ABSTRACT
A comprehensive understanding of the relationships among carbon emissions, the industrial structure and economic growth holds great significance for China's transition to a low-carbon economy, industrial structure optimization, and achievement of energy conservation and emission reduction targets. We selected six major industrial sectors (agriculture, industry, construction, transportation, retail and accommodation and other industries) as research objects, introduced the extended STIRPAT decomposition model, Tapio decoupling model and the grey relation analysis to discuss the relationship among the three. Results showed that (i) since 2000, the proportions of value added of agriculture, manufacturing, and transportation are negatively correlated with carbon emissions, while those of construction, retail and accommodation, and other industries are positively correlated with carbon emissions. (ii) The overall economic growth and carbon emissions of these six major industries have experienced the process of decoupling-coupling-decoupling-coupling-decoupling. (iii) The relevance of these six industries to GDP is ranked as follows: transportation > manufacturing > retail andaccommodation > agriculture > construction > other industries. Additionally, accelerating the achievement of a clean energy structure, strengthening the strength and speed of industrial structure adjustment and reducing the dependence on fossil energy are the key steps for China to reach carbon emissions peak goal.
