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Record W7161942304 · doi:10.82308/44744

Street tree pits as bioretention units: analysis of their performance in a residential area of Montreal, Canada

2019· dissertation· en· W7161942304 on OpenAlexaboutno aff
Marcelo Frosi

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsnot available
Fundersnot available
KeywordsBioretentionStormwaterSurface runoffHydrology (agriculture)Infiltration (HVAC)Water qualityFlux (metallurgy)Urban runoffContamination

Abstract

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Urbanization, increased surface impermeability, and climate change have resulted in changes in the quantity, intensity and quality of urban stormwater runoff. Urban stormwater runoff has ecological impacts. Generally, these impacts are related to the total and peak flow volumes, and the presence of contaminants in runoff. Low impact development (LID) techniques are emerging as alternatives to traditional stormwater management systems to mitigate these impacts. One such technique is to combine soil, plants and infrastructure in a bioretention unit. This technique involves the use of multiple smaller units spread across an area; street tree pits may be suitable as bioretention units.The objective of this research was to analyze different designs of newly developed tree pits as bioretention units in the city of Montreal. These tree pits soil comprise the soil of the open part, where trees are planted, and the soil underneath the sidewalk. The two design factors were soil organic matter (SOM) content, and the permeability of the surrounding area (sidewalks and front lawns). A total of 24 tree pits were used in this study. The concentrations of trace metals and sodium were analyzed in soil solution and soil matrix. Using the estimated water flux mass flux of each contaminants was calculated. The mean contaminant concentration increased from the surface to the deep sampling depths (e.g. 46% for Ni, and 18% for Cu) but taking into account the accompanying decrease in water volumes, mass flux of contaminants decreased with the increase in depth (e.g. 72% for Ni, and 81% for Cu). In addition, tree pits with higher SOM content presented a higher reduction of mass flux of contaminants than tree pits with lower SOM content between surface and deep sampling depths. For example, tree pits with higher SOM content reduced the mass flux of Cr and Cu by 65%, and 86%, respectively, while tree pits with lower SOM content reduced the mass flux of Cr and Cu by 39% and 73% respectively.Tree pits with higher SOM content presented higher concentrations of Cr, Cu and Pb in the soil matrix. For instance, in the soil matrix of tree pits with higher SOM, Cr and Cu concentrations were 19.9 mg kg-1 and 15.3 mg kg-1, respectively, but were 17.4 mg kg-1 and 13.5 mg kg-1, respectively, in tree pits with lower SOM. This corroborates the observed effect on mass flux of Cr and Cu. In addition, an overall increase of contaminants was observed over time. For example, the concentration in soil of Cr increased from 15.9 mg kg-1 to 20.0 mg kg-1 and of Ni from 11.9 mg kg-1 to 14.4 mg kg-1 representing increases of 26% and 21% after about 18 months of monitoring. The soil matrix contained approximately one third of the maximum permitted concentration of contaminants stipulated by the Canadian Council of Ministers of the Environment for Cr and Ni in residential and park areas. High local permeability and high SOM bioretention units are recommended to mitigate the adverse effects of urbanization on runoff quality and quantity. In this study, tree pits with higher SOM retained contaminants better for all contaminants analyzed (except Pb). The increase in permeability of surrounding surfaces decreased the observed flux of water as well as the mass flux of contaminants observed in the open part of the tree pit. The reduced flux of water in the open part of the tree pit was likely a result of increased infiltration into the soil of the lawn and through the permeable sidewalk. The soil underneath the sidewalk is the same as, and contiguous with, the open area of the tree pit so it is designed to retain runoff contaminants. In this study, higher local permeability and higher SOM were both generally correlated with lower mass flux of contaminants and water. Tree pits can be used as bioretention units having their performance improved by increasing SOM and local permeability.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.131

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.010
GPT teacher head0.199
Teacher spread0.189 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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