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A process-level hierarchical structural decomposition analysis (SDA) of energy consumption in an integrated steel plant

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Abstract

A hierarchical structural decomposition analysis (SDA) model has been developed based on process-level input-output (I-O) tables to analyze the drivers of energy consumption changes in an integrated steel plant during 2011-2013. By combining the principle of hierarchical decomposition into D&L method, a hierarchical decomposition model for multilevel SDA is obtained. The developed hierarchical IO-SDA model would provide consistent results and need less computation effort compared with the traditional SDA model. The decomposition results of the steel plant suggest that the technology improvement and reduced steel final demand are two major reasons for declined total energy consumption. The technical improvements of blast furnaces, basic oxygen furnaces, the power plant and the by-products utilization level have contributed mostly in reducing energy consumption. A major retrofit of ancillary process units and solving fuel substitution problem in the sinter plant and blast furnace are important for further energy saving. Besides the empirical results, this work also discussed that why and how hierarchical SDA can be applied in a process-level decomposition analysis of aggregated indicators.

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References

  1. SU B, ANG B W. Structural decomposition analysis applied to energy and emissions: Some methodological developments [J]. Energy Economics, 2012, 34(1): 177–188.

    Article  Google Scholar 

  2. SHAHIDUZZAMAN M, LAYTON A. Changes in CO2 emissions over business cycle recessions and expansions in the United States: A decomposition analysis [J]. Applied Energy, 2015, 150: 25–35.

    Article  Google Scholar 

  3. SUMABAT A K, LOPEZ N S, YU K D, HAO H, LI R, GENG Y, CHIU A S. Decomposition analysis of Philippine CO2 emissions from fuel combustion and electricity generation [J]. Applied Energy, 2016, 164: 795–804.

    Article  Google Scholar 

  4. CANSINO J M, ROMÁN R, ORDÓÑEZ M. Main drivers of changes in CO2 emissions in the Spanish economy: A structural decomposition analysis [J]. Energy Policy, 2016, 89: 150–159.

    Article  Google Scholar 

  5. ANDREONI V, GALMARINI S. Drivers in CO2 emissions variation: A decomposition analysis for 33 world countries [J]. Energy, 2016, 103: 27–37.

    Article  Google Scholar 

  6. TIMMA L, ZOSS T, BLUMBERGA D. Life after the financial crisis. Energy intensity and energy use decomposition on sectorial level in Latvia [J]. Applied Energy, 2016, 162: 1586–1592.

    Google Scholar 

  7. FERNÁNDEZ GONZÁLEZ P. Exploring energy efficiency in several European countries. An attribution analysis of the Divisia structural change index [J]. Applied Energy, 2015, 137: 364–374.

    Google Scholar 

  8. YUAN B, REN S, CHEN X. The effects of urbanization, consumption ratio and consumption structure on residential indirect CO2 emissions in China: A regional comparative analysis [J]. Applied Energy, 2015, 140: 94–106.

    Article  Google Scholar 

  9. LAN J, MALIK A, LENZEN M, MCBAIN D, KANEMOTO K. A structural decomposition analysis of global energy footprints [J]. Applied Energy, 2016, 163: 436–451.

    Article  Google Scholar 

  10. SHAO S, LIU J, GENG Y, MIAO Z, YANG Y. Uncovering driving factors of carbon emissions from China’s mining sector [J]. Applied Energy, 2016, 166: 220–238.

    Article  Google Scholar 

  11. GAMBHIR A, TSE L K C, TONG D, MARTINEZ-BOTAS R. Reducing China’s road transport sector CO2 emissions to 2050: Technologies, costs and decomposition analysis [J]. Applied Energy, 2015, 157: 905–917.

    Article  Google Scholar 

  12. LIU Z, GENG Y, ADAMS M, DONG L, SUN L, ZHAO J, DONG H, WU J, TIAN X. Uncovering driving forces on greenhouse gas emissions in China’ aluminum industry from the perspective of life cycle analysis [J]. Applied Energy, 2016, 166: 253–263.

    Article  Google Scholar 

  13. KARMELLOS M, KOPIDOU D, DIAKOULAKI D. A decomposition analysis of the driving factors of CO2 (Carbon dioxide) emissions from the power sector in the European Union countries [J]. Energy, 2016, 94: 680–692.

    Article  Google Scholar 

  14. ALISES A, VASSALLO J M, AYMERICH M. Comparison of road freight transport trends in Europe: Results of an input-output structural decomposition analysis [C]// Transportation Research Board 94th Annual Meeting. Washington, D.C.: TRB, 2015: 1–15.

    Google Scholar 

  15. TAN X, DONG L, CHEN D, GU B, ZENG Y. China’s regional CO2 emissions reduction potential: A study of Chongqing city [J]. Applied Energy, 2016, 162: 1345–1354.

    Article  Google Scholar 

  16. LU Q, YANG H, HUANG X, CHUAI X, WU C. Multi-sectoral decomposition in decoupling industrial growth from carbon emissions in the developed Jiangsu Province, China [J]. Energy, 2015, 82: 414–425.

    Article  Google Scholar 

  17. WANG Z, LIU W. Determinants of CO2 emissions from household daily travel in Beijing, China: Individual travel characteristic perspectives [J]. Applied Energy, 2015, 158: 292–299.

    Article  Google Scholar 

  18. XIA X H, HU Y, ALSAEDI A, HAYAT T, WU X D, CHEN G Q. Structure decomposition analysis for energy-related GHG emission in Beijing: Urban metabolism and hierarchical structure [J]. Ecological Informatics, 2015, 26(1): 60–69.

    Article  Google Scholar 

  19. ZHI Y, YANG Z, YIN X A, HAMILTON P B, ZHANG L. Evaluating and forecasting the drivers of water use in a city: Model development and a case from Beijing [J]. Journal of Water Resources Planning and Management, 2015, 142(1): 04015042.

    Article  Google Scholar 

  20. LIN X, POLENSKE K R. Input-output modeling of production processes for business management [J]. Structural Change and Economic Dynamics, 1998, 9(2): 205–226.

    Article  Google Scholar 

  21. ALBINO V, DIETZENBACHER E, KÜHTZ S. Analysing materials and energy flows in an industrial district using an enterprise input–output model [J]. Economic Systems Research, 2003, 15(4): 457–480.

    Article  Google Scholar 

  22. JUNG J, von der ASSEN N, BARDOW A. Comparative LCA of multi-product processes with non-common products: A systematic approach applied to chlorine electrolysis technologies [J]. The International Journal of Life Cycle Assessment, 2013, 18(4): 828–839.

    Article  Google Scholar 

  23. MILLER R E, BLAIR P D. Input-output analysis: Foundations and extensions [M]. New York: Cambridge University Press, 2009.

    Book  MATH  Google Scholar 

  24. DIETZENBACHER E, LOS B. Structural decomposition techniques: sense and sensitivity [J]. Economic Systems Research, 1998, 10(4): 307–324.

    Article  Google Scholar 

  25. SEIBEL S. Decomposition analysis of carbon dioxide-emission changes in Germany-Conceptual framework and empirical results [J]. Luxembourg: Office for Official Publications of the European Communities, European Communities, 2003.

    Google Scholar 

  26. SONIS M, HEWINGS G J, GAZEL R. The structure of multi-regional trade flows: Hierarchy, feedbacks and spatial linkages [J]. The Annals of Regional Science, 1995, 29(4): 409–430.

    Article  Google Scholar 

  27. DIETZENBACHER E, LOS B. Structural decomposition analyses with dependent determinants [J]. Economic Systems Research, 2000, 12(4): 497–514.

    Article  Google Scholar 

  28. KAGAWA S, INAMURA H. A structural decomposition of energy consumption based on a hybrid rectangular input-output framework: Japan’s case [J]. Economic Systems Research, 2001, 13(4): 339–363.

    Article  Google Scholar 

  29. WU J H, CHEN Y Y, HUANG Y H. Trade pattern change impact on industrial CO2 emissions in Taiwan [J]. Energy Policy, 2007, 35(11): 5436–5446.

    Article  Google Scholar 

  30. LIU X, WANG Hong-tao, CHEN J, HE Q, ZHANG H, JIANG R, CHEN X. Method and basic model for development of Chinese reference life cycle database of fundamental industries [J]. Acta Scientiae Circumstantiae, 2010, 30(10): 2136–2144.

    Google Scholar 

  31. WORLDSTEEL. CO2 emissions data collection (User Guide, version 6) [R]. Brussels: Worldsteel Association, 2012.

    Google Scholar 

  32. NORGATE T, HAQUE N. Energy and greenhouse gas impacts of mining and mineral processing operations [J]. Journal of Cleaner Production, 2010, 18(3): 266–274.

    Article  Google Scholar 

  33. MARINKOVIC S, RADONJANIN V, MALEŠEV M, IGNJATOVIC I. Comparative environmental assessment of natural and recycled aggregate concrete [J]. Waste management, 2010, 30(11): 2255–2264.

    Article  Google Scholar 

  34. JIANG R, WANG H, ZHANG H, CHEN X. Life cycle assessment of cement technologies in China and recommendations [J]. Acta Scientiae Circumstantiae, 2010, 30(11): 2361–2368.

    Google Scholar 

  35. CHEN C, HABERT G, BOUZIDI Y, JULLIEN A, VENTURA A. LCA allocation procedure used as an incitative method for waste recycling: An application to mineral additions in concrete [J]. Resources, Conservation and Recycling, 2010, 54(12): 1231–1240.

    Article  Google Scholar 

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Correspondence to Sheng-ming Liao  (廖胜明).

Additional information

Foundation item: Project(2012GK2025) supported by Science-Technology Plan Foundation of Hunan Province, China; Project(2013zzts039) supported by the Fundamental Research Funds for Central South University, China

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Liu, Xj., Liao, Sm., Rao, Zh. et al. A process-level hierarchical structural decomposition analysis (SDA) of energy consumption in an integrated steel plant. J. Cent. South Univ. 24, 402–412 (2017). https://doi.org/10.1007/s11771-017-3442-8

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  • DOI: https://doi.org/10.1007/s11771-017-3442-8

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