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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)

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Presentation on theme: "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)"— Presentation transcript:

1 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) Spatial Distribution of Isoprene Emissions from North America: New Constraints from OMI NASA-ACMAPNOAA C&GC Postdoctoral Program OMI Science Team thanks to American Geophysical Union Fall Meeting 2006 San Francisco, CA INTEX Science Teams

2 VOCs Affect Atmospheric Chemistry and Climate Isoprene Most important non-methane VOC Global emissions ~ methane (but > 10 4 times more reactive) ~ 6x anthropogenic VOC emissions

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

4 25x10 15 NCAR (DC8)Aircraft P HCHO (10 12 molec cm -2 s -1 ) Testing the Approach: What drives variability in column HCHO? Measured HCHO production rate vs. column amount Ω HCHO variability over N. America driven by isoprene Other VOCs give rise to a relatively stable background Ω HCHO  Not to variability detectable from space Error Characterization INTEX-A/B Ω HCHO (10 16 molec cm -2 ) Millet et al., JGR (2006). Ω HCHO = SE isoprene + B Mean bias Precision clouds primary source of error 25–31% error (1σ) in HCHO satellite measurements URI (DC8) OMI 25x10 15 HCHO Column Comparison isoprene

5 mismatch in hotspot locations Defining Spatial Distribution of E isoprene Using OMI HCHO Isoprene emissions from the MEGAN biogenic emission inventory (summer 2006) implications for OH, O 3, SOA production HCHO columns from OMI satellite instrument (summer 2006) ? test bottom-up inventories against top- down constraints from OMI

6 Model of Emissions of Gases and Aerosols from Nature G2006 Guenther [2006] (MODIS3) CLM Community Land Model (AVHRR) [10 13 atomsC cm -2 s -1 ] Environmental drivers (T, h, LAI, leaf age, …) Vegetation-specific baseline emission factors Drive MEGAN with 2 land cover databases MEGAN Isoprene Emissions w/ G2006 vegetation MEGAN Isoprene Emissions w/ CLM vegetation Guenther et al., ACP (2006) 14.6 TgC12.2 TgC

7 OMI vs. GEOS-Chem with MEGAN Emissions But important discrepancies  regional & landscape scale  emission hotspots [10 15 molecules cm -2 ] Similarity in broad spatial distribution (r 2 = 0.86) OMI HCHO: June-August 2006 GEOS-Chem HCHO: June-August 2006

8 Relating HCHO Columns to Isoprene Emissions Uniform Ω HCHO -E isoprene relationship Variable Ω HCHO -E isoprene relationship Ω HCHO = SE isoprene + B [10 15 molecules cm -2 ] [10 13 atomsC cm -2 s -1 ] 11.3 TgC11.1 TgC GEOS-Chem HCHO ColumnMEGAN Isoprene Emissions Slope OMI Isoprene Emissions

9 Spatial Patterns in Isoprene Emissions Uniform Ω HCHO -E isoprene relationship Variable Ω HCHO -E isoprene relationship OMI - MEGAN MEGAN w/ CLM vegetation 11.3 TgC11.1 TgC 12.2 TgC OMI Isoprene Emissions

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

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

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

13 OMI HCHO columns show similar magnitude & broad spatial patterns as state-of-the-art bottom-up emission inventories (R 2 = 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? Conclusions


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