Recent advancements in biomass to bioenergy management and carbon capture through artificial intelligence integrated technologies to achieve carbon neutrality

Sustainable Energy Technologies and Assessments, Journal Year: 2024, Volume and Issue: 73, P. 104123 - 104123

Published: Dec. 7, 2024

Language: Английский

Experimental and artificial intelligence optimization of paint wastewater (PWW) coagulation using novel Phaseolus vulgaris seed extract (PVSE)

Heliyon, Journal Year: 2024, Volume and Issue: 10(14), P. e34229 - e34229

Published: July 1, 2024

This study investigated the application of artificial intelligence algorithms (AIA) in coagulation treatment paint wastewater anchored by novel Phaseolus vulgaris seed extract (PVSE). Untreated discharge harms ecosystem, and therefore harmful industrial effluent, such as wastewater, must be brought to safe levels before being released into environment. In addition AIA, comprehensive characterization tests, kinetics, process optimization were also executed. Characterization results revealed that total solid PWW was above allowable standard, justifying need for effective particle decontamination. The XRD FTIR indicated PVSE structure is amorphous with abundant amine groups. Results analysis variance (ANOVA) obtained from modeling coagulation-flocculation a nonlinear quadratic system (F-value = 45.51) which mostly influenced coagulant dosage 222.48; standardized effect 14.85). Artificial neural network training effectively captured nature ANN (RMSE 0.00040194; R 0.98497), ANFIS 0.003961) algorithms. Regression coefficient highlighted suitability RSM (0.9662), (0.9739), (0.9718) forecasting process, while comparative statistical appraisal authenticated superiority model over models. kinetics experiment, used kinetic model, constant flocculation (Kf-value) all jar test batches strong association between Menkonu (Km) Kf values. Best removal efficiency 97.01 % using coupled genetic algorithm (ANN-GA) at 4 g/L, time 29 min temperature 25.1oC.

Language: Английский

Sizing a System for Treating Effluents from the Mozambique Sugar Cane Company

Sustainability, Journal Year: 2024, Volume and Issue: 16(19), P. 8334 - 8334

Published: Sept. 25, 2024

The sugar industry must be managed in a manner that encourages innovation with regard to the waste generated throughout process. organic load of mill is high, as its potential pollute water bodies at various stages production process, including cooling bearings, mills, cane washing, bagasse and cleaning products. It therefore necessary identify treatment mechanisms not only reduce this but also return purer environment, combining reuse applications. objective study was analyze results physical chemical properties effluents principal technologies employed for remediation industrial wastewater from factories. Mozambique’s mills has high levels dissolved or suspended solids, matter, pressed mud, atmospheric pollutants. BOD/COD ratio low (<2.5), indicating need secondary or, more specifically, biological treatment. This can achieved through humid systems built stabilization ponds, resulting suitable agricultural irrigation. In work, an educational proposal been developed engineering students where they learn calculate optimize, among other parameters, natural compare it conventional

Language: Английский