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Arctic tundra landscapes are highly complex and are rapidly changing due to the warming climate. Datasets that document the spatial and temporal variability of the landscape are needed to monitor the rapid changes. Synthetic Aperture Radar (SAR) imagery is specifically suitable for monitoring the Arctic, as SAR, unlike optical remote sensing, can provide time series regardless of weather and illumination conditions. This study examines the potential of seasonal backscatter mechanisms in Arctic tundra environments for improving land cover classification purposes by using a time series of HH/HV TerraSAR-X (TSX) imagery. A Random Forest (RF) classification was applied on multi-temporal Sigma Nought intensity and multi-temporal Kennaugh matrix element data. The backscatter analysis revealed clear differences in the polarimetric response of water, soil, and vegetation, while backscatter signal variations within different vegetation classes were more nuanced. The RF models showed that land cover classes could be distinguished with 92.4% accuracy for the Kennaugh element data, compared to 57.7% accuracy for the Sigma Nought intensity data. Texture predictors, while improving the classification accuracy on the one hand, degraded the spatial resolution of the land cover product. The Kennaugh elements derived from TSX winter acquisitions were most important for the RF model, followed by the Kennaugh elements derived from summer and autumn acquisitions. The results of this study demonstrate that multi-temporal Kennaugh elements derived from dual-polarized X-band imagery are a powerful tool for Arctic tundra land cover mapping.

Permafrost thaw poses diverse risks to Arctic environments and livelihoods. Understanding the effects of permafrost thaw is vital for informed policymaking and adaptation efforts. Here, we present the consolidated findings of a risk analysis spanning four study regions: Longyearbyen (Svalbard, Norway), the Avannaata municipality (Greenland), the Beaufort Sea region and the Mackenzie River Delta (Canada) and the Bulunskiy District of the Sakha Republic (Russia). Local stakeholders’ and scientists’ perceptions shaped our understanding of the risks as dynamic, socionatural phenomena involving physical processes, key hazards, and societal consequences. Through an inter- and transdisciplinary risk analysis based on multidirectional knowledge exchanges and thematic network analysis, we identified five key hazards of permafrost thaw. These include infrastructure failure, disruption of mobility and supplies, decreased water quality, challenges for food security, and exposure to diseases and contaminants. The study’s novelty resides in the comparative approach spanning different disciplines, environmental and societal contexts, and the transdisciplinary synthesis considering various risk perceptions. In the Arctic, the risks of the permafrost thaw are perceived differently by communities, and key hazards include infrastructure failure, mobility disruption, decreased water quality and food security, and exposure to diseases, according to a transdisciplinary analysis based on workshops and a thematic network approach.

Ongoing climate warming in the western Canadian Arctic is leading to thawing of permafrost soils and subsequent mobilization of its organic matter pool. Part of this mobilized terrestrial organic matter enters the aquatic system as dissolved organic matter (DOM) and is laterally transported from land to sea. Mobilized organic matter is an important source of nutrients for ecosystems, as it is available for microbial breakdown, and thus a source of greenhouse gases. We are beginning to understand spatial controls on the release of DOM as well as the quantities and fate of this material in large Arctic rivers. Yet, these processes remain systematically understudied in small, high-Arctic watersheds, despite the fact that these watersheds experience the strongest warming rates in comparison. Here, we sampled soil (active layer and permafrost) and water (porewater and stream water) from a small ice wedge polygon (IWP) catchment along the Yukon coast, Canada, during the summer of 2018. We assessed the organic carbon (OC) quantity (using dissolved (DOC) and particulate OC (POC) concentrations and soil OC content), quality (δ13C DOC, optical properties and source apportionment) and bioavailability (incubations; optical indices such as slope ratio, Sr; and humification index, HIX) along with stream water properties (temperature, T; pH; electrical conductivity, EC; and water isotopes). We classify and compare different landscape units and their soil horizons that differ in microtopography and hydrological connectivity, giving rise to differences in drainage capacity. Our results show that porewater DOC concentrations and yield reflect drainage patterns and waterlogged conditions in the watershed. DOC yield (in mg DOC g−1 soil OC) generally increases with depth but shows a large variability near the transition zone (around the permafrost table). Active-layer porewater DOC generally is more labile than permafrost DOC, due to various reasons (heterogeneity, presence of a paleo-active-layer and sampling strategies). Despite these differences, the very long transport times of porewater DOC indicate that substantial processing occurs in soils prior to release into streams. Within the stream, DOC strongly dominates over POC, illustrated by DOC/POC ratios around 50, yet storm events decrease that ratio to around 5. Source apportionment of stream DOC suggests a contribution of around 50 % from permafrost/deep-active-layer OC, which contrasts with patterns observed in large Arctic rivers (12 ± 8 %; Wild et al., 2019). Our 10 d monitoring period demonstrated temporal DOC patterns on multiple scales (i.e., diurnal patterns, storm events and longer-term trends), underlining the need for high-resolution long-term monitoring. First estimates of Black Creek annual DOC (8.2 ± 6.4 t DOC yr−1) and POC (0.21 ± 0.20 t yr−1) export allowed us to make a rough upscaling towards the entire Yukon Coastal Plain (34.51 ± 2.7 kt DOC yr−1 and 8.93 ± 8.5 kt POC yr−1). Rising Arctic temperatures, increases in runoff, soil organic matter (OM) leaching, permafrost thawing and primary production are likely to increase the net lateral OC flux. Consequently, altered lateral fluxes may have strong impacts on Arctic aquatic ecosystems and Arctic carbon cycling.

Permafrost soils are particularly vulnerable to climate change. To assess and improve estimations of carbon (C) and nitrogen (N) budgets it is necessary to accurately map soil carbon and nitrogen in the permafrost region. In particular, soil organic carbon (SOC) stocks have been predicted and mapped by many studies from local to pan-Arctic scales. Several studies have been carried out at the Canadian Beaufort Sea coast, though no regional maps of terrestrial carbon stocks based on spatial modelling has been conducted yet. This study combines available field data from the Canadian Yukon coastal plain and uses it to map regional SOC and N stocks using the machine learning algorithm random forest and environmental variables based on remote sensing data. We developed models using the data for the entire region and separate models for the coastal mainland area and Qikiqtaruk Herschel Islandand. Each model was used to map SOC and N stocks for its respective area. We assessed the performance of the different random forest models by using crossvalidation. We further assessed model results using the Area of Applicability (AOA) method and the quantile regression forest approach, comparing the results and discussing their implications within the context of both methods. We explore local differences in soil properties and how soil data distribution across the region affects the accuracy of the predictions of SOC and N stocks. The estimated SOC stock for the upper metre is 48.7 ± 6.6 kg m−2 and the N stock 3.03 ± 0.30 kg m−2. The average SOC stocks vary significantly when creating separate models for subsets of the data. Qikiqtaruk Herschel Island is geologically different from the coastal mainland and has on average lower SOC stocks. Including Qikiqtaruk Herschel Island soil data to predict SOC stocks at the mainland has large impact on the results. Differences in N stocks were not as dependent on the location as SOC stocks and rather differences between individual studies occurred. The results of the separate models show 38.0 ± 5.6 kg C m−2 and 2.87 ± 0.34 kg N m−2 for Qikiqtaruk Herschel Island and 52.5 ± 6.3 kg C m−2 and 3.15 ± 0.32 kg N m−2 for the mainland. These estimates refer to the entire study area, without masking out regions outside the Area of Applicability (AOA). Our results indicate that the spatial perspective, whether regional or local (whole area vs. mainland and Qikiqtaruk Herschel Island separately), can affect the patterns and values represented in the resulting maps, highlighting the importance of scale when interpreting SOC and N stock distributions. Using a more densely sampled, region-specific dataset, our study captures finer regional-scale patterns than previous lower-resolution or pan-Arctic analyses.

This work presents results from an original open-source low-cost sensor (LCS) system developed to measure tropospheric O3 in a remote high altitude alpine site. Our study was conducted at the Col Margherita Observatory (2543 m above sea level), in the Italian Eastern Alps. The sensor system mounts three commercial low-cost O3/NO2 sensors that have been calibrated before field deployment against a laboratory standard (Thermo Scientific; 49i-PS), calibrated against the standard reference photometer no. 15 calibration scale of the World Meteorological Organization (WMO). Intra- and intercomparison between the sensors and a reference instrument (Thermo Scientific; 49c) have been conducted for 7 months from May to December 2018. The sensors required an individual calibration, both in laboratory and in the field. The sensor's dependence on the environmental meteorological variables has been considered and discussed. We showed that it is possible to reduce the bias of one LCS by using the average coefficient values of another LCS working in tandem, suggesting a way forward for the development of remote field calibration techniques. We showed that it is possible reconstruct the environmental ozone concentration during the loss of reference instrument data in situations caused by power outages. The evaluation of the analytical performances of this sensing system provides a limit of detection (LOD) <5 ppb (parts per billion), limit of quantification (LOQ) <17 ppb, linear dynamic range (LDR) up to 250 ppb, intra-Pearson correlation coefficient (PCC) up to 0.96, inter-PCC >0.8, bias >3.5 ppb and ±8.5 at 95 % confidence. This first implementation of a LCS system in an alpine remote location demonstrated how to obtain valuable data from a low-cost instrument in a remote environment, opening new perspectives for the adoption of low-cost sensor networks in atmospheric sciences.

This work presents results from an original open-source low-cost sensor (LCS) system developed to measure tropospheric O3 in a remote high altitude alpine site. Our study was conducted at the Col Margherita Observatory (2543 m above sea level), in the Italian Eastern Alps. The sensor system mounts three commercial low-cost O3/NO2 sensors that have been calibrated before field deployment against a laboratory standard (Thermo Scientific; 49i-PS), calibrated against the standard reference photometer no. 15 calibration scale of the World Meteorological Organization (WMO). Intra- and intercomparison between the sensors and a reference instrument (Thermo Scientific; 49c) have been conducted for 7 months from May to December 2018. The sensors required an individual calibration, both in laboratory and in the field. The sensor's dependence on the environmental meteorological variables has been considered and discussed. We showed that it is possible to reduce the bias of one LCS by using the average coefficient values of another LCS working in tandem, suggesting a way forward for the development of remote field calibration techniques. We showed that it is possible reconstruct the environmental ozone concentration during the loss of reference instrument data in situations caused by power outages. The evaluation of the analytical performances of this sensing system provides a limit of detection (LOD) <5 ppb (parts per billion), limit of quantification (LOQ) <17 ppb, linear dynamic range (LDR) up to 250 ppb, intra-Pearson correlation coefficient (PCC) up to 0.96, inter-PCC >0.8, bias >3.5 ppb and ±8.5 at 95 % confidence. This first implementation of a LCS system in an alpine remote location demonstrated how to obtain valuable data from a low-cost instrument in a remote environment, opening new perspectives for the adoption of low-cost sensor networks in atmospheric sciences.

Cardiac amyloidosis (CA) leads to variable degrees of myocardial infiltration with a final echocardiographic phenotype of “hypertrophy.” Although many non-invasive imaging techniques (MRI, CT, scintigraphy, PET) are useful, the definitive diagnosis is still based on myocardial histology. We explored the possible role of [18F]-NaF PET/CT in the diagnosis of this disease in two cases with wild-type (ATTRwt) or mutant (ATTRm) Ile68Leu transthyretin (TTR)-related CA.

Background: Transarterial Radioembolisation (TARE) requires multidisciplinary experience and skill to be effective. The aim of this study was to identify determinants of survival in patients with hepatocellular carcinoma (HCC), focusing on learning curves, technical advancements, patient selection and subsequent therapies. Methods: From 2005 to 2020, 253 patients were treated. TARE results achieved in an initial period (2005–2011) were compared to those obtained in a more recent period (2012–2020). To isolate the effect of the treatment period, differences between the two periods were balanced using “entropy balance”. Results: Of the 253 patients, 68 were treated before 2012 and 185 after 2012. In the second period, patients had an Eastern Cooperative Oncology Group (ECOG) Performance Status (PS) score of 1 (p = 0.025) less frequently, less liver involvement (p = 0.006) and a lesser degree of vascular invasion (p = 0.019). The median overall survival (OS) of patients treated before 2012 was 11.2 months and that of patients treated beginning in 2012 was 25.7 months. After reweighting to isolate the effect of the treatment period, the median OS of patients before 2012 increased to 16 months. Conclusions: Better patient selection, refinement of technique and adoption of personalised dosimetry improved survival after TARE. Conversely, sorafenib after TARE did not impact life expectancy.

Cardiac amyloidosis (CA) leads to variable degrees of myocardial infiltration with a final echocardiographic phenotype of \"hypertrophy.\" Although many non-invasive imaging techniques (MRI, CT, scintigraphy, PET) are useful, the definitive diagnosis is still based on myocardial histology. We explored the possible role of [18F]-NaF PET/CT in the diagnosis of this disease in two cases with wild-type (ATTRwt) or mutant (ATTRm) Ile68Leu transthyretin (TTR)-related CA.Cardiac amyloidosis (CA) leads to variable degrees of myocardial infiltration with a final echocardiographic phenotype of \"hypertrophy.\" Although many non-invasive imaging techniques (MRI, CT, scintigraphy, PET) are useful, the definitive diagnosis is still based on myocardial histology. We explored the possible role of [18F]-NaF PET/CT in the diagnosis of this disease in two cases with wild-type (ATTRwt) or mutant (ATTRm) Ile68Leu transthyretin (TTR)-related CA.