1 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 PM 10 State Implementation Plan

Docket No. EPA

- R09

- OAR

- 2016

- 0660

November 2016

Scott Bohning, Air Quality Analysis Office

Ginger Vagenas, Air Planning Office

Christine Vin eyard, Rules Office

Reviewed by Ann Lyons, Office of Regional Counsel2

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. PM 10 is among the ambient air pollutants for which the EPA has established health

based standards. PM 10 causes adverse health effects by penetrating deep in the lungs, including lung damage, increased respiratory dise ase, and premature death. Children, the elderly, and people with asthma and heart conditions are the most vulnerable. The 24

- hour PM 10 NAAQS of 150 micrograms pe r cubic meter (μg/m 3 ) is attained when the expected number of days with a
24

- hour average conce ntration above 150 μg/m 3 per 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 Clea n 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 PM 10 by operation of law. 56 FR 11101 (March 15, 1991 )

. Once an area is designated nonattainment for PM 10 , 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, a ll PM 10 nonattainment areas, including the Owens Valley PM 10 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 PM 10 NA could not practicably attain the PM 10 NAAQS by December 31, 1994 and reclassified the area as serious. 58 FR 3334 (January 8, 1993).

As a serious area, the Owens Valley PM 10 NA acquired a new attainment deadline of no later than December 31, 2001. On September 3, 1999, EPA app roved the serious area 1998 PM 10 Plan for the Owens Valley PM 10 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) an d 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 PM 10 planning in the Owens Valley PM 10 NA. 1

On June 6, 2007, EPA found that the Owens Valley PM 10 NA failed to attain the 24

- hour PM 10 NAAQS by the applicable attainment date of December 3 1, 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).3

The Governing Board of the Great Basin Unified Air Pollution Control Disrtrict ( GBUAPCD ) adopted the “2008 Owen s Valley PM 10 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 P lan was subsequently updated and superseded by the submittal of the 2016 PM 10 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 do cument sets forth the EPA’s evaluation of two elements of the 2016 PM 10 Plan: the attainment demonstration and the control measure analysis.

II. Attainment Demonstration Analysis
A key part of a PM 10 attain m ent plan is the attainment demonstration. This is a d emonstration by the State that the existing and planned emission control measures are sufficient to result in attainment of the PM 10 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 PM 10 SIP Development Guideline (EPA

450/2

- 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 de sired 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 usuall y 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 impac ts 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 m odeling approaches, such as the “rollback” of monitored concentrations in proportion to emissions, have been used in fugitive dust and other PM 10 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 contrib ution of sources to monitored concentrations, rather than their absolute contribution in μg/m 3 . 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 s ince they are tied to actual monitored values. In all of the approaches, projected emissions reductions due to control measures are applied to the emission source4

contributions, and attainment is demonstrated if the resulting concentrations are below the
N AAQS. 2

A. Modeling in Submittal
The modeled attainment demonstration is described chiefly in Chapter 7 of the 2016 PM 10 Plan, with additional details in Appendix VIII

- 1, the 2003 SIP Modeling Protocol, 3 and 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 PM 10 Plan section 7.2 and in the Owens Lake Dust ID Program Field Manual 4 as w ell as in articles

. 5 The monitored component is used to represent the effect of other sources off the lake bed (“out

- of

network”), which are not otherwise included in the CALPUFF modeling; it is a time

- varying background concentration that declines over ti me 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 PM 10 emission factors for input to the dispersion model. The emission factors (also called “K factors” and denoted Kf) take the form of PM 10 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
PM 10 dus t 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 indivi dual 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 PM 10 NAAQS when the “design value,” the expected number of daily exceedances of the NAAQS level of 150 μg/m 3 , 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 SO 2 , PM 10 , CO, Pb, and NO 2 ” The design concentration is sometimes referred to as the “design value,” but strictly speaking the PM 10 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, 20 01

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, Ju ne 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, 20045

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 PM 1 0 emissions part of the PM 10 per sand movement emission factor is back

- calculated using initial runs of the CALPUFF model, in combination with PM 10 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 calcul ated 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, obs erved 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 PM 10 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 PM 10 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 square s, and modeled as area sources in the CALPUFF model to estimate the lake bed portion of PM 10 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 PM 10 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 PM 10 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 storm s observed in imagery recorded by the District. (Plan App. VII

- 1, p.VII

- 13). The meteorological input to the model includes a three

dimensional wind field based on five

- minute wind and other measurements at 16 stations on or near the lake bed. For each yea r 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 PM 10 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 PM 10 emission sources not explicitly represented in the CALPUFF input, a background concentration is added to the CALPUFF6

model prediction. In previous plans the background was a constant value of 20 μg/m 3 , 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 PM 10 NAAQS attainment, regardless of the impact of off

- lake sources. In the 2016 PM 10 Plan, to more fully account for those off

- lake sources and ensure that the attainment demonstration is valid when such sources are included, t he 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/m 3

. To predict future concentrations for this “out

- of

- ne twork” contribution, the 2016 PM 10 Plan makes two important assumptions for this off

- lake source component. First, it is assumed that, aside from the minimum 20 μg/m 3 , the principal PM 10 contribution from off

- lake sources is from locations relatively near the lake shore. This is supported by a District review 6 of 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 study 7 of 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 PM 10 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 evaluation 8 of the Hybrid Model, checking model pred ictions 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 statist ics 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 PM 10 Plan, Appendix VII

- 1: Air Quality Modeling Report, sec. 5.7

performance is good, with high correlation (83%), predictions mostly within a factor of two, and very good agreement at the highest concentr ations (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 mod eling that is consistent with the PSDG. The Plan states that the monitor locations were chosen to be downwind of the largest PM 10 source areas, so that they represent the highest PM 10 concentrations in the area. (Plan p.62)

The attainment demonstration exa mined 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 PM 10 Plan. For 2017, the highest the design concentration is 142 μg/m 3 and all concentrations are less than 150 μg/m 3 , demonstrating attainment of the PM 10 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 P M 10 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 locale

specific 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 PM 10 emission factors, back

- calculation from monitored concentrations, depend s 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 allow s PM 10 emissions to follow a realistic curved trajectory between the source area and8

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 stead y

- 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 Guide line 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 ve rsion 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 characteristi cs. 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 CALPU FF 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 proposal 10 to remove CALPUFF from 40 CF R Appendix W as a “preferred” model for long

range 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 demonstr ation.

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 th an 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 PM 10 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 em i ssions 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 45349.9

supporting documentation for the assumptions convincing. The lake bed and near

- lake bed emissions are large rela tive 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/m 3 represents a measured general regional contribution, the cumulative effect of more dist ant 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 emission s 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

B y 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 PM 10 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 PM 10 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 a ny 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 cou ld 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 l ake bed; the large number of monitor locations provides sufficient spatial coverage of concentrations for the attainment demonstration.10

III. B est A vailable C ontrol M easures (BACM) Analysis

A. Background
The Federal Clean Air Act (CAA) section 189(b)(1)(B) requires areas designated as Serious nonattainment for PM 10 to implement BACM 11 on all significant sources of direct PM 10 and
PM 10 precursors. The CAA does not define a BACM

- level of control for specific sources. In our guidance for serious PM 10 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 ener gy, economic and environmental impacts. Consistent with the General Preamble Addendum, a BACM analysis should include the following elements for the Owens Valley PM 10 NA:

 Preparation of an inventory of PM 10 sources;

 Identification of source categories hav ing a greater than de minimis impact on ambient
PM 10 concentrations;

 Comparative analysis of the controls implemented in the Owens Valley PM 10 NA and BACM in other serious nonattainment areas for significant source categories; and

 Evaluation of reducing e missions 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 de tailed 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 PM 10 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 PM 10 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 em pirical 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 ap plies to stationary sources, a subset of BACM.

12 2016 PM 10 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 i n 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 PM 10 Plan, Figure 7

- 6.11

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 are as 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 outs ide 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 e xceedances 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 ca n be planted for dust control. Compliance is assessed using ground

- truthed satellite imagery. 20

16 2016 PM 10 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

- 1.12

4. Gravel Cover
Application of gravel to the dry lakebed prevents PM 10 emissions by preventing the formation of efflorescent evaporite salt crusts and by establishi ng 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 b e 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 Flood ing) 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 surfa ce 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 effici ency. 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 PM 10 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 th e controlled area on the lake bed an additional 3.62 square miles. GBUAPCD estimated that the PM 10 emissions reduction strategies made further enforceable by the submitted GBUAPCD Rule 433, Control of Particulate Emissions at Owens Lake, are, with some

exc eptions, 99 to 100 percent effective in control ling emissions

. 22 Rule 433 requires the implementation of all required controls, including those established under Phase 9/10, by n o 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 Res ources. 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, modelin g or13

monitoring demonstrates controls are needed in an ECR area to attain or maintain the PM 10 standard, the City will be required to implement BACM.