Abstract
Greenhouse gas satellites can provide consistently global CO(2) data which are important inputs for the top-down inverse estimation of CO(2) 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 CO(2) emissions monitoring and verification support capacity drive the payload design of future CO(2) satellites. In this study, we quantitatively evaluate the performance of satellite in detecting CO(2) plumes from power plants based on an improved Gaussian plume model, with focus on impacts of the satellite spatial resolution and the satellite-derived XCO(2) precision under different meteorological conditions. The simulations of CO(2) plumes indicate that the enhanced spatial resolution and XCO(2) precision can significantly improve the detection capability of satellite, especially for small-sized power plants with emissions below 6 Mt CO(2)/yr. The satellite-detected maximum of XCO(2) enhancement strongly varies with the wind condition. For a satellite with a XCO(2) precision of 0.7 ppm and a spatial resolution of 2 km, it can recognize a power plant with emissions of 2.69 Mt CO(2)/yr at a wind speed of 2 m/s, while its emission needs be larger than 5.1 Mt CO(2)/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 XCO(2) measurements and the hypothesized CO(2) emissions, their cumulative contribution to the overall accuracy of the satellite's ability to identify realistic enhancement in XCO(2) are investigated in the future. The uncertainties of ΔXCO(2) 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 CO(2)/yr, with the wind speed increasing from 0.5 m/s to 4 m/s, the simulated ΔXCO(2) 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 km(2) and 2 × 2 km(2) pixel size, respectively. Generally, even for a wind direction with a higher overall uncertainty, satellite still has a more effective capability for detecting CO(2) emission on this wind direction, because there is more rapid growth for simulated maximal XCO(2) enhancements than that for overall uncertainties. A designed spatial resolution of satellite better than 1 km and a XCO(2) precision higher than 0.7 ppm are suggested, because the CO(2) 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 CO(2) satellites, this study still can provide valuable insights for enhancing satellite monitoring of anthropogenic CO(2) emissions.