Coupling the Driving Forces of Urban CO₂ Emission in Shanghai with Logarithmic Mean Divisia Index Method and Granger Causality Inference


This paper investigates the potential indicators influencing CO2 emission in Shanghai during 1995-2017 by a combined method of logarithmic mean Divisia index method (LMDI) and Granger causality test for the purpose of strengthening the sustainability in dynamic perspectives. Firstly, we quantify the contributions of potentially influential factors of CO2 emission, and then a further analysis of different relationships between CO2 emission and the mainly potential factors are identified. The results show that the motor vehicle amount, the disposable personal income, the carbon intensity, and the urbanization rate are the top four driving forces of CO2 emission. The result of Granger causality test indicates that the motor vehicle amount has a bidirectional Granger causality relationship with CO2 emission in different lags, while the urbanization rate, per motor vehicle secondary industry, per secondary industry population, per residents’ income GDP support coefficient and the carbon intensity have a one-way Granger causality relationship with CO2 emission. Interestingly, it is found that the policy implementation or main events are closely related to the influential factors of CO2 emission. Thus, policy makers should not only continue to implement current related policies of reducing CO2 emission but also pay attention to the effect of great events of urban development.


Civil, Architectural and Environmental Engineering


National Natural Science Foundation of China, Grant 19CH191

Keywords and Phrases

CO emission 2; Granger causality test; LMDI; Shanghai

International Standard Serial Number (ISSN)


Document Type

Article - Journal

Document Version


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© 2020 Elsevier, All rights reserved.

Publication Date

20 May 2021