Peaking Industrial Energy-Related CO2 Emissions in Typical Transformation Region: Paths and Mechanism
| Autor: | Junnian Song, Zhiyuan Duan, Xize Dong, Xian'en Wang, Haiyan Duan |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
020209 energy
stirpat model lcsh:TJ807-830 Geography Planning and Development lcsh:Renewable energy sources co2 emissions 02 engineering and technology 010501 environmental sciences Management Monitoring Policy and Law reduction path 01 natural sciences industrial energy consumption 0202 electrical engineering electronic engineering information engineering Baseline (configuration management) lcsh:Environmental sciences 0105 earth and related environmental sciences lcsh:GE1-350 Clean coal Renewable Energy Sustainability and the Environment lcsh:Environmental effects of industries and plants Environmental engineering Energy consumption Clean coal technology peak lcsh:TD194-195 Industrialisation Greenhouse gas Energy intensity Environmental science Energy (signal processing) |
| Zdroj: | Sustainability, Vol 12, Iss 3, p 791 (2020) Sustainability Volume 12 Issue 3 |
| ISSN: | 2071-1050 |
| Popis: | Reducing CO2 emissions of industrial energy consumption plays a significant role in achieving the goal of CO2 emissions peak and decreasing total CO2 emissions in northeast China. This study proposed an extended STIRPAT model to predict CO2 emissions peak of industrial energy consumption in Jilin Province under the four scenarios (baseline scenario (BAU), energy-saving scenario (ESS), energy-saving and low-carbon scenario (ELS), and low-carbon scenario (LCS)). We analyze the influences of various factors on the peak time and values of CO2 emissions and explore the reduction path and mechanism to achieve CO2 emissions peak in industrial energy consumption. The results show that the peak time of the four scenarios is respectively 2026, 2030, 2035 and 2043, and the peak values are separately 147.87 million tons, 16.94 million tons, 190.89 million tons and 22.973 million tons. Due to conforming to the general disciplines of industrial development, the result in ELS is selected as the optimal scenario. The impact degrees of various factors on the peak value are listed as industrial CO2 emissions efficiency of energy consumption > industrialized rate > GDP > urbanization rate > industrial energy intensity > the share of renewable energy consumption. But not all factors affect the peak time. Only two factors including industrial clean-coal and low-carbon technology and industrialized rate do effect on the peak time. Clean coal technology, low carbon technology and industrial restructuring have become inevitable choices to peak ahead of time. However, developing clean coal and low-carbon technologies, adjusting the industrial structure, promoting the upgrading of the industrial structure and reducing the growth rate of industrialization can effectively reduce the peak value. Then, the pathway and mechanism to reducing industrial carbon emissions were proposed under different scenarios. The approach and the pathway and mechanism are expected to offer better decision support to targeted carbon emission peak in northeast of China. |
| Databáze: | OpenAIRE |
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