Reclamation measurements are commonly applied to mitigate the leaching of metal pollutants in order to reduce the risk for humans and the environment. Organic and/or inorganic amendments are often recommended to stabilize tailings and to reduce leaching of contaminants. In a recent microcosm percolation experiment (Thouin et al., 2019), the addition of a mining slurry called ochre and manure, either alone or in combination, drastically reduced the leaching of several metal pollutants, notably Pb. Nevertheless, the biogeochemical processes involved in the immobilization of metal pollutants remain unknown, preventing the management of this remediation technique from being optimized and its extension to other sites. To fill this gap, a multicomponent reactive model was developed to simulate and forecast the impact of amendments on the leaching of metal pollutants. This model accounts for the following biogeochemical processes: kinetically-controlled dissolution and precipitation reactions, sorption reactions (i.e. surface complexation reactions), water-gas interactions and microbially-driven redox reactions with an explicit microbial growth. For all treatments, simulations revealed that Pb reactivity followed dynamic patterns driven by watering steps. The decrease in Pb concentration in the leachates of amended tailings compared to untreated tailings was also accurately reproduced. In untreated tailings, Pb reactivity is mainly controlled by the dissolution of Pb-bearing mineral phases. These reactions were maintained in thermodynamic disequilibrium due to the renewal of pore solution at each watering step. In amended tailings, this pattern was strengthened as the iron oxides contributed by ochre maintained a low Pb concentration in pore solution by sorbing released Pb. Sorption reactions were enhanced by the increase in pH induced by the dissolution of calcium carbonate initially present in ochre. The latter reaction was partially counterbalanced in tailings amended with manure as organic matter provided sufficient energy to fuel microbial aerobic respiration, leading to the release of protons. Pb desorption was promoted by this pH drop. By providing a better understanding of the effect of amendment, this multicomponent reactive model is a powerful tool to optimize the reclamation of tailings, in order to limit contaminant transfer to the environment.
Thouin H. et al. (2019), Appl. Geochem. 111, 104438
Advanced techniques have been recently used to obtain information on Natural Organic Matter (NOM). However, the current knowledge of the chemical structure of humic substances (HS) is still incomplete. These substances appear to be too complex mixtures of charged organic molecules, and their characterization remains one of the most stimulating challenges in modern environmental science. Knowledge of the chemical composition of NOM is of great importance for the definition of soil and water properties because it has a significant impact on the understanding of numerous molecular and global-scale processes.
This study aims to apply two-dimensional graphical methods to resolve homologous series in mass spectra of humic extracts (Suwannee River, Nordic Aquatic and Soil) obtained using FT-ICR / MS (Thermo LTQ FT, 7 Tesla) in negative ionization mode. Electrospray ionization (ESI) coupled with ultra-high resolution mass spectrometry offered by Fourier transformed ion cyclotron resonance (FT-ICR / MS) has emerged with great promise as it can provide an overview of the NOM composition and details on a molecular scale. NOM's very high-resolution FT-ICR spectra can be extremely complicated. These spectra usually contain many peaks at each nominal mass and thousands of peaks across the entire spectrum. Each peak can represent a chemically distinct compound. This complexity poses an analytical challenge to the study of spectra for structural interpretation. Two-dimensional graphing methods, such as Kendrick and van Krevelen graphs, have been successfully applied to very high-resolution mass spectra, allowing peaks to be sorted into complicated spectra from their homologous relatives across the mass range.
In van Krevelen plots, ionic signals corresponding to structural similarities between homologous series of compounds involved in the loss or gain of functional groups are found on straight lines. We identified many interesting homologous regions and compared the three humic standards with each other. Finally, we recognized the structural relationships of the homologous series obtained through Kendrick graphs.
The results showed homologous series in the Suwannee River and Nordic Aquatic samples compared to the soil-extracted samples (soil-FA and soil-HA). In particular, homologous series signals related to methylation/demethylation, hydrogenation/dehydrogenation, hydration/dehydration, and oxidation/reduction processes were lower in the soil-FA van Krevelen diagrams. On the contrary, the differences were not so evident in all the homologous series for the soil-HA samples.
National geodetic reference systems can be continuously monitored using applications of Global Navigation Satellite Systems (GNSS). Within these reference systems, Continuously Operating GNSS Reference Stations (CORSs) are often employed to provide 24/7 satellite tracking data. Understanding the influence of the surroundings of a CORS on the recorded satellite tracking data is indispensable for quality analysis of both acquired data and station location suitability. One of the main sources of inaccurate tracking data is the result of the combined reception of direct as well as indirect, environment-reflected satellite signals by the CORS, in which the latter can be considered interference compromising the signal’s accuracy. The magnitude of this interference is usually evaluated by the Signal-to-Noise Ratio (SNR), a parameter stored by default in the RINEX interchange format for raw GNSS data. The technique of GNSS Interferometric Reflectometry (GNSS-IR) exploits the availability of the SNR data and has been frequently used for applications such as soil moisture monitoring, detection of vegetation water content, measuring snowfall or determining water levels. In this research, we propose to employ GNSS-IR to investigate the effect of the surrounding on a CORS in order to evaluate station location suitability. More specifically, this will be done by using the signal to estimate the Reflector Height (RH), which depends on the reflector roughness (i.e. the roughness of the surface surrounding the CORS). The quality of this estimation will be validated by comparing with the actual measurement of the RH of the CORS on site.
In our approach, a statistically sound method is developed quantifying the stability of the RH determination. The proposed methodology consists of using Lomb-Scargle periodograms to select the dominant oscillation frequency of each satellite track SNR data, followed by an analysis and filtering of the peak amplitudes. This leads to the analysis product: number of significant peak amplitudes for an individual CORS over (sub-)daily timeframes. With historical data covering long time periods, statistical analysis of the (sub-)daily timeseries allows for reviewing the station location suitability. In Belgium, CORS are located on two typical positions: in Flanders, the 32 antennas are mainly installed on rooftops of buildings; in Wallonia, the 23 antennas are installed on a concrete pole next to highways. There is no evidence of one choice of station position being more suitable than the other. However, cars are known to be an important factor in signal reflections. In our analysis of station suitability, the effect of cars passing by on the highway near a Walloon CORS, but also movements on, e.g., parking lots next to buildings with a rooftop CORS, will be investigated. With the developed methodology, guidelines for station location selection could be further developed, together with a system to continuously monito
Methods to quantify plastic transport in rivers have greatly improved during the past few years. As a first approach, visual counting is currently the simplest way to assess plastic transport with minimal effort and cost. It usually results in underestimations of plastic input into the sea of about one to two order of magnitude when compared to models such as the Jambeck’s approach. The latter shows statistical weaknesses and data availability issues leading to large uncertainties, while visual counting miss the water column compartment and often has a low spatiotemporal representativeness. In order to give another ground-truth estimation of plastic transport able to challenge both models and visual counting, we developed innovative methods based on environmental management data in the Seine estuary (500 m3/s) and the Huveaune River ( 2 m3/s; Marseille, France). First, we used data from institutional cleaning in the Seine estuary that consist in litter collection on riverbanks. Their efficiency was measured based on capture-recapture design. Mass flows of plastic debris were then calculated based on the capture rate over one year, the estimation of the fraction of plastic debris which are never collected (hidden or too small) and the assumption that all plastic debris strand on riverbanks. Second, we used data from bar screens spaced of 3 cm in the Huveaune, a small urban river flowing in Marseille, South France. All the water column is screened, and captured waste are automatically collected in dumpsters. Grab sampling were performed after a dry, a wet and a flood period. The corresponding annual mass flows of plastic debris was then calculated relative to the mean fraction of time corresponding to those hydrological periods over 2017 and 2018. Annual mass flows of plastic debris were normalized to the population in both basins. Although methods were different, mass flows of plastic debris per capita are very similar with 8.5 – 13.6 g/cap/yr for the Seine River and 2.4 – 14.9 g/cap/yr for the Huveaune River. This is one to two order of magnitude lower than the Jambeck’s approach. However, when focusing on the fraction ending into the Sea, bar screens in Marseille enable to decrease the mass flow of plastic debris of about one additional order of magnitude, while cleaning of riverbanks decreases it of about 10%. This is related to the nature of the rivers that calls for different solutions, screening the whole Seine River being a tricky idea. Nevertheless, when normalized to water volume, the Huveaune River is visually much more polluted (16.4–102.2 mg/m3) than the Seine estuary (9.0–14.5 mg/m3). In conclusion, environmental management data can help to estimate mass flows of plastic debris and calls for better consideration. However, they often need an improved scientific framework.
Image-based analytical tools in geosciences are indispensable for the characterization of minerals, but most of them are limited to the surface of a polished plane in a sample and lack 3D information. X-ray micro computed tomography (micro CT) provides the missing 3D information of the microstructures inside samples. However, a major drawback of micro CT in the characterization of minerals is the lack of chemical information that makes mineral classification challenging.
Spectral X-ray micro computed tomography (Sp-CT) is a new and evolving tool in different applications such as medicine, security, material science, and geology. This non-destructive method uses a multi-pixel photon-counting detector (PCD) such as cadmium telluride (CdTe) in combination with a conventional CT scanner (TESCAN CoreTOM) to image a sample and detect its transmitted polychromatic X-ray spectrum. Based on the spectrum, elements in a sample can be identified by an increase in attenuation at specific K-edge energies. Therefore, chemically different particles can be distinguished inside a sample from a single CT scan. The method is able to distinguish elements with K-edges in the range from 25 to 160 keV, which applies to elements with Z > 48 (Sittner et al., 2020).
We present results from various sample materials. Different pure elements and element oxides were measured to compare the position of theoretical and measured K-edge energies. All measured K-edge energies are slightly above the theoretical value, but based on the results a correction algorithm could be developed. Furthermore, different monazite grains were investigated, which can be divided into two groups with respect to the content of different RE elements on the basis of the spectrum: La-Ce-rich and La-Ce-poor. In addition, samples from the Au-U Witwatersrand Supergroup demonstrate the potential applications of Sp-CT for geological samples. We measured different drill core samples from the Kalkoenkrans Reef at the Welkom Gold field. Sp-CT can distinguish gold, uraninite and galena grains based on their K-edge energies in the drill core without preparation.
Sittner, J., Godinho, J. R. A., Renno, A. D., Cnudde, V., Boone, M., De Schryver, T., Van Loo, D., Merkulova, M., Roine, A., & Liipo, J. (2020). Spectral X-ray computed micro tomography: 3-dimensional chemical imaging. X-Ray Spectrometry, September, 1–14.
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