Using strontium isotopes to trace dust from a drying Great Salt Lake to adjacent urban areas and mountain snowpack

With the desiccation of saline lakes around the globe, it is increasingly important to quantify the impacts of playa dust on downwind urban areas and mountain snowpack. In this study, we used 87Sr/86Sr ratios of carbonate minerals to trace dust from playas to urban areas and mountain snowpack. We focused on dust contributions from Great Salt Lake (GSL), in northern Utah, USA, which recently reached historic lows in water levels exposing large areas of dry lakebed. We measured 87Sr/86Sr ratios in dust from GSL, Sevier Dry Lake (SDL), and other playas across western Utah and compared them to 87Sr/86Sr ratios in dust across the urban Wasatch Front and mountain snowpack collected seasonally from 2015–2018. Dust from GSL had unique 87Sr/86Sr ratios (∼0.715) relative to SDL (∼0.710) and other playas (∼0.711 to 0.712), providing a potentially powerful tool for tracing GSL dust to downwind areas. Dust deposition had 87Sr/86Sr ratios ranging from ∼0.710 to ∼0.712 in the urban area and snowpack, within the range of playa dust sources. Using a simple two-endmember mixing model considering only GSL and SDL as sources, GSL contributed 5% of the dust flux to the southern Wasatch Front (Provo) and between 30%–34% of the dust flux to the northern Wasatch Front (Salt Lake City, Ogden, and Logan). For mountain snowpack, GSL contributed 11% of the dust flux to the Uinta Mountains and 22% of the dust flux to the Wasatch Mountains. Dust transport modeling could be combined with 87Sr/86Sr fingerprints for source apportionment in northern Utah and other areas that are impacted by regional playa dust.


Introduction
Mineral dust is globally important as it affects climate and biogeochemical cycles (Engelbrecht andDerbyshire 2010, Mahowald et al 2010) and decreases total mountain runoff by causing earlier snowmelt that exposes plants and soils to increased evapotranspiration , yet it is often difficult to identify specific dust sources. Dust storms typically contain a mixture of particles from different sources (Lawrence and Neff 2009), which may include playas, alluvial fans, sand dunes, and anthropogenically disturbed soils (Reheis and Kihl 1995, Belnap and Gillette 1997, Neff et al 2008, Bullard et al 2011. In particular, playas represent an increasing source of dust with the global desiccation of saline lakes by water diversions (Wurtsbaugh et al 2017). Dust is tracked using atmospheric transport modeling (Mallia et al 2017), satellite imagery (Hahnenberger and Nicoll 2012), geochemistry (Reheis et al 2002), mineralogy and particle size distributions (Munroe 2014), and isotope fingerprinting . Each of these has significant uncertainties, such that improved methods are needed for tracing dust from sourceto-sink to inform strategies for mitigating dust emissions.
Strontium isotope ( 87 Sr/ 86 Sr) ratios are widely used for fingerprinting dust sources but have not been used to track dust from playas at a regional scale. Commonly 87 Sr/ 86 Sr ratios are analyzed on the aluminosilicate mineral fraction after removing the carbonate minerals by rinsing with acetic acid (Biscaye et al 1997, Chen et al 2007, Palchan et al 2013, Zhao et al 2015, Gross et al 2016 or by checking that carbonate minerals do not exist in the samples (Zdanowicz et al 2006). Grain size typically affects the 87 Sr/ 86 Sr ratio of the silicate mineral fraction given high Rb concentrations and high 87 Sr/ 86 Sr ratios in clays (Chen et al 2007). The carbonate mineral fraction may contain important fingerprinting information in carbonate-rich dust, particularly in regions dominated by playa dust sources. For example, pedogenesis studies use 87 Sr/ 86 Sr ratios of the carbonate mineral fraction (from acetic acid leaching) and the silicate mineral fraction (from total digestion) to determine calcium sources from atmospheric inputs versus silicate weathering (Capo et al 1998, Capo and Chadwick 1999, Naiman et al 2000. Carbonate-rich playas may have unique 87 Sr/ 86 Sr ratios if the watersheds contain different bedrock types, which would make it possible to trace the carbonate fraction of dust from playa sources. Dust storms occur frequently along the Wasatch Front in northern Utah, USA, with negative impacts on air quality and mountain snowpack (Hahnenberger and Nicoll 2012, Steenburgh et al 2012, Carling et al 2012, Reynolds et al 2014. Dust sources are dominated by regional playas, including Sevier Dry Lake (SDL) and the lakebed of Great Salt Lake (GSL) (Hahnenberger and Nicoll 2014, Hahnenberger and Perry 2015, Skiles et al 2018, which are remnants of Pleistocene Lake Bonneville (Oviatt and Shroder 2016) (figure 1). The largest dust events typically occur with strong south-southwesterly flows ahead of cold fronts, carrying dust from southwest Utah to the Wasatch Front (Steenburgh et al 2012, Nicoll et al 2020. The importance of regional playa dust inputs to the Wasatch Front, and minimal inputs from longrange global dust, is supported by grain-size distribution, mineralogy, and chemistry data (Goodman et al 2019) and satellite imagery Nicoll 2014, Nicoll et al 2020). Due to irrigation diversions, SDL has remained dry since 1880 except during years of high snowmelt runoff (Oviatt 1988). The GSL, located immediately adjacent to two million people in the Wasatch Front, reached its lowest lake level in recorded history in November 2016 with a 50% reduction in lake area relative to 1847. The long-term decline in GSL water levels is due to water development and river diversions (Wurtsbaugh et al 2017). A proposed diversion on the Bear River, the largest tributary of GSL, would cause further decline in the lake level and expose another 80 km 2 of lakebed (Wurtsbaugh et al 2017). As water levels continue to drop, dust events may increase in frequency and intensity in the future (Skiles et al 2018). Ultimately, decreasing water levels on GSL could create a 'dust bowl' similar to Owens Dry Lake in California (Gill 1996, Reheis 1997, Reheis et al 2002).
The purpose of our study is to use 87 Sr/ 86 Sr ratios in carbonate minerals as a tracer of dust from playa sources to urban areas and mountain snowpack. Specific objectives are to: (1) evaluate the regional variability of 87 Sr/ 86 Sr ratios in carbonate minerals from playas; (2) evaluate the seasonal 87 Sr/ 86 Sr ratios of dust in urban areas and mountain snowpack downwind of the playas; and (3) quantify the amount of dust from specific playa sources using isotopic fingerprints. The study was carried out in Utah, USA, where the dust system is characterized by regional dust emissions from playas and deposition along the populated Wasatch Front (>2 million people) and the Wasatch and Uinta Mountains (Dastrup et al 2018, Skiles et al 2018 al 2019) (figure 1). We hypothesized that variable 87 Sr/ 86 Sr ratios in lacustrine carbonates and modern river inflows to lakes and playas across the Bonneville Basin (Hart et al 2004) could be used as a tracer of dust from specific playas. Identifying the origin of dust storms is important for determining how future water diversion schemes could alter dust source regions and affect downwind populations and mountain snowpack. For example, 87 Sr/ 86 Sr ratios could help determine whether dust fluxes from GSL increase with the proposed Bear River diversion.

Study background
In a previous study, we investigated the geochemistry, mineralogy, and grain size of dust from the GSL lakebed and other regional dust sources, including SDL, Sevier Desert, Tule Valley, Fish Springs playa, and Wah Wah Valley (Goodman et al 2019). The study showed that playas are the dominant source of dust to the urban Wasatch Front and mountain snowpack, contributing up to 90% of the total dust flux. Bulk geochemistry and mineralogy were similar amongst the various dust sources, providing no diagnostic fingerprints for source apportionment. Concentrations of specific elements (e.g. V, Cd, Sb, and Se) were higher in the Wasatch Front relative to dust sources, reflecting anthropogenic inputs of these elements. Here, we expand on the dataset to explore the use of isotopic fingerprints to identify the specific playas that contribute dust to the Wasatch front, with an emphasis on quantifying dust from SDL and GSL.

Sample locations and timing
To compare the isotopic composition of dust emissions from western Utah playas with dust deposition across northern Utah, we sampled 15 representative playa dust source locations during 2016-2017, four urban sites along the Wasatch Front during 2015-2018, and dust in snowpack from the Wasatch and Uinta Mountains during springtime from 2016-2018 ( figure 1). Details about sampling methods are provided in Goodman et al (2019). Briefly, dust was collected from playas using passive BSNE (Big Springs Number Eight) samplers with one port at 50 cm above the ground surface (single-port sampler) or four ports at 10, 15, 20, and 50 cm (four-port sampler). Playa dust samples were collected at SDL (SDL1, SDL2, and SDL3), Tule Valley (TV1 and TV2), Dugway Proving Grounds (DPG), and GSL (GSL1, GSL2, GSL3, and GSL4). The samplers were deployed for several months to collect sufficient dust for geochemical analyses, with one to three deployments per site, for a total of 69 unique samples. At the urban sites, wet and dry deposition (including dust and other aerosols) was collected at Provo, Salt Lake City (SLC), Ogden, and Logan on the roofs of fourstory university buildings using a large plastic tote covered by a screen with marbles. The samplers were placed for 2-month periods during fall 2015, spring 2016, and from June 2017 through September 2018, for a total of 35 urban samples over nine sample periods capturing seasonal and interannual variability. This included two samples that were collected for short 1-week periods at Provo when dust events were predicted in the weather forecast to compare isotopic ratios in short-and long-term samples. For snowpack, we sampled discrete dust layers at peak snowpack from the Wasatch and Uinta Mountains during spring 2016, 2017, and 2018, for a total of 22 samples, each likely representing an individual dust event including mineral particles and other aerosols.

Sample treatment and geochemical and isotopic analyses
To prepare samples for geochemical and isotopic analyses, dust was dried in a laminar flow hood at 50 • C and treated with 30% hydrogen peroxide to remove organic matter. A subset of playa dust samples was wet sieved through a 52 µm nylon mesh screen to compare the chemical and isotopic composition of 'bulk' versus 'fine' samples. Of the 69 playa samples, we analyzed 28 on the bulk fraction, 32 on the fine fraction, and 9 on both bulk and fine fractions.
Dust samples were analyzed for trace and major element concentrations and 87 Sr/ 86 Sr ratios following a four-step sequential leaching procedure. Each 200 mg sample aliquot was reacted with 1 M ammonium acetate (buffered to pH = 7), 1 M acetic acid, 1 M nitric acid, and aqua regia (1:3 ratio of concentrated nitric acid to hydrochloric acid). The goal of the sequential leaching procedure was to target the exchangeable and water-soluble fractions with ammonium acetate, the carbonate mineral fraction with acetic acid, the feldspar and clay mineral fractions with nitric acid, and refractory minerals with aqua regia, although not all silicate minerals were completely dissolved (Lawrence et al 2010, Dastrup et al 2018, Goodman et al 2019. In particular, acetic acid effectively reacts with the carbonate mineral fraction of dust and soils for 87 Sr/ 86 Sr analyses (Naiman et al 2000). The four leachates from each sample were analyzed for trace and major element concentrations using an Agilent 7500ce quadrupole inductively coupled plasma mass spectrometer (ICP-MS), as described in Goodman et al (2019).
All dust samples (n = 135), with the exception of one snow dust sample with insufficient sample mass, were analyzed for 87 Sr/ 86 Sr ratios on the acetic acid leachate using a Thermo Scientific Neptune multicollector ICP-MS. Additionally, to compare 87 Sr/ 86 Sr ratios within different mineral fractions, a subset of playa, urban, and snow dust samples were analyzed for 87 Sr/ 86 Sr ratios on the ammonium acetate leachate (n = 52) and nitric acid leachate (n = 22).
The samples were purified inline using a Sr-FAST ion chromatographic column packed with a crown ether resin (Mackey and Fernandez 2011). During the analyses reported herein, we determined the 87 Sr/ 86 Sr ratio of the standard reference material SRM987 (certified value of 0.71034 ± 0.00026) to be 0.710293 ± 0.000013 (n = 133; mean ± standard deviation). Analytical precision (standard error) of all samples ranged from ±0.000003-0.000030. The 87 Sr/ 86 Sr ratios were corrected for mass bias using an exponential law, normalizing to 86 Sr/ 88 Sr = 0.1194 (Steiger and Jäger 1977). Isobaric interferences on the 87 Sr/ 86 Sr ratios, such as from 87 Rb and 86 Kr, were corrected by simultaneously monitoring 85 Rb and 83 Kr using the corresponding invariant ratios of 87 Rb/ 85 Rb = 0.385706 and 86 Kr/ 83 Kr = 1.502522 (Steiger and Jäger 1977).

87 Sr/ 86 Sr ratios in dust from the playas, urban area, and mountain snowpack
Strontium isotope ( 87 Sr/ 86 Sr) ratios in the acetic acid leachate (or carbonate mineral fraction) ranged widely in the playa dust sources, with generally increasing 87 Sr/ 86 Sr ratios from south at SDL (~0.710) to north at GSL (~0.715) and intermediate values (~0.711 to~0.712) in between (figure 1). Specifically, the values ranged from 0.71008 ± 0.00009 (mean ± standard error) at SDL (n = 14) to 0.71476 ± 0.00006 at GSL (n = 32), with intermediate values of 0.71178 ± 0.00010 at the other playas (n = 32) (figure 2). These values are averages from fine and bulk samples within each group, where fine samples were sieved to <52 µm and the bulk samples contained particles >200 µm that are likely not available for aeolian transport (Goodman et al 2019).
To evaluate a potential grain-size effect on 87 Sr/ 86 Sr ratios, we analyzed for both fine and bulk fractions in a subset of samples (n = 9) with similar values in both fractions ( figure 3). Further, the ammonium acetate, acetic acid, and nitric acid leachates had similar 87 Sr/ 86 Sr ratios (figure 4). In the dust samples, >83% of Sr was contained in the ammonium acetate and acetic acid leachate fractions, with up to 14% of Sr in the nitric acid and up to 3% in the aqua regia fractions (Goodman et al 2019).
The 87 Sr/ 86 Sr ratios in dust deposition across the Wasatch Front urban area (Provo, SLC, Ogden, and Logan) and snowpack (Wasatch and Uinta Mountains) were within the range of playa values (figure 2). At the urban sites, the 87 Sr/ 86 Sr ratios ranged from 0.71022 ± 0.00010 at Provo (n = 10) to 0.71169 ± 0.00013 at Ogden (n = 8), with SLC and Logan showing similar values as Ogden. Ratios for dust in snow were lower at the Uinta Mountains relative to the Wasatch Mountains but both were within the range of urban dust, averaging 0.71055 ± 0.00013 in the Uintas (n = 10) and  0.71111 ± 0.00012 in the Wasatch (n = 11) over three sampling seasons. Raw 87 Sr/ 86 Sr ratios and geochemical data for all samples are provided in the Supplementary material (table S1 (available online at https://stacks.iop.org/ERL/15/114034/mmedia)).

Seasonal variability in 87 Sr/ 86 Sr ratios of urban dust
The 87 Sr/ 86 Sr ratio in dust varied over time at the urban sites (figure 5). Provo dust consistently had the lowest 87 Sr/ 86 Sr ratio during each sampling period. The ratios from the four urban sites converged during Feb-May 2016 and Jan-Mar 2018 but Provo still had the lowest values. During most sampling periods, there was a large separation between Provo and the other sites. The site with the highest ratio changed during each sampling period, with SLC, Ogden, and Logan showing the highest values but the most variability in 87 Sr/ 86 Sr ratios. Provo, the southernmost sampling site in the urban area, had 87 Sr/ 86 Sr ratios similar to SDL while the 87 Sr/ 86 Sr ratios at SLC, Ogden, and Logan were more similar to GSL and other playas. The 1-week sample from Provo had the same 87 Sr/ 86 Sr ratio as the corresponding seasonal

Variability in the 87 Sr/ 86 Sr ratio of playa dust sources
Strontium isotope ( 87 Sr/ 86 Sr) ratios varied from 0.710 in the Sevier Desert to 0.715 at GSL in the carbonate mineral fraction (figures 1 and 2), which is a wide range in values (relative to analytical errors on the order of ±0.00001) that provides leverage for discriminating the relative importance of dust from each source (Chen et al 2007). Other playas from the GSL Desert and Sevier Desert contained intermediate 87 Sr/ 86 Sr ratios of~0.711 or~0.712 (figure 1). The variability in 87 Sr/ 86 Sr ratios (increasing values from south to north) is primarily a result of lacustrine carbonate mineral precipitation from Lake Bonneville and subsequent lakes over time depending on river inflows and separation of the lake into different basins (Hart et al 2004). The Bear River, which is the dominant Sr source to GSL, contains elevated 87 Sr/ 86 Sr ratios relative to the Sevier River, the dominant Sr source to SDL. The high 87 Sr/ 86 Sr ratio in the Bear River is due to thermal spring and groundwater additions to the lower section of the river, including Crystal Hot Springs with a Sr concentration of 36 ppm and 87 Sr/ 86 Sr ratio of 0.72341 (Hart et al 2004). Two unusually low values at GSL (figure 2) are from GSL2, which may reflect the mixing of dust inputs from the Kennecott tailings pile or other localized sources on the south end of the lake. However, even the two 'low' values at GSL are higher than 87 Sr/ 86 Sr ratios from any other sources.

Using 87 Sr/ 86 Sr ratios to quantify dust inputs from the dry lakebed of Great Salt Lake
With the newly developed 87 Sr/ 86 Sr isotopic fingerprinting tool, we can begin to identify specific dust sources that affect the Wasatch Front and monitor changes over time. In a previous study, we showed that regional playas are responsible for most of the dust mass deposited along the Wasatch Front (Goodman et al 2019). Other studies highlight the importance of regional playas contributing to Wasatch Front dust Nicoll 2014, Nicoll et al 2020). Thus, tracking playa sources using 87 Sr/ 86 Sr ratios would describe a majority of regional dust transport and deposition. The similarity in 87 Sr/ 86 Sr ratios regardless of grain-size fraction (figure 3) or leaching fraction (figure 4) further strengthens the use of an 87 Sr/ 86 Sr fingerprint for playa dust sources. The similarities in 87 Sr/ 86 Sr ratios among size fractions and the readily leached mineral fractions may be a result of mineral precipitation in the playa environment, with mineral precipitation resulting in the same 87 Sr/ 86 Sr ratio regardless of mineral grain size (e.g. precipitation of fine carbonate mud and large ooids) or mineral phase. Further, the nitric acid leachate fraction may contain trace amounts of unreacted carbonate minerals, such as dolomite, that dominate the 87 Sr/ 86 Sr ratio over the feldspar or clay fraction.
The observed 87 Sr/ 86 Sr ratios in the Wasatch Front urban area and mountain snowpack could be explained as a mixture of inputs from SDL, GSL, and/or other playas. As a first attempt at source apportionment, we used a two-endmember mixing model to compare the relative amount of dust from SDL and GSL, assuming these are the two major sources of dust to the Wasatch Front (Hahnenberger and Nicoll 2014, Hahnenberger and Perry 2015, Skiles et al 2018, Nicoll et al 2020. Other playas besides SDL and GSL contribute dust to the Wasatch Front, yet the 87 Sr/ 86 Sr ratios for Provo dust were nearly identical to the 87 Sr/ 86 Sr ratios for SDL, highlighting the importance of SDL as the primary dust source. Sites further north (SLC, Ogden, and Logan) had higher 87 Sr/ 86 Sr ratios that could reflect additional inputs from GSL or other playas (figure 2). Given their proximity to GSL, it seems likely that at least a portion of the dust is from the GSL lakebed, contributing to the higher 87 Sr/ 86 Sr ratios at SLC, Ogden, and Logan relative to Provo. The two-endmember mixing model results should be considered maximum values for GSL dust inputs since other playa sources also contributed to the observed 87 Sr/ 86 Sr ratios, but are at least an approximation of the potential impact of GSL dust.
To quantify seasonal contributions of GSL dust to each urban area and to mountain snowpack, the two-endmember mixing model (Naiman et al 2000) included average 87 Sr/ 86 Sr values from GSL and SDL: where ( 87 Sr/ 86 Sr) GSL is the average value of 0.71476 for GSL, ( 87 Sr/ 86 Sr) SDL is the average value of 0.71008 for SDL, and x is the fraction of GSL dust contributing to observed values in urban or snow dust. A major assumption in this mixing model is that Sr concentrations are equal across the playa dust sources since isotopic mixing is a function of both Sr concentrations and 87 Sr/ 86 Sr ratios. From the samples we collected, Sr concentrations were similar for GSL and SDL in the ammonium acetate fraction but much higher for GSL in the acetic acid fraction (supplementary material, figure S1). Thus, using Sr concentrations from the acetic acid fraction in the mixing equation would result in lower estimates of GSL dust inputs. The mineralogy and Sr concentration of playa soils and dust depends on the location within the playa that was sampled. Therefore, the relative differences in Sr concentrations is likely an artifact of under-sampling because we only had four sampling locations at GSL and three sampling locations at SDL. If we were able to sample dust emissions across the entire playa surface at GSL and SDL, we assume that both playas would have similar Sr concentrations. Clearly, additional work is needed to characterize spatial heterogeneity in Sr concentrations across dust-producing areas of the playas. On the other hand, 87 Sr/ 86 Sr ratios from our limited sampling at each playa are likely representative of the entire playa surface since these values in the readily leachable fraction represent Sr that precipitated from well-mixed water, regardless of the dominant mineralogy upwind of the sampling location.
The mixing model shows seasonal and spatial variability in the amount of GSL dust inputs to the Wasatch Front over the 3-year period (supplementary material, table S2). The fraction of GSL dust ranged from 0%-18% at Provo, 16%-48% at SLC, 24%-48% at Ogden, and 12%-49% at Logan during the study period. On average, GSL contributed 5% of the dust to Provo and between 30%-34% of the dust to SLC, Ogden, and Logan. These values show a clear trend from south to north, with Provo receiving less dust from GSL than SLC, Ogden, or Logan. This is expected because the dust storms are typically driven by south-southwesterly winds that would send GSL dust to SLC, Ogden, and Logan but not to Provo (Jewell and Nicoll 2011). At Provo, the dust is likely sourced from SDL since the Provo 87 Sr/ 86 Sr values matched so closely with SDL and were lower than GSL and other playas. For snowpack, GSL dust contributed 0%-22% (average: 11%) of the dust to the Uinta Mountains and 13%-41% (average: 22%) of the dust to the Wasatch Mountains. These differences are also expected since the Wasatch Mountains are closer to GSL and thus should receive more dust from GSL. Notably, in all cases SDL was a more important dust source than GSL, even at the northernmost sampling sites, in part because SDL covers a larger surface area than the dust-producing areas of GSL. However, with ongoing declines in the GSL water level there could be relatively greater amounts of GSL dust in the future.
Seasonal differences in the inputs of GSL dust suggest that the relative importance of the GSL lakebed as a dust source may change depending on meteorological patterns or surface conditions on the lakebed. Higher 87 Sr/ 86 Sr ratios of urban dust during fall 2015 and fall 2018 may reflect seasonal wind patterns or drier conditions on the GSL lakebed during fall, leading to a greater input of GSL dust to the Wasatch Front. While the inputs of GSL dust to SLC, Ogden, and Logan changed across sampling periods, during most sampling periods GSL dust did not impact Provo. For snowpack, the Wasatch Mountains received more dust from GSL relative to the Uinta Mountains during all 3 years.
While the two-endmember mixing model is a first approximation at dust source apportionment for the Wasatch Front, a three-endmember mixing model including SDL, GSL, and other playas would more accurately predict dust contributions from playa sources. However, it is not possible to solve the equation for three endmembers because there is not a unique solution. An independent method for assessing contributions from each source is needed, which could then be tested with 87 Sr/ 86 Sr data. It is possible that atmospheric transport modeling could be an independent test of dust production from various sources.
To show how modeling and isotopic data could complement one another, we provide an example of applying 87 Sr/ 86 Sr ratios as a check on modeling studies. A modeling study for a dust storm on 13-14 April 2017 predicted that the dust deposited to snowpack near Alta, Utah, contained a mixture of 21% SDL dust, 7% GSL dust, and 72% dust from other playas (Skiles et al 2018). For this dust event, we measured an 87 Sr/ 86 Sr ratio of 0.71078 in dust from Alta snowpack (supplementary material, table S1, sample 13 754). Our two-endmember mixing calculations indicate that this dust layer contained 15% GSL dust, higher than the 7% contribution predicted by the modeling study. A three-endmember mixing model, using dust contributions from the modeling study (21% SDL dust, 7% GSL dust, and 72% dust from other playas) and average 87 Sr/ 86 Sr ratios values from SDL (0.71008), GSL (0.71476), and other playas (0.71178), results in a 87 Sr/ 86 Sr ratio of 0.71163. This value of 0.71163 calculated using dust proportions from the model is higher than the measured value of 0.71078 in the dust layer. We can more closely match the model results by either (1) decreasing the amount of GSL dust with a corresponding increase in SDL dust or (2) increasing the amount of SDL dust and decreasing the amount of dust from other playas. Since GSL dust likely does affect local snowpack to some extent, we assume that option 2 is more reasonable and use a nominal value of 7% GSL dust as predicted by the model. With option 2, we can match the observed 87 Sr/ 86 Sr ratio of the dust layer with a combination of 73% SDL dust, 7% GSL dust, and 20% dust from other playas. Thus, the model likely underpredicted the amount of SDL dust and overpredicted the amount of dust from other playa sources. This may be because the dust transport model was unable to account for playas that were covered by temporary standing water, resulting in predicted emissions from areas where dust production was unlikely, as noted in Skiles et al (2018).
This example of comparing measured 87 Sr/ 86 Sr ratios to results from modeling studies, using an iterative process, shows that this may be a powerful tool for dust apportionment in northern Utah. More examples are needed to verify that this method could be used for different dust storms. By coupling 87 Sr/ 86 Sr data with modeling studies, we could better quantify GSL dust using an iterative approach. The isotopic data could also be used to validate and refine dust transport models. The feedback between geochemical observations and dust transport models would greatly improve dust apportionment studies and source tracking in northern Utah and other areas affected by regional playa dust sources.

Conclusion
Tracking dust from playas to urban areas and mountain snowpack is increasingly important with the desiccation of lakes worldwide. In our study, we show how the 87 Sr/ 86 Sr ratio in the carbonate mineral fraction of playa dust can be used to quantify dust contributions from playas to downwind areas. Unique 87 Sr/ 86 Sr ratios of western Utah playas, ranging from~0.710 at SDL to~0.715 at GSL, explained seasonal variability in 87 Sr/ 86 Sr ratios in the Wasatch Front urban area and snowpack of the Wasatch and Uinta Mountains. Our mixing model indicates that the dry lakebed of GSL contributed up to 34% of the dust flux to the northern Wasatch Front 22% of the dust flux to Wasatch Mountain snowpack during the study period. With the ongoing desiccation of GSL, these observations could have major impacts on understanding future dust emissions from the dry lakebed and impacts on downwind areas. The 87 Sr/ 86 Sr fingerprint of playa dust sources can be used to refine dust transport models to better quantify the amount of dust from GSL and other playas. To our knowledge, this is the first study to use 87 Sr/ 86 Sr ratios to trace dust from specific playas to downwind areas of deposition. The combination of 87 Sr/ 86 Sr fingerprints in carbonate minerals from playa dust and dust transport modeling may be the state-ofthe-art for dust source apportionment in northern Utah and other areas impacted by regional playa dust sources.