Recommendations on benchmarks for chemical transport 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 (CTM) 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 simulated O₃ concentration differences from observed values, highlighting the necessity for standardized benchmarks in O₃ evaluation.

Built upon our previous work, this study conducted a thorough literature review of CTM applications simulating O₃ in China from 2006 to 2021. 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-hr 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 4–25 μg/m³, with anthropogenic volatile organic compound (AVOC) emissions contributing most to the uncertainty of O₃ in coastal regions and O₃ boundary conditions playing a dominant role in the northwest region. The proposed benchmarks for assessing simulated O₃ concentrations, in conjunction with our previous studies on PM_2.5 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 their CTM applications. These statistical benchmarks need to be periodically updated as models advance and better inputs become available in the future.