Analysis of drivers of China's carbon intensity under the background of carbon peaking and carbon neutralization: based on LMDI and attribution model

Against the backdrop of China’s carbon peaking and neutrality objectives, this study aims to systematically identify the drivers of China’s carbon intensity (CI) and quantify their sector-specific impacts. Using a multiplicative Logarithmic Mean Divisia Index (LMDI) decomposition model, we analyze provincial panel data from 2000–2020 to evaluate the contributions of six factors—carbon coefficient, fossil energy structure, nuclear energy share, renewable energy share, energy intensity, and industrial structure—to CI changes, and further attribute these effects to 41 economic sectors via an attribution model. The results showed that: (a) the decline of energy intensity is the leading factor to promote the reduction of carbon intensity in China; (b) The transformation of fossil energy and industrial structure inhibited China's carbon intensity reduction; (c) Renewable energy consumption and carbon coefficient promoted carbon intensity reduction in some degree; (d) Energy intensive sectors have had an important impact on China's carbon intensity. Therefore, targeted interventions in energy-intensive sectors, coupled with the deployment of low-carbon energy-saving technologies, energy efficiency improvements, and renewable energy promotion, are effective strategies to promote the reduction of China's carbon intensity.