“Eco-friendly” road deicers may not be so friendly: assessing the toxicity of beet-juice brine and potassium chloride to <i>Daphnia pulicaria</i>
Bibliographic record
Abstract
There is increasing concern over rising salinity in freshwater ecosystems, which is often associated with deicing salt usage in temperate regions that experience cold winters. Negative impacts of deicing salts on the environment include changes to aquatic community composition and loss of biodiversity. Consequently, many municipalities are increasing their usage of alternative deicers that are reported to be "eco-friendly" and require lower application rates. One example of an organic alternative is a beet juice and salt brine mixture that contains degraded beet sugar and chloride salts. There is limited research on the effects of these products on aquatic organisms, including zooplankton, which are critical components of freshwater food webs. To address this knowledge gap, we compared the acute toxicities of a beet-brine product (Fusion 2330) with potassium chloride (KCl, >99% pure) and sodium chloride (NaCl, >99% pure), which are components of beet-juice brine, to a single iso-female line of Daphnia pulicaria using 48-hr median lethal concentration (LC50) toxicity tests. We found that Daphnia pulicaria was more tolerant to NaCl and KCl than beet-juice brine with 48-hr LC50 values of 1,812 mg Cl-/L, 254 mg Cl-/L, and 82 mg Cl-/L, respectively. Considering toxicity related to K+, we determined 48-hr LC50 values of 276.7 mg K+/L and 10.3 mg K+/L for KCl and beet-juice brine, respectively. We also found that dissolved oxygen concentration decreased with increasing concentration of the beet-juice brine product, which may contribute to the negative impact of beet-juice brine application. These results suggest that caution should be taken when using organic deicers, as beet-juice brine is more toxic to D. pulicaria than the commonly used rock salt (NaCl).
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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 | 0.000 |
| 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 | 0.001 | 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".