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Carbon

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A fuzzy robust optimization model for dual objective forward and reverse logistics networks considering carbon emissions.

PloS one
The inherent unpredictability within the low-carbon integrated supply chain logistics network complicates its management. This paper endeavours to address the challenge of designing a low-carbon logistics network within a context of uncertainty and w...

Machine Learning-Assisted Biomass-Derived Carbon Dots as Fluorescent Sensor Array for Discrimination of Warfarin and Its Metabolites.

Langmuir : the ACS journal of surfaces and colloids
Warfarin (WAR), an effective oral anticoagulant, is of utmost importance in treating many diseases. Despite its significance, rapid and precise discrimination of WAR remains a formidable challenge, especially facing its structural analogs of metaboli...

Exploring spatio-temporal heterogeneity of rural settlement patterns on carbon emission across more than 2800 Chinese counties using multiple supervised machine learning models.

Journal of environmental management
China, the world's largest carbon emitter, plays a pivotal role in achieving carbon neutrality. This study systematically analyzes the impact of landscape indices on carbon emissions from rural settlements across more than 2800 counties using eight s...

Optimization of carbon footprint management model of electric power enterprises based on artificial intelligence.

PloS one
This study intends to optimize the carbon footprint management model of power enterprises through artificial intelligence (AI) technology to help the scientific formulation of carbon emission reduction strategies. Firstly, a carbon footprint calculat...

Dissolved organic carbon estimation in lakes: Improving machine learning with data augmentation on fusion of multi-sensor remote sensing observations.

Water research
This paper presents a novel approach for estimating Dissolved Organic Carbon (DOC) concentrations in lakes considering both carbon sources and sink operators. Despite the critical role of DOC, the combined application of machine learning, as a robust...

Driving factors of TOC concentrations in four different types of estuaries (canal, urban, agricultural, and natural estuaries) identified by machine learning technique.

Marine pollution bulletin
Mangroves are among the most significant organic carbon sinks on Earth. However, the drivers of mangrove carbon remain poorly understood due to the lack of data on organic carbon across different types of estuaries. In this study, boosted regression ...

Machine learning-assisted prediction and identification of key factors affecting nitrogen metabolism for aerobic granular sludge.

Environmental research
To achieve higher denitrification efficiency with reduced energy consumption in aerobic granular sludge (AGS) system, a systematic evaluation of the carbon and nitrogen metabolism process for AGS under different stage is essential. Herein, this study...

Carbon source dosage intelligent determination using a multi-feature sensitive back propagation neural network model.

Journal of environmental management
The carbon reduction concept drives the development of low-carbon and sustainable wastewater treatment plant (WWTP) operation technologies. In the denitrification stage of WWTPs in China, there are widespread problems of uneconomical dosage consumpti...

Machine learning-assisted prediction of engineered carbon systems' capacity to treat textile dyeing wastewater via adsorption technology.

Environmental monitoring and assessment
Dyes are widely used in industries like printing, cosmetics, paper, leather processing, textiles, and manufacturing to add color to products. However, improper disposal of dyes into wastewater has raised major concerns due to their harmful effects on...

Forecasting deforestation and carbon loss across New Guinea using machine learning and cellular automata.

The Science of the total environment
The island of New Guinea harbors some of the world's most biologically diverse and highly endemic tropical ecosystems. Nevertheless, progressing land-use change in the region threatens their integrity, which will adversely affect their biodiversity a...