A Retrospective of Global Dust Deposition Rates Calls for More Systematic and Comprehensive Data Collection

Lawrence and Neff (2009) compiled observational data on the deposition rates, chemical composition, mineral content, and particulate size distributions of wind-blown dust from fifty-two peer-reviewed, published articles throughout the world. They found that the particulate size distribution of wind-blown dust tends to negatively correlate with the distance traveled from the source; the farther the dust travels, the smaller the dominant particle size. Correspondingly, the mineral distribution also changes according to distance, and all dust tends to carry more trace elements such as rare earth metals than the average upper continental crustal rock (UCC), which gets used as a comparative proxy between standard soil composition and dust. While the results of the compiled data are entirely unsurprising, they do demonstrate some major quandaries with current methods of dust data collection, and highlight the inaccuracies of current global dust models, which overestimate global, and underestimate local and regional sources. .— Elise Wanger
Lawrence, C., Neff, J., 2009. The contemporary physical and chemical flux of aolian dust: A synthesis of direct measurements of dust deposition. Chemical Geology 267, 46–63.

Lawrence and Neff compartmentalized the data into three categories according to distance traveled: local (0–10 km), regional (10–1000 km), and global (>1000 km). The deposition rates decreased with distance in a predictably exponential progression. Local emissions had an average deposition rate of 200 g m–2yr–1, followed by a mere 20 and 0.4 g m–2yr–1 for average regional and global depositions, respectively. The local dusts contained more coarse silts and fine sands than the regional or global samples, such that 10–60% of total mass comprised of particles greater than 20 µm diameter, and an average of 30% of the particulate was sand. Regional dusts contained more fine silts and clay, comprising an average of 85% of the total mass, while global emissions contain only fine silt and clay in about a 70:30 ratio. Mineral content fits accordingly with particulate distribution, such that the sand-containing local dust contained more quartz, the regional dust contained equal concentrations of feldspar and phyllosilcate minerals, and the silt-dominant global dust contained the most phyllosilcates. Yet these arbitrary dust categories considerably overlap, making the distinction less decipherable from the data tables. Local dust still consists of 5–30% phyllosilcate and 10–30% feldspar minerals, and global dust still typically consists of 20% quartz and 20–30% feldspar. Likewise, silt-sized particles greater than 10 µm predominate in all dust samples, probably due to their ideal transport size: just enough surface area to get picked up by the wind, but still small enough to be energetically economical.

As crustal soil gets physically and chemically eroded into the loose, small-sized particulates that become wind-blown dust, the more mobile elements that can bond with into larger compound molecules and leach into lower soil layers decrease in concentration. Thus a common earth element like sodium (Na) averages only half the concentration in dust as in the UCC, while iron (Fe), calcium (Ca), phosphorus (P), titanium (Ti), nickel (Ni), copper (Cu) and lead (Pb) are an average 0.5–4.8 times higher in dust samples, in ascending order, than the UCC. Such elemental enrichment in dust may significantly contribute to biogeochemical cycling in ecosystems; for example, plants depend on trace levels of titanium and copper to continue growth, often making such elements limiting factors of productivity. The effects of the enriched Pb content—as well as zinc (Zn) and cadmium (Cd) (for which observational data were too sparse in the peer-reviewed literature to be quantitatively evaluated)—cannot be accounted for through means of natural geochemical weathering, and thus most likely derive from mixing with other emission sources such as industrial production, volcanic activity, and biomass burning. These factors may also increase the organic P content, since wind-blown dust often has a higher P concentration than could be explained by weathering processes or the parent soil.
Although still qualitatively valuable, many of the results Lawrence and Neff compiled lack reliability because of inconsistent data collection methods between studies. Lawrence and Neff only included passive sampling from direct observational research. Passive sampling typically consists of measuring the deposits that land on a non-reactive collection pan filled with glass marbles to provide ample surface area and cohesion. Deposits that land on snow, ice, or even soil and can still be distinguishably measured also count as passive sampling, analogous to the collection pan method, and can even reveal seasonal and annual variations through core extractions. However, Lawrence and Neff took core data solely from snow or ice, since sediment cores get more chemically and physically confounded from weathering. Active sampling—collecting particles with an air filter near the ground, usually some poly-fiber material—was entirely excluded because such methods don’t typically entrap wet deposition such as dust particulates in raindrops, and don’t account for the further fractionalization of particulates during the deposition process, when the dust combines and collides with the surface. Lastly, active sampling requires a modeling-derived conversion of atmospheric dust concentrations—which is what the filter traps—into dust deposition rates, which is how much dust actually lands on the ground and stays there in a given time span.
Lawrence and Neff used the compiled data from passive collections in the field to verify the accuracy of global dust models. Dust circulation and deposit models have highly sensitive input parameters calculated using an often inadequate amount of raw data. The limited data inputs are partially an attempt to simplify the model by focusing specifically on the range of dust the model is concerned with, typically long-distance transport (>1000 km), but to a greater extent are more symptomatic of an overall lack of dust collection field data. Furthermore, the observational data that do manage to get collected lack a universal method that allow it to be systematically compared to or combined with previous studies. Most researchers only examine particulates within a restricted diameter of micrometers, as is often necessary given that the frequency of spectroscopy waves will only detect certain particulate sizes. However, since no standardized protocol exists, every study subjectively determines its own diameter range, meaning that every new data collection examines particulates that partially overlap with some previous studies, and not entirely with any. Furthermore, without a standardized manner to arrange collection trays or filters, each study has a slightly distinctive set-up, and no studies try to synchronize seasonally, which can confound the results of compiled data if studies have been conducted over limited time periods (under a year) with incongruous start and end dates.
Dust carries many nutrients, microorganisms, and essential elements that can bolster ecosystem productivity and augment biotic development. Yet dust can also carry heavy metals, pathogens, and contaminants (such as from human activity and volcanic influences) that may harm both ecosystems and human health. To help better understand where our dust travels—and what deleterious or beneficial particles it transmits in the process—Lawrence and Neff advocate for studies to be more comprehensive in particulate diameters and conducted over longer periods (at least one year) using a standardized system of analysis and methodology. Most areas of environmental research derive conclusive, globally applicable statistics by compiling the extensive research gathered over multiple years and continents. Because of the inconsistent practices of dust collection, Lawrence and Neff could not make any such significant conclusions, nor enhance the accuracy of current models (except for pointing out that they may underestimate shorter-distance deposits, and overestimate global ones). Hopefully this initial compilation will help the sedimentary research community implement research practices that could be compared within different regions and eras.

Wind-Blown Dust Deposits Show a Pattern in the Intensity of Dust Flux Between Glacial and Inter-glacial Periods

The bedrock of Mallorca, Spain, consists almost entirely of limestone, making the fundamental base of the island primarily and homogenously carbonate. Yet the sedimentary layer directly above this limestone parent rock has quartz, silicates, metals, and rare earth minerals, none of which can be found in prominent concentrations in the parent rock. This layer is called terra rosa soil, a colloquial name for a variety of reddish, clay-loaded soils found in Mediterranean zones from South Australia to the United States—and, of course, in the European Mediterranean. In Mallorca, the terra rosa soil alternates in the geological stratigraphy with eolianite, a dominantly carbonate rock formation derived from lithified wind-blown sediment. Muhs et al. (2010) analyzed the chemical composition of these geological layers down to the parent rock at five different locations on the island to determine if the terra rosa soil has wind-blown African dust as its primary source. Confirming the source of the paleosols will not only allow scientists to further understand the current patterns of global dust travel, but also begin to document the variations in the rate of dust travel and magnitude throughout different climatic eras. .— Elise Wanger
Muhs, D., Budahn, J., Avila, A., Skipp, G., Freeman, J., Patterson, D., 2010. The role of African dust in the formation of Quaternary soils on Mallorca, Spain and implications for the genesis of Red Mediterranean soils. Quaternary Science Reviews 29, 2518–2543.

The African Sahara or Sahel regions make a probable source of terra rosa soil simply by a matter of deduction. Terra rosa soil—which Muhs et al. call paleosols since the informal “terra rosa” constitutes a number of different soil taxa, and paleosols include sediments deposited by gravity from the mountains—has a different particulate size and mineral composition than the dissolved bedrock, and the acute contrast between parent rock and soil negate the possibility that the paleosols could derive entirely from Mallorca itself. Silt from France, although chemically compatible with the paleosol, has limited capacity for transport to Mallorca given the geographic distribution of the silt and the patterns of global tradewinds. More importantly, wind-blown silt from northern France should deposit at least thin layers along the route, meaning that such sediment would be observed in central and southern France, and isn’t. Also, wind-traveling silt from Europe peaked during glacial periods, and the Mallorca paleosols most likely were formed during interglacial periods. Mallorca paleosols have high levels of marine fossils whose species correspond to interglacial eras, and such fossils in the soil indicate a higher sea level such as observed during interglacial periods (since during interglacial eras less water gets stored as ice). The fossil shells have also been dated by radioactive decay with elements such as uranium, although these methods can be unreliable. However, paleomagnetic dating and optically stimulated luminescence (OSL) agree with the shell dating estimates, as well as each other. Paleomagnetic dating consists of observing which direction iron molecules in igneous rock orient themselves in relation to the Earth’s poles, which switch magnetic directions intermittently every couple of millennia, making North the new South (and vise versa). Whatever the magnetic orientation of the time that material cooled and hardened into rock will be the manner in which the metals are oriented. OSL involves shining a light on a material to excite the unstable electrons outside a valence shell, the amount of which increases at a consistent rate from the time of light exposure, which would be the last time the sediment was at the surface and therefore around when it was deposited.
While dating methods and fossil organisms suggest paleosols develop interglacially, eolianite builds during glaciation. While currently submerged underwater, the carbonate-sand beach sources of eolianite would be exposed during glacial periods, when sea levels are at least 120 m lower. Further evidence comes from eolianite dating in the two most recent layers, which correspond perfectly to the last two glacial periods, about 21,000 and between 200,000–125,000 years ago.      Therefore, given the low levels of paleosol composites in eolianite, the dust source that creates the reddish deposits of silicates and metals must be dominant during interglacial periods and fairly inconsequential during glacial ones. African dust has been the most dominant source of wind-blown sediment during our current interglacial state, and Muhs et al. predict that during glaciations, African dust would most likely remain suspended in the atmosphere longer and not deposit so heavily near its source. The low levels of dust that still managed to descend on Mallorca during glacial eras would get diluted in the carbonate sands anyway, reduced to a minor contributor of the dominant composition.
As probable as the hypothesis of African dust as the paleosol source may be, however, it warrants confirmation by analysis of the mineral content. Muhs et al. used two samples of African dust that they assumed to be reflective of the Sahara-Sahel combination of sources that would reach Mallorca. The first sample came from wind-blown dust deposited in Barbados, which had already been confirmed as African-derived in previous studies and likely an accurate indicator of the mix that would reach Mallorca. Yet just in case weathering during the travel or inaccurate dust combinations didn’t truthfully portray sources analogous to the paleosols, Muhs et al. also used samples from the “red rain” (2526) dust events that deposited red dust from the Sahel and Sahara carried in rain clouds to Mallorca repeatedly between 1982–2003. These two sources overlapped in composition almost completely, meaning that Muhs et al. could confidently use their range of elemental components as that of African wind-blown dust reaching Mallocra.
Trace elements—such as scandium (Sc), chromium (Cr), thorium (Th), tantalum (Ta), hafnium (Hf), and zirconium (Zr)—and rare earth elements, some of which include the elements above, create unique identification codes that allow scientists to decipher the origin of a sediment. These elements do not leach into other layers easily, and don’t change or deplete during chemical weathering, making them highly reliable. The proportions of trace elements tended to fall in the range of African dust in the paleosols, while the non-carbonate sections of eolianite (since the more pure carbonate has little else to be measured) rarely fell within even the most extreme variation observed. The ratio between silicon (Si) and aluminum (Al) as well as the proportions of carbonate, manganese oxide, calcite and quartz, were also documented to get a complete picture of the region’s geography. The Si/Al ratio for the paleosols fell just outside the African dust range at one site, but fit well within the range at the others, while the eolianite sample always had a much higher Si/Al. That one site didn’t completely correspond to the African dust ratio suggests that some eolianite (probably the quartz sections) eroded into the paleosol layers.
As expected, Muhs et al. concluded that African dust fits as the most logical source of Mallorca paleosols, which may suggest other terra rosa soils also share this source as a contributor. According to the patterns in the stratigraphy between paleosols and eolianite, the amount of dust from Africa depositing in Mallorca shifts in intensity between interglacial and glacial eras. More dust suspended in the atmosphere absorbs more solar radiation, keeping the Earth’s surface cool in a reverse Greenhouse Effect. As the suspended particulates keep surface cool and prevent rain clouds from forming due to inversion layers, less vegetation grows and more sediment gets exposed, which can add more dust to the atmosphere in a positive feedback cycle. Thus increased dust flux could act as a counter to rising temperatures from global warming.

Ocean Sediment Core Delineates 100,000 Years of Monsoonal Variation

In 2004, an oceanographic cruise along the Nile delta off of the Mediterranean Sea extracted a 7 m long ocean core from a site 1389 m below the surface. Six years later, Revel et al. (2010) published the data from this core, which provide a record of the past 100,000 years of climate variability and Nile river outflow. Through identifying major elements, calibrating isotopic ratios, measuring particulate grain-size, and collating the data with previously collected paleo-climatic records, the ocean core, known as MS27PT, creates an uninterrupted database of Nile river runoff and the corresponding precipitation rates of the region. The results agree with previously observed records of climatic shifts, and provide higher resolutions than previous studies, typically from about 2–10 years. They also confirm monsoon fluctuation as the primary determinant of river flow, and show that the end of the Nabtian period—a pluvial (rainfall-constituting) era—ended 3 ka earlier along the Nile region than in equatorial Africa. .— Elise Wanger
Revel, M., Ducassou, E., Grousset, F., Bernasconi, S., Migeon, S., Revillon, S., Mascle, J., Murat, A., Zaragosi, S., Bosch, D., 2010. 100,000 Years of African monsoon variability recorded in sediments of the Nile Margin. Quaternary Science Reviews 29, 1342–1362.

The location from which scientists extracted the core—about 100 km from the Nile River mouth—makes the MS27PT core ideal for monitoring the history of the Nile discharge while avoiding the erosion and down-sloping turbidity currents of the Rosetta channel. Thus the core provides an uninterrupted record with no evidence of erosion or displacement from visual examination, X-ray radiography or thin section slices. Three sources of sediment in the core were identified: the Sahara, the White Nile, and the Blue Nile. The Blue Nile sources derive from metamorphic basalt rock younger than 30 Ma, while the White Nile is a granite. The Saharan dust derives from Precambrian granite significantly older than any other source, full of large-grained, quartz particles. Because the parent rocks of all three locations formed at different times and different rates, they each have a distinct strontium (Sr) isotope ratio that makes them easy to distinguish.
Both strontium (Sr) and neodymium (Nd) exist in all crust or mantle earth materials, and come in a variety of stable isotopes, making them effective geological fingerprints from which to determine sediment sources. From these isotopes, scientists have been able to determine that the overflow of Lakes Albert and Victoria that drain into the White Nile began only 11.5 ka BP, and have an almost negligible contribution to the sedimentary discharge during peak flow, due to both the White Nile’s weaker fluvial contribution, and the limited erosion or weathering of the rock material. Lastly, while the Blue Nile receives intense precipitation at higher elevations from the mountains, creating a speedy, downward flow, the White Nile travels along a fairly flat, slow-moving plane, where most sediment would end up sinking in the Sudd swamps of Sudan. These factors make the White Nile’s contribution to the Nile margin typically negligible, and therefore the core can be analyzed in terms of only two sources: Saharan dust and Blue Nile sediments.
The core length (in millimeters), was calibrated into age (in years before present) using a radiocarbon dating of planktonic foraminifera and sapropel events. Sapropels are darkly-colored layers laden with organic carbon that correspond to interglacial periods when rainwater and river runoff are highest. The influx of freshwater into the Mediterranean Sea has a lower salinity which means a lower density, making the incoming water unable to sink and mix with the deep-sea water. Since deep waters can only receive oxygen through circulation and ventilation, this breakdown of the cycle creates anoxic conditions on the sea floor, killing organisms in deep organic matter while simultaneously delaying decomposition. Thus sapropels are preserved organic matter. Sapropel events are well studied and already labeled and dated from previous research. The planktonic foraminifera allowed Revel et al. to confirm these studies as analogous to their core as well as gain a higher temporal resolution. The foraminifera were crushed and their constituents ionized with phosphoric acid, which gives the carbon a charge. Then the ions were separated by accelerator mass spectrometry, which runs them through an electrically charged field at high kinetic energies so that the lighter carbon-12 carrying molecules will move further than the carbon-14. All living material has the same 14C:12C ratio as the atmosphere while alive, but upon dying the organism no longer exchanges carbon with the outside world, and therefore cannot take in more carbon-14. The carbon-14, being an unstable isotope, will decay to the stable carbon-12 at a predictable rate.
Grain-size analysis was calibrated using a laser microgranulometer, which sends out an x-ray and measures the diffraction patterns that deviate from the calibrated expectation of sea water. Element concentrations were similarly determined with an XRF Core Scanner, which recorded images with visible and ultraviolet light waves at three different kilovolt levels. Major elements were also detected and measured through X-ray fluorescence. All these techniques allowed Revel et al. to take pictures of the core without disrupting the integrity of its form, and showed high precision and accuracy to other analyses. The elements evaluated were iron (Fe), sulfur (S), barium (Ba), calcium oxide (CaO), and manganese oxide (MnO).
Oxygen isotope ratios (δ18O) were measured to determine the past climate conditions within the sample. Oxygen comes in three naturally occurring isotopes, with oxygen-16 being the lightest and most prevalent, and oxygen-18 the heaviest and second-most prevalent. Colder or wetter climates (which are not necessarily inclusive) tend to have more oxygen-18 in the water, since the heavier oxygen isotope falls more readily as precipitation and takes more energy to evaporate, while the oxygen-16 will be more likely to freeze in glacial ice. Since calcite, the primary constituent of marine shells, requires oxygen from the environment to form, its oxygen isotope ratio is reflective of the environment in which it was formed, and therefore the calcite of planktonic foraminifera shells in ocean cores can be used to create a δ18O record. The oxygen isotope record can also help determine the contribution of river water to a sample. In being entirely composed of rainwater, river runoff has a lower δ18O than the sea. Yet given the multifarious influences on the δ18O, this record cannot give a complete narrative of the paleoclimate without the auxiliary records of sediments and other elements to complete the picture. A lower ratio tends to be indicative of wetter conditions, but other variables, indicative of sea-surface interactions, need to be considered, such as the productivity of surface biota that may use more oxygen during certain eras, constraining the oxygen that reaches the sea floor, or the if reduced circulation also led to less oxygen access. Revel et al. calibrated the δ18O appropriately for these non-climatic influences, and did not have to worry about the incongruous dichotomy between temperature and humidity, since the region of Africa throughout the last 100,000 years has been much more significantly influenced by climate change concerning moisture, with temperature fluctuations less pertinent to consideration.
Barium and sulfur proved to be a reliable proxy of the organic carbon content, and Revel et al. used the peak of these elements to designate the median of the sapropel thickness. Iron-rich sediments tend to be from the Blue Nile, while carbonate-rich sections—which also have high CaO and a high Si:Al ratio—act as proxies for Saharan aeolian dust. The Fe content strongly correlates to the Sr and Nd isotopes of the Blue Nile basalt as well. Larger grain size, depending on the material, could be correlated to either higher winds if from the Sahara, or higher river current if from the Blue Nile (usually from a mass flooding period).
Most data can be explained with a simple mixing model between the two sources, but the core also reveals distinct periods in which one mode dominates. Saharan dust contributes anywhere from 30–85% as the conditions shift from interglacial monsoon to arid glacial. The rates of sedimentation also shift dramatically from as little as 3 cm/ka to 108 cm/ka during high flood.
These eras of aridity and rainfall, that the Saharan dust and river deposits each respectively indicate, congruously follow monsoonal patterns. As the summer equinox approaches, the Inter Tropical Convergence Zone (ITCZ)—a latitudinal range of wind convergence that forms mass condensation and precipitation—migrates northward to about 20ºN, following the sun’s zenith point and causing a “wet season” (and a dry season at the equator). Given the absorptive and insulating capacity of land, the direct impact of the sun heats the land surface faster and more intensely than the ocean, which is fairly reflective and less susceptible to temperature change. This generates a pressure gradient between the ocean and the land surface (land having the lower pressure due to the warmer air rising), which draws moist, maritime air to the region which quickly rises over the land surface and condenses. Mountains will enhance this cycle by forcing the maritime air upwards and more readily inducing condensation, such as happens in the Ethiopian Highlands, of which Lake Tana and Blue Nile make up the drainage basin.
This monsoonal cycle is indicative of our current climate, but on a millennial timescale this patterns oscillates with the axial precession and orbital eccentricity of the Earth. The Earth rotates along the pole axes in a precessional cycle that takes about 26,000 years to complete, or about 1º per 72 years. This rotation follows a cone-shape with an angle of 23.5º, meaning that the summer and winter equinoxes shift in relation to the changing distance from the sun, and therefore the regions with the most intense sunlight and seasonal contrast move northwards in latitude, and regress back to the equator, every cycle. The orbital eccentricity of the Earth—the shape of it’s orbit—fluctuates from more circular to more oblong in an arguably 100,000 year average cycle, although this varies. When the orbital eccentricity and precession are matched up so that the sun is closest the Northern Hemisphere during its summer season and farthest during its winter—correlating to the precessional minimum and eccentricity maximum—the ITCZ extends the most northward, and the monsoon is the most intense. Conversely, a precession maxima and eccentric minima will create less seasonal variation and less monsoon, which creates an arid and dusty regional climate. The ocean core data accords with these shifts, with a weak monsoon season (which means a precessional minima and minimal ITCZ migration) reflected in a higher oxygen-16 to oxgyen-18 (δ18O), high levels of Saharan dust; and an intense monsoon reflected in a lower δ18O and more Blue Nile sedimentary deposits.
Saharan dust contributions tend to escalate in a snowball effect as more factors enhance the positive feedback of dust flux. The reduced migration of the ITCZ, due to the minimization of the precessional cycle, stimulates a greater thermal gradient between latitudes, causing air to travel as faster speeds as the difference between equatorial climate and the cooler North African region induces a pressure gradient. The dust plumes in the air then keep the North African land surface cool by insulating the area from the sun’s rays and stopping air from rising, through the creation of an inversion—when the air above is warmer than that below—which reduces the monsoonal effect even more, since the monsoon depends on the difference between heated land and the cooler ocean surfaces. The aridity therefore continues and begins to attenuate the soil moisture, making the land less hospitable to plant life which reduces the “savannah-like vegetation” (Revel et al., 2010; 1355) that holds the sediment in place. This cycle is reflected in the record, as Saharan dust gradually builds in concentration during low-monsoon periods. Likewise, precessional maximas correlating with the northwards expansion of the ITCZ reverse this model in the opposite direction, with wet seasons provoking wetter seasons.
Two periods of peak humidity conditions at 34–30 ka BP and 63–50 ka BP are evidenced in the core record. A 6% increased Fe content peaks from 34–30 ka BP, and the period from 63–50 ka BP shows higher organic carbon, as well as higher Fe and Ba, concentrations. Greenland ice cores have found increased methane-levels (CH4) during these same periods, which are usually caused by the circulation and melting of wetlands that have reservoirs of CH4 beneath the surface soil. Revel et al. propose that tropical wetlands during the African monsoonal peak could be the major source pertaining to the ice core record.
Another notable climate event recorded in the core is the end of the Nabtian pluvial period at about 8 ka, dated much earlier than indicated in lake cores from the East Equatorial African region, where rains begin to desist around 5.5 ka. The core shows a shift in the Sr ratio around 8 ka that corresponds to the basaltic parent rock of the Ethiopian highlands, indicating the intensification of an appreciable Blue Nile flow before declining into an arid stage. This transitional period from pluvial to arid from about 14–8 ka caused abnormal weather fluctuations of intense and irregular rains. Revel et al. track this period of “highly variable precipitation intensity” (Revel et al., 2010; 1360) closely along the core at a 2 year resolution. The discrepancy in dating between the MS27PT ocean core and equatorial lake cores most likely denotes the time in which the ITCZ began its gradual reversal southward, instigating increased rains to the Nile region as it passed, but not influencing the lower latitudes of the equatorial climate.
The MS27PT doesn’t only accord with previous paleoclimatic records. It provides a new degree of chronological resolution and reveals the local nuances that solely pertain to the unique trade winds of the North African region, providing a history specific to the Nile River. It also highlights the intricate relationships between systems from macrocosmic astronomical inputs to chemical reactions of benthic microorganisms. As the minima of the precessional cycles intensifies summer monsoon, rainfall increases and with it the freshwater input into the Nile Margin, creating anoxic deep-sea conditions which instigates the formation of sapropel layers that coincide with low δ18O. These interwoven phenomena reinforce each other’s validity by producing a precise and consistent set of variables that all contribute to a coherent story.

From Desert to Jungle: How Sahel Dust Sustains Amazonian Life

Without the African Sahara, the Amazon would be a desert as well. While intense precipitation and the ensuing floods wash most soluble minerals from the rainforest soil, mineral dust blown from the Sahara provides elemental nutrients such as aluminum, silicon, iron, titanium, and manganese (Al, Si, Fe, Ti, and Mn, respectively). Ben-Ami et al. (2010) combined satellite data with on-site analyses to better understand exactly how much dust from the Bodélé region of the Sahara reaches the Amazon, at what times, and in what routes. They examined two major dust events both in February 2008 and concluded that the Bodélé dust takes an average of 10 days to reach the Amazon forest canopy and that it mixes with both marine aerosols and biomass-burning aerosols along the way. The aerosol layer had more vertical range than expected as well, from 3 km above ground to the boundary layer, the more turbulent air layer below the cloud level. Such concrete data on the evasive study of global dust flux patterns allows scientists to better comprehend not only global climate patterns, but the dependency of biota on mass geochemical processes.— Elise Wanger
Ben-Ami, Y., Koren, I., Rudich, Y., Artaxo, P., Martin, S., Andreae, M., 2010. Transport of North African dust from the Bodélé depression to the Amazon Basin: a case study. Atmospheric Chemistry and Physics 10, 7533–7544.

The Bodélé has a unique combination of geological and meteorological qualities conducive to supplying the Amazon with nutrient elements. The estimated 133,532 km2 Bodélé depression sits in a valley which lake Mega-Chad formerly extended into in the Holocene several thousand years ago. Thus the soil contains SiO2, Al2O3, and Fe due to the diatomite and diatomite sand. Diatoms, single-celled algae that grow in massive numbers, leave elemental nutrients in the form of fossil deposits on lake bottoms, and the diatomaceous earth or sedimentary rock that contain these elements are known at diatomite. This uniquely signatured soil gets picked up by the Harmattan trade winds arriving from the northeast, which cross directly over the region. As these winds enter the Bodélé, the funnel effect of the valley narrows the passage of air and causes an acceleration of persistent high winds, perfect for dust transport. The Harmattan winds are seasonal, prevailing from December to mid-March, when the pressure along the equator is lowest, amplifying the gradient between regions, which is why the dust deposition in the Amazon occurs during the wet season. During the dry season, biomass smoke will often precede crustal dust particles as a prelude to the wet season, although as of yet no biological benefit has been found related to smoke aerosols on terrestrial life. For the 2003–2004 winter and spring seasons, researchers Koren et al. (2006) estimated that the Bodélé depression emitted (58±8) ´ 106 tons of dust, corresponding to over 7´105 tons per day. Although this number is significantly higher than the 1´106 tons observed by Ben-Ami et al. in regards to the February 2008 dust events (which only calculates a half-day of emission), both studies elucidate just how extensive the transport and deposition of Bodélé dust emissions can be.
The ground measurements of soil took place between February 7 and March 14, 2008, in a relatively unmanipulated forest of Brazil. The elemental analyses and proportion of Bodélé sediments were used to confirm the satellite findings. Polycarbonate filters above the canopy were installed in same location to analyze aerosol content as well, which gave a better sense of how much wind-blown particulate was biomass-burning aerosols or seawater particulates instead of dust. The surface wind speed and the direction of the wind were both calibrated using resolution imaging and spectroradiometry from a daytime and evening-time satellite. A spectroradiometer measures the radiation emitted per unit wavelength, in this situation being 440 nanometers (nm), which provides a resolution of 1 km2 per pixel. The Aerosol Optical Depth (AOD) was measured using the same “evening” satellite at 550 nm, providing a 10 km2/pixel resolution. The optical depth measures the transparency of an object by calculating how much radiation travels through it by looking at the intensity of the photons (the amount of light), the distance the light travels, and the amount of light backscattered or absorbed. The more light that travels through the material, the lower the AOD. In areas without clouds and few other particulate matters, the AOD can be assumed to be almost completely an analysis of dust, and the mass can therefore be easily calculated as a matter of the volume of the air column multiplied by a coefficient compensating for the influence of aerosols such as air pollutants on the AOD. Ben-Ami et al. chose a coefficient correlating to levels of other aerosols during moderate dust events, potentially making their estimates of the Bodélé region dust events overly conservative. Yet even veering on the safe side, the AOD of the dust route regions during a dust event is quite high and calibrates to an astounding mass of between 1´105–1´106 tons of emissions in the Bodélé from early morning to 12:30 P.M.
The fraction of aerosols with various diameters was also measured over satellites at 550 nm and through applying the Angström exponent to the hard data. The Angström exponent describes the effect of wavelength on the AOD, so that the AOD can be calibrated for any frequency of light. The lower the Angström exponent, the less wavelength level changes the amount of absorption and backscatter. Since large particles change less with wavelength, calculating the respective Angström exponent can indirectly measure the particulate size of the dust. Biomass-burning aerosols and marine aerosols from sea salts and organic matter were measured and subtracted from the total AOD in areas with more potential particulates, identified by their respective sizes (all under 1 mm).
The segregation of dust from clouds in the data was determined by calculating the “volume depolarization ratio” (VDR; Ben-Ami et al. 2010; 7535) with a satellite that uses infrared rays to capture cloud aerosol levels through measuring the polarization of the rays. As light hits a surface, it will usually backscatter, meaning that it will reflect back in the same direction it came from. This is typically the case with symmetrical particles. But less symmetrical particles, like dust, will reflect some of the waves perpendicular to the direction from which the wave derived. So while clouds, having fairly spherical particles will have a relatively low VDR, dust will have quite a high VDR. Looking at the different backscatter patterns themselves also help separate satellite data for dust versus clouds. Clouds have a strong backscatter signal with different vertical dimensions and horizontal dimensions.
Once the actual dust measurements could be calibrated—after correcting for other aerosols and cloud cover—Ben-Ami et al. could calculate the mass, rate, and elemental composition of the Bodélé dust from source to sink. Forward trajectories from the satellite data show that the crustal elements in the Amazon take between 10–17 days to arrive from the Bodélé, and back trajectory calculations show that the Bodélé dust takes about 2.5 days to reach the AERONET station in south-central Nigeria. According to the decreasing VDR over the course of the route, significant sedimentation of the dust occurs over the ocean along the way, more than doubling dust loading over the Atlantic. The VDR also indicated that many regions had a value right in between that expected for biomass smoke and that of dust, meaning the two aerosols are probably mixing in the trade winds. This mixing increased over the course of the dust event; for some reason more dust seems to dissipate towards biomass-burning regions. As expected, from the soil analysis on-site, Ben-Ami et al. observed more than tenfold more Si, Al, Fe, Mn, and Ti from the 18–19 of February dust deposition period. They also detected a chlorine content, apparently a result of dust mixing with the sea salt over the ocean before depositing.

The results from the study of Ben-Ami et al. lack any major conclusions, and an overall mass cannot be determined given the ±30% uncertainty in the calculation. As the article recommends, further satellite analyses and more extensive physical data should be collected, especially since dust deposition levels may shift with climate change.

Dust-on-Snow Causes Early Waterflow Rates and Decreased Overall Water Runoff in the Colorado Riverd

Twenty-seven million people within seven states and Mexico all depend on the Colorado River for water. Without its continuous and consistent level of flow, cities such as Phoenix, Las Vegas, and Los Angeles would quickly become uninhabitable. Unfortunately, current climate change models predict a 7–20% decrease in Colorado River runoff by 2050 due to increasing temperatures and lower precipitation, both direct factors of global warming. One possible strategy to help offset this impending blow to a crucial water source could be stabilizing soil surfaces and increasing vegetation areas, as the research of Painter et al. (2010) implies. Painter et al. analyzed the impact of dust on snowmelt rates throughout the Upper Colorado River Basin (UCRB) using a standard hydrologic simulation model to determine exactly how much snowmelt runoff is lost from varying levels of dust input on snow; runoff which could help counterbalance the lowering levels already being observed in the Colorado River. The results suggest that the dust-induced earlier snowmelt causes more water loss through evapotranspiration, makes runoff levels less constant and manageable, and deprives the region of substantial runoff in July, which could impede riparian vegetation health and fish survival and place further undue stress on the Colorado Basin reservoir in late-summer.–Elise Wanger
Painter, T., Deems, J., Belnap, J., Hamlet, A., Landry, C., Udall, B., 2010. Response of Colorado River runoff to dust radiative forcing in snow. PNAS Early Edition 10, 1–6.

Painter et al. used the Variable Infiltration Capacity (VIC) model to simulate runoff rates from snowmelt after dust loading (ADL) in comparison to before dust loading (BDL). The VIC model divides the region into small, homogenized grid cells that each get analyzed separately for their predicted runoff and evapotranspiration rates. These cells can be layered by elevation, and sized to a resolution small enough that the area can be justifiably stereotyped for a uniform precipitation rate, air temperature, wind speed, humidity, shortwave and longwave radiation, and snow albedo. Since Painter et al. only concerned themselves with the influence of dust and therefore only the changing the albedo factor and subsquent melting rates, these fundamental variables provided enough accuracy to calculate significant differences without obscuring the predicted results. Painter et al. used a grid cell resolution of 1/8º for the years 1915–2003; each cell covered about 1/8º in longitude and latitude. The variables for the model (daily temperature, radiation, precipitation, etc.) from the years 1915–2003 were taken from a physically based hydrology model from a previous study (Hamlet et al. 2007). These calculations fit actual data from a study in the east central UCRB, making their results a reliable choice for the region.
The albedo factor indicates the reflectivity of a surface from a scale of 0–1. Zero means that all radiation reaching the surface gets absorbed, and 1.0 means that all radiation reaching the surface gets reflected back into the atmosphere. Pristine snow has an albedo factor typically around 0.98, reflecting most of the sunlight and keeping the snow cool and compact. Dust-laden snow, however, has a much lower albedo factor, since the larger, darker dust particles absorb short- and long wave radiation. As these dust particles absorb heat and radiate it to the surrounding snow, the snow gets denser and its grain-size increases. These large grain sizes absorb more heat more easily (having a larger surface area to absorb radiation), creating a positive feedback system so that the snow melts even faster. This is why dust-on-snow creates earlier snowmelt and therefore higher runoff rates earlier in the season, and exposes more vegetation and soil earlier in the season by melting too quickly.
The model simulated the predicted runoff rates from 1915–2003, estimating wind-blown dust emission levels based on lake core sediments in the eastern UCRB. Since remote sensing, isotope analyses and ensemble backtrajectories have all shown that the dust on UCRB snow derives from the Colorado Plateau and the Central Basin, previous studies easily figured out the percentage of sediment from dust emission for each period represented in the lake core samples. Painter et al. assigned this simulation ADL, since wind-blown dust levels from 1916 to the present have been amplified by human activities. In fact, the lake core sediments indicate wind-blown dust levels increased six-fold by the early 20th century. Ranching, agriculture, deforestation, oil drilling and other anthropogenic disruptions left the surface soil more vulnerable to getting picked up by wind. The biological crusts of bacteria, fungi, and bugs create a moist mat of decomposing material netted in place by the extensive cell systems of biota. The soil above has a physically-derived mat as well, from retaining moisture which makes the soil more dense and bonds with many water-bonding minerals. When the soils get broken up and turned over, moisture quickly evaporates and the cohesive biological mat fragments, leaving discontinuous, dry dirt that easily blows away.
Lake cores show that before around 1850, however, this was not the case. Snow before the silver mines and ranching was fairly clean, providing Painter et al. with an undisturbed set of dust-level data to which the ADL model could be compared. Using the same variables as from 1916 (temperature, wind speeds, etc.), the model was run a second time with albedo factors reflective of pre-1850 dust levels, the BDL model. Dust levels as low as those in the BDL could not be fit to the ADL parameterization because dust’s influence on melting rates is more complex than simply lowering the albedo; the “snow metamorphism” (the building of denser, larger grain-sized snow from the melting process) also enhances melting. Although snow metamorphism is fairly consistent past a certain threshold dust level, at concentrations below this threshold the impact of metamorphism is probably less consequential than melting rates calculated from dust-laden snow can account for. Painter et al. therefore estimated the lower melting rates for the BDL higher albedo using a parameterization model from data at Morteratshglestcher, Switzerland, and the Storglaciären Glacier, Sweden, instead, which both receive less dust than the current UCRB. Like the previous model—which was based on observations of high dust levels—the values from Switzerland and Sweden were graphed to indicate the relationships between dust load and melt rates. Painter et al. fit this relationship between albedo and melting rates on a straight line, thus overestimating the melting rate of clean snow. Additional dust loads don’t absorb as much radiation per increase in mass as initial deposits, making the relationship plateau more (lowering the slope) as dust amounts increase. Therefore the first layer of dust has the highest impact on albedo reduction, creating a non-linear progression; the difference between a thin layer of dark color and white is much more significant than between a thin layer of dark and a slightly thicker layer of dark. The first layers of dust also increase snow grain size the most and therefore melting rates the most as well. Yet Painter et al. intentionally kept the relationship linear in order to take a conservative stance on ADL and BDL differences. If true BDL dust levels have less of an impact on radiative absorption than the model estimates, than the differences in runoff between disturbed and undisturbed dust-loads is probably even greater than the model created by Painter et al. infer. So the fact that this cautious parameterization still predicts 2.5-fold less dust-related absorption during the accumulation seasons (when more snow is falling than evaporating or melting), and 3-fold less during the ablation season (when more snow is being lost to evaporation and melting than falling) makes quite a statement.
Once Painter et al. registered all these data into the VIC model, they calculated the difference in melting rates between BDL and ADL snow by predicting when the snow would be at only 10% of its peak level. Once 90% of the snow has melted, artifacts on the soil layer (such as vegetation and rock) begin to influence melt rates much more than dust, and some areas maintain 5–10% of its snow year-round, making 10% snow cover a reasonable end-point to see the impact of dust load. From 1916–2003, the mean difference between the time BDL and ADL snow cover loss reaches 10% of its original value is 21 days. In contrast, the mean difference between BDL and pristine snow cover loss is only seven days.
As expected, areas with the most snow differed in melting rates the most between BDL and ADL. Since more snow takes a longer time to melt in either model, the different rates of melting lead to the greatest difference in days to reach 10% of peak snow cover with high levels of snow. Years with the most annual runoff (which implies more snow) also showed the greatest difference in runoff rates between BDL and ADL snow. This is why even exclusively within the ADL or BDL seasons, the date at which half the river flow occurs can differ as much as 9–21 days; though on average, ADL years still reach half the annual flow an average of two weeks earlier than BDL years, meaning that more water is flowing faster earlier in the season after dust disturbances (and subsequently less water is flowing later).
On the other hand, vegetation mitigates the difference between BDL and ADL models, since the forest canopies will block dust and light radiation from reaching the snow layer. With or without dust, snow on the forest floor won’t melt as readily, especially in evergreen forests where the needles block sunlight and particulate deposition year-round. For this reason, studies measuring the impact of increased radiative forcing (the radiation hitting a surface, measured in Watts per meter2) are currently being conducted in forests infested with pine beetles. Dead, needle-less pines would expectedly increase snowmelt rates simply by exposing more ground to sunlight.
Evapotranspiration levels also differ in respect to dust flux. Since snow absorbing more radiation is wetter and warmer than pristine, hard snowpack, dust-laden snow not only melts more, but a greater portion returns to the atmosphere as vapor. Furthermore, shorter snow-covered seasons due to faster melting mean that vegetation and bare soil have more time exposed to the hot and dry mountain air. Evapotransporation (ET) is the combination of evaporation and transpiration levels. Water that vaporizes from soil, groundcover, lakes, or leaf-surfaces (especially along the forest canopies) all count as evaporation. Transpiration is also a vaporization process, conducted by the living plants themselves. Cells on leaves create openings called stomata, allowing water collected from the plant roots to be released as vapor into the atmosphere. This sometimes serves a useful purpose in cooling the plant down or facilitating the transport of minerals, but often it’s just a byproduct of the need to open stomata to admit CO2 for photosynthesis.
The ADL earlier exposure of vegetation and soils causes an estimated runoff loss of 1.0 bcm (billion cubic meters) of water per year, which equates to about 5% of the annual average. To put that amount in perspective, Las Vegas is allocated only half that amount per year, and Los Angeles only two-thirds. The increase in ET is greatest between ADL and BDL models in June and July, when the difference in exposed soil is highest and the grain sizes the most differentiated. By August, the majority of the UCRB receives daily afternoon rainstorms, which nullify the differences in ET between dust-on-snow and clean snow by melting down snow and saturating the water-holding capacity of land. However, Painter et al. conjecture that regions without considerable late-summer rainfall (such as Sierra Nevada in California) could have lower ET rates because the ground would have the most water before the ET rate peaks in June. In other words, the most snowmelt usually corresponds with the highest period of ET, which quickly depletes the just-melted water into vapor. If dust causes the melting period to precede the period of hot weather and ET peak, the water-melt would remain intact and allow for high runoff rates later in the season, as would be routine in BDL environments. However, this possible exception to the rule (the rule being that earlier melt equals earlier runoff) has not been investigated. Scientists would have to confirm that a lower ET rate during high levels of water is enough to counter the lesser overall snowmelt by mid-late summer, and soil analyses of the region would have to negate the likely possibility that the soil in such areas would not simply store the excess water, since no afternoon rains will create an increased infiltration potential—the soil would be further from the saturation threshold for water-holding capacity, and therefore store more water than in the UCRB.
Although the VIC models’ assumptions are simple and the results insightful as to our alpine ecosystem’s relationship with dust, as with any model the estimations don’t perfectly reflect real-world conditions and all the factors for which the model does not account. Calibrating natural flows of billions of cubic meters worth of snowmelt from a smaller-scale grid model ignores a lot of detailed complications that influence the true runoff levels, and the representations of vegetation cover influences, although specified for foliage type (conifer, deciduous, shrub) are static, meaning that all conifer forests are assumed to intercept the same degrees of radiation and dust. Painter et al. also concede that changes in vegetation transience did not get accounted for in the model. Industrial era logging in the later 1800s would probably have significantly different runoff rates than the 1960s reforestation movement (which is probably one of the reasons the researchers started the simulations at 1916). Change in stomatal resistance also did not factor into the model, although in the relatively clean air of the UCRB this dynamic may not be much of an issue. In the presence of increased CO2, plants will conserve their water and open their stomata less, leading to less transpiration. If this phenomenon is significant from the past 150 years, then BDL transpiration would be even lower and the difference between total runoff between ADL and BDL even more pronounced.
Most significantly, the VIC models do not factor in surface-temperature interactions, namely the way surface absorbance or reflectivity influences weather conditions in the troposphere. In the case of the BDL model—in which the majority of light radiation reflects off the snow and returns to the atmosphere—the surface temperature and subsequently the overlying atmosphere might be cooler than the temperatures entered into the model (which are the same as for ADL). Cloud patterns and thus precipitation might differ from the cooler climate created, causing snowmelt rates to be even lower than estimated. This means, just as with the linear relationship fitted between dust load and melt rates, the model has steered towards the more conservative route, understating the possible variation between BDL and ADL runoff.
Especially given the water loss that will continue with global warming, understanding the seasonal runoff rates of UCRB snow will allow policymakers to adjust their habits and water deliveries accordingly to maximize efficient allocation. From 2000 to 2010, unprecedented dust emissions caused sharply earlier runoff rates. Yet normal deliveries from Lake Powell to the Lower Basin continued as usual without compensating for the seasonal variation, and by the end of the decade Lake Mead went from a nearly full reservoir of 30.8 bcm in 2000 to only 42% of capacity (12.8 bcm). Yet taking more water earlier is an inadequate solution to a long-term problem, and does nothing to compensate for the overdraft of taking more from a decreasing source. A more effective, long-term initiative that Painter et al. endorse is to reduce dust loading by increasing surface stabilization. This would entail further curbing of large livestock grazing, restrictions of vehicles on dirt roads, and more regulated agricultural practices in lower elevations, including minimizing plowing and soil turn-over. The physical crust can repair in a matter of days with a good rain, and the cyptobiotic mat only takes a few years to establish, once the land no longer gets disturbed. Reinstating native plants that are capable of germinating in drought years would also reduce soil exposure and stabilize the soil, since more dirt would be rooted in place and shielded by plant-life.
The droughts in the Colorado River Basin predicted by global warming can’t provide a complete picture of the severity of water loss without acknowledging the role of dust loads. Dust-on-snow generates irregular runoff rates and increases the rate of ET. The research of Painter et al. shows that as dust emissions increase depletion of Colorado River reservoirs, countering the trend by restabilizing surface soil could be feasible. 

Snow Samples on Berkner Island, Antartica, Indicate Varying Seasonal Sources of Wind-Blown Dust

During the summer work seasons on the Antarctic island of Berkner, Bory et al. (2010) excavated samples from a slab of snow 3 meters long and 1 meter wide, taking 14 successive layers from the first fresh-snow deposits downwards, each sample about 6.510 cm thick from the slab. The 14 samples represented about two years worth of dust deposition and precipitation from the summer of 2001 to early December, 2003. Cut with a stainless steel saw and protected against particulate contamination with plastic sheets and no downwind activity, each layer was melted down into 60 liter samples of meltwater, which Bory et al. analyzed for radioisotope ratios of strontium (Sr) and neodymium (Nd), dust particulate size, and oxygen 18 isotope ratios. The research team then used the isotope signatures and particulate size to determine the source from which the dust deposits arrived, comparing their samples to those from the East Antarctic Plateau (EAP) in both glacial and interglacial eras. The concentration and isotopic make-up of the Berkner island samples varied seasonally as well as in regards to the EAP samples, meaning that the Berkner deposits came from other places than the EAP’s, and that the source of dust may shift from summer to winter as the amount of dust and the wind currents in various land masses fluctuate. Such results suggest that the air masses traveling to the Antarctic are more specified than previously thought, and perhaps from more diverse sources.Elise Wanger
Bory, A., Wolff, E., Mulvaney, R., Jagoutz, E., Wegner, A., Ruth, U., Elderfield, H., 2010. Multiple sources supply eolian dust to the Atlantic sector of coastal Antarctica: Evidence from recent snow layers at the top of Berkner Island ice sheet. Earth and Planetary Science Letters 291, 138–148.

            Bory et al. filtered each 60 l sample from the snow-pit slabs to separate impurities, leaving 12 ml of larger particulate materials to be analyzed for grain size and composition. The rest of the sample was measured for the oxygen 18 isotope ratio. Oxygen naturally comes in three isotopes: oxygen-18, 17 and 16, with oxygen-16 being the most prevalent. Since oxygen-18 has two more neutrons, making it significantly heavier,  it falls more readily in precipitation and therefore is first to fall as water vapor cools and condenses into precipitation. By the time water vapor reaches the Antarctic, more oxygen-16 is left. Therefore a higher concentration of oxygen-16 correlates to colder, wetter seasons. Bory et al. used this to date the sample layers of snow. The samples were excavated in 2003 from the surface layer downwards, so the oxygen isotope ratios could be fitted with the record of surface temperatures from that given starting date. These analyses were also compared with samples taken down the entire snow pit wall (1 m deep) in 2 cm intervals, which allowed Bory et al. to check their fitted dates for coherency and provide a higher resolution. The resulting time-scale provided periods as discrete as three weeks to as much as three months. The layers of snow in the samples were visible from various storms due to different grains sizes and colorations, and these horizons were fairly straight and blatant, indicating that each statigraphic layer would be accurately compatible with the fitted time periods across the 3 meter width.
            Next Bory et al. analyzed the concentrations and isotope ratios of Sr and Nd. Strontium and neodymium are both earth metals present in both the crust and the mantle. The crust is the geologic layer on the surface of the earth in the form of land and oceanic sediment and makes up about 1% of the earth’s thickness. The mantle is the layer below the crust and composed of a high pressure, high temperature liquid. The concentration and isotope ratios of Sr and Nd are unique to each geologic land mass depending on when the land was formed and how fast (and therefore the temperature) the rock cooled on the surface. Strontium can bond in the same ways calcium can, and Nd can bond in the same manner as potassium (K). Therefore the amount of non-soluble Sr and Nd is also contingent upon the concentration of Ca and K, respectively, even while still below the crust. As the mantle material cools, different minerals crystallize at different temperatures, and therefore each rock-forming event carries different concentrations of elements like Ca and K at different levels. And since different continental land masses formed at different times, the radioactive decay of 87Sr (with a half-life 4.88×1010 years) and 144Nd (with a half-life of 2.29×1015 years)  can also act as a geological fingerprint, describing with land mass the deposit originated. For convenience in graphing and calculations, Bory et al. measured the 143Nd/144Nd ratio in respect to the deviation from the standard 143Nd/144Nd ratio of chondrites, which are essentially meteorites impervious to geologic melting and chemical weathering (making them a default reference point for universal original starting ratios and chemical compositions).
            In order to account for the possibility of Sr from oceanic distributions (the Berkner island site is right along the coast, and high amounts of Sr exist in sea-salt),  the dry residue of the filtered particles (about 12 mL) were analyzed for saltwater content by finding the concentration of sodium (Na+) and chloride (Cl) ions (which are the components of salt) through ion chromatography. These ions would be almost entirely sea-water derived. If the Sr/Cl and Sr/Na ratios were comparable to those of seawater (4.15×10–4 and 4.33×10–4),  this would further indicate a direct seawater influence. Possible Sr from soluble carbonates like ikaite—a crystalline mineral that only exists in conditions too cold for calcite—were also a concern, which could have entered the sample layers with sea-water contributions. The researchers checked for this possibility by measuring the Ca2+ cation content, since carbonates such as ikaite contain significant calcium contents. Also, as with seawater, a predictable Sr/Ca ratio from ikaite would be expected, about 0.01. Of course, any calcium form could just as likely be dust-derived, even in the form of a carbonate, so to assume the calcium-based Sr is completely from salt-water sources provides a “maximum correction” (Bory et al., 2010; 141). In other words, if anything, compensating for Sr from calcium by multiplying the 87Sr/86Sr ratio to that of seawater (0.709) will underestimate the ratio to something lower than the reality.
            Assuming that the dust in the sample contains the standard 25 parts per million (ppm) of neodymium (Nd), the concentration of dust in the snow samples could be determined by measuring the total Nd in the sample, deriving the assumed mass of dust from that value, and dividing the mass of dust by the mass of the entire sample. Bory et al. compared this value to the mass of dust particles measured using a laser-sensing particle detector, which yielded the same results within standard error, and also checked the results against previous studies. All the different methods indicated extremely low values of 1 to 6 ppb (parts per ten thousand) of dust. The concentrations varied seasonally, as did the 87Sr/86Sr and 143Nd/144Nd ratios, although to assume consistent seasonal fluctuations from a two-year diagnosis would be quite imprudent, especially since they were inconsistent even within the short temporal range of data. The fall and winter of 2002 and 2003 had the lowest concentrations of dust, while the following springs and summers had the highest. The summer of 2001 (from the earliest samples) defied this pattern with relatively low concentrations. Correspondingly, the two spring/summers with the highest concentrations also had less negative 143Nd/144Nd deviations from the chondritic value than average— meaning that the 143Nd/144Nd  ratio was closer to the chondritic value, and thus lower and more radiogenic, than usual—while the summer of 2001 was anomalously quite negative. The 87Sr/86Sr ratio of these seasons was lower—meaning less radiogenic—which makes sense since a higher 143Nd/144Nd ratio (ie. less radiogenic) typically corresponds with a less radiogenic Sr ratio. The Sr ratio between summers, however, do not correspond in the same range of values and the assumption that the fluctuations are seasonal (as opposed to completely random) is questionable. As with Nd, the Sr ratio in the summer of 2001 defies the trend, in the case of the 87Sr/86Sr ratio by being abnormally high and therefore quite radioactive. Bory et al. suggest the patterns from 2001 could be related to the peculiar atmospheric circulation patterns over the Weddell Sea during that season, although such a suggestion is purely conjecture.
            Either way, the purpose of the elemental analyses in the samples was primarily to determine where the dust derives and if the sources change seasonally, as well as if these sources differ from those in other regions of Antarctica, especially the East Antarctic Plateau (EAP). Samples from the glacial period of the EAP (during the last ice age) show significant isotopic differences: glacial EAP samples are less radiogenic in regards to Sr and more radiogenic for Nd. Interglacial samples from the EAP—during our era—are more radiogenic in Sr than the glacial EAP but still less than the Berkner samples, and less radiogenic in Nd that the glacial EAP but still more radiogenic on average than Berkner samples. In other words, the interglacial EAP samples are intermediate between the two, and in some cases even overlap the Berkner isotope ratios. Berkner and the EAP could therefore plausibly receive some dust from the same continental origins, also Bory et al. also propose that various mixing could create incidental similarities in ratios too, even without sharing sources. No one has yet determined the exact location of dust sources in Antarctica in any region, except for the glacial EAP that has a “young” radioisotope signature distinct of Patagonia and the Puna-Altiplano region in Southern South America. Past and present wind currents also validate Patagonia as the probable source of glacial EAP dust. Interglacial EAP also has the characteristic isotope signature of Patagonia and the Puna-Altiplano area. For both the glacial and interglacial EAP samples, other possibilities have yet to be confirmed or rejected, and areas such as around the Magellan Strait, the Andes, or Argentina could all possibly contribute, but only Patagonia and the Puna-Altiplano region have been definitively confirmed.
            Still, the EAP samples all fall in the range of the Southern South American candidates, unlike the Berkner isotope ratios. Some of the negative deviations from the chodritic 143Nd/144Nd ratios exceed any range in Southern South America, and is less cohesive with the Patagonian signature. The Puna-Altiplano region matches the Berkner region better, and has the ratios to be the sole provenance of the 2002 and 2003 spring/summer seasons. But for the other periods an older land mass is necessary to explain the low Nd radioactivity. Bory et al. propose Australia for an older ratio, but the lower latitude of the land makes the long-distance dust travel less feasible than from Patagonia, and no data supports the transport of Australian dust to Antarctica. Whether dust could travel such as distance on the given wind patterns is undetermined, and even if it could the particulate size would be much smaller than that observed in the samples. Furthermore, the Berkner isotope ratios still fall far outside even the most Australian-favored models of a realistic mixing with Patagonian dust. Another older-crust like isotopic ratio in the southern hemisphere is southern Africa. The Kalahari desert and Coastal Namibia fit with the ratios observed in Brekner, but once again the complications of travel hinder the plausibility of the dust deriving from these sources. Although these particulate sources cannot be discounted, the best option given the grain sizes of the sediments and the dominant wind patterns is for the other source beyond southern South America to be the snow-free regions of EAP. At the edges of the East Antarctic ice caps, between the southern ocean and the Berkner Islands, the land is geologically pre-Cambrian: old enough to have the low radiogenic ratios of Nd, with scattered 87Sr/86Sr ratios. And wind patterns are conducive to having Patagonian and East Antarctic dust mixing and landing on Berkner island together, granted such a possibility is still purely hypothetical. And since such dust would be traveling from low altitudes in the direction of Berkner, it would completely evade the EAP samples, reinforcing the differentiation observed in isotope analysis.
            If climate change is as highly contingent on atmospheric circulation as many scientists suspect, understanding global wind circulations could provide insight into creating more accurate future climate models. Our current wind patterns are what keeps the Mediterranean climate temperate, the Sahara hot and dry, and the eastern United States snowy and rainy. As they change, so does global weather. Looking at where dust derives in Antarctica provides further insight into these wind currents and where they travel. If we can compare the current dust sources to those of the last glacial period, we can even understand the differences between our contemporary currents now and those of the ice ages. The Berkner isotope analyses add one more piece to the puzzle of where particles are traveling, and what weather may be traveling with them.

Chemical Compositions of Rocky Mountain Dust-on-Snow

In mid-February, 2006, a dust cloud from windstorms in Arizona, Utah, and western Colorado deposited dust on snow throughout the majority of the Colorado Rockies, creating a 0.5–2.0 cm layer of red snow that remained visible throughout the year. Rhoades et al. (2010) examined the chemical compositions of dust-event snow layers from south-central Colorado up to Southern Wyoming, comparing the dust-laden layer to snow layers 25–35 cm below and above the layer from the dust event. They also compared dust-layer samples in different regions, at different elevations, and during different seasons. Rhoades et al. concluded from their analyses that dust-event snowpack had a pH 1.5 units higher, on average, than snow before and after the event. The dust-event snow also had 100-times the capacity to neutralize acids, and 10-times the amount of calcium, as well as completely different elemental distributions than non-dust layers. As of yet, no chemical changes of the stream or lake waters have been observed in relation to the dust, nor have other snow layers been affected. However, the possible consequences of the dust in changing the quality of soil—especially between upper and lower elevations—and the earlier seasonal snowmelt could influence the biodiversity of animal and plant life in the region. In providing the chemical compositions of dust-event snow, this study lays the foundation for further research on the possible implications of dust-laden snow on alpine ecological cycles.—Elise Wanger
Rhoades, C., Elder, K., Greene, E., 2010. The influence of an extensive dust event on snow chemistry in the southern Rocky Mountains. Arctic, Antarctic, and Alpine Research 42, 98–105.

Dust regularly travels to the Rockies from neighboring regions in Colorado, Utah, Wyoming, and occasionally even Arizona, making dust-on-snow events a long recognized phenomenon. Geology studies have long confirmed that cations from dust deposits (Ca2+, Mg2+, Na+ and K+) elevate the pH and the pH buffering capacity. The pH specifies the concentration of hydrogen ions (H+) in a solution, with a higher pH designating a lower concentration. Since H+ concentrations tend to be incredibly small, the pH takes the negative log of the moles per liter, or molarity (M). For example, the H+ concentration of pure water is 10-7 M, or 0.0000007 M, making the pH –log (10-7) = – (-7) = 7. Thus every unit difference in pH means a 10-fold difference in H+ concentrations. Acid ions (NO3, Cl, SO42-), carbonates (HCO3), and bicarbonates (CO32-) will often raise the pH by bonding with H+ ions, while cations will lower the pH by bonding with acid ions and reducing acid ion availability for H+: which is why cation-laden dust elevates pH.
Dust events in the Rockies have also enhanced the nutrient availability of soils. Inputs from the Colorado Plateaus double the phosphorus content of surface soil, as well as adding carbonates, calcium, magnesium, potassium, sodium, and various micronutrients (chemicals that biota need only in trace amounts, like zinc). The calcium (Ca2+) concentration of Colorado lakes that receive dust inputs is higher in comparison to California lakes with no dust and similar geology. The addition of fine-textured clay particles from dust also increases the water- and nutrient-holding capacity of the soil, which has a huge impact on the fertility of the earth in regions that would otherwise be barren rock.
Given the myriad benefits, Alpine ecosystems have depended on regular deposits of dust to maintain biodiversity and vitality for millennia. Yet not until about five years ago had dust-on-snow made enough of a visible impact to draw the attention of researchers to investigate the possible ecological consequences of increased dust, and the source of such amplified dust storms. The cause of recent major dust events remains uncertain, although most scientists attest to combinations of agricultural practices such as ranching, that kick up dust; the ten year drought from the mid-nineties to mid-2000’s breaking up the cyptobiotic mat keeping soil intact; and oil drilling in southeast Arizona. Whatever the cause, increased amounts of dust on snow have created major changes, especially pertaining to the rate of snowmelt. Snow has a very high albedo factor, meaning that it’s incredibly reflective. Pristine snow reflects up to 98% of the sun’s radiation back into the atmosphere, keeping the snow cool and the ice-pack thick. When the snow is darkened by dust, however, the darker color absorbs more UV rays, reducing the albedo factor to reflecting only 50–60% of the radiation and making the snow melt faster. And since water is denser than snow, the snow melts from the bottom out, so that the red-dust layer remains on top until everything beneath has melted away. After the 2006 dust event, snow melted 18–35 days ahead of the usual pattern, and late-season avalanches became more prevalent with the softer, weakened snowpack. Such a change in seasonal melting patterns changes the length and period of the growing season for high-alpine plants, and the fluctuation of water-levels. Faster snowmelt means that rivers run higher and faster earlier, and lower and slower later. In late August, mountain rivers rely on that last reservoir of snowmelt to keep flowing, which depends on a gradual rate of melting throughout the summer months.
Rhoades et al. examined the molecular compositions of dust-laden and dust-free snow, as well as wetfall precipitation before, after, and during the dust event to help future research shed light on the possible chemical consequences of dust events on soil and water content. They took snowpack and wetfall precipitation samples at 17 sites throughout the Colorado Front Range and Southern Wyoming. The 30-kilometer radius that received the greatest impact from the dust storm—about 85-km west of Denver, in the heart of the Fraser Experimental Forest (FEF)—was most extensively studied, and in the geographic center of their range of sites. Rhoades et al. compared samples of snow 25–35 cm below and above the dust-layer to dust-layer snow from all sites, as well as pre- and post-dust precipitation to precipitation during the dust event. They then compared the data in the 30-kilometer radius to the FEF precipitation and snowpack records from the past 17 years.
The concentration of anions and cations were analyzed using ion chromatography and an 18-minute isocratic method. Chromatography separates the components in a solution—in this case, water—by moving the solution through a medium in which different materials will move at different rates. In ion chromatography, the medium is a gel matrix with polar functional groups. The solution gets pushed through the gel by adding concentrations of similarly charged ions that repel the ions in the solution, forcing them to move forward. Sometimes the volume of charged ions necessary to push the solution ions forward is enough information to identify the element, but usually the separated ions get identified through conductivity or UV/visible light absorbance. The isocratic method is a form of ion chromatography in which the mobile phase—when charged ions are being added—is constant for the respective time of the process, in this case 18 minutes.
Using these techniques, Rhoades et al. discovered that dust event snowfall precipitation around the Fraser Experimental Forest (FEF) had 35, 9, 16 and 5-fold higher levels of Ca2+, Mg2+, Na+, and K+, respectively, than the pre- or post-event snowfalls. In other words, the two-day dust event from February 14–15 deposited as much calcium as half the annual average, and provided as much Mg2+, Na+, and K+  as during a typical snow-free month, when soil-derived cations typically peak in concentration.
The electrical conductivity (EC) in dust-free wetfall precipitation from FEF averaged 3.6 mS cm-1, while dust-event snowfall had an EC of 26.3 mS cm-1. Conductivity increases with carbonate minerals, dissolved salts, and dissolved ions. Distilled water, for instance, has almost no conductivity (and correspondingly a neutral pH of 7). EC is measured by two metal electrodes exactly 1 cm apart in the water (which is why the units are in micro-Seimens per centimeter), from which a constant voltage creates an electric current indicative of the ion content. The raw data of the electric current then gets standardized to a temperature of 25°C—since warmer water tends to be more conductive—and thus the current flow in amperes (I) gets converted to Seimens (S).
FEF snowfall typically lacks any acid neutralizing capacity (ANC), and therefore can’t buffer an influx of acids that would lower pH. Buffers are any molecules that attenuate the change in pH an influx of strong acids or bases would typically cause, either by providing a balance of weak acids and bases that will offset the contribution of new ions, or by bonding with them and neutralizing their charge. During the dust event, snowfall had an ANC of 198.7 meqL-1. The ANC is calculated as the difference between strong bases (Ca2+, Mg2+, Na+, K+, NH4+) and strong acid anions (NO3, Cl, SO42-), including bicarbonate and carbonate (HCO3 and CO32-), which are most responsible for neutralizing acids. Because of this influx of acid neutralization, pH in the dust event snowfall increased from 5.4 to 8.2. This conclusion is reiterated in the snowpack cores as well, in which pre- and post-dust snow for all sites had an average 16-fold higher concentration of H+ than dust-layer snow.
To the researchers’ surprise, these differences of the dust-laden snow in composition did not change the composition of the non-dust layers neither before nor after the event. Nor did the influx of bases and carbonates change the composition of rivers, snowmelt streams or glacial lakes in chemical compositions or pH. The dust-layer snow did differentiate by elevation, however, and Rhoades et al. suggest further research to see if snowmelt and soil near the treeline has changed more that that from lower elevations. Treeline snowpack (3350 m) had a pH 0.6 units higher both in the dust-layer and post-event snow, as well as 40-fold higher ANC and double the calcium than the lowest sample sites tested (2750 m). This is most likely due to trees acting as a barrier to dust reaching the ground in forested areas, while high elevations are more exposed. Whether this elevation difference has ecological consequences, especially in regards to snowmelt rates, demands further research.
Larger dust storms have continued to dominate the western landscape since the 2006 event. Twelve dust-on-snow events from 20082009 caused record streamflow rates earlier in the season, with snowmelt 4050 days faster than the non-dust predicted rate. The 20092010 season estimated eight dust events, with the effects yet to be published, but will certainly reflect the same patterns. As dust flux continues to escalate, non-profits and research groups are beginning to measure the impact of dust-on-snow, and the National Foundation of Science (NFS) has been funding researchers to continue investigating the source of the dust and the dust’s influence on alpine ecology. The data from Rhoades et al. will help propel the conclusions of future findings, and hopefully shed light on these new patterns.
Other sources:
Dybas, C. Dust-on-snow: On spring winds, something wicked this way comes. The National Science Foundation [database online]. Arlington, Virginia, 2010. http://www.nsf.gov/discoveries/disc_summ.jsp?cntn_id=116707.