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Carbon

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Waste-to-energy incineration site selection framework based on heterogeneous fuzzy regret-PROMETHEE model considering life-cycle carbon emissions.

Environmental science and pollution research international
Waste incineration technology has received extensive attention for its advantages of being harmless, reducing, and recycling. However, the waste-to-energy incineration project confronts significant "not-in-my-backyard (NIMBY) concerns," and irrationa...

Toward a comprehensive understanding of alicyclic compounds: Bio-effects perspective and deep learning approach.

The Science of the total environment
The escalating use of alicyclic compounds in modern industrial production has led to a rapid increase of these substances in the environment, posing significant health hazards. Addressing this challenge necessitates a comprehensive understanding of t...

Emerging Directions for Carbon Capture Technologies: A Synergy of High-Throughput Theoretical Calculations and Machine Learning.

Environmental science & technology
As the world grapples with the challenges of energy transition and industrial decarbonization, the development of carbon capture technologies presents a promising solution. The Scalable Modeling, Artificial Intelligence (AI), and Rapid Theoretical ca...

How does the robot adoption promote carbon reduction?: spatial correlation and heterogeneity analysis.

Environmental science and pollution research international
Along with the continuous improvement of industrial intelligence, robots are widely used in various aspects of production and life, playing an essential role in achieving carbon reduction targets. However, the existing research on the carbon reductio...

Application of artificial intelligence in quantifying lung deposition dose of black carbon in people with exposure to ambient combustion particles.

Journal of exposure science & environmental epidemiology
BACKGROUND: Understanding lung deposition dose of black carbon is critical to fully reconcile epidemiological evidence of combustion particles induced health effects and inform the development of air quality metrics concerning black carbon. Macrophag...

Artificial intelligence, industrial structure optimization, and CO emissions.

Environmental science and pollution research international
The carbon-reducing effects of artificial intelligence (AI) will be a critical means of achieving carbon peak and carbon neutrality in China. However, in order to efficiently harness the power of AI, the relationship between AI and carbon reduction n...

Do industrial robots reduce carbon intensity? The role of natural resource rents and corruption control.

Environmental science and pollution research international
Although the research on the impact of robotics on carbon emissions is increasing, there are still relatively few studies on the impact of robots on carbon intensity from the perspective of natural resources and corruption. In order to fill in the re...

Optimization of biogas production from straw wastes by different pretreatments: Progress, challenges, and prospects.

The Science of the total environment
Lignocellulosic biomass (LCB) presents a promising feedstock for carbon management due to enormous potential for achieving carbon neutrality and delivering substantial environmental and economic benefit. Bioenergy derived from LCB accounts for about ...

Deep learning-based fast denoising of Monte Carlo dose calculation in carbon ion radiotherapy.

Medical physics
BACKGROUND: Plan verification is one of the important steps of quality assurance (QA) in carbon ion radiotherapy. Conventional methods of plan verification are based on phantom measurement, which is labor-intensive and time-consuming. Although the pl...

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...