Données nouvelles sur les formations superficielles de la plaine de la Scarpe et de ses bordures (Nord de la France)

The synthesis of about 400 borings in the Plain of the Scarpe, between Douai to and St Amand-les-Eaux and on its boundaries, shows evidence of an important complexity of the superficial formations, one meter to seven meters thick. 19 sedimentary sequences are differentiated and show a stratigraphie continuity between the slope deposits and those of the plain, according to a lateral variation of their facies, and in an eolian environment. The obvious absence of Eemien soil, the evidences locally kept of the Kesselt level and of the Warneton soil, allows to think that the superficial formations (except the holocene deposit), have been deposited during the Weichselian period.L'interprétation d'environ 400 sondages, réalisés dans la Plaine de la Scarpe et sur ses bordures, a permis de caractériser 19 séquences sédimentaires qui rendent compte de la grande complexité des formations superficielles. Les corrélations établies entre la sédimentation des versants et de la plaine, plaident en faveur d'une continuité stratigraphique selon une variation latérale des faciès, et dans un environnement où l'agent éolien a joué un rôle prépondérant. L'absence manifeste de sol eemien, la présence locale du niveau de Kesselt et du complexe de Warneton, permettent de considérer que les formations superficielles, hormis les quelques témoins holocénes présents dans l'axe de la dépression, se sont mises en place durant le Weichselien.Fourrier Hervé. Données nouvelles sur les formations superficielles de la plaine de la Scarpe et de ses bordures (Nord de la France). In: Hommes et Terres du Nord, 1992/4. pp. 206-216

Integration of in situ and satellite multi-platform data (estimation of carbon flux for trop. Atlantic)

This report presents the results of task 7.3 on “Quantification of improvements in carbon flux data for the tropical Atlantic based on the multi-platform and neural network approach”. To better constrain changes in the ocean’s capture and sequestration of CO2 emitted by human activities, in situ measurements are needed. Tropical regions are considered to be mostly sources of CO2 to the atmosphere due to specific circulation features, with large interannual variability mainly controlled by physical drivers (Padin et al., 2010). The tropical Atlantic is the second largest source, after the tropical Pacific, of CO2 to the atmosphere (Landschützer et al., 2014). However, it is not a homogeneous zone, as it is affected by many physical and biogeochemical processes that vary on many time scales and affect surrounding areas (Foltz et al., 2019). The Tropical Atlantic Observing System (TAOS) has progressed substantially over the past two decades. Still, many challenges and uncertainties remain to require further studies into the area’s role in terms of carbon fluxes (Foltz et al., 2019). Monitoring and sustained observations of surface oceanic CO2 are critical for understanding the fate of CO2 as it penetrates the ocean and during its sequestration at depth. This deliverable relies on different observing platforms deployed specifically as part of the EuroSea project (a Saildrone, and 5 pH-equipped BGC-Argo floats) as well as on the platforms as part of the TAOS (CO2-equipped moorings, cruises, models, and data products). It also builds on the work done in D7.1 and D7.2 on the deployment and quality control of pH-equipped BGC-Argo floats and Saildrone data. Indeed, high-quality homogeneously calibrated carbonate variable measurements are mandatory to be able to compute air-sea CO2 fluxes at a basin scale from multiple observing platforms

Development of BGCArgo data quality validation based on an integrative multiplatform approach

This report presents the results of Task 7.3 on “Development of BGC-Argo data quality validation based on an integrative multiplatform approach”. Observing changes in ocean conditions on the spatiotemporal scales necessary to constrain carbon uptake is a challenge. Defined as an Essential Ocean Variable (EOV) by the Global Ocean Observing System (GOOS, e.g., Tanhua et al., 2019), pH is relevant to assess numerous crucial questions regarding the oceanic evolution in response to the current global changes. However, the large spatiotemporal variability of this carbonate system parameter requires sustained observations to decipher trends and punctual events. Within this scope, numerous pH sensors suitable for deployments both on autonomous observing tools and fixed stations have been developed. Nevertheless, as interpreting changes relies on accurate data, and because offsets or drifts in pH data might appear in response to changes in the sensor k0 constant, a consistent and rigorous correction procedure to quality-control and process the data has been implemented. This report presents the application of this method to pH data acquired by BGC-Argo floats launched in the Tropical Atlantic area

A Regional Neural Network Approach to Estimate Water-Column Nutrient Concentrations and Carbonate System Variables in the Mediterranean Sea: CANYON-MED

International audienceA regional neural network-based method, "CANYON-MED" is developed to estimate nutrients and carbonate system variables specifically in the Mediterranean Sea over the water column from pressure, temperature, salinity, and oxygen together with geolocation and date of sampling. Six neural network ensembles were developed, one for each variable (i.e., three macronutrients: nitrates (NO − 3), phosphates (PO 3− 4) and silicates (SiOH 4), and three carbonate system variables: pH on the total scale (pH T), total alkalinity (A T), and dissolved inorganic carbon or total carbon (C T), trained using a specific quality-controlled dataset of reference "bottle" data in the Mediterranean Sea. This dataset is representative of the peculiar conditions of this semi-enclosed sea, as opposed to the global ocean. For each variable, the neural networks were trained on 80% of the data chosen randomly and validated using the remaining 20%. CANYON-MED retrieved the variables with good accuracies (Root Mean Squared Error): 0.73 µmol.kg −1 for NO − 3 , 0.045 µmol.kg −1 for PO 3− 4 and 0.70 µmol.kg −1 for Si(OH) 4 , 0.016 units for pH T , 11 µmol.kg −1 for A T and 10 µmol.kg −1 for C T. A second validation on the ANTARES independent time series confirmed the method's applicability in the Mediterranean Sea. After comparison to other existing methods to estimate nutrients and carbonate system variables, CANYON-MED stood out as the most robust, using the aforementioned inputs. The application of CANYON-MED on the Mediterranean Sea data from autonomous observing systems (integrated network of Biogeochemical-Argo floats, Eulerian moorings and ocean gliders measuring hydrological properties together with oxygen concentration) could have a wide range of applications. These include data quality control or filling gaps in time series, as well as biogeochemical data assimilation and/or the initialization and validation of regional biogeochemical models still lacking crucial reference data. Matlab and R code are available at https:// github.com/MarineFou/CANYON-MED/

A neural network approach to estimate water-column nutrient concentrations and carbonate system parameters in the Mediterranean Sea: CANYON-MED

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Contamination of urban soils in an area of Northern France polluted by dust emissions of two smelters

Water Air Soil Poll 252WD Times Cited:37 Cited References Count:36International audienceThe contamination of 27 urban topsoils has been assessed around two lead and zinc smelters (Metaleurop Nord and Umicore) in the North of France. Eighteen trace elements have been analysed (Ag, As, Bi, Cd, Co, Cr, Cu, Hg, In, Ni, Pb, Sb, Se, Sn, Tl, Th, U and Zn). The investigation included the study of the vertical distribution of Cd, Pb and Zn as indicators of pollution. It was shown that Cd, In, Pb, Sb and Zn were major pollutants followed in lesser quantities by Ag, Bi, Cu and Hg. In addition, As, Ni, Se, Sn and Tl were present at levels slightly higher than regional agricultural values. The other elements (Co, Cr, Th and U) were at endogenous levels. The observations have highlighted the strong heterogeneity of the physico-chemical parameters of urban soils and the existence of heavy contamination of the under layers by Cd, Pb and Zn. A potential transfer of metals from the topsoil to the deeper layers and especially Cd and Zn, is not excluded. Indeed the soil rework is not the only factor explaining contamination level of the deeper layers of the studied soils. The comparison of the studied element concentrations in urban soils with nearby local agricultural values shows that the dust emission originating from the Metaleurop and Umicore smelters were not the only source of contamination. Thus a large contamination of the studied urban soils by Sb and In could be explained by domestic combustion of coal for heating

A neural network approach to estimate water-column nutrient concentrations and carbonate system variables in the Mediterranean Sea: CANYON-MED

International audienc