The necessity of energy is continuously increasing, whereas fossil fuel sources are gradually depleting. To mitigate this problem, fish processing waste of the bluespotted stingray (Neotrygon kuhlii), available in the Borneo region, was investigated for an alternative feedstock of bioenergy production. The fish wastes are hazardous for the environment, whereas the biodiesel from fish waste is pollution-free and produces less contaminant gas and carbon dioxide than fossil fuel. From the proximate analysis, the moisture content, volatile matter, fixed carbon, and ash content of the fish waste were achieved as 4.88%, 63.80%, 15.03%, and 16.29%, respectively. The proportion of carbon, hydrogen, nitrogen, sulfur, and oxygen was found as 42.06%, 5.99%, 10.77%, 0.91%, and 40.27%, respectively, from the ultimate analysis. The calorific value was 21.53 MJ/kg, which would be highly effective in biofuel production. The morphology analysis results of the biomass are favorable for renewable energy sources. The major bondage between carbon and hydrogen and oxygen was found using Fourier transform infrared spectroscopy. The thermogravimetric analysis and derivative thermogravimetry revealed that the highest weight loss occurred at 352 °C temperature with a decomposition rate of 4.57 wt.%/min in pyrolysis circumstances, and at 606 °C temperature with a decomposition rate of 3.77 wt.%/min in combustion conditions. In the pyrolysis process for 25 °C/min heating rate, the yield of biochar, bio-oil, and bio-syngas was found as 33.96, 29.34, 23.46% at 400 °C, 47.72, 49.32, 33.87% at 500 °C, and 18.32, 21.34, 42.37% at 600 °C, respectively. The characteristics and pyrolysis yields of fish waste are suitable for being an effective renewable energy source.

Despite numerous studies on residential rainwater tank, studies on commercial rainwater tank are scarce. Corporate authorities pay little heed on this sustainable feature. With the aim of encouraging corporate authorities, this study presents the feasibility and economic benefits of rainwater harvesting (RWH) in commercial buildings in the capital city of Bangladesh, where water authority struggles to maintain town water supply. The analysis was conducted using a daily water balance model under three climate scenarios (wet, dry and normal year) for five commercial buildings having catchment areas varying from 315 to 776 m² and the storage tank capacity varying from 100 to 600 m³. It was found that for a water demand of 30 L per capita per day (lpcd), about 11% to 19% and 16% to 26.80% of the annual water demand can be supplemented by rainwater harvesting under the normal year and wet year climate conditions, respectively. The payback periods are found to be very short, only 2.25 to 3.75 years and benefit–cost (B/C) ratios are more than 1.0, even for building having the smallest catchment area (i.e., 315 m²) and no significant overflow would occur during monsoon, which leads to both economic and environmental benefits. Though the findings cannot be translated to other cities as those are dependent on factors like water price, interest rate, rainfall amount and pattern, however other cities having significant rainfall amounts should conduct similar studies to expedite implementations of widescale rainwater harvesting.

There has been a steady growth in the length of pipelines over the past 45 years, with over 6000 operating platforms extracting oil. Several facilities would reach their operational life, which can no longer be economically viable for their production and will eventually undergo the decommissioning procedure. Almost 3000 petroleum industries will likely be decommissioned worldwide in the next 17 years. By 2030, the total cost of decommissioning globally amounted to about USD 104.5 billion. The choice to decommission the offshore oil and gas sector is considered complicated and crucial as it must evaluate numerous variables such as cost, health and safety, and environmental consequences. This review paper aims to assess the decommissioning activity, specifically on pipelines in the oil and gas industry. The purpose of this study is to understand and evaluate significant environmental impacts associated with decommissioning of oil pipelines and to propose mitigation measures to address the challenges of decommissioning. Waste disposal, a threat to biodiversity and air pollution, is a major environmental concern in decommissioning oil and gas pipelines. Among the decommissioning measures, leave in-situ has the lowest environmental impact while repurposing and recycling, with the application of environmental impact qualitatively and quantitatively by integrating 3D information models, mathematical models embedded in hydrodynamic models look promising for decommissioning.

To overcome the consequences of arsenic contaminations, several methods are being proposed. However, practical implementation of those studied methods is rare, mainly due to uncertainties in perception regarding the treatment efficiency of a particular method under different operating conditions. A parametric mathematical model is proposed for the estimation of arsenic-trapping efficiency using saxaul ash sand as adsorbent for the treatment of arsenic-contaminated water under different input conditions. The developed model is based on three independent factors: adsorbent dose concentration, solution pH and initial arsenic concentration in the solution. These factors were selected based on a rigorous experimental study using saxaul ash as adsorbent, which was conducted earlier. Individual relationships between each of those contributing factors and arsenic-removal efficiencies were established based on experimental results. Each relationship was expressed with a best-fit equation and converted to a contributed factor. It is found that the derived best-fit relationships of removal efficiencies follow polynomial patterns with pH and logarithmic patterns with initial concentration and dose concentration. Finally, all the contributed factors were amalgamated into a single equation representing arsenic-removal efficiency for any pH, initial arsenic concentration, and dose concentration. Model-predicted results are compared with the original measured data from the earlier experiments. It is found that the developed best-fit equations for pH, initial arsenic concentration and dose concentration can replicate measured values with coefficient of determination values of 0.88, 0.96 and 0.99, respectively. A comparison of final equation predictions reveals that the predictions are quite accurate, except for a few estimations yielding general statistical errors such as RMSE = 8.07, MAE = 4.73 and RAE = 0.10. Discrepancies in a few predicted values can be attributed to the non-adherence of original measured values to the adopted best-fit trend, especially for the case of pH. Such a developed model can be used for the estimation of arsenic-trapping efficiency with any desirable mix of independent variables selected in this study.