Top-down constraints on emissions of biogenic trace gases from North America: Mapping isoprene emissions from space Dylan Millet with D.J. Jacob and K.F. Boersma Atmospheric Chemistry Modeling Group, Harvard University T.P. Kurosu and K. Chance Harvard-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) IGAC-WMO-CACGP Symposium Cape Town, South Africa September 17-22, 2006

Biogenic Emissions Affect Atmospheric Composition and Climate HCHO O3 SOA … OH, h, O3 Air Quality VOC NOx, VOC, SO2 Tropospheric chemistry Climate Isoprene Most important biogenic NMVOC ~ 6x anthropogenic VOC emissions

Mapping Isoprene Emissions from Space HCHO vertical columns measured by OMI (K. Chance, T.P. Kurosu et al.) VOCs HCHO OH, h ki, Yi kHCHO VOC source Distance downwind ΩHCHO Isoprene a-pinene propane 100 km detection limit Local ΩHCHO-Ei Relationship Palmer et al., JGR (2003,2006).

Ratio between HCHO along light path and the vertical column amount Testing the Approach: Errors in satellite HCHO measurements ΩHCHO = SEisoprene+ B HCHO GOME/OMI sensitivity Main Sources of Error Fitting uncertainty ~ 4 x 1015 molecules cm-2 Ratio between HCHO along light path and the vertical column amount HCHO vertical profile scattering by air molecules, aerosols, clouds surface albedo 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).

Testing the Approach: Relating isoprene emission to HCHO column ΩHCHO = SEisoprene+ B What drives variability in column HCHO? Test model HCHO yield M = 3.5 M = 3.6 Observed GEOS-Chem Measured HCHO production rate vs. column amount PHCHO (1012 molec cm-2 s-1) INTEX-A ΩHCHO (1016 molec cm-2) ΩHCHO (1016 molec cm-2) Isoprene dominant source when ΩHCHO is high Other VOCs give rise to a relatively stable background ΩHCHO  Not to variability detectable from space ΩISOP (1016 molec cm-2) HCHO yield from isoprene: Y = 1.6 ± 0.5 ΩHCHO variability over N. America driven by isoprene Millet et al., JGR (in press).

Using OMI HCHO to Define Spatial Distribution of Eisoprene HCHO columns measured with the OMI satellite instrument (summer 2005) Isoprene emissions from the MEGAN biogenic emission inventory (summer 2005) ? Comparison between emission inventory and HCHO columns from OMI indicates mismatch in hotspot locations Implications for O3, SOA production

Model of Emissions of Gases and Aerosols from Nature Guenther et al., Atmos. Chem. Phys., 6, 3181–3210, 2006. Vegetation-specific baseline emission factors Environmental drivers (T, h, LAI, leaf age, …) Land cover database MEGAN Isoprene emissions

Similarity in broad pattern (r2 = 0.80) … but fine-scale discrepancies OMI vs. GEOS-Chem with MEGAN Emissions OMI 44% lower Similarity in broad pattern (r2 = 0.80) … but fine-scale discrepancies

ΩHCHO-Eisoprene relationship ΩHCHO-Eisoprene relationship Relating HCHO Columns to Isoprene Emissions ΩHCHO = SEisoprene+ B Domain-wide ΩHCHO-Eisoprene relationship Local ΩHCHO-Eisoprene relationship

Spatial Patterns in Isoprene Emissions MEGAN w/ Community Land Model (CLM) Domain-wide ΩHCHO-Eisoprene relationship Local ΩHCHO-Eisoprene relationship Normalized OMI - MEGAN Normalized OMI - MEGAN

Spatial Patterns in Isoprene Emissions MEGAN w/ CLM Land Cover MEGAN w/ Olson Land Cover Normalized OMI – MEGAN July-August, 2005 Scale up OMI to remove overall bias Drive MEGAN with 2 land cover databases Olson [2001] Community Land Model (CLM) Large sensitivity to surface database used MEGAN higher than OMI over ‘hotspots’ such as the Ozarks, lower over deep South & Atlantic coast

Emissions Overestimated in Ozarks & Other ‘Hotspots’ MEGAN w/ CLM Land Cover MEGAN w/ Olson Land Cover Normalized OMI – MEGAN July-August, 2005 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

Emissions Underestimated in Deep South & Atlantic Coast Bottom-up emissions are too low in deep South, Atlantic coast MEGAN w/ CLM Land Cover MEGAN w/ Olson Land Cover Normalized OMI – MEGAN July-August, 2005 Underestimate of pine emissions in Southeast? Errors in vegetation cover? Underestimate of regional crop emissions also possible? (cotton, peanuts, tobacco) CLM Fineleaf Evergreen Trees CLM Crops

Conclusions 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?

Acknowledgements NOAA Postdoctoral Program in Climate and Global Change NASA/ACMAP OMI science team B. Yantosca, P. Palmer (now at Leeds), M. Fu, and other coworkers at Harvard The INTEX-A science team