## 1 Introduction  
Atmospheric CO\({}_{2}\) concentrations are increasing at their fastest observed decadal rate as a result of growing anthropogenic CO\({}_{2}\) emissions [1; 2]. There is a near-linear relationship between CO\({}_{2}\) emissions and resultant global warming effects [3]. About 70% of these emissions originate from urban areas, which is expected to increase as urbanization continues, with forecasts predicting an additional 2.5-3 billion people relocating to urban areas by 2050 [4; 5]. Thus, to aid policymakers in their mitigation strategies, it is essential to undertake emission quantification and monitoring efforts near urban areas (e.g., [6; 7]). Currently, urban emission quantification efforts rely heavily on self-reported estimates following one of a few standard protocols, such as those laid out in, e.g., [PERSON] [8], [PERSON] and Manarolla [9], [PERSON] et al. [10; 11], with only a few scientifically intensive investigations undertaken for a handful of cities, e.g., [12]. While it is difficult to quantify the uncertainty in any inventory estimate (e.g., [13]), those with a heavy reliance on self-reported data may be particularly susceptible to biases and errors [14; 15]. Therefore, an independent quantification method is extremely useful for analysis and attempted verification. Atmospheric methods, including direct measurement and model-based approaches, can provide additional constraints on anthropogenic carbon emissions to better inform policymakers about their decisions (e.g., [16; 17; 18; 19]). Mesoscale urban-related CO\({}_{2}\) quantification has been conducted using a combination of atmospheric transport models and in situ observations in \"mega-city\" regions such as Paris [18; 19; 20; 21; 22] and Los Angeles [23; 24; 25; 26], in regions with smaller cities around varying terrain such as Salt Lake City [27; 28], Boston [29], and Indianapolis (e.g., [30; 31]), and in regions such as the Korean Peninsula [32]. The advent of satellite measurements has also allowed for some comparisons using total-column XCO2, including in Berlin [33] and Reunion island [34]. These investigations have been able to address a wide range of complicating issues around CO\({}_{2}\) emission validation, as each geographic region brings its own challenges. Coastal regions bring unique difficulties as well, and there have not been many CO\({}_{2}\) analyses in such areas. Los Angeles, a coastal city that has been well-studied, has complex air transport because of regional effects, for instance \"Catalina\" eddies induced by the shape of the Southern California Bight [35; 36; 37]. The surrounding mountain ranges and large number of daily emitters lead to a persistent urban dome where CO\({}_{2}\) builds up [23], while sea-breeze conditions that are strong enough to truly flush the basin are only episodic [26]. In a study of the coastal region of Valencia, Spain, [PERSON] et al. [38] found it challenging to quantitatively match modeled CO\({}_{2}\) to observations due to modeling limitations and the complexity of the territory, in particular the land-sea breezes. Despite these difficulties, they were able to reproduce proper transport processes during their period of observation, including a CO\({}_{2}\) vertical depletion between 500-2000 km with permanent buildup below. Addressing the paucity of CO\({}_{2}\) studies in other urban/coastal regions with complex terrain is a major aim of the present study. The SUD-PACA (Provence-Alpes-Cote d'Azur) Region in southeastern France presents a unique opportunity in Europe to assess the formation and variability of atmospheric CO\({}_{2}\) over a large coastal metropolitan area, namely, Marseille. Marseille is the second-largest city of France by population, with over 869,000 inhabitants as of 2015 [39]. It is situated on hilly terrain along the coast of the Mediterranean Sea.