Event-Based Heat-Related Risk Assessment Model for South Korea Using Maximum Perceived Temperature, Wet-Bulb Globe Temperature, and Air Temperature Data

Abstract

This study aimed to assess the heat-related risk (excess mortality rate) at six cities, namely, Seoul, Incheon, Daejeon, Gwangju, Daegu, and Busan, in South Korea using the daily maximum perceived temperature (PTmax), which is a physiology-based thermal comfort index, the wet-bulb globe temperature, which is meteorology-based thermal comfort index, and air temperature. Particularly, the applicability of PTmax was evaluated using excess mortality rate modeling. An event-based heat-related risk assessment model was employed for modeling the excess mortality rate. The performances of excess mortality rate models using those variables were evaluated for two data sets that were used (training data, 2000–2016) and not used (test data, 2017–2018) for the construction of the assessment models. Additionally, the excess mortality rate was separately modeled depending on regions and ages. PTmax is a good temperature indicator that can be used to model the excess mortality rate in South Korea. The application of PTmax in modeling the total mortality rate yields the best performances for the test data set, particularly for young people. From a forecasting perspective, PTmax is the most appropriate temperature indicator for assessing the heat-related excess mortality rate in South Korea.

Heat Stress Indicators in CMIP6: Estimating Future Trends and Exceedances of Impact‐Relevant Thresholds

“…Despite the widespread usage of HSIs, epidemiological studies considering multiple indicators (i.e., temperature and different HSIs) often find comparable predictive skills for adverse health effects with no single indicator being superior to the others (e.g., Barnett et al., 2010; Burkart et al., 2011; Heo & Bell, 2018; Kim et al., 2011; Ragettli et al., 2017; Vaneckova et al., 2011). Additionally, the indicator showing the highest impacts on mortality or morbidity rates varies across geographic locations, seasons, or age groups (Barnett et al., 2010; Chung et al., 2009; Heo et al., 2019; Kang et al., 2020; Rodopoulou et al., 2015). To date, evidence from epidemiological studies suggest that HSI perform similarly well as temperature and, thus, do not seem to be particularly more suitable for predicting adverse health effects related to heat stress (e.g., Armstrong et al., 2019; Kent et al., 2014; Vaneckova et al., 2011).…”

Heat Exposure Information at Screen Level for an Impact-Based Forecasting and Warning Service for Heat-Wave Disasters

“…In this study, it was found that the highest PT max during the day showed the best performance in expressing the thermal stress for Koreans. To use PT max , the necessity of collecting temperature, dew point temperature, relative humidity, wind speed, cloud amount, and geographical information data was presented [11]. However, at present, spatially detailed data are not available for all areas of Korea.…”

“…In 2018, the government legislated heat-waves to be a form of natural disaster and began responding at the government level. However, as the damages caused by heat-waves manifest differently depending on age, occupation, type of household, and climate [11,12], the meteorological data within downscaled spaces and conditions in terms of the population, society, economy, and environment should be considered for forecasting and responding to the impacts of heat-waves [13][14][15][16][17][18][19][20].…”

Toward sustainable cities: Monitoring thermal environment for buildings and pedestrian space using drone-captured 3D thermal imaging

“…The findings above indicate that the presence and type of shade (e.g., natural shaded grass surface vs. unshaded sand surface), the type and color of building surface material (e.g., dark green DGS glass surface material vs. white DGS glass surface material), and building design and orientation (e.g., left direction vs. right direction) have a significant impact on the thermal environment of buildings, and pedestrians' space in the context of UAEU campus during the Spring season. It also indicates that the comfort and thermal environment of outdoor pedestrians, building components, and surface materials are improved by shade, vegetation, and the structural design and position of a building (Lin and Matzarakis, 2008;Yin et al, 2022;Kang et al, 2020). However, it is crucial to keep in mind that the placement and orientation of buildings, the patterns and types of vegetation (such as grass, shrubs, and trees), variation in solar irradiance, and ambient conditions altogether affect the thermal comfort of occupants as well as the load profile of buildings.…”