Transcript Document

Constraining Anthropogenic Emissions of Fugitive Dust
with Dynamic Transportable Fraction and Measurements
Daniel Tong1,2, Daewon Byun1, George Pouliot3, David
Mobley3, Prakash Behave3, Rohit Mathur3, Tom Pierce3,
Tom Pace4, Shaocai Yu3, Tianfeng Chai1,2, Heather Simon3
1 US NOAA Air Resources Laboratory, Silver Spring, MD
2 Science & Technology Corp., Silver Spring, MD
2 U.S. EPA National Exposure Research Laboratory, RTP, NC
4 US EPA OAQPS, RTP, NC
Chapel Hill, NC
October 22, 2009
Fugitive Dust Emissions
Natural Fugitive Dust
Anthropogenic Fugitive Dust
Unpaved Road
Construction
Paved Road
Wind-blown dust from
barren or disturbed land
Tilling
Mining
Anthropogenic Fugitive Dust
Major Sources
Chemical Profiles of Fugitive Dust
(Source: SPECIATE Database)
Concept of Transportable Fraction
 Direct use of emission inventories results in severe
PM2.5 over-prediction (Pace 2005);
 The model assumes emissions are mixed across a grid
cell (100 to 1000 km2) instantaneously and evenly;
 In reality, 75% of emitted dust particles are deposited
within 1 km from the source;
Transportable Fraction (TF) (Cowherd and Pace 2002) :
The fraction of particle emissions that remains airborne
after near source enhanced deposition and is available for
transport away from the vicinity of the source.
Methods of Determining Transportable Fraction (TF)
 In the mid 1990s, the US EPA OAQPS used an ad hoc
“divide-the-inventory-by-four” approach to adjust the
fugitive dust emission estimates (Pace 2005);
 Since 2003, the Pace conceptual model was used to
determine the adjustment factor (Static TF);
Transportable Fraction (TF) = 1 – Capture Fraction (CF)
Proposed Dynamic Transportable Fraction (TF)
 The dynamic TF: Derived based on land cover, vegetation
growing season, and changing atmospheric conditions.
 TF1: above-canopy effect
N -- number of LU types;
u* -- friction velocity;
fi – Land use fraction
Vd – dry deposition parameterized after
Slinn (1982), Minvielle et al. (2002).
 TF2: Land use based capture fraction
TF2 = 1 – CF
Static vs Dynamic Transportable Fraction (TF)
TF2 - Obstruction Impact
TF – Pace Model
TF1 – Above Canopy
TF1 x TF2
Applying new TF to SMOKE and AQ modeling
Applying new TF
 The TF1 and TF2 values are calculated using land use
data (BELD), surface wind, friction velocity and roughness
(from the MET model) and parameters from literature;
 Dynamic cropland fraction is calculated based on 27
major crop growing seasons; so both TF1 and TF2 change
with time;
 TF1 and TF2 are applied to each grid cell to adjust the
original fugitive dust emission estimates;
CMAQ Modeling
 CMAQ (v4.6) runs with three emission datasets: Fugitive
dust without TF; with Pace TF; with the new TF;
Effect of TF on Fugitive Dust Emissions
POC
PMFINE
Before
After
Fugitive Dust Emissions and CMAQ PM Conc.
PM2.5 (13%)
A25 (42%)
PM10 (18%)
AORGPA (9%)
Potential Effects of TF on CMAQ Performance
CMAQ vs. Obs.
Percentage of dust AORGPA
(source: Mathur et al., 2008)
 The transportable fraction brings down both A25 and POA
concentrations in CMAQ;
 Help with A25 over-prediction, and the effect on POA is limited.
Conclusion
 Proposed a dynamic transportable fraction to adjust
fugitive dust emissions;
 The dynamic TF takes consideration of land use, crop
growth, and meteorological parameters; both TF1 and TF2
change with time;
 The TF effect is most significant in the forested eastern
US, and less so over the barren land;
 Applying the TF brings down CMAQ prediction of PM2.5,
mostly A25, and primary OC; Reducing A25 overprediction and having a limited effect on OC prediction.
Future work
1. Study the forces controlling enhanced near source removal
 Impaction by surface obstructions;  Electrostatic forces;
 Particle agglomeration;
 Thermal deposition;
2. Compare model results with the adjusted emissions with
measurements of dust fingerprint constituent (crustal);
3. Examine temporal profiles of
fugitive dust emissions
IMPROVE measurements show a clear weekly
pattern in all crustal elements
(source: Murphy et al, ACP, 2008)