Analysis of Potential Factors Influencing Ground-Level Ozone Concentrations in Chinese Cities

  • Pengfei Liu
  • Hongliang Li
  • Ziyun Jing
  • Hongquan Song
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1228)


Based on Geodetector model, this study adopted the 2016 O3 concentration data, meteorological factor data and anthropogenic emissions data to explore the driving factors of urban O3 concentrations in China. The results show that: in general, meteorological factors dominate the urban ozone concentration in China, but there are some differences in the driving factors of ozone concentration at different scales. From the national scale, sunshine duration and temperature are the most significant driving factors, among which temperature is the most critical, while relative humidity and temperature have prominent interactions. From the seasonal perspective, the dominant factors for O3 pollution in spring and winter are the duration of sunshine, the relative humidity in summer, and the temperature in autumn. In addition, the main interaction in spring, autumn and winter is the interaction between sunshine duration and temperature, while in summer it is air pressure and relative humidity. From the perspective of the zoning, the O3 pollution in South China is dominated by the duration of sunshine, and the other regions are dominated by temperature. In terms of factor interaction, the strongest interactions in Central China, Northeast China, and Southwest China are combined with relative humidity and temperature. East China, North China, and Northwest China are the duration and temperature of sunshine, while South China is the duration of sunshine and wind speed. From the seasonal influence of different zones, the influencing factors of O3 concentration changes in each region in different seasons are very different. The influence of evaluation factors on this scale is generally not obvious, and the driving factors and interactions are complicated.


O3 concentration Geodetector model Meteorological condition Anthropogenic emissions precursors Chinese cities 



This study was financially supported by the National Science Foundation of China (41401107) and Henan Basic Frontier and Technology Research Project (162300410132) and 2017 Key Research Project of Henan Province Higher Education (17B170003).


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Pengfei Liu
    • 1
    • 3
  • Hongliang Li
    • 2
    • 3
    • 4
  • Ziyun Jing
    • 1
  • Hongquan Song
    • 2
    • 3
    • 4
  1. 1.Key Research Institute of Yellow River Civilization and Sustainable Development, Ministry of EducationHenan UniversityKaifengChina
  2. 2.Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions, Ministry of EducationHenan UniversityKaifengChina
  3. 3.Institute of Urban Big Data, College of Environment and PlanningHenan UniversityKaifengChina
  4. 4.Henan Key Laboratory of Integrated Air Pollution Control and Ecological SecurityHenan UniversityKaifengChina

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