Toxic Risk Assessment of Arsenic in Males Through Drinking Water in Tharparkar Region of Sindh, Pakistan

Integrated Approach to Hydrogeochemical Assessment of Groundwater Quality in Major Industrial Zone of Punjab, Pakistan

Groundwater contamination with arsenic (As) is a significant concern in Pakistan's Punjab Province. This study analyzed 69 groundwater samples from Faisalabad, Gujranwala, Lahore, and Multan to understand hydrogeochemistry, health impacts, contamination sources, and drinking suitability. Results revealed varying as concentrations across districts, with distinctive cation and anion orders. Faisalabad exhibited Na+ > Mg2+ > Ca2+ > K+ > Fe2+ for cations and SO42- > Cl- > HCO3- > NO3- > F- for anions. Gujranwala showed Na+ > Ca2+ > Mg2+ > K+ for cations and HCO3-  > SO42- > Cl- > NO3-  > F- for anions. In Lahore, demonstrated: Na+ > Ca2+ > Mg2+ > Fe > K+ for cations and HCO3-  > SO42- > Cl- > NO3-  > F- for anions. Multan indicated K+ > Ca2+ > Mg2+ > Na+ > Fe for cations and HCO3-  > SO42- > Cl- > F- > NO3- ) for anions. Hydrochemical facies were identified as CaHCO3 and CaMgCl types. Principal Component Analysis (PCA), highlighted the influence of natural processes and human activities on groundwater pollution. Water Quality Index (WQI) result reveal that most samples met water quality standards. The carcinogenic risk values for children exceeded permissible limits in all districts, emphasizing a significant cancer risk. The study highlights the need for rigorous monitoring to mitigate (As) contamination and protect public health from associated hazards.

Hydrogeochemistry and prediction of arsenic contamination in groundwater of Vehari, Pakistan: comparison of artificial neural network, random forest and logistic regression models

Arsenic contamination in the groundwater occurs in various parts of the world due to anthropogenic and natural sources, adversely affecting human health and ecosystems. The current study intends to examine the groundwater hydrogeochemistry containing elevated arsenic (As), predict As levels in groundwater, and determine the aptness of groundwater for drinking in the Vehari district, Pakistan. Four hundred groundwater samples from the study region were collected for physiochemical analysis. As levels in groundwater samples ranged from 0.1 to 52 μg/L, with an average of 11.64 μg/L, (43.5%), groundwater samples exceeded the WHO 2022 recommended limit of 10 μg/L for drinking purposes. Ion-exchange processes and the adsorption of ions significantly impacted the concentration of As. The HCO3- and Na+ are the dominant ions in the study area, and the water types of samples were CaHCO3, mixed CaMgCl, and CaCl, demonstrating that rock-water contact significantly impacts hydrochemical behavior. The geochemical modeling indicated negative saturation indices with calcium carbonate and other salt minerals, encompassing aragonite, calcite, dolomite, and halite. The dissolution mechanism suggested that these minerals might have implications for the mobilization of As in groundwater. A combination of human-induced and natural sources of contamination was unveiled through principal component analysis (PCA). Artificial neural networks (ANN), random forest (RF), and logistic regression (LR) were used to predict As in the groundwater. The data have been divided into two parts for statistical analysis: 20% for testing and 80% for training. The most significant input variables for As prediction was determined using Chi-squared analysis. The receiver operating characteristic area under the curve and confusion matrix were used to evaluate the models; the RF, ANN, and LR accuracies were 0.89, 0.85, and 0.76. The permutation feature and mean decrease in impurity determine ten parameters that influence groundwater arsenic in the study region, including F-, Fe2+, K+, Mg2+, Ca2+, Cl-, SO42-, NO3-, HCO3-, and Na+. The present study shows RF is the best model for predicting groundwater As contamination in the research area. The water quality index showed that 161 samples represent poor water, and 121 samples are unsuitable for drinking. Establishing effective strategies and regulatory measures is imperative in Vehari to ensure the sustainability of groundwater resources.

Arsenic health risk assessment and the evaluation of groundwater quality using GWQI and multivariate statistical analysis in rural areas, Hashtroud, Iran

Arsenic (As) is a toxic metalloid that can cause significant health issues through drinking water. The present study was aimed to evaluate As distribution and the related health risks from drinking groundwater in rural areas of Hashtroud, Iran. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were also applied to better explain relationship pattern between different resources. The samples were taken from 51 locations in 37 villages. Arsenic concentration was determined by a polarograph device, and the corresponding carcinogenic and non-carcinogenic health risks were calculated based on US Environmental Protection Agency (EPA) guideline. PCA analysis extracted four main components that explained nearly 62% of data variance. Results pointed severe As contamination in the studied area, where As was detected in 78% of the samples ranging from less than 0.001 to 0.250 mg/L. Forty percent of the contaminated places violated guideline value of 10 μg/L suggested by EPA and institute of standards and industrial research of Iran (ISIRI). Based on our findings, 1329 people including 239 children were living in the areas with higher As contamination. Hazard quotient (HQ) in 72%, 59%, and 33% of the samples was higher than one for children, adolescent, and adult age groups, respectively. Excess life time cancer risk (ELCR) in almost 80% of all age groups was significantly higher than EPA recommended guideline (10^-4 or 10^-6). In summary, from the view point of arsenic HQ and ELCR, water resources in the studied areas were not appropriate for drinking and hygienic purposes; necessary and urgent management strategies to guarantee water supply and health safety for local residents should be considered.

Evaluation of Arsenic, Cadmium, Nickel and Lead in Common Spices in Pakistan

The quantitative assessments and daily intake of arsenic (As), cadmium (Cd), nickel (Ni) and lead (Pb) were conducted in the 26 common spices collected from the market of Hyderabad, Pakistan. Conventional acid digestion procedure was applied for dissolution of common spices and the contents of toxic elemental were determined by graphite furnace atomic absorption spectrometry. The conventional acid digestion method was validated by certified reference materials and standard addition. A wide variability was observed in the levels of toxic elements in common spices. The toxic elements in common spices were found in decreasing order as Ni > Pb > As > Cd. The contents of As, Cd, Ni and Pb in common spices were observed highest in coriander seed, allspices, nigella seed and black cumin seed, respectively. The current study revealed that the toxic elements in common spices were varied from region to region. However, the estimated intake of As, Cd, Ni and Pb from common spices were within the WHO tolerable weekly intake. The data of risk assessment indicated that As, Cd, Ni, and Pb in common spices may not have any toxic risk except the As in carom, coriander and nigella seeds.

Arsenic in the groundwater: Occurrence, toxicological activities, and remedies

Arsenic (As) contamination in groundwater has become a geo-environmental as well as a toxicological problem across the globe affecting more than 100-million people in nearly 21 countries with its associated disease "arsenicosis." Arsenic poisoning may lead to fatal skin and internal cancers. In present review, an attempt has been made to generate awareness among the readers about various sources of occurrence of arsenic, its geochemistry and speciation, mobilization, metabolism, genotoxicity, and toxicological exposure on humans. The article also emphasizes the possible remedies for combating the problem. The knowledge of these facts may help to work on some workable remedial measure.