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Abstract For high rate water electrolysers, minimising Ohmic losses through efficient gas bubble evacuation away from the active electrode is as important as minimising activation losses by improving the electrode’s electrocatalytic properties. In this work, by a combined experimental and computational fluid dynamics (CFD) approach, we identify the topological parameters of flow-engineered 3-D electrodes that direct their performance towards enhanced bubble evacuation. In particular, we show that integrating Ni-based foam electrodes into a laterally-graded bi-layer zero-gap cell configuration allows for alkaline water electrolysis to become Proton Exchange Membrane (PEM)-like, even when keeping a state-of-the-art Zirfon diaphragm. Detailed CFD simulations, explicitly taking into account the entire 3-D electrode and cell topology, show that under a forced uniform upstream electrolyte flow, such a graded structure induces a high lateral velocity component in the direction normal to and away from the diaphragm. This work is therefore an invitation to start considering PEM-like cell designs for alkaline water electrolysis as well, in particular the use of square or rectangular electrodes in flow-through type electrochemical cells.

Abstract Explosive volcanic eruptions represent a serious threat to agriculture in many countries. Ashfall can cause substantial damage to crops, jeopardizing farmers' livelihoods and potentially endangering food security. Previous field‐based studies have associated ash impact on crops with the deposit thickness, or, correspondingly, with the mass load. However, non‐volcanic factors, including plant traits and growth stage, also influence the vulnerability of crops to ashfall. To accurately estimate the risk of crop production loss in ash‐prone areas, it is essential to evaluate how these factors govern the impact of ash on crops. We grew leafy (lettuce, Lactuca sativa; hative d'Heverlée, and cabbage, Brassica oleracea; cabus de Chateaurenard) and bulb and root (onion, Allium cepa; blanc premier, and carrot, Daucus carota; hative d‘Oxhella) vegetables in a greenhouse and exposed them at two growth stages to simulated ash deposits ranging from 5 to 40 kg m−2. Our results confirm that crop production loss increases with higher ash mass load, reaching 27%–69% for deposits of 20–40 kg m−2. Additionally, they indicate a higher vulnerability of carrot and onion plants than previously reported. Lettuce and cabbage plants were more severely impacted by ash compared to onion and carrot plants, illustrating the role of plant traits in controlling ash interception and retention on foliage. Furthermore, the plant growth stage emerged as another vulnerability factor. Using the new impact data, we calculated a theoretical production loss in a cultivated area potentially affected by ashfall. This revealed that a significant portion of the crop production loss can be associated with low ash mass loads (5 kg m−2), emphasizing the importance of including distal regions in the impact assessment of ashfall on crops.

Ashfall from volcanic eruptions endangers crop production and food security while jeopardising agricultural livelihoods. As populations in the vicinity of volcanoes continue to grow, strategies to reduce volcanic risks to and impacts on crops are increasingly needed. Current models of crop vulnerability to ash are limited. They also rely solely on ash thickness (or loading) as the hazard intensity metric and fail to reproduce the complex interplay of other volcanic and non-volcanic factors that drive impact. Amongst these, ash retention on crop leaves affects photosynthesis and is ultimately responsible for widespread damage to crops. In this context, we carried out greenhouse experiments to assess how ash grain size, leaf pubescence, and humidity conditions at leaf surfaces influence the retention of ash (defined as the percentage of foliar cover coated with ash) in tomato and chilli pepper plants, two crop types commonly grown in volcanic regions. For a fixed ash mass load (∼570 g m−2), we found that ash retention decreases exponentially with increasing grain size and is enhanced when leaves are pubescent (such as in tomato plants) or when their surfaces are wet. Assuming that leaf area index (LAI) diminishes with ash retention in tomato and chilli pepper plants, we derived a new expression for predicting potential crop yield loss after an ashfall event. We suggest that the measurement of crop LAI in ash-affected areas may serve as an impact metric. Our study demonstrates that quantitative insights into crop vulnerability can be gained rapidly from controlled experiments. We advocate this approach to broaden our understanding of ash–plant interactions and to validate the use of remote sensing methods for assessing crop damage and recovery at various spatial and time scales after an eruption.

Vegetation plays a key role in the hydrological and biogeochemical cycles. It can influence soil water fluxes and transport, which are critical for chemical weathering and soil development. In this study, we investigated soil water balance and solute fluxes in two soil profiles with different vegetation types (cushion-forming plants vs. tussock grasses) in the high Ecuadorian Andes by measuring soil water content, flux, and solute concentrations and by modeling soil hydrology. We also analyzed the role of soil water balance in soil chemical weathering. The influence of vegetation on soil water balance and solute fluxes is restricted to the A horizon. Evapotranspiration is 1.7 times higher and deep drainage 3 times lower under cushion-forming plants than under tussock grass. Likewise, cushions transmit about 2-fold less water from the A to lower horizons. This is attributed to the higher soil water retention and saturated hydraulic conductivity associated with a shallower and coarser root system. Under cushion-forming plants, dissolved organic carbon (DOC) and metals (Al, Fe) are mobilized in the A horizon. Solute fluxes that can be related to plant nutrient uptake (Mg, Ca, K) decline with depth, as expected from biocycling of plant nutrients. Dissolved silica and bicarbonate are minimally influenced by vegetation and represent the largest contributions of solute fluxes. Soil chemical weathering is higher and constant with depth below tussock grasses but lower and declining with depth under cushion-forming plants. This difference in soil weathering is attributed mainly to the water fluxes. Our findings reveal that vegetation can modify soil properties in the uppermost horizon, altering the water balance, solute fluxes, and chemical weathering throughout the soil profile.

Although the generally high fertility of volcanic soils is often seen as an opportunity, short-term consequences of eruptions on natural and cultivated vegetation are likely to be negative. The empirical knowledge obtained from post-event impact assessments provides crucial insights into the range of parameters controlling impact and recovery of vegetation, but their limited coverage in time and space offers a limited sample of all possible eruptive and environmental conditions. Consequently, vegetation vulnerability remains largely unconstrained, thus impeding quantitative risk analyses. Here, we explore how cloud-based big Earth observation data, remote sensing and interpretable machine learning (ML) can provide a large-scale alternative to identify the nature of, and infer relationships between, drivers controlling vegetation impact and recovery. We present a methodology developed using Google Earth Engine to systematically revisit the impact of past eruptions and constrain critical hazard and vulnerability parameters. Its application to the impact associated with the tephra fallout from the 2011 eruption of Cordón Caulle volcano (Chile) reveals its ability to capture different impact states as a function of hazard and environmental parameters and highlights feedbacks and thresholds controlling impact and recovery of both natural and cultivated vegetation. We therefore conclude that big Earth observation (EO) data and machine learning complement existing impact datasets and open the way to a new type of dynamic and large-scale vulnerability models.

Agriculture is an economic and social pillar for the least developed countries. When these regions host volcanoes that exhibit explosive behaviour, a serious risk for agricultural production arises as crops endure various impacts from tephra fall. In order to gain new insights into the factors that govern tephra impacts on crops, we collected farmers’ perceptions of crop damage and production loss due to exposure to tephra fallout in 15 villages affected by the 1999–2014 eruptions of Tungurahua volcano, Ecuador. Crop type and developmental stage - both influenced by altitude - strongly modulate the level of tephra-induced impact. Using these observations, we illustrate how crop vulnerability fluctuates spatially and temporarily in the surveyed area. The study also highlights that fine tephra (

Abstract Background Anticoagulant therapies are used to prevent atrial fibrillation-related strokes, with warfarin and direct oral anticoagulant (DOAC) the most common. In this study, we incorporate direct health care costs, drug costs, travel costs, and lost working and leisure time costs to estimate the total costs of the two therapies. Methods This retrospective study used individual-level patient data from 4000 atrial fibrillation (AF) patients from North Karelia, Finland. Real-world data on healthcare use was obtained from the regional patient information system and data on reimbursed travel costs from the database of the Social Insurance Institution of Finland. The costs of the therapies were estimated between June 2017 and May 2018. Using a Geographical Information System (GIS), we estimated travel time and costs for each journey related to anticoagulant therapies. We ultimately applied therapy and travel costs to a cost model to reflect real-world expenditures. Results The costs of anticoagulant therapies were calculated from the standpoint of patient and the healthcare service when considering all costs from AF-related healthcare visits, including major complications arising from atrial fibrillation. On average, the annual cost per patient for healthcare in the form of public expenditure was higher when using DOAC therapy than warfarin therapy (average cost = € 927 vs. € 805). Additionally, the average annual cost for patients was also higher with DOAC therapy (average cost = € 406.5 vs. € 296.7). In warfarin therapy, patients had considerable more travel and time costs due the different implementation practices of therapies. Conclusion The results indicated that DOAC therapy had higher costs over warfarin from the perspectives of the patient and healthcare service in the study area on average. Currently, the cost of the DOAC drug is the largest determinator of total therapy costs from both perspectives. Despite slightly higher costs, the patients on DOAC therapy experienced less AF-related complications during the study period.

NDS is an interactive, web-based system, for the visualization of multidimensional neighborhood dynamics across the 50 largest US Metropolitan Statistical Areas (MSAs) from 1980 to 2010 (http://neighborhooddynamics.dreamhosters.com). Four different visualization tools are developed: (1) an interactive time slider to show neighborhood classification changes for different years; (2) multiple interactive bar charts for each variables of each neighborhood; (3) an animated neighborhood’s trajectory and sequence cluster on a self-organizing map (SOM) output space; and (4) a synchronized visualization tool showing maps for four time stamps at once. The development of this interactive online platform for visualizing dynamics overcomes many of the challenges associated with communicating changes for multiple variables, across multiple time stamps, and for a large geographic area when relying upon static maps. The system enables users to select and dive into details on particular neighborhoods and explore their changes over time.

In 1914, a magnificent reliquary cross dating from the early XIIIth century was discovered in a safe from the Liège Cathedral. This double-arm cross shows a wooden structure, covered by gold-coated copper on the front, and by carved silver plates on the back. Its total length is 34 cm, and it is covered by filigrees, gems, glass beads, and pearls on its front. The reliquary cross was analysed by Raman spectrometry and X-ray fluorescence spectrometry (pXRF) to determine the mineralogical and chemical compositions of gems, glass beads, and metals that have been used to decorate it. The results confirm the identification of twenty-five turquoises from Egypt, one garnet from Sri Lanka, as well as six quartz and one opal whose origin is difficult to certify. Twelve glass beads, showing green, blue, or amber tints, were also identified. Their compositions either correspond to soda lime glasses with natron or to potash–lead glasses similar to those of Central Europe. Moreover, a small polished red cross and a green stone appear to be constituted by nice doublets, composed of coloured glass covered by quartz. The filigrees contain Au and Cu, while carved plates covering the edges and the back of the cross are made of silver.

The last decade of urbanization throughout many cities have seen a perceptible shift in the demand for centralized urban amenities while poverty has increasingly decentralized. Yet, the opportunity landscape of these shifting geographies of poverty and prosperity are not well understood. In this article, we examine how access to employment for low-income households has been impacted as a result of these changing geographies. Using a case study on the Charlotte metropolitan area we examine whether the suburbanization of poverty and reinvestment in the center city has reshaped the job opportunity landscape for low-wage residents. The objectives of this article are twofold. First, we calculate and map autobased accessibility from all neighborhoods in the Charlotte metropolitan area to job locations, differentiated by wage categories, in 2010 and 2017 to identify potential changes in the mismatch between low-income households and access to employment. We use a point-level employment dataset for these two years and calculate accessibility originating from census block groups. Second, we estimate the extent to which access to employment has affected employment rates and household incomes at the neighborhood level using a first-difference, spatial two-stage least squares model with instrumental variables. Our findings suggest that changes in accessibility had no significant effect on changes in neighborhood employment rates. However, we find evidence that increasing accessibility for lower-income households could have a positive effect on neighborhood median household incomes. Overall, the polycentric nature of Charlotte appears to have reduced the spatial mismatch between low-income workers and low-wage jobs.

Abstract In active volcanic regions, high‐temperature chemical reactions in the hydrothermal system consume CO2 sourced from magma or from the deep crust, whereas reactions with silicates at shallow depths mainly consume atmospheric CO2. Numerous studies have quantified the load of dissolved solids in rivers that drain volcanic regions to determine chemical weathering rates and atmospheric CO2 consumption rates. However, the balance between thermal and non‐thermal components to riverine fluxes in these areas remains poorly constrained, hindering accurate estimates of atmospheric CO2 consumption rates. Here we use the Ge/Si ratio and the stable silicon isotopes (δ30Si) as tracers for quantifying non‐thermal silicon contributions in rivers draining the Yellowstone Plateau Volcanic Field, USA. The Ge/Si ratio (µmol.mol−1) was determined for seven thermal water samples (183 ± 22), eight rivers (35 ± 23) and six creeks flowing into Yellowstone Lake (5 ± 3) during base flow and during peak water discharge following snowmelt. The δ30Si value (‰) was determined for thermal waters (−0.09 ± 0.04), Yellowstone River at Yellowstone Lake outlet (1.91 ± 0.23) and creek samples (0.82 ± 0.29). The calculated atmospheric CO2 consumption associated with non‐thermal waters flowing through Yellowstone's rivers during peak discharge is ∼3.03 ton.km−2.yr−1, which is ∼2% of the annual mean atmospheric CO2 consumption in other volcanic regions. This study highlights the significance of quantifying seasonal variations in chemical weathering rates for improving estimates of atmospheric CO2 consumption rates in active volcanic regions.

Peer-reviewed publications are the most common way of sharing scientific knowledge internationally. Volcanica is the only fully diamond open access journal in volcanology, publishing peer-reviewed articles without costs to authors or readers. As part of our wider journal mission, Volcanica also aims to address some of the biggest barriers in research publication and to increase accessibility to published, written research outputs. In this Editorial, we discuss Volcanica’s latest venture: to publish a complete Special Issue of Reports—one of our flagship publication formats designed specifically for cutting edge, direct observations from volcanoes—and to do so in both English and Spanish languages. Las publicaciones revisadas por pares son la forma más común de compartir el conocimiento científico a nivel internacional. Volcanica es la única revista de tipo “diamond open access” en volcanología que publica artículos revisados por pares sin ningún costo para los autores o lectores. Volcanica también tiene como objetivos reducir algunas de las mayores barreras de las publicaciones científicas y aumentar la accesibilidad a los resultados de las investigaciones publicadas. En este editorial, analizamos la última aventura de Volcanica: publicar un número especial constituido íntegramente por Reportes –uno de nuestros formatos de publicación insignia, diseñado específicamente para observaciones directas y de vanguardia sobre volcanes– en los idiomas inglés y español.

As the threat of arboviral diseases continues to escalate worldwide, the question of, “What types of human communities are at the greatest risk of infection?” persists as a key gap in the existing knowledge of arboviral diseases transmission dynamics. Here, we comprehensively review the existing literature on the socioeconomic drivers of the most common Aedes mosquito-borne diseases and Aedes mosquito presence/abundance. We reviewed a total of 182 studies on dengue viruses (DENV), chikungunya virus (CHIKV), yellow fever virus (YFVV), Zika virus (ZIKV), and presence of Aedes mosquito vectors. In general, associations between socioeconomic conditions and both Aedes-borne diseases and Aedes mosquitoes are highly variable and often location-specific. Although 50% to 60% of studies found greater presence or prevalence of disease or vectors in areas with lower socioeconomic status, approximately half of the remaining studies found either positive or null associations. We discuss the possible causes of this lack of conclusiveness as well as the implications it holds for future research and prevention efforts.

We determine the impact of residential mobility in the prevalence and transmission dynamics of sexually transmitted infections. We illustrate our approach on reported chlamydia infections obtained from the Michigan Disease Surveillance System for Kalamazoo County, USA, from 2006 to 2014. We develop two scenarios, one with fixed residential addresses and one considering residential mobility. We then compare the resulting space-time clusters and relative risk (RR) of infection. The space-time scan statistics showed increased RR in an area with previously low risk of sexually transmitted infections. In addition, even though the spatial extent of the three clusters identified did not change significantly at the scale we conducted our analysis at, the temporal extent (duration) did exhibit significant changes and could be considered for unique interventions. The results indicate that residential mobility has some dependency on the prevalence and transmission dynamics of sexually transmitted infections to new areas. We suggest that strategies adopted to reduce the burden of sexually transmitted infections take into consideration the relatively high residential mobility of at-risk populations to reduce spreading the infections to new areas.

Mine wastes and tailings derived from historical processing may contain significant contents of valuable metals due to processing being less efficient in the past. The Plombières tailings pond in eastern Belgium was selected as a case study to determine mineralogical and geochemical characteristics of the different mine waste materials found at the site. Four types of material were classified: soil, metallurgical waste, brown tailings and yellow tailings. The distribution of the mine wastes was investigated with drill holes, pit-holes and geophysical methods. Samples of the materials were assessed with grain size analysis, and mineralogical and geochemical techniques. The mine wastes dominantly consist of SiO2, Al2O3 and Fe2O3. The cover material, comprising soil and metallurgical waste is highly heterogeneous in terms of mineralogy, geochemistry and grain size. The metallurgical waste has a high concentration of metals (Zn: 0.1 to 24 wt.% and Pb: 0.1 to 10.1 wt.%). In the tailings materials, Pb and Zn vary from 10 ppm to 8.5 wt.% and from 51 ppm to 4 wt.%, respectively. The mining wastes comprises mainly quartz, amorphous phases and phyllosilicates, with minor contents of Fe-oxide and Pb- and Zn-bearing minerals. Based on the mineralogical and geochemical properties, the different potential applications of the four waste material types were determined. Additionally, the theoretical economic potential of Pb and Zn in the mine wastes was estimated.

Accelerated processing capabilities are deemed critical when conducting analysis on spatiotemporal datasets of increasing size, diversity and availability. High-performance parallel computing offers the capacity to solve computationally demanding problems in a limited timeframe, but likewise poses the challenge of preventing processing inefficiency due to workload imbalance between computing resources. Therefore, when designing new algorithms capable of implementing parallel strategies, careful spatiotemporal domain decomposition is necessary to account for heterogeneity in the data. In this study, we perform octtree-based adaptive decomposition of the spatiotemporal domain for parallel computation of space-time kernel density. In order to avoid edge effects near subdomain boundaries, we establish spatiotemporal buffers to include adjacent data-points that are within the spatial and temporal kernel bandwidths. Then, we quantify computational intensity of each subdomain to balance workloads among processors. We illustrate the benefits of our methodology using a space-time epidemiological dataset of Dengue fever, an infectious vector-borne disease that poses a severe threat to communities in tropical climates. Our parallel implementation of kernel density reaches substantial speedup compared to sequential processing, and achieves high levels of workload balance among processors due to great accuracy in quantifying computational intensity. Our approach is portable of other space-time analytical tests.

Scholars are in agreement that the local food environment is shaped by a multitude of factors from socioeconomic characteristics to transportation options, as well as the availability and distance to various food establishments. Despite this, most place-based indicators of “food deserts”, including those identified as so by the US Department of Agriculture (USDA), only include a limited number of factors in their designation. In this article, we adopt a geodemographic approach to classifying the food access landscape that takes a multivariate approach to describing the food access landscape. Our method combines socioeconomic indicators, distance measurements to Supplemental Nutrition Assistance Program (SNAP) participating stores, and neighborhood walkability using a k-means clustering approach and North Carolina as a case study. We identified seven distinct food access types: three rural and four urban. These classes were subsequently prioritized based on their defining characteristics and specific policy recommendations were identified. Overall, compared to the USDA’s food desert calculation, our approach identified a broader swath of high-needs areas and highlights neighborhoods that may be overlooked for intervention when using simple distance-based methods.

This analysis examines the spatial fragmentation of the urban landscape with respect to neighborhoods classified according to their racial, demographic, housing and socioeconomic characteristics. The analysis is performed on the 50 largest metropolitan areas throughout the United States from 1990–2010, and looks at both global trends over time using a landscape ecology metric of edge density to quantify fragmentation over time. It then analyzes the spatial clustering of each neighborhood type over time, for each city. Results illustrate an increasingly fragmented urban landscape with respect to neighborhood type, led by Los Angeles as the most fragmented metropolitan area. Decomposed by neighborhood type, both racially concentrated high-poverty neighborhoods, as well as neighborhoods with a highly educated population, have increased in spatial concentration in large cities over time, exposing rises in spatial inequalities even as global patterns suggest a breaking up of neighborhood types. The global patterns are therefore driven by declines in more moderate-income and multiethnic neighborhoods, and a decline in the spatial concentration of newer, white, single-family housing neighborhoods.