[Paper Review] Information and communications technologies for carbon sinks from economics and engineering perspectives
The paper analyzes ICT applications in carbon sink projects from economic and engineering viewpoints, showing blockchain improves trading speed by 40% and AI reduces operating costs by 15%, and discusses future integration and challenges.
Climate change has intensified the urgency of effective carbon sink solutions, yet the integration of Information and Communications Technologies (ICT) in these systems remains fragmented despite its transformative potential. This paper provides a comprehensive analysis of ICT applications in carbon sink projects from both economic and engineering perspectives, a dual lens approach rarely explored in the existing literature. In carbon trading, blockchain has improved transaction speed by 40%, while AI-based optimizations have reduced operational costs by 15% in projects such as Petra Nova.Through systematic examination, we identify three key findings: (1) ICT transforms carbon economics through digital financing platforms and blockchain-based trading systems, with AI enhancing price prediction, though data interoperability remains challenging; (2) digital technologies advance both natural and artificial sequestration from forest monitoring to Carbon Capture, Use and Storage (CCUS) optimization, yet lack integrated real-time control solutions; (3) realizing ICT's full potential requires addressing its environmental costs, strengthening policy support, and fostering interdisciplinary collaboration. By bridging the economic engineering divide and mapping current applications alongside future opportunities, this paper demonstrates that deeper integration of digital technologies is essential to scale carbon sink solutions to meet climate targets.
Motivation & Objective
- Introduce the operational and engineering foundations of carbon sink projects to help readers grasp the core framework.
- Analyze how ICT integrates into the economic operations of carbon sinks, including financing, trading, and forecasting.
- Examine ICT’s role in engineering implementation of natural and artificial sequestration and identify technical bottlenecks.
- Highlight environmental costs, policy needs, and interdisciplinary collaboration to realize ICT’s full potential.
Proposed method
- Review and synthesize current ICT applications in carbon sink economics and engineering.
- Examine blockchain-based trading, digital financing, and AI-based forecasting with empirical and theoretical references.
- Compare traditional Browser/Server architectures to decentralized blockchain setups for carbon trading.
- Assess forecasting models for carbon prices and market signals, including hybrid and deep learning approaches.
- Identify gaps, challenges, and future directions for standardization, interoperability, and environmental impact.
Experimental results
Research questions
- RQ1How are ICTs currently used in the economic operations (financing, trading, forecasting) of carbon sink projects?
- RQ2What are the engineering applications and bottlenecks of ICT in natural and artificial sequestration (forest monitoring, CCUS, other)?
- RQ3What environmental, policy, and interdisciplinary factors influence the effective, scalable integration of ICT in carbon sinks?
Key findings
- Blockchain-based trading can increase transaction speed by about 40% and reduce costs by about 15% in carbon markets.
- AI-based forecasting models improve predictive accuracy for carbon prices, with examples showing reduced RMSE and MAPE in specific studies.
- ICT enhances market transparency, automation via smart contracts, and cross-platform interoperability, though data interoperability remains a challenge.
- Digital financing platforms and tokenized assets (e.g., NFTs) contribute to more efficient carbon finance and potential interoperability across registries.
- Integrated ICT applications in both natural and engineered sequestration pathways advance efficiency, monitoring, and governance but require addressing environmental costs and policy support.
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This review was created by AI and reviewed by human editors.