1. The CCRSPI Conference, 15-17th February 2011, Melbourne
Modeling N2O emissions
from agricultural soils
Deli Chen1, Yong Li1, Bob Farquharson1, Richard Eckard1, Kevin
Kelly2, Louise Barton3 , Peter Grace4
1Melbourne School of Land and Environment, The University of Melbourne
2 DPI Victoria, 3UWA, 4QUT

2. 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-

3. Measurement of N2O
GC
Close path FTIR
Fc KT cc / z
Flux wc
TDL

4. High spatial variability: N2O fluxes varying 40 folds within one ha
(Turner et al, Plant and Soil, 2008)
4

5. 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

6. 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

7. 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

8. 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)

9. ArcView interface
……
9

10. N2O emissions from irrigated maize, Yuci, Shanxi

11. N2O Emissions in USA
CT-CC-224 CT-CC-224
0.45 30
Soil 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.

12. N2O Emissions in Mexico
WNMM simulations, Yaqui Valley, Mexico, Stanford University
12

13. 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

14. Irrigated pasture at Kyabram, VIC
14

15. 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

16. 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

17. 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

18. Murwillumbah: OCT 2005-SEP 2006
Treatment: 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

19. 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

20. Shading area
indicates
nitrification
contribution to
N2O emissions
(irrigated pasture)

21. Options to increase N efficiency and mitigate
N2O emission
 Use right amount, right type, apply at right time
More 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

22. 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+I
NH 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-98
Example: Reduced ammonia
emission Crop/pasture Water Nutrients (N&P)
Irrigating immediately after Crop yield Soil water content Soil mineral-N content
fertiliser application was
predicted 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

24. Development of policy options
by integrating biophysical and economic models
State
Farm economic
model
Driving 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
Economic
Crop rotation Groundwater Farm decision and
Policies extraction biophysical processes
Groundwater simulation
pollution Farmers’ input
N2O emission behaviour
Crop growth
Water dynamics
Nitrogen dynamics

25. 1.2 25
N2O 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)

26. 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

27. Effect of urease inhibitor on NH3 loss
14
Cumulative NH3 loss
12
29% of applied N
10
NH3 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

28. Effect of nitrification inhibitor on N2O emission
2.5
2.0
DMPP Urea
1.5
N2O (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

29. 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±290b
Sulfur coated urea 0.44±0.07e 13,270±130a

30. 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?