Vulnerability of groundwater from elevated nitrate pollution across India: Insights from spatio-temporal patterns using large-scale monitoring data

Environmental perchlorate, thiocyanate, and nitrate exposures and bone mineral density: a national cross-sectional study in the US adults

Associations of perchlorate, thiocyanate, and nitrate exposures with bone mineral density (BMD) in adults have not previously been studied. This study aimed to estimate the associations of individual and concurrent exposure of the three chemicals with adult BMD. Based on National Health and Nutrition Examination Survey (NHANES, 2011-2018), 1618 non-pregnant adults (age ≥ 20 years and 47.0% female) were included in this study. Survey-weighted linear regression models were used to estimate individual urinary perchlorate, thiocyanate, and nitrate concentrations with lumbar spine BMD and total BMD in adults. Then, weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR) models were conducted to evaluate associations of co-occurrence of the three chemicals with adult BMD. In all participants, nitrate exposure was inversely associated with lumbar spine BMD (β =  - 0.054, 95%CI: - 0.097, - 0.010). In stratification analyses, significant inverse associations were observed in female and participants older than 40 years old. In WQS regressions, significant negative associations of the weighted sum of the three chemicals with total and lumbar spine BMD (β =  - 0.014, 95%CI: - 0.021, - 0.007; β =  - 0.011, 95%CI: - 0.019, - 0.004, respectively) were found, and the dominant contributor was nitrate. In the BKMR models, non-linear dose-response associations of nitrate exposure with lumbar spine and total BMD were observed. These findings suggested that environmental perchlorate, thiocyanate, and nitrate exposure may reduce adult BMD and nitrate is the main contributor.

Human health risk of nitrate in groundwater of Tehran-Karaj plain, Iran

Groundwater pollution by nitrate has is a major concern in the Tehran-Karaj aquifer, Iran, where the wells provide up to 80% of the water supply for a population of more than 18 million-yet detailed human health risks associated with nitrate are unknown due to the lack of accessible data to adequately cover the aquifer in both place and time. Here, using a rich dataset measured annually in more than 75 wells, we mapped the non-carcinogenic risk of nitrate in the aquifer between 2007 and 2018, a window with the most extensive anthropogenic activities in this region. Nitrate concentration varied from ~ 6 to ~ 150 mg/L, around three times greater than the standard level for drinking use, i.e. 50 mg/L. Samples with a non-carcinogenic risk of nitrate, which mainly located in the eastern parts of the study region, threatened children's health, the most vulnerable age group, in almost all of the years during the study period. Our findings revealed that the number of samples with a positive risk of nitrate for adults decreased in the aquifer from 2007 (17 wells) to 2018 (6 wells). Although we hypothesized that unsustainable agricultural practices, the growing population, and increased industrial activities could have increased the nitrate level in the Tehran-Karaj aquifer, improved sanitation infrastructures helped to prevent the intensification of nitrate pollution in the aquifer during the study period. Our compilation of annually mapped non-carcinogenic risks of nitrate is beneficial for local authorities to understand the high-risk zones in the aquifer and for the formulation of policy actions to protect the human health of people who use groundwater for drinking and other purposes in this densely populated region.

Sources and seasonal variations of nitrate in the coastal multiple-aquifer groundwater of Beihai, southern China

Elevated nitrate (NO3-) loadings in groundwater may cause health effects in drinking water and nutrient enrichment of aquatic ecosystems. To reveal the sources and seasonal variations of NO3- in the coastal groundwater of Beihai, southern China, we carried out hydrochemical and isotopic (δ15N-δ18O in NO3-) investigations in the summer and winter, respectively, concerning multiple-aquifer groundwater, rainwater, seawater, and surface water. The sources of the main elements present in the waters were interpreted by ionic ratios. NO3- sources were identified by combined use of the δ15N values and δ18O values or NO3-/Na+ molar ratios, with estimations of the proportional contribution by the Bayesian stable isotope mixing model. Denitrification was interpreted along the flow paths. The results show groundwater main elements are originated primarily from silicate weathering, and secondarily from anthropogenic inputs and carbonate dissolution. Its qualities are largely affected by seawater intrusion along the coastline. Because of difference in the predominant minerals within the aquifers and in scale and extent of seawater intrusion, the groundwater displays distinct ionic ratio characters. NO3- concentrations are up to 33.9 mg/L, with higher loadings in the plains relative to along the coastline. Soil N, domestic sewage, rainwater, chemical fertilizers, and algae are NO3- sources, with average proportional contributions of 0.255, 0.221, 0.207, 0.202, and 0.116, respectively. In relation to the winter, higher production of NO3- from nitrification of soil N- and algae-derived ammonium induced by higher temperatures in the summer accounts for increases in groundwater NO3- loadings. In the rural areas, elevated loadings of NO3- in the winter may be due to larger infiltration fractions of sewage. Seasonal variations of atmospheric NO3- deposition and farming may also cause the dynamics. Our results improve the understanding of sources and seasonal dynamics of NO3- in coastal groundwater.

Occurrence, speciation, and controls on arsenic mobilization in the alluvial aquifer system of the Ghaghara basin, India

High concentrations of arsenic (As) in groundwater are among the long-standing environmental problems on the planet. Due to adverse impacts on the human and aquatic system, characterization and quantification of individual inorganic As species are crucial in understanding the occurrence, environmental fate, behaviour, and toxicity in natural waters. This study presents As concentration and its speciation As(III) and As(V) data, including the interrelationship with other major and trace aqueous solutes from parts of the Ghaghara basin, India. More than half (57%) of the groundwater samples exhibited elevated As concentrations (> 10 μg/L), whereas 67.4% of samples have higher As(III) values relative to As(V), signifying a potential risk of As(III) toxicity. The elevated concentration of As was associated with higher Fe, Mn, and HCO3-, especially in samples from shallow well depth. PHREEQC modeling demonstrates the presence of mineral phases such as hematite, goethite, rhodochrosite, etc. Therefore, it is inferred that the release of As from sediment particles into pore water via microbially mediated Fe/Mn oxyhydroxides, and As(V) reduction processes mainly control high As concentrations. The heavy metal pollution indices (HPI) and (HEI) values revealed heavy metal pollution in low-lying areas deposited by relatively younger sediments along the Ghaghara River. Large-scale agricultural practices, overexploitation of groundwater, and indiscriminate sewage disposal, in addition to geogenic factors, cannot be ruled out as potential contributors to As mobilization in the region. This study recommends conducting seasonal hydrogeochemical monitoring and investigating regional natural background levels of As, to precisely understand the controlling mechanistic pathways of As release.

Analysis of hydrochemical characteristics and assessment of organic pollutants (PAH and PCB) in El Fahs plain aquifer, northeast of Tunisia

The availability of good quality groundwater constitutes a major concern in many developing countries. The El Fahs shallow aquifer, northeastern Tunisia, is an important source of water supply for various economic sectors in the agricultural region. The intensive exploitation of this groundwater has led to its quality degradation. In fact, assessment of water quality degradation is very useful in planning the conservation and management practices of water resources in this watershed. This research aims to evaluate the groundwater quality and its suitability for irrigation uses, identify the main processes to assess their chemical composition, and investigate the potential sources of persistent organic pollutants (POPs). The hydrogeochemical investigation is thus conducted by collecting groundwater samples and analyzing their physicochemical characteristics. Polycyclic aromatic hydrocarbons (16 PAHs) and polychlorinated biphenyls (7 PCBs) were determined in groundwaters from nine stations. The sampling took place in July 2020. The relative abundance of ions was Na > Mg > Ca > K for cations and Cl > SO4 > HCO3 for anions. The groundwater exhibits two predominant hydrochemical facies: Ca-Mg-Cl/SO4 and Na-Cl. The relevant recorded pollutant is nitrate, which was generally far above values of pollution thresholds indicating the influence by the intensive agricultural activity. The suitability for irrigation purposes was assessed using several parameters (EC, SAR, %Na, TH, PI, Mh, and Kr). As a matter of fact, the results mentioned that the majority of the samples are unsuitable for irrigation uses. An analysis of the organic pollutants indicates that the total PAH and PCB concentrations are above the permissible values. Therefore, a considerable predominance of naphthalene and PCB28 was observed in order to discriminate between pyrolitic and petrogenic PAH sources; low-molecular-weight (LPAH)/high-molecular-weight (HPAH) ratio was calculated. Results showed that PAHs were mainly of petrogenic origin. The results revealed also that the chemical composition of groundwater is influenced by evaporation process, ion exchange, and water-rock interaction during the flow. A high risk of organic contamination has been highlighted linked to anthropogenic activities which have exerted increasing pressure on groundwater quality. The presence of organic pollutants in groundwater is becoming a serious threat to the environment and human health.

Geochemistry, stable isotopes and statistic tools to estimate threshold and source of nitrate in groundwater (Sardinia, Italy)

In the European Union, nitrate vulnerable zone (NVZ) should be designed for the mitigation of nitrate (NO₃^-) contamination caused by agricultural practices. Before establishing new NVZ, the sources of NO₃^- must be recognized. A geochemical and multiple stable isotopes approach (hydrogen, oxygen, nitrogen, sulfur and boron) and statistical tools were applied to define the geochemical characteristics of groundwater (60 samples), calculate the local NO₃^- threshold and assess potential sources of NO₃^- contamination in two study areas (hereafter Northern and Southern), located in a Mediterranean environment (Sardinia, Italy). Results of the integrated approach applied to two case study, permits to highlight the strengths of integrating geochemical and statistical methods to provide nitrate source identification as a reference by decision makers to remediate and mitigate nitrate contamination in groundwater. Hydrogeochemical features in the two study areas were similar: near neutral to slightly alkaline pH, electrical conductivity in the range of 0.3 to 3.9 mS/cm, and chemical composition ranging from Ca-HCO₃^- at low salinity to Na-Cl^- at high salinity. Concentrations of NO₃^- in groundwater were in the range of 1 to 165 mg/L, whereas the nitrogen reduced species were negligible, except few samples having NH₄⁺ up to 2 mg/L. Threshold values in the studied groundwater samples were between 4.3 and 6.6 mg/L NO₃^-, which was in agreement with previous estimates in Sardinian groundwater. Values of δ³⁴S and δ¹⁸O_SO4 of SO₄^2- in groundwater samples indicated different sources of SO₄^2-. Sulfur isotopic features attributed to marine SO₄^2- were consistent with groundwater circulation in marine-derived sediments. Other source of SO₄^2- were recognize due to the oxidation of sulfide minerals, to fertilizers, manure, sewage fields, and SO₄^2- derived from a mix of different sources. Values of δ¹⁵N and δ¹⁸O_NO3 of NO₃^- in groundwater samples indicated different biogeochemical processes and NO₃^- sources. Nitrification and volatilization processes might have occurred at very few sites, and denitrification was likely to occur at specific sites. Mixing among various NO₃^- sources in different proportions might account for the observed NO₃^- concentrations and the nitrogen isotopic compositions. The SIAR modeling results showed a prevalent NO₃^- source from sewage/manure. The δ¹¹B signatures in groundwater indicated the manure to be the predominant NO₃^- source, whereas NO₃^- from sewage was recognized at few sites. Geographic areas showing either a predominant process or a defined NO₃^- source where not recognize in the studied groundwater. Results indicate widespread contamination of NO₃^- in the cultivated plain of both areas. Point sources of contamination, due to agricultural practices and/or inadequate management of livestock and urban wastes, were likely to occur at specific sites.

Novel machine learning algorithms to predict the groundwater vulnerability index to nitrate pollution at two levels of modeling

The accurate mapping and assessment of groundwater vulnerability index are crucial for the preservation of groundwater resources from the possible contamination. In this research, novel intelligent predictive Machine Learning (ML) regression models of k-Neighborhood (KNN), ensemble Extremely Randomized Trees (ERT), and ensemble Bagging regression (BA) at two levels of modeling were utilized to improve DRASTIC-LU model in the Miryang aquifer located in South Korea. The predicted outputs from level 1 (KNN and ERT models) were used as inputs for ensemble bagging (BA) in level 2. The predictive groundwater pollution vulnerability index (GPVI), derived from DRASTIC-LU model was adjusted by NO₃-N data and was utilized as the target data of the ML models. Hyperparameters for all models were tuned using a Grid Searching approach to determine the best effective model structures. Various statistical metrics and graphical representations were used to evaluate the superior predictive performance among ML models. Ensemble BA model in level 2 was more precise than standalone KNN and ensemble ERT models in level 1 for predicting GPVI values. Furthermore, the ensemble BA model offered suitable outcomes for the unseen data that could subsequently prevent the overfitting issue in the testing phase. Therefore, ML modeling at two levels could be an excellent approach for the proactive management of groundwater resources against contamination.

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 (GW_NO3 ) 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 GW_NO3 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 GW_NO3 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 GW_NO3 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 GW_NO3 pollution. The outcomes show that the climate factors may impose a significant influence on the GW_NO3 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.

Patterns during Evaporative Crystallization of a Saline Droplet

In the present work, we investigate the influence of substrate wettability and crystal morphology on the evaporative crystallization of saline droplets. On a superhydrophilic substrate, the evaporative crystals formed during the drying of a saline droplet of aqueous potassium nitrate are observed to be long and needle-shaped, oriented along the substrate. The crystal deposits form a flower-shaped pattern when the initial contact angle of the droplet increases to ∼72°. The orientation of the crystals along the triple contact line of the droplet controls the self-amplifying creeping growth of the salt crystals that eventually determines the overall evaporative patterns. The crystals change from being needle-shaped to globular salt deposits as the volume of liquid available for crystallization reduces. We demonstrate that the arrangement of the crystal with respect to the substrate and the droplet-air interface governs the rate of evaporation, growth, and morphology of the crystals.