Identification of low-carbon strategies for post-earthquake development in the city of Guangyuan based on an inexact two stage stochastic programming approach

In this research, an interval-parameter two-stage stochastic programming approach was developed for supporting the identification of low-carbon strategies and the post-earthquake reconstruction in the city of Gugangyuan, Sichuan province of China. The approach can effectively deal with uncertainties that can be expressed as both probability density functions and interval numbers without any distribution information. Also, the approach can provide useful decision alternatives for supporting long-term corrections for any plans associated with carbon dioxide emission limits within a city context. The developed approach was applied in the city of Guangyuan. Three scenarios were established including the baseline (i.e., regional planning) as scenario 1, zero carbon emission as scenario 2, and carbon sink as scenario 3. Also, based on practical information and the collected data, three projection values (i.e., low, medium and high levels) for the carbon emission of the entire city were generated and analyzed under varying probability levels (i.e., 20, 60, and 20%). The results indicated that in order to achieve low-carbon post-earthquake development in the city, the priority areas and industries for carbon emission reduction would be Chaotian (the secondary industry) > Wangcang (the secondary industry) > Lizhou (the secondary industry) = Qingchuan (the tertiary industry) > Cangxi (the secondary industry) = Chaotian (the tertiary industry).