Snow Specific Surface Area Research Articles

A Dynamic Model To Study the Exchange of Gas-Phase Persistent Organic Pollutants between Air and a Seasonal Snowpack

An arctic snow model was developed to predict the exchange of vapor-phase persistent organic pollutants between the atmosphere and the snowpack over a winter season. Using modeled meteorological data simulating conditions in the Canadian High Arctic, a single-layer snowpack was created on the basis of the precipitation rate, with the snow depth, snow specific surface area, density, and total surface area (TSA) evolving throughout the annual time series. TSA, an important parameter affecting the vapor-sorbed quantity of chemicals in snow, was within a factor of 5 of measured values. Net fluxes for fluorene, phenanthrene, PCB-28 and -52, and alpha- and gamma-HCH (hexachlorocyclohexane) were predicted on the basis of their wet deposition (snowfall) and vapor exchange between the snow and atmosphere. Chemical fluxes were found to be highly dynamic, whereby deposition was rapidly offset by evaporative loss due to snow settling (i.e., changes in TSA). Differences in chemical behavior over the course of the season (i.e., fluxes, snow concentrations) were largely dependent on the snow/air partition coefficients (K(sa)). Chemicals with relatively higher K(sa) values such as alpha- and gamma-HCH were efficiently retained within the snowpack until later in the season compared to fluorene, phenathrene, and PCB-28 and -52. Average snow and air concentrations predicted by the model were within a factor of 5-10 of values measured from arctic field studies, but tended to be overpredicted for those chemicals with higher K(sa) values (i.e., HCHs). Sensitivity analysis revealed that snow concentrations were more strongly influenced by K(sa) than either inclusion of wind ventilation of the snowpack or other changes in physical parameters. Importantly, the model highlighted the relevance of the arctic snowpack in influencing atmospheric concentrations. For the HCHs, evaporative fluxes from snow were more pronounced in April and May, toward the end of the winter, providing evidence that the snowpack plays an important role in influencing the seasonal increase in air concentrations for these compounds at this time of year.

Measuring specific surface area of snow by near-infrared photography

AbstractThe specific surface area (SSA) is considered an essential microstructural parameter for the characterization of snow. Photography in the near-infrared (NIR) spectrum is sensitive to the SSA. We calculated the snow reflectance from calibrated NIR images of snow-pit walls and measured the SSA of samples obtained at the same locations. This new method is used to map the snow stratigraphy. The correlation between reflectance and SSA was found to be 90%. Calibrated NIR photography allows quantitative determination of SSA and its spatial variation in a snow profile in two dimensions within an uncertainty of 15%. In an image covering 0.5–1.0 m2, even layers of 1mm thickness can be documented and measured. Spatial maps of SSA are an important tool in initializing and validating physical and chemical models of the snowpack.

A mean field model of the decrease of the specific surface area of dry snow during isothermal metamorphism

The surface area of snow that is accessible to gases is an essential parameter for quantifying the exchange of trace gases between the snowpack and the atmosphere and is called the specific surface area (SSA). Snow SSA decreases during metamorphism, but this is not described in current snow models owing to the complexity of the physics and geometry of snow. In this paper, we test whether it is possible to model snow SSA changes during isothermal metamorphism without accounting for all the complexity of the three‐dimensional (3‐D) structure of real snow. We have developed a mean field model of snow metamorphism under isothermal conditions, grounded in the theoretical framework of transient Ostwald ripening and representing snow as a distribution of spherical particles. Analytical expressions of the growth rates of these spheres are obtained, and the evolution of two measurable parameters that characterize snow geometry, the SSA and the distribution of radii of curvature (DRC), are simulated and compared to experimental data obtained by X‐ray tomography. The qualitative effects of temperature, snow density, and the condensation coefficient on the rate of SSA decrease are examined. The model predicts very well the rate of evolution of the particle size distribution, which validates our physical description of isothermal metamorphism. In particular, we find that vapor phase diffusion is rate limiting. However, the calculation of the SSA from the DRC appears delicate and evidences too crude approximations in our description of the 3‐D geometry of snow. Finally, it is stressed that the initial DRC can greatly influence the rate of SSA decrease, while experimental measurements of the rate of SSA decrease suggest that all snow types evolve in a similar way. It is thus proposed that most natural fresh snows have similar DRCs.

Grain growth theories and the isothermal evolution of the specific surface area of snow

Quantifying the specific surface area (SSA) of snow and its variation during metamorphism is essential to understand and model the exchange of reactive gases between the snowpack and the atmosphere. Isothermal experiments were conducted in a cold room to measure the decay rate of the SSA of four snow samples kept in closed systems at −15 °C. In all cases, a logarithmic law of the form SSA=B−A ln(t+Δt) fits the SSA decrease very well, where A, B and Δt are adjustable parameters. B is closely related to the initial SSA of the snow and A describes the SSA decay rate. These and previous data suggest the existence of a linear relationship between A and B so that it may be possible to predict the decay rate of snow SSA from its initial value. The possibility that grain coarsening theories could explain these observations was investigated. The logarithmic equation was shown to be an approximation of a more general equation, that describes the time evolution of the mean grain radius R in most grain coarsening theories, such as Ostwald ripening: R̄n−R̄0n=Kt. R0¯ is the initial mean grain radius, R̄ is the mean grain radius, n and K are the growth exponent and the growth rate, respectively. Values of n between 2.8 and 5.0 are found. It is concluded that snow metamorphism and Ostwald ripening processes are governed by similar rules. Ostwald ripening theories predict that a steady-state regime is reached after a transient stage, but our results suggest that the steady-state regime is not reached after a few months of isothermal snow metamorphism. This last feature makes is difficult to predict the rate of decrease of snow SSA using the theory of Ostwald ripening.

Investigating the occurrence of persistent organic pollutants (POPs) in the arctic: their atmospheric behaviour and interaction with the seasonal snow pack

POPs in the Arctic are the focus of international concern due to their occurrence and accumulation in Arctic food webs. This paper presents an overview of the major pathways into the Arctic and details contemporary studies that have focused on the occurrence and transfer of POPs between the major Arctic compartments, highlighting areas where there is a lack of quantitative information. The behaviour of these chemicals in the Arctic atmosphere is scrutinised with respect to long-term trends and seasonal behaviour. Subtle differences between the PCBs and OC pesticides are demonstrated and related to sources outside of the Arctic as well as environmental processes within the Arctic. Unlike temperate regions, contaminant fate is strongly affected by the presence of snow and ice. A description of the high Arctic snow pack is given and the physical characteristics that determine chemical fate, namely the specific surface area of snow and wind driven ventilation, are discussed. Using a well-characterised fresh snow event observed at Alert (Canadian high Arctic) [Atmos. Environ. 36(2002) 2767] the flux of γ-HCH out of the snow is predicted following snow ageing. Under conditions of wind (10 m/s) it is estimated that ≈75% of the chemical may be re-emitted to the atmosphere within 24 h following snowfall, compared with just ≈5% under conditions of no wind. The implications of this are raised and areas of further research suggested.

Rate of decay of specific surface area of snow during isothermal experiments and morphological changes studied by scanning electron microscopy

The quantification of the specific surface area (SSA) of snow crystals and of its variation during metamorphism are essential to understand and model the exchange of reactive gases between the snowpack and the atmosphere. Therefore, the decay rate of SSA of five fresh snow samples was studied in the laboratory at –4, –10, and –15°C under isothermal conditions in closed systems. The time-evolution of the snow SSA can in all cases be very well described by an empirical law of the form, SSA = – A log(t + Δt) + B, where A, B, and Δt are adjustable parameters. B seems to be closely related to the initial SSA of the snow, and A describes the SSA decay rate. Our preliminary findings at –15°C suggest that a linear relationship exists between A and B, so that it may be possible to predict the decay rate of snow SSA from its initial value. For the first time, images obtained from scanning electron microscopy show that crystal rounding of snow is the main process taking place during isothermal metamorphism. New grain boundaries also form. More surprising, however, was the formation of new basal, prismatic, and pyramidal crystal faces, sometimes with very sharp angles, especially at –15°C. The growth of facets with sharp angles is not fully explained by current theories of snow metamorphism and has not been observed before. PACS Nos.: 68.35Md, 68.37Hk, 81.20Ev, 81.05Rm

Specific surface area of snow samples determined by CH4 adsorption at 77 K and estimated by optical microscopy and scanning electron microscopy.

Snow is a divided medium that can adsorb atmospheric trace gases. Evaluating the impact of the snow cover on atmospheric chemistry therefore requires the knowledge of the specific surface area (SSA) of snow. This paper compares the results of three methods used to measure or estimate the SSA of four snow samples: CH4 adsorption at 77 K, optical microscopy (OM), and scanning electron microscopy (SEM, used only on two samples). Within error bars, CH4 adsorption and OM yield similar results on three of the four snow samples. Values for the 4th sample are within a factor of 2. For both samples where CH4 adsorption, OM, and SEM are used, all three methods yield similar results, but CH4 adsorption always has a better accuracy and a much better precision. Thus, despite its ease of use, estimates from OM images are often not accurate enough to monitor the evolution of snow SSA. The main sources of error in the OM method are the difficulty to determine snow crystal thicknesses and to take into account the topography of the snow crystal surface. The combination of CH4 adsorption and OM or SEM can provide useful information on the evolution of both the SSA and the shape of snow crystals. This will be useful to evaluate the respective contributions of adsorption/desorption and sublimation/condensation processes to the impact of the snow cover on atmospheric chemistry.

The specific surface area of fresh dendritic snow crystals

The surface area to mass ratio or specific surface area (SSA) is an often neglected characteristic of the snowpack that varies substantially with time, and with the shape of the individual snow crystal for fresh snow. The SSA for the dendritic shape of snow crystals was computed using a series of images photographed by W. A. Bentley. The specific images were dendritic crystals (P1d, P1e, P1f) and crystals that take a partial dendritic form and have ends or extensions (P2a, P2b, P2d, P2e, P2f, P2g) according to the Magono and Lee snow crystal classification. Image analysis, using known geometric relationships between length and width, and particle size distributions, examined the spatial properties of 50 sample snow crystals. Probability distribution functions were derived for SSA and these compared well with measured and other computed estimates of fresh snow SSA. For the non-rimed condition, the average SSA was 0.182 m 2 /g with a range from 0.09 to 0.33 m 2 /g. The presence of rime is discussed, and depending on the shape of the rime particles and the degree of surface coverage, the SSA can be doubled (20% coverage for needle or plate shaped rime). Fractal analysis was performed to determine various geometric relationships that characterize the dendritic form of snow crystal.

Modelling the fate of non-polar organic chemicals during the melting of an Arctic snowpack

Recent advances in the understanding of the interactions between non-polar organic chemicals and frozen water have revealed the immense importance of the ice-air interface and the possibility of quantitatively treating the adsorption process on the ice surface in terms of chemical-specific interfacial partition coefficients and the snow specific surface area. A simple fugacity-based chemical fate model is used to describe quantitatively the behaviour of selected non-polar organic contaminants during snowpack melting, namely atmosphere-snow exchange, redistribution within the snowpack and draining with meltwater. The simulations are evaluated using field data on snowpack and meltwater concentrations of these chemicals measured in a small watershed in the Canadian Arctic during the melting period of 1993. The model reproduced the observed preferential elution of hexachlorocyclohexanes in the first meltwater fractions, and the relative retention of polychlorinated biphenyls within the snowpack. The model calculations indicate that the specific surface area of the ice crystals and the air-ice and air-water partition coefficients of the chemical are key parameters controlling the extent and timing of chemical loss with the meltwater. For particle-sorptive substances, the fate of particlcs during snowmelt must also be considered. Uncertainty in describing interfacial partitioning and the behaviour of particles during melting presently limits the capabilities of models to simulate and ultimately predict meltwater concentrations of non-polar organic contaminants.

Measurement of the Specific Surface Area of Snow with the Nitrogen Adsorption Technique

Few data exist for the surface area of snow despite its importance for modeling wet deposition and migration of reversibly deposited contaminants in snow. A method for determining the surface area of snow is described that uses a commercial nitrogen adsorption instrument (Gemini III 2375, Micromeritics Instruments Inc.). The method uses a sample vial containing snow and a reference vial containing an equal amount of snow that has been melted and refrozen in order to minimize its surface area. The basic quantity measured is the difference in volumes of nitrogen delivered to the sample and reference vials. This volume difference must be corrected for the free space difference in the vials before the adsorbed volume of nitrogen can be inferred. Two methods for obtaining this correction are discussed, measured, and estimated, and the results of BET analysis are presented for both types of correction. Fresh snow samples collected in southern Ontario exhibit type II isotherms with moderate to small BET constant...