A Hybrid Approach to Carbon Monitoring in India by combining Satellite-based NO2 and CO2 mixing ratios

Quantifying carbon emissions in the Indian region is fraught with uncertainties, largely due to the limited availability of atmospheric trace gas observations and robust techniques. Atmospheric inverse modeling approaches, though highly potential, are often constrained by sparse observational datasets over India. To address these challenges, this study investigates a novel data-driven methodology that leverages satellite-based NO₂ and CO₂ concentrations for plume detection and associated emission quantification. Specifically, we utilize highly accurate and precise NO₂ measurements from the TROPOMI instrument onboard Sentinel-5P to identify and trace emission hotspots, such as thermal power plants and densely populated urban centers, which significantly contribute to regional emissions. Using this NO₂-driven plume detection as a proxy, we explore the potential of atmospheric dry-air column CO₂ concentrations to quantify hotspot emissions. The present study utilises the modeled dry-air column CO₂ concentrations, which observations can later replace. The focus is given to illustrate a methodology that can combine both  NO₂ and CO₂ concentrations derived from satellite instruments to infer the spatial distribution of  CO₂ emission over a region that is rapidly evolving and industrialized, like India. The above task is particularly in preparation for upcoming satellite missions like CO2M, which will offer co-located NO₂ and CO₂ observations that can be utilized for cost-effective solutions for carbon monitoring. Hence, the study outcome will not only improve our understanding of regional emissions but also establish a framework for leveraging future satellite missions to assist in establishing carbon emission reduction policies.