Scenario-based Kaya identity analysis for city-level carbon dioxide emissions

基于情景的Kaya恒等式分析用于城市级二氧化碳排放

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Abstract

Many countries worldwide have committed to reduce their carbon dioxide emissions in response to climate change. In China, cities are striving to achieve their 2030 peak carbon emission targets. In this study, we developed a scenario-based Kaya identity analysis methodology to explore the notable uncertainty inherent in future carbon dioxide emissions. Using the case of Changning City, Hunan province, China, we found that under the business-as-usual scenario, the city's carbon dioxide emissions of 3,839.1 thousand tons in 2022 are projected to reach 4,674.3 thousand tons in 2031. Changning is unlikely to achieve its carbon peak target. In a more challenging future scenario of rapid economic growth, carbon dioxide emissions are expected to rise from 3,839.1 thousand tons in 2022-5,447 thousand tons in 2031. Under the environmentalist scenario, Changning could achieve its carbon peak target before 2030 (carbon dioxide emissions would peak at 3,922 thousand tons in 2028). Under a slowed economic development scenario, Changning could also achieve a carbon peak in 2028 (carbon dioxide emissions would peak at 3,980.2 thousand tons in 2028). However, without sufficient energy-saving and emissions-reduction measures, annual increases in carbon dioxide emissions are likely to resurge during periods of rapid economic development.

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