Abstract
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.
Highlights
The Paris Agreement, which came into effect in 2015, requires countries to report on the long-term strategy for low-carbon development in 2050 [1]
Combined the energy consumption situation in Jilin Province in recent years and the method provided by Intergovernmental Panel on Climate Change (IPCC) guidance catalog, the medium mode is set to reach the average level around 2020 of the European Union (EU) developed countries by 2050, in which this value is about 2.0 tCO2/tce; the high mode is set to reach the average level around 2030 of the EU developed countries by 2050, in which this value is about 1.5 tCO2/tce [22]
The results show that CO2 emissions from industrial energy consumption in Jilin Province increase first and decrease in different scenarios, which is basically consistent with most research results
Summary
The Paris Agreement, which came into effect in 2015, requires countries to report on the long-term strategy for low-carbon development in 2050 [1]. According to existing research, influencing factors such as population, economic output, investment intensity, and energy structure are the drivers for the increase of CO2 emissions, and only the positive effect of energy intensity on CO2 emissions reduction is almost unanimously recognized. Taking northeast China as the research area, some scholars have carried out relevant studies to analyze the influencing factors of CO2 emissions in old industrial bases, CO2 emissions peak prediction, and CO2 emissions reduction countermeasures. In order to fill in the gap, this study empirically explored the main driving path and mechanism of CO2 emissions peak in industrial energy consumption from the perspective of peak by associating taking Jilin Province as the target area from 1995 to 2015.
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