There is a growing interest in meeting the rising energy demand from a more sustainable source. Biomass energy has the potential to act as a sustainable and environmentally friendly alternative to fossil fuels and help achieve net-zero emissions in the near future. This study proposes an economically feasible method to enhance biogas efficiency by co-digesting cow dung (CD), food waste (FW), rice straw (RS), with the addition of Coconut husk Bio-Char (BC). The present research aims to study the variation in the biogas yield from biochar addition by monitoring the alteration in the influential parameters such as pH, temperature, total solids (TS), volatile solids (VS), volatile fatty acids (VFA), and carbon to nitrogen ratio (C/N). The biochar addition stabilized both pH and temperature due to its intrinsic properties by transforming intermediates like H2S and CO2. It also significantly increased the VFA accumulation and degradation attributed to the buffering ability of the biochar. The methane yield of blends with biochar was significantly higher than that of the blends without biochar. The mixture CD 30: FW 50:RS 20 containing biochar showed a peak methane yield of 165.08 mL. The statistical model developed using response surface methodology (RSM) predicted the methane yield with an accuracy of 99.07 % and a statistical significance level of 0.05. The accuracy of the RSM model was validated by comparing it with the existing Gompertz kinetic model. The performance evaluation error metrics, Coefficient of Correlation (R), and Root Mean Square Error (RMSE) results were observed to be 0.966, 0.925, and 62.89 mL/gVS, 87.24 mL/gVS for RSM model and Gompertz model, indicating the superior performance of the RSM model developed in this study.

Affordable and swiftly available h-BN@SnO2/TiO2 photocatalysts are being developed through an easy hydrothermally approach was used urea as boric acid precursors. With their constructed photo catalysts, the effect of h-BN@SnO2/TiO2 has been investigated under the assessment of Adsorption agents utilizing X-ray diffraction pattern (XRD), Scanning electron microscopy, Energy dispersive spectroscopic analysis (SEM/EDS), transmission electron microscopy (TEM), high resolution transmission electron microscopy (HR-TEM), and Burner Emit Teller (BET) isotherm testing methods, which also indicated that SnO2/TiO2 and h-BN have been tightly bound together. Because turquoise blue (TB) and Methyl orange (MO) fabric dyes can be found in the industrial wastewater being processed, the photo catalytic degradation process happens to be applied. According to the advantageous linkages of h-BN@SnO2/TiO2 photocatalysts, fantastic efficacy in breakdown towards hazardous compounds has been found. For the decomposition of Turquoise blue (TB) and Methyl orange (MO), the h-BN@SnO2/TiO2 catalysts proved the best performance stability (0.0386 min-1 and 1.524min-1) but were significantly 22 times quicker. Optical catalysis has additionally demonstrated extraordinary resilience and durability throughout five reprocessed efforts. On top of that, an approach enabling photocatalytic breakdown of harmful substances upon h-BN@SnO2/TiO2 has been presented.

Abstract The obsolete efficiencies in conventional centralized wastewater treatment systems call for implementation of source separation and treatment of wastewater. Approximately 60–75% of domestic wastewater is attributed to greywater, which could be reused to combat freshwater crisis. The present study investigates qualitative and quantitative attributes of greywater from different sources in High-Income Countries (HICs) and Low-Income Countries (LICs). The quantity of greywater generation is positively correlated with country’s per capita income, but feebly negatively correlated with temperature. Kitchen source is the highest contributor of total suspended solids (134–1300 mg/l), whereas in case of turbidity, laundry is the major contributor (39–444 NTU). Also, kitchen greywater is characterized by comparatively high biochemical oxygen demand (BOD) of 100–1850 mg/l, low pH of 5.6–8, and elevated total nitrogen (TN) of about 1.5–48 mg/l. The high pH (7.3–10) and chemical oxygen demand (COD) levels (58–2497 mg/l) in laundry greywater are due to usage of sodium hydroxide-based soaps, while usage of wash detergents containing phosphates like sodium tripolyphosphate contribute to high total phosphorus (TP) (0.062–57 mg/l). The qualitative characteristics of greywater in HICs are perceived to be superior compared to LICs. Furthermore, the most widely used physicochemical, biological, and advanced oxidation treatment technologies for greywater are outlined briefly. It can be observed that economical treatment systems like phytoremediation or biological technologies combined with sand filtration systems can be implemented to treat greywater with high organic content in LICs, whereas in HICs where greywater is generated in large quantities, electro-coagulation combined with advanced oxidation technologies can be used to treat its higher COD levels. Graphical Abstract

Rapid progress was made in the development of additive manufacturing process, which went commencing being uncomplicated model substitutes to talented additive process. With powders, additive method such as full melting, segment by segment material fusion, and congeal of fine particles may present inimitable opportunities and compensation. Titanium carbide (TiC) and titanium diboride (TiB2) are employed as reinforcements in the creation of AM60-based hybrid metal matrix magnesium composites. Hybrid AM60 nanocomposites were made using well-known additive manufacturing techniques such selective laser melting. The AM60 bar was created from cylindrical type specimens. The reinforcements are increased by percentages two combination of hybrid composites are prepared AM60 with 4 % Titanium carbide (TiC) and titanium diboride (TiB2) and 8 % Titanium carbide (TiC) and titanium diboride (TiB2). Consequences of the reinforcement were evaluated using micro tensile and micro hardness tests. Among the samples and specimens are showed in harmony through ASTM values, micro tensile and micro hardness characteristics are evaluated using Digital tensometer instrument and a Vickers hardness tester. Vickers Hardness Numbers (VHN) for AM60 magnesium alloy with 4, and 8 % reinforcing are 185.9, and 206.8, respectively. The highest ultimate tensile strengths are, respectively, 703.15, and 809.9 MPa. An Optical Micrograph is used to evaluate the bonding structure of composites, while a Field Emission Scanning Electron Microscope (FESEM) is used to evaluate micro tensile specimens. The greater impact of the different reinforcements Titanium carbide (TiC) and titanium diboride (TiB2) has led to more improved tensile and hardness properties.

A novel way of performing nondominated sorting in a multiobjective optimization problem is proposed using a modified directional Bat algorithm. Unlike NSGA-II, where the solutions of two generations are merged and then sorted for elitism, in the proposed algorithm, the solution is generated and compared with all the previous solutions one by one. Hence, this method reduces the computational time by avoiding the comparison of solutions of two generations, at the same time, generates a diverse solution. A unique way of sorting the solutions is proposed using a Nondomination matrix, which can easily be updated if a new solution is accepted. The Nondomination matrix serves as an archiving strategy to preserve elitism. Detailed criteria are proposed for the selection of a new solution. We have tested the proposed algorithm on some of the standard benchmark optimization problems. The results show that the proposed algorithm is very competitive and outperforms other algorithms in terms of efficiency and other performance metrics for most problems. The algorithm also provides a standard platform for nondomination sorting, which can be applied to any other metaheuristic algorithm.

The Penman-Monteith evapotranspiration (ET) model has superior predictive ability than the other methods, but it is challenging to apply for several Indian stations, owing to the need for a large number of climatic variables. The study investigated an artificial neural network (ANN) model for calculating ET for various agro-climatic regions of India. Sensitivity analysis showed that the overall average change in ET0 values for 25% change in the climatic variables were 18, 16, 14, 7, 5, and 4%, respectively, for T-max, RHmean, R-n, wind speed, T-min, and sunshine hours. The dominant climatic variables were identified from the principal component analysis (PCA) and ET0 was computed using an ANN with dominant climatic variables. The ANN architecture with backpropagation technique had one hidden layer and neurons ranging from 10 to 30 for all climatic variables and from 5 to 10 for PCA variables. The new ET models were statistically compared with Penman-Monteith ET estimate, and found reliable. PCA variables guaranteed an estimate of ET0 accounting for 98% of the variability. The average values of coefficient of determination, standard error of estimate, and percentage efficiency were observed as 0.96, 0.24, and 94%, respectively.

Due to increasing human settlements, agricultural development, and economic activities, the extraction of groundwater is increasing. The over-exploitation of aquifers has become a cause for concern within the last century due to these developmental activities and the accurate estimation of sustainable yield from aquifers is very important. Assessing natural aquifer recharge is one of the key challenges in determining the sustainable yield of aquifers. In this study, an integrated model using the SCS-CN method, remote sensing, and Geographic Information System (GIS) is developed for estimating the natural aquifer recharge for the recharge area of the sub-basin of the Vellar river basin, Tamil Nadu, India. Also, actual infiltration measurements were conducted and an infiltration-based model is developed to compute natural groundwater recharge and compared it with empirical methods. On average, the recharge is 17% of the rainfall for the recharge area.

The synergism effect of sodium tartrate and Zn2+ binary inhibitor system on the corrosion inhibition efficiency of mild steel in an potable water medium containing was analyzed by means of gravimetric and electrochemical spectroscopic measurements. The effect of weight loss method and immersion time on the corrosion behavior of mild steel has also been studied. The scanning electron microscopic (SEM) images showed that the roughness and the deep cracks of the metal surface are reduced significantly by the inhibitor system. Results indicated that the formulation acted as anodic inhibitor. Adsorption of used inhibitor lead to a decrease in the double layer capacitance and an increase in the charge transfer resistance and confirm protective layer by SEM, EDX, AFM and FT-IR. Simple and novel binary inhibitors approach was developed for generating superhydrophobic surface modification of mild steel. Interestingly, Water droplets falling on the leaves bead up and roll off, mild steel immersed in potable water in the presence of binary inhibitor system (sodium tartrate and Zn2+) was attempted to create superhydrophobic surfaces. However, the water contact angle in presence of binary inhibitor system was found to be 152°±4°, whereas in the case of mild steel, it was 55°±2°. A detailed description of the surface-modified superhydrophobic in potable water on mild steel is presented in this article.

The uncertainty in the climate projection arising from various climate models is very common, and averaging such results poses a risk of underestimation or sometimes overestimation of impact in magnitude and frequency. Further, the performance of various climate models in monsoon degrades drastically due to the skewed nature. Under these circumstances, the performance of the climate model in the monsoon and non-monsoon periods is critical for accurate assessment. A multimodal approach has been used in the present work to quantify the uncertainty involved in the climate model using reliability ensemble averaging (REA). Based on AR6 of IPCC, the ensemble of 26 global climate models (GCMs) was used to evaluate the model performance and possible change in seasonal precipitation in four cities with distinct climate conditions, namely, Coimbatore, Rajkot, Udaipur, and Siliguri. The results show that non-monsoon and monsoon rainfall are expected to increase in all the regions. Most of the models perform poorly in simulating monsoon climate, especially in the monsoon period and are highly inconsistent spatially. The study also finds that the model performance is largely linked to the ratio of natural variability and mean.

An efficient dewatering scheme helps the management authority of mines in decision-making on the minimum quantity of withdrawal of groundwater from open-cast mines to avoid excessive groundwater withdrawal from the mines. Karst aquifers are characterized by a dual flow system consisting of Darcy flow and non-Darcy flow in the Matrix and conduits respectively. Due to lack of site-specific data, it is difficult to model the flow behavior in the dual flow system. This study evaluated equivalent porous medium (EPM) approach and the hybrid approach/combined discrete-continuum approach (CDC) for modeling groundwater flow in a karst aquifer and found that hybrid approach is suitable for modeling the flow in the karst aquifer system. Hybrid approach is applied to derive the optimum dewatering scheme for safe mining of limestone in the Adanakurichi limestone mines of Tamil Nadu, India and was found that an additional 20% increase in pumping is required in the year 2020 compared to 2016 to bring the water level to the limestone bottom. Wavelet coherence diagram was used to identify the interrelation between rainfall and groundwater levels, and also between the groundwater levels at different locations. The results from the study will be helpful for the better management of groundwater control operations in karst aquifers, under various safe level of operations. MODFLOW 2005 was used to model the aquifer based on EPM approach and for modeling based on hybrid approach conduit flow process (CFP) Mode 1in MODFLOW was used.

Abstract Climate change has a tremendous effect on the evapotranspiration (ET) process worldwide and the computation of ET for various climatic regions is essential for efficient water management. ET was estimated using Artificial Neural Network models for 10 stations falling under different agro-climatic regions of India. Although the Penman–Monteith ET model has superior predictive ability than the other methods, owing to the need for a large number of climatic variables, it is difficult to use in data-short conditions and it is necessary to determine the most important climatic variables for the agro-climatic regions. Most sensitive climatic variables were identified from the Principal Component Analysis (PCA) for all the stations. Sensitivity analysis showed that the overall average change in ET0 values for 25% change in the climatic variables were 18%, 16%, 14%, 7%, 5%, 4% respectively for Tmax, RHmean, Rn, Wind speed, Tmin and sunshine hours. New ET models were developed for each station, both with all climatic variables and with the important climatic variables identified by PCA, using the ANN model and compared the performance with Penman–Monteith ET estimates. Net radiation, high and low temperatures, usual relative humidity, wind velocity, and the ratio of daily sunshine hours are all input variables to the model, with ET0 values as an output. Several neurons in the hidden layer for each station for the best model performance were found. PCA variables guaranteed the most reliable estimation of potential evapotranspiration (PET) accounting for 98% of the variability. The average values of coefficient of determination (R2), standard error of estimate (SEE), and percentage efficiency (%) were observed as 0.96, 0.24, 94% respectively. There was no significant difference between the ANN model with all climatic variables and with the PCA variables identified indicating that the ANN model with variables resulting from PCA can be preferred for practical applications.

Pharmaceutical industries are known for their batch operations using wide varieties of solvents, reactants, and catalysts. To study the efficiency of production process within a pharmaceutical industry, synthesis of an active pharmaceutical ingredient (API) namely, aliskiren hemifumarate (AH) was analyzed, which is a blood-pressure-lowering medicine. The process mass index, a metric to assess the efficiency of AH production, was calculated. It was found that the process mass index for the AH synthesis was 109 kg raw materials/kg of product, which showed the amount of waste generated during its synthesis. In addition, a life cycle assessment (LCA) study was performed on AH synthesis to understand the overall impacts throughout the life cycle of the product. The results of the LCA revealed that among the various raw materials required, the metal catalyst palladium and solvent dichloromethane were found to have the highest impact on the environment as well as on human health. Both the metal catalyst and solvent play important roles in improving the sustainability of the production. Therefore, the study was extended by comparing the base case with two scenarios of process modification, replacing the toxic palladium with other catalysts and replacing dichloromethane with ethanol, acetone, and benzene. The results of the modified case showed a reduction in the impacts on human health by 97.7%, on the ecosystem by 98.3%, and on resources by 74.1%, thus enhancing the sustainability of the overall process. (C) 2022 American Society of Civil Engineers.

Treated effluents from a pharmaceutical industry were analysed using purge and trap coupled with gas chromatography-mass spectrophotometry to determine the presence of organic solvents. Solvents such as dichloromethane, chloroform, toluene, tetrahydrofuran and chlorobenzene were detected. A health risk assessment study using both the deterministic method and a probabilistic approach by Monte Carlo simulations were then carried out on children, adults and pregnant women considering oral ingestion, dermal contact and fish intake as the exposure routes. Among the various categories of receptors considered, the results obtained by both methods revealed that children are more sensitive followed by pregnant women, since their total hazard index (HI total risk ) exceeded the safe exposure limit for non-carcinogens. It is also evidenced that oral and dermal contact are the crucial routes of exposure among children, adults and pregnant women. The fish intake had the minimal impact on all receptors, which might be due to the lesser affinity of these solvents to sorb onto fish tissues. Cancer risk because of dichloromethane and chloroform exposure was found to be negligible (2.8×10 -8 for children, 1.3×10 -7 for adults, 3.9×10 -7 for pregnant women) since the computed risk was well below the acceptable range (10 -4 - 10 -6 ). The total non-carcinogenic risk calculated from the probabilistic approach exceeded the deterministic approach by 1.9 times, 1.02 times, 1.8 times for children, adults and pregnant women, respectively. This might be due to incorporating lower values among the possible range for the parameters involved during deterministic risk assessment.

A forecast is an estimate of what will happen in the future. It is hardly an unequivocal prophecy. Even the most well-crafted projections might be incorrect. In reality, it is quite uncommon for a prognosis to be completely accurate. Even if forecasting attempts are not perfect, they should not be overlooked. Forecasting aids in both long-term strategic decisions and shorter-term decisions in day-to-day operations. Businesses must create projections of the level of demand that they should be prepared to fulfill. Because service operations cannot typically keep its staff and capability as inventory, they must strive to forecast future demand in order to have the appropriate quantity of service capacity. They squander resources when they overstaff; when they understaff, they risk losing business, time, customers, and exhausted workers.

Open dumping of Municipal Solid Waste (MSW) results in generation of leachate that contains large amounts of organic matter, ammonia, heavy metals, chlorinated organics, phenolic compounds, phthalates, and pesticide residues which irreparably contaminate both surface and groundwater. Advanced Oxidation Processes (AOP) have been reported as one of the effective treatment methods, especially in improving the biodegradability of the leachate as well as effective in removing recalcitrant organics. With AOP pre-treatment rendered the leachate becomes more amenable to further treatment using biological treatment, adsorption, or ion-exchange processes. The study reported in this paper mainly aims at assessing the suitability of ozone and peroxone (O3+H2O2) based advanced oxidation processes (AOP) for the treatment of MSW leachate from the open dumpsite. The effect of reaction time, impact of O3 dose, and H2O2 concentration on the efficiency of COD removal, improvement in the biodegradability of the leachate, and pH change were determined as the performance parameters for the treatment process. The maximum COD removal efficiency was found to be 46% and 82% with ozone alone (3975 mg/L) and with ozone (9275 mg/L) + 50 mg/L H2O2 each with 120 min. reaction time. It is also found that the BOD5/COD ratio has been increased from 0.09 to 0.58 at optimum O3 + 50 mg/L H2O2 treatment would offer as an effective method for increasing the biodegradability.

Abstrac:- Solid Waste is one of the major environmental problems of Indian cities. The quantity of solid waste produced in city depends on the type of the city, its population, living standards of the residents and degree of commercialization, industrialization and various activities prevailing in the city. Solid Waste Management is an obligatory function of municipal corporations, municipalities and other local bodies in India. Waste quantities are increasing and municipal authorities are not able to upgrade the facilities required for proper management of such wastes. In many cities and towns, garbage is littered on roads and foot-paths; almost 90% of Solid waste is disposed of unscientifically in open dumps and landfills, creating problems to public health and the environment. This study is carried out on Municipal solid waste management practice by five major municipalities of Erode District. This study includes review of the waste generation, characterization, collection, transportation, disposal of MSW, Government participation and available income to government through municipal solid wastes. Survey has been conducted to know the public participation towards municipal solid waste management. Some locations were identified for setting up Transfer stations for handling municipal solid waste and sanitary Landfill sites for safe disposal of solid wastes, treatment technologies for MSW along with their benefits, remedial measures and suggestions on future MSWM strategies were also discussed. This study also aims at encouraging authorities/researchers to work towards the improvement of the present system through suggestions, recommendations and also to create awareness among each individual to make pollution free environment

In this article, we see the limit of utilising different city solid waste streams as feedstock for effective power energy creation. These waste streams include ordinarily degradable waste, yet are not limited to mixed burnable waste, versatile and plastic waste, clinical waste with benefits, normal biodegradable waste, biomass, and sewage grime. Current advancements such as anaerobic dealing, gasification, and pyrolysis have been investigated in close proximity to the area and waste stream sums in the chosen test region.It was seen that there are run of the mill, social and monetary benefits in the waste to energy approach for the waste streams kept an eye out for. The reachability of executing such advances is, on an exceptionally fundamental level, dependent upon the fundamental capital hypothesis and the important cost of the work space. Various factors blend the size of the waste stream, the cost of things, and deals. The quick urbanisation and change in lifestyle has increased the waste weight and, as required, ruining loads on the metropolitan environment to unmanageable and upsetting degrees. This assessment revelation embraced existing to foster waste dumping fights are fully past their end and under unsanitary conditions, impelling defiling of water sources, augmentation of vectors of communicable contamination, foul smells and aromas, the appearance of disastrous metabolites, sedative environment and imperfection, etc.

The development of a novel textile sludge based activated carbon (TSBAC) adsorbent and its performance for the treatment of textile dyeing effluent, have been explained in this paper. TSBAC was prepared by the thermal treatment of textile effluent treatment sludge followed by the chemical activation using phosphoric acid. Characterization of TSBAC resulted in enhanced specific surface area (123.65 m2/g) along with the presence of active surface functional groups including -OH, -COOH, -CO. TSBAC showed superior adsorption capacity for methylene blue (123.6 mg/g), reactive red 198 (101.4 mg/g), and reactive yellow 145 (96.8 mg/g) individually, and from the synthetic textile effluent (106 mg/g). The pseudo-second order model and Langmuir isotherm model were found to be fitted well with batch experimental data. The results of the continuous column studies showed that adsorption capacity for methylene blue, reactive red 198, reactive yellow 145 are 101.8 mg/g, 76.6 mg/g, and 75.1 mg/g respectively, and the synthetic textile effluent resulted in an adsorption capacity value of 79.1 mg/g. The reuse potential of TSBAC was proved by effective dye removal up to six reuse cycles. The leachability studies proved that the used adsorbent could be safely disposed of without any harmful effect to the environment.

Sustainable groundwater management necessitates evaluation of the performance of recharge structures to replenish the aquifer without sacrificing quality. Different recharge arrangements were constructed independently in different locations, and also in combination in Cuddalore aquifer in the Tamil Nadu, India, to assess artificial recharge. The individual and combined effectiveness of these structures were studied using water level fluctuation, water balance, and numerical models. It was found that a check dam, a check dam with one recharge well, and a percolation pond with percolation wells had monthly recharge rates 0.30 m3/m2, 0.54 m3/m2 and 0.69 m3/m2 of ponding area respectively. Computational approach based on finite difference method was also used to find the effectiveness of recharge structures. MODFLOW was used to create a finite-difference model and the same was applied to Cuddalore aquifer and the simulated head contours for different scenarios for individual and combined structures were compared to the condition without recharge structures. The study was carried out for three years: one year preceding, and two years following the construction of recharge structures. Maximum water level increase was obtained as 2.54 m, 3.46 m, and 4.7 m for the percolation pond, check dam, and combination structure arrangement, respectively. The developed flow model can be used for groundwater management in the area.