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Quantifying Particulate Matter Emissions from Wind Blown Dust Using Real-time Sand Flux Measurements

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Title: Quantifying Particulate Matter Emissions from Wind Blown Dust Using Real-time Sand Flux Measurements


1
Quantifying Particulate Matter Emissions from
Wind BlownDust Using Real-timeSand Flux
Measurements
  • Duane Ono Scott Weaver,
  • Great Basin Unified Air Pollution Control
    District
  • Ken Richmond, MFG, Inc.
  • April 2003
  • US EPA Emission Inventory Conference
  • San Diego, California

2
Two Methods to EstimatePM-10 Emissions Due
toWind Blown Dust
  • AP-42 method for Industrial Wind Erosion (Section
    13.2.5)
  • Dust ID method developed at Owens Lake

3
AP-42 PM-10 Emissions
  • e PM-10 emission factor g/m2/yr
  • k 0.5 for PM-10
  • Pi erosion potential corresponding to the ith
    period
  • N number of disturbances per year
  • Pi 58(ui- ut)2 25(ui- ut) g/m2/period
  • Pi 0, for ui lt ut
  • ui Friction velocity for the fastest mile
    m/s
  • ut Threshold friction velocity

4
Dust ID Methodbased on Shao, et al., 1993
5
Dust ID Method
  • Fa Kf x q
  • Fa PM-10 emissions g/cm2/hr
  • Kf K-factor
  • q sand flux at 15 cm g/cm2/hr

6
Owens Lake Dust ID Monitoring Network135 sand
flux sites6 PM-10 TEOM sites13 10-m met
towersUpper air profilerTime-lapse camera
sitesDust observer sites
7
Sand Flux Monitors
  • Cox Sand Catcher - Collects saltation-size
    particles
  • Sensit - Electronically records sand flux.

8
Sensits Cox Sand Catcher
9
Sensit Reading vs. Sand Catch
10
PM-10 Monitors Sites
11
K-factor Calculations
  • Kf Hourly K-factor
  • Ki Initial K-factor (5 x 10-5)
  • Cobs. Monitored hourly PM-10
  • Cbac. Hourly background PM-10
  • Cmod. Modeled PM-10 at monitor site

12
Dust Storm at Owens Lake
13
VISIBLE DUST PLUMES SAND FLUXObserved dust
plume locations corresponded to the hotspot areas
identified by the sand flux monitoring
network.Example Storm Feb. 6-8, 2001(52 hour
total)
14
PM-10 concentrations and sand flux were monitored
for 30 months at Owens Lake.
15
Hourly Storm Average Kf for the South Area
16
Temporal Spatial K-factors  

17
Univ. of Guelph Wind Tunnel
18
Comparison of Wind Tunnel Dust ID K-factors
19
Comparison of Hourly Monitored and Modeled PM-10
at Shell Cut, May 2-3, 2001
20
Daily PM-10 Emissions
21
Dust ID vs AP-42 PM-10 Emission Estimates
22
Owens LakePM-10 Emissions
  • Peak Daily PM-10 7,200 tons
  • Annual PM-10 79,200 tons
  • Dust ID Period July 2000 - June 2001.

23
Conclusions
  • PM-10 emissions due to wind erosion were found to
    be proportional to the saltation flux and could
    be estimated from measured sand flux.
  • Proportionality factors, or K-factors could be
    derived by comparing monitored PM-10
    concentrations to modeled values using the
    measured sand flux with an initial K-factor.
  • Average K-factors were found to vary spatially
    and temporally at Owens Lake.
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