Geochemical processes and groundwater quality assessment in the Yamuna-Hindon interfluve region of Bagpat district, Western Uttar Pradesh, India

The present research work aims to understand the geochemistry of groundwater resources of the Yamuna—Hindon interfluve region of Bagpat district, Western Uttar Pradesh, India. The region is a part of Indo-Gangetic belt, one of the world's most fertile and intensely farmed areas. To investigate the geochemical processes governing groundwater quality, a total of 105 groundwater samples were collected during pre-monsoon season and analyzed for various physico-chemical parameters, namely, pH, electrical conductivity (EC), total dissolved solid (TDS), total hardness (TH), turbidity, major anions (HCO₃⁻, SO₄²⁻, F⁻, Cl⁻, NO₃⁻)_, cations (Ca²⁺, Mg²⁺, Na⁺, K⁺) following the methods outlined in the American Public Health Association (APHA). The dissolved heavy metals (Fe, Mn, Zn, Pb, Cu, Cr, Ni, As, Se, Co, Cd and Al) in groundwater were analyzed by ICP-MS following the instrument manual. The analysis results revealed that the groundwater is pre-dominantly neutral to mildly alkaline in nature. The major cation chemistry majorly followed the occurrence pattern of Na⁺ > Mg²⁺ > Ca²⁺ > K⁺, while for anions it was HCO₃⁻ > Cl⁻ > SO₄²⁻ > NO₃⁻ > F⁻. The data plotted on Piper triangular diagram indicated that Ca²⁺-Mg²⁺-HCO₃⁻ and Na⁺-K⁺-HCO₃⁻-Cl⁻ were major hydrogeochemical facies. Weathering of rock-forming minerals mainly governed the groundwater geochemistry in this region, although part of the cations associated with Cl⁻, F⁻ and NO₃⁻ may originate from anthropogenic sources. TDS, TH, turbidity and F⁻ were identified as the major parameters that violated the prescribed limits for drinking water. Most of the heavy metals were found within the drinking water prescribed limits except for Fe, Mn, Al and Se. Elevated salinity, %Na, and magnesium hazard (MH) at certain sites limit its suitability for agricultural use. The assessment of selected organochlorine and organophosphorus pesticides in five samples indicated presence of lindane, β-endosulfan and DDT isomers in few samples. However, a detailed investigation of possible pesticide contamination in this intensive agriculture area is required before drawing any final conclusions.

Groundwater is the ultimate and most suitable freshwater resource for human consumption in both urban as well as rural areas. 80% of the rural population and 50% of the urban population in India are using groundwater for domestic purposes [1]. More than 60% of irrigated agriculture and 85% of drinking water supplies are dependent on groundwater sources [2]. There are several states in India where more than 90% population is dependent on groundwater for drinking and other purposes. Increased groundwater abstraction especially after the green revolution and intensive multiple-crop agricultural practices make India a global leader in groundwater-fed irrigation [3,4,5]. Rapid growth in population, haphazard industrialization, unplanned urbanization, and intensive use of groundwater in irrigation coupled with increased human activities pose a great threat to the quality and quantity of groundwater resources in many parts of India [6, 7]. In the last few years, great success has been achieved in providing safe drinking water to a large population in India but a new problem of contamination and depletion of freshwater aquifers arises due to human-induced activities and mismanagement of water resources. As per the NITI Aayog report [8], India is undergoing the worst water crisis in its history and nearly 600 million people are facing high to extreme water stress. The report estimates that around 70% of fresh water is contaminated, and around two lakh people die every year due to inadequate access to safe water. Today, many parts of India are facing serious problems of water level depletion and groundwater contamination by arsenic (As), fluoride (F⁻), nitrate (NO₃⁻), chromium (Cr), iron (Fe) and pesticides [9,10,11,12,13,14,15,16]. Safe drinking water is an internationally accepted human rights, therefore, the issue of sustainability and quality maintenance of supplied drinking water is an area of great concern for the country.

The Indo-Gangetic plains are the world's most fertile and intensely farmed areas and have a significant contribution to the Indian agricultural economy. Indo-Gangetic plains are characterized by highly productive multi-aquifer systems and constitute the most potential and productive groundwater reservoir. At the same time, Indo-Gangetic Plains are also ranked among the world’s most densely populated areas and the majority of the water sources in this region are considered at high risk due to aquifer overexploitation and anthropogenic activities [17, 18]. Overexploitation of groundwater resources and enhanced agricultural and industrial activities in the Indo-Gangetic belt causes water table depletion and deterioration in the quality of water resources. This has not only created a problem of potable water availability but also the availability of safe irrigation water. This has led to a number of studies related to aquifer characterization and groundwater quality status in the Indo-Gangetic plain [19,20,21,22,23,24,25]. The present study employed an integrated approach to evaluate the physicochemical characteristics of groundwater resources in the Yamuna-Hindon interfluve region of the Bagpat district, Uttar Pradesh and to assess geochemical processes controlling the groundwater composition and its suitability for drinking, irrigation and industrial uses. The study further apportions groundwater contaminants into geogenic and anthropogenic components based on relative concentration abundance, elemental ratios, partial correlation and principal component analysis.

Study area

Bagpat district is a part of Yamuna—Hindon doab in the Yamuna sub-basin of the Indo-Gangetic plain on the north-western part of Uttar Pradesh state, India. The district is bounded by 28°47′ to 29°18′N latitude and 77°07′ to 77°75′E longitude, covering an area of 1321 km². District Muzaffarnagar lies on its north, Ghaziabad district in the south, Meerut on its east, and Sonipat district of Haryana on the west (Fig. 1). The river Yamuna separates the district boundary on the western side with the Haryana state and river Hindon limits the eastern boundary of the district. Bagpat is 48 km away from India’s capital New Delhi and is a part of the National Capital Region (NCR). It is one of the major agrarian districts of Uttar Pradesh State, known for its sugar cane production. Agricultural land is the dominant land use, comprising 82% of the total land area of the district. The Yamuna canal flows in the central part of the district from north to south. The general elevation of the area varies from 218 to 233 m above mean sea level and a slightly higher elevation in the central part of the district act as a water divide between the Yamuna and Hindon sub-catchment [26]. The older alluvial plain is the oldest geomorphic unit, covering about 80% of the district area. The older flood plain is limited to the higher elevation zones and occurs as narrow curvilinear, lenticular patches along with the courses of the Yamuna and Hindon Rivers.

Location map of Bagpat district showing water sampling sites

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The major part of the district is covered by thick alluvial sediments deposited by the Yamuna and Hindon Rivers. Basically, the deposited sediments are an admixture of clay, silt and fine to coarse sand [26, 27]. Central Ground Water Board [28] identified three aquifers in the region at a depth of 0.0–125, 130–260 and 275–425 m below the ground (mbgl) and designated them as aquifers I, II and III respectively. The aquifer-I is generally consisting of comparatively coarser material than the deeper aquifer and is the main productive unit catering to the major water requirement of the area. The average rainfall of the area is 768 mm, out of which 90% of rainfall occurs during June to September months. Rainfall is the main source of groundwater recharge. The other sources of groundwater replenishment are infiltration from the river, return seepage from irrigation and inflow from neighboring areas. Dug wells (8–25 m deep) and shallow to deep tube wells (70–110 m) are the major water tapping units. Ground water occurs under confined to semi-confined conditions in aquifer-I and confined conditions in deeper aquifers i.e. aquifer-II and III. The depth of groundwater level in the area varies from 4.71 to 32.03 mbgl in pre-monsoon and 4.72 to 32.08 mbgl. Water levels are relatively shallow in the vicinity of the Yamuna and Hindon Rivers and along the Yamuna canal as compared to other parts of the district.

Sampling and analytical procedures

Groundwater samples were collected from hand pumps and tube wells at 105 pre-selected sampling locations in the Bagpat district during the pre-monsoon season (April, 2015). The geographical locations of sampling sites were recorded with the help of the Global Positioning System (Fig. 1). The hand pumps/tube wells were pumped for 3–5 min before collecting groundwater samples in 500 ml narrow-mouth high-density polypropylene bottles. For heavy metal and cation analysis, 100 ml water samples were preserved with supra pure HNO₃ after filtration. Electrical conductivity (EC) and pH were measured at the site with a portable EC/pH meter (Eutech) and turbidity by Turbidity Meter (Eutech TN-100). Water samples were filtered using 0.45 µm Millipore membrane filters with the help of a vacuum pump and preserved at 4 °C for further analysis. All analyses were completed within ten days after sampling following the standard protocols described in APHA [29]. The total dissolved solids (TDS) were determined by gravimetric method, in which a 100 ml water sample was evaporated at 180 °C until a constant weight of the dissolved solids residue was obtained. The TDS value was calculated by determine the weight difference between the empty beaker and the beaker containing the dried residue [29]. The concentration of bicarbonate (HCO₃⁻) was estimated by the acid titration method while the concentrations of other major anions (SO₄²⁻, F⁻, Cl⁻, NO₃⁻) were determined by ion chromatograph (Dionex IC-900) after calibrating with known standard solutions. Atomic absorption spectrophotometer (AAS) was used for estimating major cations (Ca²⁺, Mg²⁺, Na⁺, K⁺) concentration in flame mode. Concentrations of heavy metals (Fe, Mn, Zn, Pb, Cu, Cr, Ni, As, Se, Co, Cd and Al) in water samples were determined by ICP-MS (Perkin Elmer, Elan DRC_e). Five groundwater samples collected from at vicinity of agricultural fields were also analyzed for selected organo-chlorine and organo-phosphorus pesticides following the standard protocol [29]. GC–MS (Varian), equipped with Ni-63 micro-electron capture detector (GC-ECD) was used for pesticide analyses. Helium (1.2 ml min⁻¹) and high purity N₂ (40 ml min⁻¹) were used as a career and make-up gas respectively.

Quality control

The data quality assurance for major ions analysis was checked by computing charge balance error (CBE) using Eq. 1. The CBE was found to be within ± 5% for each water sample. While heavy metals analytical data was validated by performing Certified Reference Material (CRM) of water standard such as 1640a and 1643 provided by National Institute of Standards and Technology (NIST), USA. The recovery of CRM was 95.3% to 105% which supported the accuracy of the results (Table S-1). Simultaneously, calibration blank and calibration verification standards were also analyzed after every 15 samples to verify the calibration status of the running instrument.

Correlation and principal component analysis

Multivariate statistical techniques, such as factor analysis in conjunction with correlation analysis, have been extensively employed in recent years to pinpoint the origins of heavy metals and major solutes as well as to identify the possible mechanisms and processes influencing groundwater quality [30]. The multivariate statistical analyses such as correlation matrix and principal component analysis (PCA) were performed using SPSS software by compiling the selected water quality parameters such as pH, TDS, TH, TA, turbidity, major ions (SO₄²⁻, F⁻, Cl⁻, HCO₃⁻, NO₃⁻, Ca²⁺, Mg²⁺, Na⁺ and K⁺) and heavy metals (Fe, Mn, Zn, Pb, Cu, Cr, Ni, As, Se, Co, Cd and Al) together to implicate their specific sources in groundwater environment. The KMO (Kaiser–Mayer–Olkin) threshold (˃ 0.5) and the significance level (< 0.05) in Bartlett’s test favoured the method’s reliability for the groundwater samples. Principal components were extracted using an eigenvalue greater than one, and to compute rotational factor loadings, the varimax normalized approach was applied.

Water quality indices for irrigation and industrial applications

Complex agricultural water quality management requires comprehensive regulations, as well as ongoing monitoring, improvement, and control of water resource contamination [31]. Defining water quality through an indexing approach is a widely used tool in the agricultural domain. Simultaneously, characterizing the scaling and corrosion properties of the water can be helpful in managing water quality for industrial sectors [32]. By addressing these water quality parameters, industrial plants can last longer, reduce the expenses associated with rebuilding pumps, pipes, and other equipment, and improve the efficiency of appliances. To assess the suitability of water quality for irrigation and industrial applications, various indices are calculated using different equations, which are summarized in Table 1.

A statistical summary of the analytical data, including various groundwater quality parameters and their comparison with BIS [33] drinking water standards, is presented in Table 2. Figure 2 illustrates a boxplot that displays the variations in the concentrations of the measured parameters in the groundwater of the Bagpat district.

Boxplots of measured parameter concentration in groundwater of the Bagpat district

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pH, EC, TDS, TH and turbidity

The groundwater of Bagpat district was neutral (7.05) to alkaline in nature (8.69) with a mean pH of 7.68. The distribution was found to be near normal but slightly skewed to the left. The electrical conductivity (EC) of groundwater varied widely from 426 to 3278 µS cm⁻¹ (mean 1152 µS cm⁻¹). The EC distribution was also left skewed but far from normal. Interestingly, in some locations, EC was very high (> 3000 µS cm⁻¹), rendering the water unsuitable for agricultural use. The spatial variation of total dissolved solids (TDS) followed a similar trend to that of EC and exceeded the BIS [33] drinking water acceptable limit of 500 mg l⁻¹ in about 82% of groundwater samples. The TDS value in one groundwater sample (W-98, Sarikod village) exceeded the maximum drinking water permissible limit of 2000 mg l⁻¹.

Total hardness (TH) is a water quality parameter primarily governed by two divalent cations namely, Ca²⁺ and Mg²⁺, although other cations may also contribute at some extent. Groundwater is characterized as soft (TH < 75 mg l⁻¹), moderately hard (TH 75–150 mg l⁻¹), hard (TH 150–300 mg l⁻¹) and very hard water (TH > 300 mg l⁻¹) types [34]. TH values in the groundwater samples ranged from 86 mg l⁻¹ to 1064 mg l⁻¹ and exceeded BIS [33] drinking water acceptable limit of 200 mg l⁻¹ in 81% of water samples (Table 2). Although water hardness does not pose a direct effect on health, but it can cause CaCO₃ precipitation in the distribution network, impairing water flow. Scale formation in appliances using hard water reduces energy efficiency and also inhibits lather formation, thereby making soap less effective. There is some evidence from epidemiological studies for a protective effect of magnesium or hardness on cardiovascular mortality, however the evidence is being debated and does not prove causality [35]. The concentration contours plotted of TDS and TH indicated relatively higher values in the wells located along the Yamuna River, especially on the south-western side, indicating lateral inflow of contaminated water from nearby river channels (Fig. 3a, b).

Concentration contour maps of TDS, TH, F⁻, Fe, Mn and Al

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The bivariate plot between total hardness (TH) and total dissolved solids (TDS) shows that around 58% of water samples have TH values > 300 mg l⁻¹ and data points fall in the hard to very hard water zone (Fig. 4) [36]. Similarly, TDS content in 80% of the analyzed water samples was < 1000 mg l⁻¹, classified into freshwater category [37, 38]. TDS and TH values exceeded the limits of 1000 mg l⁻¹ and 300 mg l⁻¹ limits in about 20% and 58% of the total analyzed samples respectively and categorized into brackish and very hard water categories. The spatial differences in the TDS and TH are mainly due to variations in the geochemical nature of the aquifer, hydrological setup of the area and human-induced interruptions [39]. Generally, water having TH > 200 mg l⁻¹ and TDS > 500 mg l⁻¹ is supposed to be unsuitable for drinking purposes [33].

Water classification based on concentration of Total Dissolved Solid and Total Hardness

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Turbidity is an important physical parameter for assessing drinking water suitability and represents the cloudiness or haziness of a solution caused by suspended particles and often invisible to the naked eye. Turbidity in open water may be caused by the growth of phytoplankton. High turbidity reduces the efficacy of disinfectants like chlorination, it shields microorganisms from inactivation [40] and reduces UV light transmission in UV light disinfection [41, 42]. It also reduces the aesthetic acceptability of drinking water. In the Bagpat groundwater, the turbidity ranged between 0.30 and 20.95 NTU with an average value of 1.32 NTU. It exceeded recommended drinking water acceptable value of 1 NTU in 39% of samples and the maximum permissible limit of 5 NTU in three groundwater samples (Table 2).

Major ion chemistry

Piper [43] trilinear plot drawn with AQUACHEM software for the Bagpat groundwater samples shows that the majority of plotted points fall in the Na⁺ + K⁺ dominant zone and no dominant zones in the bottom left cation triangle (Fig. 5). Combined mapping of cations and anions into the central diamond-shaped block revealed that the major hydrogeological facies in Bagpat groundwater are Ca²⁺-Mg²⁺-HCO₃⁻ (77%), Na⁺-K⁺-HCO₃⁻-Cl⁻ (12%), Na⁺-K⁺-HCO₃⁻ (5%), Ca²⁺-Mg²⁺-Cl⁻-SO₄²⁻ (4%) and Na⁺-Cl⁻ (2%) [44]. Abundance order of major cations was observed as Na⁺ > Mg²⁺ > Ca²⁺ > K⁺. Similarly, from the anion triangle at the right bottom, one might infer that HCO₃⁻ was the dominant anion in the majority of the water samples and it followed the abundance order of HCO₃⁻ > Cl⁻ > SO₄²⁻ > NO₃⁻ > F⁻.

Piper plot showing water type and hydrochemical facies

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Calcium (Ca²⁺) alone accounted for 26.3% of the total cationic charge balance (TZ⁺) while 32% was contributed by Mg²⁺. Interestingly, the average Na⁺ concentration (107.8 mg l⁻¹) was much higher than Ca²⁺ (63.2 mg l⁻¹) and Mg²⁺ (46.2 mg l⁻¹) contrary to usual observations (Fig. 2a). Na⁺ contribution towards total cations (TZ⁺) was 40%, higher than Ca²⁺ and Mg²⁺. Expectedly, the average K⁺ concentration (7.5 mg l⁻¹) was the lowest one, accounting for < 2% of the TZ⁺. The less contribution of K⁺ towards total cationic balance indicates its lower geochemical mobility and adsorption on clay. Weathering of rock-forming minerals and cation exchange processes normally control the levels of these cations in the groundwater. Natural sources contribute more calcium and magnesium to the environment than all anthropogenic sources. Carbonate minerals in sedimentary rocks and aluminosilicate and ferromagnesian minerals in igneous rocks are the major sources of Ca²⁺ and Mg²⁺ in natural water. The concentration of Ca²⁺ and Mg²⁺ exceeded the drinking water acceptable levels of 75 and 30 mg l⁻¹ in about 31% and 76% of all analyzed groundwater samples (Table 2). Though calcium is an essential element for the development of cells, bone and nervous systems but ingestion of calcium-rich water for a longer period may pose a risk of kidney stones.

With regards to anions, bicarbonate (HCO₃⁻) concentration varied from 231 to 897 mg l⁻¹ (mean 484 mg l⁻¹) and account for 71% of the total anionic (TZ⁻) charge equivalence (Table 2, Fig. 2a). Contributions of Cl⁻ and SO₄²⁻ to TZ⁻ were 16.3% and 10.7% respectively. Bicarbonate in water is mainly sourced from the interaction of CO_2, derived from the decay of organic matter and root respiration with rainwater and the dissolution of carbonates and silicate minerals by carbonic acid [45]. The chloride (Cl⁻) concentration in the groundwater of the Bagpat district varied between 6.4 and 350.6 mg l⁻¹ with an average value of 77.2 mg l⁻¹. Sulphate (SO₄²⁻) concentration exceeded the drinking water acceptable limit of 200 mg l⁻¹ in 7% of the analyzed groundwater samples (Table 2). High SO₄²⁻ content in some of the samples might be attributed to both geogenic and anthropogenic sources. Oxidative weathering of sulphur bearing minerals such as pyrite and gypsum might contribute sulphate geogenically, while the application of sulphatic soil conditioners and fertilizers is the major anthropogenic source of SO₄²⁻ in groundwater.

Weathering of halite, evaporite, and rainwater are natural sources of Cl⁻ in groundwater, whereas major anthropogenic sources include fertilizers, animal wastes, and leachates from industrial waste [46]. The concentration of Cl⁻ exceeded the prescribed drinking water limit of 250 mg l⁻¹ in only two groundwater samples. However, non-uniform spatial variation and enhancement in Cl⁻ concentrations at some sites indicate local recharge of domestic and industrial wastewater from nearby sources. Contributions of nitrate (NO₃⁻) and fluoride (F⁻) to the anionic charge balance (TZ⁻) are relatively low (< 4%). NO₃⁻ concentrations exceeded the drinking water acceptable limit (45 mg l⁻¹) at two sites (22 and 88). Higher NO₃⁻ concentrations at these sites are likely related to localized anthropogenic activities involving septic systems, application of agricultural fertilizers, and livestock manure [47]. Fluoride concentrations varied from 0.17 to 4.34 mg l⁻¹, exceeding the drinking water acceptable limit of 1.0 mg l⁻¹ in about 32% of samples (Table 2). Fluoride is considered an essential element for the normal development of teeth and bones, but prolonged consumption of high-fluoride water may cause dental and skeletal fluorosis, such as mottling of teeth, ligament deformation, and spinal cord bending [33, 48]. The origin of fluoride may be traced back to the weathering of fluoride-bearing minerals like muscovite, biotite, fluorite, and fluoro-apatite. Phosphatic fertilizers from agricultural runoff might be another anthropogenic source of fluoride in the study area. The concentration contour plot of F⁻ shows relatively higher concentrations in the north-central part of the district, which is distinct from the patterns of TDS, TH, Fe, and Mn, and probably sourced from the anthropogenic activities like application of phosphatic fertilizers and agricultural runoff (Fig. 3c).

Heavy metal and pesticide distribution

Statistical summary of heavy metal concentrations in the analyzed groundwater samples is present in Table 2, including specified drinking water limits and the percentage of samples exceeding those limits. Figure 2b visually displays the selected heavy metal concentration range using box plots. Some heavy metals, such as manganese (Mn), zinc (Zn), copper (Cu), arsenic (As) and aluminum (Al) were grouped in the relaxable category and these were assigned two limiting values in Indian drinking water norms under BIS [33] i.e. (i) Acceptable limit (ii) Permissible limit in the absence of alternate source. Some metals such as iron (Fe), chromium (Cr), lead (Pb), selenium (Se), nickel (Ni) and cadmium (Cd) were grouped under the non-relaxable category and assigned only one limiting value. It is apparent from Table 2 that with regards to heavy metals, Fe, Mn, Al, Cr and Se posed quality issues in Bagpat groundwater. The concentration contour plots of Fe, Mn and Al show relatively higher values in the southern part of the district which also support the lateral infusion of contaminated water from nearby Yamuna and Hindon River channels (Fig. 3d, e, f). Fe concentrations exceeded the limiting value of 300 µg l⁻¹ in 84% of groundwater samples. The rationale for assigning non-relaxable status to Fe with a limiting value of 300 µg l⁻¹ in BIS [33] was questioned by some authors [49]. The concentration of Al and Mn also exceeded the drinking water acceptable limit of 30 µg l⁻¹ and 100 µg l⁻¹ in 36% and 21% of groundwater samples respectively. It was interesting to note that Fe and Mn co-occurred in 20% of samples at concentrations above the highest acceptable level. Corresponding data for Fe-Al were 36%, Mn-Al 7% and Fe–Mn-Al 7%. This observation strongly underlined the possibility of Fe, Mn and Al emanating from the same source, presumably from anthropogenic sources such as effluents from metal processing industries, besides contribution from geogenic sources.

Pollution problem associated with pesticide application is one of the serious issues in India and groundwater contamination by pesticides may take place from multiple sources such as pest control chemicals, sewer and septic tank leakage, industrial wastewater, agricultural runoff and landfill leaching [50]. Of all these, the residual fraction of the pesticides applied in fields to ward off pests, insects, fungus etc., are transported by surface run-offs which eventually percolate through the vadose zone [51]. Because of their non-biodegradable nature, these residual pesticides remain in the vadose zone for a very long time and eventually contaminate groundwater as well [52]. Unfortunately, India is among the few countries that are still producing and using some of the restricted chlorinated pesticides such as DDT and lindane [53, 54]. Uttar Pradesh is the second largest pesticide-consuming state after Maharashtra in India [55].

In this study, we have analyzed five groundwater samples for a number of organochlorine and organophosphorus pesticides and the results have been tabulated in Table 3. Organo-chlorine pesticides comprised α-HCH, β-HCH, δ-HCH, γ-HCH (lindane), DDT (o,p-DDE, p,p-DDE, o,p-DDD, p,p-DDD, o,p-DDT, p,p-DDT), dieldrine, α-endosulfan and β-endosulfan. Organo-phosphorous pesticide groups included methyl parathion, malathion, and chlorpyrifos. In the organochlorine group, γ-HCH (lindane) was present in all the samples but its other isomers such as α-HCH, β-HCH and δ-HCH were conspicuously absent. The concentration of γ-HCH ranged from 0.07 to 0.10 µg l⁻¹, which was much lower than the IS-10500 [33] acceptable limit of 2.0 µg l⁻¹. All isomers of DDT except for o,p-DDE were present in all the samples. The concentration of total DDT in four samples was less than the permissible limit, however, at one place (Tikris) its concentration (4.46 µg l⁻¹) was higher than the permissible limit of 1.0 µg l⁻¹. Dieldrin concentration varied between < 0.01 and 5.93 µg l⁻¹, the highest being found at Tikris (5.93 µg l⁻¹), which was much above the permissible limit of 0.03 µg l⁻¹. Trace β-endosulfan was detected at the Tikris site but it is much below the permissible limit. Organophosphorus pesticides were either absent or present much well below the permissible limit. The concentrations of methyl parathion and chloropyrifos ranged between 0.07—0.09 µg l⁻¹ and 0.38—12.4 µg l⁻¹ respectively. Malathion concentration was negligible in the analysed samples. It must be noted with caution that only five groundwater samples were examined for possible pesticide contamination in this study. Though pesticide contamination in groundwater apparently appeared not to be alarming but present study provides enough justification for undertaking a detailed investigation on possible pesticide contamination in Bagpat groundwater.

Weathering and hydrogeochemical processes

Groundwater chemical composition is governed by a number of factors including recharge water composition, mineralogy of the soil and aquifer rocks, land use of the area, aquifer structure, subsurface flow patterns and sea proximity. Various natural geochemical processes such as rock weathering, evapotranspiration, precipitation, oxidation/reduction, cation exchange, water mixing and anthropogenic activities influence groundwater chemistry [13, 46]. Generally, aquifer recharge water whether it is rain or river water has low concentrations of dissolved salts. The dissolved load increases as infiltrating water leaches natural salts from the rocks and soil profile during downward movement. The relative concentration of various dissolved ionic species in groundwater is determined by their abundance in the host rocks and solubility of the source minerals [21, 56, 57]. The hydrogeochemical data of any region can be used to gain insight into the possible sources of dissolved ions in water. Gibbs [58] boomerang diagrams of TDS Vs (Na⁺ + K⁺)/(Na⁺ + K⁺ + Ca²⁺) and TDS Vs Cl⁻/(Cl⁻ + HCO₃⁻) can be used to deduct the functional sources of dissolved ions such as precipitation, rock weathering and evaporation in groundwater (Fig. 6). Mapping of all the plotted points of Bagpat groundwater in the middle part of the boomerang plot affirmed weathering of rock-forming minerals as the primary geochemical process that control the groundwater chemistry of this region.

Gibbs diagrams, illustrating the mechanisms controlling groundwater chemistry

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Interestingly, two major water types could be observed in Bagpat groundwater with reference to alkali (Na⁺ + K⁺) and alkaline earth metal (Ca²⁺ + Mg²⁺) ions. In about 70% water samples, alkaline earth metal exceeded alkali while in the rest 30% it was the reverse (Fig. 5). This was a clear pointer toward the role of the cation exchange process in controlling the major ion chemistry. This can be further verified by plotting the data on a bivariate plot of (Ca²⁺ + Mg²⁺)—(HCO₃⁻ + SO₄²⁻) against (Na⁺ + K⁺)-Cl⁻ (Fig. 7), where the excess equivalence of (Ca²⁺ + Mg²⁺) over (HCO₃⁻ + SO₄²⁻) represents the amount of Ca²⁺ and Mg²⁺ gained or lost relative to that provided by the dissolution of gypsum, calcite and dolomite [59]. Likewise, excess (Na⁺ + K⁺) over Cl⁻ demarcates the gained or lost of alkalis relative to that provided by halite dissolution. An impressive inverse straight line with a slope of 0.982 and a goodness of fit (R²) value of 0.876 is a clear testimony that cation exchange might be an important composition controlling process for Bagpat groundwater [60]. The negative slope indicates the participation of cations in ion exchange reactions and suggests that an increase in Na⁺ + K⁺ is related to decreasing in Ca²⁺ + Mg²⁺ or an increase in HCO₃⁻ + SO₄²⁻ [61].

Variation plot between (Ca²⁺ + Mg²⁺- HCO₃⁻-SO₄²⁻) Vs (Na⁺ + K⁺- Cl.⁻)

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The high content of HCO₃⁻ and SO₄²⁻ in groundwater are indicators of natural sources, while higher concentrations of F⁻, Cl⁻ and NO₃⁻ can be used as a tracer for anthropogenic sources [62]. It is supposed that Ca²⁺, Mg²⁺, HCO₃⁻ and SO₄²⁻ in water are mainly derived during weathering of carbonate and sulphide-bearing minerals. Sodium in water may be added from atmospheric precipitation, halite dissolution and weathering of silicate minerals. Weathering of albite (NaAlSi₃O₈), microcline (KAlSi₃O₈) and orthoclase (KAlSi₃O₈) were possible lithogenic gateways through which sodium and potassium might enter the aquifer. Silicate minerals weathering might also lead to HCO₃⁻ build-up in groundwater [63]. Figure 8 shows bivariate plots of Na⁺, Ca²⁺, Mg²⁺ and their binary and ternary combinations with HCO₃⁻ + SO₄²⁻ and Na⁺ + K⁺ against Cl⁻. Plots of individual Na⁺, Ca²⁺ and Mg²⁺ against HCO₃⁻ + SO₄²⁻ demonstrate that the plotted points were much below the equiline (Fig. 8a–c). It indicates that alone these cations on their own could not account for the combined equivalence of HCO₃⁻ and SO₄²⁻. Looking at the binary combinations of these cations, the situation appeared to have improved remarkably but still fell short of HCO₃⁻ + SO₄²⁻ equivalence. The majority of plotted points on the binary plot of (Ca²⁺ + Mg²⁺) against (HCO₃⁻ + SO₄²⁻) fall below 1:1 equiline, suggesting that excess (HCO₃⁻ + SO₄²⁻) may be contributed from non-carbonate and/or non-gypsum source and should be compensated by alkalis (Fig. 8 d). Further, the relationship of (HCO₃⁻ + SO₄²⁻) improved against the combination of (Na⁺ + Mg²⁺) and (Ca²⁺ + Na⁺), indicating a significant contribution of dissolved ions via silicate weathering (Fig. 8e, f). A high (Na⁺ + K⁺)/Cl⁻ ratio i.e. 5.1 also reveals that a major portion of alkalis was derived from weathering of sodium and potassium silicates (Fig. 8h). Ternary combination (Na⁺ + Ca²⁺ + Mg²⁺), however, overcompensated for (HCO₃⁻ + SO₄²⁻), thus indicating Na⁺, Ca²⁺ and Mg²⁺ not only taking care of the entire HCO₃⁻ and SO₄²⁻, but part of it might conjugate with other anions such as Cl⁻, F⁻ and NO₃⁻ as well (Fig. 8g). This lead was mathematically pursued as described below.

Bivariate plot of (HCO₃⁻ + SO₄²⁻) Vs Na⁺, Ca²⁺, Mg²⁺, (Ca²⁺ + Mg²⁺), (Na⁺ + Mg²⁺), (Ca²⁺ + Na⁺), (Ca²⁺ + Mg²⁺ + Na⁺) and (Na⁺ + K⁺) Vs Cl⁻

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Let α, β and γ were three exponents that defined the part of Na⁺, Ca²⁺ and Mg²⁺ that accounted for HCO₃⁻ + SO₄²⁻ equivalence such that,

α, β and γ were optimized through minimization of sum square error by continuous variation technique. MS-Excel Solver program was used for this purpose. The optimized equation was,

The equiline plot for Eq. 3 has been shown in Fig. 9a along with the goodness of fit. It was apparent from the plot that even after accounting for all HCO₃⁻ and SO₄²⁻, still some residual Na⁺, Ca²⁺ and Mg²⁺ would remain, which might conjugate with Cl⁻, F⁻ and NO₃⁻, sources of which might be attributed to anthropogenic and/or geogenic sources. The data plot of estimated residual Na⁺ + Ca²⁺ + Mg²⁺ against Cl⁻ + F⁻ + NO₃⁻ exhibited excellent linearity with a correlation coefficient (r²) of 0.969 (Fig. 9b). Thus, one can assertively state that while weathering of silicate, carbonate and sulphatic rocks of Na, Ca and Mg contributed most to the major ion chemistry of the Bagpat groundwaters. However, the presence of a linear relationship between residual divalent cations and these anions i.e. Cl⁻ + F⁻ + NO₃⁻, suggests a significant contribution from other sources, likely from anthropogenic, which introduce these anions and associated cations into the groundwater system. The impact of anthropogenic activities in the study area can also be visualized through sodium normalized molar ratios of NO₃⁻, Cl⁻ and SO₄²⁻ [64]. It is apparent from the plots Cl⁻/Na⁺ versus NO₃⁻/Na⁺ and NO₃⁻/Na⁺ against SO₄²⁻/Na⁺ that the majority of groundwater samples are dispersed between agriculture and municipal sewage domain, implicating the combined effects of the human activities on groundwater regimes (Fig. 10a and b).

Plot between (a) [HCO₃⁻] + [SO₄²⁻] Vs [Na⁺]^α + [Ca²⁺]^β + [Mg²⁺]^γ as per Eq. 2, and (b) Residual (Na⁺ + Ca²⁺ + Mg²⁺) Vs (Cl⁻ + F⁻ + NO₃.⁻)

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Sodium normalized ratios of (a) Cl⁻/Na⁺ Vs NO₃⁻/Na⁺ and (b) NO₃⁻/Na⁺ Vs SO₄²⁻/Na⁺

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Partial correlation and principal component (PCA) analysis of major ions and heavy metals

A water sample is an ensemble of a large number of physicochemical parameters. These parameters may or may not be mutually dependent. In groundwater chemistry, partial correlation is utilized to ascertain the link between two variables while controlling for the effects of other potentially confounding variables [65]. This makes it possible to comprehend the direct relationship between particular chemical characteristics more precisely, regardless of other variables that may be affecting the system. For example, if some elements originate from the same source, in all likelihood they may be correlated to each other through some function, especially if the source is geogenic. Table 4 shows the binary linear correlation matrix of the selected water parameters involving general parameters, major ions and heavy metals together. A strong correlation refers the matrix value equal or more than 0.75, while good correlation may be obtained when the matrix value is between 0.5 to 0.75. TDS showed strong correlation with Cl⁻ (0.79), SO₄²⁻ (0.77), TH (0.74), Mg²⁺ (0.74), Na⁺ (0.74), and good to moderate correlation with Ca²⁺ (0.65), TA (0.55) and K⁺ (0.54) inferring that ionic concentrations of these ions contributed significantly in enhancing the dissolved loads of groundwater. Similarly, strong to good positive correlations in descending order were observed between Ca²⁺-Mg²⁺ (0.79), Cl⁻-Mg²⁺ (0.74), Cl⁻-Ca²⁺ (0.71), SO₄²⁻-Na⁺ (0.62), Mg²⁺-K⁺ (0.60), SO₄²⁻-Mg²⁺ (0.58), HCO₃⁻-Na⁺ (0.53) and SO₄²⁻-Ca²⁺ (0.52). These correlations, however, did not provide any clinching evidence of a particular type of mineral involved in the weathering process. On the contrary, these were pointers of complex weathering processes involving both carbonate and silicate minerals and a possible mix-up of water from both natural and anthropogenic sources. Fe indicated a strong correlation with Ni (0.88), while good positive correlation with Ca²⁺ (0.65), TH (0.61), Mn (0.54), Mg²⁺ (0.51) and Cl⁻ (0.50). Natural geological processes are the most frequent source of Fe, Mn and Ni in groundwater [66]. Likewise, low As concentration and positive correlations of As-Cl⁻ (0.68) and As-TDS (0.66), indicating the common sources probably from anthropogenic activities.

Principal component analysis (PCA) was carried out compiling 23 physicochemical parameters for the groundwater of the Bagpat region using SPSS software, and the outcomes are summarized in Table 5. Six important factors with eigen values > 1 were extracted from the principal component matrix through varimax rotation which could explain 73.9% of the total variance. Factor-I accounted for 35.9% of the total variance with loading of TDS, SO₄²⁻, Cl⁻_, As, Na⁺, Mg²⁺ and TH. This factor supports anthropogenic origin of these elements and non-carbonate hardness of the studied groundwater. Factor-II corresponded the loading of Ca²⁺, Mg²⁺, K⁺ and TH. The components associated with this factor may originate from weathering of rock-forming minerals such as carbonates and silicates. Factor-III consisted of higher loading of alkalinity, HCO₃⁻ and Na⁺. Geogenic processes involving weathering of sodium-bearing silicate minerals such as alkali feldspars might be responsible enhancing Na⁺ and HCO₃⁻ into the groundwater [67]. Factor-IV comprised relatively higher loading of Mn, Fe, Zn and Ni, which are naturally present in various rocks and soils, weathering of which may release these elements into water regimes [68]. Factor-V was characterized by a loading of NO₃⁻ which may be attributed to the agricultural activities and use of fertilizers and pesticides [69]. Factor-VI involved the loading of Cr and Se which might be originated from the leaching of waste disposal specifically of municipal and industrial waste [70]. Other similar sources of Cr and Se include tire wear and fuel combustion through which the groundwater may be impacted [71]. Thus, it might be safely reckoned that the groundwater geochemistry of Bagpat district was primarily governed by the weathering of carbonate and silicate minerals along with a significant contribution from anthropogenic sources.

Quality assessment for irrigation and industrial application

The use of poor-quality water not only affects human health but also impacts soil health and crop productivity. Plant roots assimilate water through capillary action driven by osmotic pressure, which is governed by the total ionic concentration. The total amount of salt present in water determines its suitability for irrigation, but the type of salt is also equally important [72]. Several total ion-based indices have been proposed by various researchers to describe the irrigation worthiness of a water sample [73,74,75,76,77,78,79,80]. These include salinity, sodium absorption ratio (SAR), %Na, residual sodium carbonate (RSC), permeability index (PI), magnesium hardness (MH), etc. All these indices were calculated for the groundwater samples from Bagpat, and the expressions used for calculating these indices have been consolidated in Table 1.

Salinity and sodium are the two most important parameters in assessing the water quality for irrigation uses. High salt concentration in irrigation water makes soil inappropriate for agriculture and pose problems to farmers in the crops selection and development. Based on electrical conductivity (EC) water can be classified into four categories: excellent (100–250 µS cm⁻¹), good (250–750 µS cm⁻¹), fair (750–2250 µS cm⁻¹) and poor (> 2250 µS cm⁻¹). In the present case, 16% samples fall into good category, 80% into the fair category and only 4% samples into the poor category. Similarly, based on Sodium adsorption ratio (SAR), irrigation water can be divided into four categories i.e. excellent (0–10), good (10–18), fair (18–26) and poor (> 26). The SAR value in the Bagpat groundwater ranges from 0.30 to 8.69 and all the water samples fall into excellent category. The data plotted on USSL [73] diagram where SAR has been plotted against EC, representing alkalinity and salinity hazard respectively indicates that majority of the groundwater samples can be mapped in the C2S1 (medium salinity, low alkalinity) and C3S1 (high salinity, low alkalinity) regions (Supplemental Fig. S-1). Data points of eight groundwater samples fall under C3S2 (high salinity, medium alkalinity), two into C4S2 (very high salinity, medium alkalinity) and one under C4S3 (very high salinity and high alkalinity) regions. The USSL diagram very clearly underscores that the groundwater of the study area is medium to high saline and low alkaline water. Such water can be safely used for the purpose of irrigation, although some samples may not be ideally suitable due to high salinity and requires special management for salinity control. For the application of such water in irrigation, soil must be permeable, drainage must be adequate and irrigation water must be applied in excess to facilitate considerable leaching and salt-tolerant crops should be given preference for such regions.

The percent sodium (%Na) value in the studied water samples ranges from 5.8 to 77.4 with an average value of 41.5. The water classification for irrigation suitability with respect to %Na shows that 8.8% of the samples are classified under the excellent category, 78% within the good to permissible and 13% under doubtful categories (Table 6). The data plotted on the Wilcox diagram [74], which shows %Na against EC, indicates that 87% of groundwater belong to excellent and permissible categories for the purpose of irrigation (Supplemental Fig. S-2). EC value is exceeding the recommended value of 2000 µS cm⁻¹ in 6% of total samples and %Na exceeds the guideline value of 60% in 13% water samples. Using water with high salt and %Na levels not only directly affects plant growth but also impacts soil structure, permeability, and aeration, which indirectly hampers plant development. High salinity poses more serious problems in regions with poor drainage, where salts tend to accumulate in the soil due to rising water tables, hindering osmosis and preventing plants from absorbing essential nutrients from the soil.

The excess equivalence of (HCO₃⁻ + CO₃⁻) over alkaline (Ca²⁺ + Mg²⁺) can lead to complete precipitation of Ca and Mg as carbonate, making these elements scarce for plants [75]. Eaton [76] proposed the term residual sodium carbonate (RSC) to determine the effects of carbonate and bicarbonate in irrigation water and divided water into four classes (i) harmful (RSC > 5), (ii) unsuitable (RSC 2.5–5), (iii) marginally suitable (RSC 1.25–2.5) and (iv) suitable (RSC < 1.25). According to this classification, 51% of the Bagpat district groundwater samples are in the safe category, 21% under marginally suitable and 22% in unsuitable categories. Additionally, 6% of the samples fall under harmful category and cannot be used for irrigation (Table 6).

Long-term use of Na⁺, Ca²⁺, Mg²⁺ and HCO₃⁻ rich water affects the soil permeability and is harmful for irrigation uses. Doneen [77] proposed three-fold classification of irrigation water based on the permeability index. Class I (≥ 75%) and Class II (25–75%) waters are categorized as good for irrigation, while Class III waters are unsuitable for irrigation with 25% of maximum permeability. Permeability index data in Table 6 shows that 99% of groundwater samples of Bagpat district belonged to Class I and Class II water types and are good for irrigation uses [78].

Magnesium Hazard (MH) is yet another index often used to adjudge the irrigation suitability of the water sample [79]. The increase in magnesium concentration in groundwater is related to the occurrence of exchangeable sodium in the soil. High Mg²⁺ content in irrigation water causes loss in hydraulic conductivity and clay dispersion, particularly in non-calcareous soils. Crop yield in non-calcareous soil irrigated with high MH value water (50–65%) may decrease due to magnesium-induced calcium deficiency [80]. MH values in Bagpat groundwater samples ranged from 36 to 75% and exceeded 50% MH limit in 63% of groundwater samples. It suggests that the agricultural productivity in the area may reduce with irrigation of such water for a longer period (Table 6).

Water is an industrial commodity and has a great demand in a wide range of industrial applications, especially where boilers, tanks, reactors and associated pipelines are in use. Scaling and corrosion are two main phenomena that occur as direct fall out of water quality. pH and hardness of water individually or in combined governed the scaling or corrosive properties of water. Low pH causes corrosion while high hardness results in scaling. Scaling causes the deposition of salts on the internal walls of the vessels while corrosion leads to material loss due to electrochemical reactions. Several empirical and semi-empirical indices have been put forward by various researchers to label the rigorous nature of scaling and/or corrosion of water samples. Four such indices, namely, Langelier saturation index (LSI), Ryzner stability index (RSI), Aggressive index (AI) and Puckorioius scaling index (PSI) [81,82,83,84] have been used in the present study to understand the scaling/corrosion behaviour of Bagpat groundwater. The Langelier saturation index determines whether water is likely to precipitate calcium carbonate scale or dissolve existing scale. It depends on the actual pH of the water to the saturation pH, which is the pH at which calcium carbonate is in equilibrium with the water. The Aggressive index depends on pH, total alkalinity, and calcium hardness and advantage over LSI and RSI is that it does not require temperature or TDS values for calculation. The Ryznar saturation index (RSI) is based on alkalinity, hardness, and temperature. Meanwhile, the Puckorius scaling index (PSI) calculates an"equilibrium pH"(pHeq) using the total alkalinity and considered to be more reliable than LSI and RSI in some applications, especially in cooling water systems with buffering agents.

The equations used to calculate these four indices to express the potential of scaling and corrosive intensity of the studied water samples have been listed in Table 1 and the calculation results in Table 6. It was apparent from the Table 6 that about 94% of water samples are non-corrosive (AI > 12) in nature. Similarly, LSI > 0 in 95% of water samples shows the non-corrosive characteristics or possibility of scaling if such water is supplied for industrial purposes. According to PSI, around 40% studied groundwater depicted non-corrosion nature. Likewise, groundwater samples deciphered RSI < 8.5 signifying insignificant corrosion or non-corrosive nature. Overall, non-corrosion characteristics of the groundwater of Bagpat region were identified inferring a possibility of scaling in water distribution system due to precipitation of carbonates.

This study provides comprehensive insights into the groundwater geochemistry and water quality in the Yamuna-Hindon interfluve region of Bagpat district, focusing on the geochemical processes that control water chemistry and its suitability for domestic, industrial, and irrigation uses. The groundwater is generally neutral to mildly alkaline in nature. Significant variability in TDS levels across the district indicates that both geogenic and anthropogenic processes influence groundwater chemistry. The dominant anions include HCO₃⁻, Cl⁻, and SO₄²⁻, while Na⁺, Ca²⁺, and Mg²⁺ are the primary cations. On average, Na⁺ contributes about 40% of the total cations, and HCO₃⁻ accounts for approximately 71% of the anionic charge balance. The dominant hydrogeochemical facies are Mg-Ca–HCO₃ and Na–K-HCO₃-Cl. Rock weathering and ion exchange processes primarily control solute concentrations, although some parts of cations associated with Cl⁻, F⁻, and NO₃⁻ may also originate from anthropogenic sources. A broad infringement of drinking water standards is observed in relation to TDS, TH, turbidity, F⁻, Fe, Mn, and Al. Concentration contour plots reveal better groundwater quality in the central and eastern parts of the district, while western and southwestern areas, especially near the Yamuna River exhibit poorer quality due to lateral infusion of contaminants from river channels. For irrigation purposes, most samples are deemed suitable; however, some samples display high salinity, %Na, RSC, and MH values, which could adversely affect soil health and crop productivity over time. Estimated LSI and AI indices for industrial applications indicate that most groundwater is non-corrosive and prone to scaling, which could cause scaling in boilers and other water distribution systems. However, RSI and PSI indices suggest a tendency toward neutral to likely corrosive water. The detection of pesticides such as lindane, DDT, and β-endosulfan in some groundwater areas highlights potential contamination concerns, necessitating a detailed investigation of pesticide contamination across the entire district.

Future research could expand to include stable isotopic analyses, such as δ¹⁵N, δ³⁴S, δ³⁷Cl, δ¹⁸O, and δ²H, as well as groundwater modelling. Investigating stable isotopes would enhance understanding of groundwater recharge processes, surface–groundwater interactions, and mixing dynamics, and also aid in tracing anthropogenic sources by comparing their isotopic ratios with known sources. Concurrently, groundwater modelling could help determine flow directions and velocities of specific pollutants and pesticides, as well as delineate contaminated zones. To mitigate groundwater pollution, stakeholders should be advised to prioritize preventing contamination at its source, to enhance recharge through rainwater harvesting or other methods to minimize water level depletion, and to promote sustainable agricultural practices to improve groundwater quality. Scaling in the distribution system reduces water flow velocity by clogging pipes, which can lead to the regrowth of microorganisms and water contamination. Regular adjustment of pH and alkalinity levels, along with routine cleaning and maintenance of water distribution networks, is essential to preserve water quality and protect the integrity of the distribution system.

No datasets were generated or analysed during the current study.

The authors take this opportunity to thank Director, CSIR-CIMFR for his permission to publish this paper. The authors are thankful to Dr. Santanu Bhattacharjee for his help in the conceptualization of the concept and to other lab colleagues for their support in sampling and analysis work. Abhishek Pandey Bharat also wishes to acknowledge AcSIR

The study has been sponsored by Water and Power Consultancy Services Limited (WAPCOS Ltd.), New Delhi under National Aquifer Mapping Project.

Authors and Affiliations

1. Water Resource Management Group, CSIR-Central Institute of Mining and Fuel Research, Dhanbad, 826001, Jharkhand, India

   Gautam Chandra Mondal, Abhishek Pandey Bharat & Abhay Kumar Singh

2. Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, 201002, Uttar Pradesh, India

   Gautam Chandra Mondal, Abhishek Pandey Bharat & Abhay Kumar Singh

Contributions

All authors have contributed to the study conception, data generation and manuscript design. Dr. Gautam Mondal and Abhishek Pandey Bharat have contributed to the laboratory analysis, compilation of chemical data and formatting of the manuscript. Dr. Abhay Kumar Singh conceived the concept and prepared the manuscript.

Corresponding author

Correspondence to Abhay Kumar Singh.

Ethics approval and consent to participate

The authors declare that they have no competing interests in this study.

Consent for publication

All authors have given their consent for publication of this manuscript.

Competing interests

The authors declare no competing interests.

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