scholarly journals Industrial Structure Optimization and Low-Carbon Transformation of Chinese Industry Based on the Forcing Mechanism of CO2 Emission Peak Target

2021 ◽  
Vol 13 (8) ◽  
pp. 4417
Author(s):  
Feng Wang ◽  
Changhai Gao ◽  
Wulin Zhang ◽  
Danwen Huang
Keyword(s):  
Co2 Emissions ◽  
Co2 Emission ◽  
Carbon Emission ◽  
Industrial Structure ◽  
Objective Assessment ◽  
Structure Optimization ◽  
Emission Peak ◽  
Low Carbon ◽  
Chinese Industry ◽  
Industrial Structure Optimization

The setting of a CO2 emission peak target (CEPT) will have a profound impact on Chinese industry. An objective assessment of this impact is of great significance, both for understanding/applying the forcing mechanism of CEPT, and for promoting the optimization of China’s industrial structure and the low-carbon transformation of Chinese industry at a lower cost. Based on analysis of the internal logic and operation of the forcing mechanism of CEPT, we employed the STIRPAT model. This enabled us to predict the peak path of China’s CO2 emissions, select the path values that would achieve the CEPT with the year 2030 as the constraint condition, construct a multi-objective and multi-constraint input/output optimization model, employ the genetic algorithm to solve the model, and explore the industrial structure optimization and low-carbon transformation of Chinese industry. The results showed that the setting of CEPT will have a significant suppression effect on high-carbon emission industries and a strong boosting effect on low-carbon emission industries. The intensity of the effect is positively correlated with the target intensity of the CO2 emissions peak. Under the effect of the forcing mechanism of CEPT, Chinese industry can realize a low-carbon transition and the industrial structure can realize optimization. The CEPT is in line with sustainable development goals, but the setting of CEPT may risk causing excessive shrinkage of basic industries—which should be prevented.

Analysis of Industrial Structure Optimization Based on Energy Saving

2014 ◽  
Vol 986-987 ◽  
pp. 219-222
Author(s):  
Ying Ying Cao ◽  
Ya Ling Zou
Keyword(s):  
Energy Saving ◽  
Industrial Structure ◽  
Technology Policy ◽  
Supply And Demand ◽  
Optimal Path ◽  
Structure Optimization ◽  
Industry Structure ◽  
Energy Industry ◽  
Low Carbon ◽  
Industrial Structure Optimization

The industrial structure optimization based on energy saving is different from the traditional industrial structure optimization. It relays on the supply and demand of industrial structure. It takes low carbon cycle, energy conservation and environmental protection as guiding principles and maximization of the use of resource and minimization of production from environmental pollution as the goals. Innovation of technology has also be taken as a means to help industry be sustainable, healthy and orderly and to shape an industrial optimization model that economy, society, nature are harmoniously existed. In this paper, we have an analysis of the energy industry structure to point out the shortages of the structure, technology, policy, talent and so on in energy industry. Then based on these shortages we explored the optimal path of industrial structure for energy saving.

scholarly journals Pulp and Paper Industry: Decarbonisation Technology Assessment to Reach CO2 Neutral Emissions—An Austrian Case Study

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1161
Author(s):  
Maedeh Rahnama Mobarakeh ◽  
Miguel Santos Silva ◽  
Thomas Kienberger
Keyword(s):  
Energy Consumption ◽  
Co2 Emissions ◽  
Emission Reduction ◽  
Co2 Emission ◽  
Manufacturing Industry ◽  
Paper Industry ◽  
Heat Pumps ◽  
Pulp And Paper ◽  
Low Carbon ◽  
Co2 Emission Reduction

The pulp and paper (P&P) sector is a dynamic manufacturing industry and plays an essential role in the Austrian economy. However, the sector, which consumes about 20 TWh of final energy, is responsible for 7% of Austria’s industrial CO2 emissions. This study, intending to assess the potential for improving energy efficiency and reducing emissions in the Austrian context in the P&P sector, uses a bottom-up approach model. The model is applied to analyze the energy consumption (heat and electricity) and CO2 emissions in the main processes, related to the P&P production from virgin or recycled fibers. Afterward, technological options to reduce energy consumption and fossil CO2 emissions for P&P production are investigated, and various low-carbon technologies are applied to the model. For each of the selected technologies, the potential of emission reduction and energy savings up to 2050 is estimated. Finally, a series of low-carbon technology-based scenarios are developed and evaluated. These scenarios’ content is based on the improvement potential associated with the various processes of different paper grades. The results reveal that the investigated technologies applied in the production process (chemical pulping and paper drying) have a minor impact on CO2 emission reduction (maximum 10% due to applying an impulse dryer). In contrast, steam supply electrification, by replacing fossil fuel boilers with direct heat supply (such as commercial electric boilers or heat pumps), enables reducing emissions by up to 75%. This means that the goal of 100% CO2 emission reduction by 2050 cannot be reached with one method alone. Consequently, a combination of technologies, particularly with the electrification of the steam supply, along with the use of carbon-free electricity generated by renewable energy, appears to be essential.

Carbon Emission of Mining Industry’s Energy Consumption in Heilongjiang Province

2015 ◽  
Vol 1092-1093 ◽  
pp. 1597-1600
Author(s):  
Zhong Hua Wang ◽  
Xin Ye Chen
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Carbon Emission ◽  
Industrial Structure ◽  
Mining Industry ◽  
Calculation Model ◽  
Energy Utilization ◽  
Utilization Efficiency ◽  
Heilongjiang Province ◽  
Low Carbon

The need to reduce carbon emission in Heilongjiang Province of China is urgent challenge facing sustainable development. This paper aims to make explicit the problem-solving of carbon emission to find low carbon emission ways. According to domestic and foreign literatures on estimating and calculating carbon emissions and by integrating calculation methods of carbon emissions, it was not possible to consider all of the many contributions to carbon emissions. Calculation model of carbon emissions suitable to this paper is selected. The carbon emissions of energy consumption in mining industry are estimated and calculated from 2005 to 2012, and the characteristics of carbon emission are analyzed at the provincial level. It makes the point that carbon emissions of energy consumption in mining industry can be reduced when we attempt to alter energy consumption structure, adjust industrial structure and improve energy utilization efficiency.

scholarly journals The Regional Inequity of CO2 Emissions per Capita in China

2017 ◽  
Vol 9 (7) ◽  
pp. 228 ◽  
Author(s):  
Ting Liu ◽  
Wenqing Pan
Keyword(s):  
Co2 Emissions ◽  
Emission Reduction ◽  
Co2 Emission ◽  
Energy Intensity ◽  
Industrial Structure ◽  
Theil Index ◽  
Energy Structure ◽  
Co2 Emission Reduction ◽  
Index Method ◽  
Per Capita

This paper combines Theil index method with factor decomposition technique to analyze China eight regions’ inequality of CO2 emissions per capita, and discuss energy structure, energy intensity, industrial structure, and per capita output’s impacts on inequality. This research shows that: (1) The trend of China regional carbon inequality is in the opposite direction to the per capita CO2 emission level. Namely, as the per capita CO2 emission levels rise, regional carbon inequality decreases, and vice versa. (2) Per capita output factor reduces regional carbon inequality, whereas energy structure factor and energy intensity factor increase the inequality. (3) More developed areas can reduce the carbon inequality by improving the energy structure, whereas the divergence of energy intensity in less developed areas has increased to expand the carbon inequity. Thus, when designing CO2 emission reduction targets, policy makers should consider regional differences in economic development level and energy efficiency, and refer to the main influencing factors. At the same time, upgrading industrial structure and upgrading energy technologies should be combined to meet the targets of economic growth and CO2 emission reduction.

scholarly journals Spatio-Temporal Analysis of CO2 Emission Driving Force in Various Provinces in China Using the Extended STIRPAT-GWR Model

2021 ◽  
Author(s):  
Yulin Zhang
Keyword(s):  
Co2 Emissions ◽  
Co2 Emission ◽  
Energy Intensity ◽  
Industrial Structure ◽  
Temporal Analysis ◽  
Energy Structure ◽  
High Effect ◽  
Northern Regions ◽  
Spatio Temporal ◽  
Gwr Model

To fill the shortcomings of traditional research that ignores the driver’s own spatial characteristics and provide a theoretical support to formulate suitable emission reduction policies in different regions across China. In this pursuit, based on the panel data of provincial CO2 emission in 2007, 2012, and 2017, the present study employed the extended environmental impact assessment model (STIRPAT-GWR model) to study the effect of population, energy intensity, energy structure, urbanization and industrial structure on the CO2 emissions in 29 provinces across China. The empirical results show that the effect of drivers on the CO2 emissions exhibited significant variations among the different provinces. The effect of population in the southwest region was significantly lower than that of the central and eastern regions. Provinces with stronger energy intensity effects were concentrated in the central and western regions. The effect of energy structure in the eastern and northern regions was relatively strong, and gradually weakened towards the southeast region. The areas with high urbanization effect were concentrated in the central and the eastern regions. Furthermore, significant changes were observed in the high-effect regions of the industrial structure in 2017. The high-effect area showed a migration from the northwest and northeast regions in 2007 and 2012, respectively, to the southwest and southeast regions in 2017. Urbanization showed the strongest effect on the CO2 emissions, followed by population and energy intensity, and the weakest effect was exhibited by the energy and industrial structure. Thus, the effects of population and energy structure showed a downward trend, in contrary to the effect of urbanization on the CO2 emissions in China.

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