Constraining global isoprene emissions with GOME formaldehyde column

measurements

Changsub Shim, Yuhang Wang, Yunsoo ChoiGeorgia Institute of Technology

Paul Palmer, Dorian Abbot Harvard University

Kelly ChanceHarvard-Smithsonian Center for Astrophysics

NO2 NO

OH

CO

O2

hv

hv

H2O

HO2

O3

ISOPRENE C5H8

Most dominant biogenic hydrocarbon

Global budget is highlyuncertain.

Emission dependence- Temperature,- Vegetation type,- Leaf Mass- Light intensity, etc…

Global Atmospheric Isoprene

HCHO for constraining isoprene

• It is a high-yield byproduct of the isoprene oxidation & VOCs

• It also has a short lifetime (order of hours)

• HCHO atmospheric columns have been measured by a satellite instrument (GOME) at 337 ~ 356 nm

• HCHO is a good proxy for isoprene by remote sensing! ( Chance et al., 2000; Palmer et al., 2003)

Objectives

Obtaining better global isoprene emissions based on

GOME HCHO measurements (Sep. 1996 ~ Aug. 1997)

Application of Inverse Modeling

8 regions for Inverse modelingHigh Signal-to-noise ratio HCHO GOME observationsAccount for ~65% of global a priori isoprene emissions

Tropical rain forest

Grassy lands

Savanna

Tropical seasonal forest

Mixed deciduous

Farm land & paddy rice

Dry evergreen

Regrowing wood (natural + artificial)

Drought deciduous

Other biogenic source

Biomass burning emission

Industrial emission

State vectors (Source parameters)

Isopren

e

Application of Inverse Modeling (10 biogenic state vector distribution)

V1: Tropical rain forest V2: Grass & shrub

V3: Savanna V4: Tropical seasonal forest & thorn woods

V5: Mixed deciduous V6: Farm land & paddy rice

V7: Dry evergreen V8: Regrowing wood

V9: Drought deciduous V10: Other biogenic source

Inverse modeling ( Bayesian Least Squares, Rodgers, 2000)

y = Kx + e

y : observations (GOME HCHO) x : defined source parameters: GEOS-CHEM K : Jacobian matrix (sensitivity of x to y :GEOS-CHEM) e : error term

GEOS-CHEM v5.05- Resolution: 4ox5o

- GEOS-STRAT (26 vertical layers)

The solution,

ˆ x x a (KTSe 1K Sa

1) 1KTSe 1(y Kx a ),

aT

aT

aa

aT

KSSKKSKSS

SKSKS1

111

)(

)(ˆ

Results (Annual HCHO columns)

Results:Monthly mean HCHO for 8 regions

A priori

A posteriori

GOME

Month : Sep96 Aug97

Results (Annual isoprene emissions)

Discrepancy over northern equatorial Africa.

Results: Annual isoprene emissions

Continent Weighted Uncertainty(%)

Isoprene Annual Emissions ( Tg C yr-1)

A Priori A Posteriori A Priori A Posteriori GEIA

N. AmericaEurope

East AsiaIndia

S. AsiaS. America

AfricaAustralia

291287280285298337332302

699663

12211075

10296

431928113795

10336

5030431555

12518953

4314221760

17813332

Total 370 560 499

The impact of a posteriori isoprene emissions

• In order to constrain global isoprene emissions, source parameters for 10 vegetation groups, biomass burning, and industrial emissions are considered in inverse modeling over 8 regions with high signal-to-noise ratios in GOME measurements.

• Global a posteriori isoprene annual emission is higher by 50% to 566 Tg/yr (a priori : 397 Tg/yr). The a posteriori global isoprene annual emissions are generally higher at mid latitudes and lower in the tropics when compared to the GEIA inventory

• There is a significant discrepancy between the seasonality of GOME measured and GEOS-CHEM simulated HCHO columns over the northern equatorial Africa. We attribute this problem to the incorrect seasonal cycle in surface temperature used in GEOS-CHEM. As a result, isoprene emissions over the region are overestimated.

• The a posteriori results suggest higher isoprene base emissions for agricultural land and tropi

cal rain forest and lower isoprene base emissions for dry evergreen

• The a posteriori biomass burning HCHO sources increase by a factor of 2 – 4 in most regions with significant emissions except for India. The industrial HCHO sources are higher by ~20% except for East Asia and India (~60%).

• The a posteriori uncertainties of emissions, although greatly reduced, are still high (~90%) reflecting the relatively large uncertainties in GOME retrievals.

• This higher isoprene emissions reduces the global mean OH concentration by 11%. The corresponding CH3CCl3 lifetime is increased to 5.7 years.

Conclusions

Acknowledgements

We thank Alex Guenther for his suggestion of conducting inverse modeling on a regional basis.

We thank Daniel Jacob and Robert Yantosca for their help. We also thank Mark Jacobson for his suggestions.

The GEOS-CHEM model is managed at Harvard University with support from the NASA Atmospheric Chemistry Modeling and Analysis Program.

This work was supported by the NASA ACMAP program.

Results ( Regional Statistics )

GOME

Weighted uncertaintie

s2

Correlation coefficient(R)

3

Model bias (%) Isoprene emission (Tg C/yr)

RegionsΩ

(%)4 PRI POST PRI POST PRI POST PRI POST GEIA

North America 59 291 69 0.84 0.84 -14.3 -3.6 22.2 25.7 21.4

Europe 69 287 96 0.52 0.60 -29.9 -11.9 9.5 12.0 6.1

East Asia 56 280 63 0.63 0.75 -39.2 -18.6 17.4 24.8 12.8

India 59 285 122 0.57 0.56 -33.2 -18.4 10.5 14.4 15.2

Southeast Asia 54 298 110 0.66 0.69 -35.8 -19.4 20.2 29.1 38.2

South America 54 337 75 0.58 0.64 -31.8 -12.6 79.4 106.4 163.5

Africa 53 332 102 0.56 0.54 -46.3 -23.6 60.3 103.3 105.7

Australia 69 302 96 0.52 0.56 -40 -24.8 33.3 50.6 31.1

Global 60 0.68 -35 375 566 503

Results (Emission Type)

N. America Europe E. Asia India S. Asia

S. America Africa Australia

Pri pos Pri Pos Pri pos Pri Pos Pri pos Pri pos pri Pos pri pos

V1 - - - - - - - 1.5 5 7.913.8

17.9 2 6.4 - -

V2 6.12 8.5 2.3 5.4 8.121.8 2.5 6.5 1.6 1.6 8.6 4.3 2.7

10.3 4.8 2.9

V3 1 1 - - - - - - - -15.6

21.4

10.5

14.6 1.2 5

V4 - - - - - - - - 4.6 6.9 8.516.2 4.5 4.5 - -

V5 7.813.3 5.7

10.3

12.5 1.3 - - 3.2 4.8 - - - - 1.6 1.6

V6 5.6 8.9 4.816.3 4.9

12.8 8.3 7.4 4.9

14.3 1.2 1.2 2.1 2.1 - 1.8

V7 4.6 3.2 1.2 2 - - 1.9 1.9 1.2 1.2 2.6 2.6 1.4 1.414.5

10.1

V822.6

18.1 3.7 4.1 1.3 5.2 7.5

13.5 8.3 8.3 1.6 1.6 3.4 3.4 - 5.9

V9 - - - - - - 2.4 3.4 3.5 1.7 1.8 1.6 6.915.2 4.3 4.7

RV30.7 40

34.6 38

28.5

48.5 3.4 8.3 3.7

11.7 9.9

17.9 8.4

21.8

16.2

35.9

BB - - 1.8 1.8 3.4 14 9.910.8 5.6

11.3 2.3

11.3 4.2 8.8 - -

IND 6 7.2 5.4 6.4 4.8 8.1 5.2 7.7 4.2 5.1 1 1 1.2 1.2 - -

Total 125 141 90 115 98 146 88 108 89 118 98 129 78 121 67 91