Industrial SO₂ emissions treatment in China: A temporal-spatial whole process decomposition analysis

Effectively treating industrial SO₂ emissions depends on the synergy of different factors from the industrial SO₂ generation source to the end of treatment. Applying a whole process treatment perspective, this paper decomposes industrial SO₂ emissions into six specific driving factors in three whole process treatment dimensions (i.e. source prevention, process control, and end-of-pipe treatment), and economic scale. A temporal index decomposition analysis (Temporal-IDA), attribution analysis (AA), and spatial index decomposition analysis (Spatial-IDA) methods are then applied to quantify each dimension's treatment effect and its spatial differences. The empirical study across 30 regions in China using data from 2005 to 2015 shows that: (1) The end-of-pipe treatment is the dominant dimension for decreasing industrial SO₂ emissions, followed by process control. The contribution of source prevention to reduce industrial SO₂ emissions has begun to appear, however, there remains room for further improvement; (2) End-of-pipe treatment strength and energy intensity are key factors in reducing industrial SO₂ emissions; Inner Mongolia, Henan, and Shandong are the main contributors; (3) The treatment emphasis are different among regions; as such, there are different treatment effects across the three dimensions of the whole process treatment. Regions can be classified into four categories: the Leading type, Process-dependent type, End-dependent type, and Lagging type. Based on the empirical results, this paper identifies the policy implications of promoting whole process treatment on China's industrial SO₂ emissions.