Application of a Combined Measurement and Modeling Method to Quantify Windblown Dust Emissions from the Exposed Playa at Mono Lake, California

Particulate matter <= 10 mu m (PM(10)) emissions due to wind erosion can vary dramatically with changing surface conditions. Crust formation, mechanical disturbance, soil texture, moisture, and chemical content of the soil can affect the amount of dust emitted during a wind event. A refined method of quantifying windblown dust emissions was applied at Mono Lake, CA, to account for changing surface conditions. This method used a combination of real-time sand flux monitoring, ambient PM(10) monitoring, and dispersion modeling to estimate dust emissions and their downwind impact. The method identified periods with high emissions and periods when the surface was stable (no sand flux), even though winds may have been high. A network of 25 Cox sand catchers (CSCs) was used to measure the mass of saltating particles to estimate sand flux rates across a 2-km(2) area. Two electronic sensors (Sensits) were used to time-resolve the CSC sand mass to estimate hourly sand flux rates, and a perimeter tapered element oscillating microbalance (TEOM) monitor measured hourly PM(10) concentrations. Hourly sand flux rates were related by dispersion modeling to hourly PM(10) concentrations to back-calculate the ratio of vertical PM(10) flux to horizontal sand flux (K-factors). Geometric mean K-factor values (K(f)) were found to change seasonally, ranging from 1.3 x 10(-5) to 5.1 x 10(-5) for sand flux measured at 15 cm above the surface (q(15)). Hourly PM(10) emissions, F, were calculated by applying seasonal K-factors to sand flux measurements (F = K(f) x q(15)). The maximum hourly PM10 emission rate from the study area was 76 g/m(2).hr (10-m wind speed = 23.5 m/sec). Maximum daily PM(10) emissions were estimated at 450 g/m(2).day, and annual emissions at. 1095 g/m(2).yr. Hourly PM(10) emissions were used by the U.S. Environmental Protection Agency (EPA) guideline AERMOD dispersion model to estimate downwind ambient impacts. Model predictions compared well with monitor concentrations, with hourly PM(10) ranging from 16 to over 60,000 mu g/m(3) (slope = 0.89, R(2) = 0.77).