 μg g^-1); and in sediments in Zimapán, Hidalgo (up to 11,810 μg g^-1) and Matehuala, SLP (up to 28,600 μg g^-1). In contaminated arid and semi-arid areas, the plants P. laevigata and A. farnesiana exhibit the highest As levels. These findings emphasize the human and environmental risks associated with the presence of As in such regions. A synthesis of the available techniques for the removal of As in water and the remediation technologies for As contaminated soils and sediments is given. The As occurrence, origin (geogenic, thermal, mining and anthropogenic) and evolution in specific regions is summarized. Also, the mobilization and mechanisms to explain the As variability in continental environments are concisely given. For future research, a stratified regional sampling is proposed which prioritizes critical sites for waters, soils and sediments, and biota, considering the subpopulation of foods from agriculture, livestock, and seafood. It is concluded that more detailed and comprehensive studies concerning pollution levels, as well as As trends, transfer, speciation, and toxic effects are still required.

Probabilistic human health risk assessment associated with fluoride and arsenic co-occurrence in drinking water from the metropolitan area of San Luis Potosí, Mexico

A major public health concern in Mexico is the natural contamination of groundwater with fluoride and arsenic. Therefore, this work aimed to evaluate the magnitude of human health risk after determining fluoride and arsenic concentrations in groundwater samples (n = 50) from the Metropolitan area of the city of San Luis Potosi, Mexico. Fluoride levels in water were determined via a potentiometric method using an ion-selective electrode. Arsenic concentrations in water samples were determined with an Atomic Absorption technique. Subsequently, a probabilistic health risk assessment was developed (Monte Carlo Analysis). Fluoride levels in water ranged from 0.20 to 3.50 mg/L. For arsenic, the mean level found in the assessed water samples was 15.5 ± 5.50 μg/L (range: 2.50-30.0 μg/L). In addition, when the probabilistic health risk assessment was completed, a mean HI (cumulative hazardous index) of higher than 1 was detected, indicating a high NCR (non-carcinogenic risk) for children and adults. According to the results found in this study, exposure protection campaigns are imperative in the Metropolitan area of the city of San Luis Potosí, Mexico, to successfully diminish exposure to arsenic and fluoride and, as a consequence, decrease the NCR in the population living in that region of Mexico.