Investigating the possibility of PCCP mortar coating leaching and the impact on drinking water quality
Bibliographic record
Abstract
Abstract The objective of this article was to investigate the potential for the dissolution and leaching of certain chemical elements from the protective mortar coatings of prestressed concrete cylinder pipe (PCCP) into drinking water in the event of leakage and how this might affect the overall quality of the water delivered to consumers. The mortars as linings are also typically used for renovation of old pipes. Samples from three frequently used mortar coating mixtures underwent immersion in water after 28 days of curing and were monitored for 430 days. The water was tested for pH levels and the presence of aluminum, chromium, lead, and iron, in accordance with the standards set for human consumption in Moroccan and other countries such as Australia, Canada, and the United States, as well as organizations such as the European Union and World Health Organization. The results indicate that the highest levels of aluminum, iron, chromium, and lead leaching occurred after the initial contact with water, gradually declining over time. Furthermore, the inclusion of silica fume and fly ash in the coating increases the potential for chemical element leaching. Additionally, preinstallation pipeline washing demonstrates its effectiveness in reducing the leaching of chemical elements into drinking water in the event of leakages. The overall results suggest that the likelihood of contamination of drinking water by leaching of chemical elements from the mortar coating in case of a leakage appears to be negligible under the studied conditions.
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 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) | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".