Projections of climate-change-driven losses in occupational work capacity — from global assessments to the regional study of Kim and Lee (2020) on heat-vulnerable occupations in the Republic of Korea — rest on population-average exposure–response functions that map wet-bulb globe temperature to work capacity for a standard worker at a few fixed work intensities. The source study explicitly concedes that it does not estimate thermal effects on individual workers' characteristics or physical capacities, and therefore cannot resolve how personal factors such as heat acclimatization, clothing, hydration, and aerobic fitness modify the projected losses. The later literature has documented these factor effects in occupational physiology (Foster et al. 2020), built fitness-parameterized laboratory work-capacity curves (Foster et al. 2021), catalogued twenty inter- and intra-individual modifiers of heat strain in a meta-analysis of 2,409 outdoor workers (Ioannou et al. 2022), and applied the ISO 7933 Predicted Heat Strain model to future climate scenarios with fixed standard-person assumptions (Hunt et al. 2023). No study has yet incorporated individual-factor modifiers into climate–labour projections, and the most recent projections and syntheses (2024–2026) continue to flag this as needed. The open problem is to quantify how acclimatization, clothing, hydration, and fitness modify heat-induced physical work-capacity loss and to integrate these modifiers into work-capacity projections under climate warming, replacing the standard-worker assumption.

Background

Work capacity refers to the maximum physical work output a person can sustain, and it falls as environmental heat stress rises because the human body must both rid itself of metabolic heat and defend a safe core temperature. The standard tool for grading occupational heat stress is the wet-bulb globe temperature (WBGT), a composite index of shade air temperature, humidity (via a naturally ventilated wet-bulb thermometer), and radiant heat, adopted in ISO 7243 and by NIOSH (the United States National Institute for Occupational Safety and Health) for setting work–rest limits. On this basis, Kjellstrom, Kovats, Lloyd, Holt and Tol (2009) constructed the widely used relationship between WBGT and hourly work capacity at four metabolic work-intensity levels of roughly 200–500 W, derived from ISO/NIOSH threshold-limit assumptions for a standard worker; Dunne, Stouffer and John (2013) used it to project global labour-capacity declines under climate warming. Kim and Lee (2020) applied the same curve family at subnational scale in the Republic of Korea: they classified 147 occupations into work-intensity (watt) levels using the Korean Working Conditions Survey, combined this with regional employment from the 2010 census and station-based WBGT, and projected work-capacity loss to 2050 under the RCP 8.5 scenario (the Intergovernmental Panel on Climate Change pathway with high greenhouse-gas emissions), finding 52 heat-vulnerable occupations and spatial clusters of diminishing capacity in southwest Korea. All of these projections share one structural limitation, which the source states directly: the analysis does not estimate thermal effects on individual workers' characteristics or physical capacities. Yet heat strain is strongly modified by individual factors — heat acclimatization (the physiological adaptation that develops over repeated heat exposure and improves sweating and cardiovascular response), clothing insulation (garment layers impede evaporative heat loss; insulation is measured in clo units), hydration state (sweat-driven body-water deficit degrades thermoregulation and performance), and aerobic fitness (fit workers sustain more work at a given cardiovascular strain). The analytical alternative to the standard-worker curves already exists in outline: the ISO 7933 Predicted Heat Strain (PHS) model computes safe work durations from first principles with explicit inputs for acclimatization, clothing, and fluid replacement, and laboratory programmes (e.g., Foster, Smallcombe, Hodder, Jay, Flouris, Nybo and Havenith's empirical physical-work-capacity equations, and the companion study of aerobic fitness) have begun parameterizing capacity curves by worker characteristics. The unresolved question is how these individual modifiers change the projected, climate-driven loss of work capacity — a question the field's major syntheses, from Ioannou, Foster, Morris, Piil, Havenith, Mekjavic, Kenny, Nybo and Flouris (2022) to Dasgupta, Robinson, Shayegh, Bosello, Park and Gosling (2024), repeatedly identify as required but unanswered.

Problem Statement

Quantify how individual thermoregulatory and behavioral factors — heat acclimatization status, clothing insulation, hydration state, and aerobic fitness — modify the loss of physical work capacity caused by heat stress, and incorporate these modifiers into projections of occupational work-capacity loss under climate warming, so that projected losses no longer rest on the standard-average-worker assumption. The target is validated quantitative response functions (or a validated physiological model) that isolate the modifying effect of the named factors on heat-related work capacity across the relevant work intensities and heat conditions, integrated into a work-capacity projection under a climate-warming scenario and occupational context, characterizing the direction and magnitude of the resulting correction relative to standard-worker projections such as the RCP-8.5-based 2050 estimates of the source study.

References

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