OC & BC 0.5° (ton)OC & BC 0.5° (ton)

Eric F. Vermote1,2, Evan A. Ellicott1, Tatyana Laypyonok3, Oleg Dubovik4, & Mian Chin2 1Department of Geography, University of Maryland, USA;

2NASA/GSFC; 3Science Systems and Applications, Inc., Greenbelt, USA; 4Laboratoire d’Optique Atmospherique/USTL, Lille, France

1Contact info: eric@ltdri.org

Fire Radiative Power Relates to Biomass Fuel Fire Radiative Power Relates to Biomass Fuel Consumption and EmissionsConsumption and Emissions

Current estimates of emission loading from biomass burning are still uncertain (IGAC, IGBP) - Why?

Current estimates of emission loading from biomass burning are still uncertain (IGAC, IGBP) - Why?

Emissions = burned area × fuel load × combustion completeness × emission factorEmissions = burned area × fuel load × combustion completeness × emission factor

Satellite derived estimates of Net

Primary Production based on empirical

relationships derived using a handful of field

measurements

Field based parameterizations based on fuel types and fuel

moisture.• No seasonal measurements of emission factors or combustion

completeness.

–Joint GOFC/GOLD Fire and IGBP-IGAC/BIBEX Workshop stated: “Current approaches for estimating global emissions are limited by accurate information on area burned and fuel available for burning.”

–Joint GOFC/GOLD Fire and IGBP-IGAC/BIBEX Workshop stated: “Current approaches for estimating global emissions are limited by accurate information on area burned and fuel available for burning.”

An alternative approach to biomass burning emission estimates uses the measure of radiated energy liberated during combustion. First developed by Kaufman et al. (1998) and later refined and validated by Wooster et al. (2003, 2005), the integrated fire power (Figure 1), or fire radiative energy (FRE) can be used to estimate the fuel combusted (Figure 2) and thus emission loading.

An alternative approach to biomass burning emission estimates uses the measure of radiated energy liberated during combustion. First developed by Kaufman et al. (1998) and later refined and validated by Wooster et al. (2003, 2005), the integrated fire power (Figure 1), or fire radiative energy (FRE) can be used to estimate the fuel combusted (Figure 2) and thus emission loading.

Fire radiative power can effectively estimate biomass burning emission loads on a global basis. Further refinement to characterize the fire cycle behavior and associated variation in emissions has been demonstrated for the savanna/shrubland biome using the MODIS CMG Aqua/Terra ratio as a surrogate for total energy. The next steps will include analyzing the fire cycle role in FRP based emission estimates for other landcover types. In addition, we plan to investigate the relationship between the Aqua/Terra FRP ratio and total fire energy (FRE) using SEVIRI and GOES.

Fire radiative power can effectively estimate biomass burning emission loads on a global basis. Further refinement to characterize the fire cycle behavior and associated variation in emissions has been demonstrated for the savanna/shrubland biome using the MODIS CMG Aqua/Terra ratio as a surrogate for total energy. The next steps will include analyzing the fire cycle role in FRP based emission estimates for other landcover types. In addition, we plan to investigate the relationship between the Aqua/Terra FRP ratio and total fire energy (FRE) using SEVIRI and GOES.

Figure 2. Relationship between fire radiative energy and fuel biomass combusted (Wooster et al., 2005)

MODISMODIS: Global observations of : Global observations of ambient aerosolambient aerosol

AERONETAERONET: Semi-Global accurate : Semi-Global accurate observations of aerosolobservations of aerosol

GOCARTGOCART: : GlobalGlobal aerosol simulations aerosol simulations

- assimilated meteorologyassimilated meteorology- advection and convectionadvection and convection- removal processesremoval processes

Main Uncertainty: aerosol sourcesMain Uncertainty: aerosol sources

Synergy of Observation and Synergy of Observation and

ModelingModeling: : Retrieving sources (location and Retrieving sources (location and

strength) providing best agreement strength) providing best agreement

between observations of MODIS between observations of MODIS

/AERONET and GOCART simulations /AERONET and GOCART simulations

To retrieve organic and black carbon particulate matter emissions from biomass burning, a combination of satellite and ground-based observations, along with chemical transport modeling, was used in concert with forward and inverse modeling.

To retrieve organic and black carbon particulate matter emissions from biomass burning, a combination of satellite and ground-based observations, along with chemical transport modeling, was used in concert with forward and inverse modeling.

Goal: To Reduce Uncertainty in Current Biomass Goal: To Reduce Uncertainty in Current Biomass Burning Emissions Estimates Using Fire Radiative Burning Emissions Estimates Using Fire Radiative PowerPower

Figure 1. The MODIS Fire Radiative Power (FRP) global monthly climate modeling grid product (CMG) was used in this study.

Figure 1. The MODIS Fire Radiative Power (FRP) global monthly climate modeling grid product (CMG) was used in this study.

Organic and Black Carbon Aerosol Emissions From Fire – Organic and Black Carbon Aerosol Emissions From Fire – A Proxy for Total Biomass Burning EmissionsA Proxy for Total Biomass Burning Emissions

Developing the FRP – Aerosol Emissions RelationshipDeveloping the FRP – Aerosol Emissions Relationship

FRP CMG 0.5° (MW)FRP CMG 0.5° (MW)

Fossil Fuel EmissionsFossil Fuel EmissionsOC & BC adjusted for OC & BC adjusted for

anthropogenic sources anthropogenic sources

(Cooke et al., 1999).

The relationship was analyzed on a global basis for 2001. Using stratified regions developed by van der Werf et al. (2005), the Terra MODIS CMG product and the OC/BC particulate matter estimates were compared.

Preliminary results show a strong relationship for many regions. However, even in regions with similar vegetation types, the emission factor (Eƒ) varies – Why?

Investigation of Landcover as Source of Variation in Emission Investigation of Landcover as Source of Variation in Emission Coefficients – A Function of Diurnal CycleCoefficients – A Function of Diurnal Cycle

MODIS Terra OC & BC particulate emission and FRP: NHAF

y = 0.0112x + 6.45

R2 = 0.4977

0.00

5.00

10.00

15.00

20.00

25.00

0.00 100.00 200.00 300.00 400.00 500.00 600.00 700.00 800.00 900.00

Monthly Mean Energy (mw)

Ave

rage

Em

itted

Car

bon

(Tg/

day)

MODIS Terra OC & BC particulate emission and FRP: SHAF

y = 0.0254x + 6.6246

R2 = 0.8834

0

5

10

15

20

25

30

35

0 200 400 600 800 1000 1200

Monthly Mean Energy (mw)

Ave

rage

Em

itted

Car

bon

(Tg/

day)

MODIS Terra OC & BC particulate emission and FRP: SHSA

y = 0.0247x + 4.7637

R2 = 0.6827

0

5

10

15

20

0 50 100 150 200 250 300 350 400 450

Monthly Mean Energy (mw)

Ave

rage

Em

itted

Car

bon

(Tg/

day)

MODIS Terra OC & BC particulate emission and FRP: NHSA

y = 0.0698x + 5.3168

R2 = 0.5421

-5.00

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

0.00 100.00 200.00 300.00 400.00 500.00

Monthly Mean Energy (mw)

Ave

rage

Em

itted

Car

bon

(Tg/

day)

SHAF: Eƒ = 0.0254 SHSA: Eƒ = 0.0247

NHAF: Eƒ = 0.0112 NHSA: Eƒ = 0.0698

We analyzed savanna/shrubland land cover – the dominant source of global fire activity and emissions:

•750 million ha/year (Hao et al.,1990)

•1/3 of global burning (Dwyer et al., 2000)

•50%+ detected in Africa (Dwyer et al., 2000)

We analyzed savanna/shrubland land cover – the dominant source of global fire activity and emissions:

•750 million ha/year (Hao et al.,1990)

•1/3 of global burning (Dwyer et al., 2000)

•50%+ detected in Africa (Dwyer et al., 2000)

SHAF SavannasEf = 0.019******************2003-2005Aqua/Terra = 3.383

BOAS Open ShrublandEf = 0.042*******************2003-2005Aqua/Terra = 1.119

Annual Total FRP (Tw): MODIS-Terra

67.84

6.06

22.30

7.46

25.64

65.68

0

10

20

30

40

50

60

70

80

2003 2004 2005

Terra Annual FRP (Tw )Aqua Annual FRP (Tw )

Annual Mean Total FRP (Tw): MODIS-Terra

137.84121.23

145.06

418.33

485.88461.70

0

100

200

300

400

500

600

2003 2004 2005

Terra Annual FRP (Tw )Aqua Annual FRP (Tw )

Differences in mean annual FRP Aqua/Terra ratio between regions

points to variation in fire cycles, total fire energy released, and thus total

emissions

Differences in mean annual FRP Aqua/Terra ratio between regions

points to variation in fire cycles, total fire energy released, and thus total

emissions

Aqua-Terra Ratio Explains the Variation Observed in Aqua-Terra Ratio Explains the Variation Observed in Savanna/Shrubland Biome Emission FactorSavanna/Shrubland Biome Emission Factor

Regions with a significant portion of fire occurring in savanna/shrubland biomes were compared based on their respective Aqua/Terra FRP ratio.

A strong relationship between the diurnal ratio and emission factor is obvious. It can be concluded that variation in regional emission factors of similar vegetation can be explained by the diurnal pattern of burning.

In addition, the Aqua/Terra ratio can serve as a proxy for calculating total fire energy.

Regions with a significant portion of fire occurring in savanna/shrubland biomes were compared based on their respective Aqua/Terra FRP ratio.

A strong relationship between the diurnal ratio and emission factor is obvious. It can be concluded that variation in regional emission factors of similar vegetation can be explained by the diurnal pattern of burning.

In addition, the Aqua/Terra ratio can serve as a proxy for calculating total fire energy.

Emission = Eƒterra x Terra Energy

Emission = Eƒ x ∫FRE dt

Emission = Eƒ (biome) x ƒ (Aqua/Terra) x Terra Energy

Theory

Demonstrated empirically

Tested for Savanna/Shrubland

ConclusionsConclusions

Savannas/ShrublandsIGBP Landcover: Open Savannas, Woody Savannas, Savannas

y = -0.0129x + 0.0566R2 = 0.8028

0.000

0.005

0.010

0.015

0.020

0.025

0.030

0.035

0.040

0.045

0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00

Aqua/Terra ratio

emis

sion

fact

or

BOAS

SHSA

NHSA

SHAF

NHAF

Proposed Global alternative approach for Fire emission estimateProposed Global alternative approach for Fire emission estimate

MODIS+AERONET Observations

Observations fromRetrieved emission

Testing of emission inversion: GOCART

reproduces observed aerosol using retrieved emissions

dtFREEEmission f

Satellite derived estimates of burned

area, though improving, may have

an error of greater than 35%