Arsenic is the only contaminant for which exposure through drinking water has been proven to cause cancer in humans. The US Environmental Protection Agency has concluded that the present drinking water limit of 50 ug/L arsenic is not sufficiently protective and proposes a new limit of 10 ug/L. In most cases, the arsenic originates in the geologic materials of the aquifer. While correlations with bedrock types have been made, the factors that affect arsenic concentrations and speciation in drinking water are poorly understood. As(III), the reduced inorganic form, is more mobile and more toxic than As(V), thus speciation affects both the concentration and the health implications of arsenic exposure. Microorganisms probably affect As concentrations in groundwater, but the magnitude and nature of their participation in the arsenic cycle have not yet been clarified. Microorganisms can affect the chemistry of arsenic compounds in a number of ways. Laboratory and field studies as proposed in this program will build on the PI\u27s preliminary data that indicate the presence of arsenate reducing microorganisms in well water to determine how microbial activities affect soluble arsenic concentrations. This information will be used to create a conceptual model of the processes that affect As in groundwater. Molecular probes will be developed to determine the importance of the isolated arsenate-degrading microorganisms in situ. Existing geological data and field data gathered by high school and undergraduate students will be used to assess whether or not the model derived from laboratory experiments is supported by field observations. Since the project requires an interdisciplinary approach, links with microbial ecologists and environmental microbiologists will be strengthened to support the investigator\u27s research goals. The research results will form the basis of new modules in two undergraduate environmental engineering courses. An outreach program for high school students will also contribute to the collection of field data
