Mapping and statistical analysis of NO2 concentration for local government air quality regulation

Jieun Ryu, Chan Park, Seong Woo Jeon

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


With the growing interest in healthy living worldwide, there has been an increasing demand for more accurate measurements of the concentrations of air pollutants such as NO2. In particular, analyzing the characteristics and sources of air pollutants by region could improve the effectiveness of environmental policies applied in accordance with the environmental characteristics of individual regions. In this study, a detailed nationwide NO2 concentration map was generated using the cokriging interpolation technique, which integrates ground observations and satellite image data. The root-mean-square standardized (RMSS) error for this technique was close to 1, which indicates high accuracy. Using spatially interpolated NO2 concentration data, an administrative unit map was generated. When comparing the data for four NO2 data sources (observation data, satellite image data, detailed national data interpolated using cokriging, and NO2 concentrations averaged by an administrative unit based on the interpolated NO2 concentration data), the average concentrations were highest for remote sensing data. Land use regression (LUR) models of urban and non-urban regions were then developed to analyze the characteristics of the NO2 concentration by region using NO2 concentrations for the administrative units.

Original languageEnglish
Article number3809
JournalSustainability (Switzerland)
Issue number14
StatePublished - 2019


  • Cokriging
  • County level
  • Interpolation
  • Land use regression model
  • NO concentration map
  • Nitrogen dioxide
  • Satellite image
  • Urban forest


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