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In this paper, an inductively coupled capacitively loaded ring resonator (IC-CLRR)-based microwave resonant sensor has been proposed for the accurate identification of any unknown liquid sample and its permittivity estimation. The key element of this work is the sensor's wide range capability towards the non-invasive testing of liquids covering a wide dielectric range of liquid samples, i.e., εr = 2 to 80. The proposed microwave sensor is etched over the FR-4 substrate and is excited by the microstrip line through inductive coupling. The placement of an unknown liquid sample in close proximity to the sensor alters its natural resonant frequency due to a change in effective inductance and capacitance as per the dielectric property of the liquid sample. Further, a mathematical formulation using curve fitting has also been derived. The measurement results show a good accuracy in estimating the permittivity and, thus, the unknown liquid identification capability of the designed sensor with a very low error (nearly 5%). This sensor design is simple to fabricate, cost-friendly, and small in size. [ABSTRACT FROM AUTHOR]

Wastewater generated by the textile industry contains a variety of harmful and complex substances. These effluents can negatively impact aquatic ecosystems and human health if not managed properly. The textile industry relies on various chemicals and water to dye and wash fabric. The textile effluent exhibits vibrant colours, elevated pH levels, increased temperature, and higher COD levels. Various factors contribute to the increased pollutant load in effluents, including diluted solids, suspended particles, colours, and toxic metals. Various techniques are used to address textile wastewater, including mechanical, chemical, biological, hybrid, and advanced oxidation methods. This study offers a thorough examination of the dyes and chemicals utilized in the textile industry. It specifically looks at various treatment methods for removing pollutants from industrial wastewater, including chemical, biological, physical, AOPs, and hybrid systems. The findings suggest that photocatalytic techniques are the most effective in terms of rapid dye removal, cost-effectiveness, timeliness, and environmental friendliness. This review also offers a detailed analysis of the past decade and explores the challenges and potential of this innovative approach in the context of sustainable development. [ABSTRACT FROM AUTHOR]

Soil decontamination and restoration continue to be a key environmental concern around the globe. The degradation of soil resources due to the presence of potentially toxic elements (PTEs) has a substantial influence on agricultural production, food security, and human well-being, and as a result, urgent action is required. PTEs pollution is not a threat to the agroecosystems but also a serious concern to human health; thereby, it needs to be addressed timely and effectively. Hence, the development of improved and cost-effective procedures to remove PTEs from polluted soils is imperative. With this context in mind, current review is designed to distinctly envisage the PTEs removal potential by the single and binary applications of biochar (BC) and nanomaterials (NMs).2 Recently, BC, a product of high-temperature biomass pyrolysis with high specific surface area, porosity, and distinctive physical and chemical properties has become one of the most used and economic adsorbent materials. Also, biochar's application has generated interest in a variety of fields and environments as a modern approach against the era of urbanization, industrialization, and climate change. Likewise, several NMs including metals and their oxides, carbon materials, zeolites, and bimetallic-based NMs have been documented as having the potential to remediate PTEs-polluted environments. However, both techniques have their own set of advantages and disadvantages, therefore combining them can be a more effective strategy to address the growing concern over the rapid accumulation and release of PTEs into the environment. [ABSTRACT FROM AUTHOR]

Traditional freshwater sources have been over-abstracted in the worldwide crisis of water scarcity. Effluents have extremely high amounts of Zn2+ and Pb2+, according to an investigation of wastewater samples taken from several industrial zones. However, these heavy metals are among the most harmful to both humans and wildlife that are currently known. Streptomyces sp. is utilized in this study as a biosorbent to biosorb Zn2+ and Pb2+ from single and binary aqueous solutions. Several factors, such as biomass concentration (0.25–4 g), metal solution concentration (5–50 mg L−1), solution pH (2–5), and contact time were standardized. Streptomyces sp. biomass was able to extract 93% Pb2+ and 91% Zn2+ from a single and 95% Pb2+ and 97% Zn2+ from a binary metal aqueous solution containing 25 mg L−1 and pH 4. The highest adsorption capacity in both single and binary sorption experiments was determined to be shared by Zn2+ and Pb2+. The biosorbent's metal adsorption increased from 0.48 to 4.56 mg g−1 for Pb2+ and from 0.21 mg g−1 to 4.65 mg g−1 for Zn2+ when the metals were present singly, and from 0.44 to 4.18 mg g−1 for Pb2+ and from 0.41 mg g−1 to 5.67 mg g−1 for Zn2+ when the metals were present in binary form. The amount of metal ions was raised from 5 to 50 mg L−1. Correlation coefficient (R2) values indicate that the adsorption pattern for Zn2+ and Pb2+ followed Freundlich isotherm R2 > 0.9543 for single and 0.9582 for binary sorption system. In order to remove Zn2+ and Pb2+ from an aqueous solution, Streptomyces sp. is a potential and different source of adsorbents. [ABSTRACT FROM AUTHOR]

Most of the dyes are toxic and non-biodegradable in textile industry wastewaters. Therefore, removal of textile dye using agriculture waste becomes crucial for the environment. This can be accomplished by the biosorption process which is the passive uptake of pollutants by agricultural waste. In this study, Response Surface Methodology (RSM), Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) were used to obtain optimum conditions for Methylene Blue (MB) removal using sugarcane bagasse and peanut hulls as low-cost agricultural waste. The experimental design was carried out to study the effect of temperature, pH, biosorbent amount and dye concentration. The maximum MB dye removal considering the effect of total dissolved solids from aqueous solutions of 74.49% and 67.99% by sugarcane bagasse and peanut hulls, respectively. The models specify that they could predict biosorption with high accuracy having R2-value above 0.9. Statistical studies for RSM, ANFIS and ANN models were compared. Further, the models were optimized for maximum dye removal was at 1.21 g of biosorbent, pH 5.24, 31.24 mg/L MB concentration, 22.29°C of dye solution using sugarcane bagasse and at 1.37 g of biosorbent, pH 5.77, 36.7 mg/L MB concentration, 26.8°C of dye solution using peanut hulls. Additionally, Fourier Transform Infra-Red (FTIR) spectral analysis was also carried out to confirm the biosorption. [ABSTRACT FROM AUTHOR]

Dyes are a significant group of organic contaminants known to negatively affect both humans and aquatic environments. In the textile industry, interest in agricultural-based adsorbents has increased, particularly around adsorption. In this study, methylene blue was eliminated from an aqueous solution using a walnut (Juglans regia) shell. These materials are widely available and inexpensive, and its cost can be a major factor in wastewater treatment batch experiments. Response surface methodology (RSM) is based on a face-centred central composite design, used to identify the independent variable. With the use of RSM, the biomass of J. regia shells was assessed for its capacity to absorb dyes from aqueous solutions, including methylene blue. Maximum methylene blue dye removal percentages (97.70%) were obtained with a 30 mg/L concentration of methylene blue dye, 1.5 gm of biomass, an initial pH of 6, and a contact duration of 60 min at 25 °C. Additionally, particles were absorbed onto the J. regia shell's surface throughout the biosorption process, according to scan electron microscopy. Functional groups were discovered in the Fourier Transform Infrared Spectroscopy spectra, which are crucial for binding during the biosorption of methylene blue. It has been demonstrated that J. regia shell biomass performs well as a biosorbent in the removal of methylene blue from wastewater effluents. It is also a promising, biodegradable, environmentally friendly, economical, and cost-effective biosorbent. [ABSTRACT FROM AUTHOR]

Forward osmosis (FO) has recently gained interest in wastewater treatment and seawater and brackish groundwater desalination. Response surface methodology (RSM) was used for the prediction and optimization of the FO process using a low‐concentration draw solution (DS). The process variables were the feed solution (FS) temperature, the DS concentration, and the FS concentration. These variables were subjected to regression models and had R2 values > 0.9. The FS temperature had a negative impact on the weight transfer from the DS, while the FS and DS concentrations had a direct correlation with the performance. At an FS temperature of 29 °C, the DS at 13 986 mg L−1 and the FS at 1702 mg L−1 produced the best results, thereby lowering the DS regeneration costs. Under this condition, the models were experimentally validated, confirming the predictive ability of the models. [ABSTRACT FROM AUTHOR]

Penoxsulam is new triazolopyrimidine sulfonamide herbicides; it is used to control annual grass and weeds in rice but it disrupts internally growing weeds in rice and inhibits the acetolactate synthase which is commonly found in plants. Sulfonamides drugs may also implicate in any allergic reactions in the body. In agricultural field farmers deals with various herbicides. Skin is the vital path of enter into the body for vulnerability situations and due to large surface area lot of chemicals infilterate the skin can metabolize foreign compound. As Rat and Human both have similar body plans and organs, therefore rat is used as the best model for biological scanning. The present study was conducted to determine the effect of repeated exposure of Penoxsulam herbicide for 28 days by topical route on the physiology of Wistar rats. This study evaluates that there was no clinical signs, skin reactions (Draize method) was noticed and no significant changes was observed in Bodyweight, Haematology, Biochemistry and Histopathology in treated groups after compared with control group of animals. Therefore, Penoxsulam at 1000 mg/kg body weight did not showed any adverse effect on skin to treated rats during the experimentation period. [ABSTRACT FROM AUTHOR]

This research focuses on the viability of removing basic dye methylene blue (MB) from water solutions by the application of sugarcane bagasse (SCB), an economic natural biosorbent. Batch experiments were conducted based on solution pH, contact period, initial adsorbate dye concentration, biosorbent amount, and temperature as independent variables by employing a central composite design approach of response surface methodology (RSM). With the use of RSM, the optimization of the MB biosorption process was carried out for maximum MB removal. The biosorption equilibrium of the dye solution was achieved after a contact time of 90 min and explained by the Langmuir and Freundlich isotherms. The biosorption data is employed for the kinetic modeling, from pseudo-first- and pseudo-second-order kinetic equation. Thermodynamic parameters (Enthalpy change ΔH, entropy change ΔS, and Gibbs free energy ΔG) were studied, which showed that biosorption is natural and endothermic in nature by reducing color randomness at the liquid and solid interface. Biosorbent characterization explained in this analysis is performed through Fourier-transform infrared spectroscopy before and after MB biosorption. Characteristic tests and separation factor proved that SCB was able to be used as an option to commercial biosorbents for the aqueous solution and removal of MB from wastewater. [ABSTRACT FROM AUTHOR]

Desalination of brackish groundwater has emerged as a major option to overcome water scarcity, since quantity and quality of surface water is not appropriate for the continuously growing water demand of two-thirds of the world’s population. Photovoltaic (PV) solar energy powered reverse osmosis (RO) system can be the best option in secluded and isolated areas of the world that are suffering from a shortage of electricity energy and drinking water. This technique is likely to be the lowest energy demanding technology among other desalination techniques. Further, adopting measures like energy recovery devices, hybrid pretreatment process, and battery-less system reduces overall cost of the system. But, the capital cost of the system is still too high to support this technology competitively in the market. In the present paper, a review of the PV-RO systems employed for drinking water treatment in non-electrified rural areas of developing countries has been provided. The status of development in the last few years, along with the attempts towards finding rational solutions for cost reduction are also summarized. [ABSTRACT FROM AUTHOR]

The present study aims at evaluating a small-scale brackish water reverse osmosis (RO) process using parameter optimization. Experiments were carried out using formulated artificial groundwater, and a predictive model was developed by using response surface methodology (RSM) for the optimization of input process parameters of brackish water RO process to simultaneously maximize water recovery and salt rejection while minimizing energy demand. The result of multiple response optimization along with analysis of variance for RSM predictions showed that the optimal water recovery (19.18%), total dissolved solids rejection (89.21%) and specific energy consumption (17.60 kWh/m3) occurred at 31.94 °C feed water temperature, 0.78 MPa feed pressure, 1500 mg/L feed salt concentration and 6.53 pH. Furthermore, confirmation of RSM predictions was carried out by an artificial neural network (ANN) model trained by RSM experimental data. Predicted values by both RSM and ANN modelling methodologies were compared and found within the acceptable range. Finally, a membrane validation experiment was carried out successfully at proposed optimal conditions, which proves the accuracy of employed RSM and ANN models. Present methodology can be used as a generalized way for the optimization of different RO membranes available in the market in terms of increased water recovery and salt rejection with least energy consumption to make it commercially competent. [ABSTRACT FROM PUBLISHER]

ABSTRACT Over the past two decades, the frequency of natural hazard incidents has steadily risen, leading to substantial human casualties, infrastructure destruction, societal and economic disruption. The occurrence of disasters, both of natural and human origin, has exhibited an upward trend in frequency over the past few decades on a global scale, posing a significant threat to diverse populations. Over time, remote sensing technologies have proven to be effective in analysing and monitoring diverse natural disasters, including but not limited to droughts, earthquakes, tsunamis, landslides and cyclones. The significant extent of its coverage capacity and the ability to repeat observations make its application economically efficient. This paper aims to elucidate the fundamental contributions and role of remote sensing in disaster management applications. In a comprehensive analysis, this study explores recent practical applications in the context of disaster events. The utilisation of diverse methodologies and functions of remote sensing in disaster monitoring and control is further expanded to encompass the domain of disaster risk management, employing cutting‐edge sensors and satellites from emerging technological advancements. This paper also addresses challenges related to disaster monitoring, detection and management. Emergencies, particularly during typical catastrophe scenarios, often witness partial disruptions in communication networks. Consequently, the role of alternative networks becomes paramount in enabling effective disaster detection and management strategies. Emerging issues are highlighted, and potential directions for future research are outlined and also support sustainable development goal 13 (climate action). [ABSTRACT FROM AUTHOR]