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Top-down constraints on emissions of biogenic trace gases from North America Dylan Millet with D.J. Jacob, R.C. Hudman, S. Turquety, C. Holmes (Harvard)

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Presentation on theme: "Top-down constraints on emissions of biogenic trace gases from North America Dylan Millet with D.J. Jacob, R.C. Hudman, S. Turquety, C. Holmes (Harvard)"— Presentation transcript:

1 Top-down constraints on emissions of biogenic trace gases from North America
Dylan Millet with D.J. Jacob, R.C. Hudman, S. Turquety, C. Holmes (Harvard) measurements by D. Blake, K. Chance, J. De Gouw, A. Fried, A. Goldstein, A. Guenther, B. Heikes, S. Herndon, T. Karl, T. Kurosu, G. Schade, H. Singh, B. Sive, B. Talbot, C. Warneke NOAA Summer Institute Steamboat Springs, CO July 10-13, 2006

2 Biogenic Emissions Affect Atmospheric Composition and Climate
HCHO O3 SOA OH, hu, O3 Air Quality VOC NOx, VOC, SO2 Tropospheric chemistry Climate Isoprene & Methanol Most important biogenic NMVOCs ~ 8x anthropogenic VOC emissions

3 Quantifying Trace Gas Emissions
Enclosure Measurements Surface Sites Aircraft Measurements Remote Sensing Spatial Scale: Leaf Globe Time Scale: Short-term Long-term Short-term Long-term Mechanistic Constraints: High Lower

4 Can We Map Isoprene Emissions from Space?
HCHO slant columns measured by GOME (K. Chance, T.P. Kurosu et al.) OH ~ 1 hour Isoprene HCHO HCHO vertical columns measured by OMI (K. Chance, T.P. Kurosu et al.)

5 Can We Map Isoprene Emissions from Space?
Key Questions: 1) What are the main precursors contributing to HCHO columns and variability over North America? OH Isoprene 2) What is the error in HCHO columns measured from space? HCHO Other VOCs 3) What are the implications for retrieving VOC emissions from space?  Address using aircraft measurements

6 Interpreting HCHO Columns
Many VOCs oxidize to produce HCHO But what drives variability in the HCHO column? OH, hu, O3 VOC HCHO In the model world, ΩHCHO variability is dominated by isoprene What do the data say?

7 Sources of Variability in Column HCHO
Methane & OVOCs main HCHO precursors in most of the atmosphere isoprene OVOCs But variability in column production rate is low VOC source Distance downwind ΩHCHO Isoprene a-pinene propane 100 km Isoprene dominant source when ΩHCHO is high Signal from other VOCs smears out ΩHCHO variability over N. America driven by isoprene Probability ANMHCs methane LOD / t terpenes Measured column HCHO production rate

8 Atmospheric Scattering
Errors in Satellite HCHO Measurements Fitting uncertainty (~ 4 x 1015 molec/cm2) HCHO Relating slant columns to vertical columns (Air mass factor; AMF) Atmospheric Scattering clouds, aerosols HCHO vertical profile Surface albedo Model Viewing geometry & SZA scattering HCHO vertical distribution

9 Errors in Satellite HCHO Measurements
AMF Error Clouds are the primary source of error Clear Skies: <1% mean bias; 15% 1σ error ½ Cloudy Skies: 17% mean bias; 24% 1σ error Aerosols: ↑ AMF by 16% on average Overall Mean bias Precision 1σ error in HCHO satellite measurements 25–31% Recommended cloud cutoff: 50%

10 HCHO column mass balance:
HCHO Production from Isoprene HCHO column mass balance: OBS MOD HCHO yield from isoprene: Y = 1.6 ± 0.5 Retrieval errors + yield uncertainty: 40% (1σ) error in inferring isoprene emissions from HCHO satellite measurements Millet, D.B., et al., (2006), J. Geophys. Res., doi: /2005JD006853, in press.

11 Continuing Directions
Spatial Distribution of Isoprene Emissions over North America Comparison between emission inventory and HCHO columns from OMI indicates mismatch in hotspot locations Implications for O3 production HCHO columns from the OMI satellite instrument for July 2005. Isoprene emissions estimated with the MEGAN model for July 2003 [Guenther et al., 2006].

12 Global Budget of Methanol (Tg/yr)
OH 129 Atmospheric production 38 (18-38) CH3OH Burden: ~4Tg Lifetime: ~10 d CH4 OH(aq) (in-cloud) <1 Wet deposition 12 Dry deposition (land) 55 (24-70) Urban emissions 4 (2-8) Biomass + biofuel burning 13 (6-15) Oceans: net sink 10 (0-50) Plant growth 128 (70-300) Plant decay 23 (13-23)

13 Simulated Methanol Concentrations in Surface Air
North American Methanol Sources (July) Urban Limited bottom-up data imply minor contribution Plant Decay Few direct measurements imply 2nd largest terrestrial source Biogenic Most important; 2 plant physiological schemes give comparable results

14 Data Used for Model Evaluation
Constrain North American sources and sinks by evaluating model simulation against aircraft and surface measurements

15 Comparison with Aircraft Data
… improved by specifying [CH3OH]aq [Williams et al., 2004]. This nearly doubles the net ocean sink. Measured Modeled MBL comparisons indicate underestimate of ocean sink… Both plant emission schemes give large overestimates over E. U.S.

16 Comparison with Observations
Measured Modeled Observations from cities and over Mexico imply anthropogenic source may be too low Overestimate of biogenic source evident at eastern surface sites

17 Conclusions and Future Directions
Can we use quantitatively map isoprene emissions from space using satellite measurements of HCHO? Yes Isoprene is the dominant source of ΩHCHO variability over North America Clouds are the most important source of error in the HCHO retrievals Average molar HCHO yield from isoprene oxidation is 1.6 ± 0.5 Overall uncertainty in measuring isoprene emissions from space is ~40% (1σ) Millet, D.B., et al., (2006), J. Geophys. Res., doi: /2005JD006853, in press. Ongoing work: Use OMI HCHO columns to examine spatial distribution of isoprene emissions North American methanol budget Bottom-up biogenic emission estimates are too high Bottom-up urban/industrial emission estimates are too low Doubling of ocean sink (15 to 28 Tg/yr) needed to reproduce gradients in MBL More seawater methanol and air-sea flux measurements are needed to better understand this sink Ongoing work: Continue investigation of North American methanol budget

18 Acknowledgements NOAA Climate and Global Change Program
The ITCT-2K2, NEAQS, INTEX-A, INTEX-B, and MILAGRO science teams Bob Yantosca, Brendan Field OMI science team


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