Biological and Advanced Oxidation Processes for the Treatment of Sulfolane Contaminated Waters
Bibliographic record
Abstract
Sulfolane contamination has increasingly become a major environmental concern around the world. This research builds on past research on sulfolane degradation using a variety of different advanced treatment technologies. Initially, the performance of an integrated technology combining biological activated sludge with advanced oxidation process (AOP) (UVC/H2O2) in sequence was evaluated in a batch reactor resulting in >81% sulfolane degradation in less than 24 h. Evaluation of the impact of biological process on AOP showed sulfolane concentration beyond 30 mg/L and presence of TSS >44 mg/L can negatively impact the UVC/H2O2 efficiency for sulfolane degradation. The application of UVC/H2O2 after biological treatment was an advantage as UVC/H2O2 could perform dual roles of oxidation and disinfection. As aerobic granulation is perceived to be more advanced than activated sludge process, two approaches of forming sulfolane degrading aerobic granules (SDAG) were investigated. The adaptation of pre-grown granules to sulfolane environment required a longer period to form SDAG compared to coaggregation of pre-grown granules with bacterial culture native to sulfolane contaminated site. Scanning electron microscopic images revealed dominant filamentous bacteria on the surface of granules. The stability and settleability of SDAG were also investigated under different environmental conditions. Subsequently, a novel integration of aerobic granulation with UV/H2O2 process in a continuous flow-through operation sequence showed elimination of more than 99.99% of sulfolane in less than 6.3 h of combined retention time. The degradation kinetics of sulfolane were also evaluated and the flow-through system showed generation and maintenance of a healthy aerobic granular system. Additionally, various key factors were also identified that govern residual H2O2 concentration in UV/H2O2 effluents. Finally, a pilot-scale field investigation was conducted using a pressurized ozone treatment system to degrade sulfolane in contaminated groundwaters. A series of batch and continuous flow systems were studied to determine the degradation kinetics and evaluate augmentation of oxidation process with the addition of secondary chemicals with ozone. Groundwater matrix played a crucial role in the efficacy of ozone treatment and intermittently sparged ozone injection was evaluated as a viable option for ozone field applications. Nevertheless, bromate concentrations higher than drinking water guidelines were detected in treated groundwater after ozone treatment and this will need further research.
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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) | 0.001 | 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".