U N I V E R S I T Y O F W A S H I N G T O N S C H O O L O F N U R S I N G

Global partitioning of NOx emissions using satellite observations

Lyatt JaegléUniversity of Washington

Linda Steinberger University of WashingtonRandall Martin Dalhousie UniversityKelly Chance Harvard-Smithsonian Center for Astrophysics

U N I V E R S I T Y O F W A S H I N G T O N S C H O O L O F N U R S I N G

Tropospheric NO2 columns

Top-down NOx inventory

Chance et al. [2000]Martin et al. [2002]

Martin et al. [2003]

GOME

The Global Ozone Monitoring Experiment (GOME)

Applied to GOME observations for year 2000Use GEOS-CHEM as a priori NOx inventory:

1 2

Jaeglé et al. [2004]Jaeglé et al. [2005]

Partitioned inventory

FF+BF

BB

SOILS

3

Spectral fitStratosphereAMF

Inverse modeling with GEOS-CHEM

Anthropogenic emissions: GEIA scaled to 1998Biofuel: Yevich & Logan [2003]Biomass burning 2000: Duncan et al. [2003]Soils: Yienger & Levy [1995]

Algorithm for partitioning top-down NOx inventory

Algorithm tested using synthetic retrieval

GOME NOx emissions

Fuel Combustion1. Spatial location of FF-dominated regions in a priori (>90%)1

Biomass Burning2. Spatiotemporal distribution of fires used to separate BB/soil

VIRS/ATSR fire countsSoils

No fires + background

2

Combine top-down GOME emissions (E,err) with a priori emissions (E’,err’) weighted by relative errors

optimized inventory:

Optimized inventoryGOME (E)GOME (E) A priori (E’)A priori (E’) A posteriori (E”)A posteriori (E”)

ln(E”) = ln(E) ln(err’)2 + ln(E’) ln(err)2

ln(err’)2 + ln(err)2

ln(err”)-2 = ln(err’)-2 + ln(err)-2

1010atoms N cm-2 s-1

Fuel CombustionA prioriA priori A posterioriA posteriori

(±80%) r = 0.96(±40%)

Aseasonal a posteriori fuel combustion emissions except for Europe and East Asia (wintertime heating) China and India (4.4 and 1.7 TgN/yr) are 38% and 43% higher than Streets et al. [2003] inventory

United States Europe East Asia

1010atoms N cm-2 s-1

Bars: A posteriori(FF+BF)

Line: A priori(FF+BF)

A poster : 6.4 TgN/yrA priori : 6.3 TgN/yr

4.9 TgN/yr4.9 TgN/yr

5.2 TgN/yr4.8 TgN/yr

A posteri. total

Biomass Burning (2000)A prioriA priori A posterioriA posteriori

Good agreement with BB seasonality from Duncan et al. [2003]

(±200%)

r = 0.85

(±80%)

SE Asia/India N. Eq. Africa S. Eq. Africa

N. Eq. Africa:50% increase

SE Asia/India:46% decrease

GWEMHoelzemann, ’055 TgN/yr

Line: A priori(BB)

Bars: A posteriori(BB)

1010atoms N cm-2 s-1

A posteriori total

Soil emissionsA posteriori (8.9 TgN/yr) 68% larger than a priori!

A prioriA priori A posterioriA posteriori

Largest soil emissions: seasonally dry tropical ecosystems

(±200%) (±90%)

+ fertilized cropland ecosystems

r = 0.79

Soils

Onset of rainy season: Pulsing of soil NOx!

North Eq. Africa

Mid-latitudes soil emissions: 3.9 TgN/yr (a priori: 1.7 TgN/yr)

Summer mid-latitudes: soils account for ~50% of FF emissions!

East Asia (soils = 1 TgN/yr) consistent with inverse modeling study of Yuxuan Wang et al. [2004]

United States Europe East Asia

Bars: a posterioriLines: a priori

Soils

SummaryFuel combustion emissions: 25.6 TgN/yr (±40%) within 10% of a priori emissions.

Biomass burning emissions: 5.8 TgN/yr (±80%) vs a priori 5.9 TgN/yr (±200%). Large differences: N. Eq. Africa + SE Asia/India.

Large soil emissions (8.9 vs 5.3 TgN/yr). Max during summer in NH and wet season in Tropics:Role of N-fertilizers over croplands + rain-induced pulsing from

semi-arid soils. Need to revisit Yienger & Levy? Underestimate of soil contribution to background ozone?

Soil emissions over N. Eq. Africa

Onset of rainy season: Pulsing of soil NOx!

GOME NOGOME NO22: June 10-12 2000: June 10-12 2000

IDAF surface NO2 passive samplers

Jaeglé et al. [2004]

Soils

Annual GOME top-down NOx inventory: 2000N

Ox e

mis

sion

s

1010atoms N cm-2 s-1

NO

2 col

umns

GOME GEOS-CHEM (a priori)

1015 molecules cm-2

Anthropogenic emissions: GEIA scaled to 1998Biofuel: Yevich & Logan [2003]Biomass burning 2000: Duncan et al. [2003]Soils: Yienger & Levy [1995]

Linear relationship between ENOx and NO2

Algorithm for partitioning top-down NOx inventory

Algorithm tested using synthetic retrieval

GOME NOx emissions

Fuel Combustion1. Spatial location of FF-dominated regions in a priori (>90%)

Biomass Burning2. Spatiotemporal distribution of fires used to separate BB/soil

VIRS/ATSR fire countsSoils

No fires + background

Optimized inventory

GOME (E)GOME (E) A priori (E’)A priori (E’) A posteriori (E”)A posteriori (E”)

1010atoms N cm-2 s-1

GEOS-CHEM