bluuebunny/crossref_metadata_2025 huggingface dataset:
Quantification of rhizodeposition and priming effect of intermediate crops via 13CO2 labeling.
Authors: Hulin Baptiste , Chollet Simon , Massol Folrent , Abiven Samuel
Published: March 2024

When assessing the carbon storage potential of a crop, it is useful to 1) quantify the inputs that return to the soil, such as roots, rhizodeposition and sometimes aboveground biomass, and 2) estimate the carbon gains or losses attributed to the priming effect. This allows to draw up a balance of inputs and outputs at the end of the growing season. While the quantity of carbon supplied by roots and aboveground biomass is relatively easy to measure, the quantity of rhizodeposition and the priming effect are not.To establish such a balance, 12 intercropping plant species from 3 plant families (brassicaceae, fabaceae and poaceae) were grown for two months in mesocosms (15 liters) under controlled conditions simulating a temperate summer climate in real time in an ecotron. Multi-pulse atmospheric labeling with 13CO2 99% was used to trace photosynthesized carbon and thus quantify aboveground and root biomass, rhizodeposition and variations in carbon stock due to the priming effect.The results show that rhizodeposition represents a significant carbon input (around a quarter of root biomass), positively correlated with root biomass. Root biomass is therefore one of the main traits to be considered for increasing inputs. At the same time, 10 out of 12 plants accelerated the mineralization of soil organic matter (positive priming effect), resulting in a cumulative carbon loss over the course of the plant's growth that can be of the same order of magnitude as the biomass input.This priming effect is highly heterogeneous and difficult to explain by plant traits, but seems quantitatively more important for brassicaceae. We propose that this variability is due both to the spatial heterogeneity inducing these processes, but also to the great variability of processes that can occur in the rhizosphere, processes that can simultaneously lead to an acceleration and/or deceleration of the decomposition of native soil organic matter.
Seasonal temperature patterns and variability in salt marshes: Field study and numerical simulation
Authors: Yu Xiayang , Xu Xinghua , Zhan Lucheng , Cheng Haifeng , Xin Pei
Published: March 2024

Soil temperature regulates biogeochemical processes and is a key environmental factor affecting salt marsh ecosystems. Previous studies on soil temperature and heat transport in intertidal marshes predominantly focused on short-term changes, leaving seasonal variations still unclear. This study conducted a yearlong field and modeling investigation to examine the temporal and spatial variations of soil temperature in a creek-marsh section under estuarine and meteorological influences. The porewater flow and heat transport processes were simulated using SUTRA-MS. The response of soil temperature to air and tidal water temperature conditions will be discussed here in detail. We will also discuss the impacts of tide-induced porewater circulations on soil temperature response. Finally, there will be a discussion on quantifying the thermal effects of tidal water and air on hourly and depth-averaged shallow soil temperatures in the creek-marsh system.
Machine learning based Pseudo-Dynamic rupture generator for geometric rough faults
Authors: Aquib Tariq Anwar , Cruz David Castro , Vyas Jagdish , Mai Paul Martin
Published: March 2024

Accurately predicting the intensity and variability of strong ground motions from future large earthquakes is crucial for seismic hazard analysis. While kinematic ground motion simulations are computationally efficient and can be conditioned to inferred source-inversion models of past events or ensemble statistics of rupture-model databases, they rely on predefined spatiotemporal evolution of slip. In contrast, dynamic rupture simulations solve for a physically self-consistent slip evolution under prescribed stress and friction laws on the fault, yet, they are still computationally expensive. A practical compromise, therefore, is a physics-compatible source model embedded in a kinematic approach (i.e., Guatteri et al., 2004), referred to as the Pseudo-Dynamic (PD) approach.Geologic features, such as small-scale fault roughness influence the rupture process, generating realistic high frequency radiation with  decay characteristics (Mai et al., 2017). Presently, most PD models are based on rupture simulations of planar faults (with the notable exception of Savran and Olsen, 2020). Additionally, these models rely on 1-point and 2-point statistics between source parameters, which may not adequately capture nonlinear relationships between kinematic rupture parameters.In this study, we develop a Machine Learning (ML) framework involving Fourier Neural operators (FNO) (Li et al ., 2020) to learn the interdependencies between earthquake source parameters. We train our model using 21 dynamic simulations of rough faults (15 for training, 6 for testing; all from Mai et al., 2017). Our generator initiates with a stochastic final slip (Mai and Beroza, 2002) and a slip-constrained hypocentre location (Mai et al., 2005). The local slip evolution is described by a regularized Yoffe source time function (STF) characterized by rupture onset time, slip, peak time and rise time.Dynamic rupture simulations show correlation between rupture speed and the gradient of fault roughness, with rupture deceleration in regions of positive roughness gradients, coinciding with fault areas of increased shear stress. Therefore, we establish rupture speed as a function of stress drop computed from 2D final slip and relate peak slip velocity to the estimated rupture speed. Assuming a Yoffe STF, we then compute rise time and the time of peak slip velocity, enabling a full spatiotemporal earthquake source characterization that accounts for dynamic rupture on rough faults. For the stochastic slip, we also demonstrate an approach to model roughness correlated with stress drop. Our PD rupture generator reproduces the mean and standard deviation of ground motion models for different intensity measures in simulations of M 6.0-7.0 strike slip scenarios. This outlines a new PD source modelling approach suitable for broadband physics-based probabilistic seismic hazard analysis.  
Seasonal dynamics in the allocation of newly assimilated carbon in a northern peatland
Authors: Hikino Kyohsuke , Hartmann Antonia , Öquist Mats , Järveoja Järvi , Nilsson Mats , Peichl Matthias
Published: March 2024

Peatlands play an essential role for the global climate, providing a large storage of carbon (C) and the largest natural source of methane (CH4). Previous studies revealed that carbon dioxide (CO2) flux varies at the seasonal scale depending on plant phenology and species compositions. In addition to the C sink-strength, allocation of newly assimilated C is another important process to estimate C pool size and turnover, and also a key to understand the connection between plant-assimilated CO2 and CH4 emissions. To date, seasonal variations in the link between plant CO2 uptake and CH4 emissions in response to phenology have not been investigated in detail.To reveal diurnal and seasonal dynamics of CO2 and CH4 flux with a high temporal resolution, we used data from an automated chamber system established in an oligotrophic minerogenic mire complex in northern Sweden (Degerö Stormyr). To identify the role of plant species composition, experimental plots without vascular plants (moss plots) and without any vegetation (bare peat plots for assessing heterotrophic respiration) were established next to the natural control plots. We conducted two in-situ 13C pulse labelling experiments at two distinct phenology stages (green-up and senescence) during 2023. The fate of the newly assimilated 13C was tracked through the entire C flow from plants (vascular plants and mosses), to dissolved organic and inorganic 13C in pore water, to 13CO2 and 13CH4 flux. The main objectives were to investigate 1) seasonal variations in the C allocation pattern and turnover time, and 2) the separate roles of vascular plants and mosses in regulating C allocation dynamics.Our results indicate that in the green-up stage, both natural and moss plots released around 20% of the total newly assimilated 13C as CO2 flux during the 30 days after the labelling. In the senescence stage, the amount in the moss plots increased to 26 ± 3%, while that of natural plots remained at 20%. In comparison, release of newly assimilated C as CH4 did not show any seasonal variations in neither natural nor moss plots, highlighting a close link between plant C uptake and CH4 emission. However, existence of vascular plants increased the proportional release as CH4 emission tenfold from 0-0.02% of total 13C uptake in moss plots to 0.1-0.2% in natural plots.These results highlight the importance of plant species composition and phenology in regulating the allocation of assimilated carbon in northern peatlands.
Improving troposphere mapping function by ERA5 for better space geodetic estimates
Authors: Zhou Yaozong , Lou Yidong , Zhang Weixing , Gong Xiaopeng , Chen Guo
Published: March 2024

Troposphere mapping function plays a very important role in space geodetic tropospheric correction, estimation, and application in meteorology. In the past decades, a series of mapping functions, such as NMF, GMF, VMF1 and VMF3, were successively developed for pursuing better mapping function performance. However, limited by modeling data source of numerical weather model, the mapping functions temporal-spatial resolutions are stuck in 6 h and 1°×1°, existing problems of bad applicability in extreme weather and regions with complex terrains. As the release of the generally acknowledged best global reanalysis ERA5, we have a chance to improve current mapping function modeling by taking full advantage of accuracy and temporal-spatial resolution (1h and 0.25°×0.25) of ERA5. In this contribution, we used the ERA5 reanalysis to establish the hourly site-wise Wuhan University Mapping Function (WMF) covering 1583 GNSS, VLBI and DORIS stations, and compared the accuracy and GNSS PPP performance of WMF with VMF3 at globally distributed stations. We found the significant accuracy improvements of WMF to VMF3 as well as the non-negligible vertical coordinate and ZTD difference biases between the two mapping functions.
Evaluation of the Geochemical Compositions of Western Anatolia (Turkey) Volcanic Rocks and Their Suitability for Rock Fiber Production with the Help of Fiber Modules 
Authors: Ünal Burak Can , Kaya Simge , Atalay Cüneyt , Aydar Erkan , Ersoy Orkun
Published: March 2024

Recently, rock fibers have gained attention as versatile and promising substitutes for traditional carbon and glass fibers in a range of industries, including aerospace, defence, construction, and healthcare. Shifting to the use of rock fibers represents a more sustainable and environmentally considerate approach to using natural resources. This transition likely reflects efforts to reduce reliance on less sustainable materials (such as traditional carbon and glass fibers), thereby aligning with broader goals of sustainable resource management and environmental protection. Additionally, their asbestos-free nature in construction materials makes them a healthier industrial raw material, avoiding the health hazards associated with asbestos exposure. As a result, there has been a growing interest in research initiatives aimed at evaluating the potential of volcanic rocks from diverse geographic regions for fiber production. This trend reflects an increased emphasis on understanding the geochemical properties and commercial viability of these rocks in the context of sustainable material development. Turkey's abundant volcanic rock resources offer substantial opportunities for the production of rock fibers. Recent preliminary investigations into the volcanic rocks of Central Anatolia have indicated their suitability for rock fiber production. Within the scope of this study, it is aimed to specifically evaluate the potential of Western Anatolian volcanoes for rock fiber production. Geochemical data obtained in previous studies from volcanic rocks of Western Anatolia (Afyonkarahisar, Denizli, Eskişehir, İzmir, Kütahya, Manisa, Muğla, Uşak) were used. The chemical compositions of 241 rock samples with SiO2 content of less than 63% by weight were evaluated. Using this data, key descriptive coefficients relevant to rock fiber production were calculated, including the total acidity coefficient (Ktotal), total acidity modulus (Mtotal), acidity modulus (Ma), and viscosity modulus (Mv). These metrics were then compared with those derived from rocks from Ukraine, Georgia, and Russia, currently deemed suitable for rock fiber production. Conclusively, this research highlights the potential of Western Anatolian volcanoes as viable sources for rock fiber production.
Retention capacity and thermal properties of a multilayer blue-green roof in Sardinia: two years of monitoring
Authors: Viola Francesco , Cristiano Elena , Urru Salvatore , Deidda Roberto
Published: March 2024

Many different nature-based solutions have been proposed in the literature to contribute to the sustainable development of the urban environment. Among them, multilayer blue-green roofs are becoming more and more popular, thanks to their multiple benefits. As traditional green roofs, the multilayer ones guarantee high retention capacity during rainfall events, contributing to the pluvial flood mitigation. Thanks to the additional storage layer, not only the mitigation capacity is increased, but there is the possibility to store the collected water, and reused it for some urban purposes, such as garden irrigation. Moreover, these nature-based solutions ensure thermal insultation for the underneath buildings and they help lowering the air temperature, contributing to the mitigation of the urban heat island effects.  Finally, they improve the air quality, promote the biodiversity, and increase the aesthetic value of the overall city. In June 2019, a multilayer blue-green roof prototype has been installed at the university of Cagliari, and subsequently equipped with multiple sensors to monitor and evaluate the ecohydrological and thermal dynamics. The multilayer blue-green roof, with a surface of 16 m2, presents an 8 cm layer of soil, classified as sand, and a 10 cm additional storage layer. It is characterized by Cactaceae vegetation, which shows resistance to the high temperature and low water availability and does not require additional maintenance. The prototype has been equipped with a Smart Mill, that beside opening and closing of the valve to control the storage layer, enables to measure climatological variables, such as rainfall, air temperature and wind speed, and the water level in the additional layer. Four HOBO thermometers have been installed to measure the temperature in the soil, underneath the structure and on the lateral side. Two soil moisture sensors have been placed at opposite sides of the multilayer blue-green roof. Finally, a tank with a sensor to measure the water level have been collocated at the valve opening, to measure the outflow from the additional storage layer. The collected data have been used to model the ecohydrological and thermal dynamics, with the aim to quantify the potential benefits in terms of pluvial flood mitigation and thermal insulation. Results, collected during two full years of monitoring the prototype in Cagliari, are discussed, highlighting the potential benefits of a large-scale installation for the sustainable development of urban areas.
Geochemical signals from biogenic varves reflect hydroclimate and lake oxygen conditions in central Finland
Authors: Billah Mohib , Saarni Saija , Tjallingii Rik , Schröder Birgit , Pinkerneil Sylvia , Saarinen Timo , Brauer Achim
Published: March 2024

Annually laminated (varved) lacustrine sediments are sensitive recorders of climatic-induced variability in the catchment. In a Boreal setting, climatic information is usually extracted from clastic-biogenic varves, although the potential of biogenic varves remains almost unexplored. The organic-rich sublayers of Boreal biogenic varves usually include thicker growing season lamina enriched with amorphous organic matter and thinner winter lamina reinforced with fine-grained organic matter settled under ice cover during the winter season. This study explores the properties and controls of varve formation in Lake Kallio-Kourujärvi and their implications in understanding past hydroclimate and lake oxygen conditions using micro-XRF combined with stable carbon and nitrogen isotope analysis. Lake Kallio-Kourujärvi is located in central Finland and has organic-rich varves. The thickness of these varves is controlled by the accumulation of biogenic matter that originates from terrestrial sources and autochthonous production. The varve counting provides an age estimate for the 1,8 m long varved sediment sequence of approximately 3700 years before the present (BP). The results from major elemental data reveal that changes in iron and sulfur are consistent with the varve thickness data previously shown to be sensitive for precipitation, as well as decadal changes in North Atlantic Oscillations (NAO) forced winter precipitation. Precipitation likely increases the transport of soluble Iron(II) from the catchment, which settles into sediment as particulate Iron(III) after being oxidised in the water column. Strong changes of redox conditions by the elements iron, manganese, and sulphur are indicated between around 1600 BP and 3700 BP. The variation of redox-sensitive elements suggests that changes in hydroclimatic conditions and past water mixing conditions can be reconstructed from the biogenic varve records.
Temperature regulates microbial carbon use efficiency effects on soil organic carbon storage
Authors: Luo Zhaoyang , Ren Jianning , Fatichi Simone
Published: March 2024

Microbial carbon use efficiency (CUE), describing the partitioning of microbe assimilated carbon into microbial growth and respiration, is commonly used in soil carbon models to link microbial activities with the consumption of soil organic carbon (SOC). However, the role of CUE in regulating SOC storage remains debated. Previous studies have reported that a higher CUE could not only favour SOC formation through microbial necromass accumulation, but also trigger SOC losses because an enhancement in enzyme production facilitates SOC decomposition. The former leads to a positive relationship between CUE and SOC, while the latter leads to a negative one. Temperature dependencies introduce additional uncertainties while exploring the SOC-CUE relationship since temperature affects both SOC decomposition and CUE. Based on the meta-analysis and numerical simulations with a mechanistic model (T&C), we examined the relationship between CUE, SOC storage and temperature. Numerical results recover the expected SOC storage decrease with increasing temperature when temperature effects are isolated; however, an increase of SOC storage with decreasing CUE is found once temperature effects are discounted, indicating that SOC storage increase with increasing CUE is likely a by-product of temperature dependencies. In addition, we show that CUE variability plays a more important role in affecting SOC storage at lower temperature. Our study helps refine the understanding of SOC responses in a warming climate.
A  constraint-enhanced machine learning model for predicting hydraulic conductivity of unsaturated bentonite
Authors: Taherdangkoo Reza , Nagel Thomas , Butscher Christoph
Published: March 2024

The accurate determination of hydraulic conductivity in unsaturated bentonite is important for the modeling of subsurface thermo-hydro-mechanical and chemical processes. This study introduces a new hybrid approach, employing a constrained CatBoost algorithm coupled with a genetic algorithm for hyperparameter tuning. We benchmarked the effectiveness of the constrained CatBoost model against various data-driven regression models, including lasso, elastic net, polynomial regression, k-nearest neighbors, decision tree, bagging tree, random forest, and standard CatBoost. Our findings demonstrate that the constrained CatBoost model excels in providing accurate estimations of the hydraulic conductivity of compacted bentonite during the wetting phase. The model adequately captures the U-shaped correlation between hydraulic conductivity and suction and reflects the influence of temperature changes on hydraulic conductivity. Furthermore, the bootstrapping analysis, conducted across 800 iterations, confirms the stability and robustness of the constrained CatBoost model. This work provides a reliable tool for predicting hydraulic conductivity in diverse environmental and engineering contexts.
Along-track nonlinear filtering of airborne gravity data from the GRAV-D campaign: case study for the ‘Colorado geoid experiment’
Authors: Cunderlik Robert , Zahorec Pavol , Papčo Juraj
Published: March 2024

The study presents along-track nonlinear diffusion filtering of the airborne gravity data. At first, the provided airborne gravity disturbances from the GRAV-D campaign are transformed into the airborne complete Bouguer disturbances (CBD). This aims to reduce a correlation of the filtered data with the topography. Then the nonlinear diffusion filtering in 1D based on the Perona-Malik model is applied. In this model, a diffusivity coefficient depends on the edge detector, which allows reducing noise while preserving important gradients in the filtered data. As a numerical method we use the finite volume method (FVM). The derived semi-implicit numerical scheme leads to a three-diagonal system matrix that is solved in every iterative step. Here the diffusivity coefficients are updated in every step by new values of the edge detector recomputed from the previous solution.The numerical experiment presents the along-track nonlinear filtering of the airborne CBD in high mountainous area of the ‘Colorado geoid experiment’. Afterwards, the along-track filtered data are gridded into a 2D map of the airborne CBD. The obtained results show that an appropriate choice of a sensitivity parameter of the diffusivity coefficient can better detect significant structures in the airborne CBD, especially their edges that are usually smoothed by the Gaussian filtering. Finally, the filtered and gridded airborne CBD are backward transformed into the airborne gravity disturbances.
The risks of climate tipping points for financial investors
Authors: Waidelich Paul , Klaaßen Lena , Battiston Stefano , Steffen Bjarne
Published: March 2024

While financial investors are increasingly alert to the economic threats of climate change, most academic and regulatory assessments of financial risk have not accounted for climate tipping points. Here, we combine recent advances in the integrated assessment modeling of tipping points with return projections for major stock indices to assess index-specific risk exposures to climate change damages. We find that for the MSCI World, a globally diversified stock index, tipping points increase the expected loss due to climate change damages under SSP2-4.5 by 62% (USD 0.2 trillion)—a magnitude comparable to moving from meeting the Paris targets to the "hothouse world" scenario RCP8.5. The reason is that investment horizons are more affected by near-term risks of tipping points than by long-term differences in mitigation outcomes. Risk increases are driven by methane-related tipping points (permafrost thaw and ocean methane hydrates) and ice sheet disintegration, with the highest increases for investments in emerging markets with extensive coastal areas, such as India or Indonesia. The absolute magnitude of financial risks varies substantially across damage functions and assumptions regarding damage persistence. However, the relative importance of tipping points is robust across different damage specifications and investor discount rates. Therefore, our results call for integrating tipping points into climate scenario analyses in the financial sector and climate risk stress tests by regulators.
Spatial and Temporal  Patterns of Chlorophyll-a and Sea Surface Temperature Linked to Typhoon-Induced Ocean Surface Layer Blooms in the Northwest Pacific
Authors: Putra Dimas Pradana , Hsu Po-Chun
Published: March 2024

This study analyzes typhoon-induced ocean surface layer blooms in the Northwest Pacific from 2015-2022, utilizing Himawari-8/9 satellite data. It highlights the critical importance of intense physical air-sea interactions during these extreme weather events. As typhoons traverse the ocean, their strong winds and the resultant turbulent conditions at the air-sea interface induce significant modifications in the upper ocean’s structure and biogeochemistry, impacting marine ecosystems. Utilizing multi-spectral Himawari-8/9 data, the study tracks the spatiotemporal variability of chlorophyll-a (Chl-a) concentrations and sea surface temperatures (SSTs) around individual typhoon eyes across the basin,  focusing on the seven days preceding and following each storm’s passage. The powerful winds influence upper ocean mixing and upwelling processes, injecting nutrient-rich deep water into the sunlit euphotic zone, and stimulating phytoplankton blooms. These conditions concurrently alter SSTs. A cluster analysis of the Chl-a response around typhoon eyes revealed distinct biogeochemical provinces with differential biological responses, influenced by variations in wind-driven turbulence intensity, stratification, and background nutrient levels unique to each region. Integrating SST data provided further insight into the connections between the physical drivers and variables in bloom intensities. The results offer a deeper understanding of how typhoons can dramatically yet unevenly modify regional ocean surface layer dynamics through intense atmosphere-ocean interactions, leading to pronounced localized phytoplankton blooms.
Advancing seismic imaging: Fresnel volume migration in anisotropic and anelastic media
Authors: Kühne Niklas , Hlousek Felix , Buske Stefan , Ding Hui , Schulze Maximilian
Published: March 2024

Advanced seismic imaging techniques play a crucial role in generating reliable, high-resolution subsurface images across diverse applications, such as exploring hydrocarbons and minerals, characterizing geothermal reservoirs, and selecting sites for radioactive waste disposal. In this study we present the extension of the seismic imaging technique, Fresnel volume migration (FVM), to anisotropic and anelastic media.A wavefront construction method for 3D anisotropic (TTI) velocity models was employed to compute the Green's functions required for FVM. This wavefront construction method was further developed by calculating complex traveltime fields (t*) for predefined quality factor (Q) models, describing the anelastic attenuation of seismic waves. Subsequently, these resulting traveltime fields (t*) were used in the migration process to facilitate the corresponding anelastic compensation of the amplitudes.The developed method was applied to synthetic 2D data and a real 3D dataset obtained over the "Asse" salt structure in Lower Saxony, Germany (2020). The migration with anelastic compensation demonstrated a correct enhancement of amplitudes in the synthetic data. Furthermore, the application of the anisotropic FVM to the real 3D dataset resulted in a significant improvement in the imaging quality of reflectors throughout the area surrounding the salt structure.Our findings underscore the pivotal role played by considering both anisotropy and anelastic attenuation in complex 3D models for achieving a reliable and high-resolution subsurface image using the further developed FVM approach. The latter lays the foundation for subsequent quantitative analyses of reflectors and hence supporting dependable geological interpretations.
The Pacific Decadal Oscillation modulates global temperature trends since the mid-18th century
Authors: Han Tao , Xie Zhiang , Wang Jianglin , Hu Jun , Wang Zhe , Yan Hong
Published: March 2024

The Pacific Decadal Oscillation (PDO) plays a crucial role in global decadal climate variability. However, large discrepancies persist in the determination of pre-industrial PDO variability derived from terrestrial proxy records. Here we reconstruct the PDO variability for the period 1746–2003 using a network of annually resolved marine proxy records from the extratropical North Pacific. Our PDO reconstruction (PDOrec) provides evidences for the persistent decadal variability and tropical-extratropical interactions over the North Pacific. Superposed epoch analysis does not detect a significant response of PDOrec to major volcanic eruptions, underscoring the dominant role of internal variability. Decadal changes in global temperature trends were found to correspond to PDOrec for the period 1746–2003, indicating that the decadal changes in global temperature trends do not arise solely from external forcing, and may be instead modulated by internal variability.
Landscape Modeling: Impact of Image Parameters in Processing Historical Aerial Surveys for Water Management
Authors: Brétt Dominik , Pacina Jan
Published: March 2024

Cutting-edge techniques for analyzing archival aerial survey images are crucial in enhancing terrain analysis and landscape modeling. This research study is centered on examining the effects of different image parameters, namely contrast, brightness, and smoothing, on the terrain model creation process. The goal is to determine the ideal combination of these factors that will optimize the quality of the produced models and improve their precision for water management applications.The methodology includes collecting and preparing the images (by cropping) and conducting experiments to adjust the image parameters before creating terrain models to identify the best combination of adjustments.The study's results reveal a significant influence of modified parameters on the final terrain models. Boosting contrast or brightness in images can enhance model intricacy, but excessive tweaking of these parameters may decrease accuracy. Image smoothing has emerged as a crucial component in noise reduction and obtaining smoother terrain models.
Defining Plastic Pollution Hotspots
Authors: Tasseron Paolo , van Emmerik Tim , Vriend Paul , Hauk Rahel , Alberti Francesca , Mellink Yvette , van der Ploeg Martine
Published: March 2024

Plastic pollution in the natural environment poses a growing threat to ecosystems and human health, prompting urgent needs for monitoring, prevention and clean-up measures, and new policies. To effectively prioritize resource allocation and mitigation strategies, it is key to identify and define plastic hotspots. UNEP's draft global agreement on plastic pollution mandates prioritizing hotspots, suggesting a potential need for a defined term. Yet, the delineation of hotspots varies considerably across plastic pollution studies, and a definition is often lacking or inconsistent without a clear purpose and boundaries of the term. In this paper, we applied four common hotspot definitions to plastic pollution datasets ranging from urban areas to a global scale. For each scale, hotspots were defined according to 1) values above the average of the dataset, 2) values in the highest interval, 3) outliers, and 4) values exceeding the 90th percentile. Our findings reveal that these hotspot definitions encompass between 0.8% to 93.3% of the total plastic pollution, covering
Projected changes in Köppen-Trewartha climate zones under 1.5–4°C global warming targets over mid-high latitudes of Northern Asia using an ensemble of RegCM4 simulations
Authors: Gao XueJie , Wu Jie , Tang Xianbing , Giorgi Filippo
Published: March 2024

We use an ensemble of a regional climate model (RegCM4) projections to assess future changes in surface air temperature, precipitation and Köppen-Trewartha (K-T) climate types in mid-high latitude Northern Asia (NA) under the 1.5-4°C global warming targets. RegCM4 is driven by five CMIP5 global models over an East Asia domain at a grid spacing of 25 km. Validation of the present day (1986-2005) simulations shows that the ensembles of RegCM4 (ensR) and driving GCMs (ensG) reproduce the major characters of the observed temperature, precipitation and K-T climate zones reasonably well. Greater and more realistic spatial detail is found in RegCM4 compared to the driving GCMs. A general warming and overall increases in precipitation are projected over the region, with these changes being more pronounced at higher warming levels. The projected warming by ensR shows different spatial patterns, and is in general lower, compared to ensG in most months of the year, while the percentage increases of precipitation are maximum during the cold months. The future changes in K-T climate zones are characterized by a substantial expansion of Dc (temperature oceanic) and retreat of Ec (sub-arctic continental) over the region, reaching ~20% under the 4°C warming level. The most significant change in climate types in ensR is found over Japan (~60%), followed by Southern Siberia, Mongolia, and the Korea Peninsula (~40%). The largest change in the K-T climate types is found when increasing from 2°C to 3°C.
The lateral heterogeneity of Glacial Isostatic Adjustment modelling across the Arctic
Authors: Li Tanghua , Shaw Timothy , Khan Nicole , Nixon F. Chantel , Peltier W. Richard , Horton Benjamin
Published: March 2024

The Arctic has been key area for glacial isostatic adjustment (GIA) studies because it was covered by large ice sheets at the Last Glacial Maximum. Previous GIA studies applied mainly 1D Earth models. The few studies that did include 3D Earth structures have not considered the lateral heterogeneity differences across different regions of the Arctic. Here, using the latest standardized deglacial relative sea-level (RSL) databases from Norway and Russian Arctic, we investigate the effects of 3D structure on GIA predictions and explore the magnitudes of the lateral heterogeneity in both regions.The 3D Earth structure consists of 1D background viscosity model (ηo) and lateral viscosity variation, the latter is derived from the shear velocity anomaly from seismic tomography model and controlled by scaling factor (ß) denoting the magnitude of lateral heterogeneity.The Norway RSL database includes 413 sea-level index points (SLIPs), 175 marine limiting data and 433 terrestrial limiting data, while the Russian Arctic database includes 353 SLIPs, 78 marine limiting data and 92 terrestrial limiting data.We find 3D Earth structures have significant influences on RSL predictions and the optimal 3D model notably improves the fit with RSL data. However, we realize RSL data from Norway and Russian Arctic prefer different 3D structures to provide the best fits. The Russian Arctic database prefers a softer background viscosity model (ηo), but larger scaling factors (ß) than those preferred by Norway database. We further test the extent to which the 3D structure can be eliminated by refinement of ice model.
Indian summer monsoon as a driver of summer heatwaves in the Eastern Mediterranean 
Authors: Di Capua Giorgia
Published: March 2024

Boreal summer circulation over the Eastern Mediterranean is characterized by background subsidence, which is linked to both mid-latitude wave activity and to convective activity generated in the tropical belt. Background subsidence is accompanied by northerly winds over the Aegean Sea and the Eastern Mediterranean basin, which bring cooler air from the Eurasian landmass towards the Middle East and northeast Africa. These winds, also known as Etesians, can thus mitigate heatwaves in the region. Using the Peter and Clark momentary conditional independence (PCMCI) algorithm, the causal drivers of the Etesians have been identified (Di Capua et al. in preparation). This set of causal drivers consists of (i) Rossby waves propagating from North America via the North Atlantic and (ii) convective activity over the Indian summer monsoon (ISM) region, which affects the Eastern Mediterranean circulation via a geopotential height ridge forming over the Middle East. In this new work, the aim is first to quantify the effect of enhanced Etesians in mitigating heatwaves in the Middle East. Secondly, given the causal pathway identified between the Etesians and the ISM, the aim is to quantify the effect of interannual ISM activity as a potential amplifying (or inhibiting) factor of heatwaves activity. As future projection under different anthropogenic global warming scenarios predict an intensification of rainfall activity in the ISM region, it is crucial to understand how the ISM-Mediterranean teleconnection can affect heatwave activity in the Eastern Mediterranean. Di Capua G., Tyrlis E., Matei D., Donner R. “Tropical and mid-latitude causal drivers of the summer Etesians in the eastern Mediterranean” (in preparation)
Impact of management and boreal climate on GHG exchange from Finnish grasslands on mineral and peat soils
Authors: Shurpali Narasinha , Peltola Olli , Thentu Tulasi , Virkajärvi Perttu
Published: March 2024

Grasslands are a key component of boreal agriculture and can play a significant role in soil carbon sequestration and mitigation. Grasslands have the potential to store substantial amounts of carbon in their roots and soil, making them important for soil carbon sequestration. Finland, located in the boreal climate zone, is known for its milk production with one of the highest per cow milk yields in Europe. Milk production in Finland relies heavily on grassland management. The growing season is short and varies from 105 days in the north to 185 days in the south. Finnish grasslands are managed on two types of soils: mineral soils and organic soils. Mineral soils are typically well-drained and have a low organic matter content, whereas organic soils are characterized by high organic matter content and high-water retention capacity. Therefore, we have initiated a long-term GHG monitoring framework for a sustainable grassland management and agriculture at the Natural Resources Institute Finland (Luke) across several agricultural research sites in Finland. The results presented in this study will shed light on the variability of GHG-fluxes from grasslands on different soil types and on the key drivers of the temporal and site variability of GHG-fluxes in a comparative way.
Climatic functioning of peatlands in the context of microrefugia - the MIRECLIM project
Authors: Słowińska Sandra , Słowiński Michał , Baranowski Jarosław , Bartczak Arkadiusz , Czarnecka Kaja , Halaś Agnieszka , Jarocińska Anna , Kaczorowska Joanna , Kaszkiel Adrian , Kowalczyk Patrycja , Kuchcik Magdalena , Lindner-Cendrowska Katarzyna , Łuców Dominika
Published: March 2024

Peatlands often function as glacial microrefugia, as shown by palaeoecological research and the contemporary occurrence of glacial species (e.g. Betula nana). The bogs and poor fens of Poland’s lowlands that we will focus on are islands of the young glacial landscape, which were mainly preserved within forests. Although microclimatic conditions have been identified as one of the most supportive factors for peatland microrefugia functioning, they have not yet been recognized on a larger scale.In response to this need, in 2023 we initiated the MIRECLIM project, which aims to comprehensively investigate the climatic functioning of numerous mid-forest bogs and poor fens in Poland. As multiple feedback mechanisms influence microclimatic conditions, our research will consider meteorological conditions, peatland characteristics, conservation measures, and their surrounding environment. We will also assess the impact of peatland overgrowth due to hydrological disturbance on microclimate, the rate of organic matter decomposition, moss growth and the corresponding changes in the composition of the testate amoeba communities. These indicators serve as valuable proxies for inferring moisture dynamics of peatlands in palaeoecological research.Our studies will be carried out in a multi-scale approach, from in situ measurements to the analysis of multispectral satellite images Sentinel-2 and Landsat. Measurements will be carried out for at least the next three years, so we encourage all interested people to participate.One of the significant outcomes of our project will be the development of the MIRECLIM database. It will also serve as a platform to integrate the data obtained from the in situ field measurements with analysed satellite imagery. Another important aspect of our project will be to educate children and local communities about the importance of peatlands as key ecosystems for climate change mitigation, both globally and locally.Research carried out as part of research project number 2022/45/B/ST10/03423 financed by the National Science Center in Poland.
Spatial prediction of borehole yield in southern Mali using machine learning classifiers
Authors: Gómez-Escalonilla Victor , Diancoumba Oumou , Traoré Dasso Yolande , Montero Esperanza , Martín-Loeches Miguel , Martínez-Santos Pedro
Published: March 2024

Groundwater plays a vital role in drinking water supply, food security and ecosystem services. Approximately 2.5 billion people worldwide rely exclusively on groundwater to meet their daily needs, while hundreds of millions of farmers depend on groundwater resources to sustain their livelihoods. Groundwater potential mapping based on machine learning (ML-GPM) can be used to support groundwater exploration, planning and management practices. Most ML-GPM studies aim to predict a positive or negative outcome, that is, to identify areas of high or low groundwater potential. This work takes this conventional bivariate outcome approach one step further by predicting borehole yields and applying a multiclass approach. The method is illustrated through an application over a study area of 21,000 km2, including the administrative region of Bamako and the municipalities of Kati and Kangaba in the Koulikoro region of southern Mali. Logistic Regression, Gradient Boosting and Extra Trees classifiers were trained on an imbalanced multiclass database of 483 boreholes and 20 explanatory variables. The explanatory variables include information on lithology, geomorphology, soil, land use/land cover, topography, drainage and slope-related variables and rainfall, among others. All models returned prediction scores between 0.80 and 0.87. The most important variables include elevation, vegetation cover, basement depth and geology. The alluvial sediments of the Niger river banks, especially in the southern and northern sectors, are clearly associated with the most productive class. In contrast, the Mandingue plateau has the lowest groundwater potential. The piedmont areas present an intermediate groundwater perspective. These maps could be used to inform water supply policy at a regional scale.
From build-up to caldera collapse: High resolution modelling of large scale magmatic systems
Authors: Aellig Pascal , de Montserrat Albert , Kaus Boris
Published: March 2024

In order to understand the cause of a caldera-forming eruption, it is crucial to study the pre-eruptive processes, from build-up to the collapse. In recent years, the cyclicity of large-scale magmatic systems and their corresponding caldera collapses has been described through various geochemical and petrological studies. Numerical modelling studies have investigated the collapse stage using a pressurised cavity or gas-filled chamber, studying the evolution of the surrounding lithosphere by inflating and deflating the chamber. Another modelling approach involves investigating the displacement effects of moving a piston-shaped object.In this study, we use a multi-physical numerical modelling approach to investigate different aspects of the caldera cycle, including the accumulation of magma, the evolution of stress, the strain rate and the dynamics within the forming magmatic system. To achieve this, we couple an open-source thermal evolution magma intrusion code with a Stokes solver. The coupling allows for the evaluation of thermal and volumetric changes in the magmatic system, taking into account the complex interaction between magma dynamics and the surrounding host rock. The use of nonlinear visco-elasto-plastic rheology enables the assessment of fracturing and thermal effects on the lithosphere, which create downward propagating weak zones that are later utilised as eruption channels. These faults not only provide pathways but are also associated with the caldera collapse stage of the eruption cycle, which leads to geomorphological transformations of the surface.Our approach is also applicable for assessing the evolution of current magmatic systems taking into account their topography. The model is applied to the well-studied area of the Toba caldera in Sumatra. The magma is injected into areas where seismic inversion studies have identified a melt phase. This allows for an assessment of the system's evolution and provides insights into an active magmatic system. Additionally, it serves as a reference for correlating and referencing our model with observational data.
Impact of Upper-Level Atmospheric Circulation and El Niño-Southern Oscillation Phases on Particulate Matter Concentrations in Tropical South America
Authors: Ordóñez Carlos , Collazo Soledad , García-Herrera Ricardo
Published: March 2024

Biomass burning has been identified as a major cause of poor regional air quality and the dominant source of particulate matter (PM) in the Amazon basin. In this study, we analyse the impact of the upper-level jet on PM2.5 (PM with an aerodynamic diameter ≤ 2.5 μm) concentrations in tropical South America (SA) from December to February during the period 2003-2022, using the Copernicus Atmosphere Monitoring Service (CAMS) and ERA5 reanalyses. Furthermore, we investigate the response of air pollutants to the joint modulation of the upper-level jet and El Niño-Southern Oscillation (ENSO). First, a climatological analysis shows that PM in the region is largely composed of organic matter and black carbon, with the highest concentrations and temporal variability in Colombia and northeastern Brazil. Regarding the link with the upper-level circulation, we find that PM2.5 concentrations in northeastern Brazil are reduced on days when the subtropical jet (STJ) is absent, due to increased convection and precipitation over the region. This improvement in air quality is independent of the ENSO phase. Conversely, a prominent STJ inhibits convection and contributes to dry conditions that favour increased biomass burning and elevated pollutant concentrations in the lower troposphere. At a 3-day persistence of these STJ conditions, there is a 90% probability of exceeding the World Health Organisation threshold of 15 μg m-3. In addition, the co-occurrence of a prominent STJ with an El Niño phase acts synergistically to increase pollutant concentrations, as both reduce precipitation in northeastern Brazil. In combination with La Niña, this upper-level pattern does not modulate PM2.5 concentrations because the wet conditions favoured by this ENSO phase prevail, reducing biomass burning. This study provides new insights into the modulation of air quality by the upper-level atmospheric circulation in tropical SA. The results have the potential to improve short-term predictability and can serve as a first step towards the development of a warning system.