46 research outputs found

    Dissolved organic carbon transformations and microbial community response to variations in recharge waters in a shallow carbonate aquifer

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    © 2016, The Author(s). In carbonate aquifers, dissolved organic carbon from the surface drives heterotrophic metabolism, generating CO2 in the subsurface. Although this has been a proposed mechanism for enhanced dissolution at the water table, respiration rates and their controlling factors have not been widely evaluated. This study investigates the composition and concentration of dissolved organic carbon (DOC) reaching the water table from different recharge pathways on a subtropical carbonate island using a combination of DOC concentration measurements, fluorescence and absorption characterisation. In addition, direct measurements of the microbial response to the differing water types were made. Interactions of rainfall with the vegetation, via throughfall and stemflow, increase the concentration of DOC. The highest DOC concentrations are associated with stemflow, overland recharge and dissolution hole waters which interact with bark lignin and exhibit strong terrestrial-derived characteristics. The groundwater samples exhibit the lowest concentrations of DOC and are comprised of refractory humic-like organic matter. The heterotrophic response seems to be controlled by the concentration of DOC in the sample. The terrestrially sourced humic-like matter in the stemflow and dissolution hole samples was highly labile, thus increasing the amount of biologically produced CO2 to drive dissolution. Based on the calculated respiration rates, microbial activity could enhance carbonate dissolution, increasing porosity generation by a maximum of 1%kyr−1 at the top of the freshwater lens

    1H NMR-based metabolomics combined with HPLC-PDA-MS-SPE-NMR for investigation of standardized Ginkgo biloba preparations

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    Commercial preparations of Ginkgo biloba are very complex mixtures prepared from raw leaf extracts by a series of extraction and prepurification steps. The pharmacological activity is attributed to a number of flavonoid glycosides and unique terpene trilactones (TTLs), with largely uncharacterized pharmacological profiles on targets involved in neurological disorders. It is therefore important to complement existing targeted analytical methods for analysis of Ginkgo biloba preparations with alternative technology platforms for their comprehensive and global characterization. In this work, 1H NMR-based metabolomics and hyphenation of high-performance liquid chromatography, photo-diode array detection, mass spectrometry, solid-phase extraction, and nuclear magnetic resonance spectroscopy (HPLC-PDA-MS-SPE-NMR) were used for investigation of 16 commercially available preparations of Ginkgo biloba. The standardized extracts originated from Denmark, Italy, Sweden, and United Kingdom, and the results show that 1H NMR spectra allow simultaneous assessment of the content as well as identity of flavonoid glycosides and TTLs based on a very simple sample-preparation procedure consisting of extraction, evaporation and reconstitution in acetone-d6. Unexpected or unwanted extract constituents were also easily identified in the 1H NMR spectra, which contrasts traditional methods that depend on UV absorption or MS ionizability and usually require availability of reference standards. Automated integration of 1H NMR spectral segments (buckets or bins of 0.02 ppm width) provides relative distribution plots of TTLs based on their H-12 resonances. The present study shows that 1H NMR-based metabolomics is an attractive method for non-selective and comprehensive analysis of Ginkgo extracts

    Tracking down carbon inputs underground from an arid zone Australian calcrete.

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    Freshwater ecosystems play a key role in shaping the global carbon cycle and maintaining the ecological balance that sustains biodiversity worldwide. Surficial water bodies are often interconnected with groundwater, forming a physical continuum, and their interaction has been reported as a crucial driver for organic matter (OM) inputs in groundwater systems. However, despite the growing concerns related to increasing anthropogenic pressure and effects of global change to groundwater environments, our understanding of the dynamics regulating subterranean carbon flows is still sparse. We traced carbon composition and transformations in an arid zone calcrete aquifer using a novel multidisciplinary approach that combined isotopic analyses of dissolved organic carbon (DOC) and inorganic carbon (DIC) (δ13CDOC, δ13CDIC, 14CDOC and 14CDIC) with fluorescence spectroscopy (Chromophoric Dissolved OM (CDOM) characterisation) and metabarcoding analyses (taxonomic and functional genomics on bacterial 16S rRNA). To compare dynamics linked to potential aquifer recharge processes, water samples were collected from two boreholes under contrasting rainfall: low rainfall ((LR), dry season) and high rainfall ((HR), wet season). Our isotopic results indicate limited changes and dominance of modern terrestrial carbon in the upper part (northeast) of the bore field, but correlation between HR and increased old and 13C-enriched DOC in the lower area (southwest). CDOM results show a shift from terrestrially to microbially derived compounds after rainfall in the same lower field bore, which was also sampled for microbial genetics. Functional genomic results showed increased genes coding for degradative pathways-dominated by those related to aromatic compound metabolisms-during HR. Our results indicate that rainfall leads to different responses in different parts of the bore field, with an increase in old carbon sources and microbial processing in the lower part of the field. We hypothesise that this may be due to increasing salinity, either due to mobilisation of Cl- from the soil, or infiltration from the downstream salt lake during HR. This study is the first to use a multi-technique assessment using stable and radioactive isotopes together with functional genomics to probe the principal organic biogeochemical pathways regulating an arid zone calcrete system. Further investigations involving extensive sampling from diverse groundwater ecosystems will allow better understanding of the microbiological pathways sustaining the ecological functioning of subterranean biota

    Self-Organising Maps and Correlation Analysis as a Tool to Explore Patterns in Excitation-Emission Matrix Data Sets and to Discriminate Dissolved Organic Matter Fluorescence Components

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    Dissolved organic matter (DOM) is a complex mixture of organic compounds, ubiquitous in marine and freshwater systems. Fluorescence spectroscopy, by means of Excitation-Emission Matrices (EEM), has become an indispensable tool to study DOM sources, transport and fate in aquatic ecosystems. However the statistical treatment of large and heterogeneous EEM data sets still represents an important challenge for biogeochemists. Recently, Self-Organising Maps (SOM) has been proposed as a tool to explore patterns in large EEM data sets. SOM is a pattern recognition method which clusterizes and reduces the dimensionality of input EEMs without relying on any assumption about the data structure. In this paper, we show how SOM, coupled with a correlation analysis of the component planes, can be used both to explore patterns among samples, as well as to identify individual fluorescence components. We analysed a large and heterogeneous EEM data set, including samples from a river catchment collected under a range of hydrological conditions, along a 60-km downstream gradient, and under the influence of different degrees of anthropogenic impact. According to our results, chemical industry effluents appeared to have unique and distinctive spectral characteristics. On the other hand, river samples collected under flash flood conditions showed homogeneous EEM shapes. The correlation analysis of the component planes suggested the presence of four fluorescence components, consistent with DOM components previously described in the literature. A remarkable strength of this methodology was that outlier samples appeared naturally integrated in the analysis. We conclude that SOM coupled with a correlation analysis procedure is a promising tool for studying large and heterogeneous EEM data sets

    Towards a better control of the wastewater treatment process: excitation-emission matrix fluorescence spectroscopy of dissolved organic matter as a predictive tool of soluble BOD5 in influents of six Parisian wastewater treatment plants

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    The online monitoring of dissolved organic matter (DOM) in raw sewage water is expected to better control wastewater treatment processes. Fluorescence spectroscopy offers one possibility for both the online and real-time monitoring of DOM, especially as regards the DOM biodegradability assessment. In this study, three-dimensional fluorescence spectroscopy combined with a parallel factor analysis (PARAFAC) has been investigated as a predictive tool of the soluble biological oxygen demand in 5 days (BOD5) for raw sewage water. Six PARAFAC components were highlighted in 69 raw sewage water samples: C2, C5, and C6 related to humic-like compounds, along with C1, C3, and C4 related to protein-like compounds. Since the PARAFAC methodology is not available for online monitoring, a peak-picking approach based on maximum excitation-emission (Ex-Em) localization of the PARAFAC components identified in this study has been used. A good predictive model of soluble BOD5 using fluorescence spectroscopy parameters was obtained (r (2) = 0.846, adjusted r (2) = 0.839, p < 0.0001). This model is quite straightforward, easy to automate, and applicable to the operational field of wastewater treatment for online monitoring purposes
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