Mapping and Statistical Analysis of NO₂ Concentration for Local Government Air Quality Regulation

• Main Authors: Jieun Ryu, Chan Park, Seong Woo Jeon
• Format: Article
• Language: English
• Published: MDPI AG 2019-07-01
• Series: Sustainability
• Subjects: urban forest; nitrogen dioxide; interpolation; cokriging; NO₂ concentration map; satellite image; land use regression model; county level
• Online Access: https://www.mdpi.com/2071-1050/11/14/3809

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.