bluuebunny/crossref_metadata_2025 huggingface dataset:
Modelling phytoplankton biomass evolution in a micro-tidal estuary: the case of Fangar Bay.
Authors: Balsells F-Pedrera Marta , Grifoll Manel , Espino Manuel , Fernández-Tejedor Margarita , Sánchez-Arcilla Agustín
Published: March 2024

The primary production in coastal bays and estuaries is influenced by multiple physical variables, such as wind, tides, freshwater inputs or light availability. At short temporal scales, these factors can influence other variables such as phytoplankton biomass, as well as the amount of nutrients present in the water body. Observations made in Fangar Bay, a small, shallow, microtidal bay in the NW Mediterranean Sea, have shown that there are spatial and temporal variations in phytoplankton biomass depending on different wind events. This bay is characterised by the presence of sea breezes and episodes of very strong NW winds, which homogenize the water column for variable periods of time. The Regional Ocean Modelling System (ROMS) coupled to a nitrogen-based nutrient, phytoplankton, zooplankton and detritus (NPZD) model has been applied to understand this spatio-temporal variability of the phytoplankton biomass in Fangar Bay under a range of conditions. Four sampling points have been chosen to visualize the differences in concentration within the bay. When breezes blow (6 m·s-1), stratification predominates, featuring higher concentrations at the surface than at the bottom.  In contrast, during strong wind episodes (> 10 m·s-1), the water column is well mixed, which homogenises nutrient concentrations throughout the column and increases the phytoplankton biomass in the lower layers. The dispersion of freshwater plumes from irrigation channels conditions the spatial distribution of phytoplankton biomass within the bay. The performed numerical analyses demonstrate the influence of freshwater plume evolution on the distribution of phytoplankton biomass and other water properties, in agreement with remote sensing observations. These results provide a quantitative basis for a more sustainable management of such constrained coastal domains.
Keywords: phytoplankton biomass, ROMS-NPZD model, wind, biological parameters, physical parameters, Fangar Bay.
Acknowledgements: This work has been funded by the I+D+i project ECO-BAYS (PID2020-115924RB-I00) financed by MCIN/AEI/10.13039/501100011033; and REST-COAST (H2020-101037097-REST-COAST) under the European Union’s Horizon 2020 program.
Was the early geodynamo driven by exsolution near the CMB?
Authors: Vidal Jeremie , Monville Remy , Cébron David , Schaeffer Nathanael
Published: March 2024

Paleomagnetic data show that the Earth has owned a dynamo magnetic field for at least 3.5 Ga [1]. The geodynamo thus appeared well before the inner core nucleation [2], but its origin remains puzzling. Indeed, given the contradictory estimates of the thermal conductivity of liquid iron at core conditions [3], secular cooling may have not been strong enough to sustain it. Finding mechanisms capable of sustaining the geodynamo is thus crucial to understand the early Earth evolution. In particular, it has been proposed that the geodynamo could have been sustained by exsolution (or precipitation) of light elements near the core-mantle boundary (CMB) [4,5]. This mechanism could be powerful enough to sustain dynamo action (from an energetic viewpoint [6]), but its relevance has to be assessed using fluid dynamics models. 
Using global simulations, we explore the flow dynamics driven by exsolution of light elements in the early Earth. When the thermal conductivity is assumed to be large, we report and characterize two different flow regimes [7], which depend on the strength of thermal stratification in the core. Next, we assess the dynamo capability of these two regimes for the first time. We show that they are associated with a dipolar-multipolar transition for dynamo action. Our simulations thus constrain the thermal stratification of the core to be likely weak in the early Earth (to be compatible with the large-scale magnetic field evidenced by paleomagnetic data).
[1] Tarduno et al., 2020, PNAS, 117(5), 2309-2318[2] Zhou et al., 2022, Nat. Comm., 13(1), 4161[3] Pozzo et al., 2022. EPSL, 584, 117466.[4] Badro et al., 2016, Nature, 536(7616), 326-328[5] Hirose et al., 2017, Nature, 543(7643), 99-102.[6] Landeau et al., 2022, Nat. Rev. Earth Environ., 3(4), 255-269[7] Monville, Vidal et al., 2019, GJI, 219(S1), S195-S218
Micro-mechanism on strength development and failure mode of cemented ultra-fine tailing backfill: Influence of binder
Authors: Cheng Aiping
Published: March 2024

As cemented ultra-fine tailings filling method gains popularity, the demands for more economical and environment friendly binders rise. In order to better understand the influence of different binders on the mechanical properties of cemented ultra-fine tailings backfills (CUTBs), the CUTBs with solid materials of 72% for 3, 7, 14, 21 and 28d respectively were made by the water-quenched slag binder (WSB) and ordinary Portland cement (OPC). The microstructure characteristics and macro-mechanical properties of WSB-CUTB and OPC-CUTB at different ages were compared by uniaxial compressive strength (UCS), thermo-gravimetry (TG), X-ray diffraction (XRD) and surface electron microscope (SEM) tests. The results show that the strength development process of CUTBs with different binders has obvious phased characteristics, which can be divided into the initial germination (IG) stage, rapid growth (RG) stage and slow growth (SG) stage: the UCS of WSB-CUTB increases quicker than UCS of OPC-CUTB at the IG and RG stages, while the UCS of OPC-CUTB increases faster than UCS of WSBCUTB at the SG stage. The micro-mechanism on strength development of CUTBs with different binders was revealed by the evolutional characteristics in the amounts and shapes of hydration products: the amount and shape of AFt are the primary factors which impact the strength development at the IG and RG stages, while the amount and shape of C-S-H are the primary factors which impact the strength development at the SG stage. As the age increases, WSB-CUTB transitions from brittle failure to brittle-ductile failure, while OPC-CUTB transitions from ductile failure to brittle-ductile failure. The micro-mechanism on the failure modes of CUTBs with different binders was revealed by the different characteristics in the skeleton composed of hydration products: the CUTBs with AFt-dominated skeleton will transition from brittle failure to brittle-ductile failure, while the CUTBs with CS-H-dominated skeleton will transition from ductile failure to brittle-ductile failure. The research results provided theoretical guidance for applying CUTBs using WS as a binder.
Stratospheric Aerosol and Ozone Responses to the Hunga Tonga-Hunga Ha'apai Volcanic Eruption: Insights from Chemistry and Dynamics
Authors: Lou Sijia , Lu Jinpeng , Huang Xin , Xue Lian , Ding Aijun
Published: March 2024

The Hunga Tonga-Hunga Ha'apai (HTHH) eruption on January 15, 2022, was one of the most explosive volcanic events of the 21st century so far. According to satellite-based measurements, 0.4 Tg of sulfur dioxide (SO2) was injected into the stratosphere during the eruption. Using observations and model simulations, we investigate changes in the chemical composition of the stratosphere one year after the HTHH eruption and examine the key physical and chemical processes influencing ozone (O3) concentrations. Injected SO2 was oxidized into sulfate during the first two months and transported from the tropics to the Antarctic by the Brewer-Dobson circulation within one year. In mid-to-low latitudes, enhanced sulfate aerosol increased O3 concentrations in the middle stratosphere but declined in the lower stratosphere. In addition to the chemical processes, sulfate aerosols also reduced polar low-stratospheric O3 concentrations through enhanced Antarctic upwelling anomalies. We suggest that catalytic NOx ozone loss cycles, sulfate aerosols’ radiative effects, and vertical transport processes are the main factors influencing stratospheric ozone variations.
Combining Generative Adversarial Networks with Multifractals for Urban Precipitation Nowcasting 
Authors: Zhou Hai , Schertzer Daniel , Tchiguirinskaia Ioulia
Published: March 2024

Precipitation nowcasting, referring to short-term forecasting ahead for 0 to 6 hours, is an important aspect of many urban meteorological and hydrological studies. This is due to the fact that reliable nowcasting can serve as an early warning of massive flooding and a guide for water-related risk management, making it highly significant in urban areas from a socio-economic perspective. Precipitation exhibits extreme variability over a wide range of space-time scales, so nowcasting is essentially a spatiotemporal sequence forecasting. Convolutional long short-term memory (ConvLSTM) models are frequently used to capture the spatiotemporal correlation, but they often struggle with an issue that produces blurry predictions. Therefore, generative adversarial network (GAN) architecture is employed to achieve more detailed and realistic predictions. The framework of universal multifractal (UM) with only three scale-independent parameters (α, C1, H) is also introduced in the deep learning model to characterize the extreme variability of precipitation. The developed hybrid approach using stochastic models physically based on the cascade paradigm ensures that intermittency is directly taken into account, including in the generation of uncertainty. In addition to the common evaluating metrics, like mean absolute error (MAE), root mean squared error (RMSE), critical success index (CSI), probability of detection (POD), power spectral density (PSD) and UM are also introduced to evaluate nowcasting performance in the spectrum space. This ongoing work is based on the previous research about combining recurrent neural networks with variational mode decomposition and multifractals to predict rainfall time series in Paris area.
Impacts of Glacier Activity on Glacier Debris Flow Evolution in a Changing Climate
Authors: Li Yao , Cui Yifei
Published: March 2024

It has been widely recognized that global warming induces glacier retreat and shrinkage in the cryosphere since the mid-20th century. Such landform and glacier activity changes in the glacierized environments not only perturb the downstream hydrological conditions, but also provide favorable conditions for glacial debris flow hazards and threaten the downstream residents, industrial facilities, and hydropower stations, especially in High Mountain Asia. Quantitatively analyzing frequency-size change of glacier debris flow in a warming climate and finding its early warning indicators are critical for disaster assessment and mitigation. In this study, multi-source long-term remote sensing images and meteorological monitoring data, combined with field data, were applied to analyze the hazardous response of retreating glaciers to climate warming in Southeast Tibet. Eventually, 110 glacial debris flow events were identified from 1986-2023. These events were induced by four identified reasons: glacier lakes outburst flood (GLOF), ice-rock avalanches, precipitations, and surge of meltwater. Based on the time series catalog, it can be found that the glacial debris flow has shown the increasing frequency and scale since 1973, and the frequency of the debris flows induced by moraine landslides and ice-rock avalanches in steep terrain has increased. In the past four decades, climate change has led to complex responses in glacier activities, characterized by increased activity of smaller glaciers (high-altitude hanging glaciers) and weakened activity of glaciers in large valley. In the future, the continuous retreat of glaciers will promote the disappearance of icefalls and the development of larger-scale hanging glaciers with heightened activity, which will increase the frequency of ice-rock avalanche induced debris flow. During the evolution process of these glacial debris flows, we found four possible indicators for event warning, including crevice density, glacier velocity, glacier geomorphology change (icefall disappeared), and expanding glacial lakes.
Rapid unsupervised economic assessment of urban flood damage using SAR images
Authors: Eudaric jeremy , Camero Andres , Rafiezadeh Shahi Kasra , Kreibich Heidi , Martinis Sandro , Zhu Xiao Xiang
Published: March 2024

Climate change projections for 2030 indicate a concerning increase in the frequency of floods, which is expected to result in significant economic damages and losses on a global scale. The growth of urbanization has indeed increased flood risk, highlighting the need for a prompt evaluation of economic losses to facilitate rapid response and effective reconstruction. However, providing timely and accurate economic damage assessment immediately after a flood event is difficult and associated with high uncertainty. Remote sensing  data can support this task, but challenges such as cloud cover, infrequent return times from satellites, and the lack of ground truth data make supervised approaches challenging. To address these challenges, we propose a new economic damage assessment approach based on the analysis of multi-temporal and multi-source, Synthetic Aperture Radar (SAR) images before and after the flood peak with an unsupervised change detection method. This method utilizes computer vision techniques, specifically a pixel-based approach with SAR data (Sentinel-1 and TerraSAR-X/TanDEM-X) to monitor changes in buildings and the flood extension. It employs various threshold techniques and parameters to determine the optimal threshold values for highlighting changes and the presence of water. By using this method, our aim is to obtain an economic model based on pixels, which represents the volume of water surrounding or on each building and the flood extension. The purpose of this study is to support governments in decision-making processes and enable insurers to efficiently assess and compensate for damages caused by flood events. 
Why does irrigation with hyperoxic water alter soil biochemistry?
Authors: Baram Shahar , Levmore Hadas
Published: March 2024

In the published literature, irrigation with hyperoxic (dissolved oxygen > 15 mg/L) nanobubbles aerated water (NB-water) has a significant impact on bio-geo-chemical processes in soils. Yet, simple mass balances show that the amount of oxygen added to soils with such waters provides less than 1% of the oxygen respired. Further, such practices only slightly increase (0.1-0.5%) the oxygen concentration in the soil air. These minor contribution to the soil’s oxygen pool raises questions about the mechanisms that drive the impact on the bio-geo-chemical processes in it. Specifically on the soil’s microbial population and activity, greenhouse gasses emissions, and plant growth.  Soil respiration and nutrient uptake require a continuous supply of oxygen (O2) to the rhizosphere. However, in reality, in most soil, the rate of O2 diffusion into the soil is lower than the rate of its consumption. Hence, O2 concentrations in the rhizosphere are lower than in ambient air (20-21%; normoxia), and often sub-optimal or anoxic conditions develop. To date, the definition of sub-optimal O2 concentrations is not clear, and the general perception is that in most soils, O2 is not a crop-limiting factor. However, in recent years, more and more studies have shown that even small changes in the O2 concentration of the soil air (i.e., >0.2%) positively impact plant growth, metabolism, and yield. Results from studies with various soil aeration methods, such as the dissolution of micro- and nanobubbles and peroxides, show a positive response to O2 additions, even when the additions contributed a mere 0.01-1% of the soil respiration fluxes. The governing mechanisms for such positive responses are unclear, and further study is needed. 
Analysis of Extreme Precipitation Events in India under Shared Socioeconomic Pathway Scenarios: Application of Complex Networks
Authors: Bhadran Deepthi , Sivakumar Bellie
Published: March 2024

Analyzing the complex behavior of extreme precipitation events is essential for a better understanding of the effects of climate change on water resources and for forecasting extreme hydrologic events. In this study, complex network concepts are applied to investigate the synchronization patterns of extreme daily precipitation events across India, with an evaluation of how these patterns may vary in the future. Daily rainfall data provided by the India Meteorological Department (IMD) for the period 1961-2020 at a spatial resolution of 0.25ᵒ×0.25ᵒ are used to investigate the synchronization patterns of extreme rainfall during the historical period. To assess synchronization patterns in the future, rainfall projections from selected General Circulation Models under different Shared Socio-Economic Pathway Scenarios are employed. A day with precipitation greater than 1 mm is considered a wet day, and a wet day is then classified as an extreme precipitation event only if its precipitation exceeds the 95th percentile of all wet days. For the construction of the network, each grid is considered as a node, and the connections between them are identified using the event synchronization method. Both historical and future precipitation networks are analyzed for two different seasons: (i) Summer (June, July, August, and September); and (ii) Winter (December, January, and February). Two network measures, namely degree centrality and clustering coefficient, are determined for these networks. Changes in network measures, relative to the baseline period of 1961–2020, are analyzed across three different timeframes: the 2020s, 2040s, and 2070s. The findings from the network measures can reveal crucial geographic locations in terms of their connection patterns to other areas for both seasons.  
Modelled Emission Reduction Potentials from the Transport Sector in Nairobi City
Authors: Mwangi John Kennedy , Mwaniki George , Apondo William , Murgor Ivy , Munyambu Purity
Published: March 2024

The city of Nairobi, Kenya, is experiencing accelerated growth with increasing population. Expectedly, there is bound to be a rise in the vehicle population leading to rising pollution from the transport sector. This study proposes mitigation scenarios for pollutant reduction from the transport sector within Nairobi. Assuming that about 70% of the vehicles registered in Kenya are found within Nairobi, the vehicle population up to 2030 was projected using a growth rate of 10%. The vehicle kilometer traveled values were obtained from literature and the vehicle category distribution was determined from the values obtained in the vehicle traffic count and origin-destination data collection exercises carried out in this study. The pollutant levels were modeled using the Global Atmospheric Pollution Forum Air Pollutant Emission Inventory tool (GAPF). This tool is used to estimate emissions from various sectors and assist in the development of Emission Inventories, especially in developing countries that lack databases and relevant information. The air pollutants considered in this study are oxides of nitrogen (NOx), carbon monoxide (CO), non-methane volatile organic compounds (NMVOC), ammonia (NH3), and total particulate matter (PM10 and PM2.5). The projected emissions values for various pollutants had four scenarios including Scenario (a) Business as usual (BAU) where the vehicle growth rate was 10% per annum with only 10% having Euro IV, Scenario (b) 2023 as the base year with 10% of the vehicles having Euro IV technology and subsequent phase increase in this fraction is 5% for 2024 and 2025, 10% for 2026, 2027, and 2028 and no subsequent increase for 2029 and 2030, Scenario  (c) 2023 as the base year and all new vehicles were euro IV and Scenario (d) a combination of scenarios (b) and (c). The modeled results showed that the BAU scenario indicated a steady increase in pollutant emission levels over the period considered. For the second and third scenarios, there was an increase in the rising trend when the increase ratio was 5% followed by a sharp decline trend (especially for NMVOCs) when considered due to the increasing number of vehicles as a whole. The best intervention scenario combines the assumption that all new vehicles are meeting Euro IV standards and that there is a phase increase in the uptake of exhaust gas treatment technologies such as DPFs and catalytic converters for this scenario there was a projected decline in the emission levels of both NMVOCs and total PM. The reduction potentials were 28.5% for NMVOCs and 26.8% for total PM by 2030. This mitigation scenario could be recommended to the city government to inform the policies aimed at mitigating the pollution from the transport sectors.
Generalizability of AI-based Emulators for CFD Lagrangian methods 
Authors: Amato Eleonora , Zago Vito , Del Negro Ciro
Published: March 2024

The combination of Computational Fluid Dynamics (CFD) and Artificial Intelligence (AI) enables to expand the scope of fluid modeling and improve simulation performance. Eulerian methods have already been extensively integrated with AI, providing high-fidelity and reliable results (e.g., weather prediction); the application of AI to Lagrangian methods remains less consolidated. Smoothed Particle Hydrodynamics (SPH) is a Lagrangian mesh-less CFD numerical method with well-established advantages for the simulation of highly dynamic free-surface complex fluids. However, reliable SPH simulations require long execution times and large computational resources. This downside can be resolved using emulators, which can reproduce the dynamics of a physical system, speeding-up the simulations. In detail, an emulator is a model in which AI algorithms join or replace the equation-based mathematical representation of physics. Thus, the emulator learns from CFD simulations the behavior of the CFD reference model and reproduces it to solve fluid dynamics problems in shorter times. For the emulator to be trusted, it is important to assess the ability to generalize and correctly predict the behavior of the fluid in conditions that have not been presented during training phase. Here, we present the generalizability of an AI-based emulator for SPH, utilizing an Artificial Neural Network (ANN) to estimate the hydrodynamic forces between SPH particles. We demonstrate the capability of the emulator to reproduce particle interaction quantities, as opposed to their specific spatial configuration. Therefore, when a different problem is treated, as long as the variables values are in a range with physics meaning presented during training, the emulator will be capable to produce physically meaningful results. We discuss the salient points of designing this emulator, such as the choice of the AI model, i.e., the ANN, and the choice of the features. We show applications to different test cases, highlighting the emulator ability to generalize for problems with varying levels of complexity, and for changes in the model resolution.
Adjoint Full-Waveform Tomography around Toba Caldera: Unraveling Magma System
Authors: Liu Qiancheng , Chen Ling
Published: March 2024

The Toba Caldera, which lies in the joint area of the Eurasia, Indian-Australia, and Pacific plates, known for hosting the world's largest Pleistocene eruption 74,000 years ago, remains a focal point of geological and tectonic inquiry. Controversies persist regarding the scale of its magma system and the pathways of magma migration. The existing sparse, time-limited seismic station distribution impedes high-resolution imaging of the structures beneath the Toba Caldera and surrounding areas through traditional seismic tomography. In a pioneering endeavor, we employ adjoint full-waveform tomography to improve the resolution and reliability of structural imaging. This study represents the first application of this advanced technique to the Toba region. Our findings elucidate the debated aspects of Toba's subsurface architecture and provide valuable insights into magma storage and migration characteristics and the bonds between Toba Volcano and the surrounding ones. Beyond its geological implications, our studies on the Toba Caldera can significantly advance our understanding of the deep structure, deformation, material exchanges, and evolution history of this convergent system in the Sumatra subduction zone, offering a more comprehensive view of the tectonic and geodynamic processes shaping the region.
evapoRe: An R-based application for exploratory data analysis of evapotranspiration 
Authors: Rahmati Ziveh Akbar , Rodrigo Vargas Godoy Mijael , Thakur Vishal , R. Thomson Johanna , Hanel Martin , Markonis Yannis
Published: March 2024

Evapotranspiration (ET) is a key climate indicator closely related to the water, energy, and carbon cycles. ET datasets are produced using various methods, including satellite-based observations, hydrological models, and reanalysis. However, relying on a single ET product might lead to high uncertainty due to the spatio-temporal inhomogeneity of the dataset, highlighting the crucial need for multiple available options. evapoRe addresses the pressing issue of inhomogeneous ET datasets. This package (available at https://CRAN.R-project.org/package=evapoRe) is a pivotal tool in a landscape where diverse organizations and data providers implement varying criteria, resulting in inconsistent ET datasets. evapoRe facilitates the downloading, exploration, visualization, and analysis of ET data at monthly time step and 0.25 resolution (BESS v2.0, CAMELE, ERA5, ERA5-Land, GLEAM v3.7a, JRA-55, FLDAS, GLDAS-CLSM v2.1, GLDAS-NOAH v2.1, GLDAS-VIC v2.1, TerraClimate, MERRA-2, and ETMonitor). Further, with evapoRe, Potential ET (PET) can be calculated using temperature-based methods. In this way, evapoRe enhances ET and PET analysis by integrating diverse datasets, empowering researchers to understand water cycle change and refine models for predicting droughts and climate impacts, fundamentally advancing hydrological and climate science. 
Raindrop Collision Outcomes in Persistent Precipitation over central China during Mei-yu Front
Authors: Sun Jing , Cui Chunguang , Leng Liang
Published: March 2024

      The statistical characteristics of the raindrop size distribution (RSD) and raindrop collision outcomes over central China are investigated by using a two-dimensional video disdrometer (2DVD), micro-rain radar (MRR), and wind tunnel experiments abroad. By analyzing the evolution of each RSD in different precipitation, it is found that the RSDs have a higher mass-weighted mean diameter (Dm) and a lower normalized intercept parameter (log10Nw) for precipitation over 5 mm h-1, and the number concentration of small raindrops in convective and stratiform precipitation in this region is one order of magnitude smaller than the RSD of southern China. Moreover, the evolution of warm cloud microphysical processes based on the theoretical model, including collisional merging, spontaneous breakup, collisional breakup, bouncing, and the differences of warm cloud microphysical processes in different precipitation are also studied. The results show that the warm cloud processes in Mei-yu front precipitation are mainly dominated by raindrop merging, where the merging process includes raindrop merging and neck breakup, followed by the breakup process. The merging and neck-breakup of raindrops mainly occur in clouds with raindrop diameters between 1-2 mm, and no spontaneous breakup occurs. However, spontaneous breakup can easily occur for raindrops with diameters larger than 4 mm, and this phenomenon is conducive to the generation and development of heavy precipitation. The interesting findings of our study show the importance of large raindrops’ evolution in the development of persistent heavy rainfall, which indicates that the description of large raindrops is essential to a variety of applications such as maintaining the mechanism of extreme precipitation and forecasting.
 
Rapid change in the Arctic – North Atlantic climate: using a dynamical systems framework to explore local stability, observability and teleconnections
Authors: Wilson Chris , Oltmanns Marilena , Bacon Sheldon , Wei Xiaoyan , Shevchenko Igor
Published: March 2024

There is growing evidence for rapid Arctic climate change, including the intrusion of warm and saline Atlantic Water into the Arctic, seasonal sea ice loss and shifts in circulation pathways. These rapid Arctic changes can modulate subpolar North Atlantic processes, the connecting link between the Arctic and the North Atlantic, with potentially far-reaching and profound implications for the Northern Hemisphere weather and climate.  Across observations and model datasets, untangling this complex set of multiscale phenomena in the Arctic and their potential teleconnections is a major challenge. Yet intercomparison of different data products is necessary for understanding the mechanisms underlying the rapid Arctic changes.  In this study, we seek to understand recent changes and their underlying physical processes so that we can better observe, model and predict future climate changes. The spatiotemporal resolution of data needed to cover a sufficient range of multiscale processes tends to be high, which leads to huge volumes of data to analyse.     Fortunately, however, there have been new advances in data-driven methods. These methods abstract the problem to a dynamical systems framework of Reduced Order Modelling with the aim of discovering the key physical processes buried within the complexity.Therefore, this study simplifies the complexity of the multiscale climate variability , starting with analysis of the Arctic Subpolar Gyre sTate Estimate (ASTE), spanning 2002-2017.   We use sparse sampling methods to robustly approximate the underlying dynamics efficiently, even on huge datasets.  An advantage is that we can explore periods of rapid changes in the system as a whole, i.e. not solely via one measure or variable.   This provides a natural way to study changes to the dynamical balance across all state variables and to extract teleconnection patterns.   By taking advantage of these new, data-driven approaches, the findings of our study will inform the detection and attribution of rapid changes to the Arctic – North Atlantic climate system, especially in regions where the relevant state variables are hard to observe or estimate accurately. 
Rift evolution at the V-shaped tip of the Southwest Sub-sea basin, South China Sea: Insight into the formation of two phases of the proto-oceanic crust.
Authors: Yang Tianyi , Tang Yong , Ren Jianye , Chao Peng
Published: March 2024

This study presents evidence of the evolution of proto-oceanic crust at the South China Sea through magmatic, tectonic, and stratigraphic analysis. The evidence was obtained by interpreting seismic profiles across the V-shaped tip of the Southwest Sub-basin(SWSB) of the South China Sea (SCS). SCS is the largest marginal sea of Southeast Asia located at the intersection of the Tethys and Pacific subduction zones. The V-shaped tip of the SWSB is located at the end of the propagation of the SCS Ridge, where the lithosphere is in a critical state of breakup. This region formed an Oceanic-Continental Transition(OCT) that differs from the Atlantic rift margin and the Penrose crust. It is considered a special type of OCT with complex composition and structure and is called the proto-oceanic crust. However, the insufficient research on the OCT at the SCS hindered our comprehension of its rift margin evolution and dynamic mechanisms.
Our study establishes the tectonic-stratigraphic framework and reconstructs the rift margin evolution of the SWSB using high-quality multi-channel seismic profiles across its V-shaped tip. Based on our interpretation of magma, faults, and sequences, we present the following perspectives. The transition from continental crust to proto-oceanic crust occurred through the 'crocodile's mouth' structure, where erupted magma and bottom-invaded magma clamped the tip of the continental crust. The direction change of the seafloor spreading during the propagation process of the SCS ridge results in stratigraphic deformation and denudation, leading to the formation of the outer high and the two phases of the proto-oceanic crust. Combined with the analysis of gravimagnetic and topographic data, it is found that the two phases of proto-oceanic crust were formed before and after 20Ma when the direction of the seafloor spreading direction changed. These findings suggest that the establishment of mantle convection during the lithospheric extension and break-up of the V-shaped tip of the SWSB was jointly controlled by the evolution of the tectonic stress field and the propagation of the SCS ridge. This interaction led to the formation of the two phases of the proto-oceanic crust. This study is significant for understanding the formation and evolution of the OCT and provides insights into the interaction between magma and tectonics, as well as the dynamic mechanisms of the rift in the context of a marginal sea, which differs from the Atlantic Ocean rift.
Simultaneous Analysis of Future Canopy and Surface Urban Heat Island Effects and Their Risks Under SSPs-RCPs Scenarios
Authors: Niu Lu , Zhang Zhengfeng , Liang Yingzi
Published: March 2024

 
The Urban Heat Island (UHI) phenomenon, characterized by higher temperatures in urban areas compared to surrounding rural areas, has been documented for over two centuries. Integral to the dynamics of urban socio-ecological systems, UHIs represent a prominent environmental repercussion of anthropogenic activities. As one of the most noticeable and concerning consequences of human activities within urban socio-ecological systems, UHIs significantly impact public health and economic development. This phenomenon serves as a quasi-experimental design, offering insights into the potential impacts of urbanization. Although previous studies have utilized remote sensing and ground monitoring technologies to observe UHIs globally and in various regions, little research has focused on the future patterns and risks of UHI intensity and its changes under socio-economic and climate change scenarios. In our study, we first quantified Beijing's UHI intensity at a 1km resolution using seamless near-surface air temperature and surface temperature data, 30 m land-cover data with a fine classification system (GLC_FCS30), and topographic information, employing the simplified urban extent algorithm. We then developed a predictive model for UHI intensity using the Extreme Gradient Boosting (XGBoost) algorithm, trained with 2020 data on land use types, landscape patterns, population, and topography. Finally, using the patch-generating land use simulation (PLUS) model, we simulated future land use in Beijing from 2020 to 2100 under four SSPs-RCPs scenarios (SSP 1-RCP 2.6, SSP2-RCP 4.5, SSP3-RCP 4.5, and SSP 4-RCP 6.0), and projected the corresponding UHI intensities. We also analyzed the potential risks of UHI by considering the level of population exposure. Our results indicate that, compared to the baseline level of 2020, Beijing's overall UHI level is expected to rise under any scenario, with a more significant increase in the area affected by UHIs, especially in the urban expansion scenario of SSP 4. Due to the considerable projected decline in China's future population, the number of people affected by UHI and the overall risk of UHI in Beijing shows a decreasing trend. However, the proportion of the population affected by higher degrees of UHI is gradually increasing. Our study not only identifies the characteristics of changes in UHI intensity and risk under different future scenarios but also provides insights for future urban planning and climate-economic goal setting by identifying key areas, thereby aiming to minimize the impact of localized climate change on urban residents.
Evaluation and Projection of Diurnal Temperature Range in Maize Cultivation Areas in China Based on CMIP6 Models
Authors: Xie Wenqiang , Yan Xiaodong
Published: March 2024

The diurnal temperature range (DTR) is an important meteorological component affecting maize yield. The accuracy of climate models simulating DTR directly affects the projection of maize production. We evaluate the ability of 26 Coupled Model Intercomparison Project phase 6 (CMIP6) models to simulate DTR during 1961–2014 in maize cultivation areas with the observation (CN05.1), and project DTR under different shared socioeconomic pathway (SSP) scenarios. The root mean square error (RMSE), standard deviation (SD), Kling-Gupta efficiency (KGE) and comprehensive rating index (CRI) are used in the evaluation of the optimal model. The results show that CMIP6 models can generally reproduce the spatial distribution. The reproducibility of the annual average DTR in the maize cultivation areas is better than that in China but lower for the maize-growing season. The optimal model (EC-Earth3-Veg-LR) is used in the projection. Under the two SSPs, the DTR decreases compared with the historical period, especially in Northwest and North China. The DTR under SSP245 remains unchanged (annual) or increases slightly (growing season) during 2015–2050, while a significant decreasing trend is observed under SSP585. This highlights the importance of evaluating DTR in maize cultivation areas, which is helpful to further improve the accuracy of maize yield prediction.
Leveraging big data to unveil challenges and opportunities in truck electrification
Authors: Zhao Pei , Zhang Shaojun , Wu Xiaomeng , Wu Ye
Published: March 2024

The electrification of heavy-duty trucks is a major challenge in achieving zero-emission transportation. Despite the great ambition to promote electric trucks (ETs), their current sales are nascent now across the world compared with the soaring number of electric cars or electric buses. In this study, we gathered the year-long real-world monitoring records of 45 million trips from 60,418 electric trucks in China (over one third of 2021 global stock). Compared with similar dataset from diesel trucks (DTs), significant underusage was unveiled as a major challenge of electric truck deployment. We leveraged the big data to derive two usage metrics as feasibility indicators: “priority group ratio” denoting the ratio of vehicles feasible for one-on-one replacement, and “replacement rate” denoting the average number of ETs needed to replace one DT after matching fleet-level transport demand. We observed that for current electric delivery trucks and semi-trailers, approximately 23% and 30% of vehicles in the fleets could achieve one-on-one replacement with diesel counterparts, while on average 3.8 and 3.6 electric trucks are required to match the transportation demand served by one diesel trucks separately.
Integrating usage patterns with life-cycle modeling, we evaluated actual individual- and fleet-level cost and decarbonization effects of truck electrification by category. The results showed that although current ETs can achieve considerable well-to-wheels (WTW) CO2 emission reductions for most fleets in most of the grid regions, carbon emissions associated with battery supply chains and lower vehicle mileage lead to a mixed profile in life-cycle decarbonization effects for ETs compared with DTs. In the near future (e.g., 2030), enhancements in usage pattern, vehicle technology and charging infrastructure can effectively improve electrification feasibility, yielding cost and decarbonization benefits. For example, battery energy density increase and battery swapping can make one-on-one electrification feasible for over 85% diesel semi-trailers. Additionally, with cleaner electricity electric semi-trailers can almost achieve cost parity and decarbonization benefits in the coming decade. Our analysis highlights the importance of leveraging big data to inform the decision-making process in the electrification transition. 
Ecological engineering and circular solutions: constructed wetland case studies for wastewater treatment and reuse
Authors: Stefanakis Alexandros
Published: March 2024

Wetland systems are known for their capacity to transform and/or remove various pollutants (organics, nutrients, trace elements, etc.) via various physical, biological, and chemical processes. As wetlands provide a wide range of economic and ecological benefits, they stimulated the development of constructed wetlands (CW) to exploit this water purification capacity for wastewater treatment purposes under controlled conditions. Constructed wetland ecosystems have been used for the treatment of domestic, municipal and industrial wastewater effluents for many years.
CWs are nature-based solutions designed in such a way to mimic and enhance the functions of natural wetlands, but further to provide an added value to the known values and functions of natural wetlands, and a wider range of ecosystem services that include flood and stormwater control, habitat creation, reduced carbon footprint and biodiversity restoration. This is why CWs represent a key development in the field of ecological engineering.
The modern view of ecological engineering, as outlined by the International Ecological Engineering Society in their Manifesto, dictates that a circular approach should be adopted across the various engineering solutions, in this case in the water and wastewater sector. Adopting green technologies such as CW is the first crucial step towards circularity and overall reduced carbon and material footprint, which should further be integrated with interventions such as treated effluent valorization for irrigation of crops and plant biomass conversion to valuable organic materials.
This study will present different case studies of CW from around the world where this modern approach has already been applied in the field. Focus is given on different wastewater effluents to demonstrate the treatment capacity of this green technology, as well as on different facility scales (small and large) to showcase the feasibility of building such systems even at the largest scale and the large potential to upscale CW technology. The following CW case studies will be presented:
 

Country

Flow rate (m³/day)

CW area (m²)

Water source

Circularity aspect

Czech Republic

16.5

319

Mixed wastewater from a hotel, a restaurant and a brewery

Effluent reuse for irrigation of crops

Iran

10

250

Glass manufacturing industry

Effluent recycled in the manufacturing process

Saudi Arabia

16,000

135,000

Municipal wastewater

Effluent reused for landscape irrigation

Mexico

8,640

34,000

Municipal WWTP effuent

Effluent reused for potable water production

Oman

175,000

4.9 million

Oily produced water

Effluent reused for irrigation of commercial crops, Biomass used for compost and energy production

 
Keywords: constructed wetlands; wastewater treatment; ecological engineering; nature-based solutions; circularity; water reuse; organic waste; systems thinking; resilience; ecosystem services
Life in thermodynamic equilibrium: how does redox conditions shape the subsurface biosphere?
Authors: Milesi Vincent
Published: March 2024

Determining the limits of subsurface microbial life and its response to climatic and anthropic forcing requires understanding its link with environmental conditions. Thermodynamics has been used for decades to related mineral and fluid composition to the physicochemical variables of the environment; however, application to the biosphere has been scarce. Here, using data from shotgun metagenomic sequencing, I developed a thermodynamic model of the chemical activity of in-silico proteins to investigate the relationship between the chemical and taxonomic composition of microbial communities and subsurface redox potential. The model relies on metagenomic data from peat soils characterized by sharp redox gradients from the surface to a few meters depth.
The average oxidation state of carbon and the redox potential of maximum relative activities of in-silico proteins decrease with depth. The protein-informed Eh values are consistent with the successive occurrence of anaerobic metabolisms. The evolution of taxonomic abundance with depth encodes the chemical variability of in-silico proteins, which allows linking quantitatively taxonomic evolution and redox potential.  
These results show that a metastable state of thermodynamic equilibrium is reached between the environmental redox conditions and the chemical composition of community-level proteomes which encodes the taxonomic abundance. This is a paradigm shift in which microbial life is not entirely out of equilibrium. Instead, the minimization of chemical disequilibrium of community-level proteomes relative to the prevailing environmental conditions is an evolutionary process, resulting either from phylogenetic or ecological adaptation. By providing a mechanistic understanding of the coevolution of the biosphere and geosphere, this work offers prospects for the predictive modeling of microbial community composition and physicochemical conditions in various environments.
 
The Largely Linear Response of Earth’s Ice Volume to Orbital Forcing
Authors: Wheen Liam , Gernon Thomas , Hall Cameron , Wright Jerry , Benjamin Oscar
Published: March 2024

 We investigate the effect of Earth’s orbitally governed incoming solar radiation on global ice volume over the past 800,000 years. It is well established that the orbital parameters play some role in the pacing of the glacial-interglacial cycles. However, due to limited data and enigmatic dynamics, the mechanics that could facilitate this relationship remain unresolved. We therefore consider a simple linear model of ice volume that imposes minimal assumptions about its dynamics. This model adequately reproduces the ice volume data for most of the 800,000 year period, with the exception of Marine Isotope Stage 11. This suggests that, aside from a few extrema, the ice volume dynamics primarily result from an approximately linear response to orbital forcing. We substantiate this finding by addressing some of the key criticisms of the orbitally forced hypothesis. In particular, we show that eccentricity can significantly vary the ocean temperature without the need for amplification on Earth. We also present a feasible mechanism to explain the absence of eccentricity’s 400,000 year period in the ice volume data. This requires part of the forcing from eccentricity to be lagged via a slow-reacting mechanism, resulting in a signal that closer approximates the change in eccentricity. A physical interpretation of our model is proposed, using bulk ocean and surface temperatures as intermediate mechanisms through which the orbital parameters affect ice volume. These show reasonable alignment with their relevant proxy data, though we acknowledge that these variables likely represent a combination of mechanisms.
Invasion of the Nightcrawler: Embodied Explorations of Subterranean Spaces
Authors: Ruiz Lauren
Published: March 2024

Invaders can be quiet, unmeasured and unassuming; slowly transforming a landscape through the spread of invasive disease, religious beliefs, or beneath the grass, in the dark. One of the most commonly known earthworms in North America, the nightcrawler, arrived with the first wave of European settlers burrowed inside potted plants and sacks of spoiled crops. These annelids, traveling alongside their human counterparts as resources of free labor, now play a vital role in the complex systems of soil health and water treatment as humans confront the effects of pollution and the resulting toxicants that cycle through soil, water, and animal bodies. As a method for understanding the complex relationships between humans and earthworms, I have conducted research-based multimedia projects informed by a partnership with Cornell Cooperative Suffolk County, an extension of Cornell University, to discover the connections between animal labor, eco-colonialism, and how religious systems influence relationships to the underground. This presentation will illustrate how both human and nonhuman bodies are influenced by religious authoritative systems regarding their relationships to labor, nature, and burial, leading to greater conflicts around ideas of ownership of, and belonging to, a place. By contextualizing my projects amidst ecocritical and postnaturalist theory I will explore how the visual and sonic expressions of the Umwelt of earthworms can create a sensorial bridge between the human and annelid body and the relationship to environmental conditions. 