Post on 21-Mar-2016
description
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, O3VOC
HCHO
O3
SOA
…NOx, VOC, SO2
Air Quality
Tropospheric chemistry
IsopreneMost important biogenic NMVOC
~ 6x anthropogenic VOC emissions
Climate
Mapping Isoprene Emissions from Space
VOCs HCHOOH, h
ki, Yi
OH, h
kHCHO
ii
iEYk HCHO
HCHO1Ω
Local ΩHCHO-Ei Relationship
HCHO vertical columns measured by OMI(K. Chance, T.P. Kurosu et al.)
VOC source Distance
downwind
ΩHCHOIsoprene
a-pinene propane
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 (1
012 m
olec
cm
-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 (1
016 m
olec
cm
-2)
Millet et al., JGR (in press).
ΩHCHO = SEisoprene+ B
iiHCHO
iHCHO Y
kk
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