目前，我国近地面臭氧浓度正在急剧上升，臭氧污染频现，高浓度臭氧将引发一系列的呼吸系统和心脑血管疾病，对公众健康造成巨大威胁，同时也将导致农作物的减产。臭氧生成机制与挥发性有机化合物（VOCs）和氮氧化物（NO_x）间的相对比例密切相关，不同的VOCs/NO_x代表着多种臭氧生成机制，具体包括VOCs控制型、VOCs-NO_x协同控制型以及NO_x控制型，通过确定VOCs-NO_x协同控制型的范围，可有效区分三种不同的臭氧生成机制。

在本研究中，本研究将VOCs-NO_x协同控制型区间的左右边界定义为臭氧生成机制的关键阈值，由于臭氧前体物众多，且前体物间的化学反应复杂，目前我国的臭氧生成机制的关键阈值尚不明晰。既往研究通常采用单一模型估算臭氧生成机制的关键阈值，由于缺乏验证数据，研究结论具有较大的不确定性。为提升结果的可信度，本研究拟采用甲醛（HCHO）/二氧化氮（NO₂）近似代替VOCs/NO_x，基于近地面臭氧浓度站点观测数据和臭氧前体物浓度卫星观测数据，分别应用多项式拟合模型和因果分析模型，确定我国臭氧生成机制的关键阈值。多项式拟合模型和因果分析模型所得的VOCs-NO_x协同控制型范围分别为[1.0, 1.9]和[0.9, 1.9]，因为以上两大模型的计算结果非常接近，所以本研究所得结论可信度较高。

自2013年开始，HCHO和NO₂分别呈现上升和下降趋势，导致了HCHO/NO₂的升高，标志着我国的臭氧生成机制主要为VOCs-NO_x协同控制型和NO_x控制型，因果分析模型的结果同样表明NO_x浓度对于近地面臭氧浓度的影响大于VOCs。同时，考虑到VOCs浓度在任何臭氧生成机制内均与近地面臭氧浓度呈正相关，近年来持续增高的VOCs浓度可能为臭氧浓度急剧上升的诱因之一，为更有效地控制近地面臭氧浓度，需要同时针对VOCs和NO_x进行协同减排。此外，本研究深入探究了我国城乡臭氧生成机制的差异，基于臭氧前体物卫星数据的统计结果反映出我国各大城市群的城市地区HCHO/NO₂平均值均低于乡村地区，该现象可归因于城市地区的汽车尾气排放、工业排放普遍高于乡村地区，因此城区具有更高的NO_x浓度，乡村地区更高的HCHO/NO₂表明在该区域进行NO_x减排，相较于城区，将更有效控制近地面臭氧浓度。

Nowadays, the near-surface ozone concentration has increased significantly, and ozone pollution episodes occurred frequently. High-ozone events would lead to a series of respiratory and cardiovascular diseases, which pose a great threat to public health and contribute to crop loss. Ozone formation regimes are closely related to the ratio of VOCs to NO_x. Different ranges of VOCs/NO_x indicate three formation regimes, including VOCs-limited, transitional and NO_x-limited regimes. Through determining the range of transitional regime, the above-mentioned ozone formation regimes could be effectively distinguished.

In this research, the left and right boundaries of transitional regime were defined as the critical threshold values of ozone formation regime. Due to the unstable interactions between a diversity of precursors, the critical threshold values of ozone formation regimes remain unclear. Previous studies usually employed single model to estimate the key values of ozone formation regime. To overcome the uncertainties from single model and the lack of reference data, we used both polynomial simulation and causality model to identify the ranges of transitional regime based on surface ozone network data and ozone precursors satellite data. HCHO/NO₂ was employed as a proxy of VOCs/NO_x. The ranges of transitional regime estimated by polynomial simulation and causality model were [1.0, 1.9] and [0.9, 1.9], the close output from two different models provides a reliable reference for better understanding ozone formation regimes.

Since 2013, an upward trend of HCHO and a downward trend of NO₂ were detected, which lead to the increases of HCHO/NO₂. This fact indicates that ozone formation regime has changed to the transitional and NO_x-limited regimes all over China. The causality model also suggests that NO_x was the dominant factor for surface ozone concentrations. However, VOCs concentrations continuously exert a positive influence on surface ozone concentrations under transitional and NO_x-limited regimes. Under the circumstance of national NO_x-reduction policies, the increases of VOCs become the major driver for the soaring ozone pollution across China. For an effective management of ozone pollution across China, the emission-reduction of VOCs and NO_x should be equally considered. Meanwhile, due to the large differences in vehicle and industrial emissions, the concentration of NO_x is notably higher in urban areas. Therefore, the further reduction of NO_x emissions exerts a stronger influence on ozone reduction in rural areas compared to urban areas.