Total Dissolved Solids Research Articles

Hydrogeological studies of the Sepidan basin to supply required water from exploiting water wells of the Chadormalu mine utilizing reverse osmosis (RO) method

Due to the lack of rainfall potential in Central Iran, the water scarcity is still the main problem of production in the country. Accordingly, the use of unconventional waters will be inevitable. This study presents the amount of water required by the Chadormalu mine from the water wells of the Sepidan Plain, as well as the deficit or excess for exploiting the complex and the water treatment plant by reverse osmosis (RO) method. These studies were carried out to manage the groundwater resources of the Sepidan and Saghand basins and include the water level variations of piezometers, the water consumption of exploitive wells, aqueducts, and the Sepidan River every month. Furthermore, a sample of complete chemical analysis of the aqueducts' Saghand basin and the water entering the RO and leaving it for environmental evaluations have been carried out each season. The average discharges of water wells in the Sepidan Plain were 86.45 and 82.28l/s in 2221 and 2023, respectively. Moreover, the amount of water exploitation has been lower than the renewable (dynamic) reserves, which in the heart of the water intake has a uniform increase in the monthly hydrograph's water level. At the same time, the reduction of total dissolved solids (TDS) entering from exploitation water intakes to the amount of 580mg/l indicates the principled exploitation of dynamic reserves. The RO unit's output had no effect on the quality of the Saghand Playa's water but improved it qualitatively.

Seasonal Variation of Physicochemical Properties in the Lower River Benue, Nigeria

The study investigates the impact of seasonal changes on water quality in the River Benue, Nigeria. Conducted over eighteen months from January 2020 to June 2021, the research focuses on three locations: Ibi, Lau, and Mayo-Ranewo. Key physicochemical parameters such as temperature, pH, turbidity, conductivity, Biochemical Oxygen Demand (BOD), hardness, dissolved oxygen (DO), fluoride, and nitrate were measured to assess water quality. The findings reveal significant seasonal variations in these parameters, influenced by rainfall patterns, land use, and anthropogenic activities. Temperature ranged from 25.56°C to 30.70°C, remaining within acceptable limits for tropical waters, supporting stable biological processes. However, turbidity levels exceeded recommended values, indicating the presence of suspended solids that could impair water quality and harm aquatic life. Total dissolved solids (TDS) and conductivity showed potential contamination risks, likely due to agricultural runoff and urban discharges. Dissolved oxygen (DO) levels were generally adequate, especially during the wet season, enhancing oxygen content through increased photosynthetic activity and water inflows. However, BOD spiked with rainfall, signalling organic pollution and potential eutrophication risks. Seasonal shifts in pH and water hardness reflected changes in runoff and photosynthesis, with values largely within acceptable ranges for aquatic life. Fluoride and nitrate concentrations increased in the wet season, primarily due to agricultural runoff, highlighting the influence of land-based activities on water quality.

From Waste to Wealth: Entrepreneurial Ventures in Chitosan Extraction for Environmental Sustainability

The degradation of water quality in the environment can be attributed to the discharge of wastewater from shrimp ponds. Conversely, solid waste in the form of shrimp shells presents an entrepreneurial opportunity through the extraction of chitosan, a substance with the potential to enhance water quality while contributing to environmental sustainability. Sampling for this study was conducted at the Vannamei Nusantara Gemilang pond, located in Tambakrejo Village, Malang Regency, East Java. The research employed an experimental methodology with a quantitative approach, supplemented by a literature review. Various doses of chitosan solutions were tested on shrimp pond wastewater. The optimal results were obtained at a dosage of 80 mg/L, significantly outperforming the untreated water. The test outcomes for the 80 mg/L dosage included: BOD (Biochemical Oxygen Demand) at 4.62 mg/L, Nitrite concentration at 0.045 mg/L, turbidity at 3.55 NTU (Nephelometric Turbidity Units), TSS (Total Suspended Solids) at 14.6 mg/L, TDS (Total Dissolved Solids) at 2974 mg/L, pH level at 6.31, and temperature at 31.40°C. Notably, the Total Dissolved Solids (TDS) levels did not meet quality standards, highlighting the need for further process optimization. These findings emphasize the potential of chitosan extraction as a sustainable solution, while also underscoring the importance of continued research into the economic feasibility of this waste-to-wealth approach. Further studies are necessary to refine the wastewater treatment process, quantify the economic benefits, and ensure the long-term viability of this entrepreneurial venture in environmental sustainability.

Pre-treatment of composite industrial wastewater by Fenton and electro-Fenton oxidation processes.

The present study aims to characterize three industrial wastewater samples collected from petrochemical, food and beet sugar industries to determine the pollution potential and select the appropriate pre-treatment approach. According to the biodegradability profile of the multi-sourced mixed (composite) sample, the advanced oxidation process (AOPs) namely, Fenton (F) and Electro-Fenton (EF) were adopted as pre-treatment techniques and the operating parameters such as time, type of electrodes, pH, voltage, iron and H2O2 concentrations were critically examined. Analysis of Variance (ANOVA) was conducted to compare the performance efficiency of F& EF AOPs for treating the composite samples and the total operating costs for both approaches were assessed. The results revealed that, the initial values of the composite sample were 7.11, 19.2, 32.6, 19.3, 937, 1512, 860, 3.9, 2110 and 2.34 for pH, Total Dissolved Solids (TDS), Electrical Conductivity (EC), Salinity, BOD, COD, Oil and grease (O&G), Total Phosphorous (TP), Total Suspended Solids (TSS) and Total Kjeldahl Nitrogen (TKN), respectively. In addition, EF process achieved more removal efficiency for COD, O&G, BOD, TSS, and TKN (84.3%, 69%, 85%, 72% and 71.27%) compared to Fenton which displayed 78.43%, 66%, 69%, 70.1%, and 61%, respectively. Moreover, there are statistically significant differences (p < 0.05) between the initial and final (pretreated) values of the composite industrial wastewater for the addressed parameters and EF was significantly (p < 0.05) more effective than F process. The total operating costs were 3.117 and 2.063$ for F and EF, respectively, which confirmed that EF is more efficient and cost effective than F process. It was concluded that electro-Fenton process is favorable, eco-friendly and cost-effective option for pretreating real complicated multi-sourced industrial wastewater. The present study demonstrated a new avenue for achieving efficient management of industrial wastewater generated from similar industries.

Brackish water parameters monitoring dashboard using Internet of things and industry 4.0

INTRODUCTION: Brackish water aquaculture plays a crucial role in meeting the growing global demand for seafood. It offers an opportunity to diversify aquaculture production and reduce pressure on overexploited marine resources. OBJECTIVES: By harnessing the unique properties of brackish ecosystems, this practice contributes to food security, economic growth, and sustainable resource management, while also promoting the conservation of valuable marine habitats. The development of a cutting-edge Indigenous Water Quality Monitoring Prototype named "Aqua BuoySis" for precision brackish water aquaculture utilizing machine intelligence. METHODS: The prototype integrates sensors for Dissolved Oxygen (DO), pH, Temperature, Turbidity, and Total Dissolved Solids (TDS). These sensors are calibrated using a dynamic temperature-based machine-learning approach to ensure accuracy in real-time environments. Sensor calibration constants are uploaded to a server for comprehensive data calibration. RESULTS: The system collects data at 20-second intervals, associating it with specific pond IDs. Data refinement is achieved through Long Short-Term Memory (LSTM) processing. An Android and Web application, available in native languages such as Tamil and Telugu, has been developed to provide live updates to aqua farmers, facilitating informed decision-making. CONCLUSION: This technology represents a significant step towards enhancing precision in brackish water aquaculture through the fusion of machine intelligence and water quality management.

Variability of trace elements in bodies of scrapers (Ephemeroptera) and predators (Plecoptera) from mountain rivers of Dzungarian Alatau (Kazakhstan) and Western Carpathians (Slovakia).

Bioaccumulation of trace elements in aquatic environments can be influenced by local environmental conditions such as temperature fluctuations, pH levels, sediment composition, dissolved organic matter content, and the presence of other chemical substances. We analyzed the differences in trace elements accumulation (S, Cl, K, Ca, Ti, Cr, Mn, Fe, Cu, Zn, Rb, Sr, Mo, Ba, and Pb) between two trophic guilds-scrapers (Ephemeroptera) and predators (Plecoptera)-of freshwater benthic macroinvertebrates collected from mountain streams in Kazakhstan and Slovakia. Trace elements in dried insect bodies were analyzed using an X-ray spectrometer, and physicochemical parameters of stream water were investigated at each sampling site. Our results showed significant differences in Fe, Ti, and Sr levels in predators from Kazakhstan and Cu levels in predators from Slovakia. Despite some trace elements showing higher concentrations in one group over another, the overall differences between regions were more pronounced. Principal component analysis (PCA) revealed that the primary factors influencing trace elements variability were associated with environmental conditions such as temperature, oxygen levels, and total dissolved solids (TDS). PCA components indicated a higher load of trace elements in the warmer, less oxygenated streams, particularly in Kazakhstan. These findings suggest that both biotic (feeding strategies) and abiotic (geographical and environmental conditions) factors significantly influence trace elements dynamics in freshwater ecosystems.

Spatial variation in water quality of the Burhi Gandak River: a multi-location assessment

The Burhi Gandak River, a significant tributary of the Ganga River and a vital water source in Bihar, India, is facing critical water quality degradation due to rapid population growth, urbanization, and industrial activities. This study conducts a detailed water quality assessment of the river, focusing on the effects of these anthropogenic factors across different locations, seasons, and industrial zones. Water samples were collected and analyzed for key parameters, including pH, total dissolved solids (TDSs), total hardness (TH), biological oxygen demand (BOD), and dissolved oxygen (DO). The results indicate significant spatial and temporal variations, with water quality deteriorating notably in areas like Samastipur and Khagaria, where industrial and urban activities are more concentrated. For instance, BOD levels increased from 7.5 mg/L to 9.5 mg/l as the river flows through urban Samastipur, signaling a decline in water quality. Additionally, sugar mills located along the river contribute to higher pollution levels during operational months, especially in Lauria and Sugauli. Seasonal analysis shows that the lean season experiences the highest levels of degradation, while monsoon floods increase suspended solids due to sediment inflow. These findings emphasize the urgent need for improved regulation of industrial discharge and urban waste management to protect the water quality of the Burhi Gandak River and the livelihoods dependent on it.

A Comprehensive Review of Water Quality Analysis

The effluent discharge of domestic wastewater and industrial effluents into watercourses has necessitated the development of monitoring systems with the purpose of characterizing levels of pollution. Substantial levels of pollution in emerging nations have been exacerbated by rapidly growing populations and inefficient enforcement of sustainable management initiatives. The Water Quality Index (WQI) can help fill the gap between water quality reporting and monitoring by offering a simple and effective way to assimilate and communicate results from a large amount of data. WQIs are the kind of communication tools that can facilitate knowledge sharing between scholars and the general public. The degradation of natural water resources, such as lakes, streams, and estuaries, is the most significant problem facing humanity. Water that is not clean has far-reaching effects on all aspects of life. Water resource management is therefore essential if it is to maximize water quality. If data are analyzed and water quality can be predicted in advance, water pollution may be efficiently addressed. Although this subject has been the subject of numerous earlier studies, additional research is still required to fully understand the effectiveness, reliability, accuracy, and application of the present approaches to water quality management. In this research work, a comprehensive review has been conducted on water quality assessment using artificial techniques. It reviews 75 research works on water quality analysis. The data collected in each research work have been analyzed. Moreover, the type of water resource surface water, groundwater, drinking water as well has been analyzed. The parameters considered in each work are “Dissolved Oxygen (DO), Potential of Hydrogen (pH), Biochemical Oxygen Demand (BOD), Total Dissolved Solids (TDS), and Chemical Oxygen Demand (COD), chloride, hardness, alkalinity, nitrate–nitrite”. In addition, the Artificial Intelligence technique utilized for water quality analysis is also assessed. Finally, the research gaps identified in water quality detection are exhibited.

Investigation of particle size distribution and ultrafiltration of digestates from short-fibre residues in paper mills

ABSTRACT Industrial digestates from short-fibre residues, generated in paper recycling mills, are driving interest in resource recovery. This study aims to explore their potential for water recovery. Understanding particle dynamics aids in optimizing dewatering for digestate management. The particle size distribution in this study revealed significant fractions: &amp;lt;0.63 μm (6–20%), 0.63–20 μm (38–52%), and &amp;gt;20 μm (11–16%). Pre-treatment with Na4P2O7 and H2O2 enhances settling and lowers total dissolved solids (TDSs) but results in variation of size distribution. Additionally, this study investigates further water reuse in paper mills, focusing on the quality of ultrafiltration (UF) permeate obtained from the digestate of short fibres. UF permeate analysis reveals deviations from freshwater standards in paper mills. Despite effective TS removal, UF permeate falls short of paper mill water standards due to high TDSs, electrical conductivity, and nutrient concentrations, necessitating further downstream treatment with nanofiltration or reverse osmosis. A substantial reduction of permeate flux from 31 to 5 L/(m2·h) over the time indicated fouling and inefficient membrane wash. The silt density index of the UF membrane at 30 min registered 2.1, suggesting potential fouling. Further investigations on optimizing UF operations to enhance permeate flux and exploring alternative UF membranes are required.

Predicting COD and TN in A2O+AO Process Considering Influent and Reactor Variability: A Dynamic Ensemble Model Approach

The prediction of the chemical oxygen demand (COD) and total nitrogen (TN) in integrated anaerobic–anoxic–oxic (A2O) and anoxic–oxic (AO) processes (i.e., A2O+AO process) was achieved using a dynamic ensemble model that reflects the dynamics of wastewater treatment plants (WWTPs). This model effectively captures the variability in the influent characteristics and fluctuations within each reactor of the A2O+AO process. By employing a time-lag approach based on the hydraulic retention time (HRT), artificial intelligence (AI) selects suitable input (i.e., pH, temperature, total dissolved solid (TDS), NH3-N, and NO3-N) and output (COD and TN) data pairs for training, minimizing the error between predicted and observed values. Data collected over two years from the actual A2O+AO process were utilized. The ensemble model adopted machine learning-based XGBoost for COD and TN predictions. The dynamic ensemble model outperformed the static ensemble model, with the mean absolute percentage error (MAPE) for the COD ranging from 9.5% to 15.2%, compared to the static ensemble model’s range of 11.4% to 16.9%. For the TN, the dynamic model’s errors ranged from 9.4% to 15.5%, while the static model showed lower errors in specific reactors, particularly in the anoxic and oxic stages due to their stable characteristics. These results indicate that the dynamic ensemble model is suitable for predicting water quality in WWTPs, especially as variability may increase due to external environmental factors in the future.

Evaluation of Physicochemical Parameters of Water in Three Lakes of Dindigul District, Tamil Nadu, India

The investigator's goal was to evaluate the effects of pesticide pollution brought on by the vegetable market's wastewater outflow from nearby ponds in and around Dindigul town, Tamilnadu, India. The surrounding research area's ponds have been greatly impacted by the ongoing use of pesticides in these vegetable wastes. Three sampling sites were chosen for this study such as Sadayan, Lakshmi Puram and Nagammal pondss and samples were taken in the summer to examine critical parameters like total hardness, pH, dissolved carbon dioxide (CO2), dissolved oxygen (DO), chemical oxygen demand (COD), biological oxygen demand (BOD), chloride, total alkalinity, and total dissolved solids (TDS), as well as heavy metals. The results indicate that Sadayan Ponds is classified as severely polluted while compared other ponds. This investigation leads to the conclusion that the ponds's water is not appropriate for agriculture or for sustaining wildlife.

Slaughterhouse wastewater remediation using carbonized sawdust followed by textile filtration

Slaughterhouse wastewater (SWW) is considered an industrial wastewater, which seriously harms the environment due to the high concentration of contaminants such as biochemical oxygen demand (BOD), chemical oxygen demand (COD), and total suspended solids (TSS). Additionally, the wastewater from slaughterhouses contains harmful bacteria. This study used a lap-scale model to treat SWW from a local private slaughterhouse. The treatment process involves three stages: adsorption using activated carbon, which is derived from sawdust, followed by sedimentation, and finally, a slow sand filter with a modified layer of woven textile cotton. The first two steps were tested to obtain the ideal operation condition of the treatment system. After the final step of treatment, we evaluated the overall process using a modified slow sand filter (MSSF). We used a Jar test to determine the optimal dosage of activated carbon from sawdust (ACS). The monitored parameters were physicochemical, such as turbidity, total suspended solids (TSS), total dissolved solids (TDS), biochemical oxygen demand (BOD), chemical oxygen demand (COD), total phosphorus (TP), and total nitrogen (TN). The bacteriological examination included both total coliform count (TCC) and fecal coliform count (FCC). The results of the jar test revealed that the optimal ACS dose was 2.0 g/l. After adjusting the contact time and pH levels for the adsorption process, we discovered that the ideal contact time was 100 min and the ideal pH level was 4.0. Finally, we evaluated the entire treatment system by applying the MSSF after the sedimentation process, and found that the removal efficiencies of turbidity, BOD, COD, TSS, TDS, TP, and TN were 97.14, 94.80, 91.80, 98.96, 81.17, 81.12, and 82.50%, respectively. This is in addition to the filter's ability to remove bacteria counts at a rate of up to 98.93 and 99.13% of TCC and FCC, respectively.

Performance of water quality simulation model for lifting drainage water joints and mixing zone determination

Limited water resources with gradual increase in water demand led to higher dependence on drainage water as one of the non-conventional water resources in Egypt. However, there was no precise approach for using such resource. The practices ranged between stopping lifting drainage water to main canals at many locations due to the water quality degradation in the drains and pure dependence on polluted drainage water by farmers. This implies the importance of applying the mathematical models that provide precise and flexible alternative for the dependence on the drainage water. This procedure could save the big investments that were used in the lifting stations while mitigating the environmental hazards. Cornell Mixing Zone Expert System (CORMIX) model is one of these mathematical simulation models. The study used surface discharge sub-model (CORMIX3) to define the mixing zone between the lifted drainage water from Mehalet Rough drain and the freshwater in Mit Yazid canal, by investigated biochemical oxygen demand (BOD) and total dissolved solids (TDS). The simulation results verified that the two investigated parameters met WQ standards for the Egyptian law 48/1982. BOD standard value was met after 448.36 m, in 723 s. TDS standard value was met after 4.46 m, in 7.8 s. This was far ahead of the first municipal station regardless low quality of these parameters in the drain. This is the first time to apply this model in the irrigation sector in Egypt, and the results were promising for defining the precise approach to reuse the drainage water in Egypt.

Comparison of Hollow Fiber and Flat Sheet Membranes for Removing TDS and Turbidity of Palm Oil Mill Effluent Wastewater

The most significant pollutant produced from agricultural industry in Kalimantan, Indonesia is Palm Oil Mill Effluent (POME). Due to the high levels of suspended particles and organic matter, POME has become a brownish color with high turbidity, color, chemical oxygen demand, and oil and grease content. To recycle the POME wastewater as clean water, these pollutants must be eliminated. In this study, we compare the effectiveness of hollow fiber (HF) and flat sheet (FS) membrane to remove total dissolved solid (TDS) and turbidity from POME with varied filtration pressure. HF and FS membrane were prepared from PVDF and nylon66 polymer, respectively. The PVDF HF membrane was modified using TiO2 and SBE (spent bleaching earth) to improve HF membrane properties to maintaining fouling. Meanwhile, FS membrane was added by pectin to increase the hydrophilic properties. Overall membrane’s morphology was determined by Scanning Electron Microscopy (SEM) to investigate the membrane structure. Both of HF and FS membrane were operated via ultrafiltration (UF) under cross flow system. The filtration pressures were varied at 1-3 bar and followed by flux and rejection evaluation. The results show both HF and FS membranes has stability flux. In addition, TDS rejection up to 25% while turbidity is excellent high over 95% for all membranes. The fabrication HF membrane has finger like-sponge structure and FS membrane exhibits sponge asymmetric structure. Overall, all membranes perform highest water flux (FS membrane) while highest rejection conducted by HF membrane for POME wastewater treatment.

Assessing groundwater quality in the northwestern coastal area of Sri Lanka using multivariate statistical techniques

The objective of the present study was to assess groundwater quality in the northwestern coastal region of Sri Lanka by analyzing hydrogeochemical data using multivariate techniques. The study examined the relationship between water quality and sources influencing groundwater quality and proposed useful statistical tools for water resource management. Descriptive, comparative, correlation, factor analysis (FA), and discriminant analysis (DA) were among the techniques used. The water quality in terms of electrical conductivity (EC), total dissolved solids (TDS), and dissolved nitrate and phosphate concentrations of the northwestern coastal area, where different aquifer conditions prevailed, were compared, and differences in the mean concentrations of the above parameters were identified. The study also employed ridge regression and support vector machines (SVM) to predict nitrate levels and validate the results using a 70:30 train/test split. The analysis found that the mean concentrations of EC, TDS, and HCO3- are higher in the sandy aquifer area, while Fe2+ and PO43- are higher in the regolith aquifer area. EC, TDS, PO43-, and HCO3- in the hard-rock aquifer area exceed permissible limits. Factor analysis identified four factors contributing to pollution, and a linear discriminant model classified all observations with 99.9% accuracy. The water quality index for Kalpitiya, Vanathavillu, and Katana-Negombo areas was 68.1, 99.2, and 287.9, respectively, while the World Health Organization (WHO) cutoff was 50. The use of multivariate statistical techniques demonstrated the value of analyzing hydrogeochemical data to gain valuable insights into the complex interplay of factors affecting groundwater quality. The SVM model, using a linear kernel, was identified as the best model to predict nitrate levels. A combination of statistical analyses reveals that, with the exclusion of a few wells, the groundwater in the study area is polluted and inappropriate for human consumption or culinary purposes. Nonetheless, the inhabitants persist in utilizing it as their primary source of drinking water. This study reveals the combination of statistical analyses is useful for the management of groundwater resources.

Recovery and Size-Tuning of Amorphous Silica from Geothermal Scales in Batangas, Philippines

Scale deposits in geothermal power plants are well-known potential sources of minerals. Extensive research in mineral recovery is crucial due to the considerable variability in scale composition and geochemistry based on location. Geothermal scales from Batangas, Philippines, were used to synthesize size-modified amorphous silica (SiO2) via sol-gel method. Initial analyses employing x-ray fluorescence spectroscopy (XRF), total dissolved solids (TDS), electrical conductivity (EC), and pH measurements confirmed that the scale is rich in silica and salts at neutral pH. Then, the effect of varying scale concentration, precipitation pH, and aging time on the particle size distribution of recovered amorphous silica were investigated. Dynamic light scattering (DLS) for particle size analysis (PSA) revealed that the sample with 2.5% (w/v) scale precursor in NaOH and precipitated until pH 10 had the lowest average cumulant diameter (1.66 μm). Moreover, the synergy of precipitation pH and aging time was found to significantly affect the polydispersity index and cumulative diameter of precipitated SiO2 based on 23 factorial ANOVA at 0.05 significance level. X-ray diffractometry (XRD), Fourier transform infrared (FTIR) spectroscopy and scanning electron microscopy (SEM) confirmed that the precipitates were amorphous SiO2 with spherical morphology. This study proves the viability of utilizing geothermal scales from Batangas, Philippines for the synthesis of amorphous SiO2 with controlled particle size, which is a potential filler for composite materials.

Experimental evaluation of Scenedesmus javanensis, Halochlorella rubescens, and Chlorolobion braunii for lipid-rich biomass production and phycoremediation of dairy wastewater

Phycoremediation uses algae as an ecotechnological tool to recycle eutrophic and polluted wastewater from industries. It is vital for fostering a sustainable circular bioeconomy, as the resulting algal biomass can be utilized as a versatile industrial bioresource. This approach is especially pertinent for the dairy industry, which produces substantial amounts of nutrient-rich dairy wastewater (DWW). The effectiveness of phycoremediation of DWW depends on the knowledge of indigenous algae that can thrive in such conditions and rapidly produce lipid-rich or nutraceutically or otherwise valuable biomass. This study assessed the lab-scale phycoremediation of DWW, emphasizing the biomass production potential and quality of three fast-growing green microalgae: Chlorolobion braunii, Scenedesmus javanensis, and Halochlorella rubescens, which are recognized for their high lipid yield potential in growth media. We assessed nutrient and mineral removal efficiency, biomass yield, productivity, biomass quality, and the biodiesel properties of lipids from these algae after ten days of growth in various dilutions and 100 % DWW. C. braunii demonstrated the highest biomass productivity of 149.32 mg L−1 d−1 in 100 % DWW. All species significantly reduced biochemical oxygen demand (BOD), chemical oxygen demand (COD), and total dissolved solids (TDS) of DWW, achieving complete removal of nutrients, along with 80–100 % removal of heavy metals after growth in DWW. C. braunii had a lipid productivity of 49.79 mg L−1 d−1 in 100 % DWW, and lipids from C. braunii and S. javanensis were suitable for biodiesel production, highlighting their potential for large-scale industrial phycoremediation of DWW while generating biodiesel-grade lipids and other valuable bioproducts.

Automated Monitoring System for Rainwater Harvesting Tank at Telkom University

The use of ground tank constructed by Telkom University for Rainwater Harvesting (RWH), is limited to environmental maintenance due to concerns regarding the quality of water in the underground tank. Therefore, this research aims to develop a remote monitoring device that uses Internet of Things (IoT) technology to monitor the pH, water surface, submerged materials, and water clarity levels in ground tank. To achieve the requirements, pH, ultrasonic-based volume, Total Dissolved Solids (TDS), and Turbidity sensors were selected due to the IoT connectivity. The enabling device, namely the ESP 32 microcontroller and Blynk platform were installed on monitoring dashboard on a tablet computer with 4GB of RAM. The result showed that calibration of each sensor had good accuracy, except for the Turbidity sensor due unavailable materials. In conclusion, the RWH monitoring system is suitable for use.

Physicochemical properties and antimicrobial efficacy of argon cold atmospheric pressure plasma jet activated liquids – a comparative study

Cold atmospheric pressure plasma jet activated liquids (CAPJALs) have attracted considerable scientific attention due to their peculiar antimicrobial characteristics. In the current context, there is a need to compare the bactericidal activity of CAPJALs and demonstrate the specific parameters necessary to obtain greater effectiveness. This in-vitro research examines the antimicrobial activity of liquids, such as deionized water (DI-W), drinking water (DW), tap water (TW), and normal saline (NS) activated by Ar cold atmospheric pressure plasma jet (CAPJ) against multidrug-resistant (MDR) E. coli and S. aureus. The computed D- value showed that CAPJALs' bacterial inactivation efficacy followed the trend – DI-W ≈ NS > DW > TW for both the isolates. To obtain greater bactericidal effectiveness, an optimum combination of liquid activation time by CAPJ and CAPJAL – bacteria interaction time was noticed. In addition, the rate at which the physicochemical parameters (pH, electrical conductivity (EC), total dissolved solids (TDS), and concentration of reactive species (H2O2, NO3-, and NO2-)) changed within the liquid varied in different ways. It was observed that the identified gas-phase species (Ar I, Ar+, N2, N2+, O I, OH•, OH+, NO+, O2+, N2O3-, NO3-, N2O2-, etc.) would contribute to modification of liquid physicochemical property by generating liquid phase reactive species (NO3-, NO2-, H+, H2O2, ONOOH, Cl2, HOCl, etc.) via reaction cascades. These reactive species in the liquid phase, together with other physicochemical characteristics, were found to play a part in the process of bacterial inactivation. This study into the underlying mechanism of CAPJ – liquid and CAPJAL – bacteria interaction would help to determine its potential use as a disinfectant in healthcare settings. List of microorganismsE. coli: Escherichia coli; S. aureus: Staphylococcus aureus.

Enhanced Organics Removal Using 3D/GAC/O3 for N-Containing Organic Pharmaceutical Wastewater: Accounting for Improved Biodegradability and Optimization of Operating Parameters by Response Surface Methodology

Pharmaceutical industry effluents often contain high concentrations of refractory organic solvents, chemical oxygen demand (COD), and total dissolved solids (TDSs). These wastewaters, including N-containing organic solvents known for their persistence and toxicity, pose significant environmental challenges. The study evaluated the efficacy of 3D/Granular Activated Carbon (GAC)/O3 treatment compared to linear process additions when treating real pharmaceutical wastewater, and revealed a 2.73-fold enhancement in COD mineralization. The process primarily involves the direct oxidation of monoprotic organic acids found in real pharmaceutical effluents, such as acetic and formic acid, crucially influencing mineralization rates. Optimal conditions determined via the response surface methodology were 125 g/L GAC, 30 mA/cm2, and 75 mg/L O3, achieving high total organic carbon (TOC) and COD removal efficiencies of 87.19 ± 0.19% and 89.67 ± 0.32%, respectively (R2 &gt; 0.9), during verification runs. Current density emerged as the key parameter for organic abatement, aligning with the emphasis on direct oxidation at the anode surface. This integrated approach enhances biodegradability (BOD5/COD) and reduces acute toxicity associated with persistent N-containing solvents, demonstrating promising applications in pharmaceutical wastewater treatment.