bluuebunny/crossref_metadata_2025 huggingface dataset:
Extreme flood analysis on the Garonne river at Agen, using historical information since 1435
Authors: Lang Michel , Le Coz Jérôme , Mendez-Rios Felipe , Guillemin Perrine , Penot David , Scopel Didier
Published: March 2024

The safety of nuclear power plants in France is assessed based on 1000-year flood estimates, with a safety factor accounting for uncertainty. Previous studies on the Garonne River near Agen, France, used threshold exceedance values from a continuous 85 year-long series at two hydrometric stations: Malause (1915-1966) and Lamagistère (1967-2000), and historical data at Agen since 1770. The estimate of the design flood was very sensitive to the choice of an Exponential or of a Generalized Pareto distribution, yielding 12 600 and 16 000 m3/s, respectively. This communication presents a more comprehensive study based on a GEV distribution fitted from the annual maximum values of a continuous series since 1852 (adding Agen 1852-1914) and historical data at Agen since 1435. The statistical framework accounts for both discharge and sampling uncertainty components. The first uncertainty component is about 3% for the recent years and 35% for the oldest years. The statistical framework is able to account for a multiplicative error on rating curves. This leads to corrections in peak discharge values, with better agreement between historical data at Agen and hydrometric data at Malause-Lamagistère. The final estimate of the design flood is around 10 500-11 600 m3/s, without or with the largest known historical flood of 1435. It confirms the safety of the nuclear plant, based on extensive historical information.
Gravity Modelling of a Pull-Apart Basin in Elazığ, Turkey: Unraveling the 3D Basement Geometry (Preliminary Results)
Authors: Aydın Nedim Gökhan , İşseven Turgay
Published: March 2024

This study employs gravity modelling to investigate the subsurface geometry of a pull-apart basin located in Elazığ, Turkey. The study area is situated along the East Anatolian Fault Zone—a major active system that recently produced two devastating M7.0+ earthquakes at Kahramanmaraş in February 6, 2023.Recently collected gravity data, comprising approximately 600 data points from Sivrice and Gezin provinces, form the basis of our investigation. Preliminary examinations show that the gravity anomalies in Gezin are notably lower than those in Sivrice, suggesting a deeper basement for the former. We aimed to estimate the subsurface model using a proprietary computer program. Given the known different geological units with constant density contrasts, the program was employed to deduce their geometry up to a maximum depth of 350 meters in 2D. A total of 16 sections were modeled—8 each for Sivrice and Gezin provinces—yielding RMS values consistently below 0.1 mGals. Next, quasi-3D and 3D models were prepared for Talwani models at Sivrice and Gezin. We assumed the geometry beneath Lake Hazar to be similar to the bathymetry of the lake, assigning sediment thickness to estimate the basement in this part. The individual models were then integrated into a full 3D representation of the geometry of the basin.Our findings suggest that the pull-apart basin situated here is in its extinction phase, with pull-apart tectonics no longer active, and only strike-slip movement along main East Anatolian Fault is observed. Notably, slips along the main fault have impacted the basement geometry. This study contributes valuable insights into the current state of the basin, emphasizing the importance of 3D modelling in unraveling the complexities of pull-apart basins.
Penecontemporaneous polygonal faulting triggered by sand overloading onto unconsolidated clays in the northern South China Sea
Authors: Meng Qingfeng , Hao Fang
Published: March 2024

Layer-bound polygonal fault systems are commonly found in fine-grained sediments in continental margin basins worldwide, but their origin remains a dispute. This study focuses on the structural characteristics of polygonal fault systems newly discovered in the Middle Miocene mudrocks of the Yinggehai Basin in the northern South China Sea. Our analysis reveals that the layer-bound normal faults constitute a complex network with straight or curvilinear fault traces and frequent orthogonal intersections in the Meishan Formation. We also observe structural depressions filled with syn-deformation deposits, with their long axis aligned parallel to the structural contours. Our findings suggest that the polygonal faults formed during rapid loading of fine-grained sands as gravity-flow deposits onto unconsolidated clays, resulting in density inversion and fault nucleation. Fault propagation was facilitated by continuous sediment deposition and ceased when sedimentation ended in the faulted interval. This study offers new insights into early sediment deformations in the northern South China Sea region and contributes to our understanding of the genesis of polygonal fault systems.
Petrogenesis and geochronological constraints on the timing of Carbonatite-syenite magmatism at the Archean-Proterozoic boundary in the Western Dharwar Craton, southern India.
Authors: Debnath Samir , Pandey Rohit , Belyatsky Boris , Chew David , Chalapathi Rao Nittala Venkata , Singh Mahendra Kumar
Published: March 2024

An integrated study involving field, geochronology, whole rock geochemistry and multi-isotope (Sr-Nd-Pb-Os-C-O) systematics for a newly reported carbonatite-alkaline syenite intrusive system is presented from the Gundlupete area, Western Dharwar Craton, India. The Gundlupete carbonatite (GC) is a coarse-grained calcio-carbonatite, predominantly constituting calcite, apatite, magnetite, monazite and other silicate phases. Field evidence shows its intrusive relationship with spatially associated syenite, occurring close to an E-W to ENE-WSW trending shear zone at the purported tectonic contact between the Western Dharwar Craton and the Southern Granulite Terrain, southern India. The carbonatite shows elevated LILE-LREEs content with (La/Yb)CN between 103-202 but is significantly impoverished in HFSEs. The syenite shows an ultrapotassic to shoshonitic composition (K2O/Na2O: 0.90-2.42) and a broadly similar geochemical pattern. Our in-situ U-Pb titanite and monazite dating yielded crystallisation ages of 2590 ± 42 Ma and 2470 ± 27 Ma for the syenite and carbonatite respectively, implying two discrete magmatic events. The carbonatite shows a narrow Sr [87Sr/86Sri: 0.70307-0.70321], Nd [εNdi: -3.7 to -2.1], Pb [206Pb/204Pb: 13.42-14.04, 207Pb/204Pb:14.69-14.78,208Pb/204Pb:26.60-35.20] isotopic range, whereas the syenite, although shows restricted Nd [εNdi: -1.4 to 1] isotope range but large spread in Sr (87Sr/86Sri: 0.66834-0.70210), and Pb [206Pb/204Pb: 6.60-24.38, 207Pb/204Pb:13.47-16.34, 208Pb/204Pb:13.56-164.37] isotopes limits its further usage. C-O isotopic compositions of GC exhibit -10.2 to -9.4‰ and 7.7-10.3‰, respectively, and cluster slightly below the ‘PIC’ field. The present study suggests that the GC evolved from primary carbonatite melt through processes like magmatic differentiation/fractional crystallisation and assimilation en route to the surface without involving liquid immiscibility and/or fractional crystallisation from a common parental carbonated silicate magma. The combined initial Sr-Nd-Pb isotope systematics suggest that the carbonatite magma tapped a mantle source with marginally higher time-integrated Rb/Sr, Nd/Sm, and U-Th/Pb ratios with respect to Bulk Earth and CHUR. We propose that immediately after the terminal Neoarchean collision between the Dharwar Craton and the Southern Granulite Terrain, the carbonatites and syenite were emplaced utilising similar conduits during the transition from a collisional to a post-collisional extensional regime across the Archaean-Proterozoic boundaryKeywords: Carbonatite, syenite, Archean, Proterozoic, Dharwar Craton, Southern Granulite Terrain
Modelling the changes in the upper tropospheric composition due to convective transport
Authors: Jeske Adrienne , Smoydzin Linda , Hoor Peter , Tost Holger
Published: March 2024

Atmospheric moist convection has a considerable influence on the composition of the upper troposphere. Besides the strong effects on the atmospheric moisture budget, the high vertical velocities associated with deep convection lead to a redistribution of air masses, with especially large effects on the concentration of tracers with short atmospheric lifetimes. Even though the importance of convective transport is long known, this process remains a major source of uncertainty.To diagnose the efficacy of convective tracer transport, we have developed a new modelling tool for simulations in global circulation models that rely on convection parameterisations, namely the convective exchange matrix. The exchange matrix basically links fractional contributions of inflow and outflow between any model level when convection is simulated for a given column. We apply this new tool in the chemistry climate model EMAC (ECHAM5 MESSy Atmospheric Chemistry) in order to characterise the transport of individual convective events. Beyond that, we present long-term statistics on vertical tracer transport into the upper troposphere to highlight the contribution of air masses originated at different heights to the upper tropospheric composition. This also includes the analysis of the regional and global distribution of convective outflow heights of the simulated convective clouds. Finally, we outline a potential application as a support tool for the analysis of upper troposphere aircraft observations in convectively active regions to backtrace the origin of the air masses and their overall contribution to the measured concentrations.
How catchment ecosystems globally manage root water access under different (climate) conditions
Authors: van Oorschot Fransje , van der Ent Ruud , Viering Tom , Alessandri Andrea , Hrachowitz Markus
Published: March 2024

The root zone storage capacity (Sr) is the maximum volume of water in the subsurface that can potentially be accessed by vegetation for transpiration. Sr is an essential characteristic of hydrological systems as it controls the partitioning of precipitation into evaporation and runoff. Understanding the influence of climatic and landscape characteristics on Sr is essential for predicting how different ecosystems will respond to disturbances such as human activities and climate change. While the magnitude of Sr on ecosystem scale is partly influenced by landscape characteristics such slopes, bedrock properties and soil characteristics, there is widespread consensus that it is primarily controlled by climate conditions (i.e., the temporal dynamics of water and energy availability) as vegetation optimizes its root system to sustain atmospheric water demand.Several studies have identified the influence of various climatic variables on Sr, but for different regions conflicting influences of these variables on Sr appeared. So far, it remains unclear what aspects of the climate are most important controls on Sr on global scale. This research aims to bridge this gap by exploring how different climatic and landscape characteristics influence the magnitude of Sr globally. Based on discharge measurements in a large sample of catchments worldwide (~4000), we estimated the actual Sr using the memory method as in Van Oorschot et al. (2021, 2023). With a random forest model we were able to adequately predict Sr using various climatic and landscape characteristics. Analysis of the driving variables of the random forest model show that the precipitation inter-storm duration is the most dominant control on Sr, and positively influences Sr in all regions. On the other hand, the influence of mean precipitation on Sr is conflicting in different regions. We found that in water limited regions, increased mean precipitation leads to increased Sr, while in energy limited regions, increased mean precipitation leads to decreased in Sr. Furthermore, the developed model is used to extrapolate the catchment Sr estimates to a global gridded map of Sr ensuring coverage of data-scarce regions. This extrapolated map can be used for more adequate modelling of subsurface vegetation water availability in large scale hydrological and land surface models.van Oorschot, F., van der Ent, R. J., Hrachowitz, M., and Alessandri, A.: Climate-controlled root zone parameters show potential to improve water flux simulations by land surface models, Earth Syst. Dynam., 12, 725–743, https://doi.org/10.5194/esd-12-725-2021, 2021.van Oorschot, F., van der Ent, R. J., Alessandri, A., and Hrachowitz, M.: Influence of irrigation on root zone storage capacity estimation, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-2622, 2023.
Global warming rates and surface temperature patterns through 2023: A Green’s function based investigation
Authors: Samset Bjorn H. , Zhou Chen , Fuglestvedt Jan S. , Lund Marianne T. , Marotzke Jochem , Zelinka Mark D.
Published: March 2024

The rate of global surface warming has seemingly been steady since the 1970s. Any progress towards halting climate change will be heralded by a slowdown in the warming rate, but tracking it on sub-decadal timescales is challenging because of strong interannual-to-decadal variability.Recently, we used a physics-based Green’s function approach to filter out modulations to global mean surface temperature from sea-surface temperature (SST) patterns, and showed how this results in an earlier emergence of a discernible climate response to strong emissions mitigation. We have also shown how the filtered observations reveal a marked step-up in warming rate around 1990, consistent with known increases in ocean heat uptake. CMIP6 models are currently broadly unable to simultaneously capture the observed long-term warming rate, and such a step-up in rates over the last decades.Here, we summarize these results, which were based on the CESM1 Earth System Model, and extend them to multiple, independently derived Green’s functions. We discuss how this toolkit can be complementary to existing attribution techniques. Then we apply it to an investigation of the surprising SST patterns in 2023, and what they imply about the potential causes for the high global mean surface temperature. Finally, we discuss the prospects for rapid detection of a climate response to strong greenhouse gas emissions mitigation, modulated by one or more areas of strong aerosol emissions changes, using Green’s functions or other techniques for reducing the influences of internal variability.Key references:Samset, B.H., Zhou, C., Fuglestvedt, J.S. et al. Steady global surface warming from 1973 to 2022 but increased warming rate after 1990. Commun Earth Environ 4, 400 (2023). https://doi.org/10.1038/s43247-023-01061-4Samset, B.H., Zhou, C., Fuglestvedt, J.S. et al. Earlier emergence of a temperature response to mitigation by filtering annual variability. Nat Commun 13, 1578 (2022). https://doi.org/10.1038/s41467-022-29247-y
Integrated hydrological modelling for predicting spatiotemporal variability of water table depths in Danish peatlands
Authors: Denager Tanja , Schneider Raphael , Quistgaard Thea , Riis Christiansen Jesper , L. Langen Peter , Stisen Simon
Published: March 2024

It is well known that artificially drained peatlands are net greenhouse gas (GHG) sources to the atmosphere. In peatlands, the depth of the groundwater table i.e. the water table depth (WTD), is an important driver of carbon dioxide (CO2) and methane (CH4) emissions.Integrated hydrological models simulating transient unsaturated and saturated subsurface flow in peatlands, allow mapping of the spatiotemporal variability of WTD and thereby the impact on GHG on daily, seasonal, and inter-annual timescales. Thereby, hydrological modelling of peatlands has the potential to assist more accurate estimates of GHG emissions compared to the simple default IPCC emission factors and/or long-term average WTD estimates used in prevalent national GHG inventories.Here we apply physically-based 3D modelling of the WTD to a highly monitored peatland, as a case-study representing common drained and degraded peatland soils in Denmark. The catchment scale model is based on an advancement of the National Hydrological Model of Denmark running in the numerical simulation tool MIKE-SHE/MIKE-Hydro.We identify the main processes governing peatland WTD dynamics in the model and develop a novel parameter calibration scheme focusing on WTD dynamics. We use objective functions tailored to timeseries of WTD by combining individual components of a modified version of the Kling-Gupta Efficient (KGE) with low- and highpass filters to separate the WTD signal into seasonal patterns and short-term precipitation responses. Using the Pareto Archived Dynamically Dimensioned Search (PADDS) algorithm to obtain the pareto front enables post-weighting of objective functions for optimal tradeoff analysis. The model is calibrated at 100m scale and a forward run with the optimal parameter values demonstrate mapping of WTD dynamics and statistics for potential use in GHG inventories at 20m scale.Those achievements will lead to more robust representation of peatland hydrology in hydrological models and will facilitate analysis of hotspots and hot moments in GHG emissions and enable scenario-based analysis of climate change and management impacts on WTD dynamics in peatlands. This will support the Danish rewetting strategies and better upscaling of GHG emissions for the national inventories.
Chemical Characterization of Brown Carbon Aerosol Sampled in the Indo-Gangetic Plain Area.
Authors: Chaudhary Pooja , West Christopher P , Singh Raj , Sinha Vinayak , Sinha Baerbel , Laskin Alexander
Published: March 2024

The light-absorbing fraction of organic aerosols, commonly known as brown carbon (BrC), is a significant contributor to climate change. Biomass burning (BB) emissions of BrC are ubiquitous over Indo-Gangetic Plain (IGP). BB is very common in India because of biofuel usage for heating and cooking, agricultural residue burning, and uncontrolled garbage burning. Despite their abundance, the molecular-level understanding of BrC composition in IGP area is limited. Here, we investigate chemical composition of BrC collected at a suburban site in the northwest IGP. The aerosol samples were collected at the Atmospheric Chemistry Facility (30.667° N−76.729° E, 310 m above sea level) of the IISER Mohali, India. Compositional information was obtained by employing ambient ionization with high-resolution mass spectrometry. Specifically, Direct Analysis in Real-Time High-Resolution Mass Spectroscopy (DART-HRMS) was used to analyze samples of organic aerosols collected on the filter spots of 7-wavelength aethalometer. The samples were collected in two different seasons – post-monsoon, and winter. Post-monsoon season is dominated by largescale paddy residue burning whereas winter season is dominated by biofuel (wood and dungcakes) burning for heating and cooking purposes. Comparative analysis of optical records from the aethalometer and molecular information from DART-HRMS was used to assess the relationship between the chemical composition and optical properties of BrC.
The impact of our warming climate on global groundwater temperatures
Authors: Benz Susanne A. , Irvine Dylan J. , Rau Gabriel C. , Bayer Peter , Menberg Kathrin , Blum Philipp , Jamieson Rob C , Griebler Christian , Kuryly Barret
Published: March 2024

Groundwater, the largest reservoir of unfrozen freshwater on Earth, plays a crucial role in supporting life and ecosystems. Its thermal regimes influence various environmental processes, impacting groundwater-dependent ecosystems, geothermal potential, and groundwater quality. Despite its significance, little is known about how groundwater responds to surface warming across spatial and temporal scales. Here we present a comprehensive analysis of global groundwater temperature patterns, utilizing the latest CMIP6 scenarios.In this study we developed the first global model of groundwater temperature patterns, combining analytical solutions to conductive heat transport with high-resolution maps of ground thermal diffusivity and geothermal gradient. This model, validated with over 8,000 groundwater temperature measurements, allows users to estimate present and future temperature depth profiles globally. Past trends show a median global groundwater temperature increase of 0.3 °C over the last two decades. When simulating projected groundwater temperatures globally, our model reveals an average warming of 2.2°C (SSP 245) to 3.8°C (SSP 585) between 2000 and 2100 at the depth of the water table. Regional variations are substantial due to climate change and water table depth variability, with mountainous regions exhibiting the lowest warming rates. These distinct regional variations emphasize important thermal controls and the need for localized analysis.Our work sheds light on the importance of understanding groundwater warming patterns, identifying 'hot spots' that may pose risks to both ecosystems and human well-being. In this study we also offer a specific focus on Europe, providing averages to enhance regional relevance and address emerging challenges in groundwater quality and habitat preservation.
Benthic foraminifera assemblages on the southern Portuguese margin during early Pleistocene Marine Isotope Stages 42-45
Authors: Kicsi Anna , Molina Giulia , Voelker Antje H.L.
Published: March 2024

Climate variability and glacial cycles during the Pleistocene era are well-studied phenomena, although less is known about the climate dynamics and their impact on benthic foraminiferal assemblages prior to the Mid Pleistocene Transition known as the ‘41 kyr world’.  Benthic foraminiferal assemblages are sensitive to variations in factors such as food fluxes, pore water oxygenation and bottom water conditions as well as variations in Mediterranean Outflow Water (MOW), therefore, we studied benthic foraminiferal assemblage data from IODP Site U1378 (36°48.321´N 7°43.1321´W), drilled into the Faro Drift on the southern Portuguese margin (Gulf of Cadiz) at a water depth of 559 m during IODP Expedition 339 to investigate early Pleistocene glacial/interglacial cycles of Marine Isotope Stage (MIS) 42 to late MIS 45 (1.33-1.39 Ma). In addition to the benthic assemblage data, we used epibenthic oxygen and carbon stable isotope data derived from Cibicioides pachyderma and Planulina ariminensis, insolation data of 21 June at 65°N, weight percent of organic carbon and sand (wt%).Benthic foraminiferal assemblages were picked in two fraction sizes (>250 µm and >125 µm), counting ap. 150 specimen per size fraction. A total amount of 119 species of benthic foraminifera were counted, the most abundant species being Sphaeroidina bulloides, Cassidulina laevigata, Uvigerina celtica, Cibicidoides pachyderma and Globocassidulina subglobosa (relative abundances varying between 11.04 - 5.04%). The assemblage data show variations along the analysed section, especially a significant diversity drop at 1.355 Ma (MIS 43), with high abundances (and dominance) of Bulimina mexicana striata, Uvigerina celtica and Sphaeroidina bulloides. At the same time, abundances of Cibicidoides spp., Cassidulinoides laevigata, Melonis barleeaum, and Globocassidulina subglobosa declined. These faunal changes coincided with a 0.68‰ decrease in the δ13C and a 0.22‰ increase in the δ18O values. Another change in the δ13C values, a 0.61‰ increase at 1.375 Ma (MIS 44), was associated with a high abundance peak of Globobulima spp. The abundance of Cibicidoides correlates well with the weight percentage of the sand-sized fraction (wt% sand), which likely indicates stronger current activity on the seafloor, which is also supported by the abundance of Trifarina angulosa, a species that also prefers strong currents and may be an indicator of MOW velocity at our study site.
Resolution of the bottom boundary layer in an eddy-rich model of double-gyre circulation
Authors: Chen Si-Yuan (Sean) , Marchal Olivier
Published: March 2024

The bottom boundary layer (BBL) is the portion of the water column which is directly affected by the drag of ocean currents on the seafloor. It is often assumed to coincide with the bottom mixed layer in which potential temperature is approximately uniform. Bottom mixed layers have an observed thickness of O(10 m), with maxima of O(100 m) in some basins. As a result, they are in general not represented in numerical models of large-scale circulation, which typically assume a vertical resolution of a few hundred meters near the bottom. The coarse vertical resolution near the bottom that is assumed in many numerical models implies that these models may not accurately represent the velocity shears near the bottom and the dissipation rates of kinetic energy by bottom drag, which depends on the near-bottom velocity. Here we present results from idealized numerical experiments of the circulation in a double (subtropical-subpolar) gyre, which are aimed at determining the effects of near-bottom vertical resolution on simulated ocean circulation and energetics. Results from experiments that resolve the BBL are compared to those from experiments that do not. In all experiments, the horizontal grid is fine enough to resolve the mesoscale eddy field. In our presentation, emphasis will be placed on energy dissipation by bottom drag in experiments with different near-bottom vertical resolutions. The implications of our results for the simulation of large-scale ocean circulation will then be clarified.
Revisiting the performance of CMIP6 models in the Arctic: Concerns on benchmarking climate models
Authors: Yang Shuting , Tian Tian , Hoyer Jacob L. , Nielsen-Englyst Pia , Singha Suman
Published: March 2024

Climate models are known to have difficulty in simulating the present day climate in the Arctic. Many studies, including the most recent Inter-governmental Panel on Climate Change Sixth Assessment Report (IPCC AR6), report that, comparing to reanalysis datasets such as ERA5 as reference, climate models participating the past phases of the Coupled Model Intercomparison Project (CMIP) simulate a too cold Arctic. However, recent studies reveal substantial warm biases over sea ice surface in global atmospheric reanalyses due to missing representation of physical processes such as the snow layer on top of the sea-ice.In this work we revisit the so-called long-standing climate model bias in the Arctic by using a new, satellite-derived near surface air temperature (T2m) dataset for the Arctic sea ice region as an alternative reference to the commonly used reanalysis data ERA5. This observational T2m dataset is derived from the satellite based on DMI/CMEMS daily gap-free (so called L4) sea surface temperature and sea ice surface temperature climate data record, spanning from 1st January 1982 to 31st May 2021, covering the Arctic region (> 58 ◦N). We show that, in comparison with the new observational dataset, the ERA5 reanalysis exhibits widespread warm biases exceeding 2℃ over sea ice in the central Arctic, particularly during winter when the warm bias may be as large as 6-10℃. In contrast, the CMIP6 model ensemble demonstrates reasonable performance, with an annual mean bias less than ±1℃ in the same region. We also find that the CMIP6 model mean slightly outperforms the ERA5 in capturing the observed warming trend over the central Arctic region where is fully covered by sea ice with concentration of more than 70%. Outside of this region, it is evident that ERA5 aligns well with observations, while CMIP6 models show large cold bias in the North Atlantic marginal ice zone, consistent with the well-documented results in the past.Our results challenge the current assessment of climate models in the central Arctic, suggesting that relying on existing reanalyses datasets as a reference may underestimate the climate models creditability in the region. It is thus imperative to integrate new observational data for benchmarking climate models in the Arctic region.
The Importance of Silicon Metal on the Green Transition and the Role of Northern Countries in the Silicon Metal Market
Authors: Akyıldız Ozge
Published: March 2024

With the green transition in Europe from fossil fuels to renewable energy, it will significantly change the demand for raw materials. The European Union’s new growth strategy focuses on sustainability. While doing so, the intent is to reduce the dependency on non-EU countries regarding the raw materials supply. Access to raw materials has been questioned by the European Commission for twenty years as it is foreseen as new “oil and gas”. The transition requires using carbon-free energy resources and electric vehicles which leads to a great need for raw materials that are used in the production of wind turbines, solar panels and batteries, etc. However, Europe is mostly dependent on non-EU countries which poses a risk of supply chain disruptions, as witnessed in the Covid-19 pandemic and the war in Ukraine.In this study, silicon (Si) metal, one of the critical raw materials having high economic value, will be investigated in terms of its usage, substitution, supply, demand, and future strategies. Si metal is used in aluminum alloys, electronic, chemical, and photovoltaic applications. Green transition and autonomy in the mineral supply chain in Europe both require upscaling mining and supply from secondary materials/recycling of critical raw materials. However, there is almost no recycling of Si metal since it is mostly dispersive in metallic alloys and chemical applications. Thus, mining should be considered as the main activity for the security and sustainability of the Si metal supply chain. This implies that Europe will need to overcome several disadvantages such as no sufficient exploration of resources, public opposition to mining and complex permitting procedures, since it is not given the priority to produce their raw materials. Considering the disadvantages, it is estimated that the upscaling of the mining activities will take 10 to 15 years.Today, China controls 76% of the Si metal global supply which increased by 10% since 2020 and USA shares 8 %, Brazil 7 % Norway 6 % of global production. Norway shares about 50% of the Si metal produced in Europe and there are high-purity quartz deposits distributed across the country. Furthermore, Norway possesses renewable and cheaper electricity, which is typically the most costly element in producing metals, in addition to its natural resources. The availability of affordable power will most likely become more crucial in the future as energy sources shift from hydrocarbons to green energy sources. Finland is assumed to have a high-quality reserve, while the exact quantities are unknown. In Greenland, although the purity is unknown, the reserves are thought to be substantial. Sweden is also known to have potential reserves of high-quality quartz. As a result, this study will elaborate on the potential leading role of northern countries in meeting Europe's Si metal needs in the path of green transition.
Exploring the dynamics of geodiversity and land cover diversity in Northern Albania
Authors: Albert Gáspár , Kraja Drisela
Published: March 2024

Geodiversity is expressed as a geographical index. It aims to quantify the diversity of the non-living environment. Like all diversity index it serves complex analyses and comparisons. For example, comparing geodiversity and biodiversity helps to understand the relationship between the living and non-living environment and to protect it in a coordinated way. In this study, we had a similar objective: the relationship between geodiversity and land cover diversity was explored to find out the dynamics between the two indicators.The study area is in the northern part of Albania, near Shkodra, on an area of about 1800 km2, and covers a geographic environment that is diverse in almost all respects: coastal, agricultural, urban, riverside, mid- and high mountain. These make the area remarkable for both its geodiversity and biodiversity, and although the former is not emphasised, the Theth National Park in the area aims to preserve these values.The study was conducted using open-source GIS tools (QGIS and SAGA) at a medium scale, which also determined the 2x2 km cell size of the grid over the area. For the geodiversity index we used geological, soil, morphometric categories, and paleontological and mineral sites from published sources. For surface coverage, the 100 m cell resolution Copernicus Global Land Cover 2019 data for vegetation were used. Land cover diversity was expressed by the Shannon’s diversity index averaged over each 2x2 km cell. In addition to diversity, we also examined the connectivity of land cover categories and the degree of spatial autocorrelation. The latter was assessed for the 4 km2 tiles by the global Moran index.The results were evaluated separately for low- and medium-altitude (
Fluid inclusions were used to determine gas accumulation period and accumulation process in Ledong 8-1 diapir area of Yinggehai Basin
Authors: Yang Chen , Tian Jinqiang
Published: March 2024

Yinggehai Basin is an important high-temperature and high-pressure gas producing basin in the South China Sea, and Ledong 8-1 diapir is located in the southeast of the basin, which is the focus of natural gas migration and accumulation. However, the study of fluid inclusions in this gas-bearing structure is not enough, and the accumulation period and accumulation process are not clear, which restricts the progress of exploration in this area. Taking Ledong 8-1 as the research object, this paper uses microscopic lithofacies observation, microscopic temperature measurement of inclusions, laser Raman composition identification, in situ quantitative spectroscopy based on inclusion data to recover paleo-pressure and indirect projection dating of uniform temperature-burial history to identify gas inclusions of different composition types and recover the paleo-pressure evolution history of the Huangliu Formation. The accumulation period and process of natural gas were determined. The results show that there are four types of gas inclusions in Ledong 8-1 diapir, corresponding to three phases of gas charging. The charging time of the first phase of natural gas is 2.2-1.6Ma, the gas composition is mainly CH4, and the pressure coefficient of Huangliu group is 1.13-1.42, indicating weak overpressure. The second phase of natural gas charging occurred at 1.6-0.6Ma, and the gas composition was mainly CO2. Since 0.6Ma, the third stage of natural gas was charged into the formation, and the pressure coefficient of Huangliu formation was as high as 1.8, indicating strong overpressure. It is speculated that the diapiric was opened at this stage, and the natural gas formed in the early stage of Huangliu formation and the newly generated natural gas from deep source rocks migrated upward and adjusted. Studying the fluid inclusions in Ledong 8-1 area of Yinggehai Basin and clarifying the process of gas accumulation in this area is of great significance to the oil and gas exploration in the whole basin, and it is also the key to promote the increase of oil and gas storage and production in the whole basin.
Urban Tree Health Monitoring at Grand-Scale: a Way to Target Unhealthy Individual Trees Using Remote Sensing
Authors: Tessema Tesfaye , Uzor Stephen , Mortimer Dale , Tosti Fabio
Published: March 2024

Green infrastructure is a key to sustainable development in urban environment. Trees in the parks and along the roadsides are part of green infrastructure and contribute to the health and wellbeing of the society. These trees should be monitored to identify problems at a broader scale and isolate those with health issues for detailed investigation.  Some of the health problems could be manifested in a form of discoloration and defoliation  [1].  Visual inspection is common practice to identify unhealthy trees but to observe in a grand scale, for example, county or city scale might be challenging. For this purpose, remote sensing data play an important role.We use hyperspectral images and Lidar observations to identify the changes and estimate the canopy density [2,3]. To understand the health status, we use images taken during the peak of the vegetation season where the leaves are not fallen off. The top-to-down approach will enable us to target individual trees and investigate further in detail at root and trunk levels. The overall approach will contribute the effort of the city councils to monitor trees and reduce the decision-making time in preserving them and the surrounding built environment.Keywords: Green infrastructure, tree health monitoring, hyperspectral images, Lidar Acknowledgments: Sincere thanks to the following for their support: Lord Faringdon Charitable Trust, The Schroder Foundation, Cazenove Charitable Trust, Ernest Cook Trust, Sir Henry Keswick, Ian Bond, P. F. Charitable Trust, Prospect Investment Management Limited, The Adrian Swire Charitable Trust, The John Swire 1989 Charitable Trust, The Sackler Trust, The Tanlaw Foundation, and The Wyfold Charitable Trust. The Authors would also like to thank the Tree Service at the Ealing Council for facilitating this research.  References[1] Degerickx J, Roberts DA, McFadden JP, Hermy M, Somers B. Urban tree health assessment using airborne hyperspectral and LiDAR imagery. International Journal of Applied Earth Observation and Geoinformation 2018;73:26-38.[2] Hanssen F, Barton DN, Venter ZS, Nowell MS, Cimburova Z. Utilizing LiDAR data to map tree canopy for urban ecosystem extent and condition accounts in Oslo. Ecol Ind 2021;130:108007.[3] Tessema T, Uzor S, Mortimer D, Tosti F. Estimation of tree height using radar remote sensing in urban settings: a preliminary result. Proc. SPIE 12734, Earth Resources and Environmental Remote Sensing/GIS Applications XIV, 127340O (19 October 2023); https://doi.org/10.1117/12.2684325   
Alpine-wide LIA glacier reconstruction and ELA patterns using glacier modelling
Authors: Henz Andreas , Vieli Andreas , Nussbaumer Samuel , Jouvet Guillaume
Published: March 2024

The maximum extent of the glaciers in the European Alps during the Little Ice Age (LIA) is relatively well known. However, the ice surface geometry and related ice volume are still poorly constrained. We provide an Alpine-wide reconstruction of glacier thickness using the novel Instructed Glacier Model (IGM). The IGM uses the innovative approach based on deep-learning and GPU to accelerate the solving of computationally expensive 3D physics of glacier flow, which is key to work in high-resolution at the Alpine scale. The mass-balance model is tuned to fit each glacier of the Alps to its known maximum LIA extent resulting in ice-surface geometries and volumes that are consistent with glacier physics and the principles of mass conservation. In addition, our approach provides the corresponding equilibrium-line altitudes (ELAs) for individual glaciers and thereby reveals regional ELA patterns. Comparing these patterns with pre-industrial climate model data permits to analyse the relationship between ELA and climate factors such as temperature, precipitation, aspect, and solar radiation. In conclusion, our approach not only contributes to the estimates of LIA glacier shapes and geometries, but also permits to infer first-order relationships between glacier dynamics and climate conditions.
Stream Machine Learning for Lightning Nowcasting - Harnessing the Power of Continuously Updated Data
Authors: Beneti Cesar , Pavam Luis , Oliveira Luiz , Alves Marco , Calvetti Leonardo , Verdelho Fernanda
Published: March 2024

Uninterrupted access to electricity is a fundamental feature of civilization. In its absence, an all-embracing cessation of activities occurs, ranging from essential services to more frivolous activities. The maintenance of the energy supply is critical for society's day-to-day functions. The Brazilian state of Paraná (PR) is home to the world's second-largest hydropower plant, Itaipu, which, in conjunction with other power plants in the state, provides almost one-third of the power energy production in Brazil. The transmission lines that pervade PR are essential to Brazil's power distribution system, for hydropower generation is typically made far away from the regions that most demand it, being transported by transmission lines in an interconnected power grid. This type of asset mainly depends on the forecast of Cloud-to-Ground (CG) lightning, as it is one of the leading weather-related causes of power outages. Lightning and wind gusts are the two leading weather-related causes of disruptions, representing at least 23% of the known causes of energy disruption, as declared by the local power distribution company. Our study of lightning incidence and power outages from 2017-2021 indicates a correlation of 0.98 between these events, denoting that more outages must be lightning-related. Reliable CG lightning forecasts are crucial for proactive hazard mitigation. This work expounds on developing a Machine Learning (ML) model for CG lightning forecasting for PR. Our ML model predicts the occurrence or lack of CG lightning near power company assets in PR, defining a binary classification task. The model makes its predictions based on the past spatio-temporal conditions of lightning occurrences, requiring only past lightning data to forecast lightning. We chose to use a stream ML method, i.e., the model is continuously trained as new data arrives. Using a stream ML, we intend to harness the machine's capacity to continuously learn the patterns of lightning occurrence and power outages in real-time -- thus constructing an ever-updating model capable of adapting to transient weather conditions. Given its rapid training time and aptitude for classification tasks, the chosen algorithm was a Very Fast Decision Tree. The stream ML classifier outperforms a classic static ML model by 30% regarding the ROC AUC metric (stream: 71.80%, static: 40.85%) and 50% considering the Micro-f1 score (stream: 91.05%, static: 40.91%). These results arise from the highly dynamic nature of lightning, defining an ideal phenomenon for prediction based on a constantly updated stream of data. An automatic system for CG lightning forecasting for power company assets is helpful for risk management and operational planning. Future steps include increasing the lead time from ten min. to up to one hour, allowing for more time to prepare and anticipate hazards, preventing power outages, and optimizing personnel allocation.
A model for ice-mélange based on particle and continuums mechanics
Authors: Kahl Saskia , Mehlmann Carolin
Published: March 2024

Ice mélange (a mixture of sea ice, bergy bits and icebergs) can have a strong influence on the sea-ice-ocean interaction. So far, ice mélange is not represented in climate models as numerically efficient realizations are missing. This motivates the development of an ice-mélange model based on the viscous-plastic sea-ice rheology, which is currently the most commonly used material law for sea ice in climate models. Starting from the continuum mechanical formulation, we modify the rheology so that icebergs are represented by thick, highly compact pieces of sea ice. These compact pieces of sea ice are held together by a modified tensile strength in the material law. In this framework, the ice mélange is considered as one single fluid, where the icebergs are realised by particles.Using idealized test cases, we demonstrate that the proposed changes in the material law are crucial to represent icebergs with the viscous-plastic rheology. Similar to the viscous-plastic sea-ice model, the ice-mélange model is highly nonlinear. Solving the model at the resolution needed to represent the typical size of icebergs in ice mélange (< 300m) is therefore challenging. We show that the ice-mélange formulation can be approximated efficiently with a modified Newton's method. Overall, the simple extension of the viscous-plastic sea-ice model is a promising path towards the integration of ice mélange into climate models.
Satellite-driven model to upscale Irish CO2 Net Ecosystem Exchange (ICONEEx)
Authors: Habib Wahaj , Connolly John
Published: March 2024

Climate change poses a significant environmental challenge for humanity, and accurately predicting its intensity as well as its impact on terrestrial ecosystems is crucial. To achieve this, monitoring, modelling, and mapping greenhouse gas (GHG) exchanges between the biosphere and the atmosphere is essential. Monitoring is also important to achieve the European Union’s goal to achieve a balance between GHG emissions and removals by 2050 and maintain negative emissions thereafter. While in situ measurement techniques, such as the eddy covariance flux tower (ECFT), have been used for decades to measure ecosystem-level exchanges of carbon, such as Net Ecosystem Exchange (NEE) of CO2, their footprint is limited to only 1 km². To overcome this limitation, satellite remote sensing data has been used to upscale these measurements to regional and global scales, but previous work has relied on low-resolution remote sensing data, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor (at 250m or 500m spatial resolution). This study aims to use a combination of high-resolution remote sensing data and measurements from in situ ECFT data to model the NEE of CO2 across ~92% of Ireland's terrestrial area, covering major land covers such as wetlands (coastal and peatlands), grassland, and forestry. The model will integrate datasets from both ESA (Copernicus Sentinel-1 and 2) and NASA (MODIS PAR) with the light response curve parameters derived from the ECFT data in Ireland, to model NEE CO2 at a national scale. The results will be useful for monitoring, reporting, and verifying NEE across a range of ecosystems in Ireland. They can also be used to enhance National Inventory Reporting and national ambitions on climate, influence targeted policymaking, and verify land management decisions.
Significance of high-grade metamorphic events in the Tuareg Shield and its implication for evolution of the Columbia Supercontinent
Authors: Bosch Delphine , Bruguier Olivier , Caby Renaud , Monchal Vincent , Pinon Héloïse
Published: March 2024

Using innovative methodological developments applied to the geosciences, such as "split-stream" LASS-HR-MC-ICP-MS technique, we present new geochemical results focusing on high-grade granulite facies rocks from the Iforas Granulitic Unit (IGU, Hoggar Mountains, NE Mali). This unit represents a high grade metamorphic terrane that has been only poorly studied yet. The aim of this study is to understand how granulites provide information on crustal growth processes and, in the context of the IGU, to test whether the processes identified can be integrated into global geodynamic reconstructions during the Palaeoproterozoic. Granulites can contain various U-Pb datable minerals such as zircon, monazite, rutile or apatite. These minerals record, to varying degrees (influence of temperature and/or fluids, nature of the protolith), the events that the granulites have undergone. From a global point of view, the main results of this study show that the major events recorded within the IGU have affected this unit uniformly. Five major events were identified on the basis of the nine rocks studied in detail, and correspond respectively to the following periods: c. 2.06-1.99 Ga, c. 1.95-1.96 Ga, c. 1.86-1.90 Ga, c. 1.76 Ga and c. 1.70 Ga. Present results suggest that the basement is mostly formed by leptynite and orthogneiss of Late Rhyacian age at c. 2.05 Ga. This basement was affected by two major phases corresponding to two successive but distinct granulite facies events at c. 2.0 Ga and c. 1.90 Ga. The first high-grade event is followed by an exhumation event concomitant to erosional processes and sedimentary deposition. The second high-grade metamorphic event occurred at c. 1.90 Ga and is contemporaneous to gabbonoritic magma intrusion. A retrograde amphibolite/greenschist facies metamorphism followed at 1.76-1.78 Ga. This study also highlighted the influence of fluid phases in granulitic rocks and their potential importance in supercontinent break-up. The thermal evolution of the IGU ended with cooling until c. 1.7 Ga. Finally, the Pan-African event did not affect the U-Pb system of zircon, monazite and especially rutile and apatite in the granulitic rocks studied, suggesting that the IGU represents a preserved segment of Paleoproterozoic granulitic crust. 