WRAP Wind Blown Fugitive Dust and Ammonia Emissions Updates WRAP Regional Modeling Center UC Riverside/ENVIRON Presented at RPO National Workgroup Meeting November 4 – 6, 2003 St. Louis, Missouri
Project Team Fugitive Dust • Gerard Mansell; ENVIRON • Martinus Wolf, Paula Fields; ERG • Jack Gillies; DRI • Mohammad Omary; UCR • Bill Barnard; MACTEC Engr. & Consulting • Michael Uhl; DAQM, Clark County, NV Ammonia • Mark Chitjian; UCR • Gerard Mansell; ENVIRON
Outline • Project Background & Overview • Literature Review • Estimation Methodology • Agricultural Considerations • Data Sources • Summary of Assumptions • Program Implementation • Results • Recommendations
Background and Overview of Project • Develop General Methodology to Facilitate Future Revisions and Control Strategy Development • Develop Integrated SMOKE Processing Modules for PM10 and PM2.5 Emissions Modeling • Develop PM10 and PM2.5 Emission Inventory Applicable to the Western Region
Overview of Technical Approach • Categorize Vacant Land Types • Identify Wind Tunnel Emission Factors • Develop Meteorological Data • Develop Threshold Wind Velocities, Wind Events, Precipitation Events • Apply Emission Factors to Vacant Land Categories
Literature Review • Portable field wind tunnels have been used to investigate particle entrainment thresholds, emission potentials, and transport of sediment by wind. • Major contributions of information on: • thresholds from Gillette et al. (1980), Gillette et al. (1982), Gillette (1988), Nickling and Gillies (1989); • emission fluxes from Nickling and Gillies (1989), James et al. (2001), Columbia Plateau PM10 Program (CP3), Houser and Nickling (2001). • Key information has also come from dust emission modeling (e.g., Alfaro et al., 2003) and desert soil characterization studies (e.g., Chatenet et al., 1996).
Wind Tunnel Study Results: Thresholds *(Gillette et al., 1980; Gillette et al., 1982; Gillette, 1988; Nickling & Gillies, 1989) * Comparison between modeled relationship of threshold friction velocity and aerodynamic roughness length and wind tunnel data.
Wind Tunnel Study Results: Emissions The emission flux as a function of friction velocity predicted by the Alfaro and Gomes (2001) model constrained by the four soil geometric mean diameter classes of Alfaro et al. (2003).
Wind Tunnel Study Results: Emissions as a function of texture Relations between the soil types deduced from aggregate size distributions of various desert soils and soil textural categories (Chatenet et al. 1996). The “gray” highlighted textural classes indicate the 4 sediment types; the arrows indicate the pathways linking these types to the other textures. These can be linked to the North American soil texture triangle.
Wind Tunnel Study Results: Emissions Comparison between model relationship for FS and CS sizes and the wind tunnel data of Nickling and Gillies (1989). Ten (out of 13) sites have a dust production potential similar to the FS model and one site (Mesa agricultural) is closely aligned with the CS model (after Alfaro et al., 2003).
Emission Rates by Soil Group for Stable Soils 0.035 0.03 0.025 Soil Group 1 Soil Group 2 0.02 Soil Group 3 Emission Factor (ton/acre/hour) Soil Group 4 0.015 Soil Group 5 0.01 0.005 0 20 - 24.9 25 - 29.9 30 - 34.9 35 - 39.9 40 - 44.9 45 - 49.9 50 - 54.9 10-m Wind Speed (mph)
Emission Rates by Soil Group for Unstable Soils 0.03 0.025 0.02 Soil Group 1 Soil Group 2 0.015 Soil Group 3 Emission Factor (ton/acre/hour) Soil Group 4 Soil Group 5 0.01 0.005 0 20 - 24.9 25 - 29.9 30 - 34.9 35 - 39.9 40 - 44.9 45 - 49.9 50 - 54.9 10-m Wind Speed (mph)
Agricultural Considerations • Non-climatic factors significantly decrease soil loss from agricultural lands • Similar approach to CARB, 1997 • Five “adjustment” factors simulate these effects: • Bare soil within fields • Bare borders surrounding fields • Long-term irrigation • Crop canopy cover • Post-harvest vegetative cover (residue)
Agricultural Adjustment Factor Development • New regional data collected for WRAP project: • Crop calendars with growth curves from Revised Universal Soil Loss Equation (RUSLE2) model • Residues remaining after harvest due to conservation tillage practices from Purdue’s Conservation Technology Information Center (CTIC) • Irrigation events from crop budget databases • Factors applied by county/crop type, crop management zones (CMZs)
Data Sources • Land Use/Land Cover (LULC) • Biogenic Emission Landcover Database (BELD3) • North American Land Cover Characteristics • National Land Cover Database (NLCD) • Soils Characteristics • State Soil Geographic Database (STATSGO) • Soil Landscape of Canada (SLC_V2) • International Soil Reference and Information Centre • Meteorological Data • 1996 MM5 36-km (Wind Velocity, Precipitation, Snow/Ice, Soil Temperature)
Land Use/Land Cover Data • BELD3 LULC Data
Meteorological Data • 1996 MM5 • 1996 Annual, hourly, gridded meteorology • 36-km horizontal resolution • 10-m wind speeds • Precipitation rates • Snow/ice cover flag • Soil temperature
Data Compilation for Land Use and Soil Types • Land use and soil texture aggregated to 12-km resolution • Major land use categories • Urban • Agricultural • Shrub and grasslands • Forest • Barren and Desert • Land use fractions from 1-km data retained as percentages • Dominate soil texture at 12-km resolution
Soil Texture Categorization • Standard soil types mapped to 5 major types for dust calculations • Silty Sand and Clay • Sandy Silt • Loam • Sand • Silt
Vacant Land Stability • Windblown dust emissions affected by soil stability • Stability determination based on land types • Urban lands may be stable or unstable
Urban Land Stability • Urban lands divided into core and boundary areas • Core = 92.67%; Boundary = 8.33% • Core urban areas: • 8 % unstable • 92% stable • Boundary urban areas: • 30% unstable • 70% stable
Reservoir Characteristics • Reservoirs characteristics based on stability • Stable = limited • Unstable = unlimited • Stable reservoirs are depleted within 1 hour • Unstable reservoirs are depleted within 10 hours • Reservoirs require 24 hours to recharge
Precipitation and Freeze Events • No dust emissions during rain events • Rainfall from MM5 at 36-km resolution • No dust emissions if snow/ice cover present • Dust emissions re-initiated: • 72 hours after rain • 72 hours after snow/ice meltdown • 12 hours after thaw
Vegetative Cover Adjustments • Vegetation cover reduces dust emissions • Methodology developed for bare soil • Emissions reduction factors developed from White (2000) • Vegetation density based on land use types
Summary of Assumptions • Threshold velocity = 20 mph • Vacant land stability • Urban lands • Dust reservoirs • Reservoir depletion and recharge times • Precipitation, snow and freeze events • Vegetation density
Program Implementation • Daily/Hourly Meteorological Data • State/County, Crop Management Zone, and Soil Type, For Each 12km Cell. • Area fractions For Each 12km Cell, and Land Use For Each Area Fraction. • Agricultural Adjustment Data • Emission Rates by Soil and Wind Speed Categories
Agricultural Input Data • County and CMZs for 12-km grid cells • Crop area percentages for 12-km cells • Barren, border and crop fractions for BELD3 crops • Long term irrigation factors by soil type • Irrigation fraction by county and crop • Tillage fractions by crop and county • Planting and harvesting dates by crop (crop calendars) • Crop canopy cover by crop (growth curves) • Residue cover
Sensitivity Simulation • Evaluate impact of threshold velocity and reservoir assumptions • Extend emissions factor relations to lower wind speeds • Relax reservoir recharge assumptions: • 6 hours between wind events • 24 hours after rain events • 24 hours after snow/ice meltdown • 6 hours after thaw
Recommendations • Methodology review and refinement • Current, detailed data to characterize vacant lands • Methodology validation with small-scale, high resolution domain • Comparison with other methodologies • Identification and evaluation of additional wind tunnel studies • Application to other domains, years