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Classification preparation areas

Figure 9.4 Examples of improved urban land-use classifications prepared for a) the Copenhagen metropolitan area (shown as a percentage of the urban class representation in each grid-cell of the domain) used in the DMI-HIRLAM simulations (Left panel) (b) the Marseilles metropolitan area (shown as a presence of 9 classes in domain, see Long et al. 2003 [375]) used in the SUBMESO/ SM2-U simulations (Right panel). Figure 9.4 Examples of improved urban land-use classifications prepared for a) the Copenhagen metropolitan area (shown as a percentage of the urban class representation in each grid-cell of the domain) used in the DMI-HIRLAM simulations (Left panel) (b) the Marseilles metropolitan area (shown as a presence of 9 classes in domain, see Long et al. 2003 [375]) used in the SUBMESO/ SM2-U simulations (Right panel).
Double-Ended Autoclaves In many industrial applications autoclaves will be bridges between areas with different cleanliness classifications. The two main scenarios are that of an autoclave being loaded in a nonsterile preparation area for its sterilized contents to be unloaded in an aseptic filling room, and of an autoclave being loaded in a clean filling room for its sterilized contents to he unloaded into an uncontrolled packing area. In either example the risk is com-... [Pg.96]

Define work areas within each process area Select and prepare sampling sites Define employee job classifications... [Pg.86]

The preparation of intermediate petrochemical streams requires different processing alternatives depending on the feedstock quality. In our classification of petrochemical feedstocks we closely follow that of Gary and Handwerk (1994) consisting of aromatics, olefins, and parafftn/cyclo-parafftn compounds. The classification of petrochemical feedstocks into these clusters helps to identify the different sources in the refinery that provide suitable feedstock and, therefore, to better recognize areas of synergy between the refinery and petrochemical systems. [Pg.14]

Various criteria can be considered in the classification of the SEC applications. The most important are the analytical SEC procednres. The preparative applications, which encompass the purification of complex samples before their further treatment, draw rather wide attention. In this latter case, analytes are preseparated by SEC according to the size of their components and either macromolecular or low molecular fractions are subject to further analyses by other methods. The production oriented SEC did not find wide application in the area of synthetic polymers due to both the high price of organic solvents and the ecological considerations. [Pg.473]

Due to the variety in porous structure, particle size and surface area, pure silica gels and powders find a very wide range of applications. Variation in preparation methods and parameters allows the tailoring of the substrate properties for specific application needs. The main features in the silica applications are its porosity, active surface, hardness, particle size and the viscous and thixotropic properties. Although most applications are based on a combination of those, a classification according to the main properties of interest may be set up. For references, the reader is referred to the works of Iler6 and Unger7 and to the references cited in chapter 8. [Pg.27]

Preparative work is not the main topic of this book, so that classification must be in accordance with the other areas of TLC, i.e. identity testing, purity testing and assaying. The demands made on these and hence the differences between them begin with the choice of the layers and end only with the documentation. [Pg.50]


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