Phytoremediation of Soil containing \nMixed Contaminants
Bibliographic record
Abstract
Phytoremediation of Soil containing Mixed Contaminants \n \nRamin Memarian, Ph.D. \nConcordia University, 2012 \n \nThis study investigated the application of surfactants and chelates to enhance the removal of mixed contaminants [Cd (II), Pb (II) and used engine oil] from a sandy soil cultivated with Indian mustard plants. For chelate additives, EDTA (Ethylenediamine tetraacetic acid) was found to be more efficient than EDDS (Ethylenediamine disuccinic acid) in increasing the accumulation of metal contaminants Pb (II) in the plants. EDTA was also more capable of removing the used engine oil through rhizodegradation than EDDS. EDTA caused a sharper decrease in basal soil respiration (BSR) than EDDS, indicating that the former was much more toxic to the microbes. \nFor surfactant additives, the results showed that Triton X-100 and Tween 80 at concentrations higher than their critical micellar concentration enhanced phytostabilization of Pb (II). The application of Tween 80 resulted in an increase in phytoremediation of Pb (II). At the same concentrations, Tween 80 was more effective than Triton X-100 in facilitating rhizodegradation of the used engine oil. Soil basal microbiological respiration tests showed that the application of Tween 80 resulted in an increase in BSR. These tests indicated that the lower concentration of Triton X-100 had a slightly positive effect on BSR, whereas at higher concentrations, it was inhibitory to the microbes. \nEmpirical phytoremediation models linked to the removal of the heavy metals from the soil were formulated in the study. The two first order kinetic models were able to describe the leaching process for both Cd (II) and Pb (II). The models also revealed that the uptake of Pb (II) and Cd (II) were well described by the Freundlich type model, in the presence of surfactants. On the other hand, in the presence of chelates the uptake of Pb (II) and Cd (II) was found to follow the Langmuir type model. According to the leachability index (LI) determined in the tests, all surfactants tested can be considered as safe additives for enhancing phytoremediation. Compared to Triton X-100, Tween 80 resulted in lower diffusivity of metals tested and higher values of LI indicating that this surfactant was also safer from the point of view of reducing ground water pollution. Compared to EDTA, EDDS resulted in higher values of LI, which is desirable.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".