Biofiltration of dichlorobenzenes
Bibliographic record
Abstract
The use of air biofiltration for the degradation of dichlorobenzenes (1,2-DCB and 1,4-DCB) was studied at a refinery site. At this plant, 93 m3/h of contaminated groundwater, used in a cooling system and containing a maximum of 2 ppm of dichlorobenzenes, had to be treated. Stripping of the DCBs followed by biofiltration was selected as the most suitable technology to avoid volatilization in ambient air as expected with a wastewater aerobic treatment system. A stripper of 15 m height and 1.27 m diameter was designed as a first step treatment to volatilize DCBs with 3400 m3/h of air. Two f ull-scale biofilters of 70 m3 each were built and filled with 45 m3 of filtering media for the adsorption and biodegradation of the DCBs in the gas-phase. Filtering media was composed mainly of peat moss, with animal manure, wood chips and DCBs contaminated soil. Air to be treated was also contaminated with naphthalene. Laboratory tests showed an effective microbial activity in the contaminated soil and in the filtering media for DCBs degradation. Degradation of naphthalene induced slower degradation of DCBs. Full-scale operation was studied during four months. Water flow and DCBs content in the water entering the stripper were lower than expected with only 57 m3/h and a maximum concentration of only 240 ppb. Effective desorption was obtained in the stripper in the full-scale operation (more than 99% removal). Full-scale biofilters maintained a DCB concentration of less than 1 ppmv in the air outlet, but removal efficiency varied between 0 and 79% because of the low DCB inlet concentrations, load variations and sporadic naphthalene presence.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".