Active and passive sampling techniques in headwater streams to characterize acesulfame-K, pharmaceutical and phosphorus contamination from on-site wastewater disposal systems in Canadian rural hamlets
Bibliographic record
Abstract
On-site wastewater disposal systems have been identified as a source of contamination for nutrients and emerging contaminants (ECs), such as artificial sweeteners and pharmaceutical compounds. The passive sampling technique Polar Organic Chemical Integrative Sampler (POCIS) and phosphorus sampler (P-Trap) have been widely used for tracking polar organic contaminants and total dissolved phosphorus in environmental waters such as surface water and wastewater. However, limited studies have been conducted on application of passive sampling techniques to track contamination in headwater streams impacted by on-site wastewater disposal systems. In this study, active sampling (discrete samples) and passive sampling (P-Trap and POCIS) techniques were applied in upstream and downstream locations at three rural hamlets to compare and track the contamination of total dissolved phosphorus (TDP) and seven ECs, including six pharmaceuticals and one artificial sweetener acesulfame-K (ACE-K), in the shallow headwater streams of rural hamlets in southern Ontario, Canada that exclusively rely on septic systems for wastewater disposal. Results show that POCIS and P-Trap yielded comparable time-weighted average (TWA) concentrations of target ECs and TDP, respectively, to mean concentrations of discrete samples during the seasonal (spring, summer, and fall) and two-week intensive study periods. Field-derived sampling rates ( R s - field ) of target contaminants compared well to literature-reported values indicating POCIS and P-Trap were applicable in determining the concentrations of target contaminants in the investigated streams, even though some environmental factors, such as dry stream conditions and fouling, occurred during the sampling period. The low but stable R s - field of ACE-K (∼0.001 L d −1 ) from this study indicates consistency in application of POCIS for capturing ACE-K. The results of this study provide insight into the confidence and limitations for using POCIS and P-traps to track ECs and TDP in shallow headwater streams impacted by septic systems. • Discrete and passive sampling showed target pollutants downstream of septic systems. • Good agreement between discrete and passive sampling results for target pollutants • Field-derived R s values determined for ACE-K and six pharmaceuticals • Environmental factors, such as biofouling can affect uptake on passive samplers. • POCIS with HLB sorbents is applicable to sample ACE-K with low but stable R s .
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".