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Record W2586889745

Sustainability assessment of energy systems

2013· dissertation· en· W2586889745 on OpenAlexaboutno aff
Kyrke Gaudreau

Bibliographic record

VenueUWSpace (University of Waterloo) · 2013
Typedissertation
Languageen
FieldEnergy
TopicGlobal Energy and Sustainability Research
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityEnergy (signal processing)Energy systemEnvironmental resource managementEnvironmental sciencePhysics
DOInot available

Abstract

fetched live from OpenAlex

This research project set out to develop and apply a framework for assessing how energy systems may be structured to help society progress towards sustainability. The general intent was to outline a way to decide upon the things that matter in order to make better decisions that will lead to positive near- and long-term outcomes. There are various ways of reaching the goal described above, and the path chosen in this dissertation centred on Gibson’s (2006) sustainability assessment framework, an approach to integrated sustainability-based decision-making. In order to contribute to extending and specifying Gibson’s approach to sustainability assessment for energy undertakings, this project developed a theoretical framework grounded in various forms of complexity and energy.
\n
\nThe journey described in the dissertation begins with an exploration of the complexity of science, the subject of Chapter 2. We live in a world characterized by inherent uncertainty, multiple worldviews, conflicting values, power dynamics and a whole host of other challenges to science and decision-making. Many of the environmental and human challenges we currently face have arisen in part because we do not sufficiently respect the limits to knowledge and the personal biases we all bring to the table. Chapter 2 develops a framework for knowledge generation and decision-making situated within its social context, and operationalizes this framework through the process of criteria specification. Drawing from multiple sources of data – particularly documentary analysis, semi-structured interviews and observation – the criteria specification cycle provided the means of and determining and deciding upon the things that matter in a given case and context. 
\n
\nThe complexity of science is only half the story emerging from the complex systems literature. From a different perspective, it is evident that we live in a world of complex dynamics and interconnections, and it is important to ensure that whatever energy paths we set out on recognize these dynamics. Fortunately, there is a wide range of literature relating to the characteristics of complex systems in general, as well as their energy and material flows in societies. These literatures are explored in Chapter 3 to develop an understanding of and guidelines for managing complex systems to the extent possible and appropriate. 
\n
\nBuilding on the theory developed in Chapters 2 and 3, the discussion in Chapter 4 began to develop an understanding of energy systems and energy decision-making and was structured around three general questions: (1) what is the energy problem? (2) what are the characteristics of an appropriate and constructive relationship with energy? and (3) how can the necessary and desired sociotechnical systems changes be achieved. These questions were largely addressed through an exploration of the soft energy path and transition management and led to two sets of guidelines designed to address energy systems structure and change.
\n
\nThe theoretical framework developed over Chapters 2-4 was consolidated into a proposed set of sustainability criteria for energy undertakings. The sustainability criteria set represents the principal theoretical contribution of the dissertation to the academy and the broader assessment community, and outlines a suite of generally desirable system attributes and actions for achieving progress towards sustainability, as opposed to an acceptability threshold. The proposed sustainability criteria are primarily intended for application regarding energy undertakings at a wide variety of scales, but are much more broadly relevant. 
\n
\nIn a manner that is more iterative than can be described in this abstract, the sustainability assessment framework described in this dissertation was applied in, and enriched through, four distinct case studies that assessed
\n(1)\tthe 2006 Ontario Integrated Power Systems Plan proposed by the Ontario Power Authority. The Integrated Power Systems Plan was originally framed as a coal versus nuclear problem, as opposed to a critical appraisal of power systems planning; and in doing so it underplayed potential for conservation, demand management, increased renewable energy, and social change;
\n(2)\ta small-scale biodiesel operation in Barbados. The plant owner collected used cooking oil from restaurants, roadside stands, and individual homes, and converted it into biodiesel using a first-generation processing technology known as transesterification.
\n(3)\ta sugarcane-ethanol plant in the Tietê-Jacaré Watershed of São Paulo, Brazil. The sugarcane ethanol mill harvests approximately 21,000 hectares of sugarcane crops from seven municipalities and produces hydrated ethanol for domestic markets, and sugar for domestic and international markets; and 
\n(4)\tthe agricultural and energy systems in Senegal. Senegal suffers from significant deforestation and soil fertility decline coupled with demographic change. The many interconnections between the energy and agricultural systems require an integrated assessment of both.
\nEach individual case study stands alone in providing novel insights emerging from application of the framework in the particular case and context. At the more general level, five important insights emerged from the case studies, including: (1) the benefits of, and need for, maintaining a flexible unit of analysis so as to improve problem structuring; (2) the importance of grounding an assessment within its context; (3) the benefits of seeking integration and positive indirect effects; (4), the need to plan for and develop energy bridges towards feasible and desirable energy futures; and (5), the need for caution in the face of thresholds and uncertainty. 
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\nThe individual and general insights from the case studies were incorporated into the most recent version of the sustainability assessment framework described in this dissertation. The framework is suitable for application, with specification for particular case and context, to all types of energy systems at all scales.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.868
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.008
GPT teacher head0.240
Teacher spread0.232 · 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

Citations6
Published2013
Admission routes1
Has abstractyes

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