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In December 2019, a novel coronavirus broke out in Wuhan City, Hubei Province, and, as the center of the coronavirus disease 2019 (COVID-19) epidemic, the economy and production throughout Hubei Province suffered huge temporary impacts. Based on the input–output and industrial pollution emissions data of 33 industrial industries in Hubei from 2010 to 2019, this article uses the non-parametric frontier analysis method to calculate the potential production losses and compliance costs caused by environmental regulations in Hubei's industrial sector by year and industry. Research has found that the environmental technology efficiency of the industrial sector in Hubei is showing a trend of increasing year-on-year, but the overall efficiency level is still not high, and there is great room for improvement. The calculation results with and without environmental regulatory constraints indicate that, generally, production losses and compliance costs may be encountered in the industrial sector in Hubei, and there are significant differences by industry. The potential production losses and compliance costs in pollution-intensive industries are higher than those in clean production industries. On this basis, we propose relevant policy recommendations to improve the technological efficiency of Hubei's industrial environment, in order to promote the high-quality development of Hubei's industry in the post-epidemic era.
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PurposeThe COVID-19 pandemic has brought tremendous changes in society. Universities were among the few organisations with some previous knowledge of online education, being able to rapidly adapt by transferring already known best practices to the new context. As teaching moved to online, students encountered less sustainable implementation by their universities. This allowed the development of previously planned sustainable strategies so that when face-to-face teaching resumed, universities could be even more sustainable. This paper aims to explore loyalty to the sustainable university during the later COVID-19 pandemic based on the university's efforts to manage a green campus. Design/methodology/approachTo investigate loyalty towards the sustainable university during the later COVID-19 pandemic, a conceptual model is proposed. This research is grounded in an empirical investigation using a quantitative online survey implemented with online interviews, the relations between all latent constructs being analysed with SmartPLS. FindingsThe results show that university sustainability reflects student loyalty, outlining the image developed under the influence of green campus management. The results show that universities must intensify their efforts to support the sustainable agenda and create a sustainable academic brand, inducing student loyalty. The findings may attract the attention of other universities wishing to gain knowledge about the factors that students consider important in generating their loyalty. Research limitations/implicationsAs this research was carried out in the later COVID-19 pandemic context from 2021, the students already had experience of online teaching, so their assessment of the sustainability strategies implemented could be quite different from their perceptions in the first months of the pandemic. This research provides a comprehensive insight into the overall strategy that a sustainable university might apply in a crisis context. Social implicationsResearch has shown that green campus management has a positive impact on the sustainability of a university's image, on how students perceive the university at which they study and on the university's efforts to ensure efficient campus management. These factors contribute to the development of a strong and sustainable image of the university within the community. Originality/valueThe originality of this paper lies in the research questions designed to conceptualise and operationalise the generation of students' loyalty towards their university by encouraging and implementing sustainable strategies on campus. This paper highlights a structural model that combines strategic practices to determine students' loyalty towards a sustainable university during the COVID-19 pandemic.
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In recent work, a Hierarchical Bayesian model was developed to predict occupants' thermal comfort as a function of thermal indoor environmental conditions and indoor CO2 concentrations. The model was trained on two large IEQ field datasets consisting of physical and subjective measurements of IEQ collected from over 900 workstations in 14 buildings across Canada and the US. Posterior results revealed that including measurements of CO2 in thermal comfort modelling credibly increases the prediction accuracy of thermal comfort and in a manner that can support future thermal comfort prediction. In this paper, the predictive model of thermal comfort is integrated into a building energy model (BEM) that simulates an open-concept mechanically-ventilated office space located in Vancouver. The model predicts occupants' thermal satisfaction and heating energy consumption as a function of setpoint thermal conditions and indoor CO2 concentrations such that, for the same thermal comfort level, higher air changes per hour can be achieved by pumping a higher amount of less-conditioned fresh air. The results show that it is possible to reduce the energy demand of increasing fresh air ventilation rates in winter by decreasing indoor air temperature setpoints in a way that does not affect perceived thermal satisfaction. This paper presents a solution for building managers that have been under pressure to increase current ventilation rates during the COVID-19 pandemic. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.
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Owing to the COVID-19 pandemic, many companies have introduced working from home to avoid the risk of infection. In this study, we conducted questionnaire surveys and analysed the building energy management system (BEMS) in an office building where the number of employees working from home increased after the onset of the pandemic. The influence of working from home on the indoor environment satisfaction and the variability in energy consumption at home and office was determined. The indoor environment satisfaction was significantly higher when working from home than when working at the office. In 2020, the total energy consumption at home and office decreased by 30% in April and increased by 22% in August compared to the previous year. To work from home while saving energy regardless of the season, it is necessary to reduce office energy consumption by decreasing the number of workers present at the office. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.
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China has recently declared its role as a leading developing country in actively practicing carbon neutrality. In fact, its carbon-neutral policy has accelerated from a gradual and macroscopic perspective and has been actively pursued given the changes not only in the overall social system but also in its impact on various stakeholders. This study analyzed the patterns of carbon neutrality (CN) and the actors of policy promotion in China from a long-term perspective. It collected policy discourses related to CN posted on Chinese websites from 2000 to 2022 and conducted text mining and network analysis. The results revealed that the pattern of CN promotion in China followed an exploration-demonstration-industrialization-digitalization model, similar to other policies. Moreover, the policy promotion sector developed in the direction of unification-diversification-specialization. Analysis of policy promotion actors found that enterprises are the key driver of continuous CN. In addition, the public emerged as a critical actor in promoting CN during the 12th-13th Five-Year Plans (2011-2020). Moreover, the central government emerged as a key driving actor of CN during the 14th Five-Year Plan. This was a result of the emphasis on efficiency in the timing and mission process of achieving CN. Furthermore, based on the experience of COVID-19, the rapid transition of Chinese society toward CN emphasizes the need for a central government with strong executive power. Based on these results, this study presents constructive suggestions for carbon-neutral development in China.
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According to the World Economic Forum, the building sector is responsible for 40% of global energy consumption and 33% of greenhouse gas (GHG) emissions, and this is expected to increase due to population growth and the subsequent impact on the environment, economy and health. To tackle the problem, countries have set new construction codes, policies and regulations for the construction of new buildings in an effort to make them greener. However, there is a need to enhance the status of the existing buildings, especially mosques, as they are the main contributors to energy usage and water consumption in the United Arab Emirates (UAE). Therefore, this research seeks to fill this gap, aiming to evaluate the energy usage and water consumption practices employed in the existing mosque buildings within the UAE and to provide recommendations for improving the sustainability of mosques, with a focus on the environmental and economic pillars. The methodology relies mainly on data collected from 146 existing mosque buildings that have undergone energy saving audits across the UAE. Descriptive statistical analysis is performed to analyze the data from the period of 2018–2019 in order to determine the most significant factors related to energy inefficiency in existing mosque buildings in the UAE and to determine the most cost-effective and energy-saving corrective measures for energy and water conservation. The findings further enhance the standard of experience for mosque visitors (social aspect);reduce energy bill expenses, providing an acceptable return on investment from the proposed energy conservation measures for stakeholders (economic);and reduce the overall energy consumption, which can reduce the total CO2 emissions from mosque buildings (environmental).
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This study aims to propose building envelope retrofit packages for existing naturally ventilated school buildings in the hot–humid climatic region of Chennai, India. Indoor thermal parameters were collected through field studies from nine sample classrooms of a selected school building in May 2019, between 9.00 am and 4.00 pm. The thermal performance assessment of the existing building was performed by examining the discomfort hours using the CBE thermal comfort tool. Envelope retrofit strategies gathered from the literature and building standards were applied and studied through simulation. The findings reveal the enormous potential to increase the thermal comfort of existing school buildings through envelope retrofit measures. The results demonstrate that the whole-building temperature can be reduced up to 3.2 °C in summer and up to 3.4 °C in winter. Implementing retrofit measures to the building envelopes of existing buildings will help school owners to increase the comfortable hours of whole buildings by up to 17%. In comparison, annual energy savings of up to 13% for the whole building can be made by enhancing the thermal performance of the building envelope. The findings will also help architects to optimise thermal performance and energy usage with minimal interventions.
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Owning to the outbreak of COVID-19, individuals have to spend more time indoor. It is therefore essential to prepare for a long-term healthy indoor working environment in the transition of post COVID-19 pandemic. However, there is no relevant research so far in investigating such crisis impacts around indoor environmental quality and economic-health issues while home offices are expected becoming common practice soon. Therefore, a case of single-family house in Sweden is specially investigated using IDA ICE. By comparing four predominant ventilation approaches, three operational schedules are proposed, covering different confinement for occupants. Main results show that the demand response ventilation (DRV) generally should sacrifice in remarkable performance in energy saving, and emission reduction to better confront with more challenges in indoor air quality, occupied thermal dissatisfaction fraction and air stagnation under the challenge of COVID-19 pandemic scenario. Altered ventilation strategy should be customized from increased outdoor air supply, various demand-control signal, displacement method towards a heathier homeworking environment. © International Building Performance Simulation Association, 2022
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Decision trees are powerful tools for data classification. Accelerating the decision tree search is crucial for on-the-edge applications with limited power and latency budget. In this paper, we propose a content-addressable memory compiler for decision tree inference acceleration. We propose a novel ”adaptive-precision”scheme that results in a compact implementation and enables an efficient bijective mapping to ternary content addressable memories while maintaining high inference accuracies. We also develop a resistive-based functional synthesizer to map the decision tree to resistive content addressable memory arrays and perform functional simulations for energy, latency, and accuracy evaluations. We study the decision tree accuracy under hardware non-idealities including device defects, manufacturing variability, and input encoding noise. We test our framework on various decision tree datasets including Give Me Some Credit, Titanic, and COVID-19. Our results reveal up to 42.4%energy savings and up to <inline-formula><tex-math notation="LaTeX">$17.8\times$</tex-math></inline-formula> better energy-delay-area product compared to the state-of-art hardware accelerators, and up to 333 million decisions per sec for the pipelined implementation. IEEE
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This case study examines the Indian Institute of Technology Gandhinagar (IITGN) campus's monthly energy consumption profile in detail to understand how it varies according to academic calendar, seasonal variability, and the recent COVID 19 pandemic. In addition, a detailed assessment of the electricity bill and its sub-component calculations are intended to understand how the energy consumption pattern affects the overall monthly electricity bill. From this study, it is observed that the energy consumption of academic areas, hostel areas, and chiller plants account for 80-90% of total energy consumption. The on-site solar PV energy generation at IITGN campus accounts for 1014% of total monthly energy consumption, which varies greatly by season. The analyses performed in this paper were inferred by three years of historical data of actual energy consumption and monthly electricity bills. Based on the analysis presented in this paper some recommendations towards the energy conservation measures are also given. © 2022 IEEE.
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This paper explores ways to save energy in households with energy prosumers who generate energy using photovoltaic panels and heat pumps. On the basis of a literature analysis, we formulated a research gap in the case of the energy behaviors of prosumers. This research is important due to the growing demand for energy and the transitions of countries toward renewable energy sources. The role of prosumers in the economy is growing as they ensure energy independence and cost savings. The main purpose of this research is to understand the energy behaviors of prosumers and to examine the differences in energy behaviors between users of photovoltaic systems and heat pumps. A sample of 326 Polish prosumer households was selected using the CAWI method in order to obtain empirical data. The results suggest that prosumers show advanced ecological behaviors, and more than half of the respondents implement pro-ecological behaviors in their homes. Being a prosumer is associated with energy independence, which leads to economic stability and less dependence on traditional energy sources. The results indicate that prosumers show a general inclination toward pro-ecological behavior. Thus, this study recommends promoting prosumers and encouraging the use of pro-ecological energy as a priority for the economy. This initiative will contribute to a reduction in energy consumption in various areas, thus raising ecological awareness and a sense of responsibility for the environment.
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The energy consumption of Heating Ventilation and Air Conditioning (HVAC) systems accounts for a large proportion of global energy usage so even a small percentage of energy savings in these systems will account for important absolute value savings. One such saving can be realized by better designs as well as optimizing existing air distribution system. The indoor air quality (IAQ) is also greatly impacted by the air distribution system. In this work, the task of optimizing both the placement and the design of diffusers is investigated so acceptable Air Changes per Hour (ACH) numbers are attained with less energy consumption and good thermal comfort. The ANSYS Fluent software was used to optimize the design and placement of a newly developed diffuser. The proposed air distribution system is design to produce conditions like what one would experience while standing outside in a small breeze while experiencing perfect weather (room temperature, uniform air temperature distribution, air speed less than 2 m/s) [1]). This work is an extension of a previous study where a new diffuser design was proposed, which takes advantage of the Coanda effect [2]. The numerical analysis includes realistic models of a 9 × 9 × 3 m (width × length × height) classroom, which is occupied by students and a teacher. To be more realistic, it includes furniture, a door and windows. The simulated Heating Ventilation and Air Conditioning (HVAC) system complies with ASHRAE (American Society of Heating, Refrigerating and Air-Conditioning Engineers) standards for acceptable air quality. This investigation proposes a template on how anyone can optimize the location and placement of the air diffusers while achieving both thermal comfort and good IAQ. While this work was inspired by the COVID-19 pandemic this is foreseen to be an important ongoing issue and could lead to future advances in HAVC system that improve IAQ and produce better thermal comfort with improved energy savings. Copyright © 2022 by ASME.
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In energy saving operation of buildings, it is important to understand the energy consumption characteristics of university campuses in order to formulate specific energy saving plans. Due to COVID-19 expansion, it is assumed that infection prevention measures such as behavior change of students and ventilation are affecting the energy consumption characteristics. It is necessary to understand the energy consumption characteristics that have changed from the conventional ones. In this study, we analyzed energy consumption data on Meiji university campuses for the three years from 2019 to 2021. we clarify the energy consumption characteristics that have changed due to COVID-19 expansion. © 2023 Architectural Institute of Japan. All rights reserved.
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Postacute sequelae of COVID-19, also known as long COVID, affects approximately 10% to 30% of the hundreds of millions of people who have had acute COVID-19. The Centers for Disease Control and Prevention defines long COVID as the presence of new, returning, or ongoing symptoms associated with acute COVID-19 that persist beyond 28 days. The diagnosis of long COVID can be based on a previous clinical diagnosis of COVID-19 and does not require a prior positive polymerase chain reaction or antigen test result to confirm infection. Patients with long COVID report a broad range of symptoms, including abdominal pain, anosmia, chest pain, cognitive impairment (brain fog), dizziness, dyspnea, fatigue, headache, insomnia, mood changes, palpitations, paresthesias, and postexertional malaise. The presentation is variable, and symptoms can fluctuate or persist and relapse and remit. The diagnostic approach is to differentiate long COVID from acute sequelae of COVID-19, previous comorbidities, unmasking of preexisting health conditions, reinfections, new acute concerns, and complications of prolonged illness, hospitalization, or isolation. Many presenting symptoms of long COVID are commonly seen in a primary care practice, and management can be improved by using established treatment paradigms and supportive care. Although several medications have been suggested for the treatment of fatigue related to long COVID, the evidence for their use is currently lacking. Holistic treatment strategies for long COVID include discussion of pacing and energy conservation;individualized, symptom-guided, phased return to activity programs;maintaining adequate hydration and a healthy diet;and treatment of underlying medical conditions.Copyright © 2022 American Academy of Family Physicians.
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Since the coronavirus disease 2019, the extended time indoors makes people more concerned about indoor air quality, while the increased ventilation in seeks of reducing infection probability has increased the energy usage from heating, ventilation, and air-conditioning systems. In this study, to represent the dynamics of indoor temperature and air quality, a coupled grey-box model is developed. The model is identified and validated using a data-driven approach and real-time measured data of a campus office. To manage building energy usage and indoor air quality, a model predictive control strategy is proposed and developed. The simulation study demonstrated 18.92% energy saving while maintaining good indoor air quality at the testing site. Two nationwide simulation studies assessed the overall energy saving potential and the impact on the infection probability of the proposed strategy in different climate zones. The results showed 20%–40% energy saving in general while maintaining a predetermined indoor air quality setpoint. Although the infection risk is increased due to the reduced ventilation rate, it is still less than the suggested threshold (2%) in general. © 2022, Tsinghua University Press.
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In recent years, the production and consumption of fossil jet fuel have increased as a consequence of a rise in the number of passengers and goods transported by air. Despite the low demand caused by the coronavirus 2019 pandemic, an increase in the services offered by the sector is expected again. In an economic context still dependent on scarce oil, this represents a problem. There is also a problem arising from the fuel's environmental impact throughout its life cycle. Given this, a promising solution is the use of biojet fuel as renewable aviation fuel. In a circular economy framework, the use of lignocellulosic biomass in the form of sugar-rich crop residues allows the production of alcohols necessary to obtain biojet fuel. The tools provided by process intensification also make it possible to design a sustainable process with low environmental impact and capable of achieving energy savings. The goal of this work was to design an intensified process to produce biojet fuel from Mexican lignocellulosic biomass, with alcohols as intermediates. The process was modeled following a sequence of pretreatment/hydrolysis/fermentation/purification for the biomass-ethanol process, and dehydration/oligomerization/hydrogenation/distillation for ethanol-biojet process under the concept of distributed configuration. To obtain a cleaner, greener, and cheaper process, the purification zone of ethanol was intensified by employing a vapor side stream distillation column and a dividing wall column. Once designed, the entire process was optimized by employing the stochastic method of differential evolution with a tabu list to minimize the total annual cost and with the Eco-indicator-99 to evaluate the sustainability of the process. The results show that savings of 5.56% and a reduction of 1.72% in Eco-indicator-99 were achieved with a vapor side stream column in comparison with conventional distillation. On the other hand, with a dividing wall column, savings of 5.02% and reductions of 2.92% in Eco-indicator-99 were achieved. This process is capable of meeting a demand greater than 266 million liters of biojet fuel per year. However, the calculated sale price indicates that this biojet fuel still does not compete with conventional jet fuel produced in Mexico. © 2022 Society of Chemical Industry and John Wiley & Sons, Ltd. © 2022 Society of Chemical Industry and John Wiley & Sons, Ltd.
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World scenario after pandemic COVID-19 has been drastically changing and researchers more focusing on, to minimize the post-pandemic effects on economy, energy sustainability and food security. Agriculture sector is playing pivotal role in world food security and energy sustain -ability. There is high need to optimize the mechanization technologies to increase the yield in limited energy inputs and operation time to fulfill the world growing food demand. This research is mainly focused on the design development and structural analysis aiding with Finite Element Analysis (FEA) approach for Cotton Stalk Puller and Shredder machine (CSPS) to cut the crop leftovers, soil conditioning (shredding the plant waste into soil) and sowing of next crop in single run by con-serving input resources. The experimental trials revealed that there is high pressure on cutting blades, chocking of shredder section and excessive pulling load on tractor hitches, which affected the machine's performance. To mitigate deficiencies and design optimization to improve the machine safety/reliability, the structure analysis carried out. Six core components of machine including baseplate, blade, gear system, root digger, pulley and shaft has investigated as per field conditions. The results revealed that the material of blade, root digger and teeth of gear system receiving the high stress under the operational conditions which results the edge wear and damage. The carbonization up to one-millimeter thickness can provide the extra strength to bear the exces-sive load on edge layers.(c) 2022 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).
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With the increasing requirements for fresh air supply in buildings after the COVID-19 pandemic and the rising energy demand from buildings, there has been an increased emphasis on passive cooling techniques such as natural ventilation. While natural ventilation devices such as windcatchers can be a sustainable and low-cost solution to remove indoor pollutants and improve indoor air quality, it is not as reliable as mechanical systems. Integration with low-energy cooling, heating or heat recovery technologies is necessary for operation in unfavourable outdoor conditions. In this research, a novel dual-channel windcatcher design consisting of a rotary wind scoop and a chimney was proposed to provide a fresh air supply irrespective of the wind direction. The dual-channel design allows for passive cooling, dehumidification and heat recovery technology integration to enhance its thermal performance. In this design, the positions of the supply and return duct are "fixed” or would not change under changing wind directions. An open wind tunnel and test room were employed to experimentally evaluate the ventilation performance of the proposed windcatcher prototype. A Computational Fluid Dynamic (CFD) model was developed and validated to further evaluate the system's ventilation performance. The results confirmed that the system could supply sufficient fresh air and exhaust stale air under changing wind directions. The ventilation rate of the rotary scoop windcatcher was higher than that of a conventional 8-sided multidirectional windcatcher of the same size. © 2023 The Author(s)
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Floor radiation (FR) is one of the widely used heating modes in winter. However, the widespread and high outbreak of Corona Virus Disease 2019 (COVID-19) has made the disadvantage of floor radiation that lacks fresh air and air movement exposed as a deficiency. To seek a heating mode that can realize a comfortable and healthy indoor environment with low cost, the interactive cascade ventilation (ICV) coupling with multiple low-grade sources was proposed in this study. Energy efficiency, thermal comfort and air quality were investigated by comparing with FR and floor radiation with mixing ventilation (FRMV). The results showed that by elevating the same indoor temperature, ICV can reduce indoor heat transfer by 28.41% and 30.94% than FR and FRMV, respectively. And ICV also presented the highest system COP by introducing multiple low-grade sources. In terms of thermal comfort, the indoor environment served by ICV was closer to thermal neutrality, and the subjective thermal comfort can also be enhanced by 10% and 8% relative to FR and FRMV. The CO2 test results indicated that by introducing the ICV, indoor air quality can be improved by 36.68% and 61.45% over FR and FRMV with the contaminant removal rate significantly accelerated. During the pandemic, ICV can reduce the COVID-19 infection rate by 9.6% and 55.5% within 8 h and 30 min compared with FRMV. The conclusions obtained in this paper can provide new ideas for designing air conditioning systems in the epidemic and the context of carbon reduction.
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The COVID-19 crisis has demonstrated the importance of being able to understand complex computational models for everyday life. To make sense of the evolving predictive models of the COVID-19 pandemic, global citizens need to have a firm grasp of both systems thinking (ST) and computational thinking (CT). ST is the ability to understand a problem or phenomenon as a series of interconnected elements that produce emergent behaviors. CT involves decomposing a problem into quantifiable elements represented in an algorithmic form that can be interpreted or calculated by either a computer or a person. One new framework seeks to support student engagement in ST and CT by contextualizing these two types of thinking within the practice of constructing computational models. This framework explores how various aspects of ST and CT are embedded within different modeling practices, as well as how these modeling practices can help students as they construct, revise, and use computational models. This article explores how students interact with the various aspects of ST and CT as they build and refine computational models using SageModeler (a free web-based semi-quantitative system modeling application) in a chemistry unit on evaporative cooling. Through the examples presented in this article, the authors illustrate ways in which this framework can inform curriculum design and pedagogical practice.