Spatial pattern and structural transformation of industrial carbon dioxide emissions in China

Abstract

Abstract Industrial carbon emissions are a critical component of China’s carbon peaking and carbon neutrality strategy, yet their long-term spatial evolution and underlying drivers remain insufficiently understood. Using the China City Greenhouse Gas (CCG) dataset and urban statistical data for 2005–2020, this study integrates ArcGIS spatial analysis, standard deviation ellipse modeling, and multiple linear regression to investigate the spatiotemporal dynamics and driving mechanisms of industrial CO 2 emissions across China. The results show that industrial CO 2 emissions rose from 5.66 to 9.83 billion tonnes, accounting for a growing share of national total carbon emissions from 69.96 to 77.70%, with the overall growth rate gradually slowing. Nationwide per capita industrial carbon emissions jumped by 156.57% from 3.96 tonnes in 2005 to 10.16 tonnes in 2020, while industrial carbon intensity dropped continuously from 2.62 tonnes per ten thousand CNY of GDP to 1.64 tonnes per ten thousand CNY of GDP, though 36.11% of Chinese cities still saw rising carbon intensity. Spatially, emissions remained concentrated in northern and eastern China but exhibited significant inland expansion and regional restructuring. A notable finding is that the gravity center of industrial carbon emissions shifted continuously westward and crossed the Hu Huanyong Line, indicating a fundamental transition from coastal concentration to inland diffusion driven by industrial relocation. High-emission clusters characterized by high total emissions, high per capita emissions, high carbon intensity, and low efficiency emerged in resource-dependent regions such as Xinjiang and Inner Mongolia, where carbon intensity of some cities exceeded 10 tonnes per ten thousand CNY of GDP. Furthermore, energy-consumption-related emissions declined steadily, whereas process-related emissions continued to rise, revealing a structural transformation in industrial emission sources and suggesting that future mitigation efforts should increasingly focus on process decarburization rather than solely improving energy efficiency. The regression results indicate that urban construction scale, population size, economic development, R&D investment, foreign direct investment, tertiary-sector development, and environmental governance capacity significantly influence industrial emissions. The study further identifies a phenomenon of “carbon transfer without proportional economic convergence,” whereby less-developed regions increasingly absorb carbon-intensive industries without receiving equivalent economic benefits. These findings provide new insights into China’s industrial carbon transition and offer scientific support for differentiated regional mitigation strategies and coordinated interregional carbon governance.