Yu Li1,2, Miaomiao Cheng This email address is being protected from spambots. You need JavaScript enabled to view it.2, Zheng Guo3, Youjiang He2, Xiuying Zhang4,5, Ximin Cui This email address is being protected from spambots. You need JavaScript enabled to view it.1, Shenghai Chen6


College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China
State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
Division of Remote Sensing Data Application, National Satellite Meteorological Centre, Beijing 100081, China
International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing 210023, China
State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China


Received: November 21, 2019
Revised: April 10, 2020
Accepted: April 22, 2020

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

Download Citation: ||https://doi.org/10.4209/aaqr.2019.11.0603

Cite this article:

Li, Y., Cheng, M., Guo, Z., He, Y., Zhang, X., Cui, X. and Chen, S. (2020). Increase in Surface Ozone over Beijing-Tianjin-Hebei and the Surrounding Areas of China Inferred from Satellite Retrievals, 2005-2018. Aerosol Air Qual. Res. 20: 2170–2184. https://doi.org/10.4209/aaqr.2019.11.0603


  • The long term SOC was retrieved based on satellite data and GWR model.
  • The highest and lowest SOCs occurred in the southeast and northeast, respectively.
  • The growth of the SOC in cold season had a key contribution for annual growth.
  • The SOC increased faster since 2012 because of the rapid decrease of NO2.


This study analyzed the increase in the surface ozone over Beijing-Tianjin-Hebei (BTH) and its surrounding areas during the period of 2005–2018 using satellite-retrieved data. First, a geographically weighted regression (GWR) model was developed to estimate the surface ozone concentration (SOC) between 2005 and 2018 based on Ozone Monitoring Instrument (OMI) ozone profiles. The resultant values and their growth rate were then analyzed. The SOC exhibited significant variation in the spatial distribution over the study area, with the maximum and the minimum values occurring in the southeast and the northeast, respectively. The latter region also displayed the highest SOC growth rate, however, whereas the southwest displayed the lowest one. Additionally, prominent seasonality was observed in the SOC: The concentration peaked during the warm season and troughed during the cold season, but the growth rate showed the opposite trend. The values during the cold season greatly affected the annual spatial distribution and the growth rate of the SOC, whereas those during the warm season significantly contributed to the annual concentration. From 2005 till 2018, the SOC showed an upward trend with an average growth rate of 3.4 µg m3 y1, with a greater increase in the second half (2012–2018) than the first half (2005–2011) of the study period because of the stronger photochemical reactions caused by the continual increase in HCHO during summer and the weaker NO titration effect caused by the rapid decrease in NO2 during winter. With constantly rising levels of HCHO and a VOCs-limited regime in the study area, we must formulate an effective reduction scheme for VOCs and NO2 co-emissions in order to mitigate the surface ozone pollution, despite the risk that decreasing the NO2 will lead to a certain increase in the SOC.

Keywords: OMI ozone profile; Geographically weighted regression model; Surface ozone concentration; Spatio-temporal distribution; Beijing-Tianjin-Hebei and the surrounding areas.

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