Decomposition analysis of energy efficiency in China’s Beijing-Tianjin-Hebei region

• Autorzy: Li W. , Zhang H.
• Języki publikacji: EN

Abstrakty

EN

This manuscript first gives a separate decomposition analysis on the factors that affect regional energy efficiency in Beijing, Tianjin, and Hebei, China, during 2005-12 based on the logarithmic mean divisia index (LMDI) model, and then makes an in-depth investigation on impact factors in the Beijing-Tianjin-Hebei (BTH) region of China. Energy efficiency is decomposed into carbon productivity, carbon emission coefficient, energy structure, energy intensity, economic output, and reciprocal effect of per capita energy consumption. Different impact factors in various areas have diverse influences on energy efficiency due to the evident regional differences in Beijing, Tianjin, and Hebei. On the whole, the primary positive driver of energy efficiency is the economic output in the BTH region, followed by carbon productivity, carbon emission coefficient, and energy structure. However, energy intensity and the reciprocal effect of per capita energy consumption are the major inhibitory factors. Finally, we emphasize a series of policy implications to speed up the achievement of China’s 12th Five-Year Plan goal. It also has the vital practical significance of carrying out energy policy and a low-carbon economic development strategy in the BTH region in the future.

• Wydawca: -
• Czasopismo: Polish Journal of Environmental Studies
• Rocznik: 2017
• Tom: 26
• Numer: 1
• Opis fizyczny: p.189-203,fig.,ref.

Twórcy

autor

Li W.

• School of Economics and Management, North China Electric Power University, Baoding, Hebei 071003, China
• Philosophy and Social Science Research Base of Hebei Province, North China Electric Power University, Baoding, Hebei 071003, China

autor

Zhang H.

• School of Economics and Management, North China Electric Power University, Baoding, Hebei 071003, China

Bibliografia

• 1. NBSC (National Bureau of Statistics of China). China Statistics Yearbook of 2014. China Statistics Press; 2014.
• 2. NBS (National Bureau of Statistics of the People’s Republic of China). China energy statistical yearbook 2005-2013. China Statistics Press; 2013.
• 3. Ang B.W., Zhang F.Q. A survey of index decomposition analysis in energy and environmental studies. Energy, 25, 1149, 2000.
• 4. Liao H., Wei Y.M. China›s energy consumption: a perspective from Divisia aggregation approach. Energy, 35, 28, 2010.
• 5. Zhao X., Li N., Ma C. Residential energy consumption in urban China: a decomposition analysis. Energy Policy, 41, 644, 2012.
• 6. Kahrl F., Roland-Holst D., Zilberman D. Past as Prologue? Understanding energy use in post-2002 China. Energy Econ. 36, 759, 2012.
• 7. Ang B.W. Decomposition analysis for policymaking in energy: which is the preferred method? Energy Policy, 32, 1131, 2004.
• 8. Ang B.W., Liu F.L. A new energy decomposition method: perfect in decomposition and consistent in aggregation. Energy, 26, 537, 2001.
• 9. Ang B.W. The LMDI approach to decomposition analysis: a practical guide. Energy Policy, 33, 867, 2005.
• 10. Xu M., Li R., Crittenden J.C., Chen Y.S. CO₂ emissions embodied in China’s exports from 2002 to 2008: a structural decomposition analysis. Energy Policy, 39, 7381, 2011.
• 11. Du H.B., Guo J.H., Mao G.Z., Smith A.M., Wang X.X., Wang Y. CO₂ emissions embodied in China-US trade: Input-output analysis based on the emergy/dollar ratio. Energy Policy, 39, 5980, 2011.
• 12. Wang Y., Zhao H.Y., Li L.Y., Liu Z., Liang S. Carbon dioxide emission drivers for a typical metropolis using input-output structural decomposition analysis. Energy Policy, 58, 312, 2013.
• 13. Ang B.W., Zhang F.Q. Inter-regional comparisons of energy-related CO₂ emissions using the decomposition technique. Energy, 24, 297, 1999.
• 14. Zhang J.Y., Zhang Y., Yang Z.F., Fath B.D., Li S.S. Estimation of energy-related carbon emissions in Beijing and factor decomposition analysis. Ecol. Model. 252, 258, 2013.
• 15. Shao C.F., Guan Y., Wan Z., Guo C.X., Chu C.L., Ju M.T. Performance and decomposition analyses of carbon emissions from industrial energy consumption in Tianjin, China. J. Clean. Prod. 64, 590, 2013.
• 16. Wang W.X., Kuang Y.Q., Huang N.S. Study on the Decomposition of Factors Affecting Energy-Related Carbon Emissions in Guangdong Province, China. Energies, 4, 2249, 2011.
• 17. O’Mahony T. Decomposition of Ireland’s carbon emissions from 1990 to 2010: An extended Kaya identity. Energy Policy, 59, 573, 2013.
• 18. Wang C.J., Wang F., Zhang H.O. Carbon Emissions Decomposition and Environmental Mitigation Policy Recommendations for Sustainable Development in Shandong Province. Sustainability, 6, 8164, 2014.
• 19. Chen Y.N., Lin S. Study on factors affecting energyrelated per capita carbon dioxide emission by multi-sectoral of cities: a case study of Tianjin. Natural Hazards, 77, 833, 2015.
• 20. Ang B.W., Zhang F.Q., Choi K.H. Factorizing changes in energy and environmental indicators through decomposition. Energy, 23, 489, 1998.
• 21. Wang C., Chen J., Zou J. Decomposition of energy-related CO₂ emission in China: 1957-2000. Energy, 30, 73, 2005.
• 22. Wen L., Cao Y., Weng J.F. Factor decomposition analysis of China's energy-related CO₂ emissions using extended STIRPAT model. Pol. J. Environ. Stud. 24, 2261, 2015.
• 23. Zhou G.H., Chung W., Zhang Y.X. Carbon dioxide emissions and energy efficiency analysis of China’s regional thermal electricity generation. J. Clean. Prod. 83, 173, 2014.
• 24. Balezentis A. The energy intensity in Lithuania during 1995-2009: A LMDI approach. Energy Policy, 39, 7322, 2011.
• 25. Wen L., Liu Y.J. The peak value of carbon emissions in the Beijing-Tianjin-Hebei region based on the STIRPAT model and scenario design. Pol. J. Environ. Stud. 25, 823, 2016.
• 26. Lin B.Q., Long H.Y. How to promote energy conservation in China’s chemical industry. Energy Policy, 73, 93, 2014.
• 27. Wang Z.H., Zeng H.L., Wei Y.M., Zhang Y.X. Regional total factor energy efficiency: an empirical analysis of industrial sector in China. Appl Energy, 97, 115, 2012.
• 28. Shao C., Guan Y., Wan Z., Chu C., Ju M. Performance analysis of CO₂ emissions and energy efficiency of metal industries in China. J Environ Manag. 134, 30, 2014.
• 29. He F., Zhang Q., Lei J., Fu W., Xu X. Energy efficiency and productivity change of China›s iron and steel industry: accounting for undesirable outputs. Energy Policy, 54, 204, 2012.
• 30. Li Y., Sun L., Feng T. How to reduce energy intensity in China: a regional comparison perspective. Energy Policy, 61, 513, 2013.
• 31. Yuan Y., Zha J. Study on the supply capacity of crop residue as energy in rural areas of Heilongjiang province of China. Renew Sustain Energy Rev. 38, 526, 2014.
• 32. Wu Y. Energy intensity and its determinants in China's regional economies. Energy Policy, 41, 703, 2012.
• 33. Lee J.J. Can we accelerate the improvement of energy efficiency in aircraft systems? Energy Convers Manage. 51, 189, 2010.
• 34. He H., Jim C.Y. Coupling model of energy consumption with changes in environmental utility. Energy Policy, 43, 235, 2012.
• 35. IPCC, Intergovernmental Panel on Climate Change Guidelines for National Greenhouse Gas Inventories, OECD, Paris, France, 1999.

Identyfikatory

DOI

10.15244/pjoes/65290