Dynamics of trace metals and de-icing salt in compost-amended urban soils
Bibliographic record
Abstract
A collaborative study between McGill University and the City of Montreal sought to design an improved soil mixture in order to promote street tree health and improve urban runoff water quality. A preliminary chemical analysis was done on 73 tree pit soil samples selected based on land use category, soil age, and soil organic matter. Significantly higher concentrations of Cu, Zn, Cd, and Pb were observed in soils from commercial (vs. residential) streets, possibly as a result of the heavier traffic on commercial streets. A coefficient of variation exceeding one for Na levels in tree pit soils of commercial zones is likely linked to the application of de-icing salt on the street. An analysis of plant nutrients (Ca, Mg, K, P, and total mineral N, including NH4+ and NO3-) in tree pit soils showed no deficiencies as compared to the recommended concentration of available nutrients in horticultural soils. The use of wood chips as tree pit cover material and soil age had significant effects on K, P, and N availability. Street width and soil pH were positively correlated with Na availability in tree pit soil, possibly due to the heavier traffic on wider streets splashing more de-icing salt into the tree pits, and the consequent displacement of H+ by Na+ in the tree pit soil. An investigation was conducted into the efficiency of biochar and compost in immobilizing potentially toxic metals in tree pit soils in the presence of de-icing salt. Using a central composite rotatable design, the soil used by the City of Montreal when transplanting nursery trees to sidewalk tree pits was amended with nine different combinations of compost (0-15% w/w) and biochar (0-10% w/w). The sorption and desorption of Na, Cu, Zn, Cd, and Pb were then evaluated for the different soil mixtures. The two amendments showed different abilities to immobilize potentially toxic metals in the tree pit soil impacted by de-icing salt. The soil amended with 7.5% compost indicated the best sorption and retention of Zn and Pb. The positive effect of compost on metal sorption and retention may be attributed to its high cation exchange capacity and its positive effect on soil pH. For Na, Cu, and Cd, soil alone appeared to be the best adsorbent. The biochar used in this study did not improve the ability of the soils to retain contaminants. Following the sorption and desorption tests, a phytotoxicity trial was conducted to evaluate metal bioavailability in the soil mixtures including 0, 5, or 10% (w/w) of compost. Soil mixtures, spiked with known concentrations (control, medium and high levels) of Na, Cu, Zn, Cd and Pb, were used in a 14-day growth trial of barley (Hordeum vulgare L.). Based on emergence, growth, and the measured concentrations of potentially toxic metals in the roots and shoots of the barley plants, compost-amended soils showed less Cu, Zn, Cd, and Pb absorption by barley plants than non-amended soil. This was probably attributable to the specific complexation of the metals and the provision of macronutrients such as Ca2+ and Mg2+ by the compost. These macronutrients possibly compete with trace metals for absorption by plants. Amendment with compost also decreased Na and Cd absorption by barley plants, likely through an indirect process involving its effects on CEC and pH. The amendment of soil with compost also increased Ca, Mg, K, and P availability. However, compost did not have a significant effect on NH4+ and NO3- availability for the barley plants.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".