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The importance of the sustainability concept has gained increasing attention from scholars and practitioners. In this context, the aim of this study was to examine the determinants of intention to continue to use the new Metro in Qatar, which is considered a sustainable mode of travel. Therefore, in this paper, a special attention was paid to certain variables, such as environmental concern, perceived quality, and perceived benefits. A quantitative method approach was employed, in which data were collected based on self-administered questionnaires. A total of 1334 Qatar residents responded to the survey questionnaire, and Structural Equation Modeling (SEM) was used for hypothesis testing. The results confirmed the direct effects of perceived behavioral control, social influence, and attitudes on the intention of residents to continue to use the Metro network in their travel. Moreover, perceived behavioral control was found to play a mediating role, enhancing the indirect relationship between perceived benefits and intention to continue to use the Metro network. More importantly, environmental concerns significantly and positively affected the attitudes and perceived behavioral control of travelers; furthermore, these variables presented a mediated influence—through service quality—on the intention to continue to use the Metro network. This study enriched the sustainability behavior literature by examining the influences of crucial factors. Thus, this study is considered of great value for policy-makers who hope to maximize the awareness level of environmental sustainability among the population, in order to encourage them to embrace changes in their lifestyle towards becoming more environmentally responsible.

Microbial electrochemical technologies (METs) constitute the core of a number of emerging technologies with a high potential for treating urban wastewater due to a fascinating reaction mechanism—the electron transfer between bacteria and electrodes to transform metabolism into electrical current. In the current work, we focus on the model electroactive microorganism Geobacter sulfurreducens to explore both the design of new start-up procedures and electrochemical operations. Our chemostat-grown plug and play cells, were able to reduce the start-up period by 20-fold while enhancing chemical oxygen demand (COD) removal by more than 6-fold during this period. Moreover, a filter-press based bioreactor was successfully tested for both acetate-supplemented synthetic wastewater and real urban wastewater. This proof-of-concept pre-pilot treatment included a microbial electrolysis cell (MEC) followed in time by a microbial fuel cell (MFC) to finally generate electrical current of ca. 20 A·m−2 with a power of 10 W·m−2 while removing 42 g COD day−1·m−2. The effective removal of acetate suggests a potential use of this modular technology for treating acetogenic wastewater where Geobacter sulfurreducens outcompetes other organisms.

Dynamics of societal material stocks such as buildings and infrastructures and their spatial patterns drive surging resource use and emissions. Building up and maintaining stocks requires large amounts of resources; currently stock-building materials amount to almost 60% of all materials used by humanity. Buildings, infrastructures and machinery shape social practices of production and consumption, thereby creating path dependencies for future resource use. They constitute the physical basis of the spatial organization of most socio-economic activities, for example as mobility networks, urbanization and settlement patterns and various other infrastructures. This dataset features a detailed map of material stocks for the whole of Germany on a 10m grid based on high resolution Earth Observation data (Sentinel-1 + Sentinel-2), crowd-sourced geodata (OSM) and material intensity factors. Temporal extent The map is representative for ca. 2018. Data format Per federal state, the data come in tiles of 30x30km (see shapefile). The projection is EPSG:3035. The images are compressed GeoTiff files (*.tif). There is a mosaic in GDAL Virtual format (*.vrt), which can readily be opened in most Geographic Information Systems. The dataset features area and mass for different street types area and mass for different rail types area and mass for other infrastructure area, volume and mass for different building types Masses are reported as total values, and per material category. Units area in m² height in m volume in m³ mass in t for infrastructure and buildings Further information For further information, please see the publication or contact Helmut Haberl (helmut.haberl@boku.ac.at). A web-visualization of this dataset is available here. Visit our website to learn more about our project MAT_STOCKS - Understanding the Role of Material Stock Patterns for the Transformation to a Sustainable Society. Publication Haberl, H., Wiedenhofer, D., Schug, F., Frantz, D., Virág, D., Plutzar, C., Gruhler, K., Lederer, J., Schiller, G. , Fishman, T., Lanau, M., Gattringer, A., Kemper, T., Liu, G., Tanikawa, H., van der Linden, S., Hostert, P. (accepted): High-resolution maps of material stocks in buildings and infrastructures in Austria and Germany. Environmental Science & Technology Funding This research was primarly funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950). ML and GL acknowledge funding by the Independent Research Fund Denmark (CityWeight, 6111-00555B), ML thanks the Engineering and Physical Sciences Research Council (EPSRC; project Multi-Scale, Circular Economic Potential of Non-Residential Building Scale, EP/S029273/1), JL acknowledges funding by the Vienna Science and Technology Fund (WWTF), project ESR17-067, TF acknowledges the Israel Science Foundation grant no. 2706/19.

Microbial fuel cell (MFC) has received much attention in the last decade as a promising technology to simultaneously generate electricity and decontaminate wastewater. This study aims to quantitatively review the published literature on MFC, published in the period of 1970–2020, based on the Web of Science (WoS) database. For the first time in literature, a comprehensive quantitative review of MFC has been conducted by employing the technique of bibliometric and content analyses. A total of 11,397 publications have been retrieved from WoS, out of which 81.6% are research articles. The evaluation in the field of MFC has been mapped in various categories, such as publication history, publication distribution, subject category distribution, leading journals, leading countries and leading organizations in MFC research. Additionally, content analysis has been conducted to unearth the research trends in MFC; and some hot research topics in MFC have been spotted. Results depict that the period 2011–2020 has been the most appreciating era for MFC research, as it contributed 87% of the total publications. Among the subject categories, energy fuel and microbiology lead with contributions of 26.5% for each, butthe overall growth of the energy fuel category in the last decade has been the highest. Out of 1,147 journals publishing MFC research, Bioresource Technology is the leading one; and countries like China, USA and India are the main hub of MFC research with 26.47%, 16.95% and 7.69% contributions in publications, respectively. The hottest topics in MFC research are nanoparticles, catalysts, air electrodes, graphene electrodes, power enhancement, air cathode and nitrogen removal. Moreover, major research areas are engineering, energy fuels and biotechnology with each contribution 26.5% of the total publications.

Most of the existed works on the radio resource allocation (RRA) problem commonly assume the channel-state information (CSI) can be perfectly obtained by the transmission source. However, such assumption is not practical in the realistic wireless systems. In this work, we consider the practical implementation issues of resource allocation in orthogonal frequency division multiple access (OFDMA) two-way relay networks: the inaccuracy of channel-state information (CSI) available to the source. Instead, only the estimated channel status is known by the source. In this context, a joint optimization of subcarrier pairing and allocation, relay selection, and transmit power allocation is formulated in OFDMA two-way amplify-and-forward relay networks. Moreover, the objective of this work is to minimize the energy consumption of the overall system. Further, to ensure the quality of service (QoS) or data rate requirement, the energy consumption must be minimized without compromising the QoS. Therefore, by applying convex optimization techniques, energy-efficient algorithms are developed with the objective to minimize the total transmit power with guaranteeing the required data rates. Through simulation studies, energy consumption performance of the systems under the proposed schemes is investigated. It can be observed that our proposed scheme can improve the energy consumption performance of the considered system.

This study aimed to realize Sustainable Development Goals (SDGs), i.e., no poverty, zero hunger, and sustainable cities and communities through the implementation of an intelligent cattle-monitoring system to enhance dairy production. Livestock industries in developing countries lack the technology that can directly impact meat and dairy products, where human resources are a major factor. This study proposed a novel, cost-effective, smart dairy-monitoring system by implementing intelligent wireless sensor nodes, the Internet of Things (IoT), and a Node-Micro controller Unit (Node-MCU). The proposed system comprises three modules, including an intelligent environmental parameter regularization system, a cow collar (equipped with a temperature sensor, a GPS module to locate the animal, and a stethoscope to update the heart rate), and an automatic water-filling unit for drinking water. Furthermore, a novel IoT-based front end has been developed to take data from prescribed modules and maintain a separate database for further analysis. The presented Wireless Sensor Nodes (WSNs) can intelligently determine the case of any instability in environmental parameters. Moreover, the cow collar is designed to obtain precise values of the temperature, heart rate, and accurate location of the animal. Additionally, auto-notification to the concerned party is a valuable addition developed in the cow collar design. It employed a plug-and-play design to provide ease in implementation. Moreover, automation reduces human intervention, hence labor costs are decreased when a farm has hundreds of animals. The proposed system also increases the production of dairy and meat products by improving animal health via the regularization of the environment and automated food and watering. The current study represents a comprehensive comparative analysis of the proposed implementation with the existing systems that validate the novelty of this work. This implementation can be further stretched for other applications, i.e., smart monitoring of zoo animals and poultry.

Abstract This paper investigates the impact of urbanization on energy consumption by applying the Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) in case of Malaysia. The study covers the time period of 1970Q1–2011Q4. The unit root test and the ARDL bounds testing approach have been applied to examine integrating properties and long run relationship in the presence of structural breaks. Our results validated the existence of cointegration and exposed that urbanization is a major contributor in energy consumption. Affluence raises energy demand. Capital stock boosts energy consumption. Trade openness leads to affluence and hence increases energy consumption. The causality analysis finds that urbanization Granger causes energy consumption. The feedback effect is found between energy consumption and affluence and, energy consumption and capital. The bidirectional causality exists between trade openness and energy consumption.

This paper analyses the impact of postponing global mitigation action on abatement costs and energy systems changes in China and India. It compares energy-system changes and mitigation costs from a global and two national energy-system models under two global emission pathways with medium likelihood of meeting the 2 °C target: a least-cost pathway and a pathway that postpones ambitious mitigation action, starting from the Copenhagen Accord pledges. Both pathways have similar 2010–2050 cumulative greenhouse gas emissions. The analysis shows that postponing mitigation action increases the lock-in in less energy efficient technologies and results in much higher cumulative mitigation costs. The models agree that carbon capture and storage (CCS) and nuclear energy are important mitigation technologies, while the shares of biofuels and other renewables vary largely over the models. Differences between India and China with respect to the timing of emission reductions and the choice of mitigation measures relate to differences in projections of rapid economic change, capital stock turnover and technological development. Furthermore, depending on the way it is implemented, climate policy could increase indoor air pollution, but it is likely to provide synergies for energy security. These relations should be taken into account when designing national climate policies.