Recommendations on benchmarks for numerical air quality model applications in China – Part 2: Ozone and uncertainty analysis

Abstract. Ground-level ozone (O3) has emerged as a significant air pollutant in China, attracting increasing attention from both the scientific community and policymakers. Chemical transport models (CTMs) serve as crucial tools in addressing O3 pollution, with frequent applications in predicting O3 concentrations, identifying source contributions, and formulating effective control strategies. The accuracy and reliability of the simulated O3 concentrations are typically assessed through model performance evaluation (MPE). However, the wide array of CTMs available, variations in input data, model setups, and other factors result in a broad range of differences between simulated and observed O3 concentrations, highlighting the necessity of standardized benchmarks in O3 evaluation. Building upon our previous work, this study conducted a thorough literature review of CTM applications simulating O3 in China from 2006 to 2021. A total of 216 relevant articles out of a total of 667 reviewed were identified to extract quantitative MPE results and key model configurations. From our analysis, two sets of benchmark values for six commonly used MPE metrics are proposed for CTM applications in China, categorized into “goal” benchmarks representing optimal model performance and “criteria” benchmarks representing achievable model performance across a majority of studies. It is recommended that the normalized mean bias (NMB) for hourly O3 and daily 8 h maximum O3 concentrations should ideally fall within ±15 % and ±10 %, respectively, to meet the goal benchmark. If the criteria benchmarks are to be met, the NMB should be within ±30 % and ±20 %, respectively. Moreover, uncertainties in O3 predictions due to uncertainties in various model inputs were quantified using the decoupled direct method (DDM) in a commonly used CTM. For the simulation period of June 2021, the total uncertainty of simulated O3 ranged from 4 to 25 µg m−3, with anthropogenic volatile organic compound (AVOC) emissions contributing most to the uncertainty regarding O3 in coastal regions and with O3 boundary conditions playing a dominant role in the northwestern region. The proposed benchmarks for assessing simulated O3 concentrations, in conjunction with our previous studies on PM2.5 and other criteria air pollutants, represent a comprehensive and systematic effort to establish a model performance framework for CTM applications in China. These benchmarks aim to support the growing modeling community in China by offering a robust set of evaluation metrics and establishing a consistent evaluation methodology relative to the body of prior research, thereby helping to establish the credibility and reliability of CTM applications. These statistical benchmarks need to be periodically updated as models advance and as better inputs become available in the future.