Compound heat events, encompassing compound hot and dry events (CHDEs) and compound hot and wet events (CHWEs), pose substantial health risks due to their increasing frequency and intensity. CHDEs, characterized by consecutive hot days without precipitation, increase water and energy demands, worsen urban air quality, and elevate risks of heat-related illnesses. CHWEs exacerbate heat stress due to high humidity, promoting mold growth and increasing vector-borne disease risks. Traditional health risk assessments often focus solely on temperature, neglecting the crucial role of relative humidity (RH). This study addresses this gap by integrating ambulance dispatch data with temperature and RH data to assess human impacts on high health-risk compound events in China, projecting future changes under different emission scenarios.

Previous research has documented increases in CHDEs and CHWEs globally, including in China, attributing these increases to anthropogenic activities like greenhouse gas emissions, urbanization, and industrialization. Studies often compare observed climate data with climate model simulations (with and without anthropogenic forcing) to assess the human contribution to extreme events using metrics such as probability ratio (PR) and fraction of attributable risk (FAR). While these methods have successfully analyzed temperature extremes, their application to compound heat events, especially with integrated health data, has been limited. This study bridges this gap by incorporating health data to better understand the human impact on high health-risk compound heat events.

This study uses daily ambulance dispatch data from 13 Chinese cities (2013-2019) as a proxy for health impacts, combined with ERA5 reanalysis data (1979-2022) for temperature and relative humidity. High health-risk thresholds for CHDEs and CHWEs were defined based on the 80th and 90th percentiles of temperature, respectively, coupled with corresponding percentiles of relative humidity (10th and 55th, respectively) identified via regression analysis relating ambulance dispatches to temperature and humidity conditions. The relative risk (RR) of ambulance dispatches under different temperature and humidity combinations was calculated. The study uses CMIP6 data from 10 climate models to simulate the frequency of CHDEs and CHWEs under all forcings (ALL) and natural forcings only (NAT). The anthropogenic impact was quantified using PR and FAR, comparing ALL and NAT simulations with observations. Future projections (2021-2100) were made using SSP-1-1.9 (low emissions), SSP-2-4.5 (intermediate emissions), and SSP-5-8.5 (high emissions) scenarios.

Analysis of the 1979-2014 period revealed distinct geographical patterns in high health-risk CHDEs and CHWEs. High health-risk CHDEs were most frequent in Northwest China and the middle-lower Yangtze River region, while CHWEs were more prevalent on the Qinghai-Tibet Plateau and in Northeast China. These high-incidence areas overlapped with regions experiencing rapid growth. Human activities significantly increased the frequency of high health-risk CHDEs by a factor of 2.34 (PR = 2.34, FAR = 0.43) and decreased the frequency of high health-risk CHWEs by a factor of 0.63 (PR = 0.63, FAR = -0.60) nationwide. Regional variations were observed, with increases in CHDEs in Northwest China and decreases in CHWEs in Southwest China. Future projections under the carbon-neutral SSP-1-1.9 scenario showed a reduction in high health-risk CHDEs and CHWEs compared to the high emissions SSP-5-8.5 scenario by about half and one-fifth, respectively, by 2060. However, even under the carbon-neutral scenario, an increase in the number of high health-risk CHDE and CHWE days is projected compared to the past climate.

This study's findings highlight the significant influence of human activities on the frequency and distribution of high health-risk CHDEs and CHWEs in China. The contrasting impacts on CHDEs and CHWEs emphasize the need to consider both temperature and humidity in assessments of heat-related health risks. The results are consistent with previous research on the impact of anthropogenic climate change on extreme weather events. The use of ambulance dispatch data provides a novel and timely approach to assess the health consequences of compound heat events. The future projections underscore the importance of mitigating greenhouse gas emissions to reduce the health burden from compound heat extremes. The regional variations suggest the need for tailored adaptation strategies based on specific climatic and geographic conditions.

This research demonstrates the substantial influence of human activities on high health-risk compound heat events in China. It reveals a contrasting pattern: anthropogenic activities increase hot-dry events while decreasing hot-wet events. The study emphasizes the importance of considering both temperature and humidity when evaluating health risks associated with compound events. Future research should focus on refining regional health-risk thresholds, expanding the analysis to other geographical areas, and investigating the socioeconomic factors that modulate heat-related health impacts.

The study uses ambulance dispatch data as a proxy for health impacts, which may not fully capture the spectrum of heat-related illnesses. The analysis is limited to 13 cities in China, limiting generalizability to other regions or countries. The future projections rely on climate model simulations, which have inherent uncertainties. The study focuses on a specific definition of high health-risk compound events; different thresholds might yield different results. Finally, the SSP-2-4.5nat scenario is the only one available that includes only natural forcings, which limits the comparison of human influence across a wider range of scenarios.