## 4 Results
### The Spatiotemporal Patterns of the Exceedances of the Estimated MDA8  
Figure 5 illustrates the spatiotemporal distribution of the MDA8 exceedances as well as the month in which the highest number of MDA8 exceedances occurred. Figure 5a-c revealed the annual cumulative distribution of MDA8 exceedances (MDA8 > 160 \(\upmu\)g m\({}^{-3}\)) in the NCP from 2019 to 2021. The annual analysis of ozone pollution reflected in the cumulative count of MDA8 exceedances showed that the overall ozone pollution levels in the region have declined year by year from 2019 to 2021. Notably, from 2019 to 2020, the severity of ozone pollution and its spatial coverage decreased significantly. This reduction may be attributed to the lockdown measures implemented in response to the COVID-19 pandemic during the first half of 2020, which led to a decrease in the intensity of human activities including transportation and industrial operations in the region [53; 54]. Consequently, there was a reduction in the emissions of substances that contribute to the formation of ozone pollution. This decrease in precursor emissions played a pivotal role in mitigating the intensity of ozone pollution within the NCP. Moreover, the severity and spatial coverage of ozone pollution in Beijing, Tianjin, and Hebei were found to have been further reduced in 2021 compared to 2020. This could be linked to the resurgence of the pandemic in 2021 [55] as well as the persistent efforts by the government to advance collaborative management and emission reduction policies for PM\({}_{2.5}\) and O\({}_{3}\) pollution. These policies include strengthening emission controls in industrial and transportation sectors and promoting the use of clean energy [30]. During the period spanning from 2019 to 2020, the Xiongan New Area emerged as the locality within the NCP that was predominantly affected by the highest levels of ozone pollution. This high level of pollution may be associated with the intensive urban construction and human activities that took place in the area during that period [56; 57; 58; 59; 60]. Figure 4: Spatial distribution of the seasonal averaged and annual averaged MDA8 concentration in the 2019–2021 period. (**a–d**) indicate the MDA8 in spring, summer, autumn, and winter, respectively. (**e–g**) indicate the annual averaged MDA8 in 2019, 2020, and 2021. Figure 5d-f reveals the spatial distribution of the MDA8 exceedances for the months from 2019 to 2021 in the NCP. It was observed that from 2019 to 2021, the majority of months with the highest frequency of ozone pollution in the region were concentrated in June. Therefore, the month of June was predominantly identified as the period with the greatest number of ozone content exceedances in the NCP, primarily associated with the prevalence of high temperatures, intense ultraviolet radiation, and scant rainfall in most areas of Beijing, Tianjin, and Hebei during this month [46; 47; 48; 61; 62]. Additionally, the peak levels of ozone pollution along the coastal regions of Hebei, Tianjin, and Shandong in 2019 and 2021 were noted to occur in May. This may be correlated with the climatic conditions specific to these coastal areas. In contrast, the highest levels of ozone pollution in these coastal regions in 2020 appeared in July, potentially due to reduced precipitation, elevated temperatures, and robust ultraviolet radiation in the region during that month [62]. In particular, the month characterized by excessive ozone pollution in the southern region of Tianjin during 2019 and 2021 predominantly occurred in July. This occurrence may have been precipitated by reduced rainfall during this month [62] (Figure S1). In both 2019 and 2021, the most severe ozone pollution zones in Hebei Province and northern Beijing were observed in May. This could also be linked to the levels of ultraviolet radiation and precipitation in these areas [46; 62]. Overall, the prevalence of excessive ozone pollution in the NCP was primarily noted during the summer months, aligning with findings from previous research.