Cornell engineers create real-time virtual replica of Manhattan's CO2 landscape

Cornell engineers have developed a 'digital twin' framework that creates a real-time virtual replica of urban carbon dioxide levels, using Manhattan as a test case. The system integrates data from multiple sources and employs Bayesian modeling and machine learning to estimate conditions across space and time. Published in Environmental Modelling & Software, it aims to help city planners monitor emissions and evaluate interventions before real-world implementation.