The Role of Big Data, IoT, And AI in Monitoring and Enhancing Global CO₂ Removal Projects

Fast-progressing climate change has made carbon dioxide (CO₂) removal a fundamental component of global climate mitigation plans presently. Among them, artificial intelligence (AI) in conjunction with IoT and Big Data analytics currently enables continuous enhancements in CO₂ removal initiatives by means of enhanced efficiency and accuracy and broadened scalability. This research looks at the disruptive potential of these new technologies for tracking and improving the verification process of CO₂ trapping devices and underground storage methods. The work evaluates how sensor-based IoT networks allow real-time environmental monitoring as well as Big Data techniques managing large climate and geospatial data along with machine learning application and artificial intelligence algorithms for CO₂ flux forecasts and operational optimization and system reliability monitoring. Recent research has produced three significant influential innovations: predictive artificial intelligence models for direct air capture (DAC) efficiency, smart forest and soil carbon monitoring systems, and blockchain-enabled carbon offset verification systems. The paper offers a study of the high expectations and ethical dilemmas arising from large-scale technology deployment, particularly with regard to data privacy, interoperability, and algorithmic bias. This paper's review of multi-disciplinary research and case studies suggests that combining digital technology with climate science offers a hopeful way to enhance global CO₂ removal plans. The reasoning put together in this paper aims to lead authorities and technical professionals as well as environmental campaigners through the creation of framework-based carbon reduction projects producing great effect.