The present study aimed to find a relationship between turbidity removal percent in tube settler clarifier and independent variables (tube inclination, alum dosage, and surface loading rate) by constructing a statistical model and categorizing these explanatory variables according to their impact on turbidity removal percentage. A pilot scale of tube settlers was designed and fabricated to conduct the experiments. It consisted of a coagulation and flocculation basin, pre-tube settler chamber, and tube settler. Alum was used to coagulate the Tigris river raw water at different dosages. After flocculation, water is transferred to the pre-tube settler chamber and flows through the tube settler. It consists of four tubes of square section, 4 centimeters in diameter, with the flexibility of changing tube length and inclination angle to obtain different levels of surface loading rate. More than 120 experiments were conducted, and the results were analyzed statistically. A regression model was found with a coefficient of determination of 0.802 between turbidity removal percentage as a dependent variable and each tube inclination, alum dosage, and surface loading rate as independent variables. The model is considered good as the model’s relationship between actual and predicted values has a slope of one and a constant near zero. Surface loading rate has the highest effect on turbidity removal percentage with 4.44 times that of inclination angle and 2.5 times for the optimum alum dosage model. The study concluded that the linear model is suitable to represent the performance of tube settlers at optimum alum dosage.

Mathematical Modeling of the activated sludge process (ASP) enhances the understanding of the process and improves the quality of the effluent released. However, as the process is complex and nonlinear, mathematical modeling of the process has been a challenge. In this study, multi-layer perceptron neural networks (MLP-ANN) are investigated to predict water quality parameters for better control of wastewater treatment plants employing an activated sludge process. The study area selected was in a central district of the southern state of India. The parameters to be investigated are biochemical oxygen demand (BOD), suspended solids (SS), and pH. The model is evaluated based on statistical parameters of correlation coefficient R and mean square error (MSE). The neural network toolbox of MATLAB 2015b is used for modeling and simulation study. It has been found that effluent biochemical oxygen demand was predicted with a maximum correlation coefficient of 0.927 and minimum mean square error of 0.0022, effluent suspended solids were predicted with a maximum correlation coefficient value of 0.947 and minimum mean square value of 0.0058, effluent pH was predicted with a maximum correlation coefficient value of 0.8299 and minimum mean square value of 0.0132.

With India’s population growing at a rapid pace, traditional agriculture will have a tough time meeting future food demands. Water availability and conservation are major concerns for farmers. This paper aims to discuss the aspects related to designing and fabricating an automatic irrigation system using the Internet of Things (IoT) which will save the farmer’s time and money significantly. Human intervention in fields will be reduced. Changes in soil moisture are detected by soil moisture sensors and irrigation is automated using IoT. The proposed system is most economical for underdeveloped places because it is very cost-effective. Based on the soil moisture content, the sensor detects and sends signals to the node MCU, which activates the motor. When the plants receive enough water, the motor automatically shuts off. The user will be alerted about the soil’s moisture content through his mobile phone. The proposed smart irrigation system is implemented at our campus which conserves energy and water.

The Rumei Hydropower Station is a typical cascade hydropower development project in a plateau area. The dam site is located in an area with complex topography, lithology, and geological structure. Geological disasters are developed in the area, mainly debris flow. Thus, taking the dam site and the surrounding areas as key evaluation objects, the engineering geological characteristics, geological environment characteristics, and the susceptibility and risk of geological disasters that may be caused are predicted and evaluated. The main methods used in this assessment are the binary logistic regression model and expert evaluation. The results show that the susceptibility to geological disasters is small and medium. The results of this study could provide a scientific basis for the rationality of the general layout and site selection of the project construction in the plateau water elevator level development reservoir area.

The objective of the research was to evaluate the effect of geographic altitude on the carbon stock in two physiographic units of the Reserved Forest of the Universidad Nacional Agraria de la Selva, Tingo Maria-Huanuco. The methodology used was the field manual for the remeasurement and establishment of plots of the Amazon Forest Inventory Network (RAINFOR), for which 2 hectares were permanently established (one hectare in low and high hills) in which the diameter (greater than or equal to 10 cm) and the height of the trees were measured. Finally, the density of the wood was obtained from previous studies. The pantropical model formula was used to estimate the carbon stock. The results show that geographic altitude significantly affects carbon stock (p < 0.05) in low and high-hill forests, concluding that this may be due to differences in meteorological variables such as precipitation, temperature, and humidity.

An ecological vitrimer is being developed using activated carbon pyrochar from municipal mixed plastic waste pyrolysis into an epoxy composite. Durable vitrimeric materials may be created by adding pyrochar to polymeric composites. Due to their ductility, reusability, and recyclability, vitrimeric materials have become popular and reliable materials. As a result, the self-healing temperature of composite vitrimers is lower via disulfide exchanges than that of virgin epoxy vitrimers. Additionally, compressive studies have been used to study self-healing capacities, and modulus variations have been used to highlight changes in the healing efficiency of the materials.

Characterization and treatment of greywater are major environmental issues in most nations of the world. The research aims to characterize and evaluate recycling technologies using an analytical hierarchical process for Afe Babalola University Ado-Ekiti (ABUAD) community. A survey was conducted around ABUAD to determine the number of functioning boreholes and active water systems in the area, the total population of students was derived from the total head count of each room and student in each hostel, and a population projection for the next 3 years was conducted to determine the rate at which the student body will grow in terms of future water demands, and daily water volume and questionnaires were used to collect data. Before developing the small-scale model of the greywater filter system (consisting of activated carbon, shaft sand, pebbles, cotton fiber, and gravel), water grey samples were gathered from several ABUAD locations to evaluate the pollution level of each greywater source. A total of 88 students (43 males and 45 females) replied to the survey, revealing their high need for clean water and their dissatisfaction with the water supply in their respective hostels. The water quality tests conducted in the various locations of ABUAD reveal high levels of total dissolved solids (TDS) and turbidity, particularly in the girl’s hostels, and the water was discovered to be predominantly alkaline. After passing a sample of greywater through the small-scale greywater filtering device, it was determined to be effective, since it produced clear, reusable water and a greywater filtration system in ABUAD will yield favorable outcomes.

Goa is a coastal State located on the west coast of India, known for its pristine sandy beaches and environment. Ministry of Environment and Forest implemented Coastal Regulation Zone Notification in 1991 for monitoring the coastal zones for unplanned developmental activities but has been just for name-sake purposes (Mascarenhas 1999, Agarwal 2019). The regulation has been changed in recent years thereby making the coastal and the riverine ecosystem more vulnerable to human interference. In the name of development, various hap-hazardous, unplanned activities have taken place which is degrading the coastal and riverine environment, especially mangroves. This paper studies the vulnerability of mangroves to the changing regulations with respect to 1991 and the 2018 CRZ notifications considering the land use land cover changes in the regulated zones of Mandovi and Zuari rivers. Spatial analysis techniques and software such as Arc GIS 10.3, and ERDAS IMAGINE 2014 have been used for analysis and results. The findings from the study can be effectively implemented in monitoring the regulated zones and protecting mangroves efficiently.

The study assessed the status of water quality parameters for an urban water body (Hatirjheel Lake) in Dhaka, the Capital city of Bangladesh. Nine different water samples were collected from nine points of the lake during the dry season in January 2021. Water quality parameters such as pH, electrical conductivity (EC), total dissolved solids (TDS), total suspended solids (TSS), total alkalinity, total acidity, total hardness, Ca2+ hardness, free CO2, and dissolved oxygen (DO) were determined for the samples. The status of the parameters is pH (6.51-7.05), EC (510-600 μS.cm-1), TDS (450-590 ppm), TSS (0.0-0.034 mg.L-1), total alkalinity (80-392 mg.L-1), total acidity (224-500 mg.L-1), total hardness (348-452 mg.L-1), Ca2+ hardness (74-162 mg.L-1), free CO2 (730-1170 mg.L-1), DO (2.7-5.5 mg.L-1). However, the DO value at some points of the lake is too less (2.7 mg.L-1 and 3.7 mg.L-1) than the standard value (> 5-6 mg.L-1) of ECR, DoE, which might not be healthy for any water body and aquatic ecosystem. Other water quality parameters are within the permissible limit of WHO and ECR, DoE.

Due to anthropogenic activities and the advancement of industries, metal contamination is growing globally. Aluminum toxicity is seriously endangering plants, animals, and humans by rapidly rising in soil and water. Even though some fungi can tolerate aluminum, researchers are interested in finding bacteria that are resistant to aluminum. The current state of knowledge on bacteria resistant to aluminum is extremely limited. In the present study, bacterial isolates from soil near a metal electroplating and automobile industry in Punjab, India, were isolated and then screened for high aluminum metal tolerance. The aluminum tolerant bacterial isolate was identified as Cedecea davisae M1, a member of the Enterobacteriaceae family, using morphological, biochemical, and 16srRNA gene sequence analyses. The spectroscopic results indicate that the strain may tolerate up to 150 ppm of aluminum. Antibiotic resistance of Cedecea davisae M1 was determined using disks on Luria agar plates, and the bacteria were found to be resistant to vancomycin, ampicillin, carbenicillin, and rifampicin. The findings of the study indicated that the strain might be able to remove aluminum toxicity from the environment, which needs to be further explored.