In-depth Analysis of Artificial Intelligence for Climate Change Mitigation

  1. Liyu Lu

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Abstract

Due to the major impact of climate change on the world's environment, political and economic systems, climate change mitigation has become a pressing priority for the international community and requires rapid action from the whole society. With the continuous advancement of artificial intelligence research, the integration of AI and other technologies makes it more and more used in the whole society. It has become a promising and innovative avenue in the field of climate change mitigation. This paper comprehensively considers the key role of AI technology in the field of climate change mitigation, such as climate modeling, the optimization of renewable energy systems, the development of intelligent solutions for sustainable practices and CSS technology, and affirms its future prospects. It also describes the challenges of AI in the field of climate change mitigation. As researchers, policymakers, and industries collaborate to refine AI methodologies and integrate them into practical applications, a concerted effort is required to establish ethical guidelines, transparency standards, and inclusive governance frameworks.

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  1. PREreview

    This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/14712742.

    Review by Mehdi Zoghaib of: "In-depth Analysis of Artificial Intelligence for Climate Change Mitigation"

    Liu, Lucy, (2025). In-depth Analysis of Artificial Intelligence for Climate Change Mitigation, Preprint

    Key words: AI, Climate Change, Renewable energy systerm

    Abstract:

    This paper explores how artificial intelligence (AI) contributes to mitigating climate change by enhancing climate modeling, optimizing renewable energy systems, promoting sustainable practices, and supporting carbon capture and storage (CCS) technologies. It also discusses challenges related to AI adoption, including ethical concerns, data quality, and transparency.

    1. AI's Role in Climate Change Mitigation

    Climate Modeling: AI helps improve climate models by analyzing vast datasets, making predictions more accurate and useful for policy decisions.

    Renewable Energy Optimization: AI-driven smart grids enhance energy distribution, balance supply and demand, and improve renewable energy integration.

    Agriculture: AI aids in precision agriculture by optimizing irrigation, reducing pesticide use, and increasing crop yields while minimizing environmental impact.

    Carbon Capture and Storage (CCS): AI helps identify ideal carbon capture sites and optimizes CCS operations to reduce carbon emissions.

    2. Evolution of AI Methods in Climate Mitigation

    Traditional AI:

    Rule-based systems and symbolic AI relied on predefined rules but lacked adaptability.

    Expert systems emulated human decision-making but struggled with complex environments.

    Recent AI Advances

    Machine Learning & Deep Learning: AI now learns from large datasets to identify patterns and make accurate predictions.

    Transfer Learning: Pre-trained AI models improve climate research by leveraging knowledge from related domains.

    3. Challenges in Applying AI to Climate Change

    Data Quality & Availability: Climate models require large, high-quality datasets, which may not always be accessible or accurate.

    Transparency & Interpretability:

    AI decisions need to be explainable to ensure trust among policymakers and stakeholders.

    Ethical Considerations: AI should be designed to avoid biases and ensure equitable distribution of benefits.

    4. Future Prospects & Recommendations

    Transparent AI policies and frameworks are necessary to guide responsible AI use in climate action. Interdisciplinary Collaboration Governments, industries, and researchers must work together to integrate AI effectively into climate strategies.

    Scaling AI Solutions: Future advancements should focus on making AI-driven climate solutions more accessible and impactful globally.

    Conclusion

    AI has significant potential to aid in climate change mitigation by improving climate predictions, optimizing renewable energy use, and promoting sustainability. However, challenges related to data, ethics, and transparency must be addressed through interdisciplinary collaboration and governance frameworks. This paper emphasizes that AI is not a standalone solution but a powerful tool that, when used responsibly, can drive significant progress in the fight against climate change.

    Competing interests

    The author declares that they have no competing interests.

  2. Version published to 10.20944/preprints202402.0022.v1