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As smart cities become a global topic, interest in smart mobility, the core of smart cities, is also growing. The technology that comes closest to general users is “autonomous driving”. In particular, the successful market entry and establishment of some private companies proved that “autonomous driving” is not technology of the future but imminent reality. However, safety in autonomous vehicles that rely on sensors instead of the driver’s five senses has been the focus of attention from the beginning and continues to be so. In this study, we attempted to counter this interest. Based on the actual data of thirty traffic accidents, assuming the AEBS (Autonomous Emergency Braking System) was installed to assist the driver in safe driving, it was reinterpreted through simulation to see what changes occurred in the accident. In the computer program, PC-Crash, the results were first analyzed through simulation using Euro NCAP (New Car Assessment Program)’s AEBS test standards. Subsequently, the other variables in the AEBS were controlled and the accident was reinterpreted by changing only the angle of the radar detection sensor. As a result, it was confirmed that a total of 27 accidents out of thirty accidents could have been prevented with the AEBS. In addition, it proved that the crash avoidance rate of vehicles gradually increased as the radar angle increased.

Purpose This study aims to consider environmental sustainability, a global challenge under the preview of sustainable development goals, highlighting the significance of knowledge economy in attaining sustainable aggregate demand behavior globally. For this purpose, 155 countries that have data available from 1995 to 2021 were selected. The purpose of selecting these countries is to test the global responsibility of the knowledge economy to attain environmental sustainability. Design/methodology/approach Results are estimated with the help of panel quantile regression. The empirical existence of aggregate demand-based environmental Kuznets curve (EKC) was tested using non-linear tests. Moreover, principal component analysis has been incorporated to construct the knowledge economy index. Findings U-shaped aggregate demand-based EKC at global level is validated. However, environmental deterioration increases with an additional escalation after US$497.945m in aggregate demand. As a determinant, the knowledge economy is reducing CO2 emissions. The knowledge economy has played a significant role in global responsibility, shifting the EKC downward and extending the CO2 reduction phase for every selected country. Further, urbanization, energy intensity, financial development and trade openness significantly deteriorate the environmental quality. Originality/value This study contains the empirical existence of aggregate demand-based EKC. The role of the knowledge economy is examined through an index which is calculated by using four pillars of the knowledge economy (technology, innovations, education and institutions). This study is based on a combined panel of all the countries for which the data was available.

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 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.

This study searches the impact of tourism growth on emission pollutants in Cyprus (north), which is a small island in the Mediterranean and has shown significant development in hotel and casino sectors in the last two decades. Results from time-series analyses reveal that an inverted U-shaped EKC hypothesis is confirmed for Cyprus with and without tourism development. Tourism also exerts positively significant and long-term effects on the levels of carbon emissions, revealing that growth in the tourism sector causes degradation in the environment.

Microplastics are a growing concern in the environments and especially agricultural soil due to numerous negative impacts on the ecosystems and human health. This study aimed to investigate the properties of microplastics (including quantity, shape, size, and polymer types) in five samples (DA1-5) taken from agriculture soil in Dong Anh district, Hanoi using Nicolet iN10 MX Fourier transform infrared (µFTIR) microscope. The study found that the microplastic content in these soils ranging from 494 ± 292 items/kg dry weight to 1031 ± 379 items/kg dry weight. In terms of shape, microplastic fragments accounted for the majority of microplastics found in soil (65% - 86% of the total microplastics). Fifteen types of microplastic polymers were identified in the soil samples, with PET being the most common polymer of 38%, followed by urea-formaldehyde resin of 15%, and nylon of 13%. Microplastics with sizes ranging from 50-150 µm were the dominant group (39% - 57% of the total microplastics). This study provides an initial assessment of the presence of microplastics in the agricultural soil of the suburban area of Hanoi, highlighting the potential risk of contamination that may effect on environment and pose a threat to human health.

Shading the greenhouses is necessary in summer to reduce the solar radiation load. This however generates a considerable amount of thermal radiation heat load that needs to be removed via cooling systems. This study aimed to evaluate the effect of different shading configurations on the solar and thermal radiation in a greenhouse. Nets at four different locations were employed to shade the roof and side-walls of a polycarbonate, mechanically ventilated greenhouse. The spectral radiative properties of all these plastic materials were measured in short and long wave spectrum bands. The net solar and thermal radiations and air temperature were measured outside and inside two identical shaded and unshaded greenhouses. The results showed that external roof-shading is desirable, as it reduced the generated thermal radiation in the greenhouse by 21% and 15% during the day and night time, respectively and reduced the greenhouse air temperature during the day. The internal shading (roof and side walls) is undesirable, since it drastically increased the generated thermal radiation in the greenhouse by 147% and strongly increased the greenhouse air temperature during the day. Shading the side-walls is not recommended because it significantly reduces the transmitted solar radiation in the morning and afternoon (when the outside irradiance is low) and is useless at around noon when the outside irradiance is extremely high.

Room occupancy prediction based on indoor environmental quality may be the breakthrough to ensure energy efficiency and establish an interior ambience tailored to each user. Identifying whether temperature, humidity, lighting, and CO2 levels may be used as efficient predictors of room occupancy accuracy is needed to help designers better utilize the readings and data collected in order to improve interior design, in an effort to better suit users. It also aims to help in energy efficiency and saving in an ever-increasing energy crisis and dangerous levels of climate change. This paper evaluated the accuracy of room occupancy recognition using a dataset with diverse amounts of light, CO2, and humidity. As classification algorithms, K-nearest neighbors (KNN), hybrid Adam optimizer–artificial neural network–back-propagation network (AO–ANN (BP)), and decision trees (DT) were used. Furthermore, this research is based on machine learning interpretability methodologies. Shapley additive explanations (SHAP) improve interpretability by estimating the significance values for each feature for classifiers applied. The results indicate that the KNN performs better than the DT and AO-ANN (BP) classification models have 99.5%. Though the two classifiers are designed to evaluate variations in interpretations, we must ensure that they have accurate detection. The results show that SHAP provides successful implementation following these metrics, with differences detected amongst classifier models that support the assumption that model complexity plays a significant role when predictability is taken into account.