• Energy Research
• 2021-2025close
• 13. Climate action close
• 7. Clean energy close
• 11. Sustainability close
• 6. Clean water close
• BD close

Rapid urbanization combined with high economic growth, industrialization, and changes in socio-economic conditions increase the quantity of municipal solid waste. Cities located in South-Asia are facing serious issues due to waste, with countries like India, Bangladesh, and Pakistan top of the list of bad waste management. The increasing generation of solid waste and also the improper management of waste in Bangladesh leads to environmental degradation. Current waste management practice in Bangladesh is so weak that day by day it is harming the climate and creating a lot of unwanted situations. This research consists of an examination of the current administrative measures and presents another proposition for the executive cycle to decrease ecological contamination. The research study aims to decrease the amount of waste being dumped into municipal sanitary landfill sites & converting the waste into energy which is both financially and environmentally suitable by involving unemployed people in the management system. The results of this study will give an idea of how waste can be utilized as a resource and how this resource can be a capital good as well as how the local level problems can be solved by taking some strategies and making our environment suitable for future generations.

Bangladesh is currently hosting about 1.30 million Rohingya people in its southeastern region, the most persecuted ethnic minority of the world. The present semi structured living shelters mostly made of bamboo and plastic sheets, are not resistant to environmental disasters like- monsoon rain, cyclone, mudslide, and prone to cause vector borne diseases. This study developed plastic brick, where a waste 500 mL polyethylene terephthalate bottle was utilized which was manually compacted with air dried fine sand as the filler material. Cardboard frame was used to shape the brick like a normal clay brick. The filled bottle was placed at the central portion of the frame where hand blended mortar was used to cover the whole frame up to the marked dimensions. The prepared brick samples were subjected to compression test and the average strength obtained was 2.88 and 3.29 N/mm2 for 14- and 28-day crushing age samples, respectively and demonstrated a high potential for the bricks to be used in construction works. The hazard due to environmental disasters in the displacement camps along with managing plastic waste, utilization of plastic brick can be a low cost, useful, and sustainable way towards a safe and rigid living structure.

More and more renewable energy sources are integrated into power grids, leading to a power electronic-based low-inertia power system. The grid-forming (GFM) inverter is an effective method for improving the inertia of the system. However, with the increased GFM inverters in the system, how the multiple control parameters affect the frequency response is still not clear. In this study, first, the power-phase model of the power grid is established; then, a small-signal distributed frequency model of the GFM inverter-based power system is established associating with the power-phase model of the power grid and the power-frequency model of the GFM inverter. Based on the proposed model, the influence of the multiple parameters to the frequency response is analyzed. It is concluded that both the inertia and damping coefficient affect the settling time, overshoot, and oscillation of the frequency. Finally, the simulation results verify the proposed model and the conclusion.

Ionic liquids (ILs) are molten salts that are entirely composed of ions and have melting temperatures below 100 °C. When immobilized in polymeric matrices by sol–gel or chemical polymerization, they generate gels known as ion gels, ionogels, ionic gels, and so on, which may be used for a variety of electrochemical applications. One of the most significant research domains for IL-based gels is the energy industry, notably for energy storage and conversion devices, due to rising demand for clean, sustainable, and greener energy. Due to characteristics such as nonvolatility, high thermal stability, and strong ionic conductivity, IL-based gels appear to meet the stringent demands/criteria of these diverse application domains. This article focuses on the synthesis pathways of IL-based gel polymer electrolytes/organic gel electrolytes and their applications in batteries (Li-ion and beyond), fuel cells, and supercapacitors. Furthermore, the limitations and future possibilities of IL-based gels in the aforementioned application domains are discussed to support the speedy evolution of these materials in the appropriate applicable sectors.

AbstractThis study is aimed to apply dry anaerobic digestion (DAD) for methane (CH4) enriched biogas production from unsorted organic municipal solid waste (MSW). Cumulative biogas production was monitored for 35 days of operation in batch digesters at fixed feedstock to inoculum (F/I) ratio 2. Anaerobic sludge (AS) and cow manure (CM) were used as inoculum in single and mixed modes. Several process parameters such as inoculum flow pattern (single layer, multilayer, and spiral), digestion temperature (25 to 40 °C), inoculation modes (single and mixed mode), and inoculation proportion (AS:CM = 1:1, 1:2, 1:3, and 2:1) were investigated to determine the optimum DAD conditions to maximize the CH4 laden biogas yield. The study of inoculum flow pattern showed that digester with multilayer inoculum configuration generated the maximum 555 mL cumulative biogas with the production rate of 195 mL/day (at 25 °C). Biogas production rate and cumulative biogas production were found to increase with a rise in temperature and the maximum values of 380 mL/day and 1515 mL respectively were observed at 37 °C. The mixed mode of inoculation containing AS and CM augmented the biogas yield at previously optimized conditions. Final results showed that digester with multilayer inoculum flow pattern at 37 °C produced 1850 mL cumulative biogas with 1256.58 mL CH4/kg volatile solid (VS) when the mixed inoculum was used at the AS:CM—1:2 ratio. Biogas production with this significant amount of CH4 justifies the use of the DAD process for energy (biogas) generation from widely available biomass feedstock (MSW), offering various advantages to the environment.

This paper presents a comprehensive review of machine learning (ML) based approaches, especially artificial neural networks (ANNs) in time series data prediction problems. According to literature, around 80% of the world’s total energy demand is supplied either through fuel-based sources such as oil, gas, and coal or through nuclear-based sources. Literature also shows that a shortage of fossil fuels is inevitable and the world will face this problem sooner or later. Moreover, the remote and rural areas that suffer from not being able to reach traditional grid power electricity need alternative sources of energy. A “hybrid-renewable-energy system” (HRES) involving different renewable resources can be used to supply sustainable power in these areas. The uncertain nature of renewable energy resources and the intelligent ability of the neural network approach to process complex time series inputs have inspired the use of ANN methods in renewable energy forecasting. Thus, this study aims to study the different data driven models of ANN approaches that can provide accurate predictions of renewable energy, like solar, wind, or hydro-power generation. Various refinement architectures of neural networks, such as “multi-layer perception” (MLP), “recurrent-neural network” (RNN), and “convolutional-neural network” (CNN), as well as “long-short-term memory” (LSTM) models, have been offered in the applications of renewable energy forecasting. These models are able to perform short-term time-series prediction in renewable energy sources and to use prior information that influences its value in future prediction.

The Rooppur Nuclear Power Plant (RNPP), the first nuclear power plant in Bangladesh with a capacity of 2.4 GWe, is under construction on the bank of the river Padma, at Rooppur in Bangladesh. Measurement of background radioactivity in the natural environment adjacent to RNPP finds great importance for future perspectives. Soil and sediment samples collected from upstream and downstream positions of the Padma River (adjacent to RNPP) were collected and analyzed by HPGe gamma-ray spectrometry for primordial radionuclides. The average activity concentrations (in Bqkg−1) of 226Ra, 232Th and 40K radionuclides in soil samples were found to be 44.99 ± 3.89, 66.28 ± 6.55 and 553 ± 82.17 respectively. Respective values in sediment samples were found to be 44.59 ± 4.58, 67.64 ± 7.93, 782 ± 108. Relevant radiation hazard indices and dosimetric parameters were calculated and compared with the world average data recommended by US-EPA. Analytical results show non-negligible radiation hazards to the surrounding populace. Measured data will be useful to monitor any change of background radioactivity in the surrounding environment of RNPP following its operation for the generation of nuclear energy.