Water Quality Assessment of Urban Canals in Ho Chi Minh City, Vietnam: Effectiveness of Renovation Efforts in Minimizing Pollution
Bibliographic record
Abstract
This research comprehensively assessed the water quality in three urban canals within Ho Chi Minh City (HCMC), Vietnam, representing waterways affected by various pollutants. In Vietnam, the rapid pace of urbanization and industrialization has exerted significant pressure on urban water bodies, turning many canals into repositories for untreated domestic sewage, industrial discharge, and urban runoff. Ho Chi Minh City, as the nation's largest economic hub, has been particularly affected, with urban canals serving both as drainage systems and informal waste disposal sites. These issues have led to severe water quality degradation, impacting aquatic ecosystems and posing health risks to local communities. The study focused on three representative canals: 1. Tham Luong–Ben Cat–Vam Thuat (Vam Thuat), impacted by industrial and domestic wastewater, 2. Kenh Doi–Kenh Te (Kenh Te), influenced by domestic wastewater and waterborne transportation, and 3. Nhieu Loc–Thi Nghe (Nhieu Loc), renovated and has been receiving domestic wastewater. The study employed the extensive water pollution index (WPI) and heavy metal evaluation index (HEI) using fourteen physicochemical parameters and sixteen heavy metals, respectively. Five heavy metals, including manganese (Mn), iron (Fe), arsenic (As), cadmium (Cd), and barium (Ba), exceeded the allowable limits of the National technical regulation on surface water quality (QCVN 08:2023/BTNMT, level A). The WPI values for Vam Thuat, Kenh Te, and Nhieu Loc canals were 4.68–5.56, 1.85–4.48, and 1.87–2.45, respectively, indicating severe pollution. HEI values ranged from 25.59–49.83 (Vam Thuat), 33.62–54.32 (Kenh Te), and 6.05–16.54 (Nhieu Loc), with Vam Thuat and Kenh Te exhibiting high heavy metal pollution, while Nhieu Loc had moderate pollution levels. The study demonstrated that renovation efforts can significantly reduce pollution levels in megacity canals. However, further remediation is necessary to improve water quality in highly impacted canals and ensure compliance with standards for sustainable urban development and public health.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 teacher head, 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".