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Carbon

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Spatial differentiation of carbon emissions from energy consumption based on machine learning algorithm: A case study during 2015-2020 in Shaanxi, China.

Journal of environmental sciences (China)
Carbon emissions resulting from energy consumption have become a pressing issue for governments worldwide. Accurate estimation of carbon emissions using satellite remote sensing data has become a crucial research problem. Previous studies relied on s...

Thermodynamics and explainable machine learning assist in interpreting biodegradability of dissolved organic matter in sludge anaerobic digestion with thermal hydrolysis.

Bioresource technology
Dissolved organic matter (DOM) is essential in biological treatment, yet its specific roles remain incompletely understood. This study introduces a machine learning (ML) framework to interpret DOM biodegradability in the anaerobic digestion (AD) of s...

Deep learning artificial neural network framework to optimize the adsorption capacity of 3-nitrophenol using carbonaceous material obtained from biomass waste.

Scientific reports
The presence of toxic chemicals in water, including heavy metals like mercury and lead, organic pollutants such as pesticides, and industrial chemicals from runoff and discharges, poses critical public health and environmental risks leading to severe...

Transition from sulfur autotrophic to mixotrophic denitrification: Performance with different carbon sources, microbial community and artificial neural network modeling.

Chemosphere
To address the limitations inherent in both sulfur autotrophic denitrification (SAD) and heterotrophic denitrification (HD) processes, this study introduces a novel approach. Three carbon sources (glucose, methanol, and sodium acetate) were fed into ...

Carbon dot unravels accumulation of triterpenoid in Evolvulus alsinoides hairy roots culture by stimulating growth, redox reactions and ANN machine learning model prediction of metabolic stress response.

Plant physiology and biochemistry : PPB
Evolvulus alsinoides, a therapeutically valuable shrub can provide consistent supply of secondary metabolites (SM) with pharmaceutical significance. Nonetheless, because of its short life cycle, fresh plant material for research and medicinal diagnos...

Leveraging machine learning algorithms in dynamic modeling of urban expansion, surface heat islands, and carbon storage for sustainable environmental management in coastal ecosystems.

Journal of environmental management
Climate change and rapid urbanization are dramatically altering coastal ecosystems worldwide, with significant implications for land surface temperatures (LST) and carbon stock concentration (CSC). This study investigates the impacts of day and night...

AI-based green technology implementation simulation for achieving carbon neutrality: exploring the role of subsidies and knowledge management.

Environmental science and pollution research international
This study investigates the role of green technology implementation (GTI) based on artificial intelligence (AI) at the household level to achieve carbon neutrality by addressing gaps in the existing research. The research focuses on understanding how...

Machine learning constructs the microstructure and mechanical properties that accelerate the development of CFRP pyrolysis for carbon-fiber recycling.

Waste management (New York, N.Y.)
The increasing use of carbon-fiber-reinforced plastic (CFRP) has led to its post-end-of-life recycling becoming a research focus. Herein, we studied the macroscopic and microscopic characteristics of recycled carbon fiber (rCF) during CFRP pyrolysis ...

Leveraging experimental and computational tools for advancing carbon capture adsorbents research.

Environmental science and pollution research international
CO emissions have been steadily increasing and have been a major contributor for climate change compelling nations to take decisive action fast. The average global temperature could reach 1.5 °C by 2035 which could cause a significant impact on the e...

Do China's ecological civilization advance demonstration zones inhibit fisheries' carbon emission intensity? A quasi-natural experiment using double machine learning and spatial difference-in-differences.

Journal of environmental management
China's National Ecological Civilization Demonstration Zone (NECDZ) policy has a significant role in ensuring national ecological security, and it is essential to investigate how the NECDZ policy affects the carbon emissions intensity of fisheries (C...