Emissions of CO from Asia during TRACE-P

Paul Palmer, Daniel Jacob, Dylan Jones, Colette Heald

David Streets, Glen Sachse, Hanwant Singh

http://www.people.fas.harvard.edu/~ppalmer

Global emissions of CO are highly uncertain

KEY QUESTIONS:1) Are bottom-up estimates of CO sources

consistent with measured concentrations of CO?

2) How much information do concentration measurements of CO provide on CO sources?

Forward model (GEOS-CHEM)

Inverse model

P3B, DC8 observations

D. Streets’ Emissions

*

FF

BB

BF

Modeling Overview

*

*

Logan/Heald

Emissions *

*

Xs = Xb + SbK (KTSbK + SY)-1(Y – HXb)SS = (KTSY

-1K + Sb-1)-1

GEOS-CHEM

Tagged CO simulation for TRACE-P (also state

vector)

China

India

Japan

Southeast Asia

Korea

Rest of World

Some sources/regions are combined due to interdependency of emissions

Global 3D CTM 2x2.5 deg resolution

GEOS-CHEM

CO

[p

pb

]

Lat [deg]

Observation

A priori

A priori emissions have a large negative bias in the boundary layer

o Emission uncertainties for Asia:

Anthropogenic (D. Streets): China (78%), Japan (17%), Southeast Asia (100%), India (100%), other (42%)

Biomass burning: 50%

o Measurement uncertainty:

Observation accuracy (1%)

Representativeness (14ppb or 25%)

Estimated: 1 sigma value about mean observed 2x2.5 value

Model error

GEOS-CHEM

GEOS-CHEM

2x2.5 cell

TRACE-P

Detailed error specification for inverse model

GEOS-CHEM

All latitudes

(measured-model) /measured

Alt

itu

de [

km

]

Model error: (y*RRE)2 ~38ppb (>70% of total measurement

error)

Mean bias

RRE

A posteriori emissions are insensitive to assumptions made

in inverse analysis

Kore

a +

Jap

an

Ind

ia

Rest of World/10

Sou

theast

Asia

Ch

ina (

BB

)

Ch

ina

(an

thro

pog

en

ic)

A prioriA posteriori

1-sigma uncertaint

y

GEOS-CHEM

CO

[p

pb

]

Lat [deg]

Observation

A priori

A posteriori

A posteriori emissions improve agreement with observations

[1018 molec cm-2]

MOPITT shows low CO columns over Southeast Asia during TRACE-P

GEOS-CHEM

MOPITT

MOPITT – GEOS-CHEM

[1018 molec cm-2]c/o Heald, Emmons, Gille

Largest difference

Conclusions1) A priori emissions are inconsistent with BL

data

2) Error analysis is crucial for accurate determination of emissions from concentration data

3) Inverse model shows:

* increased anthropogenic emissions (30% from China)

*decreased biomass burning (results inconclusive)

Multi-species inversion is the next important step