Effect of Calcium on Moving‐Bed Biofilm Reactor Biofilms
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
The effect of calcium concentration on the biofilm structure, microbiology, and treatment performance was evaluated in a moving-bed biofilm reactor. Three experiments were conducted in replicate laboratory-scale reactors to determine if wastewater calcium is an important variable for the design and optimization of these reactors. Biofilm structural properties, such as thickness, oxygen microprofiles, and the composition of extracellular polymeric substances (EPS) were affected by increasing calcium concentrations. Above a threshold concentration of calcium between 1 and 50 mg/L, biofilms became thicker and denser, with a shift toward increasingly proteinaceous EPS at higher calcium concentrations up to 200 mgCa2+/L. At 300 mgCa2+/L, biofilms were found to become primarily composed of inorganic calcium precipitates. Microbiology was assessed through microscopy, denaturing grade gel electrophoresis, and enumeration of higher organisms. Higher calcium concentrations were found to change the bacterial community and promote the abundant growth of filamentous organisms and various protazoa and metazoan populations. The chemical oxygen demand removal efficiency was improved for reactors at calcium concentrations of 50 mg/L and above. Reactor effluents for the lowest calcium concentration (1 mgCa2+/L) were found to be turbid (>50 NTU), as a result of the detachment of small and poorly settling planktonic biomass, whereas higher concentrations promoted settling of the suspended phase. In general, calcium was found to be an important variable causing significant changes in biofilm structure and reactor function.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 0.010 |
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