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Environmental Science and Pollution Research

, Volume 26, Issue 4, pp 4041–4055 | Cite as

Explore the influence mechanism of carbon emissions decline on energy intensity with two-layer factor decomposition method in Beijing-Tianjin-Hebei region

  • Jingmin Wang
  • Xueting ZhangEmail author
  • Fan Yang
  • Qingwei Zhou
Research Article
  • 51 Downloads

Abstract

Understanding the intrinsic mechanism behind changes on energy intensity provides insights about reducing carbon emissions and promoting the sustainable development of Beijing-Tianjin-Hebei (BTH) region. Although various studies have found a causal relationship between energy intensity and energy-related carbon emissions, the internal mechanisms are still unclear. This paper presents a comprehensive analysis of the impact of energy intensity on carbon emissions from 2005 to 2015. With an association established between logarithmic mean Divisia index (LMDI) and generalized Fisher index (GFI), two-layer factor decomposition model is proposed to explore the factor analysis in-depth. (1) LMDI method proves that energy intensity is the main contributor that reduces carbon emissions in BTH. (2) GFI model further decomposes energy intensity into five effects, namely energy substitution, technology progress, labor productivity, capital substitution, and labor-capital resources allocation. (3) The results reveal that the effect of capital-energy substitution in declining energy intensity surpasses technology progress. (4) Energy-labor substitution has increased energy intensity, while energy-energy substitution is negligible. For the coordinate development of BTH, the government should aim at energy intensity and attach importance to encouraging entrepreneurship, accelerating the construction of carbon trading market, allocating resources rationally, and guiding the capital flow into energy-efficient direction.

Keywords

Carbon emissions Energy intensity Two-layer decomposition Influence mechanism Policy implications Beijing-Tianjin-Hebei 

Nomenclature

Cij

Carbon emission of the jth energy type in ithindustry

i

Number of industries

j

Number of energies considered in consumption

P

Population effect

A

Per capita GDP (affluence) effect

Gi

Gross domestic product of ith industry (GDP)

Eij

Energy consumption of the jth energy type in ith industry

ISi

Total added value share of the ith industry

EIi

Energy consumption per unit GDP of ith industry

ESi

Total energy consumption share of the jth energy type in ith industry

Cecij

Carbon emission coefficient of the jth energy type in ith industry

EI

Energy intensity

Li

Labor input of ith industry

Ki

Capital stock of ith industry

ES

Energy substitution effect

LP

Labor productivity effect

TPi

Technology progress effect of ith industry

CS

Capital substitution effect

LcRA

Labor-capital resources allocation effect

References

  1. Ang BW (2004) Decomposition analysis for policymaking in energy: which is the preferred method? Energ Policy 32:1131–1139CrossRefGoogle Scholar
  2. Ang BW (2005) The LMDI approach to decomposition analysis: a practical guide. Energ Policy 33:867–871CrossRefGoogle Scholar
  3. Ang BW (2015) LMDI decomposition approach: a guide for implementation. Energ Policy 86:233–238CrossRefGoogle Scholar
  4. Ang BW, Liu FL, Chung HS (2004) A generalized Fisher index approach to energy decomposition analysis. Energy Econ 26:757–763CrossRefGoogle Scholar
  5. Chen WH, Lei YL (2017) Analysis of the impact path on factors of China’s energy-related CO2 emissions: a path analysis with latent variables. Environ Sci Pollut Res 24:5757–5772CrossRefGoogle Scholar
  6. Chen DK, Chen SY, Jin H (2018) Industrial agglomeration and CO2 emissions: evidence from 187 Chinese prefecture-level cities over 2005-2013. J Clean Prod 172:993–1003CrossRefGoogle Scholar
  7. Cui EQ, Ren LJ, Sun HY (2016) Analysis of energy-related CO2 emissions and driving factors in five major energy consumption sectors in China. Environ Sci Pollut Res 23:19667–19674CrossRefGoogle Scholar
  8. Dietz T, Rosa EA (1997) Effects of population and affluence on CO2 emissions. Proc Natl Acad Sci U S A 94:175–179CrossRefGoogle Scholar
  9. Dong KY, Sun RJ, Hochman G, Li H (2018) Energy intensity and energy conservation potential in China: a regional comparison perspective. Energy 155:782–795CrossRefGoogle Scholar
  10. Ehrlich PR, Holdren JP (1971) Impact of population growth. Science 171(3977):1212–1217CrossRefGoogle Scholar
  11. Fan FY, Lei YL (2016) Decomposition analysis of energy-related carbon emissions from the transportation sector in Beijing. Transp Res Part D: Transp Environ 42:135–145CrossRefGoogle Scholar
  12. Fan FY, Lei YL (2017) Factor analysis of energy-related carbon emissions: a case study of Beijing. J Clean Prod 163:S277–S283CrossRefGoogle Scholar
  13. Guo J, Zhang YJ, Zhang KB (2018) The key sectors for energy conservation and carbon emissions reduction in China: evidence from the input-output method. J Clean Prod 179:180–190CrossRefGoogle Scholar
  14. Hao Y, Chen H, Wei YM, Li YM (2016) The influence of climate change on CO2 (carbon dioxide) emissions: an empirical estimation based on Chinese provincial panel data. J Clean Prod 131:667–677CrossRefGoogle Scholar
  15. IPCC (1997) Intergovernmental panel on climate change guidelines for national greenhouse gas inventories. OECD, ParisGoogle Scholar
  16. Jiang JJ, Ye B, Xie DJ, Li J, Miao LX, Yang P (2017a) Sector decomposition of China’s national economic carbon emissions and its policy implication for national ETS development. Renew Sust Energ Rev 75:855–867CrossRefGoogle Scholar
  17. Jiang JJ, Ye B, Xie DJ, Tang J (2017b) Provincial-level carbon emission drivers and emission reduction strategies in China: combining multi-layer LMDI decomposition with hierarchical clustering. J Clean Prod 169:178–190CrossRefGoogle Scholar
  18. Kang ZY, Li K, Qu JY (2018) The path of technological progress for China’s low-carbon development: evidence from three urban agglomerations. J Clean Prod 178:644–654CrossRefGoogle Scholar
  19. Kopidou D, Diakoulaki D (2017) Decomposing industrial CO2 emissions of southern European countries into production- and consumption-based driving factors. J Clean Prod 167:1325–1334CrossRefGoogle Scholar
  20. Li JL, Lin BQ (2016) Inter-factor/inter-fuel substitution, carbon intensity, and energy-related CO2 reduction: empirical evidence from China. Energy Econ 56:483–494CrossRefGoogle Scholar
  21. Li W, Qu QX, Chen YL (2014) Decomposition of China’s CO2 emissions from agriculture utilizing an improved Kaya identity. Environ Sci Pollut Res 21:13000–13006CrossRefGoogle Scholar
  22. Li AJ, Zhang AZ, Zhou YX, Yao X (2017) Decomposition analysis of factors affecting carbon dioxide emissions across provinces in China. J Clean Prod 141:1428–1444CrossRefGoogle Scholar
  23. Lin BQ, Tan RP (2016) Ecological total-factor energy efficiency of China’s energy intensive industries. Ecol Indic 70:480–497CrossRefGoogle Scholar
  24. Liu J, Zhang SH, Wagner F (2018a) Exploring the driving forces of energy consumption and environmental pollution in China’s cement industry at the provincial level. J Clean Prod 184:274–285CrossRefGoogle Scholar
  25. Liu K, Bai HK, Yin S, Lin BQ (2018b) Factor substitution and decomposition of carbon intensity in China’s heavy industry. Energy 145:582–591CrossRefGoogle Scholar
  26. Liu QL, Lei Q, Xu HM, Yuan JH (2018c) China’s energy revolution strategy into 2030. Resour Conserv Recycl 128:78–89CrossRefGoogle Scholar
  27. Liu X, Zhou DQ, Zhou P, Wang QW (2018d) Factor driving energy consumption in China: a joint decomposition approach. J Clean Prod 172:724–734CrossRefGoogle Scholar
  28. Long XL, Luo YS, Wu C (2018) The influencing factors of CO2 emission intensity of Chinese agriculture from 1997 to 2014. Environ Sci Pollut Res 25:13093–13101CrossRefGoogle Scholar
  29. Ma MD, Cai WG (2018) What drives the carbon mitigation in Chinese commercial building sector? Evidence from decomposing an extended Kaya identity. Sci Total Environ 634:884–899CrossRefGoogle Scholar
  30. Madaleno M, Moutinho V (2017) A new LDMI decomposition approach to explain emission development in the EU: individual and set contribution. Environ Sci Pollut Res 24:10234–10257CrossRefGoogle Scholar
  31. Mahmood T, Ahmad E (2018) The relationship of energy intensity with economic growth: evidence for European economies. Energy Strateg Rev 20:90–98CrossRefGoogle Scholar
  32. Meng J, Mi ZF, Yang HZ, Shan YL, Guan DB, Liu JF (2017) The consumption-based black carbon emissions of China’s megacities. J Clean Prod 161:1275–1282CrossRefGoogle Scholar
  33. Mi ZF, Wei YM, Wang B, Meng J, Liu Z, Shan Y, Liu J, Guan D (2017) Socioeconomic impact assessment of China’s CO2 emissions peak prior to 2030. J Clean Prod 142:2227–2236CrossRefGoogle Scholar
  34. Peng X, Tao XM (2018) Decomposition of carbon intensity in electricity production: technological innovation and structural adjustment in China’s power sector. J Clean Prod 172:805–818CrossRefGoogle Scholar
  35. Pretis F, Roser M (2017) Carbon dioxide emission-intensity in climate projections: comparing the observational record to socio-economic scenarios. Energy 135:718–725CrossRefGoogle Scholar
  36. Shao CF, Guan Y, Wan Z, Guo CX, Chu C, Ju MT (2014) Performance and decomposition analyses of carbon emissions from industrial energy consumption in Tianjin, China. J Clean Prod 64:590–601CrossRefGoogle Scholar
  37. Shen LY, Wu Y, Lou YL, Zeng DH, Shuai CY, Song XN (2018) What drives the carbon emission in the Chinese cities?-a case of pilot low carbon city of Beijing. J Clean Prod 174:343–354CrossRefGoogle Scholar
  38. Shi Q, Chen JD, Shen LY (2017) Driving factors of the changes in the carbon emissions in the Chinese construction industry. J Clean Prod 166:615–627CrossRefGoogle Scholar
  39. Shi LY, Sun J, Lin JY, Zhao Y (2018) Factor decomposition of carbon emissions in Chinese megacities. J Environ Sci 75:209–215.  https://doi.org/10.1016/j.jes.2018.03.026 CrossRefGoogle Scholar
  40. Tan RP, Lin BQ (2018) What factors lead to the decline of energy intensity in China’s energy intensive industries? Energy Econ 71:213–221CrossRefGoogle Scholar
  41. Wang M, Feng C (2017) Understanding China’s industrial CO2 emissions: a comprehensive decomposition framework. J Clean Prod 166:1335–1346CrossRefGoogle Scholar
  42. Wang SJ, Li CF (2018) The impact of urbanization on CO2 emissions in China: an empirical study using 1980-2014 provincial data. Environ Sci Pollut Res 25:2457–2465CrossRefGoogle Scholar
  43. Wang SJ, Ma YY (2018) Influencing factors and regional discrepancies of the efficiency of carbon dioxide emissions in Jiangsu China. Ecol Indic 90:460–468CrossRefGoogle Scholar
  44. Wang ZH, Yang L (2015) Delinking indicators on regional industry development and carbon emissions: Beijing–Tianjin–Hebei economic band case. Ecol Indic 48:41–48CrossRefGoogle Scholar
  45. Wang QW, Chiu YH, Chiu CR (2015) Driving factors behind carbon dioxide emissions in China: a modified production-theoretical decomposition analysis. Energy Econ 51:252–260CrossRefGoogle Scholar
  46. Wang CJ, Wang F, Zhang XL, Deng HJ (2017a) Analysis of influence mechanism of energy-related carbon emissions in Guangdong: evidence from regional China based on the input-output and structural decomposition analysis. Environ Sci Pollut Res 24:25190–25203CrossRefGoogle Scholar
  47. Wang JM, Shi YF, Zhao X, Zhang XT (2017b) Factors affecting energy-related carbon emissions in Beijing-Tianjin-Hebei region. Math Probl Eng 167:653–664Google Scholar
  48. Wang Y, Liu HW, Mao GZ, Zuo J, Ma JL (2017d) Inter-regional and sectoral linkage analysis of air pollution in Beijing-Tianjin-Hebei (Jing-Jin-Ji) urban agglomeration of China. J Clean Prod 165:1436–1444CrossRefGoogle Scholar
  49. Wang QW, Hang Y, Su B, Peng Z (2018) Contributions to sector-level carbon intensity change: an integrated decomposition analysis. Energy Econ 70:12–25CrossRefGoogle Scholar
  50. Wang Y, Zhou Y, Zhu L, Zhang F, Zhang YC (2018c) Influencing factors and decoupling elasticity of China’s transportation carbon emissions. Energies 11:1157CrossRefGoogle Scholar
  51. Xu SC, He ZX, Long RY (2014) Factors that influence carbon emissions due to energy consumption in China: decomposition analysis using LMDI. Appl Energy 127:182–193CrossRefGoogle Scholar
  52. Xu SC, He ZX, Long RY, Chen H, Han HM, Zhang WW (2016) Comparative analysis of the regional contributions to carbon emissions in China. J Clean Prod 127:406–417CrossRefGoogle Scholar
  53. Xu Q, Dong Y-X, Yang R (2018) Urbanization impact on carbon emissions in the Pearl River Delta region: Kuznets curve relationships. J Clean Prod 180:514–532CrossRefGoogle Scholar
  54. Yan QY, Wang YX, Balezentis T, Sun YK, Streimikiene D (2018) Energy-related CO2 emission in China’s provincial thermal electricity generation: driving factors and possibilities for abatement. Energies 11:1096CrossRefGoogle Scholar
  55. Yu T (2011) China’s low carbon economic rise and countermeasures of research. Int Conf Comput Inf Ctrl 231:244–247Google Scholar
  56. Yu SW, Wei YM, Wang K (2014) Provincial allocation of carbon emission reduction targets in China: an approach based on improved fuzzy cluster and Shapley value decomposition. Energ Policy 66:630–644CrossRefGoogle Scholar
  57. Zhao MM, Li RR (2018) Decoupling and decomposition analysis of carbon emissions from economic output in Chinese Guangdong Province: a sector perspective. Energ Environ 29:543–555CrossRefGoogle Scholar
  58. Zheng HM, Wang XJ, Li MJ, Zhang Y, Fan YC (2018) Interregional trade among regions of urban energy metabolism: a case study between Beijing-Tianjin-Hebei and others in China. Resour Conserv Recycl 132:339–351CrossRefGoogle Scholar
  59. Zhou X, Zhang M, Zhou MH, Zhou M (2017) A comparative study on decoupling relationship and influence factors between China’s regional economic development and industrial energy–related carbon emissions. J Clean Prod 142:783–800CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Economics ManagementNorth China Electric Power UniversityBaodingChina
  2. 2.Beijing Key Laboratory of New Energy and Low-Carbon DevelopmentNorth China Electric Power UniversityBeijingChina

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