Search

Simulations of a fluidised bed reactor for gasification of municipal solid refuse-derived fuel were performed using OpenFOAM software. Firstly, evaluation was made of a simplified gas-solid two-phase model, considering sand and air as the components, according to a transient Eulerian-Eulerian approach. A scale-up study was also performed to obtain thermal-fluid dynamic parameters. Then, a real dimensions non-reacting model was developed, based on the experimental information from a semi-industrial gasification plant with capacity for processing 7.1 t day−1 of municipal refuse-derived fuel, producing 16.9 t day−1 of syngas. The fluidising regime was mapped for different inlet conditions, at 1,123 K, with air velocities ranging from 0.01 to 1.25 m s−1, and the continuous operation of the reactor was analysed, where in the solid particles packing remained at approximately 88% from maximum, with bed height of 2.05 m. The results were in good agreement with data available in the scientific literature, and the computational model was able to provide consistent results when compared to the experimental information for the semi-industrial reactor. The authors’ major remark was the hability of this computational model in obtaining consistent results from simulations of the semi-industrial scale reactor, with good prediction of the internal fluid dynamics characteristics.

Benzophenone-3, fipronil and propylparaben are micropollutants that are potential threats to ecosystems and have been detected in aquatic environments. However, studies involving the investigation of new technologies aiming at their elimination from these matrices, such as advanced oxidation processes, remain scarce. In this study, different iron complexes (FeCit, FeEDTA, FeEDDS and FeNTA) were evaluated for the degradation of a mixture of these micropollutants (100 µg L−1 each) spiked in municipal wastewater treatment plant (MWWTP) effluent at pH 6.9 by solar photo-Fenton. Operational parameters (iron and H2O2 concentration and Fe/L molar ratio) were optimized for each complex. Degradation efficiencies improved significantly by increasing the concentration of iron complexes (1:1 Fe/L) from 12.5 to 100 µmol L−1 for FeEDDS, FeEDTA and FeNTA. The maximum degradation reached with FeCit for all iron concentrations was limited to 30%. Different Fe/L molar ratios were required to maximize the degradation efficiency for each ligand: 1:1 for FeNTA and FeEDTA, 1:3 for FeEDDS and 1:5 for FeCit. Considering the best Fe/L molar ratios, higher degradation rates were reached using 5.9 mmol L−1 H2O2 for FeNTA and FeEDTA compared to 1.5 and 2.9 mmol L−1 H2O2 for FeEDDS and FeCit, respectively. Acute toxicity to Canton S. strain D. melanogaster flies reduced significantly after treatment for all iron complexes, indicating the formation of low-toxicity by-products. FeNTA was considered the best iron complex source in terms of the kinetic constant (0.10 > 0.063 > 0.051 > 0.036 min−1 for FeCit, FeNTA, FeEDTA and FeEDDS, respectively), organic carbon input and cost-benefit (USD 327 m−3 > USD 20 m−3 > USD 16 m−3 > USD 13 m−3 for FeEDDS, FeCit, FeEDTA and FeNTA, respectively) when compared to the other tested complexes.

Wastewater and soil treatment processes based on Fenton's reagent have gained great attention in recent years due to its high oxidation power. This review describes the fundaments of the Fenton and photo-Fenton processes and discusses the main aspects related to the degradation of organic contaminants in water such as the complexation of iron, the use of solar light as the source of irradiation and the most important reactor types used. An overview of the main applications of the process to a variety of industrial wastewater and soil remediations is presented.

Aquaculture contributes significantly to the sustainable livelihood improvement of a considerable portion of Bangladesh's population. However, fish farmers often encounter the challenge of receiving lower market prices, necessitating the exploration of market choice options to mitigate economic losses. Using cross-sectional data collected from 200 fish farmers, this study applied the multinomial logit (MNL) model to identify the factors influencing fish farmers' decision to select a fish market. Results indicate that the bargaining power of the fish farmers can increase the probability of selling their fish at the upazila and district markets by 44% and 36%, respectively. Conversely, education, age and distance from the market display a negative association with market choices. The findings suggest several interventions to facilitate fish sales through alternative marketing outlets, including financial assistance for fish production, promoting collective marketing, strengthening extension services, and investing in logistics services, particularly improving the dissemination of market information. [ABSTRACT FROM AUTHOR]

Highland areas are more susceptible to climate change impacts. This study investigates the highland communities' climate change perceptions, climatic hazards, and livelihood practices during the COVID-19 pandemic. Using a multi-stage random sampling technique, survey data were gathered from 425 respondents living in highland areas of Panchagarh district, a drought-prone region in Bangladesh. Perception analysis indicates that most respondents (77%) believe their area's climate has significantly changed over the past 10 years. The bivariate and multivariate regression model results reveal that age, education, income, occupation, land ownership, and socioeconomic status substantially impact local community perceptions of climate change and climatic shocks during the COVID-19 pandemic. Besides, land ownership, socioeconomic level, and crop sowing are also important determinants of erratic rainfall that impacts climate change and shocks during COVID-19. This study suggests the local government get involved and enhance the highland community's ability to adapt to climatic shocks. [ABSTRACT FROM AUTHOR]