Xiaoyan Wang

Xiaoyan Wang

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article


Xiaoyan Wang has a total of 19 co-authors. Here are the top co-authors by number of shared publications:

  • Bing Liu

    China Natl Environm Monitoring Ctr, Beijing, Peoples R China

    1 shared publication
  • Dongjie Shang

    State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Research Center for Atmospheric Research (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing, China

    1 shared publication
  • Huihui Zheng

    China National Environmental Monitoring Centre, No.8-2 Anwai Dayangfang, Chaoyang District, Beijing 100012, China

    1 shared publication
  • Jiaqi Sun

    China National Environmental Monitoring Centre, Beijing 100012, China

    1 shared publication
  • Lili Zhu

    Aerospace Information Research Institute, Chinese Academy of Sciences, No.9 Dengzhuang South Road, Haidian District, Beijing 100094, China

    1 shared publication
  • Limin Zeng

    State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China

    1 shared publication

Latest Publications

  • Open Access

    Comparative Study of O3 Forecast Performance Using Multiple Models in Beijing–Tianjin–Hebei and Surrounding Regions

    by Lili Zhu, Wei Wang, Huihui Zheng, Xiaoyan Wang, Yonghai Huang, Bing Liu

    In order to systematically understand the operational forecast performance of current numerical, statistical, and ensemble models for O3 in Beijing–Tianjin–Hebei and surrounding regions, a comprehensive evaluation was conducted for the 30 model sets regarding O3 forecasts in June–July 2023. The evaluation parameters for O3 forecasts in the next 1–3 days were found to be more reasonable and practically meaningful than those for longer lead times. When the daily maximum 8 h average concentration of O3 was below 100 μg/m3 or above 200 μg/m3, a significant decrease in the percentage of accurate models was observed. As the number of polluted days in cities increased, the overall percentage of accurate models exhibited a decreasing trend. Statistical models demonstrated better overall performance in terms of metrics such as root mean square error, standard mean bias, and correlation coefficient compared to numerical and ensemble models. Numerical models exhibited significant performance variations, with the best-performing numerical model reaching a level comparable to that of statistical models. This finding suggests that the continuous tuning of operational numerical models has a more pronounced practical effect. Although the best statistical model had higher accuracy than numerical and ensemble models, it showed a significant overestimation when O3 concentrations were low and a significant underestimation when concentrations were high. In particular, the underestimation rate for heavy polluted days was significantly higher than that for numerical and ensemble models. This implies that statistical models may be more prone to missing high-concentration O3 pollution events.


  • Open Access

    Spatial Inhomogeneity of New Particle Formation in the Urban and Mountainous Atmospheres of the North China Plain during the 2022 Winter Olympics

    by Dongjie Shang, Min Hu, Xiaoyan Wang, Lizi Tang, Petri S. Clusius, Yanting Qiu, Xuena Yu, Zheng Chen, Zirui Zhang, Jiaqi Sun, et al.

    The new particle formation (NPF) process is a significant source of atmospheric secondary particles, which has remarkable impacts on the regional air quality and global radiative forcing. Most NPF studies conduct their measurements at a single site, which can hardly provide information about the regionality of NPF events at large scales (>100 km). During the 2022 Winter Olympic and Paralympic Games, simultaneous measurements of particle number size distributions and NPF-associated precursors were conducted at a mountainous site close to the Winter Olympic Village in Chongli (CL), Zhangjiakou, and an urban site in Beijing (BJ) located 150 km southeast of the CL site. High NPF frequencies were observed at the CL (50%) and BJ (52%) sites; however, the fraction of concurrent NPF events was smaller than the results in other regions. In addition, the wind distributions exhibited distinct air mass origins at the two sites during the concurrent NPF events. Compared with the BJ site, the NPF growth rates were higher at the CL site due to higher levels of volatile organic compounds (VOCs) and radiation. Surprisingly, the formation rates at the CL site were lower than at the BJ site, even with a higher sulfuric acid concentration and lower CS, which may be attributed to lower dimethylamine concentrations in the mountainous area. This study reveals that, although NPF events are commonly thought to occur on regional scales, their intensity and mechanisms may have significant spatial inhomogeneity. Further studies are required to reduce the uncertainty when expanding the mechanisms based on the urban conditions to regional or global scales in the models.