Optimal economic restructuring to reduce carbon emissions intensity using the projected gradient algorithm

2021 ◽  
Author(s):  
Canh Q. Le ◽  
Hoang-Mai T. Bui
Keyword(s):  
Carbon Emissions ◽  
Economic Restructuring ◽  
Gradient Algorithm ◽  
Projected Gradient ◽  
Emissions Intensity

scholarly journals An Examination of Green Credit Promoting Carbon Dioxide Emissions Reduction: A Provincial Panel Analysis of China

2021 ◽  
Vol 13 (13) ◽  
pp. 7148
Author(s):  
Wenjie Zhang ◽  
Mingyong Hong ◽  
Juan Li ◽  
Fuhong Li
Keyword(s):  
Carbon Dioxide ◽  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Industrial Structure ◽  
Emissions Reduction ◽  
Green Finance ◽  
Carbon Emissions Reduction ◽  
Negative Effect ◽  
Emissions Intensity ◽  
The Impact

The implementation of green finance is a powerful measure to promote global carbon emissions reduction that has been highly valued by academic circles in recent years. However, the role of green credit in carbon emissions reduction in China is still lacking testing. Using a set of panel data including 30 provinces and cities, this study focused on the impact of green credit on carbon dioxide emissions in China from 2006 to 2016. The empirical results indicated that green credit has a significantly negative effect on carbon dioxide emissions intensity. Furthermore, after the mechanism examination, we found that the promotion impacts of green credit on industrial structure upgrading and technological innovation are two effective channels to help reduce carbon dioxide emissions. Heterogeneity analysis found that there are regional differences in the effect of green credit. In the western and northeastern regions, the effect of green credit is invalid. Quantile regression results implied that the greater the carbon emissions intensity, the better the effect of green credit. Finally, a further discussion revealed there exists a nonlinear correlation between green credit and carbon dioxide emissions intensity. These findings suggest that the core measures to promote carbon emission reduction in China are to continue to expand the scale of green credit, increase the technology R&D investment of enterprises, and to vigorously develop the tertiary industry.

scholarly journals A Block Coordinate Descent-Based Projected Gradient Algorithm for Orthogonal Non-Negative Matrix Factorization

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 540
Author(s):  
Soodabeh Asadi ◽  
Janez Povh
Keyword(s):  
Matrix Factorization ◽  
Synthetic Data ◽  
Coordinate Descent ◽  
The Other ◽  
Gradient Algorithm ◽  
Block Coordinate Descent ◽  
Projected Gradient Method ◽  
Projected Gradient ◽  
Factorization Problem ◽  
Non Negative Matrix Factorization

This article uses the projected gradient method (PG) for a non-negative matrix factorization problem (NMF), where one or both matrix factors must have orthonormal columns or rows. We penalize the orthonormality constraints and apply the PG method via a block coordinate descent approach. This means that at a certain time one matrix factor is fixed and the other is updated by moving along the steepest descent direction computed from the penalized objective function and projecting onto the space of non-negative matrices. Our method is tested on two sets of synthetic data for various values of penalty parameters. The performance is compared to the well-known multiplicative update (MU) method from Ding (2006), and with a modified global convergent variant of the MU algorithm recently proposed by Mirzal (2014). We provide extensive numerical results coupled with appropriate visualizations, which demonstrate that our method is very competitive and usually outperforms the other two methods.

Convergence of carbon emissions intensity across Chinese industrial sectors

2018 ◽  
Vol 194 ◽  
pp. 179-192 ◽  
Author(s):  
Shiwei Yu ◽  
Xing Hu ◽  
Jing-li Fan ◽  
Jinhua Cheng
Keyword(s):  
Carbon Emissions ◽  
Industrial Sectors ◽  
Emissions Intensity

scholarly journals The Potential For Economic Growth And Carbon Dioxide Emissions Reduction: Using Input-Output Framework

2020 ◽  
Vol 214 ◽  
pp. 01038
Author(s):  
Lihao Sun ◽  
Yuxiang Shen
Keyword(s):  
Economic Growth ◽  
Carbon Emissions ◽  
Carbon Dioxide Emissions ◽  
Economic Structure ◽  
Emissions Reduction ◽  
Heat Power ◽  
Input Output ◽  
Key Factor ◽  
The Status ◽  
Emissions Intensity

As people’s living standards continue to ameliorate, people become more and more demanding of the status of eco-environment, and carbon emissions are a key factor affecting the eco-environment. We analyze the carbon emissions intensity and carbon emissions potential of different sectors in China based on the input-output model. The results show that the sector of Production and Supply of Electric Power and Heat Power has the highest embodied carbon emissions intensity because the sector provides the country with necessary electricity and heat power for its economic growth. In addition, this paper determines the key carbon emissions sectors using elasticity method, and the results show that Construction is the most influential carbon emissions sector in the future. By restricting key carbon emissions sectors and encouraging the non-key carbon emissions sectors, we can take into account both economic development and carbon emissions reduction with the multi-objective model. The results show that under the present economic scale of China, carbon emissions can decrease from 11591 million ton to 11011 million ton, with a difference of 580 million ton. This indicates that with the assurance of present economic growth, we can achieve the goal of reducing carbon emissions by adjusting the economic structure. Based on results of this paper, we have also made recommendations for adjusting the economic structure to achieve emission reduction targets.

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 Carbon emissions intensity ratio: an indicator for an improved carbon labelling scheme

2012 ◽  
Vol 7 (1) ◽  
pp. 014014 ◽  
Author(s):  
Rui Zhao ◽  
Pauline Deutz ◽  
Gareth Neighbour ◽  
Michael McGuire
Keyword(s):  
Carbon Emissions ◽  
Intensity Ratio ◽  
Emissions Intensity ◽  
Labelling Scheme
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