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An estimation of Nitrous Oxide Emissions from Agricultural Soils within the EU15 using a mechanistic model. Declan Mulligan

Declan Mulligan

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An estimation of Nitrous Oxide Emissions from Agricultural Soils within the EU15 using a mechanistic model. Declan Mulligan. Table of Contents. Introduction. Modelling, data feedback 2. European Database Data sources, gaps, Uncertainties . Model description Why this model was chosen - PowerPoint PPT Presentation

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An estimation of Nitrous Oxide Emissions from Agricultural Soils within the EU15 using a mechanistic model.

An estimation of Nitrous Oxide Emissions from Agricultural Soils within the EU15 using a mechanistic model.

Declan Mulligan

• Introduction.

• Modelling, data feedback

• 2. European Database

• Data sources, gaps, Uncertainties.

• Model description

• Why this model was chosen

• Results

• Comparison with IPCC

• Conclusion

Table of ContentsTable of Contents

UNFCCC

Secretariat

DG Env

Monitoring

Mechanism

EEA

ETC ACC

Reference System

Research

•Modelling

• Inventory estimation

•Measuring campaigns

Member states

Importance of this StudyImportance of this Study

•EU member states must gather greenhouse gas emission data (Kyoto Protocol)

•EU reference system to assess and improve the quality of EU inventory produced by the Monitoring Mechanism.

Official data:

•European Soil Bureau

•Eurostat

•GISCO

•EMEP

•Others…

OverviewOverview

Process Based Model

Data:

Multiple Sources & Formats

Harmonized Geographical

Database

Alternative

Scenarios

Results

NitratesAmmonium bicarbonate Urea

Anhydrous ammonia

Country NO3 NH4HCO3 Urea NH3Austria 0.00 0.38 0.04 0.00Belgium-Lux 0.00 0.25 0.01 0.00Denmark 0.09 0.43 0.01 0.00Finland 0.00 0.88 0.00 0.00France 0.30 0.32 0.08 0.00Germany 0.00 0.36 0.11 0.00Greece 0.21 0.37 0.01 0.00Ireland 0.00 0.40 0.15 0.00Italy 0.05 0.21 0.38 0.00Netherlands 0.00 0.14 0.01 0.00Portugal 0.00 0.30 0.12 0.00Spain 0.09 0.30 0.22 0.00Sweden 0.09 0.33 0.00 0.00United Kingdom 0.29 0.33 0.05 0.00

270671 18.40 10.80 0.00 2 19.40 13.60 0.00 3 21.00 14.40 0.00 4 17.40 12.60 0.00 5 17.40 8.80 0.00 6 16.40 9.80 3.00 7 14.00 9.80 0.40 8 17.00 8.80 0.00 9 17.00 10.60 0.00 10 16.20 12.00 3.80 11 16.00 11.20 0.00 12 16.40 6.20 0.00 13 18.20 12.20 0.00

GIS

Access

1 Unit_ID 10012 NUT_ID IT1123 Nut_Name Torino4 Longitude 7.4832435 Latitude 45.21259

County Characteristics

1 Unit_ID 10012 Climate_file 450553 N_conc 0.95

Climate Details

1 Grid_ID 450552 Julian Day 13 Max Temp 4.74 Min Temp -0.75 Rainfall (cm) 0.1

Climate File

1 Unit_ID 10012 SOC 0.13234 Clay content 0.46 pH 7.38 BD 1.66

Soil Properties

1 Unit_ID 10012 Cropland 2582983 Sown area 2965064 Fertiliser T 172295 Fertiliser Kg Ha 66.76 Irrigation 0.47 Partition of Fert. *

Farming Management

EUROSTAT - http://europa.eu.int/comm/eurostat/

•GISCO – (GIS database)

•New Cronos - (statistical database).

•ESB (European Soil Bureau), IES JRC

• http://ies.jrc.cec.eu.int/Projects/ESB/

•MARS (monitoring Agriculture with remote sensing) ,IPSC JRC

•(climate & rapid areas estimate sites) http://mars.jrc.it/

•EMEP - (Co-operative Programme for Monitoring and Evaluation of the Long-Range Transmission of Air pollutants in Europe)

•http://www.emep.int/

•FAO - Food and Agriculture Organization of the United Nations.

•IFA - International Fertiliser Industry Association.

2. Model Database: Data Sources2. Model Database: Data Sources

2. Model Database: Geographic units2. Model Database: Geographic units

1 Unit_ID 10012 NUT_ID IT1123 Nut_Name Torino4 Longitude 7.4832435 Latitude 45.212593

County Characteristics

Digital Degrees

•Model run daily for one year for each crop type within each predetermined geographic unit.

•Grid or Administrative unit (i.e.Nuts ).

•Nomenclature of territorial Units

for statistics

•The scale of the unit should best represent the scale of input data.

•50 km Interpolated climate grid (MARS database).

•1500 meteorological stations received via the Global Telecommunication System (GTS) of the World Meteorological Organisation (WMO).

2. Model Database: Climate2. Model Database: Climate

Daily data.

• Maximum Air Temperature oC• Minimum Air Temperature oC• Precipitation mm• Mean wind speed (at 10m height) m/s• Mean Vapour Pressure hPa• Calculated Potential Evaporation mm• Calculated Global Radiation KJ/m2

Meteo Grid 65040

0

5

10

15

20

25

Julian Day

oC

Rainfall mm Prec_mm W MIN_TEMP W MAX_TEMP W Solar Radiation Mj/m2

1 Unit_ID 10012 Climate_file 450553 N_conc 0.95

Climate Details

1 Grid_ID 450552 Julian Day 13 Max Temp 4.74 Min Temp -0.75 Rainfall (cm) 0.1

Climate File

2. Model Database: Climate2. Model Database: Climate

1 Unit_ID 10012 Climate_file 450553 N_conc 0.95

Climate Details

2. Model Database: Climate2. Model Database: Climate

• Total N (NH4+ & NO3-) mg l conc. in rainfall from point source data (EMEP).

• Paucity of Data.

• EMEP 50 K grid data in mg N/m2)

2. Model Database: Soil Parameters2. Model Database: Soil Parameters

•European Soil Database 1:1,000,000

(European Soil Bureau).

SMU 1STU_74 85 %STU_5 5 %STU_23 10 %

DOM_STU DominantSTU = STU 74

STU 74SOIL …TEXT1 …TD1 …IL …… …

SMU 1Country= SP SMU 2

Country= SP

2. Model Database: Soil Parameters2. Model Database: Soil Parameters

•10 x 10 km grid of dominant soil type/ soil profile linked to pedotransfer soil profile database.

•Horizon 1 (top layer)

•Classes

1 Unit_ID 10012 SOC Max, min 0.0124 Clay content max, min 0.46 pH max, min 7.38 BD max, min 1.66

Soil Properties

2. Model Database: Soil Parameters2. Model Database: Soil Parameters

•Minimum and maximum soil values produce range wide enough to cover the true emission with a high probability.

•Topsoil organic carbon content (OC_TOP) (0 - 25 cm)

•Soil organic carbon (SOC) relation of 1:1.72 with soil organic matter.

SNTEXTUSEATC

- FAO soil name- Topsoil textural class- Regrouped land use class- Accumulated mean temp.

H(igh): > 6.0% (0.06)M(edium): 2.1-6.0% (0.021 to 0.06)L(ow): 1.1-2.0% (0.011 – 0.02)V(ery) L(ow): < 1.0% (0.01)

Soil Organic Carbon

0

1

2

3

4

5

6

7

8

9

10

0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.1 0.11

SOC kg C kg

N2O

kg

N/h

a

M HLVL

•Model very sensitive to SOC.

•Measured SOC data used for Italy

•1: 250,000

2. Model Database: Soil Parameters2. Model Database: Soil Parameters

1 Unit_ID 10012 SOC Max, min 0.0124 Clay content max, min 0.46 pH max, min 7.38 BD max, min 1.66

Soil Properties

2. Model Database: Soil Parameters2. Model Database: Soil Parameters

•Dominant Surface Texture class

0 No information

9 No texture (histosols, ...)

1 Coarse (clay < 18 % and sand > 65 %)

2 Medium (18% < clay < 35% and sand > 15%, or clay < 18% and 15% < sand < 65%)

3 Medium fine (clay < 35 % and sand < 15 %)

4 Fine (35 % < clay < 60 %)

5 Very fine (clay > 60 %)

1 Unit_ID 10012 SOC Max, min 0.0124 Clay content max, min 0.46 pH max, min 7.38 BD max, min 1.66

Soil Properties

2. Model Database: Soil Parameters2. Model Database: Soil Parameters

SNUSE

- FAO soil name- Regrouped land use class

L(ow): < 50%M(edium): 50-75%H(igh): > 75%

Low base 5 - 6.5 pHMedium 6.5 – 7.5 pHHigh > 7.5 pH

•Base saturation (%) as a proportion of the CEC taken up by exchangeable bases (TEB/CEC)

1 Unit_ID 10012 SOC Max, min 0.0124 Clay content max, min 0.46 pH max, min 7.38 BD max, min 1.66

Soil Properties

2. Model Database: Soil Parameters2. Model Database: Soil Parameters

STR_TOPTEXTUSE

- Topsoil structure class- Topsoil textural class- Regrouped land use class

 L(ow): < 1.4 g/cm3M(edium): 1.4 – 1.75 g/cm3

PD = BD + 0.009*clay.Low < 1.45 g g/cm3Med 1.45 – 1.75 g/cm3High >1.75 g/cm3

•Topsoil Packing Density (PD_TOP)

•New Cronos

•Data reported at differing regional scales

•Crop data

•Nitrogen balance data

Model Database: Crop AreaModel Database: Crop Area

•Crop data 1997

Model Database: Crop AreaModel Database: Crop Area

New Cronos Class AT1Total agricultural area 1162550Arable area ha 860930Common wheat and spelt 184380Durum wheat 12410Rye 47010Barley 190430Oats 21350Grain maize 69570Rice 0Other cereals 12670Dried vegetables 32880Root crops 62860Potatoes 19420Sugar-beet 42880Industrial plants 82060Forage plants 80910permanent pasture and meadows 244250

•New Cronos data spatially disaggregated using areal weighting method based on Corine 100m landsclasses and regional trends.

Model Database: Crop AreaModel Database: Crop Area

Model Database: Crop AreaModel Database: Crop Area

0 fallow1 CORN2 Winter wheat3 SOYBEAN4 other cereals5 Non leguminous hay6 Spring Wheat7 winter_barley8 spring BARLEY9 OATS

10 durum wheat11 Grassland12 Pasture13 SORGHUM14 triticale15 Rye16 pulses17 fodder roots18 POTATO19 Sugar Beet20 Paddy_Rice21 RAPE21 Tobacco22 other ind crops23 SUNFLOWER

•Disaggregated Crop data.

•Model contains default crop characteristics for the following crops

Model Database: Manure ApplicationModel Database: Manure Application

•Manure application data

•New Cronos 1997

Model Database: Land UseModel Database: Land Use

1 Unit_ID 10012 Cropland 2582983 Sown area 2965064 Fertiliser T 172295 Fertiliser Kg Ha 66.76 Irrigation 0.47 Partition of Fert. *

Farming Management

•Disaggregated crop totals

•Crop wise distribution of fertiliser based on IFA International Fertiliser Association data.

•Irrigation index – ESB database

•Fertiliser type – FAO data

•Farm files generated using Mars data containing planting, harvest, fertilisation, and fertilisation rate

NO3 - Nitrates (low)

•NH4HCO3 - Ammonium bicarbonate (high)

•Urea (low) Very high useage in Italy.

•NH3 - Anhydrous ammonia (low)

•NH4NO3 - Ammonium nitrate (low)

•(NH4)2SO4 - ammonium sulphate (high)

•(NH4)2HPO4 - Di-ammonium Phosphate (low)

NH3 Volatilisation rate indicated)

Other Complex Fert (N)

Calcium Ammonium NitrateCalcium NitrateUrea

Ammonium Sulphate

Ammonium Sulphate Nitrate

Ammonium Phosphate (N)

Sodium Nitrate

Other Nitrogenous Fert

Ammonium Nitrate

3. Model3. Model

• DNDC (Denitrification-Decomposition)

• Satisfies more IPCC requirements than other models reviewed.

• Simulation model of carbon (C) and nitrogen (N) biogeochemistry for agroecosystems.

• Simulates soil organic C and N dynamics, plant growth, N leaching, and emissions of trace gases including N2O, NO, N2, NH3, CH4 and CO2.

• Can be used as a tool to predict long-term soil fertility variation, C sequestration capacity, and greenhouse gas fluxes under alternative climate change or management scenarios.

http://www.dndc.sr.unh.edu/

3. Model3. Model

From 1989-2001, the DNDC model has been continuously supported by the U.S. NSF, NASA, USDA, and EPA. Many researchers from the U.S., China, Germany, the U.K., Canada, the Netherlands, and Australia have made substantial contributions to development, validation, and application of the model.

N2O-N emission kg/ha(and counties per class)

6.51 to 7.46 (5)5.59 to 6.51 (4)4.67 to 5.59 (4)3.75 to 4.67 (6)2.83 to 3.75 (19)1.91 to 2.83 (15)0.99 to 1.91 (10)0.07 to 0.99 (4)

Labile humads

NH4

NO3-

CO2

NO2 -

N2O

N2

Water uptakeby roots

Daily water demand

Daily N uptake by roots

Daily biomassaccumulation ( LAI )

N demand Grain

Stalks

Roots

Very labilelitter

Labilelitter

Resistantlitter

Labile microbes Resistant microbes

DOC

DOC

Nitratedenitrifier

Nitritedenitrifier

N2Odenitrifier

NO

Water stress

The DNDC Model

Passive humus

Resistent humads

Annual averagetemperature

Daily potentialET

EvaporationWater flowbetween layers

LAI-regulated albedo

Soil temperatureprofile

Soil moistureprofile

Transpiration

Soil Eh profile

Oxygendiffusion

Oxygenconsumption

NH4+DOC Nitrifiers

Clay-NH4+NH3NO3-

NH3NON2O

Root respiration

Soilenvironmental variables

Ecological drivers

Substrates (NH4+, NO3- and DOC)

Effect of temperature and moisture on decomposition

pHMoistureTemperature

Climate Soil Vegetation Anthropogenic activity

Soil climate

Plant growth

Decomposition

NitrificationDenitrification

Eh

CH4NH4+ Soil Eh

Aerenchyma

DOC

CH4 production

CH4 oxidation

CH4 transport

Fermentation

Figure 2

4. Results: Nitrous Oxide emissions4. Results: Nitrous Oxide emissions

•Total N2O Kg N

4. Results: Nitrous Oxide emissions4. Results: Nitrous Oxide emissions

•Emission factors

•N20 Kg N as percentage of total mineral and manure fertiliser applied.

Results: Nitrous Oxide emissionsResults: Nitrous Oxide emissions

UNFCCC 1997 modelled results

Country Agricultural soils N2O (kt)Arable area (000 Ha) high SOC low SOC mean

Ave KG N ha

Total Fert (000 t)

Total man (000 t)

Ave Em rate (N fert + man)

Austria 3.3 3261.2 11.8 4.8 8.3 2.5 184.6 157.7 0.02Belgium 10.4 1478.9 11.1 4.5 7.8 6.0 162.2 322.0 0.016Denmark 30.3 2789.7 28.9 10.0 19.5 5.1 351.8 318.0 0.026Finland 7.3 2043.9 44.1 17.5 30.8 14.9 165.1 79.6 0.123France 165.0 26880.0 103.6 34.0 68.8 2.7 2940.9 1256.6 0.019Germany 77.0 17063.7 117.4 39.8 78.6 4.5 1981.0 1116.5 0.025Greece 19.0 1839.6 24.9 7.9 16.4 6.5 170.7 87.0 0.044Ireland 19.6 4414.0 16.3 7.3 23.6 5.4 497.7 542.9 0.023Italy 63.0 11320.6 128.4 44.9 86.7 7.7 597.8 545.0 0.094Luxembourg 0.5 126.4 0.7 0.3 0.5 3.6 14.6 14.4 0.016Netherlands 24.8 2132.64 19.65 9.23 14.44 5.83 377.85 559.04 0.014Portugal 7.2 2138.18 34.31 13.49 23.90 14.09 214.44 82.04 0.091Spain 60.4 19048.8 72.4 25.9 49.2 2.3 1140.4 467.7 0.038Sweden 11.1 n n n n n n n n

United Kingdom91.4 16150.4 88.1 28.5 58.3 4.5 2050.8 1418.8 0.021

Total 590.3Total ( -SE) 579.3 701.8 248.2 486.8

UK-dndc 91.4 62.50 30.50 50.90Italy 250k 63 11320.6 80.5 25.1 52.8 4.8 597.8 545.0 0.053

Conclusion:Conclusion:

•The results show that a wide range of emission rates often exceeding the IPCC rate.

•This method is very dependent on accuracy of SOC data

•The results would be improved by more accurate crop and fertilisation data.

•Scenario analysis to be undertaken