Advertisement

Natural Hazards

, Volume 95, Issue 1–2, pp 381–399 | Cite as

Evolution of CO2 emissions and driving factors in the Tongzhou District in Beijing

  • Jing-Li Fan
  • Zhe Cao
  • Mian Zhang
  • Li Liu
  • Xian ZhangEmail author
Original Paper
  • 150 Downloads

Abstract

As Beijing put forward its “one core, two wings” development plan, the development and construction in the Beijing Tongzhou District have turned into a national strategy. However, as a municipal district, energy and CO2 emission data and other statistics are difficult to obtain in Tongzhou and CO2 emissions accounting for a district at this level is rare. This study applies the accounting method of city carbon emissions to the district level. Firstly, we account for the CO2 emissions in the Tongzhou District from 2008 to 2015 according to data availability. Secondly, by using the logarithmic mean Divisa index decomposition approach, the Tongzhou CO2 emissions are decomposed into six main driving factors, including population, per capita GDP, industrial structure, energy intensity, energy consumption structure, and energy-related CO2 emission factors. The result shows that (1) from 2008 to 2015, the CO2 emissions in the Tongzhou District first increased and then decreased and peaked in 2011. (2) Population and per capita GDP both contributed to the change in CO2 emissions in the Tongzhou District during the study period and resulted in 407,200 tons and 346,200 tons increase, respectively. The industrial structure, energy consumption intensity, and energy structure exerted inhibiting effects, offsetting 29,300 tons, 571,500 tons, and 29,300 tons, respectively, and the energy consumption intensity was the most important factor. (3) On this basis, we discuss the annual effects of the driving factors. The results of this study provide great significance and references for research in order to implement the low-carbon development and the “one core, two wings” strategy in the Tongzhou District.

Keywords

Tongzhou district Carbon emissions accounting LMDI Driving factors 

Notes

Acknowledgements

The authors gratefully acknowledge the financial support of the National Natural Science Foundation of China under Grant (Nos. 71503249, 71521002), Beijing Excellent Talent Program (No. 2015000020124G122), the Open Research Project of State Key Laboratory of Coal Resources and Safe Mining (China University of Mining and Technology) (No. SKLCRSM16KFC05).

References

  1. Ang BW, Liu FL (2004) Decomposition analysis for policy-making in energy: which is the preferred method? Energy Policy 32(4):1131–1139CrossRefGoogle Scholar
  2. Ang BW, Zhang FQ, Choi K (1998) Factorizing changes in energy and environmental indicators through decomposition. Energy 23(6):489–495CrossRefGoogle Scholar
  3. Beijing Municipal Bureau of Statistics (2009–2016a) Beijing statistical yearbook. China Statistics Press, Beijing (in Chinese)Google Scholar
  4. Beijing Municipal Bureau of Statistics (2009–2016b) Beijing regional statistical yearbook. The general team of the Beijing survey team of the National Bureau of Statistics, Beijing (in Chinese)Google Scholar
  5. Beijing Municipal Peoples Government (2016-03-28) Outline of the thirteenth five year plan for national economic and social development in Beijing. http://zhengwu.beijing.gov.cn/gh/xbqtgh/t1434999.htm (in Chinese)
  6. Bureau of statistics of Tongzhou District, Beijing (2009–2016) Statistical yearbook of Tongzhou District in Beijing. Beijing Tongzhou District Statistics Bureau, National Bureau of statistics Tongzhou District investigation team, Beijing (in Chinese)Google Scholar
  7. Chen L, Xu L, Xu Q et al (2016) Optimization of urban industrial structure under the low-carbon goal and the water constraints: a case in Dalian, China. J Clean Prod 114:323–333CrossRefGoogle Scholar
  8. Cheng XL, Liu XM, Liu YJ et al (2018) Characteristics of CO2 concentration and flux in the Beijing Urban area. J Geophys Res Atmos 123(12):1785–1801Google Scholar
  9. China National Bureau of Statistics (2009–2016a) China statistical yearbook. China Statistics Press, Beijing (in Chinese)Google Scholar
  10. China National Bureau of Statistics (2009–2016b) China Energy Statistics Yearbook. China Statistics Press, Beijing (in Chinese)Google Scholar
  11. Deng JX, Liu X, Wang Z (2014) Regional differences and evolution characteristics of China’s carbon emissions and factor decomposition. J Nat Resources 29(2):189–200 (in Chinese)Google Scholar
  12. Dhakal S (2009) Urban energy use and carbon emissions from cities in China and policy implications. Energy Policy 37(11):4208–4219CrossRefGoogle Scholar
  13. Dhakal S (2010) GHG emissions from urbanization and opportunities for urban carbon mitigation. Curr Opin Environ Sustain 2(4):277–283CrossRefGoogle Scholar
  14. Fan JL, Liang QM, Wang Q, Zhang X, Wei YM (2015a) Will export rebate policy be effective for CO2 emissions reduction in China? a CEEPA-based analysis. J Clean Prod 103:120–129CrossRefGoogle Scholar
  15. Fan JL, Yu H, Wei YM (2015b) Residential energy-related carbon emissions in urban and rural China during 1996–2012: from the perspective of five end-use activities. Energy Build 96:201–209CrossRefGoogle Scholar
  16. Fan JL, Zhang YJ, Wang B (2017) The impact of urbanization on residential energy consumption in China: an aggregated and disaggregated analysis. Renew Sustain Energy Rev 75:220–233CrossRefGoogle Scholar
  17. Hu Y, Yin Z, Ma J, Du W, Liu D, Sun L (2017) Determinants of GHG emissions for a municipal economy: structural decomposition analysis of Chongqing. Appl Energy 196:162–169CrossRefGoogle Scholar
  18. Hutchins MG, Colby JD, Marland G, Marland E (2017) A comparison of five high-resolution spatially-explicit, fossil-fuel, CO2 emission inventories for the United States. Mitig Adapt Strat Glob Change 22:947–972CrossRefGoogle Scholar
  19. IPCC (2006) IPCC guidelines for national greenhouse gas inventories: general guidance and reporting, vol 1. Institute for Global Environmental Strategies (IGES), HayamaGoogle Scholar
  20. Jia J, Gong Z, Xie D et al (2018) Analysis of drivers and policy implications of CO2 emissions of industrial energy consumption in an underdeveloped city: the case of Nanchang, China. J Clean Prod 183:843–857CrossRefGoogle Scholar
  21. Lin J, Gao M, Su Y (2015) Concept, location and development model of city sub center—Take Beijing as an example. Popul Econ 03:1–12 (in Chinese) Google Scholar
  22. Mi ZF, Jing M, Guan DB, Shan YL, Liu Z, Wang YT, Feng KS, Wei YM (2017) Pattern changes in determinants of Chinese emissions. Rev Environ Res Lett 12(7):1–10.  https://doi.org/10.1088/1748-9326/aa69cf Google Scholar
  23. Mousavi B, Stephen N, Lopez A et al (2017) Driving forces of Iran’s CO2 emissions from energy consumption: an LMDI decomposition approach. Appl Energy 206:804–814CrossRefGoogle Scholar
  24. Shan Y, Guan D, Liu J et al (2017) Methodology and applications of city level CO2 emission accounts in China. J Clean Prod 161:1215–1225CrossRefGoogle Scholar
  25. The people’s Government of Tongzhou District, Beijing (2016) Tongzhou District’s “13th Five-Year” period and 2016 energy saving and carbon reduction target decomposition plan. Office of the People’s Government of Tongzhou District, Beijing (in Chinese) Google Scholar
  26. Timilsina GR, Shrestha A (2010) Factors affecting transport sector CO2, emissions growth in Latin American and Caribbean countries: an LMDI decomposition analysis. Int J Energy Res 33(4):396–414CrossRefGoogle Scholar
  27. Tobin TS, Bitz CM, Archer D (2017) Modeling climatic effects of CO2 emissions from Deccan Traps volcanic eruptions around the Cretaceous-Paleogene boundary. Palaeogeogr Palaeoclimatol Palaeoecol 478:139–148CrossRefGoogle Scholar
  28. Wang Y (2015) Research on location decision of Beijing sub center. Jiaotong University, Beijing (in Chinese) Google Scholar
  29. Wei J, Huang K, Yang S, Li Y, Hu T, Zhang Y (2017) Driving forces analysis of energy-related CO2 emissions in Beijing: an input-output structural decomposition analysis. J Clean Prod 163:58–68CrossRefGoogle Scholar
  30. Wen L, Li Q, Li Y et al (2017) Carbon emission and economic growth model of Beijing based on symbolic regression. Pol J Environ Stud 27(1):365–372CrossRefGoogle Scholar
  31. Yan D, Lei Y, Li L, Song W (2017) Carbon emission efficiency and spatial clustering analyses in China’s thermal power industry: evidence from the provincial level. J Clean Prod 156:518–527CrossRefGoogle Scholar
  32. Yu Y, Kong Q (2017) Analysis on the influencing factors of carbon emissions from energy consumption in China based on LMDI method. Nat Hazards 88:1691–1707CrossRefGoogle Scholar
  33. Yuan R, Zhao T, Xu J (2017) A subsystem input–output decomposition analysis of CO2 emissions in the service sectors: a case study of Beijing, China. Environ Dev Sustain 19(6):2181–2198CrossRefGoogle Scholar
  34. Zhang YJ, Hao JF (2017) Carbon emission quota allocation among China’s industrial sectors based on the equity and efficiency principles. Ann Oper Res 255:117–140CrossRefGoogle Scholar
  35. Zhang W, Zhang JS, Zou SH, Xu J (2013) Decomposition of energy consumption carbon emissions in Shaanxi based on LMDI. J Arid Land Resources Environ 27(9):26–31Google Scholar

Copyright information

© Springer Nature B.V. 2018

Authors and Affiliations

  • Jing-Li Fan
    • 1
    • 2
    • 3
  • Zhe Cao
    • 1
  • Mian Zhang
    • 1
  • Li Liu
    • 4
  • Xian Zhang
    • 5
    Email author
  1. 1.School of Resources and Safety EngineeringChina University of Mining and Technology, Beijing (CUMTB)BeijingChina
  2. 2.State Key Laboratory of Coal Resources and Safe Mining (China University of Mining and Technology)BeijingChina
  3. 3.Center for Energy and Environmental Policy ResearchBeijing Institute of TechnologyBeijingChina
  4. 4.Beijing Municipal Science and Technology CommissionBeijingChina
  5. 5.The Administrative Centre for China’s Agenda 21 (ACCA21)Ministry of Science and Technology (MOST)BeijingChina

Personalised recommendations