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Blockchain-Powered NFTs: A Paradigm Shift in Carbon Credit Transactions for Traceability, Transparency, and Accountability

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Information Systems (EMCIS 2023)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 501))

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Abstract

The adoption of carbon credit systems has emerged as a pivotal strategy in addressing climate change and promoting sustainable environmental practices. This research paper delves into the multifaceted landscape of carbon credit systems, specifically focusing on the challenges inherent in their design and implementation. We investigate the innovative use of Non-Fungible Tokens (NFTs) as a transformative approach to carbon credits, exploring the intricacies of NFT structures tailored for carbon credit trading. Furthermore, the paper presents a comprehensive examination of the system architecture underpinning a blockchain-enabled NFT trading platform for carbon credits. The architectural framework’s design and components are meticulously scrutinized to ensure transparency, security, and efficiency in the trading ecosystem. The research also dissects the intricate functionalities that empower the blockchain-NFT trading system, facilitating seamless transactions and traceability. A pivotal facet of this study is a compelling case study spotlighting the application of a Blockchain-NFT trading system for Agricultural Carbon Credits within a rural farming community. The case study highlights the tangible benefits reaped by farmers through the innovative system, shedding light on how the technology incentivizes sustainable farming practices and offers an additional revenue stream.

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Correspondence to Piyush Maheshwari .

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Khanna, A., Maheshwari, P. (2024). Blockchain-Powered NFTs: A Paradigm Shift in Carbon Credit Transactions for Traceability, Transparency, and Accountability. In: Papadaki, M., Themistocleous, M., Al Marri, K., Al Zarouni, M. (eds) Information Systems. EMCIS 2023. Lecture Notes in Business Information Processing, vol 501. Springer, Cham. https://doi.org/10.1007/978-3-031-56478-9_6

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  • DOI: https://doi.org/10.1007/978-3-031-56478-9_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-56477-2

  • Online ISBN: 978-3-031-56478-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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