A Simple Metric, Total PM10:Total Wind Power Density, to Quantify Changes in Dust Emission from Areas of Interest as a Function of Environmental Change

The flux of wind-driven dust emissions from a susceptible area is determined by a complex relation between the driving force of the wind and the emissivity of the surface.  This relation is also modulated by the availability of sand-sized particles available for saltation, the roughness of the surface, and environmental conditions related to moisture, i.e., soil moisture and relative humidity.  The flux (F, µg m^-2 s^-1) of dust-sized particles from the surface scales non-linearly with the shear stress (τ, N m^-2, or shear velocity u_*, m s^-1 [τ=ρu_*², where ρ is fluid density]) created by the wind flowing over the surface.  Shear stress or shear velocity are not easily measured without the use of multiple instruments to characterize the vertical gradient of wind speed; vertical flux of particles requires measurement of vertical gradient of particle concentration or application of the eddy covariance method.  Here we describe a simple but effective metric to track changes through time due to physical alteration of a surface or due to changes in the environment.  The metric is based on measuring mean hourly concentrations of particulate matter, e.g., PM₁₀ (µg m^-3) and mean hourly wind power density (WPD=0.5×ρ×A×wind speed³, W m^-2), which quantifies the power in the moving air.  A is area, that we arbitrarily set at 1 m².  These hourly values are individually summed over a period of interest (e.g., monthly) to calculate the ratio value of total PM₁₀:total WPD.  These data can also be filtered to isolate the effect of the source area emissions on the receptor site, for example, by wind direction range.  Tracking this metric on a monthly basis across multiple years at the Oceano Dunes State Vehicular Recreation Area has allowed for the characterization of the change in dust (PM₁₀) production due to dust control measures (i.e., hectares of dust control) being placed onto the dunes, as well as the changes to the dust emission system during a period in 2020 when the area was left relatively undisturbed due to restrictions due to COVID-19.  We suggest, and demonstrate, that this method can be broadly applied, is effective in quantifying change, and cost-effective.