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Record W2016220637 · doi:10.4081/xeno.2012.e3

Low removal of acidic and hydrophilic pharmaceutical products by various types of municipal wastewater treatment plants

2012· article· en· W2016220637 on OpenAlex
Christian Gagnon, André Lajeunesse

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Xenobiotics · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicPharmaceutical and Antibiotic Environmental Impacts
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsClofibric acidEffluentChemistryIbuprofenNaproxenWastewaterSewage treatmentActivated sludgeDiclofenacAquatic environmentEnvironmental chemistryCarbamazepineChromatographyPharmacologyEnvironmental engineeringBiochemistryBiologyEnvironmental science

Abstract

fetched live from OpenAlex

Pharmaceutical substances represent a risk for aquatic environments and their potential impacts on the receiving environment are poorly understood. Municipal effluents are important sources of contaminants including common pharmaceuticals like anti-inflammatory and anti-convulsive substances. The removal of pharmaceuticals, particularly those highly soluble can represent a great challenge to conventional wastewater treatment processes. Hydrophilic drugs (<em>e.g.</em> acidic drugs) have properties that can highly influence removal efficiencies of treatment plants. The performance of different wastewater treatment processes for the removal of specific pharmaceutical products that are expected to be poorly removed was investigated. The obtained results were compared to inherent properties of the studied substances. Clofibric acid, carbamazepine, diclofenac, ibuprofen and naproxen were largely found in physicochemical primary-treated effluents at concentrations ranging from 77 to 2384 ng/L. This treatment type showed removal yields lower than 30%. On the other hand, biological treatments with activated sludge under aerobic conditions resulted in much better removal rates (>50% for 5 of the 8 studied substances). Interestingly, this latter type of process showed evidence of selectivity with respect to the size (R2=0.7388), solubility (R2=0.6812), and partitioning (R2=0.9999) of the removed substances; the smallest and least sorbed substances seemed to be removed at better rates, while the persistent carbamazepine (392 ng/L) and diclofenac (66 ng/L) were poorly removed (<10%) after biological treatment. In the case of treatment by aerated lagoons, the most abundant substances were the highly soluble hydroxy-ibuprofen (350-3321 ng/L), followed by naproxen (42-413 n/L) and carbamazepine (254-386 ng/L). In order to assess the impacts of all these contaminants of various properties on the environment and human health, we need to better understand the chemical and physical transformations occurring at the treatment plant and in the receiving waters.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.451

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.028
GPT teacher head0.284
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it