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Alternative Strategies for Evaluating Emission Potential and/or K-Factors: Portable Instruments

Alternative Strategies for Evaluating Emission Potential and/or K-Factors: Portable Instruments. Dr. J.A. Gillies Research Professor Division of Atmospheric Sciences Desert Research Institute Reno NV 89512. Alternative Strategies for Evaluating Emission Potential and/or K-Factors.

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Alternative Strategies for Evaluating Emission Potential and/or K-Factors: Portable Instruments

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  1. Alternative Strategies for Evaluating Emission Potential and/or K-Factors:Portable Instruments Dr. J.A. Gillies Research Professor Division of Atmospheric Sciences Desert Research Institute Reno NV 89512

  2. Alternative Strategies for Evaluating Emission Potential and/or K-Factors • Much discussion has centered on alternative strategies that may be able to provide model-independent estimates of source emission potential and K-factors. • Portable Emission Measurement Devices: PI-SWERL Wind Tunnels • What are these instruments capable of providing to the development and improvement of the Dust ID model?

  3. PI-SWERL in use at Williston Reservoir, British Columbia, Canada

  4. GBUAPCD Tunnel, Owens Lake, CA

  5. Guelph Wind Tunnel, Owens Lake, CA

  6. PI-SWERL/Wind Tunnels • These portable emission measurement devices offer a means to evaluate emission potential both spatially and temporally. • These devices provide essentially point measurements of PM10 emission potential of a surface, which if taken in sufficient coverage provide a reasonable estimate of the mean and variance of this surface property for the environmental conditions under which the tests were made.

  7. How does the small sampling footprint relate to the spatial magnitude and distribution of shear and emissions during dust events? • Up-scaling small scale measurements is always and issue. How can it be addressed? • Must obtain replicate measurements at multiple spatial scales. • A nested grid sampling scheme could be used to allow quantification of the spatial variability and the application of geostatisticalanalysis (e.g., semi-variogram analysis). • Geostatistical analysis will provide a scale measurement to indicate the measurements are no longer related by a spatial (length) scale.

  8. Semi-variance Lag distance beyond which the variance is random (unrelated) Lag Distance (m)

  9. Discussion Points • How is a the emission flux related to the saltation flux? (A critical assumption of the Dust ID model:there is a characteristic F/Q relationship for and area) Instrument Issues: Wind tunnels: the scale of the saltation process (i.e., the lengths associated with particle trajectories) in small cross section wind tunnels is compromised. PI-SWERL: are saltation-like processes present, or is it another abrasion-type force applied to the surface? In all small (and all but the biggest wind tunnels) the “F/Q” ratio is not the same as in the field. How they scale with each other or with the atmosphere could be instrument specific.

  10. PI-SWERL • PI-SWERL (and small wind tunnels) has been compared to the largest available field wind tunnel, and show good comparability.

  11. Discussion Points • Sediment supply: no device “delivers” sand in saltationas if it was coming from an unlimited upwind source. This imposes some amount of supply limitation on a test, which may not be the case in the field.

  12. Instruments for Measuring PM10 and Sand Flux • PI-SWERL: TSI DustTrak (PM10), Optical Gate Sensor (sand). • Wind Tunnels: Filter (PM10), TSI DustTrak (PM10) collection of all sediment at outlet (sand), sub-sampled with traps (sand)

  13. Issues: 1) Relationship between optical measurements and gravimetric equivalent. Range of Slope Coefficient: 1.02 to 2.14 (Yakima WA, Yuma AZ, Ft. Carson CO)

  14. Issues: 2) optical measurements (OGS) and mass flux equivalent. Development is on-going to relate the signal from the OGS sensor to particle size. Particle counts by size bin can (in theory) be related to mass flux assuming a particle size (volume, m3) and density (kg m-3) Requires calibration with known mass flux for confidence

  15. PI-SWERL/Wind Tunnels • K-factors • Can these devices be used to estimate K-factors for a given area equivalent to a DustID K-factor? • All the preceding arguments/observations are still valid. • K-factors have previously been developed using portable wind tunnels at Owens Lake.

  16. 1.00E+00 WO WF 1.00E-01 Gillette et al (1997) mean for 2000 mean for 2001 1.00E-02 median 2001 1.00E-03 ) -1 1.00E-04 F/q (m 1.00E-05 1.00E-06 1.00E-07 1.00E-08 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60 1.80 u (m/s) * F/q derived from Guelph Wind Tunnel 2003 default K-factors May-Nov Keeler Dunes, 2003 Central, 2003 North, 2003 South, 2003

  17. 1.00E+00 WO WF 1.00E-01 Gillette et al (1997) mean for 2000 mean for 2001 1.00E-02 median 2001 1.00E-03 ) -1 1.00E-04 F/q (m 1.00E-05 1.00E-06 1.00E-07 1.00E-08 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60 1.80 u (m/s) * F/q derived from Guelph Wind Tunnel 2003 default K-factors Dec-April Keeler Dunes, 2003 Central, 2003 North, 2003 South, 2003

  18. F/q derived from PI-SWERL F (avg. kg m-2 s-1)/(avg. particle counts s-1) Provides a Relative K-factor Could provide a mass flux based K-factor if particle counts can be replaced by kg m-1 s-1 Equivalency to full scale remains uncertain Can provide data on the variability of K as a function of time and space, which can be compared with DustID Ks to provide

  19. Applications of:PI-SWERL/Wind Tunnels • These instruments could be used to evaluate if an area identified as a potential emission source, which may require remediation, has emission levels that are (or are not) at levels that support this identification. • How?

  20. Applications of:PI-SWERL/Wind Tunnels Identifying/Confirming Areas for Treatment • Identify areas of the lakebed (from historical Dust ID records?) that have been identified as a source at levels that do not and do require remediation. • Develop a database of emission potential for those surfaces using PI-SWERL/WT.

  21. Applications of:PI-SWERL/Wind Tunnels Identifying/Confirming Areas for Treatment • This database provides a basis for comparison with a data set that consists of measurements that were taken for a surface that has either totally unknown emission properties or one that has already been identified at some level as a “surface of interest” for applying controls. • Do emissions from the unknown surface, checked on some time-frame (acknowledging temporal variability) exceed/not-exceed those of the reference surface(s) that are not targeted for control?

  22. Concluding Remarks/Challenges: PI-SWERL/Wind Tunnels These devices are tools that can be used to provide insight into the dynamic nature of the dust emission system at Owens Lake. They can quantify variability in emissions (F) and K, but variability is not accounted for in the DustID-based evaluation of emissions (the conditions are treated as being static over discrete time periods) Can they provide equivalent K-factors? The scale of determination is different. DustID calculates K based on receiving a time and space integrated concentration of PM10. Devices determine point measurements of K and then averages these values to provide a spatially averaged K. Can these be reconciled? Which is correct?

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