A city-scale decomposition and decoupling analysis of carbon dioxide emissions: A case study of China

Abstract Cities consume large amounts of fossil fuels and this results in significant increase of global anthropogenic greenhouse gases. Using city-level carbon dioxide emission data from Shijiazhuang, a traditional heavy manufacturing city and one of the key cities in Jing-Jin-Ji urban agglomeration in Northern China, this paper employs logarithmic mean Divisia index decomposition method (LMDI) to explore the influence of energy intensity, consumption structure, industry structure, per capita Gross Domestic Product (GDP), and population on Shijiazhuang's total carbon dioxide emissions from 2005 to 2016. The LMDI method is further extended to analyze the impacts of above factors at the industry-segment level. This paper finds that the reduction of energy intensity is the major contributor of decreasing carbon dioxide emissions in Shijiazhuang, whereas the growth of per capita GDP is the main driving force for emission accretion. The dominant industrial segments contributing to increasing emissions in Shijiazhuang City from 2005 to 2016, have changed from CMD (coal mining and dressing), EPSH (electric power, steam and hot water production and supply) to SPFM (smelting and pressing of ferrous metals) and PPC (petroleum processing and coking). The CMD industrial segment shows a significant carbon reducing effort and indicates a strong decoupling status. However, the SPFM and PPC respectively show expansive negative decoupling and weak decoupling status, enlightening a change in the policy focus when Shijiazhuang formulates its emission-reduction plans in the future. This study provides important policy insights for the heavy manufacturing cities in other countries with similar industrial structure, as the industry-based carbon mitigation policies should always be adjusted in different stages of the cities' development according to the change of carbon emission driving industries.