Unveiling the ecological landscape of bacterial ß-lactam resistance in Delhi-national capital region, India: An emerging health concern.

Inappropriate antibiotic use not only amplifies the threat of antimicrobial resistance (AMR), moreover exacerbates the spread of resistant bacterial strains and genes in the environment, underscoring the critical need for effective research and interventions. Our aim is to assess the prevalence and resistance characteristics of ß-lactam resistant bacteria (BLRB) and ß-lactamase resistant bacterial genes (BLRBGs) under various environmental conditions within Delhi NCR, India. Using a culture-dependent method, we isolated 130 BLRB from 75 different environmental samples, including lakes, ponds, the Yamuna River, agricultural soil, aquatic weeds, drains, dumping yards, STPs, and gaushalas. Tests for antibiotic susceptibility were conducted in addition to phenotypic and genotypic identification of BLs and integron genes. The water and sediment samples recorded an average bacterial abundance of 3.6 × 106 CFU/mL and an average ampicillin-resistant bacterial count of 2.2 × 106 CFU/mL, which can be considered a potent reservoir of BLRB and BLRBGs. The majority of the BLRB discovered are opportunistic pathogens from the Bacillus, Aeromonas, Pseudomonas, Enterobacter, Escherichia, and Klebsiella genera, with Multiple Antibiotic Resistance (MAR) index ≥0.2 against a wide variety of ß-lactams and ß-lactamase (BLs) inhibitor combinations. The antibiotic resistance pattern was similar in the case of bacteria isolated from STPs. Meanwhile, bacteria isolated from other sources were diverse in their antibiotic resistance profile. Interestingly, we discovered that 10 isolates of various origins produce both Extended Spectrum BLs and Metallo BLs, as well as found harboring blaTEM, blaCTX, blaOXA, blaSHV, int-1, and int-3 genes. Enterobacter cloacae (S50/A), a common nosocomial pathogen isolated from Yamuna River sediment samples at Nizamuddin point, possesses three BLRBGs (blaTEM, blaCTX, and blaOXA) and a MAR index of 1.0, which is a major cause for concern. Therefore, identifying the source, origin and dissemination of BLRB and BLRGs in the environment is of the utmost importance for designing effective mitigation approaches to reduce a load of antimicrobial resistance factors in the environmental settings.

Metagenomics analysis of water samples collected from the Yamuna River of Agra city, India.

Yamuna River water in Agra city of India is contaminated with toxic pollutants, including heavy metals that cause damage to the environment and human health. At present, the direct use of river water for drinking purposes and household activities lead to the direct exposure of society to the contaminants. In this study, Yamuna River water samples were collected from three different sites in Agra city during the monsoon, summer, and winter seasons. The physico-chemical parameters were estimated along with heavy metals. In physico-chemical parameter, the values found were mostly above the permissible limits. The results water samples contain high levels of cadmium, chromium, lead, and nickel above the desirable levels in most cases. The metagenomic analysis revealed that Proteobacteria, Bacteroidetes, Verrucomicrobia, Actinobacteria, and Planctobacteria were the most abundant phyla with a relative abundance of 61%, 9.34%, 5.23%, 4.64%, and 4.3%, respectively. The Comamonadaceae, the most abundant family consists of the genera involved in hydrogen oxidation, iron reduction, degraders of polycyclic aromatic hydrocarbons, and fermentation. The presence of Pseudomonas, Nitrosomonas sp., Thauera humireducens and Dechloromonas denitrificans (decomposition of sewage and organic matter) and Pseudomonas aeruginosa indicates the presence of heavy metal degrading bacteria in water sample. Functional prediction showed the presence of genes responsible for different metabolic pathways that could help developing new bioremediation strategies. The study concludes the status of water contamination, the presence of complex microbial community and suggests the futuristic use and their role in bioremediation.

Phosphorus distribution in the water and sediments of the Ganga and Yamuna Rivers, Uttar Pradesh, India: insights into pollution sources, bioavailability, and eutrophication implications.

River nutrient enrichment is a significant issue, and researchers worldwide are concerned about phosphorus. The physicochemical characteristics and phosphorus (P) fractions of 36 sediment and water samples from the Ganga (Kanpur, Prayagraj, Varanasi) and Yamuna (Mathura, Agra, Prayagraj) rivers were examined. Among the physicochemical parameters, pH exceeded the permissible limit in Ganga and Yamuna River water and sediment samples. Electrical conductivity (EC) and alkalinity were within the permissible limits, whereas total nitrogen (TN) exceeded the limit in Yamuna water. The analysis of phosphorus fractions indicated the dominance of inorganic phosphorus (IP) (76% in Ganga and 96% in Yamuna) over organic phosphorus in both rivers, suggesting the mineralization and microbial degradation as major processes responsible for transforming OP to IP. The positive correlation of pH with IP, AP (apatite phosphorus), and NAIP (non-apatite inorganic phosphorus) explains the release of inorganic phosphorus under alkaline conditions. The correlation between total organic carbon (TOC), TN, and organic phosphorus (OP) indicated the organic load in the rivers from allochthonous and autochthonous sources. Phosphorus released from river sediments and the concentration of phosphate in overlying river water show a positive correlation, suggesting that river sediments may serve as phosphorus reservoirs. The average phosphorus pollution index (PPI) was above one in both rivers, with relatively higher PPI values observed in the Yamuna River, indicating the contamination of sediment with phosphorus, indicating the contamination of sediment with phosphorus. This study revealed variations in the P fractionation of the sediment in both rivers, primarily as a result of contributions from different P sources. This information will be useful for applying different mitigation techniques to lower the phosphorus load in both river systems.

Spatio-temporal investigation of physico-chemical water quality parameters based on comparative assessment of QUAL 2Kw and WASP model for the upper reaches of Yamuna River stretching from Paonta Sahib, Sirmaur district to Cullackpur, North Delhi districts of North India.

An accurate investigation of bio-physical and chemical parameters as proxy of in situ water quality conditions in the Himalayan region is highly challenging owing to cumbersome, strenuous, and physically exhausting sampling exercises at high altitude locations. The upper stretches of Yamuna River in the Himachal Pradesh are typical examples of such sampling locations that have rarely been examined in the past studies. A widely accepted and recognized QUAL 2Kw model is applied for estimating the water quality parameters on the upper segment of the Yamuna River from Paonta Sahib to Cullackpur. These water quality indicators mainly included electric conductivity, pH, dissolved oxygen, temperature, carbonaceous biological oxygen demand (CBOD), inorganic suspended solids, total nitrogen, total phosphorus, and alkalinity, which were systematically investigated for predicting the spatio-temporal trends during the year 2018. A total of 12 distantly located river sites were identified for sample collection and data validation using QUAL 2Kw model. The present investigation attempts to reveal long-term degraded impact of untreated wastewater and biased agricultural practices on the water quality conditions over the upper stretches of Yamuna River. The QUAL 2Kw-derived values for selected variables were inter-compared with in situ values, and any deviation from measured values was ascertained based on meaningful statistical measures. The lower error of RMSE, MRE, and BIAS, corresponding to < 15%, ± 10%., ± 20%, and ~ 1 slope evidently indicated better matchup of values, wherein, higher slope correlation coefficient (R2) of ~ 90% indicated the robust performance of the QUAL 2Kw algorithm in accurately predicting the chosen variables. A comparative assessment of QUAL 2Kw and WASP has been performed to justify aptness of water quality model in scenarios of lean flow.

Assessment of toxicity and potential health risk from persistent pesticides and heavy metals along the Delhi stretch of river Yamuna.

The present study aims at the assessment of environmental quality of the most polluted stretch of river Yamuna along the megacity of Delhi. The study was conducted in order to examine toxicity and health hazards associated with persistent pollutants present in the fluvial ecosystem. Eighty four sediment and 56 vegetable samples from same locations were collected from the Delhi segment of river Yamuna flood plain in order to examine 20 organochlorine pesticides (OCPs) and 9 heavy metals (Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn). Both the organic and inorganic groups of persistent toxic substances were monitored and analysed for the extent of eco-toxicological as well as dietary health risks posed to the local population. Eco-toxicological assessment was done based on sediment quality guidelines, enrichment factor, geo-accumulation index, degree of contamination and Pollution Load Index. The dietary-risk was assessed with the help of translocation factors (TF) of these pollutants in vegetables. Carcinogenic and non-carcinogenic health risks from consumption of vegetables were also investigated. The level of concern for heavy metals was greater than that of OCPs as per the sediment quality guidelines. DDT, Cd, Pb and Zn had maximum concentrations corresponding to level 3 of concern, while Cr and Ni reached up to the highest i.e., 4th level of concern. Sediment samples were found to be enriched and contaminated significantly with Cd and moderately with Pb, as represented respectively by enrichment factors and contamination factors (CF). CF for metals lied in order Zn > Cd > CrNi > PbCu. Pollution load index was highest at the location lying on the exit point of Yamuna in Delhi. TF values greater than 1 were observed in majority of samples analysed for Ni, Cr, Cu and Zn. Spinach topped among vegetables in terms of metal contamination. Cd, Ni and Pb accumulated more in the roots, as against Mn, Zn, Cu and Cr which had higher accumulation in the shoots. Translocation factors were substantially high in vegetables for most of the OCPs, clearly indicating bioaccumulation and potential health risk to the consumers. Health risk to humans was assessed for non-carcinogenic and carcinogenic potentials from ingestion of vegetables. Hazard Quotient (HQ) > 1 due to radish (roots and leaves) and cauliflower consumption in children indicated non-carcinogenic risk. Hazard Index (HI) beyond 1 for all the vegetables (except onion leaves) confirmed substantial cumulative risk. Lifetime cancer risk (LCR) revealed moderate (spinach, radish, beet root and cauliflower) to low (all the others) levels of carcinogenic risk to humans. Cancer risks from γ-HCH, ß- HCH, Hept, Hept Ep, Ald, p,p'-DDT, and Cr exposure through the food chain could be well established.

Assessment of heavy metal pollution in Yamuna River, Delhi-NCR, using heavy metal pollution index and GIS.

The present study was conducted on the river Yamuna, which passes through Delhi-NCR from Baghpat to Chhainssa, a distance of about 125 km, at six sampling locations to evaluate the concentrations of heavy metals in surface water using heavy metal pollution index (HPI) approach. The river serves both urban-industrial and rural areas in the study area; hence, domestic, industrial, and agricultural wastes are being contributed greatly in the contamination of river water. The Yamuna River is one of the major tributaries of the river Ganga originated in the Himalayas and is flowing through a varied geological terrain. Metals such as iron (Fe), copper (Cu), cobalt (Co), zinc (Zn), lead (Pb), cyanide (CN), nickel (Ni), and chromium (Cr) in selected sites of Yamuna River water were determined by using atomic absorption spectrophotometer. The concentrations of Fe, Cu, Co, Zn, Pb, CN, Ni, and Cr in the river water were found to be in the range of 40-190, 50-120, 4-66, 840-1800, 2-40, 100-600, 88-253, and 35-52 µg/L, respectively. The results show that the maximum heavy metal content was found at sampling site S3 (Nizamuddin) followed by S6 (Chhainssa), S4 (Okhla), S1 (Baghpat), S5 (Manjhawali), and S2 (Pachahira). The heavy metal data was integrated in GIS environment for preparing spatial distribution maps of sampling sites. A scatter plot matrix was created to assess the pattern and interrelationships between heavy metals. The average concentration of heavy metals was recorded high, often exceeding the permissible limits for drinking of surface water prescribed by the Bureau of Indian Standards (BIS) and World Health Organization (WHO). Based on HPI (varies from 98.2 to 555.1), about 85% of the river water was classified as highly polluted; hence, it is not recommended for drinking. Overall, significant variations were observed in concentrations of heavy metals from one location to the other which may be because of toxic industrial effluents and domestic sewage wastes being added to the river water by various anthropogenic activities in the study area. The present work highlights the pollution load of heavy metals in the river Yamuna and also advocates an urgent attention towards minimizing the health risk of people residing not only along the river banks and surrounding regions but also for city population.

Seasonal variation of potentially toxic metal contamination in Yamuna riverine ecosystem, Delhi, India.

The River Yamuna in Delhi region, the National Capital Territory (NCT) of India, carries potentially toxic metals such as Cr, Pb, Mn, Mg, Hg, Fe and Zn. These contaminants are discharged mainly from industrial wastes, agricultural and household activities and domestic sewage. A total of 12 stations (2.5 to 3.5 km apart from each other) were selected for the study, covering the upstream and downstream areas of river Yamuna in Delhi. The investigated sites were evaluated for significant difference between upstream and downstream locations of river Yamuna in three different time periods (June, October, February). Metal contamination were measured in water, sediments (2 µm) and nearby agriculture soil of the river Yamuna, and found with high metal loads as compared with the international standards, chiefly in the downstream sites as the river flows through the Delhi stretch. The multivariate statistical analysis revealed spatial and temporal variations in the metal concentrations which suggest seasonal variation and common point source of some metals while different sources of other metals. The contamination of the river water and adjoining agriculture soils points towards possible entry of these metals into the food chain. The study indicates that considering the current status of metal pollution, the surface water is not in good conditions for use as drinking purpose because of the high concentrations of few potentially toxic metals. Our study recommends regular monitoring of toxic metals in Yamuna river water and sediments, strict ban on the domestic, agriculture and industrial waste disposal for the restoration of the river to its natural state.

Identification of emerging contaminants and their transformation products in a moving bed biofilm reactor (MBBR)-based drinking water treatment plant around River Yamuna in India.

The prevalence of emerging contaminants of concern in water regimes is very common these days. High anthropogenic intervention is leading to occurrence of various types of microcontaminants of concern in drinking water systems. Their removal using conventional form of treatment systems employed in water treatment plants is not widely researched upon. Their fate in the conventional as well as advanced water treatment system needs to be focused upon for efficient and safe water disposal. Some compounds may leave the system unchanged or some might transform into much more toxic byproduct. Moreover, understanding level of occurrence of these emerging contaminants in source water bodies is also quintessential for assessing their fate in treatment plant itself as well as in the final treated water. Here in this study, the occurrence and removal of various classes of emerging contaminants were investigated in a moving bed biofilm reactor (MBBR)-based advanced drinking water treatment plant (ADWTP) alongside one conventional drinking water treatment plant, both of which use River Yamuna as the source of water. Non-target analysis utilizing high-performance liquid chromatography combined with time of flight (HPLC-QToF) identified more than 300 compounds. Pharmaceuticals accounted for a major fraction (58%) of the identified compounds, followed by plasticizers and insecticides. Nine parent compound and their transformation products were additionally identified using solid-phase extraction followed by analysis using gas chromatography mass spectrometry and HPLC-QToF. The degradation pathway of the parent compounds in MBBR-based ADWTP was also analyzed in depth. The efficiency of each unit process of MBBR-based drinking water treatment plant was studied in terms of removal of few emerging contaminants. Pharmaceutical compound like diclofenac supposedly was persistent, even, toward the end of the treatment train. Semi-quantitative analysis revealed ineffective removal of pyridine, hydrochlorothiazide, and diethyl phthalate in the outlet of ADWTP. ADWTP was able to remove a few emerging contaminants, but a few were recalcitrant. Likewise, it was established that although some parent compounds were degraded, much more toxic transformation products were formed and were prevalent at the end of the treatment.

Identifying waterborne disease prone areas using geospatial approach along the right bank of Yamuna River in Delhi.

This paper presents a spatial risk analysis of waterborne diseases using analytical hierarchy process that rely on geographical information system (GIS)-automated techniques. We selected nine parameters for assessing waterborne diseases prone areas (WBDP). All the weighted parameter layers were integrated to obtain WBDP map. Of the total WBDP area, 42% area was found under medium category, 34% and 24% area under high and low category, respectively. We have also empirically analysed the factors influencing WBDP areas using regression model. Results revealed that explanatory variables like purification of water, washing hand before drinking and eating, and Surface Water Quality Index (SWQI) are the most influential and positively associated while dipping hand in the vessel is negatively associated with the WBD. Further, WBDP areas were validated by analysing their relationship with the actual incidences of WBD(s). Our study may prove to be beneficial for managing and formulating guidelines for the WBDP areas in similar geographical regions. Abbreviations: GIS: Geographical information system; WBDP: Water borne diseases prone areas; SWQI: Surface water quality index; WBD: Water borne Disease; MDG: Millennium Development Goal; AHP: Analytical hierarchical process; GPS: Global Positioning System; NCR: National Capital Region; IDW: Inverse distance weighted; pH: Potential of Hydrogen; TDS: Total dissolved solid; COD: Chemical Oxygen Demand; BOD: Biochemical Oxygen Demand; TA: Total alkalinity; TH: Total Hardness; Cl: Chlorination; SO4: Sulphate, NO3: Nitrate; FL: Floride; ICMR: Indian Council of Medical Research; ISB: Indian Standards Bureau; RW: Relative weights; WQI: Water Quality Index; DJB: Delhi Jal Board; MDG: Millennium Development Goals; GWQI: Ground Water Quality Index; MCD: Municipality Corporation of Delhi; CPCB: Central Pollution Control Board.

Development of indices for surface and ground water quality assessment and characterization for Indian conditions.

Water quality indices are mathematical equations that transform water quality data into a particular number which describe the status of water. A number of water quality indices have been developed by various researchers for categorizing the water quality for different uses. These indices are developed based on classification criteria, sub-indices, and aggregation function. In the present study, a generalized Composite Water Quality Index (CWQI) is developed to classify the water into five categories, viz excellent, good, fair, poor, and polluted. For this purpose, the concentration ranges have been categorized on the basis of the Indian Standards (IS) and Central Pollution Control Board (CPCB) standards and considering International standards of World Health Organization (WHO) and European Commission (EC). Twenty-five water quality parameters are selected based on the social and environmental impacts, and weights are computed using the Saaty's Analytic Hierarchy Process (AHP) Multiple Criteria Decision Analysis (MCDA) tool. These parameters are selected such that the same indices can be used to assess the quality of both surface and ground water. The computed weights minimize the subjectivity in assigning the parameter weights. The proposed index improves understanding of water quality issues by integrating complex data and generates a score which describes the status of water quality. The index will be very useful for the water management authorities to maintain good health of surface water resources.

Comprehensive evaluation of water quality status for entire stretch of Yamuna River, India.

This study represented the first comprehensive assessment of the physicochemical water quality status of the entire Yamuna River stretch in India. The upper zone had "excellent-to-good" water quality index (WQI) with mean 5-day biochemical oxygen demand (BOD5) values of 2.1 and 2.4 mg/L during monsoon and non-monsoon, respectively. The middle region was described by "poor-to-marginal" WQI with average BOD5 values of 13.1 mg/L (monsoon) and 32.3 mg/L (non-monsoon). The low WQI observations at the midstream region were due to the negative impact of two major drains, namely Najafgarh and Shahdara, that carry partially treated effluents from industrial units. Further, BOD5 decreased to 1.9 mg/L (monsoon) and 1.8 mg/L (non-monsoon) in the lower zone, and the WQI values improved to "good" and "excellent". The dilution and depuration effects of the Chambal, Sindh, Betwa, and Ken Rivers recovered the environmental conditions in downstream stations. The oxygen sag curve complied with the water quality status along the river stretch. Based on the principal component analysis, the Yamuna River was strongly influenced by dissolved mineral salts originating from atmospheric deposition, weathering of soils and rocks, and application of deicing chemicals and landfills. Moreover, organic and nutrient substances and biological activities resulting from the discharge of sewage, and the utilization of fertilizers in agriculture, were the second contributors to pollution. The statistical techniques employed in this work could be beneficial for decision-makers (government and stakeholders) to identify the pollution sources/factors and to determine the viability of water bodies for domestic applications.

Fate of pharmaceutical active compounds (PhACs) from River Yamuna, India: An ecotoxicological risk assessment approach.

The river Yamuna is a major tributary of river Ganges and is a major source of freshwater in the National Capital Territory (NCT) catering 16.8 million people. This is the first report on occurrence, fate and ecotoxicological risk assessment of various pharmaceuticals active compounds (PhACs) in the Yamuna river. In this study, spatial and temporal distribution of nine PhACs "aspirin, ibuprofen, paracetamol, caffeine, ranitidine, diclofenac, carbamazepine, codeine, and diazepam", belonging to different therapeutic groups have been reported. Nine PhACs were analyzed in all the samples collected from the NCT stretch of river Yamuna. No specific trend in the distribution of the pharmaceutical residues was observed, however, the results revealed comparably higher PhACs contamination at YMN-2 (downstream Wazirabad, at this point, Najafgarh drain joins river Yamuna). Ecotoxicological risk assessment was carried out using Hazard quotients (HQ) for normal and worst case scenarios. The HQ showed that the levels of PhACs present in the samples were insufficient to cause acute toxicity to the flora and fauna of the river Yamuna. However, such residues could possibly cause chronic toxicity to the aquatic life and human beings as a huge amount of water of the river Yamuna is used for the drinking purposes in the NCT Delhi, the state capital of India.

Estimation of environmental flow incorporating water quality and hypothetical climate change scenarios.

Environmental flows (Eflow, hereafter) are the flows to be maintained in the river for its healthy functioning and the sustenance and protection of aquatic ecosystems. Estimation of Eflow in any river stretch demands consideration of various factors such as flow regime, ecosystem, and health of river. However, most of the Eflow estimation studies have neglected the water quality factor. This study urges the need to consider water quality criterion in the estimation of Eflow and proposes a framework for estimating Eflow incorporating water quality variations under present and hypothetical future scenarios of climate change and pollution load. The proposed framework is applied on the polluted stretch of Yamuna River passing through Delhi, India. Required Eflow at various locations along the stretch are determined by considering possible variations in future water quantity and quality. Eflow values satisfying minimum quality requirements for different river water usage classes (classes A, B, C, and D as specified by the Central Pollution Control Board, India) are found to be between 700 and 800 m3/s. The estimated Eflow values may aid policymakers to derive upstream storage-release policies or effluent restrictions. Generalized nature of this framework will help its implementation on any river systems.

Environmental health risk assessment and source apportion of heavy metals using chemometrics and pollution indices in the upper Yamuna river basin, India.

River Yamuna is the largest tributary of the Ganges with great economic importance, and provides water for about 57 million people and accounts for more than 70% of Delhi's water supply. Various pollution indices and chemometric methods were used to investigate heavy metal pollution, associated risks, and probable sources in the upper Yamuna river water. A total of 56 river water samples, 28 each in pre and post-monsoon season were collected and analysed for 15 heavy metals. The findings reveal that Al (38.66 ± 21.14 µg/L), As (16.52 ± 15.81 µg/L), and Mn (41.06 ± 89.25 µg/L) in pre-monsoon and Al (45.77 ± 29.46 µg/L), As (10.30 ± 12.15 µg/L), Fe (48.03 ± 81.11 µg/L), and Mn (31.02 ± 70.13 µg/L) in post-monsoon exceeded the Bureau of Indian Standards (BIS) acceptable limits. The pollution indices (HPI, NPI, HEI, and Cd) indicate that most locations are low to moderately polluted, except for the lower catchment. Health indices, i.e., hazard Index (HI) and incremental lifetime cancer risk (ILCR), suggest that the prolonged consumption of river water may cause potential human health hazards. In contrast, the water is suitable for domestic and other uses as the dermal risk is less prominent. The ecological risk index (ERI) of pre (0.22-58.75) and post-monsoon (0.12-44.21) were in the low-risk category (<110), indicating no ecological risk associated with heavy metals. In pre and post-monsoon, four principal components (PCs) described 73.97% and 76.18% of the total variance respectively, suggesting the mixed impact of numerous geogenic and anthropogenic sources in the region's water chemistry. Cluster analysis demonstrates that the lower catchment samples (National Capital Region, Delhi) significantly vary from each other due to wastewater discharge, industrialisation, and rapid urbanization, while the upper and mid-catchment samples are less distinct. Hence, more than 90% of the Yamuna water is extracted from the upper region; present findings may aid in developing an effective catchment scale management strategy.

Ecological and human health risk from exposure to metal contaminated sediments in a subtropical river affected by anthropogenic activities: A case study from river Yamuna.

Heavy metal enrichment in river sediments poses a significant risk to human and aquatic health. The Yamuna River faces severe challenges due to untreated industrial and domestic wastewater discharge. The study evaluates sediment metal content, ecological and human health risks, and potential sources. Results showed Cd and Pb exhibited moderate to severe contamination and displayed ecological risk based on contamination factor, enrichment factor, and potential ecological risk. According to synergistic indices (pollution load index, PINemerow, toxic risk index, contamination security index, mean probable effects level quotients, and probability of toxicity), the sediment in the Yamuna River doesn't seem to have a risk or enrichment from combined metals. Cd and Pb mainly originate from anthropogenic sources. Hazard index (< 1) and carcinogenic risk (2.2 × 10-7 to 4.7 × 10-5) assessments suggest metal didn't pose any risk to humans exposed to sediment. The present study aids in developing pollution control strategies for the Yamuna River.

A comprehensive assessment of macro and microplastics from Rivers Ganga and Yamuna: Unveiling the seasonal, spatial and risk factors.

There have been growing apprehensions and concerns regarding the increasing presence of plastic pollutants in the holiest river of India, the Ganga, and its major tributary, Yamuna. In response to this issue, the current study aimed to conduct a comprehensive investigation of the seasonal and spatial distribution of macro to microplastics (MPs) in the surface water, water column, and sediments from the River Ganga and Yamuna. MP samples were collected from various points of these Rivers, including upstream, downstream, and drainage points around the vicinity of Haridwar, Agra, Prayagraj, and Patna cities. With a significant seasonal variation, the estimated MPs and plastic flux were higher during the wet season than during the dry season. MPs sized 300 µm-1 mm and fibre-shaped blue and black colored MPs were pre-dominant in both rivers. Polyacrylamide, polyamide, and polyvinyl chloride were the most ascertained polymers. MPs including hazardous polymers (hazard score >1000) may pose a risk to the population of Indo-Gangetic Plain via direct and indirect exposure to MPs. The information provided in this study could serve as a starting point for the action plan required by municipal corporations to mitigate plastic pollution and target the possible sources at each location.

Degradation effectiveness of hexachlorohexane (ϒ-HCH) by bacterial isolate Bacillus cereus SJPS-2, its gene annotation for bioremediation and comparison with Pseudomonas putida KT2440.

The contamination of Hexachlorohexane (Lindane) in soil and water has toxic effects due to its persistent nature. In our study, an indigenous HCH (gamma isomer) degrading bacterium viz Bacillus cereus SJPS-2 was isolated from Yamuna river water using enrichment culture method. The growth curve indicated that Bacillus cereus SJPS-2 was able to degrade ϒ-HCH effectively with 80.98% degradation. Further, process was improved by using immobilization using alginate beads which showed enhanced degradation (89.34%). Interestingly, in presence of fructose, the ϒ-HCH degradation was up to 79.24% with exponential growth curve whereas the degradation was only 5.61% in presence of glucose revealing diauxic growth curve. Furthermore, The FTIR results confirmed the potential lindane degradation capability of Bacillus cereus SJPS-2 and the bonds were recorded at wavelengths viz. 2900-2500 cm-1, 3300-2800 cm-1 and 785-540 cm-1. Similarity, the GC studies also reconfirmed the degradation potential with retention time (RT) of ethyl acetate and lindane was 2.12 and 11.0 respectively. Further, we studied the metabolic pathway involved for lindane utilization in Bacillus cereus using KEGG-KASS and functional gene annotation through Rapid Annotation using Subsystems Technology (RAST) resulted in the annotation of the lin genes (lin A, lin B, lin C, lin X, lin D, lin E) and respective encoding enzymes. The comparative ϒ-HCH degradation potential of B. cereus and P. putida KT2440 was also evaluated. The island viewer showed the different colors on circular genome indicate the coordinates of genomic islands resulted with some common genomic islands (GEIs) between both bacteria indicating the possibility of horizontal gene transfer at contaminated site or natural environment. These genomic islands (GEIs) contribute in the rearrangement genetic material or to evolve bacteria in stress conditions, as a result the metabolic pathways evolve by formation of catabolic genes. This study establishes the potential of Bacillus cereus SJPS-2 for effectual ϒ-HCH degradation.

The plight of Najafgarh drain in NCT of Delhi, India: assessment of the sources, statistical water quality evaluation, and fate of water pollutants.

The Najafgarh drain is the first major drain that joins the Yamuna River at Wazirabad in Delhi, India, and is known to contribute to the maximum pollution load to this river. The drain is originally an extension of the Sahibi River and was intentionally constructed as a canal to carry stormwater, but presently, it is carrying more of sewage, agricultural, and industrial effluents received through various small and large secondary drains. The present study has analyzed the water quality status of this interconnected system, i.e., the Najafgarh drain, its associated secondary drains, and the Yamuna River for physicochemical parameters (n = 16), microbiological parameter (n = 1), and heavy metal concentrations (n = 8). The analysis of the surface water samples collected during pre- and post-monsoon seasons showed that secondary drain discharges significantly impacted the water quality of the Najafgarh drain, which in turn affected the Yamuna River. Out of the eight selected secondary drains for this study, the Goyla dairy outlet came out as the most polluted site in terms of organic pollutants while the Basaidarapur drain was loaded with heavy metal contaminants. Statistical tools comprising hierarchical cluster analysis (HCA), Pearson's correlation, and principal component analysis (PCA) were further implemented on the water quality dataset for a better understanding of the possible sources of contamination for organic and inorganic pollutants in the selected sampling sites. The present study, thus, might help in providing key highlights to the policymakers for effective regulation and management of the point source discharges in Najafgarh drain, which will ultimately restrict its pollution loadings in Yamuna River, Delhi, and also help in the restoration of this important water body.

Water quality assessment of a river using deep learning Bi-LSTM methodology: forecasting and validation.

Water is a prime necessity for the survival and sustenance of all living beings. Over the past few years, the water quality of rivers is adversely affected due to harmful wastes and pollutants. This ever-increasing water pollution is a big matter of concern as it deteriorating the water quality, making it unfit for any type of use. Recently, water quality modelling using machine learning techniques has generated a lot of interest and can be very beneficial in ecological and water resources management. However, they suffer many times from high computational complexity and high prediction error. The good performance of a deep neural network like long short-term memory network (LSTM) has been exploited for the time-series data. In this paper, a deep learning-based Bi-LSTM model (DLBL-WQA) is introduced to forecast the water quality factors of Yamuna River, India. The existing schemes do not perform missing value imputation and focus only on the learning process without including a loss function pertaining to training error. The proposed model shows a novel scheme which includes missing value imputation in the first phase, the second phase generates the feature maps from the given input data, the third phase includes a Bi-LSTM architecture to improve the learning process, and finally, an optimized loss function is applied to reduce the training error. Thus, the proposed model improves forecasting accuracy. Data comprising monthly samples of different water quality factors were collected for 6 years (2013-2019) at several locations in the Delhi region. Experimental results reveal that predicted values of the model and the actual values were in a close agreement and could reveal a future trend. The performance of our model was compared with various state of the art techniques like SVR, random forest, artificial neural network, LSTM, and CNN-LSTM. To check the accuracy, metrics like root mean square errors (RMSE), the mean absolute error (MAE), mean square error (MSE), and mean absolute percentage error (MAPE) have been used. Experimental analysis is carried out by measuring the COD and BOD levels. COD analysis reveals the MSE, RMSE, MAE, and MAPE values as 0.015, 0.117, 0.115, and 20.32, respectively, for the Palla region. Similarly, BOD analysis indicates the MSE, RMSE, MAE, and MAPE values as 0.107, 0.108, 0.124, and 18.22, respectively. A comparative analysis reveals that the proposed model outperforms all other models in terms of the best forecasting accuracy and lowest error rates.

Implementation of data intelligence models coupled with ensemble machine learning for prediction of water quality index.

In recent decades, various conventional techniques have been formulated around the world to evaluate the overall water quality (WQ) at particular locations. In the present study, back propagation neural network (BPNN) and adaptive neuro-fuzzy inference system (ANFIS), support vector regression (SVR), and one multilinear regression (MLR) are considered for the prediction of water quality index (WQI) at three stations, namely Nizamuddin, Palla, and Udi (Chambal), across the Yamuna River, India. The nonlinear ensemble technique was proposed using the neural network ensemble (NNE) approach to improve the performance accuracy of the single models. The observed WQ parameters were provided by the Central Pollution Control Board (CPCB) including dissolved oxygen (DO), pH, biological oxygen demand (BOD), ammonia (NH3), temperature (T), and WQI. The performance of the models was evaluated by various statistical indices. The obtained results indicated the feasibility of the developed data intelligence models for predicting the WQI at the three stations with the superior modelling results of the NNE. The results also showed that the minimum values for root mean square (RMS) varied between 0.1213 and 0.4107, 0.003 and 0.0367, and 0.002 and 0.0272 for Nizamuddin, Palla, and Udi (Chambal), respectively. ANFIS-M3, BPNN-M4, and BPNN-M3 improved the performance with regard to an absolute error by 41%, 4%, and 3%, over other models for Nizamuddin, Palla, and Udi (Chambal) stations, respectively. The predictive comparison demonstrated that NNE proved to be effective and can therefore serve as a reliable prediction approach. The inferences of this paper would be of interest to policymakers in terms of WQ for establishing sustainable management strategies of water resources.