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Journal of Environmental Accounting and Management
António Mendes Lopes (editor), Jiazhong Zhang(editor)
António Mendes Lopes (editor)

University of Porto, Portugal

Email: aml@fe.up.pt

Jiazhong Zhang (editor)

School of Energy and Power Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi Province 710049, China

Fax: +86 29 82668723 Email: jzzhang@mail.xjtu.edu.cn


Embodied Services of Greenhouse Gas Emissions: A Case Study of the EU Member Countries

Journal of Environmental Accounting and Management 4(3) (2016) 269--286 | DOI:10.5890/JEAM.2016.09.003

Meirong Su$^{1}$, Ying Zheng$^{2}$, Stephan Pauleit$^{3}$, Yan Hao$^{2}$, Xuemei Yin$^{2}$, Gengyuan Liu$^{2}$, Yan Zhang$^{2}$

$^{1}$ School of Eco-environment and Architectural Engineering, Dongguan University of Technology, Dongguan 523808, China

$^{2}$ State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China

$^{3}$ Strategic Landscape Planning and Management, Technical University of Munich, Freising 85354, Germany

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Abstract

Decreasing Greenhouse Gas (GHG) emissions is a globally agreed goal for mitigating climate change. Considering previous disputes between countries and the negative emotions subconsciously injected into those responsible for the management of the problem, it is useful to reconsider how to ensure that more countries actively contribute to climate change mitigation. Here, we propose a new concept of ‘embodied services of GHG emissions’ to express the underlying services associated with GHG emissions. Based on a developed assessment framework and indicators, we rank the 28 EU member countries in terms of embodied services of GHG emissions. Analyzing these countries’ results geospatially presented an archaeopteryx pattern, where countries on the two wings have the highest levels of embodied services while those on the back and tail have the lowest. The results are also analyzed for each country over time allowing efforts made by those countries to be displayed in different aspects. We believe that the proposed concept has effective resolution for both spatial and temporal scales. We anticipate that countries’ willingness to engage in climate change mitigation will be stimulated by targeting improvement of embodied services of GHG emissions as an additional, beneficial goal, which also embodies equality and incentivizing aspects.

Acknowledgments

This work was supported by the National Key Research Program of China (Grant No. 2016YFC0502806), the Fund for Innovative Research Group of the National Natural Science Foundation of China (Grant No.51421065), and the National Natural Science Foundation of China (No. 41371482). Special thanks should also be given to the Alexander von Humboldt Foundation.

References

  1. [1]  Ayres, R.U. and Walter, J. (1991), The greenhouse effect: damages, costs and abatement, Environmental Resource and Economy 1, 237-270.
  2. [2]  Bachmann, T.M. and Van der Kamp, J. (2014), Environmental cost-benefit analysis and the EU (European Union) Industrial Emissions Directive: Exploring the societal efficiency of a DeNOx retrofit at a coal-fired power plant, Energy 68, 125-139.
  3. [3]  Carvalho, M.G. (2012), EU energy and climate change strategy Energy, 40, 19-22.
  4. [4]  Costanza, R., d’Arge, R., Groot, R.D., Farber, S., Grasso, M., Hannon, B., Limburg, K., Naeem, S., O’Neil, R.V., Paruelo, J., Raskin, R.G., Sutton, P. and Belt, M.V.D. (1997), The value of the world’s ecosystem services and natural capital, Nature 387, 253-260.
  5. [5]  Cui, L.B., Fan, Y., Zhu, L. and Bi, Q.H. (2014), How will the emissions trading scheme save cost for achieving China’s 2020 carbon intensity reduction target? Applied Energy 136, 1043-1052.
  6. [6]  Daily, G.C., Söderqvist, T., Aniyar, S., Arrow, K., Dasgupta, P., Ehrlich, P.R., Folke, C., Jansson, A.M., Jansson, B.O., Kautsky, N., Levin, S., Lubchenco, J., Mäler, K.G., Simpson, D., Starrett, D., Tilman, D. and Walker, B. (2000), The value of nature and the nature of value, Science 289(5478), 395-396.
  7. [7]  D'Amato, I. (2015), China to cut emissions intensity by 60-65% from 2005 level by 2030: INDC. Available online: http://www.theclimategroup.org/what-we-do/news-and-blogs/china-to-cut-emissions-by-60-65-from-2005-level-indc/ (accessed on 14th August 2016).
  8. [8]  Department of Energy & Climate Change (DECC) and Davey, E. (2013), Reduction in Japanese carbon emissions target for 2020: Statement by Edward Davey. Available online: https://www.gov.uk/government/news/reduction-in-japanese-carbon-emissionstarget- for-2020-statement-by-edward-davey (accessed on 14th August 2016).
  9. [9]  Department of Energy & Climate Change (DECC) (2011), The Carbon Plan: Delivering Our Low Carbon Future, Department of Energy & Climate Change, UK.
  10. [10]  Elzen, M.G.J.D., Beltran, A.M., Hof, A.F., Ruijven, B.V. and Vliet, J.V. (2013), Reduction targets and abatement costs of developing countries resulting from global and developed countries’ reduction targets by 2050, Mitigation and Adaptation Strategies for Global Change 18, 491-512.
  11. [11]  Environment Defense Fund (EDF) and International Emissions Trading Association (IETA) (2014), The World’s Carbon Markets: A Case Study Guide to Emissions Trading. Available online: http://wenku.baidu.com/link?url=M_LGaeHfLyfUltrDoWGJXSWLu_z1gUBr1OjccuGpnMUwg9HIySzWWQrs1uWPyfkRXVelHi UlyWAaVwM94qe67z9o94Yn2cUmrPdNiesgp_7 (accessed on 14th August 2016).
  12. [12]  European Environment Agency (EEA) (2015a), Application of the EU Emissions Trading Directive Analysis of national responses under Article 21 of the EU ETS Directive in 2014, European Environment Agency, Copenhagen.
  13. [13]  European Environment Agency (EEA) (2015b), Approximated EU GHG inventory: proxy GHG estimates for 2014, European Environment Agency, Copenhagen.
  14. [14]  Huo, C.F., Xu, M.H. and Ding, H. (2013), The impact brought by global warming and countermeasures. In: Proceedings of International Conference on Low-carbon Transportation and Logistics, and Green Buildings Springer-Verlag Berlin Heidelberg, pp. 1015- 1023.
  15. [15]  Jiang, Y.L., Xu C.F., Yao, Y. and Zhao, K.Q. (2004), Systems information of set pair analysis and its applications, International Conference on Machine Learning & Cybernetics 3, 1717-1722.
  16. [16]  King, E.D. (2015), EU commits to cut emissions “at least” 40% by 2030 in UN pledge. Available online: http://www.climatechangenews.com/2015/03/06/eu-commits-to-cut-emissions-at-least-40-by-2030-in-un-pledge/ (accessed on 14th August 2016).
  17. [17]  Knutson, T., McBride, J., Chan, J., Emanuel, K., Holland, G., Landsea, C., Held, I., Kossin, J.P., Srivastava, A. and Sugi, M. (2010), Tropical cyclones and climate change, Nature Geoscience 3, 157-163.
  18. [18]  Koo, C., Kim, H. and Hong, T. (2014), Framework for the analysis of the low-carbon scenario 2020 to achieve the national carbon emissions reduction target: Focused on educational facilities, Energy Policy 73, 356-367.
  19. [19]  Li, M.Q. (2011), Analysis of the bill of the basic act on global warming countermeasures reducing Japanese emission by 25 percent, Contemporary Economy of Japan 178, 61-69 (in Chinese).
  20. [20]  Liobikienė, G. and Mandravickaite, J. (2016), The EU Cohesion Policy implications to GHG emissions from production-based perspective, Environmental Science & Policy 55, 178–185.
  21. [21]  Liu, Z., Guan, D.B., Wei, W., Davis, S.J., Ciais, P., Bai, J., Peng, S.S., Zhang, Q., Hubacek, K., Marland, G., Andres, R.J., Crawford- Brown, D., Lin, J.T., Zhao, H.Y., Hong, C.P., Boden, T.A., Feng, K.S., Peters, G.P., Xi, F.M., Liu, J.G., Li, Y., Zhao, Y., Zeng, N. and He, K.B. (2015), Reduced carbon emission estimates from fossil fuel combustion and cement production in China. Nature 524, 335-338.
  22. [22]  McPhearson, T., Hamstead, Z.A. and Kremer, P. (2014), Urban ecosystem services for resilience planning and management in New York City, AMBIO 43, 502-515.
  23. [23]  Millenium Ecosystem Assessment (MA) (2005), Ecosystems and Human Well-being: General Synthesis, in: Ecosystems and Human Well-being: Synthesis, Island Press, Washington, DC.
  24. [24]  Olivier, J.G.J., Janssens-Maenhout, G., Muntean, M. and Peters, J. (2015), Trends in global CO2 emissions: 2015 Report. Available online: http://www.pbl.nl/en/publications/trends-in-global-co2-emissions-2015-report (accessed on 14th August 2016).
  25. [25]  Rapp, D. (2014), Assessing climate change: temperatures, solar radiation and heat balance. Springer International Publishing Switzerland, Cham, Heidelberg, New York, Dordrecht, London. Available online: http://www.amazon.com/gp/product/3319004549/?tag=ebooksshare0c-20 (accessed on 14th August 2016).
  26. [26]  Sergio, H., Franchito, V., Brahmananda Rao, J. and Pablo, R. (2012), Fernandez. Tropical land savannization: impact of global warming, Theoretical and Applied Climatology 109, 73-79.
  27. [27]  Su, M.R. and Fath, B.D. (2012), Spatial distribution of urban ecosystem health in Guangzhou, China, Ecological Indicator 15, 122- 130.
  28. [28]  Su, M.R., Fath, B.D., Yang, Z.F., Chen, B. and Liu, G.Y. (2013), Ecosystem health pattern analysis of urban clusters based on emergy synthesis: Results and implication for management, Energy Policy 59, 600-613.
  29. [29]  Su, M.R., Yang, Z.F. and Chen, B. (2009b), Set pair analysis for urban ecosystem health assessment, Communications in Nonlinear Science and Numerical Simulation 14, 1773-1780.
  30. [30]  Su, M.R., Yang, Z.F., Chen, B. and Ulgiati, S. (2009a), Urban ecosystem health assessment based on emergy and set pair analysis—A comparative study of typical Chinese cities, Ecological Modelling 220, 2341-2348.
  31. [31]  Su, M.R., Yang, Z.F., Liu, G.Y. and Chen, B. (2011), Ecosystem health assessment and regulation for urban ecosystems: A case study of the Yangtze River Delta urban cluster, China, Journal of Environmental Informatics 18, 65-74.
  32. [32]  Sugi, M. and Yoshimura, J. (2012), Decreasing trend of tropical cyclone frequency in 228-year high-resolution AGCM simulations, Geophysical Research Letters 39(19), 19805.
  33. [33]  Tang, Q.Y. and Feng, M.G. (2007), Data Processing System—Experiment Design, Statistical Analysis and Data Exploration, Science Press, Beijing (in Chinese).
  34. [34]  Tao, J. Fu, M.C., Sun, J.J., Zheng, X.Q., Zhang, J.J. and Zhang, D.X. (2014), Multifunctional assessment and zoning of crop production system based on set pair analysis-A comparative study of 31 provincial regions in mainland China, Communications in Nonlinear Science and Numerical Simulation 19, 1400-1416.
  35. [35]  The Economics of Ecosystems and Biodiversity (TEEB) (2011), TEEB manual for cities: ecosystem services in urban management. Available online: https://www.researchgate.net/publication/255919906_TEEB_Manual_for_Cities_Ecosystem_Services_in_Urban_Management (accessed on 14th August 2016).
  36. [36]  The World Bank (2014), World bank open data. Available online: http://data.worldbank.org/indicator (accessed on 14th August 2016).
  37. [37]  United Nations framework convention on climate change (UNFCCC) (2014), National Inventory Submissions 2014. Available online: https://unfccc.int/national_reports/annex_i_ghg_inventories/national_inventories_submissions/items/8108.php (accessed on 14th August 2016).
  38. [38]  Watson, C. and Bolton, P. (2013), Carbon Emissions Reduction Target, Environmental Management House of Commons Library.
  39. [39]  Yan, S.M. and Wu, G. (2011), Possible impact of global warming on the evolution of hemagglutinins from influenza a viruses, Biomedical and Environmental Sciences 24, 62-67.
  40. [40]  Yue, W.C., Cai, Y.P., Rong, Q.Q., Li, C.H. and Ren, L.J. (2014), A hybrid life-cycle and fuzzy-set-pair analyses approach for comprehensively evaluating impacts of industrial wastewater under uncertainty, Journal of Cleaner Production 80, 57-68.
  41. [41]  Zhao, K.Q. (1989), Set pair and set pair analysis-a new concept and systematic analysis method, Proceedings of the State Forum on System Theory and Regional Planning in China 87-91 (in Chinese).
  42. [42]  Zhu. L., Zhang, X.B. and Fan, Y. (2012), A non-linear model for estimating the cost of achieving emission reduction targets: The case of the U.S., China and India, Journal of Systems Science and Systems Engineering 21, 297-315.