bluuebunny/crossref_metadata_2025 huggingface dataset:
Dynamics of soil N2O fluxes and hot-moments typification: How are they related to environmental characteristics?
Authors: Sabaté Gil Maria Cinta , Peñuelas Josep , Fernandez-Martinez Marcos , Mattana Stephania , Tallec Tiphaine , Boland François , Heinesch Bernard , Freigenwinter Iris , Rautakoski Helena , Lohila Annaela , Magliulo Enzo , Jansens Ivan , Roland Marilyn , Poblador Sílvia , Ribas Àngela
Published: March 2024

To date, extensive field measurements of nitrogen oxide (N2O) exchanges in soils across diverse terrestrial ecosystems, complemented by controlled laboratory incubation studies, have unveiled considerable variability in N2O soil fluxes. This variability arises from the intricate interplay of various factors. Notably, soil N2O emissions display significant spatiotemporal fluctuations, including extreme events. The primary objective of this study is to enhance our understanding of the environmental factors influencing soil N2O fluxes and to characterize instances of pronounced N2O emissions, hereafter termed "hot-moments."Our investigation encompassed six distinct sites of the Integrated Carbon Observation System (ICOS) network including agricultural systems, sylvicultural systems, and unmanaged forests spanning the northern hemisphere. To identify and categorize hot-moments events, we standardized N2O values and considered events greater than or equal to 4, or -4-fold standard deviations from the mean of each site.We then conducted wavelet coherence analyses to delve into the patterns of N2O fluxes. In the biwavelet plots, our variable of interest was juxtaposed with each soil environmental variable, illustrating the distribution of correlations in the time-frequency domain of our signals. Employing this advanced approach, we explored N2O patterns and their variability in relation to specific environmental characteristics (soil water content, soil temperature, and CO2 flux) within the six temporal series (different soil types).Our analyses revealed a recurring pattern across all time series, with a frequency of approximately 24 hours for the N2O vs. CO2 plots, indicating a daily correlation between the emissions of both gases. This correlation may be linked to seasonality in certain sites. Soil temperature emerged as a leading factor in shaping the daily patterns of N2O fluxes in most sites, exhibiting also a 24-hour pattern. Although the periodicities related to soil water content were less clear, a discernible pattern persisted with variations within sites. However, we will deepen into the discussion of these results and their implications in our EGU presentation. Key words: N2O fluxes, hot-moments, soil environmental variables, temporal series, wavelet coherence analysis
Visualizing the transition from LaNiño to ElNiño from NASA's model outputs
Authors: Saberi Atousa , Shirah Gregory
Published: March 2024

The ENSO affects global weather. We used NASA GEOS Subseasonal to Seasonal (S2S) Coupled ocean-atmosphere model, NASA MERRA‐2 reanalysis, along with NOAA Niño3.4 SST anomaly index time series to visualize the transition from  LaNiño 2021 to ElNiño 2023. The visualization is a comprehensive model explainer showing changes in the top 300 meters of the Pacifc Ocean (such as thermocline flattening, movements of the temperature anomalies) coupled with the Walker Circulation and the continous coupled interaction between the ocean and the atmosphere. It's the first effort in visualizing the Walker Circulation and the moving convective branch across the Pacific without schematic plots but rather with climate model outputs.  We will also cover the effect of the two phases of ENSO on the global weather pattern. This visualization will be narrated and released to the public in the future.
Accounting for earthquake rates’ variability through Uniform Rate Zone forecasts in the 2022 Aotearoa New Zealand Seismic Hazard Model
Authors: Iturrieta Pablo , Gerstenberger Matthew , Rollins Chris , Van Dissen Russ , Wang Ting , Schorlemmer Danijel
Published: March 2024

The distribution of earthquakes in time and space is clustered and may exhibit a non-stationary behaviour. The impacts of non-stationarity are further amplified when the observation window is short compared to the timescales of the underlying tectonic process, such as in regions of low-seismicity. This can preclude a robust statistical analysis for PSHA models, which commonly assume stationary Poisson models. We investigate the performance of forecasts for PSHA, such as smoothed-seismicity models (SSM), with respect to the available training data. We design bootstrap experiments for multiple pairs of consecutive training/forecast windows of a catalogue to: (i) analyse the lowest available amount of training data for which SSM performs spatially better than the least-informative Uniform Rate Zone (URZ) model; (ii) characterise the temporal variability of rates in terms of their over-dispersion and non-stationarity. The results show rate variability up to 10 times higher than predicted by Poisson forecasts, and demonstrate the impact of non-stationarity when assuming a constant mean rate derived during a training period for forecasting purposes. Analytical distributions are used to describe rate variability, which are conditioned on the information available from a training period. Furthermore, we devise a data-driven method based on strain-rate maps to spatially delineate URZs, under the assumption that the strain-rates field is related to the time scales of earthquake occurrence and interaction. For each URZ, a rate temporal distribution is inferred from the training events within it. We provide forecasts for the update of the New Zealand Seismic Hazard Model that have increased rates by up to 10 times higher in extensive low-seismicity regions compared to optimised SSMs. The new forecasts are implemented as negative-binomial distributions in the hazard integral. For a 10% exceedance probability in 50 years, the use of URZ with rate variability descriptions increases the expected PGA by up to 0.16 g in low seismicity regions (e.g. Auckland, Dunedin) compared to SSM. Our results highlight the relevance, as well as the feasibility, of incorporating analytical formulations of seismicity that go beyond the inadequate stationary Poisson description of seismicity.
Evaluating the merit of Carbon Credits: Is there a lack of effectiveness in transitioning from direct Payments for Ecosystem Services to REDD+ community-based incentives?
Authors: Quiroga Sonia , Hernanz Virginia , Suarez Cristina , Aguiño Jose Evelio
Published: March 2024

Rich in biodiversity, Tumaco is a focal point for REDD+ projects that aim to combat deforestation and promote sustainable land use. Cacao farming, vital to the local economy, offers an opportunity to reconcile livelihoods and conservation. However, challenges remain in reconciling cacao and forest conservation. This study explores the benefits of sustainable cacao practices, such as agroforestry, for economic development and environmental conservation. It also looks at the challenges farmers face and the implications for the success of REDD+. Perceptions of climate change profoundly influence farmers' perspectives and behaviours in the context of REDD+ initiatives, shaping the sustainability and effectiveness of such efforts. Therefore, fostering a robust understanding of climate change among local farmers is critical to improving the integration of sustainable cacao production into REDD+ frameworks. This research aims to provide insights for policy makers and project implementers to advance both conservation and development goals in the Tumaco region, by addressing potential synergies and trade-offs between cacao production and REDD+ initiatives. The farmers' lack of knowledge is particularly worrying, not only for the fight against climate change, but also because if the cacao farmers of Tumaco do not see the incentives of carbon credits as a sustainable source of income, they will be forced to return to illegal crops, and the socio-environmental development of these communities will be compromised.
Infrasound as a tool for detection and characterization of bolides
Authors: Silber Elizabeth
Published: March 2024

Very bright meteors, also known as fireballs and bolides, are produced when extraterrestrial objects larger than approximately 10 cm in diameter enter dense regions of the Earth’s atmosphere. Besides the luminous phenomenon, bolides also generate shock waves, which decay to low frequency acoustic waves or infrasound. Depending on initial conditions, atmospheric propagation paths, and the mode of shock production, infrasound emanating from a bolide can be detected by microbarometers hundreds and even thousands of kilometers away. Unlike other sensing modalities that might have geographic (e.g., inaccessible regions), time-of-day (e.g., optical) or other limitations, infrasound can be utilized continuously (day and night) on a global scale. Hence, infrasound can be leveraged towards detection and localization of bolides, as well as estimating their explosive yield. Bolide infrasound detections date back to the early 20th century. On June 30, 1908, an extraterrestrial object exploded over Tunguska, Siberia, generating low frequency acoustic waves that mark the first known instrumentally observed bolide infrasound. During the mid-20th century, ten large bolides were detected by infrasound stations meant for explosion monitoring. Since the mid-1990s, many more events have been detected via infrasound. However, characterization of bolides through infrasound is not without its challenges, mainly because no two bolide events are alike. Systematic studies and data fusion can be leveraged towards efforts to better constrain some key parameters.  SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525.
Nationwide flood risk assessment using large ensemble climate change dataset and the Rainfall-Runoff-Inundation model
Authors: Sayama Takahiro , Chen Jiachao , Sugawara Yoshito , Yamada Masafumi
Published: March 2024

Floods pose significant threats, particularly in the context of climate change. This research focuses on a comprehensive analysis of river flooding nationwide in Japan. We utilize the latest dynamic downscaling data, d4PDF-5km, for the entire country, feeding this information into the Rainfall-Runoff-Inundation (RRI) model with a spatial resolution of 150 meters. The objective is to efficiently estimate the probability discharge of all rivers by developing a new method for extracting rainfall events from long-term ensemble data.　The proposed method involves extracting heavy rainfall events from 720 years (12 ensembles of 60-year records) of downscaled data for each present, 2K and 4K scenarios and inputting them into the RRI model. This approach allows for the estimation of quantiles by analyzing peak flow as non-annual data with the peak-over-threshold method. When applied to the Shikoku region, the results demonstrate the effectiveness of the method, with the ability to estimate probability flows exhibiting a bias of 10% or less compared to a comprehensive calculation of all rainfall events.　Furthermore, the research identifies variations in the increase of peak flow under climate change, particularly emphasizing differences between the main river and its tributaries. Notably, smaller rivers in the upper reaches are more significantly influenced by changes in rainfall patterns than the lower reaches of the main river.　The implications of this research extend beyond hydrologic science. The estimated probability flows and corresponding hydrographs serve as crucial boundary conditions for assessing local flood risk. This information is fundamental for informed river management by governments and local authorities. Additionally, private companies, residents, and other stakeholders can utilize this data for robust risk assessments. In conclusion, our research provides valuable insights and a practical methodology for understanding and mitigating flood risks in Japan, taking into account the complexities introduced by climate change.
Flexible Aerosol and Cloud Obstruction Mask (ACOM) for various remote sensing applications
Authors: Matar Christian , Litvinov Pavel , Chen Cheng , Momoi Masahiro , Liu Zhen , Dubovik Oleg , Goryl Philippe
Published: March 2024

Clouds and aerosols can obstruct the solar radiation propagating through the atmosphere before it reaches the Earth's surface due to the scattering and absorption processes. The impact of this obstruction on Earth observation is related to the degree of obstruction along the optical path, and to the remote sensing application in question. Usually, such obstruction is accounted for by applying cloud and shadow masking for the observed pixels or by performing simultaneous atmosphere/surface retrieval. Estimation of the atmospheric signal (clouds and aerosol obstructions) from the top of atmosphere measurements can be used to identify clouds, cloud shadows or presence of aerosol in the atmosphere. In ACOM this is done by extracting surface signal from atmospheric one and then separating clouds and aerosol features from each other using multi dimensional spectral thresholds and spatial variability tests.The concept applied in ACOM allows a quantitative estimation of the atmospheric obstruction which results in the distinction of different clouds and aerosols classes varying from low to high levels of aerosol and clouds loading in addition to cloud vicinity, cloud shadow and aerosol plumes shadow classes. ACOM shows robust results with ENVISAT/MERIS and Sentinel-3/OLCI and the algorithm can be easily extended to any other optical instruments with spectral channels in the blue and infrared ranges.
Machine Learning Modelling for Future Hydroclimatic Extremes Under Climate Change: A Review
Authors: Antunes Meira Marcela , Xuan Yunqing
Published: March 2024

Hydroclimatic extremes, such as droughts, floods, and extreme rainfall have been increasing worldwide leading to severe impacts on society and ecosystems. For that reason, hydrological modelling research has advanced to improve flood and rainfall prediction and control.  This estimation has been traditionally carried out using physical and process-based hydroclimatic models, however, they have limitations due to their physical-based nature. They often require a large amount of different hydro-geomorphological monitoring datasets, as well as in-depth knowledge and expertise regarding hydrological parameters, which must be correctly selected, calibrated, and further interpreted to ensure the reliability of the model. In recent years, data-driven hydrological modelling, such as Machine Learning (ML), Artificial Intelligence (AI), and Deep Learning (DL) methods have demonstrated a great deal of promise for enhancing the forecasting of hydroclimatic extremes. In data-driven modelling, the models use a generalized relationship between input and output disregarding the physical mechanism behind the process, built based on historical data. ML methods have some advantages over physical-based models, such as not requiring an understanding of internal specific mechanisms, which can be highly complex to reproduce, as well as having a higher calculation efficiency which may provide a quicker response to extreme events of high-intensity and short duration such as urban flash floods. Although there have been significant advances from the scientific community toward understanding and testing different ML and AI models for various hydrological applications, there are still limitations in their applications. A huge challenge that remains in ML modelling for future extreme floods, is its ‘black-box’ nature where the interactions among various components are unknown, which hinders its further use in supporting important decision-making. Along with that, other challenges in the current hydroclimatic modelling approaches presented by the hydrological community are data availability and assimilation, uncertainty analysis, and model generalisation. Some studies have addressed these issues, showing satisfactory results, especially for hybrid models between ML and traditional process-based approaches and ensembles of multiple methods. However, in light of so many new methodologies and algorithms, we must address their benefits and drawbacks, through an interdisciplinary effort. Understanding the best way to select appropriate methodologies for different settings of data availability, climate variability, and uncertainty, generating rapid and interpretable responses to urgent hydrologic hazards.
Ostwald Ripening Leads to Less Hysteresis during Hydrogen Injection and Withdrawal: A Pore-Scale Imaging Study
Authors: Goodarzi Sepideh , Bijeljic Branko , Blunt Martin
Published: March 2024

We performed three cycles of hydrogen injection (drainage) followed by brineinjection (imbibition) combined with high-resolution three-dimensional X-ray imaging on asample of Bentheimer sandstone. After each injection, the sample was imaged initially andafter waiting 16 hours. Capillary pressure was measured from the differential pressure acrossthe rock once the injection has stopped and from estimating the meniscus curvatures from theimages. In addition, the gas saturation, pore occupancy, Euler characteristic and interfacial areaswere measured. There was a significant rearrangement of the gas in the pore space after injection stopped,which we hypothesise is caused by Ostwald ripening, namely the transport of dissolved hy-drogen in the aqueous phase to equilibriate local capillary pressure. This rearrangement led tothe formation of larger, more connected gas ganglia. The capillary pressure displayed char-acteristics that cannot be explained by traditional hysteresis models. While the direct andcurvature-based measurements agreed to within experimental uncertainty, and corresponded toindependent measurements in the literature on initial displacement, Ostwald ripening allowedless trapping and less hysteresis (a smaller difference between drainage and imbibiton capillarypressure) than measured previously on mercury and oil/water systems where Ostwald ripeningdid not occur. The results imply that for gas storage applications it is not appropriate to use hysteresismeasurements based on mercury or hydrocarbon systems. Instead, in local capillary equi-librium, there is less trapping and less difference between drainage and imbibition capillarypressure.
Microbiological Analysis of SURAO Low-pH Concrete (LPC) in repository-like conditions
Authors: Hlavackova Veronika , Le Trung Duc , Riha Jakub , Vecernik Petr , Cernousek Tomas , Hausmannova Lucie , Vasicek Radek , Sevcu Alena
Published: March 2024

Low-pH concrete (LPC) is used as one of the main construction components of deep geological repositories (DGR) for radioactive waste. The mechanical and chemical stability of this material is crucial for the long term DGR sustainability. However, the presence of microorganisms in the underground environment and backfill matrices could significantly affect its stability and in turn the safety of DGRs. The buffer and backfill matrix (bentonite) and underground water are potential long-term sources of bacteria in DGR. The WP MAGIC as a part of the European joint program EURAD focuses on studying the chemo-mechanical behavior of concrete under varied conditions. The project compares the effect of three different conditions – air, water and bentonite - on aged SURAO LPC samples. The 2-year experiment is disposed in Czech Underground Research Facility (URF) Bukov. Our aim was to investigate microbial activity in LPC discs and describe the capability of present microorganisms to affect the mechanical properties of LPC in time. The microbiological analysis comprised of both cultivation dependent and independent approach. The microbial activity was also confirmed using epifluorescent microscopy and scanning electron microscopy. Our findings reveal unique microorganisms in each of in-situ condition, highlighting their potential effect on mechanical properties of LPC.
Global Flood Alerting with an Ensemble of Models and Remotely Sensed Observations
Authors: Glasscoe Margaret , Kar Bandana , Schumann Guy , Mendoza Marina , Bausch Doug , Wang Jun , Hampe Greg
Published: March 2024

Flooding is one of the most frequent and costliest extreme weather events. The Model of Models (MoM) generates integrated products using ensembled hydrologic models and flood outputs derived from Earth observations. MoM provides global flood early warning and near-real time flood severity estimation. MoM results are shared via the Pacific Disaster Center’s (PDC) DisasterAWARE® multi-hazard alerting platform to the global community. Currently, DisasterAWARE incorporates Model of Models (MoM) outputs as flood “incidents,” visually depicting potential floods in the context of population and infrastructure that may become affected. Automated procedures categorize MoM outputs as DisasterAWARE “hazards,” allowing for their dissemination to users along with other flood products that assess potential impacts.
Capturing the synergies among mitigation, adaptation and food security through smart agriculture practices in Muchinga Province of Zambia
Authors: chipanshi aston , chewe jonathan
Published: March 2024

Between March 2016 and September 2020, the Canadian government supported a Southern African Nutritional Initiative (SANI) project in Malawi, Mozambique and Zambia to enable women of reproductive age and children under the age of 5 to  produce, access, store, preserve and process high nutrient food. We report on Zambia’s agricultural component of the project summarizing the key food production techniques used to encourage sustainable agricultural production through the use of smart agricultural practices. These  practices have the potential to allow small farm holders to adapt to climate change and offer opportunities to reduce and remove Green House Gases from these systems in order to contribute to the  Nationally Determined GHG Contributions under the Paris Agreement and meet national food security and development goals. As part of the study, in person training sessions were conducted with participants on smart agricultural practices such as the promotion of local technologies around seed bed preparation of home gardens and orchards, manuring, and the use of local products to control insects, pests and  diseases instead of chemicals. Apart from receiving training in sustainable practices, participants were also trained in food preservation and value addition to harvested produce and grains in order to increase the shelf life and usability of various food types as a way of promoting food security. Anecdotal evidence through follow up field evaluations and food preparation demonstration sessions showed that project participants were adapting  and moving towards achieving a resilient status. These and scale up issues will be discussed in this contribution.
Laboratory analysis on fog harvesting meshes employing durability tests
Authors: Di Bitonto Maria Giovanna , Monticelli Carol , Viscuso Salvatore , Zanelli Alessandra
Published: March 2024

Fog harvesting, an ancient water extraction technique, has gained renewed attention in recent years with the introduction of the Fog Water Collector. Comprising a mesh and supporting structure, this collector has proven effective in extracting water from atmospheric moist air. The Raschel mesh, initially designed for agricultural purposes, has become the predominant choice due to its affordability and widespread availability. Current research endeavors aim to enhance fog water yield by optimizing both collector design and mesh properties.While Raschel mesh coatings have traditionally been explored to improve efficiency, recent findings suggest that alternative meshes may outperform the conventional Raschel mesh. However, challenges persist in understanding the resistance, lifespan, and maintenance requirements of these newer materials.Our research takes a systematic approach to address this gap by assessing the durability of various fog harvesting meshes under laboratory conditions. A series of standardized tests are conducted to evaluate their efficiency, providing insights into the intricate relationship between cost, water collection efficiency, duration, and environmental impact. The study aims to inform decision-making processes surrounding fog harvesting mesh selection, considering factors such as initial investment, operational efficiency, and long-term sustainability.By conducting these analyses in a controlled laboratory environment, we aim to provide valuable insights without the logistical challenges associated with field studies. This approach allows for a thorough examination of fog harvesting mesh performance, contributing to the broader understanding of NRWIs and their potential applications at different scales.
Density-driven flows: Plumes and Density Currents
Authors: Bhaganaagar Kiran
Published: March 2024

 Buoyancy-generated turbulence processes with substantial density variations within the flow are critical in oceanic systems. The talk highlights a universal framework to characterize density currents and turbulent plumes released from a source. Variable density effects in density currents and plumes alters the velocity field due to variation in density. Consequently the pathways for turbulence generation, mixing and transport are complicated than a passive scalar mixing. A large-eddy-simulation is used to simulate density currents and plumes released from a source.  In this talk, Favre-averaged turbulence transport equations for generalized compressible flows are presented within the context of density currents and plumes. A simplified conceptual turbulent model is presented.The study is focused on addressing a pivotal question: whether the kinetic energy spectrum follows the traditional inertial -$5/3$ spectrum, or displays a -$3$ buoyancy regime, or demonstrates a combination of both phenomena. Significant deviations from the inertial spectra are observed. New insights on the spectral transfer of energy, and turbulence mechanims for buoyancy-driven flows are presented
Relational database construction for Table of Aerosol Optics
Authors: Derimian Yevgeny , Ducos Fabrice , Lesueur Philippe , Schuster Gregory L.
Published: March 2024

This effort is dedicated to construction of a relational database and an interactive web system that organizes and communicates aerosol optical and microphysical characteristics assembled in the Table of Aerosol Optics (TAO) community repository. The TAO project (https://science.larc.nasa.gov/mira-wg/topics/tao/) is an extension of historical efforts (e.g., Shettle and Fenn, 1979; d’Almeida et al., 1991; Koepke et al., 1997; Hess et al., 1998) on providing libraries of aerosol characteristics for applications in global chemical transport modeling and remote sensing. Aerosol characteristics such as size distribution, complex refractive index, shape, mixing state, extinction, absorption, single-scatter albedo, lidar ratio, etc. are provided for different aerosol types, wavelengths, be originated from laboratory measurements, in situ or remote sensing observations. Combination of aerosol characteristics, their origins, types, spectral domains, computational techniques used for single-scatter properties become quickly very complex and is expected to evolve in future. The open access and interactive principles of TAO implies increasing complexity of its database structure that requires involvement of dedicated computer science technics for its organization and management. The relational database conception, for instance, is widely used in many domains that require such data organization and naturally appropriates to TAO. The relational database consists in structuring the data in multiple tables, with so-called primary or foreign keys that relates between entity types, parameters and their value in unique or multiple connections. We therefore started development of tools for uploading of the TAO data into the format of relational database and creation of a web interface for an interactive communication with the community. This work is expected to be presented as complimentary to a more general presentation about the TAO project by G. L. Schuster and gather valuable feedbacks from modelers, in situ and remote sensing experts on the data needs, convenient exchange formats and potential applications.
Application of Machine Learning Approaches for Cotton Seasonal Yield Estimation 
Authors: Umutoni Lisa , Samadi Vidya , Payero Jose , Koc Bulent , Privette Charles
Published: March 2024

Estimating crop yield can help farmers plan for equipment, labor, and other crop production input requirements. Forecasting crop yield is also useful for analyzing weather-related variability to guide decisions such as irrigation water and fertilizer management. This work discusses the application of Gated Recurrent Unit (GRU) and Long Short-Term Memory (LSTM) machine learning algorithms for seasonal cotton yield prediction. Simulation results from the crop model AquaCrop, consisting of irrigation depth, soil moisture content, and crop growth stage data from 2003 to 2021 were used to train the algorithms. The two developed yield-prediction models were tested against data collected from an irrigated cotton field located at Clemson University Edisto Research and Education Centre (EREC), near Blackville, South Carolina, USA during the 2023 growing season. The values of hidden layers, hidden units, dropout, learning rate and batch size hyperparameters were set to respectively, 3, 64, 0.2, 10E-3 and 64 for the GRU model and 3, 128, 0.4, 10E-3 and 64 for the LSTM model. Analysis suggested that the tested algorithms resulted in very good to excellent performance. We concluded that machine learning algorithms are useful tools that can provide insights into how much yield to expect in an upcoming season and help farmers optimize energy, water, and fertilizers applications.
Socio-metabolic class conflicts in the Anthropocene
Authors: Otto Ilona M. , Schuster Antonia
Published: March 2024

The Anthropocene epoch is characterized by an excessive use of natural resources and energy that drives the environmental destruction of the planet. However, large inequalities exist among different social groups that benefit to various degrees from the use of resources and energy, as well as among those suffering from the negative impacts of environmental destruction. In this paper, we systematically analyze these differences and propose a novel social stratification theory based not only on differences in terms of possessions or social status, but also on differences in how these groups can control and benefit from the planetary material cycles and energy flows or suffer the consequences of environmental degradation. Referring to consumption data, we propose six global socio-metabolic classes and show distinctive patterns in the energy use of these classes. More research is needed to reveal differences in the use of natural resources essential for maintaining the biosphere integrity, such as land, water, nitrogen, and phosphorus. Targeted policy measures that address excessive appropriation of energy and natural resources are needed, as are expansions in infrastructure and institutional change that supports the wellbeing of humankind, and especially of the most marginalized classes.
Assessing the effect of citrus plant on the improvement of the outdoor thermal environment using wind tunnel and ground-based Leaf Area Index measurements
Authors: Tsoka Stella , Pappa Vasiliki , Markos Nikos , Bouris Demetri
Published: March 2024

This study presents the preliminary results of the ongoing research project “Re.Nature Cities”, in which  the ability of street trees to act as an effective measure against increased urban air temperatures is evaluated via experimental and simulation means. In the existing literature, numerous studies highlight that the addition of street trees inside the canyons of urban areas may result in a significant reduction of the peak ambient summer Tair, having also a prominent effect on outdoor thermal comfort regulation. Yet, street trees also impact urban ventilation as they act as barriers, disturbing the wind flow and affecting buildings’ energy needs and thermal comfort; the positive effect of wind sheltering during the cold winter period, can be thus significantly counterbalanced during the warmer periods of the year. The existing evidence reveals that the green elements’ implementation in the built environment without holistically accounting for all the vegetation-air-buildings interactions, can even exacerbate human discomfort and deteriorate indoor natural ventilation.Based on the above, this study evaluates the mitigation potential of a tree type that is commonly encountered in Greek cities – the citrus- since it has low irrigation needs and high drought tolerance. An integrated experimental campaign, employing wind tunnel measurements, albedo and Leaf Area Index/Leaf Area Density (LAI/LAD) measurements is conducted so as to define of the aerodynamic, thermal and foliage characteristics of real trees.  Wind tunnel measurements of total drag are carried out in a wind tunnel section of 3.5m width and 2.5m height, while LAI measurements are conducted using a plant canopy analyzer, with the LAD of each layer (1 m/layer) then calculated from LAI by empirical equations. The obtained values are then used as input parameters in the vegetation model of the ENVI-met microclimate model, which is employed for the evaluation of the thermal environment of typical building blocks in Greece, considering different planting patterns and vegetation coverage scenarios.The experimental database of foliage, thermal and aerodynamic characteristics of common urban tree species, along with the detailed microclimatic simulations of typical urban districts provide a valuable tool for decision-making regarding the optimal vegetation coverage and the planting pattern for urban areas. 
Hitchikers’s Guide to Capri Island’s Geotourism, Italy
Authors: Vergari Francesca , Verga Martina Nicole , Donadio Carlo , Pica Alessia
Published: March 2024

Mass tourism affects Italian minor islands during summer, and the main attractions are seaside and boat tours, together nightlife. Nevertheless, the islands are hotspots of Mediterranean geodiversity, biodiversity, and culture. This study presents a geotourist itinerary on Capri Island based on a geomorphological survey and mapping, geoheritage inventory, and evaluation for geotourism purposes. This research highlights Capri’s geosites’ scientific, scenic and cultural values as an alternative to mass tourism focused on the coasts. The Island of Capri is the best-known Italian island worldwide, so it could be sampled for the valorization of other islands through geotourism. On the Island of Capri, 8 geosites have been inventoried and evaluated, and an itinerary is proposed mainly based on terrestrial geosites, summarizing naturalistic and cultural values. The itinerary is implemented in Google Earth Pro TM to be available remotely and on-site. Geo-interpretation of the patrimony makes it accessible to the lay public, promoting its popularization and the development of more sustainable recreational activities on the island.
Double Direct Shear Experiments as an interacting two fault system:  insights from laboratory seismic cycles on fault interaction 
Authors: Mastella Giacomo , Pignalberi Federico , Giorgetti Carolina , Scuderi Marco
Published: March 2024

Double direct shear experiments serve as established methods for delving into the physics of laboratory earthquakes. Using a biaxial shearing apparatus with dual fault configurations, these friction experiments simulate real Earth faults' behaviors during loading and failure. Despite the presence of distinct layers, double direct shear experiments are commonly perceived as a unified fault system, where the evolution of fault zone properties captured through passive or active seismic imaging can be correlated with the instantaneous stress state affecting both layers uniformly. To further explore the physics of seismic cycles generated in this setup, we perform friction experiments aiming to independently monitor the behavior of each fault layer. In our experiments, we use granular quartz (medium grain size 40 µm) to simulate fault gouge, amd we vary the normal load and shear velocity, allowing us to modify the apparatus's loading stiffness, which relies on the critical fault rheologic stiffness (kc). In the Rate-and-State framework, increasing the normal load results in an  increase of kc, pushing the system towards instability, occurring when k/kc
Using Multi-Omics and RTMS to Unravel the Microbiome Molecular Mechanisms of Carbon and Nutrient Cycling during Rewetting after Drought
Authors: Lipton Mary , Weitz Karl , Smith Montana , Moran James
Published: March 2024

Microbial response to changing environmental factors influence the fate of soil organic carbon and drought has been shown to affect microbial metabolism and respiration. We hypothesized that the access of microbes to different carbon pools in response to dry - rewet events occur sequentially at different rates.  We amended desiccated soils with 13C labeled glucose and measured the rates of 12CO2 and 13CO2 respiration in real time after rewet. Using these differentiated 12CO2 and 13CO2 respiration rates soils after rewet, we were able to deduce when microbes are accessing different pools of carbon. Immediately upon rewet, respiration of 12CO2 occurred first, with negligible 13CO2 respiration. Appreciable metabolism and respiration of the added 13C glucose did not occur until 15 minutes after rewet. We conclude that while all carbon pools are being accessed in the first 9 hours after rewet, the rate and timing that new and existing carbon pools are being accessed varies. Additionally, The metaphenome was evaluated by measuring metabolite, protein and transcript profiles through the dehydration and rewetting time course. We found that that soil microbial communities can quickly react to changes in soil moisture by shifting their metabolite compositions and this response is directly proportional to the length of drought exposure time. This may have important implications for carbon allocation within and between organisms and the soil environment.  Within this study, using stable isotope labeled substrates and multi-omics analysis to discern which carbon pools are metabolized first uniquely illustrates how microorganisms access different carbon pools which has implications into understanding how carbon metabolism can further affect climate, carbon sequestration, and soil health. 
Optomechanical inertial sensors for space and planetary sciences
Authors: Guzman Felipe
Published: March 2024

We report on the progress of our novel low-frequency optomechanical inertial sensing technologies for gravimetry, accelerometry and seismometry on ground, space and planetary applications. Our technologies are designed to be compact, portable, and are comprised of monolithically fabricated mechanical resonators that incorporate compact and highly sensitive laser interferometric displacement sensors.
Current laboratory prototypes have demonstrated mechanical quality factors Q of 4.77x105, an mQ-product above 1200 kg, a fundamental mechanical resonance of 4.7 Hz, which highlight their high sensitivity with acceleration noise floor nears 1x10-11 m s-2/√Hz. Such compact systems are excellent candidates for portable and deployable systems on compact and low SWaP platforms and flight payloads.
A prototype packaging has been developed to reduce losses caused by typical mechanical mounts. We have conducted comparison measurements with commercial low-frequency systems to an excellent agreement. Recent measurements taken with the resonator mounted in this packaging atop a vibration isolation platform have indicated that our system is seismically limited above 1 mHz. Noise floors in the order of 82 pico-g/√Hz at 0.4 Hz has been demonstrated in our laboratory.
We will present recent updates on our optomechanical inertial sensors, including up to date measurements of the resonator and interferometer sensitivity, as well as that of the combined system.  
Simulating future Food Value Chain components through the integration of biophysical and techno-economic spatial models
Authors: Teixeira Edmar , Leduc Sylvain , Tiwari Shubham , Kraxner Florian , Guo Jing , McNally Sam , Yao Richard , Yang Xiumei , Johnstone Paul , Sowersby Thomas , Edmonds Richard , Maley Shane , Sood Abha , Bristow James , Moot Derrick
Published: March 2024

We describe the methodological development and preliminary results of a new spatial modelling framework to support the evaluation and design of novel Food Value Chains (FVC). The sustainability of future FVCs will depend on how effectively these can be adapted to environmental (e.g., climate change) and socio-economic (e.g., resource access and dietary preferences) changes projected for coming decades. Our approach aims to account for the spatial and temporal complexity inherent to both biophysical (e.g., climate, genotypes and soils) and techno-economic (e.g., processing technologies and markets) components of FVCs to optimise supply- (e.g., production areas) and demand- (processing-plant locations) across landscapes. For that, we integrated georeferenced biophysical outputs of a process-based agricultural model (Agricultural Production Systems sIMulator, APSIM-NextGeneration) into a spatial techno-economic model (IIASA-BeWhere). We test the approach through a case-study to evaluate a novel (hypothetical) FVC to produce plant-based proteins from lucerne crops (Medicago sativa) across New Zealand’s agricultural landscapes. Results highlighted spatial protein production patterns driven by changes in crop canopy expansion and net carbon assimilation, with lower yields estimated in cooler and dryer environments, particularly when water supply was limited under rain-fed (non-irrigated) conditions with soils of low water holding capacity. Spatial variability in protein yields, production costs and emissions estimated by APSIM-NG running in the ATLAS framework were then used as inputs by BeWhere to optimise the location of production areas and protein-processing plants. We discuss potentials, limitations, and future development areas of this approach.
Using rapid source characterisation to improve ShakeMaps and impact forecasts for large earthquakes (M6.5+) in New Zealand
Authors: Kaiser Anna , Andrews Jen , Fry Bill , Horspool Nick , Lukovic Biljana , Massey Chris , Warren-Smith Emily , Chamberlain Calum , Goded Tatiana , D'Anastasio Elisabetta , Zweck Chris , Aden Florent
Published: March 2024

The New Zealand R-CET Endeavour programme has been developing a suite of tools to characterize the earthquake source and its shaking in near real-time.  A key goal is to provide pathways to improve rapid earthquake impact forecasts.  Small-to-moderate earthquakes can be reasonably represented by a ‘point source’.  This allows us to generate first shaking maps (GNS Shaking Layers; Horspool et al. 2023) automatically and robustly based on basic earthquake solutions (magnitude and hypocentre). These maps are now routinely available to the public within 10 – 20 minutes: https://www.geonet.org.nz/about/earthquake/shakinglayers#:~:text=What%20is%20Shaking%20Layers%3F,intensity%20anywhere%20in%20the%20country.For very large earthquakes (M6.5+), a ‘point-source’ is a poor representation of the earthquake, which can rupture tens to hundreds of kilometres of the earth.  First shaking models based on ‘point sources’ could severely underestimate shaking in areas further from the epicentre, but close to the fault rupture. Rapid 3D characterization of the rupture area, even if approximate, has the potential to significantly improve shaking estimates, and allow meaningful first impact forecasts to be generated.Here we present an overview of rapid source characterization tools implemented for New Zealand under the R-CET programme. These tools include FinDer (Andrews et al. 2023), w-phase (Fry et al. 2022), EQCorrScan (Chamberlain et al. 2017; Warren-Smith & Chamberlain 2022), G-FAST and others . We show examples of tool outputs for large (M6.5+) historical earthquakes in New Zealand and examine their potential to improve rapid shaking models, loss estimates and landslide forecasts. Our results show the importance of including rapid source characterization as a key component of our earthquake response systems, to underpin quality scientific advice for emergency responders.
Nordstream pipelines CH4 leak estimates and transport uncertainty using ICOS data and the FLEXPART Lagrangian particle dispersion model
Authors: Pisso Ignacio , Platt Stephen , Schmidbauer Norbert , Eckhardt Sabine , Evangeliou Nikolaos , Marthinsen Erik , Thompson Rona , Cassiani Massimo
Published: March 2024

Following the sabotage of the Nord Stream 1 and 2 subsea pipelines on 26 September 2022, natural gas leaks resulted in unprecedented emissions of methane that were detected by several ICOS stations. As the plume traveled North, the detections occurred mainly in Scandinavia. NILU’s initial modeling activities provided a preliminary estimate of 155 KtonCH4 for the leaks that was made public as a press release. A recent collaborative effortorganized by the United Nations Environment Programme’s International Methane Emissions Observatory (UNEP’s IMEO) provided new model-based pipeline rupture outflow rates. In combination with updated ICOS CH4 time series we updated the estimated release values produced. We discuss the uncertainties associated with the atmospheric modelling for this updated analysis with emphasis on the Lagrangian transport aspects of the problem and the associated uncertainties.
Contrasting water use strategies to climate warming in white birch and larch in a boreal permafrost region
Authors: Qi Xi , Treydte Kerstin , Saurer Matthias , Fang Keyan , Ann Wenling , Lehmann Marco , Liu Kuyuan , Wu Zhengfang , He Hong , Du Haibo , Li Mai-He
Published: March 2024

The effects of rising atmospheric CO2 concentrations (Ca) with climate warming on intrinsic water-use efficiency (iWUE) and radial growth in boreal forests are still poorly understood. We measured tree-ring cellulose δ13C,δ18O, and tree-ring width in Larix dahurica (larch) and Betula platyphylla (white birch), and analyzed their relationships with climate variables in a boreal permafrost region of northeast China over past 70 years covering a pre-warming period (1951-1979; base period) and a rapid-warming period (1980-2018; warming period). We found that white birch but not larch significantly increased their radial growth over the warming period. The increased iWUE in both species was mainly driven by elevated Ca but not climate. White birch but not larch showed significant positive correlations between tree-ring δ13C,δ18O and summer maximum temperature as well as vapor pressure deficit in the warming period, suggesting a strong stomatal response in the deciduous birch but not in the conifer larch to climate warming. The climate-warming induced radial growth enhancement in white birch is associated with a more ‘conservative’ (low gs, constant A) water use strategy than in larch (constant gs, high A), suggesting an advantage for the former than the latter in a warming world in the permafrost regions.