Mapping and Statistical Analysis of NO 2 Concentration for Local Government Air Quality Regulation

Jieun Ryu, Chan Park and Seong Woo Jeon
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Jieun Ryu: Department of Environmental Science and Ecological Engineering, Korea University, Seoul 02841, Korea
Chan Park: Department of Landscape Architecture, University of Seoul, Seoul 02504, Korea
Seong Woo Jeon: Department of Environmental Science and Ecological Engineering, Korea University, Seoul 02841, Korea

Sustainability, 2019, vol. 11, issue 14, 1-18

Abstract: 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 NO 2 . 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 NO 2 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 NO 2 concentration data, an administrative unit map was generated. When comparing the data for four NO 2 data sources (observation data, satellite image data, detailed national data interpolated using cokriging, and NO 2 concentrations averaged by an administrative unit based on the interpolated NO 2 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 NO 2 concentration by region using NO 2 concentrations for the administrative units.

Keywords: urban forest; nitrogen dioxide; interpolation; cokriging; NO 2 concentration map; satellite image; land use regression model; county level (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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