Spatial GHG inventory at the regional level: accounting for uncertainty

Chapter

Abstract

Methodology and geo-information technology for spatial analysis of processes of greenhouse gas (GHG) emissions from mobile and stationary sources of the energy sector at the level of elementary plots are developed. The methodology, which takes into account the territorial specificity of point, line, and area sources of emissions, is based on official statistical data surveys. The spatial distribution of emissions and their structure for the main sectors of the energy sector in the territory of the Lviv region of Ukraine are analyzed. The relative uncertainties of emission estimates obtained are calculated using knowledge of the spatial location of emission sources and following the Tier 1 and Tier 2 approaches of IPCC methodologies. The sensitivity of total relative uncertainty to change of uncertainties in input data uncertainties is studied for the biggest emission point sources. A few scenarios of passing to the alternative energy generation are considered and respective structural changes in the structure of greenhouse gas emissions are analyzed. An influence of these structural changes on the total uncertainty of greenhouse gas inventory results is studied.

Keywords

Emission Factor Energy Sector Emission Estimate Fuel Treatment Elementary Plot 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Bun R (ed) Gusti M, Dachuk V et al (2004) Information technologies for greenhouse gas inventories and prognosis of the carbon budget of Ukraine. Lviv, Ukraine, 376 pp. Needs call out in text Bun et al. 2004Google Scholar
  2. Bun R, Gusti M, Bun A, Hamal Kh (2006) Multilevel model for greenhouse gas inventory and uncertainty analysis concerning the Kyoto Protocol implementation. In: Intern Conf on Ecological Modelling, “ICEM 2006.” Yamaguchi, JapanGoogle Scholar
  3. Bun A, Hamal K, Jonas M, Lesiv M (2010) Verification of compliance with GHG emission targets: Annex B countries. Clim Change. doi: 10.1007/s10584-010-9906-6 Google Scholar
  4. Fuel (2005) Fuel and energy resources of Lviv Region. Reference book, Lviv, Statistical DepartmentGoogle Scholar
  5. Horabik J, Nahorski Z (2010) A statistical model for spatial inventory data: a case study of N2O emissions in municipalities of southern Norway. Clim Change. doi: 10.1007/s10584-010-9913-7 Google Scholar
  6. Industry (2005) Industry of Lviv Region. Reference book, Lviv Statistical DepartmentGoogle Scholar
  7. IPCC (2006) 2006 IPCC Guidelines for national greenhouse gas inventories. In: Eggleston HS, Buendia L, Miwa K, Ngara T, Tanabe K (eds) Prepared by the National Greenhouse Gas Inventories Programme. IGES, JapanGoogle Scholar
  8. Jonas M, Gusti M, Jêda W, Nahorski Z, Nilsson S (2010) Comparison of preparatory signal analysis techniques for consideration in the (post-) Kyoto policy process. Clim Change. doi: 10.1007/s10584-010-9914-6 Google Scholar
  9. Jonas M, Nilsson S, Bun R, Dachuk V, Gusti M, Horabik J, Jęda W, Nahorski Z (2004) Preparatory signal detection for Annex I countries under the Kyoto Protocol—a lesson for the post-Kyoto policy process. Interim Report IR-04-024 International Institute for Applied Systems Analysis. Laxenburg, AustriaGoogle Scholar
  10. Lindley SJ, Longhurst JWS, Watson AFR, Conlan DE (1996) Procedures for the estimation of regional scale atmospheric emissions. An example from the north-west region of England. Atmos Environ 30(17):3079–3091CrossRefGoogle Scholar
  11. Nahorski Z, Horabik J (2010) Compliance and emission trading rules for asymmetric emission uncertainty estimates. Clim Change. doi: 10.1007/s10584-010-9916-4 Google Scholar
  12. Pacyna JM, Graedel TE (1995) Atmospheric emissions inventories: status and prospects. Annu Rev Energy Environ 20:265–300CrossRefGoogle Scholar
  13. Power (2002) Power industry of Ukraine: 1991–2000. Reference book, Kyiv, UkrinformenergoservisGoogle Scholar
  14. Rypdal K, Winiwarter W (2001) Uncertainties in greenhouse gas emission inventories—evaluation, comparability, and implications. Environ Sci Policy 4(2–3):107–116CrossRefGoogle Scholar
  15. Statistical (2005) Statistical year-book of Lviv Region on 2005 Part II: Administrative Units and Cities of Lviv Region Lviv Statistical Department UkraineGoogle Scholar
  16. Wang X, Mauzerall D, Hu J, Russel A, Larson E, Woo J, Streets D, Guenther A (2005) A high-resolution emission inventory for eastern China in 2000 and three scenarios for 2020. Atmos Environ 39:5917–5933CrossRefGoogle Scholar
  17. Winiwarter W, Rypdal K (2001) Assessing the uncertainty associated with national greenhouse gas emission inventories: a case study for Austria. Atmos Environ 35(32):5425–5440CrossRefGoogle Scholar
  18. Winiwarter W, Dore C, Hayman G, Vlachogiannis D, Gounaris N, Bartzis J, Ekstrand S, Tamponi M, Maffeis G (2003) Methods for comparing gridded inventories of atmospheric emissions—application for Milan province Italy, and the Greater Athens Area Greece. Sci Total Environ 303:231–243CrossRefGoogle Scholar

Copyright information

© Springer Science + Business Media B.V. 2010

Authors and Affiliations

  1. 1.Lviv Polytechnic National UniversityLvivUkraine
  2. 2.International Institute for Applied Systems AnalysisLaxenburgAustria

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