Adapting to Changing Labor Productivity as a Result of Intensified Heat Stress in a Changing Climate

A New, Zero-Iteration Analytic Implementation of Wet-Bulb Globe Temperature: Development, Validation, and Comparison With Other Methods

Wet-bulb globe temperature (WBGT)-a standard measure for workplace heat stress regulation-incorporates the complex, nonlinear interaction among temperature, humidity, wind and radiation. This complexity requires WBGT to be calculated iteratively following the recommended approach developed by Liljegren and colleagues. The need for iteration has limited the wide application of Liljegren's approach, and stimulated various simplified WBGT approximations that do not require iteration but are potentially seriously biased. By carefully examining the self-nonlinearities in Liljegren's model, we develop a zero-iteration analytic approximation of WBGT while maintaining sufficient accuracy and the physical basis of the original model. The new approximation slightly deviates from Liljegren's full model-by less than 1°C in 99% cases over 93% of global land area. The annual mean and 75%-99% percentiles of WBGT are also well represented with biases within± 0.5 °C globally. This approximation is clearly more accurate than other commonly used WBGT approximations. Physical intuition can be developed on the processes controlling WBGT variations from an energy balance perspective. This may provide a basis for applying WBGT to understanding the physical control of heat stress.

The uneven impacts of climate change on China's labor productivity and economy

Climate change is considered to increase economic costs by worsening heat-related labor productivity loss. While extensive global and national research has been conducted on this topic, few studies have analyzed subnational and individual economic impacts, potentially weakening local governments' motivation to tackle climate change. Figuring out the most affected regions and labors could help climate policymakers to identify priority regions and sectors to allocate adaptation resources efficiently, and enhance stakeholder engagement. This study adopted a provincial Computable General Equilibrium model by distinguishing different labors and regions in modelling work to address the aforementioned gap. The study estimated economic costs at different level under three climate change scenarios (lower (SSP126), middle (SSP245), and higher (SSP585) warming scenario). Low-income regions located in southwest part of China (such as Guangxi and Guizhou), would experience the largest economic loss, 3.4-7.1 times higher than high-income in China by 2100 under SSP245 scenario. Additionally, wages for labors highly sensitive to heat in these regions are expected to rise, for example, by an 8.3% rise in Guangxi, driven by the rising demand for these labors. Conversely, others would experience a significant wage decrease, especially those with less sensitivity (e.g., managers). Therefore, we recommended that national financial supports be allocated more to these most affected regions and that government encourage managers provide assistance to workers vulnerable to heat.

Projecting future labor losses due to heat stress in China under climate change scenarios

Climate change is expected to increase occupational heat stress, which will lead to diminished work performance and labor losses worldwide. However, sub-regional analyses remain insufficient, especially for countries with a heterogeneous spatial distribution of working populations, industries and climates. Here, we projected heat-induced labor losses in China, by considering local climate simulations, working population characteristics and developing an exposure-response function suitable for Chinese workers. We showed that the annual heat-induced work hours lost (WHL), compared to the baseline of 21.3 billion hours, will increase by 121.1% (111.2%-131.1%), 10.8% (8.3%-15.3%), and -17.8% (-15.3%--20.3%) by the end of the century under RCP(Representative Concentration Pathways)8.5, RCP4.5, and RCP2.6, respectively. We observed an approximately linear upward trend of WHL under RCP8.5, despite the decrease in future working population. Notably, WHL will be most prominent in the southern, eastern and central regions, with Guangdong and Henan accounting for a quarter of national total losses; this is largely due to their higher temperature exposure, larger population size, and higher shares of vulnerable population in total employment. In addition, limiting global warming to 1.5 °C would yield substantial gains. Compared to RCP2.6, RCP4.5, and RCP8.5, all provinces can avoid an average of 11.8%, 33.7%, and 53.9% of annual WHL if the 1.5 °C target is achieved, which is equivalent to avoiding 0.1%, 0.6%, and 1.4% of annual GDP losses in China, respectively. This study revealed climate change will exacerbate future labor losses, and adverse impacts can be minimized by adopting stringent mitigation policies coupled with effective adaptation measures. Policymakers in each province should tailor occupation health protection measures to their circumstances.

Broad Scale Spatial Modelling of Wet Bulb Globe Temperature to Investigate Impact of Shade and Airflow on Heat Injury Risk and Labour Capacity in Warm to Hot Climates

While shade and air flow are recognised factors that reduce outdoor heat exposure, the level of reduction in terms of labour capacity at varying air temperature and humidity levels is poorly understood. This study investigated cooling effects on the commonly used heat index, wet bulb globe temperature (WBGT), and subsequent impact on labour capacity, for a range of air flow and shade conditions in warm to hot climates. We modelled heat exposure using a physics-based method to map WBGT for a case study region which experiences a range of heat categories with varying levels of health risks for outdoor workers. Continent-scale modelling confirmed significant spatial variability in the effect of various shade and wind speed scenarios across a range of real-world mid-summer daytime conditions. At high WBGTs, increasing shade or air flow for outdoor workers lowered heat exposure and increases labour capacity, with shade giving the greatest benefit, but cooling varied considerably depending upon underlying air temperature and humidity. Shade had the greater cooling effect; reducing incident radiation by 90% decreased WBGT by 2-6 °C depending on location. Wind had a lower cooling effect in the hottest regions, with a decreasing exponential relationship between wind speed and WBGT observed.

Extreme Heat and COVID-19: A Dual Burden for Farmworkers

Currently, there is an extensive literature examining heat impacts on labor productivity and health, as well as a recent surge in research around COVID-19. However, to our knowledge, no research to date examines the dual burden of COVID-19 and extreme heat on labor productivity and laborers' health and livelihoods. To close this research gap and shed light on a critical health and livelihood issue affecting a vulnerable population, we urge researchers to study the two topics in tandem. Because farmworkers have a high incidence of COVID-19 infections and a low rate of inoculation, they will be among those who suffer most from this dual burden. In this article, we discuss impacts from extreme heat and COVID-19 on farm laborers. We provide examples from the literature and a conceptual framework showing the bi-directional nature of heat impacts on COVID-19 and vice versa. We conclude with questions for further research and with specific policy recommendations to alleviate this dual burden. If implemented, these policies would enhance the wellbeing of farmworkers through improved unemployment benefits, updated regulations, and consistent implementation of outdoor labor regulations. Additionally, policies for farmworker-related health needs and cultural aspects of policy implementation and farmworker outreach are needed. These and related policies could potentially reduce the dual burden of COVID-19 and extreme heat impacts while future research explores their relative cost-effectiveness.