bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Secondary Ice Production Processes on the Simulation of ice pellets using the Predicted Particle Properties microphysics scheme
Authors: Lachapelle Mathieu , Cholette Mélissa , Thériault Julie M.
Published: March 2024

Abstract. Ice pellets can form when supercooled raindrops collide with small ice particles that can be generated through secondary ice production processes. The use of atmospheric models that neglect these collisions can lead to an overestimation of freezing rain. The objective of this study is therefore to understand the impacts of collisional freezing and secondary ice production on simulations of ice pellets and freezing rain. We studied the properties of precipitation simulated with the microphysical scheme Predicted Particle Properties (P3) for two distinct secondary ice production processes. Possible improvements to the representation of ice pellets and ice crystals in P3 were analyzed by simulating an ice pellet storm that occurred over eastern Canada in January 2020. Those simulations showed that adding secondary ice production processes increased the accumulation of ice pellets but led to unrealistic size distributions of precipitation particles. Realistic size distributions of ice pellets were obtained by modifying the collection of rain by small ice particles and the merging criteria of ice categories in P3.
MIR spectroscopy combined with meteorological data can estimate soil compaction risks in top and subsoils.
Authors: de Santana Felipe , Hall Rebecca , Shi Longnan , Lowe Victoria , Hodgson Jim , Daly Karen
Published: March 2024

Soil compaction is an important physical characteristic that affects agricultural productivity by increasing soil density, which reduces the volume of a given soil mass. Due to the higher compaction, plant roots find resistance in penetrating deeply into the soil, limiting their access to essential nutrients and moisture, impacting the plant health with lower levels of N, P and K, resulting in lower productivity. Soil compaction can also reduce soil porosity, aeration, carbon mineralisation/sequestration and increasing the production of greenhouse gases through denitrification in anaerobic sites. Besides that, soil compaction can cause surface runoff and erosion, increasing the risk of flooding and soil loss. A partial recuperation of compacted soils is an expensive and labour-intensive task. In addition, agricultural land expansion for crops is limited. Hence, mapping agricultural areas at risk of soil compaction is essential to implement strategies to mitigate the adverse effects of soil compaction.Soil particle size and soil drainage were used to classify topsoil's (T) compaction risk class. For subsoil (S) soils (after horizon A), the subsoil particle size, packing density (bulk density + 0.009 * clay (%)), soil drainage and field capacity days were used to estimate the compaction risks. The main problem of this strategy is that these analyses are expensive and time-consuming, i.e., soil particle size analysis requires an average time of 1 month per 100 samples and costs ~ 40.00 per sample. Bulk density analysis costs ~ € 7.00 per sample and is also time-consuming; consequently, bulk density values are mainly predicted using pedo-transfer functions in mapping studies.To speed up the analysis and minimise the costs, vibrational spectroscopy combined with chemometrics was used to determine soil particle size and bulk density. Both parameters were combined with field capacity days (obtained from 104 national wide meteorological stations) and drainage class (obtained from Irish - Environmental Protection Agency) to map soil compaction risk areas in the northern half of the Republic of Ireland with a resolution of 4 km2 (2x2km) and 1 km2 grid for regional and periurban regions, respectively (Tellus achieve). To confidentially map these regions, spectral control charts based on PCA were used to identify unrepresentative sample spectra based on the spectral models used. Only samples classified as representative were predicted by the spectral models. Using this strategy, we could predict ~ 90% (T) and ~66% (S) compaction risks in non-peat soils. The prediction results showed that ~33% (T) and ~43% (S) were classified as high risks of compaction, ~19% (T) and ~23% (S) as moderate, and ~37% (T) and
Analysis of coastal breeze and low-level jets events from numerical modeling and LiDAR measurements
Authors: Landreau Mathieu , Conan Boris , Calmet Isabelle
Published: March 2024

The complexity and variety of phenomena that can occur in coastal areas (e.g. breezes, internal boundary layers, low-level jets (LLJ)) often result in wind profiles strongly deviating from the Monin-Obukhov similarity theory. Moreover, the lack of offshore experimental data leads to gaps in knowledge of the marine coastal atmospheric boundary layer (MCABL). Characterizing the wind resources in MCABL has been identified by Veers et al. (2022) as one “Grand Challenge” for the development of offshore wind farms.To partially fill these gaps, a joint numerical and experimental study is currently being performed. In 2020, scanning LiDAR measurements were carried out within a few kilometers of the French Atlantic coastline (Conan and Visich, 2023). In parallel, mesoscale to microscale simulations are performed with the Weather Research and Forecasting (WRF) code, using the grid-nesting method to progressively decrease the horizontal mesh size from a few kilometers (RANS modeling) down to a hundred meters (LES modeling). The simulation, giving access to more atmospheric variables in a large area, allows a complementary analysis.On a particular week of this experiment, complex velocity profiles have been observed in the LiDAR data, highlighting the presence of LLJ and high wind-shear events. Velocity profiles from RANS simulations show good comparison with LiDAR data, which suggests that the mechanisms responsible for the observed phenomena are well reproduced. In addition, these large-scale simulations allow the identification of a complete sea-breeze circulation in the complex coastal area of Brittany.The marine extent of the sea-breeze can be defined as the isoline where cross-coast velocity component decreases with the distance from the coast to a value of 1 m/s (Arritt, 1989 ; Finkele et al., 1995). The RANS results indicate that the sea-breeze can reach a distance of 70 km offshore during the studied period. A first analysis of the simulations also suggests that the nighttime LLJ observed on the Atlantic coast is related to the residual of a sea-breeze front moving southward from the north coast of Britanny.Analysis of the LES simulations will permit to study more precisely the onset of the sea-breeze, the evolution of the LLJ across the coastline (related to transition in atmospheric stability and surface roughness) or the turbulence kinetic energy budget in the jet core. Arritt, R.W. 1989. Quarterly Journal of the Royal Meteorological Society 115 (487): 547‑70. https://doi.org/10.1002/qj.49711548707.Conan, B.,and A. Visich. 2023. Wind Energy Science Discussions, October, 1‑23. https://doi.org/10.5194/wes-2023-141.Finkele, K., et al.. 1995. Boundary-Layer Meteorology 73 (3): 299‑317. https://doi.org/10.1007/BF00711261.Veers, P., et al.. Wind Energy Science 7 (6): 2491‑96. https://doi.org/10.5194/wes-7-2491-2022.
Is green waste fertilization in agriculture an important source of VOC?  A field study based on  PTR-Qi-TOF-MS and eddy covariance
Authors: Liu Yang , Buysse Pauline , Loubet Benjamin , Lafouge Florence , Feron Anais , Depuydt Jérémie , Levavasseur Florent , Ciuraru Raluca
Published: March 2024

Agriculture is a potentially large yet poorly characterized source of volatile organic compounds (VOCs). Crops are the largest and most well-known source of VOCs from agriculture. Agricultural management practices, and especially organic fertilization is an especially unknown source of VOCs. A 3-week field campaign was conducted in September 2023 in Saclay, France, 30 km southwest of Paris. We investigated VOC fluxes over a mustard and moha field (cover crops) by eddy covariance using a PTR-Qi-TOF-MS. Green waste was applied during the second week of measurements.We detected over a hundred VOCs with fluxes 3 times above the detection limit, and found that: 1) Oxygenated VOCs and monoterpenes are the most emitted compound groups. 2) High fluxes of methanol, ethanol, acetone, and acetaldehyde were detected after organic fertilizer spread. 3) A relatively strong sesquiterpene emission was observed after fertilization and was not previously reported. Our results provide new insights into VOC emissions from cover crops and green waste application.    
Multi-sensor System for Detecting Land Subsidence in Central Taiwan
Authors: Hung Wei-Chia , Lin Shao-Hung , Chen Yi-An , Lin Guan-Zhong
Published: March 2024

During 1992-2022 excessive withdrawal groundwater caused large-scale aquifer-system compaction and land subsidence in the Choshui River Alluvial Fan (CRAF) in Taiwan. How to effectively monitor land subsidence has become a major issue in Taiwan. In this paper, we introduce a multiple-sensor monitoring system for detecting land subsidence in central Taiwan, including 46 continuous operation reference stations (CORS), multi-temporal InSAR (MT-InSAR), a 1000-km leveling network, 36 multi-layer compaction monitoring wells, 7 automatic record extensometers, and 223 groundwater monitoring wells. This system can monitor the areal extent of land subsidence and provide data for studying the mechanism of land subsidence. We also develop new low-cost high-performance GNSS equipment and automatic multi-layer compaction monitoring equipment to monitor different aquifer compaction. We also use the Internet of Things (IoT) technology to control and manage the sensors and develop a big data processing procedure to analyse the data from the system of sensors. The procedure makes land subsidence monitoring more efficient and intelligent.
A Transformer-Based Model for Effective Representation of Geospatial Data and Context
Authors: Deng Rui , Li Ziqi , Wang Mingshu
Published: March 2024

Machine learning (ML) and Artificial Intelligence (AI) models have been increasingly adopted for geospatial tasks. However, geospatial data (such as points and raster cells) are often influenced by underlying spatial effects, and current model designs often lack adequate consideration of these effects. Determining the efficient model structure for representing geospatial data and capturing the underlying complex spatial and contextual effects still needs to be explored. To address this gap, we propose a Transformer-like encoder-decoder architecture to first represent geospatial data with respect to their corresponding geospatial context, and then decode the representation for task-specific inferences. The encoder consists of embedding layers that transform the input location and attributes of geospatial data into meaningful embedding vectors. The decoder comprises task-specific neural network layers that map the encoder outputs to the final output. Spatial contextual effects are measured using explainable artificial intelligence (XAI) methods. We evaluate and compare the performance of our model with other model structures on both synthetic and real-world datasets for spatial regression and interpolation tasks. This work proposes a generalizable approach to better modeling and measuring complex spatial contextual effects, potentially contribute to efficient and reliable urban analytic applications that require geo-context information.
Water-driven geothermal heat extraction with simultaneous CO2 injection: overview of concepts, benefits and challenges
Authors: Loschetter Annick , Kervévan Christophe , Stead Rowena , Le Guénan Thomas
Published: March 2024

Geothermal energy production and CCS (Carbon Capture and Storage) represent promising technological solutions to help mitigate climate change and aid the current global energy crisis. In recent years, the number of concepts that propose to combine and mutualize these technologies has risen dramatically. While a number of concepts (notably CPG and CO2-EGS) use supercritical CO2 as the heat vector, another promising route for hybridization is to inject dissolved CO2 in the geothermal brine. This is the focus of our current work. An extensive literature review was carried out of the concepts, complemented by interviews of some of the developers.A few concepts are still theoretical (only described in the literature), but most technological ones are on the way to pilot/demonstration projects at progressively increasing scale. The main projects and their associated sites are:CO2-DISSOLVED technology, with potential sites identified in the Paris basin (France);
AAT-G / Cleag technology, with a site in Croatia;
Related projects CarbFix, GECO and SUCCEED, with sites in Hellisheidi (Iceland), Nesjavellir (Iceland), Bochum (Germany), Kızıldere (Turkey), Castelnuovo in Italy (as case study due to permitting issues);
Reinjection of CO2 from geothermal brines at Ngatamariki and Te Huka sites in New Zealand.
Despite similarities, these solutions are differentiated by their purpose:either to store CO2 from an external industrial emitter (notably for the CO2-Dissolved concept), thus bringing a contribution to CCS,
or to reinject CO2 emitted by CO2-rich brine during geothermal exploitation, thus bringing geothermal to near-zero emissions.
Because of the CO2 solubility limit in brine, the performance of heat extraction is generally higher than that of CO2 storage. For instance the CO2-DISSOLVED technology is particularly well-suited to small CO2 industrial emitters (ca.
Emission location shape atmospheric and climate effects of alternative fuels in domestic aviation
Authors: Klenner Jan , Lund Marianne Tronstad , Muri Helene , Strømman Anders Hammer
Published: March 2024

Aviation emissions significantly contribute to global warming, necessitating reductions to align with the 1.5°C target. Beyond carbon dioxide emissions from fossil jet fuel combustion, non-CO2 emissions play a crucial role, exhibiting diverse impacts on atmospheric chemistry and radiative forcing based on geographic location, altitude, and time. To enhance comprehension of aviation emissions and potential alternative fuels, we introduce the AviTeam model—a data-driven, high-resolution model utilizing ADS-B data to quantify emissions of various species, including NOx, CO, BC, SO2, H2O, and hydrocarbons, alongside CO2. 

Integrating AviTeam's emission inventory with the OsloCTM3 chemical transport model allows us to assess the regional impact of aviation emissions. We explore the atmospheric chemistry effects of transitioning to liquid hydrogen and synthetic fuels as alternatives to fossil jet fuel. Additionally, a contrail formation potential analysis reveals that hydrogen exhibits a higher non-persistent contrail-forming potential than kerosene due to its elevated water vapor emissions. Our findings suggest that in high-latitude regions, adopting alternative aviation fuels may yield different mitigation effects with fewer trade-offs between non-CO2 and CO2 impacts than global averages suggest. However, the mitigation potential of alternative aviation fuels from a life cycle perspective is constrained to 44–56% reduction in GWP100, attributed to short-lived climate forcings and additional fuel demand for liquid hydrogen. Notably, the mitigation potential is less pronounced on shorter flights. Our results underscore the importance of integrating models like AviTeam with chemical transport models and life cycle perspectives to emphasize the significance of accounting for local atmospheric conditions and better understand variability in aviation emissions studies. 
Using Novel Lake-based Snowfall Measurements in the Alps and Himalayas to optimise Cloud and Precipitation processes in a Regional Atmospheric Model (MetUM)
Authors: Gumber Siddharth , Orr Andrew , Field Paul , Pritchard Hamish , Covi Federico , Deb Pranab , Girona-Mata Marc , Widmann Martin , Potter Emily
Published: March 2024

Complex mountain orography induces sharp gradients in precipitation accumulation locally. The associated complexity in understanding these events depends on local orographic, microphysical, and dynamical conditions, which makes simulating snowfall a major challenge for regional atmospheric models. This study addresses these deficiencies by using a unique repository of snowfall measurements at a range of ‘super sites’ in the European Alps and Himalayas, which are used to produce a precipitation-optimised version of the atmosphere-only UK Met Office Unified Model (MetUM) at a spatial resolution of 1.5 km. The snowfall measurements involve using the winter time-series of water pressure in frozen lakes to measure the mass of falling snow during extreme precipitation events directly over the lake area, which are comparable in size to the model’s grid cells. Development of the precipitation-optimised version of the MetUM involves undertaking a series of model sensitivity experiments focused on varying the physical representation of cloud and precipitation microphysics, with the aim of better capturing the onset and end periods, and amounts of received snowfall during these extreme events. The MetUM is configured to use a double moment cloud microphysical scheme (CASIM: Cloud AeroSol Interacting Microphysics) with prescribed hydrometeor spectral attributes necessary to quantify both the auto-conversion rates and thresholds for the cloud conversion to take place. Results from these experiments suggest that local microphysical processes, often subsumed within small spatial scales, can influence dynamics at larger scales, impacting gradients in precipitation. Cloud radiative properties, including the hydrometeor effective radii and optical depths are further validated against satellite-based observations.
Carbonate-associated organic matter: A form of “dissolvable” organic matter?
Authors: Zeller Mary , Van Dam Bryce , McKenna Amy , Lopes Christian , Osburn Christopher , Fourqurean James , John Kominoski , Böttcher Michael
Published: March 2024

Carbonate-associated organic matter (CAOM) is the organic matter associated with carbonate minerals, and a survey of carbonate-rich surface sediments suggests that it is incorporated at a consistent amount scaling with the internal surface area of the carbonate grains. As the carbonate sediment is sensitive to changes in saturation state due to benthic biogeochemical processing, we predicted that CAOM could exhibit interesting biogeochemical cycling, based on its potential to bridge particulate and dissolved pools of organic matter. Here, we report on a study in a seagrass meadow in central Florida Bay, USA. We utilize a combination of inorganic stable isotope (C, S, O) and high resolution mass spectrometry (21T FT ICR-MS) techniques to explore the carbon and sulfur cycles here, with a particular emphasis on dissolved organic matter (DOM) characterization. CAOM is examined similar to standard solid phase extraction (SPE-DOM) methods, after first washing carbonate sediment and dissolving it incompletely under a mild hydrochloric acid treatment. The δ34S and δ18O of sulfate, as well as the δ13C of dissolved inorganic carbon (DIC), suggest that the promotion of sulfide oxidation in the seagrass rhizosphere drives rapid carbonate dissolution and re-precipitation cycles. Sulfide oxidation, as well as elevated sulfide concentration, promotes sulfurization of CAOM, which is more sulfurized than porewater and surface water, as 42% of CAOM formulas vs 28% of surface water are sulfurized. Furthermore, a substantial quantity of molecular formulas present in the overlaying surface waters (90% of formulas, 97% by relative abundance) are also present in CAOM. Despite the CAOM sample containing nearly twice the number of formulas compared to surface water, due in part to its higher dissolved organic carbon concentration, these shared formulas make up 75% of the abundance of CAOM formulas. We argue that repeated coupled sulfur and inorganic carbon cycles, intensified by seagrasses, leads to increased sulfurization and release of CAOM, affecting DOM quality in the broader aquatic system. We estimate that approximately 9% of the particulate organic carbon (POC) stored in the sediments of this site are CAOM. Our results suggest that CAOM here is a form of “dissolvable” organic carbon which cycles much more rapidly than POC more broadly.
Identifying key indicators and exploring gender intersectional vulnerabilities to climate change in agricultural households: A study of Central Himalaya
Authors: Choudhary Akshita , Sam Anu Susan , Kaechele Harald , Joshi Pawan Kumar
Published: March 2024

Gender vulnerabilities to climate change are increasingly recognized in the global arena; however, attention to gender in the context of climate change in India is relatively recent. Agriculture is a crucial part of the country’s economy and the agricultural practices in the Indian Himalaya are highly influenced by gender dynamics due to traditional gender roles and various social and cultural constraints. This study provides empirical evidence on how gender plays a role in the susceptibility to climate change from a district of Central Himalaya in Uttarakhand. The study identifies the key indicators that affect vulnerability both within and between genders. Additionally, the gender data is categorized based on caste (social segregation) and lower and higher elevation in the hills (geographical segregation) for investigating gender-specific vulnerabilities - both inter and intra-gender - in agricultural households. The primary data were collected in the months, April - June 2022 from 298 sample households based on stratified sampling selected from 20 villages in the district, Almora, Uttarakhand. Categorical principal component analysis (Cat-PCA) was used to develop weights for adaptive capacity and sensitivity indicators. Based on the Inter-governmental Panel on Climate Change (IPCC) framework 2014 and the theory of intersectionality, an intrinsic gender vulnerability index is developed. A sensitivity analysis approach is further adopted to pinpoint the major indicators influencing gender intersectional vulnerabilities. The expected results go beyond the conventional gender paradigms by exploring the intersectional nature of vulnerability and recognizing the complex interplay of various socioeconomic factors such as caste, education, income, and access to resources that contribute to differential gender vulnerabilities.Keywords: Gender vulnerability, intersectionality, climate change, Cat-PCA, Sensitivity analysis.
Nitrate spatial predictions by means of machine learning to improve groundwater monitoring networks
Authors: Gómez-Escalonilla Victor , Martínez-Santos Pedro , Pacios David , Ruíz-Álvarez Lidia , Díaz-Alcaide Silvia , Montero-González Esperanza , Martín-Loeches Miguel , De la Hera-Portillo África
Published: March 2024

Recently, machine learning approaches are being explored as tools to underpin water management, encompassing applications such as groundwater level prediction and the integration of artificial intelligence combined with classical numerical models. This study introduces a method to support the design of groundwater quality monitoring networks through machine learning spatial predictions. Several supervised classification algorithms were trained to identify spatially distributed variables explaining the presence of nitrates in the groundwater of various aquifers in central Spain, including the Madrid Tertiary Detrital Aquifer. The dataset comprised over 240 nitrate concentration measurements and 20 explanatory variables related to geology, climatic factors, and pressures such as agricultural land, urban areas or intensive farming location. Subsequently, the algorithms with the best predictive capability were used to map nitrate contamination in order to locate unmonitored sites where contamination is likely to occur. Ensemble tree-based classifiers, such as random forests or gradient boosting, showed the most accurate predictions of groundwater contamination, with area under the curve scores around 0.8. The map-based output of this approach facilitates identifying new areas of interest requiring observation points. This method provides an alternative to expert-based criteria for locating new groundwater monitoring stations and is easily transferable to other environments.
Towards seamless prediction of Earth system feedbacks to air quality under climate change: Challenges and new modeling capabilities
Authors: Lin Meiyun , Horowitz Larry , Dunne John , Ginoux Paul , Malyshev Sergey , Shevliakova Elena , Harris Lucas , Zhao Ming , Pouyaei Arman , Smith Steven
Published: March 2024

With rising temperatures and shifting rainfall patterns, compound drought and heatwaves are increasing in frequency and intensity under climate change. Future air quality is vulnerable to large land-biosphere feedbacks, such as reduced ozone removal by drought-stressed vegetation, increasing wildfire and dust emissions, and varying BVOC emissions from plants amidst changing land cover. These interactions are poorly represented in the CMIP6 global chemistry-climate models, limiting our ability to accurately predict future air quality and design effective mitigation strategies. In this presentation, we will discuss recent and ongoing research at NOAA’s Geophysical Fluid Dynamics Laboratory (GFDL) to address these challenges. Specifically, we present a new variable-resolution global chemistry-climate model (AM4VR) designed for a seamless prediction of global dimensions to US climate and air quality across times scales from days to decades, with particular focus on integrating physical, chemical, and biological components. In contrast with the global models contributing to CMIP6, AM4VR features more than 10 times finer spatial resolution over the contiguous US (13 km), allowing it to better represent US climate mean patterns and variability, including hydroclimate extremes, drought, fire weather, and air pollution meteorology over complex terrain. With the resolution gradually reducing to 25-50 km over Europe and 50-100 km over Asia, we achieve multi-decadal simulations with prescribed SSTs at 50% of the computational cost for a 25 km uniform-resolution grid. With increased interactivity of atmospheric composition with vegetation dynamics and reactive nitrogen partitioning in wildfire plumes, AM4VR features much improved representation of US air quality extremes during compound events. We are conducting a suite of century-long  (2000-2100) AMIP simulations under SSP1-2.6, SSP2-4.5 and the Global Methane Pledge to assess compounding climate and air pollution risks under 1.5, 2.0, and 3.0 °C of warming. 
Improving recharge-controlled groundwater level behavior in a transient data-driven 3D model
Authors: Tsypin Mikhail , Cacace Mauro , Guse Björn , Güntner Andreas , Scheck-Wenderoth Magdalena
Published: March 2024

Data-driven models are powerful tools for analyzing the evolution of groundwater flow and thermal field in response to hydrometeorological forcing. However, they usually come with uncertainties in flux boundary conditions and in the distribution of rock properties. To overcome this, we coupled a subsurface 3D model of Brandenburg (NE Germany) with the distributed hydrologic model mHM to simulate a 60-year-long monthly time series of regional groundwater dynamics.Recharge fluxes, derived from mHM and assigned to the top of the saturated subsurface model, allowed us to reproduce magnitudes of seasonal groundwater level fluctuations as observed in shallow monitoring wells (0-5 m). However, approximating the multi-annual periodicity that is pronounced in deeper wells (10-30 m) and the long-term decline in groundwater levels recorded in parts of Brandenburg has proven to be more challenging. This highlights the need to consider damping the infiltration signal in order to better approximate the delayed response of the subsurface to the imposed precipitation pulses, as well as additional sinks contributing to the loss of groundwater storage.To this purpose, we analyzed the frequency of groundwater level fluctuations in >100 observation wells as a function of the unsaturated zone thickness and compared them against the results obtained from a 1D analytical model solution. The established relationship of recharge damping with depth was then utilized to correct the flux boundary conditions. This, along with optimization of river network density and aquifer storativity, resulted in an improved match in modeled versus monitored hydraulic heads. This enables further use of the coupled groundwater and surface-water model for ongoing forecasting studies of the thermo-hydraulic evolution of the aquifer system with respect to climate scenarios.
Use of simulations to evaluate the balance between recharge and pumping to contribute to the development of policies for sustainable groundwater use in the Kumamoto area, southern Japan
Authors: Kawasaki Masatoshi , Sawada Motomitsu , Tawara Yasuhiro , Kobayashi Takamaru , Fukuoka Yo-ichi , Tada Kazuhiro , Shimada Jun , Hosono Takahiro , Katsuya Kimio , Shin-no Keiichi , Koga Hitomi , Nakahori Yasunori
Published: March 2024

For sustainable use of groundwater, it is important to know the past and current water balance and the impact of changes in land and water use for working with stakeholder collectively. In order to understand these issues, a distributed hydrological model that includes the key processes of the regional hydrological system is considered to be a powerful tool, as it enables us to understand the impact of human activities at any given site.In the Kumamoto region, which is almost 100% dependent on groundwater for drinking water, there have been attempts to understand groundwater flow and water balance qualitatively and quantitatively. For example, groundwater levels have been monitored for about 30 years or more, mainly by the local government, to understand the current status of groundwater in the Kumamoto area. Based on these data, a multi-stakeholder group including government, academia and the private sector has developed an integrated surface-subsurface model to reproduce long-term changes in groundwater levels (Kawasaki et al., 2023).This presentation will present the results of several simulations using this model of possible future scenarios in the Kumamoto region, which identify key factors for sustainable groundwater use in the Kumamoto region.
SO2 and NOx emissions from European shipping: a measurement study
Authors: Lee James , Pasternak Dominika , Wilde Shona , Lacy Stuart
Published: March 2024

The shipping industry is a significant source of both SO2 and NOx, two air pollutants which have neg-active implications for climate and air quality. SO2 is heavily regulated such that January 2020 marked a global reduction of the maximum permitted sulfur fuel content (SFC) in shipping fuel from 3.5% to 0.5% by mass. There are also various limits on NOx in coastal and inland waterways with more widespread NOx emissions limits likely to be implemented in the future. The anticipated effect of the new regulations is an improvement of coastal air quality, but there is a potential drawback in terms of reducing the climate cooling effect of SO2 caused by a change in cloud properties. However, the difficulty in measuring emissions from ships means that the overall impact and level of compliance with new and future regulations is unclear. Therefore, monitoring strategies capable of providing regular and long-term measurements of air pollutant emissions from the shipping industry are essential for fundamental research and compliance monitoring. Here we present top-down methodologies for calculating the SFC, along with emission ratios of ∆NOx/∆CO2 from individual ships. First, we demonstrate the application of an airborne platform to perform targeted measurements of ship plumes in the English Channel and Atlantic shipping lanes, allowing the comparison of emissions inside and out of sulfur emission control areas (SECAs). Second, we implement a stationary, point-sampling approach to measure ships arriving and departing two European ports.Our results show there has been a significant reduction in the SFC of ships in the open ocean shipping lanes due to the new emission regulations, with most ships now well below the 0.5% limit imposed in 2020. Our measurements also show good agreement with a comprehensive ship specific emissions inventory (the Ship Traffic Emission Assessment Model – STEAM). This confirms the validity of models that use the new sulfur limit for radiative forcing calculations. In terms of NOx, the measured ∆NOx/∆CO2 ratios were generally greater than those from diesel vehicles operating within a typical European fleet, suggesting ships could be a significant source of NOx to cities, especially where ports are close to populated areas. It is envisaged that the presented methodologies could be implemented to facilitate widespread monitoring of ship emissions, which could provide the basis for policy formulation and validation.
Research on the Multi-Modal Flow Mechanism of Oil and Water in Fractured Carbonate Reservoirs under Multiple Coupling Effects
Authors: Wang Hongshan , Wu Zhiping
Published: March 2024

In a fracture-cavity carbonate reservoir, a myriad of irregular cavities is distributed, serving as primary reservoirs for oil storage. Simultaneously, fractures play a pivotal role by establishing efficient pathways for the movement of oil and water between these cavities, thereby facilitating fluid migration. Consequently, gaining a comprehensive understanding of the connectivity between the cavities and fractures within the reservoir is crucial for optimizing and implementing efficient development strategies. However, the fluid flow behavior within the cavities and fractures, under the influence of multiple coupled fields, remains highly complex, and previous studies have yet to fully elucidate this intricate phenomenon. This study addresses the knowledge gap by employing numerical simulations to investigate the interactions between cavities and fractures, as well as the fluid flow patterns within them. The study utilizes porous media permeability based on Darcy's law to characterize fluid flow within the matrix, fracture flow described by the Brinkman equation for fluid movement within fractures, and free flow based on Navier-Stokes equations to depict fluid motion within solution cavities. Building upon this foundation, and applying the theory of multi-field coupling, different flow models were tailored for the cavities, fractures, and rock matrix, taking into account key factors such as fracture angle, stress state, and fracture connectivity. The simulation results provide valuable insights, from which we draw the following conclusions: (1) When the maximum principal stress direction is perpendicular to the fracture direction, the fractures experience compression perpendicular to their normal direction, leading to a tendency of closure and consequently reducing the efficiency of oil migration within the fractures. Conversely, when the maximum principal stress is parallel to the fracture direction, the fractures undergo tension along their normal direction, causing them to open up and thereby enhancing the efficiency of oil migration within the fractures. (2) With an increasing fracture angle, the angle between the fractures and the principal stress increases. As a result, the fractures experience an increased compressive stress component, leading to a decrease in their conductivity and reducing the efficiency of fluid migration between different cavities. (3) Increasing the tortuosity of the fractures reduces the flowability of the fluid within the fractures. The larger the tortuosity of the fractures, the poorer the conduit capacity of the fractures for the oil phase, resulting in a decrease in the efficiency of oil migration between different cavities.
Prediction of Adverse effects of Geomagnetic storms and Energetic Radiation (PAGER) – project conclusion
Authors: Shprits Yuri , Bianco Stefano , Wang Dedong , Haas Bernhard , Khawaja Muhammad Asim , Wilgan Karina , Arber Tony , Bennett Keith , Santolik Ondrej , Kolmasova Ivana , Taubenschuss Ulrich , Liemohn Mike , van der Holst Bart , Forest Julien , Trouche Arnaud , Tezenas du Montcel Benoit
Published: March 2024

The European Union's Horizon 2020 Prediction of Adverse effects of Geomagnetic storms and Energetic Radiation (PAGER) project was successfully concluded in 2023. This project provides real-time space weather forecast initiated from the solar observations as well as predictions of radiation in space and its effects on satellite infrastructure. Real-time predictions of particle radiation and cold plasma density allow for evaluation of surface charging and deep dielectric charging. The project provides a 1-2-day probabilistic and data assimilative forecast of ring current and radiation belt environments, which allows satellite operators to respond to predictions that present a significant threat. As a backbone of the project, we use the state-of-the-art codes that currently exist and adapt existing codes to perform ensemble simulations and uncertainty quantifications. Within PAGER, a number of innovative tools was obtained, including data assimilation and uncertainty quantification, new models of near-Earth electromagnetic wave environment, ensemble predictions of solar wind parameters at L1, and data-driven forecast of the geomangetic Kp index and plasma density. In this presentation, we show the overview of the outcomes and the products obtained within the project. The developed codes may be used in the future for realistic modelling of extreme space weather events.
Microbial evidences of abrupt shifts in dunes ecosystems after passing an aridity threshold
Authors: Wu Shuai , Delgado-Baquerizo Manuel , Ruan Aidong
Published: March 2024

Dune ecosystems are among the most vulnerable regions to climate change worldwide. However, studies on how crossing critical aridity thresholds influence the microbiome of these ecosystems remains scarce. These microbes play a pivotal role in shaping terrestrial ecosystem traits and functions.In this study, we collected 1.4-meter sediment cores at 5 cm intervals from deserts in Xinjiang, China, in two study sites before and after crossing a previously described aridity threshold. We conducted a comprehensive analysis of community diversity and spatial structure, in light of the changes in environmental heterogeneity and autocorrelation, further exploring the community’s differential sensitivity to fluctuations and evidence of state transitions under various states.The results demonstrate that microbial communities in sand dunes before and after crossing aridity thresholds exhibit distinct vertical ecological niche differentiation patterns under spatial effects. This includes variations in their beta diversity, rarity mode, assembly process, topological properties, and the stability of their networks. This offers new insights into the possible evidence of microbial community state transitions and potential mechanisms in deserts crossing aridity thresholds.
Exploring the potential of normal mode seismology for the assessment of geodynamic hypotheses
Authors: Schneider Anna , Schuberth Bernhard , Koelemeijer Paula , Shephard Grace , Al-Attar David
Published: March 2024

Fluid dynamics simulations are a powerful tool for understanding processes in the Earth's deep interior. Mantle circulation models (MCMs), for example, provide important insight into the present-day structure of the mantle and its thermodynamic state when coupled with mineralogical models, which is essential information for other fields in the geosciences. The evolution of the heat flux through the core-mantle boundary, for instance, is a prerequisite for geodynamo simulations that aim to model the reversal frequency pattern of the Earth's magnetic field on geologic time scales. However, geodynamical modelling requires extensive knowledge of deep Earth properties and plate motions over time. Uncertainties in these model inputs propagate into the MCMs, which subsequently have to be evaluated with independent data, such as the seismological or geological record. Although state-of-the-art MCMs typically explain statistical properties of seismological data, they do not consistently reproduce the location of features in the mantle.In this contribution, we explore the effect of varying the absolute position of mantle structure on seismic data by applying first-order modifications to an initial MCM. Normal mode data are particularly well suited for assessing the resulting changes in the location of mantle structure, as they capture its long-wavelength component throughout the entire mantle. In addition, the global sensitivity of normal modes reduces the drawbacks of uneven data coverage. Specifically, we use two different seismic forward modelling approaches, an iterative direct solution method for computing full-coupling spectra and a splitting function calculation that is based on the self-coupling approximation. Our goal is to quantify the effects of a limited number of large-magnitude earthquakes, the adequacy of the self-coupling approximation, and the resolvability of relevant model differences through a comprehensive data analysis. Our synthetic forward modelling framework is moreover well suited for testing the depth sensitivity associated with specific frequency intervals in the spectrum that generally is inferred from seismic 1-D profiles within the splitting function approximation.
Sedimentological control on permeability heterogeneity, and its effects in fluid-flow modelling: a case study of the Middle Buntsandstein sandstones, Upper Rhine Graben, Eastern France
Authors: Medeiros Bofill Lucas , Schäfer Gerhard , Bozetti Guilherme , Schuster Mathieu , Ghienne Jean-François , Ackerer Philippe , Scherer Claiton , Souza Ezequiel , Armelenti Garibaldi
Published: March 2024

Sedimentary processes govern fluid-flow heterogeneities in porous media in several scales, therefore, their understanding is a common practice in the petroleum industry. However, hydrogeologists have lagged behind when it comes to discretising porous sedimentary aquifers in flow, heat and transport models. At the Upper Rhine Graben, in Eastern France, the Lower Triassic Buntsandstein Group serves as an important reservoir for groundwater and lithium-rich geothermal brines. The main objective of this study is to assess the architecture of the Lower Grès Vosgien Formation (LGV), Middle Buntsandstein, and how sedimentological processes, at different scales, generate significant permeability heterogeneities. It is implemented a high-resolution sedimentological characterisation, through vertical profile descriptions, digital outcrop model, and petrographic analysis. Subsequently, permeability measurements are coupled with sedimentological data, to identify different scales of sedimentary controls on permeability distribution. Finally, a realistic 2D hydrostratigraphic conceptual model is generated as a reference, allowing the evaluation of how different scenarios of heterogeneity simplification impact fluid-flow modelling, concerning particle residence time, macro-dispersivity, and upscaled anisotropy.Results indicate that 93% of the LGV is composed of sandstones deposited by a braided fluvial system, with evidence suggesting that discharge variability was a main depositional controlling factor of sedimentary facies and heterogeneity distribution. The LGV stacking pattern reveals periods when fluvial processes were absent, and aeolian processes dominated sediment transport and deposition, comprising 7% of the total LGV thickness. The aeolian deposits record signs of persistent water in the system, either due to water table rise, or ephemeral floods, primarily contributing to the sedimentary facies association with the lowest permeabilities of the LGV, exceeding 3 orders of magnitude lower than the fluvial deposits. Despite representing only 7% of the LGV total thickness, the aeolian deposits exhibit lateral extensions that extrapolate outcrop scales (hundreds of metres), representing significant vertical flow baffle zones.Fluid-flow simulations demonstrate that model simplifications, whether through assigning deterministic permeability values (mean), or stochastically distributing permeabilities, unconstrained by realistic sedimentary architectures, have a direct impact on macro-dispersivity (both vertical and horizontal), vertical mean residence time, and upscaled anisotropy results. Nevertheless, the results for horizontal mean residence time show no significant effect when simplifying the observed sandstone heterogeneities.
Juno-UVS Observations of Io during the PJ58 Flyby
Authors: Greathouse Thomas , Gladstone Randy , Hue Vincent , Versteeg Maarten , Kammer Joshua , Giles Rohini , Bonfond Bertrand , Grodent Denis , Gerard Jean-Claude , Bolton Scott , Levin Steven
Published: March 2024

Currently in its first extended mission, NASA’s Juno spacecraft has made several close approaches to Jupiter’s Galilean satellites.  The final of these very close flybys will be of Io during the perijove (PJ) 58 orbit, scheduled to occur at 17:48:35 UTC on 3 Feb. 2024, about 3h59m prior to PJ58. Juno’s Ultraviolet Spectrograph (UVS) is a photon-counting far-ultraviolet (FUV) imaging spectrograph with a bandpass of 68-210 nm, which will be used to observe Io’s numerous FUV emissions during the flyby. The circumstances of the flyby are similar to that for Ganymede during PJ34 at 16:56 UTC on 7 June 2021, with the satellite only observable for a few minutes on either side of Juno’s closest approach. We plan to record data +/-5 min (at best 20 swaths of data) about the closest approach time hoping for a significant decrease in the high radiation background due to shielding provided by Io itself.  Our observations will range from an altitude of 1500 km (closest approach) to 7820 km, giving the UVS data an expected spatial resolution of 6 to 28 km at the sub-spacecraft point.  As with the similar close flyby of Ganymede (Greathouse et al. 2022; Molyneux et al. 2022), UVS will attempt to measure reflected FUV sunlight from the surface of Io and airglow emissions from oxygen and in this case sulfur atoms. These observations will be more challenging than at Ganymede, however, since the background due to penetrating (>10 MeV) electrons at Io is expected to be a factor of 10 or more larger than at Ganymede. In this talk we will present results from the initial reduction and analysis of the UVS data obtained during the flyby of Io.