Abstract: We examined the spatial-temporal evolution of O₃ across 237 cities in the east of the Hu Huanyong Line. The socio-economic data, air pollutant (PM_2.5, SO₂, NO₂) and O₃ concentration data during the period of 2015-2020 were analyzed using the spatial autocorrelation method. The spillover effects of influencing factors were examined by employing the spatial Durbin model. The results showed that: (1) O₃ pollution demonstrated an “M-shaped” fluctuation tendency. The spatial distribution of O₃ presented positive associations and characteristics of significant spatial agglomeration. High-value areas of O₃ dominated in the Beijing-Tianjin-Hebei, Central Plains, and Shandong Peninsula. (2) The direct effect of the influencing factors was ranked as follows: per capita GDP > PM_2.5 concentration > proportion of the tertiary industry > proportion of the secondary industry > SO₂ concentration > NO₂ concentration. There was no significant direct effect of industrial SO₂ emissions and highway freight traffic on O₃. The intensities of the indirect driving factors’ effect were as follows: per capita GDP > proportion of the tertiary industry > proportion of the secondary industry > PM_2.5 concentration. The PM_2.5 concentration, the proportion of the secondary, and the tertiary industry exerted positive impacts on O₃, while per capita GDP was the opposite. The effects of SO₂ concentration, NO₂ concentration, highway freight traffic, and industrial SO₂ emissions on O₃ were not significant. This study reveals the complexity of regional O₃ pollution, and emphasizes the importance of regional joint prevention and control of atmospheric O₃ pollution from the perspective of social and economic linkages, providing a reference for inter-regional collaborative pollution control.

Key words: O₃, Hu Huanyong Line, spatial Dubin model, influencing factor, spatial-temporal evolution