Impacts of Spatial Resolution and XCO₂ Precision on Satellite Capability for CO₂ Plumes Detection

Greenhouse gas satellites can provide consistently global CO₂ data which are important inputs for the top-down inverse estimation of CO₂ emissions and their dynamic changes. By tracking greenhouse gas emissions, policymakers and businesses can identify areas where reductions are needed most and implement effective strategies to reduce their impact on the environment. Monitoring greenhouse gases provides valuable data for scientists studying climate change. The requirements for CO₂ emissions monitoring and verification support capacity drive the payload design of future CO₂ satellites. In this study, we quantitatively evaluate the performance of satellite in detecting CO₂ plumes from power plants based on an improved Gaussian plume model, with focus on impacts of the satellite spatial resolution and the satellite-derived XCO₂ precision under different meteorological conditions. The simulations of CO₂ plumes indicate that the enhanced spatial resolution and XCO₂ precision can significantly improve the detection capability of satellite, especially for small-sized power plants with emissions below 6 Mt CO₂/yr. The satellite-detected maximum of XCO₂ enhancement strongly varies with the wind condition. For a satellite with a XCO₂ precision of 0.7 ppm and a spatial resolution of 2 km, it can recognize a power plant with emissions of 2.69 Mt CO₂/yr at a wind speed of 2 m/s, while its emission needs be larger than 5.1 Mt CO₂/yr if the power plant is expected to be detected at a wind speed of 4 m/s. Considering the uncertainties in the simulated wind field, the satellite-derived XCO₂ measurements and the hypothesized CO₂ emissions, their cumulative contribution to the overall accuracy of the satellite's ability to identify realistic enhancement in XCO₂ are investigated in the future. The uncertainties of ΔXCO₂ caused by the uncertainty in wind speed is more significant than those introduced from the uncertainty in wind direction. In the case of a power plant emitting 5.1 Mt CO₂/yr, with the wind speed increasing from 0.5 m/s to 4 m/s, the simulated ΔXCO₂ uncertainty associated with the wind field ranges from 3.75 ± 2.01 ppm to 0.46 ± 0.24 ppm and from 1.82 ± 0.95 ppm to 0.22 ± 0.11 ppm for 1 × 1 km² and 2 × 2 km² pixel size, respectively. Generally, even for a wind direction with a higher overall uncertainty, satellite still has a more effective capability for detecting CO₂ emission on this wind direction, because there is more rapid growth for simulated maximal XCO₂ enhancements than that for overall uncertainties. A designed spatial resolution of satellite better than 1 km and a XCO₂ precision higher than 0.7 ppm are suggested, because the CO₂ emission from small-sized power plants is much more likely be detected when the wind speed is below 3 m/s. Although spatial resolution and observed precision parameters are not sufficient to support the full design of future CO₂ satellites, this study still can provide valuable insights for enhancing satellite monitoring of anthropogenic CO₂ emissions.