1. The 6th CMAS Workshop
Using the CMAQ Model to Simulate a Dust Storm in the Southwestern United States
Daniel Tong$, George Bowker*, Rohit Mathur+, Tom Pierce+, Shaocai Yu$, Dale Gillette+
Atmospheric Sciences Modeling Division, ARL/NOAA, RTP, NC 27711
* Atmospheric Modeling Division, US EPA, RTP, NC
$ On assignment from STC
+ on assignment to NERL/ORD/EPA
October 2, 2007
Chapel Hill, NC

2. Environmental Impacts of Dust Particles
Climate :
Direct: absorbing & scattering;
Indirect: CCN;
Bio-available iron  phytoplankton  CO2 sink;
Atmospheric Chemistry:
Reduce photolysis rates by over 50%;
Reacting platform for O3, HO2 and N2O5;
Buffering acid rain;
Air Quality:
Reduce visibility;
PM air quality standards;
Human Health:
Sources for toxic metals;
Ubiquitous constituents of inhalable PM;
(Source: IPCC, 2007)

3. Sources of Dust Emissions: 3 major types Anthropogenic sources
EPA’s National Emission Inventory (NEI) includes anthropogenic dust emissions
(Dust from unpaved road)
(Dust from crop land)
Agricultural sources
(Chihuahua desert)
Natural desert sources
The other two major sources are not accounted for

4. Impact on CMAQ Modeling CMAQ simulation of PM2.5 on April 15, 2003

5. Comparing CMAQ with IMPROVE
MODIS Image on April 15, 2003 – Wind-blown dust storm

6. How to Simulate Dust Storm with CMAQ?
Box Model
Met-Driven Dust Emission Model
Size distribution
Chemical speciation
Merge with SMOKE
Other
CMAQ Simulation
(w/ dust emissions)
Post-processing
Dust Emission
Model Evaluation
IMPROVE, AQS, etc
Satellite

7. Modeling Wind-blown Dust Emissions
Important parameters
Open barren areas (land use data);
Dry soil (precipitation, soil moisture, and snow cover);
Soil components – sand, silt and clay (soil type data);
Vegetation coverage (seasonal crop data, roughness)
High wind to mobilize particles (surface wind speed);
Threshold wind speed for each soil type (threshold wspd)

8. Building a Box Model
Purpose: Sensitivity test and compare various parameters
Dust emission modeling fundamentals
Dust Emission Flux = Kvh * [Horizontal Flux]
Horizontal flux Equations were derived from wind tunnel and field experiments over different soils.
Dust emission is more sensitive to threshold friction velocity than to formulation of flux equation

9. The Stand-alone Dust Emission Model
Purpose: put everything together to cook some dust
Dust emission model:
Driven by MM5 with Pleim-Xiu scheme;
Owen’s flux equation;
USGS land use and soil data;
Model dust emissions from desert and agricultural lands;
Threshold friction velocities taken from field and wind tunnel measurements;
MM5-predicted U* adjusted for local conditions;
Crop map subroutine by Shan He;

10. The Dust Emission Model (Continued)
Owen’s Equation (source: Marticorena et al, 1997):
Threshold Friction Velocity (source: Gillette 1980, 1988):
Soil type
Sand
Loamy Sand
Sandy Loam
Silt Loam
Loam
Sandy Clay Loam
Silty Clay Loam
Clay Loam
Sandy Clay
Silty Clay
Clay
Desert Land
0.42
0.51
0.66
0.34
0.49
0.78
0.33
0.71
0.56
Agricultural
0.28
0.29
1.08
0.64
0.54
Convert MM5-predicted U* into surface U* (U*s) (source: Marticorena et al, 1995):

11. Monthly average rate of dust emissions (DTOT)
We got some dust here!

12. Comparing Dust Emissions with SENSIT Measurement
15-m Met. Tower
Sensit
Sediment collector
Accurate capture of the occurrence and frequency of dust emissions. Nice!

13. (We put 45% into fine mode and 55% into coarse)
Make it Ready for CMAQ
Splitting b/w Fine and Coarse Modes (Cheng et al, 1997):
Sites
Sanggen Dalai
Beijing
Species
PM2.5
PM10
Non-dusty day 36 53 81
142
Heavy dusty day
2815
4128
200
444
Difference
2779
4073
119
302
PM2.5 / PM10
68.2%
39.2%
(We put 45% into fine mode and 55% into coarse)
Chemical Speciation (Pelt & Zobek, 2007; Ansley et al., 2006):
FAC_PSO4 = ! Sulfate
FAC_PNO3 = ! Nitrate
FAC_PEC = ! EC
FAC_POA = ! OC
FAC_PMF = FAC_PSO4 - FAC_PNO3 …
FAC_PMC = 0.55

14. Toxic Metal Emissions with Dust
Chemical speciation for toxic metal (Pelt & Zobek, 2007):
FAC_PHG = ! Hg
FAC_PPB = ! Pb
FAC_PFE = ! Fe
FAC_PCR = ! Cr
FAC_PCD = ! Cd
FAC_PAG = ! Ag
FAC_PAS = ! As
FAC_PCU = ! Cu
…… (factors may vary with soil type and land use)
If not running CMAQ with toxic pollutants, these are put into the “other” portion in PM2.5

15. CMAQ Simulation with Wind-Blown Dust
CMAQ modeling details:
SAPRC gas chemistry, ae4 with recent updates (v4.6.1?)
36 km resolution, vertical 14 layers
Domain over continental U.S., northern Mexico and southern Canada
Dust Impact on O3 Concentrations (max difference)
Missing in this version of CMAQ: online calculation of photolysis; dust as reaction platform for O3, N2O5, HO2 etc.

16. Dust Impacts on PM2.5 Concentrations Maximum hourly difference
Mean difference (dust – base)
Maximum hourly difference
Huge impact on Peak PM2.5!

17. Comparison with IMPROVE
(Now with dust emissions)
Improved, but not enough. Why?

18. Comparison Dust Sources with MODIS
(Source: Rivera et al., 2006)
Missing Dust Sources in Northern Mexico
So we have missed at GUMO1 site!

19. Conclusion A stand-alone emission model for wind-blown dust
CMAQ modeling of a dust storm
Missing PM emissions from desert and crop lands
Captured occurrence and frequency of dust emissions
Potentially useful for both Criteria and Toxics air pollutants
Dust impact on O3 is small – maybe too small!
Improved CMAQ performance for PM at some sites;
Missing dust source outside US;

20. Future Work Chemical speciation and size distribution
Finer and more complete land use and soil data
Vegetation cover
Chemical speciation and size distribution
More calibration and evaluation
Sources outside US;
Resolution of barren areas;
Temporal variation;
Canopy scavenging;
Surface sheltering;

21. Acknowledgement
We thank Daiwen Kang for comments, Lucille Bender for providing CMAQ input, Steve Howard, David Wong, Rob Pinder for help with data processing, and Shan He for an earlier version of the dust emission algorithm.
Disclaimer: The research presented here was performed under the Memorandum of Understanding between the U.S. Environmental Protection Agency (EPA) and the U.S. Department of Commerce's National Oceanic and Atmospheric Administration (NOAA) and under agreement number DW This work constitutes a contribution to the NOAA Air Quality Program. Although it has been reviewed by EPA and NOAA and approved for publication, it does not necessarily reflect their policies or views.