Nitrate contamination of water in dug wells and associated health risks of rural communities in southwest Bangladesh

Heavy metals in five commonly consumed fish species from River Swat, Pakistan, and their implications for human health using multiple risk assessment approaches

This study analyzed the levels of heavy metals bioaccumulation in commonly consumed riverine fish species, including G. cavia, T. macrolepis, G. gotyla, S. plagiostomus, and M. armatus from River Swat in Pakistan, and quantify their potential risk to children and adults in general and fisherfolk communities using multiple pollution and risk assessment approaches. The highest metal detected by inductive coupled plasma mass spectrometry (ICP-MS) was Zn, which ranged from 49.61 to 116.83 mg/kg, followed by Fe (19.25-101.33 mg/kg) > Mn (5.25-40.35 mg/kg) > Cr (3.05-14.59 mg/kg) > Ni (4.26-11.80 mg/kg) > Al (1.59-12.25 mg/kg) > Cu (1.24-8.59 mg/kg) > Pb (0.29-1.95 mg/kg) > Co (0.08-0.46 mg/kg) > Cd (0.01-0.29 mg/kg), demonstrating consistent fluctuation with the safe recommendations of global regulatory bodies. The average bioaccumulation factor (BAF) values in the examined fish species were high (BAF > 5000) for Pb, Zn, Mn, Cu, Cr, Ni, and Cd, bioaccumulate (1000 > BAF < 5000) for Co, and probable accumulative (BAF <1000) for Fe, and Al, while the overall ∑heavy metals pollution index (MPI) values were greater than one (MPI > 1) indicating sever heavy metals toxicity in G. cavia, followed by S. plagiostomus, M. armatus, G. gotyla, and T. macrolepis. The multivariate Pearson's correlation analysis identified the correlation coefficients between heavy metal pairs (NiCr, CuCr, PbCr, AlCo, CuNi, and PbNi), the hierarchical cluster analysis (CA) determined the origin by categorizing heavy metal accumulation into Cluster-A, Cluster-B, and Cluster-C, and the principal component analysis (PCA) discerned nearby weathering, mining, industrial, municipal, and agricultural activities as the potential sources of heavy metals bioaccumulation in riverine fish. As per human risk perspective, S.plagiostomus contributed significantly to the estimated daily intake (EDI) of heavy metals, followed by G.cavia > M.armatus > G.gotyla > T.macrolepis in dependent children and adults of the fisherfolk followed by the general population. The non-carcinogenic target hazard quotient (THQ) and hazard index (HI) values for heavy metal intake through fish exposure were < 1, while the carcinogenic risk (CR) for individual metal intake and the total carcinogenic risk (TCR) for cumulative Cr, Cd, and Pb intake were within the risk threshold of 10-6-10-4, suggesting an acceptable to high non-carcinogenic and carcinogenic risk for both children and adults in the fisherfolk, followed by the general population.

BRIDGE methodology-based quality standards to assess aquifer chemical status in the southwest Bengal Basin, Bangladesh

Assessment of natural background levels (NBLs) of compositional groundwater parameters helps to identify the potential threats to groundwater resources. This study is the first attempt to apply the pre-selection-based BRIDGE (Background cRiteria for the IDentification of Groundwater thrEshold) methodology to calculate the NBLs and threshold values (TVs) of major groundwater constituents in the southwest Bengal Basin, Bangladesh. A database consisting of 78 groundwater samples was used to assess the NBLs and associated TVs of the major groundwater parameters (EC, Ca²⁺, Mg²⁺, Na⁺, K⁺, Cl^-, NO₃^-, SO₄^2-, PO₄^3-, Mn²⁺, and Fe²⁺). NBLs were derived based on 90th and 97.7th percentiles. The status of regional groundwater resources was assessed by applying 90th percentile NBL on a regional dataset (n = 196). Results revealed the "poor" chemical status of shallow aquifers denoting heavy deterioration of the groundwater quality due to anthropogenic interventions. Nitrate contamination and salinization were identified as the major threats to the deep groundwater of the southwest Bengal Basin. Finally, to verify the chemical status of groundwater in a heavily urbanized area, derived TVs were applied throughout the experimental site Khulna. Twenty-five deep groundwater samples were collected for this purpose. Though most of the parameters exhibited "good" chemical status, nitrate demonstrated anthropogenic groundwater contamination in Khulna City. Thus, the developed TVs would provide an early warning system of pollution. On a national scale, it is expected to facilitate the sustainable groundwater management of the country and contribute to achieving the Sustainable Development Goals (SDG) of the United Nations (UN) in Bangladesh.

Predicting Potential Climate Change Impacts on Groundwater Nitrate Pollution and Risk in an Intensely Cultivated Area of South Asia

One of the potential impacts of climate change is enhanced groundwater contamination by geogenic and anthropogenic contaminants. Such impacts should be most evident in areas with high land-use change footprint. Here, we provide a novel documentation of the impact on groundwater nitrate (GWNO3 ) pollution with and without climate change in one of the most intensely groundwater-irrigated areas of South Asia (northwest India) as a consequence of changes in land use and agricultural practices at present and predicted future times. We assessed the probabilistic risk of GWNO3 pollution considering climate changes under two representative concentration pathways (RCPs), i.e., RCP 4.5 and 8.5 for 2030 and 2040, using a machine learning (Random Forest) framework. We also evaluated variations in GWNO3 distribution against a no climate change (NCC) scenario considering 2020 status quo climate conditions. The climate change projections showed that the annual temperatures would rise under both RCPs. The precipitation is predicted to rise by 5% under RCP 8.5 by 2040, while it would decline under RCP 4.5. The predicted scenarios indicate that the areas at high risk of GWNO3 pollution will increase to 49 and 50% in 2030 and 66 and 65% in 2040 under RCP 4.5 and 8.5, respectively. These predictions are higher compared to the NCC condition (43% in 2030 and 60% in 2040). However, the areas at high risk can decrease significantly by 2040 with restricted fertilizer usage, especially under the RCP 8.5 scenario. The risk maps identified the central, south, and southeastern parts of the study area to be at persistent high risk of GWNO3 pollution. The outcomes show that the climate factors may impose a significant influence on the GWNO3 pollution, and if fertilizer inputs and land uses are not managed properly, future climate change scenarios can critically impact the groundwater quality in highly agrarian areas.

Groundwater quality evaluation and human health risks assessment using the WQI, NPI and HQnitrate models: case of the Sfax intermediate aquifer, Sahel Tunisia

Groundwater is a vital natural resource required to satisfy the domestic and agricultural needs. In general, human health is linked to the quality of the consumed water. For instance, long-term exposure to high nitrate levels in groundwater may cause problems. Hence, the present study was conducted to assess the nitrate contamination of groundwater as well as its related health risks for the inhabitants of the Sfax region, Sahel Tunisia. Irrigation groundwater suitability has been evaluated with sodium content (%Na), electrical conductivity (EC), magnesium hazard (MH), sodium adsorption ratio (SAR), permeability index (PI), Kelly's ratio (KR) and soluble sodium percent (SSP). The results indicate that the selected groundwater is characterized by low to moderate quality for irrigation. Furthermore, the drinking water quality index (DWQI) was assessed using potential of hydrogen (pH), total dissolved solids (TDS), magnesium (Mg²⁺), calcium (Ca²⁺), sodium (Na⁺), chloride (Cl^-), sulfate (SO₄^2-), potassium (K⁺), bicarbonate (HCO₃^-) and nitrate (NO₃^-). The results indicate that 3.63% of samples have good quality of water, while 41.82% have poor to very poor water quality and the rest (54.55%) are unfit for drinking. The nitrate pollution index (NPI) model revealed that about 42% of the samples present significant to very significant type of pollution. Based on human health risk assessment, the children are at higher risks compared to the other affected groups. The obtained results could be used as a basic document for realistic management of groundwater quality and to provide an overview for decision-making authorities to take necessary actions.

Application of novel framework approach for prediction of nitrate concentration susceptibility in coastal multi-aquifers, Bangladesh

This study aims to construct a novel framework approach for predicting and mapping nitrate concentration susceptibility in the coastal multi-aquifers of Bangladesh by coupling the K-fold cross-validation method and novel ensemble learning algorithms, including Boosting, Bagging and Random Forest (RF). In total, 286 nitrate sampling sites were employed in the model work. The dataset was demarcated into a 75:25 ratio for model construction (75% 3-fold ≅ 214 sites) and (25% 1-fold ≅ 72 sites) for model validation using the 4-fold cross-validation schemes. A total of 14 groundwater causative factors including salinity, depth, pH, EC, As, HCO₃^-, F^-, Cl^-, SO₄^2-, PO₄^2-, Na⁺, K⁺, Mg²⁺, and Ca²⁺ were adopted for the construction of the proposed models. OneR relative importance model was employed to choose and rank critical factors for spatial nitrate modeling. The results showed that depth, pH and As are the most influential causative factors in the elevated nitrate concentration in groundwater. Based on the model assessment criteria such as receiver operating characteristic (ROC)'s AUC (area under curve), sensitivity, specificity, accuracy, precession, F score, and Kappa coefficient, the Boosting model outperforms others (r = 0.92, AUG ≥ 0.90) in mapping nitrate concentration susceptibility, followed by Bagging and RF models. The results of mapping nitrate concentration also demonstrated that the south-central and western regions had an elevated amount of nitrate content than other regions due to depth variation in the study area. During our sampling campaign, we observed hundreds of fish hatcheries operation, a fish landing center and aquaculture farms which are the reasons for overexploitation and excessive agrochemicals used in the study area. Thus, the dependability of ensemble learning modeling verifies the effectiveness and applicability of the proposed novel approach for decision-makers in groundwater pollution management at the local and regional levels.

Characterization of groundwater nitrate exposure using Monte Carlo and Sobol sensitivity approaches in the diverse aquifer systems of an agricultural semiarid region of Lower Ganga Basin, India

Prevalence of nitrate in different aquifer systems is a growing environmental and public health concern. Efforts were made for the first-time to achieve a higher accuracy in health risks characterization associated with the nitrate in groundwater of the diverse aquifer systems on the residents of a semi-arid rural tract of Lower Ganga Basin using Monte Carlo Simulations and Sobol Sensitivity analyses. The nitrate levels in groundwater varied between 0 and 508.3 mg/L with a mean of 19.79 ± 32.78 mg/L and 0-435.0 mg/L with a mean of 24.44 ± 35.15 mg/L during the pre-monsoon and post-monsoon periods, respectively. About 847.12-1000.25 km² area of the survey area (total area 4545 km²) exhibited nitrate concentrations (C) > the pre-intervention limits (45-50 mg/L). Minor populations, especially the infants from the granite gneiss, Rajmahal traps, laterite, recent alluvial and old alluvial aquifer zones under the Central Tendency Exposure (CTE) condition and all the aquifer zones (including the Gondwana supergroup aquifer zone) under Reasonable Maximum Exposure (RME) scenarios, were characterized as being at high risks of methemoglobinemia, primarily due to ingestion of untreated nitrate contaminated groundwater. Residents of the alluvial aquifer zones of the study area were found to the most vulnerable to the groundwater nitrate toxicity through oral and dermal exposures. The study validated the prediction accuracies of different interpolation methods including the Spline, Kriging, polynomial and Inverse Distance Weighted and revealed that Kriging predicted the Spatio-seasonal variations of groundwater nitrate of the district more accurately. Sobol Sensitivity analysis revealed C and the interaction effects of C and groundwater Ingestion Rate (IR), and C and Fraction of skin area contacted with groundwater (F) as the influential parameters for oral and dermal health risks exposure models. Therefore, the study recommends to residents of the study area to consume treated groundwater to mitigate nitrate related health morbidities.

Health risk assessment of nitrate and fluoride in bottled water: a case study of Iran

Bottled water use has become widespread in recent years. Many Iranian cities are located in regions with a hot and semi-hot climate, and the quality of drinking water is low in most of these areas. Nitrate and fluoride are chemical constituents of drinking water with significant health concerns since they can be harmful in concentrations higher than drinking water standards. This study aims to determine nitrate and fluoride concentrations in different bottled water brands in the study region; evaluate the non-carcinogenic health risks posed by nitrate and fluoride exposure via the ingestion of bottled water; and compare the measured nitrate and fluoride concentrations with the amounts reported on the bottle labels. Twenty bottled water brands were sampled, and their nitrate and fluoride amounts were determined using the spectrophotometry method. The results revealed that 100% of nitrate and 70% of fluoride in samples had concentrations greater than the levels reported on bottle labels. Minimum, maximum, and mean concentrations for nitrate were, respectively, 1.1, 28, and 8.37 mg/L, and for fluoride were 0.014, 2.36, and 0.63 mg/L. The hazard quotient (HQ) values due to nitrate intake were > 1 in 10% of the samples (n = 2) for both infants and children, indicating potential adverse non-carcinogenic health effects upon consumption. For fluoride intake, the potential adverse health effects (HQ > 1) for infants, children, teenagers, and adults were respectively high in 30, 20, 10, and 10% of the samples. For nitrate, the 95th centile for infants was 1.547, and for fluoride, it was 2.62, 2.19, 1.15, and 1 for infants, children, teenagers, and adults, respectively.

Assessment of the management scenarios for groundwater quality remediation of a nitrate-contaminated aquifer

Nitrate contaminant degrades groundwater quality and threatens the health of the humans, livestock, and the environment. Damaneh-Daran aquifer is located at upstream of the Zayandehrood reservoir in west-central Iran. This aquifer has been highly contaminated by nitrate and is still rapidly being contaminated. Thus, its quality needs to be remediated. This paper is focused on the quantity-quality modeling to predict the average nitrate concentration of the aquifer. Several remediation scenarios are presented in a period beginning from fall 2019, ending in spring 2024. These scenarios address several ways to mitigate the injection of the major sources of contamination in the region, such as equipping the urban regions with wastewater collection and treatment plants and reducing the fertilizers' use. The decreased use of the fertilizers may be achieved through two strategies: directly reducing the amount of the fertilizers by several specific and predefined rates of reduction and indirectly decreasing the amount of the fertilizers used by crop pattern modification. The latter strategy is evaluated to replace all or a part of the areas allocated to the more fertilizer-demanding crops with those of the less fertilizer-demanding crops. Furthermore, some of these scenarios are hybridized to more mitigate groundwater quality degradation. The results of performing the proposed scenarios are once compared together and then compared with the trend scenario letting current case study conditions and facilities be held in the future. The results suggest that the scenario hybridizing the effects of the wastewater treatment plants-equipping scenario with those of the quality-enhancing crop pattern modification scenario is evaluated as the most effective and best-performing scenario, implementation of which offers 20% and 30% reduction of the nitrate concentration for the agricultural and urban areas, respectively.