us agricultural ghg emissions: challenges and opportunities for mitigating plot scale vs. whole farm...
DESCRIPTION
Presentation from the WCCA 2011 conference in Brisbane, Australia.TRANSCRIPT
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US Agricultural GHG Emissions: challenges and opportunities for
mitigating plot scale vs. whole farm (and larger) emissions
Steve Del Grosso, et al.
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OUTLINE
• US Agricultural GHG Sources and Sinks
• GHG intensity and Nitrogen Use Efficiency
• Scaling paradox
• Farm system emissions: conventional vs. organic
• To what extent does Jevon’s paradox apply?
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US Agricultural GHG Emissions
-100
0
100
200
300
Soil CO2 energy useCO2
Soil N2O enteric CH4 manureCH4+N2O
Tg
CO
2 e
q.
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US Cropped Land Δ Soil C
-40
-30
-20
-10
0
10
20
30
40T
g C
O 2 e
q. y
r-1
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Synthetic N Organic N Residue N
Mineral Soils
Organic Soils
Atmospheric N2O
Direct Emissions
Indirect Emissions
Temperate:8 kg N2O-N/ha
Subtopics:12 kg N2O-N/ha
1.0% (applied N)
NH3 & NOx Volatilization (10% Synthetic N, 20% Manure N)
NO3- Leaching/Runoff (30%)
1%
0.75%
2.0% (PRP N)
IPCC METHODOLOGY FOR N2O
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Uncertainty Framework
SimulationModel
Input Uncertainty
Scaling Uncertainty
Results
Structural UncertaintyPDF
95%ConfidenceIntervalInput
Uncertainty
Input Uncertainty
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At plot level, process based models usually perform better than simple models
Site Level Mean N2O Emissions
05
10152025303540
N2 O
gN
ha-1
d-1 measured
DAYCENT
IPCC
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As scale increases, simple models become more reliable
Global Anthropogenic N2O
0
2
4
6
8
Top Down lower bound Top down upper bound IPCC
Tg
N
US major Crops N2O
0.0
0.2
0.4
0.6
DAYCENT Lower bound DAYCENT Upper bound IPCC
Tg
N
Del Grosso et al. 2008
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as scale decreases, CIs get wider
Most of this uncertainty is due to model structure
Del Grosso et al. 2010
0%
200%
400%
600%
800%
1000%
1200%
0 5 10 15 20 25Monte Carlo Counties in Region
CI Wi
dth
0%
200%
400%
600%
800%
1000%
1200%
0 5 10 15 20Regional N2O Emisisons (gG N)
CI Wi
dth
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US Corn, Wheat, Cotton, Sorghum Yieldsand N Fertlizer Applied
05
1015202530354045
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
N fert Tg
grain yield Tg * 10
NUE is increasing
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GHG Intensity for N2O from US Corn and Soy
0.29 gCO2/g grain
0.22 g CO2 eq./g grain
GHG intensity is decreasing
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Theoretical GHG Intensity
0
0.02
0.04
0.06
0.08
0.1
0.12
0 5 10 15 20 25 30 35
N inputs g N m-2
N2O
CO
2-C
eq.
/gra
in-C
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DayCent GHG Intensity
0
0.02
0.04
0.06
0.08
0.1
0.12
0 5 10 15 20 25 30 35
N inputs g N m-2
N2O
CO
2-C
eq.
/gra
in-C
Irrigated Corn CO - N2O GHG Intensity
0
0.01
0.02
0.03
0.04
0.05
0.06
corn 0-N, no-till
corn 0-N,conventional-
till
corn Hi-N, no-till
corn Hi-N,conventional-
till
CO
2-C
eq
/gra
in-C
0 N NT 0 N NT High N NT High N CT
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Global Warming Potential
CO2 eqvt(kg CO2eqvt ha-1 y-1)
System DSoil C N2O Energy GHGnet
No-Till 0 b 303 b 807 1110 b
Chisel Till 1080 a 406 ab 862 2348 a
Organic -1953 c 737 a 344 -872 c
Cavigelli et al. 2009
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Greenhouse Gas Intensity
SystemGHGnet
(kg CO2eqvt ha-1 y-1)
Crop Yield(Mg ha-1 y-1)
GHGI(kg CO2eqvt Mg grain-1)
No-Till 1110 b 7.25 a 153 a
Chisel Till 2348 a 7.14 a 330 a
Organic -872 c 5.12 b -169 b
Cavigelli et al. 2009
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Change in System Carbon due to Enhanced Production
0
200
400
600
800
1000
1200
1400
1600
1800
2008 2012 2016 2020 2024 2028
g C
m-2
Compost carbon
Change in system carbon
The change in system carbon is the total system carbon from the compost simulation minus the compost carbon. This represents the carbon sequestration due to enhanced plant production.
Updated 13 July 2011
California Annual GrasslandCompost Addition Study
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California Annual GrasslandCompost Addition Study
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Current US Farming Practices and Mitigation Outlook
50% employ conservation tillage or no till
Small minority use improved fertilizers
Most farmers do not greatly exceed recommended rates
Slow release fertilizers and nitrification inhibitors are more effective in the drier western US
Practices that reduce direct N2O are also likely to reduce indirect N2O
Urease inhibitors may increase direct N2O
Model results suggest that rates could be reduced with stabilized N sources, but need observations to verify
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Jevon’s Paradox
• Many assume that increases in efficiency will solve our problems
• Is increasing yield but keeping emissions constant (or decreasing) the same as deceasing emissions but keeping yield constant (or increasing)?
• Probably not – as efficiency increases people tend to consume more
• So absolute emissions will continue to increase
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Summary and Issues
• Currently available technologies can reduce emissions (in at least some regions) but incentives are needed
• at small scales, fluxes can be measured precisely and accurately, but models usually do better at large scales.
• Benefits of stabilized N likely scale up to the farm system level and include improved water and air quality
• However, entity level observations are not feasible and model uncertainty at the farm scale is huge
• If GHG intensity is minimized then yields would plummet
• If increasing NUE is the goal then BAU is sufficient
• If the goal is to increase yields and decrease absolute emissions then things get challenging
• Need to define life cycle analysis boundaries carefully