bluuebunny/crossref_metadata_2025 huggingface dataset:
Clouds and Seasonality on Terrestrial Planets with Varying Rotation Rates 
Authors: Williams Daniel , Ji Xuan , Corlies Paul , Lora Juan
Published: March 2024

Clouds have been observed on Venus, Mars and Titan, and a growing number of exoplanets, yet the connection between planetary rotation rate and cloud distribution has not previously been extensively investigated. Using an idealised climate model incorporating seasonal forcing, we investigate the impact of rotation rate on the abundance of clouds on an Earth-like aquaplanet, and the resulting impacts upon albedo and seasonality. We show that the cloud distribution varies significantly with season, depending strongly on the rotation rate, and is well explained by the large-scale circulation and atmospheric state. Planetary albedo displays non-monotonic behaviour with rotation rate, peaking around one half of Earth’s rotation rate. Clouds reduce the surface temperature and total precipitation relative to simulations without clouds at all rotation rates, and reduce the dependence of precipitation on rotation rate. Clouds also affect the amplitude and timing of seasonality, in particular by modifying the width of the Hadley cell at intermediate rotation rates. The timing of seasonal transitions varies with rotation rate; the addition of clouds further modifies this phase lag, most notably at Earth-like rotation rates. Our results may inform future characterisation of terrestrial exoplanets, in particular informing estimates of planetary rotation for non-synchronous rotators.
Drought Vulnerability Concepts and User-Endorsed Factors in Forested Ecoregions in Cold and Continental Climates
Authors: Stenfors Elin , Blicharska Malgorzata , Grabs Thomas , Teutschbein Claudia
Published: March 2024

In a changing climate, the assessments of drought risk and vulnerability are becoming increasingly important. Responding to the global call for a proactive approach to drought risk management, there is now a growing emphasis on drought vulnerability assessments within the drought research community. Since the manifestation of drought vulnerability depends on the social, ecological, and hydroclimatic context in which it unfolds, recognizing vulnerability factors specific to particular climatological and ecological regions could enhance the accuracy and reliability of vulnerability assessments. However, a holistic overview of factors affecting vulnerability in polar and cold climates is currently lacking, although these regions accommodate extensive socio-hydrological systems, encompassing urban areas, energy infrastructures, agricultural practices, and vast boreal forests. Through an interdisciplinary and systematic exploration of existing literature, we identified the manifestation and conceptualization of drought vulnerability for forested ecoregions in the Köppen–Geiger D and E climates. Factors contributing to vulnerability, as delineated by several scientific disciplines, were identified and synthesized into a novel conceptual framework that categorizes vulnerability factors by their location in a socio-hydrological system, and their relation to blue or green water sources (Stenfors et al., 2023). To further assess their relative importance in cold and continental climates, a survey with more than 100 respondents from various sectors (e.g., agriculture, forestry, energy, water supply, environment, etc.) and different governance levels was conducted to validate and rank the identified factors and measurable indicators. Thus, we provide a list of user-endorsed drought vulnerability factors and corresponding indicators, which allows for identification of systemic vulnerability patterns, providing new insights into regional differences in drought vulnerability and a base for stakeholders performing proactive drought risk assessments in the study region.Reference:Stenfors E, Blicharska M, Grabs T, Teutschbein C. 2023. Droughts in forested ecoregions in cold and continental climates: A review of vulnerability concepts and factors in socio-hydrological systems. WIREs Water: e1692 DOI: https://doi.org/10.1002/wat2.1692
Fire, permafrost, and people: Late Holocene fire regimes and their impacts on lake systems in Yakutia, Siberia
Authors: Glückler Ramesh , Dietze Elisabeth , Kruse Stefan , Andreev Andrei , Biskaborn Boris K. , Zakharov Evgenii S. , Baisheva Izabella , Stieg Amelie , Tsuyuzaki Shiro , Stoof-Leichsenring Kathleen , Pestryakova Luidmila A. , Herzschuh Ulrike
Published: March 2024

The Republic of Sakha (Yakutia), the coldest permanently inhabited region on Earth, is characterized by unique ecological relationships between larch forest, permafrost, and wildfires. Together, they can stabilize each other, preserving the larch-dominated biome. Abundant lakes have important cultural and subsistence-related functions and are dynamically connected to warming permafrost processes. Recently intensified wildfire seasons, however, raised questions regarding the causes and impacts of long-term (centennial to millennial) fire regime changes. Despite recent progress, eastern Siberia is still sparsely covered by reconstructions of long-term fire history. This also limits any evaluation of fire regime impacts on permafrost lake development and catchment erosion. Past studies have shown the benefit of combining paleoecological fire reconstructions with geochemical data to shed light on fire regime changes and their impacts on lake catchments, as well as traces of potential human land use.We present nine new records of Late Holocene wildfire activity, based on macroscopic charcoal in lake sediments (including information on charcoal particle sizes, morphologies, and length to width ratios), accompanied by sediment geochemistry data from high-resolution XRF core scanning. The studied lakes are located in the Lena-Amga interfluve of the Central Yakutian Lowlands, the Verkhoyansk Mountains, and the Oymyakon Highlands. The new data cover both thermokarst and glacial lakes, and a range from remote to rural settings and low to high elevations. Charcoal concentration in the lowland lakes is on average three times as high as in the highland lakes. Contrary to our hypothesis, charcoal concentration in most lakes is negatively correlated to many XRF-derived lithogenic elements indicating detrital input from catchment erosion (e.g., Ti, K). Reminiscent of earlier findings [1], multiple lowland sites share a signal of sharply decreasing biomass burning around 1300 CE. This coincides with the initial settlement of the Sakha people and increased catchment erosion. The new fire reconstructions allow for the evaluation of potential human impacts on past fire regime changes in Yakutia, while improving the region’s representation in global synthesis studies.[1]  Glückler R. et al. (2021): Wildfire history of the boreal forest of south-western Yakutia (Siberia) over the last two millennia documented by a lake-sediment charcoal record. Biogeosciences 18 (13): 4185–4209. https://doi.org/10.5194/bg-18-4185-2021.
In-stream measurements at low-flow reveals transport and denitrification patterns in the sub-surface
Authors: Vautier Camille , Coche Alexandre , de Dreuzy Jean-Raynald , Pinay Gilles
Published: March 2024

Excess nitrogen in surface and groundwater, mainly in the form of nitrates, is a major concern for all stakeholders, because it leads to the degradation of drinking water resources and to the eutrophication of ecosystems. The export of nitrogen from inland to the coast is strongly determined by the transport and denitrification processes occurring in headwater catchments. Yet, most regulatory frameworks, such as the EU Water Framework Directive, impose the monitoring of medium-to-large rivers (> 100 km2) while headwaters, too numerous to be systematically monitored, are poorly understood. Headwater catchments are often characterized by strong connections between surface water and shallow aquifers, leading to a high impact of sub-surface processes on river water quality. Understanding the processes occurring in the sub-surface is thus necessary to predict river water quality, but it remains a major challenge because of the difficult access to groundwater.Here we propose a new approach to infer sub-surface processes in headwater catchments from in-stream measurements. In an agricultural catchment, we measured nitrate and silica along headwater streams fed by a crystalline shallow aquifer, during low-flow period. Silica was used as a proxy for water residence time. We observed several trends between the nitrate concentrations and the water residence times, interpreted as the result of distinct patterns of transport and denitrification in the sub-surface. Based on this case study, we propose a general framework to infer the processes occurring in the sub-surface from the resulting chemical trends observed in low-flow streams. Regarding the simplicity of the measurement method, this framework appears as a powerful tool for water management practices. Further studies in several areas in the world will allow to validate its broad applicability.
An integrated modelling framework to predict the fate and transport of antimicrobial resistance in Singapore coastal waters
Authors: Tong Xuneng , You Luhua , Goh Shin Giek , Ng Shimin Charmaine Marie , Zhang Jingjie , Aung Kyaw Thu , Khor Wei Ching , Gin Karina Yew Hoong
Published: March 2024

Predicting the transport and fate of antimicrobial resistance (AMR) in aquatic environments is crucial for managing this pressing environmental issue. We proposed a hybrid modeling framework that couples process-based and data-driven models to predict the spatiotemporal distribution of antibiotics and their related antibiotic resistance genes (ARGs) in Singapore's coastal waters (SCW). In this study, Lincomycin and its related ARGs were selected for analysis. Firstly, this study provides valuable insights into the complex dynamics of ARGs in coastal waters through the application of a meticulously constructed Random Forest (RF) model. This model helps identify key environmental drivers of ARGs, specifically Lincomycin, pH, zinc, DO and temperature, thereby illuminating the factors influencing ARG levels. Subsequently, we applied a process-based model using the Delft 3D suite to simulate the fate and transport of these key environmental drivers. Finally, the outputs from the process-based model were integrated with the RF model to predict ARGs. The modelling framework was calibrated and validated against monthly data collected from 12 sampling points around SCW during 2022-2023. The results revealed that the simulation performance provided 'reasonable prediction' results, with all modeled targets showing an R² above 0.7 and an NSE greater than 0.8. The research presented in this study not only enhances our understanding of the intricate interplay between environmental variables and ARG levels but also has significant implications for environmental and public health management. By emphasizing the importance of specific environmental factors, these models offer a proactive approach to addressing the urgent challenge of antibiotic resistance in coastal ecosystems. This ultimately contributes to the preservation of both the environment and public health.
A million years of regional hydroclimate oscillations in West Africa reconstructed from Lake Bosumtwi
Authors: Vinnepand Mathias , Zeeden Christian , Wonik Thomas , Gosling William , Noren Anders , Kück Jochem , Pierdominici Simona , Voigt Silke , Sadar-Abadi Mehrdad , Ulfers Arne , Danour Sylvester , Afrifa Kweku , Kaboth-Bahr Stefanie
Published: March 2024

Situated within a 1.07 million-year-old meteorite crater, Lake Bosumtwi in Ghana stands as a pivotal location for comprehending fluctuations in the hydro-climatic situation in sub-Sahara West Africa. The region is highly sensitive to climate oscillations due to the movements of the tropical rain belt driven by atmospheric circulation leading to pronounced dry or wet conditions on seasonal to orbital scales. Considering that climatic changes may trigger severe socio-economic crises in this area due to negative impacts on the agricultural sector- especially the cacao farming, a better understanding on the responses of the regional hydro-climatic situation to global warming tendencies is crucial. Recently a robust age-depth model was developed for the lacustrine sequence of Lake Bosumtwi, the only continental record spanning the last million years in West Africa. This provides the unique opportunity to gain detailed insights into the hydroclimatic situation. Yet, the natural gamma radiation (NGR) signal that we interpret as a proxy for terrestrial sediment input throughout the 300 m thick record, triggered by fluvial in wash from the crater rims, shows quasi-cyclic patterns. Based on this along with evidence from additional proxies, we discuss these patterns at Lake Bosumtwi and their relation to orbital forcing including fluctuations in the hydroclimate.
Groundwater vulnerability and pollution risk assessment in the Estonian-Latvian transboundary area
Authors: Männik Magdaleena , Bikše Jānis , Karro Enn
Published: March 2024

Protecting groundwater resources is of fundamental importance as groundwater is a crucial source of drinking water worldwide. Despite its overall abundance, the task of maintaining both the quality and quantity of groundwater is challenging due to population growth and intensified agricultural activities. Therefore, proactive protection measures are needed to prevent the contamination of this vital resource. In order to improve groundwater management and protection, groundwater vulnerability assessment methods are developed to identify the most vulnerable areas.This study focuses on the Estonian-Latvian transboundary area, recognizing the need to effectively manage the protection of the shared resource between the countries. The assessment of the natural groundwater vulnerability in the Estonian-Latvian transboundary area is conducted with the index-based modified DRASTIC method. Particularly crucial in areas characterized by diverse Quaternary sediments and a confined aquifer, a modified version of the DRASTIC method increases precision in vulnerability assessment results. Additionally, a numeric vulnerability assessment method based on pollutant movement time is used to compare and validate the results, enhancing the reliability of the vulnerability maps.In addition to the natural vulnerability assessment, the pollution risk map serves as a valuable tool in identifying areas in need of protection by connecting the impact of anthropogenic pressure with the vulnerability defined by hydrogeological factors. To accomplish this, the DRASTIC-L method is used to determine the pollution risk in the Estonian-Latvian transboundary area. The DRASTIC-L method uses an additional parameter, land use, for a more precise vulnerability assessment.The results emphasize the importance of developing accurate vulnerability assessment methods based on regional geological conditions. While natural vulnerability maps offer insights to the intrinsic vulnerability of an area to groundwater contamination, a comprehensive risk assessment requires the inclusion of pollution risk maps, highlighting the significance of anthropogenic activities in shaping contamination risks.In addition to advancing groundwater vulnerability and pollution risk assessment methodologies, this study emphasizes the necessity of international collaboration. Groundwater flow knows no national borders, highlighting the collective responsibility for protecting this shared resource and ensuring the availability of safe drinking water for present and future generations.
Decadal trends in groundwater quality observed in national groundwater monitoring wells - assessment of climate change effects using machine learning.
Authors: Xenakis Georgios Ikaros , Jessen Søren , Koch Julian , Kazmierczak Jolanta
Published: March 2024

As pressures on water resources are expected to increase due to climate change and population growth, ensuring sufficient quantity and quality of drinking water emerges as a global challenge. Climate change can affect groundwater quantity and quality through changes in chemical equilibria, reaction kinetics, and soil processes induced by shifting temperature, precipitation, and evapotranspiration. However, the impact of climate change on groundwater quality has not been studied thoroughly and thus is identified as an important scientific challenge and knowledge gap. To address this challenge, we analyzed high-quality long-term datasets, spanning from 1993 to 2022 of several environmental and hydroclimatic factors, as well as groundwater quality and quantity, available at national scale in Denmark. Initial results from around 200 groundwater monitoring wells distributed across Denmark show a decrease in pH and oxygen content in most of the wells for the period 1993-2022. Expected results will show the temporal change of selected geogenic compounds and other major chemicals and physical properties and their trends for this climatic period. Machine learning analysis will be applied in future work to identify the main drivers of change in concentrations of selected geogenic compounds, oxygen, and pH, and to create baseline maps of the recent period (2017-2022/23). The baseline maps, representing current conditions, will be derived by geospatial machine learning modelling frameworks linking covariate maps with borehole scale information of water quality parameters. How to distinguish the impacts of climate change from human-induced changes such as pumping, as well as link observed trends in the past, current baseline maps, and expected future hydroclimatic changes to investigate groundwater quality patterns under future conditions still needs to be studied. As some geogenic compounds are harmful to human health and the environment, decrease drinking water quality and increase purification costs, a better understanding of the linkages between climate change and groundwater chemistry will be vital for future groundwater management in Denmark. The developed machine learning model and its potential for global upscaling could contribute to sustainable groundwater management worldwide.
Global atmospheric impacts of aerosols emitted from the 2023 Canadian wildfires
Authors: Rosu Iulian-Alin , Kasoar Matt , Boletti Eirini , Parrington Mark , Voulgarakis Apostolos
Published: March 2024

Wildfires are a central but relatively unexplored component of the Earth system. Severe wildfire events can lead to intense destruction of both nature and property, as was the case during the anomalously intense 2023 Canadian wildfire event. Last year, approximately 5% of the total forest area of Canada burned [1] [2], which is the highest wildfire damage Canada has ever sustained [1].Conditions pertaining to climate change and modifications in atmospheric conditions are considered to be responsible for this record series of wildfires [3]. Increasing mean temperatures and decreasing humidity in the region has exacerbated wildfire risk. Carbon emissions from the 2023 Canadian wildfires have been the highest on record [4], including large amounts of carbonaceous aerosol which can exert substantial atmospheric radiative forcing. Also, Canadian fire emissions contributed around 20% of global emissions from vegetation fires. Thus, beyond the well-known health risks of wildfire emission compounds, it is important to also study the consequences of these emissions on large-scale atmospheric composition and meteorological behavior.In this work, the global and regional atmospheric impact of the previously mentioned series of wildfires is investigated using the EC-Earth3 and UKESM1 earth system models. Simulated atmospheric conditions with and without the wildfire emissions, as provided by the Copernicus Atmosphere Monitoring Service (CAMS) Global Fire Assimilation System (GFAS), are compared through atmospheric modelling in the context of the Canadian 2023 fire season. The investigation reveals the connections between the emissions produced by this series of wildfires and atmospheric phenomena of importance, such as large-scale circulation, temperature patterns, and precipitation.[1] "Fire Statistics". Canadian Interagency Forest Fire Centre. Retrieved January 4, 2024.[2] The State of Canada’s Forests: Annual Report 2022. Canadian Minister of Natural Resources.[3] Barnes, Clair, et al. "Climate change more than doubled the likelihood of extreme fire weather conditions in eastern Canada." (2023).[4] “Copernicus: Emissions from Canadian wildfires the highest on record – smoke plume reaches Europe”. Atmosphere Monitoring Service, Copernicus. Retrieved January 4, 2024.
Evaluation of the Performance of a Simple Fetch-Based Wave Model in FVCOM in theWadden Sea of the North Sea for the Use in Long-Term Biogeochemical Integrations
Authors: Lettmann Karsten , Mohammadi Ramez , Pätsch Johannes
Published: March 2024

In order to accurately model biogeochemical processes, especially primary production, the prevailing light condition within the water column is very important. In coastal waters, suspended particles can have a large impact on the light field, which itself can be influenced by wave dynamics. Therefore, using a proper wave model is essential to simulate these processes in the ocean and coastal waters.
Using a simple wave model, such as a simple fetch-based parameterization, could be very efficient in long-term simulations and climate-relevant time periods to capture a proper light field and particle resuspension that are necessary to predict phytoplankton dynamics. However, they are limited in their ability to model all wave phenomena, such as wave refraction and non-linear wave-wave interactions (e.g. quadruplet and triad interaction), which could be important, especially in shallow coastal waters. Therefore, it is crucial to evaluate the performance of simple wave models against more sophisticated models, such as third-generation surface-gravity wave models, and measurements in coastal waters.
To achieve this goal, a simple fetch-based wave model is implemented into the Finite Volume Community Ocean Model (FVCOM) on an unstructured grid to simulate the North Sea region with a special focus on the shallow area of the Wadden Sea, where suspended material has a particular effect on primary production. A comparison of the wave's hydrodynamic characteristics obtained from this simple wave model against measurements and publicly available model data will be done to evaluate the performance of this simple wave model at hand.
Impacts and risks of “realistic” global warming projections for the 21st century
Authors: Scafetta Nicola
Published: March 2024

The IPCC AR6 assessment of the impacts and risks associated with projected climate changes for the 21st century is both alarming and ambiguous. According to computer projections, global surface may warm from 1.3 to 8.0 °C by 2100, depending on the global climate model (GCM) and the shared socioeconomic pathway (SSP) scenario used for the simulations. Actual climate-change hazards are estimated to be high and very high if the global surface temperature rises, respectively, more than 2.0 °C and 3.0 °C above pre-industrial levels. Recent studies, however, showed that a substantial number of CMIP6 GCMs run “too hot” because they appear to be too sensitive to radiative forcing, and that the high/extreme emission scenarios SSP3-7.0 and SSP5-8.5 must be rejected because judged to be "unlikely" and "highly unlikely", respectively. Yet, the IPCC AR6 mostly focused on such alarmistic scenarios for risk assessments. This paper examines the impacts and risks of “realistic” climate change projections for the 21st century generated by assessing the theoretical models and integrating them with the existing empirical knowledge on global warming and the various natural cycles of climate change that have been recorded by a variety of scientists and historians. This is achieved by combining the "realistic" SSP2-4.5 scenario and empirically optimized climate modeling. The GCM macro-ensemble that best hindcast the global surface warming observed from 1980–1990 to 2012–2022 is found to be made up of models that are characterized by a low equilibrium climate sensitivity (ECS) (1.5
Diverse and high pollution of microplastics in seasonal snow across Northeastern China
Authors: Wang Xin , Wen Hanxuan
Published: March 2024

Snow scavenging is recognized as one of the major sinks for atmospheric microplastics (MPs). However, little is known about the properties of MPs in large-scale surface snow. Using Nile Red staining and micro-Fourier transform infrared spectroscopy, we identified the shapes, sizes, and polymer components of MPs in seasonal snow across northeastern (NE) China, a major industrial area. The average concentration of MPs was (4.52 ± 3.05) × 104 MPs L−1 , and the highest contamination (6.65 ± 3.89) × 104 MPs L−1 was observed in Changbai Mountains, which was the highest concentration observed in surface snow to the extent of literature. The majority of snow MPs were smaller than 50 μm and composed primarily of fragments. Ethylene vinyl acetate and polyethylene were the dominant contributors to their chemical components. Investigation with positive matrix factorization revealed that the MPs were primarily generated by debris from packaging materials, followed by industrial and construction activities. In addition, the winter atmospheric circulation over the northwestern Siberian and Mongolian plateaus likely dominated the wide-range dispersion and deposition of the MPs across NE China. These results provide a first comprehensive perspective of MPs from sources to removal associated with snow in a large geographic region.
Using machine learning to model Soil Aggregate Stability as an indicator for soil erosion susceptibility at the catchment scale
Authors: Feldmann Deborah , Kuhwald Michael , Saggau Philipp , Duttmann Rainer
Published: March 2024

Soil aggregate stability (AS) is a key component for numerous soil processes and a significant factor in soil erosion. Despite its significance, the research on AS has been comparatively limited, possibly due to the high monetary, work and time expense needed to gain data. Furthermore, the spatial distribution of aggregate stability is influenced by various topographic and physical factors, such as surface curvature and soil characteristics. It is also affected by non-numerical conditions, for instance land use and crop type. This combination of quantitative and qualitative variables highlights the complexity of AS modeling. Therefore, it is even more important to gain further insight on the spatial distribution and prediction techniques suitable for AS.The aim of the ESTABLE project is to model the spatial variability and distribution of AS and analyze its relationship to soil erosion processes at the catchment scale. To accomplish this, a total of 500 topsoil samples were collected from the two study sites in Northern Germany (Lamspringe and Ascheberg). All soil samples were analyzed for aggregate stability, soil texture, organic carbon content, pH, and electric conductivity.To represent the complexity of the relationship of factors influencing AS, various machine learning models, including Boosted Tree and Random Forest, are tested to implement categorical data in addition to the wide range of numerical input variables. These models were evaluated based on their performance, parameterization, and interpretability in comparison to traditional interpolation techniques like multiple linear regression and regression kriging. It has become evident that most machine learning techniques are more effective at capturing the intricate interactions that influence aggregate stability.The best performing model is then used to verify, that low aggregate stability areas are also prone to erosion. The use of UAVs and field mapping enable a detailed and accurate assessment of the spatial distribution of soil erosion. This model could also serve as a valuable tool for other sites and subsequent studies.
Improving our Understanding of Melt-Affected Ice Cores Through In-Situ Percolation Tracer Experiments
Authors: Moser Dorothea Elisabeth , Thomas Elizabeth R. , Spolaor Andrea , Gallet Jean-Charles , Freitag Johannes
Published: March 2024

Rising global temperatures and accelerated melting cause glaciers across the globe to shrink, thereby hampering our ability to reconstruct past climate from ice cores across the globe. In this context, melt-induced alterations of chemical signals in ice cores are an increasing issue not only for researchers working on mid- and low-latitude glaciers but in coastal Antarctica, Greenland, and other (sub-)polar sites, too.Aiming to contribute to a more comprehensive understanding of ice cores as environmental archives when affected by melt, Moser et al. (2023) have recently conducted an in-depth review of the existing literature regarding external drivers of melt events, physics of melt layer formation and behaviour during snow metamorphism, identification and quantification of melt, structural characteristics of melt features, effects of melting on records of chemical impurities, stable water isotopic signatures, and gas record, as well as applications of melt layers as environmental proxies. By briefly walking through formation, manifestation and potential interpretation of refrozen melt sections, we here provide an overview of those aspects of near-surface melting, which are important for ice-core record interpretation more widely.Against this backdrop of existing research and gaps of knowledge, we present the setup and first results of percolation tracer experiments conducted during a field campaign near Ny-Ålesund, Svalbard, in March-April 2023. Showing the alteration of snowpack structure and chemistry through liquid water in-situ, the experiments have provided new insights into (1) meltwater flow and refreezing processes in the vicinity of Ny-Ålesund, and (2) the informational value of stable water isotope records before and after rain-on-snow induced melt events. Finally, we compare these in-situ observations to high-resolution structural scans of melt features in ice cores to explore further conclusions, which help to improve our understanding of melt-affected ice cores. Moser, D. E., Thomas, E. R., Nehrbass-Ahles, C., Eichler, A., & Wolff, E. (2023). Melt-Affected Ice Cores for (Sub-)Polar Research in a Warming World. EGUsphere Preprint. https://doi.org/10.5194/egusphere-2023-1939
Exploring the Synergy of Enhanced Weathering and Rhizobacteria in Sustainable Agriculture
Authors: Niron Harun , Steinwidder Laura , Rijnders Jet , Boito Lucilla , Vicca Sara
Published: March 2024

Enhanced Weathering (EW) is a promising negative emissions technology for atmospheric CO2 removal, particularly in agricultural setups. Spreading silicate rock powder, such as basalt, over extensive agricultural lands not only sequesters CO2 but also provides essential nutrients like K, Mg, and Fe to crops. However, the efficiency of carbon sequestration in this system varies strongly, posing a challenge to widespread adoption, particularly among stakeholders like farmers.Climate change intensifies weather extremes, exacerbating crop drought and heat stress, with detrimental effects on production. To address these challenges, the use of Plant Growth-Promoting Rhizobacteria (PGPR), such as Bacillus subtilis, emerges as a nature-based strategy. In addition to inducing stress resistance, B. subtilis possesses Fe and P solubilizing features, potentially enhancing EW rates. Indeed, our previous study demonstrated B. subtilis efficacy in accelerating basalt weathering by increasing Ca, Mg, and Fe dissolution in bare soil.In a maize mesocosm experiment combining B. subtilis, basalt, and water content as variables, we observed a significant impact of B. subtilis on plant biomass in treatments, while basalt showed no major effect. In treatments with reduced irrigation, plants that were amended with basalt and B. subtilis displayed elevated leaf chlorophyll levels and improved nitrogen balance compared to plants that were not amended with B. subtilis. Across both high and low watering conditions, plants amended with basalt and B. subtilis exhibited enhanced photosynthetic activity and improved stomatal regulation. These findings suggest a promising added effect of PGPR B. subtilis to basalt-based EW for efficient crop health management under varying environmental conditions. This synergy has the potential to address the challenge of variable carbon sequestration efficiency and can provide a robust basis for improving crop health under diverse settings.
Land use intensity has a stronger effect on the temperature sensitivity of soil microbial carbon cycling processes than long-term climate change.
Authors: Domeignoz-Horta Luiz , McLaughlin Matthew , Soares Fontes Marcelo , Sebag David , Aubertin Marie-Liesse , Verrecchia Eric , Kahmen Ansgar , Nelson Daniel , Laine Anna-Liisa , Niklaus Pascal , Butterbach-Bahl Klaus , Kiese Ralf
Published: March 2024

Microbes are responsible for the cycling of carbon (C) in soils, and predicted changes in soil C stocks under climate change are highly sensitive to shifts in the mechanisms thought to control microbial physiological response to warming. Two mechanisms have been proposed to explain the long-term effects of warming on microbial physiology: microbial thermal acclimation and changes in the quantity and quality of substrates available for microbial metabolism. However, studies disentangling these two mechanisms and assessing how land use affects them are lacking. To disentangle the drivers of changes in microbial physiology in response to long-term climate change, we sampled soils from a 10-year old global change and land use intensity experiment at the Pre-Alpine Terrestrial Environmental Observatories (TERENO project). The global change treatment includes a warming of 2oC and a reduction in precipitation of about 450 mm. We took soil samples at different time-points during the spring season and depths. We performed short-term laboratory incubations over a range of temperatures to measure the relationships between temperature sensitivity of physiology (growth, respiration, carbon use efficiency with the 18O-H2O method) and we characterized the quantity and quality of soil organic matter with the ramped thermal rock-eval pyrolysis at different depths. In this ongoing project, we did not observe thermal acclimation of microbial respiration, growth or CUE to climate change. However, fertilization had the strongest effect on the temperature sensitivity of microbial respiration. In the next steps of this project, we will determine whether climate change and/or land use intensity has an effect on soil organic carbon fractions with different residence times. Our preliminary results show that land use intensity has an overriding effect on the temperature sensitivity of microbial processes compared to long-term climate change.
Insights from a Year-long Study on Ice-Nucleating Particles in Helsinki
Authors: Perez Fogwill Germán , Welti André , Nontasin Patipun , Mustonen Linnea , Álvarez Piedehierro Ana , Lehtipalo Katrianne
Published: March 2024

This study explores the seasonal dynamics of ice-nucleating particles (INPs) in Helsinki over a year. Using an automatic sampler, we collected atmospheric particle samples daily onto filters, which were subsequently analyzed offline through drop freezing experiments in our laboratory. The year-long measurements are used to study the temporal variations and seasonal patterns of INP concentrations in Helsinki. Measurements of different meteorological variables are also considered for the study. Additionally, we present case studies with higher temporal resolution. The offline laboratory analysis of the collected filters enables the characterization of INP concentrations in an urban environment with changing aerosols sources in different seasons. The presented results contribute to the understanding of the variation of INPs in an environment where anthropogenic activity is a main contributor to the present aerosol load.
MicroWave Expertise center : a work environment for microwave data exploration
Authors: Frery Marie-Laure , Siméon Mathilde , Fjortoft Roger , Charlois Sébastien , Prugniaux Mélanie , Raynal Matthias
Published: March 2024

The MicroWave Expertise center has first been developed to provide a  work environment to support the calibration/validations activities and address the high resolution of Surface Water Ocean Topography (SWOT) mission, launched on December 16th, 2022.  Onboard, the new instrument ‘KaRIn’, is a revolution for both oceanography and hydrology communities and gives access to small scale measurements over ocean, worldwide river heights and flows, and lake heights.With optimized storage and computation methods, the MicroWave Expertise Center is designed to ease the exploration and studies of 16TB/day products. The tools developed for SWOT are generic and can now be applied to any altimetric mission.Experts are provided simple and scriptable explore numerous data providers such as copernicus dias, ecmwf, hydroweb.next.Some tutorials are already available along with visualisation tools. And the list will be growing up in close future from users requirements.The expertise center is operational and ensure SWOT calval activities. Prospects address SWOT ocean and hydrology studies but could be enlarged to  hydrological research, multi-sensor comparison
Analysis of debris-flow dynamics based on seismic signals: Insights from laboratory experiments and field monitoring
Authors: Cui Yifei , Zhou Xinzhi , Yan Yan , Tang Hui
Published: March 2024

Debris flow can cause severe damage due to its high velocity, large volume, and long transport distance. The monitoring and early warning system is one of the key approaches in debris-flow hazard mitigation. Monitoring and early warning equipment are easily damaged by debris flows, which directly affects the monitoring system. In recent years, environmental seismology has provided a new research method for debris flow monitoring and early warning due to the advantages of long-distance, non-contact monitoring and rich, dynamic information. However, we still lack essential understanding regarding the relationship between the basal force and physical properties of debris flow at the channel bed and the relationship between the impact mechanisms of the granular flow barrier and the generated seismic signal. We designed a series of flume experiments to analyze the distribution of base force and the link between the impact mechanism and seismic signals in geophysical flow. We examine the probability density function (PDF) of the basal impact force and establish a relationship between the PDFs distribution parameters and the geophysical flow's physical properties. We found that there are peak amplitude thresholds of the seismic signal that can distinguish between runup and pile-up mechanisms when considering engineering mitigation measures in the channel. Finally, by integrating laboratory experiments and field monitoring, we establish the relationship between seismic signals and debris-flow dynamics.
Integrating Quality Control and Data Gathering in Space-Time Analysis for Temperature Assessment in European Cities
Authors: Amini Setareh , Brönnimann Stefan
Published: March 2024

Urban areas across Europe are facing unprecedented challenges from climate change, further intensified by the emergence of urban heat islands (UHIs). The resulting elevated temperatures within cities have profound implications for public health, energy consumption, and overall urban liveability. Climate adaptation and evidence-based urban planning that are needed to address these pressing issues require a better understanding of urban temperature dynamics. To address this pressing issue, our research aims to bridge a critical gap in our understanding of urban temperature dynamics through a comprehensive space-time analysis focused on 9 European cities. The primary emphasis at this stage is placed on the foundational step: collection, enhancement, and intercomparison of local temperature information. This initiative, which is part of the European COST-Action FAIRNESS (https://www.fairness-ca20108.eu/), is driven by the imperative need for accurate and localized data to inform evidence-based urban planning and climate adaptation strategies, highlighting the urgency and significance of our research. We collected measurements from nine European cities, namely, Amsterdam, Basel, Bern, Biel, Turku, Rennes, Novi Sad, Birmingham, and Zurich The initial phase of the work involved the collection of raw data from different networks, encompassing varying time periods. The datasets exhibited considerable diversity in formats and temporal resolutions, necessitating meticulous handling. In parallel, metadata relevant to each dataset was collected. The primary step was to standardize all data into a common file format, with the Station Exchange Format (SEF) being the chosen standard. During this formatting process, a version with harmonized time resolution was generated, ensuring coherence across the datasets. Subsequently, a series of automatic quality control procedures were developed to systematically enhance the reliability and precision of the datasets. These procedures were designed to be universally applicable to all stations, promoting consistency in the assessment of temperature data. Additionally, for certain networks, a radiation correction was implemented to further refine the accuracy of the collected information. Looking ahead, the datasets will be published, offering accessibility to urban planners and other stakeholders. The outcomes of this preliminary phase not only contribute to advancing space-time analysis in temperature assessment but also establish a robust foundation for subsequent research stages. The significance of this work resonates with urban planners, environmental scientists, and policymakers actively involved in crafting localized strategies for climate-resilient urban planning in European cities.
The role of pre-eruptive bubble characteristics in modulating andesitic magma fragmentation
Authors: Weller Daniel , Montanaro Cristian , Dingwell Donald , Cronin Shane , Scheu Bettina
Published: March 2024

Various processes involving nucleation, growth, and interaction of bubbles occur as water-rich magma —e.g., of andesitic composition— ascends through a volcanic conduit towards shallower depths. These mechanisms significantly affect the properties of the magma upon fragmentation, including porosity, permeability, and magma strength. Such properties, in turn, can influence the dynamics of fragmentation —such as its speed and efficiency— thus impacting eruptive behaviour. Precisely measuring and understanding how the pre-eruptive bubble size distribution and texture affect fragmentation dynamics poses a scientific challenge that lacks comprehensive quantification methods to date.In this study, we employed a combination of analytical and experimental methods to explore the processes governing bubble formation and to quantify the impact of their size, distribution, and texture on andesitic magma fragmentation. Our investigation utilised a series of andesitic products originating from the AD 1655 Burrell eruption of Mt. Taranaki, New Zealand. The pyroclasts from this eruption exhibited varying porosity (10 – 80 %) and permeability (10-16 - 10-11 m²). Using scanning electron microscope imagery, we employed FOAMS, an image analysis software, to compute bubble size distributions. Subsequently, we performed rapid decompression experiments on selected samples, capturing the process of fragmentation and clast ejection using two synchronized high-speed cameras. This approach allowed us to track fracture location and evolution over time, enabling the assessment of fragmentation speed and fracture density. Further analyses involved examining the grain size distribution of generated clasts to evaluate the efficiency of fragmentation.Our texture analysis unveiled that bubble nucleation and growth occurred concurrently during various eruption stages, as evidenced by changes in bubble number density, porosity, and polydispersivity. Correlating these results with the high-speed camera analysis, we observed a significant influence of bubble number density and average diameter on fragmentation speed. Moreover, large bubble clusters appeared to intensify fragmentation speed by weakening local rock strength. Both the number and diameter of bubbles exhibited additional relationships with particle size, efficiency of fragmentation, and fracture density in our samples.Drawing from the correlation between bubble texture and petrophysical properties, we proposed a conceptual model elucidating the impact of bubble textures on fragmentation dynamics. Furthermore, we evaluated and discussed our findings in the context of previously developed eruptive models of Mt. Taranaki. Our findings, together with variation in the density of the expelled particle-gas mixture, align well with the model depicting a transition in eruptive behaviour and plume stability of Mt. Taranaki during the deposition of the Burrell formation. 
A monitoring-forecasting tool for advancing surface water quality management in lakes, reservoirs and major rivers 
Authors: Kakati Riddick , Dall’Amico Matteo , Toffolon Marco , Di Paolo Federico , Tasin Stefano , Piccolroaz Sebastiano
Published: March 2024

In water resources management, predictive services are essential to support sustainable planning and operations over a range of time scales, from the short term (days) to the medium term (seasons) to the long term (years to decades). Current forecasting tools mainly address water availability (i.e., quantity), with limited practical applications for water quality. Within the framework of the project called “Strumenti di monitoraggio e previsionali sullo stato di QUalità delle Acque Superficiali” (SQUAS; founded by CARITRO Foundation, Italy; website: https://sites.google.com/unitn.it/hydrosquas), we aim to fill this gap, which is particularly relevant in view of the ongoing transformation of water resources due to rapidly changing climatic conditions. More specifically, we aim to 1) increase the accessibility of tools for diagnosing and predicting surface water quality for use by local authorities and managers of surface water resources, such as agricultural consortia, hydroelectric plant operators, municipal companies, and public entities, and 2) improve the ability of these entities to plan and manage water resources efficiently and sustainably. Anchored in a multidisciplinary approach, the project integrates physical-based modelling used to forecast key water quality parameters with satellite remote sensing data for monitoring purposes. As for the modelling component, the project will be based on the widely used air2water and air2stream models for water temperature prediction in lakes and rivers. Central to the project is the revision, improvement and extension of these models by including water quality variables (e.g., turbidity, dissolved oxygen) and by integrating them into a state-of-the-art web-based Geographic Information System (GIS) platform. The web-GIS platform will not only allow to forecast future conditions based on the above models but also allow for real-time monitoring of water quality. Its Python fast-api based interface will provide a user-friendly GUI for the user interaction, using any web browser. The speed of computation of the forecasting models will be ensured by efficient Cython-based functions. The intuitive interface of the web-GIS platform will appeal to a wide range of users, from policy makers and water resource managers to academic researchers, facilitating informed decision-making and sustainable management practices. An interactive presentation of the web-GIS tool will be given during the session.