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Record W2184427682 · doi:10.82308/13979

Concept of copper mobility and compatibility with lead and cadmium in landfill liners

2003· dissertation· en· W2184427682 on OpenAlexfundno aff
Saleh Kaoser

Bibliographic record

VenueeScholarship@McGill (McGill) · 2003
Typedissertation
Languageen
FieldEnvironmental Science
TopicLandfill Environmental Impact Studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLeachateBentoniteCadmiumAdsorptionCopperChemistryLeaching (pedology)Environmental chemistryGeosynthetic clay linerMetalCompatibility (geochemistry)GroundwaterEnvironmental scienceHydraulic conductivityEnvironmental engineeringGeologyMaterials scienceGeotechnical engineeringSoil waterSoil scienceComposite material

Abstract

fetched live from OpenAlex

Despite improved liner design, there are still reported incidences of landfill leachate, rich in heavy metals, percolating through to groundwater and threatening ecosystems. This thesis introduces the concept of segregating municipal solid wastes (MSW) according to their major heavy metals and their metal's adsorption compatibility. Each segregated portion can be disposed in a different landfill compartment to minimize leaching of these heavy metals with the greatest bioactive impact. The validity of the concept was evaluated by batch and column retention mobility studies using copper (Cu) alone or with either lead (Pb) or cadmium (Cd) in solutions bearing various pHs. This was supported by selective sequential extraction (SSE) to determine the affinity to specific liner fractions. The following summarizes the procedure used. Beforehand, a soil column test using sand with 5 and 10% bentonite was conducted to develop an equation predicting liner permeability, k , under simulated field conditions. The column permeability test revealed that a liner with 5% bentonite resulted in a k value which respected the North American criteria of 10-5 m/s. In the batch experiments, solutions with Cu alone or with Cd or Pb, adjusted to pH of 3.7, 5.5 or 7.5, were applied to sand liners with 0%, 5% or 10% bentonite, having CEC's of 2.0, 6.4, and 10.8 (cmol(+) kg-1 ), respectively. Bentonite, pH and Pb significantly affected Cu adsorption. Cu was adsorbed by the liners at pH <6.5 whereas Cu precipitated at pH >6.5. Cu retention was higher in the presence of Cd than in that of Pb, at all combinations of CEC and pH. Competition between metals was greater in liners with lower CEC and therefore fewer adsorption sites. Limiting Pb in a landfill compartment can improve Cu adsorption at pH's below the precipitating threshold. In the SSE procedure, the liner samples were centrifuged, decanted from their solutions and each adsorption fraction analyzed for Cu content. Results indicated that the carbonate fraction adsorbed more Cu, and that Pb significantly increased the mobility of Cu due to competition for exchangeable sites. In the final soil column test using a sand liner with 5% bentonite, the leachate had an initial pH of 3.7. The leaching test confirmed the compatibility of Cu with Cd. The leaching of Cu was greater in the presence of Pb. Total metals in leachate was greater for the Cu-Cd solutions than for the Cu-Pb, because of Cd's relatively high mobility. The sequential extraction results showed again that the carbonate fraction dominated metal adsorption. Total heavy metal leaching followed the order of Cu/Cd > Cu/Pb > Cu alone. Thus, disposing MSW in landfill compartments based on their heavy metal compatibility can minimize migration of heavy metals.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.011
GPT teacher head0.231
Teacher spread0.220 · 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".

Quick stats

Citations0
Published2003
Admission routes1
Has abstractyes

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