• Energy Research

Integrating thermochemical–biochemical methods overcomes the single-path limits for bioenergy production. This synergy lowers costs and enhances energy sustainability, highlighting waste-to-energy's vital role in the circular economy transition.

AbstractA major environmental problem on a global scale is the contamination of water by dyes, particularly from industrial effluents. Consequently, wastewater treatment from various industrial wastes is crucial to restoring environmental quality. Dye is an important class of organic pollutants that are considered harmful to both people and aquatic habitats. The textile industry has become more interested in agricultural-based adsorbents, particularly in adsorption. The biosorption of Methylene blue (MB) dye from aqueous solutions by the wheat straw (T. aestivum) biomass was evaluated in this study. The biosorption process parameters were optimized using the response surface methodology (RSM) approach with a face-centred central composite design (FCCCD). Using a 10 mg/L concentration MB dye, 1.5 mg of biomass, an initial pH of 6, and a contact time of 60 min at 25 °C, the maximum MB dye removal percentages (96%) were obtained. Artificial neural network (ANN) modelling techniques are also employed to stimulate and validate the process, and their efficacy and ability to predict the reaction (removal efficiency) were assessed. The existence of functional groups, which are important binding sites involved in the process of MB biosorption, was demonstrated using Fourier Transform Infrared Spectroscopy (FTIR) spectra. Moreover, a scan electron microscope (SEM) revealed that fresh, shiny particles had been absorbed on the surface of the T. aestivum following the biosorption procedure. The bio-removal of MB from wastewater effluents has been demonstrated to be possible using T. aestivum biomass as a biosorbent. It is also a promising biosorbent that is economical, environmentally friendly, biodegradable, and cost-effective.

The presence of dye pollutants in industrial wastewater poses significant environmental and health risks, necessitating effective treatment methods. The optimal adsorption treatment of methylene blue (MB) and crystal violet (CV) dye-simulated wastewater utilising Saccharum officinarum L presents a key challenge in the selection of appropriate modelling approaches. While RSM and ANN models are frequently used, there is a noticeable knowledge gap when it comes to evaluating their relative strengths and weaknesses in this context. The study compared the predictive abilities of response surface methodology (RSM) and artificial neural network (ANN) for the adsorption treatment of MB and CV dye-simulated wastewater using Saccharum officinarum L. The process experimental variables were modelled and predicted using a three-layer artificial neural network trained using the Levenberg-Marquard backpropagation algorithm and 30 central composite designs (CCD). The adsorption study used a specific mechanism, which led to noteworthy maximum removals of 98.3% and 98.2% for dyes (MB and CV), respectively. The RSM model achieved an impressive R2 of 0.9417, while the ANN model achieved 0.9236 in MB. Adsorption is commonly used to remove colour from many different materials. Saccharum officinarum L., a byproduct of sugarcane processing, has shown potential as an efficient and ecological adsorbent in this environment. The purpose of this study is to evaluate sugarcane bagasse's potential as an adsorbent for the removal of dyes MB and CV from industrial wastewater, providing a long-term strategy for reducing dye pollution. Due to its beneficial economic and environmental characteristics, the Saccharum officinarum L. adsorbent has prompted research into sustainable resources with low pollutant indices.

AbstractThe iron impregnated fungal bio-filter (IIFB) discs of luffa sponge containing Phanerochaete chrysosporium mycelia have been used for the removal of As(III) from water. Two different forms of same biomass viz. free fungal biomass (FFB) and modified free fungal biomass (chemically modified and iron impregnated; CFB and IIFB) have been simultaneously investigated to compare the performance of immobilization, chemo-tailoring and iron impregnation for remediation of As(III). IIFB showed highest uptake capacity and percentage removal of As(III), 1.32 mg/g and 92.4% respectively among FFB, CFB and IIFB. Further, the application of RSM and ANN-GA based mathematical model showed a substantial increase in removal i.e. 99.2% of As(III) was filtered out from water at optimised conditions i.e. biomass dose 0.72 g/L, pH 7.31, temperature 42 °C, and initial As(III) concentration 1.1 mg/L. Isotherm, kinetic and thermodynamic studies proved that the process followed monolayer sorption pattern in spontaneous and endothermic way through pseudo-second order kinetic pathway. Continuous mode of As(III) removal in IIFB packed bed bioreactor, revealed increased removal of As(III) from 76.40 to 88.23% with increased column height from 5 to 25 cm whereas the removal decreased from 88.23 to 69.45% while increasing flow rate from 1.66 to 8.30 mL/min. Moreover, the IIFB discs was regenerated by using 10% NaOH as eluting agent and evaluated for As(III) removal for four sorption–desorption cycles, showing slight decrease of their efficiency by 1–2%. SEM–EDX, pHzpc, and FTIR analysis, revealed the involvement of hydroxyl and amino surface groups following a non-electrostatic legend exchange sorption mechanism during removal of As(III).