Global supply chains amplify economic costs of future extreme heat risk

The increasing frequency and severity of heatwaves pose significant socioeconomic risks. Previous research has documented the direct impacts of heat stress on human health (increased morbidity and mortality) and labor productivity (lost work time, reduced efficiency). However, the indirect economic consequences due to disruptions in global supply chains have remained largely unexplored. This study addresses this gap by developing a comprehensive analytical framework. The importance of this research lies in providing a more complete picture of the economic costs of climate change, particularly the cascading effects across interconnected global markets. Understanding these indirect impacts is crucial for effective climate change mitigation and adaptation policies. The study aims to quantify the direct and indirect economic losses caused by heat stress, considering the complex interplay of climate change, human health, labor productivity, and global supply chain dynamics.

Existing research has extensively examined the direct impacts of heat stress on mortality and productivity, particularly focusing on specific regions and sectors. Studies have shown a clear link between rising temperatures and increased heat-related deaths and work losses. However, previous analyses often either insufficiently addressed the indirect economic effects of supply chain disruptions or completely ignored them, reporting only aggregated losses. This study addresses a key gap in the literature by explicitly modeling the amplifying effects of the global trade system on heat-related economic losses, offering a more nuanced and complete understanding of the overall impact.

The study employs a novel disaster footprint analytical framework. This framework integrates three key modules: (1) a climate module using CMIP6 data from 14 global climate models to project future temperature and humidity; (2) an epidemiological module using empirical functions to estimate heat-related mortality and labor productivity losses; and (3) a hybrid input-output and computable general equilibrium global trade module to simulate the cascading effects of heat stress through global supply chains. The framework assesses impacts across 141 regions and 65 sectors worldwide. Three SSP-RCP scenarios (SSP 119, SSP 245, SSP 585) are considered, representing different pathways of greenhouse gas emissions and socioeconomic development. The model accounts for health loss (excess mortality), labor productivity loss (decreased daily labor productivity), and indirect loss (production stagnation due to supply or demand disruptions). The study uses static production and trade relationships which may not fully capture dynamic long-term interactions.

The study reveals a nonlinear growth trend in global heat-related economic losses. Under the low-emissions SSP 119 scenario, total global GDP loss is projected to be 0.8% by 2060 (0.4% health loss, 0.3% labor productivity loss, and 0.1% indirect loss). However, under the high-emissions SSP 585 scenario, this loss increases dramatically to 3.9% (1.6% health loss, 0.8% labor loss, and 1.5% indirect loss). The proportion of losses attributed to supply chain disruptions increases exponentially, becoming the dominant contributor to total losses. Small and medium-sized developing countries face disproportionately high health and labor losses, while manufacturing-heavy countries like China (2.7% GDP loss) and the USA (1.8% GDP loss) suffer significant indirect losses. South-Central Africa experiences the highest health losses, while West Africa and Southeast Asia suffer the greatest labor productivity losses. The spatial distribution of indirect losses is widespread, impacting even high-latitude countries through disruptions in global value chains. Sectoral analysis shows that the agriculture, construction, and mining sectors are most vulnerable, especially in low-latitude countries. Manufacturing industries suffer significant indirect losses due to raw material shortages. The study identifies two distinct supply chain vulnerabilities: upstream constraints (insufficient supply of raw materials) and downstream constraints (lack of demand). The Indian food production sector, heavily reliant on upstream suppliers, experiences significant supply chain disruptions. In contrast, the Dominican Republic's tourism sector is more affected by reduced downstream demand from major tourism markets.

The findings highlight the significant and underestimated role of global supply chains in amplifying the economic costs of future heat stress. The nonlinear relationship between heat stress and economic losses, driven by increasingly significant indirect effects, underscores the urgent need for comprehensive adaptation strategies that go beyond addressing direct impacts. The disproportionate impact on developing countries highlights the need for international cooperation to support their adaptation efforts. The study’s results provide valuable insights for targeted risk governance and regional cooperation. Supporting adaptation efforts in vulnerable regions can indirectly benefit countries further along the supply chain by mitigating disruptions.

This study demonstrates the substantial and escalating economic costs of future extreme heat, emphasizing the significant amplification of these costs through global supply chains. The findings highlight the need for a shift in global supply chain organization from a focus solely on efficiency to one that prioritizes both efficiency and resilience. International cooperation and targeted adaptation strategies are crucial to mitigating the disproportionate impacts on developing countries and ensuring the long-term stability of the global economy. Future research should focus on refining dynamic modeling of supply chain responses to heat stress and exploring innovative adaptation strategies.

The model relies on static production and trade relationships, potentially underestimating dynamic long-term industry and country interactions. Uncertainty exists in parameters used in the three model modules. While the global estimate of indirect losses is robust, regional estimates show some variability based on the input-output database used. The study acknowledges the limitations inherent in using static models for assessing long-term dynamic processes.