Removal of colour from secondary treated whole mill kraft effluent using dead aspergillus niger as a biosorbent
Bibliographic record
Abstract
The pulp and paper industry is widespread in Canada and many other countries. The effluent from this industry is generally highly coloured and typically measures are not taken to prevent or remove this colour due to prohibitory cost and, presently, lack of universal regulation. However, this does not preclude coloured effluents from impacting the public and the environment. Treatment of pulp mill effluent colour has been approached using a number of different treatment technologies, including lime, membrane filtration, oxidants and adsorption. Unfortunately, biological treatment systems commonly employed to treat pulp and paper effluents are not effective in treatment of colour. However, biological treatment using live fungal biomass, generally white rot fungi, has proven to be effective at pulp mill effluent colour removal. Additionally, biosorption treatment using any biological matter in live or dead form, has been successful in the removal of metals, textile dyes and humic acids fiom water. Nonetheless, no research has been reported on the use of dead fungal biomass on pulp mill effluent colour. As such, the present study researches the use of dead Aspergillus niger biomass for the treatment of pulp mill effluent colour. Using a batch test system approach, the present research addressed effluent characterization, pretreatment, effluent pH, biomass washing, mixing, biological inhibition, kinetic rate, isotherm, temperature, molecular weight fraction removed and practical application studies. From these studies it has been determined that autoclave-only pretreatment and initial effluent pH of 4 and 8 provided optimum colour removal. Under biologically inhibited conditions, maximum removal occurred in the first hour of biomass contact with the effluent and the kinetic models by Lagergren (1898) and Ho et al. (1996) roughly described the kinetic rate. The maximum colour removal was over 900 TCU, with a biomass doses in the range of 13-20 g/L. The equilibrium isotherms of the study fit the BET model well, which indicated, with the support of other results of the current study, that this biosorption was predominately due to physical mechanisms. In addition, the application of the biomass in a batch activated sludge process did remove colour.
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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 | 0.000 |
| 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 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".