## 3 Results
### Analysis of Results
#### 3.3.2 Characterization of Changes in NO\({}_{2}\) Diffusion Under Mountainous Terrain Scenarios  
Figure 12a,b present the cloud and streamline diagrams of NO\({}_{2}\) diffusion results in the Urumqi area when the pollution source is located at the entrance. The study area encompasses Urumqi city and its surrounding regions, and by gathering simulation data, we obtained pollution mass fractions at various locations. The simulation reveals that during the inlet diffusion process, NO\({}_{2}\) near the ground forms a clockwise vortex upon encountering the mountain ranges, and the number of vortices increases with the deepening terrain. In terms of the pollution mass index, higher values are observed on the northern side of the mountains, indicating a significant accumulation of pollutants on the northern side of the mountain range.  
When the diffusion source is set to a local pollution source, the backflow phenomenon in the direction of NO\({}_{2}\) diffusion can be observed from Figure 12c,d. Due to the presence of a ground-based NO\({}_{2}\) emission source, the concentration of NO\({}_{2}\) is inevitably higher near the release source. In areas with low wind speed close to the mountain range, the NO\({}_{2}\) mass index is typically low. As the topography deepens, wind speed and turbulence intensity decrease, weakening the exchange of pollutants with the external environment. Consequently, NO\({}_{2}\) pollutants cannot effectively diffuse outward. This leads to a backflow of wind speed, and the speed of the backflow winds blowing back to the urban area gradually decreases, as shown in Figure 10b. The generation of eddies in the study area indicates that the specific geographical location of the mountain range causes changes in the wind fields of nearby cities, making it difficult for pollutants in the area to disperse.  
Figure 11: Wind speed data graph.  
Figure 12: _Cont._By organizing the simulation results of the selected data points and comparing the results when the pollution source is set at the entrance and those when it is set in the local area, as shown in Figure 13, both diffusion trends are similar. The pollution quality index is generally lower in the case of entrance-source pollution compared to regional pollution diffusion. This is because during entrance-source diffusion, the pollutant concentration decreases due to long-distance transportation. In contrast, local pollution has a shorter distance to the data points.  
Both diffusion modes show a pollution aggregation trend in the basin in the middle of the mountain range. The pollution gradually decreases on the leeward side, blocked by the mountain range, which is consistent with the results simulated by the inverse distance weighting method in the preparatory work.  
Figure 14 shows the AQI data for NO\({}_{2}\) at selected stations in Urumqi. Pollution aggregates in the basin, and with the obstruction of the mountain range on the right-hand side, the pollution gradually decreases on the leeward side. Both diffusion modes exhibit a trend of being high in the west and low in the east, and high in the north and low in the south, which is in line with the actual pollution situation simulated by the inverse distance weighting method in the preparatory work and also demonstrates the applicability of this technique.  
Because mountains surround this area on three sides and the wind field is very prone to vortex, NO\({}_{2}\) pollution, whether transported over long distances from the outside world or released locally, will accumulate in this area. There is no way to spread it outwards.  
Figure 12: NO\({}_{2}\) diffusion cloud: (**a**) pollution source set at the entrance; (**b**) pollution dispersion diagram; (**c**) pollution sources are set locally; (**d**) local pollution dispersion trace maps.  
Figure 13: NO\({}_{2}\) mass index curve for data points.