The escalating issue of heavy metal pollution is a global concern, primarily due to its toxic and persistent nature, further exacerbated by a continuous surge in concentrations above recommended thresholds. This study examines the spatial-temporal dynamics of water quality along the Yamuna River through physicochemical parameters, heavy metal analysis, advanced approaches such as the Heavy Metal Pollution Index (HPI) & Ecological Risk Index (ERI), and multivariate statistical techniques (Principal Component Analysis). It was identified that Wazirabad after drain (WBAD) exhibits poor water quality, with levels of Dissolved Oxygen (DO), Ammonia, Electrical Conductivity (EC), and five heavy metals (Fe, Mn, Pb, Cr, and Ni) exceeding Bureau of Indian Standards (BIS) permissible limits. During the pre-monsoon season, HPI values surpassed the critical threshold (100) in WBBD (146.69), WBAD (267.13), and PJ (204.80), while in the post-monsoon season, only PJ (115) exhibited elevated HPI values. Ecological risk assessment highlighted Cd, Pb, and Ni as major risk elements, posing significant environmental threats. Pearson Correlation analysis and PCA identified two distinct groups of heavy metals, suggesting distinct contamination sources for Co, Cd, and Cu compared to the Fe-Cr-Pb-Mn-Zn-Ni group. This thorough study not only emphasizes the critical condition of water quality in the Delhi region but also provides valuable insights into the sources and distribution of heavy metals, offering a valuable foundation for targeted intervention and mitigation strategies to address the pressing issue of heavy metal pollution.
Research Article
Insights into Water Quality of River Yamuna, India: A Comprehensive Spatial-Temporal Analysis Using Advanced Indices and Multivariate Statistical Techniques.
https://doi.org/10.21203/rs.3.rs-4072812/v1
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Yamuna River
Heavy Metal Pollution Index (HPI)
Ecological Risk Index (ERI)
Mitigation
Principal Component Analysis (PCA)
and Water Quality
Water plays a significant role in ecological systems and is a necessity for the existence of life. Rivers are the primary source of freshwater for agricultural, domestic, and industrial use. However, rivers play a integral part in shaping any nation's natural, cultural, and economic features and are essential to the routine life of people living along river banks and in surrounding areas (Rafiq et al. 2016; R. Sharma et al. 2020). Over the last few decades, rivers have been contaminated all over the world (Q. Zhou et al. 2020). Numerous pollutants, such as heavy metals, pesticides, fertilizers, etc., are dumped into rivers, posing a serious health risk to humans and aquatic life. Among these pollutants, heavy metal contamination is a global concern due to its toxic, enduring nature and the ongoing rise in concentration above the recommended values (Fu et al. 2015; Islam et al. 2015; Varol 2011; Xie and Ren 2022; Yuan et al. 2012). Heavy metal contamination has existed ever since humans started processing ores. However, heavy metal usage began to rise alarmingly only after the industrial revolution. Both naturally occurring (bedrock erosion and weathering) and human-caused (electroplating, pesticides, paint industries, mining, batteries, etc.) activities are responsible for the introduction of heavy metals into the river water (Q. Zhou et al. 2020). Urbanization is the primary contributor to river pollution, which leads to the continuous discharge of domestic, industrial, and agricultural runoff that disturbs the natural functioning and ecological services they provide (Dudgeon et al. 2006; Woodward et al. 2012). The accumulation of heavy metals poses severe risks to human health, including kidney disease, renal tumors, eyelid edema, lung cancer, high blood pressure, etc. (Asim and Nageswara Rao 2021). Heavy metal-contaminated river water can also change the physicochemical properties of groundwater adjacent to river channels (Krishan et al. 2021). The Niger River in Nigeria, the Korotoa River in Bangladesh, the Yangtze and the Yellow Rivers in China, the Citarum River in Indonesia, the Ganga and the Yamuna Rivers in India, the Sarno River in Europe, the Meycauayan River in the Philippines, the Matanza-Riachuelo River in Argentina, etc., are among the most polluted rivers (Asim and Nageswara Rao 2021; Ezewudo et al. 2023; Fahimah et al. 2023; Hu et al. 2019; Magni et al. 2021; Montuori et al. 2013; Pleto et al. 2020; Siddiqui and Pandey 2019; Xie and Ren 2022; Q. Zhou et al. 2020).
The River Yamuna delivers lots of ecosystem services throughout its span of 1376 km right from its mouth, Yamunotri Glacier, at an elevation of 3293 meters. At Prayagraj, the Yamuna and Saraswati rivers converge with the Ganga River to form Triveni Sangam. However, in recent years, the Yamuna River and its tributaries have become severely contaminated with heavy metals, especially along a 22 km section in Delhi (Asim and Nageswara Rao 2021; Jaiswal et al. 2019; Lokhande and Tare 2021; R. Sharma et al. 2020). The Yamuna River flows through a number of major cities and metropolitan regions, including Paonta Sahib, Yamunanagar, Karnal, Panipat, Sonipat, Delhi, Faridabad, Mathura, and Agra, where it is directly or indirectly impacted by a vast amount of untreated and partly treated domestic and industrial wastewater. These areas serve as industrial hubs for pulp and paper, rubber, glass, chemicals, food processing, steel, tannery, etc., that produce large amounts of chemical effluents in the Yamuna River. Delhi holds only 2% of Yamuna’s total length but contributes a maximum pollution load of approximately 70% (R. Sharma et al. 2020). In Delhi NCR, approximately 22 drains containing partial or untreated domestic and industrial sewage enter into the Yamuna River and increase the heavy metals load which causes potential impacts on human health and the ecological balance. Of these, the Najafgarh drain has the highest potential to pollute the Yamuna River (Jaiswal et al. 2019; Lokhande and Tare 2021). The Yamuna River is severely polluted, and to maintain and conserve water quality, a proper and regular assessment and monitoring system is essentially required (Kisi et al. 2023). In 1993, the Ministry of Environment and Forests, GOI (Government of India) introduced the Yamuna Action Plan to safeguard the river's water quality, particularly in the Delhi region (Jaiswal et al. 2022).
Numerous research investigations have explored the spatial distribution, migration patterns, bioavailability, and the assessment of associated risks related to heavy metals in the Yamuna River (Ahmed et al. 2022; Asim and Nageswara Rao 2021; Bhardwaj et al. 2017; Jaiswal et al. 2019, 2022; Katyal et al. 2012; Kisi et al. 2023; Mandal et al. 2010; R. Sharma et al. 2020). To the best of our information, no studies have been reported on the whole stretch of the river from starting points to destinations. This is the initial reconnaissance study to address the existing research gap by conducting a comprehensive examination of the spatial and seasonal fluctuations in the hydrochemistry of the Yamuna River in pre-monsoon (PRM) and post-monsoon (POM) seasons and covering the entire length of the river, from Yamunotri (Origin point) to Prayagraj (Ending point). Therefore, this study investigates the physical-chemical properties and heavy metal concentrations along the Yamuna River. Employing the Heavy Metal Pollution Index (HPI) and Ecological Risk Index (ERI) tools provides a holistic understanding of the heavy metal load and its possible consequences to human and ecological health. By assessing parameters at multiple points and utilizing comprehensive indices, the study aims to serve as a crucial resource to the authorities for ongoing monitoring and implement strategies for the revival of the river Yamuna, ensuring the well-being of both the ecosystem and human populations in the region.
A total of five sampling sites (Yamunotri (YM), Paonta Sahib (PS), Wazirabad Before Drain (WBBD), Wazirabad After Drain (WBAD), and Prayagraj (PJ)) covering the entire stretch of Yamuna River have been chosen for collecting water in the month of April 2022 (Pre-Monsoon) and September 2022 (Post-Monsoon). Water samples were systematically collected in triplicate from each site, and information regarding the sampling locations was documented with the aid of a handheld GPS instrument (Table 1 & Fig. 1).
Analysis of Physical-chemical parameters of water
Samples collected and bring to Ciliate Biology Laboratory (Acharya Narendra Dev College) in polyethylene plastic bottles, which were meticulously rinsed three times with deionized water to minimize any potential contamination. On-site, the water temperature was measured using a precise thermometer, and the pH levels were determined through the use of pH strips, ensuring accurate assessments of these crucial parameters. Water hardness (WH), was determined titrimetrically by the EDTA method using ammonia buffer solution and Eriochrome black-T as indicators, and dissolved oxygen (DO) was determined using the Winkler’s method (Winkler 1888; Montgomery et al. 1964; Eaton et al. 2005; Gautam et al. 2011). Electrical conductivity (EC), Total dissolved solids (TDS), Oxidation-Reduction potential (ORP), Resistivity, and Salinity were measured by means of water multiparameter analysis apparatus. Nitrate (NO3−), nitrite (NO2−), and Ammonia (NH3) concentrations were estimated by API-test kit following the manufacturer’s protocol (Naigaga et al. 2017).
Heavy metal analysis
For the heavy metal analysis of water, 100 ml of well-mixed sample was placed in an acid-resistant beaker and treated with high-purity nitric acid to maintain a low pH (< 3), preventing precipitation and absorption on container walls (APHA 1998). The mixture was then digested on a hot plate just below the boiling point until half of the volume was left. After cooling, the digested samples underwent dilution with de-ionized water and subsequent filtration using Whatman no. 42 filter paper (Maurya et al. 2022). Further, concentration of heavy metals was examined through Inductive Coupled Plasma -Mass Spectrometry (ICP-MS) (Herrero Fernández et al. 2021).
Heavy metal pollution index (HPI)
HPI is a comprehensive numerical metric designed to assess and evaluate the combined impact of various heavy metals on overall water pollution within aquatic ecosystems (Mohan et al. 1996). This method employs a weighted arithmetic quality mean approach, assigning specific weights to chosen heavy metals based on their significance and criticality in relation to human and river health (Asim and Nageswara Rao 2021). The calculation incorporates all examined heavy metals and their BIS (Bureau of Indian Standards, 2012) water quality standards for drinking water. The critical threshold for HPI is established at 100, and any value surpassing this threshold signifies a notable increase in the level of heavy metal pollution. The HPI is determined using the following formula:
$$HPI=\frac{{\sum }_{i=1}^{n}WiQi}{{\sum }_{i=1}^{n}Wi}$$
where Wi is the unit weight assigned to each heavy metal, Qi is the subindex of the parameter (ith heavy metal). Wi is computed from the following formula:
$$Wi=\frac{K}{Si}$$
where k is the constant set at 1 and Si is the standard value of ith heavy metal by BIS (2012). Wi varies between 0 and 1.
Qi was evaluated based on the given formula:
$$Qi=\sum _{i=1}^{n}\frac{\left|Mi-Ii\right|}{\left(Si-Ii\right)}\times 100$$
where Mi is the assessed value of heavy metals, Ii is the ideal value of ith heavy metal.
Ecological risk index (ERI)
The ERI was employed to assess the potential ecological risk posed by the heavy metals and differentiated into 5 groups, namely: RI < 40 (low potential ecological risk), 40 < RI < 80 (moderate potential ecological risk), 80 < RI < 160 (considerable potential ecological risk), 160 < RI < 320 (high potential ecological risk), and > 320 (very high potential ecological risk) (Ahmed et al., 2022). It is calculated as follows:
$$ERI=\sum _{i=1}^{n}[Ti\times \left(\frac{Mi}{Ii}\right)]$$
where, Ti is the biological toxicity factor of ith heavy metal (Fe, Mn, Zn, Cr = 1; Co, Ni, Cu, Pb = 5; Cd = 30) (Ahmed et al. 2022).
Statistical analysis
To assess the interrelationships among water quality parameters, a Pearson's correlation matrix was computed for five sampling stations during two distinct seasons (Pre-Monsoon and Post-Monsoon). Pearson correlation, Principal Component Analysis (PCA) methodology, incorporating varimax rotation, was employed to elucidate the sources of heavy metal pollution influencing the study area. PCA aims to unveil the most pivotal factors while minimizing data complexity (Belkhiri and Narany 2015). Factors with eigenvalues surpassing one were considered to optimize variability (Ahmed et al. 2022). Factor loadings were then categorized into low (0.3–0.5), intermediate (0.50–0.75), and strong (> 0.75) categories (Liu et al. 2003). The Kaiser-Meyer-Olkin (KMO) and Bartlett’s test of sphericity was employed to confirm the suitability of the data for PCA. Additionally, a two-way ANOVA test was conducted to discern differences in water quality parameters between sites and seasons, assessing whether the averages of more than two independent groups differ from each other. All the statistical analysis and graphs were done in SPSS (version 21.00) and R-Studio.
Physical and Chemical parameters
The average values and standard deviation for 11 physical-chemical parameters measured in the Yamuna River during Pre-monsoon (PRM) and post-monsoon (POM) periods is summarized in Table 2.
Temperature
In the PRM season, water temperatures ranged from 8.3°C to 28.7°C, while in the POM period, varied between 10.3°C to 29 °C (Table 2). The highest temperature was recorded at Delhi region (WBBD & WBAD), and PJ in PRM and POM, respectively (Table 2, Fig 2). Significant variations were observed both in spatial distribution and temporal scales (Table 2, Fig 2). These variations were significantly influenced by seasonal factors such as winter cooling, raining and increased solar radiation (Barik et al. 2017). Higher water temperatures can impact water quality by accelerating chemical reactions, reducing gas solubility, and intensifying tastes and odors. Additionally, turbidity, water density, and the solubility and toxicity of certain compounds like heavy metals, elevate with rising water temperature (Bhateria and Jain 2016; Hung Anh and Pásztory 2021). Furthermore, elevated water temperature can lead to decreased dissolved oxygen levels (Bhat and Pandit 2014; Bouslah et al. 2017). Notably, the lower temperatures recorded at YM can be attributed to differences in altitude and latitude. Pearson correlation analysis unveiled positive relationships between water temperature and total dissolved solids, electrical conductivity, and salinity, while conversely, a negative correlation was noted with dissolved oxygen levels. Overall, the measured water temperatures fell within the favorable range of 20-25°C for aquatic organisms (Dauda 2020), indicating suitability for the Yamuna River's ecosystem in both seasons.
pH
pH levels in the Yamuna River ranging from 7.27 to 8.56 in PRM and 7.17 to 8.03 in POM season (Table 2). During the PRM season, the pH of the water was observed to be slightly more alkaline compared to the POM season. This suggests a seasonal variation in the acidity or alkalinity of the water in the Yamuna River, highlighting the dynamic nature of its physicochemical characteristics. Factors contributing to this variation include rainwater addition (decrease buffering capacity of the river), low photosynthetic rates, and organic matter decomposition during POM (A. Kumar et al. 2020; R. Sharma et al. 2020). Pearson correlation indicates that pH positively correlates with temperature and negatively correlates with DO (Table 3). Spatially, pH levels generally fell within permissible limits of 6.5–8.5 (BIS 2012), except for an outlier at WBBD (8.56) in PRM. Elevated pH can lead to skin and eye irritation and a bitter taste in water (WHO, 2004). However, aside from the exception at WBBD, the Yamuna River's pH levels were found to be within a range considered suitable for both drinking water and aquatic life.
DO
DO values varied from 3.0-9.62 mg/L in PRM and 3.6-8.52 mg/L in POM (Table 2). There was significant spatial and temporal variability (Table 2, Fig 2) in DO, which may be related to temperature, turbulence, river flow, and anthropogenic impacts. The highest value of DO was recorded at YM followed by PS, PJ, WBBD, and WBAD in both seasons. Importantly, DO concentrations were recorded out of the permissible limit (≤ 5 mg/l) at sites WBBD (3.7 mg/L), WBAD (3 mg/L), and PJ (4.17 mg/L) in the PRM season, and at WBAD (3.6 mg/L) & PJ (4.8 mg/L) during the POM season. Low Dissolved oxygen (DO) levels in the water negatively impact biological diversity as it governs various metabolic activities in aquatic biological communities (Matta et al. 2015; Ranković et al. 2010). Low DO level at WBBD, WBAD and PJ could be due to low turbulence, high temperature and continuous discharge of untreated or partially treated domestic, industrial, and agricultural waste (Mir and Gani 2019). Low temperatures and high turbulence at YM lead to increased dissolved oxygen (DO) levels, as the cold water has a greater capacity to hold dissolved oxygen compared to warmer water (Dimri et al. 2021). Pearson correlation analysis showed DO has a negative correlation with temperature, TDS, EC, water hardness, salinity, nitrite, and ammonia, whereas positive correlation with resistivity (Table 3). High TDS, electrical conductivity, hardness, and salinity often indicate the presence of dissolved salts and minerals in the water (Darko et al. 2023). These dissolved solids can reduce the water's capacity to hold oxygen, leading to lower dissolved oxygen levels (Zhao et al. 2021). Therefore, there was an inverse relationship between DO and these parameters. High levels of nitrite and ammonia in water are often indicative of pollution or poor water quality from organic matter and can lead to oxygen depletion (Hlordzi et al. 2020). Microorganisms involved in the decomposition of organic materials consume oxygen in the process, leading to lower DO levels (Hlordzi et al. 2020). Higher resistivity indicates pure water with fewer ions including salts, making it more capable of holding dissolved oxygen. DO data indicates that river water is not suitable for drinking and domestic uses in the lower regions (WBBD, WBAD, PJ).
Ions Concentration (EC, TDS, water hardness, and salinity)
Electrical conductivity (EC), is the ability of water to conduct an electrical current, varied from 180.8-1999.8 µS in PRM, 205.66-1167.7 µS in POM along the entire river course (Table 2). The concentration of TDS, water hardness, and salinity varied from 90.5-1217 mg/L, 83.83-323.8 mg/L, and 0.073-1.296 psu, respectively, in PRM, while 102.21-582.52, 95.33-164.3 mg/L, and 0.1-0.584 psu in POM (Table 2). All four parameters are observed high in the PRM season except YM. This indicates that the Yamuna River’s water quality is poor in the PRM season related to the POM season. Low EC, TDS, water hardness, and salinity in POM season are attributed to the high flow of River water that dilutes and improves the water quality (Asim and Nageswara Rao 2021). Temperature is another crucial factor that modifies the ions concentration in water, as discussed earlier. The highest value of EC (1999.8 ± 0.749 mg/L: PRM, 1167.7 ± 1.155 mg/L: POM), TDS (1217 ± 2.646 mg/L: PRM, 582.52 ± 1.53 mg/L: POM), WH (323.8 ± 1.103 mg/L: PRM, 164.3 ± 2.032 mg/L: POM), and salinity (1.296 ± 0.045 mg/L: PRM, 0.584 ± 0.015 mg/L: POM) was recorded at WBAD and lowest at YM in both seasons (Table 2, Fig 2). High concentration at WBAD is mainly due to an increase in contamination load by the Najafgarh drain, and the addition of agricultural runoff in the river (Jindal and Sharma 2011). TDS, WH, and salinity were found within the BIS (2012) permissible limit at all the sites, but EC was found out of the permissible limit (750 µS) at WBBD (PRM) and WBAD (in both seasons). EC, TDS, WH, and salinity have a very close relationship (Directly) with each other (Dimri et al. 2021). Pearson correlation results also validate this, as all four parameters show a positive correlation with temperature & a negative correlation with resistivity and DO (Table 3). EC, TDS, water hardness, and salinity are related to the concentration of ions in water and share a common source of pollution. When one of them increases, it suggests a higher overall ion concentration, which tends to cause an increase in the other parameters as well.
Resistivity
Resistivity varied from 0.426-5.168 kΩ in PRM and 0.853-4.827 kΩ in POM (Table 2). There is no permissible limit set by BIS (2012) for resistivity but it provides a very significant idea about the quality of water. But so far, resistivity has been ignored in most water quality studies. Resistivity measures the ability of water to resist the flow of electricity, which is closely linked with dissolved salt concentration in water. Water with a low concentration of dissolved salts has high resistivity. During the study, we observed that resistivity is directly proportional to the water quality. The highest resistivity was observed at YM and lowest at WBAD in both seasons. At WBAD, water quality was very poor (High dissolved salt concentration) due to the continuous discharge of effluent by the Najafgarh drain, which lowers the resistivity at this site (Asim and Nageswara Rao 2021). High resistivity at YM as it is the origin point of Yamuna River and very less or no anthropogenic interference. All the parameters along with resistivity indicate that at WBAD water is highly polluted and not recommended for drinking and domestic purposes.
Nitrogenous components (nitrate, nitrite, and ammonia)
The concentration of nitrogenous components; nitrate, nitrite, and ammonia varied from 0.237-9.665 mg/L, 0-0.483 mg/L, and 0.273-7.5 mg/L, respectively, in PRM and 1.05-10.33 mg/L, 0-0.093 mg/L, and 0.13-9 mg/L in POM (Table 2, Fig 2). Nitrogenous components were found to be significantly variable, as high concentrations of nitrate at PS in both seasons, nitrite at WBAD and PJ in PRM and POM, respectively, and ammonia at WBAD in both seasons. There is no permissible limit set by BIS (2012) for nitrite. Nitrate were found within the BIS (2012) permissible limit (45mg/L) in all the sites but ammonia was recorded above the BIS (2012) permissible limit (0.5 mg/L) at WBAD (PRM, POM) and PJ (POM). The elevated concentration of ammonia at WBAD and PJ, and nitrate at PS and PJ indicated the contribution of industrial sources, agricultural fertilizers, and mixing of domestic waste (Jaiswal et al. 2019). Despite of highest polluted water at WBBD and WBAD nitrate concentration was low, and the system was found to be nitrogen-limited from a stoichiometric perspective. Algal growth might have consumed nitrate (Ahmed et al. 2022), making the system nitrogen-limited in this region. However, there is no pollution in the Delhi region due to Nitrate. The enrichment of surface water with nitrogen components can result in rapid growth of aquatic plants leading to oxygen depletion as DO at WBAD was found below the BIS (2012) permissible limit. The Nitrite content in the Yamuna River was found in very low concentration and almost remained undetectable at all the sites in POM and at YM & PS in PRM. This may be due to the unstable nature of nitrite, and similar results were also reported for the Chaliyar River (Saha et al. 2022), El Fuerte River, Mexico (Fregoso-López et al. 2020). Nitrite is the transitional oxidation state between ammonia and nitrate, and the appearance of this transient species in water is due to the oxidation of ammonia or reduction of nitrate. This makes it the most unstable form in water, and thus, there were wide fluctuations in nitrite concentration during this study.
Heavy metal analysis
In the present study four biologically essential heavy metals, i.e., Iron (Fe), Zinc (Zn), Manganese (Mn), and Copper (Cu), and five biologically non-essential heavy metals i.e., Lead (Pb), Cadmium (Cd), Nickel (Ni), Cobalt (Co), and Chromium (Cr) were measured and presented in the Table 4. The occurrence of heavy metals in the PRM season was found in the order: Fe > Mn > Zn > Cu > Cr > Ni > Pb > Co > Cd, while in the POM season, the order was: Fe > Mn > Zn > Cr > Pb > Ni > Cu > Co > Cd.
Essential Heavy metals
Iron (Fe)
In this study, the Fe concentration exhibited considerable variability, varying from 0.145 to 2.727 mg/L in the PRM season and 0.0403 to 1.173 mg/L in the POM season (Table 4). Spatially, Fe concentration was found to be considerably varied, being highest at WBAD (2.727 ± 0.218 mg/L: PRM, 1.173 ± 0.15 mg/L: POM) in both seasons and lowest at YM (0.145 ± 0.004 mg/L: PRM, 0.0403 ± 0.008 mg/L: POM) (Table 4, Fig 3). Importantly, Fe concentrations were found to exceed the BIS (2012) permissible limit (0.1 mg/l) at all sites and seasons, except for YM in the POM season. Notably, the Fe levels recorded in this study were significantly elevated related to the earlier research by Sharma et al. (2022), Asim and Rao (2021), and Jaiswal et al. (2019) (Asim and Nageswara Rao 2021; Jaiswal et al. 2019; K. Sharma et al. 2022). Several factors could contribute to this excess Fe concentration, including rock mining activities at the YM site, the introduction of untreated or partially treated industrial effluents, soil containing Fe, and the potential dissolution of Fe from old water supply system pipes at other sites. It's crucial to acknowledge that elevated Fe levels in river water can have severe health implications, including respiratory problems, cardiac issues, and diabetes, as noted by the World Health Organization (WHO) in 2011 and reiterated by Jaiswal (2019) (Jaiswal et al. 2019).
Manganese (Mn)
Mn concentrations displayed a range of variability, varying from 0.0035 to 0.319 mg/L in the PRM season and 0.00186 to 0.248 mg/L in the POM season (Table 4). Spatially, manganese concentrations exhibited significant variation at p<0.05, with the highest levels recorded at WBAD (0.319 ± 0.015 mg/L in PRM and 0.248 ± 0.027 mg/L in POM) during both seasons. Conversely, the lowest concentrations were observed at the YM site (0.0035 ± 0.0005 mg/L in PRM and 0.00186 ± 0.0002 mg/L in POM) (Table 4, Fig 3). Importantly, Mn concentrations surpassed the permissible limit (0.1 mg/l) at sites WBBD, WBAD, and PJ in the PRM season, and at WBBD & WBAD during the POM season. Mn enters water bodies through both natural processes, like soil erosion, and anthropogenic activities, including mining and various human actions (Dey et al. 2023). It's crucial to note that excessive and prolonged exposure to manganese has been linked with severe neurological disorders such as Parkinson's disease, Huntington's disease, Alzheimer's disease, dystonia, and manganism (Ikeda et al. 2017).
Copper (Cu), Zinc (Zn), and Cobalt (Co)
Other essential heavy metals such as Cu, Zn, and Co were found within the BIS (2012) permissible limit. Concentrations of Cu, Zn, and Co during the PRM season ranged as follows: 0.0049 to 0.1139 mg/L, 0.0485 to 0.347 mg/L, and 0.000493 to 0.00684 mg/L, respectively (Table 4). In the POM season, concentrations ranged as follows: Cu (0.00194 to 0.2419 mg/L), Zn (0.0251 to 0.223 mg/L), and Co (0.000787 to 0.02716 mg/L) (Table 4). Elevated levels of Cu in the POM season can be linked to high urban runoff and wastewater discharge (Boller and Steiner 2002). Spatially, the highest Cu concentrations were recorded at WBAD (0.1139 ± 0.011 mg/L in PRM, 0.2419 ± 0.015 mg/L in POM), while the lowest was at PS (0.0049 ± 0.00035 mg/L in PRM) & YM (0.00194 ± 0.00065 mg/L in POM). Cu naturally enters water bodies through processes such as rock weathering and volcanic activity. Anthropogenic sources of copper include mining, smelting, industrial processes (such as leather and paint production), and the utilization of copper-containing products like pesticides, fungicides, fertilizers, and plumbing materials. (Hussain et al. 2021; Jaiswal et al. 2022). Similarly, Zn concentrations peaked at WBAD (0.347 ± 0.0252 mg/L in PRM, 0.223 ± 0.026 mg/L in POM) and were lowest at the WBBD site (0.0485 ± 0.0058 mg/L in PRM) & PJ site (0.0251 ± 0.0058 mg/L in POM) ((Table 4, Fig 3)). Zn enters water bodies through natural rock weathering and human activities such as mining and the use of zinc-containing products like galvanized coatings, fertilizers, paints, and pipes (Hussain et al. 2021). Co concentrations exhibited a similar pattern, being highest at WBAD (0.00684 ± 0.0014 mg/L in PRM) & PJ (0.02716 ± 0.0027 mg/L in POM), while lowest at YM (0.00079 ± 0.0002 mg/L in PRM) & PS site (0.000787 ± 0.00014 mg/L in POM) (Table 4). Cobalt also naturally finds its way into water bodies similarly to copper and zinc, with additional industrial activities contributing to its release into the environment.
However, the high level of all the essential metals at WBAD can be attributed to industrial waste transported by the Najafgarh drain and use of pesticides, fertilizers, and fungicides in agricultural activities along the Yamuna riverbank (Asim and Nageswara Rao 2021; Bhardwaj et al. 2017; Hussain et al. 2021; Jaiswal et al. 2022). This finding raises serious concerns about the suitability of the water for drinking and domestic use in this area.
Non-Essential heavy metals
Cadmium (Cd)
Cd is a highly hazardous heavy metal known for causing food poisoning and acute toxicity in various organs such as the lungs, liver, kidneys, and bones (Jaishankar et al. 2014). Cd concentrations varied from 0.000077 to 0.002057 mg/L during the PRM season and 0.0004 to 0.001713 mg/L during the POM season (Table 4). Cd concentrations exhibited significant variability both Spatially and temporally at p<0.05. The highest levels were observed at the PJ site (0.002057 ± 0.00014 mg/L in PRM, 0.001713 ± 0.0001 mg/L in POM) during both seasons, while the lowest concentrations were detected at the YM site (0.000077 ± 0.0000058 mg/L in PRM) & PS site (0.0004 ± 0.0001 mg/L in POM) ((Table 4, Fig 3)). Importantly, the concentration of Cd fell within the permissible limits (0.003 mg/L) set by the BIS (2012). The elevated concentration at PJ can be linked to the disposal of electronic waste, including Ni-Cd batteries, and the release of untreated or partially treated waste from metal industries and medical institutions (L. Zhou et al. 2023). Additionally, the degradation of galvanized pipes from urban areas like Delhi, Agra, Mathura, and Prayagraj could contribute to the higher levels of Cd (Bhardwaj et al. 2017). A higher concentration of Cd was observed at the WBBD compared to WBAD in the POM season can be linked to the agricultural activities at WBBD. Intensified use of Cd-containing fertilizers and pesticides by farmers to increase crop yields in response to the high disease pressure and slower growth caused by excessive rainfall during the monsoon and post-monsoon seasons (Alengebawy et al. 2021).
Lead (Pb)
Pb varied from 0.0029- 0.0842 mg/L in PRM and 0.00033-0.0346 mg/L in POM (Table 4). Spatially, Pb was also found to be significantly (p<0.05) variable as highest at WBAD (0.0842 ± 0.00058 mg/L) in PRM and PJ (0.0346 ± 0.002517 mg/L) in POM seasons & lowest at YM (0.0029 ± 0.0011 mg/L) in PRM and at PS (0.000633 ± 0.00008 mg/L) in POM (Table 4, Fig 3). Pb was found out of the permissible limit (0.01mg/l) at WBBD, WBAD, and PJ in pre-monsoon, while at WBAD and PJ in POM (Table 4). The highest concentration of Pb at WBAD in pre-monsoon could be due to improperly treated waste from electroplating, paints, and batteries manufacturing industries along which is discharged by the Najafgarh drain as well as leaching from municipal landfills (Jaiswal et al. 2022; S. Kumar et al. 2022). The highest concentration at PJ in post-monsoon could likely be attributed to the corrosion of galvanized pipes, and waste disposal from the industrial area of Mathura, Agra, and Prayagraj (Asim and Nageswara Rao 2021; Jaiswal et al. 2022). Pb is a very hazardous metal that poses major health risks including kidney failure, damage to the CNS (Central nervous system) and PNS (Peripheral nervous system), and a decrease in sperm count (Collin et al. 2022). Pb level in Yamuna River increasing day by day, though it requires urgent attention to manage its level.
Chromium (Cr)
Cr varied from 0.01679- 0.25994 mg/L in PRM and 0.00949-0.11703 mg/L in POM (Table 4). Spatially, Cr was also found significantly (p<0.05) variable as highest at PJ (0.25994 ± 0.01 mg/L in PRM and 0.11703 ± 0.208 mg/L in POM) in both seasons & lowest at YM (0.01679 ± 0.0007 mg/L in PRM and 0.00949 ± 0 mg/L in POM) and out of BIS (2012) permissible limit (0.05 mg/l) at WBAD and PJ in both the seasons (Table 4, Fig 3). High levels of chromium at PJ could be due to waste from the leather tanning, petroleum, electroplating, mud drilling, and textile industries (K. Sharma et al. 2022). Cr is a naturally occurring element found in the Earth's crust and present in different forms such as less harmful trivalent Cr (III) and highly toxic hexavalent Cr (VI) that poses risks to human health, including respiratory problems and skin irritation (P. Sharma et al. 2022).
Nickel (Ni)
Ni varied from 0.00737- 0.08897 mg/L in PRM and 0.0021-0.0306 mg/L in POM (Table 4). Ni level was also found significantly (p<0.05) variable as highest at WBAD (0.08897± 0.00359 mg/L in PRM and 0.0306 ± 0.0072 mg/L in POM) in both seasons & lowest at YM (0.00737 ± 0.00068 mg/L in PRM and 0.0021 ± 0.00053 mg/L in POM) and out of permissible limit (0.05 mg/l) at WBAD in the PRM season (Table 4, Fig 3). However, high Ni concentration at WBAD and out of permissible limit could be due to waste emission from stainless steel, batteries, and alloys production which is carried by the Najafgarh drain (V. Kumar and Dwivedi 2021).
Two-way ANOVA results suggest that there is a significant difference (p<0.05; Least significant difference, LSD) between the five sites of Yamuna River in the term of Cr (F=29.696, p<0.001), Mn (F=64.733, p<0.001), Fe (F=56.125, p<0.001), Co (F=33.849, p<0.001), Ni (F=15.324, p<0.001), Cu (F=128.318, p<0.001), Zn (F=92.028, p<0.001), Cd (F=18.032, p<0.001), Pb (F=61.312, p<0.001) (Table 4). Post hoc Tukey analysis also suggests that there is a significant difference between all the sites in terms of heavy metals (p<0.05). Site-wise variations in concentrations of heavy metals in the Yamuna River can be linked to a range of anthropogenic activities, contributing diverse contaminants that are often added without effective mitigation measures. It was also noted that there was a significant seasonal difference in all the metals (p<0.05) except Cd (F=0.053, p=0.82) and the highest concentration in pre-monsoon. Seasonal variation in the concentration of heavy metals could be due to salinity, geomorphological structure, rainfall, and industrial runoff (Tepe et al. 2022). This can be explained by the high-water flow in POM due to rainfalls in the monsoon season which dilutes the heavy metal concentration. Higher levels during the PRM season are caused by excessive evapotranspiration, followed by scorching temperatures and a drop in the water level, which allows heavy metals to aggregate. Higher heavy metal concentrations in pre-monsoon for Yamuna River were also reported by Bhardwaj et al. (2017) and Sharma et al. (2020) (Bhardwaj et al. 2017; R. Sharma et al. 2020).
Heavy metal pollution index (HPI)
The computation of the HPI for each sampling site is detailed in Table 6. During the Pre-Monsoon (PRM) season, HPI values ranked as WBAD (267.13) > PJ (204.80) > WBBD (146.69) > PS (48.91) > YM (11.85). Conversely, in the Post-Monsoon (POM) season, the sequence was PJ (115) > WBAD (75.35) > WBBD (38.1186) > YM (21.99) > PS (16.624). In the PRM season, HPI values for WBBD, WBAD, and PJ exceeded the critical value (100), while in the POM season, only PJ value was high. However, heavy metal concentrations at YM and PS were comparatively lower than at WBBD, WBAD, and PJ. It demonstrates that YM and PS are less urbanized and there isn’t any major source of contamination sources close to the river. The elevated HPI in WBBD, WBAD, and PJ primarily because these areas being highly urbanized and continuously producing vast amounts of waste, such as industrial, domestic, and agricultural, that enters into Rivers through drains. Approximately 8 drains in Haryana, 22 in Delhi, and 14 in Mathura and Vrindavan that dispose industrial and domestic wastes into the river and increase heavy metal load at WBBD, WBAD, and PJ. Among these, Najafgarh drain (between site WBBD and WBAD) carries approximately 23.17 m3/s of industrial & domestic waste, has the most significant impact and drastically worse the water quality at WBAD (Sharma et al. 2017). Furthermore, agricultural activities in the river floodplain area, particularly in WBBD, WBAD, and PJ, contribute to heavy metal concentrations through the excessive use of chemical fertilizers and pesticides, further compromising water quality (Alengebawy et al. 2021). Heavy metals in river also alters the physical-chemical properties of water as HPI found to be positively correlated with temperature, pH, EC, TDS, WH, salinity, nitrite, and ammonia & negatively correlated with resistivity and DO at p<0.05 (Table 3). Asim and Rao (2021) also reported a high HPI value (593.04) in the Delhi region of the Yamuna River downstream of the Najafgarh drain (Asim and Nageswara Rao 2021). Similar results in the Yamuna River were also reported by Ahmed et al. (2022) and Bhardwaj et al. (2017) (Bhardwaj et al. 2017; Ahmed et al. 2022).
Ecological risk index
The ERI values in Yamuna River ranged from 5.353 to 110.6952 during PRM and 8.7175 to 56.11639 in POM (Table 6). In Pre-monsoon, YM and PS had a low ecological risk; WBBD and PJ had a moderate ecological risk; WBAD had a Considerable ecological risk (Table 6). In POM, YM, PS, and WBBD had a low ecological risk; WBAD and PJ had a moderate ecological risk. Cd, Pb, and Ni were the main pollutants in most of the sites but their order was varying. The biotoxicity factors of Cd were the highest (30), followed by Pb (5) and Ni (5), so they are the main risk elements and pose a threat to the ecology. Cd, Pb, and Ni come under the category of non-essential toxic metals posing a serious threat to the water ecosystem. High heavy metal contamination in the water bodies causes deleterious effects in terms of growth, survival, behavior, reproduction, development, and enzymatic system of aquatic organisms as well as humans (Ahmed et al. 2022; Sfakianakis et al. 2015). Ahmed et al. (2022) also reported that Cd, Ni, and Pb were responsible for the high value of ERI and PIG (Pollution index of groundwater) in the groundwater aquifers(Ahmed et al. 2022).
Source identification of Heavy metal pollution
Pearson’s correlation coefficients for various heavy metals are summarized in Table 5. The analysis of correlations revealed that there was a significant positive correlation between Mn-Cr, Fe-Mn, Cr-Fe, Ni-Mn, Ni-Cu, Ni-Cr, Ni-Fe, Zn-Mn, Zn-Cr, Zn-Ni, Zn-Fe, Pb-Mn, Pb-Cr, Pb-Zn, Pb-Fe, and Pb-Ni at a confidence level of P < 0.01. The metals Fe, Cr, Pb, Mn, Zn, and Ni collectively constitute a distinctive group due to their significantly positive correlations. This pattern of correlation strongly suggests that these metals share a common source of contamination within the Yamuna River. Another significant positive correlation is observed between Co-Cu and Cd-Co. These three metals, Cu, Co, and Cd, are linked to an independent source of contamination. It's worth noting that Co, Cd, and Cu do not display significant correlations with the heavy metals in the previous group, except Cd-Cr, Cu-Fe, and Cu-Mn. This indicates that the sources of contamination for Co, Cd, and Cu, are distinct from those of the other metals in the Fe-Cr-Pb-Mn-Zn-Ni group. As previously discussed, Cu, Co, and Cd likely originate from effluents released by industries such as electroplating, steel, fertilizers, and pulp manufacturing.
The Kaiser-Meyer-Olkin (KMO) value and Bartlett’s test of sphericity (Significance < 0.01) together verified the appropriateness of applying PCA to the dataset. The PCA analysis effectively extracted two principal components (PC1 and PC2) with Eigenvalues 4.795 and 1.718 respectively, explaining a cumulative variance of 72.361% (Table 7). PC1 was dominated by strong loading of Mn, Fe, Ni, Zn, Pb, and had moderate loadings of Cr, and Cu, while PC2 was primarily influenced by strong loadings of Cd, and moderate Co, and Cr loading (Fig 4). The moderate influence of Cr in both components signifies its prominence as a prevalent pollutant in the Yamuna River (Bhardwaj et al. 2017). Strong loading and high correlation of Mn, Fe, Ni, Zn, Pb, and Cd clearly indicate their common source of pollution i.e., anthropogenic (Fig.4). High PC1 and PC2 scores were mainly reported from WBAD and PJ sites which receive a large amount of industrial waste (Fig 5). Descriptive data also showed high levels of these metals at Delhi and Prayagraj, confirming anthropogenic sources of pollution. There are many small and mid-scale industries that continuously discharge partly and untreated waste into the Yamuna River by drains. Najafgarh drain plays a significant role in carrying industrial (electroplating, steel, leather, paints, and pulp industries) and domestic waste from various regions of NCR, Delhi, and enhances the load of these metals in the river(Asim and Nageswara Rao 2021; Bhardwaj et al. 2017; Mandal et al. 2010).
In the current study, water quality parameters and heavy metal concentration during pre-monsoon and post-monsoon seasons were evaluated along the entire stretch of Yamuna River (YM, PS, WBBD, WBAD, and PJ). It was noted that the Delhi region, particularly WBAD, has very poor water quality, with levels of DO, EC, Ammonia and a suite of heavy metals (Pb, Fe, Mn, Cr, and Ni) beyond the BIS permissible limit and unsuitable for drinking and domestic use. In Yamuna River, Fe was found most prevalent heavy metal, while Cd was the least prevalent. The heavy metals were distributed in PRM and POM in the following order: Fe > Mn > Zn > Cu > Cr > Ni > Pb > Co > Cd and Fe > Mn > Zn > Cu > Ni > Pb > Co > Cd, respectively. Descriptive data and HPI value suggest that WBAD is the major contaminated site of the Yamuna River. Ecological risk assessment suggests that Cd, Pb, and Ni were the major risk elements and pose serious threats to ecology. Pearson correlation and PCA results clearly indicate that anthropogenic activities were responsible for heavy metal contamination in the Yamuna River. Poor water quality and heightened concentrations of heavy metals at WBAD highlight that untreated or partially treated waste from industries, STPs, medical institutes, and domestic as well as agricultural runoff was discharged into Yamuna River through the Najafgarh drain. It is recommended that regulatory authorities take immediate strict action to improve the waste treatment process and restoration mechanisms within the Najafgarh drain. Furthermore, stringent action should be implemented to control the dumping of untreated waste from industries, medical institutes, and STPs. More and more detailed investigation of water quality including heavy metal levels at regular intervals in the Yamuna River particularly Delhi National Capital Region (NCR) is essential to ensure the long-term sustainability and well-being of the Yamuna River ecosystem and the communities that depend on it.
Acknowledgement
The authors appreciate the facilities provided by the Principal of Acharya Narendra Dev College, University of Delhi, for carrying out the present study. The authors also thankfully acknowledge the financial support provided by CSIR (Council of Scientific and Industrial Research) to Mr Sandeep Antil & Ms Swati Maurya and DST-SERB (Department of Science and Technology-Science and Engineering Research Board) to Ms Jyoti Dagar. We also acknowledge Mr Ankit Arora, Ms Radha, Ms Megha Sharma & Ms Monika for their help in statistical analysis and Sachin & Dharmendra Kumar, Laboratory assistant at the Ciliate Biology laboratory, for helping in sample collection.
Funding information
This study sponsored by CSIR (Council of Scientific and Industrial Research), UGC (University Grants Commission), DST-SERB (Department of Science and Technology-Science and Engineering Research Board) and DBT (Department of Biotechnology) STAR College Scheme.
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Affiliations
- Ciliate Biology Laboratory, Department of Zoology, Acharya Narendra Dev College, University of Delhi, Govindpuri, Kalkaji, New Delhi, 110019, India
Sandeep Antil, Swati Maurya, Jyoti Dagar, Seema Makhija & Ravi Toteja
- Department of Chemistry, Acharya Narendra Dev College, University of Delhi, Govindpuri, Kalkaji, New Delhi, 110019, India
Pooja Bhagat
Corresponding author
Correspondence to Ravi Toteja.
Authors contribution
Dr. Ravi Toteja, Dr. Seema Makhija, and Dr. Pooja Bhagat collaborated in designing the study. The execution of the study, including sample collection, experimental work, and the initial draft of the manuscript, was undertaken by Sandeep Antil, with invaluable support from Swati Maurya and Jyoti Dagar. All the authors commented on the previous version of the manuscript. All authors read and approved the final manuscript.
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The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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Tables 1 to 8 are available in the Supplementary Files section
No competing interests reported.