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Dylan Millet Harvard University with

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1 Spatial Distribution of Isoprene Emissions from North America: New Constraints from OMI
Dylan Millet Harvard University with D.J. Jacob and K.F. Boersma (Harvard), C.L. Heald (UC Berkeley), A. Guenther (NCAR), T.P. Kurosu and K. Chance (Harvard-Smithsonian) thanks to NASA-ACMAP NOAA C&GC Postdoctoral Program OMI Science Team INTEX Science Teams American Geophysical Union Fall Meeting 2006 San Francisco, CA

2 VOCs Affect Atmospheric Chemistry and Climate
Isoprene Most important non-methane VOC Global emissions ~ methane (but > 104 times more reactive) ~ 6x anthropogenic VOC emissions

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

4 Testing the Approach: ΩHCHO = SEisoprene+ B
What drives variability in column HCHO? Error Characterization Measured HCHO production rate vs. column amount Mean bias Precision PHCHO (1012 molec cm-2 s-1) isoprene 25–31% error (1σ) in HCHO satellite measurements INTEX-A/B ΩHCHO (1016 molec cm-2) clouds primary source of error HCHO Column Comparison ΩHCHO variability over N. America driven by isoprene 25x1015 25x1015 Other VOCs give rise to a relatively stable background ΩHCHO  Not to variability detectable from space URI (DC8) OMI 25x1015 25x1015 Millet et al., JGR (2006). NCAR (DC8) Aircraft

5 Defining Spatial Distribution of Eisoprene Using OMI HCHO
HCHO columns from OMI satellite instrument (summer 2006) Isoprene emissions from the MEGAN biogenic emission inventory (summer 2006) ? test bottom-up inventories against top-down constraints from OMI mismatch in hotspot locations implications for OH, O3, SOA production

6 Model of Emissions of Gases and Aerosols from Nature
Vegetation-specific baseline emission factors Environmental drivers (T, h, LAI, leaf age, …) Guenther et al., ACP (2006) Drive MEGAN with 2 land cover databases G2006 Guenther [2006] (MODIS3) CLM Community Land Model (AVHRR) MEGAN Isoprene Emissions w/ G2006 vegetation MEGAN Isoprene Emissions w/ CLM vegetation 14.6 TgC 12.2 TgC [1013 atomsC cm-2 s-1]

7 OMI vs. GEOS-Chem with MEGAN Emissions
OMI HCHO: June-August 2006 Similarity in broad spatial distribution (r2 = 0.86) GEOS-Chem HCHO: June-August 2006 But important discrepancies  regional & landscape scale  emission hotspots [1015 molecules cm-2]

8 Relating HCHO Columns to Isoprene Emissions
GEOS-Chem HCHO Column MEGAN Isoprene Emissions [1015 molecules cm-2] [1013 atomsC cm-2 s-1] Slope ΩHCHO = SEisoprene+ B Uniform ΩHCHO-Eisoprene relationship Variable ΩHCHO-Eisoprene relationship OMI Isoprene Emissions OMI Isoprene Emissions 11.3 TgC 11.1 TgC [1013 atomsC cm-2 s-1]

9 Spatial Patterns in Isoprene Emissions
OMI Isoprene Emissions OMI Isoprene Emissions 11.3 TgC 11.1 TgC MEGAN w/ CLM vegetation Uniform ΩHCHO-Eisoprene relationship Variable ΩHCHO-Eisoprene relationship 12.2 TgC OMI - MEGAN OMI - MEGAN

10 Spatial Patterns in Isoprene Emissions
MEGAN higher than OMI over dominant emission regions OMI – MEGAN Isoprene Emissions June-August, 2006 MEGAN w/ G2006 Land Cover Ozark Plateau Upper South Wisconsin-Minnesota Large sensitivity to surface database used MEGAN w/ CLM Land Cover CLM-driven MEGAN lower than OMI over deep South & Atlantic coast

11 Why are Emissions Overestimated in Dominant Source Regions?
Bottom-up emissions are too high in Ozarks, upper South, MN/WI OMI – MEGAN Isoprene Emissions June-August, 2006 MEGAN w/ G2006 Land Cover Average Bias: Ozarks: 30-70% Upper South: 20-45% Large emissions driven by oak tree cover, high temperatures Broadleaf tree isoprene emissions overestimated? MEGAN w/ CLM Land Cover G2006 Broadleaf Trees

12 Why Are CLM Emissions Too Low in Deep South?
Average Bias: 50 to >100% OMI – MEGAN Isoprene Emissions June-August, 2006 MEGAN w/ G2006 Land Cover Underestimate of broadleaf tree or shrub coverage? CLM – G2006 Broadleaf Tree Cover CLM – Guenther Shrub Cover MEGAN w/ CLM Land Cover Modeled emissions from evergreen trees or crops too low? CLM Fineleaf Evergreens CLM Crops

13 Conclusions OMI HCHO columns show similar magnitude & broad spatial patterns as state-of-the-art bottom-up emission inventories (R2 = 0.86)  But reveal major discrepancies at the regional scale Bottom-up isoprene emission estimates are 20 to >70% too high in the dominant emission regions  Ozarks, upper South, MN/WI  Overestimate of broadleaf tree emissions? CLM-driven isoprene emission estimates are 50 to >100% too low over the deep South and along the Atlantic coast  Underestimate of broadleaf tree and shrub cover?  Underestimate of fineleaf evergreen or crop emissions?

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