Environmental monitoring and assessment
Jan 9, 2026
Atmospheric methane (CH), a potent greenhouse gas, has shown a consistent rise since the Industrial Revolution, contributing significantly to global warming and climate change. Understanding the temporal and spatial variability of methane concentrati...
Riverine and lake ecosystems are sources of global non-CO greenhouse gases (GHGs) and serve as sinks for pollutants, facing the dual challenges of mitigating GHG emissions and controlling water pollution. However, interactions between pollutant input...
Halonitromethanes (HNMs) were high-toxicity nitrogenous disinfection byproducts generated by amino acids (AAs) during UV/monochloramine (UV/NHCl) disinfection in bromide-containing water. HNM concentrations fell over time, highlighting disinfection t...
The essential need to identify the most informative sources of greenhouse gas emissions (climate change drivers) impacting the food security nexus in Africa requires a comprehensive and holistic approach. Machine learning method excels in the identif...
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 investigated the impact of alkaline pretreatment on the biomethane yield of Xyris capensis experimentally and computationally using machine-learning (ML)-based techniques. Despite extensive studies on the anaerobic digestion of lignocellul...
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...
Microbial sequencing data were rarely integrated into the prediction of methane production using machine learning (ML) models because of high dimensionality and the lack of a systematic way to evaluate the change of insight gained from modelling with...
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...
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