bluuebunny/crossref_metadata_2025 huggingface dataset:
CCS Reservoir Characterisation using Carbon Quantum Dots
Authors: Glover Paul
Published: February 2023

Efficient use of new CCS resources depends critically on their characterisation. This is as true for CCS reservoirs that are deep aquifers or reservoirs that have previously been exploited as oil or gas reservoirs. Conventional pre-existing or newly commissioned reservoir characterization methodologies, such as well logs, 3D and 4D seismic reflection and cross-well electromagnetic imaging are limited in their scope and resolution. For CCS, the  crucial characterisation is that of the connectivity of the pore network. Carbon quantum dots (CQDs) are inert carbon nano-particles less than 10 nm in diameter. They can be made easily from environmentally-friendly stock materials and remain stable in aqueous solution no matter the pH or salinity, unlike conventional nanoparticles. In fluorescence spectroscopy CQDs demonstrate a strong absorption in the UV region with peaks at 228 nm and 278 nm. Their fluorescence spectra occupy the visible spectrum and are related to the stimulating frequency. These optical properties allow the number of particles to be ascertained easily and their small size allows them to be pervasive in the porous medium. Consequently, CQDs are ideal for use as a conservative tracer. Core and bead–pack tests have shown that almost 100% of the injected CQDs can be recovered from the porous medium indicating that there would be no damage to the CCS resource by their use. Breakthrough curves (BTCs) can be used to calculate the porosity and connectivity of water saturated rocks and the water saturation and connectivity of rocks from previously exploited hydrocarbon reservoirs at temperatures up to 80oC. Indeed it is possible that CQDs could be used to monitor quantitatively the emplacement of CO2 along the injection path. Although these CQDs have an attenuated performance in carbonate rocks, surface coatings are expected to resolve this question. Surface functionalisation will also allow the properties of the reservoir, such as temperature to be measured by altering the frequency of the emerging CQDs.
Projection of future rainfall erosivity over China under global warming
Authors: Wang Wenting , Yin Shuiqing , He Zeng , Chen Deliang , Wang Hao , Klik Andreas
Published: February 2023

Five CMIP6 models were selected to project changes in rainfall erosivity of China for two future periods (the near-term in 2041-2065, the long-term in 2076-2100) under SSP1-RCP2.6 and SSP5-RCP8.5 scenarios. Models’ capacity in estimating two erosivity indices, annual average rainfall erosivity (R-factor) and the storm erosivity at 10-year return level (10-year storm EI) were evaluated by comparing the model derived indices for the historical period with the state-of-the-art reference erosivity maps of China interpolated with hourly observations. Results show that GFDL-ESM4, IPSL-CM6A-LR, and UKESM1-0-LL outperform the other two models with higher NSEs and better spatial correlation, especially in the water erosion regions. R-factor and 10-year storm EI estimated using MMEs (the arithmetic means of the aforementioned three models) for the historical period are generally underestimated, and the median biases are 0.80 and 0.66, respectively. Biases for each grid were determined as the bias-correction factors for future erosivity projection. Generally, most areas in eastern and central China are expected to experience larger rainfall erosivity. Under SSP1-RCP2.6 and SSP5-RCP8.5 scenarios, R-factor over mainland China is projected to increase by 18.9% and 19.8% for the near-term and 26.0% and 46.5% for the long-term, respectively; and 10-year storm EI is projected to increase by 14.2% and 17.4% for the near-term, and 14.9% and 45.0% for the long-term, respectively. The projected increases in rainfall erosivity are mainly due to the increasing probability of extreme precipitation. This implies that soil and water conservation measures in China need to be further strengthened to meet the challenges brought by the increasing number and magnitude of extreme events in the context of global warming.
Role of atmospheric moisture sources and pathways in the seasonality of extreme precipitation over the eastern United States
Authors: Dhakal Nirajan , Aljoda Ali
Published: February 2023

AbstractThe empirical probability distribution of extreme precipitation in the eastern United States comprises heavy rainfall events stemming from the moisture held by the Atmospheric Rivers (ARs). In many sites, ARs trajectories can have varying impacts on the extreme precipitation seasonality based on the moisture source and tracks. Consequently, a characterization of location specific and regional patterns of timing of extreme precipitation caused by ARs and their non-stationarity has salience for both scientific and engineering concerns. To this end, analysis of annual maximum daily precipitation (AMP) at 581 long-term stations across the eastern United States was pursued in this study to evaluate the role of moisture sources and tracks in the seasonality of extreme rainfall-AR related events (AMP-AR) and their temporal changes over the 1950–2015 period. The key results from this study include: (a) spatio-temporal variation in the fraction of annual maximum precipitation events linked to ARs, and (b) a marked influence of moisture sources on the seasonality of AMP-AR related events. Results from this study have important bearing on the flood risk management and preparedness.
CO2 emissions estimate from Mexico City using ground- and space-based remote sensing
Authors: Che Ke , Lauvaux thomas , Taquet noemie , Xu Yang , Lopez Morgan , Stremme Wolfgang , García-Reynoso Agustín , Ciais Phillipe , Liu Yi , Ramonet Michel , Grutter Michel
Published: February 2023

The Mexico City Metropolitan Area (MCMA) has become the most populous urban region in North America and in the top five megacities worldwide (around 22 million inhabitants). To quantify the urban CO2 emissions of MCMA, a dense network of  Fourier Transform Infrared (FTIR) spectrometers with 6 portable EM27/SUN and 1 IFS 125HR were deployed within and around the MCMA  tracking gradients in atmospheric column CO2 concentrations (XCO2) from October 2020 to May 2021 (part of the French-Mexican MERCI-CO2 project). During these 7 months, twenty  XCO2 images (Snapshot Area Mode)  were collected by the NASA Orbiting Carbon Observatory (OCO-3) mission over the MCMA. By comparing  ground- and space-based observations, we found a positive XCO2 difference with a mean (± one standard uncertainty) of 1.16 (± 1.14) ppm between OCO-3 and FTIR column measurements, most probably caused by their respective calibration procedures. XCO2 gradients observed between the urban plume and its surroundings  show a good agreement between OCO-3 and the FTIR stations with a correlation coefficient (R) of 0.92,  decreasing significantly when comparing intra-city gradients (R=0.24). In a second phase, we assimilated these two types of dense column-integrated observations (FTIR network and OCO-3 SAM observations) separately to optimize the anthropogenic emissions from the MCMA and the biogenic CO2 fluxes in and around the city limits, in addition to the CO2 background concentrations. The X-Stochastic Time-Inverted Lagrangian Transport (X-STILT) model driven by the Weather Research and Forecasting (WRF) at 1-km resolution was used here to relate our atmospheric observations to surface fluxes and background conditions. An analytical Bayesian inversion technique was used here to robustly update the prior estimates at 1-km and 1-hour resolution. High-resolution prior biogenic CO2 emissions were computed with the light-use efficiency model CASA and our prior backgrounds from the global CAMS CO2 atmospheric inversion (version: v21r2). Prior anthropogenic CO2 emissions at 1 km are coming from a Mexico-specific inventory UNAM and from the global inventory ODIAC. These two inventories contain large discrepancies over MCMA (~40 %), while UNAM provides more detailed  information of point sources across our inversion domain. We performed sensitivity control experiments to quantify the effects from different prior fluxes and different covariance parameters. Furthermore, we combine OCO-3 and FTIR together in the same inversion process, a promising step toward providing a verification to  combine multiple data streams over a specific city. 
Building an EPS-SG Microwave Imager Retrieval Suite: Level-1 Proxy Data Record
Authors: Petković Veljko , Stegmann Patrick , Meng Huan , Ferraro Ralph , Yang John Xun
Published: February 2023

Following the success of MetOp, EUMETSAT Polar System Second Generation (EPS-SG) will provide satellite observations from polar orbit to support Numerical Weather Prediction and climate monitoring in the 2024 to mid-2040's timeframe. Designed to fly on board the EPS-SG satellite-B series and cover 19-183 GHz frequency range, Microwave Imager (MWI) is expected to deliver high-quality measurements of radiometric properties relevant to precipitation, clouds, near-surface ocean winds and snow/ice cover. With a goal to build an enterprise MWI retrieval in support to NOAA operational Environmental Data Records (EDRs) production, a development of new and adaptation of the existing microwave imager algorithm procedures are underway at University of Maryland. As part of this effort and to ensure timely delivery of day-1 retrievals, we simulate MWI level-1 data over prolonged periods of time (up to 12 months) using radiative transfer techniques. Two datasets will be presented. The first, oriented towards precipitation retrieval development, relies on Global Precipitation Measurement (GPM) Dual-frequency Precipitation Radar (DPR) observations to construct a state vector in radiative transfer calculations. The second dataset relies exclusively on ERA5 parameters. Two radiative transfer models have been considered in the production of simulated MWI brightness temperatures: a) Community Radiative Transfer Model (CRTM) and b) Edington model. Each model uses MWI observation geometry, following DPR and GCOM-W1 AMSR2 sampling, respectively. To deliver the product, CRTM has been updated by, for this purpose derived, MWI coefficients using an idealized Spectral Response Function at each of the 26 channels. When compared to the common channels of AMSR2 sensor, the simulations reflect exceptionally high accuracy. In addition to the methodology and proxy data sets, preliminary results for MWI precipitation EDR retrieval will be presented.
Predicting Terrestrial Water Storage Anomalies at the Global Scale with a Machine-Learning Model
Authors: Palazzoli Irene , Ceola Serena , Gentine Pierre
Published: February 2023

Changes in the level of the world freshwater storage, the Terrestrial Water Storage Anomalies (TWSA), may be induced by natural variability, climate change, and human activities. Since 2002 the Gravity Recovery and Climate Experiment (GRACE) has been measuring the Earth’s gravity field providing estimates of the TWSA at the global scale.Here, we aim to develop a machine learning model that can reproduce the GRACE monthly time series covering the period between 2002 and 2017 from climate data, identifying to what extent the TWS fluctuations have been caused by climate variability. We used a Long Short-Term Memory (LSTM) neural network trained with meteorological variables (precipitation, air temperature, solar net radiation, snow cover, relative humidity, and leaf area index) and soil properties data (soil porosity, soil texture, and clay, sand, and silt fractions). Our results show that the model is able to consistently reconstruct the observed freshwater anomalies, especially in the humid regions. Furthermore, we observed that as climate change trends are removed from input data, the bias between model predictions and observed data becomes larger, proving the influence of climate change on TWSA.
Added value of modeling regional climate over areas characterized by complex terrain: precipitation over the Colombian Andes
Authors: Baquero-Bernal Astrid , Espitia-Rodríguez Javier Fernando
Published: February 2023

The added value (AV) of the dynamic downscaling of precipitation over the Colombian territory was investigated using simulations made with the RegCM4 regional model in the context of the CORDEX experiment. The simulations were forced by two different global models (GCM) from the CMIP5 project (HadGEM2-ES and MPI-ESM-MR), cover the period 1981-2005, and have resolutions of 0.44° and 0.22°. The comparison with the CHIRPS/GPCC reference data showed that RegCM4 degrades the results of the GCMs, that is, it does not provide AV for all selected metrics and this occurs not only when going to fine scales but also when we scale up to the resolution of the GCMs.
Pan-European earthquake risk modelling – leveraging the latest science in catastrophe modelling and implications for (re)insurance decision-making
Authors: Papaspiliou Myrto , Petrone Crescenzo , Tomassetti Umberto , Kalita Pratim , Panchireddi Bhaskara
Published: February 2023

Catastrophe models are fundamental tools in the quantification of risk for the (re)insurance industry. When it comes to European earthquake risk modelling, the most widely used vendor models available in the industry have not been updated since 2011 and are largely out of date with respect to the latest scientific findings and data from the recently released pan-European earthquake hazard (ESHM20) and risk (ESRM20) models (e.g. Danciu et al., 2021, Crowley et al., 2021). This presentation aims to showcase our work to incorporate the latest pan-European hazard and risk research within the catastrophe modelling framework, using a largely consistent methodology across the continent. We will focus on the type of datasets that have been leveraged across hazard, exposure and vulnerability and present how these have been utilized for the validation of each component of the catastrophe model, from hazard to vulnerability and loss. We will subsequently demonstrate how we have adjusted the existing catastrophe models, as well as the challenges faced. Finally, we will then proceed to highlight the impact of incorporating such pan-European studies in our View of Risk for loss modelling across 12 different countries in Europe and what are the implications for reinsurance pricing and decision-making.  
Mountain climate: one of the multipronged challenges in Ethiopia’s Agriculture
Authors: Negash Emnet , Van Schaeybroeck Bert , Termonia Piet , Van Ginderachter Michiel , Van Weverberg Kwinten , Podevyn Maarten , Nyssen Jan
Published: February 2023

The Ethiopian highlands are home to more than 90% of the Ethiopian population and constitute for 90% of total area suitable for agriculture (Hurni et al., 2010). The livelihood of 66% of Ethiopia’s population depends on subsistence agriculture, mostly rainfed. Little rainfall variability can therefore cause massive economic loss for farmers reliant on rain-fed agriculture, making differences in wealth among farmers on different sides of the mountain. This study aims at understanding the sub daily distribution of summer rain over the Ethiopian highlands using the ALARO-0 regional climate model at convection-permitting resolution of 4 km. The dependence on factors such as leeward or windward conditions, and elevation are explored to categorize and relate the diurnal cycles of surface variables including precipitation, wind speed, humidity, and temperature. Rainfall occurrence in these mountains is mainly influenced by circulation patterns, orography, surface heating and convection, making its distribution very heterogeneous. Elevation is the most important determinant factor leading to increased average rainfall and rainfall per rainfall event towards higher elevations. Ethiopia’s summer rain exhibits a pronounced diurnal cycle with the highest rainfall occurring during the early afternoon hours (12:00–16:00) and the minimum occurring in the late night (04:00–11:00). Windward average rainfall and rainfall per rainfall event are on average 0.05mm h-1 and 0.08 mm hr-1 (respectively) larger than leeward events, except during peak hours when leeward events have 0.05 mm higher average rainfall and rainfall per rainfall event. In contrast to average rainfall events, extreme events in the afternoon are often followed by another peak rainfall event at night. Leeward wind speed features a weak diurnal variation as compared to the strong contrast between day and night for windward wind speed. The diurnal cycles of temperature and humidity start earlier in the morning and recede later than the cycles of wind speed and rainfall. Moreover, rainfall peaks occur earlier in the day at higher elevations, and at night in valleys and in Afar Triangle. The prevalence of windward over leeward event probability, the stark contrast in wind speed diurnal cycle between windward and leeward events, and the early peak hour of dewpoint and air temperature all point towards temperature-induced rather than wind-induced convection. Rainfall-temperature dependence, in other words Clausius-Clapeyron relationship, in the lowlands such as the Afar triangle is however at its lowest due to moisture deficit. These differences are very likely to determine hydrology and vegetation distribution, and farmers economy at large.
Long-term tectonic evolution of the Eastern Southern Alps (Italy): a reappraisal from new structural and radiometric constraints
Authors: Vignaroli Gianluca , Curzi Manuel , Zuccari Costantino , Aldega Luca , Billi Andrea , Carminati Eugenio , Van der Lelij Roelant , Kylander-Clark Andrew , Viola Giulio
Published: February 2023

Constraining the timing of tectonic events is of prime importance for the in-depth understanding of the complex evolution of orogenic deformation, particularly in the case of fold-and-thrust belts. In this work, we combined U-Pb dating of tectonic carbonates and K-Ar dating of fault gouges of selected key outcrops along two main thrusts of the Paleogene-Neogene Eastern Southern Alps (ESA), Italy. The ESA are the south-verging fold-and-thrust retrobelt of the Alpine orogen, offering spectacular exposures to study the details of past tectonic processes. However, despite a few published papers regarding the deformation mechanisms of a major thrust in the ESA (the Belluno Thrust), modern, multiscale structural and radiometric studies of fault zones in the ESA are missing, such that detailed reconstructions of the local and regional tectonic evolution through space and time remain only loosely constrained. We focused on the (i) Valsugana Thrust, which is a first-order thrust separating the Dolomites s.s. to the north from the Venetian Pre-Alps to the south, and (ii) the more external Belluno Thrust. We coupled U-Pb dating of tectonic carbonates and X-ray diffraction and K-Ar dating of clay minerals in fault gouges with structural analysis and microtextural characterization. We show that the Valsugana Thrust represents an inherited pre-Alpine structure that (i) registered far field deformation during the Early Cretaceous (K-Ar gouge age of 140 ± 32 Ma), (ii) strongly influenced the geometry and kinematics associated with deformation structures during the Alpine orogenesis and (iii) recorded multiple reactivations in Late Cretaceous (K-Ar age of 79.2 ± 8.4 Ma and 76.2 ± 1.4 Ma), late Miocene (U-Pb age of 9.1 ± 0.8 Ma), and Miocene-Pliocene (U-Pb age of 5.3 ± 1.6 Ma) times. Radiometric constraints from the Valsugana Thrust attest to remarkable out-of-sequence compressional movements in the inner ESA after the orogenic wave had progressed farther south to the more external Belluno Thrust, whose activity is constrained to the Oligocene by a 30.6 ± 5.8 Ma K-Ar gouge age and a 23 ± 14 Ma U-Pb syn-tectonic vein age.
Land subsidence and coastal retreat as observed using Sentinel-1, tide dynamics, and socio-cultural survey of Sayung, Demak, Indonesia
Authors: Budiyono Yus , Zahro Qoriatu , Oktaviani Aulia , Riyalda Bondan Fiqi , Siriwardane-de Zoysa Rapti
Published: February 2023

The coastal zone of northern Java experiences rapid land subsidence. Satellite-derived InSAR data and GPS had provided evidence  displaying the spatio-temporal rates of the subsidence. Interestingly, inhabitants do not always recognize this phenomenon. However, they do recognize that flooding from the sea (called ‘rob’) has changed from gift to disaster, viz. from shallow infrequent flooding that carry inshore fishes, to regular deep and widespread disastrous floods. In the Demak regency, more than 300 families have moved to locations further inland. In some locations rob flooding has caused a coastline retreat of up to 5kms.Our initial Sentinel-2 analysis comparing 2016 and 2022 images have showed the change of ecosystem in the area. In addition to that, social surveys revealed timely change of the ecosystem and point places where coastlines have moved.For this study, we use Sentinel-1 imagery for SAR coupled with tide data to determine the behavior of coastline change from 2018-2022. Sentinel-1 is selected due to the temporal resolution and performance in  all-weather. Ground Range Detected (GRD) of Sentinel-1, is single look complex data projected using an earth ellipsoid, will be used as main input in spatial analysis to observe shoreline condition. There are 4 types of polarization of GRD data: HH,VV, HH+HV and VV+HV. Polarization type will be tested and determined to get less noise images result. Image masking and pixel analysis will sequentially be conducted to segregate the land and the sea. The analysis will be managed in Sentinel Application Platform (SNAP).Tide data plot from nearby station is used to assign at what phase Sentinel-1 imagery is acquired. Additional analysis from tide data plot is applied to predict land/inundation at important sites and when imagery is not available. The social research component of the study through preliminary survey data , our initial survey showed residents relocation had been started before the period covered by the SAR data sets. Hence, random purposive sampling will be used for a follow-up mixed-methods survey to gather more data on social and economic dynamics arising from the geomorphological shifts in coastline. Ultimately, we hope  our study will help unravel land subsidence and the resulting coastline retreat to provide a strong basis for mitigation and adaptation options by the people and the government.
Relationship between rainfall and flood frequency curves in high elevation areas
Authors: Evangelista Giulia , Monforte Irene , Demateis Raveri Marco , Claps Pierluigi
Published: February 2023

Flood hazard assessment and its relationship with extreme rainfall probabilities is a well-addressed topic in the literature, but not enough in mountain areas, where the climate change effect can hit much more than in other physical contexts. In mountain basins, the lack of systematic data and the complexity of the rain/snow phenomena make investigations even more necessary to figure out the consequences of global warming.This study explores how the partial contributing area effect due to snow accumulation, on the one hand, and the basin runoff coefficient, on the other hand, shape the relationship between rainfall and flood probabilities in high elevation areas. To this aim, the FloodAlp geomorphoclimatic model (Allamano P. et al., 2009) is used.The model is based on the derived distribution approach, producing as a result a simplified flood frequency curve based on the intra-annual variability of the portion of the catchment area covered by snow, according to simple descriptions of the seasonal variation of the freezing elevation and of the hypsographic curve of the basin.To model the basin hypsometric features, we propose the use of a two-parameter Strahler function, which is a more accurate and alternative formulation to the simple one-parameter function originally used in the model. The role of the extreme rainfall frequency analysis is also explicitly analysed, by applying the model using rainfall extremes recorded both in the daily and 24-hours windows. In this application, the only parameter that requires calibration is the runoff coefficient. Considering recordings of annual maximum daily discharges, the runoff coefficients for more than 100 gauged basins in north-western Italy have been calibrated. Comparisons are then possible between the shapes of rainfall and flood frequency distributions within the sample analysed, that also take into account the basin geomorphoclimatic features. Results of this application address the selection of relevant characteristics in relation to the impact of climate change on mountain floods as a result of changes in temperatures and in the statistics of rainfall extremes. 
Improving large-basin streamflow simulation using a modular, differentiable, learnable graph model for routing
Authors: Bindas Tadd , Tsai Wen-Ping , Liu Jiangtao , Rahmani Farshid , Feng Dapeng , Bian Yuchen , Lawson Kathryn , Shen Chaopeng
Published: February 2023

Differentiable modeling has been introduced recently as a method to learn relationships from a combination of data and structural priors. This method uses end-to-end gradient tracking inside a process-based model to tune internal states and parameters along with neural networks, allowing us to learn underlying processes and spatial patterns. Hydrologic routing modules are typically needed to simulate flows in stem rivers downstream of large, heterogeneous basins, but obtaining suitable parameterization for them has previously been difficult. In this work, we apply differentiable modeling in the scope of streamflow prediction by coupling a physically-based routing model (which computes flow velocity and discharge in the river network given upstream inflow conditions) to neural networks which provide parameterizations for Manning’s river roughness parameter (n). This method consists of an embedded Neural Network (NN), which uses (imperfect) DL-simulated runoffs and reach-scale attributes as forcings and inputs, respectively, entered into the Muskingum-Cunge method and trained solely on downstream discharge. Our initial results show that while we cannot identify channel geometries, we can learn a parameterization scheme for roughness that follows observed n trends. Training on a short sample of observed data showed that we could obtain highly accurate routing results for the training and inner, untrained gages. This general framework can be applied to small and large scales to learn channel roughness and predict streamflow with heightened interpretability.  
A Framework for Flash Drought Progression
Authors: Basara Jeffrey , Christian Jordan
Published: February 2023

Not all droughts are the same.  In some cases, drought rapidly intensifies at subseasonal to seasonal scales with significant impacts to agriculture and water resources along with the increased propensity for heatwaves and wildfires.  Soil moisture is a critical drought variable, and the desiccation of the terrestrial surface is an effective resource for monitoring drought development and associated impacts.  During flash drought, soil moisture can play two critical roles: (1) drought enhancement via dry soils, enhanced sensible heat flux, reduced evaporation, and enhanced vapor pressure deficit and, (2) drought resistance via moist soils that cool the surface via evaporation and decreased vapor pressure deficit.  Thus, a fundamental question is at what point during flash drought development does the environment transition from drought resistance (a negative feedback) to drought enhancement (a positive feedback) and vice versa? Further, how do surface-layer processes impact the development of the planetary boundary layer (PBL) during this transition?  Finally, what is the overall relationship between atmospheric demand, evaporative stress, terrestrial desiccation, and precipitation in the progression of flash drought.  This study provides a conceptual framework that captures the critical processes that drive flash drought progression (and moderation) through a relative parameter space approach. Using this framework, the onset, development, intensification, moderation, and termination of flash drought can be diagnosed by the complex interactions between terrestrial and atmospheric variables.
Enzymatic kinetics and microbial growth in the rhizosphere of maize: visualization and quantification of the functions
Authors: Blagodatskaya Evgenia , Martin Roldan Maria , Shen Guoting
Published: February 2023

Biochemical processes in the rhizosphere are distributed heterogeneously and depend on biotic and abiotic factors such as root morphology and physiology which affect the allocation of substrates, nutrients and water availability. In the frame of Priority Program ‘Rhizosphere Spatiotemporal Organisation – a Key to Rhizosphere Functions ’ we aim to visualize and quantify enzymatic activity related to C, N and P turnover in order to link them with microbial functional traits in space and time. To do that, we apply a time-lapse zymography of hydrolytic and oxidative enzymes coupled to micro-sampling of rhizosphere hotspots for enzymatic kinetics determination at the early vegetation stage of maize. Kinetic parameters of microbial growth will be estimated by micro-calorimetry. Traditional approaches of rhizosphere sampling will be compared with novel methodology at the level of individual soil aggregates. Specific strategies of two plant genotypes (wild type and root hair deficient mutant) in response to limiting conditions of water and nutrients content will be tested on two soil substrates of contrasting texture (loam and sand). Field experiments in a long-term maize monoculture will help disclose the interactions between rhizosphere and detritusphere from decaying roots of previous years.
DemoStorage - an ATES demonstrator in an urban environment.
Authors: Rettenmaier Detlev , Zorn Roman , Blum Philipp , Kathrin Menberg , Herrmann Matthias , Viernickel Michael , Eichelbaum Fabian , Fleuchhaus Paul , Stoeck Thorsten , Katzenmeier Sven , Breiner Hans-Werner , Hahn Hans Jürgen , Fuchs Andreas
Published: February 2023

Aquifer thermal energy storage (ATES) is comparatively rarely used in Germany, in contrast to neighboring countries such as the Netherlands. This also applies to lower temperature ranges of less than 50 °C, which are mostly technically easier to handle than high-temperature storage. Since there is a lack of demonstration plants nationally, the goal of our BMBF-funded joint project “DemoSpeicher” (Development and Monitoring of Seasonal Heat and Cold Storage for the Demonstration of Aquifer Storage) is to implement and scientifically accompany a near-surface low-temperature aquifer storage system (NT-ATES). Within the scope of the project, the entire construction cycle of an NT-ATES is to be covered, which ranges from design and planning to grid integration and commissioning to thermal energy supply. An urban site in Germanys capital Berlin-Mitte was selected for the implementation of the demonstration plant, which is to be converted to climate-friendly heating and cooling concepts at an existing construction site. In addition to the necessary preliminary site investigations for the technical-economic feasibility, questions regarding legal approval requirements will also be presented.For this reason, a extensive monitoring program is planned, which provides the metrological supervision of the thermal-hydraulic underground processes. Another focus of the project will be possible changes in groundwater chemistry and temperature-sensitive groundwater ecology as a result of thermal loading. Monitoring of energy flows is also planned in order to estimate the thermal energy exchange between the aquifer reservoir and the building's systems engineering. This will include a heating and cooling demand analysis, as well as an assessment of potential synergistic use effects with other technologies that could be used, for example, for thermal loading of aquifer storage. All results will be presented in a coupled thermal-hydraulic modeling of the planned thermal energy storage. The project and the first results of the implementation of an ATES in a densely populated urban area will be presented and discussed in this presentation.
Soil and plant nutrient status in temperate forests as affected by long-term drying-rewetting conditions
Authors: Luster Jörg , Ulmann Antonia , Herzig Angélique , Walthert Lorenz
Published: February 2023

The increasingly warmer and drier climate will change the geographic distribution of tree species. Here, apart from direct effects of changes in temperature and soil moisture on tree physiology, indirect effects via interactions between soil environmental conditions and the bioavailability of nutrients may play an additional role. Specifically, this comprises effects of desiccation and rewetting on soil properties, and of drought and drought release on root-soil interactions in the rhizosphere. Such effects may be particularly strong for phosphorus, considering its low solubility and mobility in soils.For this study, we considered data from 44 forest sites across Switzerland representing soil moisture gradients for each of the four major tree species beech (Fagus sylvatica L.), oak (Quercus sp.), pine (Pinus sylvestris L.) and spruce (Picea abies Karst). First, we explored the relations between the nutrient status of the soil (total N, hydrogencarbonate extractable inorganic and organic P, microbial P, exchangeable K, Mg, Ca) and soil environmental conditions during four years before soil sampling (average water potential and temperature, number of dry days and drying-rewetting [DRW] cycles as defined by a given water potential threshold). Second, we performed the same analysis using the nutrient status of mature trees (as indicated by nutrient concentrations in bark) instead of the soil nutrient status.Results indicate a strong influence of DRW on the soil’s P status, whereas other nutrients in the soil are only little affected. On beech and oak sites, the N and P status of the trees increased with increasing moisture and decreasing temperature, and the P status was in addition negatively affected by the length and number of DRW cycles during which high drought stress levels were reached. By contrast, the Ca status of the trees increased with temperature and soil dryness.Considering observations by others regarding positive effects of high plant nutrient status on a plant’s resilience to drought, our results call for more in-depth studies on the feedback-loops between soil water supply, soil nutrient availability, plant-physiology and root-soil interactions.
An automated GIS procedure for mapping ballistic projectiles by using UAVs imagery: the case of the 3rd July, 2019 paroxysm at Stromboli
Authors: Bisson Marina , Spinetti Claudia , Gianardi Roberto , Strehlow Karen , De Beni Emanuela , Landi Patrizia
Published: February 2023

This study presents an application based on UAS optical data for mapping at very high spatial resolution the ballistic projectiles erupted during an explosive volcanic eruption. The novelty consists in the development of a GIS-based automate procedure that, elaborating high spatial resolution UAV optical imagery (RGB) acquired within few days from the explosive event, is able to reproduce the boundary of each ballistic projectile as georeferenced polygon feature. This procedure, applied for the first time at Stromboli volcano (Aeolian Archipelago, Italy), has reconstructed in 2D digital format the shape of the ballistic spatter clasts emplaced on the East flank of the volcano during the paroxysm of the 3rd July, 2019. The dimensions of the clasts, reproduced as polygon features stored in WGS 84 UTM 33 metric coordinates, range from 0.03 m2 (16 cm x 16 cm) to 4.23 m2 (~2 m x 2 m). Respect to the classic field survey, the application here presented is able to generate, in efficient and rapid way, a large amount of data and information on ballistic deposits, covering also the areas inaccessible and/or dangerous as particularly affected by ballistic fallout. Such application allowed  to better understand the dynamic of ballistics emplacement, providing a useful contribution to volcanic hazard mitigation.
Mapping grid-scale social-ecological system archetypes from the perspective of human-environmental interactions using multisource geospatial big data
Authors: bao wenkai
Published: February 2023

Social-ecological system (SES) archetype has been an emerging research frontier in landscape and sustainability science which acts as a key tool in understanding complex human-environmental interactions in different social-ecological contexts, diagnosing context-specific sustainability challenges and developing transferrable solutions that can be adapted effectively to multiple locations. However, state-of-art mapping of SES archetypes are mostly bounded to administrative borders, andthe lack of spatial details in SES maps hinders us from capturing the panorama of spatial heterogeneity and undergoing challenges of SESs. Here, we propose a conceptual framework to characterize SES archetypes from the perspective of human- environmental interactions, and develop a novel data-driven approach to operationalise it for mapping grid-scale SES archetypes at an unprecedented spatial resolution by combining multiple open-access data streams (remote sensing, model simulations and geospatial big data). By applying this approach to the Beijing-Tianjin-Hebei (BTH) urban agglomeration,our analyses present a two-tier system of SES archetypes consisting of 5 typical SES archetypes, i.e. urban systems, urban-rural transition systems, agricultural systems, ecological transition systems and natural systems, and 11 regional SES subarchetypes. These findings are capable of retaining both general patterns and local details of SESs, which can contribute to identifying location-specific sustainability challenges faced by different SESs, and therefore to provide spatial templates for targeting policy responses to common challenges such as climate change impacts, air pollution, biodiversity loss, urban-rural disparity and cropland abandonment, etc.Besides, we reveal an interesting social-ecological gradient across SESs about trade-offs in the presence and influence between the human part and natural part of human-environmental interactions, which can further improve our understanding of their inherent mechanisms.Generally, our approach demonstrates great potentials for being generalized to other locations to facilitate the recognition of local needs and gaps in existing policies and promote sustainable landscape management, and also provides opportunities in scaling up case-based knowledge to advance SESs theories for addressing global challenges in the Anthropocene.
Land Subsidence Effect on Coastal Sediment Transport pattern in Pekalongan Beach, Central Java - Indonesia
Authors: Yuanita Nita , Kurniawan Alamsyah
Published: February 2023

Pekalongan Beach, lying on the northern part of Java Island in Indonesia, is one of the main cities in Central Java because it is famous for its traditional craft, especially batik. has suffered from coastal flooding and abrasion over the last ten years. This disaster is getting worse due to the significant impact of land subsidence. This study examines sediment transport conditions on the Pekalongan coast using field observation data and a numerical model computation using the Delft3D Flow model. The research was started by collecting and analyzing primary and secondary field data. After the model was calibrated to tidal water level elevation and current velocity field data, hydrodynamic and sediment transport simulations for two scenarios representing the conditions before land subsidence in 2016 and after subsidence in 2021. The input land subsidence rate was assumed based on the recent data at a station 10 cm/year. Sensitivity analysis was carried out to examine which input parameters most sensitive to coastal sediment transport conditions. In the sensitivity analysis, various sediment grain size, wave height and wave direction were used in the numerical model. It is found that sediment grain size is the most sensitive effect on sediment transport condition. The simulation results indicate that the sedimentation rate increased by 56% after land subsidence. In contrast, the erosion rate decreased by 4% after one neap-spring tidal cycle (around 15 days) in the study area. Coastal inundation in Pekalongan was getting worse due to land subsidence and higher wave condition in recent years.
Data management in resource-limited settings: Unpacking the role of robust digital solutions for air quality data management in African cities.
Authors: Okure Deo , Ogenrwot Daniel , Nsimbe Noah , Muyama Lillian , Adong Priscilla , Sserunjogi Richard , Bbaale Martin , Bainomugisha Engineer
Published: February 2023

Increasing awareness of air pollution requires access to timely and reliable air quality data and information, and yet many African cities lack effective air quality monitoring infrastructure, largely because of the resource constraints of establishing and managing a continuous monitoring network. Low-cost sensor platforms have the potential to close the air quality data gaps in resource-strained settings such as Africa, but the continued lack of accessible and reliable infrastructure for data management is a major hindrance to effective air quality management.Moreso, managing a large Internet of Things (IoT)-based sensor network can be complex, and the demand for a case-specific and highly customizable platform, coupled with its conceptualization & implementation complexities, renders most existing IoT platforms ineffective. There is a need for a platform infrastructure for continuous support and management of air quality data with a high spatial and temporal resolution to facilitate sophisticated analysis; while taking care of the associated structural challenges of low-cost sensors.  The AirQo platform, a robust could-native software is a novel communityaware digital platform for managing large-scale air quality networks, applicable in resource-strained environments. This customisable and scalable platform attempts to address the data access challenges, with capabilities to become a ‘one-stop centre’ for management of other third party IoT sensor networks. Different interfaces through mobile application, web-based dashbord and platform cater for diverse data needs. The robust approach enables decision makers and other stakeholder communities have access to timely and quality assured air quality data. Using a set of metrics, user-experiece can be computed and compared with existing IoT management platforms. Software design considerations including (1) Multi-tenancy, (2) Data pipeline, (2) Sharded Database Cluster, (3) Microservices architecture, (4) Containerized deployment, and (5) Interoperability are recommended to support replication in other use-cases.  
Direct measurements can help to understand the changes in ecosystems: Amazonia a case study
Authors: Gatti Luciana , Cunha Camilla , Marani Luciano , Cassol Henrique , Messias Cassiano , Arai Egidio , Soler Luciana , Almeida Claudio , Setzer Alberto , Domingues Lucas , Denning Scott , Miller John , Gloor Manuel , Correia Caio , Crispim Stephane , Correa Sergio , Neves Raiane , Silva Francine , Machado Guilherme
Published: February 2023

The Amazon is the largest rainforest on the planet and was an important carbon sink. The carbon sink is declining, mainly due to an increase in tree mortality as a result of deforestation, degradation, and local, regional and global climate change. In addition, deforestation and forest degradation reduce the ability of the Amazon rainforest to act as a carbon sink. CO2 Vertical Profiles (VP) were performed from 2010 to 2021 (805), using small aircraft at 4 locations: SAN (2.86° S 54.95° W), ALF (8.80° S 56.75° W), RBA (9.38° S 67.62° W) and from 2010 to 2012 on TAB (5.96° S 70.06° W) and since 2013 at TEF (3.39° S 65.55° W). The question if Amazonia is a carbon source or sink is an important role in the global carbon budget. Amazonia vertical profile annual mean derived from CO2 annual mean vertical profiles (VP subtracted from the background concentration: ∆VP) from the 4 studied sites can help to clarify this important question. The sampling frequency was approximately 2 times per month in each location, from 4.4 km height (a.s.l.) until near surface 300 m (a.s.l.), and usually carried out between 12:00 and 13:00 local time. The CO2 samples were analyzed at INPE's LaGEE (Greenhouse Gas Laboratory), in São Jose dos Campos. This result is a direct indication of the regional source in the global carbon budget, indeed there are well-known discrepancies from many studies using different methodologies (bottom-up, top-down techniques, and a wide variety of global, regional, and inversion models). In this study, we will present Carbon flux from the time series for the 4 sites and Amazon Carbon balance using the column budget technique, and analyze the correlations with various parameters related to climate, vegetation, deforestation, and biomass burning.
Linking enstatite meteorites to a unique source.
Authors: Avdellidou Chrysa , Delbo Marco , Morbidelli Alessandro , Walsh Kevin , Munaibari Edhah , Bourdelle de Micas Jules , Devogele Maxime , Fornasier Sonia , Gounelle Matthieu , van Belle Gerard
Published: February 2023

The identification of meteorite parent bodies provides the context for understanding planetesimal formation and evolution as well as the key Solar System events they have witnessed. However, identifying such links has proven challenging and some appear ambiguous. Here, we identify that the family of asteroid fragments whose largest member is (161) Athor is the unique source of the rare EL enstatite chondrite meteorites, the closest meteorites to Earth in terms of their isotopic ratios. The Athor family was created by the collisional fragmentation of a parent body 3 Gyr ago in the inner main belt. We calculate that the diameter of the Athor family progenitor was 64 km in diameter, much smaller than the putative size of the EL original planetesimal. Therefore, we deduce that the EL planetesimal that accreted in the terrestrial planet region underwent a first catastrophic collision in that region, and one of its fragments suffered a more recent catastrophic collision in the main belt, generating the current source of the EL meteorites. 
Education for climate change - Utilizing atmospheric research facilities
Authors: Kalivitis Nikos , Stavrou Dimitris , Vrekoussis Mihalis , Levrini Olivia , Tasquier Giulia , Riuttanen Laura , Ginoudi Athina , Bellentani Giorgia , Mavromanolakis Georgios , Kanakidou Maria
Published: February 2023

In order to face the challenges of climate change, coordinated actions and efforts are required on global, regional and local scales. To succeed, they must be conveyed to informed, conscious and active citizens who understand the challenges and are ready to alter their way of living and thinking toward protecting our planet. Therefore, educating young people is one of the most effective tools for combating climate change. However, the increasing interest in climate change education by stakeholders, policymakers and the research community is not yet broadly incorporated into science education activities.
Atmospheric research stations provide valuable information about evolving climate change. Long-term observations of atmospheric parameters provide scientific evidence for the connections between the anthropogenic effect on atmospheric composition and the resulting changes in the planet’s climate.
Here we present educational activities at well-established atmospheric observatories part of international observational networks like ACTRIS, LTER, GAW and ICOS. The stations in those networks provide the necessary data and the links between atmospheric composition changes and climate perturbations. At the same time, these stations host at their premises local hubs where teachers and students have the chance to receive hands-on training on using environmental data in education and, ultimately, in school classrooms. The atmospheric research stations support networking, training and community building by stimulating personal engagement and out-of-school education of trainees.