Guanhui Cheng

Observable climate change has led to an increase in compound heat events, thereby amplifying the economic impacts of labor heat stress and necessitating intervention strategies. Current research lacks high-resolution precision in projecting future heat stress and quantifying adaptation strategies, which is particularly critical for China given its spatial disparities in climate, workforce distribution, and economic development. This study integrates high-resolution CMIP6 climate models, a Wet-bulb Globe Temperature (WBGT) algorithm, and localized Exposure-response Functions (ERFs) to project heat-induced labor productivity loss across China under the SSP5-8.5 scenario. It systematically analyzes and quantitatively compares the effectiveness of two adaptation strategies (shading and work schedule adjustments) while estimating direct economic losses in outdoor heavy labor industries. This study precisely identifies the thermal stress hotspots categorized as primary (South China: loss rate > 11%, increment 5–7%), secondary (middle-lower Yangtze River: 7–11% loss, 3–5% increment), and tertiary hotspots (Yangtze River Delta & North China Plain: 6–9% loss, 2–4% increment) based on productivity loss magnitudes. Our findings also reveal that optimal strategies diverge north-south along the 33°N: shading dominates in the south and schedule adjustments in the north due to distinct heat patterns, though future climate trends may reduce the efficacy of time shift adjustments nationwide. Additionally, economic loss estimation reveals surging heat-induced losses in agriculture and construction over two decades (annual growth rates of 11.16% and 20.69%, respectively), with combined strategies potentially reducing direct losses by 65–70% in hotspot provinces. These findings enable province- and industry-specific intervention designs considering regional climate variations and strategy effectiveness.