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Estimation of energy saving potential in China's paper industry

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  • Lin, Boqiang
  • Moubarak, Mohamed

Abstract

The objective of this paper is to estimate the energy saving potential in China's paper industry by determining energy intensity under different scenarios. Cointegration model and stability test are applied to formulate the equilibrium equation. Results show that energy price, industry structure, profit margin and technology have significant impact as they are negatively correlated to changes in energy intensity. Three scenarios (BAU (business as usual), intermediate and active) are designed to estimate the future trend of energy intensity in paper industry. In 2010, the energy intensity (energy consumption per unit of value added) was 4 tce/10,000 RMB, and by the scenarios it is expected to considerably decline. According to the BAU (business as usual) scenario, the energy intensity will decrease to 2.56, 1.43 and 0.70 tce/10,000 RMB by 2015, 2020 and 2025, respectively. With respect to the intermediate scenario it is expected to drop further to 0.44 tce/10,000 RMB. Yet by the active scenario, the energy intensity is expected to considerably decline to 0.36 tce/10,000 RMB by 2025. Using the BAU forecast as a baseline, the quantity of energy savings is estimated to be 185.6 billion tce by 2025. Considering this important potential, we also provided some policy suggestions.

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  • Lin, Boqiang & Moubarak, Mohamed, 2014. "Estimation of energy saving potential in China's paper industry," Energy, Elsevier, vol. 65(C), pages 182-189.
  • Handle: RePEc:eee:energy:v:65:y:2014:i:c:p:182-189
    DOI: 10.1016/j.energy.2013.12.014
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    Cited by:

    1. Adom, Philip Kofi, 2015. "Determinants of energy intensity in South Africa: Testing for structural effects in parameters," Energy, Elsevier, vol. 89(C), pages 334-346.
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    3. Adom, Philip Kofi, 2015. "Business cycle and economic-wide energy intensity: The implications for energy conservation policy in Algeria," Energy, Elsevier, vol. 88(C), pages 334-350.
    4. repec:eee:energy:v:155:y:2018:i:c:p:782-795 is not listed on IDEAS
    5. Fei, Rilong & Lin, Boqiang, 2016. "Energy efficiency and production technology heterogeneity in China's agricultural sector: A meta-frontier approach," Technological Forecasting and Social Change, Elsevier, vol. 109(C), pages 25-34.
    6. repec:eee:energy:v:161:y:2018:i:c:p:284-298 is not listed on IDEAS
    7. Loganthurai, P. & Rajasekaran, V. & Gnanambal, K., 2016. "Evolutionary algorithm based optimum scheduling of processing units in rice industry to reduce peak demand," Energy, Elsevier, vol. 107(C), pages 419-430.
    8. Park, Nyun-Bae & Park, Sang Yong & Kim, Jong-Jin & Choi, Dong Gu & Yun, Bo Yeong & Hong, Jong Chul, 2017. "Technical and economic potential of highly efficient boiler technologies in the Korean industrial sector," Energy, Elsevier, vol. 121(C), pages 884-891.
    9. Lin, Boqiang & Du, Kerui, 2014. "Measuring energy efficiency under heterogeneous technologies using a latent class stochastic frontier approach: An application to Chinese energy economy," Energy, Elsevier, vol. 76(C), pages 884-890.
    10. repec:eee:energy:v:140:y:2017:i:p1:p:1047-1058 is not listed on IDEAS
    11. Lin, Boqiang & Wang, Ailun, 2015. "Estimating energy conservation potential in China's commercial sector," Energy, Elsevier, vol. 82(C), pages 147-156.
    12. Sucic, Boris & Al-Mansour, Fouad & Pusnik, Matevz & Vuk, Tomaz, 2016. "Context sensitive production planning and energy management approach in energy intensive industries," Energy, Elsevier, vol. 108(C), pages 63-73.
    13. Adom, Philip Kofi, 2016. "The transition between energy efficient and energy inefficient states in Cameroon," Energy Economics, Elsevier, vol. 54(C), pages 248-262.
    14. Boqiang Lin & Weisheng Liu, 2017. "Scenario Prediction of Energy Consumption and CO 2 Emissions in China’s Machinery Industry," Sustainability, MDPI, Open Access Journal, vol. 9(1), pages 1-18, January.
    15. Lin, Boqiang & Wang, Xiaolei, 2014. "Promoting energy conservation in China's iron & steel sector," Energy, Elsevier, vol. 73(C), pages 465-474.
    16. Jiang, Xuemei & Zhu, Kunfu & Green, Christopher, 2015. "China's energy saving potential from the perspective of energy efficiency advantages of foreign-invested enterprises," Energy Economics, Elsevier, vol. 49(C), pages 104-112.
    17. repec:eee:rensus:v:89:y:2018:i:c:p:216-227 is not listed on IDEAS
    18. Li, Ke & Lin, Boqiang, 2014. "The nonlinear impacts of industrial structure on China's energy intensity," Energy, Elsevier, vol. 69(C), pages 258-265.
    19. Adom, Philip Kofi, 2015. "Asymmetric impacts of the determinants of energy intensity in Nigeria," Energy Economics, Elsevier, vol. 49(C), pages 570-580.
    20. Li, Ke & Lin, Boqiang, 2015. "The improvement gap in energy intensity: Analysis of China's thirty provincial regions using the improved DEA (data envelopment analysis) model," Energy, Elsevier, vol. 84(C), pages 589-599.
    21. repec:eee:rensus:v:81:y:2018:i:p2:p:2421-2430 is not listed on IDEAS
    22. Lin, Hsin-Chiu & Chan, David Yih-Liang & Lin, Wei-Chun & Hsu, Chung-Hsuan & Hong, Gui-Bing, 2014. "Status of energy conservation in Taiwan's pulp and paper industry," Energy, Elsevier, vol. 73(C), pages 680-685.

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