OpenLB
Open Library of Bioscience
Advanced Search
Environmental science and pollution research international
Sep, 2022;29 (42): 63846-63858.

Decoupling relationship between carbon emission and economic development in the service sector: case of 30 provinces in China.

Chang Gan, Kai Wang, Mihai Voda
Author Information
  1. Chang Gan: College of Tourism, Hunan Normal University, Changsha, China.
  2. Kai Wang: College of Tourism, Hunan Normal University, Changsha, China. kingviry@163.com.
  3. Mihai Voda: Geography Department, Dimitrie Cantemir University, Targu Mures, Romania.
PMID: 35462585 DOI: 10.1007/s11356-022-20032-4

Abstract

The decoupling relationship between carbon emissions and the economic development in the service sector is conducive to promoting sustainable development. Taking 30 provinces of China as case studies, this study not only examined the decoupling relationship between carbon emissions and economic development in the service sector by adopting Tapio decoupling elasticity model but it also explored the driving factors affecting the changes of carbon emissions of the service sector at different stages by using the Logarithmic Mean Divisia Index. The main results are as follows. First, the rapid development of the service sector inevitably consumed a large number of energies, thus generating a deal of carbon emissions in China. Second, the majority of provinces have achieved a weak decoupling relationship between carbon emissions and economic development in the service sector during the four Five-Year Plans. Third, although the inhibiting effect of energy efficiency and energy structure saw a fluctuant growth trend, the provincial average accumulative reduction of carbon emissions was still smaller than that of the industry scale.

Keywords

Carbon emission Decoupling Logarithmic Mean Divisia Index Service sector

References

  1. Alajmi RG (2021) Factors that impact greenhouse gas emissions in Saudi Arabia: Decomposition analysis using LMDI. Energy Policy 156:112454. https://doi.org/10.1016/j.enpol.2021.112454
  2. Alcántara V, Padilla E (2009) Input–output subsystems and pollution: An application to the service sector and CO2 emissions in Spain. Ecol Econ 68(3):905–914. https://doi.org/10.1016/j.ecolecon.2008.07.010 [DOI: 10.1016/j.ecolecon.2008.07.010]
  3. Ang BW (2005) The LMDI approach to decomposition analysis: a practical guide. Energy Policy 33(7):867–871. https://doi.org/10.1016/j.enpol.2003.10.010 [DOI: 10.1016/j.enpol.2003.10.010]
  4. Butnar I, Llop M (2011) Structural decomposition analysis and input–output subsystems: Changes in CO2 emissions of Spanish service sectors (2000–2005). Ecol Econ 70(11):2012–2019. https://doi.org/10.1016/j.ecolecon.2011.05.017 [DOI: 10.1016/j.ecolecon.2011.05.017]
  5. Chen X, Shuai C, Wu Y, Zhang Y (2020) Analysis on the carbon emission peaks of China’s industrial, building, transport, and agricultural sectors. Sci Total Environ 709:135768. https://doi.org/10.1016/j.scitotenv.2019.135768 [DOI: 10.1016/j.scitotenv.2019.135768]
  6. Collard F, Fève P, Portier F (2005) Electricity consumption and ICT in the French service sector. Energy Economics 27(3):541–550. https://doi.org/10.1016/j.eneco.2004.12.002 [DOI: 10.1016/j.eneco.2004.12.002]
  7. Du X, Shen L, Wong SW, Meng C, Yang Z (2021) Night-time light data based decoupling relationship analysis between economic growth and carbon emission in 289 Chinese cities. Sustainable Cities and Society 73:103119. https://doi.org/10.1016/j.scs.2021.103119
  8. Fang CY, Hu JL, Lou TK (2013) Environment-adjusted total-factor energy efficiency of Taiwan’s service sectors. Energy Policy 63:1160–1168. https://doi.org/10.1016/j.enpol.2013.07.124 [DOI: 10.1016/j.enpol.2013.07.124]
  9. Farreny R, Gabarrell X, Rieradevall J (2008) Energy intensity and greenhouse gas emission of a purchase in the retail park service sector: An integrative approach. Energy Policy 36(6):1957–1968. https://doi.org/10.1016/j.enpol.2008.02.013 [DOI: 10.1016/j.enpol.2008.02.013]
  10. Gao C, Ge H, Lu Y, Wang W, Zhang Y (2021) Decoupling of provincial energy-related CO2 emissions from economic growth in China and its convergence from 1995 to 2017. J Cleaner Prod 297:126627. https://doi.org/10.1016/j.jclepro.2021.126627
  11. Guo S, Li Y, Hu Y, Xue F, Chen B, Chen Z-M (2020) Embodied energy in service industry in global cities: A study of six Asian cities. Land Use Policy 91:104264.  https://doi.org/10.1016/j.landusepol.2019.104264
  12. IPCC (2006) IPCC Guidelines for National Greenhouse Gas Inventories. Hayama, Japan. Retrieved from Kanagawa:  https://www.ipcc.ch/report/2006-ipcc-guidelines-for-national-greenhouse-gas-inventories/ . Accessed 13 Aug 2021
  13. IPCC (2008) IPCC Guidelines for National Green Gas Inventories: Volume II. Kanagawa, Japan. Retrieved from Kanagawa: https://www.ipcc.ch/ipccreports/Methodology-reports.htm . Accessed 16 Aug 2021
  14. IPCC (2014) Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Geneva, Switzerland. Retrieved from Geneva: https://www.ipcc.ch/report/ar5/syr/
  15. Ivanova O (2021) The Economics of Reducing Carbon Emissions From Air and Road Transport. In: Vickerman R (ed) International Encyclopedia of Transportation. Elsevier, Oxford, pp 457–463 [DOI: 10.1016/B978-0-08-102671-7.10085-5]
  16. Lai JHK (2015) Carbon footprints of hotels: Analysis of three archetypes in Hong Kong. Sustain Cities Soc 14:334–341. https://doi.org/10.1016/j.scs.2013.09.005 [DOI: 10.1016/j.scs.2013.09.005]
  17. Li L, Hong X, Peng K (2019) A spatial panel analysis of carbon emissions, economic growth and high-technology industry in China. Struct Chang Econ Dyn 49:83–92. https://doi.org/10.1016/j.strueco.2018.09.010 [DOI: 10.1016/j.strueco.2018.09.010]
  18. Li K, Zhou Y, Xiao H, Li Z, Shan Y (2021a) Decoupling of economic growth from CO2 emissions in Yangtze River Economic Belt cities. Sci Total Environ 775:145927.  https://doi.org/10.1016/j.scitotenv.2021.145927
  19. Li Z, Sarwar S, Jin T (2021b) Spatiotemporal evolution and improvement potential of agricultural eco-efficiency in Jiangsu Province. Front Energy Res 9:746405.  https://doi.org/10.3389/fenrg.2021.746405
  20. Lin B, Zhang G (2017) Energy efficiency of Chinese service sector and its regional differences. J Clean Prod 168:614–625. https://doi.org/10.1016/j.jclepro.2017.09.020 [DOI: 10.1016/j.jclepro.2017.09.020]
  21. Liu X, Zhao T, Chang C-T, Fu CJ (2021) China’s renewable energy strategy and industrial adjustment policy. Renewable Energy 170:1382–1395. https://doi.org/10.1016/j.renene.2021.02.045 [DOI: 10.1016/j.renene.2021.02.045]
  22. Lundquist S (2021) Explaining events of strong decoupling from CO2 and NOx emissions in the OECD 1994–2016. Sci Total Environ 793:148390. https://doi.org/10.1016/j.scitotenv.2021.148390 [DOI: 10.1016/j.scitotenv.2021.148390]
  23. Ma Y, Wang J (2021) Time-varying spillovers and dependencies between iron ore, scrap steel, carbon emission, seaborne transportation, and China's steel stock prices. Res Policy 74:102245.  https://doi.org/10.1016/j.resourpol.2021.102254
  24. Mairet N, Decellas F (2009) Determinants of energy demand in the French service sector: A decomposition analysis. Energy Policy 37(7):2734–2744. https://doi.org/10.1016/j.enpol.2009.03.002 [DOI: 10.1016/j.enpol.2009.03.002]
  25. Mulder P, de Groot HLF, Pfeiffer B (2014) Dynamics and determinants of energy intensity in the service sector: A cross-country analysis, 1980–2005. Ecol Econ 100:1–15. https://doi.org/10.1016/j.ecolecon.2014.01.016 [DOI: 10.1016/j.ecolecon.2014.01.016]
  26. Ortega-Ruiz G, Mena-Nieto A, Garcia-Ramos JE (2020) Is India on the right pathway to reduce CO2 emissions? Decomposing an enlarged Kaya identity using the LMDI method for the period 1990–2016. Sci Total Environ 737:139638. https://doi.org/10.1016/j.scitotenv.2020.139638 [DOI: 10.1016/j.scitotenv.2020.139638]
  27. Pardo Martínez CI (2013) An analysis of eco-efficiency in energy use and CO2 emissions in the Swedish service industries. Socioecon Plann Sci 47(2):120–130. https://doi.org/10.1016/j.seps.2012.11.004 [DOI: 10.1016/j.seps.2012.11.004]
  28. Pardo Martínez CI, Silveira S (2012) Analysis of energy use and CO2 emission in service industries: Evidence from Sweden. Renew Sustain Energy Rev 16(7):5285–5294. https://doi.org/10.1016/j.rser.2012.04.051 [DOI: 10.1016/j.rser.2012.04.051]
  29. Qi Y, Harrod S, Psaraftis HN, Lang M (2022) Transport service selection and routing with carbon emissions and inventory costs consideration in the context of the Belt and Road Initiative. Transp Res Part E Logist Transp Rev 159:102630.  https://doi.org/10.1016/j.tre.2022.102630
  30. Quan C, Cheng X, Yu S, Ye X (2020) Analysis on the influencing factors of carbon emission in China’s logistics industry based on LMDI method. Sci Total Environ 734:138473. https://doi.org/10.1016/j.scitotenv.2020.138473 [DOI: 10.1016/j.scitotenv.2020.138473]
  31. Schindler M, Dionisio R (2021) A framework to assess impacts of path dependence on urban planning outcomes, induced through the use of decision-support tools. Cities 115:103256.  https://doi.org/10.1016/j.cities.2021.103256
  32. Schleich J, Gruber E (2008) Beyond case studies: Barriers to energy efficiency in commerce and the services sector. Energy Economics 30(2):449–464. https://doi.org/10.1016/j.eneco.2006.08.004 [DOI: 10.1016/j.eneco.2006.08.004]
  33. Von Wald G, Mastrandrea MD, Cullenward D, Weyant J (2020) Analyzing California’s framework for estimating greenhouse gas emissions associated with retail electricity sales. Electr J 33(8):106818. https://doi.org/10.1016/j.tej.2020.106818 [DOI: 10.1016/j.tej.2020.106818]
  34. Waheed R, Sarwar S, Mighri Z (2020) Role of high technology exports for energy efficiency: Empirical evidence in the context of Gulf Cooperation Council countries. Energy & Environment 32(5):803–819. https://doi.org/10.1177/0958305x20954196 [DOI: 10.1177/0958305x20954196]
  35. Wang K, Li J, Tang Y, Liu H (2013) Carbon emissions accounting and decomposition analysis of energy consumption of service industry in China. China Popul Resour Environ 23(5):21–28
  36. Wang K, Tang X, Gan C, Liu H (2021) Temporal⁃spatial evolution and influencing factors of carbon emission intensity of China. China Popul Resour Environ 31(8):23–31 (in Chinese)
  37. Wang M, Feng C (2021) Towards a decoupling between economic expansion and carbon dioxide emissions in resources sector: A case study of China’s 29 non-ferrous metal industries. Res Policy 74:102249.  https://doi.org/10.1016/j.resourpol.2021.102249
  38. Wang R, Hao J-X, Wang C, Tang X, Yuan X (2020a) Embodied CO2 emissions and efficiency of the service sector: Evidence from China. J Clean Prod 247:119116.  https://doi.org/10.1016/j.jclepro.2019.119116
  39. Wang X-X, He A-Z, Zhao J (2020b) Regional disparity and dynamic evolution of carbon emission reduction maturity in China’s service industry. J Clean Prod 244:118926.  https://doi.org/10.1016/j.jclepro.2019.118926
  40. Wen L, Li Z (2020) Provincial-level industrial CO2 emission drivers and emission reduction strategies in China: Combining two-layer LMDI method with spectral clustering. Sci Total Environ 700:134374. https://doi.org/10.1016/j.scitotenv.2019.134374 [DOI: 10.1016/j.scitotenv.2019.134374]
  41. Xiao H, Shan Y, Zhang N, Zhou Y, Wang D, Duan Z (2019) Comparisons of CO2 emission performance between secondary and service industries in Yangtze River Delta cities. J Environ Manage 252:109667. https://doi.org/10.1016/j.jenvman.2019.109667 [DOI: 10.1016/j.jenvman.2019.109667]
  42. Xing R, Hanaoka T, Kanamori Y, Masui T (2018) Estimating energy service demand and CO 2 emissions in the Chinese service sector at provincial level up to 2030. Resour Conserv Recycl 134:347–360. https://doi.org/10.1016/j.resconrec.2018.02.030 [DOI: 10.1016/j.resconrec.2018.02.030]
  43. Yang J, Tang L, Mi Z, Liu S, Li L, Zheng J (2019) Carbon emissions performance in logistics at the city level. J Clean Prod 231:1258–1266. https://doi.org/10.1016/j.jclepro.2019.05.330 [DOI: 10.1016/j.jclepro.2019.05.330]
  44. Yao L, Wang Z, Xu S (2020) Intensity of energy consumption and characteristic of carbon emission for mountain hotel: A case study of Huangshan Xihai Hotel. Scientia Geographica Sinica 40(6):965–972. https://doi.org/10.13249/j.cnki.sgs.2020.06.012 [DOI: 10.13249/j.cnki.sgs.2020.06.012]
  45. Yu S, Hu X, Li L, Chen H (2020) Does the development of renewable energy promote carbon reduction? Evidence from Chinese provinces. J Environ Manage 268:110634. https://doi.org/10.1016/j.jenvman.2020.110634 [DOI: 10.1016/j.jenvman.2020.110634]
  46. Zha J, Dai J, Ma S, Chen Y, Wang X (2021) How to decouple tourism growth from carbon emissions? A case study of Chengdu China. Tour Manag Perspect 39:100849. https://doi.org/10.1016/j.tmp.2021.100849 [DOI: 10.1016/j.tmp.2021.100849]
  47. Zhang G, Lin B (2018) Impact of structure on unified efficiency for Chinese service sector—A two-stage analysis. Appl Energy 231:876–886. https://doi.org/10.1016/j.apenergy.2018.09.033 [DOI: 10.1016/j.apenergy.2018.09.033]
  48. Zhang YJ, Wang W (2019) Do renewable energy consumption and service industry development contribute to CO2 emissions reduction in BRICS countries? Environ Sci Pollut Res Int 26(31):31632–31643. https://doi.org/10.1007/s11356-019-06330-4 [DOI: 10.1007/s11356-019-06330-4]
  49. Zhang J, Zhang Y (2018) Carbon tax, tourism CO 2 emissions and economic welfare. Ann Tour Res 69:18–30. https://doi.org/10.1016/j.annals.2017.12.009 [DOI: 10.1016/j.annals.2017.12.009]

Grants

  1. 5010002/Construction Program for First-Class Disciplines of Hunan Province, China

MeSH Term

Carbon
Carbon Dioxide
China
Economic Development
Industry

Chemicals

Carbon Dioxide
Carbon
Journal Article

Word Cloud

Created with Highcharts 10.0.0carbonemissionsdevelopmentservicesectordecouplingrelationshipeconomicprovincesChina30caseLogarithmicMeanDivisiaIndexenergyDecouplingemissionconducivepromotingsustainableTakingstudiesstudyexaminedadoptingTapioelasticitymodelalsoexploreddrivingfactorsaffectingchangesdifferentstagesusingmainresultsfollowsFirstrapidinevitablyconsumedlargenumberenergiesthusgeneratingdealSecondmajorityachievedweakfourFive-YearPlansThirdalthoughinhibitingeffectefficiencystructuresawfluctuantgrowthtrendprovincialaverageaccumulativereductionstillsmallerindustryscalesector:CarbonService

Similar Articles

Cited By