Bibliographic record
Abstract
As a typical type of Low Impact Development technologies, green roofs have become widely used recently to restore the changes in stormwater runoff resulted from urbanization. To present, many studies have showcased their benefits in managing stormwater in particularly in the mild and temperate climatic zones. However, studies in other climatic zones (e.g., semi-arid and cold climate) are still lacking for their implementation with confidence. Additionally, acknowledging that green roofs might leach pollutants especially at their early ages, knowledge and understanding of this technology in this aspect is still very limited. Therefore, this dissertation aimed to filling these research gaps through conducting both the field observation and the laboratory experiment. The investigated field green roof situated in the City of Calgary, Alberta and the laboratory cells constructed using three media types leached several pollutant constituents including nutrients and conductivity during the study period; while the field green roof behaved as the sink of metals. Antecedent moisture condition and media type were identified to be the most influential factors on green roof hydrological and water quality performance, respectively. The degree of the chemical leaching declined exponentially with cumulative inflow initially, and then linearly later. The high explanatory ability of the cumulative inflow implied that the primary source of the pollutant constituents leached was the media of green roofs, namely the pollutants in media gradually leached out/washed off from green roofs. Based upon this notion, a semi-physically based leaching model was proposed. In this model, the maximum pollutant amount was determined according to its initial content in media, and its leaching was expressed as the wash-off function applied in stormwater runoff quality modeling. The model application further confirmed the primary source and the governing process of chemical leaching from green roofs. However, the modeling results also revealed the need to further improve the phosphorus leaching modeling, especially for the field green roof, as it appeared to be also affected by other chemical and biological processes besides the wash-off process. The identified differences between the laboratory and field observations called attention when translating knowledge from the laboratory investigation into real practice.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".