SCS-curve number (CN) is one of the most well-liked and commonly applied methods for estimating surface runoff. The present study aims to calculate surface runoff using SCS-CN watershed-based calculation and geospatial technology in the Kurumballi sub-watershed Shivamogga District of Karnataka, India. The study area covers about an area of 47.67 sq. km. The union of land use/land cover classification with hydrological soil groups (HSG) yields the runoff estimation by the SCS-CN curve approach. This method calculates the runoff volume from the land surface flows into the river or streams. Moreover, the study area’s delineation of runoff potential zones was done using the thematic integration method. Different thematic layers were used, including lithology, geomorphology, soil, slope, land use and land cover, drainage, surface water bodies, groundwater contour, and isohyetal maps. Furthermore, associating it with the SCS-CN technique, the total surface runoff volume of the study area was estimated. The total surface runoff volume in the study area is 21065849.7 m3. To this study, thematic integration with the SCS-CN approach to estimate runoff for watersheds is valuable for improving water management and soil conservation.

Biofuels are the cheapest source of energy, and the continuous decline of traditional sources of energy with the increasing population leads to looking for alternatives to reduce the consumption of traditional sources of energy. Bioethanol production from lignocellulosic wastes and cellulosic wastes is not a new approach for fuel production but a cheap and accessible way for the production of fuel. Bacillus is one of the major species that can act as a source of diversified enzymes. In this study, it was emphasized on screening and isolation of a novel, characterization, and best catalytic action on both celluloses and proteins in the presence of different carbon and nitrogen sources. It was observed the effective catalytic breakdown of cellulose with the crude enzyme to glucose allowed fur for fermentation with Saccharomyces, ultimately leading to the generation of alcohol. The study aims to isolate the microbes that can produce cellulases and enzymes and could be used for biodegradation to produce ethanol in the reaction. The maximum enzyme activity was achieved at 3.112 UI with optimized pH and temperature, and the maximum conversion of sugars into alcohol was about 70% in the newspaper, cartons, colored paper, and disposable paper cups. An essential observation was the decolorization of the origami craft paper within 24 hours. The study was involved in enhancing the maximum Enzyme activity of cellulases from different cellulosic raw materials. Hence, it was achieved by JCB strain, optimization of pH, temperature, and acids for the biodegradation. The presence of peaks at 3200 and 2900 was a confirmation of ethanol bonds in the biodegradation reaction mixtures.

Over time, predictive models tend to become more accurate but also more complex, thus achieving better predictive accuracy. When the data is improved by increasing its quantity and availability, the models are also better, which implies that the data must be processed to filter and adapt it for initial analysis and then modeling. This work aims to apply the Random Forest model to predict PM10 particles. For this purpose, data were obtained from environmental monitoring stations in Mexico City, which operates 29 stations of which 12 belong to the State of Mexico. The pollutants analyzed were CO carbon monoxide, NO nitrogen oxide, and PM10 particulate matter equal to or less than 10 μg.m-3, NOx nitrogen oxide, NO2 nitrogen dioxide, SO2 sulfur dioxide, O3 ozone, and PM2.5 particulate matter equal to or less than 2.5 μg.m-3. The result was that when calculating the certainty of our model, we have a value of 80.40% when calculating the deviation from the mean, using 15 reference variables.

Aging oil is a common pollutant in petrochemical enterprises due to its severe emulsification and flocculation, poor settling performance, low oil recovery rate, and high difficulty in treatment. This article adopts the method of mechanical, ultrasonic, and chemical coupling demulsification to treat aging oil, with the water content and oil recovery rate of the treated aging oil as the inspection indicators. The experiment shows that when the oil-water ratio is 1:4, the heating temperature is 50℃, the stirring speed is 180rpm, the ultrasonic frequency is 25kHz, the power is 40W, the ultrasonic time is 25min, and the pH is adjusted to 3-4. The additional amount of FeSO4 is 160mg/L, the additional amount of H2O2 is 0.11%, and the heating stirring reaction is 40min. When the dosage of cationic PAM with an ion degree of 50 is 35mg/L, the centrifugation speed is 3200rpm. The centrifugation time is 20 min, the crude oil recovery rate after aging oil treatment can reach over 94.6%, and the water content of the treated crude oil is less than 0.5%, meeting the standards for crude oil gathering and transportation in China. The oil content in the water generated after aging oil treatment is about 150 mg.L-1, the suspended solids content is 200 mg.L-1, the oil content in the residue is 6%, and the water content is 53%. By analyzing the appearance of aging oil before and after treatment, it was found that when using this process to treat aging oil, the original spatial cross-linking network structure of the aging oil was broken, allowing the water droplets wrapped in the oil to be released, thereby significantly reducing the water content in the recovered oil and improving the oil recovery rate.

The coir industry in India’s southern coastal regions, especially in the state of Kerala, is becoming increasingly concerned about the environmental impact of the accumulation and incremental increase of coir pith each year. The objective of this study was to assess the effect of pretreatment on the anaerobic digestion of coir pith. The characterization study of coir pith shows high organic content, which can be anaerobically digested to produce biogas. But, the high lignin content (30.91%) makes the process slow. To overcome this, a biological pretreatment method was tried using two microbial cultures belonging to fungal genera known to be lignin decomposers, viz., Trichoderma and Pleurotus. By using Trichoderma, lignin content was reduced by 3.7%, and the maximum gas production was obtained in a shorter time (19 days) in comparison with the sample without any pretreatment (24 days). When Pleurotus was used for lignin degradation, the lignin content was reduced by 6.78%, and the maximum gas production was obtained in a much shorter time period (14 days) in comparison with the former two methods. The gas produced comprises 74 ppm of methane, which has fuel value. The sludge after digestion was tested, which indicated a marginal increase in NPK value and hence can be used as fertilizer. The results of the study appear to be quite promising in the transition towards green energy by providing scope for the process of biomethanation, with the conclusion that further research can transform coir pith into a good renewable energy resource.

For many years, especially in emerging nations like India, the environment has been threatened by the increased output of industrial wastes and heavy metal toxicity. The usage of inexpensive adsorbents has recently attracted a lot of attention in studies on the removal of heavy metals like nickel from industrial wastewater. The use of agro-based adsorbent is an alternative to conventionally used activated charcoal. In this research, adsorption experiments were carried out using agro-based adsorbent prepared from rice husk, wheat husk, and soybean husk to reduce nickel from industrial wastewater. The adsorption process is simple, economical, and effective is the most preferred method used for the removal of toxic metals like nickel from industrial wastewater. Adsorbents prepared from these husks can be effectively used for adsorption due to low cost & high availability. Characterization of agricultural material by various tests like XRF, proximate analysis, bulk density, and iodine number was conducted on agro-based adsorbents to know the co-relation between removal efficiency and adsorption capacity. The effect of turbidity and pH parameters on Ni removal efficiency is also studied. Results indicated that wheat husk adsorbent appeared to be the most effective for the adsorption of Ni from wastewater as compared to soybean husk and rice husk adsorbent. Wheat husk, soybean husk, and rice husk have removal efficiency in the range of 62.50 to 73.33. Composite absorbents CA-2 with the proportion of 50% wheat husk, 33% soybean husk, and 17% rice husk have 82.50% efficiency, and CA-3 has 80.83% efficiency in removing Nickel. Wheat husk adsorbent, CA-2, and CA-3 are more effectively and sustainably used for the treatment of industrial wastewater to remove heavy metals.

In recent years, Electric Vehicles (EVs) are contributing a major share in Thailand and benefit the environment. Most of the EV charging stations are sourced from solar energy as it becomes a carbon-free source of energy production. Secondly, Thailand is rich in solar irradiance, and higher irradiance leads to higher power production. On the other hand, in tropical conditions, solar Photovoltaic (PV) module temperature increases following the solar irradiance due to high ambient temperature, resulting negative impact on the efficiency and lifespan of photovoltaic (PV) modules. Further, to increase PV power production, in this study, different rates of cooling strategies are proposed. The study found that reducing the temperature by 5% to 25% resulted in increased average power outputs of 5947.94W, 6021.43W, 6094.92W, 6168.41W, and 6241W, respectively. Notably, 25% of the cooling rate achieved higher production. However, it is lower than the nominal power production. Following that, economic analysis and environmental impacts are analyzed for Thailand’s EV charging station using a different cooling rate of PV module. Overall, it is concluded that, depending on the economic viability of the EV charging station, cooling technology can be applied, and it will benefit the EV charging station both economically and environmentally. To further enhance the solar PV power production approach for EV charging stations in Thailand, it is imperative to prioritize future endeavors towards optimizing cooling technology, integrating energy storage, and implementing supportive policies.

The sustainability of using industrial by-products for the construction of landfill cover was determined using Life Cycle Assessment (LCA). LCA was carried out on four materials: sand- bentonite mix, red earth- bentonite mix (amended soil), Waste Foundry Sand (WFS)- Bentonite mix, and WFS- marine clay mix. The former two are commonly used cover soils and the latter two are alternative materials proposed. Environmental impacts based on the extraction of resources, processing, transportation to the site, and site preparation were considered using the ‘cradle to site’ approach. Analysis was carried out in OpenLCA software using the ReCiPe (H) Midpoint method of impact assessment. Required data for analysis was taken from the Ecoinvent database supplemented with inputs from a field survey. The use of WFS in landfill cover systems was found to be sustainable using LCA studies when compared to conventional materials.

Air quality is a vital concern globally, and Sri Lanka, according to WHO statistics, faces challenges in achieving optimal air quality levels. To address this, we introduced an innovative IoT-based Air Pollution Monitoring (APM) Box. This solution incorporates readily available Commercial Off-The-Shelf (COTS) sensors, specifically MQ-7 and MQ-131, for measuring concentrations of Carbon Monoxide (CO) and Ozone (O3) ,Arduino and "ThingSpeak" platform. Yet, those COTS sensors are not factory-calibrated. Therefore, we implemented machine learning algorithms, including linear regression and deep neural network models, to enhance the accuracy of CO and O3 concentration measurements from these non-calibrated sensors. Our findings indicate promising correlations when dealing with MQ-7 and MQ-131 measurements after removing outliers.

The world is currently facing significant environmental challenges due to increasing urbanization and globalization. Human activities can produce greenhouse gases (GHGs) such as CO2 and CH4. One of the contributors to GHG generation is the open dumping of Municipal Solid Waste (MSW), particularly because much of the waste is organic. It undergoes anaerobic decomposition, leading to the formation of GHGs, particularly methane. However, CH4 has a high potential for energy generation, and if harnessed properly, it can be highly beneficial. This study aims to assess the total air pollutants emitted from the landfill gas (LFG), including methane (CH4), carbon dioxide (CO2), and nonmethane organic compounds (NMOC) at the Regional Piyungan landfill in D.I. Yogyakarta province. The study also projected the year when the production of these gaseous pollutants would peak and when they are expected to be exhausted. Additionally, the study aimed to identify the potential health problems and clinical codification caused by these gaseous pollutants. To achieve these objectives, the LandGEM 3.03 version of the model developed by USEPA was used for the period 2023-2071. Clinical coding used the 2019 version of the ICD-10 reference. The estimated values for total LFG were 1.648E+04 (2024) and 1.584E+04 (2025) Mg/year, while CH4 was estimated at 4.403E+03 (2024) and 4.230E+03 (2025) Mg/year. CO2 was estimated to be 1,208E+04 (2024) and 1,161E+04 (2025) Mg/year, and NMOC was projected at 2,839E+01 (2024) and 2,727E+01 (2025) Mg/year. Some of the toxic effects that can occur cause respiratory, visual, and mental disorders with a variety of clinical codes.