<p>In this work, two overarching global crises are addressed with an engineering lens; the COVID-19 pandemic and climate change. Regarding the latter, an investigation is completed into the fluxes of CO2 in the wake of a simple wind farm for identification of potentially beneficial siting of Direct Capture of CO2. In this analysis, large-eddy simulations are used to quantify scalar entrainment in the turbines’ wake for several empirical CO2 profiles. In instances with positive or a combination of CO2 gradients, it was found that the concentration of CO2 increased in wake through downward mixing and entrainment. In a negative CO2 gradient, the opposite was found, with the wind turbine mixing away the increased surface<br> concentration and entraining down lower concentration air from above. These findings were used to make recommendations on scenarios in which wind turbines were beneficial to Direct Capture plants.<br> In addition, as part of the ongoing response to the COVID-19 pandemic, an innovative new technology was designed and constructed; a prototype photoacoustic spectrometer for the rapid detection of viruses. With the vision to become a viral "breathalyzer", the primary stage of development involved the creation of a prototype for proof-of-concept of viral detection using PAS. An extensive literature review was completed to determine optimal<br> design, with several distinct innovations integrated with the end-product in mind; such as a pure silicon resonator cell and a light-emitting diode source for low-cost, portable detection.<br> This was estimated to be of sufficient quality to detect single virions, as found through Finite Element Analysis.<br> Additionally, the validation of a proposed improvement on the medical mask, named Hy-Cu, is shown. Through various tests, Hy-Cu was found to have greater breathability than KN95 or surgical masks, as well as comparable efficiency in filtration of viral droplets.<br> Additionally, the novel inclusion of a diamond-like carbon-coated copper mesh layer resulted in viral inactivation of 99% after a period of 2 hours, allowing Hy-Cu to be safely reused without risk of transmission.<br> </p> <p> </p>

<p dir="ltr">The modern world faces many challenges related to sustainability, including the ability to make high-level decisions using a sustainability-oriented framework, a matter of increasing importance to the United States military with respect to energetic materials (EMs). Although a few pieces - process flowsheet optimization, life cycle assessment (LCA) studies, and the use of optimization tools to identify an option - have been studied and utilized, there exists no systematic approach that combines all these pieces to create a framework that allows for holistic decision making. This is especially true with EMs, other key critical materials, and new methods of manufacture. An interconnected framework for LCA-based decision making is developed and a tool based on this framework created for use with novel materials. The interconnected framework and tool are utilized in two case studies related to the manufacture of RDX- a lab-scale, batch-mode configuration and a simplified continuous-mode configuration, to determine the optimal reaction temperature.</p>

<p dir="ltr">Aquaculture is a controlled aquatic farming sector and one of the most important human food sources. Fish farming is one of the predominant, fast-growing sectors that supply seafood products worldwide. Along with its benefits, aquaculture practices can discharge large quantities of nutrients into the environment through non-treated or poorly treated wastewater. This study aims to understand the nutrient composition of fish wastewater and the use of indigenous bacteria, cyanobacteria, and microalgae as an alternative biological treatment method. Wastewater samples from a local fish farming facility were collected and treated using six different species of cyanobacteria and microalgae include <i>Chroococcus</i><i> </i><i>minutus</i>, <i>Porphyridium</i><i> </i><i>cruentum</i>, <i>Chlorella vulgaris</i>, <i>Microcystis aeruginosa</i>, <i>Chlamydomonas </i><i>reinhardtii</i>, and <i>Fischerella</i><i> </i><i>muscicola</i>. All the samples were incubated for 21 days, and the following parameters were measured weekly: Chemical oxygen demand (COD), phosphate, total dissolved nitrogen, and dissolved inorganic nitrogen. In addition, dissolved organic nitrogen (DON), bioavailable DON (ABDON), and biodegradable DON (BDON) were calculated from the mass-balance equations. Colorimetric and digestive methods were used for the parameter measurements. The results showed that <i>C. </i><i>reinhardtii</i> reduced the soluble COD concentration by 74.6%, DON by 94.3%, and phosphorous by more than 99%. Moreover, <i>M. aeruginosa</i>, and <i>C. </i><i>minutus</i> significantly reduced inorganic nitrogen species (>99%). This alternative fish wastewater treatment method was explored to gain insight into fish wastewater nutrient composition and to create a sustainable alternative to conventional fish wastewater treatment methods.<b> </b></p>

<p dir="ltr">Work from home (WFH) moves work into home life, reshaping the residential, workplace, and commuting activities, which further impacts greenhouse gas (GHG) emissions. Although existing work has explored individual time-use patterns under WFH, there is a lack of complete consideration of diverse activities, their durations and timelines, as well as the comparisons with traditional life at home and Work in Office (WIO). Also, existing studies have examined GHG emissions under WFH, while individual-level estimation using activity-specific data covering all major activities is lacking. In particular, limited studies explored individual time-use patterns and quantified activity-based emissions for the construction workforce. Therefore, this dissertation aims to (1) develop an activity-based individual-level model to estimate GHG emissions under WFH, (2) compare individual time-use patterns and activity-based GHG emissions between traditional life at home, WFH, and WIO to understand how WFH affects work, life, and the environment, especially for the construction workforce, and (3) propose activity-based decarbonization strategies to reduce GHG emissions. By employing the proposed model, high-resolution calculations of individual time-use patterns and activity-based emissions were achieved, revealing major activities’ durations and timing and highlighting major contributing activities to emissions under WFH. When shifting from traditional life at home to WFH, individuals reduced sleeping and leisure hours to incorporate work activity, resulting in an 11.34% reduction in GHG emissions. When comparing WFH to WIO, individuals reduced work and commuting time to include more cooking and leisure activities at home, mitigating GHG emissions by 29.11%. Demographic groups and climate regions showed different results mainly because of the varied work and household duties and the characteristics of regions. In addition, the construction workforce reduced GHG emissions by 13% and 46% under WFH compared to traditional life at home and WIO, respectively. Compared to the general public, the construction workforce had more reduction in work and commuting hours and associated emissions when shifting from WIO to WFH. The findings could help envision how WFH influences work, life, and the environment as well as assist both individuals and policymakers in achieving decarbonization and adopting low-carbon living during the work arrangement transition, which could contribute to sustainable development.</p>

Hållbar stadsbyggnad är ett ideal som syftar på att ta hänsyn till ekologiska och sociala såväl som ekonomiska aspekter så att utveckling av dagens samhälle inte skall inkräkta framtida generationers rätt till ett gott liv. Rent praktiskt måste stadsplanerare formulera om idealet till konkreta mål och åtgärder anpassade till lokala förutsättningar och tillgängliga medel. I Stockholm pågår två stadsbyggnadsprojekt med höga hållbarhetsambitioner; Norra Djurgårdsstaden (NDS) och Stora Sköndal (SSK), båda har som en del av hållbarhetsarbetet antagit s.k. hållbarhetsmål och krav kopplade till olika styrdokument och processer för att uppnå dessa ambitioner. Målet för arbetet var att genom att kvantitativt och kvalitativt jämföra projektens egna mål, krav och även andra relaterade aspekter av hållbarhetsarbetet samt tillgängliga resultat avgöra vad som är jämförbart, vilket projekt som har högst ambitioner ochprestera bäst samt finna punkter där projekten eventuellt kan förbättras. Noterbara slutsatser är att projektens ekologiska mål överlag liknar varandra och är kvantitativt jämförbara, medans de sociala målen inte är det dels som en följd av skiljda koncept för social hållbarhet och dels på grund av olika organisationer och processer. Förslagen på förbättringar gäller dels specifika höjningar av enskilda mål/krav och mer generella råd att öka antalet standardiserade och mätbara mål och krav. Trots att NDS har något högre ambitioner tyder jämförelsen av de tillgängliga sammanställda resultaten på att Stora Sköndal verkar prestera bättre än Norra Djurgårdsstaden för vissa särskilda målområden som energianvändning och grönytor / Sustainable city planning is an ideal aiming at consideration to ecological and social as well as economic aspects so that development of today’s society won’t interfere with future generations’right to a decent life. In practical terms city planners have to reformulate the ideal to concrete targets and actions adapted to local conditions and available means. In Stockholm there are two ongoing city development projects with high sustainability ambitions; Stockholm Royal Seaport (Norra Djurgårdsstaden, NDS) and Stora Sköndal (SSK), both have as part of the sustainability work adopted so called sustainability goals and requirements tied to governing documents and processes to achieve these ambitions. The goal for this examination paper was to quantitatively and qualitatively compare the projects own goals, requirements and some other aspects of the sustainability efforts alongside with available results to ascertain what comparable elements there are, what project seems to have the higher ambitions and perform the best, and find aspects where the projects may improve. Notable conclusions are that the projects’ ecological goals overall are similar and comparable, while the social one’s aren’t as a consequence of both differing concepts of social sustainability and different organizations and processes. The improvement proposals address raising specific goals/targets as well as more general advice to expand the number standardized and measureable goals and requirements. Despite NDS having somewhat higher ambitions the first comparison of available results suggest that SSK manage to accomplish better results than NDS in key areas such as energy use and green spaces.

<p dir="ltr">With the global push for sustainable energy solutions, microalgae have gained attention as a promising biofuel source, with new methods like virus-assisted lipid extraction making algae-based biofuels more cost-effective. This thesis investigated the interaction between <i>Chlorella</i> algae and <i>Paramecium bursaria chlorella virus</i>-1 (PBCV-1) using variations of the SID (Susceptible-Infected-Dead) model to improve algae biofuel production. By leveraging epidemiological modeling, the thesis aimed to understand viral infection dynamics in algae and optimize the viral infection for efficient and effective lipid extraction for biofuels. Two distinct experimental setups were conducted to evaluate how environmental conditions impact infection outcomes. Mathematical models, including SID and SEID (Susceptible-Exposed-Infected-Dead) versions, were calibrated using Bayesian inference and nonlinear optimization to estimate critical parameters such as infection and mortality rates. Key findings reveal that the Susceptible-Infected-Dead model with variable initial infection (SIDVII), which included the initial concentration of infected algae as a model parameter, offered the most reliable fit by balancing biological relevance and statistical performance. In contrast, the SEID-based models, while able to capture a latent infection phase, posed risks of overfitting with too many parameters. The study emphasized the complexity of applying modeling tools to characterize viral infections at scale, suggesting that future research should address potential trade-offs between lipid productivity and infection dynamics. The findings offer potential insights not only for biofuel production but also for broader ecological management strategies, including the targeted control of harmful algal blooms.</p>

<p dir="ltr"><a href="" target="_blank">The electrification of the transportation sector is pivotal in reducing greenhouse gas emissions and decreasing dependence on fossil fuels. Central to this transition are battery electric vehicles (BEVs) and other clean energy technologies, which rely heavily on critical materials (CMs) such as cobalt, lithium, neodymium, and nickel. </a>These materials are essential for the performance of batteries, advanced electronics, and other components in BEVs. <a href="" target="_blank">However, the limited availability of these CMs poses potential constraints on the widespread adoption of such technologies.</a></p><p dir="ltr">This research delves into the implications of widespread BEV adoption on the demand for CMs in the United States, with a focus on both light-duty vehicles (LDVs) and medium- and heavy-duty vehicles (MHDVs). Various market penetration scenarios were analyzed, revealing that while MHDVs require more CMs per vehicle, the sheer volume of LDV sales drives the overall CM demand, particularly in a scenario with 100% BEV adoption. Key findings highlight that cobalt, graphite, lithium, neodymium, and nickel are critical for BEVs, whereas palladium and rhodium are more crucial for internal combustion engine vehicles (ICEVs). Also explored is the impact of lightweighting on LDVs, revealing that while substituting steel with aluminum increases the total CM quantity per vehicle, it reduces the vehicle's mass, operational energy consumption, and the demand for high-concern battery-related CMs. Additionally, changing the battery cathode chemistry from NMC622 to LFP significantly reduces CM use but increases the demand for strategic materials like copper and phosphorus due to the lower energy density of LFP-based batteries.</p><p dir="ltr">The research also highlights the importance of rare earth permanent magnets (REPMs), <a href="" target="_blank">particularly Neodymium-Iron-Boron (NdFeB) magnets, in clean energy technologies such as electric vehicles and wind turbines.</a> Neodymium, a critical material, faces supply chain risks. To lessen these risks, circular economy strategies have been proposed, including the recovery of needed materials from end-of-life (EoL) products. <a href="" target="_blank">A dynamic material flow analysis (MFA) model was developed to forecast such EoL flows for products containing REPMs and assess the recoverable neodymium from these EoL products. </a>The results indicate that even a modest recycling efficiency of 15% could meet 12% of the Nd demand for EVs by 2050, with reuse meeting up to 70% of the demand.</p><p dir="ltr">With the dynamic MFA model showing that circular economy principles could meet up to 70% of future neodymium demand in 2050, the next step was to investigate the techno-economic feasibility of recycling REPMs. A techno-economic assessment model was developed for establishing a magnet-to-magnet recycling facility for REPMs. Results revealed a net present value (NPV) of $8,867,111 over 20 years, a payback period of 3 years, and an internal rate of return (IRR) of 53%, providing a compelling case for investment in recycling infrastructure. Sensitivity analyses point to the selling price of recycled magnets, feedstock purchase price, facility throughput, and labor costs as the most influential factors on profitability.</p><p dir="ltr"><a href="" target="_blank">Additionally, this research explored the challenges and opportunities in the disassembly and recycling of EoL EV components, particularly traction motors containing REPMs. The complexity of disassembly, driven by varying component sizes and designs, is identified as a significant barrier. By evaluating manual disassembly times and proposing potential automation solutions, the study aims to streamline the disassembly process, thus facilitating more efficient recycling and remanufacturing operations.</a></p><p dir="ltr">The key contributions of this research are summarized as follows:</p><p dir="ltr">· Evaluated the vehicle CM demand of ICEVs and BEVs for LDVs and MHDVs and explored the impact of lightweighting and changing the battery cathode chemistry from NMC622 to LFP on CM demands.</p><p dir="ltr">· Developed a dynamic material flow analysis (MFA) model to forecast end-of-life (EoL) flows of products containing REPMs and assess the recoverable neodymium from these EoL products.</p><p dir="ltr">· Developed a techno-economic assessment (TEA) model to evaluate the viability of a magnet-to-magnet recycling facility.</p><p dir="ltr">· Performed disassembly analysis to assess the ease with which EoL BEV transmissions can be disassembled with a specific focus on the retrieval of traction motors (which house the REPMs) for potential reuse or remanufacturing.</p>

<p dir="ltr">Manufacturing in the United States contributes a significant amount of money to its economy. Simultaneously, it consumes nearly one-third of the total energy produced within the nation. Computer-aided technologies have been developed to aid in streamlining the development of products created within the sector. Despite this, energy-efficiency processes are largely ignored by technologies developed by third-party vendors, within the subtractive manufacturing industry. Such benightedness sparked research into the development of mechanistic and data-driven models that attempt to accurately predict energy consumption. Unfortunately, the models largely fail to reflect the processes for which they are supposedly suitable due to poor experimental validation. The variables monitored within the literature are lacking and neglect to account for the inherent complexity of the processes. A model needs to be developed which properly accounts for the complexities associated with CNC machining. The variables such a model employs must account for variations in operations observed during manufacturing, as supplied via the process. The research conducted herein explores the development of an energy-predicting deep-learning model built upon data from data collected during complex CNC machining. Specifically, the model makes predictions by accepting supplemented numerically controlled programs and processing instructions sequentially, via a recurrent neural network layer. Four variants of the model are created to provide insights into the inclusion of supplementary information. Namely, the comparison of monitored material removal variables. The variables are depth of cut, width of cut, material removal rate, and the volume of material removed per NC instruction.</p>

<p dir="ltr">In our daily lives, we rely on a multitude of discrete products to meet our needs. Traditional product design approaches have primarily focused on economic and technical aspects, often overlooking the pressing environmental and social challenges facing society. Recognizing the limitations of our ecological systems to cope with the waste generated by our current industrial processes, there is a growing need to anticipate the potential consequences of product design across technical, economic, environmental, and social dimensions to pave the way for a sustainable future. One promising strategy within this context is the integration of sustainability principles into optimization-based design models that consider a product's entire life cycle. While there have been previous efforts to optimize product life cycles, a comprehensive exploration of optimization-based design methods with a focus on multiple objectives for discrete products is essential. This dissertation explores the integration of sustainability principles with optimization-based design by taking the electric traction motor used in electric vehicles as a case study. This complex and environmentally significant technology is ideal for investigating the tradeoffs and benefits of incorporating sustainability objectives into the design process.</p><p dir="ltr">The key tasks undertaken in this study are as follows:</p><ul><li>Development of a parametric design and optimization framework for a surface-mounted permanent magnet synchronous motor. In this task, a special emphasis is placed on reducing reliance on materials with a high supply risk, such as rare earth elements.</li><li>Creation of a parametric life cycle assessment model that combines life cycle assessment and optimization-based design to minimize a single-score environmental impact. This model offers insights into the environmental performance of product design and underscores the importance of minimizing environmental impact throughout a product's life cycle.</li><li>Integration of a life cycle costing model, incorporating techno-economic assessment and total cost of ownership perspectives, into the parametric life cycle assessment and optimization-based design models. This model is used to minimize levelized production and driving costs, shedding light on the trade-offs within this family of cost metrics and the optimization of manufacturing systems for motor production.</li><li>Proposal of a circular economy model/algorithm to assess the advantages of integrating the circular economy paradigm during the early design phase. All the mentioned objective functions are considered to study the impacts of applying the circular economy paradigm.</li></ul><p dir="ltr">The contributions of this research can be summarized as follows:</p><ul><li>Utilized a diverse array of analytical methodologies to parameterize the design process of a motor, incorporating the integration of Life Cycle Assessment (LCA) and Techno-Economic Analysis (TEA) models, as well as the incorporation of disassembly planning for informed decision-making in the early stages of design.</li><li>Proposed a generalized objective function denoted as the Supply Risk-equivalent (SR-eq.), aimed at mitigating the risks associated with the dependency on critical materials in product manufacturing.</li><li>Introduced a novel approach for visualizing non-dominated solutions within a multi-objective framework, with experimentation conducted on up to six distinct objectives.</li><li>Substantiated the significance of decarbonizing the electric grid while maintaining competitive cost structures, the importance of advancing non-destructive evaluation (NDE) procedures for assessing the condition of end-of-life (EoL) subassemblies, and optimizing the collection rate of EoL motors.</li></ul><p dir="ltr">Demonstrated that the optimization of technical metrics as surrogate indicators for economic and environmental performance does not necessarily yield designs that are concurrently optimal in economic and environmental terms.</p>