33 research outputs found

    Analyse de composés organiques purs par pyrolyse Rock-Eval et influence de la matrice minérale

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    International audienceL’utilisation croissante de la pyrolyse Rock-Eval pour caractĂ©riser les matiĂšres organiques des sols et des sĂ©diments rĂ©cents a conduit Carrie et al. (2012) Ă  analyser des produits organiques purs en vue d’interprĂ©ter les signaux et paramĂštres classiques de cette technique : S1, S2, S3, Tmax, index d’hydrogĂšne et d’oxygĂšne, etc. Si leur dĂ©marche est intĂ©ressante, elle a toutefois Ă©tĂ© menĂ©e avec une mĂ©thode inappropriĂ©e puisqu’ils ont utilisĂ© le mode ‘bulk rock basic’ adaptĂ© aux roches mĂšres pĂ©troliĂšres. En effet, la tempĂ©rature initiale de 300°C qui caractĂ©rise ce mode conduit Ă  une thermovaporisation brutale et prĂ©coce des produits organiques purs d’oĂč des pics S1 trĂšs forts et des Tmax parfois aberrants.Il nous a semblĂ© important de reprendre l’approche de Carrie et al. (2012) en commençant la pyrolyse Ă  200 °C, tel que prĂ©conisĂ© par Disnar et al. (2003) pour l’analyse des sols. Nous avons choisi d’analyser de l’albumine de sĂ©rum bovin, de la cystĂ©ine, du glucose, de la cellulose et du cholestĂ©rol comme composĂ©s modĂšles reprĂ©sentant des protĂ©ines, des carbohydrates et des lipides. Par ailleurs, nous avons examinĂ© l’influence de diffĂ©rentes matrices minĂ©rales lors de la pyrolyse de ces produits purs Ă  l’image de ce qu’avaient fait EspitaliĂ© et al. (1984) avec les kĂ©rogĂšnes. Du sable de Fontainebleau, de la calcite, de la kaolinite, de la montmorillonite et des oxy-hydroxydes de fer (ferrihydrite et goethite) ont ainsi Ă©tĂ© ajoutĂ©s Ă  sec Ă  chacun de ces produits purs. Le bilan carbone fourni par la pyrolyse Rock-Eval a Ă©tĂ© comparĂ© avec les rĂ©sultats d’une analyse Ă©lĂ©mentaire sur les mĂȘmes mĂ©langes synthĂ©tiques.Les rĂ©sultats montrent que dans la plupart des cas le bilan carbone du Rock-Eval est dĂ©ficitaire et que celui-ci l’est d’autant plus que les produits sont associĂ©s Ă  des oxy-hydroxydes de fer. Ces oxydes ont un effet catalytique qui favorise le craquage thermique du produit (fort pic S1) et la gĂ©nĂ©ration de composĂ©s oxygĂ©nĂ©s (CO et CO2) aux dĂ©pens du S2. Le sable n’apparait pas aussi inerte que prĂ©vu sur les produits purs. La kaolinite et la montmorillonite ont des effets contrastĂ©s selon la nature des produits. Il semblerait que la montmorillonite favorise la formation de coke pendant la phase de pyrolyse d’oĂč une diminution de la part de carbone pyrolysable au profit du carbone rĂ©siduel.Carrie et al. (2012) – Org. Geochem., 46, 38-53.Disnar et al. (2003) – Org. Geochem., 34, 327-343.EspitaliĂ© et al. (1984) – Org. Geochem., 6, 365-382

    Forest management and soil organic carbon

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    International audienc

    Fate of crop residues incorporated in soil: towards linking microbial diversity and evolution of organic matter

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    Communication orale, résuméAmong the microbial functions involved in biogeochemical cycles, those related to carbon cycle play a central role in the biological functioning of agro-ecosystems, in particular because of their involvement in soil fertility, environment quality and global changes. In spite of its major role in organic matter degradation processes, the microbial component involved is poorly documented, particularly in terms of populations and functions, and then considered as a "functional black box". In this context, our objective was to progress in our knowledge of the microbial populations responsible for organic matter degradation in soil. Crop residues represent one of the most important hot spots (zones of increased biological activity) and ecological niches to study microbes involved in organic matter degradation. Our objective was to characterize, in a field experiment, the dynamics of the microbial communities in the detritusphere (zone of the soil under the influence of crop residues) in relation to the biochemical quality of the residue and the evolution of the soil organic matter. For this, residues from different plant types: wheat, colza, and alfalfa were incorporated separately in different plots. From the incorporation date, soils were sample each 1 month for 1 year. The responses of microbial communities to residue supply have been assessed by using molecular methods allowing the characterization of the diversity of microorganisms (DNA fingerprinting, clone libraries). In parallel, the dynamics of the biochemical quality of the residues have been monitored (Near Infra Red Spectrometry).Results showed a strong influence of residue biochemical quality on the dynamics of microbial communities. Furthermore, most of the microbial modifications occurred in the close neighbourhood of the residue, highlighting the particular ecological significance of the detritusphere. Coupling of microbial data and organic mater biochemical data allowed linking the dynamics of microbial communities with the fate of organic matter in soil

    Peut-on calculer la valeur de paramÚtres Rock-Eval pour la couche 0-50 cm à partir des valeurs mesurées sur les couches 0-30 et 30-50 cm ?

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    Les sols sont gĂ©nĂ©ralement Ă©chantillonnĂ©s Ă  diffĂ©rentes profondeurs fixes, sous forme de couches, mais ces profondeurs peuvent varier d’une Ă©tude Ă  l’autre. Pour calculer des stocks de carbone organique du sol Ă  des profondeurs donnĂ©es, les quantitĂ©s de COS prĂ©sentes dans les diffĂ©rents horizons peuvent ĂȘtre additionnĂ©es. Nous nous sommes demandĂ©s si, de la mĂȘme maniĂšre, il est possible de combiner les valeurs d’indicateurs Rock-Eval mesurĂ©es sur diffĂ©rentes profondeurs pour obtenir des valeurs d’indicateurs reprĂ©sentatives des Ă©chantillons combinĂ©s.Pour tester la linĂ©aritĂ© des indicateurs Rock-Eval, nous avons mĂ©langĂ© des Ă©chantillons de sol prĂ©levĂ©s en surface (0–30 cm) et en profondeur (30–50 cm) dans les diffĂ©rentes proportions suivantes : 100:0 ; 90:10 ; 75:25 ; 50:50 ; 25:75 ; 10:90 ; 0:100. Ces mĂ©langes ont Ă©tĂ© rĂ©alisĂ©s pour 8 sols de forĂȘt française Ă  pĂ©dologies contrastĂ©es. Nous avons ensuite analysĂ© les Ă©chantillons purs (100:0 et 0:100) et les mĂ©langes en Rock-Eval (n = 56 Ă©chantillons). Pour diffĂ©rents paramĂštres Rock-Eval, nous avons comparĂ© les valeurs mesurĂ©es pour les diffĂ©rents mĂ©langes aux moyennes pondĂ©rĂ©es (suivant la composition du mĂ©lange) des valeurs mesurĂ©es pour les Ă©chantillons de surface et de profondeur composant ces mĂ©langes.Nos rĂ©sultats montrent que la majoritĂ© des paramĂštres Rock-Eval sont linĂ©aires et qu’il est donc possible de dĂ©terminer la valeur du paramĂštre choisi pour l’horizon 0–50 cm Ă  partir des valeurs mesurĂ©es sur les horizons 0–30 cm et 30–50 cm. C’est en particulier le cas pour les paramĂštres suivants : TOC-RE6, HI, T50CO2pyr et T50CO2ox. Cependant pour deux des paramĂštres testĂ©s (OI et T50CHpyr) la relation entre valeurs mesurĂ©es et calculĂ©es est peu satisfaisante. Cette mauvaise adĂ©quation est particuliĂšrement observĂ©e dans certains types de sol avec des processus pĂ©dogĂ©nĂ©tiques marquĂ©s et qui conduisent Ă  des horizons trĂšs contrastĂ©s. D’autre part, ces deux paramĂštres sont aussi ceux prĂ©sentant la plus grande variabilitĂ©, ce qui explique au moins en partieles diffĂ©rences entre valeurs mesurĂ©es et calculĂ©es

    Can we calculate the value of Rock-Eval parameters for the 0-50 layer from the measured values on the layers 0-30 and 30-50 cm?

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    International audienceCurrent studies investigating soils use different sampling methods. Generally, soils are sampled in different soil horizons and the sampling depths may vary across studies or according to the soil profile composition. For some soil properties such as soil organic carbon stock, it is possible to calculate the organic carbon content of a soil profile by adding the values measured in each horizon. Soil organic carbon stock is therefore independent from the sampling strategy. In the recent years, Rock-Eval has been proposed as a reliable method to investigate soil organic carbon stock and its stability. The objective of this study is to determine, whether Rock-Eval parameters of soil organic matter in a given soil horizon, can also be calculated from Rock-Eval parameters measured in subhorizons; an idea which would greatly facilitate the comparison of results of studies using different sampling methods. In this study, samples from 10 French forest sites encompassing a variety of pedoclimates were used. At each site, samples were collected from two depth ranges, 0-30 and 30-50 cm. To test the linearity of the mixing of RE indicators, binary mixtures of surface and deep soil were composed for each site using five different mixing ratios (10:90, 25:75, 50:50, 75:25, 90:10). All 70 samples were then analysed using Rock-Eval, resulting in five classical RE parameters for each sample. The values of the RE parameters measured on composite samples were generally in good agreement with theoretical values, which were calculated using values measured on 0-30 cm and 30-50 cm according to the mixing equation. This is particularly the case for the following parameters: TOCRE6, PC,RC and OI. However, for HI the relationship between measured and calculated values is unsatisfactory. For sites with a clay-rich deep soil horizon layer and a surface layer with a coarser texture the variation was the highest. Retention of hydrocarbons by clay minerals is a common mineral matrix effect in pyrolysis methods and could explain this observation. Future research should include quantification of the mineral matrix effect for different soil types and calculation of a correction factor for the addition of parameters in a soil profile. Therefore, we conclude that in most temperate soils, most classical RE parameters of a soil profile can be indeed calculated as a sum of the different horizons
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