A systematic study on occurrence, risk estimation and health implications of heavy metals in potable water from different sources of Garhwal Himalaya, India

Spatial analysis and soft computational modeling for hazard assessment of potential toxic elements in potable groundwater

Swiftly increasing population and industrial developments of urban areas has accelerated the worsening of the water quality in recent years. Groundwater samples from different locations of the Doon valley, Garhwal Himalaya were analyzed to measure concentrations of six potential toxic elements (PTEs) viz. chromium (Cr), nickel (Ni), arsenic (As), molybdenum (Mo), cadmium (Cd), and lead (Pb) using Inductively Coupled Plasma Mass Spectrometer (ICP-MS) with the aim to study the spatial distribution and associated hazards. In addition, machine learning algorithms have been used for prediction of water quality and identification of influencing PTEs. The results inferred that the mean values (in the units of µg L-1) of analyzed PTEs were observed in the order of Mo (1.066) > Ni (0.744) > Pb (0.337) > As (0.186) > Cr (0.180) > Cd (0.026). The levels and computed risks of PTEs were found below the safe limits. The radial basis function neural network (RBF-NN) algorithms showed high level of accuracy in the predictions of heavy metal pollution index (HPI), heavy metal evaluation index (HEI), non-carcinogenic (N-CR) and carcinogenic (CR) parameters with determination coefficient values ranged from 0.912 to 0.976. However, the modified heavy metal pollution index (m-HPI) and contamination index (CI) predictions showed comparatively lower coefficient values as 0.753 and 0.657, respectively. The multilayer perceptron neural network (MLP-NN) demonstrated fluctuation in precision with determination coefficient between 0.167 and 0.954 for the prediction of computed indices (HPI, HEI, CI, m-HPI). In contrast, the proficiency in forecasting of non-carcinogenic and carcinogenic hazards for both sub-groups showcased coefficient values ranged from 0.887 to 0.995. As compared to each other, the radial basis function (RBF) model indicated closer alignments between predicted and actual values for pollution indices, while multilayer perceptron (MLP) model portrayed greater precision in prediction of health risk indices.

Geospatial analysis of toxic metal contamination in groundwater and associated health risks in the lower Himalayan industrial region

Once known for its clean and natural environment, the lower Himalayan region is now no exception to human-induced disturbances. Rapid industrial growth in Baddi-Barotiwala (BB) industrial region has led to degradation of groundwater resources in the area. Groundwater samples were collected from 37 locations to study the groundwater chemistry, geospatial variation of 15 toxic metals in groundwater, source apportionment, metals of concern and associated health risks in the region. The results showed rock dominated hydrogeology with decreasing order of anion and cation abundance as HCO3- > Cl- > SO42- > NO3- > Br- > F- and Ca+ > Na+ > Mg2+ > K+ > Li+ respectively. Concentrations of Iron (BDL-3.6 mg/l), Nickel (BDL-0.023 mg/l), Barium (0.22-0.89 mg/l), Lead (0.0001-0.085 mg/l) and Zinc (0.006-21.4 mg/l) were found above the permissible limits at few locations. Principal component analysis (PCA) and coefficient of variance (CV) showed both geogenic and anthropogenic origin of metals in groundwater of the BB industrial region. A consistent concentration of Uranium was detected at all the sampling locations with an average value of 0.0039 mg/l and poor spatial variation indicating its natural presence. Overall, non-carcinogenic (N-CR) risk in the study area via oral pathway was high for adults and children (Hazard Index > 1) with geogenic Uranium as the major contributor (Hazard Quotient > 1) followed by Zinc, Lead and Cobalt. Carcinogenic (CR) risk in the region was high for adults having mean value above the threshold (1E-04) with Nickel and Chromium as the metals of major concern. Spatial variation of health risks was overlayed on village boundaries of the region to identify the potential industrial sources of the metals of major concern. The results highlight the need for immediate remediation of groundwater resources in order to achieve a harmonious coexistence between industrialization and human well-being.

Speciation characteristics, ecological risk assessment, and source apportionment of heavy metals in the surface sediments of the Gomishan wetland

Metal contamination is one of the worldwide environmental issues. The main aim of this study was to evaluate the concentration, probable environmental risk, and source of investigated elements (Al, As, Co, Cr, Cu, Fe, Mn, Ni, and Zn) in sediments and water of the Gomishan wetland. Sediment contamination indices revealed sediments were solely polluted by As. The potential ecological risk index (RI), toxic risk index (TRI), and chemical speciation assessments indicated no major ecological hazards for investigated metals. Correlation analysis and principal component analysis (PCA) indicated that all studied metals in the Gomishan wetland sediments derived from natural sources. HPI, and HEI indices showed that the water quality in terms of hazardous components was inappropriate for aquatic life.

Construction of arsenic selective chelating resin with iron precursor for removal of low-concentration arsenic: Breakthrough modeling and field deployment

The presence of exorbitant arsenic contamination in the aquatic environment causes astronomically immense health quandaries affecting millions of people, which may lead to death in the case of prolonged indigestion of arsenic-containing drinking water. Herein, we are reporting porous chelating resin with an iron precursor for the removal of arsenic ions from water. Weak acid cation resin was functionalized under varying experimental conditions to get a suitable resin with high arsenic uptake. The theoretical results revealed that the maximum Langmuir adsorption capacities of 3.27 mg g-1 and 1.13 mg g-1 were achieved for As(V) and As(III), respectively. The kinetics of adsorption followed the pseudo-second-order (PSO) model with a high determination coefficient (R2) of 0.9963 and 0.9895 for As(V) and As(III), respectively. The Adams-Bohart, Thomas, Yoon-Nelson, and Pore diffusion models were used to identify the breakthrough curve in the fixed bed adsorption column. The column performance improved with a larger bed height (55 cm), low concentration of influent (0.25 mg L-1), and low flow rate of influent (80 mL min-1). Under this condition, the breakthrough time and exhaustion time were 314 min and 408 min for As(V) and 124 min and 185 min for As(III), respectively.

Occurrences, sources and health hazard estimation of potentially toxic elements in the groundwater of Garhwal Himalaya, India

High concentrations of potentially toxic elements (PTEs) in potable water can cause severe human health disorders. Present study examined the fitness of groundwater for drinking purpose based on the occurrence of nine PTEs in a heavy pilgrim and tourist influx region of the Garhwal Himalaya, India. The concentrations of analyzed PTEs in groundwater were observed in the order of Zn > Mn > As > Al > Cu > Cr > Se > Pb > Cd. Apart from Mn and As, other PTEs were within the corresponding guideline values. Spatial maps were produced to visualize the distribution of the PTEs in the area. Estimated water pollution indices and non-carcinogenic risk indicated that the investigated groundwater is safe for drinking purpose, as the hazard index was < 1 for all the water samples. Assessment of the cancer risk of Cr, As, Cd, and Pb also indicated low health risks associated with groundwater use, as the values were within the acceptable range of ≤ 1 × 10-6 to 1 × 10-4. Multivariate statistical analyses were used to describe the various possible geogenic and anthropogenic sources of the PTEs in the groundwater resources although the contamination levels of the PTEs were found to pose no serious health risk. However, the present study recommends to stop the discharge of untreated wastewater and also to establish cost-effective as well as efficient water treatment facility nearby the study area. Present work's findings are vital as they may protect the health of the massive population from contaminated water consumption. Moreover, it can help the researchers, governing authorities and water supplying agencies to take prompt and appropriate decisions for water security.

Investigation of heavy metal contamination and associated health risks in groundwater sources of southwestern Punjab, India

Human body exposure to various toxic and non-toxic heavy metals in groundwater is a significant health concern, especially in developing countries. The present study was planned and carried out to appraise the potential health risks of eight heavy metals (Mn, Co, Cu, As, Se, Cd, Hg, and Pb) in different water sources of the Mansa and Muktsar districts of Punjab. The measurements of heavy metals were performed using the inductively coupled plasma mass spectrometry (ICPMS) technique. The health (carcinogenic and non-carcinogenic) risks and doses (ingestion and dermal) associated with exposure to heavy metals in water were estimated from the measured concentrations using USEPA guidelines. The average concentrations of heavy metals were observed in the order of Mn (13.93) > Cu (13.12) > Se (4.14) > As (3.28) > Hg (3.27) > Pb (1.29) > Co (0.20) > Cd (0.10) μg L^-1. The results show that the Hg, Pb, As, and Se concentrations are above the guideline values of the World Health Organization (WHO) in 10.34%, 3.45%, 6.90%, and 6.90% locations, respectively. The high values of these heavy metals may be due to geogenic anthropogenic activities. The hazard quotients (non-carcinogenic risk) for ingestion and dermal exposures were observed in the range of 0.32-3.79 and 8.05 × 10^-6-1.34 × 10^-4, respectively. On the other hand, the carcinogenic health risks due to ingestion and dermal exposure were observed to be 0.02-0.38 and 6.67 × 10^-8-1.15 × 10^-6, respectively. The results of this study will be helpful to the drinking water supplying agencies, water resource development authorities, etc.

Deterministic and Probabilistic Health Risk Assessment of Toxic Metals in the Daily Diets of Residents in Industrial Regions of Northern Ningxia, China

This study was designed to investigate the toxic metal (aluminum (Al), arsenic (As), chromium (Cr), cadmium (Cd), copper (Cu), nickel (Ni), lead (Pb), and zinc (Zn)) concentrations in drinking water and different foodstuffs meat (pork, beef, and mutton), cereals (rice, flour, corn, millet), beans (cowpeas, tofu), potatoes (potato, sweet potato), solanaceous fruits (pepper, eggplant, bitter gourd, cucumber), vegetables (cabbage, cauliflower, spinach), and fruits (apples, watermelons, pears, grapes)) and then estimate the potential health risks of toxic metal consumption to local residents in industrial regions of northern Ningxia, China. As in drinking water, Cr in meat, Pb in cereals, Pb in beans, As and Pb in potatoes, Pb in solanaceous fruits, Cr and Ni in vegetables, and Ni and Pb in fruits were the most contaminated heavy metals in the corresponding food with over-standard rates of 16.7%, 12.5%, 5.1%, 60%, 50%, 50%, 38.2%, 44.4%, 44.4%, 31.8%, and 31.8%, respectively.The results of the deterministic assessment of health risks showed that the total noncarcinogenic risk value of dietary intake of toxic metals by the local population was 5.6106, indicating that toxic metals pose a high noncarcinogenic risk. The order of the non-carcinogenic risk is HI_cereal (1.2104) > HI_{solanaceous fruit} (0.9134) > HI_Vegetables (0.8726) > HI_Fruit (0.8170) > HI_Meat (0.7269) > HI_{Drinking water} (0.6139) > HI_Beans (0.2991) > HI_Potatoes (0.1573). The total carcinogenic health risk from exposure to toxic metals through dietary intake was 9.98 × 10^-4, indicating that the total cancer risk value of residents is beyond the acceptable range (10^-4) under the current daily dietary exposure and implies a high risk of cancer. The order of the carcinogenic risk is R_{Drinking water} (2.34 × 10^-4) > R_Meat (2.11 × 10^-4) > R_{solanaceous fruit} (1.89 × 10^-4) > R_Fruit (1.88 × 10^-4) > R_cereal (1.36 × 10^-4) > R_Potatoes (2.44 × 10^-5) > R_Vegetables (1.51 × 10^-5) > R_Beans (0). The probabilistic assessment results showed that 98.83% of the population is exposed to severe noncarcinogenic risk and 87.02% is exposed to unacceptable carcinogenic risk. The sensitivity analysis showed that drinking water, local cereals, vegetables, and fruits were the major contributors to health risks. Our results indicated that the daily dietary exposure of residents in industrial regions of northern Ningxia poses a serious threat to human health, and it is suggested that relevant departments should strengthen monitoring and control of the current situation of toxic metal pollution in the environment and continue to pay attention and take measures to reduce the exposure of toxic metals in the diets of residents in this area.