Bibliographic record
Abstract
This thesis investigates the idluence of sludge retention tirne (SRT) on surface properties and interparticle interactions of sludge flocs, and the role of surface properties and interparticle interactions in bioflocculation, compaction and stability.Four laboratory-scale sequencing batch reactors (SBRs) were operated in parallel at different SRTs (4 to 20 days) for two years.Surface properties of sludge flocs were examined by a number of state-of-the-art techniques, including physicochemical extraction, chemical analyses and ~Itrafiltration of extracellular polymeric substances (EPS), contact angle measurement (hydrophobicity) and colloidal titration (surface charge).Interparticle interactions (electrostatic, ionic interactions and hydrogen bonds) and the stability of sludge flocs at differmt SRTs were evaluated in batch expenments by manipulating the water chemistry of the surrounding solutions.At al1 SRTs, proteins and carbohydrates were the dominant components of EPSI followed by a small amount of DNA.Acidic polysaccharides were not detected in the EPS.Molecular weights of proteins, carbohydrates and DNA in the EPS covered a broad range, fkom less than 1,000 daltons to more than 100,000 daltons.The majority (>85%) of EPS components had molecular weights larger than 10,000 daltons.The total amount of EPS was independent of the SRT.The ratio of proteins to carbohydrates in the EPS, however, increased fiom 1.5 (c0.9) at an SRT of 4 days to 5.1 ( 2 1.5) at an SRT of 12 days, and then reached an almost constant value of 4.5 (I 1.9) at SRTs from 16 to 20 days.A larger arnount of EPS was associated with a higher sIudge volume index (SVI), but no significant correlation was found between the amount of EPS and effluent suspended solids (ESS).Sludge surfaces were more hydrophobic (a higher value of water contact angle) and less negatively charged at higher SRTs (16 and 20 days) than those at lower SRTs (4 and 9 days).The contact angle values were strongly correlated to the surface charge density.A change in the proportion of EPS components provides partial explanations for changes in hydrophobicity and surface charge with respect to the SRT.A higher contact angle and lower surface charge were associated with a lower level of ESS.There was no correlation, however, either between the SV1 and contact angle or between the SV1 and surface charge.Changes in dissociation constants of sludge flocs in batch experiments indicated that electrostatic interactions were involved in disruptinp the stability of sludge flocs, and ionic interactions and hydrogen bonds were present to compensate for the negative influence of electrostatic interactions on the stability of sludge flocs and to keep flocs together.Ionic interactions and hydrogen bonds were two dominant forces that maintained the stability of sludge flocs at lower SRTs: while other mechanisms, such as physicai enmeshment and hydrophobic interactions.were likely more important than ionic interactions and hydrogen bonds in controlling the stability of sludge flocs at higher SRTs.Sludge flocs at higher SRTs (16 and 20 days) were structurally more stable than those at lower SRTs (4 and 9 days).In summary, the results from this study demonstrate that it is possible to operationally and chemically manipulate surface properties and interparticle interactions of sludge flocs for effective floc separation.A transition in floc surface properties \vas found to occur in the SRT range of 9 to 12 days.This transition in floc surface properties was linked to irnproved bioflocculation and a more stable fioc structure.It is the physicochemical properties of sludge flocs, such as hydrophobicity and surface charge, rather than the quantity of EPS, that govem the flocculating ability.In contrast, the total EPS content plays a more important role in determining the compressi bi lity of sludge flocs than hydrophobicity and surface charge.A conceptual mode1 is proposed to describe the floc structure of floc-forming microorganisms at different SRTs.1 am grateful to my supervisors.Prof Steven N. Liss and Prof. D
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.
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) | 0.026 | 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".