## 1 Introduction  
CO\({}_{2}\) emissions from fossil fuel combustion have elevated atmospheric CO\({}_{2}\) above pre-industrial levels, altering the radiative forcing of the atmosphere and the global climate. The United Nations Framework Convention on Climate Change (UNFCCC) Paris Agreement aims to address this issue by coordinating contributions to reduce greenhouse gas (GHG) emissions at various scales by nations and acknowledging the role of subnational and non-state actors. However, to better manage emissions, improved and/or complementary methods of quantifying them are needed at all spatial scales from the national level down to the facility level. National GHG emissions are reported under the UNFCCC according to protocols of the Intergovernmental Panel on Climate Change Task Force on National Emission Inventories [1]. Approved methods are mostly activity-based, assuming some quantity of emissions for a given quantity of fuel burned or other proxy, and seldom deal with atmospheric GHG measurements. While constructing a system of in situ measurements to monitor anthropogenic CO\({}_{2}\) emissions may be possible at some scales for select locations, it would be a major logistical challenge to implement globally, while satellites are frequently used as a means of acquiring global observations. Although no satellites have yet been launched specifically for anthropogenic CO\({}_{2}\) emissions monitoring, they are now being considered for this purpose [2] and could play a key role in an Integrated Global Greenhouse Gas Information System (IG3 IS) [3]. [PERSON] et al. [4] show that monitoring CO\({}_{2}\) emissions at the scale of individual mid to large sized (\(>\)10 Mt yr\({}^{-1}\)) fossil fuel burning power plants should be possible with multiple satellites. The preferred architecture for such a constellation is now being considered by space agencies, Committee on Earth Observations Satellites (CEOS), the Coordination Group for Meteorological Satellites (CGMS) and other international groups. [PERSON] et al. [5] first demonstrated with simulated data, the importance of spatially imaging column-averaged CO\({}_{2}\) mole fraction (XCO\({}_{2}\)) plume enhancements for quantifying point source emissions with a pixel size of 2 \(\times\) 2 km\({}^{2}\) as proposed for CarbonSat. [PERSON] et al. [4] used XCO\({}_{2}\) observations from NASA's Orbiting Carbon Observatory 2 (OCO-2) [6], which has a narrow swath consisting of eight parallelogram-shaped \(\leq\)1.29 \(\times\) 2.25 km\({}^{2}\) footprints, to quantify daily emissions from five power plants. For three U.S. power plants, the estimated emissions were verified to be within 1%, 4% and 17% of daily emissions reported by the U.S. Environmental Protection Agency (EPA), which enabled application of the method to power plants in India and South Africa, which have less detailed or less reliable available information on CO\({}_{2}\) emissions. The present study does not prescribe a detailed design for a future CO\({}_{2}\) monitoring constellation, which would need to function for emission estimates at various scales, but simply investigates pixel size, a multiple image averaging method, and revisit rate in the context of quantifying power plant CO\({}_{2}\) emissions. The impact of varying pixel size is explored using simulated data that contain noise and various types of biases, and the accuracy and precision of square pixels is compared to that of rectangular pixels with equal area and a 3 to 1 aspect ratio. A method is introduced and evaluated that averages multiple images with varying wind directions to obtain averaged enhancements nearly free of background noise and with a higher effective resolution.