## 4 Conclusions  
In this paper, we demonstrate the feasibility of a CO\({}_{2}\) modeling framework for the urban-coastal Mediterranean region around Marseille, France. The setup includes emissions maps from anthropogenic, net ecosystem emissions, fire, and ocean components. A seasonal analysis and case study of two specific days are used to showcase the model's ability to accurately characterize CO\({}_{2}\) enhancement events under a variety of conditions unique to the area, although there remains room for improvement in future investigations. We tested the benefits of including or excluding an urban heat island module in the simulation. Additional optimizations of the model for this specific region might include a better accounting of the terrain height and boundary layer dynamics as well as improvements taking into account the specificity of local urban vegetation and the urban background, potentially leading to better model-observation agreement in future investigations of this region. Further studies might also look into improving model performance by incorporating more accurate emission inventories, enhancing model resolution, or using Bayesian methods to estimate emission totals. Our investigation has confirmed a previously-observed result that there is a positive NEE in the region during summertime; thus, we included a springtime period in our seasonal analysis to allow for a more comprehensive comparison. Our model results seem to indicate that the vegetation signal in the region can be strong compared to the anthropogenic signal, even at the CAV and SME measurement sites situated within and along the coast of the city, respectively. Only in the wintertime was the anthropogenic signal dominant over the vegetation signal, and only at these two sites; this may at least partially be due to the characterization of the local urban vegetation not having sufficiently high accurate and resolution, which is a limitation of the presented modeling framework. We conclude that there is a need to build such databases as inputs to the C-TESSEL model in order to aid future studies. Furthermore, any analysis looking to constrain the fossil fuel CO\({}_{2}\) signal for the region will need to use additional methods to accurately account for the local vegetation signal, including using a continental background site closer to the city borders (instead of a marine one) to capture the regional biogenic signal and including the use of measurements such as those from C\({}^{14}\) and CO to help distinguish between the fossil fuel and biogenic signals. In addition, we analyzed the effects of including or excluding an urban heat island module. We found that the choice of inclusion had an effect on the boundary layer height, changing it by as much as \(\sim\)35% at SME in Summertime 2016 and by as little as \(\sim\)10% at CAV in Wintertime 2017. This amount of change in the boundary layer height can significantly affect the CO\({}_{2}\) mixing. We extended the comparison to the CO\({}_{2}\) analysis, where the simulation with the UHI module turned off performed better in almost every case we tested, presenting average values that were closer to the measured enhancements than its counterpart with the UHI module turned on. The disconnect in performance was most evident at the coastal SME site, where it was almost half a ppm of CO\({}_{2}\) closer to the measured enhancements on average for the Summertime 2016 period. We suspect that these disagreements between the model and measurements may be related to the coastal position of the SME site as well as to the previously identified interrelationship between the Marseille boundary layer and the daytime sea breeze [98; 104]. This implies a minimal impact on the ABL evolution from urban influences, such that the inclusion of the UHI module overemphasized this feature. We conclude that sites in this region should be equipped with atmospheric profiles such as those obtained from LIDAR instruments in order to properly constrain PBL simulations with real measurements in future studies.