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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
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 tra...
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Published in: | Journal of cleaner production 2018-01, Vol.172, p.466-474 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | 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.
•A typical STIRPAT model was extended and introduced into this study.•Relationship between CO2 emissions and different driving factors was determined.•Qingdao's CO2 emissions during the period 2015–2030 were predicted.•Carbon emissions peak values of Qingdao under different scenarios were acquired. |
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ISSN: | 0959-6526 1879-1786 |
DOI: | 10.1016/j.jclepro.2017.10.216 |