Arsenic contamination of the environment is a worldwide health hazard. This research project focused on four areas: development and testing of low cost, field portable devices capable of measuring levels of arsenic at 10 μg L-1 or less; specific chemical techniques for such testing; creation of educational tools and techniques to allow operators who lack advanced chemistry training to perform accurate testing; and the determination and use of a biomarker in DNA as a cancer predictor in individuals exposed to environmental arsenic. The analytical techniques explored include: (1) the Gutzeit method of arsenic determination though arsine gas production, which was investigated in three experiments: measuring arsenic levels in soil samples, using Gutzeit-based kits using silver nitrate as a reactant for arsine gas, and sensitivity comparison of three commercial test kits over varying time periods up to twenty-four hours. (2) The molybdenum blue method, technologically quantified through three different experiments: digital photographic analysis, spectroscopic analysis, and flow injection. (3) Filtration of arsenic contaminated water with wood-ash, sand, ferric oxide, and commercially available steel wool; and the construction of a filtering device constructed of recyclable discarded soda bottles. Further, single nucleotide polymorphisms in the DNA of arsenic exposed individuals were studied to determine what immune response genes might be implicated in arsenic susceptibility. The major conclusions of this research were: digital image analysis used with the Gutzeit method improves precision and accuracy; silver nitrate proved to be a better measurement tool at low concentrations of arsenic than mercuric bromide; and the Gutzeit method can be applied to soils in the Hach kit.
| Identifer | oai:union.ndltd.org:UMASS/oai:scholarworks.umass.edu:open_access_dissertations-1287 |
| Date | 01 September 2010 |
| Creators | Kearns, James Kalman |
| Publisher | ScholarWorks@UMass Amherst |
| Source Sets | University of Massachusetts, Amherst |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Open Access Dissertations |
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