Scenario Simulation of the Industrial Sector Carbon Dioxide Emission Reduction Effect
Qiaozhi Zhao1, Qingyou Yan2, Herui Cui1, Hairui Zhao1
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1North China Electric Power University, 619 North Yong-hua Street, Baoding, China
2North China Electric Power University, 2 Bei-nong Road, Beijing, China
Submission date: 2017-04-24
Final revision date: 2017-06-02
Acceptance date: 2017-06-04
Online publication date: 2017-10-17
Publication date: 2017-11-07
Pol. J. Environ. Stud. 2017;26(6):2841–2850
Differentiated carbon dioxide emission reduction targets and optimizing industrial incentive policy is an important subject in China’s low-carbon economic transformation. With the application of the environmental input-output (EIO) method and the bi-proportional scaling updating schedule, the inter-industrial inputoutput tables in 2017 are forecasted and then carbon dioxide emissions of 30 industrial sectors are simulated in seven scenarios. Based on these results, conclusions are:
1. Twenty-five high carbon dioxide emission sectors among 30 national sectors are divided into three types. Five sectors are whole-process high carbon dioxide emission type, 18 are conductive type, and two are apparent high type.
2. Final demands keep the dominant role in pushing sectorial emissions growing, whether in total carbon dioxide emission intensity or emission quantities. Technical progress leads to emissions declines in intensity and quantity. Moreover, special energy-saving technical progress will gradually exceed universal technical progress in reduction effects. Whole-process high carbon sectors are the best selection to gain favorable incentive policies to promote carbon dioxide emissions reduction. Apparent high carbon sectors are in last place.
3. With incentive policies being improved, technical progress reduction effect is increasing. However, it is not enough to offset the driving effect from final demands growing in seven scenarios. More favorable incentives and investments should be allocated into high emission sectors, especially into the most sensitive ones.