Anaerobic membrane bioreactor (AnMBR) with external ultrafiltration membrane for the treatment of sugar beet vinasse.

Vinasse, a by-product of ethanol production, is generated at significant rates. While rich in nutrients such as calcium, magnesium, and potassium, its high solids, organic matter, acidity, and sulfate content pose challenges when disposed directly on soil, necessitating treatment. Anaerobic digestion is a viable solution, reducing organic pollution while recovering energy in the form of biogas, aligning with the biorefinery concept.

Treatment of sugarcane vinasse in AnMBR and UASB: process performance and microbial community comparison.

Vinasse is a by-product of sugarcane processing which is often used in fertigation; however, the direct use of vinasse harms the environment and reduces soil productivity due to its physicochemical properties. Anaerobic digestion (AD) offers an alternative to mitigate part of the negative effects. Anaerobic high-rate reactors, which mainly rely on sludge granulation, are mostly used in AD of vinasse wastewater.

Mesophilic versus thermophilic digestion of sludge in anaerobic membrane bioreactors.

Energy-efficient wastewater treatment plants (WWTPs) utilize systems like high-rate activated sludge (A-stage) system to redirect organics from wastewater are redirected into energy-rich sludge (A-sludge). Anaerobic membrane bioreactors (AnMBRs) offer lower footprint and higher effluent quality compared to conventional digesters. In this study, the biological treatment and the filtration performances of AnMBRs for A-sludge digestion under mesophilic and thermophilic conditions were comparatively evaluated through lab-scale experiments, mass balancing and dynamic modeling.

Forecasting nitrous oxide emissions from a full-scale wastewater treatment plant using LSTM-based deep learning models.

Nitrous oxide (NO) emissions from wastewater treatment plants (WWTPs) exhibit significant seasonal variability, making accurate predictions with conventional biokinetic models difficult due to complex and poorly understood biochemical processes. This study addresses these challenges by exploring data-driven alternatives, using long short-term memory (LSTM) based encoder-decoder models as basis. The models were developed for future integration into a model predictive control framework, aiming to reduce NO emissions by forecasting these over varying prediction horizons.

Leveraging organic acids in bipolar membrane electrodialysis (BPMED) can enhance ammonia recovery from scrubber effluents.

While air stripping combined with acid scrubbing remains a competitive technology for the removal and recovery of ammonia from wastewater streams, its use of strong acids is concerning. Organic acids offer promising alternatives to strong acids like sulphuric acid, but their application remains limited due to high cost. This study proposes an integration of air stripping and organic acid scrubbing with bipolar membrane electrodialysis (BPMED) to regenerate the organic acids.