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Record W4387186387 · doi:10.26434/chemrxiv-2023-rbr9x

Compound specific isotope analysis to evaluate in situ transformation of a complex mixture of substituted chlorobenzenes in a pilot constructed wetland system

2023· preprint· en· W4387186387 on OpenAlexafffund
Shamsunnahar Suchana, Line Lomheim, Elizabeth A. Edwards, Paola Barreto Quintero, E. Erin Mack, Silvia Mancini, Elodie Passeport

Bibliographic record

VenueChemRxiv · 2023
Typepreprint
Languageen
FieldEnvironmental Science
TopicConstructed Wetlands for Wastewater Treatment
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Toronto
KeywordsEnvironmental chemistryConstructed wetlandIsotope analysisChemistryWetlandIsotope fractionationBiogeochemical cycleSurface waterPhragmitesEnvironmental scienceFractionationEnvironmental engineeringSewage treatmentEcologyChromatographyBiology

Abstract

fetched live from OpenAlex

Constructed wetlands can be a suitable remediation technique for the treatment of industrial contaminants via transfer (i.e., non-destructive) and transformation (i.e., destructive) processes. Providing direct evidence of in situ transformation using concentrations and biogeochemical parameters alone is challenging. Compound specific isotope analysis (CSIA) is a widely used tool to assess in situ transformation of contaminants based on changes in their stable isotope signatures. In this work, we evaluated the potential of CSIA to identify and possibly quantify the in situ transformation of six NO2- and NH2-chlorobenzenes in complex aqueous samples from a pilot constructed wetland system. No significant changes in δ13C, i.e., ≤2‰ were observed for any of the target compounds despite the contaminant concentration decreased by more than 99% between the inlet and outlet of the system. Using multi-element CSIA of carbon, hydrogen, and nitrogen and laboratory-derived isotope enrichment factors, we successfully identified and quantified the extent of in situ transformation of 2,3-dichloroaniline (2,3-DCA) in the pilot constructed wetlands. The isotopic trends provide evidence for aerobic biotransformation as a dominant pathway in the surface flow planted wetlands; whereas sorption was identified as the likely process in planted and unplanted upflow gravel bed wetlands during the initial wetland operation periods. Another major contaminant from the NO2-chlorobenzene group, i.e., 2-chloronitrobenzene (2-CNB), showed negligible δ13C, and small δ2H (±20‰) and δ15N (±2‰) isotope fractionation. No laboratory-controlled CSIA studies are yet available for 2-CNB biotransformation to characterize transfer and transformation processes. This study highlights the applicability of CSIA as a quantitative tool for 2,3-DCA in dynamic environmental conditions of wetlands and the need for pathway-specific isotope enrichment factors for the successful CSIA application of other target compounds.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.255
Teacher spread0.218 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2023
Admission routes2
Has abstractyes

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