The fine-scale spatial variation of mortality risk attributed to urban heat island effect in Guangzhou, China

Abstract

TPS 661: Climate change: temperature effects 1, Exhibition Hall, Ground floor, August 26, 2019, 3:00 PM - 4:30 PM Background: In the context of global warming and accelerated urbanization, the urban heat island (UHI) effect is becoming obvious, especially in large cities. From a health perspective, the UHI effect increases the risk of heat-related mortality and morbidity. However, previous studies focused on the heat-related mortality variation between different cities, and lack of directly quantified the magnitude of the UHI on mortality within a city. Methods: We first used the k-means algorithm to cluster 161 streets in Guangzhou into 105 small-areas, due to the limited number of deaths in some streets. The inverse distance weight interpolation method was used to obtain the average daily temperature in each small area from 2011 to 2017, and the distribution lag nonlinear model was applied to investigate the heat-related risk in the central small-areas (68/105). Based on the UHI intensity, attributable fraction and the number of mortalities from UHI effect in each central small-areas were calculated during high-temperature season (June-September). Results: The daily average UHI intensity (UHIi) in Guangzhou is 0.71±0.41°C (range: -0.57 to 2.26 °C). Among central small-areas, the daily average UHIi ranges from 0.10±0.26 °C to 1.13±0.34°C. During high-temperature season, the attributable fraction (AF) and attributable number (AN) of mortalities resulting from UHI were1.04% or 629 cases in the central city, with the variation of AF and AN ranging from 0.22% to 10.12% or 2 to 121 cases in different central small-areas. Conclusion: UHIi and its attributable fraction or the number of mortalities were found to be spatial variation, which make the geography-targeted UHI effect reduction strategy be important for improving public health in the climate chenage scenarios.