Determination of the Spatial Distribution of Air Pollutants in Bucheon, Republic of Korea, in Winter Using a GIS-Based Mobile Laboratory

Abstract

Driven by industrialization and urbanization, urban air pollution can increase respiratory, heart, and cerebrovascular diseases, and thus mortality rates; as such, it is necessary to improve air quality through the consideration of individual pollutants and emission sources. In Republic of Korea, national and local governments have installed urban and roadside air quality monitoring systems. However, stations are lacking outside metropolitan regions, and roadside stations are sparsely distributed, limiting comparisons of pollutant concentrations with vehicle traffic and floating population levels. Local governments have begun using mobile laboratories (MLs) to supplement the fixed measurement network and investigate road pollution source characteristics based on their spatiotemporal distribution; however, the collected data cannot be used effectively if they are not visualized. Here, we propose a method to collect and visualize global information system (GIS)-based air quality data overlayed with environmental variables to support air quality management measures. Spatiotemporal analyses of ML-derived data from Bucheon, Korea, confirmed that particulate and gaseous pollutant concentrations were high during typical commuting hours, at intersections, and at a specially managed road. During commuting hours, the maximum PM10 concentration reached 200.7 µg/m3 in the Nae-dong, Gyeongin-ro, and Ojeong-dong ready-mix concrete complex areas, and the maximum PM2.5 concentration was 161.7 µg/m3. The maximum NOx, NO2, and NO levels of 1.34 ppm, 0.18 ppm, and 1.18 ppm, respectively, were also detected during commuting hours. These findings support the need for targeted management of air pollution in this region, and highlight the benefit of comprehensively comparing road levels, driving speed, and traffic levels when identifying hotspots of air pollution. Such analyses will contribute to the development of air quality management measures customized to regional characteristics.

Keywords

• air pollution
• geographic information system
• hotspot analysis
• mobile laboratory
• spatial distribution characteristics