Carbon offsets and carbon markets have emerged as an immediate strategy to mitigate climate change. However, concerns about accurately monitoring, reporting, and verifying carbon emission reductions have undermined trust and transparency in carbon markets. Recent case studies have revealed the significance of 4.0 technologies in developing digital monitoring, reporting, and verification systems (d-MRV) to streamline data collection, processing, and quality control of GHG emissions, mitigation actions, and support. An example of such technologies includes Digital Twins (DTs) which enables the virtual representation of physical assets, real-time monitoring of parameters, and AI-powered analytics. Furthermore, the use of Distributed Ledger Technology (DLT) as a more secure and transparent solution for d-MRV data storage and assets exchange is steadily gaining traction in present carbon markets. The recent emergence of environmentally friendly low-energy consumption blockchain networks is opening new applications for carbon credits trading within the web3 ecosystem. This study proposes a novel architecture integrating DTs and DLT as a blockchain-based predictive d-MRV system integrated into Web3. The framework uses BIM, IoT, AI, and DLT to automate data collection, quantify GHGs savings, track ITMOs, and provide visual reporting. Smart contracts automate the verification process and tokenization allows the retirement of carbon credits and their exchange in international carbon markets. The results of this study will determine whether a blockchain-based predictive Digital Twin MRV system integrated into Web3 can help improve the transparency of carbon offset projects and the functioning of carbon markets.