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Record W7042417563

Passive sampling to understand and predict sources of wastewater and agricultural contamination in rural watersheds

2023· dissertation· en· W7042417563 on OpenAlexfundno aff

Bibliographic record

VenueUWSpace (University of Waterloo) · 2023
Typedissertation
Languageen
FieldComputer Science
TopicDomain Adaptation and Few-Shot Learning
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaMinistère de l’Environnement, de la Protection de la nature et des ParcsUniversity of WaterlooMinistry of Environment
KeywordsPassive samplingSampling (signal processing)SucraloseSTREAMSRange (aeronautics)WastewaterContaminationSurface water
DOInot available

Abstract

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Passive sampling techniques have emerged as valuable tools in environmental monitoring, offering distinct advantages over traditional discrete sampling methods. Discrete sampling techniques are only representative of the time of sampling, often over or underestimating concentrations of constituents in flowing surface waters. Passive samplers contain a collecting medium which accumulates and concentrates constituents to a higher level of detection, and reduces variability associated with discrete sampling. To identify and differentiate non-point sources in rural catchments, this study used passive samplers, including the diffusive gradient in thin-films (DGT) and polar organic chemical integrative sampler (POCIS), along with discrete sampling to detect a range of anthropogenic and agricultural tracers and nutrients. 
\nPassive samplers were deployed for select compounds including nutrients (PO4-P, NO3-N, NH4-N), anthropogenic tracers (caffeine, carbamazepine, gemfibrozil, ibuprofen, naproxen, sulfamethoxazole, acesulfame potassium, sucralose), and agricultural tracers (glyphosate, aminomethylphosphonic acid (AMPA)). Among the passive samplers deployed, the Metsorb®-DGT, selective for phosphate-bearing compounds, was evaluated for competition impacts between PO4-P and glyphosate. Competition between analytes can occur for sorbents selective for a range of compounds with similar properties. A new sampler using a weak anion exchange (WAX) resin was developed for the uptake of artificial sweeteners acesulfame potassium (ACE-K) and sucralose (SUC).
\nPassive samplers were deployed at three distinct locations (Hamlet, Agricultural, and Mixed-land Sites), for 3 to 14 days, while discrete samples were collected every 3 days over 2 weeks in Fall of 2021 and Spring of 2022. The effect of potentially competing ions between phosphate-bearing compounds was evaluated by deploying triplicate Metsorb®-DGT sampler in a solution of high PO4-P and low glyphosate and AMPA. Strata-DGT samplers were developed as a potential sampler for the uptake of ACE-K and SUC and deployed in the Spring 2022 sampling event. The goals of this thesis were to (1) use DGT and POCIS to delineate anthropogenic contamination from agricultural activities to surface waters in rural communities, and to compare their effectiveness to discrete samples and (2) further develop and evaluate DGT samplers.
\nDGT and POCIS had comparable concentrations with 64% of compounds not statistically different (ρ > 0.05) from discrete samples. Diffusive boundary layer (DBL) corrections were applied to Spring 2022 DGT samples, increasing the mean absolute error between DGT concentrations (CDGT) and discrete concentrations (CACTIVE) by 32% for all compounds. Phosphate was elevated at the Hamlet Site (74 ± 8.2 µg L-1) in discrete samples compared to the Agriculture Site during the Fall 2021 sampling season. The Hamlet Site land use was 40% urban and 60% agriculture, while the Agriculture and Mixed-land Sites were 94% and 88% agricultural land use, respectively. Tracers consistently showed elevated concentrations of ACE-K (412 ± 202 µg L-1) and SUC (17,089 ± 5370 µg L-1) in discrete samples across both sampling seasons as well as all other anthropogenic tracers at the Hamlet Site, while glyphosate and AMPA were elevated at the Agriculture Site (0.86 ± 1.66 µg L-1 and 1.41 ± 0.85 µg L-1, respectively). Principal component analysis (PCA) and correlation coefficients indicated a positive relationship between phosphate and anthropogenic tracers at the Hamlet Site. Biological markers (Human-specific Bacteroides), specific to human fecal contamination, were also elevated at the Hamlet Site compared to the other sites. The results of this study clearly show septic system contamination in a headwater stream and suggest impacts of septic systems to these surface water bodies may be an underappreciated nonpoint source of nutrients. 
\nThere was no apparent competition on the Metsorb®-DGT sampler at initial concentrations of 104 µg L-1 of PO4-P, 0.372 µg L-1 of glyphosate, and 2.14 µg L-1 of AMPA as uptake was mostly linear after 6 days of deployment. Strata X-AW resin was not a suitable binding medium for artificial sweeteners, resulting in concentrations only 39% of discrete samples for ACE-K at the Hamlet Site. 
\nOverall, an array of passive samplers was helpful to distinguish nonpoint sources of septic system from agricultural contamination in rural head-water streams. Passive samplers generally showed comparable results to discrete samples, with the exception of ACE-K, and reduced the variability and additional sampling and analysis associated with discrete sample collection.

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How this classification was reachedexpand

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.276
Threshold uncertainty score0.640

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 studies0.0000.000
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 head0.014
GPT teacher head0.207
Teacher spread0.193 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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