Abstract
Coal-fired power plants contribute heavily to global anthropogenic carbon emissions, responsible for over 40% of fossil fuel-related emissions worldwide (Nassar et al., 2017; Yuan et al., 2025). However, there are multiple challenges that face data collection of carbon dioxide. The largest issues tend to be limited spatial and temporal resolution, delayed reporting, and reliance on self-reported fuel data. These metrics often misrepresent actual emissions, particularly in regions with poor monitoring infrastructure (Guo et al., 2023; Hu & Shi, 2021). The study Quantifying Coal-Based Power Plant Emissions with OCO–2 investigates the potential of leveraging Orbiting Carbon Observatory–2 (OCO–2) satellite data to detect carbon dioxide emissions from individual coal-fired power plants. Rather than relying on dispersion models, such as the Wenye et al. study (2023) covering carbon emission detection in China, we conduct a comparative analysis of the top 30 and lowest 30 emitting coal-based power plants. Through performing various visualizations and a regression model, we determine whether column carbon dioxide concentrations observed by OCO–2 can be attributed to these coal-based power plants. There will be two research questions pursued: first, can you measure direct carbon emissions from coal-based power plants across the United States through OCO–2 data? If so, is there a correlation between capacity of production and carbon emission? The findings from the study will hopefully inform the usability of these data sources to track power plant emissions globally.