bluuebunny/crossref_metadata_2025 huggingface dataset:
How much data do we need to assess future flood risk in data-scarce mega-cities?
Authors: Zwirglmaier Veronika , Garschagen Matthias
Published: March 2024

Flood risk in urban areas is rising due to climate change and urbanization. Rapidly developing megacities located in the Global South are oftentimes referred to as risk hotspots with a particularly strong rise in risk. Therefore, it is essential to adapt these cities to rising risks and to minimize negative impacts for society, economy and the environment. Scenarios and simulation are popular tools to assess future trajectories of risk and the effectiveness of potential adaptation strategies. Yet, while state of the art simulation approaches are well suited to assess quantifiable flood risk processes in data-rich cities of the Global North, they often cannot be applied in data-scarce urban contexts of the Global South. Nevertheless, it is important to inform adaptation processes in these megacities, not just with respect to infrastructural development but also in terms of social adaptation measures. Here we therefore analyse how much data is actually needed in order to develop valid simulations of future flood risk and potential adaptation strategies in mega-cities with limited data availability. We apply a novel approach linking Bayesian networks with parameterized urban structure types. Bayesian networks are well suited as they allow the consideration of various data types and they are able to handle missing data. Urban structure types are used to make estimates of parameters where no data is available. Thus, we manage to represent different patterns of flood hydrology, exposure values, social vulnerability etc. We use Mumbai as a case study. The Bayesian network is built based on process understanding. For parameter learning we used three levels of data availability and validate it against observations to evaluate how much data we need to get reasonable results. In the first level we use only open-source data and expert knowledge to learn the parameters. Within the second level we further incorporate data obtained during a structured household survey and within the third level we also include data we obtained from local authorities in Mumbai. Results show that the quantity of data in general is oftentimes not decisive for the quality of representing large scale flood risk in Mumbai. Rather it is important to consider all site-specific parameters which are forming flood risk even if they are just quantified by expert estimates.  We advocate for the exploration and implementation of adaptable and versatile approaches that enable the integration of both local insights and expert knowledge while moving away from models which are limited to measured data. These approaches would prove advantageous in conducting risk assessments within contexts where data availability is limited.
Investigating spatio-temporal salinity dynamics in coastal aquifers
Authors: Skibbe Nico , Günther Thomas , Schwalfenberg Kai , Meyer Rena , Reckhardt Anja , Greskowiak Janek , Massmann Gudrun , Müller-Petke Mike
Published: March 2024

Coastal aquifers build the transition zone of freshwater and saltwater. Hence, large salinity gradients are encountered in the subsurface below beaches and it is important to assess the salinity in a high resolution in order to understand coastal groundwater flow dynamics and consequently geochemical and microbial processes in subterranean estuaries. Within the project DynaDeep, we used both geophysical and hydrogeological methods to determine the bulk and fluid electrical conductivities (bulk/fluid EC) with the aim to convert the EC to salinity to monitor its temporal and spatial changes. This was done at a high-energy beach on the North Sea Island of Spiekeroog.Numerous EC techniques have been used to acquire a unique dataset since 2022, covering a 2D transect from the dune base to the low water line. The site was subject to strong topographic changes over the seasons. Among the methods applied, we used electrical resistivity tomography (ERT) to get access to 2D distributions every six weeks. Additionally, continuous monitoring was carried out using a saltwater monitoring system (SAMOS) with a vertical electrode chain down to a depth of 20 meters located at the high water line. Direct push (DP) data at various locations as well as fluid EC values from water samples gathered via DP give access to high resolution information. In three multilevel wells (four levels each at 6, 12, 18, and 24 meter depth below ground) we logged the fluid EC and temperature and took water samples on a regular basis.For an especially dense dataset between January and March 2023 we compared in detail the applied EC methods and found a general agreement in all of the gathered data after suitable calibration and temperature correction. We furthermore derived a formation factor model for the conversion to salinity.Finally, we a combined inversion of the ERT data with the additional data aiming for fluid EC directly under the assumption of this temporally fixed formation factor model. In contrast to standard inversion techniques, this allowed for a naturally occurring smooth transition of salinities over the different geological units, which was critical when analyzing the spatial and temporal changes.
Extreme heat hazard in the urban areas of Romania in a changing climate
Authors: Micu Dana Magdalena , Cheval Sorin , Dumitrescu Alexandru , Smău Raluca , Amihăesei Vlad
Published: March 2024

Cities emerge as particularly vulnerable environments to climate extremes, exacerbated by the observed climate change These environments are human heat stress hotspots due to the amplified contribution of the urban heat island effect and joint action of extreme weather events  The study aims to detect and quantify the changing signals in the combined heat hazard (CHH), associated with concurrent hot days (HD - maximum temperature above 30˚C) and nights (HN - minimum temperature above 20˚C) in 40 large cities of Romania (>100,000 inhabitants), including the capital city. CHH is highly relevant in the assessment of heat-health risk through its inhibiting influence on the recovery from daytime heat stress and exacerbation of the extreme heat impact through sleep deprivation at night. We use homogenized climate observations (1961-2021) and ensemble EUROCORDEX simulations (RCP4.5, RCP8.5), for the near future (2021-2050) and far-future (2071-2100), to analyse the temporal changes in two CHH metrics: CHHf - frequency (number of co-occurrences of HD and HN), and CHHl - length (the maximum number of consecutive co-occurrences of HD and HN). The results show consistent geographical patterns in the change signals of the CHH metrics, over both present and future climates. The strongest change signals in CHH, as well as the most pronounced projected changes, especially in the far-future under RCP8.5 are found in the cities located in the southern, eastern and western lowlands of the country (i.e., Bucharest, Giurgiu, Iasi, Timisoara).These cities show strong increases in both frequency and duration of CHH, almost doubling by 2050 and even more by 2100. These results are suggestive of a consistent amplification and northward expansion of the areas prone to CHH (i.e., cities located in the central and northern parts of the country).The correlations between the temporal variability of CHH and the cooling degree days provide an improved understanding of the relationship between energy consumption and prevailing climatic conditions during the extreme heat episodes in urban areas, under both present and future climate warming. The study provides valuable insights into the urban heat hazard and provides science-based evidence that could be used for assessing the heat-health risk at the city scale and optimisation of decision-making for climate change adaptation. This study has been funded by the project Synergies between Urban Heat Island and Heat Wave Risks in Romania: Climate Change Challenges and Adaptation Options (SynUHI) PN-III- P4-PCE-2021-1695  
Global seasonality of small-scale livelihood fire
Authors: Kasoar Matthew , Smith Cathy , Perkins Ol , Millington James , Mistry Jayalaxshmi
Published: March 2024

Landscape fires are increasingly represented in dynamic global vegetation models to understand impacts on carbon emissions and climate. Deliberate human fire use and management influence landscape fire characteristics, varying in space and time depending on social, economic, and ecological factors. For example, fire is used variously in rural livelihoods involving e.g., agriculture, hunting, gathering, and for other cultural practices, often depending on the time of year. Yet existing global fire models typically represent human fire use as a constant function of gridded datasets such as population density or gross domestic product.Recently, initiatives have begun to draw together available data on global fire use from across multiple disciplines and disparate sources into coherent databases. We draw on information from one of these databases, the Livelihood Fire Database (LIFE), which includes case studies in 587 locations worldwide, to assess the availability of data on seasonality of anthropogenic fires associated with small-scale rural livelihoods. By defining seasonal cycles relative to the local variation of precipitation and evapotranspiration at each case study location, we look for patterns in the spatiotemporal nature of anthropogenic fires associated with different fire-use purposes - such as clearing vegetation for agriculture, maintaining pasture for livestock, or driving game when hunting - and consider the potential for this analysis to inform fire models.For many fire types, especially those related to hunting, gathering, human wellbeing, and social signalling, there are limited quantitative data available, but it is possible to draw qualitative insights from case studies. Where quantitative data are available, we find some correspondence between fire seasonality and the intended fire-use purpose, suggesting that distinguishing between distinct fire-use purposes could improve the representation of human fire use in fire models, and consequently the seasonal cycle of fire emissions. Case studies demonstrate that environmental and social conditions drive variation in fire use for the same purpose, reiterating that a wide range of factors influence human behaviour and that assumptions of uniform drivers of anthropogenic fire may be misleading. Many of the fires now being revealed in global burned area data by new fine-scale remote sensing products are likely human-set; continued collection, collation, and analyses of data on human fire use globally is important to ensure appropriate anthropogenic representation in fire models.
Benefits of initializing equatorial waves on extratropical forecasts
Authors: Wang Chen , Žagar Nedjeljka , Vasylkevych Sergiy
Published: March 2024

Large initial uncertainties in the tropics are believed to compromise medium- and extended-range extratropical forecasts. A more reliable analysis of tropical Rossby and non-Rossby waves requires more tropical observations and improved data assimilation schemes. Wind observations are known to be more valuable than mass observations in the tropics, but it is not well-understood how different types of observations affect the accuracy of equatorial wave analysis and influence extratropical predictability. 

We investigate these questions by assimilating only wind or mass observations within the tropics using a perfect-model framework and a global model based on shallow-water equations and 3D-Var data assimilation. The mass-wind relationships of equatorial waves are built into the background-error covariance matrix with Rossby and non-Rossby waves as control variables in 3D-Var and prognostic variables in the forecast model.  Results demonstrate that wind observations are more efficient at reducing both tropical and extratropical forecast errors than mass observations. Adding mass-wind coupling further improves extratropical forecasts and it is especially beneficial for mass observations.Forecast benefits are quantified along latitude circles in terms of scales. A more accurate analysis of the equatorial Rossby waves is found to be the key for the propagation of observation impact from the tropics to midlatitudes. 

 
Can Norway save the European Union's hydrogen ambition for 2030?
Authors: Viole Isabelle , van Greevenbroek Koen , Cheng Claudia
Published: March 2024

How competitive can Norway – one of the main natural gas suppliers to the European Union (EU) – be at exporting hydrogen to the EU? We explore three scenarios in which Norway’s hydrogen export market may develop: A Business-as-usual, B Moderate Onshore, C Accelerated Offshore. Applying a sector-coupled energy system model, we examine the economic, social and environmental implications of each scenario. Given a variety of cost assumptions in shipping, CCS and electrolysis, the pathways result in wide ranges of potential costs of hydrogen from 2-7€/kg hydrogen. In the cheaper scenarios A and B we identify roadblocks in social acceptance in either the expansion of onshore wind turbines, or in resistance against CCS technologies. Environmental trade-offs in land use change follow suit. Any of the pathways discussed requires fast investments in the necessary infrastructure paired with measures to increase social acceptance and to alleviate environmental impacts. Nonetheless, we show that Norway could supply a significant share of the EU’s hydrogen demand in the near-term future.
Anthropogenic intensification of climate extremes has altered vertebrate species abundance
Authors: Kotz Maximilian , Amano Tatsuya , Watson James , Wenz Leonie
Published: March 2024

Assessments of the effects of climate change on terrestrial biodiversity typically rely on species distribution models [1] which neither exploit data on historical abundance changes nor consider the potentially important role of climate extremes. Here, we combine global data on the abundance of vertebrate species populations [2] with metrics of exposure to local climate conditions to demonstrate that historical warming and increased exposure to heat, heavy precipitation extremes and drought have had significant impacts on abundance, even after controlling for changing human pressures. Fixed-effects models reveal plausibly causal impacts which vary by species class and habitat system, as well as by latitude and the extent of human pressure. Results indicate that warming and intensified heat extremes have negative impacts at low latitudes for freshwater fish and terrestrial birds. By contrast, warming can bring benefits to freshwater birds and terrestrial mammals. Heavy precipitation extremes and drought appear to have had mainly negative impacts on abundance across species’ and habitats. We then combine these empirical results with estimates of the changes in climate conditions and extremes which are attributable to anthropogenic influence, using an established impact-attribution framework [3]. This approach reveals that anthropogenic climate change has caused considerable alterations to the abundance of terrestrial life, for example by reducing the abundance of terrestrial birds and freshwater fish by up to 40% at low latitudes. [1] Thomas, Chris D., et al. "Extinction risk from climate change." Nature 427.6970 (2004): 145-148. [2] Loh, Jonathan, et al. "The Living Planet Index: using species population time series to track trends in biodiversity." Philosophical Transactions of the Royal Society B: Biological Sciences 360.1454 (2005): 289-295. [3] Mengel, Matthias, et al. "ATTRICI v1. 1–counterfactual climate for impact attribution." Geoscientific Model Development 14.8 (2021): 5269-5284.
Tracking climate-driven changes of water masses and fluxes in polar regions using acoustics. 
Authors: Ladroit Yoann , Seabrook Sarah , Weidner Elisabeth , Loranger Scott
Published: March 2024

Climate warming increases glacial melt in polar environments, altering the pressure on extensive networks of nutrient-rich fluids and climate-changing gases below the surface and connecting from land to sea.The increased transport of these fluids and gases to the marine environment has been observed in polar regions, but such processes remain difficult to detect and monitor. To that purpose, water-column acoustic measurements have proven extremely effective, allowing the detection, identification and quantification of fine changes in oceanography, stratified turbulence and mixing at large scales.Here, we highlight recent visualisations of such anomalous acoustic features in polar regions collected on broadband split-beam systems ranging from 12 to 200 kHz. This allowed us to perform fine analysis of water masses and near-seafloor features. By coupling these acoustic with profiles of chemical properties of the water column and multi-disciplinary datasets, we interpret those, including meltwater, subglacial plumes, and seafloor seeps.These observations show the potential of using water-column acoustics in the context of long-term monitoring changes in those regions, with the potential to capture short and long-term variations in sensitive areas to better understand those rapidly changing environments.
Explainable machine learning to uncover hydrogen diffusion mechanism in clinopyroxene
Authors: Li Anzhou , Wu Sensen , Chen Huan , Du Zhenhong , Xia Qunke
Published: March 2024

Estimating the water content of mantle-derived magma using clinopyroxene (cpx) phenocrysts serves as a valuable constraint on the water budget in deep Earth. Intricate magma processes and the high hydrogen diffusion rate necessitate careful evaluations of whether the water content in cpx preserves its original state. Machine learning (ML) has been utilized to develop a classifier for judging hydrogen diffusion in cpx. Never- theless, the opaqueness and complexity of most ML models hinder a clear understanding of their classification principles. To elucidate the mechanistic basis of the ML model, the Shapley theory is integrated to determine the contributions of major elements of cpx as features in a linear additive manner. This study achieves superior classification performance using an extreme gradient boosting model and innovatively presents a quantitative evaluation of feature importance at the sample level for each observation. The results indicate that Na plays a predominant role in the diffusion process surpassing other major elements and its associated hydrogen can easily diffuse out of cpx. Our model also identifies various hydrogen association modes in different elemental com- positions and puts constraints on the properties of incorporated hydrogen with non-lattice forming elements in cpx. The findings demonstrate that the application of explainable ML methods in mineralogy holds significant potential for advancing the comprehension of geological phenomena.
Comprehensive Hybrid Approach for LULC classification using GEE-API and ML
Authors: Shivamurthy Vinay , Pawale Satyam , Chandrashekar Shetty Yash , Bhat Sudarshan T
Published: March 2024

This research offers a new hybrid strategy for Land Use and Land Cover (LULC) classification that overcomes the constraints of k-Nearest Neighbors (KNN) through the use of Support Vector Machines (SVM). Our study, that makes use of the Google Earth Engine (GEE) API in conjunction with Colab, focuses on custom preprocessing that enhances data richness and context. We perform custom preprocessing, including feature scaling and data fusion of spatial, temporal, spectral, and radiometric dimensions, in order to enhance the data obtained from satellite imagery, incorporating spatial and temporal materials made of composites spectral fusion, and radiometric calibration. The approach we employ uses Rasterio for satellite images and Shapely for vector data. Geopandas encourages the smooth management of data related to geography implementing the GeoJSON format, strengthening compatibility with the Google Earth Engine, whereas Digital Elevation Models (DEMs) and Landgren software enrich LULC analysis.The hybrid approach eliminates k-Nearest Neighbours (KNN) inefficiencies through the incorporation of Support Vector Machines (SVMs). The drawbacks of KNN, including computational intensity, sensitivity to irrelevant features, susceptibility to noise, and the need for optimal hyperparameter selection, are mitigated by leveraging SVM's strengths. SVM, which has been appreciated for its information technology efficiency, ability to withstand noise and outliers, and relevance-driven decision boundary learning, is a successful complement to KNN. The combination approach encompasses pre-processing with SVM in order to enhance data quality, learning the decision boundary with SVM, and selectively applying KNN in localized regions of interest. The perpetual enhancement of the hybrid model via validation enables a balanced use of SVM's robustness and KNN's flexibility. The proposed hybrid technique is an intriguing option that could enhance the efficiency and performance of LULC classification tasks, catering to the specific characteristics of the dataset and analysis goals.Libraries for Python (Folium, Matplotlib, Seaborn) enable integration, allowing users to produce distinctive visualizations adapted to the specifications of remote sensing products designed for specific applications. Folium is used for producing interactive geographical maps, Matplotlib delivers configurable static plots, and Seaborn focuses on statistical data visualization. This combination facilitates complete investigation of complicated satellite picture collections using a variety of viewing approaches.Overall, this hybrid methods, aided by improved preprocessing, data fusion, and visualization tools, presents a promising strategy for improving the efficiency and effectiveness of LULC classification while adapting to particular characteristics of the dataset and able to analyze objectives. Keywords: LULC, Hybrid classification, SVM, KNN, Data fusion, Geospatial analysis, visualization
Monitoring of NO2 emissions from space using an aerosol chemistry transport model and a non-linear optimization system
Authors: Kudupaje Laxmana Yathin , Lauvaux Thomas , Ciais Philippe , Kumar Pramod , Cheliotis Ioannis , Lian Jinghui , Rey-Pommier Anthony
Published: March 2024

Quantification of NO2 from different sectors of economic activity remains critical to monitor air pollutants with the rapid development of infrastructures and the rapid industrialization of emerging economies. This study aims to estimate NO2 emissions using satellite NO2 measurements from TROPOMI from different activity sectors over northern Egypt using a full-chemistry atmospheric transport model (WRF-Chem, including aerosol chemistry) and a non-linear Bayesian method. Our top-down approach was carried out for two months, January and July 2022, to analyse the seasonal variations in NO2 emissions over the studied region. The major source of uncertainties in our top-down emission estimates is due to missing sources in the prior emissions (fossil fuel inventory),  lacking more frequent updates and sub-monthly information. We also explore other sources of errors, such as the level of uncertainty used for calculating error covariance factors, the estimation of biogenic emissions, the selection of a quality assurance filter of TROPOMI NO2 and the use of regularization parameters. Non-linearities are included in our optimization algorithm by performing sensitivity experiments with the direct chemistry model (error propagation) to establish daily relationships between NO2 fluxes and concentrations. Our Bayesian inversion produces optimized values over sub-regions of Egypt and for specific sectors. We defined several subregions and assessed the regional NO2 emissions. The total estimated NO2 emissions from the studied region are about 45 Kt for the month of January 2022 and 32 Kt for the month of July 2022. The results were compared to a previous study using the flux-divergence method, showing a fair agreement for the month of winter (R2=0.67) but disagree in terms of magnitude during summer. We discuss the potential causes for the observed mismatch, which is possibly due to the extreme climate of the region, the availability of satellite observations, and large seasonal variations in the lifetime of NO2.
Hydro-ecologically based operation of run-of-river reservoirs for effective sediment management and energy production
Authors: Lebar Klaudija , Rusjan Simon , Kuzmanić Tamara , Rak Gašper , Kryžanowski Andrej , Mikoš Matjaž , Vidmar Andrej , Klun Mateja
Published: March 2024

Here we present the main activities of an ongoing project aiming at effective sediment management in run-of-river reservoirs. Climate change is reflected mainly in a gradual increase of temperatures, which result in longer dry periods, frequently followed by heavy rainfalls, causing increased intensity and occurrence of floods and erosion processes. The changed hydrological conditions require proper adjustments of water management practices. Construction of water reservoirs, used for hydropower generation, offers the possibility to adapt to changed hydrological conditions, especially in terms of multipurpose water use. However, hydropower plant reservoirs disrupt the dynamics of sediment transport and may have a negative impact on the riverine environment and water organisms.  Sediment management under changing hydrological conditions is a challenge of global proportions, existing sediment management practices in water reservoirs worldwide are mostly unsustainable and lead to the loss of the multifunctional role of such facilities, such as loss of water availability for different uses and reduction of the riparian space, which worsen habitat conditions and self-cleaning capacity of the water body. Advanced, holistic sediment management strategy, which includes all elements of the natural sedimentation cycle and environmental concerns related to potential sediment pollution offers sustainable management solutions. In the presented project, a novel, active river sediment management strategy in hydropower reservoirs of the HPPs on the lower Sava, where 5 dams were built in a cascading system between 1993 and 2017, under changing hydrological conditions, will be developed. The strategy will assure to the highest possible extent of the restoration of natural dynamics of sediment transport, also considering the environmental status of sediments. To establish the presented management strategy, a holistic, interdisciplinary approach, which includes a detailed analysis of hydraulic conditions in the reservoirs and associated sedimentation processes, as well as analysis of pollutants trapped in the deposited sediment layers, will be applied. Based on the gathered data, it will be possible to further define potential measures related to the removal of sediments and the alternatives of their disposal or re-use. The developed sediment management plan for the chain of HPP on the lower Sava River will contribute to the restoration of sediment connectivity along the river course and the improvement of the river channel's ecological role. The authors acknowledge that the research is financially supported by the Slovenian Research and Innovation Agency, research core funding No. P2-0180, and research projects No. L7-50097 and by the HESS d. o. o. Hidroelektrarne na Spodnji Savi.
Reflecting on the role of science advice in theclimate crisis: The importance ofscience-society-policy interfaces
Authors: Voelker Georg Sebastian , Wirth Luisa
Published: March 2024

Anthropogenic climate change is to date one of the most pressing and challenging issues for our societies and their global interactions and dynamics. Although the material and societal causes and effects of climate change are well understood from different branches and fields of science such as natural and social sciences and the humanities, the implementation of mitigation and adaptation measures generally falls behind the self-set political goals. So why does the knowledge-action gap exist and how can it be addressed from the science community?In Germany, the recently increasing political awareness among politicians and in the society as a whole, is generally followed by progressing climate legislation. However, some recent climate-related policy proposals on the German federal level were associated with a large amount of misinformation, public mistrust, and a largely uninformed public and political debate. On the local level we observe a similar increase in political dissent on climate policy in the city of Frankfurt (Main).Aiming to inform societal processes and enable the necessary transformation to net carbon neutrality, scientists are more and more invested in both direct communication with a broader audience and direct interaction with politicians and policy-makers in science-society and science-policy interfaces, respectively. Based on our experience with both mentioned information pathways in the role of the honest broker, we argue that there is an additional need for integrated knowledge brokering in science-society-policy interactions including a larger number of stakeholders. Finally, we want to challenge the idea of science only brokering knowledge to individual stakeholders and put forward the aim of science not only informing but mediating the debate between the different agents. We are reshaping the role of scientists from being an informant to taking an active role in societal change and the debate about it.
Exploring climate-biodiversity interactions in observational data and models
Authors: Sieber Petra , Schwaab Jonas , Karger Dirk , Seneviratne Sonia ,   FeedBaCks consortium
Published: March 2024

Climate change and biodiversity loss are increasingly considered jointly, particularly to find optimal solutions for both crises and to avoid negative side-effects and feedbacks. Much research has been devoted to predicting the effects of climatic changes on the distribution of species, but the consequences of biodiversity changes for the climate system are less understood. For instance, what are the main aspects (species richness, functional diversity, land cover patchiness) and mechanisms through which biodiversity interacts with the climate? Do landscapes with different levels of diversity contribute differently to climate regulation or feedbacks? How do human choices such as nature conservation or natural resources production affect the climate? To address these questions, we combine observational and modelling approaches in a collaborative effort of ecologists and climate scientists.First, we present how ecosystem diversity affects forests’ climate response (indicated by interannual variability in summer NDVI) and climate effect (indicated by interannual variability in summer LST), using 20 years (2003-2022) of remote sensing data at 1 km resolution over Europe. We consider different diversity levels (taxonomic, functional, structural) together with various ecosystem, topography, soil, and climate predictors in a multiple linear regression with Ridge regularisation. This approach allows isolating the effects of specific biodiversity aspects (e.g. tree species richness, forest edge density), functional properties (e.g. leaf type, leaf traits), and structure (e.g. canopy height, tree cover density), and determining the sign and magnitude of their contribution. We show which aspects and scales of biodiversity are relevant for ecosystem stability and climate regulation, respectively, and classify forests into response and effect types that could be considered in coupled biosphere-atmosphere models.Second, we discuss how biodiversity aspects can be integrated into the coupled biosphere-atmosphere regional climate model COSMO-CLM2 to quantify their effects on land-atmosphere interactions and feedbacks over Europe. We demonstrate one approach, utilising future land cover scenarios derived from the Nature Futures Framework that represent different value perspectives on nature (intrinsic, instrumental, and relational), habitat types from EUNIS (European Nature Information System), and species abundances from EVA (European Vegetation Archive). Our results show temperature differences of up to several degrees locally, with enhanced temperature sensitivities under hot and dry conditions. Such findings can help identify synergies between biodiversity conservation, climate change mitigation, and adaptation, and support the development of effective policy solutions.Finally, this presentation will provide perspectives for research at the interface of biodiversity and climate change.
Multi-model seasonal forecasting service for meteorological droughts
Authors: Macian-Sorribes Hector , Avila-Velasquez Dariana , Pulido-Velazquez Manuel
Published: March 2024

Drought indicators have been proven to be powerful tools to improve drought awareness and decision-making, being a key information source for water resource management in many countries and regions over the world. However, the integration of meteorological drought indicators and seasonal forecasts is not fully explored yet, since most of the drought prediction and early warning services (e.g. European Drought Observatory, Climate Prediction Center) offer limited information on drought forecasting at the seasonal scale.This contribution presents a multi-model seasonal forecasting service of selected meteorological drought indicators, developed in the context of the WATER4CAST project, for the Jucar River Basin (Spain). This service offers seasonal forecasts (up to 6-7 months in advance) of SPI and SPEI indicators with time aggregations of 6, 12, 18 and 24 months. Input meteorological forecasts to compute them are obtained from the Copernicus Climate Change Service (C3S) for the ECMWF-SEAS5, MétéoFrance-System8, DWD-GCFS21 and CMCC-SPSv35 forecasting systems. These forecasts are post-processed against ERA5 reference data to ensure they are tailored to the climatic patterns of the Jucar River Basin, employing artificial intelligence algorithms (fuzzy logic) trained for the 1995-2014 period. Reference evapotranspiration for the calculation of SPEI indicators is estimated using the Hargreaves method. Once meteorological forecasts are post-processed and upscaled to the monthly scale, aggregated forecasts required to compute SPI and SPEI are made by combining them with past data from ERA5 (e.g. an SPI12 forecast for the next month would require 12-month aggregated precipitation forecasts made up by combining precipitation predictions for the next month with past precipitation records for the last 11 months). Finally, aggregated forecasts of precipitation (for SPI) and precipitation less reference evapotranspiration (for SPEI) are transformed into SPI and SPEI by standardizing them using the gamma (SPI) and the loglogistic (SPEI) probability functions, fitted for each ERA5 point using reference data for the 1973-2022 period. All the calculation process is coded in Python, and it is automatically launched as soon as new seasonal forecasts are available in the C3S.The resulting service offers seasonal forecasts at the monthly scale, from 1 to 6/7 months in advance (depending on the forecasting system), of SPI and SPEI for the aggregations given at each point of the ERA5 grid overlapping the Jucar River Basin. These forecasts are uploaded into a web platform (https://water4cast-app.upv.es/) that offers information both for a given point (in with the ensemble of SPI and SPEI forecast is displayed using box-whisker plots) and with a general picture (depicting the probability of being in a dry (index
Impact of oxygen fugacity on atmospheric spectra of hot rocky exoplanets
Authors: Seidler Fabian , Sossi Paolo
Published: March 2024

An essential aspect of understanding how rocky (exo-)planets form and evolve is unravelling their bulk composition. While mass and radius alone do not yield precise estimations of exoplanet compositions due to the degeneracy of interior models that can fit such observations, abundances of refractory elements in their host stars are often used as proxies to constrain terrestrial planet composition. However, oxygen, whose relative abundance governs how iron (and other siderophile elements) partition between the mantle and core, is both a volatile and a refractory element, preventing a straightforward determination from stellar abundances. Therefore, we require independent means to estimate exoplanet oxidation states through observations of their atmospheres and/or surfaces. To do so, observations of ultra-hot rocky exoplanets would be ideal, owing to the fact that their atmospheres are expected to be in thermodynamic equilibrium with their surfaces. To interpret such observations, we investigate the impact of oxygen fugacity (fO2), temperature (T) and composition on the formation of atmospheres on ultra-hot rocky exoplanets. Our approach treats melt vaporisation and atmospheric gas speciation thermodynamically self-consistently, before using radiative transfer simulations to predict atmospheric structure and emission spectra. We find that compositional effects are minor within the range of plausible rocky compositions. However, the emission spectrum is particularly sensitive to fO2, owing to its influence on the partial pressures of gas species in equilibrium with the silicate mantle. This effect is exacerbated when the atmosphere contains a volatile component such as H2O, CO2 or N2. We show that observations made with the James Webb Space Telescope (JWST) hold the potential to distinguish between fO2 scenarios, thereby paving the way for the first independent constraints on the chemistry of rocky exoplanets.
The bioleaching of metals from organic-rich black shale by Pseudomonas fluorescens
Authors: Wolszczak Mateusz , Potysz Anna , Lis Grzegorz
Published: March 2024

Biohydrometallurgy is known as one of techniques of beneficiation of metal ores, utilizing microorganism activity to enhance the extraction of metal ions from ore minerals. The method is widely known from its economic and environmental advantages in comparison to other beneficiation methods, i.e. pyrometallurgy. The development of biohydrometallurgy applications for the mining industry has continued since the eighties when several bioleach operations for low-grade copper ores and refractory gold concentrates have been commissioned. Although significant extraction rate, biological-induced leaching does not constitute main processing technique due to economic reasons, what drive researchers to searching novel ways to enhance the efficiency of metal recovery. This research came with the idea of improving the efficiency of metal bioleaching by presence of dispersed organic matter naturally occurring in some rocks. Main hypothesis of the research assumes using dispersed organic matter as a source of organic carbon by heterotrophic bacteria that could further enhance dissolution of ore minerals. The idea came from both facts: consumption and metabolic utilization of dispersed organic matter by heterotrophic microorganisms and influence of consumed organic compounds on microbial activity e.g. secretion of siderophores (metal chelating compounds, crucial for solubilization metal ions and thus acceleration the metal leaching). The examined rock is metalliferous-bearing shale enriched in dispersed organic matter (with average TOC parameter from few to even 30 wt.%). Two shale samples different in their metal and organic matter quantity were chosen for testing the hypothesis. The potential of black shale for bioleaching was examined through series of incubation experiments. Different experiment conditions were applied, involving both autotrophic (Acidithiobacillus thiooxidans) and heterotrophic (Pseudomonas fluorescens) bacteria and different medium compositions (with presence and absence of organic nutrient in particular). The incubation experiment took place in a shaker incubator at a controlled temperatures for a period of five weeks. After the incubation experiment the leachates were collected and analyzed for the concentrations of eight metals: copper, lead, zinc, molybdenum, arsenic, nickel, cobalt and vanadium. The metal recovery percent features variation depending on shale sample, specific metal, and incubation condition. The highest metal recovery was achieved for heterotrophic bacterium in case of copper and molybdenum and for autotrophic one in case of arsenic, while rest of metals showed insignificant recovery. Lack of organic nutrients weakened the activity of P. fluorescens compared to bacterium supplied with organic nutrient, however metal leaching was still maintained.
Integrating Geostationary Satellite Data for Advanced Air Quality Modeling: Evaluating GEMS NRT Observations within the ECMWF’s IFS system for the HE CAMEO Project
Authors: Paschalidi Zoi , Inness Antje , Flemming Johannes , Ribas Roberto
Published: March 2024

The advent of new satellite technologies has ushered in a promising era for trace gas and aerosol observations, offering advanced data quality and temporal resolution. Low Earth Orbit (LEO) satellites have markedly heightened our ability to generate accurate air quality forecasts. The Geo-Ring, comprising the geostationary satellites of GEMS over East Asia, TEMPO over North America and the imminent Copernicus Sentinel-4 over Europe, promises to unlock unprecedented possibilities in atmospheric monitoring.The Horizon Europe CAMEO (CAMS EvOlution) project coordinated by the European Centre for Medium-Range Weather Forecasts (ECMWF) is dedicated to upgrading the quality and efficiency of the Copernicus Atmosphere Monitoring Service (CAMS). By integrating new satellite retrievals of atmospheric composition into the Integrated Forecast System (IFS), CAMEO aims to augment the data assimilation and inversion capabilities of the global and regional CAMS production system, thereby improving the quality of atmospheric composition analyses and forecasts.During the initial year of CAMEO, the IFS was prepared to assimilate geostationary data alongside polar orbiting retrievals. This integration aims to optimise air quality modeling and provide a more accurate depiction of the diurnal cycle of O3, a pivotal component of atmospheric composition. The assimilation of a substantial volume of geostationary air quality data into the CAMS system poses challenges, necessitating the further development of the super observation software. Following updates to the IFS model and additional technical improvements, experiments were conducted using IFS version CY48R1 and the more recent CY49R1 to monitor and evaluate the Near Real-Time v.2. GEMS NO2 and O3 observations from April to December 2023.Preliminary results reveal a notable positive bias in the GEMS NO2 tropospheric column data, consistently exceeding the model's first-guess and TROPOMI satellite observations. In urban and populated areas like Beijing, while similarities in structures and patterns of NO2 data between GEMS and TROPOMI are identified, significant discrepancies persist. The GEMS NO2 data also exhibit noticeable noise attributed to factors such as stratospheric correction, cloud treatment, and unspecified measurement errors. In the case of O3, GEMS demonstrates better performance than NO2 when compared to TROPOMI and the model's first guess, with no significant bias identified. Nonetheless, the current data version features large O3 gaps due to quality control measures. These findings offer crucial insights for refining the assimilation of geostationary air quality data, thereby enhancing forecasting and monitoring of atmospheric composition in CAMS. Upcoming releases, such as v.3. GEMS data, are anticipated to address the identified data issues, further amending the usefulness of the GEMS data for air quality applications. 
Long-term Evaluation of HPGe Calibration for Environmental Radioactivity Assessment Using IAEA-U and IAEA-Th Sources
Authors: Siqueira Nascimento Debora , Ciolini Riccardo , Chierici Andrea , Chiappini Stefano , d'Errico Francesco , Chiappini Massimo
Published: March 2024

The investigation of the dynamics between environmental radioactivity and its implications for human health stands as a fundamental pursuit in contemporary scientific research. Employing the Gamma Spectrometry technique, particularly utilizing High Purity Germanium (HPGe) detectors, emerges as a pivotal methodology to study environmental radioactivity with precision. The veracity and dependability of these analyses hinge upon the scrupulous and precise energy and efficiency calibration of the HPGe system. Within this framework,  we used calibrated IAEA-U and IAEA-Th sources, thereby not only ensuring measurement accuracy but also establishing a robust foundation for comprehensive evaluation of radioactivity levels. Our findings illuminate a comprehensive understanding of the energy and efficiency calibration of the HPGe detector, exemplified by linear relationships in the energy calibration curves for both IAEA-U and IAEA-Th sources, manifesting high correlation coefficients (R² > 0.99). Essential for translating count rates to activity, the efficiency calibration consistently yielded low errors, with the maximum observed efficiency error being less than 4% for both sources, significantly below the recommended by standard rules. This study affirms the reliability and stability of our calibration methods through repeatability assessments over four years. Looking forward, the calibrated HPGe systems are prepared to assume a central role in the spectral analysis of different Italian terrains. Application of these calibrated detectors to Italian soil aims to discern and quantify the presence of radionuclides, thereby contributing into the radioprotection of the region. This prospective dimension underscores the practical application and broader implications of our calibrated systems in addressing environmental and health-related concerns.
Latest news about the auroral emission polarisation
Authors: Cessateur Gaël , Bosse Léo , Lamy Hervé , Lilensten Jean , Barthelemy Mathieu , Johnsen Magnar G.
Published: March 2024

We review the last advances in the study of upper atmospheric emissions polarisation. Since 2008, observations and modeling initiatives aimed at detecting and understanding the auroral emission polarisation. In recent years, this field saw major advances, which confirm the ionospheric origin of the polarisation. Polarisation has been observed in all four main auroral visible emissions lines (the red (630 nm), green (557.7 nm), blue (427.8) and purple (391.4 nm)), in several geomagnetic and auroral activity levels and has been confirmed for the N2+ lines through laboratory experiments. However, the origin of this polarisation is still debated. Several points show that it cannot be due to atmospheric scattering, and must originate from ionosphere. The link between the polarisation state of the emission and the local ionospheric conditions is still uncertain and raises a number of questions, such as: Can ground based measurements of the polarisation with light instruments track ionospheric currents? What is the origin of the green line polarisation?Our international collaboration gathers several instruments dedicated to the observations of the auroral emission polarisation, mainly located at the Skibotn observatory in Norway. The CRU series instruments, which are spectro-photo polarimeters able to measure faint polarized signals in a 2° FOV, are coupled with PLIP, for Polar Lights Imaging Polarimeter, able to measure polarization of the three main auroral emissions on a large FOV (~44° × 30°) on the sky. Some results will be presented from our last observation campaigns in Skibotn, Norway. Combining the CRU instruments with the PLIP imager opens a new chapter of investigation.