bluuebunny/crossref_metadata_2025 huggingface dataset:
Using 15N isotope and microbiome analysis to understand N2O production and consumption processes.
Authors: Masta Mohit , Espenberg Mikk , Pärn Jaan , Mander Ülo
Published: March 2024

Nitrous oxide is a potent greenhouse gas which is involved in stratospheric ozone depletion. Even though nitrogen cycle has been studied for a long time, it is still challenging to understand specific N2O production and consumption processes. This is due to the complexity and heterogeneity of soil, wherein multiple processes can take place simultaneously. Isotopic composition of N2O can help us solve this and provide useful information on evaluating N2O sources and calculate global budgets. N2O is a linear molecule and its understanding at molecular scale can provide major insights into partition of its source processes. The N2O site preference (SP), which is the difference in δ15N between N2O molecules substituted with 15N at the central and the peripheral position, has proved to be a major tool to tackle this problem. The objective of this study is to use isotopic and microbial research for N2O sources and process partitioning. We will bring some examples from our recent studies in the lab and in a drained peatland forest. During our lab study based on peat soil from a floodplain fen, we observed bacterial denitrification was a major source of N2O emissions under flooded conditions. We observed this using 15N isotopic mapping technique, which helped separate multiple active processes. We applied a similar method in-situ on a drained peatland in southeastern Estonia and described hybrid N2O formation, where one N atom of the N2O molecule was taken from NH4 and the other N molecule from another source such as organic N, was the dominant source of N2O emissions. The isotopic mapping and molecular enrichment of 15N during our experiment showed that. The isotopic mapping initially suggested nitrification as a major source, but on further investigation of 15N enrichment, we found the presence of hybrid processes (15N nitrogen from two pools or processes). Furthermore, we studied the genetic potential for major N2O processes (denitrification, nitrification, dissimilatory nitrate reduction to ammonium (DNRA)) and combined these with the isotope results, and this integrated approach is an important tool to partition N2O processes. When using 15N tracers, the isotopic technique can partition the sources (nitrate or ammonia) of N2O. Hence, using the isotopic mapping of natural abundances and 15N tracers to partition the source, we can get initial insights into N2O sources and processes together. Isotopic mapping is still under development and further research is required as it also has a problem of overlapping of processes.
High frequency sampling during a storm hydrograph offers insights into the possible transport and source activation dynamics of microplastics within a peri urban stream. 
Authors: Haverson Lee , Mignanelli Lisa , Schneidewind Uwe , Krause Stefan
Published: March 2024

In the last decade mismanaged plastic waste, specifically microplastics (1-5000 µm) have gained significant scientific and public interest with research from numerous disciplines highlighting the ubiquitous nature and potential harm microplastics can exert on both human and ecosystem health. Microplastics can now be found in all of Earth’s environmental compartments. Although a large level of knowledge has been obtained highlighting the sources (wastewater treatment plants, urban areas, agricultural fields etc), sinks (oceans, lakes, rivers, ground water, etc) and transport routes (rivers, air currents, ground water etc) of microplastics in the environment, our understanding of the processes that drive flux between systems is still limited. This is especially true in systems where environmental loading and activation events are less predictable, such as those found in diffuse source dominated catchments. Previous studies have highlighted storm events as significant drivers of microplastic flux in such catchments. However, little research has been conducted examining how microplastic concentrations, loading and characteristics change over the course of a storm hydrograph and also how the hydrometeorological conditions before and during an event interact with the microplastic supply dynamics.This study aims to address this gap. In June 2022 a single light storm event (1 (2.05)) with microplastic concentration peaking before peak discharge suggesting microplastic supply depletion. Furthermore, it was estimated that during the sampled portion of the storm event (around 8 hours) about six million microplastic particles were exported from the catchment. In contrast, microplastic export during baseflow ranged from around 28,000 to around 368,000 particles for the same time frame, indicating the significance of such events when calculating annual MP flux. This study demonstrates how microplastic concentrations and characteristics change over the course of a single storm event, providing a mechanistic understanding of how hydrometeorological conditions interact with microplastic supply dynamics.
 Soil Hydrophobicity Effects on Soil Erosion: Interplay between Hydrological and Mechanical Effects
Authors: Fallah Mahboobeh , Van De Wiel Marco , Holtzman Ran
Published: March 2024

 Soil erosion poses a significant threat to agricultural and natural resources. Soil water repellency (SWR), namely the resistance to wetting due to hydrophobicity, has become widespread due to variety of processes including droughts, wildfires, pollution and greywater irrigation. Recent studies showed that that SWR exerts a strong effect on soil erosion by its hydrological impact: reduction in infiltration implies increase in overland flow, the driving force for erosion. Another, much less explored and more complex effect of SWR on erosion is through its impact on soil cohesion and strength, the resisting force for erosion. Here, we focus on the combined effects of SWR on erosion. We compile the published experimental data of erosion in hydrophobic soils, which provides contradictory evidence of both increase and decrease of erosion with increasing SWR. We find that while drought- and fire-induced SWR predominantly increases erosion, there is no clear trend for pollution-induced SWR, suggesting that pollution can improve the soil’s resistance to erosion, and that this mechanical effect of SWR is stronger than the hydrological effect of increased overland flow. We establish a rational connection between the SWR and its hydrological and mechanical effects on erosion through a simple 1D numerical model. The results of the model indicate that the net erosional impacts of SWR depends on the balance between the soil hydrological and soil mechanical effects of SWR. The key insights obtained from literature and this straightforward model enhanced our understanding of the dual nature of SWR's influence on soil erosion dynamics.Keywords: Cohesion, Erodibility, Hydrophobicity, Hydrology, Runoff, Soil Erosion
CO2 emission from a subarctic mire with different permafrost status 
Authors: Łakomiec Patryk , Holst Jutta , Rinne Janne
Published: March 2024

The main goal of this work is to quantify the differences in net ecosystem exchange (NEE) of CO2, and its component processes, Gross Primary Production (GPP) and ecosystem respiration (Reco) across surfaces with different permafrost status at a sub-arctic mire complex. The study site, Abisko-Stordalen mire in Swedish Lapland, is situated in the mire (68°20' N, 19°30' E). We used data from the Integrated Carbon observation system (ICOS) Ecosystem station (SE-Sto). Palsa plateu and thawing sector data were used from the years 2014-2021, and for fen for 2014.  We analyzed CO2 diel cycle for the summer months (June, July, August), to compare it for the three ecosystems. We found out that diel cycle is similar in terms of time but order of magnitude of CO2 fluxes is different for the fen than for the palsa and the thawing sector. CO2 responds for the air temperature and incoming radiation were compared among three ecosystems.    We used three different gapfilling methods: REddyProc (Jena), artificial neural network (ANN), and generalized linear models (GLM) for the annual balance calculation. Gap-filling was made on a half-hour basis, and this allow us to divide fluxes to Reco and GPP.  Comparison of those two NEE components has been done for the palsa plateu and the thawing sector for the whole period.Of the three surfaces that were examined in this study, the tall sedge fen had the highest CO2 uptake during the daytime in the summer and the highest net respiration at night as the growing season. However, there were no significant differences in CO2 fluxes between the palsa plateau and the thawing sector, despite their different permafrost conditions and vegetation characteristics. In contrast, there were significant differences in methane emissions between these systems. Multiple gap filling methods were found to be important for accurate CO2 emission estimation.
Microtremor analysis in the central Longitudinal Valley, eastern Taiwan
Authors: Chang Jui , Wu Cheng-Feng , Rau Ruey-Juin
Published: March 2024

Eight days after the 2022 MW 7.0 Chihshang earthquake, we installed 58 short-period seismic stations in Yuli, Longitudinal Valley for a month-long measurement, and 72 stations around the earthquake rupture zones for short-term measurements. The region covers approximately 35 square kilometers, and encompasses the structures from west to east: Central Range Fault, Yuli Fault rupture zone and Chihshang Fault, a segment of the Longitudinal Valley Fault. An alluvial plain covers the topographic lows from the Central Range to Longitudinal Valley while terraces surround the river west of the Central Range Fault. We used horizontal-to-vertical spectral ratio (HVSR) analysis within the frequency range of 0.2 to 20 Hz for data processing, the region can be classified into six major categories from west to east: Category A, located in Central Range; Category B, at the terraces; Category C, situated in the plain west of the Yuli fault rupture zone; Category D, located proximal to the Yuli Fault rupture zone; Category E, located in the plain east of Yuli fault; and Category F, found in the plain east of Chihshang Fault and in the Coastal Range. Our results show that B, C and F have peak amplitudes of around 4.5 within dominant frequency (f0) range of 1.5-2.5 Hz, 2-3 within f0 range of 0.7-1.5 Hz and 3-5.5 within f0 range of 5-13 Hz, respectively. The locations of Categories B and C align with the position of Central Range fault line. Category F, located along the western boundary along the Chihshang Fault separated from the other five categories and exhibits a noticeable f0. On the other hand, A, D, and E exhibit less pronounced dominant frequencies. Category D is positioned at the center of the alluvial layer and is distributed around the rupture zone of Yuli Fault, showing high similarity in HVSR curve across numerous stations, with unclear dominant frequencies. As a result, the HVSR results in the central Longitudinal Valley are mostly related to the tectonics and topographic units in this region.
A promising approach in isotope geochemistry: 87Sr/86Sr in human teeth and hair to study dietary and environmental effects.
Authors: Arienzo Ilenia , Di Renzo Valeria , Pelullo Carlo , D'Antonio Massimo
Published: March 2024

In recent years Sr isotope geochemistry has provided a huge contribution to environmental and food traceability studies. This is possible because soils, plants and water are characterized by a specific Sr isotopic signature (expressed through the 87Sr/86Sr ratio), which derives from the local geological substratum which, in turn, depends on geological processes and on the age and initial rubidium (Rb) content of the rocks, given that 87Rb decays to 87Sr over time. Since the relative abundance of Sr isotopes does not change during the path through the food chain, the 87Sr/86Sr ratio in human tissues reflects that of the “environment” in which people live and feed. In particular, tooth enamel (which forms during the first years of life) does not exchange with external Sr after mineralization. For this reason, its isotopic composition mostly reflects the 87Sr/86Sr of the food intake that individuals used for energy, growth and maintaining the processes of life, during their childhood.In this work, the Sr isotopic characterization of deciduous human teeth and hair, water, soil, plants and food was carried out. Donors are all born and currently residing in Campania (Southern Italy), of different age and sex. The 87Sr/86Sr of deciduous teeth provides a direct link to the mother’s milk, or to the artificial milk, which are the first foods for the newborn individuals, whereas the 87Sr/86Sr of hair is directly related to the diet in adulthood. Moreover, the mother’s milk is in part related to the local geological substratum and in part to the diet that has become no longer local, but global. Despite adult individuals have different diets, the isotopic fingerprint of enamel teeth is similar for all breastfeed children. Results from this study have scientific implications also for human mobility studies.
Assessing fungal spore health impacts with real-time detection technologies
Authors: Crawford Ian , Douglas Philippa , Macchiarulo Sameirah , Marczylo Emma
Published: March 2024

Bioaerosols are ubiquitous airborne microorganisms comprised of bacteria, fungi, pollen, virus and their constituents. Fungi have been associated with negative health effects ranging in severity from allergic reactions to asthma and serious infection, where susceptible individuals are at greater risk of life-threatening health outcomes resulting from exposure. While airborne fungi are abundant, they are poorly characterized due to the low temporal resolution of traditional offline sampling methods, limiting our understanding of key emission drivers in critical micro-environments and their impacts on air quality.There is a critical need to better characterize background fungal aerosol concentrations to build baselines to explore exposure assessment. Here we investigate the utility of emerging real-time detection methods in conjunction with offline sampling during a two-week pilot study to characterize the outdoor concentrations of key aeroallergenic fungi at high time resolution.A Multiparameter Bioaerosol Spectrometer (MBS) was deployed at UKHSA Chilton alongside a Burkard sampler during August 2022; The MBS is a biofluorescence spectrometer that classifies and quantifies bioaerosols on a single particle basis via their autofluorescent signatures, allowing for fungal aerosol concentrations to be derived at 5-minute time resolution; Next Generation Sequencing (NGS) was performed on daily integrated Burkard samples to provide broader fungal compositional context. Meteorological data was also recorded.Clear diurnal behaviour in Cladosporium- and Penicillium-like aerosol was observed with the MBS, with maximums occurring in the late afternoon and early morning respectively. These characteristic emission features would not be evident from sample integrations typical of offline sampling. Comparison to the NGS bioinformatics is ongoing.We demonstrate for the first time the utility of a complimentary real-time and offline NGS dual approach to gain deeper insights into fungal spore emissions. We suggest that this approach shows promise for routine fungi monitoring to assess impacts on public health.
Testing the performance of a simplified distributed model to assess actual evapotranspiration in a Mediterranean orchard using ground and remotely sensed data
Authors: De Caro Dario , Ippolito Matteo , Capodici Fulvio , Ciraolo Giuseppe
Published: March 2024

Accurate estimations of actual crop evapotranspiration are essential to evaluate crop water requirements, to improve water use efficiency in agriculture, and to optimize the use of available freshwater resources. To this aim, several models were developed to allow quantifying crop water requirements based on the knowledge of actual crop evapotranspiration rates, ETa.The objective of this research was to estimate ETa using a simplified distributed model combining ground and remotely sensed data.The experiment was carried out in a Mediterranean commercial citrus orchard (C. reticulata cv. Tardivo di Ciaculli) located in the Northwest of Sicily, Italy, during the whole 2019. The experimental layout consisted of: i) a WatchDog 2000 standard weather station (measuring the main climate variables and the precipitation depths, P); ii) a database of irrigation volumes, I, scheduled by the farmer; iii) an Eddy Covariance tower equipped with an open patch gas-analyzer, a three-dimension sonic anemometer, a four-component net radiometer, and a soil heat flux plate iv) a dataset of 75 Sentinel-2 multispectral images, acquired in clear sky condition.In particular, the daily crop reference evapotranspiration, ETo, was calculated according to the FAO-56 Penman-Montheith equation using the climate variables; the crop coefficient, Kc, the Fractional Vegetation Cover, FVC, and, thus, the potential evapotranspiration, ETp, were computed via the processing of reflectance values in the RED, NIR and SWIR spectral bands. The Available Water, AW, the short-term water stress factor, Cws, and the ETa, were computed by analyzing cumulated ETp and water-supplying values using moving temporal windows characterized by different sizes (from 5 to 400 days).The validation of the model outputs was carried out by taking into account the ETa of the pixels within the flux tower footprints estimated at each satellite acquisition day (i.e. by selecting the pixels on the basis of the footprint shape and extension). The performance of the model was evaluated for each temporal window size using the following metrics: the Root Mean Square Error, RMSE, the Mean Absolute Error, MAE, the angular coefficient of the regression line forced to the origin, b, and the determination coefficient, R2.Results suggest that the best temporal window size for this crop is around 85 days allowing to achieve an RMSE of 0.51 mm d-1, a MAE of 0.38 mm d-1, a b value of 0.94 and an R2 of 0.96. The comparison with the model outputs over the whole field (all the pixels within the crop field) revealed that a strong decrease in all the metrics occurs if the validation of the remote sensing products is not properly carried out.
Seasonal greenhouse gas flux and microbial community dynamics along a landslide soil chronosequence at the west side of New Zealand's Southern Alps
Authors: Rasigraf Olivia , Riedel Anne , Bartholomäus Alexander , Clough Timothy , Friedl Thomas , Wagner Dirk
Published: March 2024

Landslides are an important erosion mechanism in mountainous terrain. They strip large quantities of organic material from ecosystems and expose bedrock to weathering. At the west side of New Zealand’s Southern Alps, super-humid climate and slope instabilities create ideal conditions for frequent landslides, allowing studies of soil formation processes in short-term chronosequences. Here, we investigated soils from three landslides that occurred in 2019 (“young”), 1997 (“intermediate”), and 1965±5y (“old”), respectively. Additionally, reference forest soils located outside of landslide areas were sampled at each location. Closed PVC chambers were installed at different positions on landslide surfaces and reference soils, and gas samples were collected for flux analysis. Soil samples were collected at the same positions from the surface and 20 cm depth and investigated for physico-chemical parameters and microbial community composition.Net CO2 emissions reached 830 mg h-1m-2 at the “old” site in summer and remained below 356 mg h-1m-2 in winter. Net N2O emissions showed a patchy spatial pattern, reaching rates of 0.2 mg h-1m-2 at the “old” site in summer. At most locations, N2O flux was below the detection limit during winter.Soils were dominated by bacterial phyla Acidobacteria, Bacteroidota, Chloroflexi, Gemmatimonadota, Planctomycetota, Proteobacteria and Verrucomicrobiota. Dominant archaeal phyla comprised Thermoplasmatota and Crenarchaeota. Beta diversity analysis revealed distinct community composition patterns with the “young” site forming a separate cluster from the older landslides and reference soils. Surface- and depth-associated microbial communities showed high similarity at the “young” site, but they became increasingly distinct at the “intermediate”, “old” and reference soil sites. Community composition at the “old” site showed the least difference to reference sites, indicating that ecosystem development rapidly reached a state similar to older mature forests.In general, the three landslide sites showed a gradient in the development of soil chemical parameters, microbial community composition and soil respiration rates, with the “old” site being closest to reference sites. Soil respiration rates showed strong seasonal dependence and soil temperature sensitivity.Our results indicate that respiration rates and microbial community composition of landslide soils reach those of older mature forest soils within a few decades after mass wasting events, if no reactivation occurs and soil development can proceed without disturbance.
Delineation of mine tailings by ambient noise horizontal-to-vertical spectral ratio method
Authors: Kaslilar Ayse , Wilczynski Zbigniew , Juhlin Christopher , Bastani Mehrdad
Published: March 2024

The increasing need for mineral resources and critical rare earth elements (REE) due to the transition to clean energy has attracted interest in mine wastes as they may contain significant amounts of REE that were not of interest in the past but are today. Detailed knowledge about the 3D geometry and size of the waste deposits and their mineral content is important to understanding whether waste tailings can serve as a secondary resource, contributing to the energy transition, sustainability, and the circular economy, and promoting recycling.  Geophysical methods can provide information on the geometry, and help to characterize and estimate the size of the mine waste. In the last two decades developments in sensor and computational technology have enabled cost-effective and environmentally friendly seismic ambient noise methods to be widely applied for imaging the subsurface. Among others, one of the ambient noise methods is the horizontal-to-vertical spectral ratio (HVSR) method, which is an efficient technique widely used for site characterization, estimating the thickness of overburden above bedrock, monitoring landslide, and examining the stability of tailing dams.In this study, ambient noise data and the HVSR method are used to estimate the thickness and delineate the 3D geometry of mine tailings. We use three-component (3C) ambient noise data that we collected with 50m spacing between the sensors and profiles in one of the non-active mine tailings of Nordic Iron Ore in Blötberget, Sweden, which might be a potential resource for REE.  We process the 3C data and obtain the fundamental frequency at each receiver location. Moreover, one-component ambient noise data that we collected along two perpendicular profiles with a receiver spacing of 5m are used to estimate the surface wave velocity. Combining the fundamental frequency and velocity information, we calculate the depth of the contrasting interface. We show our preliminary results obtained from ambient noise data and compare them with the previous results from the radio magnetotelluric measurements conducted by Geological Survey of Sweden.This work is part of a project supported by the Geological Survey of Sweden. We gratefully acknowledge this support.
Coupling scales in process-based soil organic carbon modeling including dynamic aggregation
Authors: Prechtel Alexander , Zech Simon , Ray Nadja
Published: March 2024

Background: Carbon storage and turnover in soils depend on the interplay of soil architecture, microbial activities and soil organic matter dynamics. For a fundamental understanding of the mechanisms that drive these processes, not only the exploitation of advanced experimental techniques down to the nanoscale is necessary, but also spatially explicit and dynamic image-based modeling at the pore scale.We present a modeling approach which is capable of transferring microscale information into macroscale simulations at the profile scale. This enables the prediction of future developments of carbon fluxes and the impact of changes in the environmental conditions linking scales.We consider a mathematical model for CO2 transport across soil profiles (macroscale) which is informed by a pore-scale (microscale) model for C turnover. It allows for the dynamic, self-organized re-arrangement of solid building units, aggregates and particulate organic matter (POM) based on surface interactions, realized by a cellular automaton method, and explicitly takes spatial effects on POM turnover such as occlusion into account. We further include the macroscopic environmental conditions water saturation, POM content, and oxygen concentration.The coupled simulations of macroscopic transport and pore scale carbon and aggregate turnover reveal the complex, nonlinear interplay of the underlying processes. Limitations by diffusive transport, oxygen availability, texture dependent occlusion and turnover of OM drive CO2 production and carbon storage.Zech, Prechtel, Ray (2024): Coupling scales in process-based soil organic carbon modeling including dynamic aggregation. J. Plant Nutr. Soil Sci.
Mechanisms and effects of Tarim rotation: 3-D thermo-mechanical modeling
Authors: Cui Qihua , Huangfu Pengpeng , Li Zhong-Hai
Published: March 2024

The rotational of rigid blocks within continental interiors, distant from plate convergence boundaries, represents a peculiar phenomenon with unclear dynamics. The Tarim block, characterized as a rigid Precambrian entity in Central Asia, is surrounded by the Tibetan–Pamir plateau to the south and the Tian Shan mountains to the north. Geophysical data strongly indicate a significant clockwise rotation of the Tarim block during the Cenozoic era. Simultaneously, distinctive deformation patterns and associated topographic responses are observed between the western–central and eastern Tian Shan regions. The intricate relationship among the India-Asia collision, Tarim's rotation, and Tian Shan's responses remains insufficiently constrained. In this study, we constructed a series of large-scale, high-resolution 3-D numerical models to study the mechanisms and effects of Tarim rotation. Our model results reveal that the collision between the advancing Indian lithosphere and the southwestern rim of the Tarim block triggers a clockwise rotation of the Tarim block. Subsequently, this rotation induces varied deformation responses along the strike of Tian Shan—resulting in heightened compression and significant uplift in central Tian Shan due to convergence, while eastern Tian Shan experiences less compression and moderate uplift attributed to divergence. Thus, the Tarim rotation emerges as an essential linkage, connecting the evolutionary dynamics of the Tibetan plateau with the far-reaching activation of Tian Shan. This research provides valuable insights into the geodynamic processes shaping continental interiors, with implications for broader tectonic frameworks and technological applications.
Analysis of Hydrogeological Parameters of the Nairobi Aquifer Suite Using GIS-Based Spatial Interpolation Methods 
Authors: Kahuthu Dennis Wambugu , Amimo Meshack O. , Oiro Samson , Székely Balázs
Published: March 2024

Groundwater resources in the Nairobi Aquifer Suite (NAS), Kenya, face significant problems largely due to rapid urbanization and the rising water demand. The depletion of groundwater resources at the local level could potentially extend to regional extents, and hence affect natural water flows. This therefore calls for the prediction of aquifer hydrogeological parameters for sustainable groundwater management. This study aims to utilize GIS-based spatial interpolation methods for the in-depth analysis of NAS hydrogeological parameters. Classical geostatistical tools are employed to develop models that can be used to accurately predict hydrogeological parameters of the NAS. Field-measurable predictors, that is, geographic position, elevation, depths and first water struck level, are used to demonstrate the efficacy of the predictive models. Data from hydrogeological measurements, geological surveys and satellite imagery are integrated during the development of the predictive models for key hydrogeological parameters, including, groundwater level, discharge, drawdown, electrical conductivity, and transmissivity. Classical geostatistical tools such as kriging and natural neighbour interpolation are applied to develop spatially explicit maps of the NAS hydrogeological parameters. The distribution of borehole data is analyzed using geostatistical tools such as trend analysis and semi variogram. Cross-validation has been performed to identify the most suitable spatial interpolation model. While, in general, the prediction worked well based on model evaluation metrics such as mean absolute error (MAE), mean squared error (MSE), root mean square error (RMSE) and coefficient of determination (R2), during the testing we observed characteristic deviations from the measured values at some locations. These differences could be due to the geological setting; however, a few outliers may appear due to yet unknown reasons. Further studies utilizing machine learning techniques are expected to develop accurate predictive models that can help in sustainable groundwater management in the NAS. The generated spatial maps provided insightful information on the spatial distribution of hydrogeological parameters in the NAS, facilitating the accurate identification of prospective locations for ideal groundwater extraction.Keywords: GIS; hydrogeological parameters; Nairobi Aquifer Suite; machine learning; predictive modelling; spatial mapping
An alternative to PCA utilizing Dynamic Time Warping
Authors: Uebbing Bernd , Höckendorff Jan , Jungheim Caroline , Driemel Anne , Sohler Christian , Kusche Jürgen
Published: March 2024

The Earth’s system is warming due to natural and human driven climate change. Observing, analyzing and understanding the associated geophysical processes is important in order to improve prediction of future changes and mitigate impacts on society and infrastructure. Investigating individual climate processes, such as sea level change, often requires partitioning of the total signal for identifying sub-signals and drivers; in the sea level example these could be trend and seasonal signals or impacts from the El Niño Southern Oscillation (ENSO).A commonly applied method is the (real) Principal Component Analysis (PCA), which factorizes a given input dataset into time-invariant Empirical Orthogonal Functions (EOF), i.e. spatial patterns, and time-variable Principal Components (PC) based on the most dominant eigenvalues. However, this real-EOF analysis assumes more or less static patterns over time and, thus, lacks the ability to capture temporal variations in the patterns. This can be circumvented by the application of complex or Hermitian EOF analysis, which also enables capturing phase shifts or in other words allows for time-varying spatial patterns.Here, we present first results from a novel approach utilizing dynamic time warping (DTW) for extracting dominant modes in the form of spatially distributed amplitudes and lags with respect to a ‘base curve’. While classic PCA methods are sensitive to outlier influence on the partitioning, our approach represents a robust alternative. Furthermore, base curves are computed that represent spatial modes via traversal matrices, which act as extensions of the base curves to capture individual lag. We introduce our new approach, compare to complex/Hermitian EOF, explain the numerical scheme, and present some first results based on gridded sea level change data.
Looking under the Lid: Understanding the Influence of Atmospheric Deserts on Heat Wave and Thunderstorm Formation
Authors: Fix Fiona , Mayr Georg , Stucke Isabell , Zeileis Achim
Published: March 2024

We introduce the concept of atmospheric deserts, air masses that originated as hot and dry boundary layers in semi-arid or desert source regions. When they are advected to regions with moister and cooler boundary layers, they can cap the local boundary layers, eliminate cloudiness, and lead to the buildup of heat underneath. Heat waves can occur when atmospheric deserts are present over a target region for several days. Thunderstorm formation can be suppressed where the capping lid is strong, but where it is punctured, thunderstorms can erupt violently.We illustrate this new concept with a case study from mid-June 2022 when an atmospheric desert was advected from its source region in North Africa towards Europe. With the Lagrangian analysis tool (LAGRANTO), approximately 200 million trajectories are traced, tracking the path of the air mass and the development of its properties as it  progresses towards and across Europe over the course of 5 days. By the end of the study period the atmospheric desert extends from the Atlantic to Eastern Europe and as far north as Sweden. k-means-clustering identifies four typical pathways that the trajectories follow. Most of the atmospheric desert air is modified along the way, with exception of one pathway for which air remains well mixed and forms an elevated mixed layer.Thunderstorms erupted along a line parallel to the northwestern edge along the surface temperature front, but were mainly absent in the core region of the atmospheric desert. A heat wave affected large parts of Europe, from the Iberian Peninsula to Central Europe. Temperatures set new records, for example in some parts of Eastern Germany. Potential temperatures in some locations even became as high as the ones of the overlying atmospheric desert air.
Remediation of rare earth elements (REE)-rich waters by precipitation of newly-formed phases.
Authors: Millan-Becerro Ricardo , Ruiz-Agudo Encarnación , Asta María P. , Bonilla-Correa Sarah , Burgos Ruiz Miguel , Santoro Francesco
Published: March 2024

The “Ría de Huelva” estuary (SW Spain) is highly affected by acid mine drainage and phosphate fertilizer industry effluents, which contain high concentrations of dissolved metal(loid)s, some of them of high economic interest such as Rare Earth Elements (REE). These elements are essential for the energy transition as they are used in various applications necessary for the production, transport, and accumulation of electrical energy from renewable sources. However, high dissolved concentrations of REE could have a significant environmental impact on aquatic organisms [1]. This research work focuses on the remediation of REE-laden solutions with different concentrations of these metals, using a sorption strategy with mineral phases such as gypsum (CaSO4·2(H2O)) and brushite (CaHPO4·2(H2O)), where these elements of high economic interest may be concentrated for its potential recovery. The main objectives of this research were to determine: (1) the removal processes of dissolved REEs, as well as (2) the preferential incorporation in the minerals studied. For this purpose, precipitation experiments of REE-rich sulfate and phosphate phases were carried out in the laboratory. The liquid and solid samples resulting from the precipitation experiments were analyzed by atomic emission spectroscopy with inductively coupled plasma (ICP-AES), mass spectrometry with inductively coupled plasma (MS), X-ray diffraction (XRD), scanning electron microscopy (SEM) and transmission Fourier transform infrared (FTIR), which allowed us to determine the capacity for REE incorporation by the tested minerals, as well as possible changes in the characteristics of the newly-formed phases. The concentrations of REE in the sulfate and phosphate phases increased progressively as solutions with higher concentrations of these metals were used in the laboratory experiments. However, the removal percentages of REE by gypsum precipitation were noticeably lower than those by brushite precipitation. This could be because brushite has a greater adsorption capacity than gypsum, as both mineral phases have similar crystalline structures and therefore the co-precipitation processes of REE with both minerals should be similar. These results show that the removal of REE from solutions during the precipitation of newly-formed phases could be a viable strategy for the concentration of these valuable elements and the remediation of contaminated waters.AcknowledgementsThis work is part of the I+D+i TRAMPA project (PID2020-119196RB-C21), funded by MCIN/AEI/10.13039/501100011033/. [1] Oral, R., Bustamante, P., Warnau, M., D'Ambra, A., Guida, M., Pagano, G., 2010. Cytogenetic and developmental toxicity of cerium and lanthanum to sea urchin embryos. Chemosphere 81:194–198.
Seawater Intrusion Mechanisms in Heterogeneous Coastal Aquifers Subject to Pumping
Authors: Geranmehr Mohammadali , Bau Domenico , Mayer Alex , Mancewicz Lauren , Yu Weijiang
Published: March 2024

Seawater intrusion (SWI) in coastal aquifers is influenced by both spatial distributions of hydraulic properties and pumping rates. The heterogeneity of parameters such as hydraulic conductivity (K) may have a significant impact on the vulnerability of these systems to SWI and the sustainability of groundwater supply.In this work vulnerability is assessed in relation to indicators such as: (a) the salt concentration of extracted groundwater (C); and (b) the total dissolved mass (TDM) of salt in the aquifer. This study delves into a modified version of the classical two-dimensional Henry's problem, featuring a single pumping well situated in proximity of the coastline. The well pumping rates are expressed as fractions of the total flow rate entering the aquifer from the inland boundary. The fraction range from a minimum of zero (no pumping) to a maximum of five.To investigate the impact of aquifer heterogeneity a series of stochastic simulations are conducted using the popular variable density flow model SEAWAT. Heterogeneity in the K spatial distribution is modelled as a geostatistical log-normal process characterized by an exponential covariance function, with variance values ranging from 0.25 to 1.0, horizontal correlation scales from 10 m up to 2000 m, and a single vertical correlation scale of 10 m. This approach allows for investigating the effects of the K heterogeneity, the layering features of the aquifer system, and the intensity of groundwater pumping on C and TDM.A detailed examination of model results reveals several interesting outcomes. Most notably, the TDM indicator is rather sensitive to the K heterogeneity, whereas the C indicator is much less affected by it. In terms of TDM, selected cases are singled out and discussed. In general, lower K values exhibit minimal SWI even with large pumpage, whereas high K values lead to pronounced SWI even at low pumping. Increased variance and horizontal correlation correspond to varied SWI behaviour. The TDM spread remains generally low due to relatively low variance. With an increase in horizontal correlation, the spread becomes more pronounced for low pumping rates and less pronounced for large pumping rates.
Characterization of compound earthquake damage empowered by AI remote sensing
Authors: Lin Feng , Song Yuqi , Hu Xie
Published: March 2024

Rapid post-earthquake response remains a significant challenge for humanity. Emergency response to earthquakes requires accurate and timely information about the geographic locations of secondary hazards and the likely compound effects, such as landslides, liquefaction, and building damage. Current methods rely on data-driven approaches, and also start to consider the complex causal dependencies associated with earthquake-induced disasters. However, the accuracy of existing pipeline is limited due to factors like atmospheric noise contaminating satellite imagery.To improve the accuracy of predicting multiple hazards and impacts, we introduce the principles of time-series Interferometric Synthetic Aperture Radar (InSAR) analysis to generate high-quality Damage Proxy Maps (DPM). Subsequently, we adopt a rapid seismic multi-hazard and impact estimation system leveraging advanced statistical causal inference and remote sensing techniques. This approach, by modeling causal dependencies from satellite images, infers multiple hazard scenarios on a regional scale at high accuracy and resolution.Data we using include landslides, liquefaction, and building damage. We also created DPMs using SAR images from the Sentinel-1 satellite. Beides the accuracy, our approach’s results also reveal quantitative causal mechanisms among earthquake-triggered multi-hazard and impact events. Our system provides a new approach to InSAR data processing and offers a novel avenue for understanding the complex interactions of multiple hazards and impacts in seismic geological processes.
Analysis of trends in surface energy fluxes under hot conditions using remote sensing products
Authors: García-García Almudena , Peng Jian
Published: March 2024

Studying land-atmosphere interactions is important for understanding the mechanisms leading to changes in temperature and precipitation extremes. However, the non-conservation of energy and water in most products and their coarse spatial and temporal resolution hamper the study of land-atmosphere feedbacks. The combination of remote sensing data and modelling frameworks allows to greatly improve the spatial coverage and resolution of data products. Here, we investigate trends in surface fluxes over Europe using the new data product generated with the high-resolution land surface fluxes from satellite and reanalysis data (HOLAPS) framework. HOLAPS is a one dimensional modelling framework that solves the energy and water balance at the land surface, providing consistent surface and soil variables derived from remote sensing data and reanalysis products as forcings. The evaluation of the HOLAPS product against eddy covariance measurements shows slightly better results than other ET and H products at daily scales in summer (KGE > 0.0 for ET and KGE > -0.3 for H) and during hot extremes (KGE > -0.15 for ET and KGE >-0.7 for H), while the state-of-the-art products show KGE > -0.49 for ET and KGE > -1.2 for H in summer and KGE > -0.49 for ET and KGE > -1.5 for H during hot extremes. These results together with the 1D conservation of energy and water in the modeling framework makes this product the perfect tool for the analysis of trends in surface energy and water fluxes during the last decades. Preliminary results for the period 2001-2016 reveals a larger increase in the energy reaching the surface during the hottest month of the year than during summer over central Europe and the Mediterranean coast. This extra energy is released as sensible heat over dry areas during the hottest month of the year. In areas where soil water is available, the extra energy available during the hottest month is released as latent heat flux, adding it to the already large latent heat flux during summer. These results support previous analyses indicating an increase of latent heat flux during hot conditions at monthly scales. However, trends at higher temporal resolutions should be examined to improve the robustness of this conclusion. 
The puzzle of shallow convection-circulation coupling
Authors: Janssens Martin
Published: March 2024

Since shallow clouds over the tropical oceans are organised into mesoscale structures, explaining the role of these clouds in climate requires understanding what governs mesoscale patterns in shallow cumulus convection. Many puzzle pieces have emerged in recent years. These include both external forcings on the boundary layer, such as the import of extratropical eddies and water vapour with the large-scale flow, weak sea-surface temperature anomalies and remotely triggered gravity waves, as well as internal feedbacks between convection and its mesoscale environment, such as cold pool dynamics and self-reinforcing low-level moisture convergence. What all these mechanisms share, is their interaction with the low-level mesoscale vertical motion field, which itself is often organised into shallow circulations that couple tightly to the convection. Here, we will therefore propose to begin assembling the puzzle pieces by analysing the origins of shallow circulations, in a conceptual framework of weak mesoscale virtual temperature gradients. The analysis is enabled by the simultaneous presence of observations of clouds, thermodynamics and mesoscale vertical motion taken during the EUREC4A field campaign, and simulations from EUREC4A-MIP; it will therefore serve as an example of what other puzzle pieces might fall in place by combining observations with other intercomparison projects in the model hierarchy, such as Lagrangian LES MIP, CP-MIP and NextGEMS.
An up-to-date seismic catalogue of the 2020 Mw6.4 Petrinja (Croatia) earthquake sequence using machine learning
Authors: Sindija Dinko , Mustac Brcic Marija , Hetenyi Gyorgy , Stipcevic Josip
Published: March 2024

Identifying earthquakes and selecting their arrival phases are essential tasks in earthquake analysis. As more seismic instruments become available, they produce vast amounts of seismic data. This necessitates the implementation of automated algorithms for efficiently processing earthquake sequences and for recognising numerous events that might go unnoticed with manual methods.In this study, we employed the EQTransformer, trained on the INSTANCE dataset, and utilised PyOcto for phase association, focusing specifically on the Petrinja earthquake series. This series is particularly interesting for its initial phase, which was marked by a limited number of seismometers in the epicentral area during the onset of the sequence in late December 2020. This limitation was subsequently addressed by the swift deployment of five additional stations near the fault zone in early January 2021, followed by a gradual expansion of the seismic network to over 50 instruments.Our analysis covers the Petrinja earthquake series from its onset on December 28, 2020, up to present, offering a complete and up-to-date view of the seismic activity as the seismic activity is still higher than in the interseismic period. We compare our findings from the machine learning-generated catalogue with a detailed manual catalogue. Focusing on the first week of the series, when the seismic network was sparse and there was a high frequency of overlapping earthquakes, we achieved a recall of 80% and a precision of 81% for events with local magnitude greater than 1.0. In contrast, for the subsequent six months of processed data, a period still characterised by a high frequency of earthquakes but with the fully expanded network, our recall improved dramatically to 95% with over 20,000 detected events. This comparison allows us to demonstrate the challenges, evolution, and effectiveness of automatic seismic monitoring throughout the earthquake sequence.