Impact of Corrosion Control on Biofilm Development in Simulated Partial Lead Service Line Replacements
Bibliographic record
Abstract
Interaction of water quality, flow conditions, and the presence of lead and biofilm was examined in simulated partial lead service line replacement. Recirculating pipe loops were connected to individual 90-L reservoirs, and biofilm was collected from polycarbonate coupons. Three corrosion inhibitors, including sodium orthophosphate (OP) (1 mg-P/L), zinc orthophosphate (ZOP) (1 mg-P/L), or sodium silicate (10 mg/L), were used to treat Pb-Cu pipe loops. Controls included an “inhibitor-free,” “galvanic free,” and “lead-free” with Pb-Cu, Pb-PVC, and PVC-PVC coupled pipe loops, respectively. Adenosine triphosphate (ATP) was used to measure energy production of living cells and as a proxy to assess biofilm growth. The two highest (significant) ATP counts were found in the OP (under stagnant conditions) and ZOP (under flow-through conditions). Sodium silicates generally produced lower ATP counts compared to the phosphate-based inhibitors in the flow-through condition, although these differences were not statistically significant. Significant positive correlation between presence of lead and biofilm (ATP) and presence of copper and biofilm (ATP) were observed, although this observation does not imply a linear relationship. Biofilm was observed to act as a significant reservoir for lead with values ranging from 0.06 to 0.81 μg Pb/cm2 before chlorination to 0.04 to 0.21 μg Pb/cm2 postchlorination. This work highlights the potential for biofilm to act as a reservoir and subsequently as a source of lead release, and underscores the value of including biofilm evaluation when selecting corrosion inhibitors.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".