# Performance Evaluation for China's Planned CO\({}_{2}\)-Ipda
## 4 Discussion
### Usage of the Planned CO\({}_{2}\)-IPDA in China  
With its current configuration, the ideal target for China's CO\({}_{2}\)-IPDA is predicted to be the majority of mainland China. Some major forested areas, including the Greater Khingan Mountains and Xishuangbanna Tropical Rainforest, are located in this area, suggesting that the launch of the CO\({}_{2}\)-IPDA could clarify the carbon uptake of China's major carbon sinks and thus deepen our understanding of the effect of this vegetation on the carbon cycle. Moreover, the CO\({}_{2}\)-IPDA would provide accurate measurements for the major grasslands in China, including the Hulunbuir Grasslands, Xilin Gol Prairie, Ili Grassland, and Nagqu Alpine Grassland, which will provide precious opportunities to study the inter-annual variations in the grassland characteristics. Based on the performance evaluation from the border of the Taklimakan Desert, inversions for Taklimakan Desert should give relative random errors of no more than 0.5. This could help verify the discovery of a hidden carbon sink in desert regions [38]. Figure 14: Weighting functions (WF) for different wavenumbers: (**a**) shows the relationship between the WF and altitude. Different colors represent different wavenumbers as per the figure legend; In (**b**), the dotted curve denotes the spectrum for R18, and the colored straight lines represent the wavenumbers shown in the left-hand panel, using the same color key. The spectrum shown in the right-hand panel was calculated using \(T\) = 296 K and \(p\) = 101325 Pa, and the line has a Voigt shape. However, the accuracy of the measurements for carbon source regions is a concern. Figure 11 shows that the ideal target will not be met for nearly all of China's cities. Referring to economic data [39], China's CO\({}_{2}\)-IPDA will not be able to obtain inversion results with errors of less than 0.3% for the regions responsible for more than 80% of China's total GDP, which could be problematic for carbon inversions in these areas. We attribute the poor performances of the CO\({}_{2}\)-IPDA to the large quantities of air pollution present in the urban areas of China. From Figures 9 and 11, a clear correlation is evident between AOD and the relative random error. Hence, we propose that with the current hardware system design and planned orbit, AOD is the most critical factor in determining the accuracy of the inversion results from China's CO\({}_{2}\)-IPDA over land areas. A novel retrieval method that suppresses errors derived from high aerosol loadings is urgently needed to solve the anticipated problem in the estimation of China's carbon emissions using data from the new satellite. Regarding the remote sensing XCO\({}_{2}\) data from sea areas, only the medium goal could be realized for coastal seas, and this would require a decrease in the spatial resolution to 100 km. The relatively low reflectance of water is identified as the primary cause of the low accuracy over seas. It is noteworthy that CO-IPDA's detection accuracy over China's Bohai Sea and Yellow Sea will be very limited because of the combined effect of high aerosol concentrations and low reflectance. This disadvantage poses a challenge in estimations of the carbon exchange between land and sea. Over the South China Sea, the ideal target can be met. In general, China's CO\({}_{2}\)-IPAD can achieve useful XCO\({}_{2}\) measurements that will facilitate a more accurate determination of carbon fluxes and thus an in-depth understanding of carbon cycle mechanisms. In just 0.031% and 0.705% of areas in China and the surrounding regions, errors will exceed 1% and 0.5%, respectively. The ideal target (i.e., errors below 0.3%) will be met in 74% of regions. If the orbit height was reduced to 450 km, the situation would be very different. A relative random error of less than 0.2% would be expected for over 75% of regions, and the ideal target could be met in over 95% of regions. This is a very promising outlook.