Integrated assessment of wastewater treatment plants and their receiving river systems in a global change context
Bibliographic record
Abstract
For a long time, there has been a need and an ambition to better understand the behavior of integrated systems by considering the whole urban water cycle, including wastewater transportation, wastewater treatment and the receiving water. On the other hand, fragmented environmental policies on wastewater sanitation, global change, and emerging contaminants are increasingly threatening freshwater ecosystems and human health. Within this context, this thesis embeds a series of research studies aiming to improve our comprehension of the functioning of urban wastewater systems (UWWS), considering both natural and artificial elements, and with a special emphasis on the occurrence of global change and on the fate of emerging contaminants. In the thesis, an integrated model for a UWWS in NE Iberian Peninsula has been developed and calibrated using data from an intensive and integrated survey, not only combining early developed mathematical models for the different sub-processes, but also verifying the model parameters with full-scale and dynamical measurements. More specifically, the work developed in this thesis was divided into three parts. First, we investigated how an UWWS perform together in the removal of conventional contaminants and evaluated the impact of future global change scenarios. Second, we investigated the occurrence and fate of pharmaceuticals and their transformation products in the UWWS. Finally, and as a continuation of the second work, we assessed the influence of the sampling strategy when estimating the loads and attenuation of emerging contaminants in UWWS under different scenarios differing from sampling strategies, consumption, and degradability of the compound under analysis. Overall, this thesis highlights the need for integrated approaches to better understand the performance of WWTPs and their receiving rivers, against the increase of micro-contaminants occurrence and the effects of global change
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".