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Modelling nitrous oxide emissions from agricultural soils - Deli Chen
 

Modelling nitrous oxide emissions from agricultural soils - Deli Chen

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    Modelling nitrous oxide emissions from agricultural soils - Deli Chen Modelling nitrous oxide emissions from agricultural soils - Deli Chen Presentation Transcript

    • The CCRSPI Conference, 15-17th February 2011, Melbourne Modeling N2O emissions from agricultural soilsDeli Chen1, Yong Li1, Bob Farquharson1, Richard Eckard1, KevinKelly2, Louise Barton3 , Peter Grace41Melbourne School of Land and Environment, The University of Melbourne2 DPI Victoria, 3UWA, 4QUT
    • Processes contributing to/interacting with N2O production in soil Ammonia NH3 volatilization (10-70%) Soil organic NH4 + matter Fertilizer Animal Waste N2 Denitrification Nitrification (5-80%) N2O (NH2OH) NO2- Nitrate leaching (5-90%) NO3-
    • Measurement of N2O GC Close path FTIRFc KT cc / z Flux wc TDL
    • High spatial variability: N2O fluxes varying 40 folds within one ha (Turner et al, Plant and Soil, 2008) 4
    • High temporal variability: N2O fluxes between 1968 and 2004 from rain-fed wheat at Rutherglen, simulated by WNMM Annual N2O Emissions (kg N ha-1 year-1) at Treatment: DD+RET+N 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 1968 1972 1976 1980 1984 1988 1992 1996 2000 2004 (Li et al, Plant and Soil, 2008) 5
    • Measurement or modelling? Expensive to measure continuously Impossible to rely on the field measurement alone to quantify regional N2O emissions Mitigation of N2O emissions requires a whole system approach  N2O loss accounts for ~1%, compared with >50% total loss of applied N Process (system) based model/DSS is a useful tool
    • N2O simulation models Since the first N2O simulation model, zero-order kinetics by Focht (1974), models of varying complexity have been developed Based on the utilisation purpose, N2O emissions models can be divided into three levels:  Laboratory  Field (process based, DCDC, DAYCENT, ecosys, WNMM )  Regional/Global 7
    • WNMM—spatially referenced water and nutrients management model , it simulates: Soil water dynamics Plant growth Comprehensive C and N cycling,including N2O emissions 8(Li et al, 2005, 2007, 2008, 2009; Chen et al 2010)
    • ArcView interface…… 9
    • N2O emissions from irrigated maize, Yuci, Shanxi
    • N2O Emissions in USA CT-CC-224 CT-CC-224 0.45 30Soil Volumetric Water Content of 0-15cm (v/v) 0.40 25 Soil Temperature at 5cm (oC) 0.35 20 0.30 15 0.25 10 0.20 5 0.15 0 1-Jan-02 30-Jun-02 27-Dec-02 25-Jun-03 22-Dec-03 19-Jun-04 16-Dec-04 1-Jan-02 30-Jun-02 27-Dec-02 25-Jun-03 22-Dec-03 19-Jun-04 16-Dec-04 CT-CC-224 CT-CC-224 100 120 75 90 CO2 Fluxes (kg C/ha/d) N2O Fluxes (g N/ha/d) 50 60 25 30 0 0 1-Jan-02 30-Jun-02 27-Dec-02 25-Jun-03 22-Dec-03 19-Jun-04 16-Dec-04 1-Jan-02 30-Jun-02 27-Dec-02 25-Jun-03 22-Dec-03 19-Jun-04 16-Dec-04 11 Conventional Tillage and Continuous Corn in ARDEC, Fort Collins, CO, USA. The dataset is provided by Arvin Mosier, USA.
    • N2O Emissions in Mexico WNMM simulations, Yaqui Valley, Mexico, Stanford University 12
    • Validation: three key outputs should be validated before validation of N2O, example of WA Rain-fed wheat Soil moisture & Temp Soil mineral N Plant growth Measured and simulated N2O fluxes 13
    • Irrigated pasture at Kyabram, VIC 14
    • Validation: three key outputs should be validated before validation of N2O, example of WA Rain-fed wheat Soil moisture & Temp Soil mineral N Plant growth Measured and simulated N2O fluxes 15
    • Regional N2O emissions, WA wheat -belt using WMM (with RS, soil database and climate data) IPCC WNMM EF (1.0%) (0.3-0.64%)N2O (t N/year) 5309 1681
    • Challenges-sugarcane studies Cumulative N2Oemissions, both sites 50 40 South fertilised kgN ha-1 30 South unfertilised 20 North fertilised North unfertilised 10 0 0 100 200 300 400 Days after fertilising• N2O: – South, extraordinarily large and long-lived; emission factor 20% – North, very much smaller and short-lived; emission factor 2.8%• IPCC: – N2O emission factor 1% (Denmead and Wang et al, 2008) 17
    • Murwillumbah: OCT 2005-SEP 2006Treatment: 160 N kg/ha UREA on 19 OCT 2005 TR fertilized TR fertilized 30 0.70 0.65 25 0.60 0.55 20 0.50 15 0.45 0.40 10 TSOIL@5cm (OBS) SWC@2-8cm (OBS) TSOIL@5cm (PRE) 0.35 SWC@2-8cm (PRE) 5 0.30 01-Oct-05 15-Nov-05 30-Dec-05 13-Feb-06 TR fertilized 14-May-06 28-Jun-06 12-Aug-06 26-Sep-06 01-Oct-05 15-Nov-05 30-Dec-05 13-Feb-06 TR fertilized14-May-06 28-Jun-06 12-Aug-06 26-Sep-06 30-Mar-06 30-Mar-06 7 ET (OBS) 0.80 N2O (OBS) ET (PRE) N2O (PRE) 0.70 6 0.60 5 0.50 4 0.40 3 0.30 2 0.20 1 0.10 0 0.00 01-Oct-05 15-Nov-05 30-Dec-05 13-Feb-06 30-Mar-06 14-May-06 28-Jun-06 12-Aug-06 26-Sep-06 01-Oct-05 15-Nov-05 30-Dec-05 13-Feb-06 30-Mar-06 14-May-06 28-Jun-06 12-Aug-06 26-Sep-06 18
    • Challenges on modellingSeparate N2O emission sources, very limited information about N2O emission in nitrification processPartition of N2O and N2 in denitrification Lack of system approaches (need to quantify all pathways of water and N and C dynamics)Very little information about indirect GHG emissionsScale up (catchment scale) 19
    • Shading area indicates nitrification contribution to N2O emissions(irrigated pasture)
    • Options to increase N efficiency and mitigate N2O emission  Use right amount, right type, apply at right timeMore effective than controlling loss processes in soil after N addition with right method  Need a practical tool to identify BMPs and incorporate land use, soil and climate variables and economic and environmental interests  GIS based Agricultural Decision Support System
    • GIS-Based Agricultural Decision Support System Outcomes in The North China Plain While maintaining/increasing crop production: Scenario Evaluation 1. Up to 30% irrigation water saving The outputs of various management 2. Up to 25% nitrogen fertiliser saving scenarios are assessed against the set criteria, Climate Soil Landuse 3. Up to 70% less ammonia N losses considering crop yield, water and fertiliser use efficiency, and environmental impacts 4. Up to 25% less N2O (a greenhouse gas) 5. Up to 50% less nitrate leaching Agricultural Survey Information about agricultural management practices (soil, climate and land use) Agricultural Practices Crops Crop harvest N fertiliser application Irrigation Tillage 18 SB 16 SB (predicted) SB+INH 3 Flux (kg N/ha/day) 14 SB+I (predicted) 12 10 Scenario Development 8 6 Fertiliser (nitrogen) 4 2 application and irrigation 0 27-Jun-98 29-Jun-98 1-Jul-98 3-Jul-98 5-Jul-98 7-Jul-98Example: Reduced ammonia emission Crop/pasture Water Nutrients (N&P) Irrigating immediately after Crop yield Soil water content Soil mineral-N content fertiliser application waspredicted to reduce NH3 loss, as Above- and below- Soil water flux Ammonia volatilisation confirmed through field Soil drainage Nitrous oxide emission measurements ground biomass Soil evaporation Nitrate leaching Best Management Practices Crop transpiration Crop N uptake For local agricultural extension officers and individual farmers
    • Development of policy options by integrating biophysical and economic models State Farm economic modelDriving forces Pressures Impacts Reponses Biophysical Policy option model Water Policy management Input data Resources and Nitrogen GIS evaluation environmental management Environmental Climate problems Social Soil EconomicCrop rotation Groundwater Farm decision and Policies extraction biophysical processes Groundwater simulation pollution Farmers’ input N2O emission behaviour Crop growth Water dynamics Nitrogen dynamics
    • 1.2 25N2O emission (kg N/ha) Nitrogen fertiliser use 1 20 efficiency (kg/ha) 0.8 15 0.6 0.4 10 y = -0.01x + 0.73 y = -4.7x + 22.72 R2 = 0.997 R2 = 0.87 0.2 5 0 0 0 5 10 15 20 25 30 35 40 0 0.5 1 1.5 2 2.5 Nitrogen price (Yuan/kg) Water price (Yuan/m3)
    • Conclusion remarksRequire regional/industry specific model or parameters for N2O estimationTo mitigation of N2O emissions, require system approachesSpatially referenced processes based model and DSS are useful tool for quantification and mitigation of N2O emissionsIncorporate impact of EEF (inhibitors and controlled release fertilisers) into models 26
    • Effect of urease inhibitor on NH3 loss 14 Cumulative NH3 loss 12 29% of applied N 10NH3 loss (kg/ha) Urea 8 Green urea 6 4 9% of applied N 2 0 0 5 10 15 20 25 30 Days after fertilisation
    • Effect of nitrification inhibitor on N2O emission 2.5 2.0 DMPP Urea 1.5N2O (g/ha.hr) 44% reduction of N2O emission 1.0 0.5 0.0 0 10 20 30 40 50 60 70 80 90 100 110 120 fertiliser applied fertiliser applied Days fertiliser applied
    • Effect of NI and SCU on N2O emission and yield N2O and yield (2007-2009) 25 U ea r NI SCU CK 20 N2O fluxes (mg∙m2∙d-1) 15 10 5 0 D e at Treatment N2O (kg N∙ha-1) Yield (kg∙ha-1) Urea 1.20±0.05b 10,700±170c Urea+NI 0.90±0.03c 11,160±290bSulfur coated urea 0.44±0.07e 13,270±130a
    • Most effective ways to mitigate N2O emission Use less N fertilizer Less Consumption (diet) Less People Population Control Without population control, China would have 300-400 million more people today What will the emissions be when we have another 3 billion people in 2050?