A review of air–ice chemical and physical interactions (AICI): liquids, quasi-liquids, and solids in snow

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 relevance to polar regions. It focuses on a description of impurities in distinct compartments present in surface snow, such as snow crystals, grain boundaries, crystal surfaces, and liquid parts. It emphasises the microscopic description of the ice surface and its link with the environment. Distinct differences between the disordered air–ice interface, often termed quasi-liquid layer, and a liquid phase are highlighted. The reactivity 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 formation of brine or disorder at surfaces of snow crystals below the freezing point may strongly modify reaction rates. Therefore, future experiments should include a detailed characterisation 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 environmental snowpack may be caused by the highly dynamic nature of the snowpack due to the fast metamorphism occurring 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 snowpack. 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 successfully been used to reproduce some field experiments. A fully coupled snow chemistry and physics model remains to be developed.

Sensitive Questions in Online Surveys: An Experimental Evaluation of the Randomized Response Technique and the Crosswise Model

Self-administered online surveys provide a higher level of privacy protection to respondents than surveys administered by an interviewer. Yet, studies indicate that asking sensitive questions is problematic also in self-administered surveys. Because respondents might not be willing to reveal the truth and provide answers that are subject to social desirability bias, the validity of prevalence estimates of sensitive behaviors from online surveys can be challenged. A well-known method to overcome these problems is the Randomized Response Technique (RRT). However, convincing evidence that the RRT provides more valid estimates than direct questioning in online surveys is still lacking. A new variant of the RRT called the Crosswise Model has recently been proposed to overcome some of the deficiencies of existing RRT designs. We therefore conducted an experimental study in which different implementations of the RRT, including two implementations of the crosswise model, were tested and compared to direct questioning. Our study is a large-scale online survey (N = 6,037) on sensitive behaviors by students such as cheating in exams and plagiarism. Results indicate that the crosswise-model RRT---unlike the other variants of RRT we evaluated---yields higher prevalence estimates of sensitive behaviors than direct questioning. Whether higher estimates are a sufficient condition for more valid results, however, remains questionable.

Using Factorial Surveys and Stated Choice Experiments to Investigate Discriminatory Attitudes and Preferences

Empirical research on discriminatory attitudes and behaviour grapples with the social undesirability of its object. In many studies using regular survey methods, estimates are biased, and the social context of discrimination is not taken into account. Several methods have been developed, especially to deal with the first problem. In this regard, the estimation of the ‘true value’ of discriminatory attitudes is at the centre of interest. However, methodological contributions focusing on the social context of attitude communication and discriminatory behaviour, as well as the correlation between both, are rare. We present two experimental methods which address those issues: factorial surveys and stated choice experiments. In a first study, the usefulness of factorial surveys is demonstrated with data on German anti-Semitism (N=279). We show that the rate of approval with anti-Semitic statements increases if (a) respondents are told that the majority of fellows agree with such statements, (b) the term “Jews” is replaced by the term “Israelis”, and (c) reference to the Holocaust is made. Apart from the main effects of these experimental factors, significant interaction effects regarding the political attitudes and social status of respondents are observed. In a second study, a stated choice experiment on the purchase of olive oil and tomatoes was conducted in Germany (N=440). We find that respondents prefer Italian and Dutch products (control treatment) compared to Israeli and Palestinian ones (discrimination treatments). There are no significant differences between preferences for a so called ‘Peace product’ (which is produced jointly by Israelis and Palestinians) and products from Italy as well as the Netherlands. Yet, taking discriminatory attitudes (anti-Semitic and anti-Arabic attitudes) into account, a strong correlation between those attitudes and stated behaviour (purchase of Israeli, Palestinian and jointly produced products) can be found. This adds support to the hypothesis that discriminatory attitudes hold behavioural consequences.

Does the Use of Mobile Devices (Tablets and Smartphones) Affect Stated Choice Behavior in Web Surveys? An Application to Environmental Valuation

Web surveys are becoming increasingly popular in survey research. Compared with face-to-face, telephone and mail surveys, web surveys may contain a different and new source of measurement error and bias: the type of device that respondents use to answer the survey questions. To the best of our knowledge, this is the first study that tests whether the use of mobile devices affects survey characteristics and stated preferences in a web-based choice experiment. The web survey was carried out in Germany with 3,400 respondents, of which 12 per cent used a mobile device (i.e. tablet or smartphone), and comprised a stated choice experiment on externalities of renewable energy production using wind, solar and biomass. Our main finding is that survey characteristics such as interview length and acquiescence tendency are affected by the device used. In contrast to what might be expected, we find that, compared with respondents using desktop computers and laptops, mobile device users spent more time to answer the survey and are less likely to be prone to acquiescence bias. In the choice experiment, mobile device users tended to be more consistent in their stated choices, and there are differences in willingness to pay between both subsamples.

Snow shielding factors for cosmogenic nuclide dating inferred from long-term neutron detector monitoring

The depth-dependent attenuation of the secondary cosmic-ray particle flux due to snow cover and its effects on production rates of cosmogenic nuclides constitutes a potential source of uncertainty for studies conducted in regions characterized by frequent seasonal snow burial. Recent experimental and numerical modelling studies have yielded new constraints on the effect of hydrogen-rich media on the production rates of cosmogenic nuclides by low- and high-energy neutrons (<10(-3) MeV and >10(2) MeV, respectively). Here we present long-term neutron-detector monitoring data from a natural setting that we use to quantify the effect of snow cover on the attenuation of fast neutrons (0.1-10 MeV), which are responsible for the production of Ne-21 from Mg and Cl-36 from K. We use data measured between July 2001 and May 2008 at seven stations located throughout the Ecrins-Pelvoux massif (French Western Alps) and its surroundings, at elevations ranging from 200 to 2500 m a.s.l. From the cosmic-ray fluxes recorded during summer, when snow is absent, we infer an apparent attenuation length of 148 g cm(-2) in the atmosphere at a latitude of similar to 45 degrees N and for altitudes ranging from similar to 200 to 2500 m a.s.l. Using snow water-equivalent (SWE) values obtained through snow-coring campaigns that overlap in time the neutron monitoring for five stations, we show that fast neutrons are much more strongly attenuated in snow than predicted by a conventional mass-shielding formulation and the attenuation length estimated in the atmosphere. We suggest that such strong attenuation results from boundary effects at the atmosphere/snow interface induced by the high efficiency of water as a neutron moderator. Finally, we propose an empirical model that allows calculating snow-shielding correction factors as a function of SWE for studies using Ne-21 and Cl-36 analyses in Mg- and K-rich minerals, respectively. This empirical model is of interest for studies with a focus on cosmic-ray exposure dating, particularly if the target rocks are made up of mafic to ultramafic units where seasonal snow-cover is a common phenomenon.

Arctic moisture source for Eurasian snow cover variations in autumn

Eurasian fall snow cover changes have been suggested as a driver for changes in the Arctic Oscillation and might provide a link between sea-ice decline in the Arctic during summer and atmospheric circulation in the following winter. However, the mechanism connecting snow cover in Eurasia to sea-ice decline in autumn is still under debate. Our analysis is based on snow observations from 820 Russian land stations, moisture transport using a Lagrangian approach derived from meteorological re-analyses. We show that declining sea-ice in the Barents and Kara Seas (BKS) acts as moisture source for the enhanced Western Siberian snow depth as a result of changed tropospheric moisture transport. Transient disturbances enter the continent from the BKS region related to anomalies in the planetary wave pattern and move southward along the Ural mountains where they merge into the extension of the Mediterranean storm track.

Modelling the system behaviour of wet snow avalanches using an expert system approach for risk management on high alpine traffic roads

The presented approach describes a model for a rule-based expert system calculating the temporal variability of the release of wet snow avalanches, using the assumption of avalanche triggering without the loading of new snow. The knowledge base of the model is created by using investigations on the system behaviour of wet snow avalanches in the Italian Ortles Alps, and is represented by a fuzzy logic rule-base. Input parameters of the expert system are numerical and linguistic variables, measurable meteorological and topographical factors and observable characteristics of the snow cover. Output of the inference method is the quantified release disposition for wet snow avalanches. Combining topographical parameters and the spatial interpolation of the calculated release disposition a hazard index map is dynamically generated. Furthermore, the spatial and temporal variability of damage potential on roads exposed to wet snow avalanches can be quantified, expressed by the number of persons at risk. The application of the rule base to the available data in the study area generated plausible results. The study demonstrates the potential for the application of expert systems and fuzzy logic in the field of natural hazard monitoring and risk management.