| Summary: | This research presents the development and application of high-throughput sample preparation methods for the analysis of organic and inorganic contaminants from solid samples. The approach presented evaluates conventional methods to identify potential areas of improvement. In this sense, conventional methods serve as a framework for the development of high-throughput sample preparation methods. In general, improvements include expansion of target analyte list thereby increase the environmental applicability, reduction of sample preparation steps, and as a result, reduction of sample preparation time. The analytical bottleneck is often associated with sample preparation, especially in the analysis of organic contaminants from environmental samples. Many environmental analytical chemistry methods can be broken down into one or more sample preparation steps followed by one or more chemical analysis steps. Improvement of historical methods has focused on the development of advance instrumentation (i.e. focusing on the chemical analysis). However, recent efforts have focused on the overall reduction of time and/or steps associated with sample preparation. For example, post-extraction cleanup adsorbents can be incorporated into the pressurized liquid extraction step to perform a selective pressurized liquid extraction (SPLE). SPLE methods significantly reduced sample preparation time, solvent requirements, and waste production. Specific examples presented in this dissertation include: 1) the development and application of SPLE methods for the analysis of organic contaminants from sediments and biological tissues; 2) the development and application of a simplified acid digestion method for the analysis of mercury and selenium in rare samples of Pacific walrus (Odobenus rosmarus divergens) muscle (L. dorsi). These examples illustrate the approach for the development of high-throughput sample preparation methods that have successfully combined techniques into a single method, and/or eliminated post-extraction cleanup ...
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