Accurate quantification of CO₂ emissions from large point sources is essential for tracking progress in emission-reduction strategies under the Paris Agreement. However, quantifying these emissions remains challenging across the Indian subcontinent due to dense clustering of co-located sources, spatially heterogeneous emissions, and a sparse observational network coupled with insufficient modeling capabilities. This study presents an NO₂-guided CO₂ plume detection and Cross-Sectional Flux (CSF) emission quantification methodology using high-resolution TROPOMI NO₂ and synthetic CO2M XCO₂ retrievals. The plume detection and quantification system is evaluated through an Observing System Simulation Experiment conducted across 14 coal-fired thermal power plants (TPPs) in India. CO2M XCO₂ retrievals are generated using the Weather Research and Forecasting model integrated with the Greenhouse Gas module by sampling through simulated CO2M satellite tracks. Several scenarios are examined to assess the potential of the quantification system and the impact of background XCO₂ estimation error on emission estimates. For the highest emission TPP in this study, Vindhyachal, our CSF approach estimates emissions with remarkable accuracy, with an uncertainty of 9 % in a background-error-free scenario. Since erroneous background XCO₂ estimations can have a considerable impact on the above emission estimates, two different methods are implemented to better decouple the anthropogenic contribution from the total measured quantity amid CO2M-level pixel noise, and their effectiveness is assessed with and without the noise-filter algorithm. The assessment of multiple power plants shows that sources exceeding 20 Mt of annual CO₂ are reliably quantified across multiple seasons, establishing the operational lower quantification bound of our methodology at ~ 20 Mt CO₂yr^-1. By combining TROPOMI observations with future CO2M retrievals, this study evaluates the potential of these data to detect and quantify CO₂ emissions from Indian thermal power plants under real observational conditions. Overall, the study demonstrates the operational readiness of the quantification methodology for upcoming satellite missions, as well as for integrated Measurement, Reporting, and Verification (MRV) systems within the Copernicus CO₂ Monitoring and Verification Support (CO2MVS) initiative.