Arsenic Contamination, Water Toxicity, Source Apportionment, and Potential Health Risk in Groundwater of Jhelum Basin, Punjab, Pakistan

Unraveling the impact of high arsenic, fluoride and microbial population in community tubewell water around coal mines in a semiarid region: Insight from health hazards, and geographic information systems

High arsenic (As), fluoride (F-), and microbial pathogens coexist in semiarid conditions afflicting > 240 million people worldwide including Pakistan. Groundwater quality has declined due to geogenic and manmade activities providing suitable ground for ubiquity, bioavailability, and toxicity of contaminants. We tested the health hazard, distribution, and apportionment of As, F-, and microbes in groundwater around coal mines in Quetta, Pakistan. The range of As, and F- concentrations in groundwater were 0.2-16.6 µg/L, 0.4-18.5 mg/L. Both, As and F- correlate with high HCO3-, pH, Na+, SO42-, Fe, and Mn, and negatively with Ca2+ water. The coalfield showed many folds higher As 15.8-28.5 µg/L, and F- 10.8-34.5 mg/L compared to groundwater-wells. Geochemical phases revealed saturation of groundwater with calcite, dolomite, fluorite, gypsum, and undersaturation with halite-mirabilite, and arsenopyrite minerals. The positive matrix factorization (PMF) model assessed five-factor solutions: geogenic, industrial, coal mining, sulfide & fluoride-bearing mineral-dissolution, and agriculture pollution delivered As, F-, and microbial contamination. About 24.6 % and 64.4 % of groundwater samples exceeded the WHO guidelines of As 10 µg/L, F- 1.5 mg/L. The carcinogenicity, and non-carcinogenicity of As, and F- were higher in children than adults. Therefore, health hazards in children are of great concern in achieving sustainable management goals.

Heavy Metals in Umbilical Cord Blood: Effects on Epigenetics and Child Development

Heavy metals like arsenic, mercury, cadmium, and lead are harmful pollutants that can change how our genes are regulated without altering the DNA sequence, specifically through a process called DNA methylation (DNAm) at 5-methylcytosine, an epigenetic mark that we will focus on in this review. These changes in DNAm are most sensitive during pregnancy, a critical time for development when these modifications can affect how traits are expressed. Historically, most research on these environmental effects has focused on adults, but now there is more emphasis on studying the impacts during early development and childhood. The placenta acts as a protective barrier between the mother and the baby, and by examining it, scientists can identify changes in key genes that might affect long-term health. This review looks at how exposure to heavy metals during pregnancy can cause changes in the gene regulation by DNAm in newborns, as seen in their umbilical cord blood. These changes reflect the baby's genetic state during pregnancy and can be influenced by the mother's environment and genetics, as well as the baby's own genetics.

Assessment of landcover impacts on the groundwater quality using hydrogeochemical and geospatial techniques

Groundwater quality is influenced by urbanization and land use land cover (LULC) changes. This study investigated their impact on groundwater quality in Quetta City, Pakistan, from 2015 to 2021. About 58 groundwater samples from monitoring wells were analyzed using hydrogeochemical and statistical methods. The water quality index (WQI), Wilcox, USSL, and various agricultural indices were employed to assess water quality trends. LULC analysis and NDVI using Sentinel-2 imagery revealed increased urban and agricultural areas and decreased barren land. Rapid urbanization was evident, with the buildup class expanding by 7.50% during this period. NDVI findings emphasized monitoring vegetation health and water quality for environmental assessments. The groundwater in Quetta was primarily classified as Cl-Ca·Mg, Cl-Ca, and Cl-Na according to the Piper diagram, with water-rock interactions and rock weathering evident. Most groundwater samples were suitable for irrigation according to the Wilcox and USSL diagrams. The WQI demonstrated overall safety for human consumption, but declining WQI values in northern parts due to urbanization are concerning. The results also revealed a moderate positive relationship between landcover classes and WQI values. It can be concluded that urbanization and excessive use of pesticides contributed to declining agricultural land quality. The spatial overlay of agricultural indices with landcover class suggested that barren land was most suitable, followed by build-up and agriculture were suitable for drinking and agriculture purposes. Moreover, agricultural indices moderately declined due to excessive fertilizers and pesticides in the agriculture landcover class. Thus, effective water resource management is crucial to address challenges. This comprehensive study serves as a baseline for future research and recommends larger-scale studies to implement efficient management strategies, urbanization planning, and safe irrigation and drinking water practices to prevent groundwater pollution.

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.

An efficient synthesis and characterization of La@MOF-808: A promising strategy for effective arsenic ion removal from water

Addressing serious waterborne arsenic issues, for the first time, lanthanum-doped MOF-808 (La@MOF-808) has been developed to remove total arsenic (Total As) and arsenite [As(III)] from water. This study involves the solvothermal synthesis of La@MOF-808, its characterization via FTIR, XRD, TGA, and SEM, in which distinct physicochemical attributes were identified, and the adsorption capacity of arsenic ions. The saturated adsorption capacity of La@MOF-808 for Total As and As(III) reached 282.9 mg g-1 and 283.5 mg g-1, as compared to 229.7 mg g-1 and 239.1 mg g-1 for pristine MOF-808, respectively. XRD and ATR-FTIR analyses underscored the central roles of electrostatic interactions and hydroxyl groups in the pollutant adsorption process. The impact of temperature, concentration, pH, and exposure duration times on adsorption performance was thoroughly investigated. The Langmuir model showed the maximum adsorption capacities (qmax) of La@MOF-808 was 307.7 mg g-1 for Total As and 325.7 mg g-1 for As(III), surpassing those of MOF-808 adsorbent, which suggests that monolayer adsorption occurred. Optimal adsorption was observed in a pH range of 2.0-7.0, and thermodynamic studies classified the process as spontaneous and endothermic. The adsorbent retains high capacity across repeated cycles, outperforming many standard adsorbents. Lanthanum doping markedly enhances MOF-808's arsenic removal, underscoring its potential for water treatment.

Heavy Metals in Surface Sediment of Plateau Lakes in Tibet, China: Occurrence, Risk Assessment, and Potential Sources

Tibetan Plateau lakes have high ecological value and play a crucial role in maintaining ecological balance. This research aimed to study the pollution characteristics, ecological risk, and potential sources of eight heavy metals (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) in the surface sediments of 12 Tibetan Plateau lakes. The results of the toxicity risk index (TRI) showed that only Gongzhu Tso (28.09) and La' ang Tso (20.25) had heavy metals that could pose a very high risk of toxicity to aquatic organisms. Hg posed the highest potential ecological risk to aquatic organisms. Based on the results of multiple analyses, we inferred that the contents of Cr, Cu, Hg, and Ni in sediments of Tibetan lakes were influenced by industrial and agricultural development; Cd, Pb, and Zn were influenced by transport and atmospheric transport; and As was derived from geothermal activity and rock weathering.

Morphological characterization, hazardous metal contamination, source identification, and health risk assessment of the fine road dust from Dachang mining area, China

Dachang mining area in China is known as "paradise for mineralogists" due to its most reserves of Sn, Sb, Pb, and Zn non-ferrous metal resources; thus, its evaluation for heavy metal assessment and consequent health risk is unavoidable. Sixty road dust samples were collected from study area to explore pollution level, ecological, and health risks from heavy metals and were analyzed by an inductively coupled plasma optical emission spectrometer and atomic fluorescence spectrometer. The results showed that average concentration of all the heavy metals in road dust in both mining and residential areas were remarkable higher than its corresponding background values, the former being more severe, except for Cr and Co. The morphological investigation showed that most of the particles were much less than 100 μm illustrating fine part of the road dust samples. Based on integrated pollution indices, Cd, Sb, As, Zn, and Pb were extremely contaminated and exceeded hundred times of the maximum risk value. The health risk assessment revealed substantially higher carcinogenic and non-carcinogenic risks to children and adult. Highest non-carcinogenic risk resulted from arsenic in mining and residential area with HQ_ing of 644.56 and 267.94 respectively (standard HQ ≥ 1) while carcinogenic risk to children (1.94E + 00) which greatly exceeded from the threshold value of (1.0E-4). Sb, Cd, and Pb also posed carcinogenic and non-carcinogenic risk in road dust which is caused by excessive mining activities and heavy vehicle movement in the study area.