Presentation on theme: "An estimation of Nitrous Oxide Emissions from Agricultural Soils within the EU15 using a mechanistic model. Declan Mulligan."— Presentation transcript:
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 Contents
UNFCCC Secretariat DG Env Monitoring Mechanism EEA ETC ACC Reference System Research Modelling Inventory estimation Measuring campaigns Member states Importance 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…
Overview Process Based Model Data: Multiple Sources & Formats Harmonized Geographical Database Alternative Scenarios Results GIS Access
EUROSTAT - http://europa.eu.int/comm/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/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 Sources
2. Model Database: Geographic units 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: 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
Total N (NH 4 + & NO 3 -) 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 Parameters European Soil Database 1:1,000,000 (European Soil Bureau).
2. 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
2. 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. SN TEXT USE ATC - 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 Model very sensitive to SOC. Measured SOC data used for Italy 1: 250,000 2. Model Database: Soil Parameters
Dominant Surface Texture class 0No information 9No texture (histosols,...) 1Coarse (clay 65 %) 2Medium (18% 15%, or clay < 18% and 15% < sand < 65%) 3Medium fine (clay < 35 % and sand < 15 %) 4Fine (35 % < clay < 60 %) 5Very fine (clay > 60 %)
2. Model Database: Soil Parameters SN USE - FAO soil name - Regrouped land use class L(ow): < 50% M(edium): 50-75% H(igh): > 75% Low base 5 - 6.5 pH Medium 6.5 – 7.5 pH High > 7.5 pH Base saturation (%) as a proportion of the CEC taken up by exchangeable bases (TEB/CEC)
2. Model Database: Soil Parameters STR_TOP TEXT USE - Topsoil structure class - Topsoil textural class - Regrouped land use class L(ow): < 1.4 g/cm3 M(edium): 1.4 – 1.75 g/cm3 PD = BD + 0.009*clay. Low < 1.45 g g/cm3 Med 1.45 – 1.75 g/cm3 High >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 Area
New Cronos data spatially disaggregated using areal weighting method based on Corine 100m landsclasses and regional trends. Model Database: Crop Area
Disaggregated Crop data. Model contains default crop characteristics for the following crops
Model Database: Manure Application Manure application data New Cronos 1997
Model Database: Land Use 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) NH 3 Volatilisation rate indicated)
3. 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 N 2 O, NO, N 2, NH 3, CH 4 and CO 2. 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. 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.
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