Evaluation of CMAQ soil-NO emissions via comparison of CMAQ output and satellite-retrieved NO2 columns

Dale Allen (University of Maryland; AOSC)Lisa Silverman (UMD; Civil & Environmental Eng)

Sheryl Ehrman (UMD ; Chemical & Biomolecular Eng)Ken Pickering (NASA-GSFC)

Heidi Plata (UMD; Chemical & Biomolecular Eng)

Objectives

• Develop a better understanding of soil based sources of nitrogen oxides

• Evaluate whether satellite observations of NO2 can be used to improve emissions estimates for soil derived NOx over the United States

• Use this understanding and satellite observations to improve model estimates of NOx emissions in BEIS3, which is the biogenic emissions module used in CMAQ

NOx Emissions Sources over the U.S. (approximate values)

Six Tropospheric Sources:

Emission Quantities:

Fossil Fuel Combustion

12-14 Tg N/yr (EPA trends report)

Soil-Biogenic Emission

0.5-1.5 Tg N/yr (10-15% of ff source)

Biomass Burning 1-2 Tg N/yr (Leenhouts, 1998)

Lightning Discharge 1-2 Tg N/yr (~10 f s-1)

Upper Tropospheric Aircraft Emissions

0.5-1 Tg N/yr

Stratospheric Injection <0.5 Tg N/yr

BEIS-3 Biogenic NO emissions (YL method) • E = R2.5 x Tadj x Padj x Fadj x Cadj

• E = Time varying NO emission flux

• R2.5 = Baseline NO emission flux (assumes 2.5% of fertilizer N is emitted as NO during growing season)

• Tadj = temperature adjustment factor

• Padj = precipitation adjustment factor (1-15). Heavy rain activates nitrifying bacteria

• Fadj = fertilizer adjustment factor (1 during April and then decreases over growing season)

• Cadj = canopy adjustment factor (1 during April and then decreases linearly to 0.5)

Yienger & Levy (1995)

Magnitude and duration of YL precipitation pulse is function of rainfall amount

Yienger and Levy(1995)

>1.5 cm day-1

0.5<P<1.5

0.1<P<0.5

For showers & heavy rain, substantial enhancementeven 4 days after event

Evaluation of soil NO source• Comparisons of models and satellite observations reveal a

factor of 2-4 underestimate of soil-NO emissions wrt to the YL a priori estimate (Martin et al., 2003; Jaegle et al., 2005; Wang et al., 2007; Boersma et al., 2008)

• YL scheme overestimates pulse duration and underestimates role of soil moisture (Hudman et al., 2010;Yan et al., 2005)

• Mean 8-hr O3 enhancement of 3-5 ppbv over agricultural Great Plains during June; Hudman et al., 2010

• CMAQ simulations were performed for March – May 2006 – nosoilNO emissions– YL (standard) soilNO emissions– Doubled YL soilNO emissionsResulting tropospheric NO2 columns are compared to

columns from the OMI instrument aboard the Aura satellite

OMI tropospheric NO2 products

1. v1.0 OMI standard product [Bucsela et al., 2008; Celarier et al., 2008] 2. v2.0 DOMINO product [Boersma et al., 2007; Boersma et al., 2011]

Each algorithm begins with same slant columns (red lines) Different methods used to remove stratospheric columns Different methods used to convert tropospheric slant cols to overhead cols Yield different tropospheric vertical column amounts

tropopause

LNOx contribution est using output from GMI model (Allen et al., 2010)

OMINASAStdproduct

CMAQnosoilNO

CMAQDbl YLsoilNO

CMAQYLsoilNO

CMAQnosoilNO

CMAQDbl-YLSoil-NO

CMAQYLSoil-no

OMIDOMINO

LNOx contribution est using output from GMI model (Allen et al., 2010)

Percent of tropospheric NO2 column with asoil-NO source (April-May 2006 mean)

Standard YLSource (peakContribution ~35%)

Doubled YLSource (peak Contribution ~60%)

Lightning-NOcontribution to column from GMI model (Allen et al., 2010)

Model columns and 30% threshold calculated w/o LNOx

LNOx contribution estimated using NASA’s GMI model (Allen et al., 2010)

Soil-NO emissions were examined following precipitation events in the

Great Plains and MidwestScreen out events if:Lightning influenced (HYSPLIT & NLDN)

Biomass burning (OMI AI > 1)

soilNO/totalNO emissions < 0.5

Case Day of Precip. Event Precipitation on Day 0 (cm) Location

1 31-Mar-06 1.60 Ravenna, NE

2 31-Mar-06 0.70 Chambers, NE

3 2-Apr-06 0.83 Great Bend, KS

4 2-Apr-06 1.67 Wayne, NE

5 2-Apr-06 1.63 Ravenna, NE

6 2-Apr-06 0.57 Briscoe, TX

7 7-Apr-06 2.55 Brady, NE

8 16-Apr-06 1.73 Wayne, NE

9 16-Apr-06 0.58 Brady, NE

10 25-Apr-06 0.97 Brady, NE

11 25-Apr-06 1.41 Great Bend, KS

12 29-Apr-06 1.82 Linn, KS

13 29-Apr-06 1.86 Briscoe, TX

14 24-May-06 1.19 Hulett, WY

15 24-May-06 0.89 Pierre, SD

16 24-May-06 1.37 Wayne, NE

16 Cases and Their Locations

Locations of Cases

SoilMoisture

CMAQColumnsoilNO

CMAQColumn

YL soilemissions

Precip

CMAQColumnOMINASA

Not surprisingly, cloud cover often hinders analysis

PRECIP

YL soilemissions

CMAQcolumn

Soilmoisture

CMAQColumnsoilNO

OMIColumnNASAproduct

Time series examined: Precipitationsoil-NO emissionsTropospheric NO2 column (NASA standard and DOMINO)Tropospheric NO2 column (YL and doubled YL emissions)

Time period examined: Day preceding precipitation event (day-1), day precipitation began

(day0) to 4-days after event (day4)

Impact of precipitation pulsing on tropospheric NO2 columns was examined using mean time series from the 16

case studies

OMI NASA cols days3-4 exceed NASA cols days0-2 by ~0.7 pmol cm-2Considerable noise as cloud cover reduces number of cases

DOMINO column days 3&4 exceed DOMINO col days 0-2 by ~0.5 pmol cm-2

Considerable noise as cloud cover reduces number of cases

CMAQ column with std YL emissions increasesby ~0.3 pmol cm-2 between days 0-1 and 2-4 (Noisy!)

CMAQ column with dbl YL emissions increases by ~0.5 pmol cm-2 between days 0-1 and 2-4

Conclusions

• Soil-NO adds 8-22% to tropospheric NO2 column over US (east of 110°W)

• Doubling YL soil-NO source decreases bias between model and satellite tropospheric NO2 cols over US (e of 110°W) from ~-10% to ~-2% (Effect of smoothing by averaging kernel not considered)

• Over central Plains, peak soil-NO contribution to column ranges from 35-60%

• Examining 16 precipitation events over central Plains regions, precipitation-pulsing increases satellite-retrieved columns by ~0.5 to 0.7 peta molecules cm-2. CMAQ columns increase by 0.3 to 0.5 (0.5 to 0.7) peta molecules cm-2 for standard YL (doubled-YL) source. However, uncertainty bars on changes are large.

Acknowledgements

• Thomas Pierce of EPA• George Pouliot of EPA• Ana Prados of UMBC

• Funding from NASA’s DSS Applied Science Air Quality Program

References

Eskes, Henk, et al. “A combined retrieval, modelling and assimilation approach to estimate tropospheric NO2 from OMI measurements .” KNMI, De Bilt, The Netherlands. 10-12 Sept. 2010. Troposperic NO2

Measured by Satellites.

J. J. Yienger and H. Levy II. “Empirical Model of Global Oil-biogenic NOx emissions.” Journal of Physical Research. 100.D6:11,447-11,464. 1995.

Plata, Heidi. “Evaluating Satellite Observations to Improve Soil NOx Emissions Estimates.” 2010. Research Report.

Plata, Heidi. “Towards improved emission inventories of soil NOx via model/satellite measurement intercomparisons.” 2010. Powerpoint Presentation.

Percent of tropospheric NO2 column with a soil-NO source

nosoilNO

Dbl YL soilNOYL soilNO

V1.0 NASAStd OMIproduct

Note: Low-bias at least partially due to lack of lightning-NO emissions

nosoilNO

Dbl YL soilNOYL soilNO

V2.0DOMINO

Low-bias at least partially due to lack of lightning-NO emissions (LNOx)Avg kernel not applied as model profile unrealistic due to lack of LNOx

Percent of CMAQ’s mean April-May 2006tropospheric NO2 column with a soil-NO source

YL source

Doubled YL source

Note: Addition of LNOx would reduce mean percent contribution valuesby ~25%

SoilMoisture

CMAQColsoilNO

OMICol(NASA)

CMAQCol(total)

Soil-NOEmission

Precip