China's provincial carbon emission driving factors analysis and scenario forecasting

Abstract

Studying the drivers of China's carbon emissions at the provincial level can clarify differences in carbon emissions due to initial resource endowments and explore pathways to achieve China's 2030 carbon peak and 2060 carbon-neutral commitments (China's 30.60 decarbonization target). In this paper, the carbon emissions of 30 provinces in China during 2000–2019 were calculated using the emission coefficient method. The LMDI model was used to investigate each province's carbon emission drivers. On this basis, the STIRPAT model is used to predict the carbon emissions of each province under three scenarios: low carbon, baseline, and high carbon. The results show that: (1) China's carbon emissions have significant regional differences, and the trend of total carbon emissions is consistent with that of per capita carbon emissions; (2) Economic development contributes the most to regional carbon emission; (3) China's carbon emission trend can be divided into four patterns: gathering type, discrete type, overlapping type, and idiotype. The results enrich the research on carbon emission drivers and forecasts, provide targeted policy recommendations for China to coordinate regional economic development, energy conservation, and carbon emission reduction, and explore a path for China to achieve the 30.60 decarbonization goal.

Keywords

• Carbon emissions
• LMDI model
• STIRPAT model
• Carbon emission forecasting