Retraction Notice: Analysis on Carbon Emission Situation of Chinese Export Industry Based on Input-Output Model

2018 ◽  
Vol 11 (1) ◽  
pp. 70-70
Author(s):  
Jiang Yuan
Keyword(s):  
Carbon Emission ◽  
Input Output ◽  
Export Industry ◽  
Chinese Export ◽  
Retraction Notice

Analysis on Carbon Emission Situation of Chinese Export Industry Based on Input-Output Model

2015 ◽  
Vol 8 (1) ◽  
pp. 172-175 ◽  
Author(s):  
Jiang Yuan
Keyword(s):  
Global Economy ◽  
Carbon Emission ◽  
Main Trend ◽  
Low Carbon ◽  
Input Output ◽  
Low Carbon Economy ◽  
Export Industry ◽  
International Pressure ◽  
Chinese Export ◽  
Carbon Economy

Low carbon economy development undoubtedly becomes the main trend of social development in future under the background of the global climate change and the increasing international pressure to reduce emissions. However, the international trade, as part of the global economy, will be carried out in accordance with the rules of low carbon economy. Therefore, it has important significance to study the relation between the carbon emission and export trade and deeply excavate carbon reduction potential of Chinese industry production for finding way to reduce carbon emission in China and striving for the carbon emission reduction space from the international. This paper constructed the input-output model to calculate the CO2 emission density of Chinese export industry according to the input-output theory, and then basically analyzed the situation of carbon emission of export industry.

Three-scale input–output modeling for urban economy: Carbon emission by Beijing 2007

2013 ◽  
Vol 18 (9) ◽  
pp. 2493-2506 ◽  
Author(s):  
G.Q. Chen ◽  
Shan Guo ◽  
Ling Shao ◽  
J.S. Li ◽  
Zhan-Ming Chen
Keyword(s):  
Carbon Emission ◽  
Urban Economy ◽  
Input Output

scholarly journals The Changes of Carbon Emission in China’s Industrial Sectors from 2002 to 2010: A Structural Decomposition Analysis and Input-Output Subsystem

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Guoxing Zhang ◽  
Mingxing Liu
Keyword(s):  
Carbon Emissions ◽  
Emission Intensity ◽  
Carbon Emission ◽  
Decomposition Analysis ◽  
Final Demand ◽  
Good Effect ◽  
Input Output ◽  
Carbon Emission Intensity ◽  
Industrial Sectors ◽  
Three Components

Based on 2002–2010 comparable price input-output tables, this paper first calculates the carbon emissions of China’s industrial sectors with three components by input-output subsystems; next, we decompose the three components into effect of carbon emission intensity, effect of social technology, and effect of final demand separately by structure decomposition analysis; at last, we analyze the contribution of every effect to the total emissions by sectors, thus finding the key sectors and key factors which induce the changes of carbon emissions in China’s industrial sectors. Our results show that in the latest 8 years five departments have gotten the greatest increase in the changes of carbon emissions compare with other departments and the effect of final demand is the key factor leading to the increase of industrial total carbon emissions. The decomposed effects show a decrease in carbon emission due to the changes of carbon emission intensity between 2002 and 2010 compensated by an increase in carbon emissions caused by the rise in final demand of industrial sectors. And social technological changes on the reduction of carbon emissions did not play a very good effect and need further improvement.

scholarly journals Inter-Regional Spillover of Carbon Emissions and Employment in China: Is It Positive or Negative?

2019 ◽  
Vol 11 (13) ◽  
pp. 3622 ◽  
Author(s):  
Wenbin Shao ◽  
Fangyi Li ◽  
Zhaoyang Ye ◽  
Zhipeng Tang ◽  
Wu Xie ◽  
...  
Keyword(s):  
Economic Development ◽  
Carbon Emissions ◽  
Decomposition Method ◽  
Carbon Emission ◽  
Spillover Effects ◽  
Efficiency Improvement ◽  
Input Output ◽  
Coastal Regions ◽  
Regional Trade ◽  
Positive Spillover

International and inter-regional trade in China has been promoted, the economic and environmental impacts of which are significant in regional development. In this paper, we analyzed the evolution of inter-regional spillover of carbon emissions and employment in China from 2007 to 2012 with structural decomposition method and multi-regional input-output tables. The index of carbon emission per employee (ICE) is designed and compared to indicate positive or negative spillover effects. We find that carbon emissions grow much more rapidly in interior regions than in coastal regions, due to spillover effects and own influences. Spillover effects rarely reduce the ICE of destination regions, but the own influences can decrease it in most regions. Although spillover may contribute to economic development in most regions, it is hardly a driver of efficiency improvement in destination regions. Based on these empirical findings, we put forward specific suggestions to improve the positive spillover effects on different kinds of regions.

An Analysis of Carbon Footprint of Beijing Based on Input-Output Model

2013 ◽  
Vol 807-809 ◽  
pp. 1052-1058
Author(s):  
Zhe Wang ◽  
Yu Li ◽  
Ze Hong Li ◽  
Liang Yuan ◽  
Ji Zheng
Keyword(s):  
Carbon Footprint ◽  
Carbon Emission ◽  
Manufacturing Industry ◽  
Industrial Sector ◽  
Human Society ◽  
Low Carbon ◽  
Input Output ◽  
Low Carbon Economy ◽  
Leontief Matrix ◽  
Annual Carbon

Climate change caused by increasing carbon emission is harmful to global environment and human society. Developing low-carbon economy through reasonable industries planning and effective utilization of resources is a significant path to achieve the aim of energy saving and carbon emission reduction. The word carbon footprint means carbon emission caused by a certain industry, activity, product or individual, and the issue of carbon emission should be linked with economic activity to analyze, while input-output model is a reliable method to contact two factors. Based on input-output model, this paper calculated direct or indirect carbon emission which is demanded for the products of final consumption in Beijing, and analyzed carbon footprint of each industrial sector in 2005, 2007 and 2010 by operating Leontief matrix. The result demonstrates annual carbon emission of Beijing increased from 10482.68×104ton to 17407.28×104ton during 2000-2011. Manufacturing industry, excavating industry, transportation and postal industry exert supreme impact on carbon emission in Beijing. Carbon footprint of transportation and postal industry and other tertiary industries such as information, business, service, education, science researching industries in 2010 had an obvious rise compare with the data of 2005 and 2007.

scholarly journals Exploring Potential Pathways toward Energy-Related Carbon Emission Reduction in Heavy Industrial Regions of China: An Input–Output Approach

2020 ◽  
Vol 12 (5) ◽  
pp. 2148 ◽  
Author(s):  
Jingyao Peng ◽  
Yidi Sun ◽  
Junnian Song ◽  
Wei Yang
Keyword(s):  
Energy Consumption ◽  
Co2 Emissions ◽  
Emission Intensity ◽  
Emission Reduction ◽  
Co2 Emission ◽  
Carbon Emission ◽  
Input Output ◽  
Carbon Emission Reduction ◽  
Industrial Regions ◽  
Co2 Emission Intensity

It is a very urgent issue to reduce energy-related carbon emissions in China. The three northeastern provinces (Heilongjiang (HLJ), Jilin (JL), and Liaoning (LN)) are typical heavy industrial regions in China, playing an important role in the national carbon emission reduction target. In this study, we analyzed the energy consumption, carbon dioxide (CO2) emissions, and CO2 emission intensity of each sector in the three regions, and we compared them with the national level and those of China’s most developed province Guangdong (GD). Then, based on an input–output (I–O) framework, linkage analysis of production and CO2 emission from sector–system and sector–sector dimensions was conducted. The results showed that the three regions accounted for about 1/10 of China’s energy consumption and 1/6 of China’s CO2 emissions in 2012. In addition, the level of energy structure, CO2 emission intensity, and sectoral structure lagged behind China’s average level, much lower than those for GD. According to the sectoral characteristics of each region and unified backward/forward linkages of production and CO2 emissions, we divided sectoral clusters into those whose development was to be encouraged and those whose development was to be restricted. The results of this paper could provide policy–makers with reference to exploring potential pathways toward energy-related carbon emission reduction in heavy industrial regions.

scholarly journals Dynamic Characteristic Analysis of Indirect Carbon Emissions Caused by Chinese Urban and Rural Residential Consumption Based on Time Series Input-Output Tables from 2002 to 2011

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Guoxing Zhang ◽  
Mingxing Liu ◽  
Xiulin Gao
Keyword(s):  
Time Series ◽  
Carbon Emissions ◽  
Rural Areas ◽  
Carbon Emission ◽  
Urban Residents ◽  
Input Output ◽  
Characteristic Analysis ◽  
Growth Trend ◽  
Rural And Urban ◽  
Residential Consumption

Carbon emissions caused by residential consumption have become one of the main sources of carbon emission and revealed a huge growth trend in China. By processing data of Chinese input-output tables available and relative Statistical Yearbook, this paper uses RAS method to update the input-output tables to obtain the time series input-output tables from 2002 to 2011. Then, we use input-output method to make a contrastive analysis of changes in carbon emissions caused by Chinese rural and urban residents’ consumption. The results show that the indirect carbon emission caused by urban residents’ consumption is the main part of carbon emission caused by residents’ consumption, and the gap between carbon emission caused by urban and rural residents’ consumption is wider and wider. The annual per capita indirect carbon emissions in urban and rural areas increase by years, and the increment of the town is much greater than that of the country. At last, we analyze carbon emissions from residents’ consumption by sectors and obtain some meaningful results. In accordance with the above conclusions, the paper puts forward some countermeasures and suggestions from consumer behaviors, structure of consumption, energy usage, and so on.

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