## 5 Conclusions  
Sub-daily photosynthetic CO\({}_{2}\) uptake and biogenic CO\({}_{2}\) emissions in DBF, EBF, ENF, GRS, and urban vegetated lands located in Tokyo and its surrounding areas were estimated via a terrestrial biosphere model driven by multiple satellite inputs and meteorological datasets. After calibrations, our modeled results were found to be consistent with both point-scale observed values and existing satellite-based data. The order of hourly integrated photosynthetic CO\({}_{2}\) uptake and \(NEE\) values in the Greater Tokyo Area was up to about 80%, or approximately half of the total anthropogenic CO\({}_{2}\) emissions in summer, and lower than one-tenth of the human-induced values in winter. Such modeling results not only provide reference data for the estimation of total natural CO\({}_{2}\) removal in our study area but also provide prior input values for the disaggregation of anthropogenic CO\({}_{2}\) emission and biogenic CO\({}_{2}\) flux when applying top-down approaches to update the megacity's CO\({}_{2}\) emissions inventory. This allows for unprecedented amounts of GOSAT and ground measurement data of CO\({}_{2}\) concentrations to be analyzed using inverse modeling of anthropogenic CO\({}_{2}\) emissions from Tokyo and the Greater Tokyo Area. The updated megacity CO\({}_{2}\) emissions inventory based on observations of CO\({}_{2}\) concentration will serve to detect changes in emission and to improve the understanding of source patterns over space and time. The updating of the urban CO\({}_{2}\) emissions inventory will also support the assessment of emission reduction efforts pledged and implemented by cities such as Tokyo. The following are available online at [[https://www.mdpi.com/article/10.3390/rs13112037/s1](https://www.mdpi.com/article/10.3390/rs13112037/s1)]([https://www.mdpi.com/article/10.3390/rs13112037/s1](https://www.mdpi.com/article/10.3390/rs13112037/s1)), Figure S1: Accumulated carbon (sum of \(SOC_{\text{rod}}\)_structural_, \(SOC_{\text{rod}}\)_metablic_, \(SOC_{\text{sol}}\)_michok_, \(SOC_{\text{sol}}\)_michok_, and \(SOC_{\text{sol}}\)_michok_) (kgC m\({}^{-2}\)) in the 0-28 cm soil layer of the study area after model spin-up; Figure S2: Structure, layers, and nodes of artificial neural network (ANN) to estimate \(K_{\text{d}}\)_diffuse_; Figure S3: Taylor diagram of hourly observed and modeled \(SR_{\text{d}}\)_diffuse_ (W m\({}^{-2}\)) at the World Radiation Data Centre Fukuoka, Sapporo, and Tateno sites. Table S1: List of variables and their acronyms used in the sub-daily \(GPP\), \(R_{e}\), and \(NEE\) model; Table S2: Evaluation metrics for model calibration and validation of hourly gross primary production (\(GPP\)), ecosystem respiration (\(R_{e}\)), and net ecosystem exchange (\(NEE\)); Table S3: Parameters to activate the ANN and predict \(K_{\text{d}}\)_diffuse_; Table S4: PFT-specific parameters used to calculate hourly \(R_{\text{m}inultounce}\). References [164; 165; 166; 167; 168; 169; 170; 171; 172; 173; 174; 175] are cited in the Supplementary Materials. Conceptualization, R.I.; methodology, Q.W., Y.A. and S.I. ; software, Q.W., Y.A. and S.I. ; validation, Q.W. and Y.A. ; formal analysis, Q.W. and Y.A. ; investigation, Q.W., Y.A. and S.I. ; resources, R.I. and Y.M. ; data curation, Q.W., Y.A. and S.I. ; writing--original draft preparation, Q.W. ; writing--review and editing, R.I., Y.M., H.K. and J.X. ; visualization, Q.W. and Y.A. ; supervision, R.I.; project administration, R.I.; funding acquisition, R.I. All authors have read and agreed to the published version of the manuscript. This research received no external funding. The data presented in this study are available on request from the corresponding author. We thank [PERSON] for his useful comments about this study. We are grateful to [PERSON] (National Institute for Environmental Studies) and [PERSON] (National Institute for Environmental Studies) for their valuable comments on model development.