Effectiveness and Impacts of Dust Control Measures for Owens Lake (2020) / Chapter Skim
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2 Air Quality
2 Air Quality
Pages 25-44
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From page 25... ...
Earth's surface exerts a drag on wind flow that results in shear forces capable of lifting and transporting sediment particles on the surface once the threshold wind velocity for that surface has been exceeded. Natural turbulence in the atmospheric boundary layer at the surface, caused by physical obstructions and convective overturn, results in wind gusts and lulls that often vary significantly from mean wind speeds.
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From page 26... ...
NOTES: The arrows on the left represent relative wind speeds and show the logarithmic decrease of velocity near the surface. Larger particles and aggregates move in creep mode, fine– and medium sand–sized particles move in saltation mode, and smaller particles enter true suspension and are transported away from the source by the wind.
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From page 27... ...
Dust control strategies such as shallow flooding take advantage of this seasonality of potential dust production, and are typically only deployed from October 16 to June 30. AIR QUALITY MONITORING REQUIREMENTS Title 40 of the Code of Federal Regulations (CFR)
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From page 28... ...
, so a 24-hour sample would not fully capture the magnitude of the event, or the relationship to the direction or speed of the wind. Sensors located next to the PM10 monitors measure wind speed and direction; the resulting information could be used to estimate the direction of the PM10 sources relative to the 1 A method for measuring the concentration of an air pollutant in the ambient air that has been designated as an equivalent method in accordance with 40 CFR 53.
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From page 29... ...
AIR QUALITY FIGURE 2-2 Locations of PM10 monitors and meteorological stations around Owens Lake.
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Additional meteorological sites support application of the Owens Lake Dust Identification Model ("Dust ID Model") , which is a tool for identifying dust control areas on the lakebed (GBUAPCD, 2016a)
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From page 31... ...
Monitoring data show the number of exceedances has steadily decreased since 2000 (see Table 2-1) because of mplementation i TABLE 2-1 Exceedances of the PM10 NAAQS at Monitors around Owens Lake from 2000 to 2019 Average Maximum Area Covered by DCMs Exceedance Exceedance Exceedance Day Year (% of lakebed)
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From page 32... ...
Careful study of the drivers of variability will be critical to management of PM10 control practices in the future. FIGURE 2-4 PM10 observations at the Keeler monitoring site from 1993 to 2018 showing a decrease in the percentage of exceedance days over time at this one location.
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From page 33... ...
However, the patterns of decrease differed between the sites: At Dirty Socks, greater reductions in PM10 concentrations occurred from 2000 to 2017 at increased wind speed, while at Keeler those reductions varied less with wind speed. An understanding of the processes that govern this behavior -- informed by more sampling with distributed sensors (Li et al., 2019)
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From page 34... ...
Estimation of PM10 emissions based on surrogate sand flux measurements involves the use of a semi-empirical relationship that relies on the horizontal movement of particles, whose sizes include diameters greater than 10 µm. The link between saltation and the emission of fugitive dust containing PM10 may be approximated by Fa ∼Kq (Equation 2-1)
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From page 35... ...
across the surface. The Cox Sand Catcher is a passive device used to capture samples of windblown, sand-sized particles of dust at a specific height above the surface.
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From page 36... ...
Use of measured horizontal sand flux to estimate PM10 emissions leads to uncertainty because of the spatial and temporal variability in surface conditions, which are not well represented by a constant K factor (Klose et al., 2019; Kok et al., 2014)
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From page 37... ...
for characterizing local environmental conditions. In addition, there should be a transition period during which the deployment of a network of PM10 sensors overlaps with the use of the current network of Sensits and Cox Sand Catchers to determine relationships between the historic sand flux measurements and more directly determined PM10 emissions.
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From page 38... ...
With emission controls established by 2017, Figure 2-9 illustrates that, based on Dirty Socks monitoring data, the dominant source regions are primarily in the south with winds greater than 10 m/s leading to high concentrations, suggesting the importance of off-lake sources. These results, although based on limited data, suggest that control strategies will need to place greater emphasis on off-lake sources to achieve attainment of NAAQS for PM10.
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. Concentration distributions vary with wind direction, and concentration magnitudes increase rapidly with wind speed.
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From page 40... ...
CALPUFF was also updated to allow for more finely resolved emissions inputs to reflect the rapidly changing emissions estimated from sand flux measurements. Critical inputs into the air quality modeling include the meteorology and the emission flux.
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From page 41... ...
The evaluation results of the model presented in Richmond (2019) focused on days for which the measured average concentrations were greater than 150 µg/m3, based on the assumption that good performance of a dispersion model for predicting high concentration days lends credibility to the model's ability to predict NAAQS attainment.
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From page 42... ...
for characterizing local environmental conditions. In addition, there should be a transition period during which the deployment of a network of PM10 sensors overlaps with the use of the current network of Sensits and Cox Sand Catchers to determine relationships between the historic sand flux measurements and more directly determined PM10 emissions.
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From page 43... ...
Conclusion: The modeling conducted as part of the 2016 SIP would be improved with increased evaluation and uncertainty analysis, as suggested by the National Research Council report Models in Environmental Regulatory Decision Making (NRC, 2007)
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