Assessing the Phytoextraction of Organic and Inorganic Pollutants From Point Pelee National Park, Ontario and Iqaluit, Nunavut
Bibliographic record
Abstract
This thesis investigated the phytoextraction of both organic and inorganic contaminants from two locations of Canada (Point Pelee National Park (PPNP), Ontario and Iqaluit, Nunavut). PPNP is a National Park that is highly contaminated with dichlorodiphenyltrichloroethane (DDT), dieldrin, arsenic and lead from historical agricultural and residential pesticide applications. Six planted native grass and weed species, and several naturally occuring species were analyzed for DDT, dieldrin, arsenic and lead in four contaminated plots of PPNP. A composting study was also completed to determine if composting of contaminated plant material is an effective and sustainable option for handling contaminated plant biomass. Of all plant species studied in PPNP, Andropogon gerardii (big bluestem) was deemed to have the most potential for phytoextraction because it had a large biomass and accumulated high amounts of all four contaminants of interest. For this reason, it was selected for a follow-up greenhouse study. Two seed sources of A. gerardii (one commercial and one collected from PNPP) were grown in PPNP soil contaminated with DDT concentrations of 1,059 ng/g (low) and 5,071 ng/g (high). Mean levels of DDT in plant shoots were significantly higher (100.64 ± 33.09 ng/g) in the high contaminated soil but did not statistically differ in dieldrin, arsenic and lead concentrations between soil types. Seed source had no effect on phytoextraction potential. Mercury (Hg) concentrations within the Canadian Arctic are a current area of concern and research on merucry accumulation in terrestrial vegetation of the Arctic remains limited. Mercury levels in 24 soil samples, 23 plant, five lichen, and eight fungal (mushroom) species were assessed from eight locations in and around Iqaluit. Soil mercury levels across locations were not statistically different; however, median mercury concentrations of plant, lichen and fungi species ranged from 0.005 µg/g Hg dw in Saxifraga cernua (nodding saxifrage) to 1.6 µg/g in Lycoperdon perlatum (puffball). Overall, this thesis contributes new information on pesticide and metal phytoremediation in PPNP, demonstrating that phytoextraction by A. gerardii may be a suitable option to remediate contaminated soils in this National Park, and that phytoextraction by some Canadian Arctic vegetation may lead to elevated mercury concentrations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".