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Updated Wind Erodibility Measurements at and Near the Oceano Dunes State Vehicular Recreation Area: Draft Overview of Findings

DRAFT Document. DO NOT CITE OR CIRCULATE

Vicken Etyemezian, John Gillies Division of Atmospheric Sciences Desert Research Institute 755 E. Flamingo Rd, Las Vegas, NV

March 30, 2016

Prepared for:

California Department of Parks and Recreation Oceano Dunes District 340 James Way, Suite 270 Pismo Beach, CA 93449

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Introduction An important factor in the overall understanding of dust emissions from the Oceano Dunes is the characterization of the variability in the wind erodibility. In August, 2013 an intensive field campaign was undertaken to characterize the spatial variability of wind erosion potential at the Oceano Dunes State Vehicular Recreation Area (ODSVRA) and surroundings (Etyemezian et al., 2014). In that study the DRI portable instrument PI-SWERL® was used to measure the potential for dust emissions. Those data were subsequently used for understanding the spatial character of wind erodibility at the ODSVRA and for planning purposes. In the present report, we provide an update on a series of PI-SWERL® measurements that were completed since the original measurements in 2013. These later measurement efforts (5 in total to date) were intended to provide supplemental information that was not made possible by the 2013 data set alone. This included supplemental information on how quickly emissions potential changes when a seasonal exclosure (for Plover) is emplaced or removed, whether emissions potential changes over time, and whether emission potential from specific areas that were targeted for mitigation were adequately represented by the initial 2013 effort. The sampling campaigns, including the initial August, 2013 effort are summarized in Table 1 and displayed graphically in Figure 1 and Figure 2.

Table 1. Summary of PI-SWERL® field sampling efforts

Nominal Date

Sample dates Number valid

Purpose of sampling effort

8/2013 8/26/13 – 9/5/13 360 Broadcast sampling to obtain wide coverage of emission potential estimate in ODSVRA (riding and non-riding), Dune Preserve, and Oso Flaco

9/2014 9/30/14 – 10/2/14 119 Straw bale locations to confirm previous estimates from extrapolation, N-S transects within and near Plover exclosure, additional E-W transect to fill 8/2013 gaps

6/2015 6/30/15 – 7/1/15 102 Emission potential from within and upwind of fence arrays

9/2015 9/28/15 – 9/29/15 114 Emission potential where fences were removed to confirm extrapolation from 8/2013 data, Plover N-S transect for comparison to after exclosure removal

10/2015 10/20/15 – 10/22/15 159 Emission potential 3 weeks following Plover exclosure removal, revisit two transects from 8/2013 for direct comparison, intensive measurement within area slated for fencing

3/2016 3/1/16 – 3/3/16 115 Emission potential 6 months following Plover exclosure removal, revisit Straw Bale area, revisit three transects from 8/2013, two of which were revisited in 10/2015.

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Figure 1. Overview of PI-SWERL® measurements by sampling campaign.

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Figure 2. PI-SWERL® measurements by sampling campaign without background imagery.

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Methods The protocols of the 8/2013 measurement effort were largely followed in all subsequent sampling efforts. Briefly, two PI-SWERL® units were used at each of the campaigns. This facilitated the coverage of more area in less time, but, more importantly, allowed for an independent check on each of the two units through frequent collocated measurements. Each testing day was started at the beginning of a chosen transect by collocating the two PI-SWERL® units within about 5 meters of each other and running the same test (Hybrid 3500). The PI-SWERL® units were then moved a nominal distance of a meter or so and another collocation test was completed. This procedure was completed one more time so that each PI-SWERL had completed three replicate measurements and the two PI-SWERL®s were collocated for the span of these replicate measurements. Next, each PI-SWERL® was operated for not more than six tests along a transect of interest. The two PI-SWERL®s were moved in leapfrog fashion at some prescribed distance. After no more than six tests, before a break in measurement, or at the end of the day the two PI-SWERL® units were collocated again for three consecutive measurements. As an example, consider that at the beginning of the day, the two PI-SWERL® units are collocated at the beginning of a transect (0 m) where they each perform three consecutive measurements. Next, one of the units makes measurements at 100 m, 300 m, 500 m, 700 m, and 900 m along a transect direction while the other measures at 200 m, 400 m, 600 m, 800 m, and 1,000 m. Next, the two units meet at 1,100 m to perform three consecutive collocated measurements each before resuming the leapfrog pattern.

At each location where a PI-SWERL® test was completed, bulk soil material was obtained in the immediate vicinity (within a few centimeters) of where the PI-SWERL® was placed. Approximately 500 grams of material from the top 1 centimeter of sand were scooped into a plastic bag and saved for subsequent analyses. Results of analyses of samples collected during the 8/2013 have been summarized in an earlier report (Gillies et al., 2014), but size analyses of samples collected since then has not been undertaken. However, the samples are archived if further analyses are required.

Each PI-SWERL® test was examined to ensure compliance with quality criteria. The criteria included adequate RPM (blade revolutions per minute) convergence to program values, DustTrak concentration upper limits, and clean air blower maintaining set-point values.

Each PI-SWERL® test was analyzed for DustTrak PM10 emissions at the three “step” portions of the hybrid test corresponding to 2000, 3000, and 3500 RPM as shown in Figure 3. The threshold RPM was also obtained using an automated algorithm that identifies systematic movements in the two optical gate sensors (OGS 1 and OGS 2). Ultimately, the data analyst reviews the findings of the algorithm in every case to ensure that it has adequately identified the threshold.

Average PM10 DustTrak concentrations at each of the three RPM steps were used to estimate equivalent PM10 emissions at those RPM values. Since there are unit-to-unit variations in DustTrak response to dust, all DustTraks that were used in the study, including spare units, were collocated in the lab and exposed to a common level of dust concentration in a resuspension chamber. A specific unit (SN: 85200415) was arbitrarily chosen as a reference unit for normalizing all other units. These in-lab colocations of DustTraks served to supplement the field colocations of the two PI-SWERL® units used.

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Figure 3. Example of data extraction from an individual PI-SWERL test. The dashed black, horizontal lines correspond to the periods of time the DustTrak PM10 average was extracted to represent the 2000, 3000, and 3500 RPM steps. The vertical dashed, black line shows the point at which threshold detection algorithms for both OGS 1 and 2 indicate that threshold has been achieved – 1609 RPM in the example above. Note that once OGS counts exceed about 200 – 250 counts per second, the sensors become overloaded and cannot accurately count sand grains. OGS data after this level of counts is reached are likely nonsensical. This is the reason for the apparent (but not actual) dip in sand movement around t = 250 seconds into the test.

Dust emissions at specific values of RPM were calculated by averaging the one-second dust concentrations over the RPM step as indicated in Figure 3 and using the equation:

𝐸𝐸𝑖𝑖 =�𝐶𝐶𝐷𝐷𝐷𝐷,𝑖𝑖×

𝐹𝐹𝑖𝑖60×1000�

𝐴𝐴𝑒𝑒𝑓𝑓𝑓𝑓

where Ei is the PM10 dust emissions in units of mg/(m2 • second) at the ith step, CDT,i is the average DustTrak PM10 in mg/m3 (corrected to reference unit), Fi is the clean air flow rate in (and out of) the PI-SWERL chamber in liters per minute, and Aeff is the PI-SWERL effective area in m2 (0.035 m2).

Note about calculation of emissions for 8_2013 data Over the course of the present data analysis effort, it was determined that there was a systematic error in the analysis of the 8/2013 data. The source of error was that instead of cumulative emissions over a constant RPM step being used to calculate emissions, average emissions over that step were used

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DustTrak PM10 ConcentrationActual PI-SWERL RPMTarget Program RPMOGS1 sand counts - 10 s moving averageOGS2 sand counts - 10 s moving averageOGS1 threshold triggerOGS2 threshold triggerCombined trigger

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instead. This has been addressed by using the PM10 concentration data to calculate emissions for all subsequent measurements and reapplying this approach for 2013_08 data. Fortunately, the impact on the conclusions from the 8/2103 data is limited since the effect of this change in approach was to cause all previously reported emissions to be approximately (but not exactly) half the value of the emissions calculated using the newer, more correct method. Since the data from 8/2013 and subsequent report (Etyemezian et al., 2014) were used for relative estimation of emissions from different locations and the absolute value of emissions was not critical for any decisions that were undertaken, using this different approach does not affect prior conclusions. However, care must be taken when comparing absolute values of emissions from the 8/2013 data as processed and reported in the Etyemezian et al. (2014) report with the 8/2013 data reported here. Figure 4 shows how the new method for calculating emissions can be related to the values reported in Etyemezian et al. (2014).

Figure 4. Comparison of old and new method of calculating PI-SWERL® emissions from 8/2013 testing effort. The blue line is the 2:1 line going through the origin.

Results and Discussion In order to differentiate between measurements completed at different times, each measurement period has been assigned a color for its symbol on map figures. The size of the circle symbol has been standardized to indicate a specific emissions bin. The differences in how these maps appear between the present study and Etyemezian et al. (2014) is illustrated for the threshold wind speed for emissions

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Figure 5. Threshold 10-meter wind speed (mph). Categories are chosen so that each category contains 20% of all data. Left: As shown in Etyemezian et al. (2014); Right: As displayed in present study.

Figure 6. PI-SWERL®-measured emissions at 3000 RPM (32 mph) in units of mg of PM10 /m2 s. Left: As calculated and shown in Etyemezian et al. (2014); Right: As calculated and displayed in present study

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in Figure 5. An example of the differences in how data are visualized here as compared to earlier reports (Etyemezian et al., 2014) is shown in Figure 6 for emissions at 3000 RPM.

Plover Exclosure Threshold estimates and PM10 emission factors at 3000 RPM for points located within the Plover exclosure are given in Figure 7 and Figure 8, respectively. The same data are presented in a slightly different format in Figure 9 and summarized more succinctly in Figure 10. Overall, the results confirm the earlier finding of Etyemezian et al. (2014) regarding the Plover exclosure. Specifically, threshold wind speeds are generally higher in the exclosure and emissions at all values of PI-SWERL® RPM are lower compared to the region immediately north of the exclosure. Although emissions exhibited a peak during the 2015_09 campaign, the differences in emissions from other sample dates are small compared to the standard deviation of the measurements. The 2015_10 campaign was intended to provide a measure of how much emissions change in the area of the exclosure within a few weeks of removal of the exclosure (removed on the last day of 2015_09 field work). However, there appears to be no increase between the 2015_09 and the 2015_10 field measurements. It is possible that the amount of vehicle traffic over the three-week period in the interim was very limited. It is also possible that all the measurements conducted during 2015_10 may have exhibited reduced emissions due to either sand or atmospheric moisture. This latter possibility will be examined later in this report.

Measurements along a transect through the Plover exclosure in 2016_03 (≈ 6 months after seasonal removal of exclosure) are less ambiguous compared to the 2015_10 measurements. On the whole thresholds were lower and emissions potentials were higher at all three RPM values compared to measurements completed immediately (or very soon) after the exclosure was removed (2013_08, 2014_09, 2015_09). This supports the idea that removing the exclosure and allowing OHV to use the area results in increased emissions by roughly a factor of 2 to 3. It is possible that this increase in emissions is caused by an unrelated (to OHV activity) parameter, but this is unlikely since comparable increases over the same time period were not observed in other areas where OHV use was relatively constant (See discussion on Transects B, G, and T2). It is not clear to what extent the Plover exclosure surface represents the characteristics of the wider ODSVRA, especially since it is known that stabilizing materials (e.g., wood chips) have been added to the surface from time to time in support of Plover nesting activities. In addition to revisiting the Plover exclosure seasonally to determine if this trend holds up, it is recommended that another location that is representative of the ODSVRA be tested before and after periods of time when OHV activity was absent.

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Figure 7. Threshold wind speed (mph) in Plover Exclosure (Outlined in Orange). Note thresholds increase with increasing symbol size.

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Figure 8. Plover, Emissions (PM10 /m2 s) at 3000 RPM.

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a. Threshold (mph)

b. E(2000)

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c. E(3000)

d. E(3500)

Figure 9. Thresholds (mph) and emissions (PM10 /m2 s) for Plover transects by date. Orange line denote fence location.

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Figure 10. Summary of thresholds and emissions from Plover transects (inside fence only)

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Table 2. Summary of thresholds and emissions by transect/Location examined over all sampling times Loc/ Tran Cnt Threshold

(mph) E_2000

(mg/m2 s) E_3000

(mg/m2 s) E_3500

(mg/m2 s) Std

Threshold Std

E_2000 Std

E_3000 Std

E_3500 Plover Exclosure

2013_08 15 20 0.02 0.2 0.5 2 0.01 0.1 0.2 2014_09 39 25 0.01 0.2 0.5 3 0.02 0.1 0.2 2015_06 2015_09 45 24 0.03 0.4 0.9 3 0.07 0.3 0.5 2015_10 45 24 0.01 0.2 0.6 3 0.02 0.1 0.4 2016_03 23 22 0.1 0.6 1.3 2 0.0 0.2 0.6 TRAN A

2013_08 15 18 0.2 1.4 2.9 1 0.2 0.6 0.9 2014_09 2015_06 2015_09 2015_10 14 20 0.2 0.7 1.7 3 0.1 0.3 0.8 2016_03

TRAN B/G 2013_08 17 19 0.2 1.4 2.6 2 0.1 0.7 1.4 2014_09 2015_06 2015_09 2015_10 36 24 0.01 0.1 0.3 6 0.01 0.1 0.2 2016_03 33 21 0.1 0.8 1.7 2 0.1 0.5 1.0

TRAN D/K 2013_08 17 21 0.1 1.0 2.3 2 0.1 0.6 1.3 2014_09 15 25 0.01 0.2 0.7 2 0.01 0.2 0.7 2015_06 2015_09 2015_10 2016_03

TRAN NST1 2013_08 16 21 0.2 1.8 3.2 2 0.2 0.4 0.9 2014_09 19 20 0.04 0.4 1.1 4 0.03 0.4 0.6 2015_06 2015_09 2015_10 2016_03 TRAN M 2013_08 6 19 0.3 1.5 2.5 6 0.4 0.9 0.6 2014_09 2015_06 23 20 0.2 1.4 2.5 3 0.1 0.8 1.2 2015_09 2015_10 2016_03 TRAN T2 2013_08 22 20 0.2 1.2 2.2 2 0.1 0.8 1.5 2014_09 2015_06 2015_09 2015_10 2016_03 22 20 0.2 0.6 1.4 2 0.1 0.6 1.1

Straw Bales 2013_08_EW 16 20 0.04 0.4 0.9 1 0.02 0.1 0.3 2013_08_NS 7 20 0.02 0.3 0.9 1 0.02 0.1 0.3

2014_09_Bales 23 20 0.03 0.3 0.8 1 0.01 0.2 0.4

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Loc/ Tran Cnt Threshold (mph)

E_2000 (mg/m2 s)

E_3000 (mg/m2 s)

E_3500 (mg/m2 s)

Std Threshold

Std E_2000

Std E_3000

Std E_3500

2014_09 W_of_Bales 12 21 0.02 0.2 0.5 2 0.01 0.1 0.2 2015_06

2015_09 W_Of_Bales 18 23 0.1 0.5 0.9 3 0.1 0.3 0.4 2015_10 2016_03 22 19 0.03 0.3 0.9 2 0.02 0.2 0.5

Fence_Area 2013_08 Fence_Vicinity 10 19 0.1 0.9 1.5 5 0.1 0.2 0.5

2014_09 2015_06 65 22 0.1 0.7 1.4 3 0.1 0.3 0.5 2015_09 61 23 0.1 0.7 1.4 2 0.1 0.3 0.7 2015_10 55 22 0.02 0.3 0.7 4 0.03 0.2 0.4 2016_03 11 23 0.04 0.4 0.8 1 0.03 0.2 0.3

Other Transect repeats Figure 11 shows that Transects A, which was first sampled in 2013_08 was resampled in 2015_10. Transects B (first sampled in 2013_08) and G (introduced in 2015_10) were also sampled in 2015_10 and 2016_03. The proximity of Transect G to Transect B makes it useful for examination. Figure 12 shows that emissions from Transect A at 2000 RPM are slightly higher in 2013_08 than 2015_10. The difference appears to be greatest at 3000 RPM. This is a frequently ridden area and it is unlikely that the dune sand has become inherently less emissive along Transect A between the 2013_08 and the 2015_10 sampling periods. In examining differences for Transect B (Figure 14) the differences are even starker between 2015_10 measurements and other measurement efforts. Overall, this suggests that there may have been an external environmental factor that was subduing emissions during the 2015_10 tests. It is possible that this was a result of either moist sand at depth (inches below the surface) from recent rains that was providing enough moisture to reduce emissions or that high ambient relative humidity imparted sufficient moisture to the dune surface to keep it from emitting as much as it would under completely dry conditions. It is noteworthy that measurements in the Plover exclosure on 10/20/15 (2015_10, Figure 10) indicate lower emissions than before the exclosure was removed (2015_09), although the relative difference is small compared to what was observed for Transect B and G.

Examination of emissions measured during 2014_09 along transects similar to those originally measured in 2013_08 (See Figure 11) points to similar phenomenon. Namely, it appears that emissions measured in 2014_09 were systematically lower than those measured in 2013_08 (Figure 17 and Figure 19). This supports the notion that there is a need for developing an objective metric for when the dune surface is considered to be dry enough for testing, a set of correction factors for “normalizing emissions” to the “dry equivalent”, or simply for awareness that there is the potential for a strong seasonal/temporal component to the emissions paradigm at the ODSVRA.

Emissions at 3500 RPM from Transect M (Figure 20), which was first measured during the 2015_06 campaign are shown in Figure 22. A comparable transect does not exist from any of the other field campaigns. However, data from several different transects that were measured during the 2013_08

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campaign can be selected to provide comparisons for Transect M. Figure 21 shows that emission from Transect M at 3000 RPM and threshold wind speeds for emissions were of comparable magnitude with earlier measurements that were conducted in 2013_08.

Along Transect T2, comparable measurements of threshold and emissions at 2000 RPM were observed in 2013_08 and 2016_03 (Figure 24). However, emissions at higher values of RPM (3000 and 3500) were greater in 2013_08 than 2016_03 by about a factor of 2.

In general, emissions in 2013_08 were higher than at other times, especially at the 3000 and 3500 RPM levels (see Table 2). It is not clear if this is related to the end of summer conditions and can be routinely expected in the August timeframe, simply a characteristic of the 2013_08 measurement conditions, or a due to measurement uncertainty. It is recommended that additional PI-SWERL® measurements be conducted again in late summer and repeated in early fall, immediately after removal of Plover exclosure.

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Figure 11. East-West 2013_08 Transects A (top) can be compared with 2015_10 Transects A, 2013_08 Transect B can be compared to 2015_10 and 2016_03 Transects B and G (middle, green and gray only). G is included because of proximity to B. East-West 2013_08 Transect T2 (between A and B) can be compared with 2016_03 T2. East-West 2013_08 Transects D (bottom) can be compared with 2014_09 Transect K. North-South 2013_08 Transect NST1 is comparable to 2014_09 Transect K.

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a. E 2000 – Transect A

b. E 3000 – Transect A

Figure 12. Comparison of Transect A emission factors between 2013_08 and 2015_10.

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Figure 13. Summary Transect A.

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a. E 2000 Transect B

b. E 3000 – transect B

Figure 14. Comparison of Transect B emission factors between 2013_08 and 2015_10.

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Figure 15. Summary Transect B (and G in 2015_10 and 2016_03)

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Figure 16. Comparison of 2013_08 East-West Transect D Emissions at 3000 RPM with those of Transect K from 2014_09

Figure 17. Transect D from 2013_08 compared to Transect K from 2014_09.

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Figure 18. Comparison of 2013_08 (North-South) Transect NST1 Emissions at 3000 RPM with those of NST1 from 2014_09.

Figure 19. Transect NST1 Summary.

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Figure 20. Transect M emissions (PM10 /m2 s) at 3500 RPM from 2015_06 measurements and selected data from 2013_08 for comparison.

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a. Threshold wind speed (mph)

b. Emissions at 3000 RPM

Figure 21. Threshold wind speed (mph) and emissions (PM10 /m2 s) at 3000 RPM for Transect M from 2015_06 and from locations close to Transect M from 2013_08 measurements.

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Figure 22. Transect M from 2015_06 and sampled points from intersecting transects from 2013_08.

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a. Threshold wind speed (mph)

b. Emissions at 3000 RPM

Figure 23. Threshold wind speed (mph) and emissions (PM10 /m2 s) at 3000 RPM for Transect T2 from 2013_08 and 2016_03

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Figure 24. Transect T2 Summary.

Straw bale measurements An array of straw bales was installed in 03/2014 to provide mitigation for blowing sand and emissions of dust. It was not possible to obtain PI-SWERL data prior to installation of the straw bale controls. However, during the 2014_09 measurement campaign and again during the 2016_03 effort, the area that contained the straw bale controls was sampled (Figure 25). Measurements within the straw bale site compare very well between 2014_09 and 2016_03. These measurements can be compared with measurements that fall nominally along the same transect, but are farther to the West and were completed at different times (2013_08 and 2015_09). A sampling of those comparisons is shown in Figure 26 for the threshold wind speed and the emissions measured at 3000 RPM. Threshold values are similar to at the Straw Bale site to those measured farther to the west. Most of the individual emissions measurements within the straw bale site are lower than those measured to the west of the straw bales. On the whole this analysis indicates that the estimates of emission potential at the straw bales (and especially how they compare to other areas) from extrapolation of 2013_08 data that were not collected specifically in the straw bale region provided reasonable estimates of emission potential. This is important since those estimates were used in part to determine impacts of dust control application in the form of straw bales.

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Figure 25. Straw bale area emissions (PM10 /m2 s) from 2014_09 (pink transect at right of figure) with premeasurement in 2016_03 and points of comparison from 2013_08 and 2015_09.

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a. Threshold wind speed (mph)

b. Emissions at 3000 RPM

Figure 26. Threshold wind speed (mph) and emissions (PM10 /m2 s) at 3000 RPM from the straw bale area and related locations measured during the 2013_08 and 2015_09 campaigns.

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Figure 27. Straw bales and vicinity summary. 2013_08 data are from nearby transects that were used to interpolate data for modeling purposes. 2014_09_W_of_bale and 2015_09_w_of_bale are transects that were completed in the E-W direction but were entirely west of where the straw bales are located.

Sand fence area In Spring 2015, a series of sand fences was emplaced within the ODSVRA riding area. The location of these fences was informed, in part, by the emissions measurements of the 2013_08 effort. However, actual measurements in the area where the fences were installed were limited in number and the estimate of emissions reduction afforded by locating the fences at their final placement relied on extrapolation from nearby PI-SWERL® measurements. During several subsequent field campaigns (2015_06, 2015_09, 2015_10) the region that was bounded by the fencing and the surrounding area was sampled more intensively with the PI-SWERL® (Figure 28). The results are shown in Figure 29 for threshold wind speed and emissions at all RPM steps. It is clear to see that, as noted before, thresholds were higher and emissions were lower during the 2015_10 measurement campaign, further providing evidence that soil conditions at that time were likely influenced by recent (through precipitation) or concurrent (through fog/ high relative humidity) moisture sources.

Data collected in 2015_06 and 2015_09 appear to show very similar emissions at all RPMs as data from 2013_08 measurements in the vicinity of where sand fencing was emplaced. Qualitatively, this suggests that estimates of emissions controlled by placing sand fences were realistic in magnitude and in relation to other locations within the ODSVRA. Note that data from 2016_03 appear to show lower emissions than 2015_06 and 2015_09. However, the number of measurement locations was fairly small in 2016_03 compared to the other two periods.

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Figure 28. Locations of PI-SWERL® measurements used to estimate emissions from sand fence area. Note 2013_08 data were used to extrapolate potential for emissions for modeling spatial emissions. Subsequent measurements targeted areas that were actually in vicinity of fencing.

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a. Threshold wind speed

b. Emissions at 2000 RPM

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c. Emissions at 3000 RPM

d. Emissions at 3500 RPM

Figure 29. Comparison of threshold wind speed (mph) in fenced area by sample date.

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Figure 30. Measurement in sand fence area. 2013_08 data represent measurements near sand fence area that were used to estimate modeled emissions for sand fence area.

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Conclusions Aggregate data for comparison of transects and areas that were measured at different times with the PI-SWERL® are provided in summary form in Table 2. The major findings that have been discussed in this interim report are:

- Measurements from the 2015_10 field campaign exhibit signs of being influenced by environmental conditions. Specifically, emissions are lower than previous measurements in several areas (Transect A, Transect B, Location of sand fencing).

- Measurements within the Plover exclosure immediately prior to the seasonal removal of the fence in 2013_08, 2014_09, and 2015_09 were compared with measurements 6 months following the removal (2016_03). This comparison suggested that emissions increases after the fence is removed are likely associated with OHV travel. It is unclear how representative the Plover nesting area is of the ODSVRA since it is known to have been amended with wood chips and other materials to aid in nesting activities. However, it would be instructive to repeat these measurements to ensure that the apparent effect of OHV riding was not an anomalous finding.

- Examination of data from 2014_09 and comparison with other measurement periods (Transect D/K and NST1) suggests that those measurements may also have been influenced by environmental conditions, albeit to a lesser degree than 2015_10.

- The area where straw bales where emplaced was sampled in 2014_09 and 2016_03. Data from those measurements agree very well. In comparing to other nearby measurements from 2013_08 and 2015_09, the emissions from the straw bales measured in 2014_09 and 2016_03 appear to be only slightly lower. This is an important comparison because the nearby measurements from 2013_08 were used to estimate the emissivity in the straw bale area for modeling purposes. If taken at face value, then this would suggest that emissions from the straw bale area were slightly overestimated (by about 10%) in earlier model estimates.

- Measurements along Transect M (cuts NW-SE across “paw print” area) were consistent between the 2013_08 sand 2015_06 sampling efforts

- Measurements within the Fence deployment area in 2015_06 and 2015_09 were consistent (within 20%) with measurements from points along nearby transects from 2013_08. This is important as those 2013_08 measurements were used to estimate emission potential of the fence installment area in a modeling exercise. Even 2015_10 measurements mostly corroborated the other measurements from within the fence area.

- On the whole it appears that 2013_08 measurements of emissions were higher than other sampling periods since that time. The cause for this is unknown at this time.

Based on these conclusions, our preliminary recommendations are:

- Establish protocol for determining if and to what degree surface emissions are being influenced by temporary environmental conditions such as sand moisture or relative humidity. Such a protocol would not necessarily be used to only conduct measurements on days when no such environmental factors are at play, but rather to inform that there is the potential that they are at play. Understanding the impact of these environmental conditions could be beneficial for an

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overall understanding of the dune emissions system and ultimately, effective controls on emissions.

- Resample the straw bale area periodically (especially in late summer) to ensure that emissions values used in modeling efforts are representative.

- Resample the Plover exclosure region immediately prior to the seasonal removal and emplacement of the exclosure fence. This will provide additional data to support the preliminary finding that OHV driving causes emissions to change within the exclosure.

- Attempt to conduct a Plover-style measurement campaign at a location where the surface has not been ammended (as it was in the Plover nesting area).

- At each field sampling effort, resample a transect where the emissions were originally measured during one or more of the other field sampling efforts (preferably 2013_08). This will serve to help understand temporal changes in emissions, both seasonally and through time.