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1. Surface modification of natural zeolite by chitosan and its use for nitrate removal in cold regions [2010]

  • ARORA, Meenakshi, EDDY, Natalia K, MUMFORD, Kathryn A, BABA, Yoshinari, PERERA, Jilska M, and STEVENS, Geoff W
  • Cold regions science and technology. 62(2-3):92-97
Subjects
Environment, Environnement, Civil engineering, Génie civil, Glaciology, Glaciologie, Geology, Géologie, Geophysics, Géophysique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Pollution, Traitement et pollution des eaux, Water treatment and pollution, Pollution des eaux naturelles, Natural water pollution, Eaux souterraines, Groundwaters, Pollution du sol et des sédiments, Soil and sediments pollution, Décontamination. Divers, Decontamination. Miscellaneous, Terre, ocean, espace, Earth, ocean, space, Sciences de la terre, Earth sciences, Géologie de l'ingénieur et de l'environnement. Géothermie, Engineering and environment geology. Geothermics, Pollution, géologie de l'environnement, Pollution, environment geology, Adsorption, Adsorción, Biopolymère, Biopolymer, Biopolímero, Bioremédiation, Bioremediation, Biorremediación, Biostimulation, Bioestimulación, Chitosane, Chitosan, Quitosano, Décontamination, Decontamination, Descontaminación, Eau souterraine, Ground water, Agua subterránea, Fertilisation azotée, Nitrogen fertilization, Fertilización nitrogenada, Hydrocarbure, Hydrocarbon, Hidrocarburo, Matériau modifié, Modified material, Material modificado, Nitrate, Nitrates, Nitrato, Pollution eau, Water pollution, Contaminación agua, Pollution sol, Soil pollution, Polución suelo, Polyoside, Polysaccharide, Poliósido, Protonation, Protonación, Prévention pollution, Pollution prevention, Prevención polución, Résine échangeuse ion, Ion exchange resin, Resina intercambiadora ión, Traitement surface, Surface treatment, Tratamiento superficie, Zone polaire, Polar region, Zona polar, Zéolite, Zeolite, Zeolita, and Remediation
Abstract
Surface modifications of natural zeolite were performed by coating it with a chitosan layer. The chitosan coated zeolite (Ch-Z) was protonated with either sulfuric or hydrochloric acid and tested for its suitability to capture nitrate from water at 20 and 4 °C. The surface characterization of the Ch-Z was done by SEM, FTIR, TGA and nitrogen adsorption tests. The results of these tests showed evidence of chitosan coating onto zeolite particles. Ch-Z has comparable capacity to other weak anion exchangers with a nitrate ion exchange capacity 0.74 mmol NO3 g―1 (protonated with HCl).

2. Automated Polar Ice Thickness Estimation From Radar Imagery. [2010]

  • Gifford, Christopher M., Finyom, Gladys, Jefferson Jr., Michael, Reid, MyAsia, Akers, Eric L., and Agah, Arvin
  • IEEE Transactions on Image Processing. Sep2010, Vol. 19 Issue 9, p2456-2469. 14p. 3 Charts, 16 Graphs.
Subjects
RADAR, THICKNESS measurement, CLIMATE change, SHIELDS (Geology), ANTARCTIC ice, and GREENLAND ice
Abstract
This paper focuses on automating the task of estimating Polar ice thickness from airborne radar data acquired over Greenland and Antarctica. This process involves the identification and accurate selection of the ice sheet's surface location and interface between the ice sheet and the underlying bedrock for each measurement. Identifying the surface and bedrock locations in the radar imagery enables the computation of ice sheet thickness, which is important for the study of ice sheets, their volume, and how they may contribute to global climate change. The time-consuming manual approach requires sparse hand-selection of surface and bedrock interfaces by several human experts, and interpolating between the selections to save time. Two primary methods have been studied in this paper, namely, edge-based and active contour. Results are evaluated and presented using the metrics of time requirements and accuracy. Automated ice thickness estimation results from 2006 and 2007 Greenland field campaigns illustrate that the edge-based approach offers faster processing (seconds compared to minutes), but suffers from a lack of continuity and smoothness aspects that active contours provide. The active contour approach is more accurate when compared to ground truth selections provided by human experts, and has proven to be more robust to image artifacts. It is shown that both techniques offer advantages which could be integrated to yield a more effective system. [ABSTRACT FROM AUTHOR]

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