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

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.