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Record W2255571727 · doi:10.14288/1.0081099

Measurements and modeling of gas fluxes in unsaturated mine waste materials

2011· article· en· W2255571727 on OpenAlexaffabout
Louis Kabwe

Bibliographic record

VenuecIRcle (University of British Columbia) · 2011
Typearticle
Languageen
FieldEngineering
TopicCoal Properties and Utilization
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEnvironmental scienceWaste managementPetroleum engineeringGeologyEngineering

Abstract

fetched live from OpenAlex

Accurate measurements and predictions of surface CO₂ fluxes are needed to quantify biogeochemical reaction rates in unsaturated geologic media and soils. However, no standard appears to exist for establishing the accuracy of field measurements of soil respiration rates. As a result, a technique to measure CO₂ fluxes from the soil surface to the atmosphere was recently developed and verified in mesocosms over the range of CO₂ fluxes reported for field conditions. The method, termed the dynamic closed chamber (DCC), was shown to accurately measure CO₂ fluxes from ground surface to the atmosphere in mesocosms. The main advantage of this direct technique is the almost instantaneous estimation of the CO₂ flux. Although the DCC is a promising technique, its ability to accurately quantify surface CO₂ flux under field conditions remains to be verified. The field application of the DCC is investigated in this thesis with a particular focus on quantifying reaction rates in waste-rock piles at the Key Lake uranium mine in northern Saskatchewan, Canada. It should, however, be noted that the dominant geochemical reactions in the two waste-rock piles at the Key Lake mine were not typical of acid rock drainage (ARD) waste-rock piles. The CO₂ fluxes measured in this study occur in the organic material underlying the waste rocks, in contrast to ARD waste-rock piles where O₂ consumption and CO₂ production are the results of sulphide oxidation and carbonate buffering. This work provided a complete suite of measurements required to characterize spatial distribution of CO₂ fluxes on larger-scale studies of waste-rock piles. There has been no previous field-scale study to quantify CO₂ fluxes across a waste-rock pile. The ability of the DCC method to accurately quantify field soil respiration was demonstrated by comparing the DCC fluxes to those obtained using two other CO₂ flux measurement techniques: the static closed chamber (SCC) and eddy covariance (EC) methods. The DCC yielded comparable data but had distinct advantages over the two other methods in terms of speed and repeatability. The DCC was also used to investigate CO₂ fluxes under the climatic variables (e.g., rainfall and evaporation) that affect soil water content at the Deilmann north (DNWR) and Deilmann south (DSWR) waste-rock piles, at the Key Lake uranium mine. The effects of rainfall events on waste-rock surface-water conditions and CO₂ fluxes were of short duration. A simple model for predicting the effects of soil water content on CO₂ diffusion coefficient and concentration profiles was developed. The model was verified with measured CO₂ fluxes obtained from mesa-scale columns of unsaturated sand. Verification of the model showed good agreement between predicted and measured data. The model was subsequently used to predict CO₂ diffusion and concentration profiles in response to changes in soil water contents in the piles and also to predict surface CO₂ fluxes from the DNWR and DSWR for a 6-d test period [August 1 (day 3) to August 6 (day 8) 2002] following a 72.9 mm precipitation event over the initial 48-h [July 30 (day 1) to July 31 (day 2) 2002]. The model predicted surface CO₂ fluxes trends that were very similar to the measured surface CO₂ fluxes from the DNWR and DSWR piles during the test period. Based on the tests conducted in this thesis the DCC method has shown to be suitable for field applications to quantify CO₂ fluxes and to characterize the spatial and temporal dynamics of CO₂ fluxes from unsaturated C-horizon soils and waste-rock piles.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.672
Threshold uncertainty score0.934

Codex and Gemma teacher scores by category

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

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 head0.033
GPT teacher head0.160
Teacher spread0.127 · 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 teacher head, 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
Published2011
Admission routes2
Has abstractyes

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