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This paper contributes an inclusive review of scientific studies in the field of sustainable human building ecosystems (SHBEs). Reducing energy consumption by making buildings more energy efficient has been touted as an easily attainable approach to promoting carbon-neutral energy societies. Yet, despite significant progress in research and technology development, for new buildings, as energy codes are getting more stringent, more and more technologies, e.g., LED lighting, VRF systems, smart plugs, occupancy-based controls, are used. Nevertheless, the adoption of energy efficient measures in buildings is still limited in the larger context of the developing countries and middle income/low-income population. The objective of Sustainable Human Building Ecosystem Research Coordination Network (SHBE-RCN) is to expand synergistic investigative podium in order to subdue barriers in engineering, architectural design, social and economic perspectives that hinder wider application, adoption and subsequent performance of sustainable building solutions by recognizing the essential role of human behaviors within building-scale ecosystems. Expected long-term outcomes of SHBE-RCN are collaborative ideas for transformative technologies, designs and methods of adoption for future design, construction and operation of sustainable buildings.

Abstract Energy-efficiency investments that are costeffective to utilities may not be cost-effective to their customers if the customers have to bear the full investment cost. Utilities must find creative ways to make energy-efficiency investments more attractive to utility customers. An innovative utility manufactured (mobile) home energy conservation programme is described to illustrate how differences in the economic perspectives of consumers and utilities can be used to design energy-efficiency programmes. This successful programme uses ‘conservation acquisition’ to make the investment attractive to manufacturers, utilities, and the consumer. The programme and framework presented here provide models for developing other energy-efficiency programmes.

Abstract As a type of solid waste, the used cigarette filters (UCF) were utilized to produce ester-rich bio-oil via a cleaner production process, namely, microwave-assisted pyrolysis (MAP). The pyrolysis efficiency was significantly enhanced owing to the high heating rate under MAP conditions with assistance of microwave absorber silicon carbide (SiC) in reactor and adding methanol into N2 carrier gas. Compared with the traditional tubular muffle furnace heating method yielding 0% of bio-oil, the MAP heating method obtained 29.17% of bio-oil from UCF. The bio-oil yield from UCF increased from 29.17% to 46.71% due to the introduction of methanol. Results of the gas chromatography/mass spectrometry showed that esters were the main components in the bio-oils (over 40%), especially of methyl acetate (over 12%). The aromatic compounds of phenols and polycyclic aromatic hydrocarbons (PAHs) were also produced from the MAP of UCF. The bio-char from MAP of UCF exhibited the mesoporous property (e.g., over 500 m2/g of specific surface area). It is expected to produce over 350000 metric tons ester-rich bio-oil if the proposed technology can be scaled up globally. It will be a preeminent contribution for the conversion of UCF to the cleaner production and our environments.

Sustainability research has coalesced around the notion that many environmental problems can be framed as social dilemmas in which conflicts often arise between consumers’ pursuit of individual, short-term and self-directed goals and their support for collective, long-term and socially-oriented interests. The need to address this challenge is simultaneously becoming more important and challenging for macromarketers and policy makers as the incidence of individualistic consumer traits (e.g., narcissism and self-esteem), already high in general population, continues to grow throughout Western societies. This article examines why and how such individualistic tendencies (here, narcissistic exhibitionism) may impact consumers’ pro-environmental behavior. This research identifies an underlying mechanism (i.e., altruism) for the proposed effect. The potential effects of manageable boundary conditions for this relationship are also proposed and tested across four studies.

Abstract This work emphases the influence of using different heating sources (direct thermal, solar, infrared, microwave heating) on the pyro-oil yield. The effect of the dominating process parameters, namely the heating rate and final temperature, are thoroughly discussed with respect to the heating and reaction mechanism involved. Emphasis is then placed on reviewing the application of microwave (MW) heating in pyrolysis as a relatively new technology with many promising features, particularly the little-known mechanisms of MW heating, new MW heating pattern and pathway using MW absorbents for pyrolysis of waste materials. Machine learning (ML) techniques were then used to statistically analyze the 182 observations in 59 pyrolysis cases obtained from previous pyrolysis practices. The ML linear regression model was developed to predict oil yield by five input variables (feedstock type, feedstock size, heating rate, final temperature, and heating source), which can be used as a guideline for pyrolysis production management. By comparing three heating sources (direct, solar and MW), MW heating is found to be the most efficient method to achieve the highest oil yield. The Decision Tree Analysis demonstrates that the importance order for key variables is as: Log feedstock size > Log heating rate > Heating rate > Temperature > Feedstock size > Heating sources > Feedstock type. Future work should focus on optimizing the heating method and heating rate to achieve optimal yield and quality of pyro-oil. The findings are envisaged to be useful for scaling up the pyrolysis of waste materials for industrial energy applications.

Abstract Lignin is considered as a renewable and sustainable resource for producing value-added aromatic chemicals and functional carbon materials. Herein, we develop a one-step catalyst-free depolymerization strategy to convert lignin into aryl monomers and carbon nanospheres simultaneously. Importantly, microwave-assisted depolymerization (MAD) in conjunction with dichloromethane (CH2Cl2) vapors is developed. The total mass yield of guaiacols reached the highest amount of 225.1 mg/g at 600 °C, and the highest yields of phenols (49.0 mg/g) and aromatic hydrocarbons (155.1 mg/g) were obtained at 700 °C. Hydrogen radicals and hydrogen chloride (HCl) are in-situ formed from CH2Cl2, significantly decreasing the activation barrier and reforming pyrolysis vapors to promote the formation of aryl monomers. Interestingly, uniform carbon nanospheres with an average size of 140 nm were produced as co-products at 700 °C. The microwave “hot-spots”, allied with the continuous surface erosion and the decrease in surface energy of lignin-derived carbon precursors by CH2Cl2 vapor, can be considered the driving force for the ultimate formation of carbon nanospheres. The CH2Cl2/MAD system produces aryl monomers (26.8 wt% yield) and carbon nanospheres (36.6 wt% yield) at 700 °C. We provide a facile, intriguing and scalable approach to convert lignin to valuable aryl monomers and sustainable carbon materials that can be applied in the chemistry, energy and environmental fields.

Agriculture Cyber-Physical System (A-CPS) is becoming increasingly important in enhancing crop quality and productivity by utilizing minimum cropland. This paper introduces the innovative idea of the Internet-of-Agro-Things (IoAT) with an explanation of the automatic detection of plant disease for the development of ACPS. Majority of the crops were infected by microbial diseases in conventional agriculture. Also, the constantly mutating pathogens cannot be known to the knowledge of the farmer, due to which, there arises a demand to develop a disease prediction system. To prevent this, we use a trained Convolutional Neural Network (CNN) model to perform an analysis of the crop image captured by a health maintenance system. The image capturing along with continuous sensing and intelligent automation is performed by the solar sensor node. The sensor node houses a developed soil moisture sensor which has a high longevity compared to its peers. A real time implementation of the proposed system is demonstrated using a solar sensor node with a camera module, a microcontroller and a smartphone application using which a farmer can monitor the field. The prototype was deployed for three months and has achieved a robust performance by remaining rust-free and sustaining the varied weather conditions. An accuracy of 99.24% is achieved by the proposed plant disease prediction framework.

AbstractThe antimicrobial triclosan was analyzed in unfiltered samples from influent, effluent, and receiving stream and before and after a pilot‐scale constructed wetland at a North Texas municipal wastewater treatment plant. Triclosan concentrations were reduced by 97 to 99% by the activated sludge treatment plant. Effluent concentrations were further reduced by passage through the constructed wetland, but receiving stream concentrations were not statistically significantly different from effluent concentrations. Effluent concentrations of triclosan were seasonal with highest concentrations occurring during the summer months. The effluent‐dominated receiving stream maximum concentrations during summer months were below reported algal no‐observed‐effect concentrations based on biomass and growth rate but exceeded concentrations reported to cause shifts in algal community structure.

This work was aimed at improving the pyrolysis oil quality of waste rubber by adding larch sawdust. Using a 1 kg/h stainless pyrolysis reactor, the contents of sawdust in rubber were gradually increased from 0%, 50%, 100% and 200% (wt%) during the pyrolysis process. Using a thermo-gravimetric (TG) analyzer coupled with Fourier transform infrared (FTIR) analysis of evolving products (TG-FTIR), the weight loss characteristics of the heat under different mixtures of sawdust/rubber were observed. Using the pyrolysis-gas chromatography (GC)-mass spectrometry (Py-GC/MS), the vapors from the pyrolysis processes were collected and the compositions of the vapors were examined. During the pyrolysis process, the recovery of the pyrolysis gas and its composition were measured in-situ at a reaction temperature of 450 °C and a retaining time of 1.2s. The results indicated that the efficiency of pyrolysis was increased and the residual carbon was reduced as the percentage of sawdust increased. The adding of sawdust significantly improved the pyrolysis oil quality by reducing the polycyclic aromatic hydrocarbons (PAHs) and nitrogen and sulfur compounds contents, resulting in an improvement in the combustion efficiency of the pyrolysis oil.