Welcome, everyone, to this public session of the Owens Lake Scientific Advisor panel. I'm Dave Allen, the panel's chair. Panel's work is being conducted under the auspices of the National Academy of Sciences in response to a request from the Great Basin Unified Air Pollution Control District and the Los Angeles Department of Water and Power. The panel has been asked to evaluate the effectiveness of alternative dust control measures to their degree of reducing particulate matter emissions from the Owens Lake bed and reducing the use of water and controlling those emissions. Today, the panel will hear several presentations that are relevant to its task. I would like to emphasize to everyone that this is an information gathering session and that the panel has not completed its deliberations. Comments made by individuals, including members of the panel, should not be interpreted as positions of the panel or of the National Academy of Sciences. Once the panel's draft report is written, it will go through a rigorous peer review process before it's considered an NAS report. Therefore, observers who draw conclusions about the panel's work based on today's discussions will be doing so prematurely. I want to note that this entire session is on the record and is being recorded. The presenters will be asked to provide remarks and panel members will have the opportunity for follow-up discussion. Because of time limitations, the panel and presenter should not be expected to entertain questions from members of the public. Anyone who wishes to submit written comments or other materials that are relevant to our charge should contact Ray Wassell, the responsible staff officer of this study. Before we begin the presentation, I would like to ask the other panel members to introduce themselves to the audience and indicate their affiliation. So, if the panel members could go off of mute and introduce themselves, let's go ahead and proceed through the role. Sorry, go ahead. Oh, this is Pratim Beswas. I'm from Washington University in St. Louis. Roya Bahraini from UC Riverside. Akula Venkatram from UC Riverside. Ted Russell, Georgia Tech. Scott Van Pelt, USDA. Scott Kyler, University of Nevada, Reno. Okay, so if all the panel members have introduced themselves, I'd like to, just for the sake of audio quality, ask that everyone go on mute, unless they're actively speaking. Our first speaker is Anne Logan from the Great Basin Unified Air Pollution District. She'll provide an update on air quality modeling and monitoring in the Owens Valley planning area. And we've asked Anne to take no more than 15 minutes for presentation that will be followed up by questions from the panel. So, Anne, the floor is yours. Present just a brief update to further discuss monitoring and modeling in the Owens Valley planning area. The three main things I hope to touch on are the recent monitoring and modeling results and trends and to discuss the primary sources that are causing or contributing to PM-10 exceedances and the steps the district sees as necessary to continue progress towards reaching national ambient air quality standards attainment for PM-10. So, this is a figure that the panel has seen before and this shows the progress that has been made since 2000 in the Owens Valley planning area. So, we have both the number of exceedance days in the red line with a clear trend downward as well as the average exceedance that is average annual exceedance. And of note, the PM-10 standard is at 150 micrograms per meter cubed. And as you can see in 2018 and 2019, our average exceedances are between 2 to 300. So, really clear trend downward from in the early 2000s when our average exceedances were well above 1,000. And this is the same data presented in a table format. Also included is the maximum exceedance for the year. And as you can see, the maximum exceedance trend shows the same declining trend. And so, in recent years, our maximum exceedance in the Owens Valley planning area is below 1,000, where in the early 2000s, our maximum exceedances were well above 10,000 micrograms per meter cubed. And so, we focus on more recent history. This is a table of the monitoring sites within the Owens Valley planning area, shown in parentheses is the data period for which there's monitoring data. The peak count is the maximum number of exceedances that were recorded in a year. And then, we have the 2018 count, which is our last full year of monitoring data. And then, for attainment redesignation, what's important is the three-year average. And so, the three-year average to be designated as attainment is not to exceed more than one violation per year on average over three years. And so, looking at all of the monitors within the OVPA, you can see that we have three monitors, Lone Pine Mill and Stanley, which have met that average. But we have several other monitoring stations that are still well above. And so, from the district, one of the things that we work to do with any exceedances is to identify the sources that are causing or contributing to the exceedance. And so, there are many different ways that we go about it. And the first is really just an evaluation of the monitoring data. And so, using wind direction and wind speed with hourly PM10 data, you can perform a wind screen to determine what direction the source is. We also utilize dust camera reviews, as well as gas goes in the field during events and following events to map source areas. We have our sand flux monitoring network, which feeds into both our daily model and our annual modeling. And I'm going to spend the next couple of slides primarily talking about the focusing on the monitoring component and the wind screen, as well as the modeling. So, the shoreline monitor that Owens Lake have wind directions that are determined to be from the lake directions and off the lake directions. And these are included in the 2016 SIP, and there's a figure on the right there to show the directions that are on lake. Obviously, this doesn't tell the full story, but it provides kind of the first preliminary analysis of data to indicate where a source might be coming from. And so, if we look at the past three years of data, these are pollution roses for each of the sites. And the pollution roses include all the data from 2016 to March 31st, 2019. And this is not just exceeding days. This is all hours. So, it includes data for days where there wasn't an exceeding. And each of the pollution roses shows the PM-10 impact with the corresponding wind direction. And with the monitor name, there is the number of federal exceeding that occurred in the 2016 to 2018 time period, which is the last three years of complete data. And if we look at Owens Lake and the primary sources, you can see that for our sites that have a lot of exceedances, there's a couple things to note. There's source impacts from the south off lake, up in the Keeler and Lizard Tail area. Pretty significant sources off lake. And then, all the sites have some impacts from on lake and some from off lake, but none are to the magnitude of in the Lizard Tail Keeler, Shellcut, Dirty Sox and Elantra areas is off lake. And we'll get into some of the causes of these in a little bit more detail. And so, I'm going to switch over to talk about modeling because this is one of the other ways we investigate source area contribution. So Ken Richmond provided the panel with a detailed presentation on the modeling system, which I'm not going to go into detail. But just to remind the panel, the critical inputs are the source area configuration, the emissions, which utilizes the SAM plus monitoring network and the meteorological data. And I want to note that it's the source areas and the SAM motion data that influence the model results more than any of the dispersion modeling options or the K-factors used to drive the PM-10 emissions. And so when the district does our annual modeling, we're calculating the PM-10 impacts just at the shoreline and community receptors for each of the sources that are input into the model. And the two results that we're interested in are what's called loan violators and watch areas. And the loan violator is a single source area that contributes at least 130 micrograms to any receptor on any day. And a watch area is a source area that contributes at least 80 micrograms. And this model we run to indeed to assist the determination of additional backbone contingencies. And on the left, there's a image of the SAM flex monitoring network. You can see both the district sites and DWP sites. And so the model results for the past four years are interesting because of the sensitive nature of a lot of the source areas, I will not be providing a map. So the results are presented here in table format. And on the left, you have the source areas grouped into different types. And then on the right, you have the model periods that we ran with the size of the loan and watch areas and acres. And so they're not necessarily just one area, it's the cumulative total. And so if you look, you know, in the 2014 to 2015, you have an impact from the phase nine, 10 areas. And this is both before and during construction. We also had impacts from the shallow flood wetness cover refinement field test area impacting the shoreline from 2014 all the way through 2017. And then, you know, the present, the areas that have a presence throughout the whole time period are the uncontrolled lakebed and some of the off-lake sources we include in the model. And so the uncontrolled lakebed is broken down into two different types. We have the eligible environmentally sensitive areas which have been ordered but are deferred for controls. And you can see that in 2017, 2018, they were the highest area of loan violators with over 300 acres coming in in the model. And we have unordered lakebed areas that are also contributing. And we call these hotspots. They're typically far away from the shoreline on the kind of inner circle of the total dust control area. And in 2017, 2018, just under 75 acres were loan violators. And then controlled lakebed, this is where we really don't wanna see emissions. So these are areas that have been ordered and controlled. And so in 2017, 2018, fortunately, we were no longer experiencing a high number of acres causing loan or watch areas at the shoreline. We did have a contribution from a minimum dust control efficiency area in 2017, 2018, and then no impacts from phase nine, 10 areas. And then down at the very bottom is the Keeler Dunes. And the Keeler Dunes is the only off-lake source that's included in the model. And it's broken down into the uncontrolled portion of the project and the controlled. And that break down, you can see that the controlled portion of the Keeler Dunes, smaller contribution than the uncontrolled portion. And the 2018, 2019 model is being run right now and we should have results this fall. And those will be used for the annual additional passive agency determination to decide if additional areas need order. And so if we combine the monitoring and modeling results along with all the work staff does to evaluate what are the primary sources contributing to PM10, National Ambient Air Quality Standard Excedences, we kind of come up with this list. And so from on-lake, we have the uncontrolled hot spots and the deferred environmentally sensitive areas that are the primary sources contributing to exceedances. And off-lake, we have the Elantra Dunes, the self-cut sand sheet, Keeler Dunes project area, which as the project has been implemented, has contributed less and less. And then the surrounding Keeler sand sheets, so that's the portion outside the project, which has a lot of mobile sand deposits that are active.  And so looking forward to ensure continued progress towards PM10 attainment, there's really three main components. And the first is that we need to maintain the current level of control. And so this is required by the Clean Air Act, with no backsliding, but it really has a lot to do with LADWP's operations and then the procedure and the method by which any refinement or testing of BACM occurs. And so to maintain the current level of control is imperative to avoid emissions from areas that are currently in control. And ways that could happen would be transition areas where one BACM is transitioned to another type of BACM, avoiding emissions from test areas. Like you saw in the model results, there were emissions from the shallow flood wetness cover refinement field test area in 2014 to 2017. And then also emissions can occur when there's breakdown or LADWP applies for a variance because of an operational issue that doesn't allow them to maintain BACM compliance in an area during the decimation. And then another part of maintaining current control is to ensure that any refinement of BACM keeps the necessary control efficiency in place. You know, the conditions by which emissions occur in Owens Lake are a very small number of days relative to the average conditions. And then the second is working to address currently a miscarriage. So the last slide was the map of areas that are causing or contributing to PM-10 exceedances. And so the district performs its annual additional BACM contingency determination to decide if any future desk control orders are needed. The district is limited to areas under 3,600 and most of the sources are above 3,600 currently. The district continues to work on the Keeler Dunes desk control project and is working with the tribes and LADWP to address the on-lake environmentally sensitive areas that have been deferred and continue to be emissive. And then there's work needed to think about how to address the major off-lake sources. And then the last and really important one I think is to avoid the creation of new desk sources. So the district is concerned with potential possibilities of groundwater pumping on and around Owens Lake and how that may impact stable vegetated dunes and salt crust areas. On the right is a map of the stable vegetated dune systems that are right at the shoreline as well as the salt crust areas. And groundwater pumping could cause changes to those systems and create new emissive areas. And then there's other anthropogenic activities and sources that could cause PM-10 emissions and district rules and regulations cover most of those. And so the district just works, maintain stationary source compliance and ensure that there aren't exceedances from other at-answer-purchase activities. And at the end of the presentation, the wind roses that I presented, I've provided large scale for the panel. I won't go through these individually, but they're for your reference. And with that, I'm happy to answer any questions. Okay, thank you. Let's open it up for questions from the panel. And let's try just to have panel members turn off their muting and go ahead and directly ask the questions if we have too much overlap of people trying to ask questions, we may try a different route, but let's just do it as informally as we can. So questions from the panel, please unmute yourselves and ask any questions. This is Venkatram from UC Riverside. I had a question about the modeling. In the last presentation, Rambold indicated that the model was not performing very well as far as paired concentrations were concerned. I was just wondering how you viewed that in the light of the results you presented, the fact that the model does not really do a good job of predicting concentrations when they do occur at high wind speeds. Dave, I don't hear any response. Yeah, and I don't either. Perhaps Anne has gone back on mute. No, we had to discuss the question a little bit. I think the understanding is actually backwards. The model doesn't perform as well when there are lower concentrations and when there's lower concentrations, there's typically lower wind speeds. No, I thought the QQ plot, you did fairly good at the QQ plot in the sense that the distribution was fine, but when I looked at the correlation plot from the previous presentation, I noticed there was a fairly large amount of scatter, and I was under the understanding that the concentrations really, especially at high wind speeds, there were cases where you did predict concentrations at high wind speeds, but there were a lot of cases where you didn't predict it and I was just wondering whether that problem has been resolved. Yeah, so the model over-predicts at higher concentrations. That has not been resolved and that is still the case. Most of the results presented in Anne's presentation were actually monitored values, not the model values. The monitor information was for the source areas. Yeah, the only modeling results presented were the size of the source areas that caused concentrations above 80 or once. Okay, okay, yeah, maybe my understanding was because as a modeler, I possibly don't have as much faith in models as you do, but I had another question relative to the monitoring. I noticed you looked at daily exceedances using your wind screens, that is the directional wind screens. How do you do that for a daily average when the winds can blow from any direction during the day? The oddly wind directions could be outside your wind screen. So how do you derive a daily average? All of the data presented in the pollution roses and with the wind screens is not daily, it's hourly PNP. No, but when you look at daily exceedances, I believe you use the wind direction screens, correct? That is when you say off-lake and on-lake, for example, when you say on-lake exceedances, and that basically refers to daily averages, correct? When you say on-lake and off-lake exceedances, those are daily averages. So when you say on-lake during any 24-hour period, the wind could be blowing in all directions. And it might not necessarily be on-lake or off-lake. So how do you decide whether that exceedance was associated with off-lake or on-lake? It has to do with what hours had the highest PNP contribution. So you take an exceedance, then you look at that hourly values for that day and the corresponding wind speeds with the PNP data. Yeah, so there's still 24 hours of input. If you're looking at, let's just take on-lake, for example, the on-lake hours use the actual on-lake values that are monitored. The off-lake values then are basically brought back down to background, which we use as 20 micrograms. So you'll have 24 hours, the on-lake values, the off-lake values converted to the background concentration of 20, and then you calculate your 24-hour average. You're gonna look at off-lake exceedances. You would do the same thing. The on-lake direction becomes the background concentration of 20, the real off-lake hourly values are used. You calculate your daily average from the 24 hours. Okay, so you assume that the odds that do not correspond to any one direction are background concentrations or on-lake concentrations. So yeah, I had some difficulty trying to decide. So maybe this clarifies it, but I need, I'll follow up a little later. Okay, hi, this is Prateem Beswas. I just had a follow-up question to Venki's first one. When you use the models or do the modeling, you take some source estimate, of course you need that as input to the model. What, do you have any comment on any, on the accuracy of this source estimation? And my understanding was you use the sand-catcher data to estimate the sources, I might be wrong, but could you just clarify, and is the uncertainty in the source estimate taken into account in the modeling? District staff determines the source areas and each source area needs at least one monitor within it. As far as uncertainty of the source area mapping, it really depends on what portion of the lake. I would say certain areas, there's a very high degree of certainty of how the sources are mapped and other areas, it can be harder to map the areas given the soil type. So it's not a uniform certainty across the lake. And then any source area has to have some type of sand-flux data and a sand-flux monitor associated with it. So any comment on the uncertainty with respect to the model predictions? Right, only as good as the input. So if you don't feel like you've mapped the area well and are characterizing it, then the model output will suffer. So for areas that have been ordered and have been environmentally sensitive areas, I think in general, we have a very high degree of certainty about those source areas. Some of the interior hotspots probably don't have as high a degree of certainty, but. You know, this is Grace Holder. One of the things that we do when we get the model results is we look at all of the data, and especially for areas that come up as loans or watches, we go back in and look at all the input data, including the sorcery, delineations, any kind of timing with respect to precipitation events or any other activities on the lake, and sort of evaluate that to see how confident we are in the model results themselves. So the model is just one tool that we use to identify which areas need control or contribute as loans or watches, all of the data is evaluated in that process. Great, thanks. Yeah. Anne, this is Ted Russell. Thanks for a nice presentation. I had just a quick question sort of following up on for teams was you indicated that of the three terms in the emission estimation, I think it was the sand flux, the KF, and the area that you said that the resuspension factor, KF, whatever, is the most certain, or you think that adds the least amount of uncertainty? I was wondering if you could just address that some more. So of the factors that go into the TM10 emissions, it's the source areas and the sand motion data that influence the results the most. The KF factor and any of the dispersion modeling options influence it less. So if you, and you can see that really clearly if you compare the model results with just the raw sand motion data, they one predicts the other very clearly. One what predicts the other? Sand motion data is clearly predicts what areas will come in in the model. So it's the most important input along with the source area associated with sand. Okay, I mean, so maybe it's, I can see that that would identify the source region, but in terms of the mass emission rates, you know, the suspension factors have quite a bit of variability in them. So I was just curious, so did you go through sort of a full uncertainty analysis to essentially look at that? Or what was done sort of to, or is it because you're backing it out from the model versus monitored analysis? You have not done an uncertainty analysis. So, or Gracie, have anything to add? Well, sure, just the modeling has been done over the years using different K-factor inputs and they've been seasonal K-factors. They've been refined to smaller areas. They've been run as the default K-factors that are established in the state implementation plan. And regardless of what K-factors set you use, even if they vary on an order of magnitude, the effects on the concentration are minimal to the value of the concentration. So if you're looking at 24-hour exchange from 1,000 to 10,000, the K-factor may change the concentration on an order of 10 to 100 micrograms per cubic meter. It's not that significant. So all of the arguing over the K-factors over the years and what's the appropriate ones to use haven't really resulted in any further refinement or less uncertainty in what those K-factors result in. Actually, in some ways, so the emissions are linear in the K-factor, right? Yes. So I would think that if you have an order of magnitude uncertainty in the K-factor, wouldn't you have a similar uncertainty in your prediction? I don't believe that's the case. I think, Ted, if we wanted to get to a real detailed answer, we'd need... I could see that that would be a real contributor. Thank you much. This is Venkatram from UC Riverside. I don't want to ask too many questions. If someone else had any questions, please go ahead, then I'll ask my question. So this is Dave. In the early part of the presentation, you gave us the data on the exceedances at the various sites. Do you have a breakdown of which of those exceedances are due by site that remain now in 2018 and 2019 are due to on-lake sources versus off-lake sources just looking qualitatively at the wind roses and where the sites remaining with large numbers of exceedances are? I just wonder how many of the remaining exceedances are being attributed primarily to off-lake sources. Do you have that information? We do. It's not necessarily just straight forward on off-lake because on any exceedance day, you can have multiple sources contributing. So even in 2018, we had events where there were both on-lake and off-lake sources contributing to an exceedance of any monitor, which was why I presented the data in the pollution rows. But we do have that information. It's for some of the exceedances is much more straightforward, but in general for 2018, more exceedances were caused by off-lake sources than on-lake sources. Okay, thank you. Venti, we still have time for a remaining question and then we'll end the questions on this part of the presentation. Okay, this will be a very short question. I noticed that you looked at progress and control using exceedances. And as you well know, exceedances represent the tail of a distribution of a concentration distribution. I was wondering whether the improvement is also reflected the mean concentrations, the arithmetic average concentration at these sites, whether the means themselves are decreasing with time. They are, that data was not presented, but it is. Not the means of the exceedances, but the actual annual average. So that's also decreasing at all the sites? I think I'll have the top of my head for all of them, but in general for most of the sites, it's decreasing. Okay, thank you. Okay, thank you, Anne, for that presentation and for addressing those questions from the panel. Let's move on now to the presentations on the dust control measures to try and keep us on time. The way we're gonna proceed with this is to have both presentations both from the district and from DWP made in sequence and then we'll turn to questions from the panel at the end of the two presentations. So I believe Grace is first up and so I'll turn the floor back over to her. All right, good morning, everybody. I'm going to be discussing some of the work that we've done with regard to roughness elements on the lake and other areas. So we've divided this into a couple different types of roughness, so there's solid roughness elements, both natural and engineered, and then porous roughness elements that are both engineered and natural. The first one I'm gonna talk about are the natural solid roughness elements and that has been conducted. So that's what the slide here to start with is, is the picture of the demonstration project in the Keeler dunes that we visited on the field trip last month. And so the demonstration project was conducted, started in 2013 and we're continuing to collect data on it, but the bulk of the test was done from 2013 to 2014 in advance of the full scale Keeler dunes project that started in 2014. So the test was really a design test for the overall Keeler dunes depth control project. The test area was 1.2 acres that measured 100 meters on one side in the long direction towards the prevailing wind and 50 meters wide. It was in the northern portion of the Keeler dunes and what we call the northern dunes. Originally the test was designed for a control efficiency of 95% because that was the target that we were aiming for for the Keeler dunes project. But we changed that to 85% so that was the new design concentration for the demonstration project. Does that correspond to the number of straw bales that you can get on one truck?  So that's how many bales that we had. If we wanted to do a 95% control efficiency, we would need like one and a half trucks of straw bales and that just wasn't feasible at the time. So we scaled back to 85% as our target. The bales were placed in an array on the site that duplicated a natural vegetation pattern. So they didn't have a regular distribution like some of the other tests that we've done. And the natural vegetation pattern was a requirement from BLM, the landowner. They had a preferred orientation. So even though they had overall, they had a natural vegetation pattern. There was a preferred orientation of the bale. So the frontal phase facing the prevailing wind direction of 326. So in terms of the performance of the straw bale test, we have some plots that are shown here. So across the top, there's two plots. The plot on the left shows the performance of the site from north winds. So if you look at the bars on the left side of the plot are towards the north and the columns on the right side of the plot are towards the south. So the winds coming in from the left hand side of the plot. And you can see it's decreasing. This is the NSF is the normalized sand flux. So that's normalized to a value that's outside of the project upwind of the test area itself. So you can see that the sand flux decreases as you go into the test area and actually reaches our target value about halfway into the project. You look at the same kind of plot for south winds which is shown on the right with the gray shaded bars or columns. In this case, the wind is coming in from the right and it's going across the test plot. You can see you have a similar reduction once you get well within the test project. So we actually reached an overall average sand flux reduction of 92% in the beginning of the project from June to September once you were about 40 meters or 42 meters in from the upwind edge. So we actually over achieved our control efficiency in the first few months. It did change over time though and that's what this bottom plot shows. So we have the mean monthly normalized sand flux on the vertical column and then we have the month or the time across the year from May 2013 to May 2014 across the bottom. You can see it's the initial portion of the test. We actually achieved our design control efficiency all the way through September. So even though there was slight increase in the control efficiency, we're still meeting the target of 85%. But then after that, as we had more material move into the project from outside because it was within an active source area all the way around it and it wasn't protected along the edges. We actually saw an increase in the sand flux inside the project. So it decreased in the control efficiency especially for the October, November period. But then it actually came back down and by the end of the project we were having about 60% control efficiency and we attribute that to material moving into the project. We actually had to try to protect the upwind edge for halfway through the project to try to prevent a lot of the material coming in from upwind side. This is a picture of a LiDAR scan that was done in the project in the early portion. So this is on the left hand side. We have May to September, 2013. So when we are achieving our control efficiency and then later at the end of the project or the end of the first year May, 2014, what it looked like and the blue and the red shading shows areas where you had either an increase in the surface topography or a decrease in the surface topography. Blue shows a decrease or erosion and then the red is an increase in the surface release. So you can see in the first few months there really wasn't a whole lot of change although we did have overall net deposition. You average it across the whole area and it averaged to 0.146 centimeters across the whole plot or about 15 tons. If you look at the end of the first year you can see that the picture now shows mostly red so we had a significant amount of material moving in especially from the northern end of the project. If you average that across the whole test area we had almost four and a half centimeters of deposition across the whole area. Obviously that wasn't uniform across the whole test area but that was the average across the whole test site. In terms of the cost, water use and energy requirements for the straw bale project, the cost, if you include plants and irrigation it's about $81,000 an acre. If you don't include plants and irrigation and it drops significantly down you don't have to have the cost of the plants and the planting and the irrigation water. So it's about $13,700 an acre. The water use is actually pretty low. So we've used an average of about 0.107 acre feet per acre over the course of the project so it's pretty low water. Obviously if you don't have plants and irrigation then the water requirement will go down to zero but you do need some kind of water for plant establishment so it's not a waterless dust control measure if you include plants. In terms of the energy costs we estimate it's about $7,000 an acre and that would be for the cost of the bale transportation, the bale delivery and then the placement of the bales out in the field. And this is all based on the full scale dust control project which has a design control efficiency of 95%. In terms of applicability and other considerations the straw bales and you could also probably include boulders in this as well they would just feel slightly different shapes but they would be a solid natural roughness element. We use the straw bales in a sandy environment the keeler dunes but it could also be utilized on other soil conditions, other soil types. Boulders could also be placed on most soil types and surface conditions as well so we think it could be broadly applied to different source areas. And then some other considerations that are important to think about are if you're gonna use just bales by themselves they do deteriorate over time so you would need to factor in bale replacement. We're not doing that with the keeler dunes project because ultimately as the shrubs grow they replace the bales as the control mechanism but if you do need to replace bales based on what we've seen on the project itself we estimate probably every eight to 10 years will be a minimum. It might be a little bit longer than that. They actually don't deteriorate very quickly out in that environment. We do see scouring and deposition zones around the bales and you probably see something similar around boulders just because of the nature of the solid element creates the scouring and deposition zones present right around the element itself. As you saw from the initial plots the project size should extend beyond the outside edge of the delineated source and this would be particularly important if it was a isolated source that didn't have other control measures around it so you get full control at the designated boundary rather than having to wait 50 meters or something into the project to get the control level that you need. We have noticed that the bales provide very significant habitat for the local wildlife. We've seen a huge increase in the number of wildlife species and overall numbers in general for those things out in the keeler dunes project. In terms of unknowns, we really don't know what the cost and energy requirements would be for boulders that have not been evaluated but that could certainly be done by just doing some kind of engineering analysis and the total would be dependent on where you get the boulders and how large the boulders are and how far apart they are in that type of thing. We have some references here. So the main reference is for the demonstration project which is the top one. It was work done by Jack Gillies and Heather Green from DRI in 2014. So they're from the Desert Research Institute up in Reno and then Jack Gillies and Heather as well as myself and Sandra and other district staff. We have an article that was published in Aeolian research that describes the work that was done on the demonstration project in 2015. All right, so that's the end of solid roughness elements. The natural solid roughness elements. So we'll move on to work that was done out on the lake with engineered solid roughness elements. So in this case it was work that was also done by Jack Gillies of the Desert Research Institute in Reno and basically has two different tests that were conducted out on the lake bed. So this is sort of a continuation of the work that was done on the Keeler Dunes project but out on the lake and instead of using straw bales it was using plastic tubs that were solid walls. The first test was done in the southern part of the lake in P1A4 and that was done in pretty short period of time in 2014 from March to June. The test actually had to be ended early because of construction for the phase 7A project down in P1A4. So we didn't really get a lot of good information from that test. So after that it was moved to the area just off of Keeler in the northern part of the lake in T26 and that was run from February 2015 to May 2016. Each one of those test areas was 100 meters by 100 meters in extent. So it was about two and a half acres in size. The control efficiency design for the test was 90%. The roughness elements that were used, like I said, were the solid wall plastic bins that measured about the same dimensions as the straw bale. So they were about three quarters of a meter long by 0.38 meters high and 0.45 meters wide. To get the 90% control efficiency, we needed 1,620 elements. They were placed in a regular staggered array instead of the natural vegetation pattern like we had in the dunes. These were placed in a regular array that were the elements for space about two and a half meters apart from center to center and row to row. So here's an aerial view of the test area in T26. So you can see the array of roughness elements. So you can see if they are in a nice regular pattern. So you have the rows and then you have their staggered. So every other rows got a bin in the, inserted in the gap from the area in front of them. And they are also with the preferred orientation in that 326 degree azimuth direction because that's still the prevailing win for that part of the lake. If you look at the performance of the engineered roughness elements, that's what ERE stands for. It's based on sand flux measurements within the test. And the sand flux measurements were done two different ways. So we have the BSNE traps and that's shown on the upper plot. And we have the Cox sand catcher traps that are shown on the bottom plot and they show similar patterns here. So we have the normalized total sand flux on the vertical column and we've got the normalized distance on the bottom. So the normalized distance is the distance from the leading edge to the element, to the locate, or yes, from the distance from the leading edge divided by the element height. So in this case that was I think 0.38 with the element height. So it gives you an idea of how far into the array and you can also actually compare one study to another because each element and different studies might be different size. So it was normalized. You can see that we get the design control efficiency would be 90%, which is 0.1 normalized sand flux all the way out about 160 normalized distance units from the upper edge of the test area from the upwind side. You see a similar pattern for the Cox sand catchers. So you get the control efficiency target at about 160 units into the project, which corresponds to about 60 meters from the leading edge. In terms of the costs and water use and energy considerations, the cost for the project was about $70,000 per acre. And that includes the cost of the manufacturing or the purchase of the elements, transportation of the elements to the lake and the delivery of those elements plus the placement of the elements in the field. There's no water use associated with the project. In terms of energy, just that would be just the $60,000 per acre and that's just for the cost of the manufacturer transportation and delivery of the elements, but it doesn't include the placement of the elements out in the field. Now, presumably if you wanted to expand this beyond the test area, you could have economies of scale and those costs might go down a little bit. This is all based off of the project design which aimed for 90% control efficiency. So if you need a higher control efficiency level that those numbers might go up. In terms of applicability, one of the nice things about this particular control measure is that it can be deployed very quickly on most soil types and surface conditions. And we think it has potential use as a temporary measure for hotspots outside of a dust control area, especially maybe before they're actually ordered for control. And also in areas where you might have transition areas going from one control measure to another that help control the surface emissions from those areas during that transition period or if there's a breakdown in the infrastructure and an area gets taken out of surface and is not able to provide the control levels that it needs is another potential control measure that might be available. In terms of other considerations, just like the straw bale, there would be scouring and deposition zones around the elements themselves because they are solid and you don't get the control efficiency target until you're well within the project. So in this particular array, it was about 60 meters. So if the source area was not next to already controlled area, you would have to extend the control area boundary out in order to get full control by the edge that you wanted. There might be potential trial concerns or permitting issues from agencies that need to be considered as well. One thing would be that because these elements are plastic, they may need to be replaced over time as the material degrades and that would be similar for other materials as well. Here's a couple of references about the work that was done. So the upper reference is from Jack Gillies and the group that he's been working with, Vic Anamizian, George Nicolich and Bill Niclain in 2017, a report that was done for the district and we also have another similar report on the same work that was published in 2018 in Earth Service Processes and Landforms. Okay, we're gonna talk now instead of about solid roughness elements, we're gonna talk about porous roughness elements and it's combined both natural and engineered roughness elements into the same presentation here. This work has not been quite as thorough and it hasn't been tested on a large scale like we did with the solid elements, but the work was conducted by Jack Gillies and his group from DRI. And the idea is that the porous roughness elements are a more optimal type of roughness elements because they allow some of the wind to go through and so they're actually more effective at controlling the surface or at least that's what appears from the data that we've seen. So there's two particular tasks that have been done. So the first testing was done in a wind tunnel up to the University of Guelph in Canada and that was done in 2015 and 2016 and that was testing the performance of porous elements with a well-defined geometry and porosity to try to see how it increased the aerodynamic drag and increase the sand trapping potential of the elements. Based on that work, there was a small-scale field test that was done and that test was done at Mono Lake instead of Owens Lake because we wanted a really active sand source and that seemed like the best area at the time and that was done in 2017 and 2018. The elements that were used in the wind tunnel testing were pretty small because of the size of the wind tunnel so they were only 10 centimeters high. The elements that were tested in the field at Mono Lake were quite a bit bigger. They were one meter cubes instead and the mesh that was used in those elements so the porosity size changed between each element. So there's actually been no testing that's been done on the natural porous roughness elements just on the engineered one. So in terms of the wind tunnel testing, you can see that from the plot right in the center of the slide or the graph in the center of the slide, there was five nested sequences of elements that were tested, both cubes and cylinders. So you have an outer one, that's the largest one, that's the 10 centimeter size. So this just shows the profile of the cube and inside of that free successive test, they added another element inside up to five elements total. So the inner element is shown as the darkest shading one and that's the smallest element. Each element was separated by one centimeter in all directions from the element that was outside of it. So the same kind of configuration was done with the cylinders. There was sand feed that was added into the wind tunnel. So here's a photo of just the outer mesh cube in the middle of the wind tunnel. We have two sand traps on either side that were blocked off below the top of the element. So it only measured the sand flux from the 10 centimeter high location and down to the wind tunnel floor. Also tested in the wind tunnel were different volumetric porosity configurations. So we've got a stack of elements that's shown over on the far right. These are also 10 centimeter blocks and the bottom one shows the front to back porosity. So there was holes that were drilled into the cube. They went from front to back. We also have front to back and side to side. So the holes were put through in two different directions and the top the holes were put through in three different directions. The front to back side to side and the top to bottom. In terms of the results, we have three plots here. So if we start on the plots on the left we have the length of the sand tail that was deposited behind the porous element. So we have both the cubes and the rounded cylinders. So if you look at the graph, the number of elements increases as you go from one over here, C1, which is the cube and RC is the cylinder. One, which is just without anything inside and then two, three all the way up to five on the right. So you can see that the tail length was the longest for just the single element without anything inside of it. And it decreased slightly as you added other elements inside. If you look at the trapping efficiency for that same configuration. So the trapping efficiency was the least for the single element. It increased the most when you added the second element especially for the cubes. And then you don't get quite as much. You get a little bit more increase all the way to four but not quite as much of a jump as you did from one to two.  In terms of the trapping efficiency, we have a plot over here on the right that shows the mean trapping efficiency for both the cubes and the cylinders. So the cubes are the upper line here with the squares, the cylinders are the circle. So you get a better trapping efficiency for the cubic shape rather than the cylinders. In terms of the field testing that was done at Mono Lake, this is a picture of the elements that are in place. So we've got six different elements going from left to right. So the pore size and the mesh increases as you go from left to right. So this is actually sort of a sand fence type material that was put on the cube. So they're actually double walled cubes. So there's an inner mesh layer that's separated by a few centimeters from the outer mesh in each one of the elements. There's cocked sand catchers in front. An array in front. There's also cocked sand catchers in the back. You can see one kind of behind that third element as well as the BS&E multi-height sand traps in the front. So in terms of the results from that project, we have the trapping efficiency shown both in terms of the three dimensional permeability on the upper plot and the hydraulic conductivity on the bottom plot that show similar relationships. So there's two different lines here. So the one line shows the main trapping efficiency overall throughout the project. And then we also have another line that shows just the initial part of the project and the trapping efficiency. So there's a little bit of change over time, although the overall pattern's pretty similar. And you see a similar pattern for both hydraulic conductivity as well as the permeability. One thing to notice that this outlier over here is not included in the curve. The curves over here on the other parts because that's the element that has a different shape pour. So the elements that are one through five, so it goes element one, two, three, four and five as you go from left to right are the elements that have the nice square shape pours and the black mesh that was in the photo above. And this is the one that has more of a rectangular pour shape and the pour shape seems to actually make a difference in terms of how the data that was collected and it doesn't fit on the same curve as the others. If you take the trapping efficiency into consideration and then extrapolate that into how it would produce, how it would affect an array of elements, the trapping efficiency reduces the sand flux more rapidly than it would for solid elements that don't trap the sand. And so you actually get an increase in the sand flux reduction so that you get the target, you would get the target control efficiency at a sooner point than you would with the solid element. So that's what this black dot shows. So rather than way out here at 160 elements to get the control efficiency that you're looking at, you would get it around 72 element distance. Or about 100, or about, yeah, 72 normalized distance versus, I guess it was 137 in this calculation for the solid element. In terms of the cost, there really isn't much known because we haven't tested on a large scale and we haven't done an engineering analysis for it, but presumably the engineered porous roughness elements would cost more than the solid elements just because it would be more complex in manufacture. You also wouldn't be able to stack them for the transportation costs and the effort that it would take to place them out in the field would be probably a little bit more than it would for the solid elements, at least for the plastic bins where you were able to stack them into large stacks and place them pretty quickly. The water use would depend, but the engineered array that's placed on the ground, it would have no water use. If you're trying to combine it with vegetation, like as a natural porous roughness element, you would need some kind of water in order to get the shrubs to survive. The energy costs are pretty much unknown at this point, but some kind of analysis could be conducted. In terms of applicability and other considerations, just like the solid elements that could be used on most soil types and surface conditions, the engineered porous roughness elements could also be used as temporary control measures and transition or breakdown areas and for hotspot control outside of control or order control areas. They could also potentially be used for environmentally sensitive areas or off-lake areas as well. One thing that appears to be good about the porous roughness elements is that they reduce the amount of scouring around the element itself, so that would be either not present or would be present to a much lesser extent than the solid elements, so you wouldn't necessarily get the tipping and the amount of scouring and deposition around each element itself. Just like the solid elements, you should extend the project size outside of the delineated source due to the edge effects if it's not adjacent to an already controlled area. The type of material that's used may have implications for tribal concerns and permitting issues. The natural porous roughness elements would need some sort of source of water or the establishment of the plants. And I think if you place shrubs directly in the ground and a lot of the real active source areas, you would easily protect those shrubs from sandblasting so that you would need some kind of other material on the surface as well. And the porous roughness elements would also require maintenance if the trapping efficiency was reduced. So one thought there is that if they're open bottom, you could simply pick them up. If the inside started to fill up with sand, you could pick them up and reseat them and then you would reestablish the full trapping efficiency and control level. If the porous roughness elements were made out of non-natural material, they would need to be replaced if the material degrades over time. There's two references here, both by Jack Gillies and his group. So we have a reference from 2017 that references the wind tunnel work that was done and a report prepared for the district. We also have a report that was done in 2018 and that was the report for the work that was done up at Mono Lake. All right, moving on to soil crust, biological soil crust. This is work that has been started by the district, although we're pretty much still in at the infant stage. So we haven't really pursued this very thoroughly at this point. We have noticed that they're present out on the lake and they have potential for possibly being used as either dust control by themselves or to supplement existing dust control measures out on the lake, but other than that, we really don't have a lot of information. So I'm just gonna kind of go over this real quickly. Biological soil crusts are simply soil crusts that consist of a whole array of different types of organisms like cyanobacteria, algae, fungi, bacteria, lichens, and mosses. They typically occur on the surface or within the top few centimeters of the soil. A lot of those organisms that form that soil crust have filaments that help bind the soil material together. So we think that they have real potential for either sort of enhancing the existing control, existing measures are being used by themselves. The community of simulages consists of a lot of different species in genera. They are desiccation tolerant, so they can be dried out. Their control level might decrease as they dry, but then as they get wet again, they actually do reform and become alive again. So like I said, we really haven't done any testing on Owens Lake, but we have started initial work just to identify where their location is. And we're gonna be doing some tests, try to figure out what type of soil crust or bio crusts that we have. And then also we've got some work that we're trying to design an area where we can try to propagate the different types of soil crusts. In our office in Keeler, we have some work tables that are being prepared. And then also ultimately we wanna see if we can actually take the soil crust that if we are successful in propagating it, and then maybe transplant it out on the lake into different areas for potentially implementing on a larger scale. In terms of other considerations like cost, water use and energy requirements, we pretty much don't know much at this point in time. So we don't know what the cost would be. We don't know what the water use would be, although presumably it would be some quantity, but that quantity is unknown. And we don't know what the energy requirements would be. In terms of applicability, we think it has potential use for environmentally sensitive areas. We have actually seen it present in the Keeler Dune, so it might potentially be useful in a dune environment, although probably less applicable than other areas that would be on the lake. There are other areas off lake that it could be used, as well as enhancing existing controls such as managed bed areas on the lake. Some considerations that are important to think about that the bio-cross are very vulnerable to disturbance, especially compressional damage, and that they recover very slowly if they are damaged, so it could take several years to reestablish control if you have significant damage to the surface. They are also sensitive to burial and abrasion, and they can experience rapid change once they're wedded. Some references for the bio-cross are... The top one is by Paige Austin. That was a report that was done for Grape Basin. We can provide that if you need it. I don't think that one's been provided to you with this one. There's also a reference down on the bottom by Young et al. from Biogeosciences in 2018. And that's it, so I'll hand it over to Mark Schauff. So...  Sorry, I'm going to spend the next 35 minutes ago talking about seven vacuum studies that DWP has either sponsored or is considering right now. Some of these are new ideas. Number 6, 11, and 12 on this list are new vacuum or at least new studies that DWP is considering. 7, 8, 9, and 10 are all studies that have been done in the past. Some of them in the quite distant past. I'm going to... What I'm going to do is go over a brief description of each one, including challenges that might have occurred in testing in the field, and then assess each one in terms of advantages, disadvantages, costs, design considerations, water use. Because I'm limited to five minutes per topic, I've scrubbed a lot of the important and interesting details out of these topics, but reports are available, reports and presentations, and we can share those if we haven't already with the panel. So the first one is shrubs. This will be quite brief because, next slide, no previous shrub vacuum studies have been conducted in the Owens Valley or on Owens Lake. At the May 3rd meeting, Evan Burgess provided some details about how we might pursue a shrub vacuum study on the lake. But just kind of build on what he said earlier. There are a couple of points that I'd like to clarify. One is that the potential use of shrubs for dust control extends beyond the flyer. I mean, there's an opportunity to kind of use shrubs or enhance shrub communities in a lot of different places. So we're not interested just because of flyer dust control. Second point is that tall shrubs have a different aerodynamic influence than soft grass, which primarily armors the surface. It covers the ground. So our focus is on learning more about the dust control potential of desert shrub communities. So our focus and research would be to answer several questions, but the chief one would be what combinations of shrub ice with ferocity, plant gas spacings would be required to achieve 99% dust control or more generally, what dust control efficiency results from different configurations that we would identify in natural settings. So even though we haven't completed a study yet, we can look ahead at what the advantages and disadvantages might be of a shrub vacuum. This would be primarily designed to be a new dust control measure, not necessarily a vacuum, but a dust control measure for areas where shrubs are the dominant vegetation component. So we're not going to try to engineer shrubs in an area where they wouldn't already grow, but there are plenty of places both on and around an off the fly where shrubs are abundant. Shubs are resilient. They have the ability to tap relatively deep water supplies unlike salt grass, that's an advantage. And they're a less engineered, more natural solution and with that might come greater public and agency acceptance. Disadvantages, chiefly not suitable for highly salient environments unless first reclaimed. So there are areas on Owens Lake that are sufficiently reclaimed and shrubs have volunteered or doing quite well on some areas. Some design considerations, this is looking beyond a vacuum study and what the challenges might be in trying to develop or enhance a shrub community through dust control. One challenge would be in designing a system for delivering water to the seedlings and small shrubs during the establishment phase. But once established, the water deliveries could be reduced substantially, even cut off completely. I think we've learned in some of our studies on around Owens Lake is that in a lot of cases, the plant and nutrient status is as important as water. Costs are unknown. As I said in the beginning, this isn't even a plan yet. It's a concept that DWP is considering. But we've learned a lot more about costs and challenges once we design and implement a test. Water usage is not known at this time either. The second vacuum study, this one was the vacuum study on Owens Lake, it's called Milton Rowe. It's so named because if we go back to just the slide. If you look to the right of the immediate foreground, you'll see a ditch, that's the moat. So the material is excavated from the moat. Excavator is on the road in the middle and it's deposited on the ridge on the other side. And then you're going up one side of the ridge and down the other creating the same kind of a pattern. I'll show you a cross section in just a minute. This is Moten Rowe. If you look to the far right of the screen, you'll see the next Moten Rowe in this test configuration. Okay, that's right. There was a single season, dust season field study that was conducted from October of 2007 to June 2008. Two sides of shows on Owens Lake. This is a jointly prepared study with Grave Basin and they requested that two sides, one of course textured soil and another of fine textured soil be included and we did. T32 is at the north end of the lake, about 100 acres, very sandy site. Now it's more frequently emissive, but less high concentrations and salutation flux has been at T12, which is on the south. This is a 200 acre area, silty clay loam soils. T12 incidentally is the same area that we tested Tilly John and is currently using TWB squared or Tilly's with back and back up. Next slide. This is the cross section I talked about earlier. It was a engineering design study and this is one of the plates from the design. You can see the two roads excavated from one side of the road, deposited on the other and the moat is about three feet deep. The resulting ridge or row in the middle is about five feet tall and a five foot porous sand fence was placed on top of the ridge. I'll talk about sand fences in a bit, but the modes of action are the same for moat and row and sand fences. They reduced emissions by modifying the airflow and lowering the wind speed at the ground, trapping mobile sand particles and reducing the fetch. So this is the view of the moat and row design. We had a very similar design. The spacings in the middle were a little bit different between T12 and T32, but overall these are both of the configurations look the same. It's a modified side-by-side H configuration. One side was designed for natural crust and the other side, the intention was not a control plot, but a pulverized crust. So if there was a lot of disturbance, we wanted to know what the difference was. In the end, as we learned from just building these structures that these soils have become easily pulverized to kind of the fineness of talcum powder and the rows had to be sealed up. We decided it was not a good idea to pulverize one side of it. So while this test was conducted, it was all natural crust surfaces on both sides. The red section in the middle is the test section. The distance between the modes and rows varies from T32-1 to T12-1. We used a model called SWEETS, the Single Event Wind Erosion Evaluation Program. It's a portion of the wind erosion prediction system and it generates saltation flux curves and from those curves we can design spacings to achieve a certain reduction in sand flux. There are untreated tails on the H. The uprights on the H are untreated areas. Both on the north end and the south end, it's oriented to align with the predominant winds. And the tails on the H also serve to sort of limit the amount of sand that could enter the test area from sort of off-wind directions, you know, off-axis directions. We wanted to filter the data so we got good winds right down the alley and that way we could see the effect of the test areas the best. Next slide. Both sides were pretty heavily instrumented. We used e-samplers, which are nephelometers. One 10-meter bed tower with wind speed at four heights. We used cocks and catchers since it's video cameras. And all that went into an assessment of control efficiency. Again, we only had one dust season, which was 2007, 2008. This shows the control efficiencies for the west side of the H. There's a west side and an east side. And so you can see on T-12, this is the fine-textured site. We achieved higher than 99% for both the east and the west side. T-32-1 was a sandy site and we achieved something lower than what we expected. We were shooting for 99%. We got 97%. And so if we were going to rebuild MotonRow on T-32, we would simply shorten the spacing and bump it up to 99%. It's all about reducing fetch. Next slide. So advantages and disadvantages. We found that MotonRow was highly effective. We achieved between 97% and 99% control efficiency. And I must say that the winds and the sand fluxes recorded during the test were as high as they ever have been on Owens Lake. The fetches at T-12 were very long. We had an enormous capture of sand in the moats. But the moats and the first ridge did the job and stopped all of the sand motion. And the report has some nice figures that show this better. Essentially, the design extinguished the sand motion entering the area. Let's go back to disadvantages. Aesthetics, I mean, this is highly engineered.  There was a lot of opposition just because of the aesthetics. There were wildlife concerns that were presented by the California Department of Inefficient and Wildlife. They were concerned about long lines of motes and rows serving as barriers to movement and trapping of fledgling birds in the boats and rapture perching and other things. Some of these things, or all of them, can be mitigated. But the bottom line was that the agencies were opposed, that there are other methods that have other benefits than dust control, and they were in favor of those. Some of the lessons we learned were that these roads are highly omitted after construction. They have to be sealed. The berms should be armored. There's a lot of sheer stresses on the tops of the berms. Deeply anchored fence posts requires removal sand from the moats after highland events. And last but probably one of the more important ones is that the surfaces between the moats and rows are naturally trusted, and effort has to be taken to preserve the crust. So if monitors out there, the people, the field technicians need to travel on a path and stick to it, and preferably the path should be armored, graveled or something. One of the advantages is that it's not snow-watery. Next slide. I'm going to move into sand fences. There's a link between sand fences and moat and row. They operate in the same way, modifying air flow, trapping moat sand, reducing fetch. Sand fences were evaluated as part of the 2007-2008 moat and row study that I just described. One of the options that we presented for different areas was sand fences by themselves. I mean, we did it to see what the differences were. And as it turns out, the agencies were opposed to the idea of moats and rows, but liked the idea of fences, and so they approved the use of fences on many areas, which is T1A1, down on the south end of the lake. It's about 250 acres. Sand fences were installed in 2010. And for years, the area was operated, I believe, without an official vacuum status, but as of the 2016 SIPP, it was officially named Vacuum and called Reduced Efficiency Vacuum. The little inset that I show you on the lower right corner is a picture of, is a view of T1A1. The red area in the middle is a natural swale that is seasonally moisture-wret. And we wanted to minimize the disturbance in that area, but add a little bit of protection against very long fetches of dry by putting in a few fences. The pattern that's there right now is about a 200-meter spacing between those fences, and not all of T1A1 was uniformly emissive, so we kind of stacked the fences in the areas that had the highest sandboxes. A few details are shown of the design in the bullets to the left. Next slide. T1A1 was monitored fairly heavily and continues to be operated, to this day. There are 18 scents at Coxeant Petra Paris within the array. The sandboxes are reported on a monthly basis to Great Basin, and once a year, control efficiency is calculated. And the next slide will show some of the results. The system has been in place for nine years. You can see the seasons. That's October of 2010 to June 2011 and so forth. There wasn't a report in the first year and a couple of other years. I don't exactly know the details, but no report was generated. But for those other years, we've been to the daily sandboxes by wind speed and then reported essentially the worst-performing site. In these annual reports, we're probably trying to inform the operators as much as anything about where potential problems lie and not necessarily assessing the overall control efficiency. So these numbers are conservatively low. In one case in 2016-2017, for high wind speeds, we had zero control efficiency at one of the points. In other words, the treatment's daily sandbox was higher than during the baseline period. So there was some remedial action taken and that area jumped back up to high 90s or high 80s thereafter. Advantages and disadvantages of sandboxes are sort of moderately costed. I mean, they're typically thought of as kind of low cost, but to really put in a sandbox system that's permanent, you need to use heavy-wooden posts and that just requires a lot of engineering and there's a lot of labor associated with it, too. It's highly effective for T1A1. The requirement is 31% overall. We achieved greater than 62%. And this has value beyond just dust control. I mean, they're used a lot around the lake to protect gravel backer areas from sand intrusion. Disadvantages are very similar to motor road disadvantages. Aesthetics, they look engineered. They're close to the road they can be seen. They require frequent maintenance of sun, salt, wind, conspire against the fabric mesh, and it gives way during high wind events and has to be repaired. But I would let the operator speak to the difficulty of that, but it seems to me maintenance is a given for any dust control measure under the conditions on Owens Lake. Wildlife concerns about barrier to movement, raptor perching. There are things that can be done. I'll talk about it in a minute. And again, agencies prefer back them with benefits outside of dust control. So in design, I wouldn't put a sand fence array in an area with high upwind sand flexes. Once those sand fences filled and you've got the problem of either having to remove the sand that's deposited or installing another line of fences, and it's just a problem that we continue chasing. So it's there on T1A1. T1A1, as I mentioned on the field trip, was never very frequently emissive. But when it was, it was significant enough that it required something. And so there's this low, relatively low level of dust control. And so that's probably the ideal use of fences for dust control. To mitigate some of the wildlife concerns, breaks in the fences are added, gravel, armored gaps under the fences are installed. Next slide on fence posts. So there are ways to mitigate. It's a non-water use dust control. Solar panels. There was a, I'll talk briefly about a test that was done between 2014 and 2017 on the north end of Owens Lake at T30-5. This was a pilot test of three solar panel arrays. There were about one and a half acres under the solar panels. And the test was of three valve configurations and two perimeter barrier configurations to the barriers installed to prevent jetting under the solar panel array. The primary dust control mechanism here in this case is reduced ground level wind speed. So this is a view of the one and a half acres of solar panels in three configurations, A, B, and C. There were 32 total, 32-cup animometers that were installed at 10 inches, 25 centimeters above ground level. A 10-meter tower located west of the array outside of it. And there were two kind of criteria for that had to be met. And one of them was wind speeds of less than four and a half meters per second at 25 centimeters or 10 inches above ground level. And 20% of the 10-meter wind speed at panel height. So there were two cup animometers that were installed, one in A and one in B, that's the pink dot in the middle at the top of the panel. There were two phases of testing. One phase had no perimeter barriers at all. Phase two tried two different configurations. One with a barrier only on the north side and the second north and south side barriers. So arrays A and C, if you want to go back to picture, A and C performed poorly. Array B performed the best. This is one that had the squat valve mount. And it did especially well during phase two with the installation of both upwind and downwind barriers. So the table on the right is for array B and for the various animometers within the array. If you look at B2 down to B10 for phase one, the highest percentage of winds above four and a half meters per second was 8.3 at B7. But under phase two with the upwind and downwind barriers to prevent jetting, the frequency of winds above four and a half dropped to less than 1%. So advantages and disadvantages. The advantage is that the potential for dust control combined with power generation and the power primarily to offset the cost of the dust control. We did do a study in 2009. It was sponsored by DWP, Great Basin, JPL, a company out of Boulder, Colorado called CTP Wind Engineering and Black and Beach at the large consulting firm. And it was a fairly intensive effort designed to demonstrate whether or not solar panel arrays could achieve 99% dust control. And the effort was successful. We were able to design it in such a way that it provided 99% dust control at the surface. There's a 48 slide PowerPoint presentation that kind of goes over the details of the study. To my knowledge, there was no final report delivered. There was only this PowerPoint presentation and it's available. Disadvantages are aesthetics. There is a cost associated with dust control when you combine it with power generation it increases the cost and lowers the probability the profitability. Next slide. Continuing on disadvantages, unknown permitting requirements when combined with dust control in no one's way. I don't know how the various agencies would respond. So it's an unknown. In designing and solar panel array, our experience with the JPL study is that the site conditions, the panel angle, orientation height, gap size, all of these things are factors to consider in design and all the effects of the amount of dust control and where there are gaps in dust control under the array. Uses no water. The costs are not zero despite the fact that the revenue is expected to exceed the cost. As I mentioned earlier, the additional cost associated with dust control can reduce those profit margins and possibly where to affect potential partners interested in building an array. Next, staff on measure that has been evaluated in no one's way because it's 12 binders. Some small scale testing was done in 2013 and 2014. But in the course of this 10 month effort, the study plots were compromised and service flooding. We lost about half of the study plots because of inundation. Some of the results were a little bit interesting and so a follow-up soil binder study was proposed in 2016 using the schematic that's shown at the right. Up to eight soil binder products would be tested. A ninth area set aside for control plots. The advantage of soil binder is that it's a waterless DCM. On the surface it would seem that soil stabilizers are a simple solution, an obvious choice. But in fact, not exactly that way. First of all, there was a fair amount of agency opposition and wildlife toxicity concerns were chief among the issues raised. We found earlier that most of the success was in topical application. Topical application means that there is a layer that is afforded some amount of protection, but once that layer is lost, then you're back to an emissive condition. It's a disadvantage that there is a need to observe these areas closely on the surfaces to detect breakdown before significant abrasion occurs. If the breakdown occurred during a large wind event, which is the most likely case, then there would be significant emissions. Overall, in my assessment, there's a fairly thin margin of safety with this measure. There are other concerns like having to... We can get the products easily enough from vendors, but they don't provide the transportation and delivery systems that would be needed on Owens Lake. For those reasons, we don't really know what the cost would be. We'd have to take it through initial product testing and then through pilot testing before we would have any idea. I think through the course of discussions and renewed planning, I think that DWP has decided that the preferred use of biners would be on road surfaces. They're currently awaiting approval from the California Department of Fish and Wildlife to test soil biners on roads. If approved, DWP would revise its focus from plia to road stabilization. The next and last presentation is soil moisture. Again, this is one of the new ideas that DWP is considering. Just like shrubs, there are various studies on Owens Lake. There's plenty of literature, though, that supports the idea that soil moisture for dust control is... Soil moisture is an effective dust control measure. John Bannister first raised some of these ideas in his talk on May 3rd in the context of the shallow flow of the presentation that he made. So a couple of points to reiterate here that it's clear from the scientific literature that even loaves soil moisture contents are sufficient to bind the particles together to prevent a treatment. This next slide here shows just some of the body of information. You can see the citations at the bottom. This is a graph that shows from Fekin et al. 99 that shows that across a range of soil textures from sandy to very fine-grained that increasing gravimetric soil moisture percent at less than saturated levels greatly influences the threshold friction velocity. In other words, water is essentially armoring the surface and fairly dramatically with small additions in the beginning of moisture contents. Next slide. The concerns have been expressed about surface drying. Our experience has shown that a dry surface with underlying moist soils did not necessarily lead to significant dust emissions. One example is that on shallow flooding, the requirement for shallow flooding is that 75% of the area we have saturated wetlands covered, 25% of the area is allowed to be dry. So, those dry islands, many of them are instrumented with sense motion devices, and we do observe continued small amounts of fairly low sand flux, but no visible dust emissions from these areas. So, in all probability, these dry islands are well-armored probably by some combination of soil moisture, salt rusting, and roughness. So, in pursuing some work on Owens Lake, I mean, if saturated soils are not crucial for dust control, then what range of soil moisture would be required to provide an adequate buffer against rapid drying during high wind events? So, worst case would be would not necessarily be during the time of the year when you had the most rapid drying, like late spring or summer, because summer crusts are set up at that time, that really effectively arm the surface. So, it'd likely be something in the middle of the winter when this crust would be destabilized, and winds are high, with temperatures are low. So, that's what we would seek to find out in different soil types, what buffer would be required. And along with that, not only for a vacuum study on the lake, but in the future, if this went to full-scale production, we would need some sensing technologies that could be used to monitor both surface and soil profile moisture conditions. The advantages of soil moisture for dust control is potential for significant water savings while maintaining dust control. We would attempt to use the existing infrastructure to maintain soil moisture just to do it in less than saturated conditions. The disadvantages, and it's a fairly important one, is that there would be substantially lower habitat value than current traditional shallow-flying ponds. And as a result of that, very likely agency and stakeholder opposition. The last background I'd like to talk about is the shallow-flying period refinement study. This study has the longest history of any of the ones that I've talked about. It was first provided for in the 2003 SIP. There was a lot going on in the early stages of the Dessai Pedigation Program in Owens Lake, and so we really didn't start serious discussions in 2007-2008. By 2014, the stipulated judgment had been signed and both parties embarked on a planning effort to come up with the shallow-flood study. That study went through a couple of phases on the lake. There were concerns raised by the district that John mentioned in his presentation. Ultimately, this study was curtailed in 2017. And to bring it up to the present, DWP has engaged the district in additional discussions about how we might do this. And the thinking has changed a little bit. The current focus now is on traditional shallow-flying ponds. It's about 12.83 square miles across the lake. So the biggest bang for the buck is to see if there's a way to refine the amount of wetness covered required for dust control on the surface. So our objective, even though we call it curb refinement, we're really looking at adjusting the single point on the curve, which is where 99% dust control occurs. Right now, the requirement is 75% wetness covered to achieve 99%. We think that it's something considerably less than that, but that's the stuff of the study. We just need to find that. So our high water savings potential, aesthetics are good in this case. Owens Lake was once a lake, and it looks nice to see water out there. This method measure could be rapidly implemented because it would use existing infrastructure. It's resilient, maintains high level of dust control even during high wind events. When you have water across the surface. There are always ways to improve any of these dust control measures. Shell flooding on Owens Lake is probably here to stay, and DWP's focus is on making those refinements to make it a better measure. And with that, that's the end of the presentation, and I'm happy to answer questions. Okay, so this is Dave Allen again. I'll note the time. We only have 10 minutes left in our scheduled session, and we've heard about 12 different control measures. And I'll note somebody's got some background music on. And so everyone could go on mute. If you're not speaking, that would be helpful. Thank you. And so what I'm going to propose is, I know a number of panel members are going to have specific questions on specific control measures. And what I would request is that we follow up on those questions by e-mail. So please, for questions on, please, for questions on, please, for questions on specific control measures, let's forward all those questions through Ray and try and get them feedback on those specific control measures. But with our few minutes of remaining time, let me open it up for generic questions regarding the control measures from the panels. So with that as a stipulation, do we have questions from the panel? This is Scott Tyler, just a somewhat generic question, just on the soil moisture and the amount of water needed. Have the calculations been done as to how much water would be saved in some of these reduced surface area of wetness and lower water, keeping soils moist versus shallow flooding where my fence is, you probably have almost the same rates of evaporation. But just like I know, those calculations have been done yet. I mean, we're working on it. I mean, it's probably very much site-specific in how the water is delivered. Do you use existing laterals and bubblers to kind of raise the water table up to provide soil moisture if you apply it with sprinklers? So I guess the short answer is that we're working on it. This is Scott VanTel, and I've got a question also about the shallow flood refinement. When we were there last month, we saw that quite a bit of the area within the sprinkler radius had been colonized by grasses, the saltgrass in particular. Have you seen many shrubs colonized in those areas? I don't know. I mean, John, do you have a... I couldn't answer. I mean, I think it's site-by-site. Yeah, that's definitely a habitat question. Questions for the operators, you know, right there all the time. This is Ted Russell again. I was just wondering, on your different control measures, you're looking for like 99%, but going to be a fair amount of variability and uncertainty with those. You know, in the difference between 99.5%, 98.5%, is a factor of three. Is attainment... You know, does that factor of three uncertainty, is that accounted for? It takes for attainment. I know they think... I had a question probably for the district. Okay, and actually I'll go the other step on that. What do you think the... When you're looking at trying to achieve 99%, what does that really mean in terms of the uncertainty associated with 99%? Is that a question for the... Probably a question for the district too. Well, actually it's for the control measures, is that when you try to achieve 99%, are you trying to achieve somewhere between 99 point, or 98.9 and 99.1, or what does 99%... What do you think the uncertainty is with that? Well, my understanding of how the district evaluates compliance is that it's pretty bright line at 99% and that if you're below it, they can accommodate, but if you're below it, you're non-compliant. If you're above it, you don't get any extra credit. There is quite a bit of a variability in time of year of site, even locations within a site where you have less than 99%, but at other areas that exceed 99%. And so overall, the site is doing well at 99% above. So there is a huge amount of variability. And I think we agree it should be accounted for, but it's mostly the district's call on how to deal with that uncertainty, because they're the ones that evaluate compliance. It's something that really should be addressed in detail during planning. We ought to all accept the fact that there's going to be a high degree of variability and what do we do with it? How do we deal with it? Any further generic questions from the panel? I know I myself have a number of questions on these specific control measures that I will put in the form of an email to Ray to get additional input from both the district and from the LA Department of Water and Power, but any further generic questions? This is Venkatram from UC Riverside. This is a follow-up on Ted's question. When you talk about control efficiency, are you talking primarily about sand flux control or are you looking at the difference between upwind and downwind concentrations of PM10? Because it would seem to me that if you measure it upwind and downwind at a control site and compared that with a control site, you'd get a measure of the efficiency. I just wanted the definition of what efficiency means. Again, because they are the authors of the procedure, it should be the district, but I can say that from the beginning of the program, sand flux is always served as a... sand flux reduction is always served as a surrogate for PM10 reduction. When we say 99% dust control efficiency, we're really talking about 99% reduction in sand flux. That's the way the district has always evaluated PM10 control on its life. Thank you. With that, if you don't mind... To answer your question about upwind downwind monitoring, sand flux is a point measurement and much more precise because of that than up and downwind PM10 concentrations because you don't really know where that mission is coming from. And there's always the possibility if you have an upwind at a downwind point that a nearby source will miss the upwind and strike the downwind, and that just happens all the time. It gives relatively uncertain results, although we do a lot of upwind downwind monitoring. Please answer the results. But ultimately, you're really interested in PM10 concentration. That's why I asked the question. It's not sand flux you're interested in. It's PM10 concentrations. Yes, and that definitely is an answer... a question for the district. Okay, with that, I'm going to call the... an end to the questions that we'll handle as part of this conference call and ask that the additional questions be addressed through email. With that, I'd like to thank very much our speakers. I think it's been very useful for the committee to get all of this input. And I will officially adjourn this meeting of the Owens Lake Scientific Advisory Panel. Thank you all for your participation today.


The Navy Supply Corps celebrated its 219th birthday Sunday. In 1795, Congress passed the bill signed by President George Washington, which created the office of purveyor of public supplies. This led to today's Navy Supply Corps. Supply officers are trained in supply chain management, acquisition management, and operational logistics. They attend a 20-week basic qualification course at the Navy Supply Corps School in Newport, Rhode Island. Supply officers are business managers that lead logistics specialists, culinary specialists, and ship servicemen to ensure you have the supplies, equipment, and proper meals to stay mission ready. Today there are more than 3,500 active duty and reserve supply corps officers keeping the Navy running. From the Defense Media Activity, I'm Petty Officer Tony Rosa.