Atmospheric Environment 193 (2018) 251–261

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Atmospheric Environment

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Aeolian dust chemistry and bacterial communities in snow are unique to airshed locations across northern , USA T

∗ D.B. Dastrupa, G.T. Carlinga, , S.A. Collinsb, S.T. Nelsona, D.P. Fernandezc, D.G. Tingeya, M. Hahnenbergerd, Z.T. Aanderudb a Geological Sciences, Brigham Young University, Provo, UT, USA b Plant and Wildlife Sciences, Brigham Young University, Provo, UT, USA c Geology and Geophysics, University of Utah, Salt Lake City, UT, USA d Geosciences, Salt Lake Community College, Salt Lake City, UT, USA

ARTICLE INFO ABSTRACT

Keywords: Wind-blown dust is an important source of trace metals, nutrients, and biological material to montane ecosys- Snow tems. Mountain ranges in northern Utah are located downwind of multiple dust sources including the Great Aeolian dust Basin and the Wasatch Front urban area, providing an opportunity to investigate regional-scale differ- Dust geochemistry ences in dust deposition chemistry and bacterial composition. We sampled discrete dust layers from snowpack Strontium isotopes across multiple locations in the Wasatch and Uinta Mountains (Utah) and the Snake Range (Nevada) during Bacteria spring 2014 and 2015. Dust chemistry was unique in each airshed, suggesting that spatial variability and local Mineralogy sources were more important than temporal variability for the sampling period. The central Wasatch dust contained the highest concentrations of playa-associated elements (U, Mg, Li, Ca, Sr, As) and anthropogenic elements (Sb, Cu, Pb, Se) compared with lowest concentrations of these elements in the northern Wasatch, which is further from playa and anthropogenic sources. Sequential extractions indicate that the majority of Ca, Sr, and Cd is potentially available for transport during snowmelt while other elements are relatively immobile. Central Wasatch dust was more reactive to acetic acid than northern Wasatch dust for most elements, including REE + Y. Sr isotopes (87Sr/86Sr ratios) were also unique to each sampling area, with the most radiogenic values in the central Wasatch. Similar to dust chemistry, bacterial communities in dusty snow reflected geographically localized dust events. In the central Wasatch, 69% of bacterial species were unique, suggesting that the airshed received the most diverse dust inputs from a combination of playa and anthropogenic sources. Gram-positive Actinobacteria and Firmicutes were common in snow but specific bacterial families distinguished airsheds (e.g., Bacillaceae, Geodermatophilaceae, Nakamurellaceae). Our results demonstrate that evaluating dust chemistry and bacteria in snow on a regional scale may more clearly link dust sources to the entrainment of pollutants and seeding of bacteria species to montane systems.

1. Introduction and biological material and causes earlier snowmelt by decreasing snow albedo (Aarons et al., 2017; Reynolds et al., 2014). Aeolian (wind-blown) dust is an important physical and biogeo- Dust deposition in the western US has increased 500% over the past chemical flux to mountain environments (Lawrence and Neff, 2009). century, resulting in increased deposition of nutrients K, Mg, Ca, N, and Dust contributes substantial loading of soluble salts, metals, and me- P to the Rocky Mountains (Neff et al., 2008). The increased dust flux is talloids to mountain snowpack (Carling et al., 2012; Clow et al., 2002; driven by human-caused disturbance of desert soils, including the ex- Ingersoll et al., 2008; Lawrence et al., 2010; Rhoades et al., 2010; Turk pansion of agriculture, livestock grazing, mining operations, and post- et al., 2001). Trace metal concentrations in dust (e.g., As, Cd, Cu, Mo, fire treatments (Belnap and Gillette, 1998; Hahnenberger and Nicoll, Pb, and Zn) are typically enriched relative to average upper continental 2014; Mahowald et al., 2010; Miller et al., 2012; Moulin and Chiapello, crust, and dust-derived trace metals are more available and mobile 2006; Neff et al., 2005; Reynolds et al., 2010). Water diversions and relative to other sources (Hahnenberger and Perry, 2015; Lawrence and groundwater withdrawal in desert areas can create dust bowls like Neff, 2009; Lawrence et al., 2010, 2013). Dust also contains nutrients Owens Dry Lake, Lake Urmia, Great Salt Lake, and other anthropogenic-

∗ Corresponding author.S389 ESC, Provo, UT, 84602, USA. E-mail address: [email protected] (G.T. Carling). https://doi.org/10.1016/j.atmosenv.2018.09.016 Received 31 January 2018; Received in revised form 27 June 2018; Accepted 11 September 2018 Available online 13 September 2018 1352-2310/ © 2018 Elsevier Ltd. All rights reserved. D.B. Dastrup et al. Atmospheric Environment 193 (2018) 251–261 disturbed playas (Elmore et al., 2008; Gill, 1996; Gill et al., 2002; water supplies across the western US. A greater understanding of dust Reheis et al., 2002, 2009; Stone, 2015; Wurtsbaugh et al., 2017). Re- sources and the impacts on biogeochemical cycling in mountain eco- gardless of direct human impacts, dust emissions in the southwest US systems may motivate better land management practices for reducing are expected to continue to increase due to climate change-driven in- dust emissions from source areas. crease in aridity and decrease in perennial plant cover (Field et al., 2009; Munson et al., 2011; Woodward et al., 2005). 2. Materials and methods Dust composition is typically characterized using isotopes, miner- alogy, and geochemistry, which together provide information on dust 2.1. Study area description sources, anthropogenic inputs, and the fate and transport of major and trace elements to the environment. The 87Sr/86Sr isotope ratio is often Dust samples were collected from snowpack in the western Uinta used for source tracking of dust because it undergoes minimal fractio- Mountains and Wasatch Mountains in Utah and the Snake Range at nation during transport (Capo et al., 1998; Miller et al., 2014) and National Park (GBNP) in Nevada (Fig. 1). The Uintas are serves as a tracer of the fate of dust-derived Sr in mountain watersheds located in northeastern Utah and run parallel to the Utah-Wyoming (Clow et al., 1997). Dust mineralogy can be used to identify spatial and border and are the most distal from desert dust sources of all sampling temporal differences between samples and possible source areas locations. The Wasatch are located in northern Utah and are oriented in (Munroe, 2014; Shao et al., 2008). Geochemical analysis through se- a north-south direction from the Utah-Idaho border to central Utah on quential leaching provides an estimate of the partitioning of elements the eastern edge of the Great Basin region. Samples were collected from among a variety of geochemical and mineral phases (Carling et al., the northern, central, and southern Wasatch (Fig. 1). The Wasatch Front 2012; Lawrence et al., 2010), which mimics the availability of major urban area, with a population of > 2 million people, is located directly and trace elements to the environment. west of the central and southern Wasatch sites. GBNP is located on the Bacteria transported on dust and deposited in snowfall may provide Utah-Nevada border in the central part of the Great Basin (Fig. 1). insights into the geographic source of the bioaerosol. Coinciding with The geologic setting in the Great Basin region combined with dust entrainment is an immense diversity of bacteria (Carey et al., complex meteorology produces episodic dust storms in Utah and 2016) with the potential to act as biological ice nucleators and enhance Nevada. Dust sources include lake-bed sediments and salt pans or snowfall (Christner et al., 2008). Soils harbor thousands of bacteria playas that are remnants of Pleistocene Lake Bonneville (Currey, 1990). species in unique combinations reflecting the biotic and abiotic factors Some of the major dust emitting playas are located in the Sevier Desert controlling bacterial community assembly. Dust originating from soil (including Sevier Dry Lake) and within the Lake surfaces may retain much of the community structure (Weil et al., Bonneville Basin (Hahnenberger and Nicoll, 2012, 2014)(Fig. 1). Ad- 2017). For example, dusty snow on Mont Blanc resembled soil-asso- ditional regional dust sources may include the ciated bacteria from four Saharan dust storms over three years (Lawrence et al., 2010) and the Snake River Plain (Spaulding et al., (Chuvochina et al., 2011) and dust collected in Israel exhibited unique 2015)(Fig. 1). The Milford Flat burn area in central Utah was a major bacterial communities from three distinct origins, North Africa, Syria, dust source after the 2007 fire, but dust emissions decreased 73.6% by and Saudi Arabia (Gat et al., 2017). Further, bacteria attached to dust 2009 with reestablished vegetation (Miller et al., 2012) and have likely particles may influence seasonal variation within the residential soil continued to decline in recent years. An analysis of dust storm events in community (Stres et al., 2013) and provide C and N resources to nu- Utah over an 80-year period (1930–2010) showed a bimodal annual trient impoverished soils (Rime et al., 2016). Desert dust, in particular, distribution with a primary peak in April, coinciding with maximum is one of the most abundant ice nucleating particles in the atmosphere snowpack accumulation in the mountains, and a secondary peak in (Boose et al., 2016) and wet deposition in the form of snowfall is an September (Steenburgh et al., 2012). Dust storms are most common in important mechanism returning dust to soil surfaces. Bacteria in fine- the late afternoon and evening hours with the greatest dust fluxes grained soil are linked to continental patterns of dust entrainment and driven by strong southerly winds and to a lesser extent, winds from the it is possible that microorganism communities can be used to trace dust northwest (Hahnenberger and Nicoll, 2012; Steenburgh et al., 2012). sources on a regional scale. While in the snowpack, specific bacteria may break dormancy and become active, encouraging the growth of 2.2. Dust sample collection cold-adapted species (Carey et al., 2016). However, if dust events are intensive enough, the bacteria deposited in snow may resemble the Dust samples (n = 14) were collected from spring snowpack in source soils and be used as a tracer of dust provenance. Taken together, Nevada and northern Utah to analyze geochemical composition. We isotopic, geochemical and biological methods may provide a synoptic sampled five distinct dust event layers, some at multiple locations, from approach to better understand potential dust source variability, an- snowpack prior to the onset of snowmelt during spring 2014 and spring thropogenic inputs, and the fate of dust after deposition to mountain 2015 (Table 1). The dust events occurred on: 1) 6 February 2014, 2) 17 environments. March 2014, 3) 22 April 2014, 4) 5 April 2015 and 5) 14 April 2015. Dust deposition is often evaluated at a single site over time, yet Dust samples were collected in acid-washed 2.5L FLPE bottles by regional-scale differences may be important for evaluating the en- scraping the open bottle across the exposed dust layer in a snow pit. The trainment of pollutants and seeding of bacteria species to montane samples were stored frozen until they were processed by melting, systems. Mountain ranges in northern Utah are located downwind of pouring off meltwater, and drying in a laminar flow hood. Dust layers multiple dust sources including playas were sampled opportunistically from snowpack because snow cover (Hahnenberger and Nicoll, 2014) and the Wasatch Front urban area, limits entrainment of local dust and provides a clean surface for dust providing an opportunity to investigate regional-scale differences in deposition. Each sample represents a single dust event layer that can be dust chemistry and bacterial composition. To investigate the spatial correlated with specific regional wind events. Not all dust events were variability in dust composition, with implications for identifying dust detectable at each sampling area and thus only discrete locations were sources, we collected dust from five individual dust events deposited sampled following a dust event. Dust event 2 (17 March 2014) was an onto spring snowpack across Nevada and northern Utah during 2014 exceptional storm that affected the entire region and was sampled at all and 2015. We analyzed mineralogy and performed a series of sequential sites, thereby providing an opportunity to compare the composition of extractions on each dust sample to measure major/trace element con- dust from a single event across a large area. Dust events 1–5 were centrations and 87Sr/86Sr ratios. Additionally, we characterized the sampled at the central Wasatch site allowing for a comparison of tem- bacterial communities present in the snowpack. Mountain snowmelt is poral variability in dust composition at a single sample location. Dust a critical resource for sustaining ecosystems and providing regional events 2 (17 March 2014), 3 (22 April 2014) and 5 (14 April 2015) were

252 D.B. Dastrup et al. Atmospheric Environment 193 (2018) 251–261

Fig. 1. Location map showing sampling locations (red dots) in Nevada and Utah, USA. Regional dust sources are labeled in italics. Dust and snow samples were collected across northern Utah and Nevada during spring 2014 and spring 2015. See Tables 1 and 2 for sampling details. observed and sampled at the western Uintas site. provided in Table 2. For bacteria in snow, we sampled the entire snowpack during spring 2014 (northern Wasatch and western Uintas) and spring 2015 (central 2.3. Dust sequential leaching and geochemical analysis Wasatch). Bacteria samples were a composite of three snow cores col- lected with a 5 cm diameter acrylic tube through the entire snow pro- To assess the distribution of elements among unique chemical file, excluding the bottom ∼20 cm near the soil. Bacteria samples were fractions, dust samples were subjected to a two-step sequential leaching not collected from GBNP, limiting the spatial coverage of the dataset, procedure of 1 M acetic acid and 0.8 M nitric acid prior to geochemical because it was not feasible to transport the necessary amount of snow analyses. For samples with sufficient mass (n = 8), a separate sub- from the remote sampling site. Details on bacteria snow samples are sample was leached with aqua regia for total element concentrations.

253 D.B. Dastrup et al. Atmospheric Environment 193 (2018) 251–261

Table 1 Dust sample information.

Sample ID Location UTMZone Easting (m) Northing (m) Dust event Sample date Leach step 1-1 M Leach step 2–0.8 M Leach step 3- acetic acid nitric acid aqua regia

1-CW central Wasatch 12 T 447790 4493939 2/6/2014 4/24/2014 X X 2-CW central Wasatch 12 T 447790 4493939 3/17/2014 4/24/2014 X X X 2-GBNP Great Basin N.P. 11 S 732327 4320706 3/17/2014 4/11/2014 X X X 2-NW-A northern Wasatch 12 T 452835 4637243 3/17/2014 3/24/2014 X X X 2-NW-B northern Wasatch 12 T 451729 4644345 3/17/2014 3/24/2014 X X X 2-NW-C northern Wasatch 12 T 457892 4634870 3/17/2014 3/24/2014 X X X 2-SW southern Wasatch 12 T 448786 4472578 3/17/2014 3/29/2014 X X X 2-WU western Uintas 12 T 504379 4503049 3/17/2014 3/25/2014 X X 3-CW central Wasatch 12 T 447790 4493939 4/22/2014 4/24/2014 X X 3-WU-A western Uintas 12 T 507089 4504010 4/22/2014 4/24/2014 X X X 3-WU-B western Uintas 12 T 502643 4503861 4/22/2014 4/24/2014 X X 4-CW central Wasatch 12 T 447790 4493939 4/5/2015 4/11/2015 X X 5-CW central Wasatch 12 T 504379 4503049 4/14/2015 4/16/2015 X X X 5-WU western Uintas 12 T 447790 4493939 4/14/2015 4/21/2015 X X X

Note: Datum is NAD83.

Table 2 Bacteria snow sample information.

Sample ID Location UTM zone Easting (m) Northing (m) Sample Date

NW-2014-A northern Wasatch 12 T 452835 4637243 3/24/2014 NW-2014-B northern Wasatch 12 T 451729 4644345 3/24/2014 NW-2014-C northern Wasatch 12 T 457892 4634870 3/24/2014 WU-2014-A western Uintas 12 T 504379 4503049 3/25/2014 WU-2014-B western Uintas 12 T 507089 4504010 3/25/2014 WU-2014-C western Uintas 12 T 502643 4503861 3/25/2014 CW-2015-A central Wasatch 12 T 447790 4493939 3/26/2015 CW-2015-A central Wasatch 12 T 447790 4493939 3/26/2015 CW-2015-A central Wasatch 12 T 447790 4493939 3/26/2015

Note: Datum is NAD83.

The goal of this extraction process was to isolate elements from the: 1) corrected for mass bias using an exponential law, normalizing to carbonate or extractable fractions (i.e., elements that are most likely 87Sr/86Sr = 0.1194 (Steiger and Jäger, 1977). Isobaric interferences on mobile during snowmelt and in slightly acidic conditions in the soil), 2) the 87Sr/86Sr ratios, such as from 87Rb and 86Kr, were corrected by si- organic matter, feldspar and clay fractions, and 3) residual element multaneous monitoring of 87Rb and 86Kr using the corresponding in- fractions, after subtracting concentrations from steps 1 and 2 (Carling variant ratios of 87Rb/86Rb = 0.385706 and 86Kr/83Kr = 1.502522 et al., 2012; Lawrence et al., 2010). (Steiger and Jäger, 1977). Major and trace element concentrations were measured on the Dust mineralogy was evaluated by x-ray diffraction (XRD). Samples acetic acid, nitric acid, and aqua regia leach fractions. Concentrations were prepared on zero background holders and analyzed using a Rigaku were measured for the following 41 elements: Ag, Al, As, B, Ba, Be, Ca, MiniFlex 600 XRD. XRD patterns were evaluated using Rietvelt PDXL2 Cd, Ce, Co, Cr, Cs, Cu, Dy, Eu, Fe, Gd, Ho, K, La, Li, Lu, Mg, Mn, Mo, Na, with 2-theta mineral intensity peaks obtained from the American Nd, Ni, Pb, Rb, Sb, Se, Sm, Sr, Tb, Ti, Tl, U, V, Y, and Zn. Samples were Mineralogist Crystal Structure Database. Qualitative mineral abun- analyzed using an Agilent 7500ce quadrupole inductively coupled mass dances and images were obtained by QEMSCAN on 9 of 14 samples. spectrometer (ICP-MS) with a collision cell, a double-pass spray QEMSCAN (Quantitative Evaluation of Minerals by SCANning electron chamber with perfluoroalkoxy (PFA) nebulizer (0.1 mL/min), a quartz microscope), FEI Company, uses a scanning electron microscope with torch, and platinum cones. The detection limit (DL) was determined as energy dispersive X-ray spectrometers to provide automated mineral three times the standard deviation of all blanks analyzed throughout analysis (Pirrie et al., 2009). A 5 μm resolution field scan was performed each run. A USGS standard reference sample (T-205) and NIST standard on dust samples that were mounted in 2 mm epoxy plugs and polished reference material (SRM 1643e) were analyzed multiple times in each optically flat. run together with the samples as a continuing calibration verification. Raw data including trace and major element concentrations, The long-term reproducibility for T-205 and SRM 1643e show that our 87Sr/86Sr ratios, and mineral abundances are provided in the results are accurate within 10% for most elements. Supplementary material (Table S1). Dust samples were analyzed for 87Sr/86Sr ratios on both the acetic acid and nitric acid leach fractions to develop isotopic fingerprints in 2.4. Statistical analysis the carbonate and silicate mineral fractions, respectively, for further evaluating spatial variability in dust composition. The samples were We used nonmetric multidimensional scaling (NMDS) to visualize purified inline using a Sr-FAST ion chromatographic column packed and explore trace and major element chemistry in dust samples and with a crown ether resin (Mackey and Fernandez, 2011). During the across airsheds. We performed a NMDS ordination based on a Bray- analyses reported herein using a ThermoScientific Neptune multi- Curtis distance matrix of the 37 measured elements (Al, As, B, Ba, Be, collector ICP-MS, we determined the 87Sr/86Sr ratio of NIST SRM-987 Ca, Cd, Ce, Co, Cr, Cu, Dy, Eu, Fe, Gd, Ho, K, La, Li, Lu, Mg, Mn, Na, Nd, (certified value of 0.71034 ± 0.00026) to be 0.71030 ± 0.000010 Ni, Pb, Rb, Sb, Sm, Sr, Tb, Ti, Tl, U, V, Y, and Zn) from the acetic acid (n = 20; 2σ standard error (SE)). Analytical precision (2σ SE) of all leach fraction of dust samples. The data were log generalized using the 87 86 samples ranged from ± 0.000010–0.000070. The Sr/ Sr ratios were equation b = log(x + xmin)-log(xmin), where xmin is the minimum value

254 D.B. Dastrup et al. Atmospheric Environment 193 (2018) 251–261 for each element. Differences in dust chemistry were evaluated with 3. Results and discussion PERMANOVA in R. Silver, Mo, and Se were not used in the ordination because a majority of values were < DL in the acetic acid leach frac- 3.1. Backward trajectories consistent with Great Basin dust sources tion. For other elements, values at or below DL were set to ½ DL for NMS analysis. Cesium was removed from NMDS analysis because there HYSPLIT backward trajectories for dust event 2 (17 March 2014) were outliers in the data (samples with concentrations > 3 standard show that dust sources were likely located across western Utah, a deviations from the mean) indicating an unquantifiable extraneous Cs known source of regional dust transport, particularly from playa source. Details defining labels and raw data associated with each sources (Hahnenberger and Nicoll, 2014) (Supplementary material, Fig. sample shown in the NMDS plot are provided in the Supplementary S1). Winds were primarily from the southwest for the 24 h period material (Table S2). preceding dust deposition to the northern Utah mountains. Springtime dust events commonly occur when frontal passages move across the Great Basin region and are often associated with colder temperatures 2.5. Bacteria in dusty snow and precipitation (Hahnenberger and Nicoll, 2012). The same me- chanism was responsible for each of the five dust events that were To investigate the potential for using bacterial community compo- observed during the study. sition to identify dust sources, bacteria from snow and dust were ge- netically sequenced, classified, and analyzed for site relationships using 3.2. Similar sample mineralogy suggests uniform types of dust sources multivariate statistics, alpha diversity, and richness metrics. Briefly, 1 kg of dusty snow was melted at 5 °C and filtered through 0.2 μm filters Dust mineralogy was dominated by quartz, K-feldspar, plagioclase, ® (Supor PES membrane) and the resulting genomic DNA on the filter illite, calcite, and dolomite (Supplementary material, Table S1). This was extracted using a PowerSoil DNA Isolation Kit (MoBio suite of minerals is generally consistent with mineralogy of Uinta Corporation). We amplified the V4 region of the16S rRNA gene with Mountain dust described by Munroe et al. (2015). Samples were PCR using bacterial -specific primer sets 515F and 806R with unique dominated either by carbonate minerals (calcite and dolomite) or sili- 12-nt error correcting Golay barcodes (Aanderud et al., 2016). The cate minerals (quartz, K-feldspar, plagioclase, and illite). Silicate mi- thermal cycle conditions were: denaturation step at 94 °C for 3 min neral abundance ranged from 32.1% to 98.7%, whereas carbonate followed by 35 cycles of denaturation at 94 °C for 45 s, annealing at mineral abundance ranged from 1.3% to 67.9%. There is no apparent 50 °C for 30 s, and extension at 72 °C for 90 s. After purifying (Agen- spatial or temporal (i.e., dust event specific) trend in silicate versus court AMPure XP PCR Purification Beckman Coulter Inc.) and pooling carbonate mineral abundance. PCR amplicons at approximately equimolar concentrations, samples The QEMSCAN images showed similar mineralogy as the XRD re- were sequenced at the Brigham Young University DNA Sequencing sults, with dominant mineral phases including feldspar (un- Center (http://dnac.byu.edu/) using an Illumina Hi-Seq 2500. We differentiated), quartz, clays, with variable amounts of calcite and analyzed all sequences and performed multivariate statistics using amphibole (Supplementary material, Fig. S2). Grain sizes for dust mothur (v. 1.39.0), an open-source, expandable software pipeline for samples were typically on the order of 50–100 μm in diameter or microbial community analysis following a similar procedure as outlined smaller, with primarily subangular grain shapes. The presence of rela- in Kozich et al. (2013). Operational taxonomic units (OTUs) were based tively large grains in the majority of samples suggests dominant con- on uncorrected pairwise distances at 97% sequence similarity, and tributions from regional dust sources (Lawrence et al., 2010). The ob- determined the phylogenetic identity of OTUs with the SILVA database. servation of large particles transported from to mountain Similar to identifying differences in dust chemistry among samples, snowpack is surprising, with some of the particles in the size range of bacteria communities in dust were visualized using NMDS based on a fine sand, but not unprecedented. A previous study of Wasatch dust on Bray-Curtis distance matrix, and site differences were tested using snow found similarly large grain sizes, with median particle sizes ran- PERMANOVA with the ‘vegan’ package of R. Also, differences among ging from 11.4 μm to 19.6 μm and particles as large as 100 μm in all communities were examined by comparing the alpha diversity of samples (Reynolds et al., 2014). Dust in San Juan Mountain snowpack communities as the inverse Simpson index (Haegeman et al., 2013) and was dominated by particles ranging in size from clays to fine sand, with richness after rarefaction by a common sequence number (20,000) particles as large as 250 μm(Lawrence et al., 2010). using one-way ANOVA with a Tukey's HSD test. Last, phylogenetic trends of twenty-six dominant bacterial families (mean re- 3.3. Dust chemistry unique to airshed location covery ≥ 0.05% in any airshed) from 7 phyla were shown in a heat map, a two-dimensional visual summary of the data represented in NMDS results show that dust from each airshed had a unique color, with hierarchal clustering using the heatmap function in the chemistry regardless of when the sample was collected (Fig. 2). The ‘gplot’ package in R (Oksanen et al., 2013). NMDS results distinguished dust samples by location in ordination space with a final stress of 0.02, and the PERMANOVA results sup- ported the ordination demonstrating a compositional difference among 2.6. Backward trajectories dust in airsheds (PERMANOVA, airsheds, F = 14.0, R2 = 0.82, P < 0.001, df = 4). In all cases, samples grouped by site rather than To identify possible dust sources using meteorological data, the the timing of the dust event, suggesting that spatial variability of dust National Oceanic and Atmospheric Administration (NOAA) HYSPLIT deposition chemistry was more important than temporal variability model was used to calculate 24 h backward trajectories (Draxler and (PERMANOVA, time, F = 4.06, R2 = 0.06, P = 0.03, df = 1). Samples Hess, 1997). HYSPLIT was run using NARR 32 km model meteor- from the central Wasatch and northern Wasatch plotted on opposite ological data using the READY (Real-time Environmental Applications ends of axis 1, representing end-of-spectrum chemistries among the and Display sYstem) provided by the NOAA Air Resources Laboratory sample set. The central Wasatch samples are defined by relatively (ARL) (NOAA, 2011). Hourly backward trajectories were run from a higher concentrations of As, B, Ca, Cu, Li, Mg, Na, Pb, Sb, Sr, and U, point located near Salt Lake City (40.7593 N, −111.8975 W) at a height whereas the northern Wasatch samples contain the lowest concentra- of 500 m above ground level (AGL) for the time period 0000 to 1800 tions of these elements, with intermediate concentrations in the UTC on 17 March 2014. This time corresponds to the period of south- southern Wasatch, western Uintas, and GBNP samples. Variability in erly and southwesterly pre-frontal winds that produced the observed Ca, Sr, and Tl concentrations explained differences along axis 2. dust event on 17 March 2014 (dust event 2). The elements found in higher concentrations in the central Wasatch

255 D.B. Dastrup et al. Atmospheric Environment 193 (2018) 251–261

Fig. 2. NMDS ordination results for all dust samples using concentrations from the 1 M acetic acid leach step. The model has a final stress of 0.02, R2 = 0.82. PERMANOVA analysis suggests that dust chemistry is controlled by airshed location (df = 4, F = 14.0, P < 0.001). Sample labels include dust event, location, and a letter if more than one sample was collected from a site for the same dust event (for example, 2-NW-A was dust event 2 collected in the northern Wasatch on the same day as sample 2-NW-B and 2-NW-C). Raw data used in the ordination are provided in the Supplementary data (Table S2).

samples relative to the other samples can be split into two groups: Dust samples from the western Uintas and central Wasatch main- playa-associated elements (As, B, Ca, Li, Mg, Na, Sr, and U) and an- tained unique geochemical signatures over time (Fig. 2). The central thropogenic metals (Cu, Pb, and Sb). Dust emissions from dry lakebeds, Wasatch samples plotted in similar NMDS space, unique from the other or playas, contain elevated concentrations of soluble salts including Na samples, for all five dust events (1-CW through 5-CW). Likewise, the and Ca (Abuduwaili et al., 2008; Hahnenberger and Perry, 2015). western Uintas samples plotted in similar NMDS space for three dust Elements such as Ca, Mg, Na, and Sr are associated with evaporite events (1-WU, 3-WU, and 5-WU). Variability in geochemistry across the minerals (halite, gypsum, calcite, and dolomite) common in Great Basin sample locations suggests that dust from different sources impacted playas (Reheis et al., 2002). Likewise, As, B, and U are found at high each area and that the particular dust sources were persistent concentrations in playa environments (Blank et al., 1999; Gill et al., throughout spring 2014 and 2015. Spatial variability arising from 2002; Noble et al., 2011). Arsenic is also sourced from anthropogenic proximity to local sources was more important than temporal varia- activities, as are Cu, Pb, and Sb (Reheis et al., 2002; Reynolds et al., bility for dust samples, indicating that similar dust sources were acti- 2010). Modern dust is highly enriched in As, Cu, Pb, and Sb relative to vated during each storm but that the dust sources varied along the Av soil horizons due to anthropogenic enrichment (Reheis et al., 2009). transect from the southern Wasatch to the northern Wasatch. Addi- Anthropogenic metals in Wasatch dust are typically associated with tional sampling is needed to determine if temporal variability is sig- organic matter from urban and industrial processes, probably including nificant over multiple years when different dust sources could be acti- mining and smelting (Reynolds et al., 2014). Notably, the northern vated due to persistent drought conditions, land disturbance, or unique Wasatch is located furthest from playa sources and urban areas and had storm conditions that would transport dust along different trajectories. the lowest concentrations of playa and anthropogenic elements. Thus, For example, the lakebed of Great Salt Lake is potentially an important the central Wasatch receives more dust from playa and anthropogenic dust source when lake levels are low but likely does not produce dust sources relative to the northern Wasatch due to the proximity of the when lake levels are high or when the lakebed is wet during springtime central Wasatch to the Great Basin playa dust sources and the Wasatch (when our samples were collected). Front urban area.

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Fig. 3. 87Sr/86Sr isotope ratios for snow dust from all sampled dust layers for the 1 M acetic acid fraction versus 0.8 M nitric acid fraction. Dashed lined is a 1:1 line for 87Sr/86Sr measurements.

3.4. 87Sr/86Sr ratios indicate unique dust sources affect each area Wasatch samples had the greatest difference between the 87Sr/86Sr ratios of the acetic and nitric leach fractions (0.00101 ± 0.00001, Dust samples showed a range in 87Sr/86Sr ratios from 0.7101 to n = 3) relative to samples from the other sites (0.00053 ± 0.00046, 0.7124 in the acetic acid leach fraction and from 0.7090 to 0.7115 in n = 11), reflecting potential differences in mineralogy or anthropogenic the nitric acid leach fraction (Fig. 3). The northern Wasatch samples inputs. It is possible that the water-soluble fraction of dust (i.e., salts) had the lowest 87Sr/86Sr ratios (0.7090–0.7107) and the central Wa- has a different 87Sr/86Sr ratio but this fraction was unmeasured since satch samples had the highest 87Sr/86Sr ratios (0.7105–0.7124), with meltwater was poured from dusty snow samples. intermediate values found at the other sites. The range in values sug- Samples from dust events 1–5 collected at the central Wasatch site gests that unique dust sources affected each airshed. 87Sr/86Sr ratios showed temporal variability in 87Sr/86Sr ratios throughout the course of from the northern Wasatch samples more closely resemble isotope ra- the study (Fig. 3). Samples from dust events 1, 2 and 5 were more tios in basalts from the Snake River Plain in Idaho (0.7060–0.7070) radiogenic (∼0.7122 and ∼0.7114 in the acetic acid and nitric acid (White et al., 1998), and may represent a mixture of dust from the fractions, respectively) relative to samples from dust events 3 and 4 Snake River Plain and Great Basin playas. Samples from the other sites (∼0.7108 and 0.7105). These differences suggest that separate dust are similar to playa sediments from the Sevier Desert (0.7103–0.7121) sources were mobilized for dust events 1, 2, and 5 than dust events 3 (Miller et al., 2014) and the Lake Bonneville Basin (Hart et al., 2004). and 4. However, given that the chemistry of these dust events was si- 87Sr/86Sr ratios in lacustrine sediments from Lake Bonneville ranged milar it is not clear why the Sr isotopes show such differences. from 0.71049 to 0.71278 depending on lake level, and Great Salt Lake carbonates have a ratio of 07.1469 (Hart et al., 2004). We are currently 3.5. Sequential leach fractions show differences in the form and availability investigating the use of unique 87Sr/86Sr ratios in carbonate minerals of specific elements from playas for source apportionment. The preliminary results show promise for differentiating dust from the various western Utah playas Partitioning of elements among the sequential leaching fractions (including Sevier Dry Lake and Great Salt Lake) and will be presented in varied widely for specific trace and major elements, with variability a future paper. among dust samples (Fig. 4). For example, a majority of Ca, Sr, and Cd Considering the samples collected at all sites for dust event 2 on 17 but almost none of the Rb, Ag, Ti, and Fe was leached with the 1 M March 2014, the northern Wasatch samples had the lowest 87Sr/86Sr acetic acid fraction. The northern Wasatch and central Wasatch samples values (ranging from 0.7090 to 0.7097 in the nitric acid leach fraction showed the largest differences in elemental distribution among the and 0.7101 to 0.7106 in the acetic acid leach fraction) and central leach fractions, with representative samples 2-NW-B and 2-CW shown Wasatch sample had the highest 87Sr/86Sr values (0.7114 in the nitric in Fig. 4. Both samples were collected from the same dust event layer acid leach fraction and 0.7122 in the acetic acid leach fraction) (Fig. 3). (17 March 2014) but responded differently to the leach steps. The Intermediate values were found in samples from the southern Wasatch, central Wasatch sample was more reactive to the 1 M acetic acid and western Uintas, and GBNP with 87Sr/86Sr values in both leach fractions 0.8 M nitric acid leach fractions, with a smaller fraction removed by ranging from 0.7103 to 0.7114. aqua regia, relative to the northern Wasatch sample. In the central Overall, 87Sr/86Sr ratios were more radiogenic in the acetic leach Wasatch sample, over 90% of the Ca, Sr, and Cd was removed with the fraction relative to the nitric leach fraction, indicating different isotope 1 M acetic acid leach fraction compared with only 50–70% in the ratios in the carbonate and silicate minerals, respectively. The northern northern Wasatch sample. Likewise, over 50% of the Mg, Na, and U was

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Fig. 4. Relative fractions of selected trace and major elements in sequential extrac- tions using 1 M acetic acid, 0.8 M nitric acid, and aqua regia for representative samples from the northern Wasatch (2-NW- B; top) and central Wasatch (2-CW; bottom). Both samples are from the 17 March 2014 dust event and represent end members for the range of values observed in this study.

removed with the 1 M acetic acid leach fraction in the central Wasatch mobility of REE + Y elements in dust given their widespread use as sample as compared with less than 30% in the northern Wasatch tracers of dust in ice cores (Kreutz and Sholkovitz, 2000; Svensson sample. These results suggest that the central Wasatch samples contain et al., 2000) and hydrologic weathering studies (Tepe and Bau, 2015; a higher percentage of carbonate and other readily extractable minerals Vázquez-Ortega et al., 2015). For example, REE + Y is more likely to derived from playa sources relative to the northern Wasatch samples. enter the hydrologic system in the central Wasatch than the northern The difference between samples may be related to distance from playa Wasatch, with implications for water quality and weathering processes. sources, such that the extractable minerals are preferentially removed or are diluted by silicate minerals during transport over the relatively 3.6. Bacteria in dust unique to airshed location greater distances to the northern Wasatch sites. Regardless of the rea- sons for these differences, the central Wasatch dust is likely more sus- Our results suggest that bacteria in dusty snow may reflect geo- ceptible to chemical weathering and could cause greater impacts to graphically localized dust events. Communities from the three airsheds water quality in local watersheds and release more bio-limiting nu- were distinct from each other (NMDS, stress value < 0.001, R2 = 0.46, trients such as Ca, Mg, and K to the aquatic ecosystem. Fig. 5) mirroring similar geographical distinctions based on dust The acetic acid leach fraction, representing the fraction of dust that chemistry (Fig. 2). The PERMANOVA supported these results with would be readily available under slightly acidic conditions in snowmelt airshed location dramatically altering community composition (df =2, and soil, contained the majority of mass for specific elements. In all F = 2.6, P = 0.006). Although snow may vary regionally year from samples Ca and Sr were leached preferentially from the acetic acid year, the region defining airsheds seems paramount since the northern leach fraction due to the dissolution of carbonate minerals. Cd was also Wasatch and western Uintas were sampled in the same year but pos- abundant in the acetic acid leach fraction, although it was poorly cor- sessed distinct bacterial communities. Bacterial community data was related with Ca and Sr concentrations, suggesting that it is associated based on the recovery of 479,216 quality sequences and 7322 unique with other readily extractable minerals besides carbonates. Similar OTUs with samples possessing an average sequencing coverage of trends in Cd availability were demonstrated by Lawrence et al. (2010), 98% ± 0.006 (mean ± SEM). The dust and snow-borne communities where it was interpreted as being leached from organic matter in the in the western Uintas were the most variable potentially due to the dust dust because Cd concentrations correlated with macronutrients rather originating the furthest away and from the largest geographical area. than Ca. Airshed location did not affect richness (one-way ANOVA, df =2, Elements associated with the residual fraction (Al, Fe, K, Tl, B, Rb, F = 3.2, P = 0.11) or diversity (one-way ANOVA, df = 2, F = 1.8, V, Ni, As, Mo, Cs, Sb, Tl, Ag) represent the immobile fraction that aids P = 0.25), but only 12% (881 OTUs) of bacterial species were shared in soil formation. These elements accumulate in soils and are not likely between the three airsheds (Fig. 5). Many bacterial species were unique to dissolve in soil water or be transported to downstream ecosystems to a given airshed, especially in the dusty snow from the central Wa- (Lawrence et al., 2013; Munroe et al., 2015). satch where 69% of the community (3572 OTUs) were unique. The Rare earth elements (REE + Y) responded differently to sequential central Wasatch possessed approximately twice the number of species leaching in the northern Wasatch and central Wasatch samples as either of the two airsheds. Central Wasatch dust originates pre- (Supplementary material, Fig. S3). In the northern Wasatch, REE + Y dominantly from desert and salt playas and is influenced by anthro- were primarily associated with the nitric acid and aqua regia leach pogenic activity. Thus, similar to desert dust entrainment across con- steps, while in the central Wasatch the majority was removed with the tinents (Chuvochina et al., 2011; Gat et al., 2017), regional dust events acetic acid and nitric acid leach steps. It is worth some discussion of the resulting in the nucleation of precipitation in the form of snow, and

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Fig. 5. A) NMDS ordination results for bacterial communities in dusty snow col- lected at the central Wasatch (CW), northern Wasatch (NW), and western Uintas (WU). The model has a final stress of < 0.001, R2 = 0.46. PERMANOVA ana- lysis suggests airshed location dramatically alters community composition (df =2,F= 2.6, P = 0.006). B) Venn diagrams showing the distribution of unique bacterial species between the three airsheds. Recovery was based on OTUs from bacterial community libraries of the 16S rRNA gene (97% simi- larity cutoff). C) Heat map and dendrogram showing relationships between the abun- dance of major bacteria species and sam- ples.

falling or washing out in alpine areas may transport unique bacterial atmospheric conditions such as desiccation and low-temperature communities. Tracking the origin of dust using snow- and dust-borne conditions may help them remain viable during dust entrainment and bacteria may further be enhanced in more localized areas. Dust event snow deposition. For example, the first investigation of bacteria in characteristics, aeolian transport conditions, and bacterial loading from dust-laden snow by Lochhead (1938) found overwhelmingly spore- original dust sources often enhance bacterial variability in snow forming Bacillus species based on live plate counts. Alternatively, in (Chuvochina et al., 2011). Evaluating bacteria present in dust events on the central Wasatch, the abundance of Cytophagaceae (11% ± 0.71) snow on a regional scale may serve as an additional constraint for de- and Chitinophagaceae (0.88% ± 0.06) was almost double compared termining dust sources, as event peculiarities may be limited, aeolian to the other sites. The abundance of a different Actinobacterial order, transport conditions may be similar, and dust sources are constrained Nakamurellaceae (0.41% ± 0.07), and an unclassified Cyanobacteria by limiting the geographical area from where the dust was entrained. (9.7% ± 2.2) also differentiated central Wasatch dusty snow. The Specific bacterial families allowed the differentiation of dust de- unclassified Cyanobacteria potentially originated from Great Salt Lake positedonsnowintheairshedsstudiedhere.Forexample,there- or other playas. In a previous study of the bacteria communities in the covery or abundance of Geodermatophilaceae and Bacillaceae from north and south arms of Great Salt Lake (Aanderud et al., 2016), the gram-positive phyla Actinobacteria and Firmicutes were at least 2.4- dominant hypersaline-tolerant cyanobacteria species was in- times higher in snow and dust from northern Wasatch determinant and most likely is the same species as the one entrained in (Geodermatophilaceae = 5.1% ± 0.62, and Bacillaceae = 3.2% ± dust. We found no one order that was consistently abundant in all 1.6) than the other two airsheds. The bacterial species belonging to western Uintas dusty snow possibly due to the dust originating from the Firmicutes and Actinobacteria may vary, but gram-positive, en- further away and across a wider region. Two Alphaproteobacteria dospore-forming bacteria are consistently common in snow and dusty families, Acetobacteriaceae and Sphingomonadaceae, were abundant snow (Amato et al., 2007; Carey et al., 2016; Chuvochina et al., 2011). in all dusty snow with recoveries ranging from 13 to 17% and The ability of gram-positive bacteria to withstand adverse 6.4–9.2% respectively. During the winter and into spring some

259 D.B. Dastrup et al. Atmospheric Environment 193 (2018) 251–261 bacteria may be metabolically active potentially altering the relative could create unique hydrologic problems and changes to biogeochem- abundance of bacteria species regardless of dust inputs. The Acet- ical cycles in their respective watersheds. Identifying potential dust obacteraceae are often abundant in subalpine and alpine snow (Carey sources and availability of dust-derived major/trace elements and et al., 2016) and may become dominant as the taxa degrade sugars or bacteria may become increasingly more important as populations in- ethanol to produce acetic acid during fermentation. Additionally, the crease and land uses change across the western US. Understanding how Sphingomonadaceae are common in snow (Wunderlin et al., 2016) dust deposition may impact mountain ecosystems is crucial for moti- and have immense metabolic versatility utilizing organic substrates vating better land management practices. ranging from glucose to aromatic hydrocarbons deposited with snow (Alonso-Gutierrez et al., 2009; Regonne et al., 2013; Xie et al., 2011). Declarations of interest In the dusty snow, 92% of bacterial orders belonged to phyla known to be biological ice nucleators and dominate precipitated bacteria com- None. munities (Hiraoka et al., 2017). Taken together, two bacterial com- munities seem to reside in dusty snowpack: a common snow micro- Acknowledgments biome that may ubiquitously flourish under atmospheric entrainment, act as biological ice nucleators, and grow in snow during the winter; This work was supported by the US National Science Foundation and the bacterial community that resides within the dust and mirrors grants EAR-1521468 and OIA-1208732. Any opinions, findings, and theuniquesoilcommunitywhereitoriginatesfrom.Forbacteria conclusions or recommendations expressed are those of the authors and communities to serve as a tracer for dust the dusty portion of the do not necessarily reflect the views of the National Science Foundation. community needs to overshadow the common snow microbiome. We thank Wil Mace for assistance with QEMSCAN analyses. We also Thus, future research needs to identify the resilience of dusty com- thank two anonymous reviewers whose suggestions greatly improved munities within snow through the winter. The extent that dust com- the manuscript. munities retain their taxonomic signature will determine the effec- tiveness of using a bacterial classification system to determine dust Appendix A. Supplementary data provenance. Supplementary data to this article can be found online at https:// 4. Conclusions doi.org/10.1016/j.atmosenv.2018.09.016.

Aeolian dust deposition is important for biogeochemical inputs and References cycling in montane environments. To test regional variability in dust composition, we sampled dust from snowpack in Nevada (Snake Range Aanderud, Z.T., Vert, J.C., Lennon, J.T., Magnusson, T.W., Breakwell, D.P., Harker, A.R., at Great Basin National Park) and northern Utah (Wasatch and Uinta 2016. Bacterial dormancy is more prevalent in freshwater than hypersaline lakes. Front. Microbiol. 7, 853. Mountains) during spring 2014 and 2015. Our results show that dust Aarons, S.M., Blakowski, M.A., Aciego, S.M., Stevenson, E.I., Sims, K.W.W., Scott, S.R., trace element chemistry and bacterial communities are unique to air- Aarons, C., 2017. Geochemical characterization of critical dust source regions in the shed location, with differences arising from proximity to regional playa American West. Geochem. Cosmochim. Acta 215, 141–161. Abuduwaili, J., Gabchenko, M.V., Junrong, X., 2008. 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