Persistent organic pollutants (POPs) are harmful chemicals that resist degradation and remain in the environment for a long time. These pollutants originate from various sources, such as industrial, agricultural, and waste disposal. They contaminate ...
Addition of abiotic and biotic factors as single or combined in anaerobic digestion (AD) improves the substrate hydrolysis, microbial nexus, and enzymatic activity. The effect of a single abiotic (salinity, micronutrients, and conductive material) or...
This study presents a comprehensive approach for optimizing biochar-augmented anaerobic digestion (AD) system through an interpretable stacking ensemble deep learning model. Extensive experimental data were compiled, incorporating feedstock character...
This study aimed to optimize biogas and methane production from Up-flow anaerobic sludge blanket reactors for treating domestic wastewater using advanced machine learning models-namely, eXtreme Gradient Boosting (XGBoost) and its hybridized form, XGB...
This study presents a novel multi-disciplinary approach, integrating explainable machine-learning with detailed chemical and biological analysis using microbial fermentation food wastewater to identify critical parameters influencing AD microbiome di...
As energy consumption and waste generation from human activities continue to rise, the technology of anaerobic digestion (AD), which converts waste into bioenergy, has gained popularity. Biogas produced from AD commonly contains 60 % CH, 40 % CO and ...
This study investigates early warning indicators for process instabilities in anaerobic digestion caused by shock-loadings in biogas plants, focussing on gas-phase parameters to avoid substrate analyses. With the increasing use of renewable energy so...
Nonlinear autoregressive exogenous (NARX) neural network models were used to forecast the time-series profiles of anaerobic digestion-elutriated phase treatment (ADEPT). Experimental data from the operation of the pilot plant and lab-scale reactor we...
This study explores the application of various machine learning (ML) models for the real-time prediction of the FOS/TAC ratio in microbial electrolysis cell anaerobic digestion (MEC-AD) systems using data collected during a 160-day trial treating bre...
Microplastics (MPs) present significant challenges for anaerobic digestion (AD) processes used in energy recovery from contaminated organic waste. Given that optimal AD conditions vary widely across studies when MPs are present, a robust predictive m...
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