modelling nitrous oxide emissions from agricultural soils - deli chen
TRANSCRIPT
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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
Modeling N2O emissions from agricultural soils
The CCRSPI Conference, 15-17th February 2011, Melbourne
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NO3-
NH4+
N2
N2O
NO2-
NH3
Den
itrificatio
n (5
-80
%)
(NH2OH)
Soil organic matter Fertilizer Animal Waste
Ammonia volatilization (10-70%)
Water is one of the key drivers
for all these processes
Nitrate leaching (5-90%)
Nit
rifi
cati
on
Processes contributing to/interacting with N2O production in soil
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Measurement of N2O
Close path FTIR
GC
/c cTF K c z wcFlux
TDL
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High spatial variability: N2O fluxes varying 40 folds within one ha (Turner et al, Plant and Soil, 2008)
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Annual N2O Emissions (kg N ha-1 year-1)
at Treatment: DD+RET+N
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
1968 1972 1976 1980 1984 1988 1992 1996 2000 2004
High temporal variability: N2O fluxes between 1968 and 2004 from rain-fed wheat at Rutherglen, simulated by WNMM
(Li et al, Plant and Soil, 2008)
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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
Measurement or modelling?
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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
N2O simulation models
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WNMM—spatially referenced water and nutrients management model , it simulates:
Soil water dynamicsPlant growthComprehensive C and N cycling,
including N2O emissions
(Li et al, 2005, 2007, 2008, 2009; Chen et al 2010)
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……
ArcView interface
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N2O emissions from irrigated maize, Yuci, Shanxi
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11Conventional Tillage and Continuous Corn in ARDEC, Fort Collins, CO, USA. The dataset is provided by Arvin Mosier, USA.
CT-CC-224
0
5
10
15
20
25
30
1-Jan-02 30-Jun-02 27-Dec-02 25-Jun-03 22-Dec-03 19-Jun-04 16-Dec-04
So
il T
em
pe
ratu
re a
t 5
cm
(o
C)
CT-CC-224
0.15
0.20
0.25
0.30
0.35
0.40
0.45
1-Jan-02 30-Jun-02 27-Dec-02 25-Jun-03 22-Dec-03 19-Jun-04 16-Dec-04
So
il V
olu
me
tric
Wa
ter
Co
nte
nt
of
0-1
5c
m (
v/v
)
CT-CC-224
0
25
50
75
100
1-Jan-02 30-Jun-02 27-Dec-02 25-Jun-03 22-Dec-03 19-Jun-04 16-Dec-04
CO
2 F
lux
es
(k
g C
/ha
/d)
CT-CC-224
0
30
60
90
120
1-Jan-02 30-Jun-02 27-Dec-02 25-Jun-03 22-Dec-03 19-Jun-04 16-Dec-04
N2O
Flu
xe
s (
g N
/ha
/d)
N2O Emissions in USA
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12WNMM simulations, Yaqui Valley, Mexico, Stanford University
N2O Emissions in Mexico
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Validation: three key outputs should be validated before validation of N2O, example of WA Rain-fed wheat
Plant growth
Soil mineral NSoil moisture & Temp
Measured and simulated N2O fluxes
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Irrigated pasture at Kyabram, VIC
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Validation: three key outputs should be validated before validation of N2O, example of WA Rain-fed wheat
Plant growth
Soil mineral NSoil moisture & Temp
Measured and simulated N2O fluxes
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Regional N2O emissions, WA wheat -belt using WMM (with RS,
soil database and climate data)
EFIPCC(1.0%)
WNMM(0.3-0.64%)
N2O (t N/year) 5309 1681
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Challenges-sugarcane studies
• 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)
Cumulative N2Oemissions, both sites
0
10
20
30
40
50
0 100 200 300 400Days after fertilising
kgN
ha
-1
South fertilised
South unfertilised
North fertilised
North unfertilised
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Murwillumbah: OCT 2005-SEP 2006Treatment: 160 N kg/ha UREA on 19 OCT 2005
TR fertilized
5
10
15
20
25
30
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
TSOIL@5cm (OBS)
TSOIL@5cm (PRE)
TR fertilized
0.30
0.35
0.40
0.45
0.50
0.55
0.60
0.65
0.70
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
SWC@2-8cm (OBS)
SWC@2-8cm (PRE)
TR fertilized
0
1
2
3
4
5
6
7
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
ET (OBS)
ET (PRE)
TR fertilized
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
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
N2O (OBS)
N2O (PRE)
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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)
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Shading area indicates
nitrification contribution to N2O emissions
(irrigated pasture)
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More effective than controlling loss processes in soil after N addition
Options to increase N efficiency and mitigate N2O emission
Use right amount, right type, apply at right time 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
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GIS-Based Agricultural Decision Support System
Crop/pastureCrop yield
Above- and below-
ground biomass
WaterSoil water
contentSoil water fluxSoil drainage
Soil evaporationCrop
transpiration
Nutrients (N&P)Soil mineral-N content
Ammonia volatilisationNitrous oxide
emissionNitrate leachingCrop N uptake
Climate Soil Landuse
Agricultural Practices
CropsCrop harvestN fertiliser applicationIrrigation
Tillage
Agricultural SurveyInformation about
agricultural management
practices (soil, climate and land use)
Scenario DevelopmentFertiliser (nitrogen)
application and irrigation
Scenario EvaluationThe outputs of various
management scenarios are assessed against the set criteria, considering crop yield, water and
fertiliser use efficiency, and environmental impacts
Outcomes in The North China Plain
While maintaining/increasing crop production:
1. Up to 30% irrigation water saving
2. Up to 25% nitrogen fertiliser saving
3. Up to 70% less ammonia N losses
4. Up to 25% less N2O (a greenhouse gas)
5. Up to 50% less nitrate leaching
Best Management PracticesFor local agricultural extension officers and individual farmers
0
2
4
6
8
10
12
14
16
18
27-Jun-98 29-Jun-98 1-Jul-98 3-Jul-98 5-Jul-98 7-Jul-98
NH
3 Fl
ux (k
g N
/ha/
day)
SBSB (predicted)SB+ISB+I (predicted)
Example: Reduced ammonia emission
Irrigating immediately after fertiliser
application was predicted to reduce NH3
loss, as confirmed through field
measurements
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Development of policy optionsby integrating biophysical and economic models
Driving forces
Input data
ClimateSoil
Crop rotationPolicies
Pressures
Resources and environmental
problems
Groundwater extraction
Groundwater pollution
N2O emission
Biophysical model
Farm economic model
GIS
State
Farm decision and biophysical processes
simulationFarmers’ input
behaviourCrop growth
Water dynamicsNitrogen dynamics
Impacts
Policy evaluation
EnvironmentalSocial
Economic
Reponses
Policy optionWater
managementNitrogen
management
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y = -4.7x + 22.72
R2 = 0.87
0
5
10
15
20
25
0 0.5 1 1.5 2 2.5
Water price (Yuan/m3)
Nit
rog
en f
erti
lise
r u
se
effi
cien
cy (
kg/h
a)
y = -0.01x + 0.73
R2 = 0.997
0
0.2
0.4
0.6
0.8
1
1.2
0 5 10 15 20 25 30 35 40
Nitrogen price (Yuan/kg)
N2O
em
issi
on
(kg
N/h
a)
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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
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0 5 10 15 20 25 300
2
4
6
8
10
12
14
Cumulative NH3 loss
Urea
Green urea
Days after fertilisation
NH
3 lo
ss (k
g/ha
)
9% of applied N
29% of applied N
Effect of urease inhibitor on NH3 loss
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Effect of nitrification inhibitor on N2O emission
0 10 20 30 40 50 60 70 80 90 100 110 1200.0
0.5
1.0
1.5
2.0
2.5
DMPP Urea
Days
N2O
(g/
ha.
hr)
fertiliser applied fertiliser applied fertiliser applied
44% reduction of N2O emission
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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
Effect of NI and SCU on N2O emission and yield N2O and yield (2007-2009)
0
5
10
15
20
25 N
2O flu
xes (m
g∙m
2 ∙d-1
)
Date
Urea NI SCU CK
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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?