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Evaluation of Health Impact of Heat Waves using Bio - Climatic impact Assessment System (BioCAS) at Building scale over the Seoul City Area

김규랑 1,  Lee, Ji-Sun 1,  이채연 2,  Baek-Jo Kim 1,  Britta Jänicke 1,  Achim Holtmann 3,  Dieter Scherer 3

1국립기상과학원
2차세대도시·농림융합기상사업단
3베를린공대 생태학과

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ABSTRACT

The Bio-Climatic impact Assessment System, BioCAS was utilized to produce analysis maps of daily maximum perceived temperature (PTmax) and excess mortality (rEM) over the entire Seoul area on a heat wave event. The spatial resolution was 25 m and the Aug. 5, 2012 was the selected heat event date. The analyzed results were evaluated by comparing with observed health impact data - mortality and morbidity - during heat waves in 2004-2013 and 2006-2011, respectively. They were aggregated for 25 districts in Seoul. Spatial resolution of the comparison was equalized to district to match the lower data resolution of mortality and morbidity. Spatial maximum, minimum, average, and total of PTmax and rEM were generated and correlated to the health impact data of mortality and morbidity. Correlation results show that the spatial averages of PTmax and rEM were not able to explain the observed health impact. Instead, spatial minimum and maximum of PTmax were correlated with mortality (r=0.53) and morbidity (r=0.42), respectively. Spatial maximum of PTmax, determined by building density, affected increasing morbidity at daytime by heat-related diseases such as sunstroke, whereas spatial minimum, determined by vegetation, affected decreasing mortality at nighttime by reducing heat stress. On the other hand, spatial maximum of rEM was correlated with morbidity (r=0.52) but not with mortality. It may have been affected by the limit of district-level irregularity such as difference in base-line heat vulnerability due to the age structure of the population. Areal distribution of the heat impact by local building and vegetation, such as spatial maximum and minimum, was more important than spatial mean. Such high resolution analyses are able to produce quantitative results in health impact and can also be used for economic analyses of localized urban development.

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