scholarly journals The Analysis of CO2Emissions and Reduction Potential in China’s Transport Sector

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Wei Li ◽  
Hao Li ◽  
Huixia Zhang ◽  
Shuang Sun
Keyword(s):  
Carbon Emissions ◽  
Emission Reduction ◽  
Reduction Potential ◽  
Intensity Change ◽  
Dominant Factor ◽  
Transport Sector ◽  
Intensity Effect ◽  
Future Emission ◽  
Policy Guidance ◽  
Kaya Identity

China’s transport sector is responsible for approximately 10% of national CO2emissions. In the process of industrialization and urbanization of China, emissions from transport sector would continuously increase. In order to investigate the emissions and reduction potential and provide the policy guidance for policymakers in China’s transport sector, this study decomposed the CO2emissions using the Kaya identity, calculated the contribution based on the Logarithmic Mean Divisia Index (LMDI) method to explore the underlying determinants of emissions change, and then constructed different scenarios to predict the emissions and estimate the potential of emission reduction in the future. Results indicated that carbon emissions in China’s transport sector have increased from 123.14 Mt in 1995 to 670.76 Mt in 2012. Income effect is the dominant factor that results in the increase of emissions while energy intensity effect is the main driving force to lower carbon emissions. The transportation modal shifting, transportation intensity change, and population growth have the positive but relatively minor impact on emissions. The accumulated emission reduction is expected to be 1825.97 Mt, which is 3 times more than the emissions in 2010. Policy recommendations are thus put forward for future emission reduction.

scholarly journals Decomposition of China’s Carbon Emissions Intensity from 1995 to 2010: An Extended Kaya Identity

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Wei Li ◽  
Qing-Xiang Ou
Keyword(s):  
Carbon Emissions ◽  
Emission Reduction ◽  
Energy Intensity ◽  
Industrial Structure ◽  
Energy Structure ◽  
Logarithmic Mean ◽  
Development Path ◽  
Optimal Outcomes ◽  
Emissions Intensity ◽  
Kaya Identity

This paper employs an extended Kaya identity as the scheme and utilizes the Logarithmic Mean Divisia Index (LMDI II) as the decomposition technique based on analyzing CO2emissions trends in China. Change in CO2emissions intensity is decomposed from 1995 to 2010 and includes measures of the effect of Industrial structure, energy intensity, energy structure, and carbon emission factors. Results illustrate that changes in energy intensity act to decrease carbon emissions intensity significantly and changes in industrial structure and energy structure do not act to reduce carbon emissions intensity effectively. Policy will need to significantly optimize energy structure and adjust industrial structure if China’s emission reduction targets in 2020 are to be reached. This requires a change in China’s economic development path and energy consumption path for optimal outcomes.

scholarly journals Research on carbon emission potential of electric vehicles and fuel vehicles

2021 ◽  
Vol 236 ◽  
pp. 01025
Author(s):  
Qiang Zhou ◽  
Wanfu Liu ◽  
Wuqin Qi
Keyword(s):  
Power Generation ◽  
Electric Vehicles ◽  
Carbon Emissions ◽  
Emission Reduction ◽  
Carbon Emission ◽  
Reduction Potential ◽  
Energy Structure ◽  
Carbon Reduction ◽  
Generation Structure ◽  
Coal Power

Electric vehicles are considered as a effective tool for energy conservation and emission reduction, Because of its zero direct carbon emissions. However, thermal power generation accounts for a large proportion in China's power generation structure, so the indirect carbon emissions of electric vehicles must be considered. In order to further study the carbon emission potential of electric vehicles compared with traditional fuel vehicles, the direct carbon emission of fuel vehicles and the indirect carbon emission of battery electric vehicles were calculated. The results show that the carbon reduction effect of electric vehicles is obvious, and the coal power technology and the energy structure of power generation have great influence on the carbon reduction potential of electric vehicles. Based on this, suggestions are put forward to promote electric vehicles and fully release their emission reduction potential from the aspects of enhancing consumers' perception of social value, improving energy structure and improving coal power technology.

Framework for accounting for tourism carbon emissions in China: An industrial linkage perspective

2020 ◽  
pp. 135481662092489
Author(s):  
Jianping Zha ◽  
Rong Fan ◽  
Yao Yao ◽  
Lamei He ◽  
Yuanyuan Meng
Keyword(s):  
Carbon Emissions ◽  
Emission Reduction ◽  
Carbon Emission ◽  
Tourism Industry ◽  
Broad Sense ◽  
Structure Effect ◽  
Energy Structure ◽  
Narrow Sense ◽  
Intensity Effect ◽  
Carbon Emission Reduction

Understanding tourism carbon emissions and their influencing factors from the perspective of industrial linkages can inform policy-making in the development of sustainable tourism. Based on a combination of the environmental input–output (I-O) model and structural decomposition analysis, this article develops a novel framework for analyzing the industrial linkage pathways of China’s carbon emissions linked to tourism and identifying the driving factors affecting change in carbon emissions embodied in the supply chain. Results reveal that most carbon emissions linked to China’s broad-sense or narrow-sense tourism industry derive from some critical upstream industries, that is, indirect carbon emissions resulting from the intermediate production processes. Significant differences exist in the industrial linkage pathways of carbon emissions between tourism subsectors; thus, emission reduction policies for the broad-sense or narrow-sense tourism industry should be formulated based on these key interindustrial linkage pathways. The direct energy consumption intensity effect and energy structure effect are beneficial to carbon emission reduction, while the I-O structure effect reverses the effect on carbon emission reduction from negative to positive.

scholarly journals Estimating Smart Grid’s Carbon Emission Reduction Potential in China’s Manufacturing Industry Based on Decomposition Analysis

2021 ◽  
Vol 9 ◽  
Author(s):  
Hua Fu ◽  
Yingying Shi ◽  
Yongchao Zeng
Keyword(s):  
Smart Grid ◽  
Carbon Emissions ◽  
Emission Reduction ◽  
Carbon Emission ◽  
Manufacturing Industry ◽  
Reduction Potential ◽  
Driving Forces ◽  
Decomposition Analysis ◽  
Carbon Emission Reduction ◽  
Emission Reduction Potential

China has a large manufacturing industry and shoulders the responsibility of reducing carbon emissions. Smart grid technologies can integrate multiple renewable energy technologies, which possess significant potential in reducing carbon emissions. To estimate the carbon emission reduction potential of the smart grid in China’s manufacturing industry, this paper applies a temporal logarithmic mean Divisia index (LMDI) method to analyze the driving forces of carbon emission changes in the whole manufacturing industry and 28 sub-industries from 2000 to 2017, respectively. The results reveal that industrial activity and energy intensity are the key factors leading to the increase and mitigation of carbon emissions, respectively. Sub-industries with high emission intensity are crucial for the reduction of carbon emissions in the manufacturing industry. By applying a smart grid, the carbon emissions could be reduced by 27.51% in the optimistic scenario.

Analysis and Quantitative Evaluation of Power Grid Corporation’s Carbon Emission Reduction Potential

2014 ◽  
Vol 1073-1076 ◽  
pp. 2624-2629
Author(s):  
Xiao Xuan Zhang ◽  
Li Ma ◽  
Su Yang ◽  
Tao Cai
Keyword(s):  
Quantitative Evaluation ◽  
Carbon Emissions ◽  
Emission Reduction ◽  
Carbon Emission ◽  
Reduction Potential ◽  
Power Grid ◽  
Emissions Reduction ◽  
Carbon Emission Reduction ◽  
Emission Reduction Potential ◽  
Carbon Emissions Reduction

As an important part of energy industry, power grid plays a pivotal and irreplaceable role in promoting low-carbon development. In this paper, the carbon emission reduction potential of power grid corporation was systematically analyzed from qualitative and quantitative perspectives respectively. First, this paper discussed the pathways of power grid corporation’s carbon emissions reduction, including decreasing line loss, promoting clean energy development, and so on. Then, a quantitative evaluation model for carbon emissions reduction potential of power grid corporation was developed. Based on the model, the carbon emission reduction benefits that promoted and achieved by State Grid Corporation of China (SGCC) in 2010 and 2015 were calculated. The results show that the carbon emission reduction benefits of SGCC is 138 million tons in 2010, and will be 481.8 million tons in 2015.

Driving Factors of Carbon Emissions in China's Municipalities: A LMDI Approach

2021 ◽  
Author(s):  
Yuanxin Liu ◽  
Yajing Jiang ◽  
Hui Liu ◽  
Bo Li ◽  
Jia-hai Yuan
Keyword(s):  
Carbon Emissions ◽  
Emission Reduction ◽  
Industrial Structure ◽  
Driving Factors ◽  
Policy Implications ◽  
Growth Effect ◽  
Structure Effect ◽  
Energy Structure ◽  
Intensity Effect ◽  
Population Effect

Abstract China, as the world’s largest carbon dioxide emitter, is bound to assume the important responsibility of energy conservation and emission reduction. To this end, each city, led by representative municipalities directly under the Central Government, must enhance efforts in carbon emission reduction to jointly realize China’s low-carbon transition. Taking four representative municipalities, namely, Beijing, Tianjin, Shanghai, and Chongqing as the case cities, this paper establishes a decomposition analysis for the driving factors of carbon emissions by applying the LMDI method covering data from 2007 to 2017. Kaya identity is used to decompose the effects into eight driving factors: GDP effect, industrial structure effect, energy intensity effect, overall energy structure effect, population effect, urbanization effect, per capita energy consumption effect, urban and rural energy structure effect. The results show that at the municipality level, the driving factors that promote the growth of carbon emissions are the GDP growth effect and the population effect, with the former still being the most important factor in the municipalities with faster economic growth; and industrial structure effect is the most important factor that inhibits the growth of carbon emissions, followed by energy structure effect. The paper thereby puts forward policy implications for China's economic policies.

scholarly journals The Evolution of Factors Influencing Green Technological Progress in Terms of Carbon Reduction: A Spatial-Temporal Tactic Within Agriculture Industries of China

2021 ◽  
Vol 9 ◽  
Author(s):  
Deng Yue ◽  
Apurbo Sarkar ◽  
Cui Yu ◽  
Lu Qian ◽  
Zhao Minjuan
Keyword(s):  
Carbon Emissions ◽  
Emission Reduction ◽  
Technological Progress ◽  
Carbon Emission ◽  
Reduction Potential ◽  
Stochastic Frontier ◽  
Green Technology ◽  
Carbon Emission Reduction ◽  
Agriculture Industry ◽  
Emission Reduction Potential

The impacts of widespread carbon emission trends possessed tremendous pressure for global food security, sustainable development, and ecosystems. Several temporal and spatial patterns of green technology have been adopted to reduce carbon emissions in different regions of China. In China, agriculture industries may have colossal importance for reducing carbon emissions. On the basis of the data from 1998 to 2018, the study uses the heterogeneous stochastic frontier model to quantify the carbon emission reduction potential of agricultural green technology progress in eastern, central, and western regions of China by using the heterogeneous stochastic frontier model. We also analyze the coefficient of variation and its spatial and temporal evolution pattern of carbon intensity decline potential index and explore the potential factors related to the agriculture green technology progress of China. The finding of the study revealed that the carbon emission rate in the agriculture industry of China is very high, whereas adopting green technology is slower because of economic and policy-related factors—the carbon emission of green technological progress. In terms of spatial variations, the changes in various regions were consistent with the overall fluctuating rate compared with the state of another country, but an increasing trend has been traced within the “east-central-west” regions. The overall regional differences are gradually trending, but differences between regions mainly cause them. The increase in the structure of the agricultural agriculture industry, the level of labor, and the increase in administrative environmental regulations will weaken the obstacles to the carbon emission reduction potential of green technological progress. The increase in urbanization, the level of the agricultural economy, and economic and environmental regulations will increase the carbon emission reduction potential of green technological progress. It is necessary to actively promote exchanges and cooperation in green agricultural technology and advanced management concepts, accelerate the optimization and upgrading of the industrial structure, and achieve the goal of peaking carbon emissions through regional coordinated development. Regionally, the overall external environment and the level of green technology progress in the western region need to be improved in all respects. The central and eastern regions need to focus on combining different policy tools to transform them from hindrance to promotion.

Sign in / Sign up

Export Citation Format

Share Document