Chronic toxicity of chloride to freshwater species: Effects of hardness and implications for water quality guidelines
Bibliographic record
Abstract
Toxicity tests using nine freshwater species (Ceriodaphnia dubia, Daphnia magna, Oncorhynchus mykiss, Pimephales promelas, Lumbriculus variegatus, Tubifex tubifex, Chironomus dilutus, Hyallela azteca, and Brachionus calyciflorus) were conducted to evaluate their sensitivity to chloride. Acute-to-chronic ratios (ACRs) from these tests indicate the ACR of 7.59 employed by the United States Environmental Protection Agency (U.S. EPA) in deriving its water quality guideline for chloride may be conservative; a revised ACR of 3.50 is presented here. The endpoints used to calculate the ACR included 24-h to 96-h median lethal concentrations (LC50s) for acute tests, and 48-h to 54-d inhibition concentration (ICx) values for growth or reproduction for chronic exposures. Data from the present chronic toxicity tests, and other investigators, were used to propose a water quality guideline for long-term exposure to chloride using a species sensitivity distribution (SSD) approach. The 5th percentile from the SSD was calculated as 307 mg/L and proposed as the water quality guideline. Cladocerans were the most sensitive species in the dataset. Ceriodaphnia dubia was used to evaluate the relationship between water hardness and sensitivity to chloride. A strong relationship was observed and was used to establish a hardness-related equation to modify the proposed water quality guideline on the basis of water hardness, resulting in values ranging from 64 mg/L chloride at 10 mg/L hardness to 388 mg/L chloride at 160 mg/L hardness (as CaCO₃). These data suggest that current water quality guidelines for chloride may be overly conservative in water with moderate-to-high hardness, and may not be sufficiently protective under soft-water conditions.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".