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This article presents the outcomes of a research study focused on optimizing the performance of soybean biofuel blends derived from soybean seeds specifically for urban medium-duty commercial vehicles. The study took into consideration elements such as production capacity, economics and assumed engine characteristics. For the purpose of predicting performance, combustion and emission characteristics, an artificial intelligence approach that has been trained using experimental data is used. At full load, the brake thermal efficiency (BTE) dropped as engine speed increased for biofuel and diesel fuel mixes, but brake-specific fuel consumption (BSFC) increased. The BSFC increased by 11.9% when diesel compared to using biofuel with diesel blends. The mixes cut both maximum cylinder pressure and NO x emissions. The biofuel-diesel fuel proved more successful, with maximum reduction of 9.8% and 22.2 at rpm, respectively. The biofuel and diesel blend significantly improved carbon dioxide ( CO 2 ) and smoke emissions. The biofuel blends offer significant advantages by decreeing exhaust pollutants and enhancing engine performance. [ABSTRACT FROM AUTHOR]

The thrust in biofuel production has pushed researchers in finding more of environmentally friendly materials for use as catalyst in the biofuel production process. Commercially available catalyst materials are not sustainable, and they generally incur higher cost of operation. In the present study, locally available native woods species of Manipur, India namely, Yenthou (Arundo donax.L) and Uningthou (Phoebe hainesiana) were exposed at elevated temperature of 400 °C and variable exposure time of 90 and 120 minutes for possible use as catalyst during biofuel production. Muffle furnace has been employed for production of catalyst and characterization techniques such as XRD, FT-IR and SEM with EDX are used. XRD analysis shows diffraction peak corresponding to (0 0 2), (1 0 0) and (1 0 1) of the face centered cubic phase at 28.61°, 28.54° and 30.02° respectively while Scherrer equation shows 29.737 nm as average grain size. FT-IR analysis also shows C=C formation from the samples. The SEM & EDX analysis shows good formation of carbon in the catalyst and the weight % of the components are obtained to be 89.18% and 10.82% for C and O respectively. Transesterification of waste cooking oil at 5% (wt%), 10:1, 75 °C and 60 minutes for catalyst loading rate, alcohol-to-oil ratio, reaction temperature and reaction time respectively shows conversion rate of 87.4±1.3% with reusability of 3 times. [ABSTRACT FROM AUTHOR]

The Corona Virus Disease of 2019 (COVID-19) pandemic in the year 2020 has become a curse for mankind and their livelihood, and India has not been exempted from it. India currently (August 2020) is among the top five countries in terms of the number of cases and is being reported on a daily basis. This also stems due to India having the world's second-largest population. The country is being largely run by the informal sector, which has brought the economic sector to a standstill. Essential service sectors such as pharmaceutical, food industry, and logistics are up and running. However, these barely contribute to the country's economy but have replenished the environment. This manuscript analyzes the environmental effects of enforced lockdown in India on air quality, water quality, and noise levels. In comparison to 2019, levels, air quality, and water quality show positive trends with a reduction in the concentration of major pollutants, such as particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), ozone (O3), and carbon monoxide (CO). Parts of the India have witnessed up to 44% reduction in the Air Quality Index. Dissolved oxygen (DO) has increased and biochemical oxygen demand (BOD) has decreased in most of the rivers in the country, enhancing the water quality. The noise levels in different parts of the country have declined during this lockdown period. However, the stockpiling of COVID-19 related biomedical waste and lack of proper handling has raised concerns over the spread of the disease. Thus, the study shows that the nature itself is capable enough to reduce the environmental pollution within a span of months. [ABSTRACT FROM AUTHOR]

This study assesses the possible reduction in carbon dioxide emissions brought on by the growth of wind power in India by developing offshore site. This study uses novel evolutionary algorithms and computational techniques to analyse wind potential on flat and offshore and sites. The wind data were recorded using remote sensing technique LiDAR (Light Detection and Ranging). This study employs the life cycle assessment (LCA) to quantify the atmospheric carbon emissions of offshore wind turbines, to understand and to guide policy regulatory for offshore wind energy, and future investment decisions for wind power expansion. Parameter estimates are used to compute wind densities. The study demonstrates that wind turbine lifespan and energy output have major effects on GHG (Green House Gas) emission, signifying that it is an efficient strategy to extend wind turbine lifetime and enhance wind turbine energy production to minimise wind turbine GHG emission intensity. Over the course of their lifetimes, offshore wind turbines emit 0.130 kg CO 2 -eq/MJ. Compared to coal power stations, wind turbines have significantly lower life-cycle GHG emission intensities. If wind turbines erected in 2014 supplant coal, the saved GHG emissions might equal 5.08 x 107t CO 2 -eq, or 0.09% of the global GHG emissions in 2021. • Study employs the life cycle assessment (LCA) to quantify the atmospheric carbon emissions. • Study uses novel evolutionary algorithms and computational techniques to analyze wind potential. • Wind data were recorded using remote sensing technique. • Compared to coal power stations, wind turbines have significantly lower life-cycle GHG emission intensities. • The saved GHG emissions might equal 5.08 x 107t CO 2 -eq, or 0.09% of the global GHG emissions in 2021. [ABSTRACT FROM AUTHOR]