Influence of tobacco product wastes in a protected coastal reserve adjacent to urbanization.

The present study, conducted at the Kendall-Frost Mission Bay Marsh Reserve in San Diego, California, aimed to assess tobacco-related pollutants in urban waters, a topic with limited prior research. Across 26 events occurring between November 2019 and February 2022, encompassing both wet and dry seasons at two outfall sites (Noyes St. and Olney St.), water and sediment samples were subjected to analysis for nicotine and cotinine levels, with Noyes St. displaying wide variation in nicotine concentrations, reaching a peak of 50.75 ng/L in water samples, whereas Olney St. recorded a peak of 1.46 ng/L. Wet seasons consistently had higher nicotine levels in water, suggesting the possibility of tobacco litter entering the reserve through stormwater runoff. Cotinine was detected in both sites in both water and sediment samples; however, these levels were considerably lower in comparison to nicotine concentrations. Limited research assesses aquatic environmental pollution from tobacco use and disposal, especially in protected areas like urban natural reserves. This study was conducted at the Kendall-Frost Mission Bay Marsh Reserve in San Diego, California, to evaluate tobacco-related pollutants in San Diego's urban waters. Twenty-six sampling events between November 2019 and February 2022, spanning wet and dry seasons at two outfall sites, were conducted. Nicotine and cotinine, a major ingredient of tobacco and its metabolite, were analyzed in the collected water and sediment samples. Nicotine concentrations differed substantially between the outfall locations (Noyes St. and Olney St.), with Noyes St. displaying wide variations, averaging at 9.31 (±13.24) ng/L with a maximum concentration of 50.75 ng/L, and Olney St. at 0.53 (±0.41) ng/L with a maximum concentration of 1.46 ng/L in water samples. In both locations, the nicotine concentrations in water samples were higher during wet seasons than dry seasons, and this pattern was more significant at Noyes St. outfall than at Olney St. outfall, which received not only stormwater runoff but also was connected to Mission Bay. Although this pattern did not directly align with sediment nicotine levels at both sites, maximum nicotine concentration in Noyes St. sediments during wet seasons was approximately 120 times higher than in Olney St. sediments. Regarding cotinine, Noyes St. outfall water averaged 3.17 ng/L (±1.88), and Olney St. water averaged 1.09 ng/L (±1.06). Similar to nicotine, the cotinine concentrations were higher in Noyes St. water and sediment compared to Olney St., but overall, the cotinine concentrations in both water and sediment were much lower than the corresponding nicotine concentrations. The study identifies urban stormwater runoff as a potential source of nicotine and cotinine pollution in a protected reserve, implicating tobacco product litter and human tobacco use as contributing factors.

Prediction of elevated groundwater fluoride across India using multi-model approach: insights on the influence of geologic and environmental factors.

Elevated fluoride in groundwater is a severe problem in India due to its extensive occurrence and detrimental health impacts on the large population that thrives on groundwater. Although fluoride is primarily a geogenic pollutant, existing model-based studies lack the amalgamation of the influence of geologic factors, specifically tectonics, for identifying groundwater fluoride distribution. This drawback encourages the present study to investigate the association of the tectonic framework with fluoride in a multi-model approach. We have applied three machine learning models (random forest, boosted regression tree, and logistic regression) to predict elevated groundwater fluoride based on fluoride measurements across India. The random forest model outperformed other models with an accuracy of 93%. Tectonics was found to be one of the most important predictors alongside "depth to water table." Two major areas of high risk identified were the northwest parts and the south-southeast cratonic peninsular region. The random forest model also performed significantly well over the validation dataset. We estimate that nearly 257 million people are exposed to elevated fluoride risk in India. We endeavor that the findings of our study would be an effective tool for identifying the areas at risk of elevated fluoride and also assist in undertaking effective groundwater management strategies.

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.

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

Agriculture-sourced, non-point groundwater contamination (e.g., nitrate) is a serious concern from the drinking water crisis aspect across the agrarian world. India is one of the largest consumers of nitrogen fertilizers in South-Asia as well as in the world but groundwater nitrate lacks critical attention as a wide-scale drinking water pollutant in the country. Our study provides the first documentation of the distribution of groundwater nitrate and the extent of elevated nitrate contamination across India, along with the delineation of the temporal trends and the natural and anthropogenic factors that influence such occurrence of groundwater nitrate. High resolution, annual-scale spatio-temporal variability of groundwater nitrate concentration and consequent contamination was delineated using groundwater nitrate measurements from ~3 million drinking water wells spread across 7038 administrative blocks between 2010 and 2017 in India. An average 8% of the studied blocks were found affected by elevated groundwater nitrate (> 45 mg/L). Depth-dependent trend demonstrated that nitrate concentrations were about 14% higher in shallow water wells (≤ 35 m) than deep wells (>35 m). The overall temporal trend of groundwater nitrate concentration was decreasing slightly nationwide in the study period. The correlation tests and causality test results indicated that the spatial distribution of groundwater nitrate was significantly associated with agricultural N-fertilizer usage, whereas the decreasing temporal trend corresponded with the overall reduced N-fertilizer usage during the study period. Spatial autocorrelation analysis identified the clustering of high nitrate areas in central, north, and southern India, specifically in areas with higher fertilizer usage. We estimate about 71 million Indians possibly exposed to elevated groundwater nitrate concentrations and the majority of them reside in rural areas. Thus, this study provides the previously unrecognized, wide-scale, anthropogenic, diffused groundwater nitrate contamination across India.

Impact of Covid-19 Lockdown on Availability of Drinking Water in the Arsenic-Affected Ganges River Basin.

The 2020 COVID-19 pandemic has not only resulted in immense loss of human life, but it also rampaged across the global economy and socio-cultural structure. Worldwide, countries imposed stringent mass quarantine and lockdowns to curb the transmission of the pathogen. While the efficacy of such lockdown is debatable, several reports suggest that the reduced human activities provided an inadvertent benefit by briefly improving air and water quality. India observed a 68-days long, nation-wide, stringent lockdown between 24 March and 31 May 2020. Here, we delineate the impact of the lockdown on groundwater and river sourced drinking water sustainability in the arsenic polluted Ganges river basin of India, which is regarded as one of the largest and most polluted river basins in the world. Using groundwater arsenic measurements from drinking water wells and water quality data from river monitoring stations, we have studied ~700 km stretches of the middle and lower reaches of the As (arsenic)-polluted parts of the river for pre-lockdown (January-March 2020), syn-lockdown (April-May), and post-lockdown periods (June-July). We provide the extent of As pollution-free groundwater vis-à-vis river water and examine alleviation from lockdown as an opportunity for sustainable drinking water sources. The overall decrease of biochemical oxygen demand (BOD) and chemical oxygen demand (COD) concentrations and increase of pH suggests a general improvement in Ganges water quality during the lockdown in contrast to pre-and-post lockdown periods, potentially caused by reduced effluent. We also demonstrate that land use (agricultural/industrial) and land cover (urban-periurban/rural) in the vicinity of the river reaches seems to have a strong influence on river pollutants. The observations provide a cautious optimistic scenario for potentially developing sustainable drinking water sources in the arsenic-affected Ganges river basin in the future by using these observations as the basis of proper scientifically prudent, spatially adaptive strategies, and technological interventions.

Occurrence, predictors and hazards of elevated groundwater arsenic across India through field observations and regional-scale AI-based modeling.

Existence of wide spread elevated concentrations of groundwater arsenic (As) across South Asia, including India, has endangered a huge groundwater-based drinking water dependent population. Here, using high-spatial resolution As field-observations (~3 million groundwater sources) across India, we have delineated the regional-scale occurrence of elevated groundwater As (≥10 µg/L), along with the possible geologic-geomorphologic-hydrologic and human-sourced predictors that influence the spatial distribution of the contaminant. Using statistical and machine learning method, we also modeled the groundwater As concentrations probability at 1 Km resolution, along with probabilistic delineation of high As-hazard zones across India. The observed occurrence of groundwater As was found to be most strongly influenced by geology-tectonics, groundwater-fed irrigated area (%) and elevation. Pervasive As contamination is observed in major parts of the Himalayan mega-river Indus-Ganges-Brahmaputra basins, however it also occurs in several more-localized pockets, mostly related to ancient tectonic zones, igneous provinces, aquifers in modern delta and chalcophile mineralized regions. The model results suggest As-hazard potential in yet-undetected areas. Our model performed well in predicting groundwater arsenic, with accuracy: 82% and 84%; area under the curve (AUC): 0.89 and 0.88 for test data and validation datasets. An estimated ~90 million people across India are found to be exposed to high groundwater As from field-observed data, with the five states with highest hazard are West Bengal (28 million), Bihar (21 million), Uttar Pradesh (15 million), Assam (8.6 million) and Punjab (6 million). However it can be much more if the modeled hazard is considered (>250 million). Thus, our study provides a detailed, quantitative assessment of high groundwater As across India, with delineation of possible intrinsic influences and exogenous forcings. The predictive model is helpful in predicting As-hazard zones in the areas with limited measurements.

Achieving Sustainable Development Goal for Clean Water in India: Influence of Natural and Anthropogenic Factors on Groundwater Microbial Pollution.

Worldwide, >2 billion people (~1/3 world population), mostly living in economically stressed areas of Africa and South Asia, still do not have access to basic sanitation, and ~1 billion still practice open defecation. Water pollution due to open defecation may primarily be linked to economy, and other factors such as social and hygiene practices, land use and hydrogeological parameters could also have sufficient influence. The present study describes the effect of human development index (HDI, 2001-2015) and economic development (NL, 1992-2013) on groundwater microbial pollution (FC, 2002-2017) across India. Economic development pattern suggested discernable inverse relationship with FC in most areas, although areas with inferior water quality, improper human practices were found to outweigh economic development. Vulnerability modelling, using these data, along with measured FC in groundwater-sourced drinking water locations (n = 235) demonstrated the heterogeneity of FC distribution potential in areas of homogenous economy, social practices, and land use. High-resolution numerical modelling of the advective transport of the hypothetical FC particles in the aquifers, suggest up to ~24 times faster movement of pollutants under irrigation-induced pumping regimes. Hence, the results of our study highlight and quantify the potential pitfalls that are possible hindrance for achieving the United Nations sustainable development goal, despite social and economic development, across the spatial scales.

Wide exposure of persistent organic pollutants (PoPs) in natural waters and sediments of the densely populated Western Bengal basin, India.

Drinking water stress in South Asia is now widely known as a global paradigm. Extensive geogenic groundwater pollution is known in this area for a long time, specifically in the densely populated (~40 million) Western Bengal basin (WBB) of the state of West Bengal, India. Though anthropogenic-sourced groundwater pollution has been long suspected, it has been only sporadically reported thus far. The present study provides one of the first documentation of widespread existence and distribution of persistent organic pollutants [PoPs, e.g. pesticide (2014-2016) and polycyclic aromatic hydrocarbons (PAHs) (2015)] in the Ganges river (32 locations) water and groundwater (235 locations) of the WBB. All locations were found to have at least one of the 40 detected pesticides [predominated by Atrazine (0.95-3.93 µg/L) and Malathion (150-9330 µg/L)], their derivatives [e.g. Malaoxon (410-1420 µg/L)] and/or 16 PAHs [e.g. Naphthalene (4.9-10.6 µg/L), Phenanthrene (3.32-6.61 µg/L)]. Atrazine and Malathion were found to have concentrations up to 46 times higher than the permissible limits. Similar to pesticides in water, most of the sediment samples investigated obtain Malathion (56-200 µg/kg), malaoxon (>900 µg/kg). Sediment samples collected from 10-20 cm to 20-30 cm depth showed total PAHs concentration of 2.02 and 1.95 µg/kg respectively. While herbicides were found to be more common in agricultural areas, insecticides and PAHs dominate in urban areas, suggesting land-use to be an important controlling factor. An estimated 53% of urban and 44% of rural residents (~20 million total residents, including those in cosmopolitan areas of Kolkata) are potentially exposed to PoPs pollution in drinking water, in addition to much ill-famed geogenic, groundwater arsenic pollution exposure known from this area.

Role of aquifer media in determining the fate of polycyclic aromatic hydrocarbons in the natural water and sediments along the lower Ganges river basin.

Groundwater-sourced drinking water quality in South Asia, specifically India, is extremely stressed, mostly from the presence of many pervasive and geogenic pollutants. The presence and behavior of anthropogenic pollutants like polycyclic aromatic hydrocarbons (PAHs) are poorly investigated on a regional or basin-wide scale. The present study provides one of the first documentation of the presence and behavior of PAH in the aquifer sediments in the Ganges river basin. Lower and medium molecular weight PAHs, e.g., naphthalene, phenanthrene, and fluoranthene were detected in 79, 36, and 13% of samples (n = 25). The PAH level in groundwater was approximately five times lower than river water. The sorption behavior of PAHs were studied in experiments in presence/absence of organic carbon and by simulating advective transport of low to medium molecular weight PAHs, e.g., naphthalene, phenanthrene, and fluoranthene in aquifer sediments collected from agricultural, peri-urban, and urban areas. Naphthalene and phenanthrene adsorbed on quartz and kaolinite, but not on clay minerals like kaolinite. Fluoranthene adsorbed more favorably on kaolinite. Numerical modeling of the advective transport of PAHs in aquifers suggest up to 25 times faster movement of pollutants from irrigation-induced pumping, indicating the strong control of hydraulics on the spatial distribution of PAHs in subsurface.

Author Correction: Impact of sanitation and socio-economy on groundwater fecal pollution and human health towards achieving sustainable development goals across India from ground-observations and satellite-derived nightlight.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Impact of sanitation and socio-economy on groundwater fecal pollution and human health towards achieving sustainable development goals across India from ground-observations and satellite-derived nightlight.

Globally, ~1 billion people, mostly residing in Africa and South Asia (e.g. India), still lack access to clean drinking water and sanitation. Resulting, unsafe disposal of fecal waste from open-defecation to nearby drinking water sources severely endanger public health. Until recently, India had a huge open-defecating population, leading declining public health from water-borne diseases like diarrhoea by ingesting polluted water, mostly sourced to groundwater. However, in recent past, sanitation development to achieve Sustainable Development Goals (SDGs) has been encouraged throughout India, but their effect to groundwater quality and human health conditions are yet-unquantified. Here, for the first time, using long term, high-spatial resolution measurements (>1.7 million) across India and analyses, we quantified that over the years, groundwater fecal coliform concentration (2002-2017, -2.56 ± 0.06%/year) and acute diarrheal cases (1990-2016, -3.05 ± 0.01%/year) have significantly reduced, potentially influenced by sanitation development (1990-2017, 2.63 ± 0.01%/year). Enhanced alleviation of groundwater quality and human health have been observed since 2014, with initiation of acceletated constructions of sanitation infrastructures through Clean India (Swachh Bharat) Mission. However, the goal of completely faecal-pollution free, clean drinking water is yet to be achieved. We also evaluated the suitability of using satellite-derived night-time light (NLan, 1992-2013, 4.26 ± 0.05%/year) as potential predictor for such economic development. We observed that in more than 80% of the study region, night-time light demonstrated to be a strong predictor for observed changes in groundwater quality, sanitation development and water-borne disease cases. While sanitation and economic development can improve public health, poor education level and improper human practices can strongly influence on water-borne diseases loads and thus health in parts of India.