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Effectively treating industrial SO 2 emissions depends on the synergy of different factors from the industrial SO 2 generation source to the end of treatment. Applying a whole process treatment perspective, this paper decomposes industrial SO 2 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 SO 2 emissions, followed by process control. The contribution of source prevention to reduce industrial SO 2 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 SO 2 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 SO 2 emissions. • We study China's industrial SO 2 emissions from a whole process treatment perspective. • Both temporal and spatial index decomposition analysis methods are used. • End-of-pipe treatment and process control majorly reduce industrial SO 2 emissions. • Industrial SO 2 emissions whole process treatment performances vary among regions. [ABSTRACT FROM AUTHOR]