『Abstract
The study evaluates the energy saving potential of the Chinese
steel industry by studying its potential future energy efficiency
gap. In order to predict the future energy efficiency gap, a multivariate
regression model combined with risk analysis is developed to estimate
future energy intensity of China's steel industry. It is found
that R&D intensity, energy saving investment, labor productivity
and industry concentration are all important variables that affect
energy intensity. We assess the possible measures as to how China's
steel industry can narrow the energy efficiency gap with Japan
by means of scenario analysis. Using Japan's current energy efficiency
level as baseline, the energy saving potential of China's steel
industry is more than 200 million ton coal equivalent in 2008,
and it would fall to zero in 2020. However, if greater efforts
were made to conserve energy, it would be possible to narrow down
the energy efficiency gap between China and Japan by around 2015.
Finally, using the results of the scenario analysis, future policy
priorities for energy conservation in China's steel industry are
assessed in this paper.
Keywords: Energy saving potential; China's steel industry; Risk
analysis』
1. Introduction
2. Literature review
3. Comparison of steel industry between China and Japan
3.1. Comparison of energy efficiency
3.2. Comparison of technology, investment, labor, structure,
etc.
3.2.1. R&D intensity (RDI)
3.2.2. Energy saving investment per unit of steel (VP)
3.2.3. Labor productivity (LP)
3.2.4. Industry concentration (CR10)
3.2.5. Other factors
4. Methodology and data sources
4.1. Methodology
4.1.1. multivariate linear regression model
4.1.2. Risk analysis
4.2. Data sources
5. Results and discussion
5.1. Current energy saving potential
5.2. Results of multivariate linear regression analysis
5.2.1. Equation of energy intensity
5.2.2. Application of fitting equation
5.3. Results of risk analysis
5.4. Future energy saving potential in different scenarios
5.4.1. Timetable of energy intensity
5.4.2. Energy saving potential
6. Conclusions and policy implications
Acknowledgments
References