Abstract
The Yamuna River is a threatened resource of freshwater in Delhi, India. The present study is focused on investigating three important contaminants, namely microplastics (MPs), heavy metals, and fecal coliforms in the surface water of the river, with major emphasis on MPs occurrence and characterization. MPs showed an increase in abundance in the river from the Wazirabad barrage (n = 500 MPs/m3) to the Okhla barrage downstream (n = 3,900 MPs/m3) in Delhi, with a maximum abundance downstream to the Najafgarh and Shahdara drain outfalls. White color and fragmented shape were prevalent characteristics of the isolated MPs. Attenuated total reflectance–Fourier transform infrared (ATR-FTIR) spectroscopy revealed five types of polymers. Heavy metals (chromium, lead, manganese, and iron) and fecal coliforms were at unacceptable levels at most of the sampling sites. Due to the emergence of issues concerning the tendency of MPs to actively interact with heavy metals and pathogenic microorganisms, investigation of the co-occurrence of such harmful pollutants is very important. The present study is aimed at this issue and urges similar kinds of investigations in other riverine regions of our country, as well as globally, due to their scarcity in literature. This study can further provide a baseline database to help the Government of India's efforts to clean and revive the Delhi stretch of the Yamuna River.
HIGHLIGHTS
Microplastics (MPs) were prevalent across the Yamuna River stretch with a mean abundance of 1.78 × 103 MPs/m3.
MPs were most abundant near the wastewater discharge points of the Najafgarh and Shahdara drains.
In addition to MPs, the presence of co-contaminants like heavy metals and fecal coliforms in the study area was also a serious concern.
Co-contaminant interactions may disturb the balance of several biological systems.
Graphical Abstract
INTRODUCTION
The deteriorating quality of natural aquatic environments is a global issue of concern. Due to the ongoing urbanization and industrialization, water pollution is increasing due to the mismanagement of water resources for developmental activities (Mumbi & Watanabe 2022). Around 2 billion people across the globe are reported to utilize contaminated drinking water for their needs (WHO 2022). Emerging contaminants like microplastics (MPs), pharmaceuticals, per- and poly-fluoroalkyl substances, and pesticides along with conventional pollutants like heavy metals and pathogenic microorganisms are identified as high-risk pollutants in aquatic environments (Kadim & Risjani 2022; WHO 2022). Partially treated or untreated industrial effluents and sewage discharges have been recognized as the major sources of toxic contaminants in these resources (Ghosh et al. 2021). Global trends reveal that wastewater treatment infrastructure is comparatively less effective in developing countries compared to developed countries which often creates losses in terms of human and environmental health (Mumbi & Watanabe 2022). In India also, a consistent degradation in the water quality of riverine resources has been reported due to the inflow of mismanaged sewage, industrial wastewater, solid waste, and agricultural run-off (Arora & Keshari 2021; Begum et al. 2022; Slathia & Jamwal 2022).
The Yamuna River is one of the most important freshwater resources for the megacity Delhi, located in Northern India. Through its course in the city, the river receives partially treated and untreated wastewater discharges from around 16 drains (Arora & Keshari 2021) and has been found contaminated with harmful pollutants like heavy metals, antibiotics, and pathogenic microorganisms (Bhardwaj et al. 2017; Lamba et al. 2020). Out of all the drains, the Najafgarh and Shahdara are of primary importance as they discharge the maximum load of wastewater into the river (Bhardwaj et al. 2017). Besides this, the river water quality is also affected by inefficient solid waste management practices in the city. The current trend of plastic waste generation in Delhi reaches nearly 2.3 × 105 tons annually which presents a significant risk of MP contamination in different environmental matrices of this city, especially the Yamuna River (CPCB 2021; Ghosh & Kumari 2021).
MPs are plastic particles less than 5 mm in size and are classified as emergent water pollutants due to their biological toxicity, bioaccumulation, and biomagnification potential (Naqash et al. 2020). MPs can originate from primary or secondary sources. Primary ones are intentionally designed for industrial applications, cleaning purposes, and personal care products while secondary ones are derived from the degradation of larger plastic items due to various factors like ultraviolet radiation, physical abrasion, temperature, and others (Xiang et al. 2022). Due to their distinctive properties like large surface area, small size, and inert nature, MPs can effectively interact with other contaminants in their vicinity through sorption mechanisms (Menéndez-Pedriza & Jaumot 2020).
Studies have shown interactions of MPs with heavy metals, organic pollutants like organophosphorus flame retardants, pesticides, antibiotics, and pathogenic microorganisms (Murphy et al. 2020; Xiang et al. 2022). Such interactions of MPs with other chemical or biological species may enhance their toxic potential and generate a range of health impacts if ingested by living organisms (Naqash et al. 2020). For instance, Rubin & Zucker (2022) have shown that the adsorption of triclosan (trace organic compound) on the surface of MPs increased the magnitude of toxicity in human epithelial cells Caco-2 in comparison to the exposure given for these pollutants individually. Chen et al. (2022) have also affirmed the negative consequences of heavy metal-contaminated MPs on human health in simulated conditions. In their study, it has been revealed that the acidic condition of the gastrointestinal tract does not favor the binding of metals like chromium, coppper, lead, nickel, zinc, arsenic, and manganese which leach from the surface of MPs and are suspected to cause severe health hazards. In another report by Sun et al. (2022), the authors mentioned that the toxicity of co-contaminants is enhanced due to the presence of MPs by nearly 18% in aquatic environments and cumulative health impacts like endocrine disruption, oxidative stress, cytotoxicity, immunotoxicity, genotoxicity, neurotoxicity, and other developmental disorders have been observed in aquatic organisms. Various characteristics of MPs like chemical nature, shape, density, age, and particle size determine their adsorption capacity for a particular pollutant. In addition to this, biofilm formation on the surface of MPs aggravates the accumulation of pollutants (like trace metals) found in the aquatic environments, which may lead to synergistic toxicities in the feeding organisms (Stabnikova et al. 2022). Such interactions of MPs with a wide variety of pollutants and pathogenic microorganisms also make them a suitable site for the enrichment of antibiotic resistance and metal resistance genes, ingestion of which poses a health risk not only to aquatic organisms but to humans as well (Li et al. 2021).
Globally, a significant presence of microplastics has been detected in riverine environments (Amrutha & Warrier 2020). However, the investigation of microplastic contamination in freshwater systems of India, especially Northern India, is in its pristine stages (Vaid et al. 2021). Even though the Yamuna River is the backbone of Delhi city and is facing severe pollution stress, the research on microplastic contamination in this river is very limited and we could find only one report in the literature (conducted by Ghosh & Kumari, 2021) which cites the investigation of microplastics in the Yamuna River system (Delhi stretch). Besides MPs, the Delhi stretch of the Yamuna River is reported to have alarming levels of heavy metals which exceed the permissible limits prescribed by the World Health Organization (WHO) and Bureau of Indian Standards (BIS) (Asim & Rao 2021). Fecal coliform levels which generally indicate the presence of pathogenic microorganisms are also found to be quite abundant in this river (Lamba et al. 2020). This requires immediate attention and intervention. Hence, the present study was designed with the following objectives: (1) to analyze the microplastics' distribution in the Yamuna River (Delhi stretch), and (2) to investigate the levels of co-contaminants, i.e., heavy metals and fecal coliforms, in the study area.
METHODS
Study area
Geographic details of the sampling locations
Sampling Site . | Name . | Latitude . | Longitude . |
---|---|---|---|
Y1 | Wazirabad barrage | 28°42.702′N | 77°13.871′E |
Y2 | Downstream of the Najafgarh drain | 28°42.248′N | 77°13.849′E |
Y3 | Old Yamuna Iron Bridge | 28°39.763′N | 77°14.598′E |
Y4 | ITO barrage | 28°37.727′N | 77°15.209′E |
Y5 | Nizamuddin Bridge | 28°36.015′N | 77°15.718′E |
Y6 | Downstream of the Shahdara drain (Okhla barrage downstream) | 28°32.307′N | 77°19.485′E |
Sampling Site . | Name . | Latitude . | Longitude . |
---|---|---|---|
Y1 | Wazirabad barrage | 28°42.702′N | 77°13.871′E |
Y2 | Downstream of the Najafgarh drain | 28°42.248′N | 77°13.849′E |
Y3 | Old Yamuna Iron Bridge | 28°39.763′N | 77°14.598′E |
Y4 | ITO barrage | 28°37.727′N | 77°15.209′E |
Y5 | Nizamuddin Bridge | 28°36.015′N | 77°15.718′E |
Y6 | Downstream of the Shahdara drain (Okhla barrage downstream) | 28°32.307′N | 77°19.485′E |
Sample collection, processing, and analysis
Surface water samples were collected during the morning from selected sites using the grab sampling approach (Han et al. 2020) in March 2020. For MPs analysis, ∼10 L of surface water sample (0–30 cm depth) was collected from each site using a stainless steel bucket. The samples were filtered in situ by stainless steel sieves (mesh size: 0.25 mm and 5 mm) and the residue collected on the 0.25 mm sieve was rinsed into a glass bottle (1 L) using double distilled water. The samples were then immediately sealed until further laboratory processing.
MPs were extracted from the collected samples following the modified methods of Masura et al. (2015). Briefly, the samples were subjected to oven drying (90 °C) and the resultant dry residue was treated with the wet peroxide oxidation method to digest the labile organic matter. After peroxide digestion, the mixture was sufficiently diluted with double distilled water and filtered. Preliminary sorting and identification of MPs were then carried out by visual observations under the microscope (Leica DM1L) for evaluation of their internal structure and physical properties. Procedural blanks were also run in parallel to check for any type of contamination due to other sources. MPs were isolated based on their size, elasticity, compressibility, and internal organization. A hot-needle test was further performed on selected MPs for preliminary confirmation of their identity (Kapp & Yeatman 2018). Classification of MP particles was then conducted based on their color and shape (fragment, film, pellet, fiber, and foam) and finally stored in glass vials for further characterization. In order to identify the type of polymers, a representative sample of the isolated MPs was taken from each location and analyzed using attenuated total reflectance–Fourier transform infrared (ATR-FTIR) spectroscopy (Agilent Cary 630 FTIR spectrometer with ATR accessory). The obtained sample spectrums were matched with their reference spectrums, and the matching of at least four absorption bands with the reference polymer spectrum was selected as the identification criteria for the unknown polymer (Jung et al. 2018).
For heavy metals analysis, grab surface water samples (0–30 cm) were collected in high-density polyethylene bottles followed by the nitric acid digestion method (APHA 1999). The chemicals used for digestion were of analytical grade. Heavy metals (Cr, Pb, Cd, Cu, Mn, Fe, and Zn) estimation was then performed using an atomic absorption spectrometer (Agilent AAS 280FS AA). The accuracy of the instrument was analyzed through standard reference material NIST 1640(a) and the range of recovery rate obtained was 91.7–98.2%. In addition, physicochemical parameters comprising temperature, pH, salinity, electrical conductivity, total dissolved solids, and turbidity were also determined in the study area using Eutech multiparameter PCSTestrTM 35 and Eutech turbidimeter (TN-100).
RESULTS AND DISCUSSION
Microplastics
Abundance of microplastics
In the present study, starting from the Wazirabad barrage (Y1) to downstream of the Shahdara drain point (Y6) in the Yamuna River, a significant presence of MPs was detected. Sampling points Y2 and Y6 which were located in the influence zones of the Najafgarh and Shahdara drains were found to have a maximum abundance of 2.5 × 103 and 3.9 × 103 MPs/m3, respectively (Figure 2). In a preliminary survey conducted by the research team, MP abundance in the Najafgarh drain was found to be 2.9 × 103 MPs/m3 while for the Shahdara drain it was 5.2 × 103 MPs/m3 (data not published) which supports our present findings of high MPs in the Yamuna River near the discharge points of these drains. In addition to the drains' contributions, background flow and construction activities occurring on the banks of site Y6 during the sampling time period might have also affected the MP levels.
During the site survey and sampling, it was found that on sites Y1, Y3, and Y4, religious activities were regularly practiced. Plastic bags, worship material, and other plastic products were found floating on the surface water and littered on the banks of these locations, eventually degrading and releasing MPs. For site Y5, the proximity to the Nizamuddin bridge and wear and tear due to transport activities were identified as possible sources in addition to the base flow. Overall, the mean abundance of MP particles in the Yamuna River was 1.78 × 103 MPs/m3. The present study also reveals that the Delhi stretch of the Yamuna River is much more abundant in MPs compared to that reported in many other riverine systems of India (Table 2). In view of the severe health and environmental impacts of MPs, as discussed earlier, the presence of MPs in such abundance in the Delhi stretch of the Yamuna River indicates a severe threat to the environment and various life forms associated with this river.
Comparison of MP abundance found in the present study with other riverine systems of India
Location . | Mean abundance of MPs (particles/m3) . | Reference . |
---|---|---|
Yamuna River (Delhi) | 1.78 × 103 | This study |
Adyar River (Tamil Nadu) | 0.33 × 103 | Lechthaler et al. (2021) |
Kosasthalaiyar River (Tamil Nadu) | 0.67 × 103 | Lechthaler et al. (2021) |
Muthirappuzhayar River (Kerala) | 0.20 × 103 | Lechthaler et al. (2021) |
Ganga River (India and Bangladesh) | 0.038 × 103 | Napper et al. (2021) |
Alaknanda River (Uttarakhand) | 2.26 × 103 | Chauhan et al. (2021) |
Ganga River (Ballia, Patna, Bhagalpur, Farakka, and Diamond Harbour) | 4.66 × 10−1 | Singh et al. (2021) |
Hooghly River (West Bengal) | 1.53 × 102–2.07 × 103 | Ghosh et al. (2021) |
Yamuna River (Kailash Ghat, Agra, Uttar Pradesh) | 4.00 | NPC (2020) |
Yamuna River (Dussera Ghat, Agra, Uttar Pradesh) | 4.62 | NPC (2020) |
Yamuna River (Prayagraj, Uttar Pradesh) | 2.43 | NPC (2020) |
Ganga River (Prayagraj, Uttar Pradesh) | 1.47–5.69 | NPC (2020) |
Ganga & Yamuna River Confluence (Sangam, Prayagraj, Uttar Pradesh) | 1.23 | NPC (2020) |
Netravathi River (Karnataka) | 2.88 × 102 | Amrutha & Warrier (2020) |
Location . | Mean abundance of MPs (particles/m3) . | Reference . |
---|---|---|
Yamuna River (Delhi) | 1.78 × 103 | This study |
Adyar River (Tamil Nadu) | 0.33 × 103 | Lechthaler et al. (2021) |
Kosasthalaiyar River (Tamil Nadu) | 0.67 × 103 | Lechthaler et al. (2021) |
Muthirappuzhayar River (Kerala) | 0.20 × 103 | Lechthaler et al. (2021) |
Ganga River (India and Bangladesh) | 0.038 × 103 | Napper et al. (2021) |
Alaknanda River (Uttarakhand) | 2.26 × 103 | Chauhan et al. (2021) |
Ganga River (Ballia, Patna, Bhagalpur, Farakka, and Diamond Harbour) | 4.66 × 10−1 | Singh et al. (2021) |
Hooghly River (West Bengal) | 1.53 × 102–2.07 × 103 | Ghosh et al. (2021) |
Yamuna River (Kailash Ghat, Agra, Uttar Pradesh) | 4.00 | NPC (2020) |
Yamuna River (Dussera Ghat, Agra, Uttar Pradesh) | 4.62 | NPC (2020) |
Yamuna River (Prayagraj, Uttar Pradesh) | 2.43 | NPC (2020) |
Ganga River (Prayagraj, Uttar Pradesh) | 1.47–5.69 | NPC (2020) |
Ganga & Yamuna River Confluence (Sangam, Prayagraj, Uttar Pradesh) | 1.23 | NPC (2020) |
Netravathi River (Karnataka) | 2.88 × 102 | Amrutha & Warrier (2020) |
Types of microplastics
MPs found in the Yamuna River, Delhi: (a) percentage composition of different types of MPs at each site; (b) percentage composition of different colors of MPs; (c) types of MPs detected in the study area; (i) fragment; (ii) pellet; (iii) foam; (iv) fiber; and (v) film.
MPs found in the Yamuna River, Delhi: (a) percentage composition of different types of MPs at each site; (b) percentage composition of different colors of MPs; (c) types of MPs detected in the study area; (i) fragment; (ii) pellet; (iii) foam; (iv) fiber; and (v) film.
The isolated MPs were 13 different colors (Figure 3(b)). White (61%) followed by transparent (13%) were among the predominant color types. These types of MPs are majorly derived from plastic bags, packaging materials, and fishing lines (Amrutha & Warrier 2020; Napper et al. 2021). Further, some studies also suggest that due to various environmental forces (like prolonged sunlight exposure) or extensive usability, discoloration of MPs occurs which might also have happened in this present case (Singh et al. 2021).
Characterization of MPs using ATR-FTIR spectroscopy revealed the presence of five different types of polymers based on their chemical composition: high-density polyethylene (HDPE), low-density polyethylene (LDPE), polystyrene (PS), polypropylene (PP), and polyethylene terephthalate (PET). Polyethylene is an important constituent of packaging material, shopping bags, ritual materials, and food wrappers (NPC 2020), which were also found prevalent in the present sampling sites. PS is used in the manufacturing of insulation and packaging products. PET is utilized in the manufacturing of synthetic textiles, while PP has applications in the manufacturing of food packaging material, food containers, automotive parts, and pipes (NPC 2020).
Co-contaminants present in the study area
The Yamuna River is the major freshwater resource in Delhi with a catchment area dominated by heavily urbanized areas and industrial sectors. Heavy metals containing effluents and sewage are generally directed in their raw or partially treated form into this river (Bhardwaj et al. 2017). Further, recent investigations have also revealed the contamination of this river with MP pollutants (NPC 2020; Ghosh & Kumari 2021). MPs have many harmful effects, and the situation can become even more dangerous when MPs sorb a variety of contaminants like heavy metals and persistent organic pollutants or act as a surface for pathogens colonization/biofilm formation. In view of these, the present study has also investigated the presence of two co-contaminants, namely heavy metals and fecal coliforms in the Delhi stretch of the Yamuna River system in addition to the MPs, and their respective results are discussed below.
Heavy metals
Concentration of heavy metals and other physicochemical parameters found in the surface water of the Yamuna River (Delhi stretch)
Sampling site . | Heavy metals (mg/L) . | Physicochemical parameters . | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Cr . | Pb . | Cd . | Cu . | Mn . | Fe . | Zn . | Temp. (°C) . | pH . | EC (μS/cm) . | Sal (ppm) . | TDS (ppm) . | Turb (NTU) . | |
Y1 | 0.33 | BDL | 0.001 | 0.06 | 0.81 | 2.16 | 0.13 | 19.1 | 8.1 | 258 | 163 | 183 | 61.7 |
Y2 | 0.39 | 0.01 | 0.001 | 0.13 | 0.60 | 12.21 | 0.34 | 22.2 | 7.3 | 1,703 | 1,130 | 1,120 | 57.5 |
Y3 | 0.32 | 0.01 | 0.002 | 0.06 | 0.49 | 5.91 | 0.16 | 19.7 | 7.6 | 614 | 392 | 435 | 54.8 |
Y4 | 0.12 | 0.03 | BDL | 0.03 | 0.17 | 6.24 | 0.05 | 20.8 | 7.6 | 578 | 369 | 410 | 31.2 |
Y5 | 0.12 | 0.06 | BDL | 0.09 | 0.18 | 3.84 | 0.07 | 19.6 | 7.7 | 410 | 259 | 291 | 22.4 |
Y6 | 0.12 | 0.07 | BDL | 0.04 | 0.26 | 10.15 | 0.08 | 20.7 | 7.6 | 569 | 364 | 403 | 33.0 |
Permissible limit for a drinking water source | |||||||||||||
BISa | 0.05 | 0.01 | 0.003 | 1.5 | 0.3 | 0.3 | 15.0 | – | 6.5–8.5 | – | – | 2,000 | 5.0 |
WHO | 0.05 | 0.01 | 0.003 | 2.0 | 0.08 | – | – | – | – | – | – | – | – |
Sampling site . | Heavy metals (mg/L) . | Physicochemical parameters . | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Cr . | Pb . | Cd . | Cu . | Mn . | Fe . | Zn . | Temp. (°C) . | pH . | EC (μS/cm) . | Sal (ppm) . | TDS (ppm) . | Turb (NTU) . | |
Y1 | 0.33 | BDL | 0.001 | 0.06 | 0.81 | 2.16 | 0.13 | 19.1 | 8.1 | 258 | 163 | 183 | 61.7 |
Y2 | 0.39 | 0.01 | 0.001 | 0.13 | 0.60 | 12.21 | 0.34 | 22.2 | 7.3 | 1,703 | 1,130 | 1,120 | 57.5 |
Y3 | 0.32 | 0.01 | 0.002 | 0.06 | 0.49 | 5.91 | 0.16 | 19.7 | 7.6 | 614 | 392 | 435 | 54.8 |
Y4 | 0.12 | 0.03 | BDL | 0.03 | 0.17 | 6.24 | 0.05 | 20.8 | 7.6 | 578 | 369 | 410 | 31.2 |
Y5 | 0.12 | 0.06 | BDL | 0.09 | 0.18 | 3.84 | 0.07 | 19.6 | 7.7 | 410 | 259 | 291 | 22.4 |
Y6 | 0.12 | 0.07 | BDL | 0.04 | 0.26 | 10.15 | 0.08 | 20.7 | 7.6 | 569 | 364 | 403 | 33.0 |
Permissible limit for a drinking water source | |||||||||||||
BISa | 0.05 | 0.01 | 0.003 | 1.5 | 0.3 | 0.3 | 15.0 | – | 6.5–8.5 | – | – | 2,000 | 5.0 |
WHO | 0.05 | 0.01 | 0.003 | 2.0 | 0.08 | – | – | – | – | – | – | – | – |
Abbreviations: Temp: Temperature, EC: electrical conductivity, Sal: salinity, TDS: total dissolved solids, Turb: turbidity, NTU: nephelometric turbidity units, BDL: below detection limit.
aBIS standards for a drinking water source refer to the standards IS 10500: 2012.
The presence of these two pollutants, i.e., MPs and heavy metals, together in the Yamuna River presents a major reason for concern as heavy metals are capable of being adsorbed on the surface of MPs. Recent investigations have revealed that for heavy metals, polyethylene (LDPE and HDPE) is the most favorable polymer of choice as an adsorption surface compared to PS, PP, and PET (Menéndez-Pedriza & Jaumot 2020). Also, aged MPs accumulate more metals than virgin ones (Naqash et al. 2020). In the Yamuna River, a majority of MPs found were of fragmented shape (secondary origin), possibly dismantled from plastic shopping bags, packaging materials, bottles, and other plastic utilities. Studies have found that ingestion of such heavy metals-adsorbed MPs could negatively impact the predatory performance, immune system, enzymatic activity, and growth behavior of living organisms. A further possibility to bioaccumulate in the tissues of different trophic levels across the food chain is another major concern (Naqash et al. 2020).
Fecal coliforms
In addition to the heavy metal contaminants, the Yamuna River is also reported to be contaminated with fecal coliforms. According to the report issued by DPCC (2020), fecal coliform levels were detected above 5 × 103 MPN/100 mL in the Yamuna River across the selected sites, which is an unacceptable level for a drinking water source. As per BIS and WHO standards, fecal coliform bacteria should be completely absent in a drinking water source. Analysis of fecal indicator bacteria is a globally adopted parameter for microbial pollution evaluation (Boni et al. 2021). High levels of fecal coliforms indicate the presence of pathogenic organisms which might have entered freshwater systems due to sewage discharges, fecal contaminations, or run-off. The Yamuna River has been found contaminated with antibiotic-resistant harmful bacteria like Escherichia spp., Aeromonas spp., Enterobacter spp., Klebsiella spp., Acinetobacter spp., and Pseudomonas spp. These antibiotic-resistant bacteria have shown a significant positive correlation with fecal coliform abundance in the river (Lamba et al. 2020).
MP pollutants can act as a suitable substratum for the colonization of human pathogenic microorganisms like Clostridium perfringens, Escherichia coli, Helicobacter spp., Arcobacter spp., and Enterobacter spp. (Murphy et al. 2020). Such pathogenic biofilm based-MPs might escape the conventional disinfection process in wastewater treatment plants and increase their viability and reach in the environment (Boni et al. 2021). Apart from this, it has also been reported that biofilm based-MPs could act as vectors for the transport of toxic pollutants like heavy metals in different environmental matrices and are a more attractive substrate of choice in comparison to virgin MPs (Xiang et al. 2022). Transport and ingestion of such contaminated MPs across various trophic levels in the food web could eventually generate severe health consequences in the interacting living organisms.
CONCLUSIONS
The Yamuna River serves as an important freshwater resource for the megacity Delhi. Continual inputs of untreated or partially treated wastewater in the river through several drains and improper solid waste management practices on the riverine bank have progressively generated a complex multitude of pollutants. Microplastics are emerging contaminants in this dimension and their tendency to interact with other pollutants in its vicinity is a rising concern. The current study has accounted for the distribution of MPs, heavy metals, and fecal coliforms in the Yamuna River starting at the Wazirabad barrage to the Okhla barrage downstream in Delhi. The population of MPs showed diversity in shape (n = 5), color (n = 13), and polymer (n = 5), indicating their variable sources of origin, such as wastewater discharges from several drains, bank run-off activities, religious practices, wear and tear on the road, aerial transport, plastic waste littering, and mismanagement. Downstream to the Wazirabad barrage, the flow regime in the Yamuna River is greatly influenced by wastewater discharges from several drains. Out of these, the Najafgarh and Shahdara are the two major drains that create a distress situation in this freshwater system and, alarmingly, their downstream locations in the river have shown maximum MP abundance in the present study. Apart from this, heavy metals have also occurred at the maximum concentration at these two sites. The distribution of fecal coliforms across the river is also concerning, revealing severe sewage contamination.
MPs can actively adsorb heavy metals on their surface and provide suitable substratum for the growth of pathogenic organisms. Further, the growth of biofilms could possibly alter the surface characteristics of MPs and influence their sorption behavior. This might lead to multiple pollutant accumulation on the surface of MPs, which when ingested by living organisms could have variable health impacts. Considering this scenario, it is important to formulate stringent policies for the release and management of these harmful pollutants in water bodies. Presently, regulatory guidelines exist for heavy metals and fecal coliforms but MPs have not yet been incorporated into the list, which needs immediate attention. In addition to this, it is necessary to upgrade the existing wastewater treatment infrastructure in the Yamuna River basin so that conventional pollutants like heavy metals and fecal coliforms could be effectively removed and emerging contaminants like MPs could also be addressed. In the present times, the management of water resources should be carried out in an integrated manner by the concerned authorities utilizing geospatial technology and real-time inspections of the water quality for any sort of contamination so that pollution sources could be delineated well on time and suitable action plans could be implemented before the worsening of such scenarios.
The present study is, therefore, a timely intervention to highlight the microplastic pollution in the Yamuna River along with its associated issue related to heavy metals and fecal coliforms. The outcomes of this study will help the stakeholders in taking necessary actions for better management of the Yamuna River system in Delhi, especially with reference to microplastic contamination before it becomes a severe environmental and health hazard.
ACKNOWLEDGEMENTS
The authors are thankful to Guru Gobind Singh Indraprastha University (GGSIPU) for supporting this research work by providing Faculty Research Grant Scheme (FRGS) to author AG. We would also like to thank University Grants Commission for providing Junior Research Fellowship (JRF) to author MV. The authors also acknowledge Quality Research and Analytical Labs Private Limited, Delhi for ATR-FTIR analysis.
FUNDING
This study was funded by Guru Gobind Singh Indraprastha University (GGSIPU) under Faculty Research Grant Scheme (FRGS) and University Grants Commission under Junior Research Fellowship (JRF).
DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.
CONFLICT OF INTEREST
The authors declare there is no conflict.