Contrasting platinum trajectories in three major French rivers using dated sediment cores (1910-2021): From geochemical baseline to emerging source signals.

Platinum (Pt) is a Technology Critical Element (TCE) which, since the 1990s, has been mainly used in the industry in catalytic converters for automobile emission control. Previous studies have shown Pt contamination of road-side sediments and surface sediments in urban rivers and lakes but few of them have addressed temporal variations. The present work presents historical Pt concentration trends in 137Cs-dated sediment cores from floodplains or secondary channels at the outlets of three major French watersheds (Loire, Rhone, and Seine Rivers) covering the past ∼110 years, i.e., from the 1910s to 2021. Platinum baseline levels in the sediment were estimated for the Loire River (0.76 ± 0.22 µg kg-1 for the period ∼1910-∼1955) and the Rhone River (1.64 ± 0.41 µg kg-1), and historical Pt variations seem to reflect variations in hydrodynamics and grain size composition. Since the early 2000s, Pt concentrations in the Loire and the Rhone River sediments tend to increase (>2.5 µg kg-1) and were attributed to the use of car catalytic converters, an emerging technology since the 1990s using >50 % of European Pt demand. High and variable historical Pt concentrations (up to 14.6 µg kg-1) in the Seine River sediments may reflect legacy Pt sources due to former anthropogenic activities in this watershed, such as the use of Pt-based catalysts for petroleum refinery since the end of the 1940s, coal handling and precious metals refining, probably concealing the likely presence of an emerging traffic-related Pt signal. This first comparison of historical Pt concentration trends in sediments from contrasting watersheds allows to distinguish signals originating from different natural and anthropogenic sources (background level, historical sources, road traffic).

Measuring aliphatic hydrocarbons in sediments by direct thermal desorption-gas chromatography-mass spectrometry: Matrix effects and quantification challenges.

Direct sample introduction thermal desorption (TD) coupled to GC-MS was investigated for the analysis of paraffinic hydrocarbons (HCs) from polluted sediments. TD-GC-MS is sometimes used for analysing paraffinic HCs from atmospheric particles but rarely for their direct desorption from sediments. So, the new TD methodology, applied to sediments, required development, optimization and validation. A definitive screening experimental design was performed to discriminate the critical factors on TD efficiency, from model sediments containing various organic matter (OM) amounts. Low molecular weight HCs had extraction behaviours markedly different from high molecular ones (HMW-HCs), but a compromise was found using very few sediment amount (5 mg), high temperature rate (55 °C min-1) and final temperature (350 °C). Linear HCs (n-C10 to n-C40) could be quantified using the matrix-matched calibration method, with very low detection limits (3.8-13.4 ng). The amount of the overall paraffinic alkanes was also determined as a sum of unresolved components between predefined equivalent carbon ranges. The developed solventless methodology was compared to an optimized solvent microwave assisted extraction (MAE). Matrix effects could be higher for TD compared to MAE but it depended on sediment matrix. When matrix effect was strong, particularly on HMW-HCs signal depletion, a dilution with pure non-porous sand was favourable for accurate quantification. The sum of resolved and unresolved HCs gave comparable results between MAE and TD extractions, with an exception of alkanes greater than C30 which were less quantitatively extracted via TD. However, TD-GC-MS was more sensitive than MAE-GC-MS. So TD-GC-MS is useful for analyzing sediments containing a great range of paraffinic HCs (C9-C34) and it has the advantages of being fully automated, with few sample preparation and operator intervention, using very low amounts of solvent, and generating few wastes.

Shifts in sediment bacterial communities reflect changes in depositional environments in a fluviatile context.

Sediments are complex heterogeneous matrices allowing to some extent the recording of past environmental conditions by integrating sediment characteristics, contamination and the microbial community assembly. In aquatic environments, abiotic environmental filtering is considered the primary deterministic mechanism shaping microbial communities in sediments. However, the number and relative contributions of geochemical and physical factors associated with biotic parameters (reservoir of microorganisms) complicate our understanding of community assembly dynamics. In this study, the sampling of a sedimentary archive in a site alternately subjected to contrasting inputs from the Eure and the Seine Rivers allowed us to study the response of microbial communities to changes in depositional environment over time. The coupling of the quantification and sequencing of the gene encoding the 16S rRNA with analyses of grain size, organic matter and major and trace metal contents demonstrated that microbial communities reflected contrasting sedimentary inputs over time. Total organic carbon (TOC) was the main factor influencing microbial biomass, while the quantity and quality of organic matter (R400, RC/TOC), major elements (i.e. Al, Fe, Ti) and trace metals (i.e. Zn, Pb, Cu, Cr, Ni, As, Co, Ag, Sb) shaped the structure of the microbial community. Besides the effect of geochemical factors, a specific microbial signature was associated with the contrasting sedimentary sources, highlighting the importance of the microbial reservoir in the assembly of microbial communities. Indeed, the main genera identified in the facies influenced by the Eure River were affiliated with the phyla Desulfobacterota (Syntrophus, Syntrophorhabdus, Smithella, Desulfatiglans), Firmicutes (Clostridium_sensu_stricto_1), Proteobacteria (Crenothrix), Verrucomicrobiota (Luteolibacter), while the contributions of the Seine River were characterised by some halophilic genera Salirhabdus (Firmicutes), Haliangium (Myxococcota) and SCGC-AB-539-J10 (Chloroflexi). This study sheds light on the overall processes determining the assembly of microbial communities in sediments and the importance of associating geochemical factors with reservoirs of microorganisms inherited from sediment sources.

Direct thermal desorption-gas chromatography-tandem mass spectrometry versus microwave assisted extraction and GC-MS for the simultaneous analysis of polyaromatic hydrocarbons (PAHs, PCBs) from sediments.

Polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs) are regulated contaminants usually investigated in sediments. Conventional approaches often use GC-MS to analyse them with a preliminary extraction step which can be solvent- and time-consuming. Here two extraction methodologies were optimized using experimental designs, and compared: microwave assisted extraction (MAE) and thermal desorption (TD); the latter was rarely used for sediments analyses. Several factors that may influence extraction recoveries were studied including matrix parameters (mass, organic matter (OM) content) and processing parameters. A definitive screening design DSD was performed to screen the 6 most influencing factors and model the extraction recoveries using TD. Whatever the OM content, a minimum sediment mass (5 mg) was better for an optimal extraction, with a minimum temperature rate (15 °C min-1), a maximum final temperature (350 °C) associated with a minimum hold time (5 min), and a maximum vent flow (150 mL min-1) between the TD unit and the cryogenic trap. Thereafter matrix effects were evaluated using standard addition, and quality assurance and control were implemented for comparing MAE and TD. TD-GC-MS/MS sensitivity was higher than MAE-GC-MS with detection limits in the range 5-1160 pg and 20-125 pg for PAHs and PCBs, respectively. When considering the appropriate strategy for quantification, TD was also reliable for sediments analysis. Although MAE was less sensitive to matrix effects, TD could significantly improve the analytical process, due to direct coupling with GC-MS/MS and complete automation. Moreover, TD offered possible higher spatial resolution than MAE, particularly for sediment cores analysis, due to the 1000-times lower sample size. At last, TD-GC-MS/MS appeared as a greener analytical procedure.

Sedimentary structure discrimination with hyperspectral imaging in sediment cores.

Hyperspectral imaging (HSI) is a non-destructive, high-resolution imaging technique that is currently under significant development for analyzing geological areas with remote devices or natural samples in a laboratory. In both cases, the hyperspectral image provides several sedimentary structures that must be separated to temporally and spatially describe the sample. Sediment sequences are composed of successive deposits (strata, homogenite, flood) that are visible depending on sample properties. The classical methods to identify them are time-consuming, have a low spatial resolution (millimeters) and are generally based on naked-eye counting. In this study, we compare several supervised classification algorithms to discriminate sedimentological structures in lake sediments. Instantaneous events in lake sediments are generally linked to extreme geodynamical events (e.g., floods, earthquakes), so their identification and counting are essential to understand long-term fluctuations and improve hazard assessments. Identification and counting are done by reconstructing a chronicle of event layer occurrence, including estimation of deposit thicknesses. Here, we applied two hyperspectral imaging sensors (Visible Near-Infrared, VNIR, 60 µm, 400-1000 nm; Short Wave Infrared, SWIR, 200 µm, 1000-2500 nm) on three sediment cores from different lake systems. We highlight that the SWIR sensor is the optimal one for creating robust classification models with discriminant analyses (prediction accuracies of 0.87-0.98). Indeed, the VNIR sensor is impacted by the surface reliefs and structures that are not in the learning set, which causes mis-classification. These observations are also valid for the combined sensor (VNIR-SWIR) and the RGB images. Several spatial and spectral pre-processing were also compared and enabled one to highlight discriminant information specific to a sample and a sensor. These works show that the combined use of hyperspectral imaging and machine learning improves the characterization of sedimentary structures compared to conventional methods.

Key factors influencing metal concentrations in sediments along Western European Rivers: A long-term monitoring study (1945-2020).

Since 1945, a large amount of heterogeneous data has been acquired to survey river sediment quality, especially concerning regulatory metals such as Cd, Cr, Cu, Hg, Ni, Pb, and Zn. Large-scale syntheses are critical to assess the effectiveness of public regulations and the resiliency of the river systems. Accordingly, this data synthesis proposes a first attempt to decipher spatio-temporal trends of metal contamination along seven major continental rivers in Western Europe (France, Belgium, Germany, and the Netherlands). A large dataset (>12,000 samples) from various sediment matrices (bed and flood deposits - BFD, suspended particulate matter - SPM, dated sediment cores - DSC) was set up based on monitoring and scientific research from the 1950s to the 2010s. This work investigates the impact of analytical protocols (matrix sampling, fractionation, extraction), location and time factors (related to geology and anthropogenic activities) on metal concentration trends. Statistical analyses highlight crossed-interactions in space and time, as well as between sediment matrices (metal concentrations in SPM ≃ DSC > BFD) and extraction procedures (also related to river lithology). Major spatio-temporal trends are found along several rivers such as (i) an increase of metal concentrations downstream of the main urban industrial areas (e.g. Paris-Rouen corridor on the Seine River, Bonn-Duisburg corridor on the Rhine River), (ii) a long-term influence of former mining areas located in crystalline zones, releasing heavily contaminated sediments for decades (Upper Loire River, Middle Meuse section), (iii) a decrease of metal concentrations since the 1970s (except for Cr and Ni, rather low and stable over time). The improvement of sediment quality in the most recent years in Europe reflects a decisive role of environment policies, such as more efficient wastewater treatments, local applications of the Water Framework Directive and urban industrial changes in the river valleys.

Historical and post-ban releases of organochlorine pesticides recorded in sediment deposits in an agricultural watershed, France.

Agricultural use of organochlorine pesticides (OCPs) increased during the twentieth century but many of them have been progressively banned several decades after their introduction. Nevertheless, these lipophilic chemical compounds may persist in soils and sediments. From sediment deposits, it is possible to reconstruct the chronology of OCP releases in relation to former applications through time. Nevertheless, long-term fate of OCPs i.e. source, transfer, and storage through the watershed, is also related to the OCPs-sediment characteristics interactions, and our study showed the significant links between OCPs and labile or refractory organic matter. From sediment cores collected in a mainly agricultural watershed, the Eure River watershed (France), aldrin and lindane widespread applications during the 1950s-1970s have been recorded. While lindane applications declined after that date, according to the temporal trend of the stable isomer of hexachlorocyclohexane (ß-HCH), α-, and γ-HCH have been recorded at significant levels in the 2000s, suggesting first local post-ban applications. Nevertheless, the relationships between these OCPs and labile organic matter resulted in an overestimation of the post-ban releases. Also, the detection of stable metabolites of dichlorodiphenyltrichloroethane (DDT) (i.e. 4,4'-DDE) and heptachlor (i.e. heptachlor epoxide) several decades after their ban, revealed the role of old deep soils erosion in the chronology of OCP releases and thus the reemergence of stable transformation products from historical OCPs.

Flux estimation, temporal trends and source determination of trace metal contamination in a major tributary of the Seine estuary, France.

Anthropogenic impacts on rivers have increased significantly over the past ~150 years, particularly at the beginning of the industrial revolution. Among other signs, this impact is manifested through the addition of trace metals and metalloid elements to rivers. The Eure River watershed in France covers an area of 6017 km2 and is a major tributary of the Seine estuary. It is not exempt from anthropogenic pressures and has been exposed to significant metal discharges over the last 80 years. The average concentrations of metals (i.e., Cr, Co, Ni, Cu, Zn, Ag, Cd, Sb, and Pb), in suspended particulate matter currently transported by the river are high compared to the local geochemical background. Moreover, the lack of correlation between concentration variations and the hydrosedimentary behaviour of the Eure River suggests that the river is currently under anthropogenic pressure. Analysis of sediment cores indicate strong As contamination during the 1940s, Cr, Co, Ni, Cu, Zn, Ag, and Cd contamination during the 1960s and 1970s, and Sb and Pb contamination during the 1990s and 2000s. The enrichment factors calculation suggests that total anthropogenic pressure within the Eure River watershed since the 1940s was comparable or higher than those in many other French watersheds. An estimation of particulate metal flux in 2017 shows that the Eure River watershed contributed to 7, 8, 9, 10 and 16% of total inputs to the Seine estuary in Cr, Cu, Zn, Cd and Pb respectively. Moreover, the estimation of past theoretical flux indicates that during the 1990s the Eure River watershed was the main contributor of particulate Pb to the estuary. The use of Pb isotopes has revealed that this contamination was primarily of industrial origin.

High-resolution prediction of organic matter concentration with hyperspectral imaging on a sediment core.

In the case of environmental samples, the use of a chemometrics-based prediction model is highly challenging because of the difficulty in experimentally creating a well-ranged reference sample set. In this study, we present a methodology using short wave infrared hyperspectral imaging to create a partial least squares regression model on a cored sediment sample. It was applied to a sediment core of the well-known Lake Bourget (Western Alps, France) to develop and validate a model for downcore high resolution LOI550 measurements used as a proxy of the organic matter. In lake and marine sediment, the organic matter content is widely used, for example, to reconstruct carbon flux variations through time. Organic matter analysis through routine analysis methods is time- and material-consuming, as well as not spatially resolved. A new instrument based on hyperspectral imaging allows high spatial and spectral resolutions to be acquired all along a sediment core. In this study, we obtain a model characterized by a 0.95 r prediction, with 0.77 wt% of model uncertainty based on 27 relevant wavelengths. The concentration map shows the variation inside each laminae and flood deposit. LOI550 reference values obtained with the loss on ignition are highly correlated to the inc/coh ratio used as a proxy of the organic matter in X-ray fluorescence with a correlation coefficient of 0.81. This ratio is also correlated with the averaged subsampled hyperspectral prediction with a r of 0.65.

2000 Years of Grazing History and the Making of the Cretan Mountain Landscape, Greece.

Understanding the processes that led to the recent evolution of Mediterranean landscapes is a challenging question that can be addressed with paleoecological data. Located in the White Mountains of Crete, Asi Gonia peat bog constitutes an exceptional 2000-years-long sedimentary archive of environmental change. In this study, we document the making of the White Mountains landscape and assess human impact on ecosystem trajectories. The paleoenvironmental reconstruction is based on high-resolution analyses of sediment, pollen, dung fungal spores and charcoal obtained from a 6-m core collected from the bog. Multiproxy analyses and a robust chronological control have shed light on anthropogenic and natural processes that have driven ecological changes, giving rise to the present-day Mediterranean ecosystem. Our results suggest that sediment accumulation began during the transition from the Hellenistic to the Roman period, likely due to watershed management. The evolution of the peat bog as well as vegetation dynamics in the surrounding area were linked to past climate changes but were driven by human activities, among which breeding was of great importance. Charcoal analysis reveals that fire was largely used for the construction and maintenance of sylvo-agropastoral areas. Pollen data allow the identification of three main vegetation assemblages: 1) evergreen oak forest (before ca. 850 AD), 2) heather maquis (ca. 850 to 1870 AD), 3) phrygana/steppe landscape. Rapid changes between phases in vegetation development are associated with tipping-points in ecosystem dynamics resulting from anthropogenic impact. The modern ecosystem did not get established until the 20th century, and it is characterized by biodiversity loss along with a dramatic drying of the peat bog.