Artificial intelligence-based solutions for climate change: a review

Environmental Chemistry Letters, Journal Year: 2023, Volume and Issue: 21(5), P. 2525 - 2557

Published: June 13, 2023

Abstract Climate change is a major threat already causing system damage to urban and natural systems, inducing global economic losses of over $500 billion. These issues may be partly solved by artificial intelligence because integrates internet resources make prompt suggestions based on accurate climate predictions. Here we review recent research applications in mitigating the adverse effects change, with focus energy efficiency, carbon sequestration storage, weather renewable forecasting, grid management, building design, transportation, precision agriculture, industrial processes, reducing deforestation, resilient cities. We found that enhancing efficiency can significantly contribute impact change. Smart manufacturing reduce consumption, waste, emissions 30–50% and, particular, consumption buildings 30–50%. About 70% gas industry utilizes technologies enhance accuracy reliability forecasts. Combining smart grids optimize power thereby electricity bills 10–20%. Intelligent transportation systems dioxide approximately 60%. Moreover, management design cities through application further promote sustainability.

Language: Английский

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Recent advances in CCUS: A critical review on technologies, regulatory aspects and economics

Geoenergy Science and Engineering, Journal Year: 2024, Volume and Issue: 238, P. 212726 - 212726

Published: April 21, 2024

Language: Английский

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Carbon capture, utilization and sequestration systems design and operation optimization: Assessment and perspectives of artificial intelligence opportunities

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 917, P. 170085 - 170085

Published: Jan. 15, 2024

Language: Английский

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A novel carbon dioxide capture technology (CCT) based on non-equilibrium condensation characteristics: Numerical modelling, nozzle design and structure optimization

Energy, Journal Year: 2023, Volume and Issue: 286, P. 129603 - 129603

Published: Nov. 9, 2023

Language: Английский

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Carbon Capture Materials in Post-Combustion: Adsorption and Absorption-Based Processes

C – Journal of Carbon Research, Journal Year: 2023, Volume and Issue: 9(1), P. 17 - 17

Published: Jan. 29, 2023

Global warming and climate changes are among the biggest modern-day environmental problems, main factor causing these problems is greenhouse gas effect. The increased concentration of carbon dioxide in atmosphere resulted capturing amounts reflected sunlight, serious acute chronic problems. reached 421 ppm 2022 as compared to 280 1800s, this increase attributed emissions from industrial revolution. release into can be minimized by practicing capture utilization storage methods. Carbon (CCUS) has four major methods, namely, pre-combustion, post-combustion, oxyfuel combustion, direct air capture. It been reported that applying CCUS up 95% produced running power plants. However, a cost penalty efficiency decrease hinder wide applicability CCUS. Advancements CCSU were made increasing decreasing sorbents. In review, we highlight recent developments utilizing both physical chemical sorbents carbon. This includes amine-based sorbents, blended absorbents, ionic liquids, metal-organic framework (MOF) adsorbents, zeolites, mesoporous silica materials, alkali-metal carbonaceous metal oxide/metal oxide-based materials. addition, comparison between recently proposed kinetic thermodynamic models was also introduced. concluded published studies considered assuperior carbon-capturing which their high stability, multifunctionality, rapid capture, ability achieve large sorption capacities. more work must done reduce it regarded drawback.

Language: Английский

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Simulating the CCUS technology diffusion in thermal power plants: An agent-based evolutionary game model in complex networks

Journal of Cleaner Production, Journal Year: 2023, Volume and Issue: 421, P. 138515 - 138515

Published: Aug. 19, 2023

Language: Английский

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An overview of pure hydrogen production via electrolysis and hydrolysis

International Journal of Hydrogen Energy, Journal Year: 2024, Volume and Issue: 84, P. 521 - 538

Published: Aug. 22, 2024

Language: Английский

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Models for Decarbonization in the Chemical Industry

Annual Review of Chemical and Biomolecular Engineering, Journal Year: 2024, Volume and Issue: 15(1), P. 139 - 161

Published: Jan. 25, 2024

Various technologies and strategies have been proposed to decarbonize the chemical industry. Assessing decarbonization, environmental, economic implications of these is critical identifying pathways a more sustainable industrial future. This study reviews recent advancements integration systems analysis models, including process analysis, material flow life cycle assessment, techno-economic machine learning. These models are categorized based on analytical methods application scales (i.e., micro-, meso-, macroscale) for promising decarbonization (e.g., carbon capture, storage, utilization, biomass feedstock, electrification) circular economy strategies. Incorporating forward-looking, data-driven approaches into existing allows optimizing complex assessing future impacts. Although advances in ecology–, economic-, planetary boundary–based modeling support holistic systems-level efforts needed consider impacts ecosystems. Effective applications advanced, integrated require cross-disciplinary collaborations across engineering, ecology, economics.

Language: Английский

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Advanced Modeling and Optimization Strategies for Process Synthesis

Annual Review of Chemical and Biomolecular Engineering, Journal Year: 2024, Volume and Issue: 15(1), P. 81 - 103

Published: April 10, 2024

This article provides a systematic review of recent progress in optimization-based process synthesis. First, we discuss multiscale modeling frameworks featuring targeting approaches, phenomena-based modeling, unit operation-based and hybrid modeling. Next, present the expanded scope synthesis objectives, highlighting considerations sustainability operability to assure cost-competitive production an increasingly dynamic market with growing environmental awareness. Then, advances optimization algorithms tools, including emerging machine learning-and quantum computing-assisted approaches. We conclude by summarizing perspectives for strategies.

Language: Английский

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Stochastic bandgap optimization for multiscale elastic metamaterials with manufacturing imperfections

International Journal of Mechanical Sciences, Journal Year: 2024, Volume and Issue: 268, P. 109035 - 109035

Published: Jan. 11, 2024

Bandgaps are endowed to elastic metamaterials (EMMs) attributed the rationally designed unit cells and extensive works devoted bandgap enlargement for improving applicability of EMMs in multi-disciplinary applications. Nonetheless, most existing optimization frameworks neglect manufacturing imperfections, such as microscale heterogeneity system uncertainties, which can significantly affect behaviours. Without properly accounting these effects, design may fail achieve optimal goal, exhibiting consistently ultra-wide wave attenuation bands practical EMMs. Herein, this paper, a stochastic framework is developed involving aiming at optimizing first two statistical moments normalized bandwidth (NB) simultaneously. To alleviate large computational costs approximating moments, surrogate model employed reveal constitutive relationship between parameters NB multiscale EMM. Moreover, solve problem effectively efficiently, high-order mutation strategy proposed develop an improved particle swarm (PSO) variant, namely adaptively mutation-based PSO (AHMPSO). demonstrate viability efficiency framework, numerical investigation implemented on 3D EMM, highlights enlarged bandwidths coupling with improvement robustness optimum.

Language: Английский

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