Potential of water hyacinth for phytoremediation in low temperature environment
Bibliographic record
Abstract
Water hyacinth, i.e., Eichhornia crassipes Solms can remove a large variety of different pollutants from water and are considered an excellent candidate for phytoremediation of contaminated waters. Nevertheless, exploitation of water hyacinth for phytoremediation has so far been limited to tropical or subtropical regions. In this study, the influence of temperature on the morphology, growth, and nutrient removal of water hyacinths was studied in a relatively low temperature range, 12–25°C, in the form of three night/day temperature cycles, i.e., 12/15°C, 15/20°C, and 15/25°C. It was shown that water hyacinth is very sensitive to temperature in the tested range and 15/25°C is the most favorable condition among the tested. A biomass productivity of 10.7 tons DW/ha/yr, total nitrogen removal rate of 400 kg N/ha/yr and total phosphorous removal rate of 65 kg P/ha/yr were estimated according to the experimental results on the basis of five operational months per year. No visible morphological changes were observed when the plants were cultivated at 15/20°C or 15/25°C but significant morphological changes were observed when the plants were transferred from a rooftop greenhouse to a growth chamber controlled at 12/15°C with plant size shrinking significantly. Nevertheless, substantial plant growth and nutrient removal were observed at 12/15°C, although with a prolonged adaptation phase of 2 weeks. Results of this research suggest good potential of water hyacinths for water phytoremediation in relatively cold regions such as Canada. © 2013 American Institute of Chemical Engineers Environ Prog, 32: 976–981, 2013
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".