Total Dissolved Solids Research Articles

Evaluation of physico-chemical quality and occurrence of Salmonella in water from food retail outlets

Salmonella is one among the most important biological contaminants in drinking water that possess safety hazards to human life. Faecal contamination of the water, indirectly from the household sewage discharge, municipal sewage etc. attributes to the repeated detection of Salmonella in water. This study aimed to investigate the occurrence of Salmonella and physico- chemical quality evaluation of samples of water collected from food retail outlets of Thrissur and Kollam districts. A total of 50 water samples (25 each from Thrissur and Kollam districts) used for cooking purpose were collected over a period of six months, March to August 2023. Water samples were subjected to comparative evaluation of physico-chemical qualities viz., pH, turbidity, total dissolved solids (TDS) and hardness. Collected water samples were examined for Salmonella spp. by conventional culture method and PCR. Genus specific and virulence genes of the isolates were detected using polymerase chain reaction. The occurrence of Salmonella spp. in samples of water collected from Thrissur was 24 per cent whereas in Kollam district it was only four per cent. The overall occurrence of Salmonella spp. in samples of water collected from both districts was 14 per cent. Physico-chemical parameters of water samples viz., pH, turbidity, total dissolved solids and hardness were within the BIS prescribed standards. The molecular characterisation of Salmonella spp. detected 16S rRNA in all isolates but invA and spvA genes were detected only in 14.28 per cent of the isolates. Hence proper disinfection of water and food sanitation in the retail outlets will help to minimize the risk of foodborne pathogens Keywords: Salmonella, water, physico-chemical quality, food retail outlets

Enhancing local-scale groundwater quality predictions using advanced machine learning approaches

Assessing groundwater quality typically involves labor-intensive, time-consuming, and costly laboratory tests, making real-time monitoring impractical, especially at the local level. Groundwater quality projections at the local scale using broad spatial datasets have been inaccurate due to variations in hydrogeology, human activities, industrial operations, groundwater extraction, and waste disposal. This study aims to identify the most dependable and resilient machine learning algorithms for forecasting groundwater quality at nearby monitoring locations by utilizing simple water quality metrics that can be quickly assessed without extensive sampling and laboratory testing. The Entropy-weighted Water Quality Index (EWQI) was calculated using a large spatial and temporal dataset (2014–2021) of 977 wells with parameters including pH, total hardness (TH), calcium (Ca2⁺), magnesium (Mg2⁺), sodium (Na⁺), potassium (K⁺), sulfate (SO₄2⁻), chloride (Cl⁻), nitrate (NO₃⁻), total dissolved solids (TDS), and fluoride (F⁻). Further, similar parameters were also observed in 33 open wells at the three local monitoring sites from December 2022 to March 2023. The EWQI was predicted using a Random Forest (RF), eXtreme Gradient Boosting (XGB), and Deep Neural Network (DNN). The pH, TH, and TDS were used as input variables for EWQI predictions, as they can be easily measured using handheld probes or multi-parameters. The model performance was evaluated using R2, MAE, and RMSE. During the training stage, all three models predicted the EWQI with an R2 greater than 90%, with minimal errors when pH, TH, and TDS were input variables. To validate the models at a local scale, the EWQI was predicted at the village level (e.g., Antoli, Balapura, and Lapodiaya) using pH, TH, and TDS as input variables. The machine learning models were able to predict the EWQI very closely to the actual EWQI, with an R2 greater than 90%. It is also evident that the models could predict the EWQI using basic parameters that are easily measured, providing an overall idea of the water quality for a small area. Hence, these machine learning models could be useful for accurately representing groundwater quality, thereby avoiding the use of time-consuming and costly laboratory techniques.

Comparative treatment of textile dye wastewater with chemical coagulants and bacterial exopolysaccharides

Traces of chemical coagulants, such as alum, commonly used in wastewater treatment, remain in the water effluent and also result in secondary sludge that is difficult to treat. On the other hand, Extracellular Polymeric Substances (EPS) are safer and can be used as alternative bio flocculants. A study was hence done to compare the effectiveness of the treatment of Reactive Black 5 (RB5) textile wastewater with chemical coagulants and bacterial EPS. The jar test method was used to treat the wastewater with Alum and Polyferrous Sulphate (PFS) at varied pH (2–10) and respective dose concentrations. EPS was produced by bacteria isolated from cotton gin trash soil collected from Kitui ginnery in Kenya. EPS treatment was done at 30 °C for 72 h. EPS-producing bacteria isolates were identified by molecular analysis. The chemically and EPS-treated wastewater was analyzed for color, Total Dissolved Solids (TDS), and Chemical Oxygen Demand (COD). Respective color and TDS removal capacity by PFS and alum were (86.1% and 42.18%) and (85.1% and 69%) at their optimal conditions of (pH 7 and 100 mg/L) and (pH 7 and 140 mg/L). Similarly, PFS and alum reduced COD by 27.25% and 26.65%. Respective dye removal by YEAK2 −5 and YEPD K2 −2 EPS was 69.1% and 85.7%. However, YEPD K2 −2 and YEAK2 −5 EPS caused a respective rise of TDS by 40.14% and 67.17%. The respective reduction of COD by YEPD K2 −2 and YEAK2 −5 EPS was 56.25% and 54.24%. The chemically and EPS-treated wastewater met the National Environment Management Authority (NEMA) limits. The YEPD K2 −2 and YEAK2 −5 isolates were both identified as Bacillus sp. GC–MS and FTIR analysis results indicated that the two EPS were heteropolysaccharides composed of different sugar derivatives and hydroxyl as the main functional group. The results for treatment of the dye wastewater by Alum, PFS, and EPS were therefore comparable. The bacterial EPS bio flocculants can therefore serve as effective and cleaner substitutes to the alum and PFS chemical coagulants.

Efficient removal of COD, BOD, oil & grease, and turbidity from oil-field produced water via electrocoagulation treatment.

The simple design, compactness, simultaneous treatment of multiple contaminants, absence of chemical usage, minimal sludge formation (reducing secondary pollution), low maintenance cost, and versatility to operate in both batch and continuous modes make electrocoagulation (EC) a promising choice for treating various types of industrial wastewater. In this study, EC was employed in batch mode to treat produced water obtained from an oil drilling site, to reuse it for injection purposes in the reservoir. Produced water typically contains high levels of total dissolved solids (TDS), turbidity, chemical oxygen demand (COD), biological oxygen demand (BOD), and oil & grease (O&G) contaminants. High-performing aluminum (Al) electrodes were chosen due to their stability, conductivity, and, most significantly, their high capacity for generating aluminum hydroxide ([Al(OH)₃]ₙ) flocs, which serve as carriers for contaminant capture. This compound has demonstrated remarkable effectiveness in trapping the aforementioned contaminants from produced water under various operating conditions, including the number of electrodes, supplied current, and electrode configuration (bipolar and monopolar). The impact of several factors, including the number of electrodes (varying from 4 to 8), current density (varying as 16, 79, 158 A/m2), and electrode configuration (bipolar and monopolar), was studied at room temperature and 250rpm agitation speed. Initial turbidity, COD, BOD, and O&G concentrations were measured at 38 NTU, 700.7ppm, 120ppm, and 32.8ppm, respectively. The EC treatment exhibited removal efficiencies of 51% for TDS, 85% for turbidity, 78% for COD, 80% for BOD, and 85% for O&G using a monopolar configuration with 8 electrodes, and 59% for TDS, 90% for turbidity, 85% for COD, 84% for BOD, and 86% for O&G using a bipolar configuration with eight electrodes. Additionally, cost estimation, considering electrode dissolution rate and power requirements, was conducted for the operation of both configurations.

Prediction of urban surface water quality scenarios using hybrid stacking ensembles machine learning model in Howrah Municipal Corporation, West Bengal

In the pursuit of understanding surface water quality for sustainable urban management, we created a machine learning modeling framework that utilized Random Forest (RF), Cubist, Extreme Gradient Boosting (XGB), Multivariate Adaptive Regression Splines (MARS), Gradient Boosting Machine (GBM), Support Vector Machine (SVM), and their hybrid stacking ensemble RF (SE-RF), as well as stacking Cubist (SE-Cubist), to predict the distribution of water quality in the Howrah Municipal Corporation (HMC) area in West Bengal, India. Additionally, we employed the ReliefF and Shapley Additive exPlanations (SHAP) methods to elucidate the underlying factors driving water quality. We first estimated the water quality index (WQI) to model seven water quality parameters: total hardness (TH), pH, total dissolved solids (TDS), dissolved oxygen (DO), biochemical oxygen demand (BOD), calcium (Ca), magnesium (Mg). Then six independent factors were utilized (i.e. Precipitation (Pr), Maximum Temperature (Tmax), Minimum Temperature (Tmin), Normalized Difference Turbidity Index (NDTI), Normalized Difference Chlorophyll Index (NDCI), and Total Dissolved Solids (TDS)) for predicting the WQI mapping through the different ML models. This study demonstrated that the SE-Cubist model outperforms other ML models. During the testing phase, it achieved the best modeling results with an R2 = 0.975, RMSE = 0.351, and MAE = 0.197. The ReliefF and SHAP analyses identified Pr and Tmax as the most significant factors influencing WQI within the study area.

Evaluation of human and ecological health risks associated with the potentially toxic heavy metals in groundwater of Vellore city, Tamil Nadu, India

Groundwater pollution by heavy metals is a significant and alarming threat globally, through its chronic effect on human health and ecosystem. The current study evaluated the identification and risk assessment of heavy metals in groundwater of the Vellore city, Tamilnadu, India. Groundwater samples were collected from 32 locations over a continuous period of 2022–2023 for every three months on seasonal basis. The samples were analysed for pH, Total Dissolved Solids (TDS), Hardness and heavy metals (Al, As, Ba, Cd, Cu, Pb, Al and Zn). The analysed mean concentrations of these heavy metals were found in the order: As > Cd > Pb > Ba >Zn >Al> Cu. Elevated concentrations of heavy metals were observed in 2022, likely influenced by rainfall and land use patterns. Heavy metals such as Al, As, Pb, and Cd exceeded the BIS limits and whereas Ba, Cu, and Zn concentrations remain within desirable limits. Groundwater Quality Index (GWQI) classified 41% as 'unfit for drinking'. Ecological risk indices (ERI) indicate significant contamination in 34% of samples, with Al and Pb being primary contributors. Non-carcinogenic health risk assessments reveal, chronic hazards, where children facing higher risks followed by men and women groups. Carcinogenic risk assessments indices such as Heavy metal pollution Index (HPI) shown 25% of samples in critical quality, Heavy metal Evaluation Index (HEI) evaluated all samples were in low contamination and Contamination Index (CI) shown 72% samples under high contamination posing high risk to humans. Probable Cancer Risk (PCR) values for As, Pb, and Cd exceed acceptable ranges across all demographic groups posing cancer risk to humans particularly children. The present study highlights the need for groundwater treatment and regulatory interventions to mitigate health and ecological risks due to the contamination of heavy metals in Vellore city.

Silver oxide integrated ionic polymer composite for wearable sensing and water purification

Integrating metal nanoparticles (NPs) with ionic polymer blends/composites showed immense interest for their potential in wearable sensors, soft robotic arms, flexible man-machine interfaces of biomedical devices, and water purification applications. However, conventional NPs attached ionic polymer composites exhibit limitations such as low sensitivity (ΔR/R), low total dissolved solids (TDS) reduction, and low phosphate (PO4-P) removal rate. Herein, ionic polymer composites (IPCs) using flower-shaped silver oxide (Ag2O) attached Poly (vinylidene fluoride) (PVDF)/ polyvinylpyrrolidone (PVP)/ionic liquid (IL) were designed and developed for wearable sensing and water purification. The IPCs demonstrated remarkably high ΔR/R values of 50, 10, and 3.5 corresponding to the wrist movement of 50°, finger movement of 180°, and chin movements respectively. The Ag2O-based IPC recorded a significant reduction of TDS from sewage water from 3405 ppm to 1035 ppm, elevated the dissolved oxygen (DO) levels in the sewage water from 1.2 mg/l to 6.8 mg/l, and removed approximately 87.38 % phosphate from sewage water. Due to the uniform distribution of Ag2O within pores of IPC, it demonstrated enhanced performance for wearable and wastewater treatment applications.

Identifying groundwater characteristics and controlling factors in Jiaozhou Bay’s northern coastal region, China: a combined approach of multivariate statistics, isotope analysis, and field empirical investigations

Explicit identification of hydrochemical processes and their controlling factors within groundwater systems is critical for the sustainable utilization of water resources in coastal urban areas. This study was undertaken in the North Coastal Region of Jiaozhou Bay (NCRJB), located in the eastern part of Shandong Province, China, an area grappling with significant issues of groundwater quality degradation and water scarcity. A total of 105 groundwater samples and 34 surface water samples, collected from 2020 to 2024, were analyzed and studied using various hydrogeological tools, multivariate statistical analyses, and water quality assessment methods. These include the Piper diagram, hydrochemical facies evolution diagram (HFE-D), Principal Components Analysis (PCA), correlation analysis, stable isotope analysis, Water Quality Index (WQI), and USSL diagrams. The results indicated that all surface water and pore groundwater samples were categorized as Na-Cl type, exhibiting high Total Dissolved Solids (TDS) and Electrical Conductivity (EC) values, characteristics that render them poor to unsuitable for drinking and irrigation purposes. The fracture groundwater is predominantly of the Ca-Na-Cl mixed type, with average suitability for irrigation and a limited proportion (22.5%) deemed suitable for drinking. Seawater intrusion, primarily through the surface water system, and the impact of human activities were identified as the predominant controlling factors con-tributing to the degradation of the local groundwater environment. Field empirical investigations further validated the results derived from hydrogeological assessments, multivariate statistical analyses, and isotopic approaches. The long-term shifts in hydrochemical properties, along with the latent threat of seawater intrusion, exhibit an upward trend during the dry season and show a certain degree of mitigation during the wet season. This study highlights that field investigations, in conjunction with hydrochemical tools, multivariate statistical analyses, and stable isotope analysis, can successfully furnish reliable insights into the predominant mechanisms governing regional groundwater evolution within the context of long-term and intricate envi-ronmental settings.

Niger Delta Oilfields Produced Water Characteristics and Treatment Technologies: Challenges and Solutions

The Nigerian Niger Delta oilfields have high water-to-oil ratio ranging from 50% to 95% water content, due to its secondary and tertiary production phases. Oil and gas producers could shut-in such wells, or develop cost effective approach for Produced Water, PW handling to meet reinjection or environmental permissibility. Thus, the study investigated the compositions and treatment techniques of Niger Delta oil and gas fields PW, and proffered solutions for actualizing minimal hazardous contaminants in PW. Characterization of PW from a Flow Station, an Oil processing and a Gas processing facilities showed biogeochemical homogeneity in the PW compositions with high organic and inorganic constituents, which are above injection and disposal specifications. The results of treated PW from the extant PW treatment (PWT) techniques showed that the total dissolved solids (TDS) concentration (6105.9 mg/l) from the Flow Station PW treatment facility did not meet the required specifications for injection into depleted wells or disposal into the environment (2,000.00 mg/l for inland, and 5,000.00 mg/l for nearshore). The salinity contents in the treated PW from the three PWT configurations were 2411.0 mg/l, 2218.6 mg/l, and 2165.4 mg/l, respectively, which were slightly above Nigerian Upstream Petroleum Regulatory Commission (NUPRC) specification (2000.0 mg/l) for nearshore disposal. The chemical oxygen demand (COD) concentration in the treated PW from the three PWT configurations were 153.0 mg/l, 148.1 mg/l, and 141.2 mg/l, respectively, which were above the NUPRC standard (125.0 mg/l). The oil and grease (O&G) concentration in the treated PW were 84.7 mg/l, 51.5 mg/l, and 58.0 mg/l, respectively, which also were above regulatory stipulation (30.0 mg/l) for nearshore disposal. The modular Bio-Unit + Ultra/Nanofiltration achieved more than 95% removal of both organic and inorganic constituents in the PW. Therefore, this study suggests that reconfiguring the extant PW treatment equipment with this cost-effective innovation would be the solution to PW treatment challenges in the Niger Delta oil and gas operations.

Impact of Plastic Mulching on Soil Properties and Heavy Metal Dynamics in Agricultural Systems: A Case Study from Manikganj, Bangladesh

This research study examines the impact of different types and sizes of plastics on various soil properties. Clay loam soil samples were collected from Paril village, Manikganj district, Bangladesh, and subjected to plastic incubation experiments. The plastics underwent 180 days of intense ultraviolet (UV) radiation to simulate natural sunlight degradation. The soil samples were mixed with three types of plastics (P1, P2, P3) and two sizes (1mm, 10mm) in individual pots, with and without the addition of zinc sulfate. The soil properties, including pH, total dissolved solids (TDS), available zinc, cation exchange capacity (CEC), nitrogen content, and total phosphorus, were analyzed using various techniques. The results indicate significant variations in pH and TDS values influenced by plastic size and type. The available zinc content differed among plastic types, and plastic size affected CEC values. Nitrogen content was influenced by plastic size, with smaller particles having a greater impact. Total phosphorus content varied with different plastic types. These findings contribute to our understanding of the potential effects of plastics on soil properties and highlight the need for further investigation into the underlying mechanisms.

Groundwater quality assessment for drinking and irrigation purposes in arid to semiarid region of Indus Basin of South Punjab, Pakistan

<p><a name="_Hlk173243332"><span style="background-color:white;color:black;font-family:"Times New Roman",serif;font-size:12.0pt;line-height:150%;">As the groundwater pollution is increasing, it is crucial to assess groundwater quality and characterize hydrogeochemistry accurately for long term water supply. </span></a><span style="background-color:white;color:black;font-family:"Times New Roman",serif;font-size:12.0pt;line-height:150%;">In this study groundwater samples were collected from 120 locations from Bahawalpur district and analyzed for electrical conductivity (EC), pH, total dissolved solids (TDS), sodium (Na<sup>+</sup>), potassium (K<sup>+</sup>), calcium (Ca<sup>2+</sup>), magnesium (Mg<sup>2+</sup>), carbonate (CO<sub>3</sub><sup>-</sup>), bicarbonate (HCO<sub>3</sub><sup>-</sup>), sulfate (SO<sub>4</sub><sup>2-</sup>), chloride (Cl<sup>-</sup>), nitrate (NO<sub>3</sub><sup>-</sup>), fluoride (F<sup>-</sup>) and heavy metals. The results obtained from the analysis of samples showed that the SAR of nearly 65% of samples collected from Bahawalpur district were in acceptable limit (<6 meq L<sup>-1</sup>), while 12% found to be unfit for irrigation (>10 meq L<sup>-1</sup>). Similarly, the RSC values depicted that 8% samples were unfit while 64% samples were falling in the category of fit irrigation water. Most of the water samples were predominantly Ca<sup>2+</sup>-HCO<sub>3</sub><sup>-</sup> and Na<sup>+</sup>-HCO<sub>3</sub><sup>-</sup> type, that were controlled by various processes of cation exchange, water-rock interaction, dissolution and evaporation. Some samples fall in the middle of diamond and lower triangles of Piper diagram are showing no dominant type of water (mixed water type) due to the complex influence of rock-water interactions as well as anthropogenic activities. The Water Quality Index (WQI) showed that out of total 120 sampling sites in Bahawalpur the number of excellent water samples were only 2% while 18% water samples were characterized as hazardous. Moreover, the number of samples falling in the categories of good, poor and very poor quality water were 36%, 29% and 13% respectively.</span></p>

A Study the Water Quality Measuring Equipment with Automatic Sensor System

This paper studied the water quality in Dong Khoai Village, Xaythani District, Vientiane Capital, which is the primary water pumping location for agriculture. The area has a population of over 1735 citizens and cover more than 450 hectares. Common issue found in Markhiaw river. Stream is its toxicity to certain rice field, causing it inability to grow rice despite using fertilizer. Furthermore, this stream gives dissatisfaction odor, negatively affects people who get into the water for fishing and occasionally found death fish in the areas. In order to assess the water quality and disseminate the results to the public. Therefore, this study aims to investigate the creating of an automated sensor system for high precision water quality monitoring in the water. Four sensors; pH (hydrogen potential), EC (electro conductivity), TDS (total dissolved solid), and temperature are used in this procedure. The sensor system was tested, and build a small station uses solar energy and saves information into the SD card and available online by Blynk, and compare the test results with national environmental standards. The research revealed that, in comparison to the standard instrument S5 pro parameter, the measuring stations for the water quality values of all four sensors are accuracy value of 92.91% to 99.34%. Based on the information gathered over the course of two months, from February 13 and March 18, the pH value will be low, at 5. The pH value is high, at 11, between 13, 17 and 18 February 2024. These numbers are considered to be in the standard ranks. Regarding the dissolved solids in the water vary from 3 to 100 mg/L, and the electrical conductivity is between 100 and 180 µS/cm. They are also fall upon the National Environmental Standard. The Temperature value is high, at 40.81 ºC on 4 February 2024 and from 02 March 2024, the Temperature value will be low, at 24.4ºC.

Ecological Implications of Seasonal Variations in Physicochemical Parameters and Phytoplankton Community in an Effluent‐Receiving Wetland in the Gulf of Guinea, Cameroon

ABSTRACTPhysicochemical parameters, chlorophyll a (Chl a) concentration, and phytoplankton community structure were assessed in the Wouri estuarine mangrove sector of the Douala Bassa Industrial Zone of Cameroon over two seasons. Three sets of water samples were collected from 10 sites for these analyses. Some physicochemical parameters were measured in situ using multiparameter equipment (HANNA 8289). The data were subjected to analyses of significant difference by an independent sample t‐test. Correlation and principal component analysis conducted between variables Temperature, salinity, total dissolved solids (TDS), resistivity, and turbidity showed a strong seasonal variation among sites. Mean Chl a concentration (3.7–48.29 µg/L for dry and 0.1–20.1 µg/L for rainy season) revealed that most sites were eutrophic, with the Euglenophycean index less than 1 in all the sites. Phytoplankton species richness exhibited seasonal and spatial variation, with a total of 74 taxa and 51 taxa for the dry and rainy seasons, respectively. The division Bacillariophyta was the most abundant, with 19 families and 24 species during the dry season and 17 families and 16 species during the rainy season. Other phytoplankton divisions present included Chlorophyta > Cyanophyta > Charophyta > > Myzozoa > Euglenophyta in the dry season; the less diverse divisions in the rainy season were Rhodophyta > Cryptophyta > Xanthophyta > Euglenophyta. High concentrations of nutrients and the presence of eutrophic species such as Microcystis aeruginosa suggest pollution and a need to monitor activities carried out along the water course with respect to the quantity and quality of industrial effluents discharged into the stream. The observed eutrophication explains the noxious odor across the city of Douala, especially during the dry season. The human health implications could be severe, with communities dependent on this contaminated stream for fish and other necessities a scenario that repeats itself in communities dependent on urban wetlands in industrial zones globally.

Greenhouse Gas Emissions Characteristics and Driving Factors Analysis in the Eutrophic Saline Lake Daihai Lake

To investigate the greenhouse gas emission characteristics and driving factors of eutrophic saline lakes in northern China, considering Daihai Lake in Inner Mongolia as an example, 10 monitoring sites were selected based on hydrological distribution characteristics in April, July, and October 2023. Using headspace gas chromatography and modeling methods, dissolved concentrations and exchange fluxes of carbon dioxide （CO2）, methane （CH4）, and nitrous oxide （N2O） were determined in the nearshore zone, open lake area, and lake center surface water. During the study period, Daihai Lake exhibited significant seasonal variations in greenhouse gas concentration and flux. The average concentrations of CO2, CH4, and N2O in surface water were （26.52 ± 17.58） μmol·L-1, （282.30 ± 172.30） nmol·L-1, and （9.09 ± 1.64） nmol·L-1, respectively. The average fluxes were （5.29 ± 11.98） mmol·（m2·d）-1, （178.24 ± 63.34） μmol·（m2·d）-1, and （-0.74 ± 1.28） μmol·（m2·d）-1, with cumulative emissions of 50 770.77, 543.52, -4.21 kg·km-2 and a global warming potential （expressed in CO2-equivalent） of 50 770.77, 15 218.49, -1 254.48 kg·km-2. Daihai Lake acted as a source of atmospheric CO2 and CH4 but a sink for N2O during the study period. Correlation and stepwise regression analyses revealed that pH and total dissolved solids （TDS） influenced CO2 concentration and flux, while the factors affecting CH4 were water temperature （WT）, water depth （WD）, wind speed （WS）, oxidation-reduction potential （ORP）, and total nitrogen （TN）. For N2O, the influencing factors were WT, WS, and TN. Additionally, Daihai Lake's eutrophication and salinity characteristics influenced the generation and emission of greenhouse gases. This study provides insights into the greenhouse gas dynamics and environmental factors in eutrophic saline lakes like Daihai Lake.

Application of a reaction-based water quality model to the total dissolved solids concentration of the Pasig River.

With the goal to support effective water resource management, water quality models have gained popularity as tools for evaluating the distributions of pollutants and sediments. This work focuses on the application of the numerical solution of an advection-dispersion-reaction (ADR) water quality model for rivers and streams to a major Philippine waterway, the Pasig River. The water quality constituent is described by a system of reaction and advection-dispersion-reaction equations. The model and method are based on a previously used strategy where Guass-Jordan decomposition is applied to the matrix system and the resulting conservative form of the model is solved numerically using the fully implicit scheme and finite element method. The methodology is demonstrated by a case study in Pasig River involving the concentrations of total dissolved solids (TDS) obtained from the Department of Environment and Natural Resources (DENR) through the Pasig River Unified Monitoring Stations (PRUMS) report. Sensitivity analysis and parameter estimation are also applied to the model to assess which parameters influence the model output the most.

IoT-based real-time biofloc monitoring and controlling system

In Bangladesh, Biofloc technology is becoming popular in aquaculture, but controlling water parameters effectively remains a key challenge for achieving high yields. In this study, a system was proposed that continuously analyzes biofloc regulating parameters, such as temperature, total dissolved solids (TDS), potential of hydrogen (pH), turbidity, dissolved oxygen (DO), and water level, to maintain the ideal circumstances for biofloc. An Internet of Things (IoT)-enabled platform was implemented to collect and analyze real-time data from sensors, including the DS18B20 water temperature, pH-4502C, analog dissolved oxygen, analog total dissolved solids, and water level sensors. The experiment was conducted with mono-sex Nile tilapia (Oreochromis niloticus). The ESP32 microcontroller utilized Wi-Fi to process sensor data, enabling real-time data analysis on mobile and computer devices through the Blynk application. The study was done as per designated conditions, and that led to the average value of temperature around 27±1 °C, DO around 6 ± 0.5 mg/l, TDS around 500 ppm, and the pH level was nearly 7.7 ± 0.5. If the temperature, water level, or dissolved oxygen changed from the expected value, it sent a signal to the Blynk. This signal then autonomously operated a relay to activate or deactivate the water heater, pump, and air pump to maintain an effective operating condition. Hence, IoT-enabled monitoring systems can have a crucial impact on managing the biofloc throughout the year and enhancing the aquaculture industry in Bangladesh.

Heavy Metals Analysis of Breweries Effluent used in Soil Cultivated with Glycine Max (L.) Merr. Accessions with Biochar Augmentation

Beer production has promulgated the prevalence of heavy metal contamination in the environment (soil and water bodies). The magnitude of breweries wastewater-effluent effect discharged on soil and its effect on crop quality in terms of growth and physiology must therefore be investigated. This study aims to assess the level of seven heavy metals (HM) (lead (Pb), nickel (Ni), chromium (Cr), copper (Cu), cadmium (Cd), zinc (Zn) and iron (Fe)) in breweries wastewater-effluent and its effect on the growth of Glycine max accessions (TGM-3990, TGM-1348, TGM-1732, TGM-2175 and TGM-928) as well as the influence of biochar soil amendment in the induction of HM tolerance in G. max. Effluent properties were analyzed using the A1 portable TDS/EC meter. HM in the wastewater-effluent was determined using Atomic Absorption Spectrometer (AAS). The experiment was set up in a complete block design. 3 seeds G. max accessions were planted in 7kg of sterilized soil (control, effluent and biochar treatments). Growth parameters were taken using standard methods, while the total photosynthetic pigments (TPP) were determined using the atLeaf chlorophyll meter. The wastewater-effluent recorded an electrical conductivity (EC) of 928µS/cm, total dissolved solids (TDS) (464ppm), Temperature (31.9-32.6°C) and pH (5.37). Results for HM concentration showed; Pb (0.20mg/L), Ni (<0.001mg/L), Cr (0.03mg/L), Cu (<0.001mg/L), Cd (<0.001mg/L), Zn (<0.001mg/L) and Fe (8.74mg/L). The trend shows that Fe˃Pb˃Cr˃Cd˃Cu˃Ni˃Zn. Cr, Cd, Cu, Ni and Zn were significantly below the World Health Organization (WHO) and Waste Water Forum (WWF) permissible limit, while Fe and Pb significantly higher. G. max accessions TGM-928 (80%) and TGM-3990 (80%) had better germination percentage (GP), TGM-1348 (60%) had the lowest GP, while TGM-2175 recorded no germination in all treatments. At 6 weeks after planting (WAP), it was observed that irrigation of G. max accessions with breweries wastewater-effluent significantly (p=0.001) stimulated growth parameters such as shoot length for TGM-3990 which recorded; Treatment=19.53±0.94cm; Control=17.10±0.67cm; Biochar=40.83±1.01cm) while TGM-1732 had the highest shoot growth (T=38.57±1.53cm; C=25.00±0.00cm; B=82.33±5.70cm) when compared to their controls. TGM-3990 (T=32.20mg/kg, C=34.10mg/kg, 43.30mg/kg) recorded the least TPP contents, while TGM-928 (T=51.00mg/kg, C=45.60mg/kg, B=43.50mg/kg) recorded the highest TPP in all treatments. Amelioration of soil with biochar significantly (p=0.001) stimulated growth above the effluent treatment and control. Similar trend was observed for leaf area, petiole length, leaf number, stem girth and internode length. This study has shown that breweries effluent has the potential of growth enhancement in G. max cultivation and in combination biochar application reduces the need for additional fertilizer application.

An uncertainty‐based evaluation of sulphuric compounds transport in reservoirs considering sensitivity analysis

AbstractDeepwater bodies such as dam reservoirs are among the most prominent water resources that supply societies' water demand. Hence, water quality in these resources requires continuous and meticulous monitoring. This study evaluated the water quality of Changuleh Dam, a dam under construction in western Iran, using the CE‐QUAL‐W2 model to predict fluctuations in sulphate (SO42−) and hydrogen sulphide (H2S) concentrations. A sensitivity analysis was conducted to assess the dependence of model outputs on input variables. Additionally, an uncertainty analysis was performed using MATLAB to address the inherent uncertainties of the input variables through an ARIMA (2, 2, 1) time series model and Monte Carlo simulations. The results indicated a high sulphate concentration averaging 955.6 mg/l, considerably exceeding the drinking water standard of 400 mg/l, identifying the reservoir as a sulphate‐rich water resource. Seasonal fluctuations of H2S concentrations were also observed in the reservoir's anaerobic bed sediments, peaking at 87 mg/l. The sensitivity analysis showed that nitrate and total dissolved solids (TDS) varied more noticeably than dissolved oxygen (DO) at different depths, with the greatest variation at 50 m. This study highlights the critical need for continuous and meticulous monitoring of water quality in dam reservoirs to meet water supply standards.

Estimating Concentration of Suspended Solids Load in Estuary System Utilizing Sentinel 2A: A Case Study of Cipatujah Beach, Indonesia

Abstract Total Suspended Soil (TSS) and Total Dissolved Solid (TDS) refer to materials in the form of sediment and organic substances suspended and dissolved in water which are used as water quality parameters to understand sediment transport, the health of aquatic ecosystems, and technical problems. Concentrations in significant amounts in water areas can be caused by the dynamics of the earth’s surface and human activities, the resulting negative impacts will reduce the quality of the ecological system and indicate the presence of pollutants. This research was conducted to determine the concentration of Total Suspended Soil (TSS) and Total Dissolved Solid (TDS) in estuary waters at Cipatujah Beach, West Java, Indonesia using remote sensing satellite imagery, namely Sentinel-2A. The research carried out focused on testing samples for Total Dissolved Solid (TDS) content, which is one indicator of the level of water pollution that is often analyzed. From the results of sample tests carried out using a TDS meter, it shows that the TDS content in Cipatujah Beach is above 400 ppm so it is not suitable for use as drinking water, and further laboratory tests need to be carried out to determine the TSS content in Cipatujah Beach water.

Analysis of Spatial and Temporal Variation of Water Quality: A Case Study of Kotagala Wetland, Nuwara Eliya, Sri Lanka

Water quality of wetland ecosystems is a critical concern due to its implications on human health and aquatic life. This study was conducted to assess the spatial and temporal variation of water quality in Kotagala wetland to understand its impact on water safety for domestic uses and ecosystem health. Water samples were collected (n = 70) from six inlets and the wetland outlet from November 2021 to August 2022, and analyzed for pH, electrical conductivity (EC), salinity, total dissolved solids (TDS), total suspended solids (TSS), nitrate, and phosphate. The pH, EC, and nitrate showed significant correlations. Spatial clustering divided the monitoring sites into two clusters, as areas of higher and lower pollution levels. Discriminant analysis highlighted the significance of EC, pH, and nitrate concentrations in differentiating these clusters. Principal According to principal component analysis (PCA) 88.8% of the total variance of spatial variation in water quality was explained by the first two components. Temporal clustering following seasonal variations revealed the influence of rainfall pattern on water quality. EC, TDS, TSS, and nitrate concentrations emerged as the most important factors in this temporal categorization. In PCA, 76.8% of the total variance of temporal variation in water quality was explained by the first two components. Findings highlight the urgent need for sustainable strategies and policies to mitigate the impacts of human activities on wetland water quality, since water quality variations in the wetland was significantly impacted by direct human activities, and variations in rainfall trends in the area.