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Record W6959398958 · doi:10.7939/r3-n6vq-pq32

Comprehensive System-level Assessments of Non-combustion Products from Wastes and By-products of Oil Sands

2024· dissertation· en· W6959398958 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2024
Typedissertation
Languageen
FieldSocial Sciences
TopicLegal and Regulatory Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsOil sandsAsphaltGreenhouse gasProduction (economics)Life-cycle assessmentCarbon footprintCapital costEnergy consumptionEnvironmental impact assessment

Abstract

fetched live from OpenAlex

Non-combustion products, i.e., those not burned for energy production, have the potential to diversify and enhance the resilience of the oil sands industry in anticipation of reduced fuel demand due to the ongoing decarbonization of the economy. Despite the significance of this transition, there are very few economic and environmental performance assessments of the production processes at a commercial scale. Such information is crucial for the development of an industry centered around non-combustion products. The primary objective of this thesis is to evaluate the economic feasibility and greenhouse gas (GHG) emissions associated with the production of non-combustion products. Techno-economic and life cycle GHG emissions assessments were conducted for three non-combustion products derived from different wastes and by-products of the extraction and processing of oil sands bitumen. Vanadium, obtained from the spent catalysts and petcoke generated during bitumen upgrading, heavy minerals (zircon and titanium minerals) concentrated in froth treatment tailings, and carbon fiber made from asphaltene after bitumen deasphalting were analyzed. Available experimental data was used to scale up the production processes from laboratory scale to commercial operation. First principles were applied to complete the material and energy balances of each relevant operation. The main equipment was sized, and energy consumption was estimated using empirical correlations and information from vendors and manufacturers. With this information, the capital cost of the production processes was calculated. Feedstock, utilities, labor-related, and facility-related costs make up the operating costs. A technoeconomic assessment was performed to estimate the production cost or the internal rate of return (IRR) of the processes. Plant capacities for a base case were defined based on the current generation rate of wastes and by-products, and economies of scale benefits were assessed, among other scenarios. The scope of the life cycle GHG emissions assessment was cradle-to-gate. The boundary system includes the upstream operations from bitumen extraction up to the generation of the waste of the by-product that feeds the production process of the non-combustion products; upstream emissions associated with the production of consumables and the electricity used in the process; and process emissions from the combustion of fuels to provide heat to the process and from the transformation of the feedstock into the final non-combustion product. Recovering vanadium from hydroconversion spent catalyst would cost $9.89/kg V2O5 and emit 10.3 kg CO2eq/kg V2O5, while doing so from petcoke fly ash would cost $18.77/kg V2O5 and generate 26.6 kg CO2eq/kg V2O5. The production cost of asphaltene-based carbon fiber (ACF) was estimated to be $10.16/kg ACF and life cycle GHG emissions to be 16.2 kg CO2eq/kg ACF. Both metrics outperform those of polyacrylonitrile (PAN)-based carbon fiber, which represents about 90% of all the carbon fiber produced worldwide. The IRR of recovering heavy minerals from froth treatment tailings would be 9.8%, considering the current market price of zircon, titanium minerals, and residual bitumen recovered in the process. Life cycle GHG emissions would be 1,499 kg CO2eq/t heavy minerals. The models developed in this study are based on assumptions that introduce uncertainty into the estimated costs and GHG emissions, either because process data unavailability at a commercial scale or because the volatility of economic and GHG emissions factors over the life cycle of the products. Monte Carlo simulations were performed to calculate the more likely range of variation of the model’s outputs considering the variability of the inputs. In addition, sensitivity analysis was conducted to identify those variables that should be estimated more accurately to reduce the uncertainty of the results. This research provides valuable insights into the economic and environmental feasibility of targeted non-combustion products from oil sands, assisting stakeholders, including oil sands operators, waste management companies, researchers, government, and investors in making informed decisions on this activity in Alberta. The results of the study also provide information to the government for policy formulation. The study framework can be adapted to evaluate the performance of other non-combustion products from oil sands wastes and by-products.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.012
GPT teacher head0.230
Teacher spread0.218 · 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
Published2024
Admission routes1
Has abstractyes

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