Assessing the full greenhouse gas balance of EU countries and ecosystems
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Presented at the 3rd ICOS Science Conference in Prague, Czech Republic, 11-13 Sep 2018.
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Assessing the full greenhouse gas balance of EU countries and ecosystems
- 1. AssessingthefullgreenhousegasbalanceofEUcountriesand ecosystems a first look at different emission estimates and their uncertainties A.M. Roxana Petrescu1,2, Han Dolman1, Efisio Solazzo2, Adrian Leip2, Gert-Jan Nabuurs3, Mart-Jan Schelhaas3, Peter Bergamaschi2, Giacomo Grassi2, Roberto Pilli2 and Glen Peters4 1 VUA- Vrije Universiteit Amsterdam, The Netherlands 2 JRC European Commission, Ispra, Italy 3 WUR - Wageningen University, The Netherlands 4 CICERO- Center for International Climate Research, Norway
- 2. “When the European balance is extended from CO2 towards the main GHGs, C-uptake by terrestrial and aquatic ecosystems is offset by emissions of non-CO2 GHGs. As such, the European ecosystems are unlikely to contribute to mitigating the effects of climate change.” S. Luyssaert et al., 2012 (GCP - RECCAP)
- 3. Where we are… • Countries report their greenhouse gas (GHG) emissions yearly to UNFCCC • The scientific community carries out measurements and is running models to understand processes and quantify GHG emissions and their uncertainties • In February this year a new EU H2020 funded project started http://verify.lsce.ipsl.fr/
- 4. What we do… Assess the existing “best available/possible estimate” of country GHG budgets from the climate perspective having UNFCCC as policy base WP5: Reconciliation and assessment of different models and tools leading to verification of GHG inventories Provide the process through which different scientific data-streams on GHG budgets from other WPs will be synthesized for comparison with official inventories aiming to obtain the smallest overall uncertainty Illustration of the main land surface sources and sinks for CO2, CH4 and N2O GHGs for Europe.
- 5. Data sources - definitions For CH4 • UNFCCC – United Nations Framework Convention on Climate Change • FAO – The food and agriculture organization (UN) • EDGAR – The Emissions Database for Global Atmospheric Research (EC-JRC and PBL) • CAPRI – Common Agricultural Policy Regionalised Impact model (EC-JRC) • Inverse model ensemble For N2O • UNFCCC • FAO • EDGAR • CAPRI For Carbon (NBP – net biome productivity) • UNFCCC • EFISCEN - The European Forest Information SCENario Model (inventory- based model Alterra & EFI) • CBM – Carbon Budget Model (inventory-based model – EC-JRC)
- 6. Data sources CH4: UNFCCC, EDGAR, CAPRI, Inverse ensemble AGRICULTURE: Enteric fermentation (ENT), Manure management (MAN), Rice cultivation INVERSIONS • EU28 and DEU, UK+IRL N2O: UNFCCC, EDGAR, CAPRI, FAO AGRICULTURE: Manure management, direct soil emissions, grazing and indirect emissions • DEU, GRC, ITA, NDL, POL, SWE Years: 1990, 2000, 2010 and 2012 Carbon (NBP): UNFCCC vs EFISCEN vs CBM – forest remaining forest • DEU, GRC, ITA, NDL, POL, SWE Years: 2010 and 2015
- 7. Research questions • Are all these different data sources linked and consistent in using the input information (e.g. AD, EFs)? • Are uncertainties calculated using the same methodology? What causes the difference? • What are countries reporting and what are they not? • How can we calculate and choose the best estimate without dismissing another and reduce the overall uncertainty to obtain the minimum C budget for the atmosphere? • Are all data sources suitable to be used for GHG calculations? (e.g. UNFCCC, models, inventories)
- 8. Research questions • Are all these different data sources linked and consistent in using the input information (e.g. AD, EFs)? • Are uncertainties calculated using the same methodology? What causes the difference? • What are countries reporting and what are they not? • How can we calculate and choose the best estimate without dismissing another and reduce the overall uncertainty to obtain the minimum C budget for the atmosphere? • Are all data sources suitable to be used for GHG calculations? (e.g. UNFCCC, models, inventories)
- 9. CH4 ENT (kg CH4 / head yr) UNFCCC EF FAO EFs all years Countries 1990 2000 2010 2012 Germany 68.25 71.07 73.26 74.06 117 Greece 68.01 73.61 73.56 72.6 117 Italy 67.93 69.73 73.7 76.09 117 Netherlands 66.55 68.12 70.83 71.76 117 Poland 76.91 77.85 78.6 79.45 99 Sweden 67.14 69.57 69.02 68.93 117 Country choice for EFs for Enteric fermentation (ENT)
- 10. VariabilityofUNFCCCEFsusedforCH4 agriculture EntericFermentation(ENT)andManureManagement(MAN)–Cattle 64 66 68 70 72 74 76 78 80 82 1985 1990 1995 2000 2005 2010 2015 EF(kgCH4/head/yr) ENT DEU GRC ITA NDL POL SWE 0 2 4 6 8 10 12 14 16 18 20 1985 1990 1995 2000 2005 2010 2015 EF(kgCH4/head/yr) MAN DEU GRC ITA NDL POL SWE
- 11. Choiceofactivitydata-PopulationDairyCattle 0 1000 2000 3000 4000 5000 6000 7000 0 2 4 6 8 10 12 14 16 Populationheads(1000s) DEU GRC ITA NLD POL SWE FAO/EDGAR UNFCCC CAPRI FAO/EDGAR UNFCCC CAPRI FAO/EDGAR UNFCCC CAPRI FAO/EDGAR UNFCCC CAPRI 1990 2000 2010 2012
- 12. 0.00 2000.00 4000.00 6000.00 8000.00 10000.00 12000.00 14000.00 16000.00 1990 2000 2010 2012 CH4kt/yr Total EU28 Agriculture CH4 emissions 95% confidence interval EDGAR UNFCCC CAPRI mean 0 100 200 300 400 500 600 700 800 900 1000 1990 2000 2010 2012 N2Okt/yr Total EU28 Agriculture N2O emissions 95% confidence interval EDGAR UNFCCC CAPRI mean
- 13. 0 5000 10000 15000 20000 25000 30000 1990 2000 2010 2012 CH4kt/yr Total EU28 Agriculture CH4 emissions 95% confidence interval EDGAR UNFCCC CAPRI mean FAO 0 100 200 300 400 500 600 700 800 900 1000 1990 2000 2010 2012 N2Okt/yr Total EU28 Agriculture N2O emissions 95% confidence interval UNFCCC EDGAR CAPRI FAO mean
- 14. Research questions • Are all these different data sources linked and consistent in using the input information (e.g. AD, EFs)? • Are emissions calculated using the same methodology? What causes the difference? • What are countries reporting and what are they not? • How can we calculate and choose the best estimate without dismissing another and reduce the overall uncertainty to obtain the minimum C budget for the atmosphere? • Are all data sources suitable to be used for GHG calculations? (e.g. UNFCCC, models, inventories)
- 15. -50 0 50 100 150 200 1990 2000 2010 2012 ktN2O/yr MAN UNFCCC MAN EDGAR MAN CAPRI DIR UNFCCC DIR EDGAR DIR CAPRI DIR UNFCCC GRA EDGAR GRA CAPRI GRA UNFCCC IND EDGAR IND CAPRI IND FAO 0 200 400 600 800 1000 1200 1400 1600 1800 1990 2000 2010 2012 CH4kt/yr Germany - CH4 and N2O emissions from agricultural sub-sectors ENT UNFCCC ENT EDGAR ENT CAPRI ENT FAO MAN UNFCCC MAN EDGAR MAN CAPRI MAN FAO
- 16. Uncertaintybetweenuncertainties 0 500 1000 1500 2000 2500 3000 3500 2012 ktCH4/yr Germany CH4 from Agriculture - Enteric Fermentation UNFCCC EDGAR CAPRI FAO
- 17. CH4 from Inversions • Inverse ensemble vs UNFCCC total CH4 (sectors 1, 2, 3 and 5) • A posteriori emissions (inversions) • Scenario S4 (2006-2012) • Total CH4 emissions in Tg / yr • Inversions compared to UNFCCC anthropogenic emissions- uncorrelated uncertainties (sectors 1,2,3 and 5) calculated from total sectoral EU28 uncertainty • Uncertainty of inverse model - 1 sigma uncertainties as provided by the data providers
- 18. 0 5 10 15 20 25 30 35 2006 2007 2008 2009 2010 2011 2012 TgCH4/yr Total EU28 CH4 emissions from Inversions UNFCCC NAT TM5 LMDZ STILT NAME TM5_CT
- 19. 0 1 2 3 4 5 6 2006 2007 2008 2009 2010 2011 2012 TgCH4/yr UK+IRL UNFCCC NAT TM5 JRC LMDZ STILT NAME TM5-CT 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 2006 2007 2008 2009 2010 2011 2012 TgCH4/yr Germany UNFCCC NAT TM5 LMDZ STILT NAME TM5-CT CH4 from INVERSE, UNFCCC and Natural
- 20. Research questions • Are all these different data sources linked and consistent in using the input information (e.g. AD, EFs)? • Are emissions calculated using the same methodology? What causes the difference? • What are countries reporting and what are they not? • How can we calculate and choose the best estimate without dismissing another and reduce the overall uncertainty to obtain the minimum C budget for the atmosphere? • Are all data sources suitable to be used for GHG calculations? (e.g. UNFCCC, models, inventories)
- 21. -20 -10 0 10 20 30 40 50 1990 2000 2010 2012 ktN2O/yr GRC UNFCCC EDGAR CAPRI N2O emissions from agricultural sub-sectors -50 0 50 100 150 200 1990 2000 2010 2012 ktN2O/yr DEU
- 22. Research questions • Are all these different data sources linked and consistent in using the input information (e.g. AD, EFs)? • Are emissions calculated using the same methodology? What causes the differences? • What are countries reporting and what are they not? • How can we calculate and choose the best estimate without dismissing another and reduce the overall uncertainty to obtain the minimum C budget for the atmosphere? • Are all data sources suitable to be used for GHG calculations? (e.g. UNFCCC, models, inventories)
- 23. Methods Uncorrelated uncertainty calculation from the IPCC guidelines 2006: between EDGAR and UNFCCC sectoral totals Variance of the 95% confidence interval: in EDGAR and between different estimates of same sector (e.g. Agriculture)
- 24. 0 5000 10000 15000 20000 25000 30000 35000 UNFCCC EDGAR UNFCCC EDGAR UNFCCC EDGAR UNFCCC EDGAR UNFCCC EDGAR UNFCCC EDGAR UNFCCC EDGAR UNFCCC EDGAR UNFCCC EDGAR UNFCCC EDGAR UNFCCC EDGAR UNFCCC EDGAR UNFCCC EDGAR UNFCCC EDGAR UNFCCC EDGAR UNFCCC EDGAR UNFCCC EDGAR UNFCCC EDGAR UNFCCC EDGAR UNFCCC EDGAR UNFCCC EDGAR UNFCCC EDGAR UNFCCC EDGAR 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 20112012 ktCH4/yr Total EU28 sectoral CH4 emissions 1A Energy Industries 1.B.1 Fugitive emissions from solid fuels 1.B.2 Fugitive emissions from oil and gas 2.B Chemical Industry 2.C Metal Industry 3.A Enteric Fermentation 3.B Manure management 3.C Rice Cultivation 5.A Solid Waste Disposal 5.D Wastewater Treatment and Discharge
- 25. 0 2000 4000 6000 8000 10000 12000 14000 16000 Energy Industries Fugitive emissions from solid fuels Fugitive emissions from oil and gas Chemical Industry Metal Industry Enteric Fermentation Manure management Rice Cultivation Solid Waste Disposal Wastewater Treatment and Discharge 1A 1.B.1 1.B.2 2.B 2.C 3.A 3.B 3.C 5.A 5.D 2012 UNFCCC 2012 EDGAR 0 50 100 150 200 250 Chemical IndustryMetal IndustryRice Cultivation 2.B 2.C 3.C CH4kt/yr EU 28 total CH4 sectoral emissions - 2012 2012 UNFCCC 2012 EDGAR CH4 total sectoral emissions 2012 0 50 100 150 200 250 Chemical Industry Metal Industry Rice Cultivation 2.B 2.C 3.C CH4kt/yr Chemical industry, Metal Industry and Rice Cultivation 2012 2012 UNFCCC 2012 EDGAR
- 26. Research questions • Are all these different data sources linked and consistent in using the input information (e.g. AD, EFs)? • Are emissions calculated using the same methodology? What causes the difference? • What are countries reporting and what are they not? • How can we calculate and choose the best estimate without dismissing another and reduce the overall uncertainty to obtain the minimum C budget for the atmosphere? • Are all data sources suitable to be used for GHG calculations? (e.g. UNFCCC, models, inventories)
- 27. Carbon NBP definitions • UNFCCC NBP is = 'net change' in 'carbon stock change in living biomass‘. • CBM NBP is = the difference between NEP and the direct losses due to harvest and natural disturbances (e.g., fires) • EFISCEN NBP is derived from total tree gross growth minus soil losses, minus (density related )mortality minus harvest. Due to different ways in calculating the NBP we have to careful when assessing their results: UNFCCC vs EFISCEN vs CBM looking only forest land remaining forest land Units: tC / ha yr
- 28. UNFCCC–EFISCEN-CBM forestremainingforest -2.5 -2 -1.5 -1 -0.5 0 0.5 tC/hayr EFISCEN UNFCCC CBM 2010 2015 DEU GRC ITA NDL POL SWE DEU GRC ITA NDL POL SWE
- 29. We observed that… CH4 & N2O: UNFCCC, EDGAR, CAPRI, Inverse models • AD and EF are different • Methodology for uncertainty calculation differ • Countries do not report always same things • Within models ensembles methods differ and uncertainties are calculated different Carbon (NBP) • Definitions and sign conventions might differ • Not always consistency in model set-up
- 30. What next… We need • more data and more uncertainties… • to narrow down the analysis to sensitive parameters (AD, EF) which may trigger the differences • to check for consistency in the way uncertainties are calculated for different data sources • to define a common methodology for overall uncertainty calculation
Editor's Notes
- Dear audience, I am glad to take part again after 4 or more years in a scientific conference. For this reason I asked for a poster and …I ended up here having a talk…I hope I wont make a big full of myself…on purpose I have the main title in very small letters because we are not there yet, assessing the full ghg balance…this presentation is about trying to put together a little bit of whats available in terms of ghg emissions and their uncertainties…
- I found this paragraph written by Sebastiaan some time ago and I must say I like it very much, it really fits the purpose of our new project VERIFY…
- Other WPs deal with data pertaining to measurements, models, inventories and inversions
- There is some difference between countries choice of EFs FAO has the same EF for all years –uncertainty is introduced when comparisons are made with FAO data
- Variation is good, AD should be very similar, then uncertainty between different emissions estimates will be minimum!
- Sometimes there is difference between AD for different sources …see the example of Germany and Poland in 1990, the rest of the countries have very similar numbers – should decrease uncertainty…
- In terms of quantifying the total CH4 and N2O what does it mean? STDEV of the variance, 95% confidence interval – variance of the best estimate First attempt to quantify an uncertainty from different instruments : strengths and weaknesses We can notice that uncertainties in 2012 are decreasing for N2O and increasing for CH4…WHY??? need to look for reasons… Shall we use UNFCCC as baseline and calculate 95% interval for the other sources?
- With FAO…clear differences due to the use of different EFs but the overall uncertainty in the trend remains more or less the same…can we conclude that by introducing more data sources the uncertainty remains constant?
- Mostly yes in UNFCCC 90% of countries use Tier 1 approach following the IPCC guidelines, some countries use Tier 2 Monte Carlo, EDGAR and FAO use same AD, EDGAR EF from IPCC - they are close by We see that different sources have different emissions, methods or AD and EF are the cause of these differences…to be investigated
- UNFCCC – IPCC Tier 1 or 2 EDGAR – 95 % confidence interval Very different magnitude of uncertainty…which one is better?
- Another methodology is applied to inversions, I present an example of CH4 inversions results vs UNFCCC
- UNFCCC uncertainty = total EU28 uncertainty 5% from 2018 submissions Inversions total CH4 with 1 sigma uncertainty as provided by the data providers Examples of countries which are best constrained by atmospheric observations (BENELUX and France as well) Natural emissions (which are not included in UNFCCC) could explain part of the difference
- Inversions total CH4 with 1 sigma uncertainty as provided by the data providers Examples of countries which are best constrained by atmospheric observations (BENELUX and France as well) Natural emissions (which are not included in UNFCCC) could explain part of the difference
- Some countries do not report all sub-sectoral uncertainties (e.g. Greece for grazing) It is also a challenge aggregate similar the emissions e.g. Capri model is more detailed and includes in direct soil emissions more activities N2OHIS(histosoils) N2OCRO(crop residues) N2OAPP(application of manure) N2OSYN (anorganic fertilizer) Indirect soil emissions, what activities are in for different data sources? Atm deposition ??? Should be taken into account and where? FAO – EDGAR how do they aggregate? What do countries report to UNFCCC?
- Total uncorrelated uncertainty between sectoral totals for UNFCCC = 16% - IPCC formula EDGAR takes AD from FAO or similar and uses IPCC defaults or similar? I am just wondering why EDGAR does not use UNFCCC directly? Is that to ensure consistent methodology over all countries?
- UNFCCC Tab 4 Forest land remaining forest land - sink cell B9 –(Net CO2 emissions/removals ) Area Table 4.1 cell B7 UNFCCC Table 4 Total LULUCF– cell B7 (Net CO2 emissions/removals ) Area Table 4.1 cell L17