This study investigates the impact of increasingly frequent extreme heat events due to climate change on carbon emission intensities in China. Using spline regressions on county-level data from 2000 to 2019, we identify an asymmetric U-shaped relationship between daily mean temperatures and carbon intensities. Each additional day with temperatures above 33 °C in each location results in a 0.9% rise in the average annual carbon intensity, driven by higher energy consumption for cooling. We also explore the mitigating effects of China's low-carbon city initiatives and emissions trading scheme. By combining our estimation results with future temperature trajectories, we simulate that, in the long run, China's carbon intensity can increase by 8–13% under the SSP1-2.6 scenario and 24–51% under the SSP5-8.5 scenario. Our findings underscore the urgency for policymakers to thoroughly assess the socioeconomic impacts of heat waves and incorporate climate resilience into overall sustainable development plans.
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Jiang et al. (2024) studied this question.
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