Projection of future temperature extremes, related mortality, and adaptation due to climate and population changes in Taiwan.

BACKGROUND: Extreme temperature events have been observed to appear more frequently and with greater intensity in Taiwan in recent decades due to climate change, following the global trend. Projections of temperature extremes across different climate zones and their impacts on related mortality and adaptation have not been well studied. METHODS: We projected site-specific future temperature extremes by statistical downscaling of 8 global climate models followed by Bayesian model averaging from 2021 to 2060 across Taiwan under the representative concentration pathway (RCP) scenarios RCP2.6, RCP4.5, and RCP8.5. We then calculated the attributable mortality (AM) in 6 municipalities and in the eastern area by multiplying the city/county- and degree-specific relative risk of mortality according to the future population projections. We estimated the degree of adaptation to heat by slope reduction of the projected AM to be comparable with that in 2018. RESULTS: The annual number of hot days with mean temperatures over 30 °C was predicted to have a substantial 2- to 5-fold increase throughout the residential areas of Taiwan by the end of 2060 under RCP8.5, whereas the decrease in cold days was less substantial. The decrease in cold-related mortality below 15 °C was projected to outweigh heat-related mortality for the next two decades, and then heat-related mortality was predicted to drastically increase and cross over cold-related mortality, surpassing it from 2045 to 2055. Adjusting for future population size, the percentage increase in heat-related deaths per 100,000 people could increase by more than 10-fold under the worst scenario (RCP8.5), especially for those over 65 years old. The heat-related impacts will be most severe in southern Taiwan, which has a tropical climate. There is a very high demand for heat-adaptation prior to 2050 under all RCP scenarios. CONCLUSIONS: Spatiotemporal variations in AM in cities in different climate zones are projected in Taiwan and are expected to have a net negative effect in the near future before shifting to a net positive effect from 2045 to 2055. However, there is an overall positive and increasing trend of net effect for elderly individuals under all the emission scenarios. Active adaptation plans need to be well developed to face future challenges due to climate change, especially for the elderly population in central and southern Taiwan.

Short-term prediction of extremely hot days in summer due to climate change and ENSO and related attributable mortality.

Summer days with extremely hot temperatures in Taiwan have been increasing for the past few decades, and this continuing trend is expected to worsen heat-related mortality. To mitigate the corresponding health impacts, in this study, we developed a statistical state-space model to predict the number of extremely hot days in June-September for the next year. Based on historical data from 1951 to 2017, we estimated the climate change trend after adjusting for the nonlinear lagged effect of the Niño 3.4 index. We then developed a predictive state-space model using these two primary factors and adjusting for residual autocorrelations. Validation results comparing the extremely hot days observed over 2015-2017 with predictions showed that 86% of the average prediction errors were within 4 days of the observations. To assess the health impacts, we applied the model to the projection of heat-attributable mortality (AM) in 2018 by adopting a comparative risk assessment (CRA) approach with the reference period of 2001-2010. The results showed that the Taipei metropolitan area in northern Taiwan is the most affected region with AM of 1501 deaths from all-causes, followed by Taichung in central Taiwan with 490 deaths. The prediction model and the CRA projection provide both a tool and guidance for public health administrators to address the imminent threat posed by climate change.