Spatial-Temporal Analysis and Driving Factors Decomposition of (De)Coupling Condition of SO₂ Emissions in China

• Main Authors: Yue Wang, Lei Shi, Di Chen, Xue Tan
• Format: Article
• Language: English
• Published: MDPI AG 2020-09-01
• Series: International Journal of Environmental Research and Public Health
• Subjects: decoupling analysis; driving factors decomposition; Moran Index; generalized logarithmic mean Divisia index; SO₂ emissions; China
• Online Access: https://www.mdpi.com/1660-4601/17/18/6725

China has a fast-growing economy and is one of the top three sulfur dioxide (SO₂) emitters in the world. This paper is committed to finding efficient ways for China to reduce SO₂ emissions with little impact on its socio-economic development. Data of 30 provinces in China from 2000 to 2017 were collected to assess the decoupling relationship between economic growth and SO₂ emissions. The Tapio method was used. Then, the temporal trend of decoupling was analyzed and the Moran Index was introduced to test spatial autocorrelation of the provinces. To concentrate resources and improve the reduction efficiency, a generalized logarithmic mean Divisia index improved by the Cobb–Douglas function was applied to decompose drivers of SO₂ emissions and to identify the main drivers. Results showed that the overall relationship between SO₂ emissions and economic growth had strong decoupling (SD) since 2012; provinces, except for Liaoning and Guizhou, have reached SD since 2015. The decoupling indexes of neighboring provinces had spatial dependence at more than 95% certainty. The main positive driver was the proportion of the secondary sector of the economy and the main negative drivers were related to energy consumption and investment in waste gas treatment. Then, corresponding suggestions for government and enterprises were made.