AIMC Topic: Methane

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Early Detection of Pipeline Natural Gas Leakage from Hyperspectral Imaging by Vegetation Indicators and Deep Neural Networks.

Environmental science & technology Jun 14, 2024
The timely detection of underground natural gas (NG) leaks in pipeline transmission systems presents a promising opportunity for reducing the potential greenhouse gas (GHG) emission. However, existing techniques face notable limitations for prompt de...
Methane Hyperspectral Imaging Natural Gas Neural Networks, Computer Environmental Monitoring
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Prediction of Individual Gas Yields of Supercritical Water Gasification of Lignocellulosic Biomass by Machine Learning Models.

Molecules (Basel, Switzerland) May 16, 2024
Supercritical water gasification (SCWG) of lignocellulosic biomass is a promising pathway for the production of hydrogen. However, SCWG is a complex thermochemical process, the modeling of which is challenging via conventional methodologies. Therefor...
Neural Networks, Computer Biomass Water Support Vector Machine Machine Learning Algorithms Hydrogen Lignin Methane Gases Carbon Dioxide
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Ensemble machine learning prediction of anaerobic co-digestion of manure and thermally pretreated harvest residues.

Bioresource technology May 3, 2024
This study aimed to clarify the statistical accuracy assessment approaches used in recent biogas prediction studies using state-of-the-art ensemble machine learning approach according to 10-fold cross-validation in 100 repetitions. Three thermally pr...
Machine Learning Biomass Support Vector Machine Biofuels Anaerobiosis Manure Methane
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Multitask Deep Learning Enabling a Synergy for Cadmium and Methane Mitigation with Biochar Amendments in Paddy Soils.

Environmental science & technology Dec 12, 2023
Biochar has demonstrated significant promise in addressing heavy metal contamination and methane (CH) emissions in paddy soils; however, achieving a synergy between these two goals is challenging due to various variables, including the characteristic...
Cadmium Methane Oryza Artificial Intelligence Soil Deep Learning Charcoal
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Optimization of biogas production from straw wastes by different pretreatments: Progress, challenges, and prospects.

The Science of the total environment Sep 17, 2023
Lignocellulosic biomass (LCB) presents a promising feedstock for carbon management due to enormous potential for achieving carbon neutrality and delivering substantial environmental and economic benefit. Bioenergy derived from LCB accounts for about ...
Bioreactors Biofuels Anaerobiosis Methane Biomass Artificial Intelligence Carbon
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Enhancing corn stalk-based anaerobic digestion with different types of zero-valent iron added during the acidification stage: Performance and mechanism.

Journal of environmental sciences (China) Aug 5, 2023
Anaerobic digestion has been defined as a competitive approach to facilitate the recycling of corn stalks. However, few studies have focused on the role of direct interspecies electron transfer (DIET) pathway in the acidification stage under the addi...
Fatty Acids, Volatile Zea mays Anaerobiosis Methane Iron Bioreactors
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Applications of artificial intelligence in anaerobic co-digestion: Recent advances and prospects.

Bioresource technology Dec 17, 2022
Anaerobic co-digestion (AcoD) offers several merits such as better digestibility and process stability while enhancing methane yield due to synergistic effects. Operation of an efficient AcoD system, however, requires full comprehension of important ...
Digestion Biofuels Methane Artificial Intelligence Bioreactors Anaerobiosis
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Adaptively Optimized Gas Analysis Model with Deep Learning for Near-Infrared Methane Sensors.

Analytical chemistry Jan 18, 2022
Noise significantly limits the accuracy and stability of retrieving gas concentration with the traditional direct absorption spectroscopy (DAS). Here, we developed an adaptively optimized gas analysis model (AOGAM) composed of a neural sequence filte...
Algorithms Deep Learning Principal Component Analysis Methane
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Prediction of biogas production in anaerobic co-digestion of organic wastes using deep learning models.

Water research Sep 24, 2021
Interest in anaerobic co-digestion (AcoD) has increased significantly in recent decades owing to enhanced biogas productivity due to the utilization of different organic wastes, such as food waste and sewage sludge. In this study, a robust AcoD model...
Bioreactors Deep Learning Food Sewage Digestion Anaerobiosis Refuse Disposal Methane Biofuels
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Predicting the performance of anaerobic digestion using machine learning algorithms and genomic data.

Water research Apr 22, 2021
Modeling of anaerobic digestion (AD) is crucial to better understand the process dynamics and to improve the digester performance. This is an essential yet difficult task due to the complex and unknown interactions within the system. The application ...
Methane Machine Learning Algorithms Genomics Anaerobiosis
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