DataSheet1_Evaluation of Long-Term Modeling Fine Particulate Matter and Ozone in China During 2013–2019.docx

Air quality in China has been undergoing significant changes due to the implementation of extensive emission control measures since 2013. Many observational and modeling studies investigated the formation mechanisms of fine particulate matter (PM2.5) and ozone (O3) pollution in the major regions of China. To improve understanding of the driving forces for the changes in PM2.5 and O3 in China, a nationwide air quality modeling study was conducted from 2013 to 2019 using the Weather Research and Forecasting/Community Multiscale Air Quality (WRF/CMAQ) modeling system. In this study, the model predictions were evaluated using the observation data for the key pollutants including O3, sulfur dioxide (SO2), nitrogen dioxide (NO2), and PM2.5 and its major components. The evaluation mainly focused on five major regions, that is , the North China Plain (NCP), the Yangtze River Delta (YRD), the Pearl River Delta (PRD), the Chengyu Basin (CY), and the Fenwei Plain (FW). The CMAQ model successfully reproduced the air pollutants in all the regions with model performance indices meeting the suggested benchmarks. However, over-prediction of PM2.5 was noted in CY. NO2, O3, and PM2.5 were well simulated in the north compared to the south. Nitrate (NO3−) and ammonium (NH4+) were the most important PM2.5 components in heavily polluted regions. For the performance on different pollution levels, the model generally over-predicted the clean days but underpredicted the polluted days. O3 was found increasing each year, while other pollutants gradually reduced during 2013–2019 across the five regions. In all of the regions except PRD (all seasons) and YRD (spring and summer), the correlations between PM2.5 and O3 were negative during all four seasons. Low-to-medium correlations were noted between the simulated PM2.5 and NO2, while strong and positive correlations were established between PM2.5 and SO2 during all four seasons across the five regions. This study validates the ability of the CMAQ model in simulating air pollution in China over a long period and provides insights for designing effective emission control strategies across China.

自2013年起，我国空气质量因实施广泛的排放控制措施而发生显著变化。众多观测和建模研究探讨了我国主要区域细颗粒物（PM2.5）和臭氧（O3）污染的形成机制。为增进对我国PM2.5和O3变化驱动力的理解，自2013年至2019年，运用天气研究预报/社区多尺度空气质量（WRF/CMAQ）建模系统开展了一次全国空气质量建模研究。在该研究中，通过关键污染物（包括O3、二氧化硫（SO2）、二氧化氮（NO2）和PM2.5及其主要成分）的观测数据对模型预测进行了评估。评估主要针对五个主要区域，即华北平原（NCP）、长江三角洲（YRD）、珠江三角洲（PRD）、成渝盆地（CY）和汾渭平原（FW）。CMAQ模型成功再现了所有区域的空气污染物，其模型性能指标符合建议的基准。然而，在CY区域观察到PM2.5预测过度。与南部相比，北部对NO2、O3和PM2.5的模拟效果较好。在污染严重的区域，硝酸盐（NO3-）和铵盐（NH4+）是PM2.5最重要的成分。针对不同污染水平的表现，模型通常高估了清洁日数，而低估了污染日数。研究发现，O3逐年增加，而其他污染物在2013至2019年间在五个区域逐渐减少。在PRD（所有季节）和YRD（春季和夏季）以外的所有区域，PM2.5与O3在四个季节中均呈现负相关。模拟的PM2.5与NO2之间观察到低至中等的相关性，而在五个区域的所有四个季节中，PM2.5与SO2之间建立了强烈且正的相关性。本研究验证了CMAQ模型在长时间模拟我国空气污染方面的能力，并为我国设计有效的排放控制策略提供了洞见。