Atmos. Chem. Phys., 14, 1587–1633, 2014 www.atmos-chem-phys.net/14/1587/2014/ doi:10.5194/acp-14-1587-2014 © Author(s) 2014. CC Attribution 3.0 License. Atmospheric Chemistry and Physics O pen A ccess A review of air–ice chemical and physical interactions (AICI): liquids, quasi-liquids, and solids in snow T. Bartels-Rausch1, H.-W. Jacobi2,3, T. F. Kahan4, J. L. Thomas5,6, E. S. Thomson7, J. P. D. Abbatt8, M. Ammann1, J. R. Blackford9, H. Bluhm10, C. Boxe11,12, F. Domine13, M. M. Frey14, I. Gladich15, M. I. Guzmán16, D. Heger17,18, Th. Huthwelker19, P. Klán17,18, W. F. Kuhs20, M. H.Kuo21, S. Maus22, S. G. Moussa21, V. F. McNeill21, J. T. Newberg23, J. B. C. Pettersson7, M. Roeselová15, and J. R. Sodeau24 1Laboratory of Radio and Environmental Chemistry, Paul Scherrer Institute, 5232 Villigen PSI, Switzerland 2CNRS, Laboratoire de Glaciologie et Géophysique de l’Environnement (UMR5183), 38041 Grenoble, France 3Univ. Grenoble Alpes, LGGE (UMR5183), 38041 Grenoble, France 4Department of Chemistry, Syracuse University, 1-014 Center for Science and Technology, Syracuse, New York, USA 5UPMC Univ. Paris 06, UMR8190, CNRS/INSU – Univ. Versailles St.-Quentin, LATMOS-IPSL, Paris, France 6University of California, Los Angeles, Department of Atmospheric and Oceanic Sciences, Los Angeles, CA 90095, USA 7Department of Chemistry and Molecular Biology, Atmospheric Science, University of Gothenburg, 41296, Gothenburg, Sweden 8Department of Chemistry, University of Toronto, 80 St. George St., Toronto, ON, M5S 3H6, Canada 9Institute for Materials and Processes, School of Engineering, King’s Buildings, The University of Edinburgh, EH9 3JL, UK 10Lawrence Berkeley National Laboratory, Chemical Sciences Division, Berkeley, CA 94720, USA 11Department of Chemistry and Environmental Science, Medgar Evers College – City University of New York, Brooklyn, NY 11235, USA 12City University of New York, Graduate Center, Department of Chemistry, Department of Earth & Environmental Sciences, Manhattan, NY 10016, USA 13Takuvik Joint International Laboratory, Université Laval and CNRS, and Department of Chemistry, 1045 avenue de la médecine, Québec, QC, G1V 0A6, Canada 14British Antarctic Survey, Natural Environment Research Council, Cambridge, UK 15Institute of Organic Chemistry and Biochemistry, Academy of Sciences of the Czech Republic, Flemingovo nam. 2, 16610 Prague 6, Czech Republic 16Department of Chemistry, University of Kentucky, Lexington, KY 40506-0055, USA 17Department of Chemistry, Faculty of Science, Masaryk University, Kamenice 5/A, 62500 Brno, Czech Republic 18RECETOX, Faculty of Science, Masaryk University, Kamenice 3, 62500 Brno, Czech Republic 19SLS Swiss Light Source, Paul Scherrer Institute, 5232 Villigen PSI, Switzerland 20GZG Abt. Kristallographie, Universität Göttingen, Goldschmidtstr. 1, 37077 Göttingen, Germany 21Department of Chemical Engineering, Columbia University, New York, NY, USA 22Geophysical Institute, University Bergen, 5007 Bergen, Norway 23Department of Chemistry and Biochemistry, University of Delaware, Newark, Delaware 19716, USA 24Department of Chemistry and Environmental Research Institute, University College Cork, Cork, Ireland Correspondence to: T. Bartels-Rausch (thorsten.bartels-rausch@psi.ch) Received: 28 September 2012 – Published in Atmos. Chem. Phys. Discuss.: 26 November 2012 Revised: 6 November 2013 – Accepted: 13 December 2013 – Published: 12 February 2014 Published by Copernicus Publications on behalf of the European Geosciences Union. 1588 T. Bartels-Rausch et al.: Air–ice chemical interactions Abstract. Snow in the environment acts as a host to rich chemistry and provides a matrix for physical exchange of contaminants within the ecosystem. The goal of this review is to summarise the current state of knowledge of physical processes and chemical reactivity in surface snow with rele- vance to polar regions. It focuses on a description of impu- rities in distinct compartments present in surface snow, such as snow crystals, grain boundaries, crystal surfaces, and liq- uid parts. It emphasises the microscopic description of the ice surface and its link with the environment. Distinct differ- ences between the disordered air–ice interface, often termed quasi-liquid layer, and a liquid phase are highlighted. The re- activity in these different compartments of surface snow is discussed using many experimental studies, simulations, and selected snow models from the molecular to the macro-scale. Although new experimental techniques have extended our knowledge of the surface properties of ice and their impact on some single reactions and processes, others occurring on, at or within snow grains remain unquantified. The presence of liquid or liquid-like compartments either due to the forma- tion of brine or disorder at surfaces of snow crystals below the freezing point may strongly modify reaction rates. There- fore, future experiments should include a detailed character- isation of the surface properties of the ice matrices. A further point that remains largely unresolved is the distribution of impurities between the different domains of the condensed phase inside the snowpack, i.e. in the bulk solid, in liquid at the surface or trapped in confined pockets within or between grains, or at the surface. While surface-sensitive laboratory techniques may in the future help to resolve this point for equilibrium conditions, additional uncertainty for the envi- ronmental snowpack may be caused by the highly dynamic nature of the snowpack due to the fast metamorphism occur- ring under certain environmental conditions. Due to these gaps in knowledge the first snow chemistry models have attempted to reproduce certain processes like the long-term incorporation of volatile compounds in snow and firn or the release of reactive species from the snow- pack. Although so far none of the models offers a coupled approach of physical and chemical processes or a detailed representation of the different compartments, they have suc- cessfully been used to reproduce some field experiments. A fully coupled snow chemistry and physics model remains to be developed. 1 Introduction Ice and snow, as present in Earth’s cryosphere, are reactive media (Takenaka et al., 1992; Klán and Holoubek, 2002; Abbatt, 2003) that play an integral role in transferring trace gases to and from the atmosphere (Domine and Shepson, 2002). Surface snow can efficiently scavenge and accumulate compounds of environmental concern (Wania et al., 1998; Dommergue et al., 2003). At the same time, snow is a highly dynamic multiphase medium. Changes in snow structure and properties critically affect both physical processes and chem- ical reactivity (Domine et al., 2008). Better understanding underlying processes and their relation to the Earth system is of importance to environmental chemistry, atmospheric sci- ence, and cryospheric science, as detailed in recent reviews on the uptake of acidic trace gases to ice (Abbatt, 2003; Huth- welker et al., 2006), snow chemistry (Grannas et al., 2007b), halogen chemistry (Simpson et al., 2007; Abbatt et al., 2012), fate of organics (McNeill et al., 2012; Grannas et al., 2013), and mercury in snow (Steffen et al., 2008). 1.1 Importance of air–snow interactions The release of reactive compounds from the snowpack to the atmosphere is of importance for the composition and the ox- idative capacity of the atmospheric boundary layer in perma- nently or seasonally snow-covered regions, including the po- lar regions (Domine and Shepson, 2002). Strikingly, the de- pletion of ozone in air masses from the ground up to heights of several kilometres had already been observed in the 1980s at the Arctic coast (Oltmans et al., 1989) and is linked – at least in part – to processes in surface snow and ice (Simp- son et al., 2007; Abbatt et al., 2012; Pratt et al., 2013). Other substantial effects include the emission of trace gases from snowpacks. For example, in Antarctica NOx levels typical for urban conditions have been observed (e.g. Davis et al., 2001, 2004; Eisele et al., 2008; Frey et al., 2013). Snow can act as an important storage and transfer medium for pol- lutants from the atmosphere to aquatic environments or to the soil. Mercury and persistent organic pollutants are ex- amples of species that may accumulate in surface snow dur- ing winter and be released during snowmelt (Wania et al., 1998; Lalonde et al., 2002). However, from a global perspec- tive the overall removal or transfer from the atmosphere to the soil and oceans is likely smaller than the depositional fluxes, because species like nitrogen oxides (Grannas et al., 2007b) and mercury (Durnford and Dastoor, 2011) are par- tially re-emitted to the atmosphere due to chemical processes in the snow. For other species such as persistent organic pol- lutants, the transfer to the soil or to the oceans may exceed the initial deposition, as those species may be formed by post- depositional processes in surface snow (Grannas et al., 2013). To fully assess the atmosphere-to-soil or -ocean fluxes from a global perspective, the post-depositional fate of pollutants and impact of chemistry in snow need to be understood. In addition nitrate and other species have been measured in firn and ice cores, giving detailed concentration profiles that may be related to past atmospheric composition and climate (e.g. Fuhrer et al., 1993; Anklin and Bales, 1997; Legrand and Mayewski, 1997; Sommer et al., 2000; Roth- lisberger et al., 2001; Frey et al., 2006). Chemical reactions and physical exchange processes have the capacity to signif- icantly modify the amounts and location of impurities stored Atmos. Chem. Phys., 14, 1587–1633, 2014 www.atmos-chem-phys.net/14/1587/2014/ T. Bartels-Rausch et al.: Air–ice chemical interactions 1589 within the snow, making the interpretation of concentration profiles impossible without the application of models (Neftel et al., 1995; Wolff, 1995). 1.2 Impurity compartments The major source of impurities in surface snow is the atmo- sphere. Riming, the freezing of aqueous droplets, leads to the retention of soluble atmospheric trace gases (e.g. SO2, H2O2, NH3, HNO3, CH2O, CHOOH, HCl, Hg(II)) into the ice par- ticles later found in snow samples (Snider and Huang, 1998; Long et al., 2010; Douglas et al., 2011). Thus rimed snow and ice are usually more concentrated with impurities than other types of deposited snow (Mitchell and Lamb, 1989; Poulida et al., 1998). Volatile atmospheric trace gases can also be taken up directly from the gas phase, likely affect- ing surface snow composition strongly (Abbatt, 2003; Huth- welker et al., 2006; Grannas et al., 2007b; Steffen et al., 2008). These adsorbed species may react rapidly to changes in the atmospheric environment, while entrapped species ex- perience more solid-state-like processes. Figure 1 illustrates the different locations that may host impurities in surface snow, such as the ice crystals with an air–ice interface to- wards the gas-filled pore space and with ice–ice interfaces at grain boundaries and triple junctions (so-called veins) and quadruple points (nodes) between ice crystals. If impurities are concentrated, colligative effects result; for example dis- solution of impurities may form brine and introduce liquid into the system or solids may precipitate (Fig. 1). Brines are impurity-rich liquid solutions that coexist with the solid ice phase in thermodynamic equilibrium and recently ap- proaches have been developed to predict the impurity con- centration in brine (Sect. 2.1). Clearly, the chemical and physical environment that impu- rities experience varies widely between individual compart- ments, as for example evident from the diffusivity of water molecules in each compartment (Sect. 4.1). How do impu- rities distribute between the individual compartments in lab- oratory samples and the field (Sect. 2)? How do exchange processes of trace gases between the atmosphere and each of these individual compartments differ? Is reversible surface adsorption (Sect. 4.3), solid-state diffusion (Sect. 4.2), or up- take to the liquid fraction in snow (Sect. 4.3.5) the dominant mechanism for specific experimental conditions, and which mechanism describes field observations best (Sect. 4.4 and Sect. 4.2.3)? Similar questions about the dominating pro- cess arise in the interpretation of chemical reactivity in ice and snow samples: how and why does the reactivity differ at ice surfaces (Sect. 5.5) from that in the bulk ice (Sect. 5.2) – such as in liquid inclusions (Sects. 5.1, 5.2, 5.3)? And, how well do models capture the complex snow chemistry and what are the limiting factors (Sect. 5.6)? The situation where bulk and surface reaction might occur is very simi- lar to other heterogeneous systems of atmospheric relevance, such as aerosols, where strategies have been developed to differentiate between the contributions of heterogeneous vs. bulk reactivity (Kolb et al., 2010; Shiraiwa et al., 2010). Next to adsorbed and dissolved impurities, snow also con- tains trapped aerosol particles. These may originate from ice condensation nuclei, from scavenging during precipitation, or from deposition from air that was wind-pumped through the porous snow (see Domine et al., 2004; Beine et al., 2011; Voisin et al., 2012; Domine et al., 2013, and refer- ences therein). Recently it was shown that reactions within such aerosols in surface snow can be the main source of trace gas emissions to the overlying atmosphere (Abbatt, 2013; Pratt et al., 2013), and it has been proposed that the main ab- sorbers of solar irradiation, driving photochemistry in snow, are in many places located in aerosol particles trapped in snow (Beine et al., 2011; Voisin et al., 2012). The reactivity of solid aerosol deposits is not further discussed in this re- view. However, Koop et al. (2000) noted that sea salt deposit may remain in liquid phase for typical Arctic temperatures, and reactivity in such liquid reservoirs is discussed through- out the review. 1.3 Snow dynamics Temperature gradient conditions, for instance when the snowpack is warmed at its surface during the day from sun or radiatively cooled at night, are common in the environ- ment. Temperature gradient changes can occur over a range of timescales: from fractions of seconds (Szabo and Schnee- beli, 2007) to diurnally and seasonally. Field measurements have shown such alternating temperature gradients in the top 0.2 m of alpine and arctic snowpacks (Birkeland et al., 1998; Dadic et al., 2008). Under the influence of these gradients, morphological changes of the surface snow occur quickly (Fig. 2), and these changes of snow shape due to temperature and vapour gradients respond in complicated, subtle ways to changes in temperature and humidity (Arons and Colbeck, 1995; Schneebeli and Sokratov, 2004). Pinzer and Schnee- beli (2009a, b) studied snow metamorphism under alternat- ing temperature gradients (with 12 h periods) using X-ray- computed microtomography (XMT). They found that up to 60 % of the total ice mass was redistributed during the 12 h cycle. Such high water fluxes mean that ice sublimates and condenses with a characteristic residence time of just 2–3 days (Pinzer et al., 2012). An illustrative video of their ex- perimental observations of the metamorphism indicates that the mass fluxes are much higher than previously thought and the fate of impurities distributed within the snow is not clear (Pinzer et al., 2012). Further, freeze–thaw cycles that are common in mar- itime mountain regions can also occur in the Arctic (Meyer and Wania, 2008) and lead to a redistribution of impuri- ties (Eichler et al., 2001). How do impurities distribute be- tween the individual compartments during the freezing pro- cess (Sect. 2.5), and how can we explain the significant re- activity and unique reaction products observed during the www.atmos-chem-phys.net/14/1587/2014/ Atmos. Chem. Phys., 14, 1587–1633, 2014 1590 T. Bartels-Rausch et al.: Air–ice chemical interactions surface reaction reaction at grain boundaries surface adsorption precipitates and brine solid solution reactions in liquid inclusions Fig. 1. Illustration of the multiple domains in snow hosting impurities and reactions. The photo shows a ≈ 1 mm-wide picture of a thin section of alpine snow as seen under a polarised microscope. Ice crystals appear coloured, interstitial air greyish (courtesy of F. Riche and M. Schneebeli, copyright by WSL SLF Davos). The schemes illustrate impurities (red and blue spheres) and their location within the individual compartments in snow – in bulk ice (dark blue) and on its surface, interstitial air (white) and liquid brine (light blue). The disordered interface at the ice crystal’s surface and its potential heterogeneity given by hydration shells surrounding impurities are illustrated as grey-bluish and light-blue areas. On the left, locations where reactions occur are sketched (top to bottom): heterogeneous (photo)reactions, (bi-molecular) reactions in grain boundaries, (photo)reactions in liquid micro-inclusions. In the right panel the different compartments are illustrated: impurities at the disordered ice surface with varying hydration shell in their vicinity, ordered arrangement of impurities in the ice crystal as solid solution, and solid precipitates and liquid brine in grain boundaries and veins. freezing process (Sect. 5.1.1)? Pockets of liquid or liquid in grain boundaries can migrate under the influence of temper- ature gradients and promote transport of species at faster dif- fusional rates than within the solid lattice (Hoekstra and Os- terkamp, 1965). Such effects have been discussed for sea ice (Harrison, 1965; Weeks and Ackley, 1986), for surface snow (Meyer and Wania, 2008), and glacial ice (Rempel et al., 2001, 2002) where the transport of species is governed by a combination of gravitation forces, diffusion and tempera- ture gradients. How impurities respond to such strong rearrangements of the ice phase is not clear, but may be more important for their ultimate fate than their initial mode of incorporation. Consid- ering the dynamic character of the ice matrix, the location of impurities in surface snow is not necessarily reflective of the way they have initially been incorporated in fresh snow. Fur- ther, adsorbing species might be trapped by water molecules that grow the ice from the gas phase (Sect. 4.3.7), leading to an enhanced uptake and capacity to trap these gases. 1.4 Structure of the snow surface At surfaces, both internal and at the air–ice interface, the crystal structure of ice is necessarily modified because of the outer layer’s missing bonds and subsequent reconstruc- tions and relaxations of the surficial molecular layers to min- imise free energy. This is a well-established phenomenon in surface physics of ice (Frenkel, 1946; Henson and Robin- son, 2004; Henson et al., 2005; Hobbs, 2010) and other solid materials such as colloids (Alsayed et al., 2005), ceram- ics (Clarke, 1987), and metals (Frenken and van der Veen, 1985). Henson and Robinson (2004) have compiled studies of this phenomenon for different materials that span triple- point temperatures from 25 to 933 K, illustrating that surface disorder is a ubiquitous property of crystals (Fig. 3). Hen- son and Robinson (2004) also proposed a functional depen- dency (solid and dashed lines in Fig. 3). This relationship is however based on crude assumptions treating the surface disorder analogously to multi-layer adsorption; also, as the authors note, only some selected studies were included in the compilation, and particularly for ice considerable dis- agreement with many other studies exists. More recent ap- proaches to derive functional relationships and a complete discussion of experimental observations are given in Sect. 3.1 and Sect. 3.3. Such molecular disorder at the surface is frequently re- ferred to as a quasi-liquid or liquid-like layer. The use of these synonyms has provoked some controversy and con- fusion (Baker and Dash, 1996; Knight, 1996b, a; Domine et al., 2013). In this review, the terms surface disorder and disordered interface (DI) are used to stress that the molec- ular disorder is an inherent interfacial property of crystals. Atmos. Chem. Phys., 14, 1587–1633, 2014 www.atmos-chem-phys.net/14/1587/2014/ T. Bartels-Rausch et al.: Air–ice chemical interactions 1591 therefore influenced by the microstructure. More precisely, the more elementary ‘‘hand-to-hand’’ events are involved, i.e., the smaller the structure and pore sizes are, the higher the turnover rate is expected to be. Figure 2 shows this behavior. The mass turnover in our experiment s3 (Figure 2b) was very high, between 2.0 and 3.5 g m!3 s!1, which was not expected given the equi-temperature like morphology. Taking an average value of 2.5 g m!3 s!1, this rate corresponds to a total daily turnover of RTGM = 216 kg m !3 d!1 — divided into one upward movement and one backward movement. Taking into account the density of experiment s3 of 180 kg m!3, this means that during one half cycle of 12 h about 60% of the ice mass was relocated. A similar figure for ETM is difficult to measure directly, but an order of magnitude estimation for RETM can be obtained from recent observations of grain growth during ETM over one year [Kaempfer and Schneebeli, 2007]. Modeling the snow as a mono-disperse collection of spheres of the mean radius for each reported measurement and assuming that the density remains constant between two measurements, then an increase of radius from r1 to r2 implies a mass relocation per unit volume of Dm V ¼ ! 1! r31=r32 ! " rice; ð2Þ where ! is the ice fraction and rice the density of ice. Typical values at !1.9!C and ice fraction ! = 0.22 [Kaempfer and Schneebeli, 2007] are r1 = 110 mm and r2 = 125mm in 1000 h, yielding RETM = 1.8 % 10!5 kg m!3 s!1 or 1.5 kg m!3 per day. Different example values could lead to a variation of up to a factor of 5. However, compared to our results, this is more than two orders of magnitude lower. For chemical Figure 1. Morphological evolution for experiment s1. (a) Microscopy images of snow grains. Initially, the grains typically showed characteristics of fresh snow like dendritic extensions. After the application of sinusoidal temperature gradients with amplitude 89.4 K m!1, the shape was much coarser but did not show any sign of conventional temperature gradient metamorphism. (b) Three-dimensional evolution of the snow. The size of the shown volumes is 3.6 mm % 1.8 mm % 3.6 mm. One structural element has been marked yellow for orientation. The morphology of the structure evolves slowly, although more than four gradient cycles were between the images and considerable ice mass has been relocated. Table 1. Snow Characteristics and Experimental Conditionsa Name r (kg m!3) rT (K m!1) T (!C) Duration (d) SSAinit/SSAfinal (mm!1) I.Thinit (mm) I.Spinit (mm) s1 127 ±89.4 !10.5 14.6 43.0/25.7 68 301 s2 245 ±87.0 !2.3 14.6 23.2/19.7 132 262 s3 180 ±127.8 !2.3 15.0 37.1/28.0 82 239 aHere r, snow density; rT, amplitude of sine gradient; T , mean temperature in snow sample; SSAinit/SSAfinal, initial and final specific surface area; I.Thinit, initial mean ice thickness; and I.Spinit, initial mean ice separation (pore thickness). Figure 2. Temporal evolution of structural parameters and mass turnover of experiment s3. (a) The microstructure evolves significantly, as seen by the 25% decrease of specific surface area (SSA) and the almost 40% increase of ice thickness and 30% increase of pore thickness. The SSA of experiment s1 is shown in gray for comparison. (b) Mass turnover rate, averaged over the 6 h period between two mCT scans. The turnover rate is very high; it amounts to 60% of the total snow mass within one half cycle of the sine gradient (12 h). Note that in Figure 2b 6 data points are missing due to a failure of the z-position measurement. L23503 PINZER AND SCHNEEBELI: TEMPERATURE GRADIENT METAMORPHISM L23503 3 of 4 Fig. 2. Morphological evolution of snow during metamorphosis un- der the influence of a temperature gradient. Three-dimensional X- ray-computed microtomography reconstructions after 0, 108, 330, and 220 h are shown. Between each image, the sample was exposed to more than four sinusoidal temperature grad ent cycles on the or- der of 90 Km−1. The size of each image is 3.6 mm × 1.8 mm × 3.6 mm. One structural element has been marked yellow for ori- entation. Reprinted with permission from Pinzer and Schneebeli (2009b). Copyright (2009) by John Wiley and Sons. Note that we avoid the use of the term premelting, even though it is commonly used synonymously with surface dis- order in material science, because we believe it invites con- fusion with the formation of a true melt. A motivation of this review is to highlight clear differences and analogies in the behaviour of disordered ice surfaces to that of a liquid phase. Further, we address the question of how chemical pro- cesses (Sect. 5.5), physical exchange processes (Sect. 4.3.3), and diffusion (Sect. 4.1.2) are affected by increasing surface disorder. Central to answering these questions is the ability to quantify the disordered fraction of ice. Recent molecular dynamic simulations (Sect. 3.2), thermodynamic considera- tions (Sect. 3.1), and experimental observations (Sect. 3.3) of the properties and extent of the disorder are reviewed. As impurities are ubiquitous in environmental snow, this review addresses how impurities impact the disordered interface in great detail (Sects. 3.2.2 and 3.3.1). 2 Chemical impurities in multiphase snow The liquid nature of sulphuric acid solutions in triple junc- tions of Antarctic ice has been shown using Raman mi- croscopy by Fukazawa et al. (1998). Koop et al. (2000) con- cluded that sea salt particles remain liquid under environ- mentally relevant temperatures both as aerosol in the bound- for argon [1] were obtained in a calorimetric study of multilayer adsorption on graphite where the melting tem- perature is measured as a function of layer thickness. Data for neon [2] were obtained in the same way. Data for lead [8] were obtained by ion scattering in shadowing and blocking experiments. These data were originally reported as the number of disordered atoms per unit area. We have divided by a surface density of 0:577! 1015 Pb atom=cm2 to arrive at a thickness in layers. The same experimental technique was applied to aluminum [9], and these data were divided by a surface density of 0:5! 0:863! 1015 Al atom=cm2 in order to plot the thickness in layers. We multiply by 0.5 as the data were originally reported in bilayers. Data from another study on aluminum [10] using core electron photoemission are plotted as originally reported. Glancing angle x-ray scat- tering data for water [16] are plotted as reported, as are the ellipsometric data for biphenyl [6] and the x-ray reflectivity data for caprolactam [5] using Tt " 342:3 K. D ta for molecular oxygen in the fluid II regime obtain d by neutr n diffraction [3] are plotted as originally re- p rted. Finally, l w thickness data for m thane [4,29] are plotted as reported using Tt " 90:65 K. There are a number of other data sets for the systems compiled in Fig. 1. For the data on lead [8], there is good agreement with other data [7]. The situation for water is more complicated [11–20]. We have presented the data of Dosch t al. [16] as most representative due to the careful attention to equilibrium conditions in that experiment. The atomic force microscopy (AFM) data for water from Doppenschmidt and Butt [17] are also in good agreement. There is considerable disagreement with many of the other studies [30]. Finally, where one crystal face pre- sented a much thicker interfacial liquid than the others we have used the data for that face. In Fig. 2, the data are replotted as a function of the liquid activity, x. The pressure above a sample is the solid sublimation pressure, as has been confirmed directly for water [16]. At equilibrium, therefore, the activity is a fixed function of the temperature through the sublimation and vaporization free energy as x " Psol Pliq " exp ! #$!Gsub #!Gvap% RT " ; (1) where the liquid pressures are extrapolated to tempera- tures below Tt. The activity can thus be calculated di- rectly from the sublimation and vaporization pressures.FIG. 1. Compilation of quasiliquid data from the literature plotted as the thickness in layers as a function of the difference temperature from the triple point. Studies are referenced in the text and include Ar (open squares), Ne (open circles), Pb (open triangles), Al (open inverted triangles and open diamonds), CH4 (solid diamonds), O2 (solid inverted triangles), H2O (solid triangles), caprolactam (solid squares), and biphenyl (solid circles). The dashed lines are guides for the eye. FIG. 2. Same compilation of data as for Fig. 1, with the same labeling of systems, now plotted as a function of the activity through Eq. (2) and the parameters of Table I. The solid line is a calculation of the thickness as a function of activity from Eq. (6). The inset is simply an expan ed scale view. P H Y S I C A L R E V I E W L E T T E R S week ending18 JUNE 2004VOLUME 92, NUMBER 24 246107-2 246107-2 ig. 3. Empir cal correlation between the thick ess of t disor- der d interface and the therm dynamic activity for different solids. Open symbols de ote atomic, and filled symbols m lecular, sys- tems. Data include neon with a triple point of ∼ 25 K (open circles), aluminium (934 K, open bottom-down triangles), oxygen (54 K, filled bottom-down triangles), and biphenyl (filled circles, 343 K). The lines give simple functional dependences for each data set; see text for details. Reprinted with permission from Henson and Robin- son (2004). Copyright (2004) by the American Physical Society. ary layer as well as in the form of deposits on snow. This is caused by the low eutectic temperatures of constituent so- lutes, as illustrated in the phase diagram in Fig. 4. Next to ice and to liquid solutions, solid precipitates might occur in envi- ronmental snow samples, when the solubility limit of solutes is reached (Thomas and Dieckmann, 2009). A noteworthy environmental signature of solutes and precipitates in such multiphase frozen systems are ozone depletion events. The release of bromine, acting as a catalyst for the destruction of tropospheric ozone, from surface snow has been outlined in recent years (Simpson et al., 2007; Abbatt et al., 2012). The bromine emissions are suggested to be a consequence of bro- mide precipitation at lower temperatures than chloride and may be enhanced (bromine explosion) by a reduced buffer- ing capacity of brine in salty snow due to calcite precipitation (Sander et al., 2006). In the case of precipitation of calcium as ikaite (CaCO3 · 6H2O), supported by recent observations, this effect is not expected (Dieckmann et al., 2008; Morin et al., 2008). Recent measurements of pH changes at the sur- face of freezing sea salt solutions suggest that buffering is www.atmos-chem-phys.net/14/1587/2014/ Atmos. Chem. Phys., 14, 1587–1633, 2014 1592 T. Bartels-Rausch et al.: Air–ice chemical interactions Brine Te m pe ra tu re Composition Ice + Brine Salt + Brine Ice + Salt Salt + H2OE L S Caption: An example of an equilibrium phase diagram for a binary solution comprised of two components, water and a typical soluble mineral salt. The lines separate regions of different phases. The liquidous (L) separates the region in which the system is completely liquid, with salt completely dissolved in liquid water forming a brine, from a region in which solid and liquid coexist. Likewise, the solidous (S) separates the latter region from the region where all of the material is solid. These two lines intersect at the eutectic point E. At salt concentrations above the eutectic water may be found in liquid brine, ice, or molecularly incorporated into salt crystals (salt+H2O). The ability of ice to exclude impurities as discussed in \ref{sec:} largely prevents the reverse case, which is therefore not depicted but would be included in a generalized binary phase diagram. Fig. 4. An example of an equilibrium phase diagram for a binary solution comprised of two components, water and a typical soluble mineral salt. The lines separate regions of different phases. The liq- uidus (L) separates the region in which the system is completely liquid, with salt completely dissolved in liquid water forming a brine, from a region in which solid and liquid coexist. Likewise, the solidus (S) separates the latter region from the region where all of the material is solid. These two lines intersect at the eutectic point E. At salt concentrations above the eutectic water may be found in liquid brine, ice, or molecularly incorporated into salt crystals (salt+H2O). maintained in the brine layer in contact with the atmosphere (Wren and Donaldson, 2012a). Recent research has focused on detecting and predicting the presence and composition of solutes in multiphase snow. How solutes distribute in snow samples has received partic- ular attention. They might be incorporated into the ice crys- tal, in liquid inclusions within bulk ice, or remain at ice sur- faces or in grain boundaries (Hobbs, 2010). This is of inter- est particularly for the freezing process, given that in many laboratory-based studies samples prepared by freezing solu- tions were used. 2.1 Amount and concentration of brine The salinity of liquid in coexistence with ice adjusts to maintain thermodynamic phase equilibrium as illustrated in Fig. 4. Above eutectic temperatures Cho et al. (2002) con- firmed that liquid NaCl concentrations are well described by the phase diagram. In these NMR studies, they derived the brine concentration at various temperatures for samples in thermodynamic equilibrium, and developed a parameterisa- tion to calculate the amount of liquid in freezing systems. This approach was expanded by Kuo et al. (2011), who sub- stituted concentrations with activities and included two addi- tional solutal loss processes during freezing, (i) the solubility 7 Figure 1: Effect of decreasing the size of “micropockets” in solution as a function of temperature.4 The rate acceleration of reactions with decreasing temperature is, of course, counter-intuitive but it has been shown in numerous experiments performed on ice systems that the freeze- concentration effect can outweigh the Arrhenius-type influence. However, not all reactions in frozen hosts are accelerated and the specific criteria for an acceleration to occur are not only difficult to discern but the magnitude of any acceleration is not easily predicted. In 1966, Pincock and Kiovsky17 attempted to construct a model of the kinetics in order to explain the acceleration process. This work was subsequently expanded upon by Takenaka and Bandow18. Hence, in the case of a second order reaction proceeding without molar change throughout the reaction, the rate coefficient after thawing, k´, can be expressed as: k´ = Aexp(-Ea / RT). (Cmp / CT) (1) Decreasing Temperature Page 7 of 25 ACS Paragon Plus Environment Submitted to Accounts of Chemical Research 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 Fig. 5. Schematic representation of how the amount of liquid rep- resented by the blue area adjusts to temperature and how it may be trapped in veins forming micro-inclusions (O’Concubhair and Sodeau, 2013). Reprinted with permission from Takenaka et al. (1996). Copyright (1996) by the American Chemical Society. of solutes in the ice crystal and (ii) release to the gas phase. With this approach the total amount and concentration of the solution can be predicted during the freezing process of so- lutions containing salts or inorganic, volatile acids, as long as the freezing is not kinetic lly hindered. In a earlier NMR stu y the liquid fraction f natur l sea ice wit a ore com- plex chemical composition was well described based on the eutectic concentrations of salts (Richardson, 1976). The to- tal volume of liquid in coexistence is thus given and can be predicted by the amount of solutes (Fig. 4). Obviously, the volume of liquid in coexistence with ice drastically shrinks with decreasing temperatures, leading to highly concentrated liquid pockets in growing ice (Fig. 5), which provide a unique and highly reactive medium (Sect. 5.1.1). In addition to colligative solute effects, geometric con- straints can stabilise liquids in confined reservoirs, as theo- retically treated by Nye (1991). If inclusions of liquid are small, with radii in the nanometre range, the Gibbs–Thomson effect leads to a substantial melting point depression. The Gibbs–Thomson effect states that the melting point depres- sion (dT ) depends on the radius (r) of a particle, or inclu- sion: dT ∼ 1/r . Melting point depressions of 15–40 K have been found for water and solutes in nanometre-sized confine- ments (Aristov et al., 1997; Christenson, 2001). The theoret- ical treatment presented by Nye (1991) combines both the Gibbs–Thomson effect and solution theory. 2.2 Solubility limits The key to predicting the amount of liquid in cold, multi- phase systems is the precise knowledge of the amount of so- lutes. At low temperatures and high concentration, the sol- ubility limits of major solutes can be reached (Fig. 4). For example, from the six major ions present in seawater, sul- phate and sodium start to precipitate in the form of mirabilite (Na2SO4 · 10H2O) at 266 K, while sodium chloride precipi- tates at 250 K and calcium carbonate at 271 K (Thomas and Dieckmann, 2009). Such solubility limits, which may signif- icantly lower the salinity of brine, are not yet included in the models by Cho et al. (2002) and Kuo et al. (2011). If liquid brine and solid precipitates are separated, the distribution of Atmos. Chem. Phys., 14, 1587–1633, 2014 www.atmos-chem-phys.net/14/1587/2014/ T. Bartels-Rausch et al.: Air–ice chemical interactions 1593 ions in bulk snow will also change. Further, buffer capacity and pH may change upon precipitation of solutes, with direct consequences for air–ice chemical exchanges and the chem- ical reactivity in this compartment. 2.3 Below the eutectic composition Surprisingly and in contrast with expectations from the phase diagram, the NMR investigations by Cho et al. (2002), Guzmán et al. (2006) and Robinson et al. (2006) have re- vealed the existence of liquid NaCl and (NH4)2SO4 solu- tions well below the respective eutectic temperatures. Cho et al. (2002) argued that kinetic limitations leading to super- cooled solutions could not explain the observations, because the amount of liquid closely followed the temperature during warming periods toward the eutectic temperature. Freezing of emulsions that resemble water droplets in the atmosphere can be kinetically hindered so that a meta-stable liquid phase exists well below the eutectic temperature (Koop et al., 2000; Bogdan, 2010). Using surface-sensitive, synchrotron-based X-ray spectroscopy, Krˇepelová et al. (2010a) found no evi- dence for liquid on the surface of frozen solutions of NaCl below the eutectic. This technique probes the local, chemi- cal environment of the chloride anions and does not rely on assumptions based on bulk properties to derive conclusions about the physical state of the probe. One difference between the two studies is that Krˇepelová et al. (2010a) exclusively probed the upper surface, while Cho et al. (2002) also probed the bulk ice. We propose here that geometric constraints to the liquid volume kept in the micro-pockets might explain the observed freezing point depression (Sect. 2.1). As the size and number of these micro-pockets strongly depend on the impurity concentration and the freezing rate (Sect. 2.5), the extrapolation to environmental snow with its low impurity levels and different origin than these laboratory ice samples might be questioned. 2.4 Spread and agglomerates of impurities At grain boundaries and at the air–ice interface, liquid can spread in channels or form isolated agglomerates (Fig. 6). Whether the liquid is trapped in such isolated patches (also referred to as micro-pockets), or if it wets the grains possibly forming interconnected channels, depends on the surface en- ergies (Nye and Frank , 1973; Waff and Bulau, 1979). These surface energies are highly compound-specific. There have been a number of studies using low- temperature scanning electron microscopy (LTSEM) which have identified solid particles such as dust and salt impuri- ties like sodium chloride and sulphate, in snow and ice (e.g. Mulvaney et al., 1988; Cullen and Baker, 2001; Barnes et al., 2002; Baker et al., 2003; Obbard et al., 2003; Barnes and Wolff, 2004; Lomonaco et al., 2011; Spaulding et al., 2011). In preparation for the LTSEM, brine is solidified, direct infor- mation on the phase of the impurities in the sample are thus Fig. 6. Low temperature scanning electron microscopy image of ice particles containing salt. The lighter-grey regions along grain boundaries and as isolated patches are NaCl · 2H2O. The darker- grey areas show ice. Reprinted with permission from Blackford et al. (2007). lost. State-of-the-art LTSEM instruments have a resolution of 5 nm, which makes SEM ideal to study impurity agglomer- ates, rather than deriving molecular level information. Also, SEM is not suitable for lighter elements such as carbon or ni- trogen. The first direct observation of sulfuric acid, concen- trated in triple junctions and to a lesser extent at grain bound- aries, in Antarctic ice was made using an electron dispersive (EDS) X-ray detector analysis in LTSEM (Mulvaney et al., 1988). Since this first observation there have been a number of LTSEM studies of polar ice with EDS analysis of impu- rities indicating that impurities are preferentially located in disconnected regions along the grain boundaries (see Black- ford, 2007, for studies prior to 2007). Yet, a clear quantitative analysis based on statistically significant data is still lacking. More studies characterising the material structure of ice are needed to be able to interpret the results in an atmospheric context. Morphology and surface energy in the ice–NaCl sys- tem have been studied by LTSEM using ice particles doped with NaCl frozen in liquid nitrogen (Blackford et al., 2007). Figure 6 shows the shape of the ice and the liquid NaCl-rich brine phase after etching of the ice matrix. The brine concen- trates in vein structures where three or more grains meet and as inclusions in grain boundaries and at the air–ice interface that appear as small mushroom-like features in the image. These images are rich in detail and provide qualitative struc- tural information, which in itself is useful – as interconnected paths or isolated pockets of second-phase liquid can be de- tected. Most studies have focused on glacial ice, which is different from surface snow, making extrapolations of impurity distri- butions from those findings to snow questionable for a num- ber of reasons: (i) glacial ice is more dense than snow and www.atmos-chem-phys.net/14/1587/2014/ Atmos. Chem. Phys., 14, 1587–1633, 2014 1594 T. Bartels-Rausch et al.: Air–ice chemical interactions temperature gradients are reduced, resulting in less sinter- ing and ice mass transport; (ii) glacial ice is much older than surface snow and impurities have had more time to be trans- ported through the ice matrix. Recently, an extensive LTSEM microstructural characterisation of Antarctic firn has been made by Spaulding et al. (2011). They observed distinct im- purity patterns and claimed that the impurities control the mi- crostructure found at those locations. This finding would be important, if true, as it means that the chemical species in the ice influence the structure, and the chemical reactions them- selves are influenced by the structure. However, the relevant processes during densification and evolution of firn structure and their timescales were not studied, and the observed pat- terns might also simply be due to different impurity sources. X-ray-computed microtomography (XMT) allows in situ ob- servations of the arrangement of snow crystals in snowpack samples (e.g. Schneebeli and Sokratov, 2004; Heggli et al., 2011) and polar firn (Freitag et al., 2004) at 5–40 µm reso- lution. It has furthermore been claimed that brine networks have been imaged in sea ice by XMT (Obbard et al., 2009) and in natural marine ice–gas–hydrate mixtures (Murshed et al., 2008), which would make XMT a promising method to investigate the distribution of brine in porous snow samples. Yet, using XMT is difficult when liquid is present, due to the small difference in absorption of liquid solutions and of solid ice. Hence it seems likely that the liquid features documented by Obbard et al. (2009) and Murshed et al. (2008) are to a cer- tain degree sea salts that have precipitated at their imaging temperature of 263 K. A contrast agent may be added to en- hance the brine–ice absorption contrast when studying saline ice grown in the laboratory (Golden et al., 2007), although laboratory ice may differ from natural sea ice. In future stud- ies the problems with the ice–brine contrast may be over- come by means of phase-contrast-based XMT (McDonald et al., 2011) enabling the observation of brine and void air simultaneously. 2.5 Solutes during the freezing process The rejection of solutes from the growing ice crystal lat- tice during the freezing of salt solutions, as predicted by the phase diagram (Fig. 4), is generally a good approximation, because solubility of solutes in ice is low (Hobbs, 2010). Molecular dynamics simulations of ice growth from super- cooled salt solutions have revealed the microscopic mech- anism whereby ions and neutral species are excluded from growing ice (Vrbka and Jungwirth, 2005; Carignano et al., 2006, 2007; Bauerecker et al., 2008; Liyana-Arachchi et al., 2012b, a). However, a small fraction of impurities may be incorporated within grains. In this case it has been found that ions are more readily incorporated into the ice ma- trix than non-ionised solutes (Hobbs, 2010). Large organic molecules such as glucose (Halde, 1980), carboxymethyl cel- lulose (Smith and Pounder, 1960), and alkylbenzenes (Fries et al., 2007) can also be incorporated within ice samples dur- ing freezing of liquid solutions. The formation of a solid so- lution, which is most likely highly supersaturated, is consis- tent with the kinetic model of Domine and Thibert (1996). Recent spectroscopic investigations have started to assess whether solutes end up in the bulk (brine inclusions and grain boundaries) or at the air–ice interface during freezing. Wren and Donaldson (2011) reported only a minor increase in ni- trate concentration at the ice surface and suggested that ni- trate might be favourably incorporated into pockets or grain boundaries inside bulk ice at 258–268 K. A similar tendency of nitrite to be captured in liquid reservoirs inside growing ice was suggested earlier (Takenaka et al., 1996). Using surface- sensitive spectroscopy Krˇepelová et al. (2010a) showed that frozen solutions of NaCl above the eutectic exhibited a com- position on the ice surface consistent with the phase diagram of the bulk solution. This is in agreement with earlier work by Döppenschmidt and Butt (2000) where solid NaCl crystals were identified at the ice surface at temperatures below the eutectic using AFM. Wren and Donaldson (2011) suggested that the preference to be trapped in pockets is a compound- specific effect. Further, Cheng et al. (2010) have shown that the presence of electrolytes can trigger the occurrence of ran- dom inclusions at high concentrations, whereas at lower con- centrations solutions tend to freeze and thereby form con- nected channels. Next to concentrations, also the freezing rates, which have a large effect on the incorporation of so- lutes (see below), might have been different in both experi- ments and also as compared to natural snow. Certainly, more studies are needed to address the environmental significance of these observations. The selective incorporation of ions into the ice matrix can lead to the generation of a charge imbalance at the freez- ing front (Workman and Reynolds, 1950). The charge im- balance creates a large electrical potential, when the product of the growth rate and electrolyte concentration at the freez- ing front exceeds a critical value that depends on pH (Bron- shteyn and Chernov, 1991; Sola and Corti, 1993). Workman and Reynolds (1950) found that the potential is larger for di- luted solutions and report potentials of up to 200 V, for solu- tions of 10−5 M. The potential is a function of the time, freez- ing rate, concentration of salt(s) as well as other solutes and crystal orientation. In follow-up studies (Lodge et al., 1956; Cobb and Gross, 1969; Murphy, 1970), the magnitudes of the freezing potentials of identical solutions were scattered be- cause these factors were not kept constant. Measuring freez- ing potentials across the interface between single crystals and electrolyte solutions significantly improved reproducibility (Wilson and Haymet, 2008). Even though the absolute val- ues of freezing potentials are poorly reproduced due to the technical difficulties, the phenomenon uncovers important micro-structural behaviour during freezing. A freezing po- tential originates from unequal distribution coefficients be- tween the solution and the ice. Thus its measurement may be one of the few options of how to access the fraction of ions incorporated into the ice lattice. Overall, the effects of Atmos. Chem. Phys., 14, 1587–1633, 2014 www.atmos-chem-phys.net/14/1587/2014/ T. Bartels-Rausch et al.: Air–ice chemical interactions 1595 freezing potential may be of importance whenever the distri- bution coefficients of cations and anions are not equal, which is expected to be the most common case for freezing of envi- ronmental solutions. 2.6 Modelling liquids in snow Physical snow models solve the energy budget of the snow- pack and have been used to simulate the amount and redis- tribution of liquid in snowpacks exposed to temperature cy- cles. To understand and predict the distribution of impurities in snow, predicting the drainage of water through the snow- pack is of importance, because these movements of the liq- uid phase can redistribute solutes (Eichler et al., 2001). Bulk snowpack models treat the liquid water content as a bulk pa- rameter, while in 1-D models different layers can have dif- ferent capacities to store liquid water. Typically, a snow layer can retain up to 10 % of its mass in the form of liquid wa- ter before it drains to deeper layers due to gravitational flow (Brun et al., 1992). In the most complex 1-D snow models existing today the vertical transport of liquid in the snow is simulated using a bucket-like approach, where each snow layer is filled up with liquid water up to its maximum reten- tion capacity before excessive liquid is drained to the next layer below (Brun et al., 1992; Bartelt and Lehning, 2002). This is certainly an oversimplification since water movement in the snow can also occur under non-saturated conditions, while capillary barriers and effects can limit or stop the liq- uid water flow. Recent attempts have been made to improve the simulation of water movement in the snowpack based on established models for the calculation of water flow through soils (e.g. Hirashima et al., 2010). Nevertheless, the simu- lation of liquid water still requires attention in the future. So far, no attempts have been made to model the impact of liquid water on the redistribution of impurities inside the snowpack. 2.7 Conclusions about the multiphase structure The location and chemical state of impurities in (multiphase) snow remain an unresolved issue. This issue is essential to as- sess the chemical reactivity and the exchange with the over- lying air, and to compare results from studies with different types of ice or snow samples. Significant progress has been made during recent years towards analysing and describing the physical state and distribution of impurities in snow: 1. Detailed modelling to derive the brine concentrations in frozen samples, based on the thermodynamic phase diagram, but also taking into account losses by release of volatile species from the brine to the gas phase and non-ideal behaviour of the brine solution, has recently been presented. 2. The total amount of solute that gets expelled from the ice during the freezing process and the precise com- partment into which they get expelled are highly un- certain: brine may end up at the air–ice interface, in grain boundaries, or trapped in micro-pockets in the bulk ice. Observing the electrical potential that builds up during the freezing of solutions at the ice–solution interface gives a quantitative measure to estimate the influence of the freezing rate and of solute concentra- tions on the distribution of solutes between the ice sur- face and the bulk ice. Better understanding the freezing process is particularly important to compare individ- ual laboratory-based studies and to extrapolate to field conditions as concentrations and freezing rates might vary widely between different experiments and com- pared to the field. 3. Observing liquid water and void air simultaneously in porous snow and ice samples is delicate, and contin- ued developments of phase-contrast XMT are one way to tackle this issue. SEM studies can assess the chem- ical composition of agglomerates of solute in micro- pockets within the ice’s microstructure. Such studies have shown that some impurities accumulate along grain boundaries, while others are concentrated in iso- lated spots. What controls the precise distribution is an area of active investigation. 4. The fate of solutes below the eutectic point is an essen- tial, yet unexplored, question. In particular, it is cur- rently not clear how liquid-like the environment that impurities experience in micro-pockets remains below the eutectic temperature. We argued that apparent dis- crepancies to the phase diagram might be due do to an additional melting point depression in nanometre- sized micro-pockets (Gibbs–Thomson effect). 3 The disordered interface The surface of snow crystals hosts chemical reactions and is the interface at which exchange with the gas phase takes place. The role of the disordered interface in promoting chemical reactions and exchange processes has been in- tensively discussed for decades (Smith and Pounder, 1960; Wang, 1961, 1964; Gross et al., 1987; Dash et al., 1995; Co- hen et al., 1996; Finnegan and Pitter, 1997; Petrenko and Whitworth, 1999; Giannelli et al., 2001; Cho et al., 2002; Heger et al., 2005; Vrbka and Jungwirth, 2005; Kahan et al., 2007; Wren and Donaldson, 2011). A key question that leads to some controversy is whether or not describing the surface in analogy to liquid phase and parameterising processes oc- curring there based on liquid phase-processes is a valid and realistic picture. Most studies have dealt with the disordered interface at clean ice surfaces, i.e. without doping the surface with impu- rities, and studies that have dealt with the thickness and the properties of the ice surface will be reviewed in this section. Key questions are the following: does surface disorder spread www.atmos-chem-phys.net/14/1587/2014/ Atmos. Chem. Phys., 14, 1587–1633, 2014 1596 T. Bartels-Rausch et al.: Air–ice chemical interactions 0.1 1 10 100 0.1110 Q L L (n m ) ΔT (a) X-ray diffraction (0001) (b) X-ray diffraction (1010) (c) X-ray diffraction (1120) (d) Proton backscattering (0001) (e) Ellipsometry (0001) (f) Ellipsometry (1010) (g) AFM (h) AFM (i) AFM (j) AP-NEXAFS (k) Optical reflectance (0001) (l) Optical reflectance (0001) (m) MD simulations (0001) (n) MD simulations (1010) (o) MD simulations (1120) (p) Theoretical curve T hi ck ne ss o f D I ( nm ) Fig. 7. Comparison of different methods to derive the thickness of the disordered interface (DI) at the free ice surface versus 1T = Tm − T obtained using different methods. Solid circles are measured data, while dashed lines are results from reported equations fit to experimental data. Molecular dynamics (MD) simulations are represented by open circles. Glancing-angle X-ray diffraction (Dosch et al., 1995) on (a) basal and (b, c) prismatic crystal surfaces, (d) proton backscattering (Golecki and Jaccard, 1978) on basal ice, ellipsometry (Furukawa and Nada, 1997) on (e) basal and (f) prismatic crystal surfaces, (g) atomic force microscopy (AFM) (Döppenschmidt and Butt, 2000) on a 100 ml frozen droplet and vapour deposited on mica, (h) AFM (Pittenger et al., 2001) for vapour-deposited ice on metal, (i) AFM (Goertz et al., 2009) for ice frozen on a metal substrate, (j) ambient pressure near-edge X-ray absorption fine structure (Bluhm et al., 2002) for vapour- deposited ice on metal, HeNe laser optical reflectance (Elbaum et al., 1993) on basal crystals in the presence of (k) water vapour and (l) 30 Torr air, TIP4P/Ice MD simulations (Conde et al., 2008) for (m) basal and (n, o) prismatic crystals, (p) general thermodynamic solution (Dash et al., 2006) . evenly along the air–ice interface? Is the disordered interface homogeneous along its depth? Is it a feature restricted to the upper few monolayers or does it stretch deep into the ice crystal at environmentally relevant temperatures? Figure 7 compiles measurements and estimates of the thickness of the disordered interface on clean ice surfaces and includes results from experimental studies, molecular dynamics simulations, and thermodynamic calculations. It is important to note that the thickness is not a direct observable in any of the experi- mental studies and the given values represent average values over the entire probing area. In particular, this explains val- ues below 0.3 nm, which is the diameter of a water molecule and sets the lower limit of a physically meaningful thickness. Additional uncertainties due to translating the observables to layer thicknesses may also partially explain low values. Some of these studies have shown that the presence of impurities can significantly impact the disordered interface. More recent spectroscopic studies allow a picture to develop of how impurities impact the hydrogen-bonding network at the ice surface. These studies, reviewed in Sect. 3.3, aim at answering the following questions: does the presence of im- purities change the hydrogen-bonding network only locally, does the disorder reach deeper into the ice crystal lattice, and does the effect depend on the type and concentration of im- purities and on temperature? 3.1 Thermodynamics of surface disorder Theoretically, the disorder can be thought of by analogy to wetting behaviour, and complete thermodynamic descrip- tions of the disordered interface have been developed and are best found in dedicated reviews on the topic (Dash et al., 2006; Luo and Chiang, 2008). As in wetting, a disordered interface, here represented with liquid properties, will exist on a solid ice surface in equilibrium if it lowers the free en- ergy of the system – that is, if by its existence an intermediate layer of thickness d reduces the total excess surface free en- ergy FS (Israelachvili, 1991; Dash et al., 2006). FS = (slv + sls − ssv)= f (d)+ ssv (1) Here slv, sls and ssv are the surface energies of the liquid– vapour, liquid–solid and solid–vapour interface, respectively. Theoretically the functional dependence of the surface en- ergy f (d) comes from knowledge of the intermolecular forces at the interface. In the case of ice and other molec- ular materials it is most common to use van der Waals forces whose long-range potential falls off with the square of the Atmos. Chem. Phys., 14, 1587–1633, 2014 www.atmos-chem-phys.net/14/1587/2014/ T. Bartels-Rausch et al.: Air–ice chemical interactions 1597 distance. The resulting thickness-versus-temperature predic- tion is shown in Fig. 7 for a clean ice surface and compared with experimental results. It is important to point out that the wetting theory treats the disordered interface as a liquid phase and input values for the calculations are those of liquid water. This approach may thus provide a unified approach to describe the disordered interface and melting in one model, but the ability to clearly differentiate between these phys- ically distinct phenomena is lost. This approach is also in contrast to other theoretical predictions and to some exper- imental evidence. Consequently, this simplified picture has provoked some discussion (Baker and Dash, 1996; Knight, 1996a). In systems with impurities or with surface charge, expo- nentially decaying electrostatic Coulomb interactions can be used to model the interactions between charged particles (Is- raelachvili, 1991), in addition to the common colligative de- pression of the melting temperature, which results in addi- tional liquid (Beaglehole, 1991). Thus the theoretical treat- ment predicts that the temperature dependence of the layer thickness varies depending on which interactions are dom- inating (Wettlaufer, 1999; Dash et al., 2006). As a conse- quence of these predictions in certain cases thickness can be- have non-monotonically with respect to temperature and/or impurity level (Benatov and Wettlaufer, 2004; Thomson, 2010; Thomson et al., 2013). 3.2 Molecular simulations of surface disorder Molecular dynamics (MD) simulations provide a useful tool to study the surface disorder of ice with resolution at the molecular level. These simulations are particularly useful for following the development of surface disorder from initia- tion to its macroscopic extent, molecule by molecule (Fig. 8). They are, however, often limited to total sample thicknesses below 10 nm. Only recently have efficient coarse-grained MD simulations allowed simulating systems with thick- nesses of 16 nm (Shepherd et al., 2012). Similar limitations also apply to the lateral dimensions of the sample. To over- come this issue, periodic boundary conditions are typically used and the simulations are, thus, effectively performed for infinite flat surfaces of single crystals. Simulations of a poly- crystalline ice surface involving multiple grain boundaries are yet to be undertaken. Simulations are also time-limited, with standard classical MD simulations covering timescales up to several microseconds. In spite of the prevailing spatial and temporal limitations of molecular simulations, important new results concerning the structure and dynamics of the ice–vapour interface have been obtained during the last decade since the pioneering work summarised in a review by Girardet and Toubin (2001). Critical to any simulation is how well the underlying poten- tials used to parameterise the intra- and inter-molecular in- teractions capture the physics of the system. Recently, much progress has been made developing and critically evaluating water models, including their ability to adequately describe the general features of water over the entirety of phase space, including fundamental quantities such as the melting point of ice (Vega et al., 2009; Vega and Abascal, 2011). While no model is perfect and universally accepted, their draw- backs are known and can be accounted for. One other ap- proach is the use of first-principle MD simulations that do not rely on the assumption of underlying potentials (Mantz et al., 2000, 2001a, b). Such simulations have been used to study molecular-level disorder with and without impurities. Here we review the primary findings of MD simulation ef- forts. To account for inter-model differences all temperatures are given relative to the individual model melting point (Tm). 3.2.1 Simulations of disorder on pure ice Molecular dynamics simulations show that a disordered layer develops spontaneously at the free surface of ice at temper- atures below the melting point (Fig. 8). This has been ob- served regardless of the water model and the crystallographic plane exposed to the vapour phase (Bolton and Pettersson, 2000; Picaud, 2006; Vega et al., 2006; Bishop et al., 2009; Neshyba et al., 2009; Pereyra and Carignano, 2009; Pfalz- graff et al., 2011; Shepherd et al., 2012). The onset temper- ature of disorder is found to depend on the crystal facet ex- posed to the vapour phase; for example on the basal plane, the first sign of interfacial disorder occurs about 100 K below the melting point, whereas on the prism plane disorder was observed around Tm − 80 K (Conde et al., 2008). The thick- ness of the disordered interface also shows small differences for different crystal facets (Conde et al., 2008; Pfalzgraff et al., 2011). It appears that the disorder on the basal plane is slightly thicker; a similar trend can also be observed in exper- iments (Sect. 3.3). Simulations reveal that the surface disor- der begins with a small fraction of water molecules leaving the outermost crystalline layer of ice and becoming mobile as adsorbed molecules on the crystal lattice (Bishop et al., 2009; Pfalzgraff et al., 2011). With increasing temperature, the number of vacancies in the outermost crystalline layer in- creases, giving rise to aggregates of (increasingly mobile) ad- sorbed molecules on top of the crystal and, at the same time, resulting in higher disorder and mobility of molecules within the outermost crystalline layer itself. While the number of disordered molecules grows steadily with temperature, the disordered interface remains up to about Tm−10 K limited to the outermost molecular layer of the ice. Only at higher tem- peratures does the disorder propagate to additional ice lay- ers, and the thickness of the disordered interface increases to about 0.5 nm (Fig. 7). It is important to note that differ- ent water models yield practically the same thickness when compared at the same degree of undercooling relative to the model melting points (Vega et al., 2006; Paesani and Voth, 2008; Bishop et al., 2009; Neshyba et al., 2009; Muchová et al., 2011; Pfalzgraff et al., 2011). A recent large-scale, long-time simulation employing a coarse-grained model of www.atmos-chem-phys.net/14/1587/2014/ Atmos. Chem. Phys., 14, 1587–1633, 2014 1598 T. Bartels-Rausch et al.: Air–ice chemical interactions Fig. 8. Snapshots of the prismatic air–ice interface for selected simulations. The simulation temperatures correspond to undercooling of −59 K through −2 K relative to the melting point of the water model (NE6, Tm = 289K). Reproduced from Gladich et al. (2011) with permission from the PCCP Owner Societies. water (Molinero and Moore, 2009) further corroborated this molecular picture of the ice surface (Shepherd et al., 2012). However, at Tm − 1 K their simulations show larger fluctua- tions of the disordered interface’s thickness, with increases of its thickness of about 2 nm for periods of about 50 ns, than do previous smaller-scale, atomistic simulations. Thus, apart from temperatures very close to Tm, molecular simulations provide a consistent and robust picture of the surface disor- der, independent of a specific water model used in the sim- ulation. In addition to the spatial and temporal limitations of current molecular simulations, obtaining reliable results at temperatures just below the melting point is further compli- cated by the fact that the melting point of the model ice is typically subject to an uncertainty of ±2 K. Large-scale sim- ulations and more-accurate estimates of the melting point of models will be needed to increase accuracy within this envi- ronmentally relevant temperature region. 3.2.2 Simulation of disorder induced by ionic impurities MD simulations of ice growth from supercooled salt solu- tions have revealed that the presence of ions increases the thickness of the interfacial disorder compared to pure ice both at the free ice surface and at the grain boundaries (Vrbka and Jungwirth, 2005; Carignano et al., 2006, 2007; Bauerecker et al., 2008). The same conclusion has been drawn for some small organics; we refer the reader to the re- cent review by McNeill et al. (2012) for an in-depth discus- sion on organics. Current molecular simulation studies are limited in terms of the size of the systems and, hence, the spa- tial scale of inhomogeneity that can be investigated. Never- theless, the existence of a uniform disordered interfacial layer is not likely in the presence of ions. Instead, a pronounced tendency for ion clustering has been seen upon freezing salt solutions, resulting in the coexistence of thick ion-containing disordered regions and regions of pure ice with thin layers of interfacial disorder. This picture agrees with recent obser- vations of impurity-induced disorder using surface-sensitive spectroscopy (Sect. 3.3). So far, only a few MD studies us- ing selected concentrations of NaCl at defined temperatures have been performed. More simulation work is needed to ob- tain quantitative results regarding the effects of temperature, salt concentration, and ionic composition on the thickness and character of the disordered interface. Uncertainty also remains as to the distribution of various ions within the dis- ordered layer and their propensity for either the ice–liquid Atmos. Chem. Phys., 14, 1587–1633, 2014 www.atmos-chem-phys.net/14/1587/2014/ T. Bartels-Rausch et al.: Air–ice chemical interactions 1599 or the liquid–vapour interfaces, or for the interior of the un- frozen liquid. 3.3 Observation of surface disorder The disordered interface on ice surfaces has been investi- gated using many techniques (Li and Somorjai, 2007). Either these techniques are based on observations of properties of the ice surface that change with the degree of molecular or- der or the structure at the surface is probed directly (see Li and Somorjai, 2007, for a complete list of individual studies). 3.3.1 The thickness and effect of impurities Experimental results for ice–vapour interfaces are sum- marised in Fig. 7, showing that the measured thicknesses vary widely between different studies. There are several fac- tors contributing to this variability. Different techniques have inherently different probing depths and examine different physical properties of the sur- face layer. For example, proton channelling is element- specific and probes atomic positions in the interfacial re- gion, while ellipsometry probes changes of the refractive in- dex and extinction coefficient with the use of an appropri- ate optical model. The different probing depth is critical in measurements of the disordered interface, because the ice surface’s properties vary over depth (Sects. 3.2 and 4.1). Some techniques also interact with the surface more than oth- ers, thereby adding uncertainty to the observations. In addi- tion to wide variations in observed or predicted thicknesses, the onset temperature at which surface disorder is observed varies between different techniques. Sum frequency gener- ation (SFG) probes anisotropic surface vibrational modes of water. Although it is difficult to quantitatively assess the thickness with this technique, it is inherently surface sensi- tive and observes an onset in surface disorder of the inter- facial water molecules near 198 K (Wei et al., 2001). In con- trast to these results, proton backscattering observes onsets at 233 K (Golecki and Jaccard, 1978) and ellipsometry at 243 K and 268 K (Furukawa and Nada, 1997; McNeill et al., 2006). As seen in Fig. 7, different ice crystal orientations give rise to different thickness results in otherwise identical experi- ments (Furukawa et al., 1987; Sazaki et al., 2012), consistent with molecular dynamics simulations (see Sect. 3.2). Surface disorder is also affected by the presence of im- purities, as theoretically predicted (Sects. 3.1 and 3.2), and experimentally verified by optical reflectance (Elbaum et al., 1993), by ellipsometry (McNeill et al., 2006, 2007), and directly by partial electron yield near-edge X-ray absorp- tion fine structure (NEXAFS) (Bluhm et al., 2002). Obser- vations of impurity-amplified or -induced disorder at ice surfaces depend on experimental conditions, the method of experimental probing, and on the type of impurity. Using synchrotron-based, surface-sensitive NEXAFS Krˇepelová et al. (2010b) reported that only about 20 % of the interfa- gas phase spectrum shown in Fig. 4C. The N K-edge NEXAFS data add further evidence that the surface species observed under both conditions is nitrate. The fact that the nitrate peak is present under low NOX conditions, even in the absence of NO2 (see mass spectra above), is a strong indication that HNO3 desorbs from the chamber walls and adsorbs to the ice surface, where it is detected as nitrate. Under high NOX conditions, the direct hydrolysis of NO2 on the ice surface directly leads to surface HNO3 or nitrate or rather a nitrate solution (see below) together with HNO3 formed on the chamber wall. All other secondary species present under both conditions (HONO, NO, N2O) only very weakly interact with ice 59 and would not lead to measurable surface coverage at the temperature of this experiment. This is in contrast to some previous experiments of NO2 on ice, which reported a number of condensed nitrogen species, but were performed at much lower temperatures.60–66 We have not observed indications for beam damage. This is likely due to the fact that radiolysis of nitrate or HNO3 would lead to NO or NO2 species that would immediately desorb from the surface under these conditions. Since both water vapor and HNO3 are continuously exchanged between the surface and the gas phase, radiation damage seemed to not affect the observables of the present experiments. Fig. 9 compares the Auger electron yield NEXAFS oxygen K-edge spectra of clean ice, ice under low NOX and ice under high NOX conditions, in the latter case most likely a solution. It shows that under the conditions where we observe a nitrate peak in the N1s XPS, a peak at 532 eV occurs in the O K-edge NEXAFS. It is due to the contribution of oxygen of adsorbed nitrate (O1s 1a1 - 2b1* transition). The more nitrate is present on the ice surface, the more significant is this peak. Under low NOX conditions, the general shape of the remainder of the O edge spectrum remained close to that of pure ice. In contrast, under high NOX conditions, the O edge spectrum significantly changed shape and apart from the nitrate peak at 532 eV closely resembled that of aqueous solutions or water. Under these conditions a solution was visibly observed on the ice film, as described above. At NO2 pressures of about 1.3 ! 10"3 mbar (lowest NO2 pressure maintained in the presence of ice, conditions still classified as high NOX), however, formation of a visible solution was not observed, and the NEXAFS spectra were still similar to the low NOX spectra, at least within the time scale of a few hours. We can use the O1s and N1s XPS data to estimate the surface elemental composition. From O1s and N1s peak areas, the photon flux ratio in O1s and N1s measurements (0.93), and O1s and N1s photoelectron cross sections (0.25 vs. 0.28 Mb, respectively) under our conditions, we determine N/O elemental ratios in the range of 0.005–0.028 for low NOX conditions, and in the range of 0.044–0.148 for high NOX conditions. These ratios are calculated assuming a homogenous distribution of N and O in the probed volume, which can be estimated from the inelastic mean free path for 200 eV kinetic energy photoelectrons in ice (B1.4 nm67), yielding a probing depth ofB1.1 nm at our photoelectron detection angle of B401 relative to the surface normal. Taking into account that each nitrate ion contains three oxygen atoms, these N/O ratios translate to nitrate ions to water mole ratios of 0.005–0.031 for low NOX conditions, and 0.05–0.27 for high NOX conditions. From the observed loss of gas phase HNO3 to ice in flow tube experiments, 68 the monolayer capacity of HNO3 on the ice surface was estimated as 2.5 ! 1014 molecules cm"2. With a density of water molecules of about 1 ! 1015 cm"2 and the probing depth of 1.1 nm in our experiments we can estimate that for low NOX conditions the nitrate coverages were less than half a monolayer, even when all HNO3 molecules would have been located at the ice/vapor interface. For the high NOX conditions, when formation of a visible solution was observed, the nitrate concentrations are in the range of about 0.05–0.27 mole ratio. Based on the HNO3—ice phase diagram presented by Thibert and Domine´69—this is consistent with an about 12 wt% HNO3 solution (0.15 mole ratio) at 230 K in equilibrium with a HNO3 partial pressure of 10 "5 mbar. Therefore, it is likely that for high NOX conditions, HNO3 partial pressures were high enough for a nitrate solution to become stable, whereas for low NOX conditions, we stayed within the ice stability regime of the HNO3 ice phase diagram. We now return to the discussion of the O K-edge NEXAFS spectra (Fig. 9). The NEXAFS spectrum of ice in the presence of nitrate under low NOX conditions can be represented as a linear combination of the spectrum of clean ice (80%) and that of the nitrate solution (high NOX measurement—20%). Notably, the contribution of the nitrate solution to the NEXAFS spectrum was within error roughly the same for all low NOX experiments and always under 20%. When the nitrate to water ratio under high NOX conditions as derived from the XPS measurement exceeded about 5%, a rapid transition of the spectral features in the O K-edge spectrum from mainly ice-like to solution-like was observed, even before the melting of the ice sample was visible by eye. This discontinuous behavior is suggestive of a phase transition. The electron yield for the NEXAFS spectra was measured at 450 eV, such that mostly oxygen Auger electrons contributed to the intensity. However, also higher energy photoelectrons with originally up to about 530 eV could contribute to the background at 450 eV via inelastic scattering, so that the inelastic mean free path of the probed electrons could be even slightly higher (2.5 nm). Because the probing depths of Fig. 9 Oxygen K-edge Auger electron yield NEXAFS spectra of clean ice, ice with HNO3 (low NOX) and HNO3 solution (high NOX). This journal is #c the Owner Societies 2010 Phys. Chem. Chem. Phys., 2010, 12, 8870–8880 | 8877 Fig. 9. NEXAFS spectra probing the oxygen of nitrate and ice at the surface at the upper few nanometres of the sample and showing little change to the structure of ice in the presence of adsorbed nitrate (red dotted line) compared to pure ice (black solid line) at 230 K. Reproduced from Krˇepelová et al. (2010b) with permission from the PCCP Owner Societies. cial H2O molecules form a hydration shell in the presence of nitrate molecules in sub-monolayer coverage on ice at 230 K (Fig. 9). The majority of the water molecules show no change in their hydrogen-bonding network in the presence of nitrate. Minor amounts of H2O hydrating sub-monolayer concentrations of acetic acid were observed at temperatures of ∼ 230–245 K, while no changes at all were observable for acetone on ice (Starr et al., 2011; Krˇepelová et al., 2013). NEXAFS probes the upper few nanometres of an ice sample, and, thus, the observation of ordered ice suggests that disor- der does not spread throughout the entire upper few nanome- tres, but leaves room for disorder on the scale of a few molec- ular layers. The observations of hydration shells surrounding the nitrate molecules on ice just as they would be in aqueous solution indicates some heterogeneity of the disordered in- terface at low surface coverage of nitrate where pronounced disorder, with liquid-like properties, is limited to the vicin- ity of the impurities. The emerging picture of the locally restricted and compound-specific changes to the hydrogen- bonding network is illustrated in the surface adsorption panel of Fig. 1. Other potential sources of thickness variability may stem from ice preparation (vapour deposition versus cleavage of a single crystal) and different ambient vapour environments (air or some inert gas versus pure water vapour). Thus, thick- ness measurements from identical experimental techniques (e.g. atomic force microscopy (AFM); see Fig. 7) can vary by more than an order of magnitude, likely due to some combi- nation of the aforementioned variability as well as, in the case of AFM, variation in the AFM tip temperature and composi- tion (Döppenschmidt and Butt, 2000; Pittenger et al., 2001; Goertz et al., 2009). www.atmos-chem-phys.net/14/1587/2014/ Atmos. Chem. Phys., 14, 1587–1633, 2014 1600 T. Bartels-Rausch et al.: Air–ice chemical interactions 3.3.2 Observation of properties Is there a gradual change from the disordered interface to liquid water, as the melting temperature is approached and crossed? Spectroscopic studies give clear indications that, with the onset of melting, the properties at the surface change abruptly and that the disordered interface has struc- tural features that are very different from supercooled wa- ter (Lied et al., 1994; Wei et al., 2001). Furthermore, sum frequency generation (SFG) (Wei et al., 2001), proton chan- nelling (Golecki and Jaccard, 1978), and glancing-angle X- ray studies (Lied et al., 1994) show that the disordered inter- face is not homogeneous perpendicular to the air–ice inter- face. Rather its properties gradually change with depth. This suggests that simple models that parameterise the disordered interface as a thin, homogenous water-like layer are ques- tionable and contradict AFM measurements, where a sharp border between the disordered interface and the bulk ice has been found (Döppenschmidt and Butt, 2000). While the thickness variation in the disordered interface has been heavily studied, few observations exist with regard to how the disorder is distributed laterally on a molecular level at the ice–vapour interface. This is a very challenging task from an experimental perspective, considering that most surface-sensitive techniques detect average thicknesses over large sample areas. Further, this question must be asked with the understanding that, under ambient conditions, the lateral distribution of water molecules evolves on short timescales, making their structure difficult to probe. Sazaki et al. (2012) recently reported pioneering observations in this direction. They used laser confocal microscopy to monitor the ice sur- face close to its melting point and observed two types of dis- ordered interfaces with different morphologies and dynam- ics. Droplets moving over the surface and their collision and coalescence were observed in both cases, with a lateral res- olution on the order of ≈ 1 µm. Thus, while the molecular- level information is not observed in the lateral direction, these interesting results challenge the current understanding of disordered interface observations, from which a homo- geneous distribution of the disordered thickness is derived. A further indication of a heterogeneous distribution of sur- face disorder comes from surface-sensitive studies that probe impurities on ice surfaces (Sect. 3.3.1). The work by Sazaki et al. (2012) further revealed that growing steps on the basal plane of ice crystals can be observed up to the melting point. This shows that surface disorder for a wide temperature range – except within a fraction of a degree from melting – may preserve some long-range order. Considering that the tem- perature during some experiments was close to the melting point, one might caution that the observations are – at least partially influenced by melting of the sample. 3.4 Conclusions about the disordered interface Even though surface disorder is a general interfacial phe- nomenon of crystals, it is most controversially discussed in the context of ice and snow. The debate is centred on the analogy to the liquid phase that is often used to describe and parameterise the surface disorder and its interaction with im- purities. Recent MD simulations and experimental observa- tions give little support for this analogy and establish a rather differentiated picture of the disordered interface: 1. To give an exact parameterisation of the thickness- versus-temperature dependence of the disordered in- terface even on clean ice is still not possible. Individual observations of the onset temperature, the thickness, and the functional dependence of this disordered inter- face with temperature differ widely, as do simulations and thermodynamic calculations based upon varying initial assumptions. What is evident from Fig. 7 is that interpreting and generalising observations of surface disorder remain difficult. 2. There are clear indications that the disordered interface is different from a supercooled liquid phase. First, the disordered interface is not homogeneous perpendicular to the surface. Secondly, some studies indicate that its structure does not continuously evolve into the struc- ture of the liquid with increasing temperatures. Third, a very recent study even claims to have successfully observed isolated disordered regions on ice surfaces (Sazaki et al., 2012) indicating some spatial hetero- geneity of the disordered interface. 3. Even small levels of impurities induce surface disor- der, with its extent critically depending on the type of impurity and on temperature. Additionally, there are indications from observations and from MD simula- tions that impurity-induced changes to the hydrogen- bonding network are most pronounced in the immedi- ate vicinity of impurities, leading to some heterogene- ity of the disordered interface. Spectroscopic studies indicate that the hydrogen-bonding network surround- ing the impurity is indistinguishable from that of an aqueous solution. 4. Thermodynamic treatments of the disordered interface can directly incorporate colligative effects allowing single unified models, for the two regimes to be treated under environmental temperature and impurity condi- tions. The validity of treating the disordered interface as a separate phase and the importance of ignoring any micro-scale inhomogeneity of the disordered in- terface in these macroscopic thermodynamic models is debated. Atmos. Chem. Phys., 14, 1587–1633, 2014 www.atmos-chem-phys.net/14/1587/2014/ T. Bartels-Rausch et al.: Air–ice chemical interactions 1601 and are marked with a blue square in Fig. 3. Temperature-scan experiments such as those shown in Fig. 1 are represented by arrows in Fig. 3. The criterion for assigning the transition between no disorder (Fig. 3, red circles) and disorder (Fig. 3, blue squares) and vice versa for these experiments was that an abrupt change in the x and y signals with a magnitude ! five times the noise must be observed during heating or cooling. Clearly, we observed an increased refractive index, which we interpret as formation of a disordered region on the ice surface, at conditions in the vicinity of the phase equilibrium line, including conditions encountered in the polar stratosphere during polar stratospheric cloud events. To the best of our knowledge, no prior direct experimental observations of HCl- induced surface disordering at stratospheric conditions exist, although we had predicted this phenomenon theoretically (7, 30). In the range of conditions on the interior of the ice stability envelope on the HCl–ice phase diagram, surface changes were not observed far from the phase equilibrium line. For example, exposing an ice surface to 10!7 torr HCl was observed to induce surface disorder only for T " 238 K and T #208 K and not for 238 K " T " 208 K. This trend is also ref lected in the results of our f low tube–CIMS studies of HCl uptake on zone-refined ice cylin- ders (Fig. 4), which further showed that the nature of the interaction of HCl with the ice samples was different under conditions for which surface change was or was not observed with ellipsometry (see Methods for details on zone-refined ice cylinder preparation). We also investigated the ClONO2 $ HCl reaction on zone-refined ice cylinders by using the f low tube–CIMS technique. As shown in Fig. 5, Cl2 production, and thus the ClONO2 $ HCl reaction efficiency, was enhanced in the presence of surface disorder. Referring to Fig. 3, if we were to traverse the phase diagram along the 10!6 torr HCl partial pressure line from 273 to 180 K, we would expect to start with a liquid HCl!H2O solution, transitioning through a region where HCl coexists with ice in the presence of surface disorder until 243 K, then HCl adsorbed on ice with no surface disorder from 243 to 210 K. At 210 K, we would expect surface disordering to return, and then possibly see formation of the metastable HCl hexahydrate phase at %188 K. This experi- ment was performed at constant reactant concentrations (10!6 torr HCl and 5 & 10!7 torr ClONO2), at two different Fig. 3. Summary of ellipsometer–CIMS study results: the HCl–ice phase diagram adapted from Molina (7). Thermodynamically stable phases are shown as a function of temperature and PHCl. Ice is the stable phase under polar stratospheric conditions (circled area). Liquid refers to a liquid solution, and HCl!3H2O and HCl!6H2O refer to the crystalline hydrate states. Blue squares indicate conditions where a change in signal consistent with forma- tion of a disordered region at the ice surface was observed, and red circles indicate conditions where no surface changewas observed. Arrows represent constant PHCl (temperature scanning) experiments. Bars represent tempera- tures at which cease!onset of surface changes were observed. Phase transi- tions are indicated by open triangles. Fig. 4. HCl adsorption on zone-refined ice at %7 & 10!7 torr HCl. Shown is the HCl mass spectrometer signal (normalized to the baseline signal) vs. time. (Upper) At 214 K (nondisordered conditions), 20% of adsorbed HCl (total uptake ' 1.2 ( 0.1 & 1015 molecules!cm!2) is desorbed after removal of the source. (Lower) Under disorder-inducing conditions (196 K), we observed a nearly constant HCl flux (5& 1011 molecules!cm!2!s!1) from the surface to the interior of the ice sample, persisting throughout the experiment (%1 h). After removal of the source,"80%of themolecules takenupare released to thegas phase. Fig. 5. The reaction of ClONO2 with adsorbed HCl on zone-refined ice at %10!6 torr HCl and 5& 10!7 torr ClONO2 and temperatureswherewedid (196 K; Right) and did not (218 K; Left) observe surface disordering with ellipsom- etry. For each temperature, the ClONO2 (Upper) and Cl2 (Lower) mass spec- trometer signals (normalized to the baseline signal) are shown vs. time. The productionof Cl2, and thus the efficiency of the reaction,was enhancedunder conditions where surface change was observed with the ellipsometer. 9424 " www.pnas.org!cgi!doi!10.1073!pnas.0603494103 McNeill et al. Fig. 10. Uptake of HCl on ice films as a function of time. Upper panel: Langmuir-type adsorption at 214 K with a surface coverage of 1×1015 moleccm−2. Lower panel: long-lasting flux into the dis- ordered interfac of 5× 1011 moleccm−2 s−1 at ∼ 196 K. This ex- ample shows how changing the exp rimental conditions can lead t significantly diff rent uptake behaviour on ic , even of the same species; see text for details. Reprinted from McNeill et al. (2006). Copyright (2006) National Academy of Sciences, USA. 4 Physical exchange processes Uptake and migration of trace gases and impurities in snow and ice have important environmental implications. They af- fect the chronology of ice core records (Barnes and Wolff, 2004), the composition of snow (Grannas t al., 2007b), the budget of atmospheric trace gases (Domine and Shepson, 2002) and the fluxes of volatile trace gases through s ow (Herbert et al., 2006; Seok et al., 2009; Pinzer et al., 2010; Bartels-Rausch et al., 2013). The observational basis of such large-scale effects in polar and even in alpine areas as well as in the upper troposphere is sound; but despite intensive re- search over recent decades, a quantitative description of the underlying processes leading to the large-scale observables can often not be given. Clearly, exchange of trace gases between the snow and the gas phase can be driven by (i) surface adsorption, (ii) up- take into the bulk (Abbatt, 2003; Huthwelker et al., 2006; Bartels-Rausch et al., 2012), (iii) or by a combination of both. Bulk refers to the interior crystal structure, grain bound- aries, micro-pockets, or the disordered interface (Fig. 1). Both types of interaction show distinct differences: surface adsorption operates at shorter timescales and, thus, responds faster to changes of environmental conditions. The total ca- pacity to accommodate trace species by adsorption is limited the structure, essentially to ease the ability of the molecules to rotate and hence change the hydrogen locations. In principle this might be done through inducing appropriate defects, such as so-called L and D Bjerrum defects (where the Bernal- Fowler rules are violated by zero or double occupation of an O–O link, respectively) and ionic defects [where a water molecule is ionized to either a hydronium (H3O þ) or hydroxyl (OH") ion (see Fig. 4)]. In principle such defects should allow easier molecular rotations. In the case of ordering ices III and VII, presumably there is a sufficient intrinsic concentration of appropriate defects to allow order- ing. In the cases of the other disordered ices that do not order on cooling, presumably the intrinsic defects are either insufficient in number or inoperative for some other reason. 3. Ordering the familiar ice Ih Much effort was spent two decades ago to try to order the familiar ice Ih by forcing extrinsic defects into the structure. This was done successfully by doping with KOH, which presumably created L Bjerrum and OH" defects. This doping was enough to allow careful, slow cooling partially to order the hydrogen atoms so that the ideal structure of the ordered phase (ice XI) could be determined (Jackson et al., 1997). The phase transition between the disordered (ice Ih) and ordered (ice XI) phases at 72 K (76 K for D2O) was reported first by Kawada (1972), with more precise calorimetric mea- surements following (Tajima, Matsuo, and Suga, 1984; Matsuo, Tajima, and Suga, 1986) in which the doped ice was held a few degrees below the transition temperature for several days to allow the growth of the ordered material. Subsequently the ideal orthorhombic structure of the ordered phase (ice XI) was determined (Jackson et al., 1997). More recent time-resolved powder neutron-diffraction studies explored the nucleation and growth of ice XI. Working with KOD-doped deuterated ice Ih, Fukazawa et al. (2005) concluded that ice XI appears to nucleate at a temperature 57< T # 62 K, some 15 to 20 K lower than the transition temperature. Annealing the material at 68 K for three days encouraged growth of the ordered phase, but the fraction of ice XI achieved leveled off at about 6%. Further work (Fukazawa et al., 2006) exploring annealing at higher temperatures to just below the transition temperature to ice Ih doubled the fraction of the ordered phase obtained to around 12%. In addition, noting that the ice XI growth rate is accelerated if the ice is annealed at temperatures lower than 64 K for sufficient time in advance to produce ice XI, they concluded that the thermal history of the sample influences the growth mechanisms of ice XI. A recent paper from the same group (Arakawa, Kagi, and Fukazawa, 2010) takes this work further by taking annealed, and hence ice XI containing, samples through the transition at 76 to 100 K to transform the sample to the disordered ice Ih. Reannealing this sample doubled the fraction of the ordered phase that was obtained. They suggest these interesting observations might be ex- plained in terms of small hydrogen-ordered domains remain- ing in ice Ih, even when the ice temperature has been taken well above (here 24 K above) the ice Ih–XI transition tem- perature. This suggestion, that residual order may remain above the transition temperature, is an interesting one that may also be relevant to the ordering of other ice phases. 4. Ordering high-pressure ices Early work on trying to order ice V by Handa, Klug, and Whalley (1987) observed that an endothermic peak on heat- ing ice V could be intensified by KOH doping. This transition was discussed, therefore, in terms of a hydrogen disorder- order transition. However, hydrogen ordering could not be confirmed by Raman spectroscopy (Mincˇeva-Sˇukarova, Slark, and Sherman, 1988). Attempts at ordering the remain- ing phases thus remained frozen, similar to the molecular rotations themselves, for nearly 20 years. The unfreezing of this problem occurred recently when the idea of trying acid rather than alkali doping was suggested by Salzmann and tested, initially, on ice V. This structure was thought to be a good candidate for ordering studies since Erwin Mayer in Innsbruck noted that up to 50% ordering had been obtained in this structure by Lobban, Finney, and Kuhs (2000) without any doping. Accordingly, studies were initi- ated using both HF and HCl doping, coupled with carefully controlled cooling procedures. The initial Raman data taken on these preparations suggested significant ordering had been achieved, an ordering that appeared to be much greater for the HCl-doped sample than the HF-doped one. So neutron powder diffraction measurements were made (on deuterated FIG. 4 (color online). Possible point defects in ice structures. FIG. 5. The three unit cell projections of the structure of ordered ice XIII; with 28 H2O molecules per unit cell it has the most complicated structure of all crystalline phases of ice. Thorsten Bartels-Rausch et al.: Ice structures, patterns, and processes: A . . . 889 Rev. Mod. Phys., Vol. 84, No. 2, April–June 2012 Fig. 11. Sketch of possible point defects in ice. Reprod ed from Bartels-Rausch et al. (2012). to the surface and is smaller than for bulk processes. As long as it is unknown which process dominates the exchange of trace gases with ice, it is impossible to estimate the exchange of trace gases under environmental conditions and to quan- tify the uptake and release that is crucial for snow chemical models. A limitation is that most of the recent studies give no direct evidence of the exchange process or of the compart- ment (Fig. 1) to which the uptake is occurring. Rather, the time profile of the exchange process is used to differentiate between surface adsorption and other processes. Figure 10 shows an example of such time profiles and how changing the experimental conditions can lead to significantly different uptake behaviour on ice, even for the same species. In the up- per panel, the gas-phase concentration of the acidic trace gas recovers to its initial concentration at≈ 1500 s after exposure of the gas phase to an ice sample (starting at t = 0 s). Such an uptake profile is well described by surface adsorption. Long-lasting uptake, as shown in the lower panel, has been observed for strong acids, such as HNO3 (Abbatt, 1997), HCl (Huthwelker et al., 2004), SO2 (Sommerfeld and Lamb, 1986; Clapsaddle and Lamb, 1989), CF3COOH (Symington et al., 2010), HONO, a weak inorganic acid (Kerbrat et al., 2010b), and the small organic molecule formaldehyde (Bar- ret et al., 2011b). It has been interpreted as diffusion into the ice crystal forming a solid solution, diffusion along grain boundaries, and dissolution into the liquid fraction of the snow. Also, surface restructuring processes induced by the dopant have been invoked to explain the uptake, for exam- ple in the study by McNeill et al. (2006) shown in Fig. 10. Each of these processes is r viewed i the following. An- other interpreta ion leading to the long-lasting uptake is the formation of hydrates (Symingt et al., 2010), which is not further considered here. www.atmos-chem-phys.net/14/1587/2014/ Atmos. Chem. Phys., 14, 1587–1633, 2014 1602 T. Bartels-Rausch et al.: Air–ice chemical interactions 4.1 Diffusion of water in pure ice Before we start to deal with the mobility of guest species in ice it is worth considering the intrinsic mobility of water molecules in bulk ice. The reason is that in general the wa- ter molecules’ mobility is important for the uptake of foreign molecular species in ice; a notable exception exists for very small species like H2 and He, which can diffuse within the perfect ice Ih lattice (Strauss et al., 1994; Satoh et al., 1996; Ikeda-Fukazawa and Kawamura, 2004) without any water re- arrangements. The mobility of water molecules and protons in bulk ice has been studied intensely for more than 50 yr (Pe- trenko and Whitworth, 1999) and we now have an in-depth view on their mobility in bulk ice, while the processes on the surface and along grain boundaries are less well understood. It turns out that a number of defects within the perfect ice crystal play a central role, most prominently vacancies and interstitials together with orientational (Bjerrum) and ionic defects (Fig. 11); water transport in bulk ice cannot be un- derstood without the presence of these defects. 4.1.1 Diffusion of water in the ice crystal Water molecules in ice are generally immobile as long as they occupy fully bonded stable crystal sites. Therefore, transport properties of water molecules in ice are thought to be determined by mobile defects. To summarise the large body of work in bulk ice, the following may be stated: at high temperatures, above 230–240 K, the long-range trans- port of protons is of interstitial nature and is achieved by the transport of intact water molecules via intrinsic defects in the crystal lattice (Geil et al., 2005; Kawada, 1978); intrin- sic defects (as shown in Fig. 11) exist also in the purest ice for entropic reasons and their numbers increase with tem- perature. On average, a water molecule traverses 1.5–4 in- terstitial cavities of the ice structure in a jump before it re- adsorbs on a regular lattice site (Geil et al., 2005). An in- terstitial mechanism for water self-diffusion is also strongly supported by the observation of moving dislocations (Goto et al., 1986). The water molecules’ diffusion coefficients, summarised in Petrenko and Whitworth (1999), decrease from ≈ 2 to 0.22× 10−15 m2 s−1 between 263 K and 233 K, in good agreement with tracer diffusion work (Blicks et al., 1966; Delibaltas et al., 1966; Ramseier, 1967) and direct observations by synchrotron X-ray tomography (Ramseier, 1967). Whether water molecules migrate in the bulk below 230 K preferentially via a vacancy mechanism as suggested by Livingston and George (2002) remains an open question; very little indeed is known about vacancies in hexagonal ice (Petrenko and Whitworth, 1999). Bjerrum and ionic defects may be injected into the bulk from the disordered ice sur- face (Devlin and Buch, 2007) where they are more abun- dant. Bjerrum defects (in terms of their concentration and mobility) play an important role for the re-insertion of water molecules into the crystalline frame at the end of an intersti- tial jump (Geil et al., 2005). This observation illustrates that the various point defects in ice interact with each other and cannot be understood without this interplay (Petrenko and Whitworth, 1999). 4.1.2 Diffusion of water at the ice surface Much less is known about the corresponding water or (con- nected) proton mobility on the ice surface, along grain boundaries and other imperfections of the ice lattice. Us- ing the technique of groove formation time (Mullins, 1957) in polycrystalline ice to deduce surface diffusivity, values of 3.5× 10−9 m2 s−1 and 3× 10−10 m2 s−1 at 271 K and 263 K, respectively, were obtained (Nasello et al., 2007). These numbers are about two orders of magnitude greater than in single crystalline bulk ice and quite close to the values of supercooled water with a value of ≈ 7× 10−10 m2 s−1 (Gillen et al., 1972; Price et al., 1999). It is noteworthy that molecular dynamics simulations that evaluated diffusivities for surface water molecules in the disordered interface of ice agree with available experimental data by Nasello et al. (2007) to within the quoted precision for the entire temper- ature range: at a temperature of Tm − 9 K a diffusivity of ≈ 8× 10−10 m2 s−1 was obtained, and 59 K below melting this value drops to 1.8× 10−11 m2 s−1 (Gladich et al., 2011). The finding that the coefficient of self-diffusion on the ice surface is similar to that of supercooled liquid casts some doubts on the earlier results by Mizuno and Hanafusa (1987) using nuclear magnetic resonance work on ice to deduce dif- fusivities. The water molecule self-diffusion coefficient was established for the temperature range from 253 K to the melt- ing point and amounts to 2.2× 10−13 m2 s−1 at 263 K, i.e. clearly slower than in supercooled liquid water. Ironically, the water mobility in the surface layer of ice situated between those of bulk ice and supercooled water thus appeared to jus- tify the name quasi-liquid layer (QLL). One should, however, note that in the experiment of Mizuno and Hanafusa (1987) some sintering of the particles may have occurred so that the diffusivities are likely not to represent true surface values. The discrepancy also illustrates one of the pertinent prob- lems in work on the disordered interface: the results often depend on the method used. Clear differences in mobility between the outermost and the inner water layers were es- tablished in the work by Nada and Furukawa (1997) and are, in fact, a ubiquitous feature of ice surfaces over a large range of temperatures (Bolton and Pettersson, 2000; Toubin et al., 2001; Grecea et al., 2004; Park et al., 2010). Consequently, techniques sensitive to the outermost surface layers will al- ways get a higher water mobility than methods looking at the bulk of the disordered interface or at grain boundaries; the differences may well span orders of magnitude. Molecular dynamics work by Pfalzgraff et al. (2010, 2011) and Glad- ich et al. (2011) confirmed the enhanced mobility of wa- ter molecules on free ice surfaces in the temperature range from 230 K to the melting point and provided more details Atmos. Chem. Phys., 14, 1587–1633, 2014 www.atmos-chem-phys.net/14/1587/2014/ T. Bartels-Rausch et al.: Air–ice chemical interactions 1603 regarding the diffusion mechanism at different temperatures. An Arrhenius analysis of MD-simulated self-diffusion coef- ficients on ice yielded a positive Arrhenius curvature, im- plying a change in the mechanism of self-diffusion with an increase in energy of activation from low to high tempera- ture. Since supercooled water is known to exhibit the op- posite Arrhenius curvature, i.e. the energy of activation is a decreasing function of temperature, it implies that self- diffusion on the ice surface occurs by significantly different mechanisms compared to bulk self-diffusion in supercooled water. A rather sharp transition to isotropic diffusivity is ob- served in the temperature range of 240–250 K; self-diffusion at higher temperatures, which occurs within an increasingly thick disordered layer, is governed by quasi-3-dimensional liquid-like mechanisms that are isotropic regardless of the geometry of the underlying crystalline ice matrix. In such a thick interface the ions display free diffusion, while in a thin layer the ions are strongly affected by the underlying crys- talline ice and move by an ice surface hopping mechanism (Carignano et al., 2007). For the ions to diffuse freely fol- lowing a Brownian pattern, the interfacial liquid layer must be at least three full molecular layers thick. For experimental studies of surface diffusivities at temper- atures well below 200 K other techniques have been devel- oped and were reviewed more recently (Park et al., 2010). There is evidence that a translational surface mobility in the outer ice layers is preserved down to temperatures of 100 K (Verdaguer et al., 2006; Lee et al., 2007; Jung et al., 2004). 4.1.3 Diffusion of water in grain boundaries Interestingly, the water mobility across grain boundaries is two orders of magnitude smaller than the mobility at the ice surface (Nasello et al., 2005) approaching the values of Mizuno and Hanafusa (1987) discussed above. Thus, it seems that the water molecules’ mobility at the surface and in grain boundaries are quite different, while the latter are still enhanced by more than 3 orders of magnitude over the bulk values (Mullins, 1957; Nasello et al., 2005). The inter- mediate diffusivity in grain boundaries between that of crys- talline ice and water was later confirmed by Lu et al. (2009) (Fig. 12). 4.2 Diffusion of impurities in pure ice Reliable data on the diffusion and solubility of impurities in ice are scarce because these are extremely difficult to mea- sure due to numerous experimental artefacts that can arise. In particular, dopant concentrations may be high enough to form hydrates in the ice, and hence direct applications to the diffusion of diluted trace gases in the thermodynamic stabil- ity domain of ice solid solutions cannot be done. Moreover it is a challenge to isolate and quantitatively measure indi- vidual processes such as surface adsorption, diffusion into grain boundaries, or the bulk ice crystal lattice. Huthwelker 10 -10 10 -11 10 -12 10 -13 10 -14 10 -9 10 -15 D iff us iv ity [m 2 s- 1 ] 273269265261 Temperature [K] Fig. 12. Diffusivities of water molecules in ice and supercooled water. Adapted with permission from Lu et al. (2009). Copyright (2009) AIP Publishing LLC. et al. (2006) presented a detailed discussion of such pitfalls and carefully re-analysed existing data. Doing so, the scatter of for example HCl diffusion measurements can be reduced from 10 to 2 orders of magnitude (Huthwelker et al., 2006). Certain impurities like HF, HCl, or NH3, which in principle have the possibility to substitute water molecules in the ice lattice, increase the number of point defects (see Fig. 11) in ice. This in turn affects the mobility of the water molecules and of the inserted species as well as the electric properties of ice (Petrenko and Whitworth, 1999). 4.2.1 Diffusion of impurities in the ice crystal Thibert and Domine (1997) exposed single ice crystals to a well-controlled atmosphere of diluted trace gases. After exposure for periods of days to weeks, the diffusion profile of the trace gas was obtained by serial sectioning of the ice crystals and subsequent chemical analysis. From these pro- files, taken at different temperatures, the thermodynamic sol- ubility in ice and diffusion coefficients were derived. While this method is limited to species with sufficient solubil- ity in ice, it is applicable to species of atmospheric rele- vance. This method provides diffusion constants at 253 K for HCl, HNO3, and formaldehyde (Thibert and Domine, 1997, 1998; Barret et al., 2011b) of ≈ 3× 10−16, 7× 10−15, and 6× 10−16 m2 s−1, respectively. These measurements are www.atmos-chem-phys.net/14/1587/2014/ Atmos. Chem. Phys., 14, 1587–1633, 2014 1604 T. Bartels-Rausch et al.: Air–ice chemical interactions technically demanding as discussed in the original work and from a broader perspective in Huthwelker et al. (2006). Infrared laser resonant desorption has also been used to study diffusion of HCl in ice (Livingston et al., 2000). The beauty of the technique is that laser ablation resolves sub- µm ice thicknesses, compared to ≈ 20 µm for serial section- ing of crystals mechanically. Hence, experiments on shorter timescales seem possible. In the experiments presented by Livingston et al. (2000) HCl dopant concentrations were high enough to form hydrates in the ice, and hence cannot be di- rectly applied to the diffusion of dilute trace gases in the ther- modynamic stability domain of ice. This was corroborated by the work of Domine et al. (2001), who used infrared spec- troscopy to show that the high concentrations used consider- ably perturb the ice structure, rendering it almost amorphous, so that the diffusion coefficients measured are not those of crystalline ice. Indeed, Livingston et al. (2000) report DHCl = 5× 10−14 m2 s−1 at 170 K, an unrealistically high value, compared to values in the range 10−16 to 10−15 m2 s−1 at 238–265 K found by Thibert and Domine (1997). The profiling techniques discussed above are destructive, render- ing direct in situ observation of the diffusion process diffi- cult. Here, accelerator-based techniques, such as Rutherford backscattering (RBS), might become viable tools. In an RBS experiment, He2+ ions are shot into ice and the energy spec- trum of the backscattered ions is a direct measure of the depth profile of the impurities in ice. It has been demonstrated that this technique can be used to follow the diffusion of HBr into ice in situ at HBr vapour pressures in the stability domain of ice and with a depth resolution of some 100 nm (Huthwelker et al., 2002; Krieger et al., 2002). In these studies the ice sam- ple was not a well-defined single crystal as in the studies by Thibert and Domine (1997, 1998) and Barret et al. (2011b). Ballenegger et al. (2006) estimated the diffusion coefficient of formaldehyde in ice using molecular dynamics calcula- tions. They obtained a value of 4× 10−11 m2 s−1 at 260 K, orders of magnitude larger than the values derived from mea- surements (Barret et al., 2011a). The overestimation of the modelled diffusion constants might be due to limitations of the model. Such limitations may include an imperfect rep- resentation of the ice structure for diffusion processes, and molecular structures that are too rigid to predict sites where formaldehyde would, in fact, be stabilised and reside longer than computed. Also, hydration of formaldehyde may take place in bulk ice, which would intuitively slow down diffu- sion because of increased molecular size. This process was not taken into account in the MD model. One may speculate that, due to the finite size typically used in molecular dynam- ics studies, the model might still not simulate a thermody- namically stable ice lattice, but rather ice in a confined reser- voir, where the diffusion is expected to be enhanced, com- pared to the one in a perfect crystal lattice. 4.2.2 Diffusion of impurities into grain boundaries Diffusion measurements of trace elements in grain bound- aries are virtually non-existent, because it is already very dif- ficult to prove the existence of impurities in these reservoirs and because it is not easy to differentiate diffusion in defects and in bulk ice (Domine et al., 1994). Grain boundaries, the contact area between two ice crystals, and other defects in the ice such as dislocations and small-angle boundaries, which are formed by a 2-D network of regrouped dislocations, can act as diffusion short-circuits (Domine et al., 1994; Thibert and Domine, 1997; Barret et al., 2011a). Similarly, the triple junctions (so-called veins) and quadruple points (nodes) be- tween ice crystals are candidates for such diffusion short cuts. One way to assess the impact of grain boundaries on the diffusion through ice is to perform the same experiment us- ing different types of ice. Indeed, there is evidence that poly- crystallinity enhances diffusion. For example, Aguzzi et al. (2003) found HCl and HBr to diffuse an order of magnitude faster in polycrystalline ice compared to single crystal ice at 200 K. In contrast, Satoh et al. (1996) measured the diffusion coefficients of He and of Ne by exposing single and poly- crystals of ice to the gas of interest and monitoring pressure changes. They found that those gases did not diffuse faster in polycrystalline ice compared to single crystals. 4.2.3 Diffusion in field samples The above suggests that solid-state diffusion can be impor- tant for understanding the composition of environmental ice and snow and its evolution, such as migration of species in ice cores and the partitioning of highly soluble species be- tween snow and the atmosphere. The following examples il- lustrate the complexity of migration in natural snow and ice, where diffusion into the solid ice crystal or liquid diffusion in grain boundaries can dominate. Peak widening and shifts in ice core signals have been ob- served for soluble inorganic and organic species (De Angelis and Legrand, 1994; Pasteur and Mulvaney, 2000). De Ange- lis and Legrand (1994) studied the volcanic signal in Green- land ice cores, and in particular the SO2−4 , F− and Cl− sig- nals. They noted that in some layers ascribed to volcanic eruptions the three signals coincided well, while in others the F− peak was shifted relative to the other two. Shifting did not occur when an (alkaline) ash layer fixing the F− was present. In the absence of ash, F− was excluded from the vol- canic acidic layer. The author proposed that migration took place in the upper part of the firn by diffusion of HF in the gas phase of the interstitial air. Solid-state diffusion of HF is also proposed to account for peak widening over the years. By comparing peak width at 1210 m depth (age 7400 yr) to those of recent eruptions, the authors proposed a diffusion coefficient for HF of 1.9× 10−12 m2 s−1 in ice. This value compares well with the coefficient of HF measured in labo- ratory ice, 5× 10−12 m2 s−1 (Kopp et al., 1965). Atmos. Chem. Phys., 14, 1587–1633, 2014 www.atmos-chem-phys.net/14/1587/2014/ T. Bartels-Rausch et al.: Air–ice chemical interactions 1605 Pasteur and Mulvaney (2000) observed the migration of methanesulfonate (MSA), a product of the atmospheric oxi- dation of dimethylsulfide, in firn and ice cores. MSA deposi- tion occurs in summer, but at some sites migration to the win- ter layer is observed after a site-dependent number of years. An interesting observation is that the migration leads to very good coincidence with the dominant Na+ ions that deposit mostly in winter. The authors analysed several hypotheses, and their favoured mechanism is “the migration of MSA in the snowpack via an initial diffusion in either the vapour or liquid phase which is halted by precipitation in the winter layer when the MSA forms an insoluble salt with a cation”. However, it is not clear why the summer sulphate peak does not migrate with the same mechanism. For sulphate, Traversi et al. (2009) postulated that the mobility depends on the pres- ence of other ions forming soluble, and thus very mobile, salts. Rempel et al. (2002) elaborated on that explanation. They suggested that most water-soluble species found in ice cores were, in fact, concentrated in triple junctions (veins) and quadruple points (nodes) between ice crystals, where they formed a concentrated liquid solution (Sect. 2.1). At the specific conditions of that study, there are more impu- rities in the winter layers, so that liquid in veins and nodes is more abundant. MSA is less concentrated in the winter lay- ers and, therefore, migrates there through the liquid veins, simply by virtue of the concentration gradient. Since there is more liquid in the winter layers and MSA concentrations are determined from bulk ice samples, eventually more MSA ends up in the winter layers and the MSA peaks essentially superimpose with the dominant Na+ signal. This elegant hy- pothesis explains the MSA observations, although as yet it has not been applied to the SO2−4 signal for further testing. In this case diffusion does not take place in crystalline ice, but in liquids. We propose here that the HF diffusion ob- served by De Angelis and Legrand (1994) is indeed in the solid phase because HF solubility in ice is sufficient to ac- commodate all the HF found in ice cores, while the solubil- ity of large molecules in crystalline ice is extremely low so that MSA is rejected to veins and nodes, as observed also for SO2−4 (Sect. 2.4). This strongly suggests that the esti- mation of the diffusion coefficient of MSA in solid ice by Roberts et al. (2009), DMSA = 4.1× 10−13 m2 s−1, is in fact diffusion in veins and not in ice crystals. Indeed, this value is orders of magnitude higher than the single-crystal diffu- sion coefficients measured for HCl, HNO3, and formalde- hyde (Thibert and Domine, 1997, 1998; Barret et al., 2011b) and even higher than the self-diffusion coefficient of water in ice (Sect. 4.1.1), which is extremely unlikely for such a large molecule. 4.3 Adsorption Interactions between atmospheric gases and ice surfaces are initiated by adsorption. Over the last decades, numerous studies have been conducted to elucidate the nature of this -25000 -20000 -15000 -10000 -5000 0 0.1 1 10 100 1000 Acetaldehyde Formaldehyde Acetone Hexanal Methanol Ethanol Propanol Formic acid H2O2 Butanol Acetic acid K lin C ∆G g-l (J mol-1) Pentanol Fig. 13. Plot of KLinC at 228 K versus the free energy of conden- sation (1DGg−l) for a range of organic alcohols (red), organic car- bonyl compounds (black), and an inorganic compound (blue). The data point for formaldehyde has little confidence as argued by Pou- vesle et al. (2010). Figure published with kind permission from John Crowley. interaction (Abbatt, 2003; Huthwelker et al., 2006) and have resulted in quantitative parameterisation of the partitioning between the gas phase and the ice surface for a number of atmospherically relevant trace gases (Crowley et al., 2010). For historic reasons, most of these studies focused on temper- atures relevant to the stratosphere or the upper troposphere. Surface snow and tropospheric ices, however, can be exposed to warmer conditions. At these temperatures either a disor- dered surface will generally exist or partial melting might occur, and recent studies have addressed the role of the dis- ordered interface, and of liquid in gas–ice interactions. Fur- ther complexity was added to the recent fundamental studies by investigating the simultaneous adsorption of several trace gases or the adsorption to growing ice samples. Combined, these studies have led to a better understanding of trace gas– ice interactions under conditions that mimic environmental conditions more closely, as reviewed in the following. 4.3.1 Langmuir isotherm The surface coverage as a function of both temperature and gas-phase concentration has been measured for a number of trace gases at temperatures ranging from approximately 250 K to below 180 K. The adsorption isotherms of many or- ganic and inorganic species to ice appear to be reasonably well described by a Langmuir mechanism both in laboratory experiments and theoretical calculations. θ = KLangC[X]g 1+KLangC[X]g (2) www.atmos-chem-phys.net/14/1587/2014/ Atmos. Chem. Phys., 14, 1587–1633, 2014 1606 T. Bartels-Rausch et al.: Air–ice chemical interactions Equation (2) displays such a Langmuir isotherm. It al- lows deriving the partition coefficient, KLangC, from mea- surements of surface coverage, θ , as a function of gas-phase concentration, [X]g. A key feature of the Langmuir isotherm is that it predicts saturation of the surface coverage (Nmax) at high gas-phase concentrations, as the adsorbing species com- pete for a fixed number of adsorption sites on the surface. At atmospherically relevant low trace gas concentration, a simplified analysis using only the linear part of the adsorp- tion isotherm is often sufficient. The partitioning coefficient, KLinC Eq. (3), has the advantage that knowledge of Nmax, which is often difficult to obtain experimentally due to lat- eral adsorbate–adsorbate interactions, is not needed. KLinC = [X]g[X]surf =KLangC ×Nmax (3) Such self-association, at higher concentrations outside the linear range, has been discussed mainly for those chemicals that can form common hydrogen bonds such as formic acid, acetic acid, ethanol, acetone, and some aromatics (Abbatt et al., 2008; von Hessberg et al., 2008; Symington et al., 2010; Kahan and Donaldson, 2007, 2008, 2010; Ray et al., 2011, 2013). In 2005, Ullerstam et al. (2005) measured the first adsorp- tion isotherms of nitric acid at atmospherically relevant par- tial pressures and found good fits to a Langmuir adsorption isotherm. Ullerstam et al. (2005) suggest that a Langmuir isotherm is not inconsistent with dissociative uptake, as it is possible that only the nitrate (and not the proton) requires ac- commodation at the ice surface. To which degree acids disso- ciate upon adsorption to ice at atmospherically relevant tem- peratures is essentially an open question (Huthwelker et al., 2006; Kahan et al., 2007; Krˇepelová et al., 2013). Recently, the dissociation of a weak organic acid, acetic acid, was di- rectly probed at the ice surface at 230–240 K using surface- sensitive core electron spectroscopy XPS (Krˇepelová et al., 2013). The degree of dissociation was found to be higher on ice than in a dilute aqueous solution in equilibrium with the same acetic acid partial pressure. Wren and Donaldson (2012b) proposed that the ionisation of HCl is inhibited at the ice surface compared to the bulk liquid and to the surface of liquid water, based on observed changes in the fluores- cence spectrum of a pH-sensitive dye. Ullerstam et al. (2005) further observed that the uptake of nitric acid at low con- centration is (partially) irreversible. This indicates that a new concept to describe the adsorptive uptake might be required, as the current Langmuir isotherm and the linear relationship rely on equilibrium conditions that are in contradiction to the irreversible nature of the uptake process. Nevertheless, for a wide range of organic and weak-acidic trace gases, the Langmuir concept gives a reliable descrip- tion of surface adsorption as illustrated in Fig. 13. It shows how KLinC correlates with the free energy of condensation (1Gg−l) at 228 K, indicating that the adsorption process is a surface process and dominated by hydrogen bonding (Pou- vesle et al., 2010). This conclusion is in agreement with ear- lier MD simulations (Girardet and Toubin, 2001; Compoint et al., 2002; Picaud et al., 2005; Allouche and Bahr, 2006; von Hessberg et al., 2008) and was recently further verified experimentally using a combination of surface-sensitive X- ray photoemission and partial electron yield X-ray absorp- tion spectroscopy in a study of ice surface properties pre- and post-acetone adsorption (Starr et al., 2011). The mea- surements of acetone directly on the surface of ice at tem- peratures below 245 K confirmed that the uptake is purely a surface process and that the Langmuir model successfully described the adsorption and identified the preferred geome- try of the hydrogen-bonded acetone. The correlation shown in Fig. 13 can also be used to predict the partitioning of trace gases to ice and indicates that the recent experiments by Pou- vesle et al. (2010) on the reversible adsorption of H2O2 to ice might describe the uptake better than older results by Clegg and Abbatt (2001) (not shown in Fig. 13). The pronounced uptake observed by Pouvesle et al. (2010) makes this surface process quite significant at environmental conditions. 4.3.2 Adsorption at higher temperatures A different uptake behaviour from that derived at low surface coverage and temperatures below 250 K has been reported at temperatures approaching the melting point in some studies. For example, benzene- and acetone-saturated surface cover- ages increased with increasing temperatures on ice films and artificial snows at temperatures up to 266 K (Abbatt et al., 2008). Early experiments on the uptake of H2O2 to artificial snow showed a slightly increased uptake at 270 K compared to 263 K (Conklin et al., 1993). In contrast, formaldehyde was not observed to undergo increased partitioning to ice at 268 K compared to 258 K or 238 K (Burkhart et al., 2002). The changes in adsorption at higher temperatures have been explained by uptake in the liquid fraction (Conklin et al., 1993) or to the disordered interface (Abbatt et al., 2008; Burkhart et al., 2002). However, surface concentrations ex- ceeded multi-layer coverage in some experiments (Abbatt et al., 2008; Burkhart et al., 2002; Conklin et al., 1993), which might explain the deviation in uptake behaviour. Fur- ther, the formaldehyde–water phase diagram and the poten- tial dissolution of formaldehyde into the bulk ice – as ob- served by Barret et al. (2011b) – was not discussed in the study by Burkhart et al. (2002), and the most likely explana- tion for their observation is that the partitioning of formalde- hyde to ice is dominated by diffusion into the bulk. 4.3.3 Uptake to the disordered interface Recently, direct laboratory evidence showed that HCl– and HNO3–ice interactions are highly dependent on the surface state of the ice substrate (McNeill et al., 2006, 2007; Moussa et al., 2013). This pioneering work overcomes the main lim- itation of the above studies, by providing a link between Atmos. Chem. Phys., 14, 1587–1633, 2014 www.atmos-chem-phys.net/14/1587/2014/ T. Bartels-Rausch et al.: Air–ice chemical interactions 1607 surface structure and adsorption behaviour. Surface disorder on ice exposed to HCl or HNO3 in the gas phase at tem- peratures as low as 189 K or 216 K, respectively, was ob- served using surface-specific ellipsometry. Uptake profiles were monitored, confirming that the presence of a disordered interface at such low temperatures goes along with a substan- tial change in the uptake from Langmuir-type adsorption to a continuous flux of acidic trace gases to the ice (Fig. 10). This is a key finding as it would provide a feedback mechanism leading to an enhanced uptake – beyond adsorption – when the adsorbate induces surface disorder. A further key finding from these studies is that the potential of either acid to induce surface disorder and, thus, to promote the long-term uptake depends on the precise temperature and partial pressure. Earlier studies have tried to estimate the capacity of the disordered interface to take up trace gases, based on the sol- ubility of the impurity in aqueous solutions. Conklin et al. (1993) argued that even at temperatures close to the melting point – where the disordered interface is thick – only 20 % of H2O2 uptake may be based on dissolution into the dis- ordered interface. This limited capacity agrees with findings that the uptake of a larger set of non-polar organics at 266 K is not explained by dissolution into the disordered interface (Roth et al., 2004). Roth et al. (2004) showed that interfa- cial disorder of 10–50 nm thickness can only (partially) ex- plain experimentally observed uptake, and if assumed thick- nesses are below 2 nm the impact of dissolution is entirely negligible. Recent developments in XPS and NEXAFS set- ups allow deriving information on the surface structure of ice and the surface concentration of dopants in situ. Starr et al. (2011) confirmed that the uptake of acetone to ice at 218– 245 K is a surface process and is well described by the Lang- muir model. The adsorption of HNO3 was not yet studied in detail with this technique, but first results presented by Krˇe- pelová et al. (2010b) of nitrate dosed to ice surfaces indicate that the disorder induced by the nitrate is limited to the hydra- tion shell in the vicinity of the individual dopant molecules (Sect. 3.3.1). These in situ results thus rather suggest that the uptake of trace gases to ice is not linked to the disordered in- terface. Certainly, more studies spanning a wider temperature and concentration range are needed. 4.3.4 Uptake to grain boundaries The Langmuir model has also been found to accurately de- scribe uptake to polycrystalline ice at temperatures below 223 K. Bartels-Rausch et al. (2004) observed indistinguish- able adsorption behaviour of acetone on different types of artificial and natural snow with varying levels of inter-grain contact area, a parameter that has been shown to vary by as much as a factor of 7 in different artificial snow types (Riche et al., 2012; Bartels-Rausch et al., 2013). Interest- ingly, a number of SO2 uptake studies on ice spheres have shown that the uptake was enhanced at higher temperatures close to the ice melting point, in contrast to the expectations of a classical adsorption process (Sommerfeld and Lamb, 1986; Clapsaddle and Lamb, 1989; Conklin and Bales, 1993). In the later experiments, kinetics were diffusion-like for the course of hours to days, and hence inconsistent with a simple Langmuir-type uptake process on the ice surface itself. Moreover, the temperature dependence of these long- lasting uptake kinetics is well described by diffusion into the veins of the highly polycrystalline ice bed (Huthwelker et al., 2001), based on the concept and thermodynamic equations suggested by Nye (1991) and Mader (1992). 4.3.5 Uptake to brine A drastic change in the adsorption properties once a liquid phase is present has been seen in well-defined laboratory ex- periments (Abbatt, 1997; Journet et al., 2005; Kerbrat et al., 2007; Petitjean et al., 2009). In these studies the uptake of volatile organics or HNO3 on pure ice surfaces and on su- percooled solutions doped with HNO3 at temperatures be- low 243 K was investigated. The findings indicated that up- take to the solutions increased enormously relative to the pure ice surface. Other early studies of SO2 uptake on ice doped with NaCl also found that the observed partitioning can be well described by dissolution into a liquid phase if its volume is estimated using melting point depression (Con- klin and Bales, 1993). Similarly, Tasaki and Okada (2009) examined the retention of water-soluble organics in a chro- matographic column packed with ice spheres. The ice was doped with NaCl and it was found that the retention largely increased with the formation of liquid brine. At low temper- atures, in the absence of brine, adsorption to the surface was the dominant retention mechanism, while at higher tempera- tures partitioning to the liquid phase became more important. Interestingly, the presence of brine at the surface of frozen ice samples does also impact the dissociation of acidic trace gases upon adsorption. An inhibition of ionisation of strong acids, as observed on pure ice surfaces, was not observed in the presence of brine (Wren and Donaldson, 2012a, b). For HNO4, significantly less adsorption to ice was found in a re- cent study by Ulrich et al. (2012) than was deduced in an earlier study (Li et al., 1996); this was attributed to high im- purity concentrations partially melting the ice film in the ear- lier work. This result highlights the importance of ice surface physical characteristics in air–ice interactions. It also shows that ice surface properties must be well characterised in order to correctly interpret experimental results such as the uptake equilibrium. 4.3.6 Co-adsorption The Langmuir model predicts that simultaneous dosing of several trace gases to an ice surface (co-adsorption) will result in competition of the trace gases for adsorption sites. The influence of acetic acid on the uptake of HONO at temperatures up to 243 K (Kerbrat et al., 2010a), and www.atmos-chem-phys.net/14/1587/2014/ Atmos. Chem. Phys., 14, 1587–1633, 2014 1608 T. Bartels-Rausch et al.: Air–ice chemical interactions the co-adsorption of formic and acetic acid (von Hessberg et al., 2008), and butanol and acetic acid (Sokolov and Ab- batt, 2002), were well described by Langmuir’s competitive adsorption model. A competition has also been observed for the strong acids HCl and HNO3. HNO3 seems to bind more strongly than HCl to the ice, allowing HCl to be displaced by HNO3 (Hynes et al., 2002; Sokolov and Abbatt, 2002; Cox et al., 2005). Co-adsorption studies of HCl and CH3COOH showed a twofold increase in acetic acid uptake when the partial pressure of HCl was increased to levels that induced surface disordering at 212 K (McNeill et al., 2006). This was the first study showing that inducing disorder by solutal dos- ing impacts the trace gas uptake at low temperatures. The fact that the increased uptake induced by co-adsorption critically depends on the experimental conditions might also explain why in other studies the presence of HCl did not significantly change the uptake behaviour of butanol (Sokolov and Abbatt, 2002). Enhancement of acetone uptake at temperatures lower than 245 K in the presence of CF3COOH was observed in co-adsorption studies of CF3COOH and acetone (Symington et al., 2010). 4.3.7 Uptake to growing ice We have so far treated the ice surface as a static interface to which trace gases adsorb and establish a reversible adsorp- tion equilibrium. However, the natural temperature gradients in snow lead to significant water vapour fluxes, resulting in an ever growing or sublimating interface (Sect. 1.3). How ad- sorbed species respond to these water fluxes and in particular to growing ice conditions depends on their residence time on the surface. If the residence time is long compared to the frequency of water molecules bombarding the surface, grow- ing ice may bury adsorbed molecules (Conklin et al., 1993; Domine and Thibert, 1996; Karcher and Basko, 2004). The surface residence time may be linked to the adsorption en- thalpy (Huthwelker et al., 2006; Bartels-Rausch et al., 2005). Thus, available parameterisations of trace gas adsorption ob- tained from experiments under equilibrium conditions may not adequately describe partitioning to snow under temper- ature gradient conditions for species with more negative ad- sorption enthalpies than water on ice. A few studies have ad- dressed this issue for HCl (Domine and Rauzy, 2004), for HNO3 (Ullerstam and Abbatt, 2005) and for aromatic hy- drocarbons (Fries et al., 2007). In general, the results show increased uptake of trace gases in growing ice, when com- pared to adsorption at equilibrium conditions. However, the interpretation of these experiments has remained difficult be- cause ice growth rates were poorly defined or could not be varied over sufficiently large ranges. 4.4 Modelling physical cycling of trace species Detailed snowpack models taking into account some of the above-described physical processes were developed for Fig. 14. Scheme illustrating two approaches to parameterise the ex- change of impurities between the snow grains and the adjacent inter- stitial air: a transport model using spherical layers (H2O2, left side). A bulk approach assuming that an uptake equilibrium between the entire ice phase and the air is established (formaldehyde, right side). species like H2O2 and formaldehyde. Hutterli et al. (2003) presented atmosphere–snow models for these two species based on 1-D models previously developed by McConnell et al. (1998) and Hutterli et al. (1999). Motivation came from the knowledge that hydrogen peroxide is the only major at- mospheric oxidant that is conserved in snow. The reconstruc- tion of its atmospheric concentration from the ice core record can deliver crucial information to constrain the photochem- istry of the past atmosphere (Thompson, 1995; Frey et al., 2005; Lamarque et al., 2011) and has attracted great interest (e.g. Neftel et al., 1995; Anklin and Bales, 1997; McConnell et al., 1997; Frey et al., 2006). Similar reasons led to the ex- amination of formaldehyde in ice cores, since reconstructed atmospheric formaldehyde concentrations would constitute a strong constraint to past methane and hydroxyl radical con- centrations (Staffelbach et al., 1991). Snowpack modelling of H2O2 and formaldehyde was ap- plied to conditions at Summit, Greenland, to simulate con- centration profiles in surface snow for a period of six years (Hutterli et al., 2003). Transport of H2O2 and formaldehyde in the interstitial air, the exchange between snow grains and the adjacent interstitial air, and snow metamorphism were treated in the model. Snow temperatures were calculated using observed air temperatures (annual mean temperature 241 K) and the heat conductivity of the snow. The conductiv- ity was determined using the snow density based on a mea- sured profile. The same density profile was used to calculate the specific surface area, which was subsequently used to es- timate an average radius of the snow grains. The transport in the interstitial air took into account molecular diffusivi- ties, which were corrected according to the snow tempera- ture and the firn density. Fresh snow was regularly added throughout the year, corresponding to a total accumulation of 23 gcm−2 yr−1. As a result, older snow was transferred Atmos. Chem. Phys., 14, 1587–1633, 2014 www.atmos-chem-phys.net/14/1587/2014/ T. Bartels-Rausch et al.: Air–ice chemical interactions 1609 into deeper layers, causing an increase of the snow density according to the employed density–depth relationship, a de- crease in the specific surface area and a corresponding in- crease of the average grain radius. Therefore, the metamor- phism of the snow is represented in the model in a simplified way. The physical cycling – the exchange of impurities between the snow grains and the adjacent interstitial air – was cal- culated based on empirical correlations from field and lab- oratory experiments (Fig. 14) (Conklin et al., 1993; Mc- Connell et al., 1997; Hutterli et al., 1999; Burkhart et al., 2002). In the case of HCHO, the concentrations in the con- densed phase were simulated according to a bulk approach assuming that formaldehyde is mostly adsorbed at the sur- face of the grains. In contrast, for H2O2 it was assumed that it is contained in the bulk solid of the snow grains and not adsorbed at the surface (McConnell et al., 1998). There- fore, a temperature-dependent air–snow partitioning coeffi- cient was employed to determine the equilibrium between firn air concentrations and the concentrations in the outer- most layer of the assumed spherical snow grains. Inside the grains, the transport of H2O2 was simulated using ten spheri- cal layers and a temperature-dependent diffusion coefficient. In the case of H2O2 the empirical equilibrium constant was considerably lower than the extrapolated Henry’s law con- stant. Moreover, the constant decreased strongly from 228 K to approximately 261 K, before slightly increasing at higher temperatures (Conklin et al., 1993). These different temper- ature dependences of the equilibrium may reflect the adsorp- tion processes at very low temperatures and the uptake in the liquid fraction at higher temperatures. Concentrations in the atmospheric boundary layer were used as an upper limit of interstitial air concentrations. These concentrations were derived by offline calculations us- ing a box model with a comprehensive atmospheric chem- istry mechanism. The obtained annual cycles for H2O2 and formaldehyde boundary layer concentrations were scaled to agree with concentrations observed at Summit. The atmo- spheric concentrations were used together with meteorologi- cal observations, such as temperature and humidity, to deter- mine H2O2 and formaldehyde concentrations in fresh snow. Diffusional growth of snow at cloud level is thought to not introduce any fractionation between water and H2O2. Thus, the co-condensation model is applied to calculate the fresh snow concentrations as described in Sigg et al. (1992). The formaldehyde concentrations in the fresh snow were further scaled in order to reproduce observed firn concentrations at greater depths. The co-condensation mechanism caused a su- persaturation of the fresh snow in formaldehyde and H2O2, and only about 50 % of the formaldehyde and H2O2 ini- tially present is preserved in the snowpack and firn. Previous simulations for H2O2 demonstrated that at the snow surface H2O2 in the ice phase was always out of phase with the gas phase due to fast changes in the atmospheric conditions and the snow properties resulting also in a non-uniform distribu- tion of H2O2 inside the grains of the older snow (McConnell et al., 1998). Sensitivity studies further revealed that only the formaldehyde concentrations were significantly affected by the transport in the interstitial air and the accumulation rates, while the effect on H2O2 concentrations remained small for typical Greenland conditions (Hutterli et al., 2003). Tripling Summit accumulation rates of 0.23 gcm−2 yr−1 did not have a large impact on H2O2 preservation. However lower snow- fall rates, like those in Antarctica (0.07 to 0.3 gcm−2 yr−1) demonstrate a large impact of accumulation rate on H2O2 (Frey et al., 2006), suggesting that if surface snow is quickly buried the resulting concentrations can be far away from equilibrium. The modelling study by Hutterli et al. (2003) thus showed that for H2O2 and formaldehyde physical cy- cling dominates in determining concentrations although both compounds undergo photochemical reactions in the snow. Although the presence or absence of liquid and/or a disor- dered interface has been neglected in the models, they have successfully been applied for a wide snow temperature range from 203 K to 273 K. Since recent studies have resulted in independent and more detailed description of the equilib- rium of H2O2 and formaldehyde between the gas phase and the snow, taking into account the adsorption at the surface and the dissolution in the bulk ice phase (Pouvesle et al., 2010; Barret et al., 2011b), new modelling studies using such data are warranted. The application of such upgraded mod- els to the same data sets as in the previous studies based on empirical relationships may be used to investigate whether the laboratory data are sufficient to reconstruct the observed H2O2 and formaldehyde profiles in the snow and in the firn cores and to determine the dominant uptake process for both species. For example, the formaldehyde exchange between the atmosphere and the surface snow has recently been stud- ied by Barret et al. (2011a), measuring formaldehyde simul- taneously in the snow and the atmosphere during a 48 h pe- riod. They were able to reproduce the variations in formalde- hyde snow concentrations using the thermodynamics of the ice–formaldehyde solid solution and by modelling diffusion in and out of snow crystals similar to the approach previously used for H2O2 (Fig. 14). In this study, the authors used the diffusion coefficient of formaldehyde that has been indepen- dently measured in well-controlled laboratory experiments by Barret et al. (2011b) (Sect. 4.2.1) showing that solid-state diffusion resulted in a fourfold increase in snow formalde- hyde over a 48 h period. We refer to the review by McNeill et al. (2012) for a detailed discussion on this topic. 4.5 Conclusions about physical processes Deducing the role and mechanism of surface and bulk uptake to snow and characterising it in laboratory experiments with ice remains a difficult and essential issue for most species. The main obstacle is that solutes can be taken up by different reservoirs: the ice crystal, grain boundaries, on the (disor- dered) surface of ice, and in liquid embedded in the snow. www.atmos-chem-phys.net/14/1587/2014/ Atmos. Chem. Phys., 14, 1587–1633, 2014 1610 T. Bartels-Rausch et al.: Air–ice chemical interactions The uptake routes dominating for individual species or con- ditions are currently unknown, but important underlying pro- cesses have been identified and characterised: 1. On shorter timescales, typical for air–ice exchange, sorption processes usually dominate. Adsorption dom- inates at temperatures below ≈ 250 K and uptake of most trace gases can be parameterised by Langmuir adsorption, even if multiple species are present. 2. The Langmuir-type parameterisation of trace gas ad- sorption might not be adequate when water molecules condense to the ice surface under non-equilibrium con- ditions for those species with a more negative adsorp- tion enthalpy than water on ice. Parameterising the up- take to growing ice needs future attention. 3. Less is known about the role of the disordered inter- face on sorption processes. Current studies focusing on typical snowpack temperatures give little to no evi- dence for a pronounced role of surface disorder in up- take processes. 4. In the presence of liquid, the partitioning of trace gases to snow changes drastically and the overall uptake might no longer be dominated by Langmuir-type ad- sorption to the ice. Possibly, Henry partitioning to the liquid fraction might be better suited to describe sorp- tion to snow. The uptake of trace gases to such wet snows has not been systematically investigated. In par- ticular, as the liquid fraction can be highly concen- trated, it should be verified whether Henry’s law con- stants determined using dilute solutions can be used to describe the equilibrium between the gas phase and the liquid phase present in the snow. Moreover, inter- actions between solutes in brine and between solutes and dissolved gases may have feedback effects on the formation and extent of brine and need to be studied in more detail. 5. Diffusion can take place in the solid ice matrix, along grain boundaries, on the surface, and in the liquid phase embedded in surface snow. The presence of im- purities can significantly influence diffusion rates and solubility by preferentially trapping certain species. Formation of ice solid solutions of small molecules such as methanol and formic acid deserves investiga- tions. NH3 is a particular case with an extremely rapid diffusion in bulk ice even at low temperatures. This makes NH3 a further candidate for uptake into the ice matrix at polar conditions, even though measurements at relevant temperatures are missing. 6. At temperatures close to the melting point, where the disordered interface is thick, the self-diffusion on the ice surface is essentially the same as that in super- cooled water. Outer surface layers diffuse more rapidly than inner layers, which makes the ice surface very different from a bulk liquid. Even in thick films cov- ering the surface, diffusion in the layers close to the surface is highly influenced by interactions with the surface molecules. Moreover, an analysis of the activa- tion energy of the diffusion reveals the opposite tem- perature dependence to what has been found in liquid water, and diffusion of ions on thin disordered layers is strongly influenced by the underlying crystal. All of this indicates that the diffusion mechanism is very dif- ferent in the disordered interface from diffusion in su- percooled water. Describing the diffusion of water in the disordered interface as liquid-like might however be a reasonable simplification: MD simulations show a sharp transition of the diffusion mechanism above 240–250 K where the diffusion constant in the upper layer of the disordered interface approaches that of su- percooled water at high temperatures. 7. Previous models to simulate the physical exchange of species like H2O2 and formaldehyde used empirical parameterisations to describe the equilibria between gas phase and condensed phase. These parameterisa- tions were developed using field observations at dif- ferent polar sites and reflect the overall exchange pro- cesses between the snow and the firn air. Using new ex- perimental results and new parameterisations these ex- change processes may be better specified in upgraded models and compared to available long-term observa- tion as in the previous modelling studies. Such simula- tion may help to better characterise driving processes for the exchange of reactive species between the snow and the atmosphere. 5 Chemical processes In recent decades numerous field and laboratory studies have established that snow hosts unique chemical reactions with large-scale impacts on air quality, climate change, and bio- chemical cycles (Klán and Holoubek, 2002; Grannas et al., 2007b; Simpson et al., 2007; Steffen et al., 2008). A uni- fied picture to describe the reactivity of chemical species in snow is still missing. In particular, detailed kinetic studies are rare and, thus, the following discussion is mostly based on observed rates of product formation or the decay of the starting compound. In that sense, some reactions are accel- erated compared to the unfrozen, liquid sample – with the same amount of reactants – at room temperature. Those ex- periments indicated that the apparent reaction rate can be en- hanced up to a factor of ten (Grannas et al., 2007a; Kahan and Donaldson, 2008; Weber et al., 2009; Kahan and Don- aldson, 2010). Other chemical systems displayed similar ap- parent reaction rates in frozen and liquid samples (Dubowski and Hoffmann, 2000; Klánová et al., 2003a, b; Ružicˇka et al., 2005; Matykiewiczová et al., 2007a; Anastasio and Chu, Atmos. Chem. Phys., 14, 1587–1633, 2014 www.atmos-chem-phys.net/14/1587/2014/ T. Bartels-Rausch et al.: Air–ice chemical interactions 1611 2009; Ram and Anastasio, 2009; Galbavy et al., 2010; Ka- han et al., 2010c; Beine and Anastasio, 2011; Gao and Ab- batt, 2011). In addition, a third kind of systems showed up to 10-times slower reactions in snow than in liquid samples for the same total concentration of reactants (Klánová et al., 2003a; Ružicˇka et al., 2005; Matykiewiczová et al., 2007a; Anastasio and Chu, 2009; Bartels-Rausch et al., 2011; Beine and Anastasio, 2011; Gao and Abbatt, 2011). Reactions oc- curring in the liquid phase during the freezing process gener- ally show a large, up to 105, increase of the apparent reaction rates (Pincock, 1969; Takenaka et al., 2003). Although we are far from reaching a detailed, quantita- tive understanding of the chemistry occurring in snow, re- cent studies have identified several factors to explain the ob- served changes in reactivity. These factors, as discussed in the following, are the increased concentration, changes in re- action mechanisms, the temperature dependence of the re- action, the local chemical environment, and the location of the reactants. The combination of all these factors controls the observed rates in snow and the question arises of which processes dominate the overall chemical reactivity in snow. 5.1 Local concentration High reactant concentrations are a major reason for the en- hanced reactivity observed in snow or in ice samples used in laboratory studies to mimic environmental snow. Figure 15 shows an example in which such an enhanced concentration accelerates bimolecular reaction steps, such as the photolytic reaction between p-nitroanisole and pyridine (Grannas et al., 2007a). 5.1.1 Freeze-concentration effect Early atmospheric chemistry work by Takenaka et al. (1992) observed a 105 acceleration rate for the oxidation of nitrite by oxygen during freezing. This implies that a reaction that is usually slow and thus negligible in the liquid phase – such as the conversion of nitrite to nitrate by oxygen – becomes important enough to modify the composition of the sample during freezing. Takenaka et al. (1992) discarded any cat- alytic properties of the ice surface to produce this acceler- ation. The dependence of the rate on the enhanced concen- tration due to the volume of liquid brine reduction during freezing was later confirmed (Finnegan, 2001; Takenaka and Bandow, 2007; Grannas et al., 2007a; Wren et al., 2010). This conclusion holds for soluble species and bimolecular (or higher-order) reactions. One important consequence of this freeze concentration for environmental chemistry is that it can lead to new products and reaction pathways. Sodeau and co-workers have recently identified new reaction path- ways for the release of nitric oxide and halogen species to the atmosphere from the freezing of sea salt solutions, of- ten via trihalide ions (O’Concubhair et al., 2012; O’Driscoll et al., 2008; O’Concubhair and Sodeau, 2012; O’Sullivan Fig. 15. Observed reactivity of p-nitroanisole in frozen aqueous so- lutions as a function of total solute concentration adjusted by the addition of NaCl at 269 K (filled circles), 254 K (filled triangles), and 242 K (open triangles). The lower the NaCl concentration, the smaller the volume of brine. The higher concentration of the bi-molecular reaction partners, p-nitroanisole and pyridine in the smaller liquid volume might explain the apparent higher reactiv- ity with lower total solute concentration. Reprinted with permission from Grannas et al. (2007a) Copyright (2007) American Chemical Society. and Sodeau, 2010). Of relevance for the cryospheric commu- nity, dissolved elemental mercury is oxidised to Hg2+ when frozen in the presence of oxidants such as hydrogen perox- ide, nitrous acid, or sulfuric acid and oxygen (O’Concubhair et al., 2012). The apparent rate of chemical reactions during the freezing process is further influenced by other factors, such as changes in pH (O’Sullivan and Sodeau, 2010). While freezing a solution, once the temperature drops be- low the eutectic point, the bulk liquid solidifies if nucleation is induced. This phase change is accompanied by reactivity changes. For example, the reactivity during the freezing pro- cess was observed to cease once the sample completely solid- ifies, as described in the early work by Takenaka et al. (1996). 5.1.2 Local concentration in bulk ice High local concentrations observed during the freezing pro- cess may prevail in frozen samples. A particular study showed that local concentrations were enhanced by 106 in frozen samples upon slowly freezing aqueous solutions (Heger et al., 2005). High concentrations can enhance the reactivity, such as the photolytic reaction between p- nitroanisole and pyridine (Grannas et al., 2007a), the pho- todegradation of organophosphorus pesticides (Weber et al., 2009), the photolysis of polycyclic aromatic hydrocarbons (Kahan et al., 2010c), or the photoreduction of ferric ions in ice by organic molecules (Kim et al., 2010). The chemistry in www.atmos-chem-phys.net/14/1587/2014/ Atmos. Chem. Phys., 14, 1587–1633, 2014 1612 T. Bartels-Rausch et al.: Air–ice chemical interactions Fig. 16. Major photolysis products of 2-chlorophenol (1) in ice and in water. In ice chlorobiphenyldiol coupling products are found, in water 2-chlorophenol forms pyrocatechol. Reproduced from Klánová et al. (2003a) with permission from The Royal Society of Chemistry. mixtures of metals and organics illustrates how the reactiv- ity in ice is linked to the freezing process (Kim et al., 2010; Bartels-Rausch et al., 2011): during freezing the metal forms complexes with organic electron donors due to the freeze- concentration effect. Upon photolysis of the frozen sample, the newly formed ligand–metal bond absorbs the photon that initiates the intramolecular redox process. Intermolecular re- dox reactions could increase their efficiency towards electron transfer with higher concentrations and contribute further to enhanced reaction rates. A quantitative description of the re- action rates is often hampered because the local concentra- tions of reactants are unknown. 5.1.3 Local concentration at surface Enhanced local concentrations of aromatic compounds such as benzene and naphthalene account for faster apparent pho- tolysis rates at ice surfaces (Kahan and Donaldson, 2010; Ka- han et al., 2010c). Considering that unimolecular reactions are not per se concentration-dependent, therefore, in such cases rather the absorption spectrum changes. In aqueous so- lutions, as well as in the gas phase, benzene does not absorb radiation at wavelengths longer than ≈ 290 nm, and naphtha- lene absorbs only weakly. On ice, however, the absorption spectra of both molecules are redshifted compared to those in dilute solutions due to self-association of benzene and of naphthalene molecules. 5.2 Mechanism Klán and co-workers observed remarkable mechanistic dif- ferences during the photoreaction of halogenated aromatic compounds in frozen and liquid aqueous solutions (Fig. 16). Dehalogenation and bimolecular (radical coupling) reactions occurred below approximately 266 K instead of the photo- solvolysis in liquid media (Klán et al., 2000; Klán et al., 2001; Klán and Holoubek, 2002; Klánová et al., 2003a, b; Ružicˇka et al., 2005; Matykiewiczová et al., 2007a, b). The environmental impact is related to the higher toxicity of the reaction products in ice than in water (Bláha et al., 2004). Increased local concentrations and/or the lack of sufficient water to act as a nucleophile in ice were invoked as rea- sons for a different reaction pathway in the frozen samples. The mechanistic change also affected the apparent reaction rates (Klánová et al., 2003a): no apparent enhanced rate was observed for these degradations in ice despite the high lo- cal concentrations. A drawback to most of these studies is that they were performed at higher concentrations than typ- ically present in the environment; these high concentrations might contribute to the unique chemistry observed. The pho- tochemical degradation of persistent organic compounds at environmentally relevant concentrations showed that differ- ent products were formed from those observed at higher con- centrations (Matykiewiczová et al., 2007a). Remarkably, it was confirmed that solvolysis did not occur for this type of compounds in ice. The importance of the reaction mechanism on the ob- served rates in ice and snow is also evident from unimolec- ular reactions, which are per se concentration-independent, and which often proceed with similar efficiencies in frozen and liquid solutions. For example, the production of hydroxyl radicals from the photolysis of precursors such as H2O2 (Chu and Anastasio, 2005; Jacobi et al., 2006), NO−3 (Dubowski et al., 2002; Chu and Anastasio, 2003; Jacobi et al., 2006; Matykiewiczová et al., 2007b) and NO−2 (Jacobi et al., 2006; Chu and Anastasio, 2007; Matykiewiczová et al., 2007b) are generally reported to proceed through similar mechanisms with comparable absorption spectra and quantum yields in frozen and liquid solutions. More-recent lab studies at high surface coverages of nitrate at the air–ice interface call this result into question (Zhu et al., 2010). While the initial pho- tolysis of these reactions is clearly a unimolecular step, it might be followed by more complex reactions such as the self-reaction of HO2 to produce H2O2. If such back-reactions are favoured, the overall product formation might decrease significantly (Dubowski et al., 2002; Beine and Anastasio, 2011). Such changes in the relative importance of individual reaction pathways might also explain why the two-step re- duction of Hg(II) in the presence of organic electron donors decreases in ice compared to water (Bartels-Rausch et al., 2011). 5.3 Reactions in the presence of solutes Directly comparing the reactivity in frozen systems to reac- tivity in liquid–solid multiphase systems has been the fo- cus of some recent studies (Guzmán et al., 2007; Grannas et al., 2007a; Kahan et al., 2010a; Gao and Abbatt, 2011). Photolytically driven bimolecular reactions of water-soluble organics were found to proceed faster in mixtures of ice and brine compared to completely frozen systems (Grannas et al., 2007a; Gao and Abbatt, 2011). In the study by Grannas et al. (2007a) NaCl was added to the sample to vary the amount of brine at a given temperature (Fig. 15). Comparison of the Atmos. Chem. Phys., 14, 1587–1633, 2014 www.atmos-chem-phys.net/14/1587/2014/ T. Bartels-Rausch et al.: Air–ice chemical interactions 1613 rates above and below the eutectic point for a given system revealed a strong dependency on concentration: at low salt concentrations, lifetimes of water-soluble organics increased when the temperature was lowered below the eutectic; at higher concentrations the observed lifetimes were longer at temperatures above the eutectic. In contrast, water-insoluble organic aromatics were found to be photolysed faster on ice surfaces in the absence of brine (Kahan et al., 2010a). Vary- ing the amount of brine systematically, the chemistry could be tuned from that observed at a pure ice surface (fast) to that observed in aqueous solution (slow) (Kahan et al., 2010a). The possibilities that chemistry in partially frozen samples may differ from chemistry in solid ice samples and that chemistry in brine might be more important than reactivity in completely frozen samples complicates the analysis of ex- periments. This becomes clear when reactions are monitored continuously during the freezing process and in the com- pletely frozen sample. For example, Kim and Choi (2011) described an enhanced reduction of chromate and arsenite in frozen ice. Since the samples were prepared from liquid solu- tions and based on the observed time dependence (Kim and Choi, 2011), it is proposed here that the major part of the observed chemistry occurred during the freezing process in agreement with the freeze-concentration effect discussed. 5.4 Chemical environments Ice and snow in the environment contain complex mixtures of chemicals, each of which can participate and alter chemical reactions (Grannas et al., 2007b). For example, organic chro- mophores act as photosensitisers that promote photochemi- cal reactions (Bartels-Rausch et al., 2010, 2011), and produce reactive species such as OH radicals (Grannas et al., 2007b; Dolinová et al., 2006). They also suppress photochemical re- actions by acting as a filter of light and by scavenging reac- tive species (Grannas et al., 2007b). The environmental im- portance of organic compounds in ice is discussed in detail by McNeill et al. (2012) and Grannas et al. (2013). Abida and Osthoff (2011) recently reported that organic co-solutes ranging from formate to phenol inhibited the release of gas- phase NO2 from nitrate photolysis in ice, likely due to scav- enging of OH. However, halogenated phenols enhanced NO2 production. The finding was related to the acidification that the ice surface underwent following the formation of HCl upon oxidation of the halogenated phenol. A suppression of mercury photoreduction was observed in ice doped with halogens and organic chromophores (Bartels-Rausch et al., 2011). The observed decrease in Hg(0) production in the presence of chloride was attributed to the formation of ox- idising halogen species or to chloride binding to mercury in concentrated brine solutions upon freezing, which might limit its reactivity (Bartels-Rausch et al., 2011). Organic co- solutes can also act as hydrogen donors upon photolysis of organic chromophores in ice (Matykiewiczová et al., 2007b). In the presence of several different types of chromophores the apparent rate of direct photolysis might be surpassed by bimolecular reactions involving photolytically produced rad- icals. Anthracene and naphthalene undergo photolysis at ice surfaces with no photolytic enhancement in the presence of nitrate or H2O2. The lack of any photolytic enhancement in- dicates that the indirect bimolecular degradation is slower (Kahan and Donaldson, 2008). The competition of primary photochemical processes and hydroxylation in the presence of H2O2 was reported (Klánová et al., 2003a; Dolinová et al., 2006). The reactivity of single reactants can change when its solubility limit is reached, resulting in physical separation of the reactants during freezing (Gao and Abbatt, 2011). In this study the reactivity of OH towards succinic acid in ice was lower than in aqueous solution, while no significant change was observed for malonic acid, which has the higher solubil- ity in water of these two molecules. Local pH can be significantly altered during freezing, and can affect the acid–base equilibrium as well as reactivity of the solutes. For example, the presence of organic acids can result in a 100 to 104 increased protonation of cresol red relative to liquid solutions, which was attributed to the higher local concentration of acids at the grain boundaries due to the freeze-concentration effect during sample prepara- tion (Heger et al., 2006). Such pH changes can significantly alter the chemistry during the freezing process, promoting pathways that do not occur in the unfrozen liquid (O’Sullivan and Sodeau, 2010). This change in local pH possibly af- fects the chemical reactions even after complete freezing. A slight increase in the apparent photolysis rate of NO−3 oc- curred with increasing pH (Chu and Anastasio, 2003), while the production of gas-phase NO2 increased with decreas- ing pH (Abida and Osthoff, 2011), and additional gas-phase products including HONO, HONO2, HO2NO, and HO2NO2 were detected at pH< 4.5 (Abida and Osthoff, 2011). The importance of these species to ice chemistry has been pre- sented (Riordan et al., 2005; Hellebust et al., 2007, 2010). The photolysis of HONO in ice yielded approximately eight times more NO and OH than the photolysis of H2ONO+ in ice (Chu and Anastasio, 2007). Faster photoreduction of Fe+3 and Cr(VI) occurred in veins than in aqueous solution at lower pH due to the exclusion of protons that accompa- nies the freezing process (Kim et al., 2010). The release of HONO from the photosensitised reduction of of NO2 in ice doped with humic acid follows the expected pH dependence if freeze-induced pH changes are accounted for (Bartels- Rausch et al., 2010). The apparent photolysis rate of H2O2, NO−3 , and NO − 2 in bulk ice samples was demonstrated to be independent of pH (Chu and Anastasio, 2003, 2007). Further, reaction efficiencies and product yields of halogen chemistry in ice are influenced by local pH as discussed in Abbatt et al. (2012). A final note here is that ammonium nitrate on ice can be photolysed to release N2O, a process that is quite different from the photolysis of nitric acid on ice (Koch et al., 1996). www.atmos-chem-phys.net/14/1587/2014/ Atmos. Chem. Phys., 14, 1587–1633, 2014 1614 T. Bartels-Rausch et al.: Air–ice chemical interactions Fig. 17. The effect of a different chemical composition of the ice matrix on the photochemistry of mercury during 30 min irradiation with UVA at 258 K (sectors A−C). Also, blank experiments in the dark are shown for comparison (sector D). The solution to freeze the ice films was always doped with Hg(II) (6×108 M) and additionally contained the following compounds as indicated: “no OC” denotes experiments of pure HgO solutions; “BPh” of 6×107 M benzophenone in unbuffered solutions at pH 7 (of the molten ice film); “BPh/pH 9” and “Ph/pH4” NaOH and H2SO4 added to 6×107 M benzophenone to reach a pH of 9 or of 4, respectively; “Ph/Br−” 6×107 M benzophenone and 5×108 M bromide; “BPh/Cl−” 7×108 M chloride, “BPh/sea” 0.5 M chloride, 1 mM bromide; “BPh/air” 6×107 M benzophenone in the ice, 20 % oxygen present in the carrier gas stream; “BPh/Ph” 5×107 M benzophenone and 6×108 M 2,6-dimethoxyphenol. In each box, the central mark is the median, the edges of the box are the 25th and 75th percentiles, and the whiskers extend to the most extreme data points. Reprinted with permission from Bartels-Rausch et al. (2011). Copyright (2011) Elsevier. Fig. 18. Formation of phenol from in situ photolysis of H2O2 in the presence of benzene in liquid solution and different ice samples. Phenol concentration is plotted as a function of irradiation time for samples containing 1 mM benzene and 0.9 mM H2O2. The solid traces are linear fits to the data, and error bars represent one standard deviation about the mean for at least three trials. Reprinted from Kahan et al. (2010b). Copyright by the authors. 5.5 Physical environments Besides the local differences in concentration and chemical environment, the location where reactions occur will affect the fate of the reaction products, its distribution, and ap- parent rates. The previous considerations were used to de- scribe the approximately 50 % reduced photoreactivity of H2O2 in flash-frozen samples compared to aqueous solu- tions or slowly frozen samples (Beine and Anastasio, 2011). Dubowski et al. (2001) determined that NO2 produced from NO−3 in the uppermost region of the spray-frozen ice sam- ples was able to escape to the gas phase, while that produced at greater depths was photolysed to NO. Subsequent studies also concluded that the detection of NO−2 is only possible after the initial photo fragments (i.e. NO−2 and O) escape the ice cage surrounding them (Chu and Anastasio, 2003, 2007; Anastasio et al., 2007). Kahan et al. (2010a, c) ob- served similar apparent rates for unimolecular and bimolec- ular reactions occurring in large ice cubes and in aqueous solution. However, the apparent reaction rates in ice gran- ules with larger surface-to-volume ratios (formed by crush- ing the ice cubes) were the same as those measured in situ at ice surfaces (Kahan et al., 2010a, c) (Fig. 18). In ice cubes, reagents are located primarily in the bulk ice, and bulk kinet- ics govern the reactions monitored after thawing the samples. Instead, high surface area samples showed that surface pro- cesses dominate offline measurements, implying that more reagent was located at the surface (Kahan et al., 2010a, c). Similar observations were made for species doped to arti- ficial snow from the gas phase and by freezing from solu- tion (Ružicˇka et al., 2005; Kurková et al., 2011)s . The high surface-area-to-volume ratio of artificial snow maximises the distribution of reagents at the surface, regardless of the sam- ple preparation method. From an atmospheric perspective, reactions at the ice- surface–air interface are important because products are readily available to escape the ice phase. Many studies in- dicate that the chemistry on the ice surface is distinctly dif- ferent from that observed in ice, in bulk water, and also on water surfaces. Scientists often use indirect methods to study reactions at ice surfaces, for example by probing the gas Atmos. Chem. Phys., 14, 1587–1633, 2014 www.atmos-chem-phys.net/14/1587/2014/ T. Bartels-Rausch et al.: Air–ice chemical interactions 1615 phase above an ice sample. We refer the reader to Huthwelker et al. (2006) for a detailed discussion on experimental meth- ods. In those experiments probing surface reactions is usually achieved by using ice samples with a high surface-to-volume ratio (e. g. Abbatt et al., 1992; McNeill et al., 2007; Bartels- Rausch et al., 2010; Kurková et al., 2011). However, these studies give no direct evidence for the surface reactions, as discussed in Bartels-Rausch et al. (2011). Monitoring reac- tions at the ice surface requires in situ analysis, which has been done in a limited number of spectroscopic experiments in the IR (e.g. Hellebust et al., 2007) and UV/VIS (e.g. Ka- han et al., 2007). The advantage of the UV/VIS spectroscopy approach is that it can be operated at temperatures typical for environmental snowpacks. A number of recent studies show that gas–ice-surface reac- tions at temperatures approaching the melting point are best described as heterogenous processes, and that the rates of these reactions are very different from those in the aqueous phase or on water surfaces. The ozonation of phenanthrene and 1,1-diphenylethylene deposited from the gas phase was accelerated at ice and artificial snow grain surfaces com- pared to liquid water surfaces (Kahan and Donaldson, 2008; Ray et al., 2011). Recently, a remarkable and unexpected in- crease in the apparent ozonation rates on ice surfaces with decreasing temperature was evaluated using the Langmuir– Hinshelwood and Eley–Rideal kinetic models, and by esti- mating the apparent specific surface area of the ice grains (Ray et al., 2013). It was suggested that an increase of the number of surface reactive sites and possibly higher ozone uptake coefficients was responsible for the apparent rate ac- celeration of 1,1-diphenylethylene ozonation at the air–ice interface at lower temperatures. Other examples are the halo- gen emissions from frozen sea ice solutions upon reaction with ozone or OH and the heterogeneous reaction of hypo- halogenic with halogen acids as recently discussed in detail (Abbatt et al., 2012). The heterogeneous photosensitised re- duction of inorganic species such as NO2 has been investi- gated in the presence of humic substances and proxies for these species. These reactions are likely due to energy trans- fer from the humic substance to the reagent on the ice sur- face (Bartels-Rausch et al., 2010). The last study found that the reaction rate depends linearly on the concentration of the organic compounds for low total concentrations in the ice sample. There was good agreement between the extrap- olation of reported reaction rates on ice and experiments on pure organic films, suggesting similar reactivity on both surfaces. For intermediate concentrations of humic acids in the ice film, the linear correlation broke presumably due to an agglomeration effect that reduced the amount of organic molecules accessible to the gas-phase NO2. Some differences in heterogeneous reaction rates at ice and water surfaces are not easily described by known reac- tion mechanisms. For example, hydroxyl radicals react less efficiently with aromatic compounds at ice surfaces than at liquid water surfaces or bulk ice (Kahan et al., 2010b). High conversion efficiencies were reported for the photolysis of aromatic compounds such as benzene, naphthalene, an- thracene, and harmine (Kahan and Donaldson, 2007, 2008; Kahan et al., 2010a). The faster loss of benzene and naph- thalene are due at least in part to their aggregation to form dimers at ice surfaces, where they experience a redshift in the absorption spectra as compared to aqueous solutions, but aggregation does not explain the photolysis behaviour of an- thracene and harmine at ice surfaces (Kahan and Donaldson, 2007; Kahan et al., 2010a). Under the same experimental conditions, anthracene photolysis in bulk ice proceeded at the same apparent rate as in aqueous solution (Kahan et al., 2010c). The observed rates did not depend on temperature in aqueous solutions (274–297 K) or at the ice surface (257– 271 K) (Kahan and Donaldson, 2007). Faster photolysis rates at the ice surfaces were explained in terms of its different physicochemical properties compared to liquid water. Differ- ent absorption spectra of inorganic acids on ice and in aque- ous solution make the adsorbed species more susceptible to photodissociation as discussed further in Abbatt et al. (2012). Such shifts in the absorption maxima allowed the evaluation of the nature and magnitude of the intermolecular interac- tions of both species in ice at 253 and 77 K (Heger and Klán, 2007). The presence of water in close vicinity to the probe molecules and the intermolecular interactions within the self- assembled molecular aggregations were believed to cause the observed shift of the absorption spectra. Enhanced ice–solute or solute–solute interactions have recently been visualised as a cage effect in which the boundaries of the cage are defined by the walls of the micro-pocket or vein that the reagents are trapped in. In the confined space of the cage, reagents and intermediates are unable to diffuse away from one another, so the cage effect reflects an enhanced reactivity unless an irreversible loss occurs (Ružicˇka et al., 2005). For a detailed discussion on the photochemistry of organic molecules in ice and on the cage effect we refer the reader to McNeill et al. (2012). McNeill et al. (2006, 2007) used ellipsometry to iden- tify an increased surface disorder at temperatures as low as 200 K caused by doping the ice surface with HCl. They re- ported the enhanced apparent rate when HCl reacted with ClONO2 for the dopant-induced disorder condition at low temperatures. At higher temperatures, surface disorder is om- nipresent (Sect. 3.3). For these conditions, Kahan and Don- aldson (2007) observed a constant apparent photolysis rate for anthracene on the ice surface between 257 and 271 K. For other species, it was argued that liquid-like properties of the disordered interface facilitate heterogeneous reactions. For example, the reaction of SO2 with H2O2 proceeds via hy- drolysis of SO2 on the ice surface (Clegg and Abbatt, 2001) and was thus suggested to be enhanced by surface disorder. Taken together, these studies show that adsorbates and molecules that were doped to the air–ice interface by freez- ing a solution in most cases show chemical rates that are best described by heterogeneous processes. Even at temperatures www.atmos-chem-phys.net/14/1587/2014/ Atmos. Chem. Phys., 14, 1587–1633, 2014 1616 T. Bartels-Rausch et al.: Air–ice chemical interactions Fig. 19. Observed quantum yield of OH production from H2O2 photolysis in water and ice (red dots). The slopes for our liquid (blue solid line) and ice (blue dashed line) results are statistically differ- ent at the 87 % confidence level, and the slope for the ice data shows a stronger temperature dependence. Comparison to earlier data by Chu and Anastasio (2005) (black dashed line) shows that observed kinetics critically depend on the type of ice matrix: the slope for the liquid data is identical to the earlier results for liquid and solid phases (black dashed line). The slope for the shock-frozen ice data (blue dashed line) indicates a stronger temperature dependency than results for slowly frozen ice samples (black dashed line). Reprinted from Beine and Anastasio (2011). Copyright (2011) John Wiley and Sons. approaching the melting point (≈ 10 K below eutectic tem- perature), chemical reactivity at the air–ice interface differs from that of the air–water interface and of bulk aqueous so- lutions. Thus, surface disorder seems not to justify the use of bulk rates to describe reactivity of the mostly insoluble organics studied at the air–ice interface at these high temper- atures. The reactivity of aerosol deposits at the air–ice interface has not been studied in detail in well-controlled laboratory studies. Given their reactivity throughout the troposphere (George and Abbatt, 2010), a critical role in snow chemistry as a source of volatile organic compounds has been proposed (Domine and Shepson, 2002). We refer the reader to Domine et al. (2013) for an in-depth discussion on this topic. 5.6 Chemical processes in models Models that include complex snowpack chemistry are rapidly emerging. Some of these models simulate the impact of chemistry in snow on the composition of air in the bound- ary layer (Michalowski et al., 2000; Boxe and Saiz-Lopez, 2008; Thomas et al., 2012). Central to these models is that all chemical reactions are parameterised to occur in a liquid en- vironment in contact with air. For example, measured liquid rate constants and Henry’s law constants are applied to a liq- uid fraction of the snow volume and used to approximate the behaviour of the snowpack. Such an approach allowed us- ing knowledge from liquid aerosol models to develop snow- chemistry models. It was further motivated by early labo- ratory work that showed the behaviour of some chemicals in frozen samples may be approximated by treating them analogously to solvated species (Sect. 5.2). An example is nitrate photolysis (Dubowski et al., 2002; Chu and Anasta- sio, 2003; Jacobi et al., 2006; Matykiewiczová et al., 2007b), even though discrepancies between model predictions based on this simplification and field observations of NOx emis- sions from snow remain (Frey et al., 2013). From a critical standpoint, the generalised concept of a surface disorder with liquid-like properties that is used to justify this approach at subfreezing temperatures is an over-simplification (Sects. 3 and 4.1). Clearly, the majority of chemical systems studied so far in ice samples show a distinctly different behaviour than that seen in liquid probes, so that a general use of aqueous- phase chemistry may be questioned and needs to be carefully re-examined in the future (Sect. 5.2). However, it is also clear that liquid might be present in surface snow at environmental conditions (Sect. 2.1), and for those instances chemical trans- formations might be well captured by this model approach. This section shows below how these models, including liquid-phase mechanisms, can capture observed fluxes and/or concentrations of trace gases measured above the snowpack. The outcome of these models can thus be used to evalu- ate whether snowpack chemistry alone can produce elevated concentrations of species such as bromine monoxide. Treat- ment of photochemistry in surface snow and ice has focused on halogens and nitrate, because laboratory and field studies have clearly shown that both reactive halogens and nitrogen oxides are emitted from irradiated snow and ice. Liao and Tan (2008) integrated simplified chemistry in a 1- D snow model aiming to simulate the formation of HONO in the snow during a 6-day period at the South Pole using prescribed and constant concentrations of nitrate and nitrite. The chemical reactions included the photolysis of NO−3 as- sumed to form directly HONO and the photolysis of HONO as its only sink. Subsequently, photolysis rates were calcu- lated based on the simulated spectral actinic fluxes within the porous snowpack. Due to the fast photolysis of HONO in the surface layers this region did not contribute to a net produc- tion of HONO in the snow. Only with the increased vertical transport due to wind-pumping could the HONO produced in the deeper layers efficiently be transported to the surface and into the atmosphere. Overall, the photolysis of nitrate re- mained smaller than the HONO loss to the atmosphere. Ob- viously, the simplified parameterisation of snow chemistry as done in this model does not adequately describe the obser- vations. For example, an additional source of HONO would be needed to close the reactive nitrogen budget. However, the simulation is based only on a few, selected reactions, and the results were not constrained by observations. The results were highly sensitive to pH, the volume of the liquid fraction, and the initial NO−2 concentration. Atmos. Chem. Phys., 14, 1587–1633, 2014 www.atmos-chem-phys.net/14/1587/2014/ T. Bartels-Rausch et al.: Air–ice chemical interactions 1617 Earlier work using a multiphase box model focused on halogen activation and ozone depletion events in the coastal Arctic region (Michalowski et al., 2000). The boundary layer was modelled using aerosol- and gas-phase chemistry. Snow and aerosol chemistry was simulated with 16 reac- tions related to the activation of reactive bromine and chlo- rine species. The free troposphere was treated as an ozone reservoir, with downward mixing of ozone to the bound- ary layer. The four model components (liquid fraction in snow, boundary layer gas phase, aerosols, and free tropo- sphere) were in contact using transfer coefficients. For the exchange between the boundary layer and the liquid frac- tion in the snow, transfer functions for HOBr, HOCl, HBr, HCl, and O3 were chosen in the range of dry deposition ve- locities to the snow surface. The release of volatile species from the liquid fraction of the snow back to the boundary layer occurred via two steps from the liquid to the inter- stitial air and from there to the boundary layer. First-order rate coefficients for transfer of molecular halogen species (Br2, Cl2, and BrCl) from the interstitial air to the bound- ary layer were also chosen similar to the dry deposition ve- locities. Using the boundary layer height and the snowpack depth along with the transfer coefficients, the rate of mixing between the interstitial air and boundary layer gas-phase vol- ume was determined. This model showed for the first time emissions of halogens from the surface snow could induce a complete ozone depletion event. The predicted ozone de- pletion event was five days after model initialisation. The study indicated the important role of atmospheric particles in contributing to ozone depletion, because removing particles delayed the onset of the ozone depletion event by two days. The model further showed that, without the influence of the snowpack, no ozone depletion was predicted. In particular this work demonstrated that the concept to restrict chemistry in the snowpack to a liquid fraction, given that all ions were concentrated in this volume, gave reasonable results for typi- cal coastal Arctic conditions. The sensitivity of model results to the volume of the liquid fraction showed that increasing the volume decreases concentrations and slows the release of halogens. Choosing an appropriate volume of the liquid frac- tion that represents natural snow reasonably is an obstacle in models. Melting point depression by impurities and geo- metric constraints might be used at temperatures above the eutectic point. At lower temperatures, models often use the thickness of the disordered interface. This is also problem- atic, because measurements do not give a consistent picture yet (Sect. 3.3) and this parameter needs thus to be assumed so that simulation results match observations. Interestingly, a recent re-run of a specific nitrate snow-chemistry model where the liquid fraction was reduced by a factor of up to 100 showed that the overall results were surprisingly robust and only slightly sensitive to the assumed volume of the liquid fraction, when other parameters – such as solubility limits – were accounted for and concentrations adjusted (Bock and Jacobi, 2010; Jacobi, 2011). Using an approach similar to Michalowski et al. (2000), Boxe and Saiz-Lopez (2008) applied a 0-D multiphase model to study NOx emissions to the boundary layer resulting from photolysis of nitrate (NO−3 ) and nitrite (NO−2 ) impuri- ties in snow. In order to calculate volume fluxes (a surface flux distributed throughout the boundary layer) the model also utilised a volumetric factor (1.22× 103) which they de- scribed as a reaction rate enhancement factor. The calculated fluxes from the 0-D model were then used in a 1-D model to predict the NO and NO2 vertical profiles as a function of height above the snowpack. While this study did not include a description of snow physics, the volume fluxes predicted from the model are in good agreement with prior work in Antarctica (Jones et al., 2011) and provided an initial step towards understanding the feasibility of predicting the mea- sured fluxes using a model. The first full 1-D model of air–snow interactions was pre- sented by Thomas et al. (2011, 2012). While simple and rea- sonable in the representation of snow physics, the model in- cluded the most sophisticated reaction mechanism for air– snow interactions involving NOx to date. The model was used to understand both NO and BrO measurements at Sum- mit, Greenland, during a three-day focus period of summer 2008. For the purposes of their study, Thomas et al. (2011) used primarily aqueous-phase chemistry to describe the liq- uid layer and varied the initial nitrate concentrations in the liquid volume so that the model results matched measured NO concentrations in the boundary layer. The remaining fraction of nitrate was treated as unavailable for photochem- istry. This was motivated, in part, by an observed fractiona- tion of nitrate between the ice surface and interior reservoirs in a recent laboratory study (Wren and Donaldson, 2011). If nitrate, in fact, is more concentrated in the liquid layer, then it is possible that nitrate reacts via different pathways in en- vironmental snow, for example with precipitates or with or- ganic molecules. For halogens, this study included all of the measured halide ions in melted surface snow (Br and Cl) in the reactive liquid volume. The concentrations for formalde- hyde and H2O2 were initialised according to their aqueous Henry’s law equilibrium concentrations. Mass transfer was treated according to Schwartz (1986), including diffusion- limited Henry’s law equilibrium to the liquid fraction and the interstitial air. In the snowpack photolysis rates varied with depth according to measured e-folding depth for nitrate at Summit. This study showed that reactions in the liquid layer followed by transfer to the interstitial air and venting of the snowpack (by wind pumping and diffusion) can ex- plain the levels of NO and BrO measured at Summit. How- ever, it required the assumption that not the entire nitrate is available for photolysis to match field observations. There- fore, either reaction rates in the snow are indeed different from those in the liquid, or nitrate preferentially does not accumulate in the liquid fraction of snow. The use of other aqueous-phase parameters, such as Henry law’s constant and www.atmos-chem-phys.net/14/1587/2014/ Atmos. Chem. Phys., 14, 1587–1633, 2014 1618 T. Bartels-Rausch et al.: Air–ice chemical interactions acid–base equilibrium, or the location of the reactive liquid could also affect the model. More recently, Toyota et al. (2013b, a) have developed a snow-boundary layer 1-D model of bromine, ozone, and mer- cury chemistry (PHANTAS) that was used to study ozone de- pletion events in the Arctic (Toyota et al., 2013b). The model uses a similar approach to that of Thomas et al. (2011) for modelling the snowpack, with a few notable exceptions. In PHANTAS, the concentration of chloride in the snow liq- uid fraction is given as a function of temperature accord- ing to Cho et al. (2002). In addition, the model includes vertical diffusion in the condensed phase of the snowpack for species dissolved in the liquid fraction. This study sug- gests that bromine release from the snowpack is sufficient to lead to an ozone depletion event, which is in agreement with recent experiments by Pratt et al. (2013). They also in- vestigated the role of snowpack photochemistry in contribut- ing to atmospheric mercury depletion events (Toyota et al., 2013a). Given that this is the first 1-D model used to inves- tigate whether snowpack chemistry can initiate and sustain bromine explosion events, which cause complete ozone de- pletion in the polar boundary layer, it is clear that future work will be needed to fully understand the connection between snowpack photochemistry and Arctic atmospheric chemistry. Future work on appropriate parameterisations and represen- tation of snow chemistry in models should clarify the uncer- tainty associated with how these processes are represented. 5.7 Conclusions about chemistry Chemistry in ice and at ice surfaces under conditions relevant to the troposphere is a relatively new area of study. The work discussed above reflects the complexity of ice and snow as a host for chemical reactions. Nevertheless, important insight into the chemical fate of atmospheric species in frozen aque- ous media can be summarised as follows. 1. A very important factor in the apparent rate of chem- ical reactions in environmental snow is the presence of a multiphase system, where liquid solutions and ice coexist. Many chemical reactions investigated so far proceed more efficiently in the presence of a liq- uid phase as compared to the ice matrix. In particu- lar, the freeze-concentration effect results in signifi- cant acceleration of observed rates. This is of impor- tance for a number of reactive systems because reac- tions that are negligible in dilute solutions may become important in snow–liquid multiphase systems due to increased concentrations in the brine and, on occa- sion, freeze-potential effects. Aqueous-phase kinetics describe the concentration-dependent chemistry well. This has been shown for heterogeneous reactions such as bromide ozonation, as well as for reactions that oc- cur within bulk regions of ice such as micro-veins and - pockets. Variables such as temperature and total solute concentration will determine the liquid content of the snow and the reagent concentrations and, thus, the ob- served reaction rates. This underlines the importance of identifying the presence of liquid or brine in labora- tory ice samples and in ice in environmental settings. 2. Some reactions were found to be moderately acceler- ated in ice compared to aqueous samples. By analogy with the freeze-concentration effect, the higher appar- ent rates can be understood as a consequence of high local reagent concentrations. Other types of reactions were found to proceed with similar or even reduced apparent rates in ice compared to the liquid phase. This shows that factors other than local concentra- tion can influence the observed reactivity. Changes in mechanism, local chemical environment, and the local physical environment were discussed, but more stud- ies are needed to develop a quantitative understanding of chemistry in snow. In particular, unimolecular re- actions such as direct photolysis show similar quan- tum yields and reaction rates in ice as in aqueous solu- tion. Parameterising these reactions based on aqueous- phase reaction rates might thus be justified. 3. Heterogeneous chemistry at the ice surface was found to be uniquely different from that in the bulk water and on water surfaces. In these instances, parameterisation based on aqueous-phase chemistry is not appropriate. First-order heterogeneous rate coefficients specific to ice surfaces should be used. Unfortunately, only a few rate coefficients for reactions at ice surfaces have been measured and more work is needed. How the surface disorder that occurs naturally on snow crystals is an important outstanding issue. As is the case for many areas of environmental study, the measurement of reaction kinetics and products at en- vironmentally relevant reagent concentrations is technically challenging. As analytical techniques gain sensitivity, revis- iting important reactions at environmentally relevant reagent concentrations will provide links between laboratory exper- iments and field observations. A second critical difference between laboratory studies and settings in the field is that in laboratory studies the ice matrix is often frozen from liquid solutions, whereas environmental snow forms mostly by wa- ter vapour condensation. Thus reactions that occur during the freezing process might be of relevance for wet snow, but not for dry snow at colder temperatures. Little is known about the reactivity in environmental snow in liquid compartments in dry snow. Impurities will lead to the formation of small amounts of highly concentrated solutions above the specific eutectic temperatures. Whether these brines also represent reservoirs for other impurities, or whether different impuri- ties mix there to foster reactivity, is unknown. Despite the challenges involved, these advances are es- sential for developing correct descriptions of environmental Atmos. Chem. Phys., 14, 1587–1633, 2014 www.atmos-chem-phys.net/14/1587/2014/ T. Bartels-Rausch et al.: Air–ice chemical interactions 1619 processes used in models. Reactive species are localised in a liquid environment with a constant volume that takes con- centration enhancements due to the reduced volume of this liquid fraction into account. A similar approach was used to reproduce laboratory experiments investigating the pho- tolysis of nitrate in snow (Honrath et al., 2000; Dubowski et al., 2002; Jacobi and Hilker, 2007; Bock and Jacobi, 2010; Jacobi, 2011). Over time the applied chemical mechanisms were upgraded from very simplified mechanisms as pre- sented by Liao and Tan (2008) to the most advanced model to date presented by Thomas et al. (2011). The most ad- vanced model extended an existing atmospheric 1-D chem- istry model including gas-phase, aqueous-phase, and hetero- geneous chemistry using additional layers to represent chem- ical processes in the snow. Nevertheless, a full representa- tion of the distinct compartments (bulk ice, grain boundaries, ice surface, liquid brine, solid precipitates) and the differ- ent physicochemical processes has not yet been attempted, in part due to the difficulty in treating the non-equilibrium chemical processes in these complex environments. Signif- icant developments in modelling these processes will be needed in the future, but will require close cooperation be- tween laboratory scientists, measurement campaigns, and a corresponding development of an interdisciplinary model community capable of including these complex processes in models. 6 Synthesis and outlook Snow is of great interest in a number of scientific disciplines ranging from fundamental materials science to applied envi- ronmental science (Bartels-Rausch et al., 2012). In this re- view, we focus on atmospheric and cryospheric science of the polar regions, where chemistry and physical processes in snow have a far-ranging environmental impact (Grannas et al., 2013). The focus was placed on studies that showed the interplay of impurities with snow and ice and that char- acterised the structural environment down to a molecular level. It was demonstrated that the structural and chemical environment of impurities varies significantly depending on their location within the snowpack and that for their fate the knowledge of the distribution of impurities between in- dividual compartments and the description of chemical and physical processes therein is crucial. For example, a sound parameterisation has been developed based on well-defined laboratory studies for the uptake of a number of atmospher- ically relevant trace gases to ice surfaces. Chemical reactiv- ity studies focused mainly on photochemical reactions and on bimolecular reactions in freezing systems. The chemistry during freezing and in partially frozen multiphase systems seems to be well understood taking concentrations in the re- maining liquid phase into account. For the chemistry in ice a detailed parameterisation cannot yet be given; apparent rates show large deviations for individual studies. Important fac- tors explaining the observed reaction rates are local concen- tration, physical and chemical environment, and mechanism changes. Clearly, more studies are needed in particular at low reagent concentrations. Previous modelling attempts in snow chemistry have addressed specific questions such as the con- servation of H2O2 and formaldehyde in snow, firn, and ice or the release of reactive species from the snowpack to the atmosphere. The objectives of the respective studies have de- termined the degree of the complexity of the physical and chemical parts of the snow models: simulation of snow and firn profiles of H2O2 and formaldehyde have emphasised the role of long-term physical and meteorological processes (e.g. accumulation, compaction, exchange between the gas phase and the bulk solid), while the studies of the nitrate photolysis concentrated on a sophisticated representation of fast chem- ical processes and the transport in the firn air. So far nei- ther of the models has included fully coupled snow physics and chemistry in which the physical properties of the snow- pack and its changes over time were fully simulated to de- liver a consistent frame for the modelling of the chemical processes in the snowpack. Understanding and modelling chemistry in snow will re- main difficult since our current knowledge of many crucial components is still very limited. A key issue is the distri- bution of impurities. For example, most of the described models including chemical reactions assume that these re- actions take place in a liquid environment in the snow ma- trix (Michalowski et al., 2000; Boxe and Saiz-Lopez, 2008; Bock and Jacobi, 2010; Thomas et al., 2012). This approach seems well justified when liquid brine is present. Laboratory work has clearly shown that even small amounts of aque- ous solution can dominate the chemical reactivity, exchange of trace gases, and distribution of impurities in snow. This induced melting and brine formation is one way of how im- purities can change the structure and composition of snow. Some experiments indicated that the concentrations in such a brine fraction can be deduced assuming a simple thermody- namic equilibrium approach using ideal behaviour of the so- lutes (Cho et al., 2002). Therefore, such an approach to define initial concentration of solutes in a given volume of brine has been used by Boxe and Saiz-Lopez (2008) and during further studies based on laboratory experiments (Jacobi and Hilker, 2007; Bock and Jacobi, 2010; Jacobi, 2011). A recent study refined this approach, taking into account the non-ideal be- haviour of the solutes in the highly concentrated brine (Kuo et al., 2011), leading to a better agreement with previous lab- oratory experiments. Open issues in this treatment remain the precipitation of solutes when solubility limits are reached (Jacobi, 2011), the solubility of impurities in the ice crys- tal, and the trapping of impurities in solid deposits, such as aerosols, within the snow. While thermodynamics predict the concentration of brine for a given amount of impurities in a snow sample, uncertain- ties with this approach stem from unpredictable fractionation of impurities between the air–ice interface and the bulk ice www.atmos-chem-phys.net/14/1587/2014/ Atmos. Chem. Phys., 14, 1587–1633, 2014 1620 T. Bartels-Rausch et al.: Air–ice chemical interactions phase. Further, such brine in snow does not necessarily form one connected phase, and little is known about the mixing of impurities, which is essential for efficient reactivity. For ex- ample, Thomas et al. (2012) found best agreement between simulations and observations if a fraction of only 6 % of the measured nitrate in the snow was present at the surface of the snow crystals. As the fractionation of solutes between the surface and interior of snow crystals is highly concentration- dependent, it remains unclear whether a similar fractionation of nitrate can also be applied to a snowpack with different nitrate or sea salt concentrations or at different temperatures. Alternatively this may indicate that reaction rates in the liq- uid fraction of snow differ from those in aqueous solutions. This is an inherent problem of snow-chemistry models: with the increase in complexity needed to capture observations, they become less confined. In principle, this thermodynamic approach holds only down to the temperature of the eutectic point, at which all components form a solid phase. Neverthe- less, a concentrated liquid fraction has been observed well below the eutectic temperature of a bulk ice sample (Cho et al., 2002). Surface-sensitive spectroscopy, on the other hand, gave no indication of liquid below the eutectic (Krˇe- pelová et al., 2010a). Possibly, the liquid observed in the bulk sample was located in nanometre-sized micro-pockets that formed during the rapid freezing of the highly concentrated solutions used in that study. Just as in small aerosol droplets, freezing might be inhibited by steric reasons in such small compartments. Projections to environmental snow might thus be highly questionable. Precise knowledge of the location of impurities is thus important and a unifying theory describing the liquid fraction of ice covering the range of temperatures and impurity concentrations observed in natural snow still needs to be developed. Modelling and interpretation of laboratory results have been based on the existence of a disordered interface on ice with properties similar to liquid water. This very simplified picture to describe the disordered interface has been used successfully in thermodynamic frameworks, and is somehow supported by water diffusion measurements on ice surfaces. Also molecular dynamics simulations indicate that in a very thick disordered interface the upper part has structural fea- tures approaching those of a supercooled liquid. However, describing the surface disorder as a homogeneous liquid-like phase contradicts direct observations showing distinct struc- tural differences between the disordered interface and a liq- uid phase. Further, the properties of such a layer, such as thickness and volume, and their dependence on temperature remain poorly defined. However, most studies on pure ice in- dicate that the disordered interface remains rather thin with structural features highly influenced by the underlying solid crystal. This and the widespread presence of impurities in the field make this disordered interface less relevant for un- derstanding snow chemistry in polar regions. It is clear that impurities increase the thickness of the disorder. Recent sim- ulations and direct observations, however, indicate that the impact of impurities on the hydrogen-bonding network at the ice surface is limited to their vicinity where they form a hy- dration shell. This means that the impurity experiences an environment similar to an aqueous solution even when the disordered interface is very thin and that the molecular struc- ture at the ice surface may be very heterogeneous. Further studies are needed for a larger set of impurities and with dif- ferent methods. How the local disorder induced by some im- purities influences the uptake, distribution and chemistry of other impurities is an essential open issue. Approaching the melting point, the lack of knowledge of the surface disorder even increases, as the number of studies investigating the sur- face disorder and its effects just below the melting point are limited. It is generally assumed that no reactions take place in the solid phase of the snow grains due to the reduced mobility of the products or because these reactions are too slow. Never- theless, this portion can constitute an important reservoir for reactive species like H2O2 and possibly also for nitrate. In these cases, adsorption, desorption and solid-state diffusion need to be considered for the successful modelling of con- centration profiles in snow, firn, and ice on longer timescales (Hutterli et al., 2003). The potential role of aerosol deposits as a host of impu- rities and of chemical reactions has not been investigated in laboratory or modelling studies (Domine and Shepson, 2002; Domine et al., 2013). For the description of chemical processes in models – in- cluding photochemical reactions, adsorption and desorption on the grain surfaces, diffusion inside the grains, and trans- port in the interstitial air – physical snow properties like temperature, density, grain shape and structure are crucial. In many models, the physical properties have been assumed to be constant and were based on observations. Such an ap- proach is reasonable for the structural parameters like density and grain shape if the simulations are restricted to shorter periods like several days and excluding fresh snow. How- ever, even on this timescale the snow temperature under- goes variations linked to diurnal cycles in radiation or rapid changes in the air temperatures, so that an explicit descrip- tion of the evolution of the temperature will be needed. Re- cent advances in X-ray-computed microtomography have en- abled us to observe the changes in the structure of a snow sample in situ under such temperature gradients. These stud- ies have revealed huge water mass fluxes on timescales of days (Pinzer and Schneebeli, 2009b; Pinzer et al., 2012). An explicit description of the evolution of the temperature will be needed in future simulations for longer periods (weeks to multi-annual cycles), and changes in the snowpack proper- ties due to metamorphism and compaction need to be consid- ered. Moreover, the fate of impurities during this movement of water molecules and the restructuring of the snow struc- ture is an essential, yet open, issue. Laboratory experiments with growing ice showed that particularly strong acids are buried by growing ice films, leading to an enhanced uptake Atmos. Chem. Phys., 14, 1587–1633, 2014 www.atmos-chem-phys.net/14/1587/2014/ T. Bartels-Rausch et al.: Air–ice chemical interactions 1621 from the gas phase. More studies are needed to asses the fate of impurities in snow that is not in equilibrium with the water-vapour pressure. The rate and timing of snow accumu- lation are important factors determining the direct input and the release of volatile impurities to the snow in the case of H2O2 and formaldehyde (Hutterli et al., 2003). Furthermore, even in polar regions fresh snow can undergo rapid changes, contributing to an enhancement of the release of incorpo- rated but volatile species like formaldehyde (Jacobi et al., 2002). Snow physics models with varying complexities exist to reproduce the development of snow properties (Schwan- der, 1989; Brun et al., 1989; McConnell et al., 1998; Hutterli et al., 1999; Bartelt and Lehning, 2002; Lehning et al., 2002). Although some of these models were developed to contribute to the forecasting of avalanches in the Alps, further studies have shown their general applicability also to other snowpack types (e.g. Lejeune et al., 2007; Jacobi et al., 2010) and even to the simulation of snowpack properties on the top of the large ice sheet (Genthon et al., 2001; Brun et al., 2011). Al- though the existing snow physics models still contain simpli- fied parameterisation of important processes (e.g. Etchevers et al., 2004) and need to be developed further, such models can constitute a useful physical frame for the simulation of chemical processes in the snow in a 1-D model on different timescales. Acknowledgements. This review was initiated and planned during the 3rd Workshop on Air–Ice Chemical Interactions held in June 2011, in New York, NY. The workshop was sponsored in part by IGAC and the Columbia University School of Engineering and Applied Sciences. T. Bartels-Rausch and M. Ammann appreci- ate support by the Swiss National Science Foundation (grants 121857, 125179, 140400, and 149629) and valuable input to this review by Sepp Schreiber. H.-W. Jacobi acknowledges support by the LEFE-CHAT program of INSU-CNRS. E. S. Thomson and J. B. C. Pettersson benefit from the scientific support of the Swedish Research Council and the Nordic top-level research initiative CRAICC. M. H. Kuo, V. F. McNeill, and S. G. Moussa acknowledge a NSF CAREER award for V. F. McNeill (ATM- 0845043). M. Roeselová acknowledges support from the Czech Science Foundation (grant P208/10/1724) and RVO 61388963. P. Klán and D. Heger appreciate support by the Czech Sci- ence Foundation (P503/10/0947), and the project CETOCOEN (CZ.1.05/2.1.00/01.0001) granted by the European Regional De- velopment Fund. M. I. Guzmán thanks the U.S. National Science Foundation for a CAREER award (CHE-1255290). F. Domine thanks the French Polar Institute (IPEV) for continuous support. H. 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