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The optical properties of snow can be strongly modified by the presence of a variety of impurities including mineral dust and snow algae. We made use of measured concentration of snow algae and mineral dust to parameterize the BioSNICAR radiative transfer model. Surficial snow samples were gathered during a field campaign on 7th July 2020 at the Presena glacier (Rhaetian Alps). We collected 18 samples of surface snow containing different amount of snow algae and mineral dust. Through radiative transfer simulations we estimated an average broadband albedo reduction of 7.4 +/- 6.1 % and 35.3 +/- 7.4 % compared to clean snow, caused by snow algae and mineral dust presence, respectively. When we considered the combined effect of snow algae and dust, we estimated a broadband albedo reduction equal to 40.8 +/- 8.4 %. We estimated an average instantaneous radiative forcing induced by snow algae, mineral dust and both impurities equals to 42.3 (+/- 36.1) W/m(2), 203.7 (+/- 45.5) W/m(2), and 211.8 (+/- 45.9) W/m(2), respectively.Using BioSNICAR simulations, we also tested a series of narrowband spectral indices to determine the concentration of mineral dust and snow algae from multi- and hyper -spectral data. Results showed that most spectral indices used for snow algae mapping are correlated also with mineral dust concentration. We found that only an index correlates uniquely with snow algae: the scaled band integral at 680 nm. A new spectral index, namely the Green Blue Normalized Index, is therefore proposed to discriminate mineral dust from snow algae when both impurities are present. The high spectral resolution of current (e.g. PRISMA, EnMAP) and future (e.g. CHIME, SBG) hyperspectral satellite missions will be fundamental to decouple the effect of mineral dust and snow algae on the optical properties of snow. In fact, from those data it is possible to calculate all narrowband indices presented in this study.

The accumulation of fallout radionuclides (FRNs) from nuclear weapons testing and nuclear accidents has been evaluated for over half a century in natural environments; however, until recently their distribution and abundance within glaciers have been poorly understood. Following a series of individual studies of FRNs, specifically 137Cs, 241Am and 210Pb, deposited on the surface of glaciers, we now understand that cryoconite, a material commonly found in the supraglacial environment, is a highly efficient accumulator of FRNs, both artificial and natural. However, the variability of FRN activity concentrations in cryoconite across the global cryosphere has never been assessed. This study thus aims to both synthesize current knowledge on FRNs in cryoconite and assess the controls on variability of activity concentrations. We present a global database of new and previously published data based on gamma spectrometry of cryoconite and proglacial sediments, and assess the extent to which a suite of environmental and physical factors can explain spatial variability in FRN activity concentrations in cryoconite. We show that FRNs are not only found in cryoconite on glaciers within close proximity to specific sources of radioactivity, but across the global cryosphere, and at activity concentrations up to three orders of magnitude higher than those found in soils and sediments in the surrounding environment. We also show that the organic content of cryoconite exerts a strong control on accumulation of FRNs, and that activity concentrations in cryoconite are some of the highest ever described in environmental matrices outside of nuclear exclusion zones, occasionally in excess of 10,000 Bq kg−1. These findings highlight a need for significant improvements in the understanding of the fate of legacy contaminants within glaciated catchments. Future interdisciplinary research is required on the mechanisms governing their accumulation, storage, and mobility, and their potential to cr

Hyphenated chromatography is among the most popular analytical techniques in omics related research. While great advancements have been achieved on the experimental side, the same is not true for the extraction of the relevant information from chromatographic data. Extensive signal preprocessing is required to remove the signal of the baseline, resolve the time shifts of peaks from sample to sample and to properly estimate the spectra and concentrations of co-eluting compounds. Among several available strategies, curve resolution approaches, such as PARAFAC2, ease the deconvolution and the quantification of chemicals. However, not all resolved profiles are relevant. For example, some take into account the baseline, others the chemical compounds. Thus, it is necessary to distinguish the profiles describing relevant chemistry. With the aim to assist researchers in this selection phase, we have tried three different classification algorithms (convolutional and recurrent neural networks, k-nearest neighbours) for the automatic identification of GC-MS elution profiles resolved by PARAFAC2. To this end, we have manually labelled more than 170,000 elution profiles in the following four classes: ‘Peak’, ‘Cutoff peak’,’ Baseline’ and ‘Others’ in order to train, validate and test the classification models. The results highlight two main points: i) neural networks seem to be the best solution for this specific classification task confirmed by the overall quality of the classification, ii) the quality of the input data is crucial to maximize the modelling performances.

Soil mobilization has been investigated by means of fallout radionuclides (FRN) in a first-order catchment of the Eastern Alps. Caesium-137, 210Pbxs. (210Pb excess or unsupported fraction), and 241Am have been measured in soil samples collected from a pasture at about 2150 m above sea level. Combining pedological and radioactivity data, including mineral-related radionuclides (primordial 40K and nuclides belonging to the 232Th and 238U decay chains), the distribution of FRNs, their spatial variability, vertical distribution, and relationships with pedological and topographical variables were assessed. Because of low activity concentration, it was not possible to use artificial long-lived 241Am as a soil tracer, but preliminary results are encouraging. Inventories of 210Pbxs. and 137Cs have been converted into soil mobilization rates applying the MODERN model. Despite the gentle steepness and the absence of evident signs of erosion, the slopes of the considered catchment are affected by erosion at a rate up to 6 t ha−1 yr−1, likely related to grazing. A comparison between 210Pbxs. and 137Cs has revealed that at this site 137Cs, the most used FRN for estimating soil redistribution, is not suitable for this purpose, probably due to its irregular spatial distribution on snow-covered ground after the Chernobyl accident. Conversely, 210Pbxs., owing to its continuous input, has provided reliable estimates of soil redistribution rates, in accordance with local morphology. The latter has in fact been related to morphometric variables in a regression model to provide an overview of soil erosion/sedimentation across the entire catchment, confirming that 210Pbxs. is a viable alternative to trace soil erosion and deposition where the Chernobyl fallout occurred on snow-covered ground.

Insoluble particles in ice cores record signatures of past climate parameters like vegetation dynamics, volcanic activity, and aridity. For some of them, the analytical detection relies on intensive bench microscopy investigation and requires dedicated sample preparation steps. Both are laborious, require in-depth knowledge, and often restrict sampling strategies. To help overcome these limitations, we present a framework based on flow imaging microscopy coupled to a deep neural network for autonomous image classification of ice core particles. We train the network to classify seven commonly found classes, namely mineral dust, felsic and mafic (basaltic) volcanic ash grains (tephra), three species of pollen (Corylus avellana, Quercus robur, Quercus suber), and contamination particles that may be introduced onto the ice core surface during core handling operations. The trained network achieves 96.8ĝ€ ̄% classification accuracy at test time. We present the system's potential and its limitations with respect to the detection of mineral dust, pollen grains, and tephra shards, using both controlled materials and real ice core samples. The methodology requires little sample material, is non-destructive, fully reproducible, and does not require any sample preparation procedures. The presented framework can bolster research in the field by cutting down processing time, supporting human-operated microscopy, and further unlocking the paleoclimate potential of ice core records by providing the opportunity to identify an array of ice core particles. Suggestions for an improved system to be deployed within a continuous flow analysis workflow are also presented.

Thanks to its insolubility, mineral dust is considered a stable proxy in polar ice cores. With this study we show that the Talos Dome ice core (TALDICE, Ross Sea sector of East Antarctica) displays evident and progressive signs of post-depositional processes affecting the mineral dust record below 1000g m deep. We apply a suite of established and cutting-edge techniques to investigate the properties of dust in TALDICE, ranging from concentration and grain size to elemental composition and Fe mineralogy. Results show that through acidic/oxidative weathering, the conditions of deep ice at Talos Dome promote the dissolution of specific minerals and the englacial formation of others, affecting primitive dust features. The expulsion of acidic atmospheric species from ice grains and their concentration in localized environments is likely the main process responsible for englacial reactions. Deep ice can be seen as a "geochemical reactor"capable of fostering complex reactions which involve both soluble and insoluble impurities. Fe-bearing minerals can efficiently help in exploring such transformations.

The worldwide distribution of microinvertebrates on glaciers, the coldest biome, is poorly known. Owing to their tolerance to hostile conditions, small size and dispersal abilities, nematodes, tardigrades and rotifers are considered cosmopolitan and together inhabit various ecosystems. In this study, we investigated their global distribution in cryoconite holes – a type of freshwater reservoir forming directly in the glacial ice that creates biodiversity hotspots on glaciers. We analysed cryoconite samples (using classical microscopic observations and environmental DNA metabarcoding) from 42 glaciers located around the world (the Arctic, Subarctic, Scandinavia, the Alps, the Caucasus, Siberia, Central Asia, Africa, South America and Antarctica), as well as using literature data. Samples from Antarctic, Karakoram and the Alps were analysed using next-generation sequencing (NGS) and classical observations under microscopes, while all other samples were analysed by microscope alone. Three general outcomes were found: (1) tardigrades and rotifers represented the most common invertebrates in cryoconite holes; (2) tardigrades and rotifers often coexisted together, with one or the other dominating, but the dominant taxon varied by region or by glacier; (3) nematodes – the most abundant, hyperdiverse and widespread metazoans on Earth, including in environments surrounding and seeding glacial surfaces – were consistently absent from cryoconite holes. Despite the general similarity of environmental conditions in cryoconite holes, the distribution of tardigrades and rotifers differed among glaciers, but not in any predictable way, suggesting that their distribution mostly depended on the random dispersal, extreme changes of supraglacial zone or competition. Although nematodes have been found in supraglacial habitats, cryoconite hole environments seem not to provide the necessary conditions for their growth and reproduction. Lack of physiological adaptations to permanently low

Worldwide, snow and ice can be polluted with impurities also referred as Light-Absorbing Particles (LAPs). In this chapter, we review the different processes occurring at middle latitudes, tropical areas, and polar regions. We show that snow and ice albedo reduction due to LAPs deposition or resurfacing is a global phenomenon with regional characteristics. Later in the chapter, we provide a classification of LAPs based on their optical features. We divided LAPs in non-carbonaceous (mineral dust) and carbonaceous (biogenic particles and cryoconite), and we created a set of radiative transfer simulations for each category. Lastly, we described different observation approaches for studying LAPs impact on snow and ice. We divided these methods in proximal (field spectroscopy) and remote (aerial surveys and satellite data) sensing. We expect that the study of LAPs in snow and ice will grow in the future, and more data and models will be developed in order to describe the hydrological and climatic effect of LAPs in the cryosphere.

Gas chromatography – mass spectrometry (GC-MS) is an important tool in contemporary untargeted chemical analysis, where the batch analysis of sample series and subsequent generation of peak tables are still commonly subject to software-uncertainty leading to issues in reproducibility and hypothesis testing. Using tensor-based modelling in combination with other machine learning tools, we were able to provide a completely automated method for turning GC-MS data into a peak-table that is absent of user-interactions, avoiding user induced differences in the peak tables. The developed tools are integrated into the software package called PARADISe. The results of using the fully automated version of PARADISe are illustrated using experimental GC-MS data. The presented approach still has room for improvement, especially when the data collinearity is broken, such as in the case of peak saturation. The proposed automated approach provides marked improvements over current analysis, including but not limited to the analysis time and reproducibility.

The release of legacy contaminants such as fallout radionuclides (FRNs) in response to glacier retreat is a process that has received relatively little attention to date, yet may have consequences as a source of secondary contamination as glaciers melt and down-waste in response to a warming climate. The presence of FRNs in glacier-fed catchments is poorly understood in comparison to other contaminants, yet there is now emerging evidence from multiple regions of the global cryosphere for substantially augmented FRN activities in cryoconite. Here we report concentrated FRNs in both cryoconite and proglacial sediments from the Isfallsglaciären catchment in Arctic Sweden. Activities of some FRNs in cryoconite are 2 orders of magnitude above those found elsewhere in the catchment, and above the activities found in other environmental matrices outside of nuclear exclusion zones. We also describe the presence of the short-lived cosmogenic radionuclide 7Be in cryoconite samples, highlighting the importance of meltwater-sediment interactions in radionuclide accumulation in the ice surface environment. It is currently unknown whether high accumulations of fallout radionuclides in glaciers have the potential to impact local environmental quality through down-wasting and downstream transport of contaminants to the proglacial environment through interaction with sediments and meltwater. We thus recommend that future research in this field focusses on processes of accumulation of FRNs and other environmental contaminants in cryoconite and whether these contaminants are present in quantities harmful for downstream ecosystems.

Developing detectors operating in time coincidence is a possible way to increase the sensitivity in gamma spectroscopy. Such design allows both the selection of specific events and the rejection of background. In this work we present a new low background detector mainly developed for the determination of radioactive contamination of liquid samples. The system was constructed by combining a liquid organic scintillator, for the detection of alpha and beta particles, and a High Purity Germanium for the detection of correlated gamma rays. Despite being located in a non-underground laboratory, the instrument can reach sensitivities in the range of tens mBq/kg for 238U, 235U and 232Th, exploiting alpha–gamma and beta–gamma coincidence events.

A deeper understanding of past atmospheric circulation variability in the Central Andes is a high-priority topic in paleoclimatology mainly because of the necessity to validate climate models used to predict future precipitation trends and to develop mitigation and/or adaptation strategies for future climate change scenarios in this region.Within this context, we here investigate an 18-year firn core drilled at Nevado Illimani in order to interpret its mineral dust record in relation to seasonal processes, in particular atmospheric circulation and deep convection. The core was dated by annual layer counting based on seasonal oscillations of dust, calcium, and stable isotopes. Geochemical and mineralogical data show that dust is regionally sourced in winter and summer. During austral summer (wet season), an increase in the relative proportion of giant dust particles (20 um) is observed, in association with oscillations of stable isotope records (D, 18O). It seems that at Nevado Illimani both the deposition of dust and the isotopic signature of precipitation are influenced by atmospheric deep convection, which is also related to the total amount of precipitation in the area. This hypothesis is corroborated by regional meteorological data. The interpretation of giant particle and stable isotope records suggests that downdrafts due to convective activity promote turbulent conditions capable of suspending giant particles in the vicinity of Nevado Illimani. Giant particles and stable isotopes, when considered together, can be therefore used as a new proxy for obtaining information about deep convective activity in the past.

This work illustrates the development of an alpha spectroscopy system dedicated to the measurement of surface contaminations in materials used for low-background radioactive experiments. The system described is sensitive to trace levels of natural radionuclides. The operating principle is based on the simultaneous measurement of time and energy for each detected particle. A dedicated selection algorithm is developed to identify events in defined temporal relationships, so as to highlight cascade decays in natural radioactive chains. The shown results highlight the potential of the technique in reducing the radioactive background and revealing contamination otherwise not observable with usual analysis techniques.

In this paper, we provide a comprehensive overview of the state-of-knowledge of dust flux and variability in time and space in different sectors of East Antarctica during the Holocene. By integrating the literature data with new evidences, we discuss the dust flux and grain-size variability during the current interglacial and its provenance in the innermost part of the East Antarctic plateau as well as in peripheral regions located close to the Transantarctic Mountains. The local importance of aeolian mineral dust aerosol deflated from low-elevation areas of peripheral East Antarctica is also discussed in the light of new data from several coastal, low-elevation sites.

The melting of glaciers and ice sheets is nowadays considered a symbol of climate change. Many complex mechanisms are involved in the melting of ice, and, among these processes, surface darkening due to organic material on bare ice has recently received attention from the scientific community. The presence of microbes on glaciers has been shown to decrease the albedo of ice and promote melting. Despite several studies from the Himalaya, Greenland, Andes, and Alaska, no quantitative studies have yet been conducted in the European Alps. In this paper, we made use of DNA sequencing, microscopy and field spectroscopy to describe the nature of glacier algae found at a glacier (Vadret da Morteratsch) of the European Alps and to evaluate their effect on the ice-albedo feedback. Among different algal species identified in the samples, we found a remarkable abundance of Ancylonema nordenskioeldii, a species that has never previously been quantitatively documented in the Alps and that dominates algal blooms on the Greenland Ice Sheet. Our results show that, at the end of the ablation season, the concentration of Ancylonema nordenskioeldii on the glacier surface is higher than that of other algal species (i.e. Mesotaenium berggrenii). Using field spectroscopy data, we identified a significant correlation between a reflectance ratio (750 nm/650 nm) and the algae concentration. This reflectance ratio could be useful for future mapping of glacier algae from remote sensing data exploiting band 6 (740 nm) and band 4 (665 nm) of the MultiSpectral Instrument (MSI) on board Sentinel-2 satellite. Here we show that the biological darkening of glaciers (i.e. the bioalbedo feedback) is also occurring in the European Alps, and thus it is a global process that must be taken into account when considering the positive feedback mechanisms related to glacier melting.

La metabolomica, che consiste nella identificazione di tutti i metaboliti presenti all’interno dei campioni biologici analizzati, è un approccio ampiamente applicato in diversi campi di ricerca quali: identificazione di biomarcatori, sviluppo di nuovi farmaci, scienze alimentari e ambientali. La metabolomica è strettamente legata alla capacità di tecniche analitiche fra queste una delle più applicate è la gas cromatografia accoppiata alla spettrometria di massa. Moderne piattaforme analitiche possono generare centinaia di migliaia di spettri, rilevando una quantità impressionante di molecole distinte. Nonostante i progressi tecnici raggiunti sul lato sperimentale, la conversione dei segnali misurati dagli strumenti in informazioni utili non è un passaggio scontato in studi metabolomici. Per ogni composto identificato, l’obbiettivo è ottenere la concentrazione relativa tra tutti i campioni analizzati e lo spettro di massa associato al composto, necessario per l’identificazione della molecola stessa. I software disponibili per l’analisi dei dati sperimentali sono stati ripetutamente indicati come una fonte importante di incertezza, limitando fortemente sia la quantità che la qualità delle informazioni estratte. Gli strumenti più applicati richiedono l’impostazione di diversi parametri da parte dell’operatore, influenzando il risultato dell’analisi. In questa tesi è descritto un nuovo approccio, chiamato AutoDise, per l’analisi dei dati GC-MS. L’elaborazione dei segnali sperimentali si basa su PARAFAC2. PARAFAC2 è un modello che scompone dati multidimensionali, discriminando tra i diversi segnali nei campioni. Grazie alle sue proprietà, PARAFAC2 non ha bisogno che i dati siano pretrattati e non richiede di impostare parametri, mentre software utilizzati in questo ambito richiedono di definire diversi parametri e un laborioso pretrattamento dei dati, richiedendo l’intervento di un utente esperto, inoltre la riproducibilità dei risultati è limitata, dipen, Metabolomics, which consists of identifying all the metabolites present in the biological samples analysed, is an approach widely applied in various research fields such as biomarker identification, new drug development, food and environmental sciences. Metabolomics is closely linked to the ability of analytical techniques, one of the most widely applied being gas chromatography coupled to mass spectrometry. Modern analytical platforms can generate hundreds of thousands of spectra, detecting an impressive number of distinct molecules. Despite the technical progress achieved on the experimental side, the conversion of signals measured by instruments into useful information is not an obvious step in metabolomic studies. For each identified compound, the goal is to obtain the relative concentration among all analysed samples and the mass spectrum associated with the compound needed to identify the molecule itself. The software available for analysing experimental data has repeatedly been cited as a major source of uncertainty, severely limiting both the quantity and quality of the information extracted. The most applied tools are based on univariate data analysis, considering each sample separately from the others and requiring the operator to set several parameters, affecting the result of the analysis. In this thesis, a new approach, called AutoDise, for the analysis of GC-MS data is described. The processing of the experimental signals is based on PARAFAC2. PARAFAC2 is a model that decomposes multidimensional data, discriminating between different signals in the samples. Due to its properties, PARAFAC2 does not need the data to be pre-processed and does not require parameters to be set, whereas software used in this field requires several parameters to be defined and laborious pre-processing of the data, requiring the intervention of an expert user, and the reproducibility of the results is limited, depending on the parameters chosen by the user. However, fitting PA

This study is a first survey of the occurrence of artificial (137Cs, 241Am, 207Bi, Pu isotopes) and natural (210Pb, 228Ac, 214Bi, 40K) radionuclides in cryoconite from a Scandinavian glacier. Cryoconite samples were collected before (12 samples) and after (5 samples) a rainfall event. The concentrations of radionuclides in cryoconite samples from the Blåisen Glacier are compared with data from the Arctic and Alpine glaciers. Cryoconite samples from the studied glacier had extremely high activity concentrations of 137Cs, 241Am, 207Bi and 239+240Pu (up to 25,000 Bq/kg, 58 Bq/kg, 13 Bq/kg and 131 Bq/kg, respectively) and also high concentrations of organic matter (OM), comparing to other Scandinavian glaciers, reaching up ~40% of total mass. The outstandingly high concentrations of 137Cs, 241Am, Pu isotopes, and 207Bi on the Blåisen Glacier is primarily related to bioaccumulation of radionuclides in organic-rich cryoconite and might be enhanced by additional transfers of contamination from the tundra by lemmings during their population peaks. The presumed influence of intense rainfall on radionuclide concentrations in the cryoconite was not confirmed.

Cryoconite is a mixture of mineral and organic material covering glacial ice, playing important roles in biogeochemical cycles and lowering the albedo of a glacier's surface. Understanding the differences in structure of cryoconite across the globe can be important in recognizing past and future changes in supraglacial environments and ice-organisms-dust interactions. Despite the worldwide distribution and over a century of studies, the basic characteristics of cryoconite, including its forms and geochemistry, remain poorly studied. The major purpose of our study is the presentation and description of morphological diversity, chemical and photoautotrophs composition, and organic matter content of cryoconite sampled from 33 polar and mountain glaciers around the globe. Observations revealed that cryoconite included various morphologies including loose and granular forms. Granular cryoconite includes smooth, rounded, or irregularly shaped forms; with some having their surfaces covered by cyanobacteria filaments. The occurrence of granules increased with the organic matter content in cryoconite. Moreover, a major driver of cryoconite colouring was the concentration of organic matter and its interplay with minerals. The structure of cyanobacteria and algae communities in cryoconite differs between glaciers, but representatives of cyanobacteria families Pseudanabaenaceae and Phormidiaceae, and algae families Mesotaeniaceae and Ulotrichaceae were the most common. The most of detected cyanobacterial taxa are known to produce polymeric substances (EPS) that may cementing matter and form granules. Organic matter content in cryoconite varied between glaciers, ranging from 1% to >40%. The geochemistry of all the investigated samples reflected local sediment sources, except of highly concentrated Pb and Hg in cryoconite collected from European glaciers near industrialized regions, corroborating cryoconite as element-specific collectors and potential environmental indicator o

Changes in the composition of dust trapped in ice provide evidence of past atmospheric circulation and earth surface conditions. Investigations of dust provenance in Antarctic ice during glacial and interglacial periods indicate that South America is the primary dust source during both climate regimes. Here, we present results from a new ice core dust archive extracted from the Taylor Glacier in coastal East Antarctica during the deglacial transition from Marine Isotope Stage 6 to 5e. Radiogenic strontium and neodymium isotopes indicate that last interglacial dust is young and volcanic, in contrast to the observed preindustrial and Holocene (Marine Isotope Stage 1) dust composition. The dust composition differences from the last interglacial and current interglacial period at the site require a profound difference in atmospheric transport and environmental conditions. We consider several potential causes for enhanced transport of volcanic material to the site, including increased availability of volcanic material and large-scale atmospheric circulation changes.

Many interpretations have been proposed to explain the presence of jarosite within Martian surficial sediments, including the possibility that it precipitated within paleo-ice deposits owing to englacial weathering of dust. However, until now a similar geochemical process was not observed on Earth nor in other planetary settings. We report a multi-analytical indication of jarosite formation within deep ice. Below 1000 m depth, jarosite crystals adhering on residual silica-rich particles have been identified in the Talos Dome ice core (East Antarctica) and interpreted as products of weathering involving aeolian dust and acidic atmospheric aerosols. The progressive increase of ice metamorphism and re-crystallization with depth, favours the relocation and concentration of dust and the formation of acidic brines in isolated environments, allowing chemical reactions and mineral neo-formation to occur. This is the first described englacial diagenetic mechanism occurring in deep Antarctic ice and supports the ice-weathering model for jarosite formation on Mars, highlighting the geologic importance of paleo ice-related processes on this planet. Additional implications concern the preservation of dust-related signals in deep ice cores with respect to paleoclimatic reconstructions and the englacial history of meteorites from Antarctic blue ice fields.

Multivariate regression is a fundamental supervised chemometric approach that defines the relationship between a set of independent variables and a quantitative response. It enables the subsequent prediction of the response for future samples, thus avoiding its experimental measurement. Regression approaches have been widely applied for data analysis in different scientific fields. In this paper, we describe the regression toolbox for MATLAB, which is a collection of modules for calculating some well-known regression methods: Ordinary Least Squares (OLS), Partial Least Squares (PLS), Principal Component Regression (PCR), Ridge and local regression based on sample similarities, such as Binned Nearest Neighbours (BNN) and k-Nearest Neighbours (kNN) regression methods. Moreover, the toolbox includes modules to couple regression approaches with supervised variable selection based on All Subset models, Forward Selection, Genetic Algorithms and Reshaped Sequential Replacement. The toolbox is freely available at the Milano Chemometrics and QSAR Research Group website and provides a graphical user interface (GUI), which allows the calculation in a user-friendly graphical environment.

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The aim of the FAMU (Fisica degli Atomi Muonici) experiment is to realize the first measurement of the hyperfine splitting (hfs) in the 1S state of muonic hydrogen Delta E-1S(hfs), by using the RIKEN-RAL intense pulsed muon beam and a high-energy mid-infrared tunable laser. This requires a detailed study of the muon transfer mechanism at different temperatures and hence at different epithermal states of the muonic system. The experimental setup involves a cryogenic pressurized gas target and a detection system based on silicon photomultipliers-fiber beam hodoscopes and high purity Germanium detectors and Cerium doped Lanthanium Bromide crystals, for X-rays detection at energies around 100 keV.Simulation, construction and detector performances of the FAMU apparatus at RAL are reported in this paper.

Cryoconite, a sediment found on the surface of glaciers, is known for its ability to accumulate radionuclides. New data on cryoconite from the Morteratsch glacier (Switzerland) are presented to shed light on the mechanisms that control the distribution of radioactivity in cryoconite. Among the radionuclides detected in our samples, we have identified 108mAg, an artificial species which has never been observed in terrestrial environments before. This finding supports that cryoconite has an extraordinary ability to accumulate radioactivity. Our results also show that the radioactivity of cryoconite from a single glacier is far from uniform. Both the absolute amount of radioactivity and the relative contribution of single radionuclides are highly variable in samples from the Morteratsch glacier. To investigate the processes responsible for such variability, we have explored the correlation between radionuclides, organic and inorganic carbon fractions and the morphological features of cryoconite deposits. We have found that the degree of connection between cryoconite and supraglacial hydrology is particularly important, since it strongly influences the accumulation of radionuclides in cryoconite. Cryoconite holes connected with supraglacial channels are rich in cosmogenic 7Be; in contrast, poorly connected deposits are rich in artificial fallout radionuclides and elemental carbon. The very different half-lives of 7Be and artificial radionuclides allowed us to discuss our findings in relation to the age and maturity of cryoconite deposits, highlighting the potential use of radionuclides to investigate hydrological supraglacial processes and material cycling at the surface of glaciers.

Cryoconite is rich in natural and artificial radioactivity, but a discussion about its ability to accumulate radionuclides is lacking. A characterization of cryoconite from two Alpine glaciers is presented here. Results confirm that cryoconite is significantly more radioactive than the matrices usually adopted for the environmental monitoring of radioactivity, such as lichens and mosses, with activity concentrations exceeding 10 000 Bq kg-1 for single radionuclides. This makes cryoconite an ideal matrix to investigate the deposition and occurrence of radioactive species in glacial environments. In addition, cryoconite can be used to track environmental radioactivity sources. We have exploited atomic and activity ratios of artificial radionuclides to identify the sources of the anthropogenic radioactivity accumulated in our samples. The signature of cryoconite from different Alpine glaciers is compatible with the stratospheric global fallout and Chernobyl accident products. Differences are found when considering other geographic contexts. A comparison with data from literature shows that Alpine cryoconite is strongly influenced by the Chernobyl fallout, while cryoconite from other regions is more impacted by events such as nuclear test explosions and satellite reentries. To explain the accumulation of radionuclides in cryoconite, the glacial environment as a whole must be considered, and particularly the interaction between ice, meltwater, cryoconite and atmospheric deposition. We hypothesize that the impurities originally preserved into ice and mobilized with meltwater during summer, including radionuclides, are accumulated in cryoconite because of their affinity for organic matter, which is abundant in cryoconite. In relation to these processes, we have explored the possibility of exploiting radioactivity to date cryoconite.

The FAMU experiment aims to accurately measure the hyperfine splitting of the ground state of the muonic hydrogen atom. A measurement of the transfer rate of muons from hydrogen to heavier gases is necessary for this purpose. In June 2014, within a preliminary experiment, a pressurized gas-target was exposed to the pulsed low-energy muon beam at the RIKEN RAL muon facility (Rutherford Appleton Laboratory, UK). The main goal of the test was the characterization of both the noise induced by the pulsed beam and the X-ray detectors. The apparatus, to some extent rudimental, has served admirably to this task. Technical results have been published that prove the validity of the choices made and pave the way for the next steps. This paper presents the results of physical relevance of measurements of the muon transfer rate to carbon dioxide, oxygen, and argon from non-thermalized excited µp atoms. The analysis methodology and the approach to the systematics errors are useful for the subsequent study of the transfer rate as function of the kinetic energy of the µp currently under way.

Accurate estimates of the past extent of the Greenland ice sheet provide critical constraints for ice sheet models used to determine Greenland’s response to climate forcing and contribution to global sea level. Here we use a continuous ice core dust record from the Renland ice cap on the east coast of Greenland to constrain the timing of changes to the ice sheet margin and relative sea level over the last glacial cycle. During the Holocene and the previous interglacial period (Eemian) the dust record was dominated by coarse particles consistent with rock samples from central East Greenland. From the coarse particle concentration record we infer the East Greenland ice sheet margin advanced from 113.4 ± 0.4 to 111.0 ± 0.4 ka BP during the glacial onset and retreated from 12.1 ± 0.1 to 9.0 ± 0.1 ka BP during the last deglaciation. These findings constrain the possible response of the Greenland ice sheet to climate forcings.

Airborne dust extracted from deep ice core perforations can provide chemical and mineralogical insight into the history of the climate and atmospheric conditions, with unrivalled temporal resolution, time span and richness of information. The availability of material for research and the natural complexity of the particulate, however, pose significant challenges to analytical methods. We present the developments undertaken to optimize the experimental techniques, materials and protocols for synchrotron radiation-based analysis, in particular for the acquisition of combined Synchrotron Radiation X-Ray Fluorescence and X-ray Absorption Spectroscopy data

The input of mineral dust from arid regions impacts snow optical properties. The induced albedo reduction generally alters the melting dynamics of the snowpack, resulting in earlier snowmelt. In this paper, we evaluate the impact of dust depositions on the melting dynamics of snowpack at a high-elevation site (2160 m) in the European Alps (Torgnon, Aosta Valley, Italy) during three hydrological years (2013-2016). These years were characterized by several Saharan dust events that deposited significant amounts of mineral dust in the European Alps. We quantify the shortening of the snow season due to dust deposition by comparing observed snow depths and those simulated with the Crocus model accounting, or not, for the impact of impurities. The model was run and tested using meteorological data from an automated weather station. We propose the use of repeated digital images for tracking dust deposition and resurfacing in the snowpack. The good agreement between model prediction and digital images allowed us to propose the use of an RGB index (i.e. snow darkening index - SDI) for monitoring dust on snow using images from a digital camera. We also present a geochemical characterization of dust reaching the Alpine chain during spring in 2014. Elements found in dust were classified as a function of their origin and compared with Saharan sources. A strong enrichment in Fe was observed in snow containing Saharan dust. In our case study, the comparison between modelling results and observations showed that impurities deposited in snow anticipated the disappearance of snow up to 38 d a out of a total 7 months of typical snow duration. This happened for the season 2015-2016 that was characterized by a strong dust deposition event. During the other seasons considered here (2013-2014 and 2014-2015), the snow melt-out date was 18 and 11 d earlier, respectively. We conclude that the effect of the Saharan dust is expected to reduce snow cover duration through the snow-albedo feedback