Humidity is a significant factor contributing to heat stress, but without enough consideration in studies of quantifying heat hazard or heat risk assessment. Here, the simplified wet-bulb globe temperature (WBGT) considering joint effects of temperature and humidity was utilized as a heat index and the number of annual total heat wave days (HWDs) was employed to quantify heat hazard. In order to evaluate the humidity effects on heat waves, we quantified the difference in the number of HWDs over global land based on air temperature and WBGT. Spatial and temporal changes in surface air temperature, relative humidity, WBGT, and the difference in HWDs were analyzed using multi-model simulations for the reference period (1986–2005) and different greenhouse gas emission scenarios. Our analysis suggests that annual mean WBGT has been increasing since 1986, which is consistent with the rising trend in surface air temperature despite a slight decrease in relative humidity. Additionally, changes in annual mean WBGT are smaller and more spatially uniform than those in annual mean air temperature as a cancelation effect between temperature and water vapor. Results show that there is an underestimation of around 40–140 days in the number of HWDs per year in most regions within 15° latitude of the equator (the humid and warm tropics) during 2076–2095 without considering humidity effects. However, the estimation of HWDs has limited distinction between using WBGT and temperature alone in arid or cold regions.

Wet bulb globe temperature (WBGT), a combined measure of temperature and humidity effects on thermal comfort, is used to define heat stress waves (HSWs). While emerging research has raised concerns on future changes in heat stress, for the first time, this study examines spatiotemporal changes in multiple HSW characteristics (intensity, duration, frequency, and cumulative mean intensity) in the 21st century under three emissions scenarios. It is the sustained nature of HSWs that impose more adverse impacts than extreme heat on a single day. HSWs are expected to be more intense, persistent, frequent, and influential due to anthropogenic influence. Models project the largest increases in multiple HSW characteristics will occur over the tropics and subtropics. The exception is maximum intensity, which displays a relative uniform increase over most global land areas. Analysis of regional population exposure to HSWs under different climate and socioeconomic scenarios emphasizes the importance of aggressive mitigation to minimize the potential impacts of HSWs. We further investigate how different regional HSW characteristics are projected to change relative to increasing global mean surface temperature (GMST). Our results confirm the varying rates and different trajectories at which regional HSWs change, independent of forcing pathway, strongly related to GMST. On both globally aggregated and regional scales, the maximum intensity and GMST are highly linearly associated, with an approximately 1:1 increase. However, the other three HSW characteristics are projected to change at a nonlinear rate per degree of GMST increase in general and display large regional variation in the rates of their changes.

Climate change leads to heat‐related changes in labor productivity, which have additional economic impacts. Based on a framework that considers the impacts evolving from climate change to labor productivity to economic impact, we estimate the changes in labor productivity for indoor and outdoor activities and different work intensities at the grid level in China under a wide range of climatic and socioeconomic conditions and then evaluate the economic impacts in seven regions and eight sectors. The results show that (a) the negative impacts of labor productivity are concentrated in outdoor sectors, and the labor productivity of indoor sectors will decrease slightly or even increase due to high air‐conditioning device penetration rates under relatively optimistic scenarios. (b) The national results show that total economic impacts increase by 0.28%–0.61% of the GDP for each 1°C rise in the temperature, and the total economic impacts of labor productivity reductions in the most pessimistic scenario reach 1.15%–2.67% of the GDP in 2100. (c) The regional results indicate that the regions with lower labor productivity impacts (Northwest and Northeast China) still suffer large economic impacts, highlighting the importance of economic impact assessments across the regions. (b) The sectors in the seven regions of China that are most sensitive to climate change are agriculture and construction. The economic impacts in the manufacturing and service sectors, which contribute 22%–35% and 11%–15% of regional GDP losses, respectively, cannot be ignored, and should receive more attention in climate mitigation policies.

Solomon Hsiang's study, which was recently published in Science, has caused extensive discussion by indicating that future climate change may exert influences on the agricultural yield, labor supply, and energy demand, among others of the United States. Based on the above study, we use an optimized input‐output model to evaluate the economic ripple effect (ERE) of the United States on the world due to climate change under Representative Concentration Pathway 4.5 with different increases in the annual mean temperature (AMT; 1, 1.5, and 2°C) between 2020 and 2100. The results show that if a loss of gross domestic product of 0.88% occurs with a 1°C AMT increase in the United States, the ERE of approximately 0.12% will be generated onto the global gross domestic product; with a 2°C increase, the ERE will triple. The time variation trend of the ERE conforms to the future variations in AMT. The degree of this effect on other regions of the world is closely related to the trade links between the United States and economic aggregates. Among these regions, Canada shows the greatest impact, followed by China. The ERE that China suffers may increase by 4.5 times as the AMT in the United States increases from 1 to 2°C. In cold regions, the benefit from global warming will decrease due to the ERE from other regions, which will inhibit their economic development. This paper aims to provide new perspectives and data‐based support for regions around the world to cope with climate change and to develop policies by studying the ERE behind international trade.

Climate is an essential element in agricultural production, and climate change inevitably have an impact on agriculture. Assessing the economic consequences of climate change requires comprehensive assessments of the impact chain from climate to crops and the economy. In our previous study, we derived a dose‐response function to estimate the response of crop yields to climate variables through a systematic review. In this paper, a dynamic multiregional input‐output model is established to assess the economic consequences of changes in agricultural production on China's regional and sectoral levels. The results show that (1) the direct economic damage is equivalent to 1% of gross domestic product (GDP) which implies the resulting economic cascade effect (ECE) that amounts to 17.8% of China's GDP. At the end of 21st century, the ECE is −0.1% to 13.6% of GDP (negative values indicate economic gains) without considering CO₂ fertilization effect, of which the ECE in the most pessimistic pathway are equivalent to the total agricultural output in China today. (2) Regional‐level results show an uneven distribution of economic impact in China, which is related to the regional economic development. The least developed region in China experiences 2.8 to 8.5 times more ECE caused by climate change than the most developed region. (3) Sector‐level results show that agriculture is still the main affected sector, but in developed regions, manufacturing and services also bear part of the ECE.