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Evaluating Municipal Climate Action: An Analysis of Performance Measurement Models, Practices, and Indicators
No full textThis thesis provides interconnected contributions to theory and practice in climate governance, specifically on municipal performance measurement practices. Key concepts, including the evaluation and control step of the strategic management process, the performance measurement process, and the indicator framework and selection process, frame this research. This thesis contains five chapters. The first and last chapters serve as the introduction and conclusion, respectively. The second, third, and fourth chapter are standalone papers. The first paper of this thesis explored the current state of social impact measurement (SIM) by examining common practices that are used to measure the post-intervention social impact of programs and projects. Using a systematic literature review, this study analyzed a decade's worth of global academic literature on SIM. Through deductive and inductive manual coding of articles in NVivo, this study identified key themes and strategies for improving measurement practices. Findings from this paper suggest strategies for improved measurement such as stakeholder engagement throughout the measurement process, utilizing existing operational data, enhancing measurement capacity, and using a combination of qualitative and quantitative data. This study contributes to the SIM field by offering an in-depth understanding of common measurement models and providing clear recommendations for practitioners to improve SIM. The second paper of this thesis used a contingency theory lens to investigate the climate-related performance measurement practices of 31 Canadian municipalities, with a focus on the influence of population size. Using a case study approach, data were gathered through interviews and document analysis. Data were analyzed through both deductive and inductive coding in NVivo 14. Results indicate that municipalities with larger population sizes prioritize more themes for measurement, employ a broader set of criteria for indicator selection, and report more frequently. Population size does not seem to influence stakeholder involvement in indicator selection or data analysis strategies. By applying contingency theory to Chapter 3, this study examined a situational approach versus the idea of a ‘one-size-fits-all’ solution for local climate-related performance measurement. The final paper explored the climate mitigation indicators currently used in practice and identified those most suitable for measuring local climate-related performance. A document analysis was conducted to identify the climate-related indicators in use by 21 Canadian municipalities, which were categorized and analyzed according to the logic model framework and GHG emissions activity sectors. An indicator evaluation matrix was employed to propose a parsimonious set of 19 new climate mitigation indicators, with the Delphi technique used to achieve consensus among experts. This study found that while a range of indicators exist across the logic model, there is an uneven distribution. The analysis also revealed the emergence of nature-based indicators for local climate mitigation performance measurement. Together, this thesis showcases and defines models and frameworks that municipalities can use to better track their climate performance, while also contributing to the broader academic discourse on measurement practices in the public sector. The findings from this thesis outline streamlined approaches to performance measurement, providing clear pathways for municipalities that are looking to more effectively track progress towards common climate goals
Paidian Playful Interaction in Non-game User Interfaces
No full textI investigate "paidian" play in the context of non-game software user interfaces. Paidian play means activities that are open-ended, exploratory, and free-form. In an initial investigation, I characterize 16 types of playful experiences, 7 characteristics of play in software, and guidelines for the role of play in user interfaces, based on a qualitative analysis of a series of surveys and a brainstorming session with experts. As a case study of inspiring design with paidian play, a second investigation focuses on Easter eggs (hidden features in software applications), an interface feature associated with one of the playful experience types. I analyze source code repositories of open-source software containing Easter eggs, scrape online Easter egg databases, and interview developers of well-known software containing Easter eggs, to characterize 14 different Easter eggs purposes. Results show that Easter eggs provide significant value to developers and users, for example, by enabling recruitment of new developers and teaching users transferable knowledge and skills. I also propose implications for how Easter eggs could be applied in new ways, such as providing educational value. In a third investigation, as a design case study for paidian play, I define and implement "digital knick-knacks" as a form of playful digital possession (e.g., virtual pet). I deploy three exemplar designs in a diary study, in which participants customize and install a digital knick-knack on a personal device. The investigation reveals implications for how playful digital knick-knacks can bring joy and even support mental health. Taken together, the investigations show how user interfaces can be designed to provide social and emotional value to users through paidian play, including in workplace contexts
Examining Social and Climate Feedbacks: Linking Climate Opinions and Climate System in Social Networks
No full textClimate change is one of the most critical challenges that humanity faces, particularly due to its impacts on ecosystems, economies, and societies around the globe. Usually, climate models focus on physical and economic factors, often overlooking social dynamics. Despite identifying human contribution to the climate crisis, behavioural factors, such as public opinion and decisions about mitigation, remain unintegrated in climate models. This research highlights the role of human actions in addressing climate challenges.
Human actions are controlled by social factors such as climate rumours. The rising popularity of social media exposes people to unverified information about climate change and its impacts. In addition to rumours, other factors, such as the high costs to switch to climate-friendly alternatives make mitigation less appealing to people. Although several models consider integrating social behaviour into climate models, these models usually treat human behaviour as a binary choice between mitigation and non-mitigation. However, choices are not too simple when it comes to climate change. People can have more or less intense climate opinions, demonstrating the importance of having a continuous range of opinions when it comes to understanding the issue of climate change. We adopt various modelling approaches to identify the factors leading to reduced response towards the issue of climate change. Our analysis reveals the important role larger groups play in determining future climate scenarios. The behaviour (mitigating or non-mitigating) of these large groups determines the overall emission levels of the population. We identified the importance of mitigation strategies to achieve our current climate targets. Moreover, frequent rumors regarding climate change can also enhance mitigative behaviour and reduce emissions. Factors such as frequent and unexpected social or climate events, stubbornness in individuals, opinion polarization, and high mitigation costs can greatly influence future climate predictions. Ignorance towards climate issues due to delayed response in switching to climate-friendly alternatives or completely forgetting about these issues are some of the major reasons for falling behind in meeting the world's climate targets. The global nature of climate issues makes finding common ground to adopt mitigative strategies difficult. This thesis underscores incorporating social dynamics into climate models, a more comprehensive framework for predicting policy outcomes. Policymakers could leverage the model outcomes to identify factors that minimize emissions by maximizing public response to climate change. Ultimately, this research emphasizes the necessity of integrating behavioural insights into climate models to support informed, and effective climate policy development
Interfacial Engineering and Intercalation Electrochemistry in All-Solid-State Lithium-ion Batteries
No full textThe development of all-solid-state batteries (ASSBs) represents a breakthrough in energy storage technology by providing safer operation with superior energy density and better electrochemical stability than traditional liquid-electrolyte systems. Despite their advantages, all-solid-state batteries face persistent problems with high interfacial resistance between solid electrolyte (SE) and catholyte, lithium dendrite formation and ion transport barriers that demand basic knowledge of solid-state interactions. This thesis investigates two critical aspects of ASSB technology: This thesis addresses (i) the interfacial stability between tantalum-doped lithium lanthanum zirconium oxide (LLZTO) and lithium metal and the heteroionic lithium metal oxychloride (LMOC) type solid electrolyte for all-solid-state lithium-ion batteries (ASSLIBs) and investigates (ii) the intercalation electrochemistry of tantalum disulfide (TaS₂) layered material used in all-solid-state lithium-sulfur batteries (ASSLSBs).
In the first part of my thesis mainly focuses on optimizing the removal of passivation layer (i.e., Li2CO3 and LiOH) from the LLZTO surface by rapid acid treatment (RAT) and heat treatment (HT) followed by analyzing the Li||LLZTO and LMOC||LLZTO interface stability, lithium-ion transport kinetics, and mechanical behaviour during operation using electrochemical impedance spectroscopy, and microstructural analysis. The study systematically investigates symmetrical cell setups, which are affected by external pressure, interfacial contact, and lithium-ion diffusion mechanisms, to determine their influence on charge transfer resistance and morphological stability. Through this stability, we optimized that the interfacial impedance of Li||LLZTO becomes small enough (Rint<10 Ω.cm2) and for heteroionic interfaces of LMOC||LLZTO, it is 80 Ω.cm2. However, we tried to show proof of concept that can be improved when designing the hybrid cell with multilayer SEs in ASSLIB for future research.
In the second part of this thesis, we reported the intercalation electrochemistry conversion of layered transition metal sulfide (TaS2) and carbon (Ketjen black) as sulfur host when used as cathode materials in ASSLSBs which will serve as a neotype hybrid cathode with mixed electronic and ionic conduction (MEIC) contributes excess capacity. This layered structure, combined with its metallic conductivity, enables lithium-ion intercalation while simultaneously acting as a mediator for sulfur redox reactions to promote high gravimetric capacity. This approach resulted in high sulfur utilization of ~99% with 2.99 mAh.cm-2 at a C/10 rate and retains 94% over 50 cycles. With a high active material loading of 9.96 mg.cm-2(S+TaS2) the S/TaS2/C electrode achieves a high areal capacity of 9.1 mAh.cm-2.
This thesis improves our knowledge of the essential processes that control ASSB performance by studying interfacial dynamics in lithium-ion systems and intercalation mechanisms in lithium-sulfur systems. The findings lead to advanced solid-state electrolytes and electrode architectures, improving stability and efficiency while creating the foundation for next-generation energy storage systems
Impact of Climate Transition Risk on Banks: Regulatory Frameworks, Carbon Pricing and Credit Risk
No full textAs the risk associated with climate change intensify, there is an observed trend of increased government and regulatory intervention targeted at mitigating the economic impacts of climate risk and facilitating the decarbonization process. These interventions primarily manifest in two ways. First is through government-imposed market-based instruments, such as carbon pricing, which apply a cost on carbon emissions to discourage pollution and ensure that emitters pay for their environmental impact. The other is through regulatory disclosure requirements that mandate specific sectors to disclose their climate-related actions, with regulatory authorities overseeing compliance within their respective jurisdictions. This research addresses these interrelated yet distinct approaches to managing climate transition risks by examining how market-driven policies, such as carbon pricing, influence bank lending practices and identifying gaps between emerging climate risk regulations and scientific research. It achieves this by assessing the impact of market-based tools, like carbon pricing, on key economies, especially those with high carbon emissions and substantial GDP reliance on carbon-intensive sectors and the impacts on various economic sectors across regions. It also evaluates how emerging regulations align with these policies by synthesizing and analyzing academic evidence on their effectiveness. Theoretically, this research contributes to the theories of credit risk, financial stability and adaptive governance, particularly in strengthening the economic resilience of critical sectors exposed to climate transition risk and enhancing the capacity of regulators and financial institutions to adapt and align their operations with the evolving climate risk regulatory landscape. This analysis provides insights into how lenders to critical sectors can improve their operational frameworks and how regulators can enhance climate regulations in response to the dynamic challenges posed by climate change
Short-Term Effect of Diffusion Optics TechnologyTM (DOT) Contrast Management Spectacle Lenses on Ocular Biometrics and Lag of Accommodation in Emmetropic Children
No full textPurpose:
Myopia, a prevalent refractive error of the eye, is experiencing a rapid increase in prevalence. According to Holden et al., approximately 50% of the global population is projected to be myopic by the year 2050. In response to this growing concern, various myopia control treatments have been developed, including spectacles, contact lenses, and pharmaceutical options. One innovative treatment is the use of Diffusion Optics Technology ™ (DOT) spectacle lenses. These lenses are designed to modulate retinal contrast, thereby reducing signals for axial elongation. The lenses incorporate thousands of microscopic dots to manage contrast, which helps reduce signal disparities between adjacent cones while maintaining good visual acuity and functional peripheral vision. However, there is a lack of published literature on the generalized effects of these contrast management spectacles (CMS) on ocular structures over a short period of wear. This thesis aimed to address this gap and determine the short-term effect of CMS on ocular structures and lag of accommodation. Additionally, the thesis also examined the repeatability of various methods of measurement of choroidal thickness.
Methods and Materials:
Chapters 3, 4, 5, 6: This study was a two-visit, prospective, randomized, controlled, participant-masked trial involving 30 emmetropic participants aged 8 to 14. The participants’ eligibility was confirmed during a screening visit, which utilized non-cycloplegic auto-refraction to ensure that the spherical equivalent was between +1.00D and -0.75D, with astigmatism not exceeding -0.75DC.
During the first study visit, ocular biometrics were assessed using the IOL Master and a Topcon DRI OCT for baseline measurements. The parameters measured included central corneal thickness (CCT), anterior chamber depth (ACD), crystalline lens thickness (LT), retinal thickness, choroidal thickness, choroidal vascularity index (CVI), and axial length (AL). After these measurements, participants were randomly assigned to wear either CMS spectacles with a 0.2 DOT pattern that covered the entire lens surface or clear +3.00D control spectacles (which acted as a positive control to induce myopic defocus). While wearing the spectacles, participants watched an age-appropriate video for 60 minutes. After 30 minutes and again after 60 minutes of viewing, the IOL Master and OCT examinations were repeated. On the second visit, participants wore spectacles that they had not used during the first visit, and the same measurements were repeated. Subsequently, the baseline OCT scans from both visits were exported, and sub-foveal choroidal thickness was measured using four different methods to evaluate the repeatability between methods. The most reliable measurement method was then used for further analysis.
Chapter 7: This was a single-visit, prospective, randomized, subject-masked study. Participants were eligible if they had ±1.00D mean sphere prescription or less and they had no history of previous myopia control treatment. The logMAR visual acuity was measured, and ocular dominance was tested using the sighting method. Participants then wore a pair of plano CMS spectacles with a 0.2 DOT pattern that covered the entire lens surface and standard plano spectacles (control) in a randomized order and, after 5 minutes of adaptation to the lenses, ten open-field autorefraction measurements (Grand Seiko 5500) were taken for each eye, with the target at 6m and 40cm. Analysis was conducted on the mean auto-refraction to determine differences in the lag of accommodation (LOA) between lens types for the right eye and also for the dominant eye.
Results:
Chapters 3,4,5,6: A total of 30 participants were enrolled in the study and completed all assessments (17 females and 13 males). The mean age of the participants was 10.9 ± 1.7 years (median 11 years, ranging from 8 to 13 years). The mean refractive error was +0.35 ± 0.29 spherical equivalent refraction (SER).
• Chapter 3: After one hour of wearing CMS spectacles, a two-way RMANOVA revealed a statistically significant reduction in AL (6µm) with p = 0.001. Similarly, a significant difference in CCT was observed, with p < 0.001 between baseline and both the 30-minute and 60-minute time points. Additionally, pairwise comparisons indicated a significance of p = 0.02 at the 30-minute time point between CMS and control spectacles. A similar reduction in AL (6µm) was noted with +3.00 control spectacles after one hour of wear. A significant difference (p < 0.001) was also observed for both ACD and LT with the +3.00D control spectacles at baseline versus 30 minutes and baseline versus 60 minutes. Furthermore, pairwise comparisons demonstrated significant differences between CMS and +3.00 control spectacles at the 30-minute (2.16 µm) time point for CCT and at both 30 (0.04 mm, 0.04 mm) and 60-minute (0.04 mm, 0.04 mm) time points for ACD and LT.
• Chapter 4: When comparing the different methods of measurement for choroidal thickness, the manual method overestimated the choroidal thickness by 40 µm when compared to the semi-automated and automated AI-based method. Although repeatability between the measurements was satisfactory, the manual method did not show an acceptable Bland-Altman agreement when compared to the other three methods. However, a good agreement was observed between the semi-automated and the automated methods.
• Chapters 5 & 6: The retinal thickness, choroidal thickness, and CVI were measured at all nine Early Treatment Diabetic Retinopathy Study (ETDRS) regions. In terms of choroidal thickness, only the outer inferior region of the retina showed a significant difference (p = 0.02) between the 30-minute and 60-minute marks when using CMS spectacles. Additionally, a significant difference was found between the CMS spectacles and the +3.0 control spectacles at the 30-minute point in 4 out of 9 macular regions. In contrast, no significant differences were found in any of the regions when using the +3.00D control spectacles. The retinal thickness and CVI did not exhibit any significant differences in any of the nine ETDRS regions for both CMS and +3.00D control spectacles.
Chapter 7: A total of 30 participants (20 females and 10 males) with a mean age of 10.4 ± 2.8 (7 to 17) years completed the study. There was no significant difference in right eye mean LOA with CMS (+0.57 ± 0.39D) versus control spectacles (+0.62 ± 0.34D); Mann-Whitney U test, p = 0.64. For dominant eyes, LOA values were +0.60 ± 0.40D and +0.68 ± 0.33D with CMS and control spectacles, respectively (p = 0.25, not significant). Additionally, no significant difference was observed in mean LOA between males and females or between age groups (7-11 years vs 12-17 years) for either right or dominant eyes with CMS or control spectacles (all p = > 0.05).
Conclusions:
Chapter 3: Short-term wear of full-field myopia control CMS did not result in significant changes in anterior segment biometrics, retinal thickness, choroidal thickness, CVI and AL. There was only a minimal decrease of 3 µm in CCT after 60 minutes of wear; however, this minimal change was considered clinically insignificant.
Chapter 4: This study concluded that manual, semi-automated, OCT inbuilt software and AI-based customized software methods are reproducible and repeatable. The manual method tends to overestimate the ChT and is time-consuming, as compared with both automated methods, which showed encouraging results for the OCT based TABS automated software.
Chapters 5 & 6: Short-term exposure to full-field CMS did not lead to any notable changes in retinal or choroidal thickness. However, a significant difference in choroidal thickness was noted between the spectacles at the 30-minute time point, suggesting a rapid yet transient response. Further research with larger sample sizes and extended monitoring durations may be necessary to determine the clinical significance of these transient changes. Similarly, short-term exposure to CMS and +3.00D control spectacles did not lead to any notable change in CVI.
Chapter 7: Full-field CMS had no significant effect on LOA compared to standard single-vision spectacle lenses, indicating no differential impact on accommodative response over the short period of lens wear tested
Phase Model Analysis of the Effect of Acetylcholine on the Neural Synchrony in Hippocampal Networks
No full textNeural assemblies—transiently coordinated groups of neurons—are observed in the hippocampus and are thought to underlie the encoding and consolidation of episodic memories. Acetylcholine (ACh), a key neuromodulator, plays a critical role in learning and memory and has been implicated in neurodegenerative disorders involving hippocampal dysfunction. A well-supported hypothesis suggests that high levels of ACh during active exploration and rapid eye movement (REM) sleep promote memory encoding, while low levels during quiet waking and slow-wave sleep (SWS) support memory consolidation.
In this study, we examine the bidirectional role of ACh in modulating neural assembly formation through its effect on neural synchrony in the CA3 region of the hippocampus. We construct a computational model of a network of excitatory pyramidal neurons, each equipped with a slow, voltage-dependent, non-inactivating potassium current (M-current), which is downregulated in the presence of ACh. Neural assemblies are modelled mathematically as cluster solutions—special types of phase-locked states. Using a phase model reduction of a pair of weakly coupled neurons, we analyze the existence and stability of cluster solutions that may emerge in larger networks equipped with all-to-all globally homogeneous, symmetric distance-dependent and nearest-neighbours coupling architectures.
Our results suggest that ACh shapes assembly formation by modulating network dynamics in CA3. Under low ACh conditions, the network tends to fully synchronize, whereas high ACh levels enable the emergence of multiple stable cluster states, allowing for distinct patterns of activity associated with memory encoding. These findings propose a mechanism by which ACh regulates transitions in hippocampal network states, supporting distinct stages of memory formation
Mathematical modeling of whole-body electrolyte homeostasis
No full textElectrolyte balance is crucial for many physiological processes, including cellular signaling, muscle contractions, membrane potentials, hormonal secretion, and bone structure. Disruptions to electrolyte balance, arising from disease, diet, or drugs can have severe health consequences, such as muscle weakness, bone fragility, and life-threatening cardiac arrythmias. Therefore, a comprehensive understanding of these regulatory systems and how they may be disrupted is important for developing effective preventative and therapeutic strategies. Mathematical modeling provides a powerful tool for investigating these systems through simulations and analysis. In this thesis, we present the development and analysis of mathematical models focused on the regulation of key electrolytes, potassium and calcium.
For potassium homeostasis, we first developed a detailed, whole-body model incorporating known regulatory mechanisms. We conducted model simulations to quantify the individual contributions of these regulatory mechanisms on long-term potassium balance and responses to a meal. Additionally, we conducted sensitivity analyses to understand how parameter variations impact potassium levels in the extracellular and intracellular fluid. Furthermore, we integrated recent experimental data on renal adaptations to high potassium intake to analyze these findings from a whole-body perspective.
For calcium homeostasis, we developed mathematical models representing a male, female, late pregnant, and lactating rat to quantify sex-specific differences and maternal adaptations in calcium regulation. These models synthesized literature data to identify key mechanisms that enable females to meet the high calcium demands of pregnancy and lactation. Finally, we developed an integrated model that represents the renin-angiotensin system, calcium regulation, and bone remodeling to investigate the impact of estrogen deficiency in post-menopausal women and common antihypertensive treatments on bone density and calcium regulation.
The research provided in this thesis contributes frameworks for understanding electrolyte homeostasis and predicting the impacts of physiological changes and pharmacological interventions on electrolyte and bone homeostasis
The Role of the Theory of Planned Behaviour (TPB) and socio-demographics in influencing Pro- climate behaviours
No full textThe study aimed to investigate the association between demographic factors and components of the Theory of Planned Behaviour (TPB) with the climate change behaviour of the people residing in Canada. The hypotheses of the research focused on the association between socio-demographics of age, gender, race, region, income, language, and education with the intention of the people to act in an environment-friendly way. Moreover, the hypotheses were also concerned with social norms, attitudes, perceived behavioural control, intention, and behaviour of the people. The data of the study was obtained from the survey of Impact Canada, selecting wave 1 responses for the research as it provided information according to the variables required for the study. The data analysis was conducted through Chi-square and Spearman correlation. The findings have provided support for all of the study hypotheses, excluding H6 and H7 which were related to the association of language and race with intention. However, the other hypotheses have been accepted, which implies that demographic factors tend to play a significant role in determining the pro-climate behaviours of the people. In addition, the relevance of TPB has been established through this study as a means of understanding the adoption of environment-friendly behaviours of the people in Canada
Novel Machine Learning-Driven Platforms for In-Situ Prediction of Vertical and Top Surface Roughness in Laser Powder-Bed Fusion
No full textControlling and optimizing surface roughness remains a significant challenge in Laser Powder Bed Fusion (LPBF), as roughness profoundly influences fatigue life, mechanical performance, and post-processing (e.g., machining) costs. While in-situ monitoring has emerged as a key approach for real-time defect detection, predicting surface roughness, particularly for both top and vertical surfaces of parts being printed, remains underexplored. Existing studies predominantly rely on camera-based methods, which usually suffer from the limitations such as lack of viewability of vertical surfaces covered by loose powder particles in LPBF, sensitivity to ambient light, resolution constraints, and the need for additional optical equipment. This research pioneers a novel photodiode-based in-situ monitoring framework integrated with machine learning (ML) algorithms to predict surface roughness in real-time for both top and vertical surfaces of LPBF-printed parts.
For top surface roughness prediction, the methodology involves capturing light intensity signals from the melt pool using an on-axial photodiode, incorporating additional process parameters, and training multiple ML models to predict surface roughness at a fine spatial resolution (690 µm × 510 µm), including edges and corners. The framework is rigorously evaluated across a wide range of roughness values, demonstrating its robustness in adapting to process parameter variations.
For vertical surface roughness prediction, this study introduces the first-ever in-situ framework using photodiode signals to overcome challenges posed by loose powder coverage, which obstructs conventional sensing techniques. Key time-domain and frequency-domain features are extracted from photodiode signals captured near vertical surfaces and combined with essential process parameters to train ML models. Among the five ML models evaluated, Random Forest (RF) and eXtreme Gradient Boosting (XGB) demonstrated the highest accuracy and lowest error rates. Incorporating in-situ data significantly improved RF’s performance, increasing R² from 0.35 (using process parameters alone) to 0.78, confirming the effectiveness of this approach.
This research introduces an innovative pathway for real-time surface roughness prediction in LPBF, enabling enhanced quality assurance, process optimization, and defect mitigation. The integration of photodiode signals with advanced ML algorithms enables precise, on-the-fly assessment of both top and vertical surfaces, enhancing the ability to detect and address irregularities as they occur. By addressing the limitations of traditional camera-based methods, this photodiode-ML framework provides a fast, adaptive, and scalable solution for real-time surface monitoring, paving the way for more advanced quality control strategies, and promising greater reliability and consistency in the production of high-performance components