AIMC Topic: Carbon

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Optimizing carbon source addition to control surplus sludge yield via machine learning-based interpretable ensemble model.

Environmental research
Appropriate carbon source addition can save operational costs and reduce surplus sludge yield in the wastewater treatment plant (WWTP). However, the link between carbon source and surplus sludge yield remains neglected although machine learning (ML) ...

Technological innovations fuel carbon prices and transform environmental management across Europe.

Journal of environmental management
This study investigates the impact of recent Artificial Intelligence (AI)-driven technological innovations on carbon prices across different quantiles, assessing the influence of AI stock prices on energy prices based on European carbon allowances wh...

Public health perspectives on green efficiency through smart cities, artificial intelligence for healthcare and low carbon building materials.

Frontiers in public health
INTRODUCTION: Smart cities, artificial intelligence (AI) in healthcare, and low-carbon building materials are pivotal to public health, environmental sustainability, and green efficiency. Despite their critical importance, understanding public percep...

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

Journal of environmental management
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...

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
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...

Machine learning prediction of fundamental sewage sludge biochar properties based on sludge characteristics and pyrolysis conditions.

Chemosphere
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...

Mapping surface soil organic carbon density of cultivated land using machine learning in Zhengzhou.

Environmental geochemistry and health
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...

Developing novel spectral indices for precise estimation of soil pH and organic carbon with hyperspectral data and machine learning.

Environmental monitoring and assessment
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...

Can big data policy drive urban carbon unlocking efficiency? A new approach based on double machine learning.

Journal of environmental management
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...

High-throughput point-of-care serum iron testing utilizing machine learning-assisted deep eutectic solvent fluorescence detection platform.

Journal of colloid and interface science
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 ...