Dylan Milletwith

D.J. Jacob and K.F. BoersmaAtmospheric Chemistry Modeling Group, Harvard University

T.P. Kurosu and K. ChanceHarvard-Smithsonian Center for Astrophysics

C. Heald (UC Berkeley), A. Guenther (NCAR), A. Fried (NCAR), B. Heikes (URI), D. Blake (UCI), and H. Singh (NASA-Ames)

Top-down constraints on emissions of biogenic trace gases from North America:

Mapping isoprene emissions from space

IGAC-WMO-CACGP SymposiumCape Town, South AfricaSeptember 17-22, 2006

Global Emissions (Tg/yr)

0

200

400

600

Isoprene Methanol AllAnthropogenic

VOCs

Biogenic Emissions Affect Atmospheric Composition and Climate

OH, h, O3

VOC

HCHO

O3

SOA

…NOx, VOC, SO2

Air Quality

Tropospheric chemistry

Isoprene

Most important biogenic NMVOC ~ 6x anthropogenic VOC emissions

Climate

Mapping Isoprene Emissions from Space

VOCs HCHOOH, h

ki, Yi

OH, h

kHCHO

ii

iEYk HCHO

HCHO

1Ω

Local ΩHCHO-Ei Relationship

HCHO vertical columns measured by OMI(K. Chance, T.P. Kurosu et al.)

VOC source Distance

downwind

ΩHCHO

Isoprene

a-pinenepropane

100 km

detectionlimit

Palmer et al., JGR (2003,2006). BSEisoprene HCHOΩ

Testing the Approach:Errors in satellite HCHO measurements

HCHO GOME/OMI sensitivity

Main Sources of Error

Ratio between HCHO along light path and the vertical column amount

HCHO vertical profilescattering by air molecules, aerosols, clouds

surface albedo

Fitting uncertainty~ 4 x 1015 molecules cm-2

Use INTEX-A aircraft data & GEOS-Chem model to test errors in HCHO measured from space

Clouds: primary source of error

1σ error in HCHO satellite measurements: 25–31%

Recommended cloud cutoff: 50%

Millet et al., JGR (in press).

ΩHCHO = SEisoprene+ B

PH

CH

O (

1012

mol

ec c

m-2

s-1)

Testing the Approach:Relating isoprene emission to HCHO column

What drives variability in column HCHO?

Measured HCHO production rate vs.

column amount

Isoprene dominant source when ΩHCHO is high

ΩHCHO variability over N. America driven by isoprene

Other VOCs give rise to a relatively stable background ΩHCHO

Not to variability detectable from space

Test model HCHO yield

M = 3.5

M = 3.6

Observed

GEOS-ChemINTEX-A

HCHO yield from isoprene:Y = 1.6 ± 0.5

ΩHCHO (1016 molec cm-2)

ΩISOP (1016 molec cm-2)Ω

HC

HO (

1016

mol

ec c

m-2)

Millet et al., JGR (in press).

ΩHCHO = SEisoprene+ B

iiHCHO

iHCHO Y

k

k

Comparison between emission inventory and HCHO columns from OMI indicates

mismatch in hotspot locations

Using OMI HCHO to Define Spatial Distribution of Eisoprene

Isoprene emissions from the MEGAN biogenic emission inventory (summer 2005)

Implications for O3, SOA production

HCHO columns measured with the OMI satellite instrument (summer 2005)

?

Model of Emissions of Gases and Aerosols from Nature

Land cover database

Environmental drivers (T, h, LAI,

leaf age, …)

MEGAN Isoprene emissions

Guenther et al., Atmos. Chem. Phys., 6, 3181–3210, 2006.

Vegetation-specific baseline emission

factors

OMI vs. GEOS-Chem with MEGAN Emissions

Similarity in broad pattern (r2 = 0.80)… but fine-scale discrepancies

OMI 44% lower

Relating HCHO Columns to Isoprene Emissions

Domain-wideΩHCHO-Eisoprene relationship

LocalΩHCHO-Eisoprene relationship

ΩHCHO = SEisoprene+ B

Spatial Patterns in Isoprene Emissions

Domain-wideΩHCHO-Eisoprene relationship

LocalΩHCHO-Eisoprene relationship

Normalized OMI - MEGAN Normalized OMI - MEGAN

MEGAN w/ Community Land Model (CLM)

Scale up OMI to remove overall bias

Spatial Patterns in Isoprene Emissions

Drive MEGAN with 2 land cover databases Olson [2001]

Community Land Model (CLM)

Large sensitivity to surface database used

MEGAN w/ CLM Land Cover

MEGAN w/ Olson Land Cover

Normalized OMI – MEGANJuly-August, 2005

MEGAN higher than OMI over ‘hotspots’ such as the Ozarks, lower over deep South &

Atlantic coast

Emissions Overestimated in Ozarks & Other ‘Hotspots’

Bottom-up emissions are too high in Ozarks, Virginia

Large emissions driven by oak tree cover, high temperatures

OMI comparison suggests broadleaf tree emissions are overestimated

Olson Broadleaf Trees

MEGAN w/ CLM Land Cover

MEGAN w/ Olson Land Cover

Normalized OMI – MEGANJuly-August, 2005

Emissions Underestimated in Deep South & Atlantic Coast

MEGAN w/ CLM Land Cover

MEGAN w/ Olson Land Cover

Normalized OMI – MEGANJuly-August, 2005

CLM Fineleaf Evergreen Trees

CLM Crops

Bottom-up emissions are too low in deep South, Atlantic coast

Underestimate of pine emissions in Southeast?

Underestimate of regional crop emissions also possible? (cotton, peanuts, tobacco)

Errors in vegetation cover?

OMI’s small footprint (13 x 24 km) allows us to define surface fluxes of trace gases with unprecedented spatial detail

OMI HCHO columns are broadly consistent with state-of-the-art bottom-up emission inventories (R2 = 0.80)

… but with important spatial differences!

Bottom-up isoprene emission estimates are too high in the Ozarks and other ‘hotspots’

Overestimate of broadleaf tree emissions?

Bottom-up isoprene emission estimates are too low over the deep South and along the Atlantic coast

Underestimate of pine (possibly crop) emissions?

Regional broadleaf tree coverage underestimated?

Conclusions

Acknowledgements

The INTEX-A science team

B. Yantosca, P. Palmer (now at Leeds), M. Fu, and other coworkers at Harvard

NOAA Postdoctoral Program in Climate and Global Change

OMI science team

NASA/ACMAP