Pilot-scale comparison of sodium silicates, orthophosphate and pH adjustment to reduce lead release from lead service lines
Bibliographic record
Abstract
Sodium silicate is thought to mitigate lead release via two mechanisms: by increasing pH and by forming a protective silica film. A pilot-scale study using an excavated lead service line (LSL) fed with water from a Great Lakes source was undertaken to: (1) clearly distinguish the pH effect and the silica effect; (2) compare sodium silicate to orthophosphate and pH adjustment; (3) determine the nature of silica accumulation in the pipe scale. The LSL was cut into segments and acclimated with water at pH 7.1. Median dissolved lead was 197 µg/L in the last 8 weeks of acclimation and dropped to 16 µg/L, 54 µg/L, and 85 µg/L following treatment with orthophosphate (dose: 2.6 mg-PO4/L, pH: 7.9), pH adjustment (pH: 7.9) and sodium silicate (dose: 20 mg-SiO2/L, pH: 7.9), respectively. When silica dose was increased from 20 mg-SiO2/L to 25 mg-SiO2/L (pH: 8.1), lead release destabilized and increased (median dissolved lead: 141 µg/L) due to formation of colloidal dispersions composed mainly of lead- and aluminum-rich phases as detected by field flow fractionation used with inductively coupled plasma mass spectrometry. Si was present in the scale at a maximum of 2.2 atomic % after 17 weeks of silica dosing at 20 mg- SiO2/L. Under the conditions tested, sodium silicate did not offer any benefits for reducing lead release from this LSL other than increasing pH. However, sodium silicate resulted in lower levels of biofilm accumulation on pipe walls, as measured by heterotrophic plate counts, when compared to orthophosphate.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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; both teacher heads agree on what is shown here.
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".