bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessing Debris Flow Susceptibility in Deglaciated Alpine Catchments: A Novel Approach Integrating Flow-path Connectivity and Sediment Availability
Authors: Chen Tzu-Yin Kasha , Sklar Leonard , Pilkington Bryanna , Dickson Emily , Kaitna Roland
Published: March 2024

Debris flows pose significant natural hazards in mountainous regions globally, with the potential to cause substantial damage to villages and infrastructure in lowland areas. To effectively mitigate these hazards, it is essential to identify catchments prone to delivering debris flows to fan areas. Topographic metrics such as fan slope and catchment Melton number are useful at a regional scale but in recently deglaciated alpine landscapes do not explain high variability in debris flow frequency among neighboring catchments. Here we assess debris flow susceptibility by quantifying the spatial extent of sediment cover across upstream catchment areas and the connectivity of potential debris flow source areas to fans at catchment outlets.The Pitztal Valley in the Austrian Alps serves as the study site, benefiting from elevation data (digital terrain model) and historical debris flow event data since the 1950s for 28 catchments, along with sediment cover maps for 18 catchments. To assess the likelihood that debris flows originating within sediment covered areas could reach the fan, we calculated the minimum mean slope angle along every flow path to the fan apex. Source areas with minimum angles lower than a dynamic friction angle are assumed to be disconnected from the fan apex because potential debris flows would come to rest and form coarse deposits upstream of the fan. This concept is utilized to calculate the fractional connectivity for sediment areas in each catchment as a function of dynamic friction angle.  Rather than assume a single friction angle, we compare catchments based on the angle corresponding to a connectivity rate of 50% for the sediment covered areas (referred to as the 50% connectivity angle).We find a highly significant positive exponential correlation between the 50% connectivity angle and the historical debris flow frequency (in units of debris flow events per square kilometer of catchment area) using data from the 18 catchments with sediment cover maps. Validation is performed in 10 additional catchments where we identified sediment covered areas using a new algorithm that can distinguish bare bedrock from sediment deposits from the local topographic roughness. The observed debris flow event frequencies align closely with or fall within the confidence bounds predicted by the 50% connectivity angles, confirming that the combined evaluation of catchment connectivity and sediment availability successfully explains debris flow frequency in this landscape.Lastly, the results are compared to models employing previously published metrics of connectivity and debris flow susceptibility, providing insights into the contribution and efficacy of this new approach.
Finding tectonic signals from ancient volcano-sedimentary successions: an example from the Miocene Janggi Basin, SE Korean Peninsula
Authors: Gihm Yongsik , Kim Min-Cheol , Chae Yong-Un
Published: March 2024

In extensional and transtensional basins, the dual action of basin-forming tectonism and explosive volcanic activity results in deposition of complex volcano-sedimentary successions. Since both aspects contemporaneously affect sediment-dispersal systems, it is difficult to distinguish one from the other by analyzing volcano-sedimentary successions. To discriminate tectonic influence, basin fills of the Miocene, pull-apart Janggi Basin were investigated. Here, the contemporaneous influence of tectonic subsidence and explosive volcanism formed
Circulation in the Guafo Mouth: the gateway to northern Patagonia
Authors: Ross Lauren , Perez-Santos Ivan , Linford Pamela , Diaz Patricio
Published: March 2024

Circulation and exchange are important factors governing material transport in all coastal areas. One  such area is Northern Chilean Patagonia, a region that boasts one of the largest aquaculture industries (salmon and mussel farming) in the world and provides habitat for several protected marine mammal species. Linkages between coastline shape and forces of hydraulic conditions are thereby important considerations when understanding constituent concentrations related to water quality issues such as harmful algal blooms (HABs), which threaten aquaculture activities and endanger wildlife and humans. The research presented here characterizes circulation patterns and variability in the Guafo Mouth, the primary connection between the Pacific Ocean and the fjords and channels of Northern Chilean Patagonia, to help inform ocean-fjord circulation in this ecologically and economically important area. In situ measurements of current velocities, salinity, temperature, dissolved oxygen, and nutrients have been collected for over two years at point measurements in the channel. These data, along with companion numerical model output and reanalysis data, provide parallel evidence of subtidal flows driven by a combination of barotropic and baroclinic pressure gradients and Coriolis, indicating a geostrophic balance. Depending on the sign of the barotropic pressure gradient, the barotropic flow either augmented (when positive) or opposed (when negative) the gravitational circulation produced by horizontal gradients in density and, in certain cases, produced subtidal outflow throughout the water column. Temporal variability of the current velocities was driven by changes in sea level gradients at ~35 d and ~50 d, linked to coastal trapped waves forced by the Madden Julian Oscillation. This variability has implications for the ocean-fjord exchange of dissolved oxygen and nutrients, which are critical to the health of the Chilean Inland Seas. Near-bottom waters with high nutrient content and low dissolved oxygen are advected in-channel when the crest of a coastal trapped wave is at the coast of Northern Patagonia due to enhanced subtidal inflows. These results highlight the importance of understanding the periodicity and amplitude of remotely forced coastal trapped waves to estimate ocean-fjord exchange through the gateway to northern Patagonia.
The internal deformation of the Praid salt diapir and implications for potential storage applications
Authors: Dohan Daria , Tamas Dan Mircea , Tamas Alexandra , Tocariu Ioana Silvia Mihaela
Published: March 2024

The Praid salt diapir is located in the Transylvanian Basin, Romania and it stands out as one of the earliest discordant salt structures to be described. The salt that forms this structure was deposited during the middle Miocene salinity crisis. Under geological conditions, rock salt exhibits plasticity, resembling a fluid, leading to highly intricate folding patterns in its deformation. Understanding the evolution of salt structures holds significant importance for a number of industries such as the hydrocarbon industry or hydrogen storage. To utilize such formations for storage purposes, a comprehensive understanding of the deformation processes, impurity distribution, and mineral composition becomes crucial. These factors wield considerable influence on the overall rock properties.Certain diapiric salt formations within these areas hold potential as sites for hydrogen storage due to their substantial dimensions, reaching around ~3500m in size, and existing caverns within some of these formations. This investigation centers on analyzing the deformation of the Praid salt diapir. The site features a public-accessible salt mine and numerous surface salt exposures. Our study involves detailed mapping of both surface and subsurface areas, focusing on internal salt deformation, the nature and distribution of impurities, and exploring salt-sediment interaction where exposed.In our research, we utilized surface and underground mapping within the accessible salt mine, coupled with photogrammetry and LiDAR technology, to construct detailed 3D models capturing complex large-scale deformation patterns. The majority of the salt layers exhibit steep to near-vertical inclinations, with diverse orientations that suggest curtain-fold-like structures. Certain areas notably display signs of refolding. Within the salt, various impurities of differing origins exist, predominantly large-scale blocks composed of siltstone to sandstone slabs that have undergone boudinage. This study is part of an ongoing initiative aimed at evaluating both the potential and associated risks of implementing hydrogen storage projects within these salt formations or similar structures.Acknowledgements: The work of DD was financed through the Scientific Performance Scholarship, offered by Babes-Bolyai University, Cluj-Napoca.
Revised Universal Soil Loss Equation, Version 2 (RUSLE2) Development: Advanced science components and web-based user interface for use in conservation planning
Authors: Darnault Christophe , Ghorbani Mahsa , Genc Kildirgici Gizem , Kethineedi Avinash , Ghimire Bigyan , Calhoun Jon , Momm Henrique , Yoder Daniel , Dalmo Vieira , Bingner Ronald , Wells Robert , Ferruzzi Giulio
Published: March 2024

The Revised Universal Soil Loss Equation, Version 2 (RUSLE2) is the water erosion prediction tool for use by the USDA National Resources Conservation Service (NRCS) for all conservation planning in the United States. USDA NRCS utilizes the Integrated Erosion Tool (IET) that combines RUSLE2 with USDA data sets for soil, climate, and agricultural management. The Agricultural Research Service (ARS) is the USDA’s research agency charged with the development of the RUSLE2 model. RUSLE2 is an advanced computer model that estimates rill and interrill erosion by water, combining empirical and process-based science, for use on personal computers. This research aims at improving RUSLE2 science components, including the development of a web-based user interface for RUSLE2, for use by USDA NRCS. Advanced science components will be developed to quantify rainfall and land management effects on spatial and temporal variability of dynamic soil properties in agricultural watersheds in the United States, with emphasis on the assessment of soil erodibility and the risk of soil erosion under climate change. State-of-the-art technologies needed to measure, identify, and link dynamic soil erodibility to soil loss in the agricultural landscape, such as machine learning algorithms, remote sensing, and non-intrusive visualization and imaging technologies will provide advanced science components for RUSLE2. For the development of a web-based RUSLE2 modeling system, a new cloud based infrastructure is being deployed using the Amazon Web Services (AWS) platform, which will support online databases for climate, soil, and agricultural management data. A new database structure is being designed for RUSLE2, to support server based erosion calculations. AWS services will also provide web servers, spatial databases, geoprocessing capabilities, cooperative source code development and all compute and storage resources. These research findings and products will help understand how climate change and modern management practices impact soil erodibility dynamics. Improvements to RUSLE2 technology will lead to advances in determining soil loss across agricultural landscapes through improved physically based water erosion models. New web-based tools will provide best management practices for soil and water resources conservation under changing environments, contributing to sustainable agriculture and food security, while ensuring environmental health.
The Exploration Cascade as a Mission Planning Algorithm for AMADEE-24
Authors: Greif Fabian , Savic Jelena , Özdemir-Fritz Seda , Grömer Gernot , Lex Klaus
Published: March 2024

In both real and analog missions, the crew can only perform activities and experiments outside the habitat for a certain amount of time. This means that the missions and therefore also the planned activities must be planned precisely to perform as many activities and experiments as possible in as short a time as possible. Such planning must consider external factors such as environmental factors, such as temperature or weather conditions, as well as the duration of experiments and dependencies on other experiments or activities. Furthermore, changes can occur continuously during a mission, which can also impact the planned schedule. In previous analog missions, this planning was performed manually, which can be very time-consuming due to the many possible conditions. This paper presents the Exploration Cascade, a mathematical algorithm that considers possible factors to create an optimal mission plan. Using the analog Mars mission AMADEE-24 as an example, we examine what results this algorithm can achieve and how flexibly it can react to changes, such as changes in weather forecasts or unforeseeable events, such as the failure of scientific equipment. Furthermore, we examined how the efficiency of the algorithm compares with manual planning and what conclusions can be drawn from it.
Developed empirical refraction model for precise trigonometric levelling of the La Valette Landslide, France
Authors: Sabzali Mansoor , Ferhat Gilbert , Pilgrim Lloyd , Khaki Mehdi , Malet Jean-Philippe
Published: March 2024

Atmospheric refraction is the main source of deviations for laser-based sensors. Having a profound understanding of refraction, and the knowledge of the geometry of the line of sight, assists in identifying an accurate model to correct this error. The height of the point, similar to two other planar coordinates, is also impacted as a result of the refracted beam line. The height can be obtained through numerous geodetic measurement approaches such as spirit levelling or trigonometric levelling. An empirical refraction model was proposed in 1984 to better quantify the observations of trigonometric levelling. In this research, we propose a developed empirical model for the La Valette Landslide (Southeast French Alps) to determine the height of the target benchmarks in a landslide zone. The landslide is located in the Ubaye Valley, where the thrust fault of clay-shale sediments at the bottom and sandstone and limestone competent rocks at the top, control the occurrence of landsliding in this region. The deformation is attributed to the low resistance of the slope material and the increase in pore-fluid pressure resulting from the different hydraulic conductivities of the two geological units. The landslide has been monitored over many years, with several remote sensing techniques, and the task is undertaken as a part of the French Landslide Observation Service - OMIV. Since September 2019, an automated total station Long-Range Trimble S9 has been monitoring 54 reflectors’ positions every 1 to 3 hours with respect to three reference control points. The targets have been uniformly distributed over the landslides at distance from 350m to 2300m from the monitoring station, and at elevations varying from 1300m to 2100m. The research determined the point heights using the empirical trigonometric levelling model with the addition of an improved refraction model incorporating the development refraction correction for the observed angles of the control points.
Numerical modeling of a multi-storey solar still in transient mode
Authors: Oluah Chukwumaobi Kingsley , Njoku Howard.O. , Ekechukwu Valentine
Published: March 2024

Climate change has intensified the scarcity of available drinking water, posing a critical challenge to communities, particularly in rural Africa. In response to this pressing issue, our study investigates the transient behavior of a multi-storey solar still as a sustainable solution. The research focuses on harnessing the latent heat of vaporization from the first stage to heat subsequent stages, utilizing pre-heated water from a reservoir. Mathematical models for each stage were developed, and the Numerical modeling of the system was carried out using the finite-forward discretization scheme on Scilab software. Insolation data for Nsukka (Lat = 6.8567, Lon= 7.3958) were extracted from NASA-SSC Database. Results showcase the temperature distribution and distillate output at each stage. The first stage reached an optimal temperature of 325K, while the second and third stages maintained averages of 322K and 319K, respectively. Distillate outputs for the first, second, and third stages were 7.5Kg, 5.7Kg, and 3.8Kg, respectively. An overall still efficiency of 16% was achieved, hence the multi-story solar still presents a promising avenue to address the water scarcity challenges faced by vulnerable rural communities in Africa.
Satellite and High-Spatio-Temporal Resolution Data Collected by Southern Elephant Seals Allow an Unprecedented 3D View of the Argentine Continental Shelf
Authors: Martinez Melina M. , Ruiz-Etcheverry Laura A. , Saraceno Martin , Gros-Martial Anatole , Campagna Julieta , Picard Baptiste , Guinet Christophe
Published: March 2024

High spatial and temporal resolution hydrographic data collected by Southern Elephant Seals (Mirounga leonina, SESs) and satellite remote sensing data allow a detailed oceanographic description of the Argentine Continental Shelf (ACS). In-situ data were obtained from the CTD (Conductivity, Temperature, and Depth), accelerometer, and hydrophone sensors attached to five SESs that crossed the ACS between the 17th and 31st of October 2019. The analysis of the temperature (T) and salinity (S) along the trajectories allowed us to identify two different regions: north and south of 42°S. Satellite Sea Surface Temperature (SST) data suggests that north of 42°S, warm waters are coming from the San Matias Gulf (SMG). The high spatio-temporal resolution of the in-situ data shows regions with intense gradients along the T and S sections that were associated with a seasonal front that develops north of Península Valdés in winter due to the entrance of cold and fresh water to the SMG. The speed of the SESs is correlated with tidal currents in the coastal portion of the northern region, which is in good agreement with the macrotidal regime observed. A large number of Prey Catch Attempts (PCA), a measure obtained from the accelerometer sensor, indicates that SESs also feed in this region, contradicting suggestions from previous works. The analysis of wind intensity estimated from acoustic sensors allowed us to rule out the local wind as the cause of fast thermocline breakups observed along the SESs trajectories. Finally, we show that the maximum depth reached by the elephant seals can be used to detect errors in the bathymetry charts. Results presented have been accepted for publication in Remote Sensing
Quantifying cross-shelf degradation of terrigenous organic carbon in Eurasian Arctic Shelf Seas
Authors: Wu Junjie , Matsubara Felipe , Wild Birgit , Mollenhauer Gesine , Stein Ruediger , Fahl Kirsten , Xiao Xiaotong , Gustafsson Örjan
Published: March 2024

The permafrost in the Northern Hemisphere holds approximately 50% of the global soil organic carbon, constituting a reservoir that is twice the size of atmospheric carbon storage. Permafrost carbon plays a vital role in governing the global carbon cycle through its reactivity and accessibility to microbial respiration to release greenhouse gases. Existing studies have revealed spatial variability of degradation of coastally-exported organic matter across regimes in the East Siberian Arctic Shelf Seas. While the degradation patterns and ambient rates are reasonably constrained for the Laptev Sea, these aspects are less well understood for the Kara Sea. Here, we quantified carbon isotopes (13C and 14C), TOC, specific surface area, lipid biomarkers, and lignin phenols along a Kara Sea cross-shelf transect to assess terrigenous organic matter degradation, and compare patterns with three East Siberian cross-shelf transects (Kara Sea, Laptev Sea, Western East Siberian Sea, and Eastern East Siberian Sea). The data demonstrate the highest degradation rate constant of 2.5 kyr-1 in the Eastern East Siberian Sea, a moderate value of 2.0 kyr-1 in the Laptev Sea, and the lowest value of 1.2 kyr-1 in the Western East Siberian Sea. Intriguingly, no statistical trend in degradation was observed across the Kara Sea. The recalcitrant fractions of terrestrial organic carbon are determined to be largest (50%) in the Western East Siberian Sea, moderate (31%) in the Eastern East Siberian Sea, and smallest (11%) in the Laptev Sea. The spatial variabilities in degradation rate constants and recalcitrant fractions are likely attributed to different organic carbon speciation across regimes on land, e.g., from fibrous plant residues to mineral-associated organic carbon, and potential biological controls (e.g., priming effect) during transport.
Cumulative storage of magma in the Paricutin-Tancítaro region, Mexico, revealed by recurrent swarm seismicity and a high spatial density of morpho-chronometrically dated Holocene monogenetic cones.
Authors: De la Cruz-Reyna Servando , Zarazúa-Carbajal María Cristina , Caballero-Jiménez Gema Victoria , Mendoza-Rosas Ana Teresa
Published: March 2024

A region located in the SW sector of the Michoacán-Guanajuato monogenetic field, in central Mexico displays a high spatial density of scoria cones, mostly around Tancítaro, a large central volcano active in the middle Pleistocene. This region became well known when in 1943 a new volcano, Paricutin, was formed in a cornfield at 11 km to the NW of the extinct stratovolcano. The birth of Paricutin was preceded by significant swarm-type seismicity. Afterward, new seismic swarms were reported in the area in 1997, 1999, 2000, 2006, 2020, 2021, 2022, and 2023, with a mean recurrence interval of only 4 yr, most of them (not all) showing the characteristics of a magmatic origin.  Aiming to shed some light on the relation between the high density of monogenetic cones and the recurrent seismicity, we have made a morpho-chronometric estimate of the relative ages of 170 scoria cones located in the Paricutin-Tancítaro region (PTR) within latitudes 19°N and 20°N and longitudes -102.0° E and -102.7° using the Average Erosion Index (AEI) which quantifies the degree of alluvial erosion of scoria cones from a Fourier analysis of their level contours. Monogenetic activity began in the PTR at about 1 Ma, and the AEI analysis shows that such activity increased after the end of the Tancítaro activity, around 232 ka, and further increased in the Holocene when about one-third of the scoria cones in the region were formed, with a mean interval between eruptions between 120 and 240 yr. On the other hand, a detailed study of two of the most energetic seismic swarms, recorded in 2020 and 2021 shows that the magma intrusion volume required to produce the measured cumulative seismic moment of both swarms amounts to about 140 million cubic meters, which is seemingly insufficient to produce a Paricutin-size eruption, which ejected about 1.3 cubic km of magma. We thus propose a possible conceptual explanation of the recurrent emplacement of monogenetic volcanoes and the frequent seismic swarm activity in terms of a persistent magma source under the crustal extension of the PTR producing numerous dike and sill forming intrusions. In some cases, such intrusions may have a cumulative effect forming temporary magma reservoirs capable of producing new monogenetic eruptions. Assuming that about 0.5 to 1 cubic kilometer of magma needs to accumulate to begin an eruption, about 7 to 14 sizable (similar to the 2020-2021) swarms may then represent a significant precursor.    
Comparison of GEMS and TROPOMI NO2 observations with ground-based measurements over South Korea
Authors: Choo Gyo-Hwang , Hong Hyunkee , Kim Goo , Kim Sang-Min
Published: March 2024

Nitrogen dioxide (NO2) is one of the most important trace gases in the atmosphere, mainly produced from the combustion of fossil fuels, thermal power plants, transportation activities, and natural sources. Short-term exposure to high concentrations of NO2 in the atmosphere can be problematic as it can cause adverse effects on human health, such as respiratory diseases, and exacerbate the symptoms of those already suffering from lung or heart conditions. The TROPOspheric Monitoring Instrument (TROPOMI) has limitations in tracking diurnal variation. TROPOMI scans South Korea only once daily. On the other hand, the Geostationary Environment Monitoring Spectrometer (GEMS) onboard the GEO-KOMPSAT 2B satellite was designed to continuously observe air pollutants, including NO2, SO2, HCHO, O3, and aerosols. The spatiotemporal pattern of total NO2 vertical column density (VCD) from GEMS shows spatial variability and the diurnal cycle of NO2. In this study, monthly averaged data were generated to compare GEMS, TROPOMI, and ground observation data. The research results showed that the monthly total NO2 VCD from GEMS and surface NO2 mixing ratio exhibited greater temporal variations compared to the total NO2 VCD from TROPOMI. Additionally, the monthly NO2 values were higher in spring and winter, while lower in summer and autumn. GEMS effectively detected the characteristics of NO2 in South Korea, including the distinct weekday-weekend effect, which is similar to ground observations. In the analysis of diurnal variations, GEMS exhibited a continuous increase in NO2 values from 9:45 to 14:45 KST for January. In contrast, other months showed a diurnal cycle. The comparison between GEMS and ground data showed a moderate level of correlation (R=0.77), while TROPOMI exhibited a higher correlation (R=0.81). However, the slope of GEMS was closer to the 1:1 line. GEMS demonstrated a good correlation, particularly in urban observation sites where total NO2 VCD was relatively high throughout the year. However, it showed a lower correlation in port observation sites.
Impact of Sub-Hourly Resolution on the Design and Reliability of Residential Energy System Models
Authors: Omoyele Olalekan , Matrone Silvana , Hoffmann Maximilian , Ogliari Emanuele , Weinand Jann Michael , Leva Sonia , Stolten Detlef
Published: March 2024

Energy system optimization has become an indispensable tool for planning the energy transition. However, model accuracy has traditionally been limited to hourly resolution due to data availability and computational complexity. This study quantifies resolution-induced inaccuracies in hourly and sub-hourly energy system optimization models. It focuses on a self-sufficient residential building by converting minutely-resolved renewable supply and demand data from Milan, Italy into data at five-, ten-, 15-, 30-, and 60-minute intervals using both averaging and sampling methods.The average hourly resolution shows an underestimation of 1.71% in the total annualized cost of the system compared to the minutely resolution. In the electrical sub-system, the photovoltaic inverter is predominantly affected, being twice as large at minutely resolution in order to handle supply and demand peaks on the sub-hourly scale. To test for reliability, the operational performance of the optimal system layouts obtained from different resolutions is tested with minutely-resolved data. Our results show that system designs obtained for lower resolutions are infeasible for minutely data with lost loads of up to 89.37 kWh per year or 1.37% of annual electricity demand. Depending on the value of the lost load cited in the literature, this accounts for up to €893.67 of yearly inconvenience costs. A second method based on regular sampling (i.e., taking every 60th value of the original time series) shows either an under- or overestimation of the total costs depending on the selected sample (there are 60 in total), with a tendency towards conservative design layouts. The two methods (sampling and averaging) reveal that hourly resolution could be sufficient with respect to total system cost approximations, but is unacceptable for sizing dynamically-operated components and strict reliability requirements.Future research should seek to provide higher-resolved data on intermittent renewable energy sources and appropriately handle the resulting increased computational complexity of energy system models.
Predicting global porphyry copper prospectivity using positive-unlabelled machine learning
Authors: Alfonso Christopher , Müller Dietmar , Mather Ben , Salles Tristan
Published: March 2024

The majority of the world’s known copper reserves is contained in porphyry copper deposits. These deposits are understood to form along subduction zones within the magmatic arc, though the exact contributions to this process of different factors within the subducting and overriding plates are not entirely certain, hampering efforts to develop large-scale prospectivity models for this deposit type. Previous efforts to tackle this problem through the use of data-driven machine learning methods have shown promise, but have been hindered by the relative paucity of fully labelled data required for training classification models. Here we present a suite of models trained using a semi-supervised positive-unlabelled (PU) algorithm, allowing the classifier to be created from data of which only a small subset of one class is labelled: in this context, known porphyry copper deposit locations. These models can be used to create time-dependent prospectivity maps representing the probability of a deposit forming at a given place and time, while model inspection can provide deeper insight into the processes behind the genesis of these deposits, at both a global and regional scale. Furthermore, deep-time erosion rate estimates extracted from global landscape evolution models are used to explore the uplift and erosion histories of known porphyry copper deposits in order to better understand the potential for these deposits to survive to the present day. These two factors of deposit formation and preservation are combined into a powerful prospectivity model, with the potential to facilitate the identification of possible new prospective zones along the world's subduction zones through time and help minimise the environmental and financial costs of mineral exploration.
Process analysis of Contribution to High Concentration PM2.5
Authors: Kim HyeunSoo , Jeong Peel-Soo , Son Eun-Seong , Han Seung-Hee , Wang Kyung-Hui , Yun Hui-young
Published: March 2024

To prevent the occurrence of high concentrations of PM2.5, Korea has implemented policies to reduce domestic emissions, such as seasonal fine dust control systems and restrictions on the operation of old diesel vehicles, and has established intensive measurement stations by region to analyze and monitor the ionic composition of major substances such as PM2.5 and PM1, which are used for policy formulation and research.The secondary reaction precursors of PM2.5 are nitrate, sulfate, and ammonium, and the contribution of these precursors varies depending on geographical characteristics and emission source characteristics. According to previous studies, the contribution of OA in Seoul was 27%, nitrate 42%, ammonium 21%, sulfate 8%, and other 2%, while the contribution of OA in Seosan was 40%, nitrate 29%, ammonium 15%, sulfate 12%, and other 4%.(Kim et al, 2022)PM2.5 is a representative secondary phase pollutant along with ozone, which is highly influenced by meteorological factors such as humidity, wind speed, and wind direction, and its concentration changes due to the combination of particulate matter and gaseous matter, so it is important to predict it. In general, chemical transport models such as CMAQ (Community Multi-scale Air Quality) and CAMx (Comprehensive Air quality Model with extensions) are mainly used to prediction PM2.5, and in recent years, LSTM models using machine learning have also been utilized.In this study, we analyze the hourly concentration of PM2.5 in Korea in 2019, analyze the physicochemical characteristics of PM2.5 concentrations to identify the causes of high concentration episodes, and identify the effects of topography characteristics on PM2.5. To analyze the causes of high PM2.5 concentrations in high concentration episodes, we first analyze the physicochemical contribution through the Process Analysis (PA) tool of CMAQ. In addition, to identify the causes of high concentrations by region, we analyze the effects of topography characteristics on PM2.5 using the National Oceanic and Atmospheric Administration (NOAA) Hybrid Single-particle Lagrangian Integrated Trajectory (HYSPLIT) model, which is a reverse trajectory model, to evaluate the causes of high concentrations.Reference:N.K. Kim, Y.P. Kim, Y.S. Ghim, M.J. Song, C.H. Kim, K.S. Jang, K.Y. Lee, H.J. Shin, J.S. Jung, Z. Wu, A. Matsuki, N. Tang, Y. Sadanaga, S. Kato, A. Natsagdorj, S. Tseren-Ochir, B. Baldorj, C.K. Song, J.Y. Lee, Spatial distribution of PM2.5 chemical components during winter at five sites in Northeast Asia: High temporal resolution measurement study, Atmospheric Environment, Volume 290, 1 December 2022, 119359https://doi.org/10.1016/j.atmosenv.2022.119359AcknowledgmentsThis research was supported by Particulate Matter Management Specialized Graduate Program through the Korea Environmental Industry & Technology Institute(KEITI) funded by the Ministry of Environment(MOE)
Ediacaran proximal glaciomarine sedimentation in the Bonavista Peninsula, Avalon Zone (Newfoundland) 
Authors: Gomez Nicolas , Lowe David , Mills Andrea , Slaney Noah , Arnott Bill
Published: March 2024

Four ice ages characterize the Neoproterozoic icehouse Earth period. The two youngest, Gaskiers and Mortensnes glaciations, correspond to relatively short duration (i.e., 30° paleo-latitude, but significantly were followed by rapid Ediacaran biota evolution. However, the recognition of their glaciogenic origin is confounded by the coeval intensification of Late Neoproterozoic rifting and breakup of Rodinia that conceivably produced coarse-grained strata with characteristics similar to glacial diamictites. The Gaskiers glaciation (ca. 580 Ma) is best characterized in sedimentary successions exposed on the Avalon Peninsula of southeast Newfoundland, where the Gaskiers Formation records deepwater glaciomarine sedimentation over- and underlain by deep-marine turbidites. However, these deep glaciomarine strata do not provide a direct record of terrestrial glaciation, nor sea level changes that would have coincided with glacial advances and retreats, and thus, their glacial origin has been questioned.Here, we present a sedimentological and stratigraphic analysis of the correlative shallow glaciomarine Trinity diamictite in the Bonavista Peninsula and associated shallow marine strata of the Rocky Harbour Formation. The Monk Bay Member underlies the Trinity diamictite and consists of stacked 6-to-10 m-thick upward-coarsening, shallow-marine clastic parasequences with rare dropstones, each capped by a gravel transgressive lag. The overlying Trinity diamictite consists of a massive clast-rich diamictite with abundant faceted, flat-iron, stoss-and-lee, or bullet-shaped clasts and rare striated clasts and an overlain by a clast-poor laminated diamictite with dropstones, dump and grounding structures. The overlying King’s Cove North Member comprises a distinctively pistachio-color silicified tuff, >50m thick mudstone succession, and uppermost stratal unit of thick-bedded turbidites.Parasequences of the Monk Bay and Trinity diamictite units are interpreted as deposits of glacial advance and retreat cycles controlled by glacio-eustatic and glacio-isostatic forces. The gravel-rich transgressive lag capping each parasequence records wave reworking of ice-rafted material. These cycles culminated in the deposition of the Trinity diamictite, marked initially by a continuous rainout, followed by finer-grained fall-out of ice-rafted debris, and finally, glacial grounding. Overlying this, the Kings Cove North facies records glacio-eustatic flooding of the shelf, driven by a glacial retreat that marks the end of the Gaskiers glaciation on the Bonavista Peninsula and coincident glacio-eustatic sea-level rise, which evidently outpaced glacial-isostatic rebound.
Modelling dependence between the ice-sheet components of sea-level rise
Authors: Grandey Benjamin S. , Dauwels Justin , Jevrejeva Svetlana , Payne Antony J. , Koh Zhi Yang , Horton Benjamin P. , Chew Lock Yue
Published: March 2024

Sea-level projections are sensitive to statistical dependence between the East Antarctic, West Antarctic, and Greenland ice-sheet components.  The dependence is produced by climate uncertainty and ice-sheet process uncertainty.  To investigate this dependence, we model the dependence using copulas.  We use a vine copula to couple the ice-sheet components of projected sea level in 2100 under the SSP5-8.5 scenario.  Assumptions about rank correlation and copula family influence both the centre and the tails of the total ice-sheet contribution.  For example, rank correlation can influence the 95th percentile by approximately 50%.  We explore three alternative approaches for specifying the dependence: shared dependence on global-mean surface temperature, dependence derived from ice-sheet model ensembles, and dependence derived from expert judgement.  Shared dependence on global-mean surface temperature produces little dependence between the ice-sheet components.  In contrast, ice-sheet model ensembles suggest that the dependence between the East and West Antarctic ice-sheet components may be strong, amplifying the uncertainty in future sea-level rise.
Machine Learning unravels the protracted role of India-Eurasia collision in the uplift of the Tibetan plateau
Authors: Luan Zhikang , Liu Jia , ZhangZhou Johnny , Xia Qunke , Hanski Eero
Published: March 2024

The Tibetan Plateau, Earth's largest and highest plateau, boasts an extraordinarily thick continental crust (60-80 kilometers) and an average elevation exceeding 4000 meters. Unraveling the plateau's uplift history, vital for comprehending Earth's Cenozoic history and its environmental impacts, has long been a subject of debate. While prior studies predominantly attribute the plateau's formation to the India-Asia collision, 45-59 million years ago, its timing and underlying mechanisms remain contentious. Airy isostasy as a response to crustal thickening during the Indian-Asian collision was considered the main factor for the uplift of the Gangdese terrain, the important portion of the Tibetan. Trace elemental ratios, e.g. Sr/Y and (La/Yb)n ratios, of the bulk magmatic rocks were the main geochemical indexes to recover the thickening history. However, the resultant crustal thickness and the consequent geodynamics recovered by different indexes remain controversial. Here, we compile the geochemical data for the volcanic rocks from global young arcs and continental orogens and built a supervised Machine Learning model to estimate crustal thickness. The reliability of this new model was tested, and the crustal thickening history of Gangdese terrain was recovered with it. The results reveal that the Gangdese terrane maintained a global-average thickness during the early stage of the India-Asia collision, which was not sufficient to support the uplift to >3000 m, as revealed by the recent paleoaltimeter data, through Airy isostasy.  This challenges the conventional belief of rapid uplift due to crustal thickening upon the Indian-Asian collision. Instead, our results suggest a protracted uplift process that parallels crustal thickening, reshaping our understanding of this iconic geological feature. 
Remote Sensing of Photosynthesis with Chlorophyll Fluorescence and Photochemical Reflectance Index
Authors: Yang Peiqi , Liu Jing
Published: March 2024

The monitoring of photosynthetic activity stands as a central objective for the upcoming generation of satellite missions. Two promising avenues, Sun-Induced Chlorophyll Fluorescence (SIF) and Photochemical Reflectance Index (PRI), have emerged for remotely sensing leaf physiology, thereby advancing our comprehension of plant–climate interactions. Over the past few decades, substantial progress has been made in measurement techniques, retrieval algorithms, and modeling biochemical and radiative transfer processes related to SIF and PRI. However, it is essential to acknowledge that SIF and PRI observations are subject to influences such as canopy structure, soil background, and sun-observer geometry, in addition to leaf physiological status. Consequently, the key challenges in SIF and PRI remote sensing involve downscaling canopy SIF and PRI to leaf-level values and decoupling structural and physiological information.
 
Drawing a comparison between the radiative transfer processes involved in SIF and reflectance, a physical relationship between reflectance and scattering of far-red SIF has been established, giving rise to the R2F (Reflectance-to-Fluorescence) theory. Based on this theory, a Fluorescence Correction Vegetation Index (FCVI) has been formulated. The R2F theory and FCVI index have been successfully applied to interpret SIF observations across various scenarios, offering a theoretical foundation for the conversion of SIF across different scales—from canopy to leaf and photosynthetic systems.
 
Furthermore, an analysis of the radiative transfer processes determining PRI signals reveals that the deviation between canopy- and leaf-level PRI primarily stems from the soil background. Both canopy structure and sun-observer geometry indirectly affect canopy PRI by altering the contribution of soil to canopy reflectance. The structural and angular variation in canopy PRI can be elucidated by considering the soil background. In order to mitigate the effects of soil background, as well as associated structural and angular effects, a soil-adjusted canopy PRI (SacPRI) is proposed. This adjustment involves subtracting the soil contribution, estimated using red reflectance, from the original canopy reflectance. Field and numerical experiments confirm that compared with the raw canopy PRI, SacPRI more closely aligns with the PRI observed in sunlit leaves.
 
In summary, the proposed R2F relationship and the soil-adjusted canopy PRI offer valuable tools for enhancing the accuracy of photosynthesis monitoring through SIF and PRI, enabling more robust assessments across various scales and environmental conditions.
A Machine Learning Based Snow Cover Parameterization  for Common Land Model (CoLM) 
Authors: Zhang Han , Li Lu , Dai Yongjiu
Published: March 2024

Accurate representation of snow cover fraction (SCF) is vital for terrestrial simulation, as it significantly affects surface albedo and land surface radiation. In land models, SCF is parameterized using snow water equivalent and snow depth. This study introduces a novel machine learning-based parameterization, which incorporates the light-GBM regression algorithm and additional input features: surface air temperature, humidity, leaf area index, and the standard deviation of topography. The regression model is trained with input features from the Common Land Model (CoLM) simulations and the labels from the Moderate Resolution Imaging Spectroradiometer (MODIS) observations on a daily scale. Offline verification indicates significant improvements for the new scheme over multiple traditional parameterizations.Moreover, this machine learning-based parameterization has been online coupled with the CoLM using the Message Passing Interface (MPI). In online simulations, it substantially outperforms the widely used Niu and Yang (2007) scheme, improving the root mean square errors and temporal correlations of SCF on 80% of global grids. Additionally, associated land surface temperature and hydrological processes also benefit from the enhanced estimation of SCF. The new solution also shows good portability as it also demonstrates similar enhancements when it is directly used in a global 1° simulation, even though it was trained at a 0.1° resolution.
Emergence of diverse failure patterns in weathering-induced landslides: Insights from high-fidelity particle finite element simulations
Authors: Wang Liang , Loew Simon , Gu Xin , Lei Qinghua
Published: March 2024

Landslides, as a ubiquitous type of mass wasting phenomena, occur under various geological and environmental conditions and exhibit diverse failure patterns. Among various factors, weathering has been widely recognised as one of the primary drivers on landslide evolution over geological timescales. However, how weathering induces slope instabilities, including how pre-failure rock mass degradation contributes to the landslide failure development and post-failure deposition of mobilised geomaterials, has not been fully understood. In this study, we develop a novel, physics-based unified computational framework to capture weathering-induced landslide evolution over multiple time scales, from the long-term pre-failure rock mass deformation to the short-term slope rupture and post-failure runout dynamics. Weathering laws and failure criteria are coupled to capture the combined effects of time-dependent strength degradation and strain-driven damage processes, while a frictional velocity-weakening law is adopted to characterise the rapid movement of yielded masses. The non-linear governing equations of landslide dynamics are solved using an implicit particle finite element framework that can model all the landslide stages from the long-term material degradation to short-term failure and runout. We further investigate the effects of weathering conditions (type and rate), geological properties (fracture sets and rock matrix) and slope geometry (angle and shape) on the failure patterns. Our high-fidelity numerical simulations capture the emergence of diverse landslide failure patterns resulting from the complex interplay among rock lithology, fracture distribution, weathering process, and gravitational forcing. Our numerical results show that matrix-dominated weathering tends to produce shallow landslides, while fracture-dominated weathering promotes the occurrence of deep landslides. For fracture-dominated weathering, the orientation of pre-existing fractures and the slope ratio significantly control the failure mode (e.g. falling, toppling, sliding, etc.), which further affects post-failure runout behaviour. Our computational framework opens the door to investigating and understanding weathering-induced rock slope failure evolution across spatial and temporal scales.