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A Blockchain AI Solution to Climate Change

Authors: Heston, Thomas F;

A Blockchain AI Solution to Climate Change

Abstract

Background: Climate change represents a critical global challenge, hindered by skepticism towards data manipulation and politicization. Trust in climate data and its policies is essential for effective climate action. Objective: This perspective paper explores the synergistic potential of blockchain technology and artificial intelligence (AI) in addressing climate change and how their integration can enhance the transparency, reliability, and accessibility of climate science. Methods: The paper analyzes the roles of blockchain technology in enhancing transparency, traceability, and efficiency in carbon credit trading, renewable energy certificates, and sustainable supply chain management. It also examines the capabilities of AI in processing complex datasets to distill actionable intelligence. The synergistic effects of integrating both technologies for improved climate action are discussed alongside the challenges faced, such as scalability, energy consumption, and the necessity for high-quality data. Results: Blockchain technology contributes to climate change mitigation by ensuring the transparent and immutable recording of transactions and environmental impacts, fostering stakeholder trust, and democratizing participation in climate initiatives. AI complements blockchain by providing deep insights and actionable intelligence from large datasets, facilitating evidence-based policymaking. The integration of both technologies promises enhanced data management, improved climate models, and more effective climate action initiatives. Conclusion: The integration of blockchain technology and AI offers a transformative approach to climate change mitigation, enhancing the accuracy, transparency, and security of climate data and governance. This synergy addresses current limitations and futureproofs climate strategies, marking a cornerstone for the next generation of environmental stewardship.

Country
United States
Keywords

Large language models (LLMs), Climate change mitigation, Artificial intelligence, Environmental stewardship, Blockchain technology, 330, Climate Change, Data transparency, 333

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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    6
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Top 10%
Green
hybrid