Quantification of N 2 O Emissions from Biofuel Feedstock Cultivation

29./30.03.2011 1 Quantification of N 2 O Emissions from Biofuel Feedstock Cultivation Renate Koeble European Commission Joint Research Centre Institute for Environment and Sustainability Ispra, Italy renate.koeble@jrc.ec.europa.eu EUROCLIMA Expert Consultation on Greenhouse Gas Emissions from Biofuels and Bioenergy Buenos Aires, 29./30.03.2011

29./30.03.2011 2 Outline of the Presentation Methods to assess soil N 2 O emissions from crop cultivation spatially The Stehfest & Bouwman statistical model combined with IPCC Tier1 approach Global calculations of N 2 O emissions general conditions - Input data (fertilizer, crop area / yield, environmental parameters) Results The results and the Renewable Energy Directive

29./30.03.2011 3 Methods to assess N 2 O emissions from crop cultivation spatially Process based agro-ecosystem models simulate the processes causing emissions in the soil require extensive data input (parameterization, meteorology etc.) require expertise of the user about bio-physical/bio-chemical processes and the modelling framework application dominantly on regional scale (e.g. Europe) typical soil N 2 O emission values for wheat, rapeseed, sugar beet and sunflower cultivation in Renewable Energy are based on results of the DeNitrification DeComposition (DNDC) model runs for Europe

29./30.03.2011 4 Methods to assess N 2 O emissions from crop cultivation spatially Statistical / regression models based on the correlation between field measurements of N 2 O fluxes and driving environmental and management factors as e.g. N input, soil carbon content etc. less data input demanding application on global scale possible distribution and quantity of available measurements (geographically, different crops) determines the quality of the model

29./30.03.2011 5 Methods to assess N 2 O emissions from crop cultivation spatially IPCC Guidelines for National Greenhouse Gas Inventories TIER1 approach N 2 O emission are calculated from N input (fertilizer, crop residues etc.) by using default emission factors The TIER1 approach does not allow to account for different environmental conditions typical soil N 2 O emission values for oilpalm, maize, soybean and sugarcane in the Renewable Energy directive are based IPCC Tier 1 approach (with modifications for soybean and oilpalm)

29./30.03.2011 6 Stehfest and Bouwman (2002, 2006) developed a statistical model to describe on-field emissions N 2 O emissions from soils under agricultural use based on the analysis of 1008 N 2 O emission measurements in agricultural fields where E E = N 2 O emission (as kg N 2 O-N ha-1 yr-1) c = constant ev = effect value for different drivers The Stehfest & Bouwman statistical model ( c ) = exp + ev Constant value -1.516 Parameter Parameter class or unit Effect value (ev) Fertilizer Input 0.0038 * N application rate in kg N ha-1 yr-1 Soil organic C content <1 % 0 1-3 % 0.0526 >3 % 0.6334 ph <5.5 0 5.5-7.3-0.0693 >7.3-0.4836 Soil texture Coarse 0 Medium -0.1583 Fine 0.4312 Climate Subtropical climate 0.6117 Temperate continental climate 0 Temperate oceanic climate 0.0226 Tropical climate -0.3022 Vegetation Cereals 0 Grass -0.3502 Legume 0.3783 None 0.5870 Other 0.4420 Wetland rice -0.8850 Soil bulk density 0-1 g cm-3 n/a 1-1.25 g cm-3 n/a >1.25 g cm-3 n/a Length of Experiment 1 yr 1.9910

29./30.03.2011 7 The Stehfest & Bouwman (S&B) statistical model IPCC emission factor for direct emissions is based on a global mean of S&B Fertilizer Induced Emissions - FIE Where: FIE = (E fert E unfert ) / N appl Fertilizer induced emissions (kg N2O-N Emissions / kg Fertilizer N input) 0.06 0.05 0.04 0.03 0.02 0.01 Variation of fertilizer induced emissions from agricultural soils under different environmental conditions and fertilizer input rates applying the Stehfest and Bouwman (2006) model E fert = Emissions from the fertilized plot (kg N 2 O-N) E unfert = Emissions from the unfertilized plot (kg N 2 O-N) 0.00 1 51 101 151 201 251 301 351 401 451 501 N appl = mineral fertilizer and manure N application (kg) N input kg ha-1 Agricultural Fields: Minimum case for Cereals in Temperate Oceanic Climate (SOC <1%; ph >7.3; medium soil texture) Agricultural Fields: Mean case for Cereals in Temperate Oceanic Climate (SOC 1-3%; ph 5.5-7.3; coarse soil texture) Agricultural Fields: Maximum case for Cereals in Temperate Oceanic Climate (SOC >3%; ph <5.5; fine soil texture) IPCC (2006) factor for direct N2O emissions from fertilizer input

29./30.03.2011 8 Combining Stehfest & Bouwman (S&B) model and IPCC (2006) TIER1 Direct Emissions N 2 O-N direct_fert = (N min + N man ) * 0.01 -> replaced by FIE based on S&B model N 2 O-N direct_cr = N cr * 0.01 N 2 O-N organic_soils Indirect Emissions = 8 kg N 2 O-N ha -1 (temperate climate) 16 kg N 2 O-N ha -1 (tropical climate) N 2 O-N volatilization = (N min * 0.1) + (N man * 0.2) * 0.01 N 2 O-N leaching/runoff* = (N min + N man + N cr ) * 0.3 * 0.0075 Blue = Emission Factors Green = fractions N min = mineral Fertilizer N Input N man = N from manure application N cr = N from crop residues Parameters are in kg/ha *only regions where leaching/runoff occurs

29./30.03.2011 9 Combining Stehfest & Bouwman (S&B) model and IPCC (2006) TIER1 Soil N 2 O Emission from different pathways under high and low fertilizer input conditions. Example: Wheat N2O-N kg / t of feedstock 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 N2O-N kg / t of feedstock 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 Direct emissions S&B Direct emissions IPCC Organic Soils Volatilization NETHERLANDS mineral N input 284 kg/ha yield 8.0 t/ha ROMANIA mineral N input 31 kg/ha yield 2.5 t/ha Leaching/Runoff Crop residues

29./30.03.2011 10 Global calculations of N2O emissions general conditions - Spatial resolution ~9 by 9km2 most global data sets required for the calculations are available at this resolution Reference year 2000 Detailed land use data set is available, providing crop area and yield for single crops and the required resolution Input data sets with global coverage Ensure as far as possible equal detail for all parts of the world Cover a wide range of potential biofuel feedstock defined by the Commission Potential Biofuel Feedstock Barley Cassava Coconut Maize Oilpalm Rapeseed Rye Safflower Sorghum Soybean Sugarbeet Sugarcane Sunflower Triticale Wheat

29./30.03.2011 11 Mineral fertilizer and manure N data based on IFA mineral fertilizer data on a country level disaggregated using FAO statistics on fertilizer use by crop for the different countries for the single crops mineral fertilizer input per ha for a ~10by10km grid was calculated manure data is based on FAO animal feedstock and IPCC default method to derive N input manure was distributed homogeneously within arable land Input data

29./30.03.2011 12 Input data Mineral fertilizer application in wheat cultivation 200 175 150 Mineral Fertilizer Input kg/ha Yield in kg/ha 8000 7000 6000 fertilizer input and yield in the TOP 10 global wheat producing countries N input in kg/ha 125 100 75 50 25 0 GERMANY FRANCE CHINA UNITED STATES INDIA PAKISTAN CANADA TURKEY RUSSIAN FEDERATION AUSTRALIA 5000 4000 3000 2000 Yield in kg/ha 1000 0

29./30.03.2011 13 Input data Crop distribution and yield available globally on a ~10 by 10km grid for >100 single crops for the years ~2000 from Monfreda et al. (2008)* *Monfreda, Ch.; Ramankutty, N. and Jonathan A. Foley, J.A. (2008), "Farming the planet: 2. Geographic distribution of crop areas, yields, physiological types, and net primary production in the year 2000", Global Biogeochemical Cycles, Vol.22, 1-19.

29./30.03.2011 14 Environmental parameters Input data - Soil properties were calculated based on the Harmonized World Soil Database by Hiederer* (2009). - Climate zones as defined in IPCC (2006) are based on Carre** et al. (2010) - Areas where leaching occurs has been calculated based on soil and climate data according to IPCC (2006) *Hiederer, R. (2009), Joint Research Centre, Institute for Environment and Sustainability, Land management and Natural Hazards Unit, pers. communication. ** Carre, F.; Hiederer, R.; Blujdea, V. and Koeble, R. (2009): Guide for the Calculation of Land Carbon Stocks Drawing on the 2006 IPCC Guidelines for National Greenhouse Gas Inventories

29./30.03.2011 15 S&B IPCC combined Global Mean Emissions 11.5 gco 2 eq/mj Weighted Emissions 14.5 gco 2 eq/mj Results Main Origin of EU consumption EU domestic 87% Ukraine 9% IPCC Global Mean Emissions 10.3 gco 2 eq/mj Weighted Emissions 11.8 gco 2 eq/mj

29./30.03.2011 16 Results S&B IPCC combined Global Mean Emissions Weighted Emissions 11.6 gco 2 eq/mj 15.3 gco 2 eq/mj Main Origin of EU consumption EU domestic 95%

29./30.03.2011 17 Results S&B IPCC combined Global Mean Emissions Weighted Emissions 2.1 gco 2 eq/mj 1.8 gco 2 eq/mj Main Origin of EU consumption Brazil 100%

29./30.03.2011 18 Results S&B IPCC combined Global Mean Emissions Weighted Emissions 7.7 gco 2 eq/mj 6.9 gco 2 eq/mj Main Origin of EU consumption Indonesia 42% Malaysia 40% Papua New Guinea 8%

29./30.03.2011 19 Results S&B IPCC combined Global Mean Emissions Weighted Emissions 7.0 gco 2 eq/mj 6.1 gco 2 eq/mj Main Origin of EU consumption Brazil 55% US 19% Argentina 11%

29./30.03.2011 20 Results NO2 as gco2eq MJ -1 of crop 30 28 26 24 22 20 18 16 14 12 10 8 6 4 2 0 maize Global average soil N 2 O emissions from potential biofuel crop cultivation JEC minimum JEC best estimate JEC maximum S&B/IPCC combined, Peatland minimum IPCC Peatland minimum sugarcan sugarbee wheat barley cassava rye sorghum tritical

29./30.03.2011 21 Results NO2 as gco2eq MJ -1 of crop 34 32 30 28 26 24 22 20 18 16 14 12 10 8 6 4 2 0 oilpalm Global average soil N 2 O emissions from potential biofuel crop cultivation JEC minimum JEC best estimate JEC maximum S&B/IPCC combined, Peatland minimum IPCC Peatland minimum rapeseed soybean sunflowe coconut cotton safflowe

29./30.03.2011 22 The results and the Renewable Energy Directive The JEC-WTW data on soil N 2 O emissions from feedstock cultivation will be updated based on these new results. This will most probably lead to an update of the default values in the RED ADVANTAGES harmonized method for all feedstocks global application possible different environmental and management conditions are taken into account as requested by the directive method is more easily reproducible by economic operators or public sector entities to show compliance with the RED sustainability criteria description of the method, input data and results will be made publicly available on our website soon http://afoludata.jrc.ec.europa.eu/index.php/dataset the calculations for users could be facilitated via a (web?)tool providing default data for a certain location on the earth based on the presented work. The user might change these parameters if there is more accurate information available. Results will be calculated within the tool.

29./30.03.2011 23 Thank you for the attention questions and comments are welcome

29./30.03.2011 24 Additional Information Origin of potential biofuel crops consumed in the EU (%) in 2008 sugarbee tritical rye barley cotton wheat rapeseed maize sunflowe oilpalm soybean sugarcan cassava sorghum EU27 domestic 100 100 100 99 96 95 87 86 71 13 coconut safflowe UKRAINE 9 12 ARGENTINA 5 9 11 12 53 MEXICO 46 BRAZIL 6 55 100 13 UNITED STATES 19 71 NIGERIA 18 CONGO, DEM. REP. 10 GHANA 5 INDONESIA 42 10 35 MALAYSIA 40 PHILIPPINES 50 THAILAND 11 PAPUA NEW GUINEA 8 9

29./30.03.2011 25 Provisions of the EU Renewable Energy Directive (RED) compliance with sustainability criteria of 35% GHG (60% in 2018) emission savings compared to fossil fuels Typical and default emission values are provided in the Annex of the RED CO2eq/MJfuel 80 70 60 50 40 30 20 10 0 RED Typical Emission Values and Savings for different Biofuel Feedstocks Sugar beet ethanol Wheat ethanol (1) Maize ethanol Sugar cane ethanol Rape seed biodiesel Sunflower biodiesel Soybean biodiesel Typical greenhouse gas emission savings Emissions from cultivation - soil N2O Emissions from cultivation - excluding soil N2O Emissions from processing, transport and distribution Fossil Fuel Comparator 83.3 gco2eq/mjfuel Palm oil biodiesel (2) 35% savings 60% savings

29./30.03.2011 26 Provisions of the EU Renewable Energy Directive (RED) General rule: to demonstrate compliance with the directive, producers may always cite the default GHG emission value for the biofuel as alternative to calculating the actual value Exception: raw materials cultivated in the EU, if they are not included in a list of areas where emissions from cultivation can be expected to be equal or lower to those reported in the directive*. The GHG emission calculations to draw up the list had to be submitted by the EU member states until 31.03.2010. The EU Commission was requested to report on the feasibility to draw up correspondingly lists of third countries with low greenhouse gas emissions from cultivation**. The Commissions communication COM(2010) 427 concerning this matter however concludes that at the current stage it is not yet feasible to set up legally binding lists of areas as the underlying calculations are uncertain (e.g. lack or insufficient quality of the data and modeling approaches). * Article 19(2) of the RED ** Article 19(4) of the RED

29./30.03.2011 27 Methodological aspects General rule: to demonstrate compliance with the directive, producers may always cite the default GHG emission value for the biofuel as alternative to calculating the actual value Exception: raw materials cultivated in the EU, if they are not included in a list of areas where emissions from cultivation can be expected to be equal or lower to those reported in the directive*. The GHG emission calculations to draw up the list had to be submitted by the EU member states until 31.03.2010. The EU Commission was requested to report on the feasibility to draw up correspondingly lists of third countries with low greenhouse gas emissions from cultivation**. The Commissions communication COM(2010) 427 concerning this matter however concludes that at the current stage it is not yet feasible to set up legally binding lists of areas as the underlying calculations are uncertain (e.g. lack or insufficient quality of the data and modeling approaches). * Article 19(2) of the RED ** Article 19(4) of the RED

Spatial Estimations of Land Carbon Stock Changes and N 2 O Emissions 29./30.03.2011 28 Reporting under RED Article 18: Verification of compliance with the sustainability criteria for biofuels and bioliquids Member States shall require economic operators to show that the sustainability criteria set out in Article 17(2) to (5) have been fulfilled. Provide methods and regional disaggregated default values to assist operators to show compliance with sustainability criteria

Spatial Estimations of Land Carbon Stock Changes and N 2 O Emissions 29./30.03.2011 29 Reporting under RED Article 19: Calculation of the greenhouse gas impact of biofuels and bioliquids By 31 March 2010, Member States shall submit to the Commission a report including a list of those areas on their territory [ ] where the typical greenhouse gas emissions from cultivation of agricultural raw materials can be expected to be lower than or equal to the emissions reported [ ] in part D of Annex V [ ]. That method shall take into account soil characteristics, climate and expected raw material yields. By 31 March 2010, the Commission shall submit a report to the European Parliament and to the Council on the feasibility of drawing up lists of areas in third countries where the typical greenhouse gas emissions from cultivation of agricultural raw materials can be expected to be lower than or equal to the emissions reported under the heading cultivation in part D of Annex V [ ] Provide typical greenhouse gas emissions from cultivation of agricultural raw materials for NUTS2 in Europe and regional level for ROW based on a single methodology and harmonized datasets

Spatial Estimations of Land Carbon Stock Changes and N 2 O Emissions 29./30.03.2011 30 Reporting under RED Article 19: Calculation of the greenhouse gas impact of biofuels and bioliquids The Commission shall, by 31 December 2010, submit a report to the European Parliament and to the Council reviewing the impact of indirect land-use change on greenhouse gas emissions The report shall, if appropriate, be accompanied, by a proposal, based on the best available scientific evidence, containing a concrete methodology for emissions from carbon stock changes caused by indirect land-use changes, ensuring compliance with this Directive, in particular Article 17(2). Provide methodology for emissions from carbon stock changes and estimate greenhouse gas emissions from indirect land use change induced by RED (carbon stock changes, N 2 O)

Spatial Estimations of Land Carbon Stock Changes and N 2 O Emissions 29./30.03.2011 31 ENVIRONMENTAL IMPACT OF INTENSIFICATION Marginal nitrogen fluxes [kg N kg-1 N] Wheat 100% 4.0% Leaching, N-export 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 3.5% 3.0% 2.5% 2.0% 1.5% 1.0% 0.5% 0.0% 0 100 200 300 Application of mineral fertilizer-nitrogen [kg N ha-1] N2O To the environmental impact of 1kg of fertilizer changes with intensity level Not considered in the current approach N-Export N-Leaching Direct N2O Emissions (right axes)

Spatial Estimations of Land Carbon Stock Changes and N 2 O Emissions 29./30.03.2011 32 BIOFUEL CROPS CONSIDERED IN RED 19 species Biofuel crop Crop class of Stehfest & Bouwman (2006)/ Smeets (2009) 16 are covered by M3 Potential growing area, expected yield and fertilizer input for jatropha, jojoba and miscanthus has to be derived barley cassava coconut cotton jatropha jojoba maize (corn) miscanthus oil palm rapeseed rye safflower soybean sugar beet sugar cane sunflower sweet sorghum triticale wheat cereal other crops other crops other crops other crops other crops other crops other crops other crops other crops cereal other crops legume other crops other crops other crops cereal cereal cereal