AIMC Topic: Carbon

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Unveiling the effects of artificial intelligence and green technology convergence on carbon emissions: An explainable machine learning-based approach.

Journal of environmental management Dec 10, 2024
Green technology and artificial intelligence (AI) are playing a positive role in reducing carbon emissions. Technology convergence, as a typical form of technological innovation, can expedite the realization of low-carbon goals through the outcomes o...
Artificial Intelligence China Cities Carbon Machine Learning Technology
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Ensemble intelligence prediction algorithms and land use scenarios to measure carbon emissions of the Yangtze River Delta: A machine learning model based on Long Short-Term Memory.

PloS one Dec 9, 2024
Land use in urban agglomerations is the main source of carbon emissions, and reducing them and improving land use efficiency are the keys to achieving sustainable development goals (SDGs). To advance the literature on densely populated cities and hig...
Sustainable Development China Machine Learning Humans Urbanization Carbon Neural Networks, Computer Cities Algorithms Rivers Environmental Monitoring
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Machine learning prediction of fundamental sewage sludge biochar properties based on sludge characteristics and pyrolysis conditions.

Chemosphere Nov 29, 2024
Sewage sludge biochar (SSBC) has significant potential for resource recovery from sewage sludge (SS) and has been widely studied and applied across various fields. However, the variability in SSBC properties, resulting from the diverse nature of SS a...
Machine Learning Pyrolysis Charcoal Waste Disposal, Fluid Sewage Carbon
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Mapping surface soil organic carbon density of cultivated land using machine learning in Zhengzhou.

Environmental geochemistry and health Nov 28, 2024
Research on soil organic carbon (SOC) is crucial for improving soil carbon sinks and achieving the "double-carbon" goal. This study introduces ten auxiliary variables based on the data from a 2021 land quality survey in Zhengzhou and a multi-objectiv...
Machine Learning Soil China Carbon Environmental Monitoring Carbon Sequestration Support Vector Machine
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Developing novel spectral indices for precise estimation of soil pH and organic carbon with hyperspectral data and machine learning.

Environmental monitoring and assessment Nov 26, 2024
Accurate soil pH and soil organic carbon (SOC) estimations are vital for sustainable agriculture, as pH affects nutrient availability, and SOC is crucial for soil health and fertility. Hyperspectral imaging provides a faster, non-destructive, and eco...
Neural Networks, Computer Soil Agriculture Machine Learning Principal Component Analysis Environmental Monitoring Carbon Hydrogen-Ion Concentration
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Can big data policy drive urban carbon unlocking efficiency? A new approach based on double machine learning.

Journal of environmental management Nov 22, 2024
In recent years, data has increasingly become the "new oil" for 21st-century economic development. However, there is still a gap in how the development of big data promotes the improvement of urban carbon unlocking efficiency (UCUE). Utilizing advanc...
China Big Data Carbon Cities Machine Learning
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High-throughput point-of-care serum iron testing utilizing machine learning-assisted deep eutectic solvent fluorescence detection platform.

Journal of colloid and interface science Nov 17, 2024
In this study, a high-throughput point-of-care testing (HT-POCT) system for detecting serum iron was developed using a hydrophobic deep eutectic solvent (HDES) fluorescence detection platform. This machine learning-assisted portable platform enables ...
Solvents High-Throughput Screening Assays Fluorescent Dyes Hydrophobic and Hydrophilic Interactions Particle Size Quantum Dots Iron Point-of-Care Testing Spectrometry, Fluorescence Fluorescence Carbon Machine Learning Point-of-Care Systems Humans
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Global forecasting of carbon concentration through a deep learning spatiotemporal modeling.

Journal of environmental management Nov 15, 2024
Given the global urgency to mitigate climate change, a key action is the development of effective carbon concentration reduction policies. To this end, an influential factor is the availability of accurate predictions of carbon concentration trends. ...
Neural Networks, Computer Models, Theoretical Carbon Methane Forecasting Deep Learning Carbon Dioxide Climate Change
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Interpretable causal machine learning optimization tool for improving efficiency of internal carbon source-biological denitrification.

Bioresource technology Nov 8, 2024
Interpretable causal machine learning (ICML) was used to predict the performance of denitrification and clarify the relationships between influencing factors and denitrification. Multiple models were examined, and XG-Boost model provided the best pre...
Carbon Nitrogen Machine Learning Sewage Wastewater Denitrification Water Purification Biological Oxygen Demand Analysis
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Predictions of the Optical Properties of Brown Carbon Aerosol by Machine Learning with Typical Chromophores.

Environmental science & technology Nov 7, 2024
The linkages between BrC optical properties and chemical composition remain inadequately understood, with quantified chromophores explaining less than 25% of ambient aerosol light absorption. This study characterized 38 typical chromophores in aeroso...
Polycyclic Aromatic Hydrocarbons Aerosols Machine Learning Carbon
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