Biodegradation Kinetics of Benzene and Naphthalene in the Vadose and Saturated Zones of a (Semi)-arid Saline Coastal Soil Environment
Bibliographic record
Abstract
Biodegradation is a key process for the remediation of sites contaminated by petroleum hydrocarbons (PHCs), but this process is not well known for the (semi)-arid coastal environments where saline conditions and continuous water level fluctuations are common. This study differs from the limited previous studies on the biodegradation of PHCs in Qatari coastal soils mainly by its findings on the biodegradation kinetics of the selected PHCs of benzene and naphthalene by indigenous bacteria. Soil samples were collected above, across, and below the groundwater table at the eastern coast of Qatar within a depth of 0 to -40 cm. Environmental conditions combining low oxygen and high sulfate concentrations were considered in this study which could favor either or both aerobic and anaerobic bacteria including sulfate-reducing bacteria (SRB). The consideration of SRB was motivated by previously reported high sulfate concentrations in Qatari soil and groundwater. Low- and high-salinity conditions were applied in the experiments, and the results showed the sorption of the two PHCs on the soil samples. Sorption was dominant for naphthalene whereas the biodegradation process contributed the most for the removal of benzene from water. Losses of nitrate observed in the biodegradation experiments were attributed to the activity of nitrate-reducing bacteria (NRB). The results suggested that aerobic, NRB, and most likely SRB biodegraded the two PHCs, where the combined contribution of sorption and biodegradation in biotic microcosms led to considerable concentration losses of the two PHCs in the aqueous phase (31 to 58% after 21 to 35 days). Although benzene was degraded faster than naphthalene, the biodegradation of these two PHCs was in general very slow with rate coefficients in the order of 10-3 to 10-2 day-1 and the applied kinetic models fitted the experimental results very well. It is relevant to mention that these rate coefficients are the contribution from all the microbial groups in the soil and not from just one.
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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".