bluuebunny/crossref_metadata_2025 huggingface dataset:
Sediment pollution and morphodynamics of an extreme event: Examples from the July 2021 flood event from the Inde River catchment in North Rhine-Westphalia 
Authors: Lehmkuhl Frank , Esser Verena , Schulte Philipp , Weber Alexandra , Wolf Stefanie , Schüttrumpf Holger
Published: March 2022

Extreme precipitation and discharge between July 13th and 16th 2021 caused serious flooding with bank erosion, including damages to infrastructure and buildings nearby the Eifel mountain region. Especially the small town of Stolberg and Eschweiler in the Inde River catchment were heavily affected. On-site investigation along the Inde River and its tributary, the Vichtbach creek, after the flood event show that mainly coarse sediments were remobilized and accumulated in the upper and middle reaches. The water masses mobilized not only sediments including gravel but also large objects like broken down trees and cars. In contrast, silty sediments were deposited in the lower reaches.

The Stolberg region is a former mining area with related industries resulting in contaminated soils and tailings close to the floodplains (Esser et al. 2020). Therefore, our investigations also focus on pollution by sediment-bound heavy metals and their distribution in the floodplains before and after this event. Flood sediment samples were taken immediately after the extreme flood event. Based on the results of flood-related pollution monitoring, conducted between 2016 and 2019 (Esser, 2020), the impact of the extreme event in July can be evaluated. During the July flood event, an exceptional amount of pollutants was remobilized. In addition to an increase in pollutants on the modern floodplain, wider areas of older and higher floodplains (Altauen) were also affected.

Esser, V. (2020): Untersuchungen zur fluvialen Morphodynamik und zur rezenten Schadstoffausbreitung in Flusssystemen - Beispiele aus der Grenzregion Belgien, Niederlande und Deutschland. PhD-Thesis, RWTH Aachen University.

Esser, V., Buchty-Lemke, M., Schulte, P., Podzun, L.S., Lehmkuhl, F. (2020): Signatures of recent pollution profiles in comparable Central European rivers - Examples from the International River Basin District Meuse. Catena 193: 104646. https://doi.org/10.1016/j.catena.2020.104646
Evaluation of the IVS contribution to the ITRF2020
Authors: Hellmers Hendrik , Modiri Sadegh , Bachmann Sabine , Thaller Daniela , Bloßfeld Mathis , Seitz Manuela , Gipson John
Published: March 2022

The ITRF2020 is the upcoming realization of the International Terrestrial Reference Frame. As the successor of the ITRF2014, it is based on an inter-technique combination of all four space-geodetic techniques, i.e., VLBI, GNSS, SLR and DORIS, and it is based on contributions from different institutions around the world. In this context, the Combination Centre of the International VLBI Service for Geodesy and Astrometry (IVS) – operated by the Federal Agency for Cartography and Geodesy (BKG, Germany) and the Deutsches Geodätisches Forschungsinstitut (DGFI-TUM, Germany) – generates the VLBI intra-technique combination for ITRF2020 utilizing the individual contributions of multiple IVS Analysis Centres (AC).

For the contribution to the ITRF2020 solution, sessions containing 24h VLBI observations from 1979 until the end of 2020 are reprocessed by 11 ACs and submitted to the IVS Combination Centre. All individual sessions include datum-free normal equations containing station coordinates and source positions as well as full sets of Earth Orientation Parameters (EOP) in the required SINEX format. For ensuring consistently combined solutions, time series of EOP and station coordinates, as well as a VLBI-only Terrestrial Reference Frame (VTRF), have been investigated.

This contribution focuses on detailed investigations concerning the session-dependency of the scale and the impact of the individual AC contributions to the combination. Thereby significant differences of the scale estimates from the different session types are investigated. Also, the evaluation of the ACs’ contributions to the combined solution will be presented.
Development of a snow reanalysis pipeline using downscaled ERA5 data: application to Mediterranean mountains
Authors: Sourp Laura , Gascoin Simon , Baba Mohamed Wassim , Deschamps-Berger César
Published: March 2022

The Snow Water Equivalent (SWE) is a key variable to characterize water resource availability in mountain catchments. Despite its hydrological significance, the snow cover is poorly monitored in many regions due to a lack of in situ measurements. 

Global climate reanalysis products provide increasingly accurate data but are too coarse to be used directly in mountain regions to reconstruct snow related variables. However these reanalyses have been successfully used to generate high resolution meteorological forcing and run a snowpack model in the central Andes and the High Atlas mountain ranges (Mernild et al. 2017; Baba et al. 2018). 

The method is based on the MicroMet/SnowModel package (Liston and Elder 2006a; 2006b). MicroMet performs spatial interpolation of meteorological variables using the digital elevation model (downscaling) and the other routines of SnowModel computes the snowpack energy and mass balance. We have implemented a tool to improve the automation and scalability of this method to simulate the snow cover distribution in other regions using ERA5 or ERA5-Land. Our snow simulation tool only requires a digital elevation model as input. The land cover is extracted from the Copernicus global land cover map and the meteorological data are retrieved from either ERA5 or ERA5-Land over the period of interest.  

We used three catchments under the influence of Mediterranean climate to evaluate the performance of this tool: Tuolumne (USA), Bassies (France) and Yeso (Chile). For each catchment either the modeled SWE depth or snow depth are compared with the validation data, over periods going from 3 to 8 years.  In the Tuolumne basin, where the dataset is the most accurate with several SWE maps per year, we find a very good agreement at the basin scale (RMSE 40 mm w.e.). However, the mean RMSE in the highest elevation band (3500-4000 m asl) can exceed 500 mm w.e., which we attribute to the  lack of gravitational transport in SnowModel and errors in the spatial distribution of precipitation. To reduce these errors in particular, we are implementing a non-deterministic representation of the precipitation input data to eventually allow the assimilation of globally available remote sensing data. 

This tool will allow us to compute snow reanalyses in key mountain ranges around the Mediterranean sea over the past two decades (Pyrenees, Atlas and Mount Lebanon) and study the influence of topography and climate on the snow cover variability.
Nature-based Solutions in actions: improving landscape connectivity during the COVID-19
Authors: Qiu Yangzi , Tchiguirinskaia Ioulia , Schertzer Daniel
Published: March 2022

In the last few decades, Nature-based Solutions (NBS) has become widely considered a sustainable development strategy for the development of urban environments. Assessing the performances of NBS is significant for understanding their efficiency in addressing a large range of natural and societal challenges, such as climate change, ecosystem services and human health. With the rapid onset of the COVID-19 pandemic, the inner relationship between humans and nature becomes apparent. However, the current catchment management mainly focuses on reducing hydro-meteorological and/or climatological risks and improving urban climate resilience. This single-dimensional management seems insufficient when facing epidemics, and multi-dimensional management (e.g., reduce zoonosis) is necessary. With this respect, policymakers pay more attention to NBS. Hence, it is significant to increase the connectivity of the landscape to improve the ecosystem services and reduce the health risks from COVID-19 with the help of NBS.

This study takes the Guyancourt catchment as an example. The selected catchment is located in the Southwest suburb of Paris, with a total area of around 5.2 km2. The ArcGIS software is used to assess the patterns of structural landscape connectivity, and the heterogeneous spatial distribution of current green spaces over the catchment is quantified with the help of the scale-independent indicator of fractal dimension. To quantify opportunities to increase landscape connectivity over the catchment, a least-cost path approach to map potential NBS links urban green spaces through vacant parcels, alleys, and smaller green spaces. Finally, to prioritise these potential NBS in multiscale, a new scale-independent indicator within the Universal Multifractal framework is proposed in this study.

The results indicated that NBS can effectively improve the connectivity of the landscape and has the potential to reduce the physical and mental risks caused by COVID-19. Overall, this study proposed a scale-independent approach for enhancing the multiscale connectivity of the NBS network in urban areas and providing quantitative suggestions for on-site redevelopment.
Experimental strain localization in granitoid ultramylonites: Pre-fracturing vs. viscous strain localization
Authors: Nevskaya Natalia , Zhan Weijia , Stünitz Holger , Berger Alfons , Herwegh Marco
Published: March 2022

Rheological models of Earth’s granitoid mid- to upper crust are commonly based on the physico-chemical properties of the most abundant rock forming minerals quartz and feldspar. However, there is increasing field evidence that deformation in these rocks localizes in ultrafine-grained polymineralic shear zones, which are weaker than any of the end member minerals. Especially at the brittle to viscous transition, the localization and deformation mechanisms, i.e. the role of incipient brittle deformation vs. continuous viscous strain localization, is not yet fully understood.

To fill this gap in knowledge, ultramylonite samples with granitic composition from the Central Aar Granite (Aar Massif, Central Switzerland) were deformed using a Griggs type apparatus. The foliation of the ultramylonitic starting material was oriented 45° to the compression direction, to investigate the influence of grain size and composition on strain localization in the different mylonite bands. Two types of coaxial experiments were conducted at 650°C, and 1.2 GPa confining pressure: A) Discrete fractures were created before the shear deformation starts; B) No fractures were induced during an early stage of the experiment.

All experiments have in common that strain is accommodated in 20-100 µm wide viscous shear zones with elongated grains and minor grain size reduction. In these shear zones, most strain is further localized in 10-20 µm wide zones, showing dramatic grain size reduction down to few tens of nanometres. In the experimentally generated shear zones, both, brittle and viscous processes are active. In terms of overall rock strength, all newly formed ultrafine-grained shear zones are up to three times weaker than comparable experiments on pure quartz or coarser grained granites – which agrees well with field observations. Furthermore, pre-fractured type A) is up to two times weaker than the non-fractured type B), and the orientation and number of shear zones is also fundamentally different between the two experiment types.

This study confirms two weakening factors promoting different types of strain localization at the brittle to viscous transition: 1) The existence of fractures and their interconnectivity – facilitating highly-localized grain size reduction; 2) Initial sample heterogeneity by polymineralic composition and ultrafine grain size – generating grain size reduction along strain gradients by activating viscous processes. Further quantitative microstructural analyses will reveal the role of chemistry and the deformation mechanisms on the localization behaviour.
Advancing drought monitoring via feature extraction and multi-task learning algorithms
Authors: Giuliani Matteo , Bonetti Paolo , Metelli Alberto Maria , Restelli Marcello , Castelletti Andrea
Published: March 2022

A drought is a slowly developing natural phenomenon that can occur in all climatic zones and can be defined as a temporary but significant decrease in water availability. Over the past three decades, the cost of droughts in Europe amounted to over 100 billion euros, with the recent summer droughts being unprecedented in the last 2,000 years. Although drought monitoring and management are extensively studied in the literature, capturing the evolution of drought dynamics, and associated impacts across different temporal and spatial scales remains a critical, unsolved challenge.

In this work, we contribute with a Machine Learning procedure named FRIDA (FRamework for Index-based Drought Analysis) for the identification of impact-based drought indexes. FRIDA is a fully automated data-driven approach that relies on advanced feature extraction algorithms to identify relevant drought drivers from a pool of candidate hydro-meteorological predictors. The selected predictors are then combined into an index representing a surrogate of the drought conditions in the considered area, including either observed or simulated water deficits or remotely sensed information on crop status. Notably, FRIDA leverages multi-task learning algorithms to upscale the analysis over a large region where drought impacts might depend on diverse but potentially correlated drivers. FRIDA captures the heterogeneous features of the different sub-regions while efficiently using all available data and exploiting the commonalities across sub-regions. In this way, the accuracy of the resulting prediction benefits from a reduced uncertainty compared to training separate models for each sub-region. Several real-world examples will be used to provide a synthesis of recent applications of FRIDA in case studies featuring diverse hydroclimatic conditions and variable levels of data availability.
Future changes in circulation types in the SMHI Large Ensemble
Authors: Wyser Klaus , Hansen Felicitas , Belusic Danijel , Koenigk Torben
Published: March 2022

Recently SMHI has completed and published 50-member ensembles for each of the Tier-1 and Tier-2 future scenarios of ScenarioMIP, using the EC-Earth3 model (SMHI-LENS, Wyser et al. 2021). Monthly and daily output from these simulations are freely available on the ESGF and can serve as a base for assessing the uncertainty of climate projections in a single model, changes in the likelihood, magnitude and duration of extremes, changes in the probability for passing tipping points, or changes in the frequency of occurrence of compound events. To our knowledge SMHI-LENS is the only single-model large ensemble that includes all ScenarioMIP scenarios.

As an application of SMHI-LENS we present results from an evaluation of changes in large-scale circulation types (CTs) over the Scandinavian domain between the present climate and two future periods in the different scenarios. For the classification in 10 CTs we are using the Simulated Annealing and Diversified Randomization (SANDRA) method applied to daily sea level pressure fields where the spatial means have been removed (Hansen and Belusic 2021). Most of the 10 CTs occur predominantly in a specific season and can hence be referred to as summer or winter CTs. We find that the frequency of the CTs does not change significantly towards the middle of the 21st century, but that most significant CT frequency changes happen towards the end of the century during summer. The magnitude of the frequency changes is found to be proportional to the warming in the different scenarios. Our results further suggest that the distinction between summer and winter season in terms of CTs becomes more pronounced in the future climate.

Each CT has its specific effect on other variables such as temperature and precipitation, meaning that a specific CT can, for example, be associated with lower-than-normal temperatures or less-than-normal precipitation. In our study, we also investigate how this effect changes in the different future scenarios. For both temperature and precipitation, the spatial extent of the effect change is considerably larger at the end of the century compared to the change at the mid-century, but the average magnitude of the change is similar in both periods. For temperature, the effect change is strongest in the winter half-year for almost all of the 10 CTs.

Ref: Hansen, F. and D. Belušić. "Tailoring circulation type classification outcomes." International Journal of Climatology (2021).
Spatio-temporal velocity variations observed during the pre-eruptive episode of La Palma eruption inferred from ambient noise interferometry
Authors: Cabrera Pérez Iván , D'Auria Luca , Soubestre Jean , Przeor Monika , Koulakov Ivan , Martínez van Dorth David , Ibáñez Jesús M. , Ortega Víctor , Barrancos José , Padilla Germán D. , García-Hernández Rubén , Pérez Nemesio
Published: March 2022

On September 19th, 2021, a volcanic eruption began on La Palma, resulting in a significant social, economic and scientific impact. Earthquakes were first recorded in 2017, however, the pre-eruptive unrest started on Sept. 11st, 2021, only a few days before the eruption. It was characterized by a seismic sequence with hypocenters located at a depth of less than 10 km and ground deformation that reached more than 20 cm in the vertical component of the GPS. Surprisingly, this episode was very short, however, given the large amount of scientific instrumentation (seismometers, GPS, etc.) operated by the Instituto Volcanológico de Canarias (INVOLCAN) and other scientific institutions, the entire pre-eruptive episode has been accurately monitored, and the civil protection authorities were notified about the development of the volcanic unrest in advance. One of the techniques that have shown great potential in volcanic monitoring is ambient noise interferometry. This method consists in estimating the relative velocity variations using empirical Green’s functions retrieved through the cross-correlations of ambient noise signals. In this study, we applied this technique to the data recorded by six broadband seismic stations that allowed us to estimate spatio-temporal relative velocity variation during the week preceding the eruption.

The overall pattern of the pre-eruptive seismicity shows a progressive westward and upward migration of the hypocenters. However, five days before the eruption, we observed the occurrence of shallow (< 5 km) low magnitude earthquakes, whose hypocenters were detached from the main seismic cluster. At the same time, seismic interferometry detected a decrease in the seismic velocity in the region where such hypocenters were located. Therefore, we interpret those earthquakes as the effect of triggering caused by hydrothermal fluids released by the ascending magma and reaching shallow depths faster than magma.

Furthermore, a couple of days before the eruption, an even more significant reduction in relative velocity variation was observed, possibly corresponding to the rapid magmatic upward intrusion process, which led to the volcanic eruption.
Erosion monitoring with terrestrial laser scanning in representative biancane badlands of Central and Southern Italy
Authors: Vergari Francesca , Marsico Antonella , Capolongo Domenico , Del Monte Maurizio
Published: March 2022

This study aims to assess erosion dynamics in two Italian biancane badland sites, by means of  Terrestrial Laser Scanner (TLS), with high spatial resolution multitemporal surveys. The study sites are located in Tuscany and in Basilicata regions and are representative of the Mediterranean badland landscape. The former is a biancana subhumid badland hillslope of the Upper Orcia Valley, while the latter is a semiarid biancana landscape located in the tectonically active area of Aliano. The multitemporal survey and the morphometric analysis of the derived high resolution digital elevation models allowed to quantify the short- to medium-term erosion rates (5-10 years) affecting these landforms and to identify the main denudation processes responsible of the morphoevolution.

The results showed a very high erosion rate at both biancane sites, where it reaches, on average, 1.4 cm y-1 in Basilicata and 2.7 cm y-1 in Tuscany. The differences could be attributed to the dissimilar climatic conditions of the two sites:  Radicofani is affected by higher annual average rainfall, mainly due to a second peak (in addition to the autumn one) that occurs in spring, that is also reflected in enhanced mass movement events that model the subhumid biancane together with water erosion;  Aliano site is characterized by lower annual rainfall, mainly concentrated in late autumn-early winter, followed by long dry periods that also affect the erosion processes.

TLS is the ideal method to quantify denudation and erosion dynamics in biancane badlands since it allows very precise and detailed morphology detection. Furthermore the obstacles due to time-consuming and labor-intensive surveys, together with the shadowing effects, can be easily overcome because biancane generally origin in gentle dipping slopes, thus effortlessly accessible areas, where vegetation is often sparse as a result of ancient anthropic deforestation practices or climatic conditions in more arid badlands.
The use of Non-Linear Geometry (NLGEOM) and gravity loading in flat and spherical Finite Element models of Abaqus for Glacial Isostatic Adjustment (GIA)
Authors: Reusen Jesse , Huang Pingping , Steffen Rebekka , Steffen Holger , van Calcar Caroline , Root Bart , van der Wal Wouter
Published: March 2022

In geodynamic studies, most Finite-Element (FE) models in the commercial FE software Abaqus use elastic foundations at internal boundaries. This method works well for incompressible and so-called material-compressible material parameters but it is unclear if it works sufficiently well for implementing compressibility, especially in a 3D spherical model. The latter is of importance in investigations of glacial isostatic adjustment (GIA). A possible alternative method is based on a combination of explicit gravity loading with non-linear geometry (NLGEOM parameter in Abaqus) (Hampel et al., 2019). This method would remove the need to make a stress transformation to get the correct GIA stresses, and automatically accounts for the change in internal buoyancy forces that arises when allowing for compression, according to the Abaqus Documentation. We compared the method for (in)compressible flat (~half-space) FE models with existing numerical half-space and spherical (in)compressible codes and tested the applicability of this method in a spherical FE model. We confirm that this method works for multi-layer incompressible flat FE models. We furthermore notice that horizontal displacement rates of incompressible flat FE models match those of spherical incompressible GIA models below the current GNSS (Global Navigation Satellite System) measurement accuracy of 0.2-0.3 mm/a, but only for ice sheets that are smaller than 450 km in extent. For compressible models, disagreements in the vertical displacement rates are found between the flat NLGEOM model and the compressible Normal Mode code ICEAGE (Kaufmann, 2004). An extension of the NLGEOM-gravity method to a spherical FE model, where gravity must be implemented in the form of body forces combined with initial stress, leads to a divergence of the solution when viscous behaviour is turned on. We thus conclude that the applicability of the NLGEOM method is so far limited to flat FE models, and in GIA investigations for flat models the applicability further depends on the size of the load (ice sheet, glacier).

References:

Hampel, A., Lüke, J., Krause, T., & Hetzel, R., 2019. Finite-element modelling of glacial isostatic ad-
justment (GIA): Use of elastic foundations at material boundaries versus the geometrically non-linear
formulation, Computers & geosciences, 122, 1–14.

Kaufmann, G. (2004). Program Package ICEAGE, Version 2004. Manuscript. Institut für Geophysik der Universität Göttingen.
Distributed databases for citizen science
Authors: Malard-Adam Julien , Harms Joel , Medema Wietske
Published: March 2022

Citizen science is often heavily dependent on software tools that allow members of the general population to collect, view and submit environmental data to a common database. While several such software platforms exist, these often require expert knowledge to set up and maintain, and server and data hosting costs can become quite costly in the long term, especially if a project is successful in attracting many users and data submissions. In the context of time-limited project funding, these limitations can pose serious obstacles to the long-term sustainability of citizen science projects as well as their ownership by the community.

One the other hand, distributed database systems (such as Qri and Constellation) dispense with the need for a centralised server and instead rely on the devices (smartphone or computer) of the users themselves to store and transmit community-generated data. This new approach leads to the counterintuitive result that distributed systems, contrarily to centralised ones, become more robust and offer better availability and response times as the size of the user pool grows. In addition, since data is stored by users’ own devices, distributed systems offer interesting potential for strengthening communities’ ownership over their own environmental data (data sovereignty). This presentation will discuss the potential of distributed database systems to address the current technological limitations of centralised systems for open data and citizen science-led data collection efforts and will give examples of use cases with currently available distributed database software platforms.
Regional Mapping of Peatland Boundaries using Airborne Radiometric Data and Supervised Machine Learning
Authors: O Leary David , Daly Eve , Brown Colin
Published: March 2022

Peatlands are recognized as important carbon sequestration centres. Through restoration projects of peatlands in which the water table is raised, they may become carbon neutral or possibly carbon negative. National restoration plans require a knowledge of peatland extent and spatial distribution across large geographic areas.

Recently the availability of large geo-spatial datasets has increased. These range from soil, quaternary, and geology maps to airborne geophysical and satellite remote sensing data. Combining such datasets may provide a means to spatially map peatland extents and boundaries traditionally mapped via in-situ measurements. However, such datasets, and the relationship between them, are often complex. Modern Machine Learning methods can play a role in combining and analysing such multi-variate data within the discipline of Digital Soil Mapping.

Current peatland maps are created using combination of optical satellite remote sensing and legacy soil/quaternary maps. Optical remote sensing cannot detect peatlands under landcover such as forest or grassland. Legacy maps are often created from sparse in-situ augur, borehole, or trial pit data. These types of measurements do not allow for accurate measurement of boundaries or intra-peat variation.

Modern airborne geophysical datasets offer a potential means to update national and local scale peatlands maps. Radiometrics, a geophysical method that measures radiation emitted from geological materials, is particularly suited to peatland studies. Peat is a mostly organic material and so is, generally, not a source of radiation. Peat is also very saturated and water acts to scatter the emitted gamma rays. These effects combined means that peatlands act as a blanket to any source of radiation from below and show as “low” radiometric signal in the landscape.

This study aims to use Airborne Radiometric data combined with modern machine learning classification techniques to examine the current spatial distribution a peatland database in the west of Ireland. The Quaternary Geology database currently maps peatland extent where peat thickness is greater than 1m at the surface and was created using traditional mapping techniques. The methodology shows that a direct measurement, such as radiometric data, analysed in a supervised machine learning framework, provides more accurate and justifiable estimates of peatland extent in this region.
Possible bias in the assessment of karst hydrological model performance. Example of alpha and beta parameters compensation when using the KGE as performance criterion.
Authors: Cinkus Guillaume , Mazzilli Naomi , Jourde Hervé , Wunsch Andreas , Liesch Tanja , Goldscheider Nico , Ravbar Nataša , Fernández-Ortega Jaime , Barberá Juan Antonio , Andreo Bartolomé , Chen Zhao
Published: March 2022

Performance criteria such as the mean squared error (MSE), the Nash-Sutcliffe efficiency (NSE) and the Kling-Glupta efficiency (KGE) are extensively used to calibrate hydrological models. In recent years, numerous authors have stressed the inherent limitations of squared-error based criteria such as MSE and NSE. As a result, KGE criterion is gaining in popularity and is being widely used for calibration and for assessment. KGE has been initially proposed to address the poor consideration of discharge variability by NSE, but it also helps to lower the impact of squared errors in highly variable time series. KGE is a combination of (i) the Pearson correlation coefficient (r), (ii) the ratio between simulated and observed means (β), and (iii) the ratio between simulated and observed variances (α). In this study, we used KGE to compare the performance of two karst hydrological models (ANN and LP) over different flow regimes (dry, intermediate, wet) of two karst springs. The considered karst systems exhibit high contrasts in geometrical and hydrodynamic properties, inducing a high variability of the discharge at the springs. The discharge time series were divided into three sub-time series (dry, intermediate, and wet flows) according to fixed thresholds of discharge values. KGE values were higher for LP model for each sub-time series of both karst systems, thus indicating a better performance of LP over ANN at dry, intermediate and wet flows. However, KGE of the whole discharge time series were higher for ANN model, thus indicating a better overall performance of ANN over LP. The analysis of the decomposition of KGE (r, β, α) alongside a visual assessment of the simulated discharges of both models revealed that a compensation bias may be induced by β and α parameters. Simultaneous and equal overestimations and underestimations of multiple parts of the discharge time series seem to favour β and α values, leading to an overall better KGE coefficient without being associated to an increased model relevance.
Regional nearshore wave height prediction using a mixed-data CNN-LSTM neural network and dynamic bathymetric maps for the East Frisian North Sea
Authors: Jörges Christoph , Stumpe Britta
Published: March 2022

Rising sea levels and a potential increase in intensity and frequency of storm events due to climate change are increasingly intensifying flood risks caused by storm surges in the coastal areas of the North Sea. The ebb tidal delta (ETD) sandbanks off the coast of the East Frisian Islands change dynamically – a single storm surge may change them significantly – and, as a natural barrier, exert a huge impact on the nearshore wave climate.
Therefore, accurate predictions of storm surge wave heights are of particular interest and essential for coastal protection. Typically, these predictions are made by time-consuming numerical models like the third-generation wave model SWAN. Therefore, we designed a machine learning method that reasonably accelerates these simulations and wave height predictions and, for the first time, takes the ETD dynamics into account. To train the model, we created a dataset by driving an unstructured grid SWAN model with in-situ measurements of wave heights (also used for model validation), water level, and wind as boundary conditions. A dynamic bathymetric input was used by simulating various potential ETD bathymetries with geostatistical variogram analysis and random field simulation. Our proposed method is a mixed-data CNN-LSTM neural network for wave height prediction. While CNN neural networks are designed for processing image data (spatial bathymetric maps), LSTM units are optimized for processing long-term time series data. The model is capable of predicting nearshore wave heights after training with the SWAN-generated events and multiple simulated bathymetries. While the SWAN model took about 60 days to simulate 6480 events, our proposed neural network improved the computational time for a single event by a factor of 100.
These results can be used to explore potential future sea states under the influence of climate change and their local impact on the East Frisian coast in no time, as well as to warn the inhabitants of the affected areas and to install location-specific e.g. sandbags and flood protection walls by using the latest water level and wind forecasts as input.
Long-term carbon transfers at the land-ocean interface: evidence from Loch Eriboll, northern Scotland
Authors: Hiles William , Smeaton Craig , Austin William
Published: March 2022

Globally, fjords are recognised as hotspots for the burial and storage of organic carbon (OC). The role of fjords as nationally and globally important carbon sinks is now well established, yet the long-term drivers and evolution of OC burial and storage in these coastal systems remains largely unknown. The location of fjords at the land-ocean interface in combination with their geomorphology results in a large proportion of the OC that is trapped in their sediments deriving from the terrestrial environment, yet the processes driving the delivery of terrestrial carbon into fjords over long timescales is often poorly constrained. In order to better understand these important processes, an understanding of terrestrial landscape change in conjunction with sedimentological data for carbon storage is required. Understanding the drivers of the carbon transfer at the land-ocean interface throughout the mid- to late-Holocene can provide insights into the sensitivity of catchments to climatic and anthropogenic pressure, which will be crucial to predicting future carbon loss, burial and storage scenarios across the land-ocean interface.

We present a new multiproxy palaeoenvironmental dataset developed from a core from Loch Eriboll, a large fjord in northern Scotland, spanning the last 5,000 years. Pollen data, taken to represent catchment-scale vegetation change, is used to investigate landscape change in response to natural and anthropogenic forcing mechanisms. Sedimentological and geochemical data are then used to reconstruct changes in the delivery of carbon into the fjord system via soil erosion. Comparison of two age models, developed from bulk radiocarbon dating and dating of shells, respectively, provide data on the relative age of carbon being reworked from the terrestrial system into the fjord.

We present evidence for links between the terrestrial and fjord systems throughout the mid to late Holocene. Throughout the record is a consistent radiocarbon age offset of approximately 800 years in the bulk data, and increases in this offset coincide with marked changes in the terrestrial vegetation on three discrete occasions: a significant reduction in Pinus, an increase in herbaceous pollen, and an expansion of heathland pollen. Complemented by a suite of geochemical proxies, including inorganic and organic geochemical signatures, these datasets provide insights into the sensitivity of fjordic systems to changes in the adjacent terrestrial system on centennial timescales.
The nature of seismicity in a complex volcanic rift setting
Authors: Reiss Miriam Christina , Muirhead James , Laizer Amani , Kazimoto Emmanuel , Ebinger Cynthia , Link Frederik , Rümpker Georg
Published: March 2022

Deciphering the nature of seismicity in regions of active magmatic and tectonic areas is critical when examining the interplay between faulting, magmatism and magmatic fluids. Here, we present a rich seismic data set from a 15-month temporary network from the Natron basin of the East African Rift System, which provides an ideal location to study these processes owing to its recent magmatic-tectonic activity and ongoing active carbonatite volcanism at Oldoinyo Lengai. We report seismicity, seismic swarms and their fault plane solutions which we use to constrain the complex volcanic plumbing system and long-term tectonic processes.

Between March 2019 and May 2020, we locate ~10 000 earthquakes with ML -0.85 to 3.6. These are related to ongoing magmatic and volcanic activity in the region, as well as regional tectonic extension. We observe seismicity down to ~17 km depth north and south of Oldoinyo Lengai and shallow seismicity (3 - 10 km) beneath the inactive shield volcano Gelai, including two likely fluid driven swarms. The deepest seismicity (down to ~20 km) occurs above a previously imaged magma body below Naibor Soito volcanic field. These seismicity patterns reveal a detailed image of a complex volcanic plumbing system, supporting potential lateral and vertical connections between shallow- and deep-seated magmas, where fluid and melt transport to the surface is facilitated by intrusion of dikes and sills.

Focal mechanisms vary spatially and are a strong indicator for differences between magmatic and tectonic forces. T-axis trends reveal dominantly WNW-ESE extension near Gelai, while strike-slip mechanisms and a radial trend in P-axes are observed in the vicinity of Oldoinyo Lengai. These observations support local variations in the state of stress, resulting from a combination of volcanic edifice loading and magma-driven stress changes imposed on a regional extensional stress field. Our results indicate that the southern Natron basin is a segmented rift system, in which fluids preferentially percolate vertically and laterally in a region where strain transfers from a border fault to a developing magmatic rift segment.
Dust storms as a means of transport for microplastics in the atmosphere 
Authors: Rezaei Mahrooz , Abbasi Sajjad , Ahmadi Farnaz , Turner Andrew
Published: March 2022

Airborne microplastic is a new area of research in the microplastic domain. Recently, microplastic presence was reported in areas remote from any urban, industrial, and agricultural sources. This reveals the role of the atmosphere in the transport and dispersion of microplastics. Dust storms can shift significant quantities of soil particles and associated microplastics, especially in arid and semi-arid regions. This study reports the presence, characteristics, and potential sources of microplastics in a severe dust storm in Shiraz, southern Iran, in May 2018. Using the method adopted by Bergmann et al. (2019), 22 dust samples were collected from parked cars directly after the event. Dust samples were analyzed for microplastic using the density extraction method and Raman Spectroscopy. The hybrid Lagrangian and Eulerian model of HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) was used for back trajectory analysis in order to determine the origin of air masses.

Results showed that MP concentrations ranged from 0.04 to 1.06 particles per g of dust. In total, 485 microplastics were detected in all dust samples. The main shape of microplastics was fibrous and polymer makeup was dominated by nylon, polypropylene, and polyethylene terephthalate. Scanning Electron Microscope (SEM) images revealed different degrees of weathering in microplastics. Results of modeling together with the geochemical evidence suggested that the Arabian Peninsula constitutes the principal distal and transboundary source. Results also estimated that about 2 * 1012 microplastics could be transported by such a dust event. According to the literature on MP concentrations in urban dust and remote arid soils, it was estimated that between 0.1 and 5% of MPs in the dust samples were originated from local sources, and the remainder arose from more distant sources. The outcome of this study is proving the atmospheric transport of microplastic far beyond its sources and a potential pathway for microplastics to the oceans and land through dust storm events.
High-resolution projections of extreme sea level changes along the coasts of western Europe
Authors: Chaigneau Alisée , Melet Angélique , Law-Chune Stéphane , Voldoire Aurore , Reffray Guillaume , Aouf Lotfi
Published: March 2022

Extreme sea levels (ESLs) are a major threat for coastal and low-lying regions. Climate change induced sea level (SL) rise will increase the frequency of ESLs. Projections of ESLs are thus of great interest for coastal risk assessment and decision-making. SL projections are typically produced using global climate models (GCMs). However, GCMs do not explicitly resolve key processes driving ESL changes at the coast (e.g. waves, tides). In this study, a regional model IBI-CCS is set up to refine SL projections of a GCM over the north-eastern Atlantic region bordering western Europe using dynamical downscaling. For a more complete representation of processes driving coastal ESL changes, tides and atmospheric surface pressure forcing are explicitly resolved in IBI-CCS in addition to the ocean general circulation. Furthermore, to include the wave setup contribution to ESLs, a dynamical downscaling of a wave global model is performed over the same north-eastern Atlantic domain using the currents and sea level outputs of the IBI-CCS regional ocean model. All the regional simulations are performed over the 1950 to 2100 period for two climate change scenarios (SSP1-2.6 and SSP5-8.5).

Comparisons to reanalyses and observations over the 1993-2014 indicate that ESLs are satisfactorily represented in the regional simulations. In a second phase, the projected changes in ESLs are analyzed, particularly in term of changes in return levels and return periods. The coupling effects between the key processes driving ESL changes at the coast are investigated. We notably assess the influence of the wave setup contribution to ESLs and to projected changes in ESLs and to their return periods. In addition, the impact of accounting for hourly sea level changes in the wave regional model on ESLs and projections of ESLs is estimated.
Mineralogical and chemical changes induced by experiments of interaction between supercritical CO2 and plutonic mafic rocks. A case study in Portugal.
Authors: Moita Patrícia , Berrezueta Edgar , Abdoulghafour Halidi , Beltrame Massimo , Mirão José , Ribeiro Carlos , Barrulas Pedro , Pedro Jorge , Carneiro Júlio
Published: March 2022

The focus of this research is a qualitative study of mineralogical and chemical changes in plutonic mafic rock samples after exposure to a CO2-rich brine, under supercritical conditions (SC), to clarify the behavior of brine and rock in the initial stages of mineral carbonation. The studied rock consists of a gabbro-anorthosite from the Odivelas massif, in southern Portugal. The sample was exposed to a SC CO2-rich brine (P≈8 MPa, T≈40◦C) for runs of 0, 30 and 90 days. Experiments were conducted in batch mode, ie. with no CO2 flow, and with a proportion of CO2 to brine of 0.226 for 30 days and 0.033 for 90 days. In addition, numerical modeling was applied to complement the experimental observations, reproducing the experimental observations and simulate the chemical behavior for longer times. The chemical analysis of the brine, before and after, the experiment, shows: (i) increase of magnesium (Mg2+), calcium (Ca2+) and silica (SiO2) for the 30 and 90 days runs and (ii) decrease of pH (8.1 to 6.1 and 8.1 to 6.3, respectively). Experimental and numerical results indicate that the rock sample suffered a slight dissolution process with mineralogical/textural readjustments on the external area of the specimens studied. This is thought to mimic the initial dissolution process under early-stage mineral carbonation. After 90 days, apart from halite, there are no significant new mineral phases. However, the elemental association in the EDS maps of carbon and magnesium dissociated from silicon suggests the residual crystallization of magnesite.

 
Mercury Life Cycle in the Dental Office
Authors: Purves William
Published: March 2022

Amalgam is the primary source of mercury entering the aqueous environment. According to the US EPA 46% of the total mercury entering the environment.  The US EPA has established a regulatory category for dental discharge (40 CFR 441). It focuses on amalgam separators and ISO 11143 standard as the primary process for amalgam removal as a solid.  The ISO standard does not address the more serious issue of dissolved mercury.

Amalgam dissolves slowly in the separator generating soluble mercury levels up to part per million concentrations which are difficult to remove.  This process defeats the purpose of the separator. The US regulation is seriously flawed as it does not address this issue by establishing a total mercury discharge limit or allow innovation to develop to reduce total mercury by allowing Best Available Technology.

Removal of amalgam from the dental waste stream can be done as a pretreatment process at the dental chair.  All dental chairs have a feature called a chair side trap.  This trap is designed to capture large particles to protect the vacuum system lines from clogging.  A proper trap design can be the most effective pretreatment step in the overall amalgam removal process and mercury reduction.

The new chair side trap design removes up to 99% of the amalgam solids at the chair as compared to <5% with current traps.  This trap simply replaces the old design and requires no change in dental office operation or equipment.  Removal of amalgam solids before the separator effectively reduces the concentration of both solid and dissolved mercury entering the environment.  The trap along with an activated carbon style separator have seen reductions of as much as 99.9%.  This paper addresses the problem and provides real time data proving the effectiveness of the system.