This paper investigates the path choice of achieving China's 2020 carbon intensity target by using a multiple attribute decision model from the perspective of "double control", i.e. quantity (energy consumption and CO2 emissions) and intensity (energy intensity and carbon intensity). Firstly, we propose a novel integrated model to predict the quantity and intensity. The cumulative effects of several drivers for CO2 emissions are examined by Logarithmic Mean Divisia Index method. Secondly, the quantity and intensity are normalized to identify the feasible pathway of "double control" in various scenarios by multiple attribute decision model, and robustness test is carried out by a case study. The results show that per capita GDP has a significantly positive cumulative effect on CO2 emissions, whereas energy intensity has significantly negative one on it. The targeted carbon intensity by 2020 can be differentially realized in all scenarios. Both slow economic growth speed and substantial energy structure adjustment facilitate "double control". The results suggest that the best pathway of "double control" depends on the policy makers' preferences on the quantity control and intensity control. The policy implications of the findings are discussed.