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Record W7106008787 · doi:10.7939/83141

Capturing Carbon, Weighing Choices: Essays in Climate Policy, Willingness to Pay, and Heterogeneous Preferences

2025· dissertation· en· W7106008787 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2025
Typedissertation
Languageen
FieldSocial Sciences
TopicSocial Acceptance of Renewable Energy
Canadian institutionsnot available
Fundersnot available
KeywordsSoftware deploymentClimate changeGreenhouse gasRenewable energyClimate change mitigationPortfolioPublic policyEnergy policyFossil fuelCarbon capture and storage (timeline)

Abstract

fetched live from OpenAlex

Carbon capture and storage (CCS) has gained attention for its potential to reduce carbon emissions from energy-intensive and industrial processes. However, public acceptance of CCS remains uncertain, shaped by perceptions of its effectiveness, safety, and cost, as well as its role in the broader landscape of climate solutions. This dissertation investigates the complexity of CCS deployment through the lens of public preferences, focusing on five countries: Canada, Germany, Netherlands, Norway, and the UK. Chapter 1 examines where CCS stands in the broader landscape of climate policy options from the public’s perspective. Reaching net-zero emissions will require a diverse portfolio of solutions as no single policy can achieve this goal in isolation. While CCS often faces resistance when considered on its own, a comparative lens provides important insights: if the public is willing to accept CCS compared to other mitigation policies, this suggests potential support for future CCS operations under the right conditions. Using a best-worst scaling experiment, this study compares the public acceptance of CCS deployment with six alternative climate change mitigation policies (i.e., Increase the share of renewable energy, Nurture forest landscapes, End fossil fuel subsidies, Put a price on CO2 emissions, Enforce reductions in personal vehicle transport to encourage public transportation, and Force households to adopt energy efficiency measures for home heating and electricity consumption). While renewable energy and forest landscapes consistently emerge as the most accepted policies across all five countries, preferences reflect public acceptance of CCS deployment against market-based and regulatory policies. The results reveal strong policy implications for integrating CCS into a broader portfolio of decarbonization strategies while accounting for within- and cross-country variations. Chapter 2 investigates the public willingness to support large-scale CCS deployment by examining how individuals evaluate trade-offs between the climate benefits and the associated deployment costs. As Chapter 1 provided evidence that CCS is recognized as a part of a broader portfolio of climate policies, understanding society’s perspective of finding the right balance between climate benefits and safety concerns is crucial for ensuring its successful implementation. Using a discrete choice experiment, this study finds that public preferences are more strongly influenced by the presence of rigorous and transparent monitoring procedures for seismic incidents than by the climate change mitigation potential of CCS. Although this preference pattern is observed across all five countries, each nation would face unique challenges in fostering CCS deployment, as public preferences vary in distinct ways depending on the national context. Chapter 3 examines individuals’ stated preferences for alternatives that scale up CCS technologies to identify different population classes in Canada. Individuals are diverse in their perceptions of climate change, CCS risks and benefits, social issues, etc., leading them to perceive CCS deployment in different dimensions. As a result, large scale deployment of CCS remains a controversial topic, despite its growing recognition for meeting net-zero goals. With known evidence for diversity of public perspectives on CCS, Canada presents a compelling case of this divide. Using a latent class analysis, this study identifies three distinct classes. All classes value rigorous monitoring for CCS deployment. Class membership is largely influenced by individuals’ political orientation, perceived benefits and risks of CCS, and environmental and social concerns. Identifying distinct class profiles can offer valuable insights for policymakers, enabling the development of more targeted and effective strategies that promote acceptance of CCS across diverse public segments while helping to minimize controversy and opposition. Together, these three chapters provide valuable insights into the ongoing debate on the successful implementation of CCS, underscoring the importance of developing more responsive, transparent, and inclusive climate policies that reflect public preferences and concerns.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.261
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.009
GPT teacher head0.231
Teacher spread0.222 · 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.

Study designQualitative
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
Published2025
Admission routes1
Has abstractyes

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