## 1 Introduction
(2016) [22] researched the impact of emission control measures on air quality during APEC (Asia-Pacific Economic Cooperation summit) China 2014 with the Weather Research and Forecasting coupled with Chemistry (WRF-Chem). [PERSON] et al. (2013) [23] evaluated the effect of air pollution control policies on air quality during the 16 th Asian Games with CMAQ (Community Multiscale Air Quality Model). [PERSON] et al. (2016) [24] analysed the influence of emission control policies on air quality during China's V-Day parade in 2015. Air quality numerical models (WRF-CMAQ, MM5-CMAQ, WRF-Chem, etc.) and scenario analyses were used widely to evaluate the effectiveness of policies on air quality. These studies only focused on the impact of policies on annual air quality in 2020 or on air quality during some major public events and did not investigate air quality on heavy pollution events. For heavy pollution, previous works focused on the characteristics and formation of pollution episodes. [PERSON] et al. (2009) [25] investigated the chemical characteristics of haze in Guangzhou(2002-2003, summer and winter) with PM\({}_{10}\) samples and gas chromatography-mass spectrometry (GC-MS). [PERSON] et al. (2015) [26] researched the formation process of a severe haze episode in the Yangtze River Delta (2013 winter) based on visibility and meteorological parameters, and backward trajectories of the air mass. [PERSON] et al. (2015) [27] applied WRF-Chem to simulate a severe haze in Beijing (2013 winter) and discussed the meteorological impacts on haze. [PERSON] et al. (2017) [7] analysed the spatial and temporal association of PM\({}_{2.5}\) pollution events between typical cities of PRD (2014 winter). [PERSON] et al. (2004) [28] discussed the effects of sea-land breezes on the transport of air pollution during an ozone episode in PRD (2001 autumn) with the MM5 (Fifth-Generation Mesoscale Regional Weather) model. [PERSON] et al. (2015) [29] researched the source of an ozone episode in PRD (2008 autumn) with the CAMx (Comprehensive Air-quality Model with extensions) model. [PERSON] et al. (2015) [30] investigated the chemical characteristics of ozone episodes in Shanghai (2010-2013, O\({}_{3}\) peaked in summer) with the differential optical absorption spectroscopy (DOAS) and the hybrid single particle Lagrangian integrated trajectory (HYSPLIT) model. [PERSON] et al. (2008) [31] simulated typical summertime ozone episodes in Beijing (2000) with the WRF-CAMx (Weather Research and Forecasting Model Comprehensive Air-quality Model with extensions) model to analyse the process, and [PERSON] et al. (2014) [32] used the CMAQ-MADRID (Community Multiscale Air Quality Model-Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution) model to evaluate the effects of NO\({}_{x}\) and VOCs emissions on ozone pollution in Beijing (2007 summer). According to previous studies, meteorological conditions and emission significantly affected pollution, and numerical models were widely used to analyse the characteristics of pollution. However, the model evaluation of the impact of the 13 th FYP on the air quality in 2020 during the pollution episode has not attracted much attention. The air pollution control strategy in China is now at the new stage that the manufacturing industry in megacities in China (e.g., Guangzhou) is no longer the dominant emission source; control on vehicle emissions is becoming the primary subject [33]; the control strategy is transforming from urban/regional control to district/town grid control [34]. The PRD region is one of the three national typical air pollution city clusters [2]. PRD has experienced the major problem of transferring from haze to complex (haze and photochemical) pollution. Moreover, it is the first city cluster to achieve the goal in the APCAP, i.e., compared with the levels in 2012, the concentration of fine particles (PM\({}_{2.5}\)) in Beijing-Tianjin-Hebei, the Yangtze River Delta, and the Pearl River Delta (PRD) reduced by 25%, 20%, and 15%, respectively, by 2017 [4].