Quantitative quality assessment of the greenhouse gas inventory for agriculture in Europe

Chapter

Abstract

The greenhouse gas inventory of the European Communities and its estimation of the uncertainty is built from 15 individual and independent greenhouse gas inventories. This presents a particular challenge and is possible only if homogeneous information is available for all member states and if a proper evaluation of correlation between member states is performed. To this end, we present a methodology that estimates a quantitative measure for the aggregated Tier-level as well as the uncertainty for the main categories in the agriculture sector. In contrast to the approach suggested in the IPCC guidelines, which uses uncertainty estimates for activity data and emissions factors for each source category, the method presented uses quantitative information from individual parameters used in the inventory calculations, in combination with a well defined procedure to aggregate the information. Not surprisingly, N2O emissions from agricultural soils are found to dominate the uncertainty. The results demonstrate the importance of correlation, if uncertainties are combined for the whole of Europe. The biggest challenge seems to be to conceptually harmonize the uncertainty estimates for the activity data (which tend to be underestimated) and emission factors (which tend to be overestimated).

Keywords

Emission Factor Manure Management Source Category Enteric Fermentation IPCC Guideline 
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. Bouwman AF (1994) Method to estimate direct nitrous oxide emissions from agricultural soils, report 773004004. National Institute of Public Health and Environmental Protection, BilthovenGoogle Scholar
  2. Bouwman AF, Boumans LJM, Batjes NH (2002) Emissions of N2O and NO from fertilized fields: summary of available measurement data. Glob Biogeochem Cycles 16(4):1058CrossRefGoogle Scholar
  3. Butterbach-Bahl K, Werner C (2005) Upscaling of national N2O emissions from soils with biogeochemical models—Germany. In: Leip A (ed) N2O emissions from agriculture. Report on the expert meeting on “improving the quality for greenhouse gas emission inventories for category 4D,” joint research centre, 21–22 October 2004, Ispra. Vol. EUR 21675. Office for Official Publication of the European Communities, Luxembourg, pp 138–134Google Scholar
  4. Del Grosso SJ, Mosier AR, Parton WJ, Ojima DS (2005) DAYCENT model analysis of past and contemporary soil N2O and net greenhouse gas flux for major crops in the USA. Soil Tillage Res 83(1):9–24CrossRefGoogle Scholar
  5. EEA (2007) Annual European community greenhouse gas inventory 1990–2005 and inventory report 2007. Submission to the UNFCCC Secretariat, European Environment AgencyGoogle Scholar
  6. EEA (2008) Annual European community greenhouse gas inventory 1990–2006 and inventory report 2008. Submission to the UNFCCC Secretariat, European Environment AgencyGoogle Scholar
  7. EEA (2009) Annual European community greenhouse gas inventory 1990–2007 and inventory report 2009. Submission to the UNFCCC Secretariat, European Environment AgencyGoogle Scholar
  8. Freibauer A (2003) Regionalised inventory of biogenic greenhouse gas emissions from European agriculture. Eur J Agron 19:135–160CrossRefGoogle Scholar
  9. Grassi G, Monni S, Federici S, Achard F, Mollicone D (2008) From uncertain data to credible numbers: applying the conservativeness principle to REDD. Environ Res Lett 3:035005CrossRefGoogle Scholar
  10. IPCC (1997) Houghton JT, Meira Filho LG, Lim B, Treanton K, Mamaty I, Bonduki Y, Griggs DJ, Callander BA (eds) Revised 1996 IPCC guidelines for national greenhouse gas inventories. IPCC/OECD/IEA, ParisGoogle Scholar
  11. IPCC (2000) Penman J, Kruger D, Galbally I, Hiraishi T, Nyenzi B, Emmanuel S, Buendia L, Hoppaus R, Martinsen T, Meijer J, Miwa K, Tanabe K (eds) Good practice guidance and uncertainty management in national greenhouse gas inventories. IPCC/OECD/IEA/IGES, HayamaGoogle Scholar
  12. IPCC (2006) Eggleston HS, Buendia L, Miwa K, Ngara T, Tanabe K (eds) 2006 IPCC guidelines for national greenhouse gas inventories, prepared by the national greenhouse gas inventories programme. IGES, JapanGoogle Scholar
  13. Jonas M, Gusti M, Jeda W, Nahorski Z, Nilsson S (2007) Comparison of preparatory signal detection techniques for consideration in the (post-)Kyoto policy process. In: Proceedings of the 2nd international workshop on uncertainty in greenhouse gas inventories, international institute for applied systems analysis, Laxenburg, Austria, pp 107–134Google Scholar
  14. Keizer Cd, Ramírez A, Sluijs JVd (2007) Uncertainty ranges and correlations assumed in tier 2 studies of several European countries. In: Proceedings of the 2nd international workshop on uncertainty in greenhouse gas inventories, international institute for applied systems analysis, Laxenburg, Austria, pp 35–39Google Scholar
  15. Leip A (2005a) Greenhouse gas emissions from agriculture in Europe. In: Kuczynski T, Dämmgen U, Webb J, Myczko A (ed). Emissions from European agriculture. Wageningen Academic Publishers, The Netherlands, pp 35–49Google Scholar
  16. Leip A (2005b) Executive summary and recommendations. In: Leip A (ed) N2O emissions from agriculture. Report on the expert meeting on “improving the quality for greenhouse gas emission inventories for category 4D”, joint research centre, 21–22 October 2004, Ispra, Vol. EUR 21675. Office for Official Publication of the European Communities, Luxembourg, pp 155–160Google Scholar
  17. Leip A, Dämmgen U, Kuikman P, van Amstel AR (2005) The quality of European (EU15) greenhouse gas inventories from agriculture. Environ Sci 2(2–3):177–192CrossRefGoogle Scholar
  18. Leip A, Marchi G, Koeble R, Kempen M, Britz W, Li C (2008) Linking an economic model for European agriculture with a mechanistic model to estimate nitrogen and carbon losses from arable soils in Europe. Biogeosciences 5(1):73–94. Available at http://www.biogeosciences.net/5/73/2008/bg-5-73-2008.html CrossRefGoogle Scholar
  19. Li CS, Zhuang YH, Cao MQ, Crill P, Dai ZH, Frolking S, Moore B, III, Salas W, Song WZ, Wang XK (2001) Comparing a process-based agro-ecosystem model to the IPCC methodology for developing a national inventory of N2O emissions from arable lands in China. Nutr Cycl Agroecosyst 60(1–3):159–175CrossRefGoogle Scholar
  20. Monni S, Syri S, Savolainen I (2004) Uncertainties in the Finnish greenhouse gas inventory. Environ Sci Policy 7:87–98CrossRefGoogle Scholar
  21. Monni S, Syri S, Pipatti R, Savolainen I (2007) Extension of EU emissions trading scheme to other sectors and gases: consequences for uncertainty of total tradable amount. Water Air Soil Pollut Focus 7(4):529–538CrossRefGoogle Scholar
  22. Monni S, Grassi G, Leip A (2008) Uncertainty estimation and management in AFOLU sector—background paper for the IPCC workshop on IPCC guidance on estimating emissions and removals from land uses, 13–15 May 2008. Helsinki, FinlandGoogle Scholar
  23. Nahorski Z, Horabik J, Jonas M (2007) Compliance and emissions trading under the Kyoto protocol: rules for uncertain inventories. Water Air Soil Pollut Focus 7(4):539–558CrossRefGoogle Scholar
  24. Olsthoorn X, Pielaat A (2003) Tier-2 uncertainty analysis of the Dutch greenhouse gas emissions 1999. Institute for Environmental Studies, AmsterdamGoogle Scholar
  25. Passant NR (2003) Estimation of uncertainties in the national atmospheric emission inventory, AEAT/ENV/R/1039 Issue 1Google Scholar
  26. Petersen SO, Sommer SG, Béline F, Burton C, Dach J, Dourmad JY, Leip A, Misselbrook T, Nicholson F, Poulsen HD, Provolo G, Sørensen P, Vinnerås B, Weiske A, Bernal M-P, Böhm R, Juhász C, Mihelic R (2007) Recycling of livestock manure in a whole-farm perspective. Livest Sci 112:180–191. Available at  10.1016/j.livsci.2007.09.001 CrossRefGoogle Scholar
  27. Ramiréz A, de Keizer C, van der Sluijs JP (2006) Monte Carlo analysis of uncertainties in the Netherlands greenhouse gas emission inventory for 1990–2004, NWS-E-2006-58. Department of Science, Technology and Society, Copernicus Institute for Sustainable Development and Innovation. Utrecht University, Utrecht, NetherlandsGoogle Scholar
  28. Rypdal K, Flugsrud K (2001) Sensitivity analysis as a tool for systematic reductions in greenhouse gas inventory uncertainties. Environ Sci Policy 4(2–3):117–135CrossRefGoogle Scholar
  29. Rypdal K, Winiwarter W (2001) Uncertainties in greenhouse gas emission inventories—evaluation, comparability and implications. Environ Sci Policy 4(2–3):107–116CrossRefGoogle Scholar
  30. Stehfest E, Bouwman AF (2006) N2O and NO emissions from agricultural fields and soils under natural vegetation: summarizing available measurement data and modelling of global annual emissions. Nutr Cycl Agroecosyst V74(3):207–228CrossRefGoogle Scholar
  31. Winiwarter W (2007) Quantifying uncertainties of the Austrian greenhouse gas inventory. Final report to project no 1 S2.00116.0.0 contracted by Umweltbundesamt, Austrian Research CentresGoogle Scholar

Copyright information

© The Author(s) 2010

Authors and Affiliations

  1. 1.European Commission Joint Research CentreInstitute for Environment and SustainabilityIspraItaly
  2. 2.John Research CenterClimate Change Unit T.P. 290IspraItaly

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