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How to promote energy conservation in China’s chemical industry

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  • Lin, Boqiang
  • Long, Houyin

Abstract

Fossil fuel consumption in China’s chemical industry accounted for 19.7% of the total industrial fossil fuel consumption, and the industry has become the second highest energy intensive sector in the country. Therefore, it is extremely urgent and important to study the problems related to fossil fuel consumption in the industry. This paper adopts the factor decomposition and the EG co-integration methods to investigate the influencing factors of fossil energy consumption and measure the saving potential of fossil fuel. The paper concludes that the influencing factors can be divided into positive driving factors (labor productivity effect and sector scale effect) and negative driving factors (energy intensity effect and energy structure effect). Among them, labor productivity and energy intensity are the main factors affecting fossil fuel demand. The largest saving potentials of fossil fuels are predicted to be 23.3Mtce in 2015 and 70.6Mtce in 2020 under the middle scenario and 46.8Mtce in 2015 and 100.5Mtce in 2020 under the ideal scenario, respectively. Finally, this paper provides some policy implications on fossil fuel conservation.

Suggested Citation

  • Lin, Boqiang & Long, Houyin, 2014. "How to promote energy conservation in China’s chemical industry," Energy Policy, Elsevier, vol. 73(C), pages 93-102.
  • Handle: RePEc:eee:enepol:v:73:y:2014:i:c:p:93-102
    DOI: 10.1016/j.enpol.2014.05.056
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    References listed on IDEAS

    as
    1. Lin, Boqiang & Zhang, Guoliang, 2013. "Estimates of electricity saving potential in Chinese nonferrous metals industry," Energy Policy, Elsevier, vol. 60(C), pages 558-568.
    2. Amarawickrama, Himanshu A. & Hunt, Lester C., 2008. "Electricity demand for Sri Lanka: A time series analysis," Energy, Elsevier, vol. 33(5), pages 724-739.
    3. Su, Bin & Huang, H.C. & Ang, B.W. & Zhou, P., 2010. "Input-output analysis of CO2 emissions embodied in trade: The effects of sector aggregation," Energy Economics, Elsevier, vol. 32(1), pages 166-175, January.
    4. Lin, Boqiang & Wu, Ya & Zhang, Li, 2011. "Estimates of the potential for energy conservation in the Chinese steel industry," Energy Policy, Elsevier, vol. 39(6), pages 3680-3689, June.
    5. Dowling, Paul & Russ, Peter, 2012. "The benefit from reduced energy import bills and the importance of energy prices in GHG reduction scenarios," Energy Economics, Elsevier, vol. 34(S3), pages 429-435.
    6. Yuan, Chaoqing & Liu, Sifeng & Wu, Junlong, 2010. "The relationship among energy prices and energy consumption in China," Energy Policy, Elsevier, vol. 38(1), pages 197-207, January.
    7. Greening, Lorna A. & Ting, Michael & Krackler, Thomas J., 2001. "Effects of changes in residential end-uses and behavior on aggregate carbon intensity: comparison of 10 OECD countries for the period 1970 through 1993," Energy Economics, Elsevier, vol. 23(2), pages 153-178, March.
    8. Meier, Alan & Rosenfeld, Arthur H. & Wright, Janice, 1982. "Supply curves of conserved energy for California's residential sector," Energy, Elsevier, vol. 7(4), pages 347-358.
    9. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    10. Jeong, Kyonghwa & Kim, Suyi, 2013. "LMDI decomposition analysis of greenhouse gas emissions in the Korean manufacturing sector," Energy Policy, Elsevier, vol. 62(C), pages 1245-1253.
    11. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    12. Mahmoud A. T Elkhafif, 1992. "Estimating Disaggregated Price Elasticities in Industrial Energy Demand," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 209-218.
    13. Li, Aijun & Zhang, Aizhen, 2012. "Will carbon motivated border tax adjustments function as a threat?," Energy Policy, Elsevier, vol. 47(C), pages 81-90.
    14. Greening, Lorna A. & Davis, William B. & Schipper, Lee, 1998. "Decomposition of aggregate carbon intensity for the manufacturing sector: comparison of declining trends from 10 OECD countries for the period 1971-1991," Energy Economics, Elsevier, vol. 20(1), pages 43-65, February.
    15. Zhang, Ming & Liu, Xiao & Wang, Wenwen & Zhou, Min, 2013. "Decomposition analysis of CO2 emissions from electricity generation in China," Energy Policy, Elsevier, vol. 52(C), pages 159-165.
    16. Lin, Boqiang & Li, Aijun, 2012. "Impacts of removing fossil fuel subsidies on China: How large and how to mitigate?," Energy, Elsevier, vol. 44(1), pages 741-749.
    17. Lin, Boqiang & Sun, Chuanwang, 2010. "Evaluating carbon dioxide emissions in international trade of China," Energy Policy, Elsevier, vol. 38(1), pages 613-621, January.
    18. Roinioti, Argiro & Koroneos, Christopher & Wangensteen, Ivar, 2012. "Modeling the Greek energy system: Scenarios of clean energy use and their implications," Energy Policy, Elsevier, vol. 50(C), pages 711-722.
    19. Ang, B.W. & Liu, F.L., 2001. "A new energy decomposition method: perfect in decomposition and consistent in aggregation," Energy, Elsevier, vol. 26(6), pages 537-548.
    20. Hasanbeigi, Ali & Morrow, William & Sathaye, Jayant & Masanet, Eric & Xu, Tengfang, 2013. "A bottom-up model to estimate the energy efficiency improvement and CO2 emission reduction potentials in the Chinese iron and steel industry," Energy, Elsevier, vol. 50(C), pages 315-325.
    21. Davidson, James E H, et al, 1978. "Econometric Modelling of the Aggregate Time-Series Relationship between Consumers' Expenditure and Income in the United Kingdom," Economic Journal, Royal Economic Society, vol. 88(352), pages 661-692, December.
    22. Zhang, Ming & Guo, Fangyan, 2013. "Analysis of rural residential commercial energy consumption in China," Energy, Elsevier, vol. 52(C), pages 222-229.
    23. Lin, Boqiang & Zhang, Li & Wu, Ya, 2012. "Evaluation of electricity saving potential in China's chemical industry based on cointegration," Energy Policy, Elsevier, vol. 44(C), pages 320-330.
    24. Su, Bin & Ang, B.W., 2010. "Input-output analysis of CO2 emissions embodied in trade: The effects of spatial aggregation," Ecological Economics, Elsevier, vol. 70(1), pages 10-18, November.
    25. Ang, B. W., 2004. "Decomposition analysis for policymaking in energy:: which is the preferred method?," Energy Policy, Elsevier, vol. 32(9), pages 1131-1139, June.
    26. Greening, Lorna A., 2004. "Effects of human behavior on aggregate carbon intensity of personal transportation: comparison of 10 OECD countries for the period 1970-1993," Energy Economics, Elsevier, vol. 26(1), pages 1-30, January.
    27. Galindo, Luis Miguel, 2005. "Short- and long-run demand for energy in Mexico: a cointegration approach," Energy Policy, Elsevier, vol. 33(9), pages 1179-1185, June.
    28. Greening, Lorna A. & Ting, Mike & Davis, William B., 1999. "Decomposition of aggregate carbon intensity for freight: trends from 10 OECD countries for the period 1971-1993," Energy Economics, Elsevier, vol. 21(4), pages 331-361, August.
    29. Türkekul, Berna & UnakItan, Gökhan, 2011. "A co-integration analysis of the price and income elasticities of energy demand in Turkish agriculture," Energy Policy, Elsevier, vol. 39(5), pages 2416-2423, May.
    30. B. W. Ang & Ki-Hong Choi, 1997. "Decomposition of Aggregate Energy and Gas Emission Intensities for Industry: A Refined Divisia Index Method," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 59-73.
    31. Jiang, Zhujun & Lin, Boqiang, 2012. "China's energy demand and its characteristics in the industrialization and urbanization process," Energy Policy, Elsevier, vol. 49(C), pages 608-615.
    32. Lin, Boqiang & Wu, Ya & Zhang, Li, 2012. "Electricity saving potential of the power generation industry in China," Energy, Elsevier, vol. 40(1), pages 307-316.
    33. Sun, J. W., 1998. "Changes in energy consumption and energy intensity: A complete decomposition model," Energy Economics, Elsevier, vol. 20(1), pages 85-100, February.
    34. Wang, Qunwei & Zhao, Zengyao & Zhou, Peng & Zhou, Dequn, 2013. "Energy efficiency and production technology heterogeneity in China: A meta-frontier DEA approach," Economic Modelling, Elsevier, vol. 35(C), pages 283-289.
    35. Zhang, ZhongXiang, 2003. "Why did the energy intensity fall in China's industrial sector in the 1990s? The relative importance of structural change and intensity change," Energy Economics, Elsevier, vol. 25(6), pages 625-638, November.
    36. Bian, Yiwen & He, Ping & Xu, Hao, 2013. "Estimation of potential energy saving and carbon dioxide emission reduction in China based on an extended non-radial DEA approach," Energy Policy, Elsevier, vol. 63(C), pages 962-971.
    37. Sanchez-Choliz, Julio & Duarte, Rosa, 2004. "CO2 emissions embodied in international trade: evidence for Spain," Energy Policy, Elsevier, vol. 32(18), pages 1999-2005, December.
    38. Li, Aijun & Lin, Boqiang, 2013. "Comparing climate policies to reduce carbon emissions in China," Energy Policy, Elsevier, vol. 60(C), pages 667-674.
    39. Kulshreshtha, Mudit & Parikh, Jyoti K., 2000. "Modeling demand for coal in India: vector autoregressive models with cointegrated variables," Energy, Elsevier, vol. 25(2), pages 149-168.
    40. Bhattacharyya, Subhes C. & Ussanarassamee, Arjaree, 2004. "Decomposition of energy and CO2 intensities of Thai industry between 1981 and 2000," Energy Economics, Elsevier, vol. 26(5), pages 765-781, September.
    41. Lin, Boqiang & Xie, Chunping, 2013. "Estimation on oil demand and oil saving potential of China's road transport sector," Energy Policy, Elsevier, vol. 61(C), pages 472-482.
    42. Sinton, Jonathan E. & Levine, Mark D., 1994. "Changing energy intensity in Chinese industry : The relatively importance of structural shift and intensity change," Energy Policy, Elsevier, vol. 22(3), pages 239-255, March.
    43. Park, Sung Y. & Zhao, Guochang, 2010. "An estimation of U.S. gasoline demand: A smooth time-varying cointegration approach," Energy Economics, Elsevier, vol. 32(1), pages 110-120, January.
    44. Worrell, Ernst & Price, Lynn & Martin, Nathan, 2001. "Energy efficiency and carbon dioxide emissions reduction opportunities in the US iron and steel sector," Energy, Elsevier, vol. 26(5), pages 513-536.
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