WRAP RMC Phase II Wind Blown Dust Project Results & Status ENVIRON International Corporation and University of California, Riverside Dust Emission Joint Forum Meeting Las Vegas, NV November 16, 2004

Phase II Project Overview Develop improved general methodology based on Phase I recommendations and recent literature review Update gridded PM inventory of WB Dust for 2002 using the Inter-RPO regional modeling domain Develop of surface friction velocities and threshold friction velocities Develop improved emission flux relationships Improve vacant land characterization – Disturbance – Land use type – Reservoirs Conduct model performance evaluation

General Formulation for Emissions Estimation Dust = f(LULC,z 0,u *,u *th,SC) u * = f(u,z 0 ) u *th = f(z 0 ) z 0 = f(LULC)

Threshold Friction Velocities u *th determined from relations developed by Marticorena, et al, (1997)

Emission Rates Depends on soil type; based on results of Alfaro and Gomes (2001)

NLCD Summary

Dust Code3467 Land use categoryAg.GrassShrubsBarren Surface roughness (cm) Threshold friction Velocity (mile/h) Threshold wind velocity at 38m height (mile/h) Characteristics of Dust Categories

Soil Characteristics

Reservoir Characteristics All soils assumed loose, undisturbed Dust events limited to 10hrs/day – Sensitivity simulations conducted based on above assumptions Rain events: Dust re-initiated after set number of days dependent on soil texture, amount of rainfall and season

Number of days after rain event to re-initiate wind erosion Rainfall > 2 inches Rainfall < 2 inches Soil typeSpring/FallSummerWinter Sand Sandy Loam Fine Sand Loam Loam Silt Loam Sandy Clay Loam Clay Loam Silty Clay Loam Clay7510 Soil typeSpring/FallSummerWinter Sand Sandy Loam Fine Sand Loam Loam Silt Loam Sandy Clay Loam Clay Loam324 Silty Clay Loam Clay

Model Sensitivity Simulations Run a : – No limitation on dust event duration – All soils considered loose undisturbed Run b : – Dust events limited to 10 hrs/day – All soils considered loose undisturbed

Model Sensitivity Simulations Run c : – No limitation on dust event duration – Assume 10% of barren, grass & shrublands area is disturbed – Threshold velocity for grass & shrublands = 0.5 * undisturbed value – Threshold velocity for barren lands =.27 * undisturbed value Run d : – Dust events limited to 10 hrs/day for undisturbed soils – Assume 10% of barren, grass & shrublands area is disturbed – Threshold velocity for grass & shrublands = 0.5 * undisturbed value – Threshold velocity for barren lands =.27 * undisturbed value

Model Results Scenario a: no limit on duration; all soils loose, undisturbed

Model Results Scenario b: event duration <=10 hrs/day; all soils loose, undisturbed

Model Results Scenario c: no limit on duration; assume 10% disturbed area for grass, shrub, barren lands

Model Results Scenario d: event duration <= 10hrs/day for disturbed soils; assume 10% disturbed area for grass, shrub, barren lands

Dust Totals for WRAP States tons/year ScenarioWRAP StatesDomain Total (US only) a2,222,219 9,451,368 b1,310,120 5,228,818 c3,077,19611,098,731 d2,165,0966,876, ,240,2884,366,907

Annual PM10

Comparison of Monthly Dust Emissions

Annual PM10 from Ag Land for WRAP States

Annual PM10 from Grass Land for WRAP States

Annual PM10 from Shrub Land for WRAP States

Annual PM10 from Barren Land for WRAP States

Scenario b Annual PM10 from All Dust Categories for WRAP States

Scenario d Annual PM10 from All Dust Categories for WRAP States

2002 Annual PMC Scenario a: no limit on duration; all soils loose, undisturbed

2002 Annual PMC Scenario b: event duration <=10 hrs/day; all soils loose, undisturbed

2002 Annual PMC Scenario c: no limit on duration; assume 10% disturbed area for grass, shrub, barren lands

2002 Annual PMC Scenario d: event duration <=10 hrs/day; assume 10% disturbed area for grass, shrub, barren lands

2002 Annual PMC Scenario b: event duration <=10 hrs/day; all soils loose, undisturbed

2002 Seasonal PMC

Model Limitations Grid resolution – Coarse resolution of met data can’t resolve high wind events; wind gusts LULC and Soils data – LULC not detailed enough on a regional-scale – Soils data lacks depth of layers, moisture data Agricultural land adjustments – No agricultural data for Eastern states (prepared for WRAP & CENRAP regions only) – Data gaps in Ag Census

Model Performance Evaluation 1. Evaluate model results for reasonableness and accuracy – Compare predicted WB dust emissions near IMPROVE monitors with measured IMPROVE dust extinction (B dust ) 2. Enhancements to CMAQ to track WB and other dust – Evaluate model CMAQ model performance with and without WB dust emissions 3. Refined model performance evaluation using results of Etyemezian, et al. – For events characterized as wind blown dust events, determine whether dust model predicts impacts

2002 Coarse Mass

Seasonal Coarse Mass (2002)

Annual Fine & Coarse Mass (2003)

Model Performance Evaluation (1) Evaluate model results for reasonableness and accuracy Compare predicted WB dust emissions near IMPROVE monitors with measured IMPROVE dust extinction (B dust ) – Identify occurrences of: 1) Zero WB dust and near-zero B dust 2) Enhanced WB dust and near-zero B dust 3) No WB dust and elevated B dust 4) Enhanced WB dust and elevated B dust Modeled dust averaged over 5 x 5 block of grid cells centered on IMPROVE sites Daily averaged model results paired (in time & space) with monitored data Compare modeled PM with Bext dust – Bext dust = [FS] + 0.6[CM]

Model Performance Evaluation (1)

Model Performance Evaluation (2) Enhancements to CMAQ to track WB and other dust emissions separately Run CMAQ w/ and w/o WB Dust emissions Evaluate CMAQ model results with and with out WB dust emissions

Model Performance Evaluation (2) January, 2002

Model Performance Evaluation (2) July, 2002

Model Performance Evaluation (2)

Model Performance Evaluation (3) Refined model performance evaluation using results of Etyemezian, et al. For events characterized as wind blown dust events, determine whether dust model predicts impacts Model and measurements agree … – Analyze for trends – Systematic over- or under-prediction ? Model and measurements disagree … – Wind speed errors ? – Landuse type mischaracterization ? – Other ?  Analyses on-going based on DRI project results

Next Steps Complete Model Performance Evaluation (end of year) Address deficiencies in Ag data for the Eastern States – Assume constant crop canopy % – Develop generic crop calendars, crop canopy %, etc. – Collect detailed Ag data from Eastern States Re-run model w/ latest MM5 data Make use of 12-km resolution MM5 data Apply to small region for verification of methods, assumptions Apply transport fraction by county for air quality model applications