Towards a more integrated approach to tropospheric

chemistry

Paul Palmer Division of Engineering and Applied

Sciences, Harvard University

Acknowledgements: Dorian Abbot, Kelly Chance, Daniel Jacob, Dylan Jones, Loretta Mickley, Parvadha Suntharalingham, Glen Sachse (NASA LaRC)

Rise in Tropospheric Ozone over the 20th Century

Observations at mountain sites in Europe [Marenco et al., 1994]

Concentrations of O3 have increased dramatically due to human activity

Tropospheric O3 is an important climate forcing agent

Boundary layer (0-2km)

NOx, RH, CO

Continent 1 Continent 2Ocean

Free troposphere

(Greenhouse gas)

NO

HO2OH

NO2

O3hv

Direct intercontinental transport of pollutants

Global background O3

O3

O3

Impact of human activity on background O3

RH+OH HCHO + products

Global 3d chemistry

transport model (GEOS-CHEM)

Constructing a self-consistent representation of the

atmosphere

GOME,

MOPITT,

SCIAMACHY

TES, OMI

•Nadir-viewing SBUV instrument

•Pixel 320 x 40 km2

•10.30 am cross-equator time (globe in 3 days)

•O3, NO2, BrO, OClO, SO2, HCHO, H2O, cloud

Global Ozone Monitoring Experiment

•HCHO slant columns fitted: 337-356nm

HCHO JULY 1997

Isoprene

Biomass Burning

Isoprene dominates HCHO production over US during

summer Southern Oxidant Study 1995

North Atlantic Regional Experiment 1997

[ppb]

Surface source (mostly isoprene+OH)

Continental outflow

Alt

itu

de

[km

]

Alt

itu

de

[km

]

measurements GEOS-CHEM model

Defined background CH4 + OH

HCHO columns – July 1996HCHO columns – July 1996

r2 = 0.7 n = 756Bias = 11%

Model:Observed HCHO columns

[1016molec cm-2]

GEOS-CHEM HCHO GOME HCHO

[1012 atoms C cm-2 s-

1]

GEIA isoprene emissions (7.1 Tg C)

BIOGENIC ISOPRENE IS THE MAIN SOURCE OF HCHO IN U.S. IN SUMMER

Using HCHO Columns to Map Isoprene Emissions

isoprene

HCHOhours

OH

hours

Displacement/smearing length scale 10-100 km

h, OH

EISOP = ___________kHCHO HCHO

Yield ISOPHCHO

Isoprene emissions (July 1996)

[1012 atom C cm-2 s-

1]

50

(5.7 Tg C)

7.1 Tg C

GEIA

GOME

GOME isoprene emissions (July 1996) agree with surface measurements

r2 = 0.77

Bias -12%

ppb0 12

GOME

r2 = 0.53

Bias -3%

GEIA

10

16 m

ole

cu

les c

m-2

°C

0

2.5

-2

2

GOME T GOME

95

INTERANNUAL VARIABILITY IN GOME HCHO COLUMNS (1995-2001)

August Monthly Means & Temperature AnomalyT

97

98

01

00

99

96

1016 molecules cm-20 2.5

Abbot et al, 2003

CO inverse modeling•Product of incomplete combustion; main sink is OH

•Lifetime ~1-3 months

•Relative abundance of observations•Big discrepancy between Asian emission inventories and observations

110 E 120 E 130 E 140 E 150 E 160 E

Longitude

0 N

10 N

20 N

30 N

40 N

50 N

Lat

itu

de

DC-8 FlightsP-3B Flights

CMDL network for CO and CO2

TRACE-P (Transport And Chemical Evolution over the

Pacific) data can improve level of disaggregation of

continental emissions

Observation vector y

State vector (Emissions x)

Modeling Overview

xs = xa + (KTSy-1K + Sa

-1)-1 KTSy-1(y – Kxa)

y = Kxa +

Inverse model

x = Annual emissions from Asia (Tg C/yr)

y = TRACE-P CO (ppb)

Forward model(GEOS-CHEM)

China Japan

Southeast AsiaRest of

World

Global 3D CTM 2x2.5 deg resolution

[OH] from full-chemistry model (CH3CCl3 = 6.3 years)

Korea

Biomass burning AVHRR (Heald/Logan)

Fuel consumption (Streets)

x = emissions

from individual countries

and individual processes

(BB, BF, FF)

Observation

A priori

CO

[p

pb

]

Lat [deg]

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

xs = xa + (KTSy-1K + Sa

-1)-1 KTSy-1(y –

Kxa)

SS = (KTSy-1K + Sa

-1)-1

Xs = retrieved state vector (the CO sources)Xa = a priori estimate of the CO sourcesSa = error covariance of the a priori K = forward model operatorSy = error covariance of observations = instrument error + model error + representativeness error

Inverse Model (a.k.a. Weighted linear least-

squares)

Gain matrix

Choice of x…

-Aggregate anthropogenic emissions (colocated sources)

-Aggregate Korea/Japan (coarse model grid resolution)

GEOS-CHEM

Error specification is crucial

Sa Anthropogenic (c/o Streets): China (78%), Japan (17%), Southeast Asia (100%), Korea (42%) Biomass burning: 50% Chemistry (~CH4): 25%

Sy Measurement accuracy (2%) Representation (14ppb or 25%)

GEOS-CHEM

2x2.5 cell

TRACE-P

All latitudes

(measured-model) /measured

Alt

itu

de [

km

]

Mean bias

RREModel error (y*RRE)2

~38ppb (>70% of total

observation error)

Ch

ina (

BB

)

Best estimate is insensitive to inverse model assumptions

A prioriA posteriori

1-sigma uncertaint

y

CO

[p

pb

]

Lat [deg]

A posteriori emissions improve agreement with

observations

Observation

A priori

A posteriori

Kore

a +

Ja

pan

South

east

Asi

a

Chin

a (

BB)

Rest

of

Worl

d

Chin

a

(anth

ropogenic

)

[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

Large differences over NW Indian & SE Asia

Observed CO2:CO correlations are consistent with Chinese biospheric emissions of CO2 40% too high

Offshore China

Over Japan

Slope (> 840 mb) = 22

R2 = 0.45

Slope (> 840 mb) = 51

R2 = 0.76

JapanChina

Suntharalingam et al, 2003

• Problem: Modeled Chinese CO2:CO slopes are 50% too large

CO2/CO

50% CO increase from inverse model not enough

Reconciliation with observations: decrease a CO2 source with high CO2:CO

biosphere

Future satellite missions

The “A Train”

MODIS/ CERES IR Properties of Clouds

AIRS Temperature and H2O Sounding

Aqua

1:30 PM

CloudsatPARASOL

CALPSO- Aerosol and cloud heightsCloudsat - cloud dropletsPARASOL - aerosol and cloud polarizationOCO - CO2

CALIPSOAura

OMI - Cloud heights

OMI & HIRDLS – Aerosols

MLS& TES - H2O & temp profiles

MLS & HIRDLS – Cirrus clouds

1:38 PM

OCO

1:15 PM

OCO - CO2 column

C/o M. Schoeberl

• Due for launch in 2004 • IR, high res. Fourier spectrometer (3.3 - 15.4 m)• Has 2 viewing modes: nadir and limb• Spatial resolution of nadir view = 8x5 km2

Potential of TES nadir observations of CO: An Observing System Simulation Experiment

Jones et al, 2003

Objective: Determine whether nadir observations of CO from TES have enough information to reduce uncertainties in estimates of continental sources of CO

New Concept: test science objectives of satellite instruments before launch

Inverse model with realistic errors

After 8 days of observations (operating half time)

Concluding remarks

•Satellite observations are starting to revolutionize our understanding of chemistry in the lower atmosphere

•Proper validation of these data with in situ measurements is critical for their interpretation – need to integrate

•Correlations between multiple species provide untapped source of information on source inversions

•Future will be fully-coupled chemical data assimilation:

Optimized, comprehensive 4-d view of the atmosphere

State estimation (e.g., large-scale t-dep. source inversions)

Spare slides

GEOS-CHEM global 3D model: 101

•Driven by DAO GEOS met data

•2x2.5o resolution/26 vertical levels

•O3-NOx-VOC chemistry

•GEIA isoprene emissions

•Aerosol scattering: AOD:O3

TRACE-P data can improve level of disaggregation of continental emissions

110 E 120 E 130 E 140 E 150 E 160 E

Longitude

0 N

10 N

20 N

30 N

40 N

50 N

Lat

itu

de

DC-8 FlightsP-3B Flights

cold front

cold air

warm air

Main transport processes:

DEEP CONVECTION

OROGRAPHIC LIFTING

FRONTAL LIFTING

100 E 130 E 160 E 190 E 220 E 250 E 280 E

Longitude

0 N

10 N

20 N

30 N

40 N

50 N

60 N

La

titu

de

DC-8 FlightsP-3B Flights

Feb – April 2001

Back-trajectories of top 5% of observed values indicate local sources (removed from

analysis)

Proxy for OH Only a strong local source

Selected halocarbons measured during TRACE-P: CH3CCl3, CCl4, Halon 1211, CFCs 11, 12 (Blake, UCI)

CH3CCl3 : CO relationships

= value above latitudinal

“background”

0

5

10

15

20

25

30

35

40

45

Gg

/yr

CH 3CCl 3

CCl 4

CFC-11

CFC-12

CH3CCl3,CCl4,CFCs 11 & 12):

-represents >80% of East Asia ODP (70% of total global ODP)

-103.1 ODP Gg/yr (East Asia)

East Asia ODP = 70%

Global ODP = 20%

Eastern Asia estimates

Large global & regional implications

Methodology has the potential to monitor magnitude and trends of emissions of a wide range of environmentally important gases

Previous workThis work

0.9

1.4

2.3

3.0

Platform multiple ERS-2 Terra ENVISAT Space station

Aura TBD TBD

Sensor TOMS GOME MOPITT MODIS/MISR

SCIAMACHY MIPAS SAGE-3 TES OMI MLS CALIPSO OCO

Launch 1979 1995 1999 1999 2002 2002 2004 2004 2004 2004 2004 2005

O3 N N/L L L N/L N L

CO N N/L L N/L

CO2 N/L N

NO L

NO2 N N/L N

HNO3 L L

CH4 N/L N

HCHO N N/L N

SO2 N N/L N

BrO N N/L N

HCN L

aerosol N N N L N N

N = NadirL = Limb

Satellite data will become integral to the study of tropospheric chemistry in the next

decade

[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

•Launched March 2002

•GOME + IR channels (CO, CH4, CO2)

•Nadir and limb viewing capabilities

•X-Y pixel resolution ~26x15 km (nadir)

SCIAMACHY/Envisat instrument

Initial comparisons

look promising (8/23/02)

C/o A. Maurellis

Eastern Europe through Africa

CO

vertical column = slant column /AMF

satellite

dHCHO

Earth Surface

HCHO mixing ratio C()

lnIB/

Scattering weights

Shape factorw() = - 1/AMFG lnIB/

Sig

ma c

oord

inate

(

)

S() = C() air/HCHO

AMF = AMFG w() S() d1

1

0

GEOS-CHEM

GEOS-CHEMGOME GOME GEOS-CHEM

1016 molecules cm-2

SEASONAL VARIABILITY IN GOME HCHO COLUMNS (’97)

0 2.5

r>0.75bias~20%

MAR

APR AUG

MAY

JUN

SEP

JUL

OCT

GEOS-CHEM

Isoprene “volcano”

[1016 molec cm-

2]

July 7 1996

July 20 1996

mm

c/o Y-N. Lee, Brookhaven National Lab.

Missouri Illinois

Kansas

[ppb]

Aircraft data @ 350 m during July 1999

OZARKS

SOS 1999

GOME

Surface temperature [K]

Sla

nt

colu

mn

HC

HO

[1

016 m

ol

cm

-2]

Temperature dependence of isoprene emission

Direct & indirect emissions

Correlations between different species provide additional constraints to inverse

problems, e.g.

Western Pacific

CO, CO2, halocarbons, BC, + many others…

Asian continent

2 km

Fresh emissions

EX = (X:CO) ECO