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Measuring the Energy Saving and CO2 Emissions Reduction Potential Under China’s Belt and Road Initiative

  • Yue-Jun Zhang
  • Yan-Lin Jin
  • Bo Shen
Article
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Abstract

Belt and Road Initiative (BRI) countries are major energy producers and consumers in the world, and they have enormous potential for energy cooperation, energy saving, and CO2 emissions reduction due to their various resource endowments. However, little quantitative research has been conducted under the BRI in the same framework. Therefore, by developing a data envelopment analysis optimisation model combined with the window analysis method, this paper investigates the energy performance of BRI countries for the period from 1995 to 2015, and evaluate the potential of energy saving and CO2 emissions reduction for each BRI country. The results show that, first, the average energy performance of 56 BRI countries is about 0.69, with evident difference across regions and countries. Specifically, in Sub-Saharan Africa and Europe and Central Asia, energy performance is relatively lower, and their averages are 0.59 and 0.60, respectively; in particular, Ukraine has the lowest energy performance among the 56 BRI countries (0.24); while the energy performance in Middle East and North Africa and South Asia appears relatively higher (0.80 and 0.89, respectively). Second, these 56 BRI countries have great energy saving potential, about 9.95 billion metric tonnes of oil equivalent from 1995 to 2015. Among them, Europe and Central Asia, East Asia and Pacific, and Middle East and North Africa make relatively larger contribution. Finally, these 56 BRI countries may produce potential CO2 emissions reduction of 50.87 billion metric tonnes during the study period, and Europe and Central Asia and East Asia and Pacific contribute the most (45.18% and 25.53%, respectively).

Keywords

Belt and Road Initiative Energy saving CO2 emissions reduction Data envelopment analysis 

Notes

Acknowledgements

We are grateful to the financial support from the National Natural Science Foundation of China (Nos. 71273028, 71322103, 71774051), National Program for Support of Top-notch Young Professionals (No. W02070325), Changjiang Scholars Program of the Ministry of Education of China (No. Q2016154), Hunan Youth Talent Program and Hunan Province Graduate Student Research and Innovation Project (No. CX2017B131). We also would like to thank the kind help of Prof. Ling-Yun He with Jinan University, China, and appreciate the seminar participants at Center for Resource and Environmental Management of Hunan University for their insightful discussions.

References

  1. Adler, N., Friedman, L., & Sinuany-Stern, Z. (2002). Review of ranking methods in the data envelopment analysis context. European Journal of Operational Research, 140(2), 249–265.CrossRefGoogle Scholar
  2. Al-Mulali, U., & Ozturk, I. (2015). The effect of energy consumption, urbanization, trade openness, industrial output, and the political stability on the environmental degradation in the MENA (Middle East and North African) region. Energy, 84, 382–389.CrossRefGoogle Scholar
  3. Beirne, J., Beulen, C., Liu, G., & Mirzaei, A. (2013). Global oil prices and the impact of China. China Economic Review, 27(4), 37–51.CrossRefGoogle Scholar
  4. Berlemann, M., & Wesselhöft, J. E. (2014). Estimating aggregate capital stocks using the perpetual inventory method. Review of Economics, 65(1), 1–34.CrossRefGoogle Scholar
  5. Bian, Y., He, P., & Xu, H. (2013). Estimation of potential energy saving and carbon dioxide emission reduction in China based on an extended non-radial DEA approach. Energy Policy, 63(4), 962–971.CrossRefGoogle Scholar
  6. Camanho, A. S., & Dyson, R. G. (1999). Efficiency, size, benchmarks and targets for bank branches: An application of data envelopment analysis. Journal of the Operational Research Society, 50(9), 903–915.CrossRefGoogle Scholar
  7. Charnes, A., & Cooper, W. W. (1984). Preface to topics in data envelopment analysis. Annals of Operations Research, 2(1), 59–94.CrossRefGoogle Scholar
  8. Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429–444.CrossRefGoogle Scholar
  9. Chen, K., Kou, M., & Fu, X. (2018). Evaluation of multi-period regional R&D efficiency: An application of dynamic DEA to China’s regional R&D systems. Omega, 74, 103–114.CrossRefGoogle Scholar
  10. Cheng, L. K. (2016). Three questions on China’s “Belt and Road Initiative”. China Economic Review, 40, 309–313.CrossRefGoogle Scholar
  11. Choi, Y., Zhang, N., & Zhou, P. (2012). Efficiency and abatement costs of energy-related CO2 emissions in China: A slacks-based efficiency measure. Applied Energy, 98(5), 198–208.CrossRefGoogle Scholar
  12. Damari, Y., & Kissinger, M. (2018). An integrated analysis of households’ electricity consumption in Israel. Energy Policy, 119, 51–58.CrossRefGoogle Scholar
  13. Du, J., & Zhang, Y. (2018). Does One Belt One Road strategy promote Chinese overseas direct investment? China Economic Review, 47, 189–205.CrossRefGoogle Scholar
  14. Duan, F., Ji, Q., Liu, B. Y., & Fan, Y. (2018). Energy investment risk assessment for nations along China’s Belt & Road Initiative. Journal of Cleaner Production, 170, 535–547.CrossRefGoogle Scholar
  15. Fei, Y., Bi, G., Song, W., & Luo, Y. (2016). Measuring the efficiency of two-stage production process in the presence of undesirable outputs. Computational Economics (in press).Google Scholar
  16. Feng, C., & Wang, M. (2017). Analysis of energy efficiency and energy savings potential in China’s provincial industrial sectors. Journal of Cleaner Production, 164, 1531–1541.CrossRefGoogle Scholar
  17. Golany, B., & Roll, Y. (1989). An application procedure for DEA. Omega, 17(3), 237–250.CrossRefGoogle Scholar
  18. Goldsmith, R. W. (1951). A perpetual inventory of national wealth. In Studies in income and wealth (Vol. 14, pp. 5–73). National Bureau of Economic Research. http://www.nber.org/chapters/c9716.pdf
  19. Guo, X., Lu, C. C., Lee, J. H., & Chiu, Y. H. (2017). Applying the dynamic DEA model to evaluate the energy efficiency of OECD countries and China. Energy, 134, 392–399.CrossRefGoogle Scholar
  20. Han, L., Han, B., Shi, X., Su, B., Lv, X., & Lei, X. (2018). Energy efficiency convergence across countries in the context of China’s Belt and Road initiative. Applied Energy, 213, 112–122.CrossRefGoogle Scholar
  21. He, H. (2016). Key challenges and countermeasures with railway accessibility along the Silk Road. Engineering, 2(3), 288–291.CrossRefGoogle Scholar
  22. He, L. Y., & Chen, Y. (2013). Thou shalt drive electric and hybrid vehicles: Scenario analysis on energy saving and emission mitigation for road transportation sector in China. Transport Policy, 25, 30–40.CrossRefGoogle Scholar
  23. He, L. Y., & Ou, J. J. (2017). Pollution emissions, environmental policy, and marginal abatement costs. International Journal of Environmental Research and Public Health, 14(12), 1509–1524.CrossRefGoogle Scholar
  24. Huang, Y. (2016). Understanding China’s Belt & Road Initiative: Motivation, framework and assessment. China Economic Review, 40, 314–321.CrossRefGoogle Scholar
  25. Huang, J., Yu, Y., & Ma, C. (2018). Energy efficiency convergence in China: Catch-up, lock-in and regulatory uniformity. Environmental & Resource Economics, 70(1), 107–130.CrossRefGoogle Scholar
  26. Katircioglu, S. T. (2013). Interactions between energy and imports in Singapore: Empirical evidence from conditional error correction models. Energy Policy, 63(3), 514–520.CrossRefGoogle Scholar
  27. Kerr, R. A. (2011). Peak oil production may already be here. Science, 331(6024), 1510–1511.CrossRefGoogle Scholar
  28. Lai, L., & Guo, K. (2017). The performance of One Belt and One Road exchange rate: Based on improved singular spectrum analysis. Physica A, 483, 299–308.CrossRefGoogle Scholar
  29. Li, J., Wen, J., & Jiang, B. (2017). Spatial spillover effects of transport infrastructure in Chinese New Silk Road Economic Belt. International Journal of e-Navigation and Maritime Economy, 6, 1–8.CrossRefGoogle Scholar
  30. Liu, Z., Qin, C. X., & Zhang, Y. J. (2016a). Energy-environment efficiency of road and railway sectors in China: Evidence from the provincial level. Ecological Indicators, 69, 559–570.CrossRefGoogle Scholar
  31. Liu, X., Zhu, Q., Chu, J., Ji, X., & Li, X. (2016). Environmental performance and benchmarking information for coal-fired power plants in China: A DEA approach. Computational Economics (in press).Google Scholar
  32. Oh, T. H., & Chua, S. C. (2010). Energy efficiency and carbon trading potential in malaysia. Renewable and Sustainable Energy Reviews, 14(7), 2095–2103.CrossRefGoogle Scholar
  33. Oropeza-Perez, I., & Østergaard, P. A. (2014). Energy saving potential of utilizing natural ventilation under warm conditions—A case study of Mexico. Applied Energy, 130(5), 20–32.CrossRefGoogle Scholar
  34. Özkara, Y., & Atak, M. (2015). Regional total-factor energy efficiency and electricity saving potential of manufacturing industry in Turkey. Energy, 93, 495–510.CrossRefGoogle Scholar
  35. Scheel, H. (2001). Undesirable outputs in efficiency valuations. European Journal of Operational Research, 132(2), 400–410.CrossRefGoogle Scholar
  36. Schinas, O., & von Westarp, A. G. (2017). Assessing the impact of the Maritime Silk Road. Journal of Ocean Engineering and Science, 2(3), 186–195.CrossRefGoogle Scholar
  37. Shan, H. J. (2008). Reestimating the capital stock of China: 1952 ~ 2006. The Journal of Quantitative & Technical Economics, 10, 17–31.Google Scholar
  38. Sheng, Y., & Shi, X. (2013). Energy market integration and equitable growth across countries. Applied Energy, 104, 319–325.CrossRefGoogle Scholar
  39. Shi, K., Yu, B., Huang, C., Wu, J., & Sun, X. (2018). Exploring spatiotemporal patterns of electric power consumption in countries along the Belt and Road. Energy, 150, 847–859.CrossRefGoogle Scholar
  40. Tan, X., Dong, L., Chen, D., Gu, B., & Zeng, Y. (2016). China’s regional CO2 emissions reduction potential: A study of Chongqing city. Applied Energy, 162, 1345–1354.CrossRefGoogle Scholar
  41. Wang, Z., He, W., & Wang, B. (2017). Performance and reduction potential of energy and CO2 emissions among the APEC’s members with considering the return to scale. Energy, 138, 552–562.CrossRefGoogle Scholar
  42. Wang, C., & Wang, F. (2017). China can lead on climate change. Science, 357(6353), 64.CrossRefGoogle Scholar
  43. Ward, H., Burger, M., Chang, Y. J., Fürstmann, P., Neugebauer, S., Radebach, A., et al. (2017). Assessing carbon dioxide emission reduction potentials of improved manufacturing processes using multiregional input output frameworks. Journal of Cleaner Production, 163, 154–165.CrossRefGoogle Scholar
  44. Wen, J., Wang, H., Chen, F., & Yu, R. (2018). Research on environmental efficiency and TFP of Beijing areas under the constraint of energy-saving and emission reduction. Ecological Indicators, 84, 235–243.CrossRefGoogle Scholar
  45. Wu, J. X., & He, L. Y. (2017). The distribution dynamics of carbon dioxide emissions intensity across Chinese provinces: A weighted approach. Sustainability, 9(1), 101–119.CrossRefGoogle Scholar
  46. Wu, G., Miao, Z., Shao, S., Geng, Y., Sheng, J., & Li, D. (2017). The elasticity of the potential of emission reduction to energy saving: definition, measurement, and evidence from China. Ecological Indicators, 78, 395–404.CrossRefGoogle Scholar
  47. Yang, D., Pan, K., & Wang, S. (2017). On service network improvement for shipping lines under the One Belt One Road Initiative of China. Transportation Research Part E (in press).Google Scholar
  48. Yang, T. J., Zhang, Y. J., Huang, J., & Peng, R. H. (2013). Estimating the energy saving potential of telecom operators in China. Energy Policy, 61(61), 448–459.CrossRefGoogle Scholar
  49. Yu, S., Agbemabiese, L., & Zhang, J. (2016). Estimating the carbon abatement potential of economic sectors in China. Applied Energy, 165, 107–118.CrossRefGoogle Scholar
  50. Yu, Y., & Choi, Y. (2015). Measuring environmental performance under regional heterogeneity in China: A metafrontier efficiency analysis. Computational Economics, 46(3), 375–388.CrossRefGoogle Scholar
  51. Zhang, Y. J., Bian, X. J., & Tan, W. (2018a). The linkages of sectoral carbon dioxide emission caused by household consumption in China: Evidence from the Hypothetical Extraction Method. Empirical Economics, 54(4), 1743–1775.CrossRefGoogle Scholar
  52. Zhang, X. P., Cheng, X. M., Yuan, J. H., & Gao, X. J. (2011). Total-factor energy efficiency in developing countries. Energy Policy, 39(2), 644–650.CrossRefGoogle Scholar
  53. Zhang, Y. J., Hao, J. F., & Song, J. (2016). The CO2 emission efficiency, reduction potential and spatial clustering in China’s industry: Evidence from the regional level. Applied Energy, 174, 213–223.CrossRefGoogle Scholar
  54. Zhang, N., Liu, Z., Zheng, X., & Xue, J. (2017a). Carbon footprint of China’s Belt and Road. Science, 357(6356), 1107.CrossRefGoogle Scholar
  55. Zhang, Y. J., Peng, Y. L., Ma, C. Q., & Shen, B. (2017b). Can environmental innovation facilitate carbon emissions reduction? Evidence from China. Energy Policy, 100, 18–28.CrossRefGoogle Scholar
  56. Zhang, Y. J., Sun, Y. F., & Huang, J. (2018b). Energy efficiency, carbon emission performance, and technology gaps: Evidence from CDM project investment. Energy Policy, 115, 119–130.CrossRefGoogle Scholar
  57. Zhang, Y. J., & Zhang, K. B. (2018). The linkage of CO2 emissions for China, EU and USA: Evidence from the regional and sectoral analyses. Environmental Science and Pollution Research, 25(20), 20179–20192.CrossRefGoogle Scholar
  58. Zhou, P., Ang, B. W., & Wang, H. (2012). Energy and CO2 emission performance in electricity generation: A non-radial directional distance function approach. European Journal of Operational Research, 221(3), 625–635.CrossRefGoogle Scholar
  59. Zhou, D. Q., Meng, F. Y., Bai, Y., & Cai, S. Q. (2017). Energy efficiency and congestion assessment with energy mix effect: The case of APEC countries. Journal of Cleaner Production, 142(2), 819–828.CrossRefGoogle Scholar

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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Business SchoolHunan UniversityChangshaChina
  2. 2.Center for Resource and Environmental ManagementHunan UniversityChangshaChina
  3. 3.Energy Analysis and Environmental Impacts DivisionLawrence Berkeley National LaboratoryBerkeleyUSA

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