This analysis explores carbon emissions impacts from GDP per capita and energy intensity in Xinjiang, indicating significant drivers.
Using the Kaya identity and LMDI method, this study analyzes the influence of population, GDP per capita, energy intensity, and carbon intensity on Xinjiang’s carbon emissions, and compares the effects of industrial structure, energy intensity, and carbon intensity on the industrial sectors during the Eighth to Twelfth Five-Year Plan (FYP) periods. Key findings are as follows: (1) Xinjiang’s carbon emissions center on resource- and energy-intensive sectors, emissions from sectors such as extraction of petroleum and natural gas, fuel processing, chemicals, ceramics and cement, iron and steel, and non-ferrous and power generation accounted for 62% of carbon emissions in 2015; (2) after the Sixth FYP, GDP per capita effect turned into the core driver of carbon emission growth, while the population effect played an auxiliary role. Meanwhile, the energy intensity effect exerted a marked inhibitory impact on the increase in carbon emissions, yet the restraining effect of carbon intensity was comparatively limited; (3) during the Eighth to Twelfth FYPs, carbon emission growth was mainly attributed to industrial structure effects of the mining and washing of coal, extraction of petroleum and natural gas, fuel processing, chemicals, ceramics and cement, iron and steel, non-ferrous and power generation. Energy intensity and carbon intensity effects in various industries inhibited emission growth. Based on new trends in Xinjiang’s socioeconomic development, policy recommendations proposed including promoting the low-carbon transformation of industrial structure, profound restructuring of energy consumption, and improving energy efficiency by advancing energy-saving technology.
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Qin et al. (2025) studied this question.
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