The surge in production and transportation industries stands as the pillar to most daily transactions, yet it also serves as a significant contributor to climate change and global warming. The implementation of blockchain technology has helped the transition of supply chains toward sustainability through successful model applications in logistics and environmental impact innovations. However, those integrations are far from being optimal since they still encounter hindrances in scalability and data privacy, which delays transactions’ performance and increases their cost. In this regard, directed acyclic graphs (DAGs) offer parallel, faster, and cost-effective transactions’ processing. Unlike traditional blockchain’s linear structure, they enable a non-sequential node representation of operations that allows their effective initiating. This paper demonstrates the efficiency of the MetaDAG model integrating blockDAG in the metaverse for carbon footprint reduction in the Moroccan air transportation industry. Based on this, transactions’ data will be processed effectively and privately within the interrelated IPFS framework using Agent-Based Modeling (ABM) for the network representation, which will enhance nodes’ NFT integration in the metaverse and extension to urban ecosystems for smart cities. Moreover, the framework is tested using OECD dataset displaying the reduction of carbon footprint and increase of carbon credits after the model implementation.