Abstract
Occupational heat stress directly hampers physical work capacity (PWC), with large economic consequences for industries and regions vulnerable to global warming. Accurately quantifying PWC is essential for forecasting impacts of different climate change scenarios, but the current state of knowledge is limited, leading to potential underestimations in mild heat, and overestimations in extreme heat. We therefore developed advanced empirical equations for PWC based on 338 work sessions in climatic chambers (low air movement, no solar radiation) spanning mild to extreme heat stress. Equations for PWC are available based on air temperature and humidity, for a suite of heat stress assessment metrics, and mean skin temperature. Our models are highly sensitive to mild heat and to our knowledge are the first to include empirical data across the full range of warm and hot environments possible with future climate change across the world. Using wet bulb globe temperature (WBGT) as an example, we noted 10% reductions in PWC at mild heat stress (WBGT = 18°C) and reductions of 78% in the most extreme conditions (WBGT = 40°C). Of the different heat stress indices available, the heat index was the best predictor of group level PWC (R2 = 0.96) but can only be applied in shaded conditions. The skin temperature, but not internal/core temperature, was a strong predictor of PWC (R2 = 0.88), thermal sensation (R2 = 0.84), and thermal comfort (R2 = 0.73). The models presented apply to occupational workloads and can be used in climate projection models to predict economic and social consequences of climate change.
Highlights
Human exposure to increased environmental heat directly impacts the global economy by decreasing occupational productivity during work hours (Flouris et al 2018; Hsiang et al 2017; Kjellstrom et al 2018)
We show that physical work capacity (PWC) is strongly influenced by air temperature, humidity, and, to a mild extent in our study, the level of clothing coverage
Since the clothing types tested only had a limited impact on PWC, models were generated from the pooled dataset, as shown in Fig. 2a–e and separated for clothing (Fig. 4)
Summary
Human exposure to increased environmental heat directly impacts the global economy by decreasing occupational productivity during work hours (Flouris et al 2018; Hsiang et al 2017; Kjellstrom et al 2018). We describe below why existing models (Dunne et al 2013; Kjellstrom et al 2018; Zivin and Neidell 2014) presently used to inform those predictions have limited applicability, especially for use on a global scale These considerations justify the development of a new series of empirically derived equations intended to quantify the loss in PWC more precisely across a wide range of environmental conditions. Such empirical equations have immediate application for those striving to evaluate the productivity and, economic consequences of hot weather, in different climate change scenarios arising from variations in projected greenhouse gas emissions
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