LAUSR

Abstract As the problem of fine dust pollution becomes increasingly serious in South Korea, the country is becoming more interested in obtaining information on fine dust levels. Fine dust level data are sufficiently local to make regional forecasting meaningless. Thus, this study proposes an alternative measurement technique to minimize differences between published and perceived levels of fine dusts. Owing to the large variations in the fine dust levels within urban areas, it is very difficult to provide measurements that are sufficiently area-representative. Because infants and elementary school students are more sensitive to fine dust than adults, it is useful to construct large data sets of measurements of fine dust levels at elementary schools. In Korea, the distribution of elementary schools is consistent with population density, which is useful for analyzing local differences in the fine dust levels in urban areas. This study will provide a basis for big data application to public health policy and infographics using color fuzzy model.