The　circulation　of　tropical　cyclones　(TCs)　exerts　a　multifaceted　influence　on　the　spatial　and　temporal　distribution　of　surface　pollutants.　This　study　investigates　the　response　of　surface　ozone　(O3)　concentration　to　the　TCs　in　Fujian　Province　from　June　to　December　2022　by　analyzing　the　contributions　of　atmospheric　pollutants,　meteorological　conditions,　and　dynamical　transports.　Empirical　orthogonal　function　(EOF)　decomposition　methods　are　used　to　analyze　the　spatio-temporal　distribution　patterns　of　affected　O3,　and　a　Gradient　Boosting　Regression　Trees　(GBRT)　machine　learning　model　is　employed　to　estimate　surface　O3　concentration,　quantifying　the　influence　of　each　factor.　The　results　indicate　an　anomaly　increase　in　O3　concentration　during　this　period,　with　photochemistry-related　meteorological　conditions　being　the　primary　influencer,　accounting　for　66.9%　of　O3　variations,　elucidating　the　interpretability　of　the　GBRT　model　for　attributing　changes　in　O3　concentration.　Low　relative　humidity　and　high　temperature　conditions　have　been　identified　as　pivotal　factors　influencing　the　rise　in　O3　concentrations.　The　presence　of　TC　undermines　this　predominant　influence,　amplifying　the　role　of　transport　factors　and　other　atmospheric　pollutants.　In　the　case　studies　of　TC　(Muifa　and　Nanmadol,　2022),　the　slow　or　stagnant　TCs　triggered　persistent　downdrafts　in　its　periphery　and　brought　favorable　meteorological　conditions　such　as　clear　sky　and　warm　temperature　for　photochemistry.　TCs　also　enhances　the　impact　of　horizontal　and　vertical　dynamic　transport　on　O3　concentrations.　This　work　provides　vital　insights　into　the　complex　interplay　between　TCs　and　surface　O3　concentrations,　highlighting　the　need　for　targeted　environmental　and　air　quality　management　strategies　in　regions　frequently　impacted　by　TCs.