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Record W2341603508 · doi:10.14288/1.0071942

Quantifying, reducing and improving mine water use

2013· article· en· W2341603508 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuecIRcle (University of British Columbia) · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicMine drainage and remediation techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEnvironmental scienceRisk analysis (engineering)Business

Abstract

fetched live from OpenAlex

Water is vital to the mining industry; mines can require substantial amounts of water and are often located in some of the driest places on earth. Reducing water withdrawals and improving mine water use are key strategic requirements for moving toward a more sustainable mining industry. Mine water requirements often have significant technical, economic, environmental and political implications. This thesis quantifies global mine water withdrawals and discusses methods of improving mine water use by reducing water withdrawals and water-related energy consumption. The thesis is composed of four main sections. First, two methods are proposed to calculate global mining water withdrawals by commodity. One method is based on the amount of water required to process a tonne of ore and the other is based on the amount of water required to produce a tonne of concentrate. A large database was created, compiling data regarding ore production, commodity production, commodity prices, and mine water withdrawals between 2006 and 2009. The study estimates that global water withdrawals range from 6 to 8 billion m3 per annum. Second, the thesis presents a case study on the challenges faced and lessons learned during the design, start-up and modification of the water systems of a large copper mine site. Third, the thesis identifies multiple mine water reduction, reuse and recycle strategies that have been implemented around the world. A model is developed and used to show the potential impact of these strategies. The results of the modelling show how a hypothetical mine could reduce water withdrawals from 0.76 m³/t to 0.20 m³/t of ore processed or lower. In particular, the combination of ore pre-concentration and filtered tailings disposal reduced water consumption by over 74% of the base case. Finally, this thesis describes and demonstrates a method of determining the lowest energy option for a mine water network. The method uses a linear programming algorithm to compare options for matching water sources with consumers at mine sites. An example illustrates the method and shows how mine water system energy requirements can be reduced by over 50%.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.937
Threshold uncertainty score1.000

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 communication0.0000.001
Open science0.0000.000
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 head0.173
Teacher spread0.162 · 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