Quantification of the nonlinearities between ambient ozone (O₃) and the emissions of nitrogen oxides (NO_x) 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-NO_x-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 NO_x-sensitive in July.

量化环境臭氧（O ₃）与氮氧化物（NO _x）和挥发性有机化合物（VOC）排放之间的非线性是有效控制O ₃的先决条件。通过将爬山自适应方法集成到优化的扩展响应表面模型（ERSM）系统中，开发了具有实时分析O ₃ -NO _x -VOC敏感性的增强型多项式函数响应表面模型（Epf-RSM）。Epf-RSM可以为每个网格单元选择最适合的多项式函数，以量化O ₃的响应前驱体排放的浓度变化。使用样本外验证对Epf-RSM和pf-ERSM（基于多项式函数的ERSM）进行了几次比较，并比较了空间分布和经验动力学建模方法图。比较结果表明，Epf-RSM有效地解决了pf-ERSM在边缘区域的过度拟合和过渡区域的高偏差方面的弊端。Epf-RSM预测的O ₃浓度与社区多尺度空气质量模拟结果非常吻合。在珠江三角洲和山东省西北地区的案例研究结果表明，O ₃在这两个区域的中心区域的形成是在一月，四月，十月人为VOC更敏感，而更多的NO _X在七月敏感的。