Water Quality Parameters Research Articles

Assessment of plankton diversity and physico-chemical characteristics for sustainable fish production in a tropical reservoir in South India

Plankton forms an important component of the aquatic ecosystem and act as indicators of fish diversity, pollution levels and environmental disturbances. They form an important natural fish food resource and play a vital role in the trophic structure of the ecosystem. In the present study a systematic assessment of the community distribution and diversity of plankton was conducted in the Karapuzha Reservoir in South India. Thirty six genera of phytoplankton belonging to 4 classes viz, Chlorophyceae, Bacillariophyceae, Dinophyceae and Myxophyceae were identified. Eleven genera of zooplankton belonging to four classes; Protozoa, Rotifera, Cladocera and Copepoda were also recorded. The Jaccard index of similarity showed that pre-monsoon and monsoon seasons shared a similar plankton composition. Diversity indices revealed the highest values during monsoon, while the Dominance index indicated the highest species dominance during post-monsoon (0.199) followed by pre-monsoon (0.1445) and monsoon (0.1417). Water quality parameters were found to have a significant correlation with plankton abundance in the reservoir. ShannonWeiner index indicated that the Karapuzha Reservoir ecosystem is moderately polluted. Seasonal variations in plankton composition showed the highest species abundance during the pre-monsoon followed by post-monsoon and monsoon seasons. Keywords: Diversity index, Plankton abundance, Planktivorous fish, Reservoir ecosystem, Seasonal variation

The Effect of Water Quality on the Performance Growth of Vannamei Shrimp (Litopenaeus vannamei) at the Center for Brackish Aquaculture Fisheries

Vaname shrimp is one of the leading commodities of the aquaculture sector, with high production rates influenced by the rapid growth period and relatively short maintenance time, high stocking density production system, has a high appetite for food and has good resistance to disease. This study aims to assess the effect of water quality on the growth of vaname shrimp (Litopenaeus vannamei) in ponds. Water quality measured includes temperature, salinity, dissolved oxygen (DO), and pH, all of which play an important role in the growth and health of shrimp. The methods used in this study included periodic measurements of water quality parameters in the morning and evening in four ponds (A5.1, A5.2, A6.1, and A6.2), as well as observations of Average Body Weight (ABW), Average Daily Growth (ADG), and Survival Rate (SR) of shrimp. The results showed that ponds A5.1, A5.2, and A6.1 showed an increase in SR and biomass values, while A6.2 experienced a decrease in SR and biomass values caused by the outbreak of White Feces Disease. This is influenced by temperature, salinity, and DO parameters that are not in the optimal range for shrimp growth. Fluctuations in water quality parameters can significantly affect shrimp metabolism and health. Therefore, good water quality management, including water change cycles and sterilisation, is essential to prevent health problems and improve the growth of vaname shrimp. This study emphasises the need for attention to water quality in vaname shrimp farming to achieve optimal results.

Assessing anthropogenic influences on the water quality of Gomati River using an innovative weighted fuzzy soft set based water pollution rating system

The increasing pollution of river systems poses a significant challenge to water quality management and public health. This study was conducted to evaluate the water quality of the Gomati River in India, focusing on the impact of anthropogenic activities on pollution levels across different seasons. The primary objective was to develop a comprehensive assessment model using an effective weighted fuzzy soft expert system (WFSES) to derive a weighted water pollution score (WWP-score) for rating water pollution levels based on various water quality parameters. To achieve this, we employed a fuzzy soft set (FSS) methodology integrated with a weighted fuzzy soft set (WFSS) model to analyze water quality indices at six sampling stations along the Gomati River, the largest river in Tripura, India. Originating from the Raima and Sarma streams, the river flows westward through key regions, providing 249.39 million cubic meters of water annually, essential for drinking, agriculture, fishing, and transportation. The study utilized crisp data summaries of key water quality parameters, including pH, total dissolved solids, total suspended solids, electrical conductivity, biochemical oxygen demand, dissolved oxygen, total hardness, chloride, total alkalinity, and total coliform, across the pre-monsoon, monsoon, and post-monsoon seasons from May 2022 to April 2023, guided by the distribution of waste discharge points. Fuzzy membership functions were defined for these parameters, and the root mean square (RMSQR) operation was used to combine multiple FSSs. The results revealed that the WWP-scores, a measure of water quality, ranged from 0.744 to 0.872 across the sampling stations, with Srimantapur exhibiting the highest level of pollution and Udaipur showing comparatively better quality. These scores indicate that water quality at all sites falls into the poor category, with Srimantapur experiencing the most severe contamination due to high levels of coliform bacteria and organic pollutants. The analysis highlights the impact of domestic wastewater and agricultural runoff on the river's health. This research offers a novel application of FSS and WFSS theory in environmental management, providing a robust framework for evaluating and ranking water quality across multiple parameters. The findings are valuable to the scientific community as they offer detailed insights into the pollution dynamics of the Gomati River and propose a methodological approach for assessing water quality in other river systems facing similar challenges. The study's results underscore the need for targeted pollution control measures and continuous monitoring to safeguard water resources and public health.

Purification Resistance Index: A new water quality assessment method toward drinking water production

Water quality assessment plays a significant role in ensuring the availability of clean and safe water. The Water Quality Index (WQI) model method has been developed to provide a basis for assessing water quality by integrating various water quality parameters. However, existing WQIs do not “actively” consider the difficulty of water treatment from raw water to specific water use scenarios. This study proposes a novel model framework, named as Purification Resistance Index (PRI), quantitatively evaluating not only the exceedance of pollutants but also how difficult they can be removed in the water treatment process. The framework is built based on the conventional drinking water treatment processes, with sub-indices for coagulation-sedimentation (rc), filtration (rf), disinfection (rd), and advanced treatment (ra). The model considers appropriate weights assigned to each sub-index to calculate the purification resistance, resulting in a comprehensive index for water quality evaluation. Case studies on nationwide and citywide water source reservoirs demonstrated the applicability of PRI approach. PRI breakthrough the traditional water quality risk assessment paradigm and extents to engineering region and provide useful tools for water source supervision, drinking water treatment plant planning and updating, operation control, and other purposes. Water authority, water utility and municipal design institute will all benefit. It is open for more localized practices validation and discussion.

Impact of Water Quality and Phytoplankton on Juvenile Vannamei Shrimp Growth in Low-Salinity Ponds

The Vannamei shrimp (Litopenaeus vannamei) is a key species in global aquaculture, with its growth influenced by various environmental factors and nutritional quality. This study aimed to analyze water quality parameters and phytoplankton density, as well as assess the growth of juvenile Vannamei shrimp in circular ponds with low salinity (5-6 ppt). Shrimp were stocked at a density of 80 individuals per square meter in 5-ton capacity tanks and fed four times daily over a 30-day period. Water quality parameters, including temperature, dissolved oxygen, pH, and light intensity, were monitored bi-daily, revealing fluctuations that impacted shrimp health. Notably, plankton density assessments showed Cyclotella present on day 14 but absent on day 28, while Microcystis and Rhizosolenia were detected on day 28, indicating shifts in the phytoplankton community. The specific growth rate (SGR) of shrimp was measured at 18.69% per day, with initial and final weights recorded at 0.01 ± 0.00 g and 2.72 ± 0.23 g, respectively. This study highlights the importance of maintaining optimal water quality and understanding phytoplankton dynamics for enhancing shrimp growth. Additionally, it explores the potential benefits of alginate supplementation and the effects of low salinity on the growth of juvenile Vannamei shrimp, contributing valuable insights for sustainable aquaculture practices.

Performance Evaluation of Hydroponic Grow-Outs in An Innovative Coldwater Aquaponic System Featuring Rainbow Trout and Lettuce

A 45-day trial was carried out to assess the production performance of different hydroponic media in a novel do-it-yourself (DIY) low-tech re-circulating aquaponic system for temperate regions with rainbow trout (Oncorhynchus mykiss) and lettuce (Lactuca sativa). Rainbow trout juveniles (average weight of 35.59 g) were stocked in the experimental units at 2.8 kg.m-3 and fed with commercial floating pelleted feed at 8 % of their body weight in three treatments and a control. The lettuce saplings were randomly planted in the river stone bed (T1), crushed stone bed (T2), raft/deep water culture (DWC) unit (T3) and control (C) soil bed (fortified with NPK fertiliser) with equivalent planting intervals of 42 saplings.m-2. The system, designed with low-tech simplicity, was managed without alkalinity correction and depended entirely on plant growth and metabolism for biofiltration. The water quality parameters such as temperature, pH, dissolved oxygen (DO), dissolved free CO2, hardness, total alkalinity, ammonium, nitrite, and nitrate varied significantly (P < 0.05) among the treatments compared to the control. The final individual weight, biomass gain, specific growth rate (SGR), and feed conversion ratio (FCR) of rainbow trout were significantly better (P < 0.05) in media beds (crushed stone and river stone) compared to control and DWC systems. The final mean weights of rainbow trout in river stone (12.33 ± 0.002 g and crushed stone (12.39 ± 0.054 g) treatments were significantly higher (P < 0.05) than in DWC (12.1 ± 0.023 g) and control (12.09 ± 0.002 g) treatments. The production of lettuce was significantly greater (P < 0.05) in all three treatments (river stone: 4.33 ± 0.123 g, crushed stone: 4.53 ± 0.09 g and DWC: 4.31 ± 0.163 g) compared to the control (3.31 ± 0.172 g). The DWC including the media bed systems facilitates the improved performance of lettuce saplings in terms of final height and leaf number. These results show that a low-tech media bed system without a supplementary biofiltration unit can achieve sustainable production of both fish and vegetables in temperate hilly terrains.

The Effects of Pond Type and Water Quality Dynamics on Vannamei Shrimp Growth: A Dummy Regression Analysis

Vannamei shrimp is one of Indonesia's leading aquaculture sector commodities due to its high survival rate, short cultivation time, and disease resistance. Vannamei shrimp cultivation in Indonesia adopts an intensive system favoured for high productivity. In intensive cultivation systems, shrimp ponds typically utilize concrete or high-density polyethylene (HDPE) ponds. Each type has its own positive and negative side that affects the growth and production of Vannamei shrimp. Apart from the type of pond, water quality also played an important role in the growth of Vannamei shrimp. Water quality is one of the important factors in intensive shrimp cultivation. Pond type is categorical data and has a nominal measurement scale, while water quality is numerical data with a ratio measurement scale; ordinary regression analysis is unsuitable for analyzing the effect of pond type and water quality on the growth of Vannamei shrimp. Therefore, a dummy regression model accommodates these measurement scale differences. This research aims to determine the effect of different types of ponds and water quality dynamics on the growth of Vannamei shrimp and to select the best type of pond for intensive cultivation of Vannamei shrimp. Additionally, it aims to identify the water quality parameters that most influence the growth of Vannamei shrimp so that it can serve as a reference for Vannamei shrimp farmers to achieve high productivity efficiently. The study was conducted from November 2022 to January 2023 in Banyuwangi Regency, East Java Province, Indonesia. There are three concrete ponds and 10 HDPE ponds. The research method employed in this study is a survey method utilizing simple random sampling. The parameters in this research are the quality of cultivation water, including pH, temperature and dissolved oxygen (DO). The water samples taken are then measured for water quality in the laboratory. The results of this study indicate that the average values for water quality are still within the optimal range. The average ABW in HDPE and concrete ponds ranges from 2.30 to 9.39 grams per shrimp and 2.22-9.73 grams per shrimp. Based on the study's results, it can be concluded that different pond types and water quality dynamics, specifically pH and temperature, affect shrimp growth based on ABW. However, when considering SGR values, the type of pond does not have a significant impact. The water quality parameters that affect SGR are pH and temperature.

Development of a machine learning model to support low cost real-time Legionella monitoring in premise plumbing systems

Legionella pneumophila (L. pneumophila) is a pathogenic bacterium primarily known for causing Legionnaires’ Disease which is known for high mortality rates, particularly in the elderly. With caseloads continuing to increase, further research is needed to improve our understanding of optimized sampling schema and safe limits of L. pneumophila, in part to target improved treatment options and realistic population-level risk modeling. Particularly in healthcare and other high-risk locations these become crucial and time sensitive needs. Therefore, we conceptualized this research as a means of incorporating easily measured physiochemical water quality parameters and generalization of the unique ecology of building water systems to build a computational model that can allow for more rapid and accurate decision making. This research uses the specific machine learning (ML) method called statistical learning theory to incorporate concentration of host cells, such as native amoeba, and physiochemical water quality parameters to estimate the probability of observing ranges of Legionella gene copy concentrations. Using data from previously published research on Legionella prevalence in a large building, our ML method trains the model on the relative impacts of physiochemical parameters on likely amoeba host cell occurrences. The model is expanded to estimate host cell concentrations using correlations and regressions operated through LASSO algorithms. After categorization variables from these results are then used to inform a logistic regression to provide an estimate of the probability of Legionella gene copy concentration ranges. In summary, conventional results generated by logistic regression and multiple linear regression quantified the associations among ecological conditions in the water and ability to predict a likely range of Legionella concentration in a management focused way. Further, two ML methods, PCA and LASSO, demonstrated feasibility in accurate real-time monitoring of Legionella through physiochemical indicators as evidenced with good accuracy of predictions based for validation results. Furthermore results demonstrate the vital need to account for the impact of water quality on building on host cells, and via their quantified water microbial ecology, not just Legionella concentrations.

Experimental Design, Statistical Analysis, and Modeling of the Reduction in Methane Emissions from Dam Lake Treatment Using Agro-Industrial Biochar: A New Methane Capture Index

This study aimed to reduce the methane (CH4) emissions originating from dam lake treatment using malt dust-derived biochar, which is an agro-industrial byproduct of the brewery industry. Optimum operating and water quality parameters for CH4 reduction were determined using statistical analyses based on the Box–Behnken design method. Also, a Monte Carlo simulation was performed to determine the correlation between CH4 emissions and operating parameters. According to the simulation, dissolved oxygen (DO) and the oxidation–reduction potential (ORP) had the highest correlation with CH4 emissions, with values of 92.03% and 94.57%, respectively. According to the Box–Behnken design methodology, the optimum operating parameters were 4 mg/L of dissolved oxygen, −359 mV of ORP, and 7.5 pH for the minimum CH4 emissions. There was a reported reduction of up to 19.4% in CH4 emissions for the dam lake treatment using malt dust-derived biochar. Finally, a new methane capture index, based on the biochar application (MCI), was developed and validated. The largest methane capture capacity was related to the malt dust-derived biochar produced at the lowest temperature (M1).

Sustainable agriculture through qanat systems in Karabakh: Water and soil characteristics in the context of climate change

This study investigates the water quality and soil characteristics associated with qanat systems in the Cebrail district of the Karabakh region, Azerbaijan. Qanat systems, traditional underground channels designed for water transport, play a crucial role in providing reliable water sources for drinking and irrigation. Water and soil samples were collected from seven qanat systems and analyzed for various physicochemical properties. Water quality parameters included pH, electrical conductivity, hardness, mineralization, and concentrations of calcium, magnesium, sodium, and other ions. Soil analyses focused on pH, electrical conductivity, organic matter content, salinization degree, and the presence of key ions like sulfate and nitrate. The results indicated that qanat water is generally of high quality, with pH levels suitable for both drinking and irrigation. However, some qanat systems exhibited high electrical conductivity and mineralization levels, suggesting potential salinity issues for sensitive crops. Soil samples showed favorable conditions for agriculture, with good pH levels, low salinity, and high organic matter content. The analysis revealed a significant interaction between water quality and soil characteristics, emphasizing the importance of integrated management practices. In the context of climate change, the sustainability of qanat systems is critical. Recommendations include regular monitoring of water and soil quality, soil amendments to mitigate salinity, efficient irrigation techniques, and the use of climate-resilient infrastructure. This study underscores the importance of qanat systems in arid and semi-arid regions and provides practical recommendations for sustainable land and water resource management, enhancing the socio-economic well-being of local communities.

Extraction of Sulfated Polysaccharides from Ulva sp. Using Acid and Toxicity Testing with the Brine Shrimp Lethality Test (BSLT)

This study investigates the extraction of sulfated polysaccharides from Ulva sp. at pH 3 and evaluates their toxicity using the Brine Shrimp Lethality Test (BSLT) with Artemia salina. Artemia salina is utilized for its rapid life cycle and sensitivity to various chemical compounds, making it an effective bioassay organism for assessing the toxicity of natural extracts. The extraction process was conducted at both hot (80°C) and cold (room temperature) conditions, with the hot extraction yielding higher amounts of polysaccharides. The results indicated a wet extraction yield of 890 mL at 80°C and 800 mL at room temperature, while the highest dry weight yield was achieved at 80°C (0.57 g). The toxicity assessment revealed an LC50 value of 15,815.85 ppm, classifying the sulfated polysaccharides as non-toxic to Artemia salina. Maintaining optimal water quality parameters, including temperature, salinity, pH, and dissolved oxygen levels, is essential for the successful cultivation of Artemia salina. Furthermore, the acidic extraction pH significantly influences the structure and chemical properties of the resulting polysaccharides, emphasizing the importance of this parameter in future applications. These findings support the potential use of sulfated polysaccharides from Ulva sp. as a safe and effective feed ingredient in aquaculture.

Correlation and regression analysis of unionised ammonia ions, NH3and pH in ornamental fish aquatic environment

Assessing ammonia in water is very important for fish farmers as it is one of the pollutants that may affect the water quality. In water, ammonia can be found either in the form of unionised ammonia NH3 or ionised ammonia NH+4, which contribute to a total ammonia nitrogen (TAN). In assessing the ammonia toxicity, NH3 provides a more accurate measure of toxicity and needs to be monitored consistently, rather than relying solely on TAN. However, the method of measuring NH3 in water can be complex and challenging. Therefore, the ability to determine the correlation between NH3 and other parameter which is easier to be measured (such as pH) is crucial to enable the estimation of NH3. This study was conducted to determine the correlation between NH3 and pH based on the data collected from Redgold Aquatics ornamental fishponds located in Sik, Kedah. The pH was assessed by a commercial measuring device, while the NH3 was calculated using an appropriate mathematical equation that requires the data of pH, TAN, and temperature. The correlation and regression analysis were conducted via the IBM SPSS tool and Microsoft Excel. The result shows that NH3 and pH are highly correlated with regression equation of NH3 = 0.01pH – 0.07. In addition, factors that may affect the total ammonia value have been discussed thoroughly in this work. The analysis of these water quality parameters may assist farmers in estimating the toxic ammonia, NH3 from the known water pH.

Spectro-environmental factors integrated ensemble learning for urban river network water quality remote sensing

Remote sensing water quality monitoring technology can effectively supplement the shortcomings of traditional water quality monitoring methods in spatiotemporal dynamic monitoring capabilities. At present, although the spectral feature-based remote sensing water quality inversion models have achieved many successes, there could still be a problem of insufficient generalization ability in monitoring the water quality of complex river networks in large cities. In this paper, we propose a spectro-environmental factors integrated ensemble learning model for urban river network water quality inversion. We analyzed the correlation between water quality parameters, spectral reflectance, and environmental factors based on an in-situ dataset collected in the northern part of Shanghai. Using the Hot Spot Analysis (Getis-Ord Gi*), we found that river network water quality parameters have different patterns in different urban functional zones. Furthermore, daily average temperature, total rainfall within the seven days, and several band combinations were also selected as the environmental and spectral features using factor analysis and Pearson correlation coefficient analysis. After the feature analysis, the spectro-environmental factors integrated ensemble learning model was trained. Compared with the spectral-based machine learning inversion models, the coefficients of determination R2 increased by about 0.50. Our model was also tested in three different test areas within and outside the in-situ sampling areas in Shanghai based on low-altitude multispectral remote sensing images. The R2 results for total phosphorus (TP), ammonia nitrogen (NH3-N), and chemical oxygen demand (COD) within the in-situ sampling areas were 0.52, 0.58, and 0.56 respectively. The mean absolute percentage error (MAPE) results were 53.36%, 63.95%, and 22.46% respectively. After adding the area outside the in-situ sampling areas, the R2 results for TP, NH3-N, and COD were 0.47, 0.47, and 0.53. The MAPE were 49.38%, 74.46%, and 20.49%. Our research provided a new remote sensing water quality inversion method to be utilized in complex urban river networks which exhibited solid accuracy and generalization ability.

Supporting the development of climate-resilient water safety plans through a risk-screening framework for drinking water source protection

ABSTRACT Climate change-induced impacts on water-quality challenge risk management of drinking water. Uncertainty around future changes and limited resources require approaches that enable prioritisation at regional or national scale for planning and adaptive intervention. This paper presents a framework for risk screening drinking water supplies, providing a staged approach to building the capacity for integrating climate change into risk management. The framework is applied to drinking water sources of the Scottish national drinking water provider, developing raw water trajectories for indicative water-quality parameters (water colour and Escherichia coli). It establishes baseline understanding of water-quality controls through multivariate statistical analysis. It incorporates climate and land-use change into the model using climate (UKCP18) and land-use projections. The results suggest potential higher organic carbon production in soils from increased production with higher temperature, combined with reduced dilution and drought effects from reductions in summer rainfall. For E. coli, risks arise through land-use change leading to potential agricultural intensification. The framework supports the targeted development of climate-resilient Water Safety Plans, prioritising systems most at risk of raw water-quality deteriorations. It emphasises source protection to maintain or improve regulatory compliance, minimise socioeconomic and environmental harms, and generate additional benefits.

Assessment of Spatial Variation in Terrain Parameters Impacting Surface and Groundwater Quality for Sustainable Geo-Environmental Management

Soil and water conservation measures crucial for quality enhancement should focus on terrain-specific challenges. Evaluating groundwater resources from wells in the area is essential to ascertain their appropriateness for different applications. In semiarid tropical regions, the risk of inland salinity can escalate under extreme conditions like droughts and reduced monsoonal rainfall. During droughts, the groundwater table declines, leading to deterioration in groundwater quality, making it unsuitable for consumption, industrial processes, and arboriculture. In this scenario, analysing the spatial variation in water quality parameters becomes crucial for safeguarding environmental geology and effectively managing the geo-environment of impacted regions. Unfavourable geo-environmental conditions can be mitigated by reducing surface and groundwater pollution, sheet erosion, landslides, and land subsidence. Examining the variation in groundwater quality across both spatial and temporal dimensions is necessary to recommend treatments that make groundwater suitable for various uses, including potable purposes. The spatial as well as temporal variations of different water quality parameters, determined through a composite water quality index, can inform land use alterations, resource exploitation without unacceptable consequences, and artificial recharge measures that do not pollute the geo-environment. Enhancing the sustainability of the geo-environment can be achieved by investigating and prioritizing conservation measures and practices. Employing temporal remote sensing alongside related datasets facilitates the assessment of delineated watersheds within the region through the Analytical Hierarchy Process (AHP) Model. This approach is essential for prioritizing watersheds and formulating strategic action plans to sustain a balanced geo-environment.

Silica Sand, Activated Carbon, and Manganese Zeolite for Clean Water Filtration

The General Background Water is essential for human life, but many rural areas still lack access to clean drinking water that meets health standards. In Sumbergedang Village, Pandaan, local water sources are often contaminated by dissolved metals and bacteria, posing risks to community health. Current filtration methods in the area are insufficient, and limited studies explore the combined use of silica sand, activated carbon, manganese zeolite, and UV sterilization for improving rural water quality. This study aims to evaluate the performance of these filtration materials and UV sterilization in producing safe drinking water for the village. The results show that the filtration system increased the pH of the water from 7.94 to 7.98, within acceptable drinking water standards. The novelty of this research lies in the integration of filtration materials with UV sterilization to address both chemical and microbial contaminants, offering a comprehensive solution for water purification. The findings suggest that, while the system effectively improves most water quality parameters, additional treatments may be required to reduce aluminum levels to meet national drinking water standards. These results have important implications for water management in rural areas facing similar challenges. Highlihts: The study combines mangan zeolite, silica sand, and activated carbon with UV sterilization for effective water purification. Filtration and UV treatment significantly reduced turbidity, odors, and bacterial contamination in spring water. Aluminum levels exceeded permissible limits, indicating the need for further modifications to the filtration system. Keywords: Water quality, filtration, UV sterilization, rural communities, aluminum levels

Comparison of water quality, planktonic community, and volatile organic compounds in the seawater from five cage culture areas of large yellow croaker

The rapid development of marine fish cage farming has led to ecological damage, adversely affecting fish quality. Significant regional quality differences in large yellow croaker under similar farming conditions suggest that the water environment plays a crucial role in fish quality. Using full-length18s/16 s rRNA sequencing with bacterial absolute quantity and headspace solid-phase microextraction coupled with gas chromatography mass spectrometry (HS-SPME-GC–MS), we investigated the planktonic community and volatile organic compounds (VOCs) in seawater from cages housing large yellow croaker at five major mariculture sites in China, including ND (26.627°E, 119.638°N), NJ (27.479°E, 121.052°N), DT (27.981°E, 121.196°N), NC (28.470°E, 121.907°N), and DJ (30.198°E, 122.698°N). Notably, three dominant ciliates, Mesodinium rubrum, Strombidium sp., and Pseudotontonia simplicidens, were identified in NJ as bioindicators for water quality. Additionally, NJ cages had the highest bacterial biomass with 54 % Synechococcus CC9902, and the lowest abundance of bacteria with pathogenic activities. These may explain NJ's optimal water quality parameters and the highest eukaryotic biodiversity. In contrast, DT and DC contained only the core ciliate M. rubrum, with no dominant ciliate in ND. Styela gibbsii, a filter feeder, predominated in ND cages, adhering to the net. The occurrence of red tide-causing species and pathogenic bacteria or fungi was notable in DJ, DC, DT, and ND, including Akashiwo sanguinea, an unclassified Dinophyceae, Gyrodinium fusiforme, Pirum gemmate, Candida parapsilosis, Hortaea werneckii, and Pseudomonas juntendi. Bacterial functional analysis showed that ND cages harbored unique strains linked to ureolysis and various pathogenic activities. Co-association networks suggested that 2,4-Di-tert-butylphenol and pentadecane might play roles in communication within plankton communities. A rise in pleasant VOCs such as acetyl valeryl, pentadecane, butyl butyrate, tetradecane, and 5-butyldihydro-2(3H)-furanone was observed in DJ, DC, DT, and NJ, compared to ND. The results provide valuable insights for improving aquaculture practices and mitigating environmental impacts. The results provide valuable bioindicators for monitoring water quality using microbial communities and VOC profiles.

Determination of Water Quality Index of Drinking Water in Aligarh District, UP, India

Water is perhaps the most precious natural resource after air. Though the surface of the earth is mostly consists of water, only a small part of it is usable, which makes this resource very limited. This precious and limited resource, therefore, must be used with prudence. As water is required for different purposes, the suitability of it must be checked before use. Nowadays fresh water cannot be used directly for drinking purposes due to contamination and pollution. So treatment is used before it is used for drinking or for industrial processes. Also, sources of water must be monitored regularly to determine whether they are in sound health or not. Poor condition of water bodies are not only the indictor of environmental degradation, it is also a threat to the ecosystem. In industries, improper quality of water may cause hazards and severe economic loss. Thus, the quality of water is very important in both environmental and economic aspects. Thus, water quality analysis is essential for using it in any purpose. The quality of water depends upon its source of history. The history of water signifies the terrain through which water is flowing, its origin and most important the extent to which it is contaminated on its way by impurities, sediments and industrial waste. The solubilisation and fragmentation of the terrain through which it flows determines its quality. The extent of dissolved solid materials present in water decides its quality. Such quality is also decided by the solubility of the geological deposits, contact of water with sediments, time of interaction and special factors related to environment. To ascertain suitability of water for consumption, it is necessary to undertake examination of quality of water. . Major information on the quality of water is obtained by physical examination. considered in the present paper for calculating the WQI such as pH, Total alkalinity, Calcium, Magnesium, Chloride, Sulphate, Nitrate and also calculated the seasonal variations of physio- chemical parameters of water quality of Aligarh District.

Exploring the impacts of steroid estrogens load and aeration intensity on the performance, membrane fouling characteristics, and bacterial community structure of the anoxic-oxic membrane bioreactor

Steroid estrogens (SEs) are typical endocrine-disrupting compounds, and they are inadequately eliminated in most wastewater treatment plants (WWTPs), contributing significantly to their environmental prevalence. In an effort to optimize the performance of membrane bioreactor (MBR) in mitigating SEs alike micropollutants, this study investigated the influences of influent loads of three typical SEs (estrone (E1), 17β-estradiol (E2), and 17α-ethynyestradiol (EE2)) and the aeration intensity on the pollutants removal performance, membrane fouling characteristics, and bacterial community structure in a lab-scale anoxic/oxic-MBR (A/O-MBR) process. The presence of SEs shed minimal impacts on the performance of A/O-MBR process as indicated by conventional water quality parameters due to gradual microbial acclimation. However, the presence and the rising input of SEs accelerated membrane fouling as a result of the enhanced EPS excretion and PN/PS ratio and the reduced floc size. The moderate aeration intensity was preferred from the perspectives of conventional pollutants removal, SEs biodegradation, biomass accumulation, and membrane fouling mitigation. Evolution of bacterial community structure and predominant genera were identified at different SEs loads and aeration intensities, with Candidatus Competibacter and Ferruginibacter detected as the predominant genera at different SEs input loads and Thiothrix, Azospira, and Saprospiraceae_norank at different aeration intensities with identical SEs input. The results demonstrated the potential of A/O-MBR as a promising barrier against SEs alike micropollutants through the regulation and control of aeration intensity.

Electrodialysis reversal (EDR) technology: a viable solution for addressing water quality challenges in the dry zone, Sri Lanka

ABSTRACT Chronic Kidney Disease of Unknown Etiology (CKDu) affects rural Sri Lankan agricultural populations, with poor-quality ground and surface water suspected as the root cause. Hence, we conducted this study to explore the effectiveness of Electrodialysis Reversal (EDR) technology in treating water quality issues related to CKDu in dry zone of Sri Lanka. The EDR plant in Kahatagasdigiliya, Anuradhapura district, managed by the National Water Supply and Drainage Board (NWS&DB) was selected. We measured both physical (colour, turbidity, pH) and chemical (electrical conductivity, total dissolved solids, chloride, alkalinity, hardness, nitrate, nitrite, sulfate, fluoride, total phosphate, iron, manganese) parameters of the EDR process. The parameters of the permeate stage of the EDR plant were validated by comparison with data from SLS 614:2013, and removal efficiencies were assessed. The results revealed that all parameters consistently fell within the permissible limits in the permeate stage of the EDR plant. Turbidity (62.65%), sulfate and manganese (50%), colour (47.37%), fluoride (44.19%), and hardness (35.71%) showed high removal efficiencies in the EDR process. The study demonstrated the effectiveness of EDR technology in addressing water quality challenges, validating its potential for groundwater treatment and this contributes to the improvement of groundwater quality in CKDu-prevalent areas.