## 3 Results and Discussion
### Effect of 13 th FYP on Air Quality during Heavy Pollution Episodes in Haizhu in 2020  
To evaluate the effect of 13 th FYP on NO\({}_{2}\) and PM\({}_{2.5}\) in the winter heavy pollution episode and O\({}_{3}\) in the summer heavy pollution episode, we conducted the WRF-Chem simulations with the four 2020 pollution control scenarios (2020A, 2020B, 2020C, and 2020D). Table 3 shows the changes in pollutant concentrations of the four scenarios. Since Table 3 has summarized the overall impacts (in numbers) of each emission reduction scenarios on the concentration of PM\({}_{2.5}\), NO\({}_{2}\), and O\({}_{3}\), we will present the spatial variation  
(1) Effect on PM\({}_{2.5}\) and NO\({}_{2}\) in winter heavy pollution episode  
For the simulated concentrations of PM\({}_{2.5}\) and NO\({}_{2}\) in Shayuan station, the concentrations of PM\({}_{2.5}\) and NO\({}_{2}\) were in the order of 2020A \(>\) 2020D \(>\) 2020B \(>\) 2020C. Comprehensive emission control measures taken in the whole of Guangzhou (2020C) would be able to reduce concentrations of PM\({}_{2.5}\) and NO\({}_{2}\) two times more than those just in Haizhu (2020B). In previous research, emission control from outside of Beijing contributed 8-14% to the improvement of the air quality in Beijing during APEC [57]. Therefore, regional control policies are needed. Regional control measures in a whole city could affect the air quality of the urban district, even if the district is just an isolated island. Referring to the measures in Haizhu, the effect of vehicle emission control (2020D) on PM\({}_{2.5}\) (NO\({}_{2}\)) reduction would be -44% (-71%) of the effect of comprehensive measures (2020B), meaning that vehicles are the major PM\({}_{2.5}\) (NO\({}_{2}\)) emission source in Haizhu. Vehicle emission is a typical problem in urban areas of China [87]. Previous studies showed that vehicle emission accounted for 21%, 10%, and 19.3% of the total PM\({}_{2.5}\) in Dongguan (2014) [68], Guangzhou (2014) [88], and PRD (2012) [89], respectively. Figure 8: Maps of the simulated mean NO\({}_{2}\) concentration distribution during the period 0000 BJT, 20 January, to 2300 BJT, 21 January, over Haizhu for 2020 scenarios (a: 2020A; b: 2020B; c: 2020C; d: 2020D; HZ: Haizhu; GZ: Guangzhou). In the worst meteorological condition, PM\({}_{2.5}\) pollution on Haizhu district would be improved, as shown in Figures 7c and 7b, which means that the effects on regional air quality of scenarios 2020C and 2020B were relatively significant. In particular, compared with 2020D (Figure 7d), the improvement on regional air quality in 2020B was more obvious, although the PM\({}_{2.5}\) pollution in the particular station (Shayuan) seemed to have no significant difference. In Figure 8, NO\({}_{2}\) pollution shows a similar situation. It indicates that regional and comprehensive measures could improve regional air quality during heavy pollution days. (2) Effect on O\({}_{3}\) in summer heavy pollution episode  
For the Shayuan station, the O\({}_{3}\) pollution in scenario 2020B would be higher than in other scenarios, and the O\({}_{3}\) pollution in the other scenarios were in the order 2020C \(>\) 2020D \(>\) 2020A (Table 3). The simulation results suggested that the O\({}_{3}\) level increases from 2015 to 2020 in all emission scenarios even in 2020C in which the rest of air pollutants decrease. Such changes of O\({}_{3}\) concentration is probably because the Haizhu district is a VOC-limited region in which the O\({}_{3}\) level increases (decreases) with the reduction of NO\({}_{x}\) (VOCs) emission (e.g., [PERSON], 1999 [90]). There are generally two pathways that can be adopted to relieve the O\({}_{3}\) pollution in VOC-limited region like Haizhu district. (1) To significantly reduce the NO\({}_{x}\) level and push the Haizhu district into NO\({}_{x}\)-limited region in which O\({}_{3}\) level decreases with the reduction of NO\({}_{x}\) and VOCs. However, in this pathway, there will be a period in which O\({}_{3}\) level significantly increases before it starts to decrease.