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UNITED STATES ENVIRONMENTAL PROTECTION AGENCY

REGION IX AIR DIVISION

Technical Support Document

For

EPA’s Notice of Proposed Rulemaking

For the

California State Implementation Plan

Great Basin Unified Air Pollution Control District

2016 Owens Valley Planning Area PM10 State Implementation Plan

Docket No. EPA-R09-OAR-2016-0660

November 2016

Scott Bohning, Air Quality Analysis Office

Ginger Vagenas, Air Planning Office

Christine Vineyard, Rules Office

Reviewed by Ann Lyons, Office of Regional Counsel
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I. Background

The national ambient air quality standards (NAAQS) are standards for certain ambient air 

pollutants set by the Environmental Protection Agency (EPA) to protect public health and 

welfare. PM10 is among the ambient air pollutants for which the EPA has established healthbased standards. PM10 causes adverse health effects by penetrating deep in the lungs, including 

lung damage, increased respiratory disease, and premature death. Children, the elderly, and 

people with asthma and heart conditions are the most vulnerable. The 24-hour PM10 NAAQS of 

150 micrograms per cubic meter (μg/m3) is attained when the expected number of days with a 

24-hour average concentration above 150 μg/m3per calendar year averaged over a three-year 

period, as determined in accordance with appendix K to 40 CFR part 50, is equal to or less than 

one. 40 CFR 50.6 and 40 CFR part 50, appendix K.

On the date of enactment of the 1990 Clean Air Act Amendments (CAA or “Act”), the Owens 

Valley Planning Area (along with many other areas meeting the qualifications of section 

107(d)(4)(B) of the amended Act) was designated nonattainment for PM10 by operation of law. 

56 FR 11101 (March 15, 1991).

Once an area is designated nonattainment for PM10, section 188 of the CAA outlines the process 

for classifying the area as moderate or serious and establishes the area's attainment deadline. In 

accordance with section 188(a), at the time of designation, all PM10 nonattainment areas, 

including the Owens Valley PM10 Nonattainment Area (NA), were initially classified as 

moderate. In accordance with section 188(b)(1) of the CAA, on February 8, 1993, EPA 

determined the Owens Valley PM10 NA could not practicably attain the PM10 NAAQS by 

December 31, 1994 and reclassified the area as serious. 58 FR 3334 (January 8, 1993).

As a serious area, the Owens Valley PM10 NA acquired a new attainment deadline of no later 

than December 31, 2001. On September 3, 1999, EPA approved the serious area 1998 PM10 Plan 

for the Owens Valley PM10 NA as meeting the requirements for such areas in CAA sections 

189(b) and (c), including the requirements for implementation of best available control measures 

(BACM) in section 189(b)(1)(B) and MSM in section 188(e). In the same action, EPA approved 

the submission with respect to the requirements of section 188(e) and granted California’s 

request to extend the attainment date for the area to December 31, 2006. This final action and the 

proposal preceding it provide a more detailed discussion of the history of PM10 planning in the 

Owens Valley PM10 NA.1

On June 6, 2007, EPA found that the Owens Valley PM10 NA failed to attain the 24-hour PM10

NAAQS by the applicable attainment date of December 31, 2006 (72 FR 31183). Accordingly, 

the State was required to submit a new plan meeting the requirements of section 189(d) by 

December 31, 2007.

 

1 See 64 FR 34173 (June 25, 1999) and 64 FR 48305 (September 3, 1999).
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The Governing Board of the Great Basin Unified Air Pollution Control Disrtrict (GBUAPCD)

adopted the “2008 Owens Valley PM10 Planning Area Demonstration of Attainment State 

Implementation Plan” (2008 Plan) on February 1, 2008. The 2008 Plan, which included a 

request for an attainment date extension was submitted by the State to the EPA on June 11, 2009. 

The 2008 Plan was subsequently updated and superseded by the submittal of the 2016 PM10

Plan, which reiterates the request for an attainment date extension and incorporates agreements 

reached between the GBUAPCD and the City of Los Angeles. This technical support document 

sets forth the EPA’s evaluation of two elements of the 2016 PM10 Plan: the attainment 

demonstration and the control measure analysis.

II. Attainment Demonstration Analysis

A key part of a PM10 attainment plan is the attainment demonstration. This is a demonstration by 

the State that the existing and planned emission control measures are sufficient to result in 

attainment of the PM10 NAAQS by the required attainment date, in this case 2017. Under CAA 

§189(b)(1)(A), the attainment demonstration for Serious nonattainment areas must include air 

quality modeling. As discussed in Chapter 4 of EPA’s PM10 SIP Development Guideline (EPA450/2-86-001, June 1987, hereafter “PSDG”), the preferred attainment demonstration approach 

is dispersion modeling, with receptor modeling or emission inventory approaches as adjuncts. 

Dispersion models account for emission source characteristics, meteorology, and optionally 

chemistry to characterize how emissions disperse in the atmosphere, in order to estimate 

concentrations at desired receptor locations; they can generally can be used even where are no air 

quality monitors. 

Emissions from fugitive dust sources are uncertain and variable in comparison with the typical 

industrial point sources to which dispersion modeling is usually applied, so modeled 

concentration estimates can also be uncertain for fugitive dust-dominated areas. Receptor models 

focus on monitored receptors and generally rely on differences between chemical compositions 

of source emissions to distinguish the impacts of the different sources at a monitor. However, in 

a fugitive dust-dominated area there are little or no chemical differences between the various 

emitting source regions within the area, so receptor modeling is of limited use. Emission 

inventory-based modeling approaches, such as the “rollback” of monitored concentrations in 

proportion to emissions, have been used in fugitive dust and other PM10 nonattainment areas, 

despite the drawback of assuming that all emissions contribute equally to monitored 

concentrations, independent of source distance. A variant of these approaches is to use a 

dispersion model to estimate the relative or percent contribution of sources to monitored 

concentrations, rather than their absolute contribution in μg/m3. This accounts for the spatial and 

temporal variation of emissions and their various distances from the monitor(s), and also reduces 

uncertainty in the results since they are tied to actual monitored values. In all of the approaches, 

projected emissions reductions due to control measures are applied to the emission source 
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contributions, and attainment is demonstrated if the resulting concentrations are below the 

NAAQS.2

A. Modeling in Submittal

The modeled attainment demonstration is described chiefly in Chapter 7 of the 2016 PM10 Plan, 

with additional details in Appendix VIII-1, the 2003 SIP Modeling Protocol,3and in several 

references provided on the District’s web site. The discussion in Plan section 5.3.4, “Off-lake 

Sources,” is also relevant. 

The modeling approach is described as a “Hybrid Model,” combining the CALPUFF dispersion 

model with a monitored component. CALPUFF is used to model the effect of emissions from 

sources on the Owens Lake bed and the Keeler Dunes. For both of these, detailed emissions 

estimates are available from the District’s Dust ID Program, described in the 2016 PM10 Plan 

section 7.2 and in the Owens Lake Dust ID Program Field Manual4as well as in articles.

5 The 

monitored component is used to represent the effect of other sources off the lake bed (“out-ofnetwork”), which are not otherwise included in the CALPUFF modeling; it is a time-varying 

background concentration that declines over time as lake bed emissions are controlled.

The Dust ID Program has been carried out over the past two decades, and comprises several 

elements to identify emitting areas of the lake bed and to estimate PM10 emission factors for 

input to the dispersion model. The emission factors (also called “K factors” and denoted Kf) take 

the form of PM10 emissions per sand movement. Sand movement is a key parameter since 

bouncing sand particles moved by the wind knock soil particles loose and are the main driver of 

PM10 dust emissions. In the Dust ID Program, sand movement (horizontal sand mass flux per 

area) is estimated by the combination of “Cox Sand Catchers” to collect moving sand and 

measure its mass over a month, and “Sensits” that electronically record hits by individual sand 

grains over a 5-minute interval. Placed in every 1 km grid square that is actively emitting (there 

 

2 Monitored concentrations meet the 24-hour PM10 NAAQS when the “design value,” the expected number of daily 

exceedances of the NAAQS level of 150 μg/m3, is no more than one per year, 40 CFR 50.6. However, for a modeled 

attainment demonstration, when five years of meteorology are modeled, the 6th highest concentration is used as the 

“design concentration” to compare to the NAAQS level; at most five exceedances of that level are acceptable for

attainment, one per modeled year. Guideline on Air Quality Models, 40 CFR 51 Appendix W, section 7.2.1.1, 

“Design Concentrations for SO2, PM10, CO, Pb, and NO2” The design concentration is sometimes referred to as the 

“design value,” but strictly speaking the PM10 design value is the expected number of exceedances per year

3 Owens Valley PM10 Attainment Demonstration Draft Modeling Protocol, prepared for the Great Basin Unified 

Air Pollution Control District by MFG, Inc., Lynnwood, Washington, March 16, 2001

4 Great Basin Unified Air Pollution Control District, Owens Lake Dust ID Field Manual, Bishop, California, 

January 24, 2007. Previous versions of this were known as the “Dust ID Protocol”, for example, the “2008 Owens 

Lake Dust Source Identification Program Protocol,” which appears within the appendixes to Plan Appendix V-1 

“OVPA 2016 SIP BACM Assessment.”

5 Ono, et al., “Locating and Quantifying Wind-Blown Dust PM10 Emissions at Owens Lake, California”, 

A&WMA’s 96th Annual Conference & Exhibition, June 2003, San Diego, California, Paper #69487, Air & Waste 

Management Association, Pittsburgh, Pennsylvania, June 2003; Gillette et al., "A combined modeling and 

measurement technique for estimating windblown dust emissions at Owens (dry) Lake, California", Journal Of 

Geophysical Research, Vol. 109, F01003, doi:10.1029/2003JF000025, 2004
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are as many as 230 of them), together they provide space- and time-resolved estimates of sand 

movement throughout the area of the lake bed. The PM10 emissions part of the PM10 per sand 

movement emission factor is back-calculated using initial runs of the CALPUFF model, in 

combination with PM10 concentrations measured at 13 monitors ringing the lake shoreline. (In 

simplified form, the back-calculation uses the CALPUFF-estimated dispersion between a grid 

square and a monitor to give a value for concentration per emissions; the monitored 

concentration is divided by this value to give emissions.) In practice there is a good deal of 

variation in the calculated emission factors for the various hours and grid squares and monitors, 

so the procedure is carried out separately by season of the year, and broadly similar lake bed 

areas are grouped together into seven general source regions. Wind direction data, observed 

surface erosive characteristics, video recordings, and direct observation of emissions are used to 

help define the boundaries of the subareas and the grid squares that are contributing emissions 

during a given PM10 episode. The 75th percentile of the set of hourly emission factors is taken as 

the final emission factor for a given season and subarea. (This gives conservatively high 

emissions in comparison with the median or 50th percentile that nominally would best fit the 

data.)

Once the PM10 per sand movement emission factors are estimated, they are used in combination 

with the sand movement measurements to calculate emissions at the various lake bed emitting 

areas. The irregularly shaped emitting areas are represented by multiple 100 m or 50 m squares, 

and modeled as area sources in the CALPUFF model to estimate the lake bed portion of PM10

concentrations. To predict future concentrations for a given year, emissions from each source 

square are adjusted downward to reflect the control efficiency of the measure employed in that 

square, and the model is run again.

The 2016 PM10 Plan applies the CALPUFF model over a large rectangular domain (21 mi by 30 

mi, or 24 km by 48 km) encompassing the lake bed and nearby high terrain. Receptors (locations 

for which the model calculates a concentration) are at the same locations as the PM10 monitors. 

Previous plans used many additional receptors ringing the lake bed, but concentrations from the 

other components of the Hybrid Model (described below) are available only at monitors. The 

Plan uses CALPUFF model version 6.42 with default settings; an advantage of this version over 

CALPUFF version 5 used in previous plans is its ability to accommodate five-minute 

meteorological data and so better simulate chaotic dust storms observed in imagery recorded by 

the District. (Plan App. VII-1, p.VII-13). The meteorological input to the model includes a threedimensional wind field based on five-minute wind and other measurements at 16 stations on or 

near the lake bed. For each year with a given set of emissions controls in place, five years of 

meteorology (July 2009 to June 2014) are modeled.

In addition to CALPUFF, the 2016 PM10 Plan’s Hybrid Model includes a component to address 

the “out-of-network” contribution, i.e. the impact from emission source locations not covered by 

the lake bed Sensit network. To account for the effect of PM10 emission sources not explicitly 

represented in the CALPUFF input, a background concentration is added to the CALPUFF 
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model prediction. In previous plans the background was a constant value of 20 μg/m3, derived 

from monitored concentrations and chosen to minimize the contribution of off-lake emission 

sources. This allowed the District to build a strong case for the controls on the lake bed itself that

were definitely needed for PM10 NAAQS attainment, regardless of the impact of off-lake 

sources. In the 2016 PM10 Plan, to more fully account for those off-lake sources and ensure that 

the attainment demonstration is valid when such sources are included, the background varies by 

day and monitor location. It uses the concentration average over hours during which wind is 

blowing toward the monitor from off-lake directions, but is kept to at least 20 μg/m3. 

To predict future concentrations for this “out-of-network” contribution, the 2016 PM10 Plan 

makes two important assumptions for this off-lake source component. First, it is assumed that, 

aside from the minimum 20 μg/m3, the principal PM10 contribution from off-lake sources is from 

locations relatively near the lake shore. This is supported by a District review6of past analyses of 

source contributions to air quality, nearby land use, and direct observation by cameras. It is also 

supported by a modeling analysis undertaken by the Maricopa Association of Governments 

(cited in the Plan in section 6.3.4 at p.56) showing that for fugitive dust areas the impact of 

emissions falls off rapidly with distance, by a factor of 10 at 0.5 km away, and by another factor 

of 10 at 2.8 km away. Accounting for emissions within a 2 km buffer area around the lake bed 

therefore captures the emissions that are likely detectable at the shoreline monitors. 

The second assumption is that the emissions from the buffer area will decline over time as 

controls are implemented on the lake bed. The District conducted a study7of the link between 

lake bed sources and off-lake emissions, the latter assessed via concentrations when the wind 

blows toward the Dirty Socks monitor from off-lake directions. A clear decline in PM10 NAAQS 

exceedances during off-lake winds was found after the implementation of lake bed controls; 

exceedances due to off-lake and to on-lake sources declined in tandem. This supports the idea 

that emissions from nearby areas are mainly re-entrained dust deposits that originated from the 

lake bed itself, and will continue to be gradually winnowed out as the lake bed dust supply 

declines. The District estimated the Hybrid Model “out-of-network” component via a

concentration that declines gradually over time (exponential decay with a 3-year time constant, 

estimated consistent with what was seen in the District study).

The District conducted a model performance evaluation8of the Hybrid Model, checking model 

predictions against monitored observations during the five-year period of July 2009 to June 

2014. The evaluation compared various statistics for each monitor site for observed and modeled 

concentrations, such as the mean and the 98th percentile, paired statistics such as linear 

correlation, and plots of predicted against observed concentrations. The District concludes that 

 

6 Holder, “Dust Sources in the Owens Valley Planning Area,” Great Basin Unified Air Pollution Control District, 

Bishop, California, January 2016

7 Ono and Howard, “Off-lake PM10 Reductions in Areas Adjacent to lake bed Dust Controls,” Great Basin Unified 

Air Pollution Control District, October 9, 2015

8 2016 PM10 Plan, Appendix VII-1: Air Quality Modeling Report, sec. 5.
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performance is good, with high correlation (83%), predictions mostly within a factor of two, and 

very good agreement at the highest concentrations (as seen in quantile-quantile plots). This 

agreement held despite slight over-prediction at the high concentrations, which in any case 

would tend to make the attainment demonstration conservative.

In the attainment demonstration, concentrations were estimated only at monitor locations; this is 

partly inherent in the Hybrid Model, for which the “out-of-network” monitored component is 

available only at monitors. The District characterizes the Hybrid Model as a combination of 

dispersion and receptor modeling that is consistent with the PSDG. The Plan states that the 

monitor locations were chosen to be downwind of the largest PM10 source areas, so that they 

represent the highest PM10 concentrations in the area. (Plan p.62)

The attainment demonstration examined the effect of the controls that would be in place by the 

end of 2017, the attainment deadline. Each of the five meteorology years was modeled, and for a 

given receptor the highest sixth-high concentration taken as the design concentration. The design

concentration results for each monitor site for 2014 through 2019 are shown in the table 7-5 of 

the 2016 PM10 Plan. For 2017, the highest the design concentration is 142 μg/m3and all 

concentrations are less than 150 μg/m3, demonstrating attainment of the PM10 NAAQS,

B. Evaluation of Modeled Attainment Demonstration

In recognition of the uncertainties in modeling for fugitive dust areas, EPA’s Guideline on Air 

Quality Models, 40 CFR Part 51 Appendix W, section 5.2.2.2.e. notes that a model may need to 

be developed for the specific situation, and recommends that the proposed procedure be cleared 

with the EPA Region Office in advance. The dry Owens Lake bed presents a unique situation, 

for which unconventional modeling approaches may be appropriate. EPA has consulted with the 

District and CARB on the modeling approach numerous times over the past decade, including 

during the year prior to the current Plan submittal.

1. Model Emissions Input

The District’s Dust ID Program, described above, provides estimates of PM10 emissions based on 

real-time measurements at numerous locations. It provides a level of detail and accuracy that is 

unique, and is a considerable refinement over standard emission factors, and even over localespecific emission factors that account for soil type and wind speed. It provides a strong 

foundation for the emission estimates needed for a modeled attainment demonstration.

2. Model Choice

The Plan’s method for estimating PM10 emission factors, back-calculation from monitored 

concentrations, depends on good characterization of source-receptor relationships (emitting 

source square and monitor receptor), to determine which particular emitting areas are 

contributing to a given monitored concentration. A (Lagrangian) puff model like CALPUFF, 

which allows PM10 emissions to follow a realistic curved trajectory between the source area and 
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the monitor, and allows different wind direction to vary by location at any given time, is 

appropriate for this. Only a crude approximation would be possible using a steady-state Gaussian 

model like AERMOD (which has identical “straight-line” trajectories within any given hour for 

all sources). The same reasoning applies to the choice of CALPUFF for modeling those 

emissions in the attainment demonstration phase. EPA’s Guideline on Air Quality Models (40 

CFR 51, Appendix W), section 7.2.8 cites CALPUFF as an appropriate model in case of 

inhomogeneous or complex winds. Even though the Owens Lake bed and nearby areas are flat 

terrain, for which winds are typically homogeneous, the observed variable nature of dust storm 

winds and the need for well-characterized source-receptor relationships call for a more detailed 

treatment of time-varying winds, making Owens Lake a complex wind situation for which 

CALPUFF is appropriate.

The version of CALPUFF used in the Plan is 6.42, whereas the “EPA-Approved” or regulatory 

version is 5.85 as of July 2016.9 As stated above, CALPUFF version 6.42 is able to 

accommodate five-minute meteorological data and so better mimic dust storm characteristics. 

The use of five-minute winds provides a refined characterization of source-receptor relationships 

for both the emission factor and the predictive attainment demonstration phases. This use 

strengthens the rationale for the Plan’s use of the chosen CALPUFF version. EPA also notes that 

in this Plan, CALPUFF is not being used for long range transport (distances of 50 km or more) 

and does not use chemistry, so it is not subject to some of the concerns expressed in EPA’s 

proposal10 to remove CALPUFF from 40 CFR Appendix W as a “preferred” model for longrange transport, and in EPA’s consideration there of chemical transport models other than 

CALPUFF. EPA finds that the Plan’s choice of model and its version are appropriate for the 

Owens Lake attainment demonstration.

3. Modeling domain and background concentration. 

While the Dust ID Program’s emission methodology used in the Plan is an excellent one, it is 

applicable only where the Sensit network extends, and so does not include any off-lake sources 

areas other than the Keeler Dunes. Similarly, the modeling domain includes only the lake bed 

and the immediately surrounding area; and actually, within that domain, only the lake bed and 

Keeler Dunes emissions are explicitly included in the model input. In order for the attainment 

demonstration to account for all the PM10 emission sources contributing to NAAQS violations, 

any other, off-lake, sources must be adequately represented by the background concentration that 

is added to the model prediction. The Plan’s procedure for determining background 

concentration was described above, along with its rationale; it is the “out-of-network” 

component of the Hybrid Model. It quantifies the two assumptions that only near-lake emissions 

contribute effectively to monitored shoreline concentrations, and that those emissions decline 

with time as controls on the lake bed are implemented. EPA finds the District’s reasoning and 

 

9 EPA web site “Preferred/Recommended Models,” “CALPUFF Modeling System 07-26-16 UPDATE”, 

https://www3.epa.gov/ttn/scram/dispersion_prefrec.htm#calpuff.

10 “Revision to the Guideline on Air Quality Models,” proposed rule, 80 FR 45340, July 29, 2015, at 45349.
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supporting documentation for the assumptions convincing. The lake bed and near-lake bed 

emissions are large relative to those of other sources in the area, and the decline with time has 

been documented by the District. The irreducible, non-declining minimum background of 20 

μg/m3represents a measured general regional contribution, the cumulative effect of more distant 

emissions that disperse and deposit out of the atmosphere as they move downwind toward the 

lake. The approach in the Hybrid Model with its background concentration component is 

unconventional, but warranted given the large size of the lake bed emissions relative to other 

source areas in the OVPA, and the extensive monitoring underlying he approach.

For a future effort, additional monitoring could help refine the background concentration. 

Current monitors are almost all at the shoreline, so when wind is blowing toward the lake they 

include the impacts of both the two-kilometer buffer zone and more distant emissions. One or 

more monitors further upwind would be affected by only the latter, and so could provide a “true” 

background concentration independent of both the lake bed and of the buffer with its lake bed 

dust deposits. The difference between the upwind and the shoreline concentrations could provide 

an estimate of the impact from just the buffer area and how it declines over time.

4. Modeling receptors

By default, a grid of model receptors is used to cover much of a nonattainment area, to ensure 

that the NAAQS is attained everywhere in the area. In the Plan, receptors are placed only along 

the lake bed shoreline, and further, only at monitor locations. As stated in the Plan, the 

monitoring sites were chosen to be downwind of the largest PM10 source areas, i.e. the lake bed, 

and so are representative of the highest expected impacts. (Plan p.62 sec.7.1) Since 

concentrations necessarily decline with distance from a non-buoyant source like fugitive dust, 

EPA agrees that the highest PM10 concentrations would be expected at the shoreline. A possible 

objection is that emission source areas downwind of the lake would have an impact that adds to 

the lake bed’s. But in the absence of large concentrated emission sources, the added impact 

would be generally comparable to the impact of similar source areas upwind of the lake, and so 

is adequately represented by the added background concentration in the Hybrid Model. In any 

case, emissions from such source areas are small relative to those of the lake bed; undisturbed 

desert has rather low emissions. Also, unlike the lake bed emissions, emissions from non-lake 

bed areas are difficult to quantify sufficiently accurately for explicit inclusion in the CALPUFF 

modeling. Handling them in the background concentration is appropriate. As for limiting 

receptors to monitor locations only, that is inherent in the Hybrid Model approach, which relies 

on monitored concentrations, and could be considered a variant of a receptor modeling approach 

as recommended in the PSDG. In any case, nearby shoreline locations would be expected to be 

little different than at the shoreline monitors, since all shoreline locations are just downwind of 

the lake bed; the large number of monitor locations provides sufficient spatial coverage of 

concentrations for the attainment demonstration.
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III.Best Available Control Measures (BACM) Analysis

A. Background

The Federal Clean Air Act (CAA) section 189(b)(1)(B) requires areas designated as Serious 

nonattainment for PM10 to implement BACM11 on all significant sources of direct PM10 and 

PM10 precursors. The CAA does not define a BACM-level of control for specific sources. In our 

guidance for serious PM10 nonattainment area plans, EPA defined BACM to be, among other 

things, the maximum degree of emission reduction achievable from a source or source category.

It is determined on a case-by-case basis, considering energy, economic and environmental 

impacts. Consistent with the General Preamble Addendum, a BACM analysis should include the 

following elements for the Owens Valley PM10 NA:

 Preparation of an inventory of PM10 sources; 

 Identification of source categories having a greater than de minimis impact on ambient 

PM10 concentrations;

 Comparative analysis of the controls implemented in the Owens Valley PM10 NA and 

BACM in other serious nonattainment areas for significant source categories; and 

 Evaluation of reducing emissions from a particular source category and costs associated 

with controls.

A summary of the GBUAPCD BACM analysis, which addresses the four elements described in 

the General Preamble Addendum,12 is included in the NPRM. In this TSD, we provide a more 

detailed description of the lake bed controls.

B. Rule 433 Controls

Lake bed controls are set forth in GBUAPCD Rule 433, which is included in the 2016 PM10

Plan. EPA has approved Rule 433 into the SIP in a separate action.13 Rule 433 requires the 

control measures described in Chapter 6 of the 2016 PM10 Plan and summarized below to be 

implemented by the City on various portions of the dry Owens Lake bed.14

The controls in Rule 433 have been required in phases as modeling and empirical evidence have 

demonstrated the need for additional controls.

15 The 2003 Dust Control Area (DCA) 

encompasses 29.8 square miles; the 2006 DCA and Channel Area encompasses 13.2 square 

 

11 Best available control technology (BACT), which applies to stationary sources, a subset of BACM. 

12 2016 PM10 Plan, page 38.

13 See 81 FR 62849 (September 13, 2016). The final action approving Rule 433 was signed by Alexis Strauss, 

Acting Regional Administrator, on November 10, 2016. It will be published in the Federal Register in the near 

future.

14 Some of these control measures are also described in our proposed approval of the 1998 Plan (64 FR 34173, June 

25, 1999).

15 2016 PM10 Plan, Figure 7-6.
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miles; the Phase 8 area encompasses 2.0 square miles, and the Phase 9/10 area encompasses 3.62 

square miles.16

1. Shallow Flooding

Shallow flooding is designed to mimic natural physical processes that wet the surface of the lake 

bed and create resistance to wind erosion. This control measure requires the application of water 

to the surface of the lake bed in amounts and by means sufficient to achieve 99 percent control 

efficiency, except for certain defined sub-areas, which are allowed to achieve a control efficiency 

of less than 99 percent.17 Generally, in shallow flooding areas at least 75 percent of each square 

mile must continuously be covered by evenly distributed standing water or surface-saturated soil 

between October 16 each year and May 15 the next year. In order to conserve water, GBUAPCD 

has developed a Dynamic Water Management (or “DWM”) approach for the flooding period. 

Under DWM, specific areas that have a history of low emissivity may be allowed to delay the 

start date for flooding and have an earlier end date. If a DWM area becomes susceptible to wind 

erosion outside the modified dust control period, flooding will be required. 

2. Minimum Dust Control Efficiency (MDCE) BACM

In limited, defined areas, control efficiency targets are based on air quality modeling and may be 

less than 99%, but are established to prevent exceedances of the NAAQS. Specifically, within 

the 2006 DCA, MDCE BACM is allowed in certain Shallow Flooding areas, in an area where 

sand fences are used to control dust, and in the 0.5 square mile Channel Area. The purpose of 

MDCE BACM is to “reduce water use and to address environmental concerns in sensitive 

wetland areas.”18 

3. Managed Vegetation BACM

As noted by GBUAPCD, vegetative cover can provide an “effective barrier that keeps surface 

wind speeds from reaching the threshold friction velocity required to generate emissions and 

traps sand and sand-sized soil particles.”19 Based on its observation that the areas on the dry lake 

bed where vegetation has naturally become established are not very emissive, the District 

developed a Managed Vegetation control measure. In order to achieve the 99 percent control 

efficiency required under Rule 433, areas utilizing Managed Vegetation BACM are required to 

maintain 37 percent overall average vegetation cover. Only pre-approved, locally adapted native 

plant species can be planted for dust control. Compliance is assessed using ground-truthed 

satellite imagery.20

 

16 2016 PM10 Plan, Figure 10-1.

17 Id. Limited exceptions to the 99% control efficiency requirement are provided. See the description of Minimum 

Dust Control Efficiency (MCDE) BACM (p. 55) and Figure S-2.

18 Id., page S-14.

19 Id., p. 46.

20 Id. Additional information is included in Appendix VI-1. 
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4. Gravel Cover

Application of gravel to the dry lakebed prevents PM10 emissions by preventing the formation of 

efflorescent evaporite salt crusts and by establishing a layer of large particles (at least 1⁄2 inch in 

diameter) that are too heavy to be transported by wind and that protect the finer particles of the 

lake bed. The Gravel Blanket control measure requires that the entire area implementing this 

measure must be covered with either a layer of gravel at least four inches thick or a layer of 

gravel at least two inches thick underlain with a permanent permeable geotextile fabric, 

sufficient to achieve 100 percent control efficiency.

Tillage with BACM (Shallow Flooding) Backup (TWB2) and Brine BACM. In those areas that 

have the infrastructure in place to implement Shallow Flooding BACM, the City is allowed to 

employ alternative approaches to controlling lake bed emissions. TWB2 allows the City to 

stabilize the surface of the lake bed by mechanically creating large soil clods. Brine BACM 

involves the creation of wet or non-emissive salt deposits that achieve a control efficiency level 

99%, or, in shallow flooding areas within the 2006 DCA, the specified control efficiency. In both 

cases, shallow flooding must be implemented if the established erosion control threshold is 

exceeded or performance requirements specified in the rule are not met. 

5. Consideration of Alternatives

Over the years, the District has considered and tested several other control measures on the dry 

lake bed including surface compaction, application of chemical dust suppressants, and the use of 

sprinklers. As noted in the 2016 PM10 Plan, the 1998 SIP documented the determination that 

these methods were found to be ineffective.21

6. Implementation Schedule

Control measures required in the 2003 DCA, the 2006 DCA, and in the Phase 8 area have largely 

been implemented. The approval of Rule 433 into the SIP will ensure continued implementation 

and will expand the controlled area on the lake bed an additional 3.62 square miles. GBUAPCD 

estimated that the PM10 emissions reduction strategies made further enforceable by the submitted 

GBUAPCD Rule 433, Control of Particulate Emissions at Owens Lake, are, with some 

exceptions, 99 to 100 percent effective in controlling emissions.

22 Rule 433 requires the 

implementation of all required controls, including those established under Phase 9/10, by no later 

than December 31, 2017.23

 

21 Id., Appendix V-1, “OVPA 2016 SIP BACM Assessment,” p 16.

22 Id., p.12 and Figure 7-5.

23 Within required control areas, significant cultural resources have been discovered on the lake bed, making these 

areas eligible for listing under the California Register of Historic Resources. Rule 433 provides for a deferred

schedule of control measure implementation in these localized eligible cultural resource (“ECR”) areas, which 

presently consist of approximately 277 acres. If, after implementation of BACM on adjacent areas, modeling or 
13

 

monitoring demonstrates controls are needed in an ECR area to attain or maintain the PM10 standard, the City will 

be required to implement BACM.