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We combine consistently dated benthic carbon isotopic records distributed over the entire Atlantic Ocean with numerical simulations performed by a glacial configuration of the Norwegian Earth System Model with active ocean biogeochemistry, in order to interpret the observed Cibicides δ13C changes at the stadial-interstadial transition corresponding to the end of Heinrich Stadial 4 (HS4) in terms of ocean circulation and remineralization changes. We show that the marked increase in Cibicides δ13C observed at the end of HS4 between ~2000 and 4200 m in the Atlantic can be explained by changes in nutrient concentrations as simulated by the model in response to the halting of freshwater input in the high latitude glacial North Atlantic. Our model results show that this Cibicides δ13C signal is associated with changes in the ratio of southern-sourced (SSW) versus northern-sourced (NSW) water masses at the core sites, whereby SSW is replaced by NSW as a consequence of the resumption of deep water formation in the northern North Atlantic and Nordic Seas after the freshwater input is halted. Our results further suggest that the contribution of ocean circulation changes to this signal increases from ~40 % at 2000 m to ~80 % at 4000 m. Below ~4200 m, the model shows little ocean circulation change but an increase in remineralization across the transition marking the end of HS4. The simulated lower remineralization during stadials than interstadials is particularly pronounced in deep subantarctic sites, in agreement with the decrease in the export production of carbon to the deep Southern Ocean during stadials found in previous studies.

The effects of antifreeze proteins (AFPs) on the freezing temperatures of water is well studiedand known today. Studies of the affects of antifreeze proteins on glass transition and melting tem-peratures have been conducted on samples containing relatively high concentrations of glyceroland water. In this paper we conduct experiments with antifreeze proteins in water-dominatedglycerol water mixtures to determine how AFPs affect the glass transition and melting temper-atures of these samples. We present theory behind the various interactions that occur betweencomponents of the various mixtures studied and provide mathematical background and proofsto verify our methods. We discuss the hardware and software setups, experimental procedure,preparation of samples and analysis of the gathered data. The experimental results obtained fromthe raw data is presented as well as information on how the data was interpreted. Our analysisof a 23% glycerol water mixture with varying concentrations of teleost fish type III anti-freezeproteins suggest that there is a lowering effect to the glass transition temperature. Uncertainties,arbitrary choices and areas of future research are established for suggestions of the continuedresearch of these phenomena.i

n°90

This study presents simulations of Greenland surface melt for the Eemian interglacial period (∼130 000 to 115 000 years ago) derived from regional climate simulations with a coupled surface energy balance model. Surface melt is of high relevance due to its potential effect on ice core observations, e.g., lowering the preserved total air content (TAC) used to infer past surface elevation. An investigation of surface melt is particularly interesting for warm periods with high surface melt, such as the Eemian interglacial period. Furthermore, Eemian ice is the deepest and most compressed ice preserved on Greenland, resulting in our inability to identify melt layers visually. Therefore, simulating Eemian melt rates and associated melt layers is beneficial to improve the reconstruction of past surface elevation. Estimated TAC, based on simulated melt during the Eemian, could explain the lower TAC observations. The simulations show Eemian surface melt at all deep Greenland ice core locations and an average of up to ∼30 melt days per year at Dye-3, corresponding to more than 600 mm water equivalent (w.e.) of annual melt. For higher ice sheet locations, between 60 and 150 mmw.e.yr-1 on average are simulated. At the summit of Greenland, this yields a refreezing ratio of more than 25 % of the annual accumulation. As a consequence, high melt rates during warm periods should be considered when interpreting Greenland TAC fluctuations as surface elevation changes. In addition to estimating the influence of melt on past TAC in ice cores, the simulated surface melt could potentially be used to identify coring locations where Greenland ice is best preserved.

Here we present a merged and calibrated dataset of temperature, practical salinity and dissolved organic matter (DOM) fluorescence obtained from several Ice Tethered Profilers (ITPs) deployed across the central Arctic (2011-2016). The data offer a unique spatial coverage of the distribution of DOM in the surface 800 m below Arctic sea ice. A total of 5044 profiles are gathered. The ITP data are level 3 data products pressure-bin-averaged at 1-db vertical resolution with depth down to either 200 or approximately 750 m. Data (max 800m depth) from CTD casts made during two oceanographic cruises are also included. These were used as part of the calibration and validation of the ITP calibration routines. The cruises were PS94 (ARK-XXIX/3) with POLARSTERN in 2015 and NAACOS with DANA in 2012. The presented DOM fluorescence data are smoothed, corrected for instrument drift and calibrated to provide intercomparable data across the sensors. Fluorescence is reported in Raman Units (nm-1), and comparable to laboratory measurements conducted according to current community recommendations.

Particle size distribution data was collected during multiple cruises globally with several regularly intercalibrated Underwater Vision Profilers, Version 5 (UVP5; Picheral et al 2010). During the respective cruises, the UVP5 was mounted on the CTD-Rosette or as a standalone instrument and deployed in vertical mode. The UVP5 takes pictures of an illuminated watervolume of about 1 Liter every few milliseconds. Imaged items are counted, their size measured and abundance and biovolume of the particles is calculated. For different size bins, this information is summarized in the columns "Particle concentration" and "Particle biovolume". For further details please refer to Kiko et al. (in prep.) "A global marine particle size distribution dataset obtained with the Underwater Vision Profiler 5".

Les rivières sont censées être les principales voies de transfert des plastiques des terres vers l'océan (Lebreton et al., 2017 ; Schmidt et al., 2017). Cependant, il existe encore un manque important de connaissances sur la façon dont les déchets fluviaux, y compris les macroplastiques, sont transférés vers l'Océan. Les mesures quantitatives des émissions de macroplastiques dans les rivières suggèrent même qu'une fraction de l'ordre de 0,001 à 3% des déchets plastiques mal gérés (MPW) générés dans un bassin fluvial atteignent finalement la mer (Emmerik et al., 2019 ; Schöneich-Argent et al., 2020 ; Tramoy et al. 2021). Au lieu de cela, les macroplastiques peuvent rester dans le bassin versant et sur les côtes en raison de la dynamique complexe du transport qui retarde le transfert des déchets mal gérés des terres vers l'océan (Olivelli et al., 2020 ; Weideman et al., 2020). Afin de mieux comprendre ces dynamiques, le laboratoire Eau et Environnement et le Laboratoire Eau Environnement et Systèmes Urbains étudient la dynamique des déchets en Seine et en Loire. Pour les macrodéchets plastiques, l'ensemble des travaux engagés sur la Seine permettent de dresser une première esquisse des flux de déchets plastiques transitant en Seine, captés par les dispositifs urbains et/ou collectés par des opérations de nettoyage. Selon nos estimations, entre 100 et 200 tonnes de déchets plastiques transiteraient chaque année en Seine. A l'échelle de l'agglomération parisienne, et bien que ces valeurs s'accompagnent de fortes incertitudes, les eaux pluviales n'apporteraient qu'une part mineure de ces flux, i.e., entre 8 et 33 tonnes par an. L'étude de la dynamique des débris plastiques montre que le transfert des plastiques est loin d'être linéaire et qu'il est soumis à de nombreux phénomènes physiques à de nombreuses échelles temporelles, i.e. d'échelles courtes allant de quelques heures à quelques jours (marées hautes / basses) à des échelles beaucoup plus longues allant de plusieurs semaines (marées de printemps / creuses et marées les plus hautes) à quelques années (crues). La conséquence de ces interactions est que le transfert des débris est chaotique et qu'une part importante de ces flux peut venir s'échouer sur les berges.