Remediation of Leachate-Metal-Contaminated Soil Using Selected Bacterial Consortia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Approximately 95% of urban solid waste worldwide is disposed of in landfills. About 14 million metric tonnes of this municipal solid waste are disposed of in landfills every year in Malaysia, illustrating the importance of landfills. Landfill leachate is a liquid that is generated when precipitation percolates through waste disposed of in a landfill. High concentrations of heavy metal(loid)s, organic matter that has been dissolved and/or suspended, and inorganic substances, including phosphorus, ammonium, and sulphate, are present in landfill leachate. Globally, there is an urgent need for efficient remediation strategies for leachate-metal-contaminated soils. The present study expatiates on the physicochemical conditions and heavy metal(loid)s’ concentrations present in leachate samples obtained from four landfills in Malaysia, namely, Air Hitam Sanitary Landfill, Jeram Sanitary landfill, Bukit Beruntung landfill, and Taman Beringin Landfill, and explores bioaugmentation for the remediation of leachate-metal-contaminated soil. Leachate samples (replicates) were taken from all four landfills. Heavy metal(loids) in the collected leachate samples were quantified using inductively coupled plasma mass spectrometry. The microbial strains used for bioaugmentation were isolated from the soil sample collected from Taman Beringin Landfill. X-ray fluorescence spectrometry was used to analyze heavy metal(loid)s in the soil, prior to the isolation of microbes. The results of the present study show that the treatments inoculated with the isolated bacteria had greater potential for bioremediation than the control experiment. Of the nine isolated microbial strains, the treatment regimen involving only three strains (all Gram-positive bacteria) exhibited the highest removal efficiency for heavy metal(loid)s, as observed from most of the results. With regard to new findings, a significant outcome from the present study is that selectively blended microbial species are more effective in the remediation of leachate-metal-contaminated soil, in comparison to a treatment containing a higher number of microbial species and therefore increased diversity. Although the leachate and soil samples were collected from Malaysia, there is a global appeal for the bioremediation strategy applied in this study.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it