# Evidence of Carbon Uptake Associated with Vegetation Greening Trends in Eastern China
## 2 Data and Methods
### Trends in Regional XCO\({}_{2}\) Summer Drawdown
#### 2.2.3 Model Simulations of XCO\({}_{2}\) and CO\({}_{2}\) Fluxes  
Estimated surface CO\({}_{2}\) fluxes and XCO\({}_{2}\) concentrations from the GEOS-Chem, CarbonTracker, and MACC models were used for two purposes: (1) To create estimates of XCO\({}_{2}\) background increase in the study area (Section 2.2.4), and (2) estimate relationships between local surface CO\({}_{2}\) fluxes and XCO\({}_{2}\) variability (Section 2.3). CarbonTracker (CT) 2017 is a global inversion model from NOAA providing atmospheric CO\({}_{2}\) mixing ratio distributions and inferred surface CO\({}_{2}\) fluxes with a time resolution of 3 h [47]. It uses the Carnegie-Ames-Stanford Approach (CASA) land surface model to estimate prior flux estimates and Transport Model 5 (TM5) to represent atmospheric circulation [65]. Optimized posterior surface flux components were solved for with a spatial resolution of 1 \(\times\) 1 degrees including fossil fuel, fire, ocean, and biosphere. Each surface flux was tagged to create associated CO\({}_{2}\) concentrations in 25 vertical atmospheric levels with spatial resolution of 2 degrees in latitude and 3 degrees in longitude. The atmospheric pressure of the different levels used was from the CT CO\({}_{2}\) total files. Contributions to XCO\({}_{2}\) from each component and background concentration were calculated from the vertical profiles based on the pressure-averaged method [66]. MACC-III is also an inversion model from the European Space Agency (ESA) providing global XCO\({}_{2}\) and net CO\({}_{2}\) fluxes with a temporal and spatial resolution of 3 h and 1.875 degrees latitude and 3.75 degrees longitude [48]. Both inversion model results have been compared to the FLUXCOM product in Asia [67], but as both are prone to different types of errors and uncertainties, there is no way to provide a robust validation of these model products. In order to separate local biospheric CO\({}_{2}\) flux influence in Eastern China from remote biospheric and other non-biospheric CO\({}_{2}\) flux influences on that region, we created estimates of various CO\({}_{2}\) flux components using transport model simulations. These simulation results were later used to remove other non-local and non-biospheric influences from observed GM-XCO2 trends using detrending methods. GEOS-Chem is a global 3-D transport model for atmospheric trace gas simulation driven by meteorological and surface flux input [49]. We adopted GEOS-Chem version 11.4 driven by MERRA-2. In the GEOS-Chem global CO\({}_{2}\) simulation, we used the CarbonTracker fossil fuel, ocean exchange, and biosphere posterior CO\({}_{2}\) fluxes to replace the standard GEOS-Chem surface CO\({}_{2}\) flux input. The biomass fire emissions were taken from the Global Fire Emission Database version 4.1s (GFEDv4.1s) [68]. We used annually neutral net terrestrial exchange fluxes and turned off ship and aviation emissions and the 3-D Chemical Oxidized Source. Fossil fuel CO\({}_{2}\) emissions used in these tracer models were from the Open-source Data Inventory for Anthropogenic CO\({}_{2}\) (ODIAC), which is a global anthropogenic CO\({}_{2}\) emission dataset based on estimates made by the Carbon Dioxide Information and Analysis Center (CDIAC) and satellite-observed nightlights and the power plant profile dataset for spatial and temporal distributions [51]. It is monthly data with a spatial resolution of 1 \(\times\) 1 degree. The global background and a nested GEOS-Chem simulated XCO\({}_{2}\) for Eastern Asia (referred as Back-GEOS-XCO\({}_{2}\) and Nested-GEOS-XCO\({}_{2}\), respectively) were used for local XCO\({}_{2}\) background corrections without introducing modeled local biosphere flux variability. In the nested Eastern Asia CO\({}_{2}\) simulation, we used the GFED 4.1s land net ecosystem exchange, CarbonTracker biosphere prior CO\({}_{2}\) fluxes with annually neutral net CO\({}_{2}\) fluxes instead of the CarbonTracker biosphere posterior CO\({}_{2}\) fluxes, which are time-varying from year-to-year.