AbstractAmong the photosynthetic powerhouses of aquatic ecosystems, microalgae are now the most promising source of sustainable and bioactive compounds with massive potential in the functional food category. Unicellular cell plants differing the synthesis of various substances, including proteins, lipids, carbohydrates and pigmented substances, which are important to their living and contribute to the workout of human health. Carotenoids and polyunsaturated fatty acids (PUFAs) present in a wealth of compounds have been the most attractive compounds due to their antioxidative and anti-inflammatory properties, which may be beneficial in alleviating oxidative stress and chronic inflammation. Spirulina and chlorella are two of the most consumable microalgae. They have been developed commercially as nutraceuticals because they offer a useful nutrient profile that includes essential amino acids, vitamins, and minerals needed to maintain human health. Because of its diverse bioactivity, microalgae can be used to create functional foods that target particular health issues like metabolic disorders and cardiovascular diseases. Because microalgae can be grown on non-arable land with little freshwater requirements, they do not compete with traditional agriculture, which further justifies their integration into the food industry. Furthermore, the heterotrophic cultivation of microalgae techniques that depend on sources of organic carbon for growth offers a chance to raise the yield of bioactive compounds and possibly lower production costs. This strategy aligns with the biorefinery concept, which maximizes resource utilization and economic viability by using microalgae as a biotechnological platform to produce high-value nutraceuticals and biofuels simultaneously. Only a few microalgal compounds have been successfully commercialized, and most studies on them are still preclinical. However, continued research and technological developments in the processing and cultivation of microalgae are opening the door to a broader range of uses in functional foods.

A document by Meiyun Lin. Click on the document to view its contents.

High-relief glacial valleys shape the modern topography of the Southern Patagonian Andes, but their formation remains poorly understood. Two Miocene plutonic complexes in the Andean retroarc, the Fitz Roy (49°S) and Torres del Paine (51°S) massifs, were emplaced between 16.9–16.4 Ma and 12.6–12.4 Ma, respectively. Subduction of oceanic ridge segments initiated ca. 16 Ma at 54°S, leading to northward opening of a slab window with associated mantle upwelling. The onset of major glaciations caused drastic topographic changes since ca. 7 Ma. To constrain the respective contributions of tectonic-mantle dynamics and fluvio-glacial erosion to rock exhumation and landscape evolution, we perform inverse thermal modeling of a new dataset of zircon and apatite (U-Th)/He from the two massifs, complemented by apatite 4He/3He data for Torres del Paine. Our results show rapid rock exhumation recorded only in the Fitz Roy massif between 10 and 8 Ma, which we ascribe to local mantle upwelling forcing surface uplift and intensified erosion around 49°S. Both massifs record a pulse of rock exhumation between 7 and 4 Ma, which we interpret as enhanced erosion during the beginning of Patagonian glaciations. After a period of erosional and tectonic quiescence in the Pliocene, increased rock exhumation since 3-2 Ma is interpreted as the result of alpine glacial valley carving promoted by reinforced glacial-interglacial cycles. This study highlights that glacial erosion was the main driver to rock exhumation in the Patagonian retroarc since 7 Ma, but that mantle upwelling might be a driving force to rock exhumation as well.

Pillar et al.

This study tackles the limitations of traditional distance metrics in machine learning, particularly their inadequacy in managing missing data and varying feature importance. We introduce a novel custom distance metric that offers a more nuanced and robust measure of similarity, addressing the complexities and imperfections of real-world data. Our extensive evaluation of the CustomKNN algorithm, leveraging this custom distance metric, reveals exceptional performance and robustness across diverse datasets, consistently outperforming traditional metrics in various classification tasks. The custom distance metric shows superior robustness to missing data and scalability, despite its higher computational complexity and memory requirements. Our findings highlight the versatility and effectiveness of the CustomKNN algorithm, establishing it as a formidable option for classification tasks. This research advances the development of more adaptable and context-aware distance metrics, significantly enhancing the accuracy and reliability of machine learning models in practical applications.

The last glacial cycle provides the opportunity to investigate large changes in the Atlantic Meridional Overturning Circulation (AMOC) beyond the small fluctuations evidenced from modern measurements. Paleotemperature records from Greenland and the North Atlantic show an abrupt variability, called Dansgaard–Oeschger (DO) events, which is associated with abrupt changes of the AMOC. These DO events also have Southern Hemisphere counterparts via the thermal bipolar seesaw, a concept describing the meridional heat transport leading to asynchronous temperature changes between both hemispheres. However, temperature records from the North Atlantic show more pronounced DO cooling events during massive releases of icebergs known as Heinrich (H) events, contrary to ice-core–based temperature records from Greenland. Here, we present two high-resolution temperature records from the southern Iberian Margin, which are derived from two independent paleotemperature proxies (RI-OH′ and UK′37). Both temperature records from the southern Iberian Margin faithfully reflect the contrasting DO cooling amplitudes with and without H events. We show that temperature records from the southern Iberian Margin better support the classical thermal bipolar seesaw model than do ice-core–based temperature records from Greenland. We also introduce an extended thermal bipolar seesaw model that considers the contrasting DO cooling amplitudes with and without H events in the southern Iberian Margin, and a Bipolar Seesaw Index to discriminate DO cooling events with and without H events. Our data-model comparison emphasizes the role of the thermal bipolar seesaw in the abrupt temperature variability of both hemispheres with a clear enhancement during DO cooling events with H events, implying a relationship that is more complex than a simple flip-flop between two climate states linked to a tipping point threshold.

A document by John Robert Potter. Click on the document to view its contents.

Many valuable economic benefits from nature have traditionally been overlooked in both national accounts and government policy. To remedy this, countries are adopting the new United Nations System of Environmental-Economic Accounting framework for valuing ecosystem services, but inclusion of key hydrological services has so far been limited. Here, we develop novel ecosystem service flow accounts linked to a natural capital assessment in Colombia's Sinú Basin to value ecosystems' contributions to water and energy security. Using integrated biophysical and economic models parameterized with local data, we find ecosystems deliver sediment retention benefits to the energy and water sectors equivalent to 1.7% of the region's GDP. A planned expansion of the region's aqueduct system would further increase these values by 12%. Our findings are informing national and regional development planning and policy within Colombia and provide lessons for the many other countries adopting natural capital accounting to support their sustainable development goals.

A document by Kate Rose. Click on the document to view its contents.

This research unpacks some of the complexities and interactions among multiple drivers of climate change by examining the role of radionuclides in the Arctic, where abnormally high levels correlate with the extremely rapid warming taking place (over three times the global average, i.e., Arctic amplification).

A document by Aparna Sharma. Click on the document to view its contents.

Bio-methanation offers a safe, effective, and efficient avenue for the environmentally sound disposal of urban organic waste, while concurrently facilitating the recuperation of valuable by-products. A well-maintained Bio-methanation facility with organic waste as input feed can not only help decrease the waste disposal costs, reduce the volume (and mass) of waste that needs to be processed, and create multilateral employment opportunities but also fosters the production of clean electricity and Compressed Biogas (CBG). Various programs and schemes initiated by different governments in India aim to address the imperatives of waste management and escalating energy demands. These strategic initiatives actively encourage the establishment of Bio-methanation plants (BMPs) by local communities, regional authorities, and private enterprises. Despite the recognition of its potential, the actual number of successfully operational BMPs across India remains relatively low. This dearth of success in operating and managing existing Bio-methanation facilities may emerge as a critical restraint for prospective stakeholders (owners, builders, and operators) when contemplating new plant installations. Consequently, comprehensive research is indispensable to advance energy recovery from waste and to establish standardized design parameters for BMPs. The present investigation intends to appraise the current status of select BMPs in India, conscientiously collating and presenting information pertaining to critical parameters such as size/design capacity, type of reactor, no. of stages employed, etc. Additionally, the study identifies the challenges encountered by plant operators and technology providers in their pursuit of effective plant operation, thus, presenting valuable insights for further development and optimization of the existing technologies. B02-07, Article available at AGU23 Website

A document by Yan Yang. Click on the document to view its contents.

This paper proposes an ocean-only dynamical framework to mitigate the influence presentday biases of Earth System Models (ESMs) on future regional ocean physical and biogeochemical projections. Initially, a control experiment is conducted using fluxes derived from an atmospheric reanalysis, excluding climate change signals. Subsequently, a climate change simulation is performed by adding historical and future fluxes perturbations from a selected ESM to these background realistic fluxes. Since part of the ESM surface heat fluxes perturbation is a direct feedback to the sea surface temperature (SST) warming, these fluxes perturbations are split into SST-dependent and independent components. The climate change simulation is forced by the independent component, while the SST-dependent component is modeled online as an SST relaxation to the control experiment, accounting for Newtonian cooling and long-wave radiative feedback. This approach demonstrates that ESMs present-day biases can heavily impact the reliability of regional physical and biogeochemical ocean projections. For instance, the strong cold-tongue bias simulated by the IPSL-CM6A-LR model causes greater warming and chlorophyll decrease in the western than in the eastern equatorial Pacific, while our bias-corrected simulation shows opposite projected patterns. Sensitivity experiments applying heat, freshwater and momentum fluxes perturbations separately further indicate that thermodynamical and dynamical processes equally contribute to this warming pattern, highlighting the strong role of the Bjerknes feedback. This cost-effective method can be applied to any ESMs oceanic component to produce more reliable regional oceanic projections and understand the mechanisms driving the projected patterns.

This study focuses on nowcasting cloud-to-ground lightning in the Amazon region, utilizing the Green Ocean Amazon (GoAmazon) campaign data. Lightning strikes can have severe socioeconomic consequences, making accurate forecasting systems crucial for risk assessment and decision making. Deep learning models have shown promising results in severe storm forecasting and are widely used in various meteorological applications. Overcoming the challenges posed by the chaotic and highly variable nature of lightning events, different deep learning models were explored for prediction. The performance of the models was compared on the basis of the architecture and data configurations, and the evaluation methods considered spatial variability and sensor accuracy. The study sought to develop a very short-term (up to 12 minutes) forecasting system for cloud-to-ground lightning in the Amazon Basin, taking into account the distinctive characteristics of the event and the uncertainties associated with predicting lightning strikes. Considering various probability thresholds for the occurrence of lightning strikes, the best thresholds were determined for two artificial neural networks, U-Net and ConvLSTM. The validation methods used for model evaluation were also important in this study, given that these methods make validations more assertive due to the consideration of characteristics associated with lightning (e.g., spatial variability) and sensors (e.g., spatial accuracy). Both models tracked lightning effectively, with the best model based on U-Net achieving 0.642 (POD) and 0.353 (FAR), and the best model based on ConvLSTM reaching 0.689 (POD) and 0.307 (FAR). Also, the smallest spatial error (e.g. < 5 km) based on the overlap analysis was also observed for these thresholds. Therefore, it is concluded that the models tested are capable of predicting lighting in the short term in the Amazon region.

U is a naturally occurring heavy metal that exists primarily in granites, granodiorites, and their sedimentary derivatives such as sandstones. In reducing environments U is relatively immobile and can be deposited as its tetravalent form U(IV) in minerals such as uranite (UO2). Conversely, oxidizing environments may result in oxidation and subsequent dissolution of U(VI), which is ≥ 10,000 times more soluble. Once dissolved into groundwater, the now mobile U can enter drinking wells and result in elevated concentrations in residential drinking water.Jacobsville Sandstone is a red and mottled sandstone which lines the northern shore of Michigan’s Upper Peninsula deposited as basin fill during the 1.1 Ga Midcontinent Rift under reducing conditions which aid in the deposition of U(IV) in minerals. Previous studies have shown an elevated level of naturally occurring U and As in drinking water as high as 415 µgL-1 and 13 µgL-1 respectively, harvested from aquifers where Jacobsville Sandstone constitutes the underlying bedrock. The same studies indicate correlation between well bottom height and concentration of U suggesting a heterogenous distribution. Rock samples were obtained from three different locations in the region where Jacobsville Sandstone is exposed. By performing large area scans with µXRF we were able to determine points of interest which were further investigated with SEM-EDS where smaller spot sizes allow for better resolving power of fine details in matrix particles and cement between sandstone grains. Utilizing both methods of analysis allowed us to investigate mineralogic and elemental composition of samples revealing V, Ce, Nd, and La co-existing with U in matrix particles bound to cement between silicate grains along with As bearing minerals.

A document by Jerome Pinti. Click on the document to view its contents.

Zircon is a key mineral in geochronology because of its chemical and physical durability and tendency to incorporate radioactive trace elements such as U and Th. Quantifying the partitioning of the actinide elements is critical to constrain initial non-secular equilibrium amounts of 230 Th in zircon. An excess or deficit of 206 Pb will be produced from such an initial excess/deficit of 230 Th from the secular equilibrium condition, which influences the calculated 206 Pb/ 238 U age (Schärer, 1984; Mattinson, 1973). However, there is no standard way to calculate Th/U partitioning ratios when applying age corrections to young igneous systems, making uncertainties hard to estimate. To address this problem, zircon was synthesized in oneatmosphere experiments using basaltic andesite, andesite, and rhyolite starting materials, doped with Zr, U, and Th. Different experimental temperatures and oxygen fugacity conditions (ΔQFM-4 to ΔQFM+4) were explored to examine non-equilibrium U and Th partitioning. U and Th concentrations in zircon crystals and coexisting melt were analyzed through EPMA. In our study, we specifically quantify the effects of sector zoning, fractional crystallization, oxygen fugacity, melt composition, and temperature on actinide element partitioning. By combing experimental and natural zircon data, we find temperature has the primary control on the partitioning of U and Th in the zircon and there is a negative relationship between partition coefficient of actinide elements and zircon crystallization temperatures. The calibrated equation can be directly applied to the 230 Th correction for an improvement in the accuracy of Thcorrected 206 Pb/ 238 U dates using estimates of the zircon crystallization temperatures.