Dust ID Field Manual Draft - January 24, 2007 

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GBUAPCD, 2007_Dust ID Field Manual-FINAL DRAFT.docDust 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 PM 10 and Meteorological Conditions............ 17

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

3.2 Methods and Instrumentation for PM 10 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 S ource 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 Fi eld 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 PM 10 Emission Rates...................... 23

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

5.2 Method for Determining PM 10 Emissions and New K-factors................ 23

5.2.1 PM 10 = 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 Even t-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 an d Rationale for Model Selection..... 28

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

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

6.4 Background PM 10 Concentrations................................................ 31

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

6.6 Estimation of PM 10 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 W ildlife 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 mon itoring 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 Li nearity 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 Configur ation 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 Availabl e 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 passiv e 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 K f Weighted-average of hourly K-f actors for a dust event, weighted by the hourly PM 10 concentration

Exceedance Modeled or monitored PM 10 > 150 μg/m 3 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 c onstant for sand flux and PM 10 emissions, K f LADWP City of Los Angeles Departme nt 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 PM 10 Planning Area

PC Particle count

PM 10 Particulate matter less than 10 microns aerodynamic diameter QA Quality Assurance RASS Radio Acoustic Sounding System

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RSIP Great Basin AP CD 2003 Owens Valley PM 10 Planning Area Revised State Implementation Plan

Sensit An electronic sand motion detector. Settlement Agreement 2006 Settlement Ag reement between LADWP and GBUAPCD Storm-average K f 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 PM 10

. USEPA United States Environmental Protection Agency USGS US Geological Survey

WD Wind direction

2003 SIP Great Basin AP CD 2003 Owens Valley PM 10 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 Sour ce Identification (Dust ID) Program is to identify dust source areas at Owens Lake that ca n cause or contribute to violations of the National Ambient Air Quality Standards (NAAQS) for PM 10 . 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 PM 10 State Implementation Plan (R SIP) 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 contri bute to an exceedance of the PM 10 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 im plemented in accordance with the RSIP and Settlement Agreement, the District will su spend 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 co llected during this pe riod 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 subjec t to dust control requir ements as provided for in the Settlement Agreement and any future revisions to the Owens Valley PM 10 State Implementation Plan.

1.2 Locating Dust Source Areas

A network of sand flux samplers, PM 10 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 monito rs at 136 lake bed sites at 1-km spacing, 7

PM 10 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, PM 10 and met

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sites will be added as necessary to collect in formation that can be used to monitor and model the impact from new areas that ma y become emissive on the lake bed. (See Appendix A, SCR - Conditions.)

The automated monitoring network will be au gmented 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) da tabase 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 PM 10 concentrations at shoreline and off-lake monitoring sites may

show that lake bed source areas cause or contribute to PM 10 exceedances. Monitoring of

PM 10 concentrations will be done using US EPA-approved monitors. Currently, hourly

PM 10 readings are obtained using TEOM (Tap ered-Element Oscillating Microbalance)

PM 10 monitors manufactured by R&P, Inc. If a PM 10 exceedance is monitored, PM 10 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 PM 10 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). PM 10 concentrations during any hour with

winds from a non-lake wind direction will be assumed to have an average background concentration of 20 μg/m 3 and from-the-lake wind directio ns will be given their hourly value. If the adjusted 24-hour average is greater than 150 μg/m 3 , then an exceedance will

have been monitored from a lake bed source or sources. (See Appe ndix B, SCR - Section 1.1.)

If a lake bed source area causes or co ntributes to an exceedance, hourly PM 10 concentrations and wind directions will be revi ewed to see if a new source area (or areas)

is associated with that exceedance. If sa nd flux data are available that show erosion activity in the direction of a ne w source area, this event will also be modeled as described in the air quality modeling protocol. If the PM 10 monitor data indicate that a new source

area caused or contributed to an exceedan ce, dust control measures (DCMs) may be required under the provisions of the Sett lement Agreement or current SIP.

1.4. Modeled Exceedances

Air quality modeling will be pe rformed with the CA LPUFF 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 shorel ine exceedances since the peri od covered by the last model

run. PM 10 emissions for the model will be base d on hourly sand flux measured at lake bed sites and spatial and temporal factor s derived using the em pirical relationship

between sand motion on the lake bed and measured PM 10 values. CALPUFF will be run using the following equation to es timate emissions and to model PM 10 impacts at the

shoreline:

Equation 1.1

PM 10

= K f × q where,

q = Sand flux measured at 15 cm above the surface [g/cm 2 /hr]

K

f = K-factor, empirically-d erived ratio of the PM 10 emission flux to the

sand flux at 15 cm.

The ratio of PM 10 to sand flux ( K f ) is referred to as the K-factor. The initial Dust ID program results showed that K-factors coul d be derived empirical ly by comparing model predictions to monitored PM 10 concentrations. Initial studi es 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 PM 10 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 th at 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 prov ide 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 de lineated by field observations.

1.6 Dust ID Field Manual Content

Section 2 of this Field Manual describes the methods and instrument ation 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 PM 10 and meteorological monitoring network that will be used to

monitor PM 10 exceedances, develop K-factors and to call public health advisories.

Section 4 describes methods that will be us ed 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 usi ng air quality modeling and monitoring data Section 6 provides the protocol for disp ersion modeling. Appe ndix A contains the

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Owens Lake Settlement Agreement, which a pplies to data collected from July 2006 through April 1, 2010. Appendix B contains th e provisions of the Supplemental Control Requirements that was approved with the RSIP.

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GBUAPCD, 2007_Dust ID Field Manual-FINAL DRAFT.doc 5 Figure 1.1 Owens Lake Dust ID monitoring network.Dust ID Field Manual Draft - January 24, 2007

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

Cox Sand Catcher Network

2.1 Objective

Sand flux measurements will be used as a surrogate to estimate PM 10 emissions coming off the lake bed. The objective of the sand fl ux 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 diffe rent locations on the

lake bed. The 2003 Sensit/CSC network lo cations 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 th e 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 Progr am 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 possibl e 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 th at 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 La ke 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 th e ground, an adjustment sleeve is used to keep the inlet height at 15 cm to comp ensate for surface erosion and deposition. Field techs use a standardized measuring device to ch eck 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 Distri ct uses the output (KE or PC) that provides the best precision a nd accuracy for the range of saltation activity expected at each site.

Because the electronic Sensit res ponse 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 th e 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 la ke 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 practi ce 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 patt ern to better represen t sand flux activity in the dust source area. In addition, many of th e original sampling sites that are now in flooded portions of the shallow flood DCM were removed, since PM 10 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 eas t 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 mi ddle 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 collecti on 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 heig ht above the surface to the center of the sensor using the Sensit Height Indicat or Tool, and adjust if necessary to 15 cm. See Figure 2.5. 11) Inspect the sensor and radio transmitter wi ring 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 re placed, 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 Ke eler 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 secti on where the condition of the sampler and any other relevant factors, su ch as surface condition will be documented. The Data Processing Department will calcula te the net sand catch weight from the CSC during data analysis. CSC lab weights, measur ed to the nearest 0.1 g will be recorded on the Lab Form shown in Figure 2.7. After comp letion of the forms, the field technician will make a copy of the completed forms and f ile the copies at the Keeler office. The original forms will be sent to Data Processi ng in the Bishop office. Data Processing will

enter the data into an electr onic file. The original hard copy forms will be filed in the Bishop office.

Each day, dataloggers for all Sensit sites wi ll 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 us ed 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 Pr ocessing as they are completed. It is the technician’s or operator’s res ponsibility 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 pers on receiving the data when delivered to the

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Bishop office. If no person is available to si gn the form in the Bishop office, the delivery person will sign and date the form an d 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 record ed 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 a nd certified at least once every year. Ten percent of the CSC sand catch samples will be st ored 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 Se nsit reading. The hourly sand flux is divided by 1.2 cm 2 , 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 bgntn tn SS CSC SSq [g/cm 2 /hr]

Where,

q n,t = hourly sand flux at site n, for hour t [g/cm 2 /hr]

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

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

S n,bg = Sensit KE background reading fo r 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/cm 2 /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 count s and kinetic energy for each Sensit. Due to

differences in individual Sens it 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 s ites, kinetic energy provides a more linear response for most Sens its. 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 dur ing 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 calcu lated 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 tota l ratio. The cumulative ratio is applied to the Sensit data to estimate the hourly sand flux. If there wa s 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 we ighed 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 neighbori ng 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 ad jacent 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 si tes measure wind erosion activity using CSCs to collect sand-sized particles and Se nsits that electronically detect moving particles. Sensit data are recorded on dataloggers and transmitted by radio from

each site to the Distri ct’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 betw een CSC mass and a Sensit reading using kinetic energy reading (Sensit No. 7291).

y = 0.33x - 0.01

R 2 = 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 labo ratory documentation form.

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3. Protocol for Measuring Ambient PM 10 and Meteorological Conditions

3.1 Objective

Ambient PM 10 monitors will be placed at locati ons generally around the shoreline of

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

PM 10 NAAQS and to develop K-factors for modeling PM 10 emissions from lake bed

sources. PM 10 monitors may be placed on the lake bed for short-term special-purpose monitoring studies.

3.2 Methods and Instrumentation for PM 10 and Meteorological Data

PM 10 monitoring will be performed using US EPA-approved referen ce or equivalent

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

PM 10 monitor sites - Keeler, Lone Pine, Olancha, Dirty Socks, Shell Cut, Bill Stanley and

Flat Rock. Each PM 10 site is equipped with a Tapered Element Oscillating Microbalance (TEOM) PM 10 monitor. TEOM monitors are capable of measuring hourly PM 10 concentrations. The Dust ID Program w ill rely on the TEOM to determine if an exceedance is caused by a lake bed source, si nce the data can be correlated with hourly

wind directions to determine dust source dire ctions. TEOM data will also be used to generate K-factors to model the PM 10 emissions from lake bed sources.

Ten-meter meteorological towers will be located near each PM 10 monitor site and at other

locations around the lakeshore and on the lake bed. The current me t 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 wi nd direction. Two lake bed met sites (A & B Towers) measure wind speed at different heig hts (0.5, 1, 2, 5 and 10 m) to determine surface roughness and vertical wind speed pr ofiles. Some met sites also measure temperature, relative humidity, barometric pressure, and/or precipitation.

3.3 Operating Procedures, Instrument Calibration and Quality Assurance

PM 10 monitoring will be performed in accord ance 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 PM 10 data will be delivered to Data Pr ocessing 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. PM 10 data from special-purpose m onitors that may be located

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

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All the PM 10 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 PM 10 , and for alerting the public in case of high concentrations. For hourly concentrations above 400 μg/m 3 the District will issue publ ic health advisories when the communities of Keeler, Lone Pine or Olancha are affected. The public can view real-time wind speed, direction and PM 10 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 th e best available information from visual observations, GPS mapping, and sand flux meas urements to delineate the boundaries of dust source areas for as many events as possibl e. 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 met hods are: 1) visual mapping by trained observers, 2) time-lapse cameras, 3) surface in spections with GPS mapping, and 4) sand flux activity (as measured with Sensits and CSCs).

4.2.1 Mapping Dust Source Areas fro m Off-Lake Observation Sites

One or more trained observers will comple te observations from viewpoints to best

observe the active dust source areas. For instan ce, two observers may be at viewpoints on the east side of the dust plume in the Inyo a nd 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 s hows 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 identi fy source areas that may have been missed by observers, or to help confirm source area activity detected by PM 10 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 PM 10 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 PM 10 concentrations and video will be used as “trigger data” to determine the time and loca tion for a Dust Source Area Survey (survey).

Sensit and PM 10 data will be automatically coll ected 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 PM 10 concentrations over 50 μg/m 3 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 corres pond with the Sensit activity and elevated PM 10 concentration. Video will be used to identif y a source or sources that were not identified by observations, Sensit data or PM 10 information. Wind speed and wind direction data will be used to help determine if a lake bed dust source could have caused elevated PM 10 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 c onditions are favorable . For larger areas, surveying may continue for several days or until precipitation obscu res the boundaries of

the source area.

In addition to the above process, general fi eld inspections will be completed after dust storms to verify lake bed emission activity a nd the need for a survey. A survey will be completed if the trigger data and /or field in spections indicate emissi ve 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 th at 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 obser vation, Sensit data, sand catch data, video,

PM 10 concentration or inspection of the lake bed surface, Great Basin staff will map the exterior boundary of as many of the source ar eas identified as possible during daylight hours, as weather conditions allow. The ma pping will begin as soon as possible after a

dust storm and continue until all the identifie d 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 survey ing 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 unrecogni zable point by precipit ation since the last

identified dust storm.

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GPS line data should be collected at an interv al of one record ever y 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 us ed. 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 stati on) to ensure positional accuracy.

Before beginning a survey, the edge of the s ource 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 evid ent if there is no visible evidence of a

disturbed lake bed surface due to wind dama ge. 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 surv eyor visually determines where a surface with 70 to 80 percent of undisturbed surf ace 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, Bounda ry 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 ma y 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. Mappi ng would be stopped at this point until a Distinct or Diffu se Boundary can be located.

Generally the surveyor will maintain a constant course of travel following the Distinct Boundary of the wind-damaged area. As th e 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 ac tive 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 bounda ry cannot be mapped during the existing

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survey and why. If the boundary cannot be ma pped, the survey shall end at that point leaving an unclosed source area polygon.

It is possible for the surveyor to find himsel f 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 trav eling 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 er osion evidence was not observed earlier along their path. If the surveyor were outside the s ource 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 c onditions. The time a nd 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 resu me 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 pr oduced between the point where the GPS unit was paused and then restarted would be dele ted and considered un-surveyed during post processing.

The presence of Indistinct Boundaries or c onditions that cause the ending of a survey must be annotated on the GPS data or expl ained in the field not es, 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 de fault 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 th ere 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 thr ough November. A new composite map will be developed for each period containing only thos e 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 ma ps 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 PM 10 Emission Rates from Sand Flux

Data

5.1 Objective

The objective of this portion of the Dust ID Program is to estimate the PM 10 emission flux for each cell or source area using the relationship PM 10

emission flux = sand flux x K-factor . PM 10 emissions for each area will be used with the CALPUFF modeling system or other USEPA approved model to determine if the PM 10 emissions will cause or contribute to a NAAQ S violation at the shoreline.

5.2 Method for Determining PM 10 Emissions and New K-factors

5.2.1. PM 10 Emission Flux = Sand Flux x K-factor

PM 10 emissions will be estimated using th e 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 discu ssed in this section, and default K-factors

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

5.2.2. Default Temporal and Spa tial Storm-average K-factors

PM 10 emissions may be estimated from defau lt K-factors that were developed from previous dust events that occurred in th e 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 site d 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 propos ed cut-points within 30 da ys. If no agreement can be reached within 60 days, the default periods will be used.

The two default periods to be used are: the wi nter/spring period that includes the months of December, January, February, March a nd 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 PM 10 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 PM 10 emissions. Modeled PM 10 predictions can then be compared

to monitored concentrations at PM 10 monitor sites to determine the K-factor that would correctly predict the monitored concentra tion 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 th e 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-processi ng step to determine the K-factor value that

would make the modeled concentration matc h the monitored concentration at the PM 10 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,

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

C obs. = Observed hourly PM 10 concentration. [μg/m 3 ]

C bac

. = Background PM 10 concentration

C mod. = Model-predicted hourly PM 10 concentration. [μg/m 3 ]

5.2.6. Screening Hourly K-factors

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

a PM 10 monitor. These hourly K-factors will be screened to remove hours that did not have strong source-receptor re lationships between the active source area (target area) and

the downwind PM 10 monitor. For example, the screen ing criteria will exclude hours when

a PM 10 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 PM 10 concentrations were both greater than 150 μg/m 3 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/cm 2 /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/cm 2 /hr.

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

7) More than 65 percent of the PM 10 contribution at a mon itor site came from the target source area (North Area, South Area, Central Area or Keeler dunes).

8) Eliminate hours when sand flux data are missi ng 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, whic h are both located 5 to 10 km from the lake bed, the distance limitation is cha nged to 10 km upwind of the shoreline.

Table 5.1 Wind Directions for the Initial K-factor Screen

PM 10 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 scr eening criterion 3) are shown in Table 5.1. From-the-lake wind directions for any new PM 10 sites will be determined by

the APCO as needed for the initial K-fact or screen. Note that ‘From-the-Lake’ wind directions in the Supplemental Control Requi rements in Appendix B are different from these K-factor screening wind directions.

Hourly K-factors that pass th rough the screening criteria wi ll 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 wi ll be calculated as the arithmetic average using all the hours when the hourly K-factor pa sses the screening criteria for the target

area.

5.3.2 Temporal & Spatial 75-Percentile K-factors

The statistical 75-percentile va lue 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 75 th percentile will be calculat ed using the Microsoft Excel

PERCENTILE function. The Microsoft Excel PERCENTILE function works by sorting

values from lowest to hi ghest, then assigns the 0 th percentile is the lowest value, the 100 th
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 k th lowest value in the list. Thus, each value is placed 1/(n-1) apart. If a request ed percentile does not lie on a 1/(n-1) step, then the PERCENTILE function linearly inter polates between the neighboring values.

5.3.3 Default K-factors

Table 5.2 shows the default K-factors for each of the K-factor ar eas and periods. These K-factors are derived for the temporal and spa tial 75-percentile values from the screened hourly K-factors for the 30-month Dust ID pe riod 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 th e SCR. The modeling techniques will be used both diagnostically to infer emission rates for source areas and prognostically to predict PM 10 concentrations at the histor ic shoreline. Following an overview of the modeling approach, the remai nder 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 Progr am. CALPUFF is the USEPA recommended modeling approach for long-range transpor t 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 app lied to near-field dispersion problems where the th ree-dimensional qualities of the wind field are important and for stagnation episodes when pollutant s remain within the modeling domain over periods of several hours or more. Dust ev ents 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 Fi gure 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, terr ain features that act to ch annel 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 meteor ological preprocessor program and the procedures employed in the RSIP. CALM ET combines surface observations, upper air observations, terrain elevations , and land use data into the format required by CALPUFF. Winds are adjusted objectively using co mbinations 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 depositi on 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 Dist rict may also install

additional stations to better characterize wi nds 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 remain ing stations. In additi on to the District’s network, surface data from other field pr ograms 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 va riable used by CALMET to estimate the surface energy fluxes and, along with ceiling hei ght, is used to calculate the Pasquill stability class. Hourly cloud cover and ceili ng 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 significan tly 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 CALPUF F dispersion model. CALPUFF considers spatial changes in land use, including th e surface roughness, and the input data are specified on a horizontal grid. The terrain data influence the constr ucted wind fields and plume trajectories in regions of sparse obser vations. Land use and terr ain 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 resulti ng grids have been plotted and checked against data from the District’s GIS data base where the modeling domain overlaps the

District’s data. The 1-km me sh size terrain used by CALMET and CALPUFF is shown in Figure 6.1.

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

construction of the wind fields and estimati on of mixing heights with CALMET. In the RSIP, both local and regional data were collected as follows:

• A 915 MHz Radar Wind Profiler and Radi o Acoustic Sounding System (RASS) were used to collect upper level wind and temperature measurements. The Wind Profiler was initially located at Dirty Sock s then moved to the Mill Site during the

4 th quarter of 2001. The District disc ontinued 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 PM 10 monitoring sites and at the historical shoreline are not usually influenced by upper leve l 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, soundi ngs from China Lake and Desert Rock

will be used to construct the data set. Th e 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 measurem ents. The default algorithms employed by CALMET based on Similarity Theory often adju st 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 unt il this program is discontinued.

CALMET options. The options employed for the appl ication of CALMET to construct the wind fields were provided in the “Mode ling 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 geometri cally from the surface to 4000 m. The geometric spacing provides better resoluti on near the surface and the upper limit is high enough to be above the boundary layer height.

• Vertical extrapolation of surface winds al oft 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 PM 10 Attainment Demonstrat ion Modeling Protocol

.

Wind fields constructed with CALMET w ill be randomly checked by plotting the

resultant fields and the surface obser vations on a base map. The CALDESK TM software package will also be used to view the CALMET wind fields.

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The application of CALPUFF i nvolves the selection of optio ns controlling dispersion. Although the simulations are primarily driv en by the meteorological data, emission fluxes, and source characterization, the di spersion options also affect predicted PM 10 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 conventiona l Pasquill-Gifford dispersion curves. Sensitivity tests were also performed by applying CALPUFF with dispersion routines based on Similarity Theory a nd estimated surface energy fluxes. These tests did not indicate improved perfor mance 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 depos ition 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. Seve ral 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 lognorma l distribution with a geometric mean diameter of 3.5 μm and a geometri c standard deviation of 2.2.

6.3 Background PM 10 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 PM 10 concentrations observed at the monitoring locations. In the RSIP a c onstant background concentration of 20 μg/m 3
was added to all predictions to account for background sources. The constant background was calculated from the average of the lowest observed PM 10 concentrations for each

dust event when 24-hour PM 10 concentrations at any of the sites were above 150 μg/m 3

. 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 PM 10 concentrations. Such hours were removed and daily average background concentrations were recalculated ba sed on the remaining

data.

Additional PM 10 monitors are proposed for installa tion at Owens Lake. These monitors can be used to measure hourly PM 10 concentrations upwind from lake bed source areas. Some of these monitors may be representative of regional PM 10 concentrations and others may be influenced by local sources that may indicate a higher PM 10 concentration than the regional background level. A method to cal culate background c oncentrations 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/m 3 will be added to the model prediction for each receptor

location.

6.4 Area Source Characterization

CALPUFF simulations at Owens Lake are sens itive 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. CALP UFF contains an area source algorithm that provides numerically precise cal culations 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 obs ervers 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 appl ied 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 ch aracterize and map source areas on the lake

bed:

• Actual source boundaries will be used wh en available to delineate emission

sources in the simulations. Actual sour ce boundaries will be determined using a weight-of-evidence approach consideri ng visual observations, GPS mapping, and

surface erosive characteristics. Erosive ch aracteristics that might be considered when defining a source boundary include prop erties of the soil, surface crusting, wetlands, and the proximity of th e brine pool and existing DCMs.

• Source boundaries will also be defined ba sed 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 representi ng that source area. Cells small than 250 m x 250 m may be used near the shoreline to better represen t source areas where predicted concentrations are expected to be particularly sens itive to the source area configuration.

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6.5 Estimation of PM 10 Emissions

Hourly PM 10 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 PM 10 NAAQS in areas without PM 10 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 shor eline 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 4055UTM North-South (km)

Figure 6.1 Model Domain, elevation cont ours 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. Pu rple lines represent the control area boundary used with the Settlement Agreement.

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Figure 6.3 The Dust ID model evaluates PM 10 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 comple te special training

courses to deal with the uni que hazards and environmental precautions that must be considered when working on the lake bed. Tr aining 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 thei r own safety. Dust storms can start within minutes exposing workers to dust and sand. Li ghtning storms often occur in the summer. Winters have sub-freezing temperatures a nd 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 requirement s is to put safety as the highest priority

at all times.

All personnel that are invol ved with any fieldwork under the Dust ID Program are required to complete all safety training befo re working on the lake. Everyone must report going onto and leaving the lake. Workers are re quired 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 ca ught in a dust storm wh ile leaving the lake. Workers are required to leave the Keeler o ffice when the dust impacts Keeler and the TEOM monitor reading exceeds 1000 μg/m 3 . Respirator training a nd face fits will be completed annually. First Aid and CPR traini ng 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 a ll 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 de fined as any area below the 3600 ft.

contour.

2. Every person or group must call the Bis hop 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 le ft 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 be low, and report the missing person if not notified before the specified time. An a ttempt 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 mi ssing person if the person cannot be contacted by phone. The search will conti nue 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 work ing 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 wo rked 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 permi ssion 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 th e 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 contra ctors are required to take precautions to avoid disturbing western snow y 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 a voidance 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 co mpleting snowy plover training, the plover protection program requires the following:

• Report snowy plover sightings to the Dist rict’s biological re sources monitor for dissemination to all lake bed personnel and for scientific data collection purposes. The biological resources monitor will map a nd mark the sightings in the case of nesting pairs, and will map the last know n 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 conf lict 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 AT V and 4WD vehicle trails to approach and depart monitoring sites. The maxi mum allowable speed on ATV and off-road 4WD on the lake bed is 15 mph dur ing the snowy plover season.

All existing and new Dust ID monitoring insta llations will be fitted with raptor perching deterrent (eg., Nixalite) at potential perch site s with a height of greater than 42 inches above the playa surface. Maintenance of perchi ng deterrents will be routinely performed. Any new construction that causes new gr ound disturbance during the snowy plover season will require a pre-cons truction 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 manne r that is least disturbing to wildlife and plant resources as possible. Potentially affected upland re sources (those located outside the playa) that could be disturbed during any new ground-disturbing construction activities were identified during District en vironmental analyses. The animals that use upland areas vary seasonally, with nesting and foraging birds, mammals, reptiles, and invertebrates occurring duri ng the period of dust monitori ng. No special training is required to work in upland areas during the dust monitoring season, however preconstruction wildlife and rare plant surveys ar e required if placement of new facilities at any time of year will caus e new ground disturbance.

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