bluuebunny/crossref_metadata_2025 huggingface dataset:
Arctic lightning and anthropogenic NOx emissions estimated from TROPOMI observations
Authors: Zhang Xin , Yin Yan , van der A Ronald , Ding Jieying , Eskes Henk , van Geffen Jos , Vagasky Chris , Lapierre Jeff
Published: March 2022

The Arctic is experiencing rapid climate change. The increasing temperature not only reduces the sea-ice extent but will also have doubled the number of lightning flashes by the end of the century. The unlocked Arctic ocean can also lead to increased human activities such as shipping and expanded oil and gas production. In addition, the increase of lightning will cause more wildfires. All of these above will give rise to emissions of nitrogen oxides (NOx).

In this study, we track and estimate three-year (2019-2021) Arctic NOx emissions by combing the TROPOspheric Monitoring Instrument (TROPOMI) observations, Visible Infrared Imaging Radiometer Suite (VIIRS) data, and the Vaisala’s Global Lightning Dataset (GLD360). The NOx emissions are divided into two different categories and estimated separately: 1) NOx emissions from lighting; 2) surface NOx emissions from all other sources.

The continuous overlapping orbits of TROPOMI passing over the Arctic provide unique opportunities for tracking the lightning NOx (LNOx) and calculating both LNOx lifetime and production efficiency. Previous studies focused on the LNOx emissions in the tropical and mid-latitude regions and estimated the global LNOx within the range of 2 to 8 T N yr-1. This study can add the missing LNOx productions in high latitudes.

Besides, a Cloud-Snow Differentiation (CSD) method is applied to get more high-precision TROPOMI observations over large boreal snow-covered areas by discriminating snow-covered surfaces from clouds. The derived NOx emissions from power plants, natural gas industries, and soil will play an important role in updating the present-day NOx inventories which have a limited number of data sets. This study highlights the potential of TROPOMI as well as future satellite missions for monitoring Arctic NOx emissions.
Monitoring the stability of leaky dams and their influence on debris transport with innovative sensor technology on the SENSUM project
Authors: Egedusevic Martina , Bennett Georgina , Roskilly Kyle , Sgarabotto Alessandro , Manzella Irene , Raby Alison , Boulton Sarah J. , Clark Miles , Curtis Robin , Panici Diego , Brazier Richard E
Published: March 2022

Woody debris dams/leaky dams are an increasingly popular Natural Flood Management (NFM) measure in low order tributaries, with preliminary evidence suggesting that they are effective in attenuating flood peaks and reducing flood risk. However, the stability of these dams is not widely monitored, and thus there is a poor evidence base for best design practice with respect to the long-term integrity of such features. This is particularly pertinent given the threat posed to downstream infrastructure by woody debris carried in floodwaters after potentially catastrophic dam failure. There is also a lack of research into how effective dams of different designs are at holding back large wood and sediment transported by the flow and reducing the impact of flood debris on downstream infrastructure, including bridges, culverts etc. In the SENSUM project (Smart SENSing of landscapes Undergoing hazardous hydrogeomorphic Movement, https://sensum.ac.uk), we are developing and applying innovative sensor technology to assess the stability of different woody debris dam designs and build an evidence base to inform policy on this NFM practice locally and nationally. We also use these sensors to track woody debris and assess how effective dams are at trapping and retaining large wood debris and cobble-sized sediment. This paper addresses these questions at several field sites across the UK and in laboratory experiments to report quantitative data which evaluate the literal success/failure of NFM interventions and how these may impact the future design of such approaches.
The potential of adaptive drainage to control salinization in Polder context 
Authors: Mehmandoost Kotlar Ali , Everaer Bert , Blanchy Guillaume , Huits Dominique , Garré Sarah
Published: March 2022

The past dry summers of 2018, 2019 and 2020 have indicated the sensitivity of Flemish agriculture to drought. In the Flemish polders, this resulted not only in crop water stress, but also in increasing soil and water salinity levels due to the high evaporative demand and the occurrence of salt water lenses in the subsurface. Due to the increasing occurrence of weather extremes as a consequence of climate change, farmers will need to deal with both too little and too much freshwater in the future. Compared to conventional drainage systems, adaptive drainage can secure food production and lower the irrigation need by only draining water when it is strictly necessary and thereby leaving more opportunities for water retention and groundwater recharge.  

In the project OP-PEIL, we will investigate the impact of adaptive drainage on water fluxes and availability, water quality as well as on the cropping system itself (crop growth, disease pressure, yield and quality) during 3 years. We will use geophysical techniques to monitor the impact of adaptive drainage on the fresh/salt water interface in the drained field, as well as in the nearby landscape. Finally, we will set up numerical experiments using water balance models (e.g. SWAP- WOFOST and DRAINMOD) and the available historical climate, field management, and soil hydraulic properties data will be performed to evaluate more extensive climatological scenarios. By the end, this four-year project will raise awareness of farmers and stakeholders about the impact of adaptive drainage on agricultural practices in the Flemish Polders in Belgium.  

 
Novel usage of remotely-sensed flood footprints in the re/insurance sector
Authors: Remondi Federica , Schenkel David , de Jong Rogier
Published: March 2022

Flooding has been consistently one of the most recurrent and costly natural catastrophes globally. Only in 2021 large flood events claimed more than 2 000 victims and caused over USD 75 billion of economic losses, of which a quarter was covered by the insurance sector.
Modelling floods and simulating their impact have proven to be particularly challenging in locations with fine-scale changes in elevation, complex terrains and man-made structures as is typical for dense urban centres.  By partnering with ICEYE, the largest commercial synthetic-aperture radar satellite operator, Swiss Re aims to advance flood risk modelling, assist disaster response and provide enhanced insights and new products to its clients. 

We present few applications for the re/insurance sector of the remotely acquired flood maps at high resolution and water depth estimations. Firstly, the flood footprints are provided to clients for assessing the event magnitude and enabling faster loss assessment and payouts. Secondly, they are used as input to flood catastrophe models to obtain a first loss estimation for reinsurance portfolios. Thirdly, new insurance products that rely on the remotely-sensed flood footprints to trigger a payout have been explored. These parametric flood insurances, even with their limitations, present relevant potential applications for cities, large regions and the agriculture sector.
Mobility and hazard analysis of selected landslides in Lower Austria 
Authors: Arango Maria Isabel , Lima Pedro , Mergili Martin , Glade Thomas
Published: March 2022

Landslide processes often cause great economic losses, infrastructure damage and numerous casualties in many mountains and hilly landscapes worldwide. Landslide processes are very diverse, and may be shallow or deep, slow, or fast, with translational or rotational movements, and can sometimes even have a compound nature, with a single event behaving in different ways along time or space. For example, under certain conditions, slow-moving landslides can increase their speed, becoming flows with a large mobility range and destructive energy.

Although the methods for creating landslide susceptibility and hazard maps are now well advanced, they often do not represent the diversity of the landslide processes. Moreover, they do not represent hazard to the different stages of land sliding sub-processes, like failure, movement, and deposition area. Even though these sub-processes are connected, the final outcome of a disastrous event can differ greatly according to the movement mechanisms and pre-event conditions. This way, reliable hazard maps for single landslides, that account for their changing behavior during motion, still faces significant challenges.

The core purpose of this research is to evaluate the mobility and hazard scenarios of three slow-moving landslides with varying extensions, depths, and topography. All the study areas are located in Lower Austria. The run-out of the landslides was estimated using r.avaflow, a physically based mass flow model. The depth and soil structure of the landslides has been previously investigated by geotechnical and geophysical analysis. Different scenarios were considered for the modelling, including different factors like landslide extent, soil depth, and assumed water saturation, that determines the flow velocity, extent, and viscosity and thus the spatial extent of the run-out. The temporal probability of failures was analyzed using a physically based slope stability model. Using rainfall, snow, and temperature records from nearby gauging stations in Lower Austria, each landslide event was linked to different triggering rainfall or snowmelt events, and the slope stability was evaluated in terms of their Safety Factor.

The output of the analysis is a set of different landslide run-out maps for each of the three study areas. These maps also include the temporal probabilities for each landslide, considering several extent and mobility scenarios. The results support the decision-making policies, including risk reduction measures, and the implementation of landslide early warning systems.
Landslides on the radar: detection, monitoring, and runout hazard forecasting
Authors: Lu Zhong , Xu Yuankun , Burgmann Roland , George David
Published: March 2022

Landslides annually cause thousands of casualties and billions of dollars in property loss. Mitigation of their hazards demands answers to three fundamental questions: where are the landslides, how are they evolving, and what damages would they cause upon a runout failure? Radar remote sensing, capable of capturing landslide deformation in near real-time, proves itself an effective and efficient tool to help address these challenges. Here, we highlight a workflow that incorporate SAR (Synthetic Aperture Radar)’s unique values to aid landslide detection, monitoring, and runout damage forecasting. By integrating field instrumentation and hydromechanical modeling, our recent studies over the U.S. West Coast substantiated SAR’s powerful capabilities: (1) Discovering approximately 600 destabilized, slow-moving landslides that were missing from the currently existing, non-systematically mapped landslide database of the United States; (2) Monitoring and characterizing spatiotemporal dynamics of landslides that destroy highways (e.g., the Hooskanaden landslide in southwestern Oregon), damage aquatic habitats (e.g., tens of irrigation-induced landslides in eastern Washington ), and endanger communities (e.g., the Cascade Locks landslide in southern Washington); (3) Constraining source volume to help predict runout hazard of landslides that threaten popular campgrounds (e.g., the Gold Basin landslide in central Washington) and urban communities (e.g., the Cape Meares landslide in northwestern Oregon). Adaptation of our methodology to assimilate SAR observations could prove useful for mitigating similar landslide hazards beyond the regional scale.
A graph-based fractality index to characterize complexity of urban form using deep graph convolutional neural networks
Authors: Ma Lei , Seipel Stefan , Brandt S. Anders , Ma Ding
Published: March 2022

Inspection of the complexity of urban morphology facilitates understanding of human behaviors in urban space, leading to better conditions for the sustainable design of future cities. Fractal indicators, such as fractal dimension, ht-index, and cumulative rate of growth (CRG) index, have been proposed as measures of such complexity. However, these major fractal indicators are statistical rather than spatial, which leads to failure of characterizing the spatial complexity of urban morphology, such as building footprints. To overcome this problem, in this paper a graph-based fractality index (GFI), based on a hybrid of fractal theories and deep learning techniques, is proposed. To quantify the spatial complexity, several fractal variants were synthesized to train a deep graph convolutional neural network. Building footprints of London were used to test the method and the results show that the proposed framework performs better than traditional indices. Moreover, the possibility of bridging fractal theories and deep learning techniques on complexity issues opens up new possibilities of data-driven GIScience.
Testing seismic velocity models with quarry blast data
Authors: Arroucau Pierre , Mayor Jessie , Grunberg Marc , Nayman Emmanuelle , Daniel Guillaume
Published: March 2022

Seismic event locations are usually performed by means of iterative, linearized arrival time inversion considering 1D velocity models with fixed data errors. Both the use of inaccurate velocity structure or data error estimates may however affect the quality of event location and uncertainty evaluation. Here, we test a 3D P- and S-wave velocity model built in a previous work for Metropolitan France (the part of France located in Europe) and we compare it with the “Auvergne” 1D velocity model used by BCSF-RéNaSS (Bureau Central Sismologique Français - Réseau National de Surveillance Sismique) using quarry blast data. The reason for using quarry blast data is that, to some extent, their epicentral location and depth are known, which is not the case for earthquakes. We first identify potential active quarries over the territory of Metropolitan France by comparing catalog quarry blast locations with those from quarries visible from satellite images. Relocation is achieved by means of a Hierarchical Bayesian inversion procedure in which not only the hypocentral parameters (longitude, latitude, depth, origin time) are inverted for, but also P- and S-wave arrival time errors. The area of interest is a 1° by 1° zone located between 4°E and 5°E in longitude and 44°N and 45°N in latitude, the region where the Le Teil earthquake occurred (Mw 4.9, 2019/11/11). We first demonstrate the ability of the algorithm to properly determine hypocentral parameters and data noise using two simple synthetic experiments. Then we apply it to real data and relocate 147 quarry blasts that occurred in the region between 1980 and 2020 and that were located wit the “Auvergne” 1D velocity model. Relocations obtained with the 1D and 3D model are rather similar. Estimated data errors are larger, in both cases, than the amplitude of picking uncertainties, meaning that both models could be improved, by seismic arrival time tomography for instance. They are larger in the 3D case, suggesting that, from that point of view, the 1D model is in better agreement with the data. Distances between relocated hypocenters and the closest known quarry are comparable but relocations with the 3D model are characterized by shallower hypocenters than those obtained with the 1D model, so they appear more consistent with the fact that events are quarry blasts. In both cases, some events are quite far away from the closest quarry, suggesting that some of them might be natural events.
Conditional normalizing flow for predicting the occurrence of rare extreme events on long time scales
Authors: Kruse Jakob , Ellerhoff Beatrice , Köthe Ullrich , Rehfeld Kira
Published: March 2022

The socio-economic impacts of rare extreme events, such as droughts, are one of the main ways in which climate affects humanity. A key challenge is to quantify the changing risk of once-in-a-decade or even once-in-a-century events under global warming, while leaning heavily on comparatively short observation spans. The predictive power of classical statistical methods from extreme value theory (EVT) often remains limited to uncorrelated events with short return periods. This is mainly due to their strong assumption of an underlying exponential family distribution of the variable in question. Standard EVT is therefore at odds with the rich and large-scale correlations found in various surface climate parameters such as local temperatures, as well as the more complex shape of empirical distributions. Here, we turn to recent developments in machine learning, namely to conditional normalizing flows, which are flexible neural networks for modeling highly-correlated unknown distributions. Given a short time series, we show how such networks can model the posterior probability of events whose return periods are much longer than the observation span. The necessary correlations and patterns can be extracted from a paired set of inputs, i.e. time series, and outputs, i.e. return periods. To evaluate this approach in a controlled setting, we generate synthetic training data by sampling temporally autoregressive processes with a non-trivial covariance structure. We compare the results to a baseline analysis using EVT. In this work, we focus on the prediction of return periods of rare statistical events. However, we expect the same potential for a wide range of statistical measures, such as the power spectrum and rate functions. Future work should also investigate its applicability to compound and spatially extended events, as well as changing conditions under warming scenarios.
Tephra layer formed in the 1996 eruption of Gjálp, Iceland
Authors: Jóngeirsdóttir Irma Gná , Gudmundsson Magnús Tumi , Larsen Gudrún
Published: March 2022

Gjálp is a hyaloclastite ridge situated beneath the western part of the ~8000 km2 Vatnajökull ice cap, located midway between the subglacial calderas of Grímsvötn and Bárdabunga volcanoes. The tephra erupted at Gjálp has affinities fitting with the Grímsvötn volcanic system while the associated seismicity and unrest preceding the eruption suggest that the eruption was caused by lateral magma flow from Bárdarbunga.  Eruptions occurred at Gjálp in 1938 and 1996 but only the 1996 eruption is thought to have broken through the ice. The 1996 eruption was first detected on the 30th of September at about 22:00 GMT by the onset of seismic tremor; the following day heavily crevassed ice cauldrons were noticed. Around 30 hours after detection of the tremor the eruption broke through the ice sheet. The eruption lasted for 13 days, during which a 6-7 km long subglacial, hyaloclastite ridge was formed. The subglacial eruption melted large volumes of ice that accumulated within the Grímsvötn caldera until early November, when it was released in a major jökulhlaup, destroying bridges and damaging roads. In comparison with the subglacial eruption the subaerial part was relatively modest. The style of activity was mostly Surtseyan and the tephra erupted is mildly intermediate in composition.

The tephra fall began on October 2 and continued intermittently until October 13. The first tephra was seen at 05:18 on October 2. By 08:50 the largest explosions threw tephra about 1 km above the ice surface and the plume rose to 4-4.5 km above sea level. This tephra was carried north and north-northeast across North and Central Iceland and was detected as far as 250 km from source. On October 3 the plume was reported to have reached 8-9 km a.s.l. Tephra was also dispersed to the east and south and most of the tephra accumulated on the Vatnajökull glacier. During the eruption, repeated snow fall caused layering within the tephra deposit. In the following year samples were collected from the tephra fall area on the glacier. These consist mostly of snow cores with tephra thickness ranging from dm to mm. The samples were processed to estimate the tephra volume and to create a dispersal and isopach map. The tephra layer deposited on the glacier is volumetrically only a few percent of the bulk volume (~0.7 km3) of the subglacial ridge formed in the 1996 eruption.
Satellite Signature of Phytoplankton in Ocean Fronts
Authors: Haëck Clément , Lévy Marina , Bopp Laurent
Published: March 2022

The contribution of sub-mesoscale fronts (10-100km) to phytoplankton growth and biodiversity is still poorly understood. It is expected that these fronts generate vertical ageostrophic secondary circulations, and thus act locally on stratification and vertical nutrient supply.
The response of phytoplankton to this input has been observed in-situ and in numerical models, but to a lesser extent by satellite imagery, which presents the opportunity to quantify results at larger spatiotemporal scales.
We improve an existing method to define sub-mesoscale frontal areas from satellite SST data in the North Atlantic. The study area is divided geographically into three zones: North of the Gulf-Stream jet, South of—and including—the jet, and further South part of the olligotrophic gyre.
For each zone the distribution of Chlorophyll-a values are estimated by satellite inside and outside these fronts. For all zones the Chlorophyll-a is found more concentrated in fronts, with differences between zones in magnitudes and seasonal cycles. The overall impact of fronts on the total Chlorophyll-a amount is quantified. We also quantify the temporal advance of the spring bloom onset in fronts. Finally, interannual trends over the last two decades are studied.
The representation of alkalinity and calcium carbonate cycling from CMIP5 to CMIP6 models and the potential influence on carbon cycle projections
Authors: Planchat Alban , Bopp Laurent , Kwiatkowski Lester
Published: March 2022

The ocean carbonate pump influences the vertical gradient in ocean carbon content alongside the soft tissue pump. However unlike the soft tissue pump, the production of calcium carbonate, its export and subsequent dissolution are also the primary drivers of the vertical gradient in ocean alkalinity. Often overlooked, alkalinity is a key conservative tracer in the ocean, critical to the uptake of atmospheric carbon in surface waters and the extent of associated acidification. Within the context of model projections of future ocean carbon uptake and potential ecosystem impacts, the representation of the calcium carbonate cycle and alkalinity are a persistent uncertainty. Here we present an assessment, conducted alongside the international ocean biogeochemistry modelling community, reviewing trends in the representation of the calcium carbonate cycle and the associated biogeochemical tracer alkalinity, in the Earth system models involved in CMIP5 and CMIP6. Model representation of calcium carbonate production, sinking, dissolution and sedimentation is highly diverse. No model represents benthic calcification, and none of the CMIP5 and CMIP6 models have an explicit representation of pelagic planktonic calcifiers. Implicit pelagic calcification schemes are highly variable, with models typically representing calcite and not aragonite. In contrast, the representation of CaCO3 sinking and dissolution can be either implicit or explicit and variably includes sensitivity to the local seawater saturation state. Between CMIP5 and CMIP6 there is a clear improvement in the representation of both surface ocean alkalinity and its vertical gradient when compared to observations. This appears to be driven by an increase in the export of calcium carbonate in the CMIP6 ensemble however it is difficult to attribute this increase to specific model developments. Ongoing work is focussing on how the improved representation of ocean alkalinity in CMIP6 may affect model representation of the ocean CO2 system and projections of future ocean carbon uptake.
Mn-rich Black Patina Formation on Built Heritage in Humid Areas
Authors: Freire-Lista David Martin , Blanco-Rotea Rebeca , Costa Maria do Rosário , Sanjurjo-Sánchez Jorge
Published: March 2022

This study aims to characterise the decay due to black patinas of Santalla de Bóveda Monument (Lugo, Northwest of Galicia, Spain).

Manganese is one of the most abundant elements on Earth, and the granite on which Santalla de Bóveda Monument was built (used as building material of the monument) has considerable amounts of Manganese. This monument shows black patinas on the surface of its building materials (mortars and granites).

Mortars and granite with Mn-rich black patinas were analysed in their chemical, mineralogical and petrographical properties (polarizing and scanning electron microscopes, X-ray diffraction and X-ray fluorescence). In addition, the water from springs near the monument was analysed.

According to the experimental study results, it was observed that rich Mn-oxide crusts are presumably induced by bacteria. That is, the oxidation of Mn fuels the growth of chemolithoautotrophic microorganisms, which need water to live. These patinas of biogenic Mn-oxide minerals presented different shapes, nano-dimensions, with low degree of crystallinity, and appear to be composed of manganese oxides such as birnessite, ramsdellite and groutellite. They were associated with large amounts of extracellular polymeric substances exuded by filamentous bacterial communities, which serve as nuclei for preferential precipitation of manganese oxides on the extracellular sheaths, as seen in scanning electron microscope analyses.

Mn required for patina formation likely derives from the reductive dissolution in water of Mn-rich minerals, as suggested by the mineralogy and chemistry of Mn-rich phases present in the building granite and mortars. Mn migrates to the exposed surface of building materials, where they are re-oxidized via biological processes. Patinas developing over time result from the alternation of wetting-reducing and drying-oxidizing cycles.

Water absorption, dampness and black patinas are among the most common and critical problems when it comes to decay of both cultural heritage and modern buildings. The climate and specifically the humidity are determinant for the development of Mn-rich black patinas. Results revealed that chemical composition and porosity played a major role in the development of biological activity that generates the black patinas of manganese oxides on mortars and granite.
Global patterns in testate amoebae diversity
Authors: Krashevska Valentyna ,   co-authors
Published: March 2022

Testate amoebae are a common group of shelled amoeboid protists that are widespread in terrestrial systems. They play a key role in microbial foodwebs and are useful bioindicators of present and past conditions due to their long-lasting shells. However, their diversity and distribution has not yet been investigated and visualised at a global scale. With extensive data collection effort involving the global testate amoebae community, we compiled data on testate amoebae from 10,889 locations worldwide: 9235 terrestrial, 1322 freshwater and 219 marine-interstitial sites. In terrestrial systems, 1187 species were recorded. The highest total number of species was documented on the continent of Asia (699 species) and the lowers in Antarctica (151 species). Preliminary analyses of terrestrial samples showed negative correlation of species number with increasing absolute latitude, peaking at low-mid latitudes. However, longitude also played a significant role in species distribution. The most studied continent is Europe (42 % of all samples) and the least studied is Africa (2 %). The data we have collected are the basis for identifying the fundamental ecological determinants of diversity and species composition of testate amoebae and for understanding patterns in microbial diversity. We will show the recent findings of this ongoing endeavour.
Impact of data time resolution in long term baseflow index assessment from mass balance filtering
Authors: Khasanova Leisan , Longobardi Antonia , Khasanov Ilmir , Elizaryev Alexey
Published: March 2022

Key words: Mass balance filtering, baseflow, BFI, time-resolution, electrical conductivity, permeability

Baseflow plays an important role in sustaining freshwaters quality and quantity at the global scale. Quantitative estimates of baseflow are necessary but no direct observations are available to the purpose, thus hydrograph filtering appears as a valid solution to quantify the baseflow process. The mass balance filter (MBF), based on electrical conductivity (EC) observations, is one of the most objective filtering techniques.

The aim of the present study is to analyze the impact of data time resolution in the assessment of the long-term scale baseflow index (BFI, the ratio between baseflow and total flow) by hydrograph filtering. The MBF method was used to estimate the long-term BFI of 64 catchments across Continental United States ranging from about 5 to 50000 Kmq, from arid to continental climate conditions and accounting for 5 to 10 years of continuous observations. Streamflow and EC data were collected from the United States Geological Survey (USGS) National Water Information System website at the 15 minutes time resolution and aggregated at the daily scale. BFI15, the BFI computed at the 15 min time resolution, was compared with BFI24, that is with the BFI computed at the daily scale. The difference among the two indices was investigated in relation to catchment climate and physiographic characteristics.

The large dataset was divided into two groups, a poorly-drained group and a well-drained group on the base of the catchment permeability assessed by the GLobal HYdrogeology MaPS (GLHYMPS) project. The first group corresponds to BFI values < 0.5, the second to BFI values > 0.5. Overall the BFI15 was found to be larger than BFI24, with an average difference of about 7%, probably caused by the fact that at finer time scale a wider spectra of streamflow processes and components can be detected, more evidently during the peak flow conditions. The average difference drops to 1% in the case of the well-drained hydrological systems, which appear likely the less impacted by the monitoring time resolution and increase on average to 11% (with maximum values approaching 50%) in the case of the poorly drained systems.

 
Investigating the sources of surface mass loading signals in coastal GNSS permanent stations 
Authors: Ray Jagat Dwipendra , Godah Walyeldeen , Devaraju Balaji , Vijayan M Sithartha Muthu
Published: March 2022

The GNSS (Global Navigation Satellite Systems) position time series contains various geophysical signals which can be grouped into tectonic and non-tectonic signals. The tectonic signals include the signals of crustal deformation, volcanic deformation, transient signals of the earthquake and even landslide. On the other hand, the non-tectonic signal contains contributions of various surface mass loadings induced by temporal mass variations within the Earth’s system. The effects of the tidal components of these temporal mass variations are generally get removed during routine GNSS data processing. However, the effects of non-tidal mass loading are typically removed in the post GNSS data processing stage. Therefore, a raw GNSS position time series provides an opportunity to study the sensitivity of a GNSS station towards various non-tidal mass loadings. The understanding of the effect of non-tidal mass loadings in coastal GNSS stations is very important as these coastal GNSS stations are generally used to constrain vertical land motions of Tide gauge stations.

The objective of this study is to investigate the effects of various non-tidal mass loadings, such as non-tidal ocean loading, non-tidal atmospheric loading, hydrological loading and sea level loading, in a few coastal GNSS permanent stations. The vertical GNSS position time series of these stations are obtained from the Nevada Geodetic Laboratory (NGL) and analysed using the seasonal decomposition method. The seasonal components of the GNSS position time series resulting from this analysis are assessed through surface deformations due to various surface mass loading effects provided by the German Research Centre for Geosciences (GFZ). Furthermore, the resulted seasonal components of the GNSS position time series are also compared with the corresponding ones obtained from Gravity Recovery and Climate Experiment/GRACE Follow-On (GRACE/GRACE-FO) satellite missions data. The results of these assessments and comparisons are analysed and discussed from the perspective of surface deformations induced by non-tidal mass loadings at coastal GNSS stations.
Projecting net primary production in a sea of uncertainty: next steps and why should we care?
Authors: Bopp Laurent , Aumont Olivier , Kwiatkowski Lester , Le Mezo Priscilla , Maury Olivier , Séférian Roland , Tagliabue Alessandro
Published: March 2022

Ocean net primary production (NPP) consists of CO2 fixation by marine phytoplankton and hence supports most marine food webs, fisheries and ocean carbon sequestration. Recent Earth System Model (ESM) projections of NPP changes under global warming scenarios, performed as part of the 6th phase of Coupled Model Intercomparison Project (CMIP6), show large uncertainty both in the magnitude and spatial distribution of NPP, which may have consequences for assessing ecosystem impacts and ocean carbon uptake. NPP uncertainty has increased since the previous intercomparion project (CMIP5), and likely does not even capture the full range of possible outcomes due to the general simplicity of ecosystem parameterizations employed in ESMs and the failure to account for non-climate drivers. Here, we exploit the full set of ESM projections from CMIP6, documenting NPP uncertainties and identifying certain physical and biogeochemical mechanisms that give rise to these uncertainties. We then use different versions of the IPSL ESM to explore (1) the specific role of N-fixation by diazotrophs in the upper ocean and (2) the influence of coupling to higher trophic levels in shaping the response of NPP, marine ecosystems and biogeochemistry to anthropogenic climate change. We show that the response of  N-fixation to global warming is a key driver of NPP projection uncertainties in the coming decades, even determining the sign of the global NPP response.  Despite contrasting projections of future NPP, all our model versions simulate similar and significant reductions in planktonic biomass. This suggests that plankton biomass may be a more robust indicator than NPP of the potential impact of anthropogenic climate change on marine ecosystems across models. In a second step, we show that an explicit coupling to higher trophic levels modifies the response of lower trophic levels (plankton) and shifts the ecosystem equilibrium, but seems to have limited influence on 21st century anthropogenic carbon uptake under the RCP8.5 high emissions scenario. These results provide new insights regarding the expectations for trophic amplification of climate impacts through the marine food chain and regarding the necessity to explicitly represent marine animals in Earth System Models.

 

 
On the role of crustal deflection in the hydraulic-mechanical simulation of sedimentary basins during glacial cycles
Authors: Silbermann Christian , Kern Dominik , Steffen Rebekka , Steffen Holger , Bense Victor , Nagel Thomas
Published: March 2022

While guidelines for the location and licensing of a deep geological repository (DGR) for high-level radioactive waste depend both on national government policies and international regulations, it is mandatory to select a site where the hydrogeological setting provides sufficiently safe natural conditions for long-term waste isolation from groundwater flow. Therefore, safety assessments of a suitable location of a DGR require the evaluation of future external events and processes that may affect its long-term evolution.
Here, glaciation cycles are of special importance: Ice sheets evoke crustal deflections  (including deformation), and impose pronounced hydraulic heads, both of which change the large-scale hydrogeological conditions. To properly assess the present and future conditions of a DGR site, its evolution in the past should be understood. For this, a sedimentary basin [3] is considered here as a large-scale hydrogeological benchmark. The evolution during one glacial cycle is simulated using the open-source multi-field finite element code OpenGeoSys. The hydraulic-mechanical impact of the glacial loading is taken into account using appropriate time-dependent boundary conditions. For comparison with a previously published study [3], the same (heuristic) displacement field is prescribed and the groundwater evolution is regarded. Then, a more realistic displacement field obtained from large-scale GIA simulations [1,2] is prescribed. Using a one-sided mechanical-hydraulic coupling with a staggered solution scheme it is possible to consider not only the hydraulic head from the glacier and the crustal deflection but also the crustal compression. Especially in regions at the margin of the glacier this is could have an impact on the hydraulic behavior at the depth of a DGR.
References & Funding
This research is funded by the Federal Office for the Safety of Nuclear Waste Management under Grant No. 4719F10402 (AREHS project)

[1] Patrick Wu. “Using commercial finite element packages for the study ofearth deformations, sea levels and the state of stress”. In: Geophysical Journal International 158.2 (2004), pp. 401–408.

[2] G. Spada et al. “A benchmark study for glacial isostatic adjustment codes”. In: Geophysical Journal International 185.1 (2011), pp. 106–132.

[3] V.F. Bense and M.A. Person. “Transient hydrodynamics within intercratonic sedimentary basins during glacial cycles”. In: Journal of Geophysical Research: Earth Surface 113.F4 (2008).
Tracing the footprint of permafrost carbon supply to the Canadian Beaufort Sea
Authors: Bröder Lisa , Lattaud Julie , Juhls Bennet , Eulenburg Antje , Priest Taylor , Fritz Michael , Matsuoka Atsushi , Pellerin André , Bossé-Demers Thomas , Rudbäck Daniel , O'Regan Matt , Whalen Dustin , Haghipour Negar , Eglinton Timothy , Overduin Paul , Vonk Jorien
Published: March 2022

The Canadian Beaufort Sea receives large quantities of sediment, organic carbon and nutrients from rapid coastal erosion and permafrost degradation. In addition, the Mackenzie River, the largest North American Arctic river, discharges great amounts of freshwater, dissolved solids and suspended sediments to the Beaufort Sea. Current changes in these fluxes in response to the warming climate have uncertain consequences for the carbon budget on the shelf and in the deep ocean. To investigate the movement and transformation of organic matter along the land-ocean continuum, we collected water and surface sediment samples along five major transects across the Beaufort Sea during the 2021 expedition of the Canadian Coast Guard Ship Amundsen. Sampling locations span from shallow, coastal, sites with water depths ≤ 20 m, to shelf-break and deep-water settings on the continental slope (water depths of ≥1000 m). For this study, we use stable and radiocarbon isotopic (δ13C and Δ14C) analyses of dissolved inorganic (DIC), dissolved organic (DOC) and particulate organic carbon (POC) for surface and bottom waters, as well as surface sediments, in order to compare, contrast and constrain the relative source contributions and ages of these different forms of carbon. Our results will help to better understand the fate of permafrost organic matter in the marine environment and to ultimately improve assessments of the Canadian Beaufort Sea shelf as a carbon source or sink and its potential trajectory with ongoing environmental changes.
Seismic Velocity Contrast Along the Longitudinal Valley Fault System, Taiwan, from Analysis of Fault Zone Head Waves and Direct P Arrivals
Authors: Lin Tzu-Chi , Hillers Gregor , Lee Shiann-Jong , Hung Shu-Huei
Published: March 2022

Fault zone head waves (FZHWs) generated by bimaterial interfaces are the first arriving seismic phases at near-fault stations on the slower side of the fault. Since FZHWs spend almost their entire path along the fault interface, imaging methods based on these phases can provide high-resolution information on fault structure at seismogenic depths. In Eastern Taiwan, many past catastrophic earthquakes highlight the need for an improved understanding of fault characteristics and mechanical properties in this tectonically active environment. Here we use FZHWs to examine the northern segment of the Longitudinal Valley (LV) fault system, a suture zone between the Eurasian Plate and the Philippine Sea plate. We focus on 44 stations within a 70 km by 28 km area located along the northern segment of the LV fault system and ~8800 small-to-moderate earthquake seismograms recorded between 2012 and 2018 by those stations. We apply a set of algorithms developed by Ross and Ben-Zion to automatically detect and pick direct P waves, S waves and potential head waves contained in the seismograms. We augment the detection using finite-difference simulations to study the effect of varying source mechanisms on the first motion polarity characteristics of the P wave and FZHW. The results indicate that head waves will be generated not only by a clean strike-slip fault but by a wider range of focal mechanisms. We discuss 414 robustly detected head waves excited by 204 events that are located within a thin volume along the west-dipping Central Range fault, which now suggests—for the first time—the existence of a consistent velocity contrast across that fault segment. We apply particle motion, polarization, and moveout analyses to confirm the robustness of our FZHW phase picks obtained with the automatic method. Most particle motion and polarization results show that the azimuths calculated from windows containing direct P waves do not consistently point to the epicentres. This variability in horizontal particle motion is likely associated with the complex structure beneath the receivers and changes in topography. To the first order, the moveout pattern of the P wave to FZHW time difference is constant. This indicates a shallow bimaterial interface along the fault that affects the wavefield near or below the stations. We fit the moveout and constant arrivals with two models to the differential P and head wave arrival times to explore possible local variations of the generally constant trend. The Akaike Information Criterion applied to the constant and the sloping moveout pattern suggests spatially complex significant results that together with the depth distribution of the involved events indicate a deeper-reaching bimaterial interface. For these configurations, the obtained average velocity contrast ranges from 0.75 to ~3 per cent.
Recovery of Te, Bi and W from mine tailings and concentrates, using environmentally-benign Deep Eutectic Solvents at Björkdal Gold Mine, Sweden 
Authors: Tritton Lara , Jenkin Gawen , Smith Dan
Published: March 2022

The mining and minerals sector faces a dilemma: the transition away from hydrocarbons and race to net-zero requires enormous quantities of mineral resources for low-carbon technologies. However, mining and processing can be hugely energy-intensive and sometimes environmentally harmful, thus there is a need for novel solutions in extraction and processing. Gold ore processing in particular often features cyanide, which is highly toxic and has a large carbon footprint [1], and the often low Au concentrations can result in relatively large volumes of waste rock.

In addition, gold deposits are often also enriched in other metals, and the Björkdal mine produces gold concentrates and tailings that also contain Te, Bi and W. Initial data indicates a high degree of liberation for bismuth-tellurides which is promising for extraction. Currently, there is little incentive and few options by which to process and extract these additional metals for Mandalay Resources, the mine operator [2]. Developing a way in which these metals could be recovered rather than sent to tailings would be ideal for meeting some of the demand for these metals, without opening any new mines.

Deep Eutectic Solvents (DES), developed at the University of Leicester, are a promising advancement for both gold and by-product extraction [3][4]. DES are eutectic mixtures of an organic salt and a hydrogen-bond donor, which are powerful solvents and liquid at room temperature. The components are cheap, readily available and environmentally-benign compounds, such as choline chloride (Vitamin B4) and urea, and can be recycled and reused. Previous work on DES has demonstrated rapid leaching of Au, Ag, Sb, Te and other metals [1], including success with dissolution of tellurides and bismuth tellurides [5].

This project aims to understand the flows of Te, Bi and W through the Björkdal processing plant, and mineralogically characterise tailings and concentrates. This will be used to test the feasibility and impacts of inserting DES leaching stages, and/or altering the processing procedure or reprocessing tailings, in order to maximise by-product recovery in an environmentally-friendly and low energy process.

References:

[1] Norgate T and Haque N (2012) J Clean Prod 29-30:53-63

[2] Jenkin G et al. (2019) 15th SGA Biennial Meeting 4:1512-1515

[3] Abbott A et al. (2004) J Am Chem Soc 126 (29):9142-9147

[4] Smith E et al. (2014) Chem Rev 224 (21):11060-11082

[5] Jenkin G et al. (2016) Min Eng 87:18-24
Broadband strong ground motion modeling using planar dynamic rupture model with fractal parameters
Authors: Gallovič František , Valentová Ľubica
Published: March 2022

Dynamic rupture modeling represents a preferable physics-based approach to strong ground motion simulations. However, its application in a broad frequency range (0-10Hz), interesting for engineering studies, is challenging. The main reason is that relatively simple models with smooth distributions of initial stress and frictional parameters on planar faults result in ground motions with depleted high-frequency content. Several studies suggested that nonplanar rupture surfaces can solve this issue. Nevertheless, fully accounting for rough ruptures typically requires supercomputers, preventing widespread use.

Here we test an efficient approach for the linear slip-weakening friction model on planar fault, based on the Ide and Aochi (2005) multiscale model, with a small-scale fractal distribution of the slip-weakening distance Dc. To intensify the incoherence of the rupture propagation, we also include a variation of the strength and initial stress correlated with Dc. We propose a way to combine the fractal variations of the dynamic parameters with a large-scale dynamic model. The planar fault assumption permits the use of the computationally very fast code FD3D_TSN (Premus et al., 2020). 

We illustrate the approach on a canonical elliptical model with linearly increasing fracture energy (i.e., constant rupture velocity) and the 2016 Mw6.2 Amatrice earthquake smooth rupture model from the dynamic source inversion by Gallovič et al. (2019). We demonstrate that the addition of the small-scale fractal properties results in sustained high-frequency radiation during the rupture propagation and omega-square (apparent) source time functions. The model improves the fit of the recordings of the Amatrice earthquake in the frequency range of 0-10Hz and generates synthetics agreeing with ground motion prediction equations up to 5Hz.

Our FD3D_TSN takes about 5 minutes to simulate the Mw6.2 rupture propagation on a single GPU. Nevertheless, the fractal dynamic model can be easily implemented in any dynamic rupture propagation code. This makes the proposed approach readily applicable in physics-based ground motion predictions for scenario earthquakes in seismic hazard assessment.