Abstract
This paper calculated the energy-related carbon emissions from production, household and energy transformation sectors in Shanghai and decomposed the effects of their changes in carbon emissions resulting from 11 causal factors of reflecting the changes in socioeconomic activity, intensity of energy and the structure by logarithmic mean divisia index. The results show that the changes of economic activity (EA), population size (PS), total energy consumption in transformation and energy consumption per capita (ECPC) increase CO2 emissions obviously. The changes of energy intensity (EI), urban and rural population distribution structure, energy mix of household and mix of energy in transformation drive the decrease of CO2 emissions. The changes of economic structure (ES), energy mix of production, and energy transformation structure (ETS) can’t increase or decreased CO2 emissions continuously in 3 periods respectively. Therefore, adjusting ES, ETS, energy mix of transformation and decreasing the EI of each production sector will be the main routes to reduce CO2 emissions. Developing clean energy to substitute fossil energy and enforcement of carbon capture will be necessary in the future.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Ang BW (2004) Decomposition analysis for policymaking in energy: which is the preferred method? Energy Policy 32(9):1131–1139
Ang BW (2005) The LMDI approach to decomposition analysis: a practical guide. Energy Policy 33(7):867–871
Ang BW, Liu FL (2001) A new energy decomposition method: perfect in decomposition and consistent in aggregation. Energy 26(6):537–548
Ang BW, Zhang FQ (2000) A survey of index decomposition analysis in energy and environmental studies. Energy 25(12):1149–1176
BMBS and NBS (1996–2010) Shanghai Statistical Yearbook. China Statistics Press, Beijing
Chen GQ (2011) An overview of energy consumption of the globalized world economy. Energy Policy 39(10):5920–5928
Chen GQ, Chen ZM (2011a) Greenhouse gas emissions and natural resources use by the world economy: ecological input–output modeling. Ecol Model 222(14):2362–2376
Chen ZM, Chen GQ (2011b) Embodied carbon dioxide emission at supra-national scale: a coalition analysis for G7, BRIC, and the rest of the world. Energy Policy 39(5):2899–2909
Chen F et al (2013) Theoretical research on low-carbon city and empirical study of Shanghai. Habitat Inter 37:33–42
Dhakal S (2009) Urban energy use and carbon emissions from cities in China and policy implications. Energy Policy 37(11):4208–4219
Intergovernmental Panel on Climate Change (IPCC 2006) Guidelines for national greenhouse gas inventories: vol. 2 Energy. Available at http://www.ipcc-nggip.iges.or.jp/public/006gl/ol2.tml
IPCC (Intergovernmental Panel on Climate Change). Climate Change 2007: Synthesis Report. Geneva, Switzerland
Li L, Chen C et al (2011) Energy demand and carbon emissions under different development scenarios for Shanghai, China. Energy Policy 38:4797–4807
Liu CC (2007) An extended method for key factors in reducing CO2 emissions. Appl Math Comput 89(1):440–451
Liu Z, Liang S, et al (2012) Features, trajectories and driving forces for energy-related GHG emissions from Chinese mega cites: the case of Beijing, Tianjin, Shanghai and Chongqing, Energy 37:245–254
National Bureau of Statistics Department of Energy Statistics (NBS DES) (1991–2010) China Energy Statistical Yearbook. China Statistics Press, Beijing
Oh I, Wehrmeyer W, Mulugetta Y (2010) Decomposition analysis and mitigation strategies of CO2 emissions from energy consumption in South Korea. Energy Policy 38(1):364–377
Olivier JGJ, Janssens MG, Peters JAHW, Julian W (2011) Long-term trend in global CO2 missions 2011 report, The Hague: PBL/JRC
Paul et al (2004) Decomposition of energy and CO2 intensities of Thai industry between 1981 and 2000. Energy Econ 26(5):765–781
Peters GP, Hertwich EG (2008) CO2 embodied in international trade with implications for global climate policy. Environ Sci Technol 42(5):1401–1407
Shao S et al (2011) Estimation, characteristics, and determinants of energy-related industrial CO2 emissions in Shanghai, 1994–2009. Energy Policy 39:6476–6494
Steffen L (2013) Low-to-no carbon city: lessons from western urban projects for the rapid transformation of Shanghai. Habitat Int 37:61–69
Tunc GI, Türüt-Asik S, Akbostancı E (2009) A decomposition analysis of CO2 emissions from energy use: Turkish case. Energy Policy 37(11):4689–4699
Wang C, Chen JN, Zou J (2005) Decomposition of energy-related CO2 emission in China: 1957–2000. Energy 30(1):73–83
Zhang JY et al (2013) Estimation of energy-related carbon emission in Beijing and factor decomposition analysis. Ecol Model 252:258–265
Zhang M, Mu HL, Ning YD, Song YC (2009) Decomposition of energy-related CO2 emission over 1991–2006 in China. Ecol Econ 68(7):2122–2128
Zhao M, Tan L (2010) Decomposing the influencing factors of industrial carbon emissions in Shanghai using the LMDI method. Energy 35:2505–2510
Zhao M, Zhang WG, Yu LZ (2009) Carbon emissions from energy consumption in Shanghai City. Res Environ Sci 22(8):984–989 (in Chinese)
Zhou SY, Chen H, Li SC (2010) Resources use and greenhouse gas emissions in urban economy: ecological input–output modeling for Beijing 2002. Commun Nonlinear Sci Numer Simul 15(10):3201–3231
Acknowledgments
This research is supported by National Science Foundation of China (No. 71333010, 70973076) and National Social Science Foundation of China (No. 11AZD080).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Fan, Cz., Gu, Hy., Jiang, H. (2015). Energy-Related Carbon Emissions in Shanghai: Driving Forces and Reducing Strategies. In: Feng, S., Huang, W., Wang, J., Wang, M., Zha, J. (eds) Low-carbon City and New-type Urbanization. Environmental Science and Engineering(). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45969-0_3
Download citation
DOI: https://doi.org/10.1007/978-3-662-45969-0_3
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-45968-3
Online ISBN: 978-3-662-45969-0
eBook Packages: EnergyEnergy (R0)