The Be rkeley H igh Spatial R esolution(BEHR) OMI NO 2 Retrieval: Recent Trends in NO 2

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AQUA. AURA. The Be rkeley H igh Spatial R esolution(BEHR) OMI NO 2 Retrieval: Recent Trends in NO 2. Ronald C. Cohen University of California, Berkeley $$ NASA . Air Quality Applications Of OMI NO 2. Key elements: total columns trends over time differences and ratios in space - PowerPoint PPT Presentation

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The Berkeley High Spatial Resolution(BEHR) OMI NO2 Retrieval: Recent Trends in NO2

Ronald C. CohenUniversity of California, Berkeley$$ NASA

AQUA

AURA

Air Quality Applications Of OMI NO2

Key elements:

• total columns

• trends over time

• differences and ratios in space

• the noontime chemical lifetime of NO2 of ~1-4hrs implies an e-folding distance of order 25km

• OH changes will be approximately equal to NO2 changes—a significant effect on lifetimes

Four Corners Power Plants: WRF-Chem

L Valin et al., Atmos. Chem. Phys. 2011

Los Angeles: WRF-Chem

OMI NO2 Riyadh

8 hours

6 hours

Deriving NO2 column densities from space-based reflectance measurements

Step 1: DOAS fit to determine slant column

Step 2: Subtract the Stratospheric contribution

Tropospheric Vertical Column Density

Summary of the NO2 retrieval process

Total Slant Column Density Stratospheric Vertical Column Density

Step 3: Convert the tropospheric slant column into a vertical column

Step 3: Convert the tropospheric slant column into a vertical column

AMFs are sensitive to • Viewing geometry• Terrain pressure and reflectivity• Shape (not magnitude) of the NO2

vertical profile• Clouds

AMF = Vertical Column Slant Column

Absorption, Scattering, and Transmission

through a cloudAbsorption and

Scattering by the surface

Atmosphere

Absorption and Scattering by aerosols and

molecules

SurfaceModified image from Richter, U Bremen

Berkeley High Resolution Retrieval (BEHR)

NASA standard BEHR Terrain pressure High-res terrain

database, center of OMI footprint

High-res terrain database, average over OMI footprint

Terrain reflectivity

Monthly 1° × 1° MODIS, 8 day 0.05° × 0.05°

NO2 profile shape

Annually 2° × 2.5° WRF-Chem, Monthly 4 × 4 km2 (CA&NV)12 x 12 km2 U.S.

Clouds OMI cloud product MODIS cloud product

Russell et al., Atmos Chem & Phys 11, 8543-8554, 2011

Terrain Reflectivity (Albedo)

NASA Standard Product June 2008

BEHR June 2008

MODIS True Color

SP NO2 June 18, 2008

OMI Monthly Albedo MODIS 8 day Albedo

Russell et al., Atmos Chem & Phys, 2011

-120.5 -120 -119.5 -119 -118.5 -11840

40.5

41

41.5

42

Terrain Reflectivity (Albedo)

Russell et al., Atmos Chem & Phys, 2011

PDF of systematic errors

Terrain Pressure

Russell et al., Atmos Chem & Phys, 2011

PDF of systematic errors

NO2 profile shape

0 0.05 0.1 0.150

0.5

1

1.5

2

2.5

3

Normalized NO2

Hei

ght (

km)

UrbanRural

Russell et al., Atmos Chem & Phys, 2011

PDF of systematic errors

The BEHR product is generally higher in urban regions and lower in rural regions than the operational products

BEHR % DifferenceStandard Product

Russell et al., Atmos Chem & Phys, 2011

Summer 2005 Russell et al., ACPD in press

molecules cm-2

Summer 2011 Russell et al., in press

molecules cm-2

Trends for select cities and power plants

Russell et al., in press

05 06 07 08 09 10 110

0.5

1

1.5

2x 10

16

Col

umn

NO 2 (m

olec

/cm

2 )

Year

Denver, CO

05 06 07 08 09 10 110

0.5

1

1.5

2x 10

16

Year

Los Angeles, CA

05 06 07 08 09 10 110

0.5

1

1.5

2x 10

16

Year

Atlanta, GA

05 06 07 08 09 10 110

0.5

1

1.5

Year

Nor

mal

ized

NO 2

All Cities

05 06 07 08 09 10 110

0.5

1

1.5

Year

Nor

mal

ized

NO 2

All Power Plants

05 06 07 08 09 10 110

2

4

6x 10

15

Year

Col

umn

NO 2 (m

olec

/cm

2 )

Intermountain, UT

05 06 07 08 09 10 110

2

4

6x 10

15

Year

Four Corners, NM

05 06 07 08 09 10 110

2

4

6x 10

15

Year

Seminole, FL

–– Weekdays

- - Weekends

–– All days

05 06 07 08 09 10 110

0.5

1

1.5

2x 10

16

Col

umn

NO 2 (m

olec

/cm

2 )

Year

Denver, CO

05 06 07 08 09 10 110

0.5

1

1.5

2x 10

16

Year

Los Angeles, CA

05 06 07 08 09 10 110

0.5

1

1.5

2x 10

16

Year

Atlanta, GA

05 06 07 08 09 10 110

0.5

1

1.5

Year

Nor

mal

ized

NO 2

All Cities

05 06 07 08 09 10 110

0.5

1

1.5

Year

Nor

mal

ized

NO 2

All Power Plants

05 06 07 08 09 10 110

2

4

6x 10

15

Year

Col

umn

NO 2 (m

olec

/cm

2 ) Intermountain, UT

05 06 07 08 09 10 110

2

4

6x 10

15

Year

Four Corners, NM

05 06 07 08 09 10 110

2

4

6x 10

15

Year

Seminole, FL

Trends in cities are similar while trends at power plants are more variable05 06 07 08 09 10 11

0

0.5

1

1.5

2x 10

16

Col

umn

NO 2 (m

olec

/cm

2 )

Year

Denver, CO

05 06 07 08 09 10 110

0.5

1

1.5

2x 10

16

Year

Los Angeles, CA

05 06 07 08 09 10 110

0.5

1

1.5

2x 10

16

Year

Atlanta, GA

05 06 07 08 09 10 110

0.5

1

1.5

Year

Nor

mal

ized

NO 2

All Cities

05 06 07 08 09 10 110

0.5

1

1.5

YearN

orm

aliz

ed N

O 2

All Power Plants

05 06 07 08 09 10 110

2

4

6x 10

15

Year

Col

umn

NO 2 (m

olec

/cm

2 ) Intermountain, UT

05 06 07 08 09 10 110

2

4

6x 10

15

Year

Four Corners, NM

05 06 07 08 09 10 110

2

4

6x 10

15

Year

Seminole, FL

Russell et al., in press

47 cities, 23 power plants!

-120 -110 -100 -90 -80 -7025

30

35

40

45

50

-50

-40

-30

-20

-10

0

10

2005 – 2011 reductions in urban regions of the US are similar (–32 ± 7%).

Russell et al., in press

The impact of the economic recession on emissions is observed by OMI

-120 -110 -100 -90 -80 -7025

30

35

40

45

50

-15

-10

-5

0

5

-120 -110 -100 -90 -80 -7025

30

35

40

45

50

-15

-10

-5

0

5

-120 -110 -100 -90 -80 -7025

30

35

40

45

50

-15

-10

-5

0

5

2005 – 2007

Russell et al., in press

The impact of the economic recession on emissions is observed by OMI

-120 -110 -100 -90 -80 -7025

30

35

40

45

50

-15

-10

-5

0

5

-120 -110 -100 -90 -80 -7025

30

35

40

45

50

-15

-10

-5

0

5

-120 -110 -100 -90 -80 -7025

30

35

40

45

50

-15

-10

-5

0

5

-120 -110 -100 -90 -80 -7025

30

35

40

45

50

-15

-10

-5

0

5

-120 -110 -100 -90 -80 -7025

30

35

40

45

50

-15

-10

-5

0

5

-120 -110 -100 -90 -80 -7025

30

35

40

45

50

-15

-10

-5

0

5

2005 – 2007

2007 – 2009

Russell et al., in preparation

2005 – 2007

The impact of the economic recession on emissions is observed by OMI

Russell et al., in press

-120 -110 -100 -90 -80 -7025

30

35

40

45

50

-15

-10

-5

0

5

-120 -110 -100 -90 -80 -7025

30

35

40

45

50

-15

-10

-5

0

5

-120 -110 -100 -90 -80 -7025

30

35

40

45

50

-15

-10

-5

0

5

-120 -110 -100 -90 -80 -7025

30

35

40

45

50

-15

-10

-5

0

5

-120 -110 -100 -90 -80 -7025

30

35

40

45

50

-15

-10

-5

0

5

-120 -110 -100 -90 -80 -7025

30

35

40

45

50

-15

-10

-5

0

5

-120 -110 -100 -90 -80 -7025

30

35

40

45

50

-15

-10

-5

0

5

-120 -110 -100 -90 -80 -7025

30

35

40

45

50

-15

-10

-5

0

5

-120 -110 -100 -90 -80 -7025

30

35

40

45

50

-15

-10

-5

0

5

2005 – 2007

2007 – 2009

2009 – 2011

-120 -110 -100 -90 -80 -7025

30

35

40

45

50

-50

-40

-30

-20

-10

0

-120 -110 -100 -90 -80 -7025

30

35

40

45

50

-50

-40

-30

-20

-10

0

-120 -110 -100 -90 -80 -7025

30

35

40

45

50

-50

-40

-30

-20

-10

0

-120 -110 -100 -90 -80 -7025

30

35

40

45

50

-50

-40

-30

-20

-10

0

Weekdays: –34 ± 8% Weekends: –27 ± 10%

Reductions on weekdays are larger than those on weekends due to reductions in diesel traffic

2005 – 2007 2007 – 2009 2009 – 2011Weekday – 6 ± 4% – 9 ± 4% – 4 ± 4%Weekend – 7 ± 5% – 6 ± 7% – 1 ± 7%

Russell et al., in press

Conclusions

• The BEHR product reduces biases in the NO2 column due to coarse resolution terrain and profile parameters. We can make it available upon request, rccohen@berkeley.edu.

• Analysis of 2005–2011 trends for cities and power plants in the US show how improved vehicle technology and the economic downturn have influenced emissions.

Ashley Russell Luke Valin(PhD May 2012) (PhD soon)

Thank you!

A.R. Russell, et al, Trends in OMI NO2 observations over the United States: Effects of emission control technology and the economic recession, ACPD. in press June 2012.L.C. Valin, et al, Effects of model resolution on the interpretation of satellite NO2 observations, ACP. 11, 11647-11655, 2011 A.R. Russell, et al., A high spatial resolution retrieval of NO2 column densities from OMI: Method and Evaluation, ACP, 11, 8543-8554, 2011.L.C. Valin, et al., Observation of slant column NO2 using the super-zoom mode of AURA OMI, AMT, 4, 1929-1935, 2011.A.K. Mebust,, Characterization of wildfire NOx emissions using MODIS fire radiative power and OMI tropospheric NO2 columns , ACP. 11, 5839-5851, 2011.

R.C. Hudman, et al., Interannual variation in soil NOx emissions observed from Space, ACP. 10, 9943-9952, 2010.

Update: Trends in urban regions of CA, 2005-2011

- 44%

- 30%- 36%

- 30%

Russell et al., 2010 (updated)

Beer-Lambert Law:

I = Io e - σ ℓ N

SAMPLE(N)LIGHT SOURCE (Io)

DETECTOR (I)

POLISHEDMIRROR

PARTICLES

CLOUDS

Entangled

MOLECULES

WRF-CHEM 1km – 4-Corners Plume

NO2 column OH Column

Large Area+Urban Sources in WRF-Chem

e-kx; x = ut; τ=k-1

NOx LifetimeBy Mass

By Decay Gradient

Integrated Observation

Resolved Observation

τ=Mobs / Erate

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