Scenario analysis of carbon emissions' anti-driving effect on Qingdao's energy structure adjustment with an optimization model, Part Ⅰ: Carbon emissions peak value prediction

Abstract

Abstract: Taking Qingdao as a case study, an extended STIRPAT model was introduced to determine the relationship between CO2 emissions and different driving factors (permanent resident population, economic level, technical level, urbanization level, energy consumption structure, service level, and foreign trade degree) based on the SPSS statistical software as well as the relevant data of Qingdao from 1988 to 2014. Combined with the satisfactory fitting results and model verification, it can be found that the STIRPAT model could be applied to the prediction of Qingdao's future CO2 emissions. To check the impact of different combinations of driving factors on CO2 emissions, scenario analysis was employed in this study, and Qingdao's CO2 emissions during the period 2015–2030 and corresponding amount as well as occurrence time of carbon emissions peak values under different scenarios were acquired. Finally, several policy recommendations were put forward to ensure the smooth implementation of Qingdao Low-carbon Development Program (2014–2020). The results could not only provide a theoretical foundation for Qingdao to build the management framework of carbon emissions peak value, set reasonable targets of social-economic development and carbon emissions reduction, but also help decision makers enact appropriate measures of energy conservation and emission reduction.