## 3 Model for Urban Area Air Quality Analysis Based on CFD Simulations  
The main focus of this research was to generate a complex analysis containing crucial data that can easily be interpreted by urban designers. Frameworks such as those presented by [PERSON] et al. [25] propose systems in which multiple simulations from different fields of study, such as wind analysis, illumination, or energy efficiency, can be performed on an urban block environment. The models of buildings would be uniformly represented, and the results of the simulations would be read in a way that can identify critical areas which are not suitable for windows or living spaces. In this paper, buildings inside the analyzed block are represented without windows and doors. Every vertical surface of the analyzed geometry is a potential location for a window. This assumption is made in order to assess the domain that cannot be easily changed by urban developers or inhabitants. If the area with stagnant air is detected near windows used for the natural ventilation of living spaces, the new opening can be placed in a more suitable location. Excluding windows and doors can change the air flow, but mostly when the circulation is provided inside of the building. In order to reduce the complexity of the simulations, we excludednatural ventilation potential from inside the buildings, although we acknowledge the recent adoption of BIM technologies in the construction industry and the potential that most of the interior space of urban block buildings could be fully represented and available in the future. Another problem for urban block natural ventilation assessment is that simulations can give different results if only certain doors and windows are opened. The results can be different in scenarios where all the doors and windows are opened, all are closed, or when combinations of dozens or hundreds of doors and windows inside the block are opened or closed. For each combination, a new model must be prepared. Although the results will not reflect the complexity of real conditions in every aspect, the model presented in this paper reduces the complexity of certain aspects of geometry. This is done in order to significantly reduce the computational time. Several studies [26; 27; 28] have made a connection between stagnant air outside of buildings with higher air pollution and human health issues for the inhabitants of an urban area. In this regard, in this study, we consider air stagnation in the urban block environment in close proximity to windows as the air of low quality. In this research, air quality is a parameter that can have either a high or a low value. A low value is considered for air velocities that do not meet the minimum requirement for air circulation, which is 0.15 m/s. This threshold was chosen based on several studies [29; 30; 31]. The number is a variable that can be changed based on research preferences. The results are a graphical representation of the areas with stagnant air on surfaces of the 3D model of the analyzed urban block. The problem is presented in respect of not just one, but eight wind directions in order to provide results that can illustrate to users more accurate data in respect of natural ventilation throughout the year. The surfaces representing the walls of buildings do not have velocity parameters, so in order to represent the results, the assumption is made that if the area that is 1 m away from a part of a wall has an average velocity lower than the threshold, that part of the wall is labeled as a stagnant air area. Our framework consists of the following procedures:  
First, the geometry of the 3D models representing the urban environment are optimized (Section 3.1). Second, the main wind directions are chosen for the simulation (Section 3.2). Third, simulations in CFD software are performed (Section 3.3). Fourth, the algorithm is used to interpret the results (Section 3.4). Fifth, visualization of the results are conducted (Section 3.5).