US Agricultural GHG Emissions: challenges and opportunities for

mitigating plot scale vs. whole farm (and larger) emissions

Steve Del Grosso, et al.

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?

US Agricultural GHG Emissions

-100

0

100

200

300

Soil CO2 energy useCO2

Soil N2O enteric CH4 manureCH4+N2O

Tg

CO

2 e

q.

US Cropped Land Δ Soil C

-40

-30

-20

-10

0

10

20

30

40T

g C

O 2 e

q. y

r-1

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

Uncertainty Framework

SimulationModel

PDF

PDF

PDF

Input Uncertainty

Scaling Uncertainty

Results

Structural UncertaintyPDF

95%ConfidenceIntervalInput

Uncertainty

Input Uncertainty

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

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

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

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

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

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

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

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

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

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

California Annual GrasslandCompost Addition Study

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

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

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