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Quantification of the nonlinearities between ambient ozone(O3)and the emissions of nitrogen oxides(NOx)and volatile organic compound(VOC)is a prerequisite for an effective O3 control strategy.An Enhanced polynomial functions Response Surface Model(Epf-RSM)with the capability to analyze O3-NOx-VOC sensitivities in real time was developed by integrating the hill-climbing adaptive method into the optimized Extended Response Surface Model(ERSM)system.The Epf-RSM could single out the best suited polynomial function for each grid cell to quantify the responses of O3 concentrations to precursor emission changes.Several comparisons between Epf-RSM and pf-ERSM(polynomial functions based ERSM)were performed using out-of-sample validation,together with comparisons of the spatial distribution and the Empirical Kinetic Modeling Approach diagrams.The comparison results showed that Epf-RSM effectively addressed the drawbacks of pf-ERSM with respect to over-fitting in the margin areas and high biases in the transition areas.The O3 concentrations predicted by Epf-RSM agreed well with Community Multi-scale Air Quality simulation results.The case study results in the Pearl River Delta and the north-western area of the Shandong province indicated that the O3 formations in the central areas of both the regions were more sensitive to anthropogenic VOC in January,April,and October,while more NOx-sensitive in July.