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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
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...

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
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...

Perceptions of GHG emissions and renewable energy sources in Europe, Australia and the USA.

Environmental science and pollution research international
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...

Deep learning-based neural networks for day-ahead power load probability density forecasting.

Environmental science and pollution research international
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...

Measure emissions to manage emissions.

Science (New York, N.Y.)
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...

Operational greenhouse-gas emissions of deep learning in digital pathology: a modelling study.

The Lancet. Digital health
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 ...

Prediction of nitrous oxide emission of a municipal wastewater treatment plant using LSTM-based deep learning models.

Environmental science and pollution research international
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...

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

Environmental pollution (Barking, Essex : 1987)
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...