AIMC Topic: Greenhouse Gases

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Municipal solid waste management for low-carbon transition: A systematic review of artificial neural network applications for trend prediction.

Environmental pollution (Barking, Essex : 1987) Jan 17, 2024
Improper municipal solid waste (MSW) management contributes to greenhouse gas emissions, necessitating emissions reduction strategies such as waste reduction, recycling, and composting to move towards a more sustainable, low-carbon future. Machine le...
Neural Networks, Computer Machine Learning Carbon Refuse Disposal Waste Management Greenhouse Gases Air Pollutants Solid Waste
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Prediction of nitrous oxide emission of a municipal wastewater treatment plant using LSTM-based deep learning models.

Environmental science and pollution research international Dec 6, 2023
Accurate assessment of greenhouse gas emissions from wastewater treatment plants is crucial for mitigating climate change. NO is a potent greenhouse gas that is emitted from wastewater treatment plants during the biological denitrification process. I...
Water Purification Deep Learning Algorithms Greenhouse Gases Nitrous Oxide
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Operational greenhouse-gas emissions of deep learning in digital pathology: a modelling study.

The Lancet. Digital health Nov 22, 2023
BACKGROUND: Deep learning is a promising way to improve health care. Image-processing medical disciplines, such as pathology, are expected to be transformed by deep learning. The first clinically applicable deep-learning diagnostic support tools are ...
Greenhouse Gases Humans Pandemics Deep Learning Carbon Dioxide Neoplasms
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Measure emissions to manage emissions.

Science (New York, N.Y.) Nov 3, 2022
In the 30 years since the world began negotiating the reduction of greenhouse gas (GHG) emissions, no one has identified exactly where all that pollution is coming from. That will begin to change next week when Climate TRACE (Tracking Real-Time Atmos...
Greenhouse Gases Greenhouse Effect Artificial Intelligence Climate Change
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Deep learning-based neural networks for day-ahead power load probability density forecasting.

Environmental science and pollution research international Oct 6, 2022
Energy efficiency is crucial to greenhouse gas (GHG) emission pathways reported by the Intergovernmental Panel on Climate Change. Electrical overload frequently occurs and causes unwanted outages in distribution networks, which reduces energy utiliza...
Forecasting Reproducibility of Results Probability Greenhouse Gases Deep Learning Neural Networks, Computer
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Perceptions of GHG emissions and renewable energy sources in Europe, Australia and the USA.

Environmental science and pollution research international Aug 25, 2021
People's sentiments and perceptions of greenhouse gas emission and renewable energy are important information to understand their reaction to the planned mitigation policy. Therefore, this research analyzes people's perceptions of greenhouse gas emis...
Renewable Energy Humans Sentiment Analysis Europe Wind Greenhouse Gases
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Impact of subclinical mastitis on greenhouse gas emissions intensity and profitability of dairy cows in Norway.

Preventive veterinary medicine Nov 27, 2017
Impaired animal health causes both productivity and profitability losses on dairy farms, resulting in inefficient use of inputs and increase in greenhouse gas (GHG) emissions produced per unit of product (i.e. emissions intensity). Here, we used subc...
Greenhouse Gases Norway Cell Count Asymptomatic Infections Cattle Lactation Dairying Female Models, Theoretical Mastitis, Bovine Animals Milk Feeding Behavior
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Machine learning-based prediction of ambient CO and CH concentrations with high temporal resolution in Seoul metropolitan area.

Environmental pollution (Barking, Essex : 1987) Jul 1, 2025
Machine learning has the potential to support the growing need for high-resolution greenhouse gas monitoring in urban and industrial environments, where deploying extensive sensor networks is often limited by cost and operational challenges. This stu...
Republic of Korea Environmental Monitoring Air Pollutants Machine Learning Carbon Dioxide Air Pollution Greenhouse Gases Methane Seoul
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Emission Factor Recommendation for Life Cycle Assessments with Generative AI.

Environmental science & technology May 13, 2025
Accurately quantifying greenhouse gas (GHG) emissions is crucial for organizations to measure and mitigate their environmental impact. Life cycle assessment (LCA) estimates the environmental impacts throughout a product's entire lifecycle, from raw m...
Greenhouse Gases Artificial Intelligence Algorithms Natural Language Processing Machine Learning
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Resilience actions to counteract the effects of climate change and health emergencies in cities: the role of artificial neural networks.

Annali dell'Istituto superiore di sanita Jan 1, 2019
Both the World Health Organization (WHO) with its 2015 "Climate and Health Country Profile Project" and the Istituto Superiore di Sanità (ISS) with its 2018 "Health and Climate Change", agree on the emergency generated by the climate change and conce...
City Planning Environmental Health Greenhouse Effect Conservation of Natural Resources Greenhouse Gases Arizona Climate Change Emergencies Humans Cities Neural Networks, Computer Environmental Monitoring
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