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Abstract The effect of the thermal environment on performance and productivity has been a focus of interest among indoor environmental researchers for nearly a century, but most of that work has been conducted in relative isolation from the cognate disciplines of human performance evaluation. The present review examines thermal environmental effects on cognitive performance research conducted across multiple disciplines. After differentiating performance from productivity, we compare the two dominant conceptual models linking thermal stress to performance; (1) the inverted-U concept and (2) the extended-U relationship. The inverted-U specifies a single optimum temperature (or its corresponding subjective thermal sensation) at which performance is maximised. In contrast, the extended-U model posits a broad central plateau across which there is no discernible thermal effect on cognitive performance. This performance plateau is bounded by regions of progressive performance decrements in more extreme thermal conditions. The contradictions between these opposing conceptual models might derive from various confounding factors at play in their underlying research bases. These include, inter alia, environment-related, task-related, and performer-related factors, as well as their associated two-way and three-way interaction effects. Methodological discrepancies that might also contribute to the divergence of these conceptual models are evaluated, along with the proposed causal mechanisms underlying the two models. The weight of research evidence reviewed in this paper suggests that the extended-U hypothesis fits the relationship between moderate thermal environments and cognitive performance. In contrast to the inverted-U relationship, implemention of the extended-U in indoor climate control implies substantial reductions in building energy demand, since it permits the heating and cooling setpoint deadband to expand across the full width of the thermal comfort zone, or even slightly further during emergencies such as peak demand events on the electricity grid. Use of personal comfort systems can further extend the thermostat setpoint range beyond the comfort zone.

Abstract Adsorbent-based carbon capture is only feasible if adsorption-desorption cycles are both fully regenerating and efficient. This work proposes a regenerative pH swing process and a pH swing regenerative adsorbent that are inspired by natural CO2 conversion by carbonic anhydrase biocatalysts found in mammalian red blood cells. The main objective is to develop, test and analyze a synthetic pH Swing Adsorption (pHSA) system as well as a pHSA compatible solid adsorbent to capture CO2 from a simulated ambient air gas stream. The lead developed adsorbent is a carbon black co-activated with potassium carbonate and nitrogenous copolymer that is impregnated with immobilized bovine carbonic anhydrase and thereby deemed “BCA/KN-CB”. BCA/KN-CB has preliminarily demonstrated both competitive CO2 adsorption capacity and limited regenerative ability under experimental pHSA conditions. In addition, BCA-based adsorbents achieved higher adsorption capacities than non-BCA adsorbent counterparts. The BCA/KN-CB adsorbent displayed both large point of zero charge (PZC) swings and regenerative stability. The proposed pHSA system requires essentially zero energy expenditure to achieve intended environments for capture and regeneration. With 1 kg of adsorbent, pHSA has the ability to capture 1 kg CO2 in less than 4 h of cycling. The tested pHSA adsorbent can also capture more than 96% of total CO2 in a given raw gas stream flowing through the capture chamber. This proof-of-concept study of a pH swing adsorption/biocatalytic adsorbent system suggests the potential to effectively operate under ambient conditions and exhibit advantageous operational efficiencies to other high-profile CO2 capture systems.

Abstract For 118 million residential housing units in the U.S., there is currently a gap between the potential energy savings that can be achieved through the use of existing energy efficiency technologies, and the actual level of energy savings realized, particularly for the 37% of housing units that are considered residential rental properties. Additional quantifiable benefits are needed beyond energy savings to help further motivate residential property owners to invest in energy efficiency upgrades. This research focuses on assessing the adoption of energy efficient upgrades in U.S. residential housing and the impact on rental prices. Ten U.S. cities are chosen for analysis; these cities vary in size across multiple climate zones, and represent a diverse set of housing market conditions. Data was collected for over 159,000 rental property listings, their characteristics, and their energy efficiency measures listed in rental housing postings across each city. Following an extensive data quality control process, over thirty different types energy efficient features were identified. The level of adoption was determined for each city, ranging from 5.3% to 21.6%. Efficient lighting and appliances were among the most common, with many features doubling as energy efficient and other desirable aesthetic or comfort improvements. Then using propensity score matching and conditional mean comparison methods, the relative impact on rent charged in each city was calculated, which ranged from a 6% to 14.1% increase in rent for properties with energy efficient features, demonstrating a positive economic impact of these features, particularly for property owners. This was further subdivided into five types of energy efficiency upgrade and three housing types. Single family homes generally demanded higher premiums with energy efficient features, however there was not a consistent pattern across the types of efficient upgrades. The results of this work demonstrate that investment in energy efficient technologies has quantifiable benefits for rental property owners in the U.S. beyond just energy savings. This methodology and results can also be used in other cities and by property owners, utility companies, or others, ultimately encouraging further investment and positive economic impact in residential energy efficiency and in turn improving energy and resource conservation in the building sector.

Interconnectivity and interoperability are very important features in the development of integrated energy management systems for industrial facilities. A simple and common strategy for exchanging energy-related information among the entities in a facility is currently lacking. To this end, the purpose of this study is to present an IoT-based communication framework with a common information model to facilitate the development of a demand response (DR) energy management system for industrial customers. Additionally, we developed and implemented an IoT-based energy-management platform based on a common information model and open communication protocols, which takes advantage of integrated energy supply networks to deploy DR energy management in an industrial facility. The experimental results of this study demonstrate that the proposed platform can not only improve the interconnectivity of the entities in industrial energy management systems but also reduce the energy costs of industrial facilities.

Abstract Energy harvesting in natural environment has attracted a great deal of attention to generate stable and continuous electrical energy. In this work, we proposed an advanced pyroelectric energy harvesting system by using form-stable phase change material (PCM) composites. The PCM composite connected pyro-electrode generated electrical polarization due to the change of external environment. Polyethylene glycol (PEG) and 1-tetradecanol (1-TD) composites with different phase transition field induced the temperature difference during light-on/-off process. Poly(vinylidene difluoride) (PVDF) was utilized for pyroelectric energy harvesting. The PVDF based pyro-electrode was applied changing the conditions of solar light irradiation and heat air flow. The PCM composites controlled the temperature fluctuation effectively and generated stable output electrical voltage and current. Numerical simulation was carried out to provided in-depth insight into the underlying physics of the system. We envisage that the developed thermal energy harvesting system can pave a way towards high-throughput and sustainable energy harvesting.

Abstract Wood biomass char was used in a direct carbon fuel cell (DCFC) as an alternative fuel. This has many advantages because the DCFC is a high-efficiency system and wood biomass is a carbon-free and regenerative material. Several analytical techniques were employed to analyze the characteristics of three fuels, their effects on the cell’s performance, and the electrochemical reactions between the fuels and the electrolyte in the system. The morphological and textural characteristics of biomass char were similar to those of two types of coal used as fuels for a DCFC system in spite of the char’s significantly lower carbon content. A practical evaluation of the fuels used in the DCFC system was conducted, and when using the biomass char, the maximum power density was 60–70% that of the corresponding value for coal under the same conditions. The performance of the biomass char fuel was improved by stirring. The possibility of its practical application was also discussed.

Abstract The South Korean government has been actively promoting an educational-facility improvement program as part of its energy-saving efforts. This research seeks to develop a decision support model for selecting the facility expected to be effective in generating energy savings and making the facility improvement program more effective. In this research, project characteristics and electric-energy consumption data for the year 2009 were collected from 6282 elementary schools located in seven metropolitan cities in South Korea. In this research, the following were carried out: (i) a group of educational facilities was established based on electric-energy consumption, using a decision tree; (ii) a number of similar projects were retrieved from the same group of facilities, using case-based reasoning; and (iii) the accuracy of prediction was improved, using the combination of genetic algorithms, the artificial neural network, and multiple regression analysis. The results of this research can be useful for the following purposes: (i) preliminary research on the systematic and continuous management of educational facilities’ electric-energy consumption; (ii) basic research on electric-energy consumption prediction based on the project characteristics; and (iii) practical research for selecting an optimum facility that can more effectively apply an educational-facility improvement program as a decision support model.

Abstract Because of the increased need for virtual analysis during the vehicle manufacturing processes, more stringent optimization methods are required for the simulation field. Owing to the use of big data from engine testing, 1D analysis can provide more powerful approaches in the conceptual design phase for car makers. In this study, system-level optimization of dual-loop EGR was performed at both the engine and vehicle level, whereas our previous research had been performed at the engine level. Depending on the virtually developed engine and vehicle models and control scheme from our previous works, improved driving capabilities could be observed under light-duty diesel vehicle systems under the world-harmonized light-vehicles test procedure (WLTP). The numerical model was extended through two steps. The first step includes model conversion from the base engine model with an HP EGR system to a virtual engine model with a dual-loop EGR system. The second step represents mode extension from the virtual engine model with a dual-loop EGR system to a vehicle model with a dual-loop EGR system. Optimizing the dominant parameters and using design of experiment (DoE)-based multi-objective Pareto optimization methods in each step, fuel economy could be improved by approximately, 1.5% and the deNOX rate was approximately 5% that of the conventional NEDC. It is implied that the dual-loop EGR system and gear strategy could improve vehicle performance under difficult driving conditions.

Abstract Bioproducts from biomass feedstocks and organic wastes have shown great potential to address challenges across food-energy-water systems. However, bioproducts production is at an early, nascent stage that requires new inventions and cost-reducing approaches to meet market needs. Biochar, a byproduct of the pyrolysis process, derived from nutrient-rich biomass feedstocks (e.g., cattle manure and poultry litter) is one of these bioproducts that has numerous applications, such as improving soil fertility and crop productivity. This study investigates the market opportunity and sustainability benefits of converting manure to biochar on-site, using a portable refinery unit. Techno-economic and environmental impact assessments are conducted on a real case study in Twin Falls, Idaho, USA. The techno-economic analysis includes a stochastic optimization model to calculate the total cost of biochar production and distribution. The environmental study employs a life cycle assessment method to evaluate the global warming potential of manure-to-biochar production and distribution network. The total cost of biochar production from cattle manure near the feedlots is approximately $237 per metric ton, and total emission is 951 kg CO2 eq. per metric ton. The on-site operation and manure moisture content are two key parameters that can reduce biochar unit price and carbon footprint of manure management. It is concluded that converting cattle manure, using the presented strategy and process near the collection sites can address upstream and midstream sustainability challenges and stimulate the biochar industry.