In response to the goals of the United Nations Framework Convention on Climate Change (UNFCCC) Paris and Montreal Agreements to reduce Carbon dioxide (CO ₂ ) emissions from burning fossil fuels, numerous space-based measurements have been undertaken recently. NASA’s Orbiting Carbon Observatory-3 (OCO-3) provides insightful observations of the column-averaged dry air mole fraction of CO ₂ (XCO ₂ ) around various power plants using the Snapshot Area Maps (SAMs) mode. This study utilizes this data, along with the column version of the Stochastic Time-Inverted Lagrangian Transport (X-STILT) model, which is driven by the Weather Research and Forecasting (WRF) model, to estimate emissions from the Bełchatów power plant in Poland, one of the largest fossil fuel-consuming power stations globally. By integrating modelled and observed data and applying a Bayesian inversion approach, which is combined with a priori CO ₂ emissions from the Open-source Data Inventory for Anthropogenic CO ₂ (ODIAC), this research demonstrates the potential of this framework to estimate CO ₂ emissions from power plants and shows the ability of CO ₂ imaging satellites to monitor and support climate policies.