Incidence du chlorure de sodium sur la dénitrification d'éluats de résines par une bactérie chimiautotrophe soufre-oxydante

L'épuration ou la destination finale des éluats de régénération des résines utilisées en dénitratation reste un problème mal résolu. De nouvelles voies sont recherchées; la dénitrification biologique semble très attrayante car elle peut être mise en oeuvre sous forme d'un réacteur de faible coût et d'exploitation facile. L'objectif de ce travail a été d'affiner la connaissance du procédé de dénitrification chimioautotrophe sur soufre en milieu salé, dirigé vers l'épuration et/ou la valorisation de ces éluats.Claus et Kutzner (1985) ont montré l'action inhibitrice de la dénitrification du chlorure de sodium à partir de 20 g/l. Une colonne contenant du soufre est alimentée en continu par une solution comportant des nitrates et des sels nutritifs. La première partie de l'étude permet de relier la charge volumique (Cv) au rendement de dénitrification. Le rendement de dénitrification est supérieur à 85 % pour Cv < 2 kg NO3-/m3.j ; il tombe à 50 % pour Cv ~ 3,5 kg NO3-/m3.j Des rapports stoechiométriques entre les nitrates réduits et les produits formés/consommés ont été établis. Ainsi : NO3- donne 0,98 SO42- et 1 NO3- consomme 0,90 HCO3-. L'incidence de la teneur en NaCl de la solution alimentaire permet de montrer l'inhibition non compétitive du chlorure vis-à-vis de la dénitrification. L'incidence de la concentration en NaCl sur le vitesse de dénitrification apparaît pour une charge de 1 kg NO3-/m3.j. On note que le rendement de 90 % ou plus est obtenu pour une concentration 2 30 g/l. La constante d'inhibition est de l'ordre de 40 g/l. L'examen de la répartition de la biomasse sur le matériau et une approximation simple d'écoulement en flux piston nous conduisent à prévoir le rendement d'élimination de NO3- par :r=1 - e[ - 143,5 ] (sur) CV (41+I)Cette équation traduit les rôles de la charge volumique (Cv) et de la concentration en NaCl (I).The treatment and ultimate disposal of saline eluates from ionic exchange resins remain a badly worked out problem. New approaches are needed and biological denitrification seems to be very attractive since it may be implemented in the form of an inexpensively and easily used reactor.The aim of the present work was to better understand the bacterial denitrification process on sulphur by a chemoautotrophic bacterium, Thiobacillus denitrificans, in a saline medium, and to apply this knowledge to the treatment and/or the recycling of these eluates. Claus and Kutzner (1985) reported an inhibitory effect of NaCl starting at a concentration of 20 g/L.A column containing elemental sulphur was continually fed by a solution containing nitrate and nutrient salts. In the first step of the study, a relationship between the volumetric load (Cv) and the denitrification efficiency was established. For Cv < 2 kg NO3-/m3/j, the denitrification efficiency was greater than 85%, whereas it decreased rapidly to 50% for Cv 3,5 kg NO3- /m3/j. Stoichiometric ratios between reduced nitrates and formed/consumed products were determined. For example, the reduction of 1 mole of NO3- induces the formation of 0,98 mole SO42- and requires 0,90 moles HCO3-. The effect of the NaCl concentration was investigated for a volumetric charge of 1 NO3-/m3/j. An uncompetitive inhibition of denitrification by the sodium chloride present in the feed solution was observed. The denitrification efficiency reaches at least 90% for NaCl concentrations up to 30 g/L. The inhibition constant is about 40 g/l. A model linking the denitrification efficiency (r) to the volumetric loading and to the sodium chloride concentration in the regeneration water was developed, based on an examination of the biomass distribution on the fill material and the assumption of plug-flow within the column:r=1 - e[ - 143,5 ] (over) CV (41+I

K-shell x-ray spectroscopy of atomic nitrogen

Absolute {\it K}-shell photoionization cross sections for atomic nitrogen have been obtained from both experiment and state-of-the-art theoretical techniques. Due to the difficulty of creating a target of neutral atomic nitrogen, no high-resolution {\it K}-edge spectroscopy measurements have been reported for this important atom. Interplay between theory and experiment enabled identification and characterization of the strong $1s$ $\rightarrow$ $np$ resonance features throughout the threshold region. An experimental value of 409.64 $\pm$ 0.02 eV was determined for the {\it K}-shell binding energy.Comment: 4 pages, 2 graphs, 1 tabl

Land use/cover classification in the Brazilian Amazon using satellite images.

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation?based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi?resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Of the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, has the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical?based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data