| Summary: | One of the largest abandoned gold mines in the Northern Territories, Canada is Giant Mine, located on the north shore of Yellowknife Bay, 5km north of the Yellowknife City. Operating from 1949 to 1999, Giant Mine produced over 7 million ounces of gold mined from arsenopyrite ore formations. Gold processing entailed roasting the ore at temperatures under 500 degrees Celsius, producing a byproduct arsenic trioxide dust (As2O3). As2O3 is the most bioaccessible form of arsenic species (Plumlee & Morman, 2011) and when dissolved, it releases highly toxic trivalent arsenic ion (As3+) into the surrounding ecosystem. Other intermediate-bioaccessible roaster products include As-bearing maghemite and hematite, which were deposited with tailings and remobilized into creek and lake sediments (Jamieson, 2014). Approximately 20,000 tonnes of arsenic aerosols were released from the roaster stacks and aerially spread into the environment. This, as well as tailings spills, are thought to have contributed to the As-enriched sediments in Yellowknife Bay. Previous work published by Andrade et al (2010) included the sampling of lacustrine sediments, submerged tailings and associated pore waters at several sites in Yellowknife Bay. Based on techniques available at that time, one conclusion was then reached that the solid-phase mid-core arsenic source was identified as roaster-generated maghemite and hematite. This was proposed to be a source for dissolved arsenic to diffuse upwards. In the last 10 years, modern SEM-based quantitative mineralogy tools have advanced rapidly, not only increasing the speed and accuracy of analysis, but also enhancing measurement automation (Fandrich et al., 2007). In SEM-based mineral liberation analysis, thousands of particles are recognized and separated through image analysis in each sample, and the mineral grains within are delineated for discrete X- ray analysis to track variations in the composition of the minerals of interest, accommodated to different measurement modes. The objective of this research is to test whether applying new methods of mineralogical analysis, specifically, SEM-MLA (SEM based mineral liberation analysis technology) to the analysis of sediments from Yellowknife Bay will facilitate a better understanding of the environmental risk associated with this area. In particular, the aim is to determine whether the identification of the arsenic minerals present by SEM-MLA will provide decision makers with useful information on long-term arsenic species’ stability and bioaccessiblity. In my research, Andrade’s samples were revisited at a microscale and Andrade’s conclusion will be reexamined by using this new advanced analytical tool SEM-MLA. SEM-MLA can define mineral hosts and help quantify relative abundances of arsenic hosts in detail, from which arsenic mass distribution can be projected. Through automatic mineralogy at high resolution, the chemical species of arsenic and forms of arsenic in sediments in Yellowknife Bay can be determined, which will help track the remobilization of As-enriched sediments, the process which would potentially harm the community health due to its bioaccessibility, especially vulnerable children, when taken in. At Yellowknife Bay, understanding the forms of arsenic in sediments is critical to assessing the risk to human and ecosystem health, developing an effective remediation plan, predicting long-term stability, and finally, establishing environmental monitoring and optimal management.
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