Allowed carbon emission for the WRE450 pathway where atmospheric CO2 is stabilized at 450 ppm (dot-dash line, right axis) as obtained with the Bern

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1 ASSESSMENT OF THE TERRESTRIAL CARBON BALANCE IN EUROPE (CARBOEUROPE) Riccardo Valentini Department of Forest Science and Environment University of Tuscia, Viterbo

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3 Allowed carbon emission for the WRE450 pathway where atmospheric CO2 is stabilized at 450 ppm (dot-dash line, right axis) as obtained with the Bern CC model (Joos et al., GBC, 2001). The model s climate sensitivity expressed as equilibrium temperature increase for a doubling of atmospheric CO2 has been varied between 0oC (no climate feedbacks), 1.5 oc, 2.5 oc (standard case), and 4.5 oc. The lower bounding curve has been calculated by phasing out CO2 fertilization, the major terrestrial sink process in the model, after year 2000 and by setting slow ocean mixing rates. The upper bounding case has been obtained by implementing no dependence of soil respiration rates on soil warming, thereby suppressing the major terrestrial source process in the model

4 Global Budget: Slow in Fast out Atmosphere Surface biosphere Atmospheric accumulation rate 3.2 GtC per year 1990s 6.3 F Fuel, Cement 2.2 Land-Use Change 2.9 Land Uptake 2.4 Ocean Uptake Fast process ( days) Slow process ( days)

5 Vulnerability of Carbon Pools Carbon in tropical vegetation: 340 Pg Carbon in wetlands: 450 PgC Carbon in frozen soils: 400 PgC Risk over the coming century of up to 200 ppm of atmospheric CO 2 Not included in most climate simulations. Gruber et al. 2004

6 Variation in T and CO 2 over last 4 gla cycles Future? Today CO 2 A stable mode of behaviour for at least the past ½ million years Temperature Petit et al., 1999 Falkowski et al., 2000

7 THE ACCOUNTING PROBLEM Kyoto carbon sequestration Disturbances Vulnerable pools

8 CARBOEUROPE Integrated Project GOAL The overarching aim of the CarboEurope-IP is to understand, quantify and predict the terrestrial carbon balance of Europe and associated uncertainties at local, regional and continental scale.

9 CarboEurope IP: Building blocks

10 CARBOEUROPE consortium 97 European Institutions affiliated ~240 scientists involved 17 EU countries involved Scientific collaborations with USA, Australia and Japan Coordination office : E-D. Schulze, Max Plank Institute, Jena Germany Component leaders : Atmosphere P. Ciais LSCE, France Ecosystems: R. Valentini Un. Tuscia, Italy Regional: H. Dolman, VUE, The Netherlands Integration : M. Heimann, MPI, Germany

11 Carboeurope use a multiple constraint approach 1000 km Upscaling Prediction 10 km ha µm dm Downscaling Verification

12 Carbon and energy flux by eddy covariance Magnesium Perchlorate Carbosorb Filter Pump 400 ml/min 6 l/m Reference Cell Sample Cell C H O P P E R Pump Filter Pressure Transducer Mass Flow Controller Sample Inlet

13 EDDY FLUX CarboEurope IP 16 Clusters 103 Eddy of covariance sites sites (different 50 forests land uses/covers) 28 grasslands 22 crops 3 others Useful data for parametrization / validation Standardized quality control and gap-filling Total 101 sites of ecosystem Centralized fluxes database with standard, Continuous fully transparent monitoring data processing (51 sites for 5 years)

14 On line data Globalstar LEO (Low Elevation Orbiting Satellites) TACOS flux data upload Data receiving modem Database

15 Net Ecosystem Exchange of CO2 for a beech forest May 22 May 24 May 26 May 5 NEE (µmolco 2 m -2 s -1 ) Day of the year

16 Sky Arrow ERA Attitude GPS Net Radiation PAR Radiation Novatel GPS Switch BOX GPS Electronics Pressure Sphere T Fast Response T Low Response IRGA Surface T Dew Point T Videocamera

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18 CarboEurope : Continental Scale Atmospheric concentration measurements Modelling CO 2 O 2, 13 C 14 CO 2, CO Concentrations Vertical profiles C 18 OO SF 6, 222 Rn Mesoscale atmsospheric transport Inversion Horizontal transects

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20 Science 2003, 300:

21 European C-balance before CARBOEUROPE-IP Janssens et al. (2003)

22 Sectorial terrestrial Carbon Budget for Europe All numbers for geographic Europe Fossil fuel emissions = -1850

23 (Janssens et al. 2004) Beyond Kyoto: Winners and losers from full carbon accounting in European countries

24 Land use acts as a driver of European Countries Carbon budget

25 European forest carbon uptake 4,0 NEE (t C ha -1 y -1 ) 2,0 0,0-2,0-4,0-6,0 2a ,0-10, Latitude ( N) Tyically maximum t C ha-1 y-1 are stored in forest soils

26 Effects of management on carbon sequestration

27 Annual carbon budgets of in different age classes of Pinus sylvestris, Finland 500 Clearcut, years, years, years, Cumulative NEE (g C m -2 ) julian date -400 Pertti Hari, Department of Forest Ecology, University of Helsinki

28 Croplands picture source:

29 Distribution of croplands in Europe

30 Why croplands? European croplands (for Europe as far east as the Urals) lose 300 Mt C y -1 (Janssens et al., 2003) Mean figure for the European Union (EU15) estimated to be 78 (SD: 37) Mt C y -1 (Vleeshouwers & Verhagen, 2002) Largest biospheric source of carbon lost to the atmosphere in Europe each year Highest uncertainty of all European fluxes There is significant potential to decrease the flux of carbon to the atmosphere from cropland, and for cropland management to sequester soil carbon. Courtesy of P. Smith

31 Agricultural non-co 2 GHG emissions in Europe GHG Yearly emission Mt CO 2 -C equivalents Carbon dioxide (CO 2 ) 78 Methane (CH 4 ) ~50 Nitrous oxide (N 2 O) ~60

32 Change in cropland SOC climate only.

33 Change in cropland SOC climate, NPP & tech.

34 Grasslands

35 Net Biome Productivity of a grazed grassland (tc ha -1 yr -1 ) CH Herbivore respiration 19 Gross primary productivity CO Animal excreta Herbivore Grazing Soil 3 Végétation 7 Root turnover Rhizodeposition Litter Vegetation 0 9 Shoot respiration 9.2 DOC, DIC? Sown grassland with intensive grazing Management, 2004) Net Biome Productivity: +0.5 Below-ground respiration grazing (Soussana et al., Soil Use and

36 Sorted dotplot of NEE and NBP over GreenGrass sites (kg C ha -1 yr -1 ) NEE and NBP Oensingen Int2002 Oak Park2002 Lille Valby2003 Oensingen Ext2002 Easter Bush2002 Oak Park2003 Oensingen Int2003 Italy2003 Bugac2003 Laqueuille Ext2002 Oensingen Ext2003 Bugac2002 Laqueuille Int2003 Laqueuille Int2002 Laqueuille Ext2003 NEE NBP Sink Source

37 Annual NEE, N 2 O and CH 4 at sites (CO 2 -C equivalents) All GHGs Oensingen Int2002 Oak Park2002 Lille Valby2003 Oensingen Ext2002 Easter Bush2002 Oak Park2003 Oensingen Int2003 Italy2003 Bugac2003 Laqueuille Ext2002 Oensingen Ext2003 Bugac2002 Laqueuille Int2003 Laqueuille Int2002 Laqueuille Ext2003 CH4 N2O CO2 (NEE) Sink t equivalent C ha -1 y -1 Source

38 PaSim model Nitrogen outputs Nitrogen Inputs Carbon Inputs CO 2 emissions NH3 N2O N2 N2O NO3- N deposition N fertiliser CO2 CH 4 emissions CH4 N fixation photosynthesis autotrophic respiration yield decomposition heterotrophic respiration substrate allocation yield volatilization nitri/ denitrification N uptake root lamina stem ear Carbon and Nitrogen BIOMASS mortality cutting grazing leaching Carbon and Nitrogen litter (structural / metabolic) animals decomposition urine dung active slow passive soil carbon and nitrogen

39 Net Primary Productivity of cut and grazed grasslands fpar (-) NPP (tc ha-1 y-1) PASIM MODIS temp ( C) precip (mm y-1) temp ( C) precip (mm y-1)

40 INTEGRATION AND DATA ASSIMILATION

41 CarboEurope comprises range of Advantages Major concern Major uncertaintie s DOPs modeling approaches Data-oriented approaches (DOP) Few parameters, flexible assumptions, computational Data efficiency, precision and representativity uncertainties easier (spatial, to definethematic) Landcover, scalingproperties ANN MOD17+, CO 2 -fix Process-oriented approaches (POP) Possible attribution of sinks/sources to human activity, predictions/ Validity extrapolations of process assumptions possible, ecological (e.g. steady interpretation state spin-up Landcover, run) management (history), soil pools and processes LPJ LU, BBGC Orchidee LU LPJ ORCHIDEE POPs

42 Lund-Potsdam-Jena DGVM (LPJ) Sitch et al., Global Change Biology 2003 Bondeau et al. in prep., Zaehle et al. in prep Weather/Climate (timeseries of temperature, precipitation and radiation) Daily processes: Photosynthesis/Transpiration Maintenance Respiration Timeseries of land-use patterns Erhard et al., (in prep.) Soil data Water balance Litter fall Heterotrophic respiration Annual processes include: Allocation & Turnover Resource competition Vegetation dynamics Disturbance (fire) Management (crops, forest) LPJ landuse classes: Cropland, pasture, managed forests, natural vegetation, barren land 13 crop functional types, 8 tree functional types, 2 herbaceous functional types

43 MODIS-MOD17 radiation-use efficiency model Daily meteorological input (DAO) GPP ( T ) f ( VPD ) ( PAR fpar) = RUEmax f1 min 2 avg, daylight According to vegetation functional type (Biome-PLUT) From RT-model, reflects vegetation structure NEE=GPP-Reco, Reco=f(T, P, LAI) cf. Reichstein et al. (2003) Courtesy M. Reichstein)

44 Artificial Neural Network training Input and Output database procedure Used to evaluate the fit Validation set Test set Training set Used to optimize the connection weights Input dataset Used to evaluate the trained ANN Input layer Hidden layer Trained ANN Output Output layer = node or unit = connection Courtesy D. Papale

45 CARBON DATA ASSIMILATION SYSTEM Reduction in uncertainty, expressed as 1-std prior/std optimized, for the 23 parameters of BETHY used in inversion against 7 days of halfhourly flux measurements at the Loobos site in the Netherlands. Standard deviation of a priori uncertainties: 25% of parameter value. Negative values are due to the different forms of the PDF before and after optimization.

46 CAMELS project findings (Kattge et al. 2004) Mean net fluxes to the atmosphere for the period (gc m-2y-1). Uncertainty of mean net flux to the atmosphere for the period (gc m-2y-1) expressed as the standard deviation. Dots indicate locations of observational sites.

47 Heat wave in Europe Anomalies fpar [%] LPJ 2003 MOD ANN avg fpar Jul-Sept AVHRR-GIMMS MODIS Dashed lines: mean +/- 5 SD Year LPJ ORCHIDEE LPJ MOD17 ANN (w/o 2000) Relative easting (km/10)

48 CONCLUSIONS AREAS OF JAPAN - EU COLLABORATION 1. Technologies on flux measurements by flux tower and aircraft Exchange of data 2. Atmospheric concentration measurements Exchanges of calibration cylinders, analytical methodologies 2. Models both process oriented and data driven Comparisons versus global constraints 3. Exchange of views on full carbon accounting and beyond Kyoto negotiation scientific inputs