Artificial Intelligence in Climate Change Mitigation: A Review of Predictive Modeling and Data-Driven Solutions for Reducing Greenhouse Gas Emissions
1 D&I Geosolutions, Schlumberger Oilfield Services, Port Harcourt, Nigeria.
2 Electrical and Computer Engineering, Southern Illinois University Edwardsville, USA.
3 Information Science, Ball State University, Muncie Indiana.
4 Mathematics, University of North Dakota, USA.
5 Project Management, Saint Louis University, Missouri, USA.
Review Article
World Journal of Advanced Research and Reviews, 2024, 24(01), 408–414
Publication history:
Received on 25 August 2024; revised on 02 October 2024; accepted on 04 October 2024
Abstract:
Artificial Intelligence (AI) is increasingly recognized as a powerful tool for addressing the challenges of climate change. Its ability to process vast amounts of data and generate advanced predictive models positions AI as a key player in efforts to reduce greenhouse gas (GHG) emissions and develop sustainable solutions. This review delves into the multifaceted role of AI in climate change mitigation, highlighting its potential in several critical areas. Firstly, AI is revolutionizing predictive climate modeling by providing more accurate forecasts and simulations, enabling better-informed policy and decision-making. Secondly, it is optimizing energy systems through smart grid management, demand forecasting, and the integration of renewable energy sources, thereby enhancing energy efficiency and reducing reliance on fossil fuels. Furthermore, AI is advancing carbon capture and storage technologies by improving the identification of optimal sites and enhancing process efficiency. In environmental monitoring, AI-driven solutions are enabling real-time detection and analysis of environmental data, contributing to more effective conservation efforts. This review also presents case studies and data that demonstrate the tangible impact of AI applications in driving progress towards global emission reduction targets. However, the adoption of AI in this domain is not without challenges. Issues such as data privacy, algorithmic transparency, and the ethical implications of AI deployment need to be carefully addressed. The paper concludes by outlining future research directions and emphasizing the need for interdisciplinary collaboration to fully harness the potential of AI in combating climate change.
Keywords:
Artificial Intelligence; Greenhouse gas (GHG) emissions; Environmental Sustainability; Global Emission Reduction; and Renewable Energy
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0