Nonmethane volatile organic compounds (NMVOCs) are important precursors of ozone (O₃) formation under sufficient nitrogen oxide conditions. Understanding the characteristics and emission sources of NMVOCs, as well as the relationship between NMVOCs and O₃, is of great significance for effective O₃ pollution control. In this study, continuous online monitoring of NMVOCs was carried out in Zhengzhou, Henan, from 1–30 June. Furthermore, the study provided recommendations for strategies aimed at reducing O₃ formation. During the observation period, the concentration of total NMVOCs (TNMVOCs) varied from 9.9 to 60.3 ppbv, with an average of 22.8 ± 8.3 ppbv. The average concentration of TNMVOCs during O₃ pollution events was higher than on clean days. Six major sources of NMVOCs were identified using the positive-matrix-factorization model. Vehicular exhausts (28 %), solvent usage (27 %), and industrial production (22 %) were the main sources. We explore the O₃–precursors relationship and propose observation-oriented O₃ control strategies. The results of the relative incremental reactivity (RIR) and the Empirical Kinetics Modeling Approach show that Zhengzhou was under an anthropogenic volatile organic compound (AVOC)-limited regime. NMVOCs had the largest RIR value, while NO_x exhibited a negative RIR value. It is noteworthy that the sensitivity of O₃ formation to biogenic volatile organic compounds (BVOCs) was greater than that to AVOCs. Considering the reduction effect, it is recommended that the ratio of AVOCs to NO_x be maintained at no less than 3:1 to effectively reduce O₃ formation.

Ground-level ozone (O₃) pollution has become a serious environmental issue in major urban agglomerations in China. To investigate the spatiotemporal patterns and regional transports of O₃ in Beijing–Tianjin–Hebei (BTH-UA), the Yangtze River Delta (YRD-UA), the Triangle of Central China (TC-UA), Chengdu–Chongqing (CY-UA), and the Pearl River Delta urban agglomeration (PRD-UA), multiple transdisciplinary methods were employed to analyze the O₃-concentration data that were collected from national air quality monitoring networks operated by the China National Environmental Monitoring Center (CNEMC). It was found that although ozone concentrations have decreased in recent years, ozone pollution is still a serious issue in China. O₃ exhibited different spatiotemporal patterns in the five urban agglomerations. In terms of monthly variations, O₃ had a unimodal structure in BTH-UA but a bimodal structure in the other urban agglomerations. The maximum O₃ concentration was in autumn in PRD-UA, but in summer in the other urban agglomerations. In spatial distribution, the main distribution of O₃ concentration was aligned in northeast–southwest direction for BTH-UA and CY-UA, but in northwest–southeast direction for YRD-UA, TC-UA, and PRD-UA. O₃ concentrations exhibited positive spatial autocorrelations in BTH-UA, YRD-UA, and TC-UA, but negative spatial autocorrelations in CY-UA and PRD-UA. Variations in O₃ concentration were more affected by weather fluctuations in coastal cities while the variations were more affected by seasonal changes in inland cities. O₃ transport in the center cities of the five urban agglomerations was examined by backward trajectory and potential source analyses. Local areas mainly contributed to the O₃ concentrations in the five cities, but regional transport also played a significant role. Our findings suggest joint efforts across cities and regions will be necessary to reduce O₃ pollution in major urban agglomerations in China.

Large emission reductions of anthropogenic nitrogen oxides (NO_x) due to the coronavirus disease 2019 (COVID‐19) lockdown policies in China have been extensively reported since the outbreak, while assessments of sectoral emission changes during that period are still limited. In this study, a source‐oriented community multiscale air quality (CMAQ) model was applied to quantify NO₂ concentrations from major emission sectors. A new optimization approach was employed to obtain the sectorial emission reductions using satellite and ground‐level observations as constraints. The optimized emissions significantly improved the model performance of NO₂ during the lockdown period. February NO_x emission changes varied with regions and sectors, with relatively larger reductions in transportation (286.6 kt) and industrial sources (260.1 kt). The maximum amount of NO_x emission reduction occurred in the North China Plain (230.6 kt). Our work presents a quick and reliable technique for assessing sector‐specific emission changes due to short‐term emission control policies.