# Evidence of Carbon Uptake Associated with Vegetation Greening Trends in Eastern China
## 4 Discussion
### Uncertainties in Constraining the Urban Dome and Remote Influence on XCO\({}_{2}\) Trends  
The XCO\({}_{2}\) trends observed over EC result from a combination of remote and local influences. Accurately quantifying the influence of regional biospheric CO\({}_{2}\) fluxes in EC depends on how well we remove the influence from non-local biospheric CO\({}_{2}\) fluxes including remote and local anthropogenic fossil and fire emissions and ocean gas exchange as well as remote biospheric influence. In this study, we tested four methods for removing the cumulated XCO\({}_{2}\) increase to better study the local biospheric component of XCO\({}_{2}\) changes. The first method using the NOAA-reported global mean CO\({}_{2}\) is not able to remove the influence from the local urban CO\({}_{2}\) dome, which increases over time and therefore underestimated the trend in XCO\({}_{2}\) due to local biospheric influence. In addition, the time series fitting of GM-XCO\({}_{2}\) removed the local annual biospheric contribution to the XCO\({}_{2}\) trend and underestimated the signal of interest, although there was still a component of GS trends in XCO\({}_{2}\) that served as a lower bound of local biospheric influence. The trends calculated from detrending using simulated XCO\({}_{2}\) using CT and GEOS-Chem transport (with and without nested grid cells) of CT surface CO\({}_{2}\) fluxes were likely the best representation of local biospheric influence on XCO\({}_{2}\) because they are designed to remove trends caused by the remote biospheric CO\({}_{2}\) fluxes over time, but retain trends in local biospheric CO\({}_{2}\) fluxes, plus remove all the non-biospheric influence. Similarities between Figure 6c,d showed that characterizing the fine spatial scale resolution of the urban XCO\({}_{2}\) dome was not critical to defining GP trends. Therefore, XCO\({}_{2}\) decreasing trends of \(-0.084\pm 0.090\), \(-0.081\pm 0.088\), and \(-0.070\pm 0.093\) ppm yr\({}^{-1}\) were our best estimates of XCO\({}_{2}\) change caused by EC region local biospheric CO\({}_{2}\) fluxes with uncertainty listed is the grid-scale spatial variability in trends (Table 2). These trends result in a total XCO\({}_{2}\) change from 2003 to 2015 of \(-0.84\) to \(-1.01\) ppm.  
This analysis is subject to two sources of bias. First, uncertainty in remote CO\({}_{2}\) fluxes could result in artificial trends in local biospheric CO\({}_{2}\) fluxes in the study region, however it is very unlikely that such an artificial signal from remote CO\({}_{2}\) flux uncertainty would correspond to the exact region that shows vegetation greening. Second, an overestimate in local fossil fuel CO\({}_{2}\) emissions from EC in the EDGAR database would result in an overestimate of local biospheric uptake. [PERSON] and [PERSON] [78] suggested that fossil fuel CO\({}_{2}\) emissions in EC may in fact be overestimated based on scaling with methane emissions. There is no independent way to verify local fossil emissions in EC at the moment. However, the correction method based on detrending using annual global mean CO\({}_{2}\) concentrations from NOAA supports a local biospheric sink in the southern portion of EC in addition to showing urban emissions increasing faster than the global mean in the northern part (Figure 4a). This correction method cannot create regional artificial biospheric uptake due to local CO\({}_{2}\) emissions uncertainty. However, the magnitude of the inferred sink is sensitive to local CO\({}_{2}\) emissions uncertainty. This demonstrates the importance of independent constraints of fossil and biospheric CO\({}_{2}\) fluxes in order to understand CO\({}_{2}\) flux trends near urban centers.