Dust ID Field Manual 

Draft - January 24, 2007 

DRAFT 

GBUAPCD, 2007_Dust ID Field Manual-FINAL DRAFT.doc 
Dust ID Field Manual 

Draft - January 24, 2007 

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GBUAPCD, 2007_Dust ID Field Manual-FINAL DRAFT.doc 
Dust ID Field Manual 

Draft - January 24, 2007 

Owens Lake Dust ID 

Field Manual

Table of Contents 

1. Program Overview ..................................................................... 1 

1.1 Introduction......................................................................... 1 

1.2 Locating Dust Source Areas..................................................... 1 

1.3 Monitored Exceedances.......................................................... 2 

1.4 Modeled Exceedances............................................................ 2 

1.5 Sand Flux Measurements......................................................... 3 

1.6 Dust ID Field Manual Content................................................... 3 

2. Protocol for Measuring Sand Flux Rates and Operation of the Sensit and Cox 

2.1 Sand Catcher (CSC) Network................................................... 6 

2.2 Objective........................................................................... 6 

2.3 Methods and Instrumentation................................................... 6 

2.4 Operating Procedures............................................................. 7 

2.5 Data Collection.................................................................... 8 

2.6 Chain of Custody.................................................................. 8 

2.7 Quality Assurance................................................................. 9 

2.8 Calculating Hourly Sand Flux................................................... 9 

2.9 Sensit Calibration and Data Analysis........................................... 10 

2.9.1 Sensit Calibration Check................................................... 10 

2.9.2 Replacing Missing Sand Catch............................................ 10 

2.9.3 Replacing Missing Sensit Data............................................. 10 

3. Protocol for Measuring Ambient PM10 and Meteorological Conditions............ 17 

3.1 Objective............................................................................. 17 

3.2 Methods and Instrumentation for PM10 and Meteorological Data.......... 17 

3.3 Operating Procedures, Instrument Calibration and Quality Assurance..... 17 

3.4 Data Handling and Data Access Via Modem.................................. 17 

4. Protocol for Observing and Mapping Source Areas and Dust Plume Paths...... 18 

4.1 Objective............................................................................. 18 

4.2 Methods and Instrumentation..................................................... 18 

4.2.1 Mapping Dust Source Areas from Off-Lake Observation Sites....... 18 

4.2.2 Video Cameras................................................................ 18 

4.2.3 Mapping Using GPS......................................................... 19 

4.2.3.1 ‘Trigger’ Levels for Initiating Field Inspections & GPS Surveys 19 

4.2.3.2 GPS Mapping Procedures.............................................. 19 

4.2.4 Using Sand Flux Monitors to Map Source Area Boundaries........... 21 

4.3 Composite Dust Source Map Development..................................... 21 

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5. Protocol for Determining K-factors and PM10 Emission Rates...................... 23 

5.1 Objective.............................................................................. 23 

5.2 Method for Determining PM10 Emissions and New K-factors................ 23 

5.2.1 PM10 = Sand Flux x K-factor................................................ 23 

5.2.2 Default Temporal and Spatial Storm-average K-factors................. 23 

5.2.3 Method to Determine Sand Flux from Areas with Implemented Dust 

 Control Measures (DCM)................................................... 23 

5.2.4 New Seasonal Cut-points.................................................... 24 

5.2.5 Using CALPUFF Modeling System to Generate New K-factors....... 24 

5.2.6 Screening Hourly K-factors................................................ 24 

 

5.3 Temporal and Spatial Event-specific K-factors................................. 26 

5.3.1 Event-Specific K-factors.................................................... 26 

5.3.2 Temporal & Spatial 75-Percentile K-factors.............................. 26 

5.3.3 Default K-factors............................................................. 26 

6. Protocol for Dispersion Modeling....................................................... 28 

6.1 Overview of Modeling Procedures and Rationale for Model Selection..... 28 

6.2 Meteorological Data Set Construction........................................... 28 

6.3 CALPUFF Options and Application.............................................. 29 

6.4 Background PM10 Concentrations................................................ 31 

6.5 Area Source Characterization..................................................... 32 

6.6 Estimation of PM10 Emissions.................................................... 33 

6.7 Simulation of Shoreline Concentrations......................................... 33 

7. Owens Lake Safety and Training Program 

7.1 Objectives........................................................................... 37 

7.2 Safety Requirements............................................................... 37 

7.3 Reporting Procedures for Working on the Lake and Contacts............... 37 

7.4 Snowy Plover Training and other Wildlife Protection Procedures.......... 39 

Appendix A – Owens Lake Settlement Agreement (December 4, 2006) 

Appendix B – Supplemental Control Requirements for the 2003 RSIP 

List of Tables 

Table 5.1 Wind Directions for the Initial K-factor Screen................................ 25 

Table 5.2 Default Spatial and Temporal K-factors for the Dust ID Model............. 27 

List of Figures 

Figure 1.1 Owens Lake Dust ID monitoring network..................................... 5 

Figure 2.1 Photo of sand flux monitoring site at Owens Lake........................... 12 

Figure 2.2 Diagram of the Cox Sand Catcher (CSC)...................................... 13 

Figure 2.3 Photo of CSC with Inner Sampling Tube Removed.......................... 13 

Figure 2.4 Example of Linearity Between CSC Mass and Sensit Readings............ 13 

Figure 2.5 Sensit Height Indicator Tool used to set sand flux inlets at 15 cm ......... 14 

Figure 2.6 CSC and Sensit Field Documentation Form................................... 15 

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Figure 2.7 Lab Form for sand catch mass measurement................................... 16

Figure 4.1 Example of dust plume maps and total sand catch............................ 22

Figure 6.1 Model Domain and 1-km Mesh Size Terrain (m)............................. 34 

Figure 6.2 Area Source Configuration Using 250-m x 250-m Cells..................... 35 

Figure 6.3 Dust ID Model Receptor Locations.............................................. 36 

Glossary of Terms and Symbols

AIRS US Environmental Protection Agency’s Aerometric Information 

and Retrieval System 

ATV All-Terrain Vehicle 

APCO Air Pollution Control Officer 

BACM Best Available Control Measure 

BACT Best Available Control Technology 

CAAA Clean Air Act Amendments of 1990 

CALMET A meteorological preprocessor program for CALPUFF. 

CALPUFF An air pollution model 

CARB California Air Resources Board 

CSC Cox Sand Catcher, a passive sand flux measurement device. 

DCA Dust Control Area 

DCM Dust Control Measure 

Dust ID Program Owens Lake Dust Source Identification Program 

EIR Environmental Impact Report 

Event-specific Kf Weighted-average of hourly K-factors for a dust event, weighted 

by the hourly PM10 concentration 

Exceedance Modeled or monitored PM10 > 150 μg/m3 at the shoreline 

FTEE Full-time equivalent employee 

GBUAPCD Great Basin Unified Air Pollution Control District 

GIS Geographic Information System 

GPS Global Positioning System 

KE Kinetic energy 

K-factor Proportionality constant for sand flux and PM10 emissions, Kf 

LADWP City of Los Angeles Department of Water and Power (also City) 

m3 cubic meter 

met meteorological 

mg milligram 

MSM Most Stringent Measure 

NAAQS National Ambient Air Quality Standards 

NEAP Natural Events Action Plan 

OVPA Owens Valley PM10 Planning Area 

PC Particle count 

PM10 Particulate matter less than 10 microns aerodynamic diameter 

QA Quality Assurance 

RASS Radio Acoustic Sounding System 

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RSIP Great Basin APCD 2003 Owens Valley PM10 Planning Area 

Revised State Implementation Plan 

Sensit An electronic sand motion detector. 

Settlement Agreement 2006 Settlement Agreement between LADWP and GBUAPCD 

Storm-average Kf Arithmetic average of hourly K-factors for a dust event 

SCR Supplemental Control Requirements of the 2003 SIP 

SFM Sand flux monitor 

TEOM Tapered-Element Oscillating Microbalance, measures PM10. 

USEPA United States Environmental Protection Agency 

USGS US Geological Survey 

WD Wind direction 

2003 SIP Great Basin APCD 2003 Owens Valley PM10 Planning Area 

Revised State Implementation Plan 

μg microgram

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Owens Lake Dust Source 

Identification Program Field Manual 

1. Program Overview 

1.1 Introduction 

The objective of the Owens Lake Dust Source Identification (Dust ID) Program is to 

identify dust source areas at Owens Lake that can cause or contribute to violations of the 

National Ambient Air Quality Standards (NAAQS) for PM10. The Dust ID Program is a 

long-term monitoring program that is intended to identify dust source areas for control 

under the provisions of the Supplemental Control Requirements (SCR) in the 2003 

revised Owens Valley PM10 State Implementation Plan (RSIP) and the 2006 Owens Lake 

Settlement Agreement (Settlement Agreement). The text of the Settlement Agreement 

and SCR provisions is included in the appendices to this document. 

The RSIP and Settlement Agreement require the City of Los Angeles Department of 

Water & Power (City) to control all sources of wind blown dust from the lake bed of 

Owens Lake that cause or contribute to an exceedance of the PM10 NAAQS at the 

historic shoreline (3,600-foot contour line). Based on dust events that occurred between 

January 2000 and July 2006, 43 square miles of the lake bed were found to cause or 

contribute to NAAQS violations. Dust controls are required to be implemented on 30 

square miles of the lake bed by December 31, 2006, and an additional 13 square miles by 

April 1, 2010. 

Provided that these control measures are implemented in accordance with the RSIP and 

Settlement Agreement, the District will suspend making determinations to control 

additional dust source areas from December 4, 2006 until May 1, 2010. During this 

period, all monitoring, modeling and observations will continue as described in this Dust 

ID Field Manual. Data and information collected during this period will be used to 

determine any control requirements for Study Areas as described in the Settlement 

Agreement, and to advise the City on any monitored dust emissions from the lake bed 

and surrounding areas. If any new lake bed dust source areas are identified from data 

collected after April 1, 2010, they will be subject to dust control requirements as provided 

for in the Settlement Agreement and any future revisions to the Owens Valley PM10 State 

Implementation Plan. 

1.2 Locating Dust Source Areas 

A network of sand flux samplers, PM10 monitors, meteorological towers and remote 

camera sites will be used to monitor and locate dust source areas at Owens Lake. Figure 

1.1 shows a map of the Dust ID network at Owens Lake. As configured in 2003, the 

Dust ID network included: sand flux monitors at 136 lake bed sites at 1-km spacing, 7 

PM10 monitors, 13 met towers, 8 observation sites, and 10 time-lapse cameras at 7 sites. 

At the discretion of the Air Pollution Control Officer, additional sand flux, PM10 and met 

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sites will be added as necessary to collect information that can be used to monitor and 

model the impact from new areas that may become emissive on the lake bed. (See 

Appendix A, SCR - Conditions.) 

The automated monitoring network will be augmented with information from observers 

who will map dust source locations from off-lake sites when dust events take place 

during normal work hours. These maps will be used to help document source areas that 

may be outside the sand flux network or that may be within the network, but missed by 

the samplers. Field personnel will inspect active source areas and map the source area 

boundaries using a GPS (Global Positioning System) as conditions allow. Data collected 

from the sand flux network, visual mapping and GPS surveys will be included in a 

Geographic Information System (GIS) database for mapping and analysis. Maps 

generated using these different methods will be compared qualitatively to help delineate 

source area boundaries. 

 1.3 Monitored Exceedances 

Analysis of hourly PM10 concentrations at shoreline and off-lake monitoring sites may 

show that lake bed source areas cause or contribute to PM10 exceedances. Monitoring of 

PM10 concentrations will be done using US EPA-approved monitors. Currently, hourly 

PM10 readings are obtained using TEOM (Tapered-Element Oscillating Microbalance) 

PM10 monitors manufactured by R&P, Inc. If a PM10 exceedance is monitored, PM10

concentrations will be paired with the local wind direction for each hour of that event to 

determine if lake bed source areas caused or contributed to the exceedance. 

Twenty-four hour average PM10 monitor concentrations will be adjusted for winds 

coming from the direction of the lake to the monitor (from-the-lake) and from directions 

not from the lake to the monitor (non-lake). PM10 concentrations during any hour with 

winds from a non-lake wind direction will be assumed to have an average background 

concentration of 20 μg/m3 and from-the-lake wind directions will be given their hourly 

value. If the adjusted 24-hour average is greater than 150 μg/m3

, then an exceedance will 

have been monitored from a lake bed source or sources. (See Appendix B, SCR - Section 

1.1.) 

If a lake bed source area causes or contributes to an exceedance, hourly PM10

concentrations and wind directions will be reviewed to see if a new source area (or areas) 

is associated with that exceedance. If sand flux data are available that show erosion 

activity in the direction of a new source area, this event will also be modeled as described 

in the air quality modeling protocol. If the PM10 monitor data indicate that a new source 

area caused or contributed to an exceedance, dust control measures (DCMs) may be 

required under the provisions of the Settlement Agreement or current SIP. 

1.4. Modeled Exceedances 

Air quality modeling will be performed with the CALPUFF modeling system or other US 

Environmental Protection Agency (US EPA) approved modeling method. At least once a 

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year, the Dust ID information will be examined and the model will be run to determine if 

there were any modeled shoreline exceedances since the period covered by the last model 

run. PM10 emissions for the model will be based on hourly sand flux measured at lake 

bed sites and spatial and temporal factors derived using the empirical relationship 

between sand motion on the lake bed and measured PM10 values. CALPUFF will be run 

using the following equation to estimate emissions and to model PM10 impacts at the 

shoreline: 

Equation 1.1 

PM10 = Kf × q 

where, 

 q = Sand flux measured at 15 cm above the surface [g/cm2/hr] 

Kf = K-factor, empirically-derived ratio of the PM10 emission flux to the 

sand flux at 15 cm. 

The ratio of PM10 to sand flux (Kf) is referred to as the K-factor. The initial Dust ID 

program results showed that K-factors could be derived empirically by comparing model 

predictions to monitored PM10 concentrations. Initial studies also showed that average 

K-factors can vary spatially and seasonally at Owens Lake. Default K-factors will be 

used with Equation 1.1 to estimate hourly PM10 emissions unless new K-factors are 

generated from future dust events following the modeling procedures in this field manual. 

If the CALPUFF model results indicate that a new lake bed source area caused or 

contributed to an exceedance at a shoreline location, dust controls may be required under 

the provisions of the Settlement Agreement or the current SIP. (See Appendix A, Section 

11) 

1.5 Sand Flux Measurements 

Sand flux is measured using a combination of Cox Sand Catchers (CSC’s) and Sensits. 

CSC’s are sand collection devices that provide a mass collection amount for a certain 

time period (about 1 to 3 months), and Sensits are electronic sand motion detectors used 

to time-resolve the collected mass to estimate hourly sand flux rates. The sand flux rate 

is applied to the area represented by the sand flux sampling site, which may vary in size 

and shape depending on the source area delineated by field observations. 

1.6 Dust ID Field Manual Content 

Section 2 of this Field Manual describes the methods and instrumentation that will be 

used to monitor sand flux with Sensits and CSC’s on the lake bed. Section 3 provides a 

brief description of the PM10 and meteorological monitoring network that will be used to 

monitor PM10 exceedances, develop K-factors and to call public health advisories. 

Section 4 describes methods that will be used by visual observers and field personnel to 

map lake bed dust source areas and delineate boundaries using GPS. Section 5 explains 

the procedures for developing K-factors using air quality modeling and monitoring data 

Section 6 provides the protocol for dispersion modeling. Appendix A contains the 

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Owens Lake Settlement Agreement, which applies to data collected from July 2006 

through April 1, 2010. Appendix B contains the provisions of the Supplemental Control 

Requirements that was approved with the RSIP. 

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Figure 1.1 Owens Lake Dust ID monitoring network. 
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Draft - January 24, 2007 

2. Protocol for Measuring Sand Flux Rates and Operation of the Sensit and 

Cox Sand Catcher Network 

2.1 Objective 

Sand flux measurements will be used as a surrogate to estimate PM10 emissions coming 

off the lake bed. The objective of the sand flux measurements is to provide an hourly 

emissions estimate for all active source areas on the lake bed. 

2.2 Methods and Instrumentation 

Sand flux will be measured with Sensits and Cox Sand Catchers (CSCs). Co-located 

Sensits and CSCs are used to measure hourly sand flux rates at different locations on the 

lake bed. The 2003 Sensit/CSC network locations are shown in Figure 1.1. The 

instruments are placed with their sensors or inlets positioned 15 cm above the surface. 

Sensits are electronic sensors that measure the kinetic energy or the particle counts of 

sand-sized particles as they saltate, or bounce, across the surface. Sensits are used to 

time-resolve the CSC mass to provide hourly sand flux rates. 

Figure 2.1 shows a Sensit suspended above the ground on the right, and a CSC in the 

ground to the left. The photo was taken at a site that was used to test the accuracy of 

Sensits and CSCs before the Dust ID Program began. The battery powered Sensits are 

augmented with a solar charging system. A datalogger records 5-minute Sensit data 

during active saltation periods. Data collection is triggered by particle count activity and 

continues until particle counts are zero for an hourly period. Each datalogger has a radio 

transmitter that sends Sensit data to the District’s Keeler field office once a day to 

provide updates on erosion activity at each site. These daily updates are used to alert field 

personnel to active source areas for possible Global Positioning System (GPS) mapping 

and inspection. Daily transmission of the data may be temporarily suspended if the solar 

battery power is low due to extended days of cloud cover. 

CSCs are passive collection instruments that capture windblown, sand-sized particles. 

These instruments were designed and built by the District as a reliable instrument that 

could withstand the harsh conditions at Owens Lake. CSCs have no moving parts and can 

collect sand for a month or more at Owens Lake without overloading the collectors. Field 

personnel visit CSC sites to measure the mass of the collected sand catch. A diagram of 

the CSC is shown in Figure 2.2. Not shown in the diagram is an internal sampling tube 

that can be seen in the photo in Figure 2.3. The internal sampling tube is removed from 

the PVC casing to measure the sand catch sample. The lengths of the sampling tubes and 

casings are adjusted during construction to accommodate the amount of sand flux in each 

area and to avoid overloading the CSC. The CSC length ranges from about one to three 

feet. Because the PVC casing is buried in the ground, an adjustment sleeve is used to 

keep the inlet height at 15 cm to compensate for surface erosion and deposition. Field 

techs use a standardized measuring device to check or adjust the sampling inlets to 15 cm 

after collecting each sample. 

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Figure 2.4 shows an example of the linear relationship between the CSC collected sand 

mass and the kinetic energy measured with a co-located Sensit. Sensits measure saltation 

in terms of kinetic energy (KE) and particle count (PC). The District uses the output (KE 

or PC) that provides the best precision and accuracy for the range of saltation activity 

expected at each site. 

Because the electronic Sensit response to the saltation flux can vary, Sensits were used in 

combination with CSCs to determine hourly sand flux rates. This combination takes 

advantage of the good precision and accuracy of the CSC sand catch data, and the ability 

of Sensits to time-resolve the sand flux for each hour of the CSC sampling period. In this 

way, the sum of the hourly sand catches always matches the CSC sand catch for each 

sampling period, and it minimizes the error in the hourly sand flux. 

Changes to the sand flux monitoring network are made as necessary to improve the 

characterization of dust source areas on the lake bed. Sand flux sampler sites are added 

to the network to monitor new source areas or to improve the sand flux estimates for 

known dust source areas. Although the sand flux network was originally designed in a 

fixed grid pattern with 1 km site spacing, the current practice is to place the samplers at 

sites that represent smaller source areas. Some sites may be less than 250 m apart, and 

their locations may be off the regular grid pattern to better represent sand flux activity in 

the dust source area. In addition, many of the original sampling sites that are now in 

flooded portions of the shallow flood DCM were removed, since PM10 emissions from 

the flooded sites can be assumed to be zero in the Dust ID model. 

2.3 Operating Procedures 

Sand captured in the CSCs will be weighed in the Keeler lab to the nearest tenth of a 

gram. A field technician will visit each site every one to three months to collect the 

sample tubes. The following procedures will be used when collecting the CSC samples 

and downloading Sensit data: 

1) Park field vehicle 10 meters or more east of the site and walk the remaining 

distance to the sampling site. Field personnel will access all Sensit and CSC 

sites from an easterly approach to minimize upwind surface impacts near the 

sampling sites. 

2) Measure and record the inlet height above the surface to the middle of the inlet. 

3) Remove the sample collection tube from the CSC. 

4) Verify collection tube number corresponds to site number on the field form. 

5) Weigh and record the gross weight of the collection tube and sample to the 

nearest 1 gram using a field scale. 

6) If any soil material is visible in the tube, seal the collection tube and place it in 

the tube rack for transport to the lab. If no soil material is visible, note this on 

the collection form and reuse the collection tube for the next sampling period. 

7) Place a clean collection tube in the CSC and record the collection tube number. 

8) Replace the CSC inlet and adjust the height to 15 cm (+1 cm). 

9) Download Sensit data from the datalogger to a storage module. 

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10) Measure and record the Sensit sensor height above the surface to the center of 

the sensor using the Sensit Height Indicator Tool, and adjust if necessary to 15 

cm. See Figure 2.5. 

11) Inspect the sensor and radio transmitter wiring and clean or repair, if needed. 

12) A field operational response test on the Sensit will be completed during each 

visit and the Sensit will be replaced, if it fails the test. 

13) CSC samples will be removed from the sample collection tubes and weighed on 

a calibrated bench-top scale in the Keeler lab to the nearest 0.1 gram. 

14) Wet samples will be removed from the collection tubes and oven dried before 

weighing in the lab. 

2.4 Data Collection 

A field form will be used to document the information for the CSC and Sensit (see 

example in Figure 2.6). The form will have the site number, date and time of 

measurement (Pacific Standard Time), “as is” CSC inlet and Sensit sensor height (+ 1 

cm), tube tare weight prior to sand catch (± 0.001 kg), total sand catch weight (± 0.001 

kg), and post-catch tube weight (± 0.001 kg), Sensit response test (particle counts or 

kinetic energy), operator’s initials, and a comments section where the condition of the 

sampler and any other relevant factors, such as surface condition will be documented. 

The Data Processing Department will calculate the net sand catch weight from the CSC 

during data analysis. CSC lab weights, measured to the nearest 0.1 g will be recorded on 

the Lab Form shown in Figure 2.7. After completion of the forms, the field technician 

will make a copy of the completed forms and file the copies at the Keeler office. The 

original forms will be sent to Data Processing in the Bishop office. Data Processing will 

enter the data into an electronic file. The original hard copy forms will be filed in the 

Bishop office. 

Each day, dataloggers for all Sensit sites will be downloaded by radio transmission to the 

Keeler Field office. Data from the storage modules will be downloaded to the computer 

at the Keeler office by the field technician at the end of a collection period. The radio 

transmitted Sensit data will be used as the data of record. Storage module data will be 

collected at least quarterly and will serve as a back-up file. 

Technicians will keep a log of all the repairs, maintenance, or replacement of Sensits or 

CSCs, radio transmitters, and datalogger equipment. This log will be kept in a field 

notebook and the field forms sent to Data Processing as they are completed. It is the 

technician’s or operator’s responsibility to review the data and notify the Air Monitoring 

Specialist and Data Processing who will decide whether any data should be edited or 

deleted and why. 

2.5 Chain of Custody 

Each field form will be initialed and dated by the field technician during each site visit. 

The form will be signed and dated by the person receiving the data when delivered to the 

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Bishop office. If no person is available to sign the form in the Bishop office, the delivery 

person will sign and date the form and place it in the Data Processor’s box.

2.6 Quality Assurance 

All field and lab scales will be checked at least every two months using Class F weights. 

Field scales will also be checked with a 100-gram weight at each sample site before 

weighing the sand catch and the weight recorded on the field form. The bench-top scale 

in the Keeler office will be checked with the Class F weights before each set of sand 

catches are weighed. The test weights will be recorded on the scale log sheet in the 

laboratory. Both scales will be calibrated and certified at least once every year. Ten 

percent of the CSC sand catch samples will be stored for at least one year from the date 

of collection before discarding. 

2.7 Calculating Hourly Sand Flux 

For modeling purposes discussed in Section 6, hourly sand flux is calculated for each 

Sensit/CSC site using the sand catch to Sensit reading ratio for each collection period and 

apportioning the sand catch to the hourly Sensit reading. The hourly sand flux is divided 

by 1.2 cm2

, which is the equivalent inlet opening size of the CSC for flux calculation 

purposes. 

For Sensits using kinetic energy, 

Equation 2.1 

( ) ( ) 2.1

1

1

,,

,

, ,, ×

−

×−=

∑=

N

t

bgntn

pn

tn bgntn

SS

CSC

SSq [g/cm2

/hr] 

 

 Where, 

 qn,t = hourly sand flux at site n, for hour t [g/cm2

/hr] 

 CSCn,p = CSC mass for site n, for collection period p [g] 

 Sn,t = Sensit total KE reading for site n, for hour t [non-dimensional] 

 Sn,bg = Sensit KE background reading for site n, [non-dimensional] 

 N = Total number of hours in CSC collection period p. 

For Sensits using particle count, 

Equation 2.2 

2.1

1

1

,

,

,, ×

′

= ′ ×

∑=

N

t

tn

pn

tntn

S

CSC

Sq [g/cm2

/hr] 

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Where, 

 = Sensit total PC reading for site n, for hour t [non-dimensional] tn S ,

′

2.8 Sensit Calibration and Data Analysis 

2.8.1 Sensit Calibration Check 

Data Processing will track Sensits by their serial number. After each sample collection 

period, Sensit and CSC data will be added to data from other sample collections. Data 

Processing will determine the average sand catch to Sensit ratio for each Sensit. Sensit 

readings will be collected for particle counts and kinetic energy for each Sensit. Due to 

differences in individual Sensit responses, some Sensits have a more consistent sand flux 

to Sensit reading ratio using particle count rather than kinetic energy. This normally 

depends on the manufacturer’s electronic design. At high sand flux sites, kinetic energy 

provides a more linear response for most Sensits. If KE is used, a background KE is 

subtracted from the reading if it is not zero. A background KE is determined from the KE 

reading when the PC reading is zero. 

The ratio of the Sensit response to the collected mass will be compared for each 

collection period to previous ratios for the same instrument to ensure that the Sensit is 

responding consistently. As seen in Figure 2.4 this ratio can vary, especially at low 

collection masses, so large deviations in the ratio should only be used as an indicator for 

a possible problem. Sensits will be replaced if they show no readings with significant 

sand associated CSC collection, have significant readings during calm wind periods, have 

an erratic response as compared to previous collection periods, or if they fail the field 

operational response test. 

 2.8.2 Replacing Missing Sand Catch Data 

Sand catch data can be lost if the CSC collector tube is full, or damaged, or if the sample 

is spilled during weighing. The lost sand catch data will be estimated using Sensit data. A 

cumulative sand catch to Sensit ratio is calculated by adding all of the valid sand catches 

and all of the corresponding Sensit data for that particular Sensit/CSC pair, and then 

dividing them to obtain the total ratio. The cumulative ratio is applied to the Sensit data 

to estimate the hourly sand flux. If there was a Sensit change, only data generated after 

the Sensit change is used to calculate the cumulative sand catch to Sensit ratio. 

CSC collection tubes will be weighed and reset at the same time as any Sensit change at a 

site in order to maintain the time correlation between the two devices. 

2.8.3 Replacing Missing Sensit Data 

Sensit data can be lost when the datalogger or Sensit fails. In such cases, the sand catch 

data will be time resolved using a neighboring site. The historical hourly sand flux data 

are compared to determine which neighboring site behaves most similarly to the site with 

the lost data. The correlation coefficients between the data sets will be used to determine 

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which site behaves most similarly. If no adjacent sites were active during the period of 

lost Sensit data, then the nearest active sites will be used for comparison. 

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Figure 2.1 Dust ID sand flux monitor sites measure wind erosion activity using 

CSCs to collect sand-sized particles and Sensits that electronically detect moving 

particles. Sensit data are recorded on dataloggers and transmitted by radio from 

each site to the District’s office in Keeler. 

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Figure 2.2 Diagram of the Cox Sand 

Catcher (CSC) used to measure sand 

flux at Owens Lake. 

Figure 2.3 Example of a Cox Sand 

Catcher (CSC) with the inner 

sampling collection tube temoved. 

Figure 2.4 Example of the linearity between CSC mass and a Sensit reading using 

kinetic energy reading (Sensit No. 7291). 

y = 0.33x - 0.01

R2

 = 0.91

0

0.1

0.2

0.3

0.4

0.5

0.6

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

Sand Catch (kg)

Sensit Reading (Kinetic Energy)

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Figure 2.5 A Sensit Height Indicator Tool is used to measure 

the height of Sensits and CSCs and to adjust the sensor and 

inlet height to 15 cm above the soil surface. 

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 Figure 2.6 Example of a CSC and Sensit Field Documentation Form. 

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Figure 2.7 Example of a CSC laboratory documentation form. 

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3. Protocol for Measuring Ambient PM10 and Meteorological Conditions 

 3.1 Objective 

Ambient PM10 monitors will be placed at locations generally around the shoreline of 

Owens Lake and in local communities to monitor the ambient air for exceedances of the 

PM10 NAAQS and to develop K-factors for modeling PM10 emissions from lake bed 

sources. PM10 monitors may be placed on the lake bed for short-term special-purpose 

monitoring studies. 

3.2 Methods and Instrumentation for PM10 and Meteorological Data 

PM10 monitoring will be performed using USEPA-approved reference or equivalent 

method monitors. The current monitoring network shown in Figure 1.1 includes seven 

PM10 monitor sites - Keeler, Lone Pine, Olancha, Dirty Socks, Shell Cut, Bill Stanley and 

Flat Rock. Each PM10 site is equipped with a Tapered Element Oscillating Microbalance 

(TEOM) PM10 monitor. TEOM monitors are capable of measuring hourly PM10

concentrations. The Dust ID Program will rely on the TEOM to determine if an 

exceedance is caused by a lake bed source, since the data can be correlated with hourly 

wind directions to determine dust source directions. TEOM data will also be used to 

generate K-factors to model the PM10 emissions from lake bed sources. 

Ten-meter meteorological towers will be located near each PM10 monitor site and at other 

locations around the lakeshore and on the lake bed. The current met sites are shown in 

Figure 1.1. The met data are used to create wind fields with the CALMET model that are 

used with CALPUFF to model air quality impacts. All met towers include 

instrumentation to measure wind speed and wind direction. Two lake bed met sites (A & 

B Towers) measure wind speed at different heights (0.5, 1, 2, 5 and 10 m) to determine 

surface roughness and vertical wind speed profiles. Some met sites also measure 

temperature, relative humidity, barometric pressure, and/or precipitation. 

 

3.3 Operating Procedures, Instrument Calibration and Quality Assurance 

PM10 monitoring will be performed in accordance with USEPA monitoring guidelines 

found in 40 CFR, Part 58 and meteorological monitoring will be performed in accordance 

with USEPA Quality Assurance Handbook for Air Pollution Measurement Systems, 

Volumes I, II, and IV. 

3.4 Data Handling and Data Access via Modem 

TEOM PM10 data will be delivered to Data Processing on a routine monthly schedule. 

After the data pass the proper data review and QA checks they will be submitted to the 

USEPA’s AIRS database. PM10 data from special-purpose monitors that may be located 

on the lake bed will not be submitted to the AIRS database. 

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All the PM10 sites and some met sites are equipped with modem links that allow for 

access to the hourly concentrations. These data are useful for alerting field personnel to 

possible new sources of PM10, and for alerting the public in case of high concentrations. 

For hourly concentrations above 400 μg/m3

 the District will issue public health advisories 

when the communities of Keeler, Lone Pine or Olancha are affected. The public can view 

real-time wind speed, direction and PM10 data from the Dust ID monitoring network on 

the District’s website at www.gbuapcd.org/data. 

4. Protocol for Observing and Mapping Source Areas and Dust Plume Paths 

4.1 Objective 

The objective for source area mapping is to use the best available information from visual 

observations, GPS mapping, and sand flux measurements to delineate the boundaries of 

dust source areas for as many events as possible. This information will be used to help 

delineate the control area boundaries for new sources. 

4.2 Methods and Instrumentation 

The Dust ID Program includes four methods to help locate dust source areas and to 

delineate the source area boundaries. The methods are: 1) visual mapping by trained 

observers, 2) time-lapse cameras, 3) surface inspections with GPS mapping, and 4) sand 

flux activity (as measured with Sensits and CSCs). 

4.2.1 Mapping Dust Source Areas from Off-Lake Observation Sites 

One or more trained observers will complete observations from viewpoints to best 

observe the active dust source areas. For instance, two observers may be at viewpoints on 

the east side of the dust plume in the Inyo and Coso Mountains and a third may be on the 

west side in the Sierra. The observers will create hourly maps of the visible boundaries of 

any dust source areas, their plume direction and note if the visible plume crosses the 

shoreline. To the extent practicable, all lake bed and off-lake dust sources will be 

included in the observations. Figure 4.1 shows an example of sand flux measurements 

and the cumulative information that can be collected by observers mapping the dust 

plumes from different locations. 

4.2.2 Video Cameras 

Remote time-lapse video cameras will record dust events during daylight hours. This 

information will be reviewed to help identify source areas that may have been missed by 

observers, or to help confirm source area activity detected by PM10 monitors or the sand 

flux network. Remote time-lapse video can also be used to help verify modeled impacts 

that were not monitored by the PM10 network, to check compliance of dust control areas, 

and to identify off-lake sources not measured by any of the other methods. 

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 4.2.3 Mapping Using GPS 

4.2.3.1 “Trigger” Levels for Initiating Field Inspections and GPS Surveys 

Dust observations, Sensit activity, elevated PM10 concentrations and video will be used as 

“trigger data” to determine the time and location for a Dust Source Area Survey (survey). 

Sensit and PM10 data will be automatically collected via radio transmission every 

workday. A technician will summarize and review the data each workday. The summary 

will list all Sensit activity greater than background output levels, and hourly TEOM PM10

concentrations over 50 μg/m3

 with corresponding wind speed and direction data. If dust 

observations are available from a recent dust storm, they will be used to confirm the 

location of the dust source(s) that correspond with the Sensit activity and elevated PM10

concentration. Video will be used to identify a source or sources that were not identified 

by observations, Sensit data or PM10 information. Wind speed and wind direction data 

will be used to help determine if a lake bed dust source could have caused elevated PM10

concentrations. All of the trigger information will be used to identify any lake bed dust 

source area to initiate a dust source survey and/or surface inspection. The survey should 

be completed the same day if weather conditions are favorable. For larger areas, 

surveying may continue for several days or until precipitation obscures the boundaries of 

the source area. 

In addition to the above process, general field inspections will be completed after dust 

storms to verify lake bed emission activity and the need for a survey. A survey will be 

completed if the trigger data and /or field inspections indicate emissive conditions in an 

area that has not been previously surveyed during the current dust period (Section 4.3) or 

in an area that has been previously surveyed but has increased in size since its last survey. 

The priorities for completing a survey are: 

1) new lake bed source areas outside the instrumented Sensit network; 

2) new lake bed source areas that have not been surveyed within the instrumented 

Sensit network; and 

3) lake bed source areas that have previously been surveyed. 

4.2.3.2 GPS Mapping Procedures 

After a dust source is identified by dust observation, Sensit data, sand catch data, video, 

PM10 concentration or inspection of the lake bed surface, Great Basin staff will map the 

exterior boundary of as many of the source areas identified as possible during daylight 

hours, as weather conditions allow. The mapping will begin as soon as possible after a 

dust storm and continue until all the identified areas are mapped or precipitation occurs. 

The boundary of the emissive area(s) will be mapped using a Global Positioning System 

(GPS). Surveyors conducting the mapping will ride an ATV or walk around the outer 

boundary of the wind-damaged surface surveying a line with the GPS. A wind-damaged 

surface is defined as a soil surface with wind erosion evidence and/or aeolian deposition 

that has not been modified to an unrecognizable point by precipitation since the last 

identified dust storm. 

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GPS line data should be collected at an interval of one record every 10 seconds or less. 

Data should be collected in NAD83 UTM Zone 11 coordinates. Only GPS units capable 

of continuously recording line data will be used. Data should be processed and corrected 

using base station data (either from a commercial correction service or using data from 

the District’s Keeler base station) to ensure positional accuracy. 

Before beginning a survey, the edge of the source area is determined by a visual review 

of the surface conditions within a representative one square meter area along the edge of 

the source area. An undamaged surface is evident if there is no visible evidence of a 

disturbed lake bed surface due to wind damage. As an aid to calibrate the level of 

disturbed surface, a surveyor will begin each survey by estimating the percentage of 

surface that is undamaged by the wind. The surveyor visually determines where a surface 

with 70 to 80 percent of undisturbed surface is located. The surveyor completes the 

survey by following a line of travel that closely represents the initial one-meter 

calibration. The following defined list, Boundary Conditions and Survey Procedures (see 

below), can be used to determine how to map the source boundary under differing surface 

boundary conditions. 

Boundary Conditions and Survey Procedures: 

Distinct Boundary: A visibly sharp transition, 25 feet or less in width, between a 

wind-damaged lake bed surface and an undamaged lake bed 

surface. The surveyor should travel directly along this distinct 

outside edge, if possible, and may deviate 25 feet to the inside 

or outside on occasion. Small (25-foot wide or less) channels, 

boundary indentations, roads, mounds, and other obstacles 

may be directly crossed if the continuation of the main source 

boundary is clearly visible on the opposite side. 

Diffuse Boundary: A visibly distinct transition, 25 to 100 feet in width, between a 

wind-damaged lake bed surface and an undamaged lake bed 

surface. Every effort should be made to travel along the 

outermost edge of the visible distinction. 

Indistinct Boundary: A boundary that is not obvious to the surveyor where the edge 

of the source is located. Mapping would be stopped at this 

point until a Distinct or Diffuse Boundary can be located. 

Generally the surveyor will maintain a constant course of travel following the Distinct 

Boundary of the wind-damaged area. As the boundary becomes less distinct, it is 

recommended to move the course of travel further into or outside the source to maintain 

recognition of surface damage. It is acceptable to travel within approximately 50 feet of 

the outer or inner edge of the larger more noticeable active area if the boundary is 

Diffuse. When encountering an Indistinct Boundary condition, the surveyor should note 

if the boundary can be found or if the boundary cannot be mapped during the existing 

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survey and why. If the boundary cannot be mapped, the survey shall end at that point 

leaving an unclosed source area polygon. 

It is possible for the surveyor to find himself or herself greater than 50 feet within or 

outside of the source area boundary. When this happens, the surveyor should turn 

perpendicular to the direction they were traveling and travel in the direction where the 

distinct edge should be located. For example, if the surveyor were inside the source area, 

they would turn in the direction where erosion evidence was not observed earlier along 

their path. If the surveyor were outside the source area, they would turn toward the side 

where they previously observed the source. Boundary loss may occur because of an 

Indistinct Boundary or unfavorable lighting conditions. The time and coordinates should 

always be noted when it is necessary to relocate the boundary during a survey. 

Another alternative for relocating a source area edge is to pause the GPS unit from 

recording data until the boundary is located and then resume with data collection. This 

allows the surveyor to travel in any direction until the edge is relocated or end the survey 

if an edge cannot be located. The line produced between the point where the GPS unit 

was paused and then restarted would be deleted and considered un-surveyed during post 

processing. 

The presence of Indistinct Boundaries or conditions that cause the ending of a survey 

must be annotated on the GPS data or explained in the field notes, including point 

coordinates. Examples would include dust storm, precipitation, lightning, mud, and 

channel with flowing water, pond, and time restraint or equipment malfunction. 

 4.2.4 Using Sand Flux Monitors to Map Source Area Boundaries 

Dust source area boundaries can be delineated or refined using default cell boundaries 

represented by active sand flux monitors. The area represented by the active SFM site 

may be shaped to exclude known non-emissive areas, such as; DCM areas, wetlands, or 

areas with different soil texture where there is evidence that it is non-emissive. 

4.3 Composite Dust Source Map Development 

Data Processing will compile the cumulative mapping information from the visual 

observers and field inspections using the GPS into a GIS database for two periods each 

year, December through June and July through November. A new composite map will be 

developed for each period containing only those data collected during that period. Hand 

drawn observation maps will be scanned and translated into the GIS database. 

Observation maps will be compared with source area locations from other methods 

through the GIS generated layers. Overlays of the maps generated from sand flux 

monitors, video cameras, visual observers and GPS’d source areas will be compared 

qualitatively, considering the information may have been collected at different times. 

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GBUAPCD, 2007_Dust ID Field Manual-FINAL DRAFT.doc 22 

Figure 4.1. Example of dust plume maps drawn by observers during 

daylight hours and total sand flux for a dust event on February 6-8, 2001. 
Dust ID Field Manual 

Draft - January 24, 2007 

5 Protocol for Determining K-factors and PM10 Emission Rates from Sand Flux 

Data 

5.1 Objective 

The objective of this portion of the Dust ID Program is to estimate the PM10 emission 

flux for each cell or source area using the relationship PM10 emission flux = sand flux x 

K-factor. PM10 emissions for each area will be used with the CALPUFF modeling system 

or other USEPA approved model to determine if the PM10 emissions will cause or 

contribute to a NAAQS violation at the shoreline. 

5.2 Method for Determining PM10 Emissions and New K-factors 

5.2.1. PM10 Emission Flux = Sand Flux x K-factor 

PM10 emissions will be estimated using the sand flux for each area represented by a 

Sensit and CSC and an appropriate K-factor for the area and period. The sand flux values 

will come from the Sensit and CSC data as discussed in Section 2. New K-factors for 

each area and period will be developed as discussed in this section, and default K-factors 

will be used to model dust events unless newer K-factors are determined. 

5.2.2. Default Temporal and Spatial Storm-average K-factors

PM10 emissions may be estimated from default K-factors that were developed from 

previous dust events that occurred in the same area and the same range of calendar 

months in previous years. 

The areas for K-factor groupings are shown in Figure 1.1: North Area, Central Area, 

Keeler dunes, and the South Area. Any new source area within the depicted boundaries 

will be associated with that area for the spatial grouping of new K-factor values. If a new 

source area and K-factor is developed for an area outside these boundaries, the area and 

default K-factor will be associated with the K-factor for an existing area with the most 

similar surface soil texture. The determination of the most similar existing area will be 

made by the Air Pollution Control Officer. 

5.2.3. Method to Determine Sand Flux from Areas with Implemented Dust 

Control Measures (DCM) 

Sand flux will be measured at sites within the shallow flood and managed vegetation 

DCM areas. Sensits and CSCs will be sited on dry areas within the shallow flood DCM 

to represent dry areas near the site. DCM areas covered with standing water will be 

assumed to have zero sand flux. For the Managed Vegetation DCM, sand flux sites will 

be placed in spatially representative areas and in areas within the DCM where wind 

blown dust may have been previously observed. 

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5.2.4. New K-factors Seasonal Cut-points 

The APCO will review the K-factor data and propose seasonal cut-points to the LADWP. 

LADWP will respond to the proposed cut-points within 30 days. If no agreement can be 

reached within 60 days, the default periods will be used. 

The two default periods to be used are: the winter/spring period that includes the months 

of December, January, February, March and April, and the summer/fall period that 

includes May through November. These same calendar months will be used to generate 

new temporal K-factors for each area and to generate new 75-percentile hourly K-factor 

values for modeling PM10 emissions. See Appendix B, SCR Sections 1.2 and 2.1 

regarding the order of priority for using K-factors for modeling.

5.2.5. Using CALPUFF Modeling System to Generate New K-factors 

New hourly K-factors can be inferred from the CALPUFF model by using hourly sand 

flux as a surrogate for PM10 emissions. Modeled PM10 predictions can then be compared 

to monitored concentrations at PM10 monitor sites to determine the K-factor that would 

correctly predict the monitored concentration for each hour. More information on the 

modeling procedures is included in Section 6. 

A K-factor of 5 x 10-5 will be used initially to run the CALPUFF model and to generate 

concentration values that are close to the monitored concentrations. Hourly K-factor 

values will then be adjusted in a post-processing step to determine the K-factor value that 

would make the modeled concentration match the monitored concentration at the PM10

monitor site. The initial K-factor will then be adjusted using Equation 5.2. 

 Equation 5.2 

K K 

C C

C f i

obs. - bac.

mod.

= ⎛

⎝

⎜ ⎞

⎠

⎟

 Where, 

 Ki = Initial K-factor (5 x 10-5) 

 Cobs. = Observed hourly PM10 concentration. [μg/m3

] 

 Cbac. = Background PM10 concentration 

 Cmod. = Model-predicted hourly PM10 concentration. [μg/m3

] 

5.2.6. Screening Hourly K-factors 

K-factors will be calculated for every hour that has active sand flux in cells upwind from 

a PM10 monitor. These hourly K-factors will be screened to remove hours that did not 

have strong source-receptor relationships between the active source area (target area) and 

the downwind PM10 monitor. For example, the screening criteria will exclude hours when 

a PM10 monitor site is located on the edge of a dust plume. Because the edge of a dust 

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plume has a very high concentration gradient, a few degrees error in the plume direction 

could greatly affect the calculated K-factor. 

The following criteria will be used to screen the hourly K-factors: 

Initial K-factor Screen 

1) Wind speed is greater than 5 m/s at 10 m height at any network site. 

2) Hourly modeled and monitored PM10 concentrations were both greater than 150 

μg/m3

 at the same monitor-receptor site. 

3) Hourly wind direction as listed in Table 5.1 for each monitor site. 

4) The mean sand flux for all sites with non-zero sand flux is greater than 0.5 

g/cm2

/hr. 

Final K-factor Screen

5) At least one sand flux site located within the target area and within a 30-degree 

upwind cone has sand flux greater than 2 g/cm2

/hr. 

6) All sources are within a distance of 15 km of the receptor. 

7) More than 65 percent of the PM10 contribution at a monitor site came from the 

target source area (North Area, South Area, Central Area or Keeler dunes). 

8) Eliminate hours when sand flux data are missing from one or more cells that are 

located within a 30-degree upwind cone and within 10 km of the shoreline 

monitor. For Olancha and Lone Pine, which are both located 5 to 10 km from the 

lake bed, the distance limitation is changed to 10 km upwind of the shoreline. 

Table 5.1 Wind Directions for the Initial K-factor Screen 

PM10

Monitor Site 

From-the-Lake Wind 

Dir. (Deg.) 

Met Tower 

Lone Pine 110<WD<190 Lone Pine 

Keeler 130<WD<330 Keeler 

Flat Rock 210<WD<360 Flat Rock 

Shell Cut WD>210 or WD<50 Shell Cut 

Dirty Socks WD>220 or WD<65 Dirty Socks 

Olancha WD>320 or WD<55 Olancha 

New Sites TBD TBD 

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The from-the-lake wind directions for the initial K-factor screening criterion 3) are shown 

in Table 5.1. From-the-lake wind directions for any new PM10 sites will be determined by 

the APCO as needed for the initial K-factor screen. Note that ‘From-the-Lake’ wind 

directions in the Supplemental Control Requirements in Appendix B are different from 

these K-factor screening wind directions. 

Hourly K-factors that pass through the screening criteria will be used to develop new 

event-specific spatial K-factors, and new 75-percentile hourly average temporal and 

spatial K-factors, if enough K-factors are available. 

5.3 Temporal and Spatial Event-specific K-factors 

5.3.1 Event-Specific K-factors 

Screened hourly K-factors will be used to generate event-specific K-factors for the active 

source areas. The event-specific K-factor will be calculated as the arithmetic average 

using all the hours when the hourly K-factor passes the screening criteria for the target 

area. 

5.3.2 Temporal & Spatial 75-Percentile K-factors

The statistical 75-percentile value will be determined from the distribution of the hourly 

K-factors that pass the screening criteria for that area and period, whenever there are nine 

or more hourly K-factors. The 75th percentile will be calculated using the Microsoft Excel 

PERCENTILE function. The Microsoft Excel PERCENTILE function works by sorting 

values from lowest to highest, then assigns the 0th percentile is the lowest value, the 100th

percentile is the largest value, and the values in between as (k-1)/(n-1) where n is the 

number of data values in the list and k is index of the kth lowest value in the list. Thus, 

each value is placed 1/(n-1) apart. If a requested percentile does not lie on a 1/(n-1) step, 

then the PERCENTILE function linearly interpolates between the neighboring values. 

5.3.3 Default K-factors 

Table 5.2 shows the default K-factors for each of the K-factor areas and periods. These 

K-factors are derived for the temporal and spatial 75-percentile values from the screened 

hourly K-factors for the 30-month Dust ID period used for the RSIP. Each of the two 

temporal periods combines hourly K-factors from the same calendar periods for 2 or 3 

years. 

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Table 5.2 Default Spatial and Temporal K-factors for the 

Dust ID Model 

AREA K-factor 

Jan.– Apr. & Dec.

K-factor 

May-Nov.

Keeler Dunes 7.4 x 10-5 6.0 x 10-5

North Area 3.9 x 10-5 1.5 x 10-5

Central Area 12. x 10-5 6.9 x 10-5

South Area 4.0 x 10-5 1.9 x 10-5

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6 Protocol For Dispersion Modeling 

This section of the Protocol discusses the dispersion model methods planned for the 

simulation of wind blown dust at Owens Lake using data from the Dust ID Program. The 

modeling procedures follow the methods used in the RSIP, with refinements based on 

experience and modifications to support the provisions of the SCR. The modeling 

techniques will be used both diagnostically to infer emission rates for source areas and 

prognostically to predict PM10 concentrations at the historic shoreline. Following an 

overview of the modeling approach, the remainder of this section discusses construction 

of the meteorological data set, dispersion model options, background concentrations and 

source area characterization. 

6.1 Overview of Modeling Procedures and Rationale for Model Selection 

The CALPUFF modeling system was used in the RSIP and has been selected for 

continuing studies in the Dust ID Program. CALPUFF is the USEPA recommended 

modeling approach for long-range transport studies and USEPA has proposed CALPUFF 

as a Guideline Model to be included in the Guideline on Air Quality Models (40 CFR Part 

51, Appendix W). Recently the modeling system is also being applied to near-field 

dispersion problems where the three-dimensional qualities of the wind field are important 

and for stagnation episodes when pollutants remain within the modeling domain over 

periods of several hours or more. Dust events on Owen Lake are sometimes influenced 

by complex wind patterns, with plumes from the North Sand Sheet traveling in different 

directions than plumes from the South Sand Sheet. 

The proposed model domain shown in Figure 6.1 includes a 34 km-by-48 km area 

centered on Owens Lake. The meteorological and computational grid will use a onekilometer horizontal mesh size with ten vertical levels extending from the surface to four 

kilometers aloft. The extent of the model domain was selected to include the “data rich” 

Dust ID Program study area, terrain features that act to channel winds, and receptor areas 

of interest. This same model domain and mesh size were used in the simulations 

supporting the RSIP. 

6.1 Meteorological Data Set Construction 

Three-dimensional wind fields for CALPUFF will be constructed from surface and upper 

air observations using the CALMET meteorological preprocessor program and the 

procedures employed in the RSIP. CALMET combines surface observations, upper air 

observations, terrain elevations, and land use data into the format required by CALPUFF. 

Winds are adjusted objectively using combinations of both surface and upper air 

observations according to options specified by the user. In addition to specifying the 

three-dimensional wind field, CALMET also estimates the boundary layer parameters 

used to characterize diffusion and deposition by the CALPUFF dispersion model. 

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6.2 CALPUFF Options and Application 

Surface Observations. The necessary surface meteorological data will come from the 

District’s network of ten-meter towers shown in Figure 1.1. The District may also install 

additional stations to better characterize winds near suspect source areas not currently 

near an existing site. Very few periods of missing data are typically contained in the 

District’s database. Periods of missing data will be flagged and CALMET will construct 

the wind fields using the data from the remaining stations. In addition to the District’s 

network, surface data from other field programs at Owens Lake will be used when 

available. 

Cloud Cover Data. The current version of CALMET also requires cloud cover and 

ceiling height observations. Cloud cover is a variable used by CALMET to estimate the 

surface energy fluxes and, along with ceiling height, is used to calculate the Pasquill 

stability class. Hourly cloud cover and ceiling height observations are being collected 

from the surrounding surface airways observations at China Lake and Bishop Airport. 

During dust event conditions, the sensitivity of the CALPUFF modeling system to these 

variables is reduced, as the stability class becomes neutral under moderate to high winds. 

Algorithms within the modeling system that depend on the surface energy fluxes are 

dominated by the momentum flux and tend to be insensitive to cloud cover under high 

winds. For these reasons, the absence of local cloud cover and ceiling height 

measurements are not expected to significantly affect the results of the modeling study. 

Surface Characteristics and Terrain. The CALPUFF modeling system requires land 

use and terrain data. These data are used by CALMET to adjust the wind field and affect 

the calculations performed by the CALPUFF dispersion model. CALPUFF considers 

spatial changes in land use, including the surface roughness, and the input data are 

specified on a horizontal grid. The terrain data influence the constructed wind fields and 

plume trajectories in regions of sparse observations. Land use and terrain data have been 

obtained from the U.S. Geological Survey (USGS) data sets on the Internet. The 

resolution of these land use and terrain data sets are 200 m and about 30 m, respectively. 

The District has prepared these data sets using the pre-processing software provided with 

the CALPUFF modeling system. The resulting grids have been plotted and checked 

against data from the District’s GIS database where the modeling domain overlaps the 

District’s data. The 1-km mesh size terrain used by CALMET and CALPUFF is shown in 

Figure 6.1. 

Upper air data. Upper air data will be collected from a number of different sources for 

construction of the wind fields and estimation of mixing heights with CALMET. In the 

RSIP, both local and regional data were collected as follows: 

• A 915 MHz Radar Wind Profiler and Radio Acoustic Sounding System (RASS) 

were used to collect upper level wind and temperature measurements. The Wind 

Profiler was initially located at Dirty Socks then moved to the Mill Site during the 

4th quarter of 2001. The District discontinued measurements with the Wind 

Profiler on June 30, 2003. The Wind Profiler with RASS samples wind and 

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temperature from 100 m, up to 5000 m with a vertical resolution as low as 60 m 

depending on the clutter environment, atmospheric scattering conditions, and 

pulse length. Experience at Owens Lake indicates wind data recovery is 

sometimes poor above 1000 m due to the dry environment and the RASS data are 

limited to the lower levels during windy conditions. 

• Regional twice-daily upper air soundings from Desert Rock Airport (Mercury, 

Nevada) and China Lake Naval Air Station. 

During high wind events, observations from the Wind Profiler at both the Mill Site and 

Dirty Socks indicate very little wind speed or wind direction shear with height. Previous 

CALPUFF simulations suggest concentrations predicted at PM10 monitoring sites and at 

the historical shoreline are not usually influenced by upper level winds because the 

sources are ground based. The highest impacts occur close to the source areas, and there 

is very little wind shear during high winds. 

Following removal of the Wind Profiler, soundings from China Lake and Desert Rock 

will be used to construct the data set. The China Lake and Desert Rock sounding will 

primarily be used for upper level temperature lapse rates. Winds aloft will be based on 

extrapolation of the surface wind measurements. The default algorithms employed by 

CALMET based on Similarity Theory often adjust the winds in the wrong direction and 

predict too much increase in wind speed with height even for very small surface 

roughness lengths. As an alternative, wind speeds aloft will be adjusted using the 

empirical results suggested by the previous Wind Profiler measurements. No wind 

direction turning with height will be assumed except near the Wind Profiler site where 

the actual data will be used until this program is discontinued. 

CALMET options. The options employed for the application of CALMET to construct 

the wind fields were provided in the “Modeling Protocol” (MFG, 2001). The majority of 

the selected model options are based on the defaults incorporated in the code by the 

model author. Notable model options include: 

• Ten vertical levels varying geometrically from the surface to 4000 m. The 

geometric spacing provides better resolution near the surface and the upper limit 

is high enough to be above the boundary layer height. 

• Vertical extrapolation of surface winds aloft using the results of the Wind Profiler 

studies. 

• Less than default smoothing of wind fields. LADWP contractors Air Sciences and 

Environ suggested less smoothing of the wind fields by CALMET after review of 

the Owens Valley PM10 Attainment Demonstration Modeling Protocol. 

Wind fields constructed with CALMET will be randomly checked by plotting the 

resultant fields and the surface observations on a base map. The CALDESKTM software 

package will also be used to view the CALMET wind fields. 

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The application of CALPUFF involves the selection of options controlling dispersion. 

Although the simulations are primarily driven by the meteorological data, emission 

fluxes, and source characterization, the dispersion options also affect predicted PM10

concentrations. The model options used in the RSIP will continue to be used for the Dust 

ID Program. In this study, the following options will be used for the simulations: 

• Dispersion according to the conventional Pasquill-Gifford dispersion curves. 

Sensitivity tests were also performed by applying CALPUFF with dispersion 

routines based on Similarity Theory and estimated surface energy fluxes. These 

tests did not indicate improved performance over the Pasquill-Gifford based 

simulations. 

• Near-field puffs modeled as Gaussian puffs, not elongated “slugs.” CALPUFF 

contains a computation intensive “slug” algorithm for improved representation of 

plumes when wind directions vary rapidly in time. This option was tested, but did 

not significantly influence the CALPUFF predictions. 

• Consideration of dry deposition and depletion of mass from the plume. The 

particle size data used will be based on measurements taken within dust plumes 

on Owens Lake as discussed below. 

Dry deposition and subsequent depletion of mass from the dust plumes depend on the 

particle size distribution. Several field studies have collected particle size distributions 

within dust plumes at Owens Lake. Based on results from Niemeyer, et al. (1999), the 

CALPUFF simulations will assume a lognormal distribution with a geometric mean 

diameter of 3.5 μm and a geometric standard deviation of 2.2. 

6.3 Background PM10 Concentrations 

The dispersion model simulations include only wind blown emissions from the source 

areas with sand flux activity measurements. During high wind events other local and 

regional sources of fugitive dust can contribute to the PM10 concentrations observed at 

the monitoring locations. In the RSIP a constant background concentration of 20 μg/m3

was added to all predictions to account for background sources. The constant background 

was calculated from the average of the lowest observed PM10 concentrations for each 

dust event when 24-hour PM10 concentrations at any of the sites were above 150 μg/m3

. 

To avoid including impacts from lake bed dust source areas in the background estimate, 

the procedures used a simple wind direction filter to exclude hours when the lake bed 

may have directly influenced observed PM10 concentrations. Such hours were removed 

and daily average background concentrations were recalculated based on the remaining 

data. 

Additional PM10 monitors are proposed for installation at Owens Lake. These monitors 

can be used to measure hourly PM10 concentrations upwind from lake bed source areas. 

Some of these monitors may be representative of regional PM10 concentrations and others 

may be influenced by local sources that may indicate a higher PM10 concentration than 

the regional background level. A method to calculate background concentrations based 

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on upwind monitor concentrations for each modeled-event approved by both the APCO 

and the General Manager of the LADWP may be developed in the future. Meanwhile, a 

default background of 20 μg/m3

 will be added to the model prediction for each receptor 

location. 

6.4 Area Source Characterization 

CALPUFF simulations at Owens Lake are sensitive to source configuration. Emissions 

will be varied hourly according to the methods described in Section 6.6 and dust sources 

represented as rectangular area sources. CALPUFF contains an area source algorithm that 

provides numerically precise calculations within and near the area source location. The 

area source configuration used for the Dust ID model run for the period from July 2002 

through June 2003 is shown in Figure 6.2. The paired Sensit and CSC measurements 

were assumed to be representative of the horizontal sand flux for irregularly shaped 

source areas near the sand flux site. Field observers determined the size and shape of the 

source areas based on GPS mapping after the storms, observation maps made during the 

storms, and physical surface characteristics. All source areas were represented by sand 

flux measured at a single site that was applied to a series of 250 m x 250 m cells that 

were configured to conform to the general shape of the source area represented by the 

sand flux site. 

The following general rules are used to characterize and map source areas on the lake 

bed: 

• Actual source boundaries will be used when available to delineate emission 

sources in the simulations. Actual source boundaries will be determined using a 

weight-of-evidence approach considering visual observations, GPS mapping, and 

surface erosive characteristics. Erosive characteristics that might be considered 

when defining a source boundary include properties of the soil, surface crusting, 

wetlands, and the proximity of the brine pool and existing DCMs. 

• Source boundaries will also be defined based on the DCM locations. For example, 

sand flux measurements outside the DCM will be assumed to apply up to the 

boundary of the DCM. Sand flux measurements inside the DCM will be assumed 

to apply to the area inside the DCM. 

• All source areas will be represented by a series of 250 m x 250 m cells that 

generally conform to the shape of the source area and share the same hourly sand 

flux rates as the sand flux site representing that source area. Cells small than 250 

m x 250 m may be used near the shoreline to better represent source areas where 

predicted concentrations are expected to be particularly sensitive to the source 

area configuration. 

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6.5 Estimation of PM10 Emissions 

Hourly PM10 emissions for each source area will be estimated using Dust ID sand flux 

data and K-factors following the procedures described in Section 5. See also SCR 

Section 1.2 and 2.1 regarding the order of priority for using K-factors for modeling.

6.6 Simulation of Shoreline Concentrations 

Under the provisions of the SCR in the RSIP, CALPUFF simulations will be used to 

assess whether lake bed source areas cause or contribute to an exceedance of the PM10

NAAQS in areas without PM10 monitoring sites. Predictions will be obtained using the 

RSIP receptor network that contains more than 460 receptor locations placed at the 

historic shoreline (approximately at the 3600' elevation) of Owens Lake (see Figure 6.2). 

The receptor spacing along the historic shoreline ranges from 100 to 200 m. Note in 

several locations along the shoreline, receptors are very close to or even within potential 

source areas. 

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400 405 410 415 420 425 430

UTM East-West (km)

4010

4015

4020

4025

4030

4035

4040

4045

4050

4055

UTM North-South (km)

Figure 6.1 Model Domain, elevation contours and UTM coordinates for the Dust 

ID Model. 

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Figure 6.2 Area source configuration using 250 m x 250 m cells for July 2002 

through June 2003 Dust ID model run. Purple lines represent the control area 

boundary used with the Settlement Agreement. 

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Figure 6.3 The Dust ID model evaluates PM10 impacts at over 460 receptor 

locations around Owens Lake. 

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7. Owens Lake Safety & Training Program 

7.1 Objective 

All field personnel that work at Owens Lake are required to complete special training 

courses to deal with the unique hazards and environmental precautions that must be 

considered when working on the lake bed. Training includes: first aid and CPR training, 

proper ATV use, respiratory protection and dust safety, lake bed access reporting, and 

snowy plover protection.

7.2 Safety Requirements

Safety is the first priority while working at Owens Lake. Training requirements are 

required for every worker at the lake for their own safety. Dust storms can start within 

minutes exposing workers to dust and sand. Lightning storms often occur in the summer. 

Winters have sub-freezing temperatures and summers have temperatures well above 100 

degrees. Access is usually restricted to ATV’s and can change often throughout each 

year. The objective of all the training requirements is to put safety as the highest priority 

at all times. 

All personnel that are involved with any fieldwork under the Dust ID Program are 

required to complete all safety training before working on the lake. Everyone must report 

going onto and leaving the lake. Workers are required to stop work and leave the lake 

when a dust storm starts. Every field worker will be issued a respirator, goggles for eye 

protection and earplugs to be used when caught in a dust storm while leaving the lake. 

Workers are required to leave the Keeler office when the dust impacts Keeler and the 

TEOM monitor reading exceeds 1000 μg/m3

. Respirator training and face fits will be 

completed annually. First Aid and CPR training and successful certification is required 

every three years. Snowy Plover training is required before any new worker can start 

work on the lake. Other safety issues that all workers will be informed of include the 

proper use of tools, special weather conditions such as temperature extremes, rain and 

lightning and training in the operation of ATVs. 

7.3 Reporting Procedure for Working on the Lake and Contacts 

1. Normal work hours on the Owens Lake are defined as sunrise to 4:45 PM, 

Monday through Friday. The lake is defined as any area below the 3600 ft. 

contour. 

2. Every person or group must call the Bishop office and leave a message or speak 

to the Administrative Specialist (AS) to notify that they are working on the lake. 

They also must inform the AS what area of the lake they will be working. 

Examples: DIVIT, Dirty Socks sand sheet, “A” Met tower or any commonly used 

identifiable name of a site or area you will be working. 

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3. The AS will record the person’s name (s) and area of the lake they are working 

on. 

4. Every person or group working on the lake must notify the Bishop office before 

4:45 PM on the same day; that they have left the lake OK. This must be done or a 

person will be sent out to look for you! False alerts will not be appreciated. 

5. The AS will call the Director of Technical Services (DTS) in Keeler or one of the 

back up persons in order on the list below, and report the missing person if not 

notified before the specified time. An attempt will be first made to contact the 

missing person by phone and determine their situation. The DTS or an assigned 

person will begin a search for the missing person if the person cannot be 

contacted by phone. The search will continue until dark or unsafe conditions at 

which time the Inyo Sheriff will be notified for assistance. 

6. Everyone may work outside normal work hours Monday through Friday at your 

own risk. However, they must call the Bishop office before the designated time 

and notify the AS that they will be working past 4:45 PM and call again and leave 

a message that they left the lake OK before 8:00 AM the next day. 

7. The AS will check the messages every morning and record the information. The 

DTS will be notified if a person that worked after normal hours did not call and 

leave a message that they left the lake OK. The DTS or an assigned person will 

follow the procedure for a missing person outlined in step 5. 

8. Nobody may work on the lake after 4:45 PM on Friday, all day Saturday or 

Sunday unless they receive special permission from their direct supervisor. The 

supervisor will be responsible for making sure the worker left the lake OK and 

responding to an emergency or search if necessary. The worker must notify their 

supervisor when they leave the lake OK during these periods. 

Emergency Assistance Reporting Contacts and Phone Numbers:

Call 911 first if you have an emergency! 

 Bishop Office AS 872-8211 

 Bill Cox (DTS) 876-8103 Cell 937-2886 Home 938-2859 

 Earl Wilson 876-8104 Cell 937-1060 Home 876-5455 

 Nik Barbieri 876-1803 Cell 937-6696 Home 873-8285 

 Grace Holder 872-8211 Cell 937-2887 Home 872-3225 

 Guy Davis 876-8115 Cell 937-1766 Home 876-0048 

 Dan Johnson 876-4544 Cell 937-1715 Home 371-1465 

 Ted Schade 872-8211 Cell 937-3360 Home 872-3419

 

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7.4 Snowy Plover Training and Other Wildlife Protection Procedures 

Field technicians and other District personnel and contractors are required to take 

precautions to avoid disturbing western snowy plovers during the nesting and brooding 

season which is from March 15 through August 30 each year. All lake bed personnel 

must complete snowy plover awareness and avoidance training before venturing onto the 

lake bed during snowy plover season. A qualified biologist will provide training for all 

lake bed personnel. In addition to completing snowy plover training, the plover 

protection program requires the following: 

• Report snowy plover sightings to the District’s biological resources monitor for 

dissemination to all lake bed personnel and for scientific data collection purposes. 

The biological resources monitor will map and mark the sightings in the case of 

nesting pairs, and will map the last known locations of broods. Lake bed workers 

will be responsible for checking the latest maps before encroaching onto potential 

snowy plover use areas. 

• If snowy plover nests are found within areas of potential conflict with Dust ID 

monitoring, they will be marked in the field with green stakes. Within the buffer 

area demarked by stakes, the maximum allowable time per visit is 10 minutes. 

• Field personnel should use established ATV and 4WD vehicle trails to approach 

and depart monitoring sites. The maximum allowable speed on ATV and off-road 

4WD on the lake bed is 15 mph during the snowy plover season. 

All existing and new Dust ID monitoring installations will be fitted with raptor perching 

deterrent (eg., Nixalite) at potential perch sites with a height of greater than 42 inches 

above the playa surface. Maintenance of perching deterrents will be routinely performed. 

Any new construction that causes new ground disturbance during the snowy plover 

season will require a pre-construction survey for snowy plover use. A qualified biologist 

will perform the survey within 1 week prior to the start of construction. 

Monitoring will be performed on site in a manner that is least disturbing to wildlife and 

plant resources as possible. Potentially affected upland resources (those located outside 

the playa) that could be disturbed during any new ground-disturbing construction 

activities were identified during District environmental analyses. The animals that use 

upland areas vary seasonally, with nesting and foraging birds, mammals, reptiles, and 

invertebrates occurring during the period of dust monitoring. No special training is 

required to work in upland areas during the dust monitoring season, however preconstruction wildlife and rare plant surveys are required if placement of new facilities at 

any time of year will cause new ground disturbance. 

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