The role of cyanobacteria in pulp and paper waste-treatment systems
Bibliographic record
Abstract
This study investigated the role of cyanobacteria in pulp and paper secondary waste-treatment systems, focusing on community and physiological characteristics as well as impacts to waste-treatment efficiency. I found cyanobacteria to be important members of the microbial community in geographically dispersed aerated stabilization basin (ASB) and activated sludge (AS) systems. Similar cyanobacterial taxa tended to dominate these communities and in some cases, biomass was equal to or greater than bacterial biomass. Although pulp and paper waste-treatment systems were severely light-limited, shade-adapted cyanobacterial communities were found to fix appreciable amounts of inorganic carbon via photosynthesis. All cyanobacterial species isolated from pulp and paper waste-treatment systems could take up glucose in the light and dark, and a number of representative taxa could grow mixotrophically. None of the cyanobacterial isolates were capable of mineralizing appreciable amounts of pulp and paper contaminants. Further studies using whole effluent from three mills showed that the softwood-based wastewaters had decreased removal of toxicity with increased cyanobacterial biomass. In contrast, the hardwood-based wastewater had increased removal of toxicity when cyanobacterial biomass increased. Cyanobacteria and their extracellular organic compounds (EOC) were shown to inhibit or stimulate bacterial degradation of organic contaminants (phenol and dichloroacetate), depending on the cyanobacterial and bacterial species. These variable impacts of cyanobacteria on toxicity removal and biodegradation efficiency suggest a complex, but important role during the biological treatment of pulp and paper wastewater.
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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".