## 3 Model
### Optimized Result  
Because there are 16 routes in Shanghai terminal area and many candidate points of the flight segment, the optimization calculation work is heavy. In this paper, the genetic algorithm (NSGA-II) [31] with gene retention strategy is selected for solution. After optimization, the normalized emission of terminal routes decreased rapidly from 1.892 to 1.746 within 120 generations, and then decreased to 1.723 within 240 generations. After 300 generations, it tended to be stable with little fluctuation, as shown in Figure 8.  
Comparing with the emissions before optimization, the pollutant emissions of the terminal area routes after optimization is decreased from 40,331.3 kg to 19,595.8 kg, and the decrement is 51.4%. The emission of \(NOx\), \(HC\), \(CO\) and total suspended particulate (\(TSP\)) are decreased from 36,998.9 kg, 297.8 kg, 2938.9 kg and 95.8 kg to 17,258.4 kg, 176.4 kg, 2106.4 kg and 54.6 kg, as shown in Figure 9.  
Figure 8: The trend of normalized emission during population evolution. Figure 9: The emissions of terminal area route. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Number** & **Priority** & **Weight Coefficient** & **Number** & **Priority** & **Weight Coefficient** \\ \hline \(R_{16}\) & 1 & 0.1581 & \(R_{8}\) & 9 & 0.0624 \\ \(R_{13}\) & 2 & 0.1567 & \(R_{9}\) & 10 & 0.0522 \\ \(R_{5}\) & 3 & 0.0843 & \(R_{3}\) & 11 & 0.0503 \\ \(R_{14}\) & 4 & 0.0802 & \(R_{10}\) & 12 & 0.0478 \\ \(R_{2}\) & 5 & 0.0764 & \(R_{15}\) & 13 & 0.0451 \\ \(R_{6}\) & 6 & 0.0742 & \(R_{4}\) & 14 & 0.0417 \\ \(R_{11}\) & 7 & 0.0736 & \(R_{7}\) & 15 & 0.0273 \\ \(R_{12}\) & 8 & 0.0660 & \(R_{1}\) & 16 & 0.0261 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Weight coefficient of terminal routes. As shown in Figure 10, the exposure population affected by noise level above 65 dB are decreased rapidly from 4.181 million to 3.353 million within 180 generations. In the 180-240 generation, the optimal value decreased slowly, from 3.353 million to 3.31 million. After 300 generations, the fluctuation is very small. Figures 11 and 12 are noise contour maps of the route network before and after optimization respectively, and the noise coverage area above 65 decibels is obviously reduced. Further analysis shows that the area affected by noise is transferred from the north-central part of Shanghai to the southeast. The noise level at the southeast side of ZSPD is significantly increased, but this area is an uninhabited area along the east coast. Although the downtown area around ZSSS is still affected by noise level above 65 dB, the affected area is obviously reduced. The number of exposure population affected by noise level above 65 dB before and after optimization are decreased from 4.181 million to 3.283 million, and the decrement is 21.5%, and the exposure population affected by noise below 55 dB is increased by 68.66% (the noise level below 55 dB is considered as a comfortable living environment), as shown in Table 4.  
Figure 11: Noise contour map of route network before optimization. Figure 10: Trend of population amount affected by noise above 65 dB in the evolution. The route optimization results are illustrated by taking ZSSS-AND-1A as an example. By comparing the routes before and after the optimization, the changes of route height and node can be intuitively seen, as shown in Figure 13. In the horizontal profile, compared with current route, the optimized route was offset, and the two routes were completely different. In the vertical profile, the optimized route maintains more high altitude before the final approach fix (FAF) and descends at a larger angle. The optimized route after FAF coincides with the path before optimization. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Noise Value (dB)** & **Before Optimization (10\({}^{4}\))** & **After Optimization (10\({}^{4}\))** \\ \hline
0–45 & 7.6 & 10.7 \\
45–55 & 477.2 & 807.1 \\
55–65 & 1526.2 & 1273.1 \\
65–75 & 349.2 & 283.2 \\
75–85 & 42.6 & 43.6 \\ \(>85\) & 26.3 & 11.5 \\ \hline \hline \end{tabular}
\end{table}