AirWare
air quality assessment & management
Reference and User Manual
AirWare   On-line Reference Manual
  Release Level 6.2
  Release Date 2013 09
  Revision Level 1.0
Last modified on:   Monday, 9-Sep-13 21:17 CEST

Dust entrainment: model basics

The dust entrainment model is a distributed, (arbitrary resolution) dynamic (hourly time step) model to predict the wind erosion and (re-)entrainment of particles from natural surfaces, primarily unvegetated or sparsely vegetated soils.

The DUST model produces dynamic (hourly) emission matrices (g/s/km2), that together with any anthropogenic emission data for point, line and area sources, provide input to the respective transport, dispersion, and deposition model used. In addition to the threshold friction velocity approach (e.g., Draxler et al. 2001) that uses geomorphology and soil properties, is also considers vegetation coverage and soil moisture as estimated by the MM5 prognostic meteorological model. MM5 is also used to forecast wind velocities, and a Weibull function to generate distributed wind speeds around the predicted hourly mean wind speed.

For specific form of landuse, special "sub-models" are used:

  • Area sources (cities, industrial areas)
  • Area sources (surface mining)
  • Line sources (unpaved roads)
The dust entrainment model estimates non-pyrogenic dust emission from natural surfaces as a function of primarily wind speed, land cover/vegetation, soil characteristics, and soil moisture, The total Dust PM10 emission [g/s/km2] is calculated as the product of
  • WindFactor, (a non-linear threshold function)
  • soil type (the wind thresholds oare soil type dependent)
  • ErosionFactor (erodibility), combining vegetation index (bare soil fraction), soil moisture,
  • a calibration factor (multiplier)
Wind Factor

The wind factor is computed from average hourly (monitored or generated by MM5) ground level wind speed (m/s) using a Weibull function to generate a distribution of wind speeds and their relative frequency around that mean, as follows:

      for v>TR: f(v) = (v - TR) **EXP
      for v<TR: f(v) = 0
where
  • TR is the (user-defined) Wind Threshold,
  • EXP is the (user-defined) Exponent

     windFactor = sum over all frequency classes of ( f(v)*frequency(v) )
     frequency(v) = (k/c) * pow( (v/c), (k-1) ) * exp( -pow( (v/c), k) )
where The Weibull distribution is a continuous probability distribution, named after Waloddi Weibull, who described it in detail in 1951. The shape parameter k is used defined s part of the model calibration. A user defined multiplier can be used to scale the original, hourly average wind speed. to account for the open-ended nature and improve computational efficiency, a maximum wind speed cutoff value defined in multiples of the average wind speed. Erosion is based on a minimum wind speed threhold, that depends on the soil type distribution within each grid cell, see below.

Soil type

Soil distribution in each model grid cell (percentage of coarse, medium, and heavy soil) is based on FAO soil map . The soil type defines the minimum wind speed for erosion.

Erosion Factor

The erosion factor is a multiplier that limits the maximum possible erosion defined by wind speed and the exponential threshold functions of the wind speed (with individual thresholds for three soil fractions).

The elements of the erodibility factor include:

  • Soil moisture: using a linear threshold function:
    • the soil moisture dependent scaling factor of erodibility is zero above the soil moisture threshold value (expressed as a percentage of water in the uppermost 20 cm soil layer as estimated by MM5).
    • between the threshold and zero soil moisture erodibility increases linearly with a user defined slope.
        soil moisture > SMT % => sm_factor = 0
        soil moisture < SMT % => sm_factor = (SMT - soil_moisture) * SMM
        where SMT is the soil moisture threshold and SMM is the soil moisture multiplier
  • Vegetation index: depending on data availability this can be derived from land use data, NDVI (e.g., from the MODIS satellite platform), or VCF: For the vegetation index, the DUST model uses Vegetation Continuous Fields, http://glcf/umd.edu/data/vcf, http://www.landcover.org.

    The Vegetation Continuous Fields collection contains proportional estimates for vegetative cover types: woody vegetation, herbaceous vegetation, and bare ground.

  • Terrain roughness: this is defined as the normalized difference in elevations (based on the 30m DEM) within any 1 km2 grid cells; with minimum of 1 (completely flat), the maximum elevation difference within a grid cell has a user defined value, that acts as a divider on the erosion factor: e.g., a value of 1.25 would reduce erosion in the roughest cell by 20% compared to any flat one.

    Terrain roughness and soil moisture are optional, the default (if no data are available) ignores their possible impacts.


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