(558e) Eco-Efficient Processing Clusters: Blockchain-Enabled Peer-to-Peer Resource and Emission Trading Framework

Achieving sustainable development goals requires seamless integration of materials and energy across industrial processes, alongside effective implementation of an Emission Trading System (ETS). The core challenge is to foster transparency and accountability, while optimizing the transformation of raw materials and energy into valuable products and maintaining data privacy and traceability within the ETS framework. This study proposes a novel framework to develop optimal processing clusters and a dual blockchain-based trading system for resources and emissions, addressing these concerns. The framework utilizes a stepwise approach to synthesize integrated processing clusters and ETS, featuring two interactive systems: a Blockchain-based system for trading resources and another for emissions. The resource trading system enhances process transparency, allowing for precise tracking of materials and energy. Additionally, we introduce a Mixed-Integer Nonlinear Program (MINLP) integrated with Ethereum blockchain's smart contracts, enhancing data privacy and traceability and facilitating fair cost distribution among the processes to achieve environmental goals. This model calculates emission trade volumes and investments in carbon capture and storage (CCS), promoting system efficiency and reliability. By equipping decision-makers and regulatory bodies with a robust tool, this framework not only enhances understanding of resource and emission trading interactions but also supports the development of new policies and regulatory compliance through blockchain technology. This advancement signifies a pivotal step towards realizing sustainable industrial practices and achieving environmental targets.