Constraining Anthropogenic Emissions of Fugitive Dust with Dynamic Transportable Fraction and Measurements Chapel Hill, NC October 22, 2009 Daniel Tong.

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Presentation transcript:

Constraining Anthropogenic Emissions of Fugitive Dust with Dynamic Transportable Fraction and Measurements Chapel Hill, NC October 22, 2009 Daniel Tong 1,2, Daewon Byun 1, George Pouliot 3, David Mobley 3, Prakash Behave 3, Rohit Mathur 3, Tom Pierce 3, Tom Pace 4, Shaocai Yu 3, Tianfeng Chai 1,2, Heather Simon 3 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

Fugitive Dust Emissions Unpaved Road Paved Road Anthropogenic Fugitive Dust Wind-blown dust from barren or disturbed land Natural Fugitive Dust Tilling Mining Construction

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)

 The dynamic TF: Derived based on land cover, vegetation growing season, and changing atmospheric conditions. Proposed Dynamic Transportable Fraction (TF) N -- number of LU types; u * -- friction velocity; f i – Land use fraction V d – dry deposition parameterized after Slinn (1982), Minvielle et al. (2002). TF2 = 1 – CF  TF1: above-canopy effect  TF2: Land use based capture fraction

Static vs Dynamic Transportable Fraction (TF) TF2 - Obstruction ImpactTF1 – Above Canopy TF – Pace ModelTF1 x TF2

Applying new TF to SMOKE and AQ modeling  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; Applying new TF CMAQ Modeling  CMAQ (v4.6) runs with three emission datasets: Fugitive dust without TF; with Pace TF; with the new TF;

PMFINE POC BeforeAfter Effect of TF on Fugitive Dust Emissions

PM 2.5 (13%) Fugitive Dust Emissions and CMAQ PM Conc. PM 10 (18%) A25 (42%)AORGPA (9%)

Potential Effects of TF on CMAQ Performance 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. CMAQ vs. Obs.

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 PM 2.5, mostly A25, and primary OC; Reducing A25 over- prediction and having a limited effect on OC prediction.

Future work 1. Study the forces controlling enhanced near source removal  Impaction by surface obstructions;  Particle agglomeration;  Electrostatic forces;  Thermal deposition; 3. Examine temporal profiles of fugitive dust emissions 2. Compare model results with the adjusted emissions with measurements of dust fingerprint constituent (crustal); IMPROVE measurements show a clear weekly pattern in all crustal elements (source: Murphy et al, ACP, 2008)