LuminoTox as a tool to monitor contaminants of emerging concern in municipal secondary effluent and their removal during treatment by ozone
Bibliographic record
Abstract
Conventional wastewater treatment plants were not designed to remove contaminants of emerging concern (CECs), and hence these chemicals have been shown to contribute to contamination into the environment, where CECs ultimately exist in the parts per trillion to parts per million concentration range. CECs have been shown to induce toxicity in aquatic life which has led to concern from researchers, governments and more recently the general public. Consequently, there is a pressing need for technologies to remove CECs and their associated toxicity, and for wastewater quality measurement methods to monitor these contaminants. Treatment of wastewater by ozone has been shown to reduce or remove many CECs; while many studies have demonstrated a decrease in the toxicity associated with their removal, some have reported a toxicity increase. This highlights the need to monitor the success of wastewater treatment by ozone using bioassays. The LuminoTox bioassay, which measures photosynthetic inhibition, was proposed as a tool for this application. While the LuminoTox has been used for different types of water analysis, there is limited research on its applicability for wastewater monitoring, and in particular, in municipal secondary effluents (SEs). In this PhD project, the LuminoTox was explored as a tool for the detection of CECs in wastewater and for monitoring the removal of CEC-associated toxicity during treatment by ozone. Two current LuminoTox biosensors were explored: Photosynthetic Enzyme Complexes (PECs), and Stabilized Aqueous Photosynthetic Systems I (SAPS I), as well as a new biosensor, SAPS II. In this PhD, the LuminoTox proved to be a good monitoring tool for toxicity of SEs and demonstrated the ability to detect and distinguish changes in CECs in wastewater mixtures. Furthermore, it proved to be excellent at monitoring wastewater during treatment by ozone. The LuminoTox, however, demonstrated limited CEC sensitivity at environmentally relevant concentrations. The LuminoTox pre-concentration method increased the sensitivity of the LuminoTox into the range applicable to native CECs in SE but further development of the sample preparation method is required prior to implementing the technology for wastewater monitoring.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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".