ALBERT

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 50〈/p〉 〈p〉Author(s): Zhengrong Li, Haowei Xing, Godfried Augenbroe〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉Although there have been numerous studies on the evaluation of models that estimate sky diffuse radiation on inclined surfaces, it is still difficult for investigators to select from available sky diffuse radiation models for urban microclimate and building performance simulation. This is due to the fact that results from different studies are not consistent, or even contradictive, which indicates the fact that the evaluation criterion itself has a great effect on the performance of the model.〈/p〉 〈p〉To explore the effect of different evaluation criteria on the performance rating of the models, four evaluation methods are applied in this paper: diffuse irradiance on facades with respect to sky condition, diffuse irradiance on facades with respect to orientation, diffuse irradiance distribution among sky dome with respect to sky condition and diffuse irradiance on buildings in obstructed environment. Based on a statistical test on available data, Igawa model is considered to be the most accurate and appropriate model for urban and building energy simulation. Besides, an evaluation criterion appropriate for screening sky diffuse models for urban and building energy simulation is proposed. Furthermore, potential errors that may occur in the measurement and the corresponding quality control is presented.〈/p〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 50〈/p〉 〈p〉Author(s): D. Koteswara Rao, D. Chandrasekharam〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Sustainable conservation of natural resources has become a primary concern for urban cities, globally as they are centers of consumption and economy. Due to population growth, cities depend more on imports of food, energy, water, and services from all over the globe, and consume more virtual water than direct water, because of their food habits and lifestyle. Most of the imported goods are water intensive and pose challenges in tracing the source of virtual water. The goal of this research is to develop a general framework to assess the water footprint (WF) of a typical city in India using existing databases. A consumer-centric approach has been adopted for assessing WF in Hyderabad Metro Development Area (HMDA). The variation of the WF across economic classes of consumers is also analyzed. The WF is estimated based on four broad categories: 1) food consumption, 2) fossil fuels based energy, 3) electric power, and 4) direct water. Average WF of HMDA region is 1041 m〈sup〉3〈/sup〉/cap/year (2852 LPCD), in which 70% (1986 LPCD) of WF was consumed by food, 25% (744 LPCD) by electric power, only 4% (121 LPCD) is from direct water consumption and surprisingly the contribution from fossil fuel WF to total per capita WF of HMDA area is less than 1%.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 5 July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society〈/p〉 〈p〉Author(s): Shuqin Chen, Xiyong Zhang, Shen Wei, Tong Yang, Jun Guan, Wenxiao Yang, Lijuan Qu, Yunqing Xu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Accurate grasp of district power demand is of great significance to both sizing of district power supply and its operation optimization. In this study, an index system has been established and visualized through a Geographic Information System, for revealing both temporal and spatial characteristics of district power loads caused by heating/cooling systems, including load level and fluctuation characteristics, spatial distribution of electric loads, and load coupling relationships between individual buildings and the district. Principal component analysis was applied to identify the buildings with significant impact on district load management. Using this method, the spatial-temporal characteristics of electric loads caused by heating in one university campus in China were analyzed. The results showed that building type and the operation modes had great effects on the level and volatility of the district electric load caused by heating. Buildings with high load levels and strong coupling with the peak district electric load, such as academic buildings, often had a major impact on the power demand of the district. Therefore, they were considered as key targets for energy-saving renovation and operation optimization. Buildings with large load fluctuation, such as teaching buildings, could contribute to the peak load shaving by adjusting the heating systems’ operation.〈/p〉〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 50〈/p〉 〈p〉Author(s): Shuo-Jun Mei, Zhiwen Luo, Fu-Yun Zhao, Han-Qing Wang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Urban ventilation is important for building a healthy urban living environment. 2-D CFD simulation has been used widely for street canyon ventilation due to its high computational efficiency, but its applicability for a 3-D simulation has never been studied. This paper tried to answer the question: if and under what conditions, the widely-adopted 2-D CFD simulations on street canyon ventilation can represent a 3-D scenarios? 3-D simulations on street canyons with various street lengths and corresponding 2-D simulations are carried out with RNG 〈em〉k〈/em〉-〈em〉ε〈/em〉 model. Our study identified two important ventilation mechanism for controlling ventilation and dispersion in a 3-D street canyon, i.e., canyon vortex on the canyon top and the corner vortices at the street ends. The relative importance of these two driving forces will change with the street length/street width ratio (〈em〉B/W〈/em〉). For isolated street canyon, when 〈em〉B/W〈/em〉 is higher than 20 (for 〈em〉H/W〈/em〉 = 1) and 70 (〈em〉H/W〈/em〉 = 2), the street canyon ventilation will be dominated by canyon vortex, and 3-D street canyon ventilation could be simplified as a 2-D case. For multiple street canyon, the threshold of 〈em〉B/W〈/em〉 will become 20 when 〈em〉H/W〈/em〉 = 1, and 50 when 〈em〉H/W〈/em〉 = 2. The findings in this study could improve our approaches for simulating urban ventilation.〈/p〉〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 50〈/p〉 〈p〉Author(s): Gaofeng Gu, Dujuan Yang, Tao Feng, Harry Timmermans〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The increasing shift of individuals to use new electric mobility tools like electric cars (EV) and electric bikes has changed household energy expenditure. It may also affect households’ investments in renewable energy equipment, i.e. solar panels, heat pumps. Relatively little research has been conducted on how the decision to purchase electric vehicles affects the decision to invest in home renewable energy equipment. This paper, therefore, aims to examine the effects of mobility tools decisions on the intention to invest in solar panels and heat pumps, based on the data collected through a stated choice experiment. A mixed logit model is estimated to capture unobserved heterogeneity among individuals. Results show that mobility tools significantly influence the choice of home renewable energy equipment. Households who prefer to purchase electric vehicles have a higher probability to invest in solar panels and heat pumps than households who prefer other mobility tools. In addition, EV adopters’ intention to invest in solar panels are stronger than the intention to invest in heat pumps. This suggests that electric vehicle users are likely the early adopters of solar panels.〈/p〉〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 50〈/p〉 〈p〉Author(s): Heictor Correia Maioli, Raíssa Corrêa de Carvalho, Denise Dumke de Medeiros〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The increase in population concentration in large cities is a trend in the world, which brings several problems. In the context of urban mobility, bicycle sharing systems deserve special mention due to the impact and growth worldwide. The dissemination and success of these systems are also linked to aspects related to quality in their provision. Thus, this paper aims to conduct a study in the context of bicycle sharing to help managers to stimulate the use of this service and contribute to the development of sustainable cities. The SERVPERF tool was adapted and used to assess the quality of bicycle sharing service, in addition to identify which aspects impact on users’ satisfaction. This approach is innovative since there is a gap in the literature about customer satisfaction analyzes and aspects related to the quality of bicycle sharing service. In this way, this study can contribute to the dissemination of this service and to the solution of urban mobility problems by identifying the aspects considered as most important for the customers and thus improving these aspects. Therefore, the bicycle sharing system may have the increasingly use and will help to reduce urban mobility problems.〈/p〉〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 50〈/p〉 〈p〉Author(s): Zhijian Liu, Di Wu, Yuanwei Liu, Guangya Jin, Qiaomei Wang, Zhonghe Han, Hancheng Yu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Low energy buildings are an efficient approach to meet space heating requirements and saving energy. Studies of low energy buildings mainly focus on cold climate regions. However, there is less research on the feasibility of low energy buildings on Qinghai-Tibetan Plateau located in a severely cold climatic region. Therefore, a low energy building equipped with an integrated heating system was built on Qinghai-Tibetan Plateau. The performance of the low energy building was quantitatively evaluated by field measurement and dynamic TRNSYS simulation. To be specific, the indoor temperature and relative humidity were measured, and further served as the data to verify the accuracy of the simulated results. The results show that the temperature and humidity were above 20 °C and 40% in the heating season, in accordance with the regulated low energy building standard (DB63/T1682-2018). According to the TRNSYS simulation, the hourly indoor temperature and relative humidity were generally in the range of 20–24 °C and 34–56%, respectively, in the heating season, with an energy demand of 16.1 kW h/(m〈sup〉2〈/sup〉 year). Overall, the building performance meets the local low energy building standard (DB63/T1682-2018). Therefore, a passive building with integrated heating system assistance is feasible for pleasant indoor comfort on Qinghai-Tibetan Plateau. These findings could explore the application potential of low energy buildings in severe cold climate areas.〈/p〉〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 73〈/p〉 〈p〉Author(s): James H. Gawron, Gregory A. Keoleian, Robert D. De Kleine, Timothy J. Wallington, Hyung Chul Kim〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Although recent studies of autonomous taxis (ATs) have begun to explore potential environmental implications of fleet deployment, little is known about their impacts over the long term. We present a life-cycle assessment framework that incorporates both direct and indirect effects of ATs at the subsystem, vehicle, and mobility-system levels. Eco-driving and intersection connectivity are the direct effects analyzed along with indirect effects that include empty kilometers, parking, charging infrastructure, powertrain rightsizing, electric vehicle adoption, ride-sharing, and fleet-turnover rates. A case study of an AT fleet in Austin, Texas from 2020 to 2050 with constant travel demand indicates the strategic deployment of an electrified AT fleet can reduce cumulative energy and greenhouse gas (GHG) emissions by 60% in the base case, with a majority of this benefit resulting from electrified powertrains. Further reductions up to 87% can be achieved with accelerated electrical grid decarbonization, dynamic ride-share, longer vehicle lifetime, more energy efficient computer systems, and faster fuel efficiency improvements for new vehicles. We highlight the major opportunities for maximizing the environmental performance of AT fleets over the long term.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 73〈/p〉 〈p〉Author(s): Ran Tu, Lama Alfaseeh, Shadi Djavadian, Bilal Farooq, Marianne Hatzopoulou〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Communication between vehicles and road infrastructure can enable more efficient use of the road network and hence reduce congestion in urban areas. This improvement can be enhanced by distributed control due to its lighter computational load and higher reliability. Despite favourable impacts on traffic, little is known about the effects of such systems on near-road air quality. In this study, an End-To-End (E2E) dynamic distributed routing algorithm in Connected and Automated Vehicles (CAVs) was applied in downtown Toronto, to identify whether benefits to network throughput were associated with lower near-road NO〈sub〉2〈/sub〉 concentrations. We observe significant reductions in the emissions of Greenhouse Gases (GHGs) with increased penetration of CAVs. Nonetheless, at times, the emissions of nitrogen oxides (NO〈sub〉x〈/sub〉) increased with higher CAVs. Besides, a higher frequency and severity of NO〈sub〉2〈/sub〉 hot-spots were observed under a 100% CAV scenario. Impacts of the proposed system on electric energy consumption in a full electric vehicle network were also investigated, indicating that the addition of CAVs that are electric did not contribute to high energy savings. We propose that such new transformative technologies in transportation should be designed with air pollution and public health goals.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 50〈/p〉 〈p〉Author(s): Abdelkader Dairi, Tuoyuan Cheng, Fouzi Harrou, Ying Sun, TorOve Leiknes〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Wastewater treatment plants (WWTPs) are sustainable solutions to water scarcity. As initial conditions offered to WWTPs, influent conditions (ICs) affect treatment units states, ongoing processes mechanisms, and product qualities. Anomalies in ICs, often raised by abnormal events, need to be monitored and detected promptly to improve system resilience and provide smart environments. This paper proposed and verified data-driven anomaly detection approaches based on deep learning methods and clustering algorithms. Combining both the ability to capture temporal auto-correlation features among multivariate time series from recurrent neural networks (RNNs), and the function to delineate complex distributions from restricted Boltzmann machines (RBM), RNN-RBM models were employed and connected with various classifiers for anomaly detection. The effectiveness of RNN based, RBM based, RNN-RBM based, or standalone individual detectors, including expectation maximization clustering, K-means clustering, mean-shift clustering, one-class support vector machine (OCSVM), spectral clustering, and agglomerative clustering algorithms were evaluated by importing seven years ICs data from a coastal municipal WWTP where more than 150 abnormal events occurred. Results demonstrated that RNN-RBM-based OCSVM approach outperformed all other scenarios with an area under the curve value up to 0.98, which validated the superiority in feature extraction by RNN-RBM, and the robustness in multivariate nonlinear kernels by OCSVM. The model was flexible for not requiring assumptions on data distribution, and could be shared and transferred among environmental data scientists.〈/p〉〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Neng Zhu, Daokun Chong〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Hyperthermal environments in public or industrial buildings impose substantial heat stress on the human body. To ensure human health in built environments, research has focused on the interactions between the heat tolerance and environments. This paper summarizes the progress in the literature concerning the evaluation and improvement of heat tolerance in three areas: environmental and physiological parameters, heat tolerance evaluation indexes, and heat acclimation (HA). This review leads to four conclusions: (1) Future indexes should give top priority to subjective perceptions to diminish individual differences; (2) machine learning techniques based on big data should be adopted to deal with complex correlations between hot environments and heat tolerance; (3) an optimal HA training regimen should be determined for workers to improve their heat tolerance and HA should be considered in the design and control strategies of indoor thermal environments for energy conservation; and (4) more field investigations should be conducted to modify laboratory-based findings. This review provides a comprehensive understanding of built environments and health and guidelines for future research.〈/p〉〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Sophie A. Nitoslawski, Nadine J. Galle, Cecil Konijnendijk van den Bosc, James W.N. Steenberg〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉Smart cities are increasingly part of urban sustainability discourses. There is a growing interest in understanding how citizen engagement, connected technology, and data analytics can support sustainable development. Evidence has also repeatedly shown that green infrastructure such as urban forests address diverse urban challenges and are critical components of urban sustainability and resilience. Nevertheless, it is unclear whether green space and urban forest management are gaining significant traction in smart city planning. It is thus timely to consider whether and to what extent urban forests and other green spaces can be effectively integrated into smart city planning, to maximize green benefits for all city dwellers.〈/p〉 〈p〉We address this gap by exploring current and emerging smart city trends and technologies, and highlight practical applications for urban forest and green space management. Current “smart urban forest” projects reveal a focus on novel monitoring techniques using sensors and Internet of Things (IoT) technologies, as well as open data and citizen engagement, particularly through the use of mobile devices, applications (“apps”), and open-source mapping platforms. We propose a definition and promising approach to “smart urban forest management”, emphasizing both the potential of digital infrastructure to enhance forest benefits and the facilitation of citizen stewardship and empowerment in green space planning. Cities are getting faster and smarter – can (and should) the trees, and their managers, do the same?〈/p〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Jun Bao, Yu Wang, Xinjie Xu, Xiaoyi Niu, Jinxiang Liu, Lanlan Qiu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The development of big data leads to the increasing heat dissipation of data center chips. As an efficient pattern to remove high heat flux, spray cooling has huge potential for data center cooling. Spray cooling system was established combined with PIV (Particle Image Velocimetry) system. The PIV was used to measure the flow pattern distribution of different nozzle sprays, while the surface heat flux and heat transfer coefficient were obtained by the thermocouples. The results show that as the spray diameter decreases, the outlet pressure and outlet velocity of the droplet increase, and the spray cone angle increases, causing only a small amount of droplets actually participate in the heat exchange, resulting in a higher velocity and a smaller heat transfer coefficient. It is also inferred that better uniformity of droplets velocity is beneficial for the heat transfer performance. Moreover, to further enhance the heat transfer performance, nano-alumina solution with five different fractions was applied to the experimental system. It is found that the heat transfer coefficient of the surface reaches an optimum value with a maximum velocity obtained by the PIV when the mass fraction of the solution is 0.08%.〈/p〉〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Peleg Kremer, Annegret Haase, Dagmar Haase〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, we introduce the special issue “The future of urban sustainability: Smart, efficient, green or just?” the special issue aims to explore the relationships, conflicts and connections between different approaches to urban sustainability and begin to build a shared understanding of the roles, synergies and tradeoffs between them. Papers in this special issue emphasize the multidimensionality of urban sustainability and its integration of social, ecological, economic, and technological systems.〈/p〉〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Sabah Abdul-Wahab, Ziyad Alsubhi〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Despite the small quantities of hydrogen fluoride (HF) that are emitted from aluminum smelters compared with the other gaseous emissions, HF is one of the most dangerous gases to be considered when studying the environmental impact of these smelters. Therefore, modeling HF dispersion is essentially important to make sure that concentrations do not exceed threshold limit, especially for buildings, which are located close to the emission source. The objective of the current study was to examine the dispersion of atmospheric HF emitted from an aluminum smelter located in Oman. The results of the study indicated that the concentrations were found to be well below the allowable concentrations. Results in winter showed that the highest hourly HF concentration (0.104 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si3.svg"〉〈msup〉〈mrow〉〈mtext〉 〈/mtext〉〈mtext〉μ〈/mtext〉〈mtext〉g〈/mtext〉〈mo〉/〈/mo〉〈mtext〉m〈/mtext〉〈/mrow〉〈mn〉3〈/mn〉〈/msup〉〈mo stretchy="false"〉)〈/mo〉〈/math〉 was occurred at 18:00 h local standard time and was found to be at a location −9.5 km west and 2.5 km north of the plant. Conversely, the simulation in summer indicated that the highest hourly HF concentration (0.374 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si4.svg"〉〈msup〉〈mrow〉〈mtext〉μ〈/mtext〉〈mtext〉g〈/mtext〉〈mo〉/〈/mo〉〈mtext〉m〈/mtext〉〈/mrow〉〈mn〉3〈/mn〉〈/msup〉〈mo stretchy="false"〉)〈/mo〉〈/math〉 was obtained at 22:00 h and was found to be at a location -8.5 km west and 3.5 km north of the plant. The results of the study will have significant importance to the residents, stakeholders, and related permitting authorities in the area.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 29 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment〈/p〉 〈p〉Author(s): Zhao Zhang, Brian Wolshon, Pamela Murray-Tuite〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Evacuations, a critical and widely used emergency response action, vary widely in terms of their scale, scope, urgency and level of organization. While they differ from event to event, history shows that there are a small set of variables, inherent to all evacuations, that largely govern their effectiveness. In this paper, these fundamental variables are described from a theoretical perspective to illustrate how factors of evacuation demand and supply affect clearance time and how they can also be used to relate evacuation planning to concepts of risk, resiliency, and resource allocation. This work provides a basis for a general theory of evacuation processes that can be used it to conceptualize relationships like cost-benefit tradeoffs in evacuation management to improve long-range evacuation planning through a better understanding of the investment and allocation of resources.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 75〈/p〉 〈p〉Author(s): Kate Hosford, Meghan Winters, Daniel Fuller〈/p〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 75〈/p〉 〈p〉Author(s): Michał A. Niedzielski, Rafał Kucharski〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Urban spatial structure, transport mode and space-time constraints are known to affect accessibility to activities for a city’s residents. However, most studies measure accessibility from home only and report accessibility in terms of the travel time or number of activities. Such studies neglect the mobility and time budget constraints on people’s accessibility. Furthermore, modal accessibility disparity studies have not considered inequality between modes during the afternoon commute. We examine accessibility to non-work activities by automobile and public transport using spatiotemporal measures that determine the number of minutes people have available to participate in activities, given time budget and activity duration constraints, rather than simply the number of activities. We examine modal accessibility disparity in Warsaw, Poland. Our two major findings are the reverse of findings in previous studies: that disparity shifts toward public transport as the activity duration increases and the travel time decreases; and that it shifts toward public transport with increasing distance away from the city center.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 75〈/p〉 〈p〉Author(s): Michael Held, Maximilian Schücking〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The utilization has a significant effect on the life-cycle assessment (LCA) of battery electric vehicles (BEVs). This article evaluates this effect in detail by presenting a case-driven LCA for BEVs deployed in two commercial mobility applications. The empirical data was recorded over 2.5 years and 450,000 km. The findings of this article indicate that regular and predictable mobility demand patterns in combination with a high vehicle utilization are favorable conditions for an environmentally beneficial deployment of BEVs. These characteristics allow tailoring the battery capacity to the requirements and avoiding an unnecessary offset from production. When charging the vehicles with electricity from renewable energy sources (RESs), the high operating grade utilizes the comparatively lower environmental impacts per kilometer. A high lifetime mileage allows breaking-even to comparable internal combustion engine vehicles (ICEVs) in most investigated impact categories. Since regular and predictable mobility patterns, as well as a high operating grade, are commonly found in commercial applications these are especially suitable for replacing ICEVs with BEVs from an environmental perspective.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Ayman Faza, Amjed Al-Mousa〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Advances in the technologies of smart grids has made it possible to monitor and control the demand side of the power grid in ways that were not possible in the past. Thanks to the advances in information and communication technologies (ICT), Demand Side Management (DSM) is now possible, and promises more efficient and reliable power grids. This paper presents a study of different dynamic pricing techniques that are used as means to shape the demand in ways that minimize generation cost or maximize profit. This is achieved by using a fuzzy logic model that takes into account the different types of customers in the system. The paper further uses Particle Swarm Optimization (PSO) algorithm to generate the parameters that can achieve optimal grid operation. Results show that when customers are actively engaged in DSM schemes, and with the proper Dynamic Pricing scheme, optimal results can be obtained that benefit both the customers and the utility company, not to mention the savings in energy production and its impact on the sustainability of our cities. The results show that savings up to 12% in generation cost and a three times increase in profit can be achieved using an optimized DSM scheme.〈/p〉〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Yewen Gu, Stein W. Wallace, Xin Wang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Global warming is a major challenge for this planet, and its solution requires efforts throughout society. Maritime transportation, which carries more than 90% of the global trade, plays a critical role in the contribution of greenhouse gas (GHG) emissions. However, the GHGs emitted by the global fleet still fall outside the emission reduction scheme established by the Kyoto Protocol. Alternative solutions are therefore sought. Several market-based measures have been proposed and submitted to IMO for discussion and evaluation. In this paper, we focus on one of these measures, namely the Maritime Emissions Trading Scheme (METS). An optimization model that integrates (global or regional) METS into the classical fleet composition and deployment problem is proposed. This model is used as a tool to study the impact of METS on fleet operations and their CO〈sub〉2〈/sub〉 emissions. The results of the computational study suggest that, in the short term, the implementation of METS does not lead to emission reduction in most scenarios. However, in the case of low bunker prices, high allowance costs or global METS coverage, a more significant CO〈sub〉2〈/sub〉 decrease in the short term can be expected.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Suman Majumder, Krishnarti De, Praveen Kumar, Ramesh Rayudu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Economic growth in the emerging countries has led to rapid urbanization and expansion of existing cities. As a result, major cities in the emerging nations experience traffic congestion and deteriorating air quality. One of the solutions to overcome these problems is to develop a comprehensive public transportation system based on clean fuel. This work proposes a public transportation system based on electric buses that can be used in the cities. Here, the proposed system is studied and analyzed for Indian scenario. High capacity batteries and distributed solar PV generation has been used to ensure that no additional burden is put on the existing distribution network. These batteries are placed at each bus stop to store energy from the grid during the off-peak hours, and the supercapacitor in the buses will be flash charged from these batteries. In this work, the architecture of the proposed system has been presented along with initial sizing of the subsystems, for understanding the operation of the system for various scenarios, and to investigate its interaction with the grid. The results show that such a system, if carefully designed, is feasible and is capable of meeting the transportation needs without adding additional burden to the grid.〈/p〉〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Saghar Mokhtarmanesh, Mohammad Ghomeishi〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Our environment is an essential factor in designing a user-preference-based place. This study investigates the effects of the environment on users in determining their preferences for schools. The school environment/surroundings affect students in terms of their behaviour and achievements. It can be an advantage if students’ take a liking to their school building, as this emotion can motivate them to attend the school eagerly. Consequently, since a child’s view of a space is different from an adult’s view, a school space should be built according to the requirements and factors that are specific to the children and important for them in this environment. In this study, female elementary schools located in District 1 of Tehran, Iran have been investigated qualitatively using card sorting techniques followed by semi-structured interviews in order to determine their preferences regarding their school buildings’ attributes. The results were analyzed using content analysis. It was revealed that students preferred having 〈em〉playgrounds〈/em〉, 〈em〉colourful buildings〈/em〉, 〈em〉big interior spaces〈/em〉, 〈em〉wide windows〈/em〉, 〈em〉curvy shaped facades〈/em〉, 〈em〉articulated facades〈/em〉, and 〈em〉stairs〈/em〉 in school buildings; they did not express a preference for 〈em〉tall buildings〈/em〉 and 〈em〉being near streets〈/em〉. The results reveal that having these spaces could influence the student’s evaluation of the school.〈/p〉〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Gholamreza Heravi, Mohammad Mehdi Abdolvand〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The growing global water crisis highlights the importance of the assessment of the amount of virtual water consumption -water consumed during production of material and construction- in residential building projects. The purpose of this research is: (1) to assess the virtual water consumption of residential building projects in Iran; (2) to compare the amount of virtual water consumption in Iran with other countries; and (3) to assess sustainability impacts of the virtual water consumption on the national level. To do so, life cycle analysis method using process analysis for gathering data is implemented. Moreover, the results are generalized to evaluate virtual water consumption on a national level. In this way, the virtual water consumption of six residential buildings in Tehran, the capital of Iran, is assessed. The findings of this study showed that the virtual water consumption of residential buildings is 20.8 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"〉〈msup〉〈mi〉m〈/mi〉〈mn〉3〈/mn〉〈/msup〉〈/math〉 per 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si2.svg"〉〈msup〉〈mi〉m〈/mi〉〈mn〉2〈/mn〉〈/msup〉〈/math〉. Assessing the sustainability impacts of the virtual water consumption on the national level in 2017 resulted in: (1) the energy of supplying water consumed in the residential building construction releases about 13,700,000 Ton of greenhouse gases; and (2) the per capita virtual water consumption is about 20% of the country’s drinking water consumption per capita.〈/p〉〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Marjan Ilbeigi, Azadeh Mahmudi KohneRoudPosht, Mohammad Ghomeishi, Emad Behrouzifard〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The aim of this study is to define aesthetic differences between architects’ and non-architects’ perspectives by considering the cognitive properties of residential buildings’ facades located in Iran. Accordingly, in order to observe perceptional similarities and differences between designers and users, the aesthetics of residential facades is investigated in Tehran, Iran, through a comprehensive case study. A quantitative method was used in the form of a questionnaire, and the corresponding data is further analyzed by SPSS software. Although architects’ and non-architects’ perspectives are somewhat similar in selecting and evaluating the chosen facade, corresponding findings reveal significant differences as well. The results further show that the classic architectural style was not appealing for the architects. Moreover, non-architects and architects think that ‘uniqueness’ is the most effective parameter; while architects believe that ‘pleasantness’ has the highest influence among the presumed six parameters in selecting the best facade. Furthermore, the outcomes indicate that the studied groups have some conflicting viewpoints about aesthetics, while there would be some similarities about the unfavorable facades. In this regard, the non-architects’ standpoints, preferences, and satisfaction should be assumed during the design procedure. This research can open a new perspective on the architect’s perception in the early design stage.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 20 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment〈/p〉 〈p〉Author(s): Elham Hajhashemi, Pamela M. Murray-Tuite, Susan L. Hotle, Kris Wernstedt〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Hurricane Sandy greatly disrupted the New York City (NYC) region’s transportation systems, electric power systems, work locations, and schools in 2012. This study uses survey responses from NYC Metropolitan Area residents to develop an agent-based model that depicts commuter travel behavior and adaptation after the disruption. Six scenarios were tested to quantify which systems were more critical to recover for an earlier return to productivity - defined as the ability to work for one’s employer. The recommended system restoration order depends on the pattern of normal commuting behavior. In the NYC Metropolitan Area, a larger share of commuters use transit to commute than in any other US metropolitan area. This resulted in the model indicating the subway/rail system recovery as the most important factor for returning the most people to productivity. The second most important factor is widespread power restoration itself, which allows residents to telework while waiting for the transportation system to recover. The next most important factor is the reopening of schools and daycares (with associated infrastructure systems), freeing parents to commute. The remaining expedited system recovery scenarios tested using the agent-based model resulted in a faster return to productivity than the baseline, but to a lesser degree than the subway/rail, power, and childcare systems scenarios. Additional analysis of recovery shows that households with higher annual income benefit more from power recovery compared to those with lower incomes. Moreover, the effectiveness of recovery scenarios can differ based on residential location and the extent of disruption in that location.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Ning Xu, Qiong Zhang, Haoran Zhang, Minsung Hong, Rajendra Akerkar, Yongtu Liang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Disasters pose a serious threat to people’ lives and urban environment, affecting the sustainable development of society. Then it's crucial to quickly develop an efficient rescue plan for the disaster area. However, disaster rescue is rather difficult due to the requirement to develop the optimal rescue plan as quickly as possible according to the information of trapped people and rescue teams, and the amount of information will continue to increase as the rescue proceeds. At present, most of the rescue plans are manually made based on previous rescue experience. But obviously these plans might be the not optimal one. Considering the real-time location data of trapped people, this paper develops a Mixed Integer Non-linear Programming (MINLP) model to find the highest efficient rescue plan To solve the model accurately and efficiently, a bi-level decomposition (BLD) algorithm is presented to iteratively solve a discretized Mixed Integer Linear Programming (MILP) model and its nonconvex Non-linear Programming (NLP) model until a converged solution is obtained. In addition, since more trapped people could be found over time, the built rescue units should also be considered when making a rescue plan for a new stage. To further improve the solving efficiency, an accelerated bi-level decomposition (ABLD) algorithm is also proposed. Finally, a real-world disaster rescue is given to validate the superiority of the proposed ABLD algorithm relative to particle swarm optimization (PSO) algorithm and BLD algorithm.〈/p〉〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Ghaffar Ali, Sawaid Abbas, Yanchun Pan, Zhimin Chen, Jafar Hussain, Muhammad Sajjad, Aqdas Ashraf〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The aim of achieving stable economic growth and development deter the pathways of being a low carbon society in developing countries. Nonetheless, it is imperative to understand and analyze the long-term goals of such societies to upgrade and redirect priorities towards the low-carbon structure. Therefore, this study is carried by applying a novel multi-criteria decision analysis (MCDA) approach and the Bilan Carbone model to examine the different possibilities for cost/benefit analysis from direct reductions in carbon emission levels in the Lahore Metropolitan Area (LMA) of Pakistan. The LMA is a metropolitan city in the developing country and is marked with a huge spike in energy demands and carbon emissions due to increasing population. Three scenarios including one current (2010), and two future (business as usual—2050BaU and low carbon scenario—2050LCS), were developed. Our findings show no evidence of renewable energy use—such as solar, wind, and biomass—in the current energy mix of LMA. Furthermore, an increase in carbon dioxide (CO〈sub〉2〈/sub〉) emissions from 3.5 in 2010 to 14 million tonnes (mt) in 2050 is found. Mitigation potential analysis of different sectors showed that the industrial sector of the city has the biggest mitigation capacity (13%) until the year 2050, whereas, the smallest proportion may come from the commercial sector (4%). The carbon emissions in LMA would be reduced as much as 50% as compared to the BaU scenario until 2050. Moreover, this mitigation potential study would also serve as a ripple effect in the data deficient cities of low-income countries.〈/p〉〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Chaoying Yin, Chunfu Shao, Chunjiao Dong, Xiaoquan Wang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Although the relationship between commuting time and residents’ happiness has been widely investigated, few studies have examined how the connection varies with urbanization levels. Using 7,774 individual samples across China, this study employs a multilevel ordered logit model to examine how commuting time is correlated with residents’ happiness. The effects of both the neighborhood and city-level built environment are revealed. Our findings show that commuting time is an essential factor correlated with residents’ happiness and the correlation varies across urbanization levels. People from cities with high urbanization rates (〉70%) have a strong mental endurance of commuting time, whereas commuting time is more influential on residents’ happiness in cities with low urbanization rates (〈50%). For the effects of the built environment, residents’ happiness is significantly associated with both levels of built environment in cities with urbanization rates higher than 50%. Conversely, residents’ happiness is only significantly correlated with the neighborhood built environment in cities with urbanization rates lower than 50%. Hence, to enhance residents’ happiness, urban planners and policy makers should consider multi-scale built environment characteristics and improve the public transport services according to local urbanization levels.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Min Zhou, Nan Kong, Lindu Zhao, Fuhua Huang, Song Wang, Kathryn S. Campy〈/p〉

Description: 〈p〉Publication date: January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 52〈/p〉 〈p〉Author(s): Andrea Patricia Cuesta-Mosquera, Matthew Wahl, Jansen Gabriel Acosta-López, José Agustín García-Reynoso, Beatriz Helena Aristizábal-Zuluaga〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Distinct times of sulfur dioxide concentration (SO〈sub〉2〈/sub〉) were observed in the main square of a tropical Andean city, revealing strong meteorological control of SO〈sub〉2〈/sub〉. Concentrations were measured by UV fluorescence at 5-minute intervals, and compared to local meteorological forcing. A consistent morning peak of SO〈sub〉2〈/sub〉 (4.32 μg∙m⁻³ at 7:40 AM) was concurrent with peak traffic, and occurred 10 minutes into an 80-minute period of calm (wind velocities ˂ 0.3 m s⁻1). Instead of accumulating, SO〈sub〉2〈/sub〉 decreased 54%, due an expanding mixing layer. Peak evening SO〈sub〉2〈/sub〉 (5.2 μg∙m⁻³ at 8:15 PM) was observed 2:15 hours after flow reversal, and consistent with travel-times of an air parcel descending from industrial facilities. The consistent anthropogenic emissions formed a pattern of daily SO〈sub〉2〈/sub〉 concentration that aided in identifying more random volcanic SO〈sub〉2〈/sub〉. Manizales (pop. 400000) is located on the western slope of the Cordillera Central in proximity to the Nevado del Ruiz volcano. The complex trajectory necessary for volcanic SO〈sub〉2〈/sub〉 to arrive in the main square was simulated for the highest observed concentration (114 μg•m⁻³), using Hysplit and Aura-OMI information. This type of analysis can be applied to urban planning - from locating industrial zones to managing transportation - particularly in tropical montane cities.〈/p〉〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Paola Lassandro, Silvia Di Turi〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Global warming increases the probability of extreme events and heat waves, intensified by Urban Heat Island phenomenon, triggering severe impacts on both human health and economy. The paper aims at developing a new methodological approach for the assessment of building ability to face rising temperatures, also considering the effects on the surrounding urban areas. It focuses on resilient retrofitting strategies need for building envelope according to three macro-categories: reliability, adaptability and mitigation ability. A set of indicators is defined to achieve a Response Index to cope with heat waves. The method is tested on reference building and its neighborhood. The selected strategies are investigated through an integrated and multilevel analysis with EnergyPlus and ENVI_met, in three different cities with increasing summer temperature. The final comparative analysis is carried out through a multi-criteria analysis according to the identified indicators. The best responsive solutions result the green ones combined with high albedo, but the research highlights also some controversial aspects. The method can be a valid tool to support the decisional process about heat waves mitigation in the roadmap towards a more responsive built environment.〈/p〉〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Reza Ramyar, Esmaeil Zarghami, Margaret Bryant〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉There is a growing concern in recent years about temperature rise resulting from climate change, especially in high-density urban areas, where it is exacerbated in urban heat islands (UHI). In hot and dry climates, this concern makes it necessary to find a practical solution to adapt to climate change. Rapidly developed cities with large populations, due to ignoring the creation of UHI in planning, mostly have fallen into severe trouble. So, finding the influence of decisions’ impacts on urban climate before implementing them would inform planners about the consequences of their decisions. Advanced 3D-4D numerical models like ENVI-met are becoming a frequent way of investigating climatic impacts of decisions and regulations. However, full-scale modeling of a neighborhood or a city cannot be widely possible at present. Therefore, a practical solution is simplification of small-scale models to calculate the consequences of decisions in developments. In this study, we systematically propose some solutions for cooling urban neighborhoods, and then, after analyzing them, possible scenarios for UHI mitigation are presented. The goal is to find the most effective urban form and design strategies across a typical range of Tehran urban development at a high-density urban fabric. Our results provide insight into the impact of urban form and design on microclimate in hotter and drier future cities by considering water shortage and utilizing mitigation strategies.〈/p〉〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Pouya salyani, Mehdi Abapour, Kazem Zare〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉With respect to the penetration of electric vehicles (EVs) due to pursuing environmental targets, EV parking lots establishment for giving charge and discharge services is necessary. Nevertheless, distribution companies (DisCos) seek to reduce the planning cost as much as possible and in this regard, demand response can be one of their effective options. However the customers participated in this program reduce or shift their consumption for the sake of increasing their benefit and accordingly DisCo must provide an incentive like the decrease in energy price which causes a competition between the DisCo and customers decisions. Because selling energy with higher price is preferable for DisCo. Hence what is proposed in this paper is the optimal probabilistic and long term planning of DGs and EV parking lots in the presence of demand response in which the mentioned competition is controlled via implementing Stackelberg game theory. In this game, DisCo plays as the leader and the customers interested in demand response play as the followers and their interaction is conducted though a decentralized distributed algorithm which finally determines the consumption profiles and the related energy selling price for all scenarios through the panning period.〈/p〉〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Lei Wang, Guoyuan Ma, Feng Zhou, Yu Liu, Tian Tian〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Ventilation heat recovery devices have been increasingly used in energy-efficient buildings. Many factors, such as the attributes of buildings and the economic conditions of decision makers, should be considered in the installation of ventilation heat recovery devices. Thus, decision makers experience a multicriteria decision-making problem. This study presented a method of combining Analytical Hierarchy Process with the Technique for Order of Preference by Similarity to Ideal Solution to provide guidance in selecting ventilation heat recovery devices on the basis of the attributes of buildings and preferences of decision makers. By using residential house, small shop, and small public service center as examples, four types of ventilation heat recovery devices (total, plate sensible, integral heat pipe (R32), integral heat pipe (R717) heat exchangers) were recommended and sequenced under different background requirements through the proposed method. Results showed that the total heat exchanger obtained the highest recommended indicator value in small load application scenario, indicating its suitability. The proposed method can completely consider the attributes of buildings and psychological preferences of decision makers and combine the characteristics of different types of ventilation heat recovery devices. This approach provides scientific and reasonable recommended results in selecting heat recovery devices.〈/p〉〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Jean Engo〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The transport sector represents one of Cameroon's economic sectors with high energy consumption and CO〈sub〉2〈/sub〉 emissions. To this end, it is clear that practical ways to save energy and reduce CO〈sub〉2〈/sub〉 emissions from this sector are needed to enable Cameroon to achieve its greenhouse gas mitigation targets. The Tapio and LMDI methods were applied in this paper, based on an extended Kaya identity, to explore the decoupling relationship among energy-related CO〈sub〉2〈/sub〉 emissions and growth from Cameroon’s transport sector, over the period 1990–2016. The decoupling indicators were broken down into five factors while considering the four fuels consumed in Cameroon's transport sector. Empirical results showed that only four states of decoupling appeared during the study’s period including weak decoupling, strong decoupling, weak negative decoupling, and strong negative decoupling. Meanwhile, scale effects, energy structure effect, and energy intensity effect prevented decoupling, whereas the economic structure effect played an important role in promoting decoupling. Based on the findings of this study, some policies aimed at reducing carbon emissions from Cameroon's transport sector were proposed in this paper.〈/p〉〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Hua Wang, De Zhao, Yutong Cai, Qiang Meng, Ghim Ping Ong〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉As a cost-effective and environmental-friendly transport means, electric vehicle (EV) has received widespread attention in the recent decade. The increasing market share and wider adoption of EV in transportation systems also bring about the energy use issues. In this paper, we propose a method to estimate network-wide EV energy consumption by taking into account battery degradation. We first derive unit energy consumption functions with respect to the battery degradation rate by quadratic regression method using EV operational data in the US. We then put forward an easy-to-implement and tangible method to estimate EV network energy consumption based on EV trajectories and the derived unit energy consumption function. In detail, EVs’ battery degradation rates are assumed to follow a given and known probability distribution and daily travel mileage of each EV is derived from EV trajectories. Based on these, we can get the expected total energy consumption in the network. We also propose a prorated assignment approach to determine the expected energy consumed by EVs through each EV charging point based on the estimated temporal-spatial charging demand distribution from EVs’ trajectories. A case study in Singapore is demonstrated in the end and the importance of incorporating battery degradation is highlighted. The results reveal that overlooking battery degradation would lead to more than 10% of estimation error in energy consumption estimation.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Yiyang Yang, Dongsheng He, Zhonghua Gou, Ruoyu Wang, Ye Liu, Yi Lu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Built environment interventions, such as creating green and walkable neighborhoods have increasingly been recognized as an effective approach to promote physical activity and health for older adults. However, evidence of the associations of urban greenery and older adults’ physical activity is still inconclusive, partially due to the difficulty to estimate eye-level urban greenery exposure. To address this gap, we assessed street greenery by Google Street View (GSV) images with machine learning techniques and associated it with walking behavior for 10,700 and 1083 Hong Kong older adults (aged 65 or above) respectively. Neighborhood socioeconomic status, individual factors, and other built environment characteristics were controlled for in the analysis. We found that street greenery assessed by GSV was positively associated with both the odds of engaging in walking and total walking time of the older adults. Our findings suggest that urban planners and policymakers should maximize residents’ greenery exposure by considering the accessibility and visibility of urban greenery from pedestrian and human-scale perspectives.〈/p〉〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Mohammad Abujubbeh, Fadi Al-Turjman, Murat Fahrioglu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Power systems across the globe witness structural challenges because of the increased concerns on climate change and vast growth in energy demand. Purposefully, new technologies and solutions have emerged such as renewable-energy systems, electric vehicles, and micro-grids. With the development of Internet of Things (IoT) and Wireless Sensor Networking (WSN) technologies, Smart Grid (SG) concept is becoming more attractive, whereby it refers to upgrading conventional power-grid infrastructure in order to offer automated control over the resources and emerging technologies in smart and sustainable cities. The implementation of this automated control requires robust and secure bidirectional communication systems. However, legacy-networking paradigms failed to address flexibility in their design to meet SG-networking requirements. Alternatively, Software Defined Networking (SDN) paradigm provides two powerful networking solutions namely, decoupling control from the data layer and network programmability, which can enhance the robustness of communication networks in modern societies. Therefore, the main aim of this article is to present an overview of integrating Software-Defined WSN (SDWSN) concept in SGs in order to solve the aforementioned challenges and improve network robustness. We categorize literature attempts, describe enabling devices and communication technologies, and we suggest open research issues and opportunities associated with integrating SDWSN paradigm into SGs.〈/p〉〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Yong-Kang Qiao, Fang-Le Peng, Soheil Sabri, Abbas Rajabifard〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Underground space has been widely used in densely populated cities across the globe, and is attracting increasing attention among academics and practitioners toward further alleviating land use pressure, improving urban resilience and the quality of life. However, few attempts have been made to probe the potential threats posed by underground space use to urban sustainability. Disregarding these threats and the socio-environmental losses accruing to unreasonable underground space use will lead to failure in the decision-making process, particularly the cost-benefit analysis, of underground space development and may to some extent compromise the urban sustainability. This research intends to investigate the potential socio-environmental losses caused by underground space use for urban sustainability from the perspectives of underground assets, including geothermal energy, groundwater, geomaterials, historical heritage, space continuum and organisms, based on their contributions to sustainable development goals (SDGs), and sets up a framework for the monetary valuation of these losses. It is anticipated that the findings of this study will assist the future planning and decision-making process in developing the sustainable urban underground space.〈/p〉〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 73〈/p〉 〈p〉Author(s): 〈/p〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Shahin Zargarnezhad, Reza Dashti, Rouhollah Ahmadi〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Energy distribution companies use various vehicles such as Outage Elimination Maintenance Vehicles (OEMVs), Maintenance Vehicles (MVs) and Supervision Vehicles (SVs) in order to resolve network faults, to conduct inspection, service and maintenance activities and to monitor the integrity of operations. These vehicles have different levels of fuel consumption which concerns companies with regards to the cost and environmental hazards. Hence, it is important to know that a distribution company how many and what types of vehicles do need to predict the fuel consumption of these vehicles. Extra fuel consumption may be required owing to carry unnecessary equipment or used vehicles with large engine volume. Therefore, in this paper, the fuel consumption levels of outage elimination maintenance, maintenance, and supervision vehicles are considered. Then, given the fact that fuel consumption increases with the increase of vehicle weight and Engine Displacement (ED), the extra fuel consumption has been predicted using Artificial Neural Networks (ANNs). In a case study, the total annual fuel cost in the network under consideration is estimated to be $66750. In the case of a 40% increase in vehicle weight, the fuel consumption cost will rise by $24500, and when the engine displacement increases for a 500 CC, the cost rises up $17400 per year.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): William Brazil, Steffen Kallbekken, Håkon Sælen, James Carroll〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Transitioning to more sustainable transport behaviours is key to achieving national and international climate change objectives. Households can contribute to the new low carbon economy by switching to more energy efficient vehicles. In addition to societal and environmental benefits, such a change should lead to private benefits for households through lower energy expenses, while avoiding the perceived costs that could accompany a modal change in personal transportation (switching away from cars). This paper uses a discrete choice experiment (stated preference) to explore the effects of using alternative fuel cost labels on the demand for more efficient cars. Results show that reframing from fuel consumption (litres) to monthly fuel costs increases the willingness to pay for higher levels of fuel efficiency. More generally, these results highlight that informational interventions can be improved by framing information in a metric that is more salient and familiar to consumers.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Gabriela Codrina Tiţă, Marina Viorela Marcu, Gheorghe Ignea, Stelian Alexandru Borz〈/p〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 76〈/p〉 〈p〉Author(s): Xiaolei Ma, Xian Zhang, Xin Li, Xingju Wang, Xu Zhao〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The development of bike sharing system (BSS) has changed travelers’ commuting and lifestyle in recent years. Whether BSSs are complementary or competitive to public transit remains controversial. This study uses a propensity score matching-based difference-in-difference (DID) method to evaluate the impact of free-floating BSS on bus ridership in Chengdu, China. The transaction data of bus service and BSS and the neighboring points of interest are investigated. Results indicate that, (a) on the bus route level, each shared bike results in a 4.23 increment and a 0.56 reduction in daily bus ridership on weekdays and weekends, respectively; (b) on the bus stop level, the increment in shared bikes significantly negatively impacts bus ridership on weekends; (c) on the route level, regarding the time of day, each unit increment of shared bike significantly increases bus ridership on weekdays by 0.54, 0.34, and 0.15 during a.m. peak, p.m. peak, and off peak, respectively; and (d) on the bus stop level, the relationship between shared bikes and bus ridership is insignificant on weekdays. This study reveals that the demand pattern of commuters strongly impacts the relationship between shared bike and public transportation.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 76〈/p〉 〈p〉Author(s): Long Cheng, Freke Caset, Jonas De Vos, Ben Derudder, Frank Witlox〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Taking into account the rapidly aging demographic landscape in China, securing elderly’s right to participate in society has become an urgent challenge. Geographical access to urban amenities is known to influence social participation and integration. However, the application of accessibility analysis to elderly population in China has received little attention to date. This study examines the walking accessibility to recreational amenities for older adults in the Chinese context with an explicit focus on equity. Building on empirically-based estimates of a cumulative opportunity approach, we calculate the levels of accessibility at the traffic analysis zone level, evaluate how accessibility varies across age cohorts, and present the distribution of accessibility across zones. To this end, we draw on the 2015 Nanjing Travel Survey and the city’s GIS database. Instead of assuming a fixed threshold, this paper applies a spatial expansion model to allow for person- and location-specific walking distances to measure accessibility. The spatial disparities in access to recreational amenities are evaluated using the notion of vertical equity for identifying areas that are better-off or worse-off. Our results show pronounced distributional effects of current land-use and transportation policies for different age cohorts. In particular, elderly people experience lower accessibility to chess/card rooms and urban parks than their younger counterparts. The empirical evidence in this research can inform planning and policy interventions and feed current scientific debates on the role of accessibility in addressing social inclusion for an age-friendly society.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Abdellah Chehri, Hussein T. Mouftah〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Every revolution promises a spirit of optimism and significant changes. Connected and automated vehicles (CAVs) are coming to our roadways. CAVs have a crucial role to play in the future of transportation. These emerging technologies will provide a safe travel mode by eliminating the human driving error. The CAVs are never distracted or tired. In the last five years, autonomous driving has gone from “may be possible” to “inevitable”. Beyond safer and more enjoyable routes for passengers, the autonomous car also represents a significant step forward in terms of sustainable development. However, many questions remaining under investigations, when will autonomous cars be available? What should be improved first, vehicles or infrastructures? What are the requirements that must be satisfied by Intelligent Transportation Systems (ITS) in smart and sustainable cities? How will these modern technologies impact our transportation systems and the social world? What and how the leading technologies can be used in autonomous cars? What type of sensors and embedded devices to be used? In this paper, we address those issues and to try to provide some suggestions for these technologies that are currently emerging.〈/p〉〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Jean-Marie Cariolet, Marc Vuillet, Youssef Diab〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Maps and Geographic Information Systems (GIS) are widely used to better understand and manage risks in modern cities. While methods for mapping hazard, vulnerability and risk are well established, mapping resilience in urban areas poses a challenge as there are no agreed-on methodological approaches for doing so. This paper surveys proposed methodologies and approaches for mapping urban resilience to disasters. Our review shows that (1) adaptive resilience is mapped after a disaster mainly through the measure of recovery and inherent resilience is mapped using top-down approaches. Regarding inherent resilience (2), very few methods have been applied at city scale; (3) the limit between resilience and vulnerability mapping is still narrow and may cause confusion for decision makers; (4) the choice of variables and indicators to measure and map resilience is often a function of data availability and reliability; (5) indicators developed in one specific context should not be applied systematically to other contexts as resilience is a context-dependent concept; (6) most resilience maps are based on an analytical approach and do not reflect the systemic property of resilience.〈/p〉〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Qiang Wang, Min Su〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Although many studies have explored the effects of urbanization and industrialization on China’s carbon emissions, no work has systematically investigated their impacts on China’s decoupling of economic growth from carbon emissions. To this end, the Tapio model, the Johansen co-integration theory and the Granger causality test are adopted in this paper. According to the results of decoupling analysis, during the period 1990–2015, China’s carbon emissions and economic growth appear to be strongly decoupled only in a limited number of years, and the remaining years are weakly decoupled. It is necessary for China to strengthen carbon emission reduction. The co-integration test results show that, both in the long-term and short-term, urbanization level is the main driving force to promote decoupling elasticity, contributing to a significant increase in carbon emissions. Due to the scale effect, industrialization exerts an inhibitory impact on decoupling elasticity in the early stage. This means that the economic benefits of industrialization are far greater than the environmental pollution it generates. The consumption structure plays a leading role in restraining the increase of carbon emissions. Based on these results, policy recommendations are put forward for policy makers.〈/p〉〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Yi Yang, Peipei Huang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Evaluating the actual progress in the green development of China’s northwestern provinces can play a role in encouraging local governments to promote the reform of the ecological civilization system. By improving the “〈em〉green development indicator system〈/em〉” formulated by the National Development and Reform Commission of China, the green development index (GDI) of Shaanxi Province from 2007 to 2016 was measured and compared with Shaanxi’s ecological footprint (EF) and related indicators. The results showed that (1) the GDI in Shaanxi Province increased from 42.774 in 2007 to 64.971 in 2016, while during the same period, the per capita EF increased from 1.994 ha/cap to 2.719 ha/cap, the ecological deficit increased from 0.782 ha/cap to 1.500 ha/cap, and the ecological pressure index increased from 1.645 to 2.176. These results indicate that the green development of Shaanxi Province is still based on excessive ecological occupation. (2) A comparison between GDI and EF shows that the development of Shaanxi Province has changed from “low GDI, low EF” to “low GDI, high EF” to “high GDI, high EF”. Thus, this study proposes countermeasures to change this trend, such as adjusting the energy structure, reducing carbon emissions, improving environmental capacity, and rigorous managing national land space.〈/p〉〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Zhaowen Qiu, Huitao Lv, Fan Zhang, Wazi Wang, Yanzhao Hao〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉To evaluate the exposure of adults and teens to fine particles (PM〈sub〉2.5〈/sub〉), black carbon (BC), and ultrafine particles (UFP) as they walked along urban roads, an investigation was performed using mobile measurement devices on two types of urban roads (arterial and collector) in Xi'an. The inhalation dose model, considering exposure concentration, inhalation rate, and trip time, was employed to estimate the personal inhaled dose of pollutants for adults and teens. Multivariate linear regression was used to explore impact factors that contributed to their exposure variability. Results showed large spatial and temporal pollutant concentration variations along the designed route. Pedestrians experienced higher exposure concentrations on the arterial road than on the collector road. Teens faced higher PM〈sub〉2.5〈/sub〉 and BC inhaled doses than adults on all the streets studied, although sometimes being exposed to lower concentrations than adults. In addition, gender-related inhaled dose differences between teens were more significant than those for adults. The overall background concentrations explained the greatest variability in pollutant exposures, from 18.7% for BC to 40.4% for PM〈sub〉2.5〈/sub〉. Ambient concentrations and traffic volume as well as pollution hotspots (pedestrian cigarette smokers, restaurants, and open burning) were identified as major factors affecting the pollutant concentrations.〈/p〉〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Himanshu Kumar Khuntia, Sanjana Chandrashekar, H.N. Chanakya〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Anaerobic treatment of greywater (GW) is challenging due to the presence of recalcitrant household chemical products (HCP) that inhibit the activity and growth of organic pollutant degrading anaerobic microbes. This research attempted to overcome this challenge through a novel, multi-chambered anaerobic biofilm reactor (AnBR) containing fluidized PVC media and packed bed lignocellulosic fiber (〈em〉Cocus nucifera〈/em〉) as biofilm support. The long-term effects of feeding HCP laden GW and effluent recycling on the performance of AnBR were corroborated with the bioconversion data and microbial community dynamics. The results indicated that the composition of wastewater and recycling both determine the rates of COD removal, microbial population, and diversity in AnBR. The inhibitory effects exhibited by GW constituents reduced the COD removal efficiencies by 74–94% in comparison to standard substrates (SS), while simultaneously reducing microbial population and diversity by 30–40%. Effluent recycling in GW and SS fed AnBR enhanced the rates of COD removal from 160 mg/L·day to 214 mg/L·day, and 627 mg/L·day to 3540 mg/L·day respectively, with the selective enrichment of 〈em〉Proteobacteria〈/em〉 sp. and 〈em〉Methanogenic〈/em〉 sp. The GW fed AnBR was dominated by aromatics degrading species of α〈em〉-Proteobacteria, Synergistetes,〈/em〉 etc., whereas, SS fed AnBR were inhabited by fermentative species of 〈em〉δ〈/em〉-〈em〉Proteobacteria, Bacteroidetes,〈/em〉 etc.〈/p〉〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Shuo Zhang, Hong Wang, Yufei Zhang, Yingzi Li, Ying Li〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Electric taxi (ET), with zero exhaust emission, plays a vital role in low-carbon sustainable development of urban public traffic to reduce fossil fuel consumption and air pollution. As the key part of ET development, charging station (CS) directly impacts ET’s widespread application by figuring out the charging difficulty of ET. Therefore, to tackle the location issues of electric taxi charging station (ETCS), a novel two-stage location model is built in consideration of ET dynamic distribution and charging requirements in this paper. Firstly, taking the complex features of ET into account, such as dynamic location and dispersed distribution, the dynamic distribution clustering model of ET is formed based on K-means method, by which lots of scattered ET locations are grouped into certain clustering blocks. Secondly, according to aforementioned blocks, the location model of ETCS is established with barycentric method to get the location of ETCS, in view of both the latitude and longitude location and charging demands of each clustering block. Finally, the two-stage location model is employed in the case study of ETCS location in Chengdu, China. The result indicates that the chosen location meets the charging requirements and the characteristic of taxi distribution in Chengdu, proving the validity of the model.〈/p〉〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Johannes Kester, Gerardo Zarazua de Rubens, Benjamin K. Sovacool, Lance Noel〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Public awareness and acceptance of electric vehicles (EVs) are essential components to catalyse a faster uptake of more sustainable passenger transport as well as vehicle-to-grid (V2G) mobility. As such, public perceptions are central to decarbonize transportation and help capture the co-benefits of reduced local pollution, noise emissions, and oil dependency. However, we observe that the general public is often treated statically and seen as either problematic or peripheral to questions within the transport and energy studies communities. This paper asks two questions. First, given increasing adoption in the Nordic region, how do ordinary members of the public perceive EVs? And second, how do they perceive V2G? With these questions, the paper offers an international and in-depth assessment of public perceptions of EVs and V2G systems across five Nordic countries using original data drawn from eight focus groups. We find eight themes of relevance for future research and policy. These include often discussed insights like an EV’s environmental sustainability, range, charging or price, but also insights around themes like social status, sound, and acceleration. Additionally, we asked the participants whether V2G strengthens (or weakens) the desirability of EVs. The paper ends with a reflection on the knowledge discrepancies between national focus groups and individuals with and without EV presence and the different informational requirements that are needed to address them.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Yuche Chen, Marc Melaina〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The future of fuel cell electric vehicle (FCEV) depends on its cost and performance competitiveness in the automobile market. In this study, we develop a techno-economic analysis framework to compare the cost and performance of major vehicle technologies (internal combustion, hybrid, plug-in hybrid, battery and fuel cell electric) under various progress scenarios for the years 2035 and 2050. We utilize a vehicle powertrain model to compare vehicle technologies with similar engineering performance and evaluate their cost competitiveness. We define the cost as (2018) U.S. dollars per mile driven ($/mile) during a certain ownership period and include the vehicle purchase price and fuel cost. Our results show that, in the 2035 scenarios, the costs per mile for FCEVs are 36% or 22% higher than those of conventional gasoline cars, based on a 5-year or 15-year ownership period, respectively. In the 2050 scenarios, the 15-year ownership costs of FCEVs are comparable to those of gasoline cars with comparable engineering performance. In all the 2035 and 2050 scenarios, fuel cell vehicles have a lower driving cost compared with electric vehicles with 200-mile driving range. Our sensitivity analysis suggests that hydrogen price and fuel cell system cost are the major uncertainties that determine cost competitiveness of FCEVs.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Bin Cheng, Zhonghua Gou, Fan Zhang, Qiushuang Feng, Zefeng Huang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Urban mountain parks are different from urban parks in that they form a unique microclimate environment with special topographical advantages and natural ecological environment. The study aims to investigate the thermal comfort condition and its related visitations in urban mountain parks in the hot summer and cold winter climate. Particularly, the research conducted thermal comfort measurement and visitation observation in three urban mountain parks in Mianyang City. The measurement and observation covered three months: August, October and December of 2018, which represents summer, autumn and winter respectively. The study included climate measurement, questionnaire survey and observation of the attendance rate in the selected parks. Results showed that temperature and solar radiation are the two most important factors affecting the use of parks. The neutral PET (Physiologically Equivalent Temperature) value is 27.0 °C in summer, 23.2 °C in autumn, and 17.3 °C in winter. This study can help to better plan and design outdoor environments of urban mountain parks to encourage people’s visits and social interaction.〈/p〉〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Bernd Herrenkind, Ilja Nastjuk, Alfred Benedikt Brendel, Simon Trang, Lutz M. Kolbe〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉The self-driving public bus (SDPB) holds the potential to replace human-operated driving with more eco-friendly means and is therefore a valuable mobility solution for our future. The SDPB is based on the innovative technology of autonomous driving, which can only be guaranteed future market success with broad enough user acceptance. This acceptance is thus an essential factor for the growth of SDPB services. In this context, the travel behavior of young people is particularly interesting, as its development will continually demonstrate future mobility behavior trends. However, little research has been conducted regarding the best methods for motivating young people to accept SDPBs as a viable mode of travel.〈/p〉 〈p〉To address this topic, we first conducted a literature review, identifying factors that potentially influence SDPB acceptance. Subsequently, we developed a comprehensive research model based on the life-oriented approach and the technology acceptance model. This conceptualization was validated by a survey of 268 SDPB riders in real-world traffic. The results reveal several novel factors influencing the acceptance of SDPBs, in particular regarding differences in age. Our research contributes to existing research on both the life-oriented and travel behavior approaches by highlighting age differences and their importance in the field. For instance, our findings demonstrate a vital need to account for age differences when deriving policy implications for future mobility solutions.〈/p〉 〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): S.M. Patella, F. Scrucca, F. Asdrubali, S. Carrese〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉This paper presents the results of a Carbon Footprint (CF) study of Autonomous Vehicles (AVs) and their environmental impact on the transportation network. By assuming that fully AVs are battery electric vehicles (BEVs) with connectivity, light detection and ranging sensors, this study measures the environmental impact at the urban mobility level. The AV complete life cycle impact was firstly evaluated. Next, by comparing the current situation with a future hypothetical scenario (100% AVs penetration), the positive environmental effect of the adoption of AVs on a real road network (city of Rome) is shown. For this scope, a traffic simulation-based approach was used to investigate the effects of AVs on the network congestion.〈/p〉 〈p〉The results show that the full AVs penetration scenario leads to an improvement in the network performances in terms of travel time and average speed. The Total Time Spent (TTS) decreases (−35% for intra-urban roads and −21% for highways), and the average network speed increases (48% for intra-urban road and 37% for highways). Moreover, the final amount of Vehicle Kilometer Traveled (VKT) shows an 8% increase on longer extra-urban routes, due to the higher capacity impact of AVs on highways, with a consequent load reduction for intra-urban shortcutting routes. In terms of life cycle impacts, AVs are characterized by the highest Greenhouse Gases (GHG) emissions related to construction, maintenance and end-of-life processes (on average 35% compared to internal combustion engine vehicles, 22% compared to hybrid electric vehicles and 5% compared to battery electric vehicles). Nevertheless, a 100% AVs penetration scenario generates a reduction of the environmental impact at the mobility system level of about 60%.〈/p〉 〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Jingjing Yu, Stefan Voß, Guolei Tang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Shore side electricity (SSE) is the use of electricity from the shore to power a ship’s system when it is berthing at ports. It is a solution to reduce the emissions of auxiliary engines at berth and to improve the local and regional air quality. This paper develops a multi-objective model that integrates spatial and temporal dimensions for strategic planning regarding whether and when to retrofit ships to use SSE. The strategic planning problem is to maximize the environmental benefit and to minimize the payback period of the investment over the entire planning horizon. By adopting an improved multi-objective genetic algorithm (NSGA-II), a series of retrofit strategies for container ships calling at Dalian Port in China are obtained under a projected annual visiting frequency of ships with different ship sizes and shipping lines. Depending on a selected retrofit strategy, the sum of the payback periods of ships that are determined to be retrofitted is 46 years (on average less than four years) and the environmental benefit of using SSE can be up to 128 million USD for Dalian Port in the planning horizon from 2020 to 2035. The results show that using SSE is an efficient method to decline emissions within the maritime sector and validate that the proposed methodology can be useful to ship owners to decide upon investing in SSE applications and to promote the development of green shipping and green ports.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Ali Ghofrani, Seyyed Danial Nazemi, Mohsen A. Jafari〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this study, we propose a methodology to assign HVAC operation planning schemes for connected buildings with the objective of energy saving and load leveling. The idea is to use building thermal inertia in a periodic pattern by relaxing the temperature setpoints to an upper bound and setting back to a lower bound to avoid air conditioning while the room is still within human comfort zone. This periodic operation planning in turn facilitates the collaboration across a building community to reduce the aggregate demand. The objective is to assign periodic temperature setpoints for a building cluster so that the aggregate cooling electric demand reduces with the minimum cost and steady aggregate load shape. Ideal operation schedule forms are identified and elaborated in detail. Human comfort level and demand-side management applications are evaluated and incorporated into an optimization framework. The impact of peak demand reduction on the grid and power generation costs and the impact on the society is also investigated. The results demonstrate up to 12.5% savings in electricity consumption and 10% peak demand reduction for a community of 26 buildings.〈/p〉〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 51〈/p〉 〈p〉Author(s): Yijie Cao, Dan Shen〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In recent years, the popularity of sharing economy has been growing worldwide. Therefore, its features must be understood to adapt the economic development for the enterprises. The performance of Mobike in Beijing is used as a case in this study. Mobike is the largest shared bike company in the world and plays a prominent role in the sharing economy. Based on data obtained, online reports, and actual situations, the factors affecting the environment from shared bikes and the usage of bikes have been analyzed qualitatively and quantitatively. From the qualitative analysis, the model of the contribution of carbon dioxide emission reduction to the society has been constructed with the significant variables of registered rate, riding distance, and usage rate for shared bikes. The influence degree of each variable and their interactions are evaluated through response surface method and Minitab. The influencing extent of factors on CO〈sub〉2〈/sub〉 emission reduction is in the following order: riding distance 〉 proportion of registered users 〉 usage rate of shared bikes. The results show that shared bike plays comprehensive and positive roles for economy and environment. The study will provide a significant help for policymakers and business supervisors on development of shared bikes.〈/p〉〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Sina Rastani, Tuğçe Yüksel, Bülent Çatay〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Electric freight vehicles have strong potential to reduce emissions stemming from logistics operations; however, their limited range still causes critical limitations. Range anxiety is directly related to the total amount of energy consumed during trips. There are several operational factors that affect the energy consumption of electric vehicles and should be considered for accurate route planning. Among them, ambient temperature arises as a key factor because cabin heating or cooling may significantly increase the energy discharged from the battery during the trip and reduce the driving range. Additionally, cold temperatures decrease the battery efficiency and cause performance losses. In this study, we investigate the effect of ambient temperature on the fleet composition, energy consumption, and routing decisions in last-mile delivery operations. First, we present the mathematical programming formulation of the problem. Next, we perform an extensive computational study based on benchmark data from the literature. For solving the small-size instances we use a commercial solver. For solving the large-size instances we employ an adaptive large neighborhood search algorithm. Our results show that the route plans made without considering the ambient temperature effect may lead to inefficient operations and disruptions. Specifically, the fleet size and energy consumption can increase by 46% and 81%, respectively, in small-size problems on average due to ambient temperature whereas the average increase can reach 15% and 68%, respectively, in large-size problems. Finally, we present a case study from a logistics company operating in Southern Turkey to provide managerial insights to both researchers and practitioners.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Alexandros T. Zachiotis, Evangelos G. Giakoumis〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The effect of various non-regulatory parameters on a vehicle’s performance and emissions is investigated in this study, i.e. road grade, presence of crosswinds, surface wetness, tire pressure and use of the vehicle’s auxiliary systems. The vehicle under study is a diesel-powered turbocharged light commercial vehicle, running on the WLTC 3–2 cycle; comparison with the NEDC is also provided. The results derive from a computational code based on an engine-mapping approach applying experimentally derived correction coefficients accounting for transient operation. The engine code is coupled to a vehicle model that calculates the main longitudinal dynamic parameters (tire rolling resistance, aerodynamic performance, gearbox efficiency) on a fundamental basis. Soot and nitrogen monoxide are the examined pollutants, with fuel and energy consumption and CO〈sub〉2〈/sub〉 emissions computed and discussed too. From the parameters examined, road grade was found to have the greatest impact on emissions (CO〈sub〉2〈/sub〉: +116.8%, NO: +107.2%, Soot: +100.7%, for the maximum road grade examined of 8%), followed by wind speed (CO〈sub〉2〈/sub〉: +38.9%, NO: +33.6%, Soot: +12%, for the maximum wind speed examined of 80 km/h). Auxiliary power demand can have a considerable effect, mostly on fuel consumption/CO〈sub〉2〈/sub〉 emissions (+13.7% for maximum auxiliary power demand of 5000 W); the impact of tire inflation pressure and surface wetness is comparably smaller. Among the two driving cycles, the WLTC proved to be more ‘sensitive’ to road load changes, due to the broader speed range encompassed and its highly transient nature, compared to the softer NEDC.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 44〈/p〉 〈p〉Author(s): Hye Soo Suh, Daeung Danny Kim〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The study demonstrated a systematic approach to achieve the nearly zero energy community building through the assessment of energy performance of the combined passive and active design solutions and renewable energy systems. Among 16 community buildings, four buildings were selected and the parameters that had an impact on energy consumption were identified through the analysis of electricity and gas consumption. After the validation with the measured data of electricity and gas, the energy simulation was used to model the newly constructed community building. A combined passive and active design strategy was applied to improve the energy performance. To offset the energy use for the domestic hot water, possible renewable energy systems such as the PV system, the solar thermal system, and the geothermal heat pump system were reviewed and their efficiency was analyzed. As a result, the combination of the PV system with additional PV modules and the geothermal system was chosen for the achievement of the nearly zero energy target.〈/p〉〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 44〈/p〉 〈p〉Author(s): Zhiqiang John Zhai, Jacob Michael Helman〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Climate change is a widely acknowledged major environmental problem whose impacts on building energy use however are not fully understood. Various climate models have been developed and used to project climate changes; however most of existing studies on climate change impacts only use few model outcomes, providing narrow predictions on the influences. This study analyzed a large number (i.e., 56) of models and scenarios. The obtained future climate data showed a wider range of potential changes and thus impacts on building energy. Four reference climate models were identified to cover the full range of the 56 models for three time periods and seven climate zones. The accuracy of model projections was validated using historical data. The study predicted the potential energy implications of climate changes to a campus building stock. Influences of these changes on utility and economics were analyzed. The study further explored the potential impacts of climate change to the current climate zones that directly relate to building energy consumption.〈/p〉〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 44〈/p〉 〈p〉Author(s): Jorge Navarro-Rubio, Paloma Pineda, Antonio García-Martínez〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Eco-efficiency and building optimization potential of prefabricated structures to be used in new buildings are studied, focusing on the analysis of a novel dry precast beam-column connection under different durability and re-using scenarios. The analyses include structural response (via numerical models), optimization potential (material take off, building schedule and economic cost) and environmental impact (via Life Cycle Assessment, LCA). The connection is applied to a case study which is representative of common buildings: a seven-story concrete structure with frames and deck slabs. The structural response of the connection accomplishes the Eurocode safety prescriptions. Man-hours and task duration decrease around 80%, and the global schedule undergoes 60% diminution. Focusing on economic issues, when the prefabricated structural elements are reused the accumulated economic cost significantly decreases. LCA shows that durability, in terms of service life, is directly related to the environmental impact. However, other design options, such us re-using, have less repercussion in the impact categories (i.e. Global Warming Potential and Embodied Energy), and in the global cost. Results from this research could contribute to the implementation of prefabricated elements in the building stock promoting eco-efficiency.〈/p〉〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 44〈/p〉 〈p〉Author(s): Fabiana Silvero, Fernanda Rodrigues, Sergio Montelpare, Enrico Spacone, Humberto Varum〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Nowadays, energy efficiency (EE) is presented as a reliable strategy towards sustainable development, but its application has not been developed equitably worldwide, since most EE policies have been implemented in industrialised nations, and developing countries are still in the process of improving their EE levels. This paper provides a contextual framework to analyse the EE situation in countries of Latin American Southern Cone, such as Argentina, Brazil, Chile and Uruguay, with the objective of describing the policies and projects implemented, highlighting the results achieved and outlining the path followed towards EE. A focus was placed on the building sector, where thermal performance standards and the programs to achieve EE in this sector were briefly described. Furthermore, a comparison between these standards was developed, to identify the country with the most demanding standard. As a result, it was found that all the countries are implementing several EE programs and recognising the importance of this issue within their policies. Through this paper, energy policy implications of the region can be identified, which can be useful for energy policymakers of other countries, who are beginning to consider EE policies and can take as an example the path followed by the countries analysed.〈/p〉〈/div〉

Description: 〈p〉Publication date: December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 65〈/p〉 〈p〉Author(s): Michel André, Anaïs Pasquier, Marion Carteret〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Low emission zones are frequently envisaged as a means of decreasing air pollution in city centres. In the present study, we used video monitoring to characterize the in-use local vehicle fleet at several points in the Île-de-France region (which includes the city of Paris), enabling accurate description of the type of engine and vehicle age and emission standard, which together determine their pollutant emission levels. Local vehicle fleets differed from French national estimates, as further confirmed by a Regional Mobility Survey. Both approaches (video monitoring and mobility survey) demonstrated geographical differences in the proportions of diesel and of recent vehicles. Economically advantaged areas, with lower rates of polluting and diesel-fuelled vehicles, are thus further advantaged as regards air quality and less affected by driving restrictions. Simulation of pollutant emissions demonstrated the sensitivity of the estimates to local fleet composition. They also raised the important contributions of traffic outside the city centre, of heavy vehicles and cold starts. Knowledge of the local vehicle fleet is thus important for designing low emission zones that will be effective in terms of air pollution and equitable in terms of geographical areas.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 45〈/p〉 〈p〉Author(s): Jinsoo Park, Dong Ho Shin, Seung Joo Lee, Youhwan Shin, Sarng Woo Karng〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Thermal energy storage is an essential technology for using renewable energy to reduce building energy consumption. Among the various energy technologies, much attention has been paid to latent thermal energy storage system using phase change materials because of its large capacity of thermal energy. However, due to the low thermal conductivity of the phase change materials, the system has disadvantages at low charging and discharging rates. To address this issue, a new latent heat thermal energy storage system using a flexible and thin pouch is proposed. The effectively designed pouch arrangement and thin pouch shape provide better heat transfer performance. The real product is tested at various flow rates of heat transfer fluids and the thermal and fluid characteristics of the system are analyzed by the computational fluid dynamics model. As a result, the proposed system has 1.4 times larger amount of discharged energy than that of the water storage system. Moreover, the system can reduce charging, discharging, and total process times by 1.7, 2.5, and 2.2 times, respectively, compared with the conventional sphere capsule piling system.〈/p〉〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 44〈/p〉 〈p〉Author(s): Logaraj Ramakreshnan, Nasrin Aghamohammadi, Chng Saun Fong, Amirhosein Ghaffarianhoseini, Li Ping Wong, Nik Meriam Sulaiman〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉A very few studies have evaluated and understood the temporal dynamics of UHI in many expanding tropical cities. Hence, this study investigated the temporal variations of canopy-level UHI in selected urban stations, namely Petaling Jaya (PJ) and Subang (SUB), of Greater Kuala Lumpur (GKL) using 2016’s hourly data set obtained from meteorological observatories. The association between meteorological factors and UHI Intensity (UHII) is evaluated using linear regression models and Pearson correlation analysis. The findings revealed positive thermal contrasts between urban and sub-urban stations with maximum UHII during dry, southwest monsoon season in PJ (June: 1.68 °C) and SUB (August: 1.29 °C) stations respectively. PJ station exhibited a distinct diurnal cycle with the maximum nocturnal UHII of 1.71 °C at about 8 p.m. after sunset under ideal meteorological conditions. The results also demonstrated that UHI events occurred more frequently at nights in urban stations in the magnitude range of 0–2 °C. Cooling at all urban sites starts around 2–3 p.m. with the highest rate of 0.73 °C/h and 0.96 °C/h in PJ and SUB stations. Meanwhile, relative humidity displayed a low positive correlation (r = 0.37, p ≥ 0.05) and a high negative correlation (r = −0.79, p 〈 0.05) with UHII in PJ and SUB stations respectively. The influence of wind speed on UHII is weak (r = −0.44, p 〈 0.05) in PJ station and strong (r = 0.83, p 〈 0.05) in SUB station. Overall, this study can be regarded as one of the comprehensive observational investigations of canopy-level UHI in a tropical city that provide vital inputs to enrich the tropical urban climate literacy.〈/p〉〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 44〈/p〉 〈p〉Author(s): Bao-Jie He, Zi-Qi Zhao, Li-Du Shen, Hong-Bo Wang, Li-Guang Li〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Numerous studies on urban heat island (UHI) effects have examined relationships between land use/land cover (LULC) and land surface temperature (LST), while impacts of environmental temperatures on these relationships have received little attention. This paper has investigated how background temperature affects performances of cool/hot sources in either enhancing or mitigating LST in Shenyang, China based on Landsat 8 image. In specific, according to the method of standard classification method with an interval of 1.0 standard deviation, LST was classified into seven temperature levels: highest, higher, high, medium, low, lower and lowest. Afterwards, the seven levels were merged into three temperature zones (TZ), namely cold TZ (CTZ, highest, higher and high), neutral TZ (NTZ, medium) and hot TZ (HTZ, low, lower and lowest), for investigating relationships between LST and LULC (including building (BU), road (RO), bare land (BA), green land (GR), agricultural land (AG) and water bodies (WA)). LST generally follows the order of BU 〉 RO 〉 BA 〉 AR 〉 GR 〉 WA, but temperature differences between cool/hot sources reduce as background temperature increases. LULC-LST relationships vary greatly with background temperature. Overall, BU and RO have significant positive relationships with LST, while negative relationships are found among GR, AR, WA and LST. However, in CTZ, RO is in negative relationships with LST, GR and WA are no longer significant in NTZ, and GR and BA play significant positive roles in aggravating LST in HTZ. Generally, this study can help orientate scientific decisions in urban environmental governance.〈/p〉〈/div〉

Description: 〈p〉Publication date: December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 65〈/p〉 〈p〉Author(s): Laura Minet, Jonathan Stokes, James Scott, Junshi Xu, Scott Weichenthal, Marianne Hatzopoulou〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This study was motivated by an interest in capturing the factors affecting the exposure of cyclists to ambient Ultrafine Particles (UFP), Black Carbon (BC), and noise (LA〈sub〉eq〈/sub〉) across the entire bicycle network of the City of Toronto. Measurements were conducted along 270 km of unique roads, and we developed land use regression models and exposure surfaces. Median UFP, BC and noise levels recorded were 19,848 part/cm〈sup〉3〈/sup〉, 1224 ng/m〈sup〉3〈/sup〉, and 72.9 dB respectively. The average UFP and BC exposures along the biking routes (18,900 part/cm〈sup〉3〈/sup〉 and 1130 ng/m〈sup〉3〈/sup〉) were higher than the average levels measured at a fixed station located in downtown Toronto (13,300 part/cm〈sup〉3〈/sup〉 and 809 ng/m〈sup〉3〈/sup〉). The highest UFP and BC levels were experienced on dedicated bicycle tracks (30,000 part/cm〈sup〉3〈/sup〉 and 1600 ng/m〈sup〉3〈/sup〉 as median concentrations), while the highest noise levels occurred on major roads (median of 74 dB). In contrast, median levels on trails were 13,200 part/cm〈sup〉3〈/sup〉, 535 ng/m〈sup〉3〈/sup〉 and 70.2 dB, for UFP, BC, and noise. The exposure surfaces developed for the air pollutants and noise were intersected with the planned extensions to the bicycle network in the City of Toronto to evaluate the distributions of exposures expected across the future cycling network. We observe that the mean and median UFP, BC, and noise levels across planned facilities are equal to or significantly higher than the levels across the current network.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S1361920918301925-ga1.jpg" width="269" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 44〈/p〉 〈p〉Author(s): Xiaojun Liu, Wei Hu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Energy conservation and consumption reduction in the field of construction are the keys to achieving the target global temperature growth of the Paris Agreement. However, the current promotion of 〈strong〉green〈/strong〉 buildings is still stuck in the rut of government excessive intervention, market less participation. In order to explore the status of the Chinese public’s attention, changing trends, sentiment orientation, and focus toward 〈strong〉green〈/strong〉 buildings, this paper collected and analyzed information of Weibo users and posts and comments of popular posts related to 〈strong〉green〈/strong〉 buildings. We used the Sina Weibo platform with web crawler technology and a text mining method. The results showed that: the public’s attention toward 〈strong〉green〈/strong〉 buildings has enhanced significantly with the change of government governance ideas, but still needs to be improved. Although vertical greening houses possess good heat preservation and thermal insulation, 46.32% of the Chinese public has negative sentiments toward vertical greening houses mainly due to worries about the increase in snakes, and mosquitoes and other insects caused by the increased vegetation cover. Price is not the main reason why the public has negative sentiments toward vertical greening houses.〈/p〉〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 44〈/p〉 〈p〉Author(s): Charles Peprah, Owusu Amponsah, Charles Oduro〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Urbanisation in the cities of Sub-Saharan Africa has been associated with urban sprawl and increased vehicular traffic, which undermine the agglomeration effects of the cities on socioeconomic development. These adverse effects will exacerbate as the human population of the region continues to increase. Some scholars argue that making the cities mobility-smart could mitigate the adverse effects of urbanisation in the region. However, the conventional literature on smart mobility in Sub-Saharan Africa does little to demonstrate how the concept can be applied. In this regard, the purpose of this study is two pronged: a) to assess the mobility smartness of Ghanaian cities and b) to demonstrate how the concept can be operationalised to mitigate some of the adverse effects of urbanisation in the cities. The research process began with a review of relevant literature to conceptualise smart mobility. The conceptual framework was then used to assess the mobility-smartness of Ghanaian cities, which was followed by a discussion of how the concept of smart cities can be operationalised in Ghanaian cities. The results show that the cities in Ghana, like many cities in Sub-Saharan Africa, depend mainly on the road sub-sector for the movement of people and freight. The rapid increases in vehicular population without a commensurate expansion in road infrastructure have undermined the cities’ productivity. The conclusion from this is that the cities are not mobility-smart and for this to change, the paper argues that efforts should be made to improve people mobility, information logistic mobility and information mobility. These require technological literate and receptive population and investments in transport infrastructure.〈/p〉〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 44〈/p〉 〈p〉Author(s): Ning Wang, Linhao Tang, Huizhong Pan〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Environmental issues and energy security have led governments to introduce lots of incentive policies on electric vehicle promotion. Benefiting from policy dividend, the global threshold of 1 million electric cars on the road had been exceeded in 2015, closing at 1.26 million. Among these incentive policies, subsidy scheme was regarded as the most important and effective. However, many governments intend to abrogate subsidy for electric vehicle, such as China, America and Germany. It`s worth finding out the key factors including incentive measures and additional socio-economic factors that promote electric vehicle adoption. Utilizing multiple linear regression method, we explore the relationship between those variables and 30 national electric vehicle market shares for the year 2015. The results show that chargers` density, fuel price and road priority are significantly positive factors correlated with a country`s electric vehicle market share. Nevertheless, fiscal incentives are no longer the reasons for the huge differences of electric vehicle promotion over countries. This paper is helpful for policymakers to adjust and improve their policy for electric mobility.〈/p〉〈/div〉

Description: 〈p〉Publication date: May 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 70〈/p〉 〈p〉Author(s): Tom Wenzel, Clement Rames, Eleftheria Kontou, Alejandro Henao〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper identifies major aspects of ridesourcing services provided by Transportation Network Companies (TNCs) which influence vehicles miles traveled (VMT) and energy use. Using detailed data on approximately 1.5 million individual rides provided by RideAustin in Austin Texas, we quantify the additional miles TNC drivers travel: before beginning and after ending their shifts, to reach a passenger once a ride has been requested, and between consecutive rides (all of which is referred to as deadheading); and the relative fuel efficiency of the vehicles that RideAustin drivers use compared to the average vehicle registered in Austin. We conservatively estimate that TNC drivers commute to and from their service areas accounts for 19% of the total ridesourcing VMT. In addition, we estimate that TNC drivers drove 55% more miles between ride requests within 60 min of each other, accounting for 26% of total ridesourcing VMT. Vehicles used for ridesourcing are on average two miles per gallon more fuel efficient than comparable light-duty vehicles registered in Austin, with twice as many are hybrid-electric vehicles. New generation battery electric vehicles with 200 miles of range would be able to fulfill 90% of full-time drivers’ shifts on a single charge. We estimate that the net effect of ridesourcing on energy use is a 41–90% increase compared to baseline, pre-TNC, personal travel.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S1361920918309878-ga1.jpg" width="298" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: May 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 70〈/p〉 〈p〉Author(s): Stefanie Peer〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper investigates the determinants of cycling in a rather unique setting: the relocation of one of the largest Austrian universities from the North to the East of Vienna (a distance of approximately 5 km). We analyze the students’ cycling behavior before and after the university relocation based on a large-scale (retrospective) online survey. Unlike earlier studies on cycling determinants, which often suffer from endogeneity, we can exploit the fact that the university relocation causes commute-related variables to change exogenously, whereas socio-economic and attitudinal characteristics as well as the trip purpose remain constant. We find a large positive correlation in the propensity to cycle to the old and the new university location at the person level as well as substantial heterogeneity in cycling inclination across students, which can only partially be explained by socio-economic and attitudinal variables. Moreover, we find evidence that past cycling times form a reference point for future mode choice decisions.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: May 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 47〈/p〉 〈p〉Author(s): Louise Krog〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Radical changes in energy production, going from sector-based energy systems based on fossil energy resources to smart energy systems based on renewable resources are starting to occur worldwide. This transition is a matter of balancing technical solutions with societal needs and possibilities, which requires a large effort in terms of policymaking and energy planning. This paper investigates how Danish municipalities are currently dealing with these issues through strategic energy planning. Through a case study of a Danish municipality, strategic and practical barriers to municipal strategic energy planning are identified. The paper ends by presenting recommendations on how to eliminate the identified barriers. In doing so, this paper brings new knowledge into further research of national and local framework conditions for strategic energy planning and thereby, the green transition of the energy system.〈/p〉〈/div〉

Description: 〈p〉Publication date: May 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 47〈/p〉 〈p〉Author(s): Meng Yuan, Qiong Zhang, Bohong Wang, Yongtu Liang, Haoran Zhang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper investigates optimal planning of a bicycle sharing system (BSS) from an integrated and long-term perspective, namely by combining strategic design and operation decisions in an integrated way while considering the stochastic demand and service level. The methodological contribution of the current research effort is to propose a unified mixed integer linear programming (MILP) model, in which several sub-problems such as the number, location, and capacity of bicycle stations; total fleet size design; depot location design; and rebalancing and maintenance plans are combined and can be solved together. A scenario-based approach is applied to deal with stochastic demand. Also, the concept of subjective distance is proposed to characterize the coverage area of bicycle stations, which together with the availability rate for bicycles are set as metrics of the service level. A case in Beijing, China is studied and sensitivity analyses are performed for key parameters. To illustrate the practical value of the proposed approach, a comparison between the planning results solved by the proposed MILP model with the BSS in real life regarding station layout is also undertaken. From the results, we observe that a balance between the costs borne by the operator and the service level for users can be achieved. The stations are distributed evenly across the study area, which could increase the coverage and thus enhance the convenience of the service. The model developed can be employed by BSS operators for the planning decisions.〈/p〉〈/div〉

Description: 〈p〉Publication date: May 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 47〈/p〉 〈p〉Author(s): Byoung Hoon Ha, Yoon-shin Kim, Pyoung Won Kim〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The smart city has become the key factor of the progression of the future city, and the smart device sensors are widely used in real-time applications to achieve smart city. Especially, super-resolution techniques have resulted in embedded video surveillance turning into a principal method of protecting public security. In this paper, we present a super-resolution method for embedded system which interpolates unknown pixel components at the zero-padded signals. This work is for a smart global village by applying real-time embedded monitoring system (such as traffic purpose) using visual sensor networks. In general, images are obtained from a number of visual sensor nodes and cameras. The visual sensor node conveys them to the computer devices for processing. To this end, a process called image super-resolution is needed. In this work, a filter design method is researched by using a regression approach. There are two main stages of this work. First, we study filter designing method training dataset. Second, we implement super-resolution process by applying pre-designed filters. Experimental results are given to show the superiority of the proposed method compared to the conventional methods. This paper also demonstrates super-resolution results obtained by designed filter and its implementation.〈/p〉〈/div〉

Description: 〈p〉Publication date: May 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 70〈/p〉 〈p〉Author(s): Emir Çabukoglu, Gil Georges, Lukas Küng, Giacomo Pareschi, Konstantinos Boulouchos〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.gif" overflow="scroll"〉〈mrow〉〈msub〉〈mrow〉〈mi mathvariant="italic"〉CO〈/mi〉〈/mrow〉〈mrow〉〈mn〉2〈/mn〉〈/mrow〉〈/msub〉〈/mrow〉〈/math〉 emissions of road freight transport may seem secondary to passenger cars, but electrification could eliminate direct emissions of cars. For heavy-duty trucks, it is unclear if substituting Diesel is even an option. We developed a data-driven approach to explore this issue: it estimates feasibility considering the daily operation patterns of every vehicle in the fleet. This paper presents results for fuel cell propulsion systems. If every Swiss truck drove on hydrogen produced exclusively by electrolysis, full decarbonisation would draw over 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si31.gif" overflow="scroll"〉〈mrow〉〈mn〉8〈/mn〉〈mspace width="0.25em"〉〈/mspace〉〈mtext〉TWh〈/mtext〉〈/mrow〉〈/math〉 of renewable electricity (〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si32.gif" overflow="scroll"〉〈mrow〉〈mn〉13〈/mn〉〈mo〉%〈/mo〉〈/mrow〉〈/math〉 of the national consumption). That corresponds to roughly 60 km〈sup〉2〈/sup〉 of photovoltaic panels with 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si33.gif" overflow="scroll"〉〈mrow〉〈mn〉1.5〈/mn〉〈mspace width="0.25em"〉〈/mspace〉〈mtext〉GW〈/mtext〉〈/mrow〉〈/math〉 peak power. We found that current fuel-cell technology almost completely realized that potential, provided vehicles could refuel during the day. The autonomy range was generally better than with battery electric systems without significant weight increase (relative to the original vehicle). Refuelling could take over half an hour, requiring a dense energy infrastructure, able to refuel hundreds of vehicles in parallel to avoid congestion (i.e. vehicles waiting). The reduction of direct emissions was easily overcompensated by indirect emissions of generation: the Swiss consumer mix lead to virtually no overall reduction, while natural gas powerplants lead to a significant 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.gif" overflow="scroll"〉〈mrow〉〈msub〉〈mrow〉〈mi mathvariant="italic"〉CO〈/mi〉〈/mrow〉〈mrow〉〈mn〉2〈/mn〉〈/mrow〉〈/msub〉〈/mrow〉〈/math〉 increase. We concluded that hydrogen is technically a very attractive decarbonisation agent for heavy-duty vehicles, but significant investments may be required to ensure that (a) hydrogen production is truly renewable and (b) vehicles have adequate access to additional energy during the day.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: May 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 47〈/p〉 〈p〉Author(s): M.A. Tavakoli Ghazi Jahani, P. Nazarian, A. Safari, M.R. Haghifam〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Distribution networks are energy sectors that usually deal with residential energy consumers whose expectations associated with voltage quality and other relevant issues should be taken into account. There are various factors that might threaten reliable/economic performance of the distribution networks. In this paper, optimal reconfiguration of distribution systems is studied under a multi-objective optimization model to enhance reliability and minimize power losses of distribution networks. The developed multi-objective model is solved with epsilon-constrained (EPC) method and the trade-off conditions are achieved with min-max fuzzy satisfying (MMFF) technique. Demand response services (DRSs) including time-of-use (TOU) mechanism are proposed to make the energy consumers capable of revising their energy usage pattern. The proposed framework is investigated regarding the IEEE 33-bus test system in general algebraic modeling systems (GAMS) and the results validating the effectiveness of the proposed model are presented and compared. According to the obtained results, after reconfiguring the distribution system under the proposed model, loss of power in the system is reduced and reliability of a system associated with energy not supplied (ENS) index is improved. After proposing DRS and having the consumers motivated to change their consumption pattern, the obtained values for the mentioned targets are more suitable.〈/p〉〈/div〉

Description: 〈p〉Publication date: May 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 47〈/p〉 〈p〉Author(s): Sadaf Feyzi, Mehrdad Khanmohammadi, Niloofar Abedinzadeh, Mehdi Aalipour〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Site selecting for installing municipal solid waste incineration power plant with sustainable development perspectives is a multi-criteria decision. Identifying the factors that affect it will lead to more advantages including reducing costs and eliminating community dissatisfaction. In this research, in order to provide the most optimal model, the criteria for installing MSWI power plant were developed in the form of three main environmental, economic, and socio-cultural criteria. First, the decision making trial and evaluation laboratory (DEMATEL) technique has been applied to identify the interrelations between factors. Then, they were ranked by importance by fuzzy analytic network process (FANP). Based on the results, the highest and least significance have been assigned to the main economic, socio-cultural criteria, and sub-criteria of land use and railway respectively. Finally, a case study was conducted in Rasht County in order to evaluate the efficiency of the obtained model. Using geographic information system, GIS, we applied the final weights to the layers of each of the sub-criteria and overlay them. The results of the output map indicated the capability of the obtained model based on FANP and GIS to select the proper place for installing MSWI power plant and its application in other similar studies.〈/p〉〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 44〈/p〉 〈p〉Author(s): Reza Sedaghati, Mahmoud Reza Shakarami〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper proposes a new control and power management strategy for a grid-connected microgrid, which includes a hybrid renewable energy sources (HRES) system and a three-phase load. The HRES system consists of a photovoltaic (PV), a battery storage system (BSS), a super-capacitor (SC) and a solid oxide fuel cell (SOFC). The dynamic model of each of these units is described. The PV is the main energy source, while the SC and the BSS due to their various power densities are considered to provide a steady and transient load demand, respectively. For increasing the reliability of the system, SOFC source is selected to keep the BSS completely charged. All these units with different DC-DC converters are connected in parallel to a common DC bus. Then, a three-phase voltage source inverter (VSI) is employed to convert the DC voltage to AC. To maintain the power balance and appropriate load-sharing, an adaptive fractional fuzzy sliding mode control (AFFSMC) strategy for VSI-based HRES system is presented. The controller is able to track the pre-defined instruction precisely and quickly in the microgrid. For stable performance of the control strategy under load variation, a fractional order-based sliding surface is considered. Moreover, fractional adaptive rules-based fuzzy sets are employed to accurately estimate the uncertain parameters in the microgrid. The simulation results demonstrate the effectiveness and capability of an AFFSMC strategy under various faults and different loading conditions. Moreover, the proposed control strategy is compared with the conventional PI controller.〈/p〉〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 45〈/p〉 〈p〉Author(s): Rupali Zope, N. Vasudevan, Shriniwas S. Arkatkar, Gaurang Joshi〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Increasing number of issues related to transport system around the world has raised concern about sustainable development. For developing country like India, the role of transportation sector has become critical in creating supporting growth of diverse sectors of its urban economy. The key issues of present state of transport system are higher level of motorization with dismally low share of public transport. Both of these issues are intertwined with number of social, economic and environmental aspects of sustainable development. Hence, there is a need for an evaluation approach which will help to analyze ‘macro-level’ system to give ‘micro-level’ analysis of the transport system. Benchmarking is one such method of comparing performances and practices and to learn from best. This paper is an attempt to study the use of benchmarking in performance improvement of the transport system. Results obtained through the study shows that the cities having a better modal share of sustainable modes occupy a higher rank with greater values of the sustainability index. In the current study, a software tool for monitoring the sensitivity of composite index of transport system towards performance indicators of sustainability is also developed. The comparative analysis of current study facilitates city-to-city learning.〈/p〉〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 44〈/p〉 〈p〉Author(s): Xueqin Chen, Hehua Zhu, Xiaojun Li, Xiaodong Lin, Xiuzhi Wang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉To investigate the inherent uncertain and dynamic deterioration of metro shield tunnels in operation, the Bayesian ordered probit model, a data mining method, was used in this study. Through Markov Chain Monte Carlo (MCMC) simulation, the uncertainty in parameter estimation was significantly reduced, and the confidence in the results was improved. The effects of influencing variables on the deterioration process were evaluated. It was found that the tunnel sections with greater burial depths were more likely to deteriorate than the shallow ones. Crossing below a river or near a station or cross passage accelerated the deterioration rate. The deterioration probability increased as the tunnel became older. Finally, the model was applied to a tunnel section. It was shown that the probability of the best state decreased while that of the worst state increased with age. For states between the best and the worst, the probability would first increase, reach a peak, and then decrease. This study found that the ordered probit model with MCMC was a valuable probabilistic method for performance prediction, which is crucial for cost-effective decision-making in future work.〈/p〉〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 44〈/p〉 〈p〉Author(s): Muhammad Waseem Khan, Jie Wang, Meiling Ma, Linyun Xiong, Penghan Li, Fei Wu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉At present, energy generation is evolving into a smart distribution system that assimilates several green energy resources at a distributed level assuring to generate clean energy without producing any harmful gases, to have consistent operational procedures, and to improve energy management and supervision arrangements. The renewable energy resources (RERs) are considered the best suitable approach to generate electrical power at the distributed level since they offer benefits to the power systems as well as to the environment. Therefore, this paper presents the recent research work on multi-agents-based coordination for the optimal management of electrical energy and its proper controlling at the distributed level exploiting RERs. The multi-agent system (MAS) technique is discussed in detail along with the storage and protection system that solve the microgrid (MG) control and management issues efficiently. Several platforms to develop the MASs are addressed including those that empower the MG to control its configuration, generation capacity, power flow, and fault control. There are several controlling approaches used on distributed generation systems to efficiently operate the whole system comprising of centralized, distributed, and hybrid control techniques are discussed. A comprehensive description about different optimization techniques applied to the energy system have also been highlighted, particularly to identify the most common and effective technique that is currently applied to hybrid energy system at the distributed level. The analysis shows that the particle swarm optimization (PSO) is the most useful and effective technique that has been applied since it can minimize the interruption costs, maximize the reliability, and optimize the operational schedules at the MG level.〈/p〉〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 44〈/p〉 〈p〉Author(s): Yi Yang, Guanfei Meng〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉China plans to pursue low-carbon development in its western megacities to control greenhouse gas emissions. Using the 〈em〉“〈/em〉2006 IPCC and the 〈em〉Chinese Guidelines”〈/em〉, the carbon footprint (CF), carbon carrying capacity, carbon deficit and carbon deficit pressure index of Xi’an were measured from 2007 to 2016. Then, the decoupling indicator was used to analyse the dynamic relationship between the urban CF and economic growth using partial least squares to explore the driving factors of CF. The results show that: (1) the CF increased from 23.34 million t CO〈sub〉2〈/sub〉eq to 32.25 million t CO〈sub〉2〈/sub〉eq, with average annual growth being 4.01%. The energy consumption accounts contributed 69.51%, far exceeding other accounts. (2) The carbon carrying capacity of Xi’an decreased from 7.78 million t CO〈sub〉2〈/sub〉eq to 7.45 million t CO〈sub〉2〈/sub〉eq, with an average annual reduction of 0.47%. The carbon deficit index fluctuated in the interval [−2.57%, 17.09%], indicating that Xi’an was in the ecological stress relief and the mildly enhanced zone. The total CF and the CF of each account exhibit a relationship of “connecting-decoupling-re-hook-re-decoupling” with economic growth. (3) The most important driver of CF growth is the per capita residential building area, while the urbanization rate restrains the growth of the CF.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 14 December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment〈/p〉 〈p〉Author(s): N. Coulombel, V. Boutueil, L. Liu, V. Viguié, B. Yin〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper investigates how and to what extent changes in user behavior may mitigate the environmental benefits of urban ridesharing, a phenomenon commonly referred to as “rebound effect”. Ridesharing reduces both the individual cost of car travel (through cost splitting) and road travel times (by decreasing congestion). This may trigger a number of behavioral changes among transportation users, including: making less detours to avoid congestion (〈em〉route choice〈/em〉 effect), switching from public transit and active modes to the car (〈em〉modal shift〈/em〉 effect), travelling longer distances (〈em〉distance〈/em〉 effect), and relocating further from the urban center (〈em〉relocation〈/em〉 effect). Taking Paris region as a case study, this research applies an integrated transportation/land-use model to evaluate several ridesharing scenarios and quantify the four rebound effects. The overall rebound effect is found to be substantial, cancelling out from 68 to 77% of CO〈sub〉2〈/sub〉 emission reductions and from 52 to 73% of aggregated social benefits (including congestion, air quality, CO〈sub〉2〈/sub〉 emissions, noise) expected from ridesharing. This is primarily the result of the modal shift effect, supplemented as ridesharing develops by the distance effect. Although the simplified representation of ridesharing in the baseline model calls for caution regarding these estimates, a sensitivity analysis corroborates the main findings and the prevalence of substantial rebound effects. The paper also investigates to what extent three complementary policies - improving public transit, reducing road capacity or increasing the cost of car travel – might limit the overall rebound effect and thereby maximize the benefits of urban ridesharing.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 11 December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment〈/p〉 〈p〉Author(s): Scott Hardman, Rosaria Berliner, Gil Tal〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Most major automakers are developing vehicles with some level of automated driving capability. These vehicles range from those with adaptive cruise control to full driverless vehicles. These vehicles are collectively referred to as automated vehicles. The adoption of automated vehicles by consumers is not well understood. It is likely that the first buyers will be typical early adopters i.e. consumers who have different lifestyles, attitudes, and socio-demographic profiles compared to the general population. Using a questionnaire survey of 2715 consumers in 36 states in the USA, we investigate the attitudes of early adopters of one automotive technology: plug-in electric vehicles (PEVs). This sample was selected so that the perceptions and purchase intentions of early adopters could be investigated. This is opposed to assessing the attitudes of the public who are unlikely to be knowledgeable about automated vehicles and unable to accurately assess the vehicles and estimate their own purchase intentions. This study finds that PEV early adopters have positive perceptions of automated vehicles. However, being a PEV adopter does not necessarily lead to interest in purchasing an automated vehicle. PEV adopters are clustered into 5 different groups with differing levels of interest in automated vehicles (from “Pioneers” to “Laggards”). The results suggest that automated vehicles are likely to be purchased by a small group of pioneering consumers. These “Pioneers” are likely to be high income consumers, with good knowledge and positive perceptions of the automated vehicles (on safety, comfort, and purchase price), and positive attitudes towards technology in general.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 67〈/p〉 〈p〉Author(s): Anders Nordelöf, Emma Grunditz, Sonja Lundmark, Anne-Marie Tillman, Mikael Alatalo, Torbjörn Thiringer〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Ongoing development of electrified road vehicles entails a risk of conflict between resource issues and the reduction of greenhouse gas emissions. In this study, the environmental impact of the core design and magnet material for three electric vehicle traction motors was explored with life cycle assessment (LCA): two permanent magnet synchronous machines with neodymium-dysprosium-iron-boron or samarium-cobalt magnets, and a permanent magnet-assisted synchronous reluctance machine (PM-assisted SynRM) with strontium-ferrite magnets. These combinations of motor types and magnets, although highly relevant for vehicles, are new subjects for LCA. The study included substantial data compilation, machine design and drive-cycle calculations. All motors handle equal take-off, top speed, and driving conditions. The production (except of magnets) and use phases are modeled for two countries – Sweden and the USA – to exemplify the effects of different electricity supply. Impacts on climate change and human toxicity were found to be most important. Complete manufacturing range within 1.7–2.0 g CO〈sub〉2〈/sub〉-eq./km for all options. The PM-assisted SynRM has the highest efficiency and lowest emissions of CO〈sub〉2〈/sub〉. Copper production is significant for toxicity impacts and effects on human health, with problematic emissions from mining. Resource depletion results are divergent depending on evaluation method, but a sensitivity analysis proved other results to be robust. Key motor design targets are identified: high energy efficiency, slender housings, compact end-windings, segmented laminates to reduce production scrap, and easy disassembly.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S1361920918302530-ga1.jpg" width="252" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 67〈/p〉 〈p〉Author(s): Aliasghar Mehdizadeh Dastjerdi, Sigal Kaplan, Joao de Abreu e Silva, Otto Anker Nielsen, Francisco Camara Pereira〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The increasing complexity and demand of transport services strains transportation systems especially in urban areas with limited possibilities for building new infrastructure. The solution to this challenge requires changes of travel behavior. One of the proposed means to induce such change is multimodal travel apps. However, understanding the motivators underlying individuals’ travel intentions is essential to design and evaluate their effectiveness. This paper pinpoints and analyses the drivers and barriers that influence individual travel decisions when using such apps. The analytical framework relies on Alderfer's ERG model of human needs that relate the individual’s intentions to three domains, namely (1) Existence, (2) Relatedness and (3) Growth needs. Furthermore, environmental attitude, information privacy concerns and perceived difficulties when using the system are incorporated as to better explain user-sided heterogeneity. The case-study focuses on a new travel information system in Copenhagen (Denmark), which is not yet operational, through a technology-use preference survey among 828 travelers. Structural equation models revealed that the motivation for choices are specific to individual users and depend on wide-ranging factors that go beyond traditional economic and socio-demographic methods. The study revealed (1) different intentions among individuals according to the perceived value of the new information system, (2) a relation between different environmental attitude constructs and users’ needs, (3) a stronger appeal to use the system for individuals with higher needs of developing social self-concept and eco-travel self-efficacy as well as with lower perceived privacy risk and perceived difficulties, (4) that both functional and psychological factors affect adoption intention.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S1361920918304735-ga1.jpg" width="366" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 67〈/p〉 〈p〉Author(s): Rafael F.F. Lemme, Edilson F. Arruda, Laura Bahiense〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Electromobility can be one of many solutions to the environmental challenge facing society nowadays, and the dissemination of policies towards the adoption of electric vehicles (EVs) urges the development of studies to assess their actual benefits in contrast to both conventional and other alternative technologies. This work proposes an optimization model to evaluate the influence of the selected parameters in the economic and environmental dimensions of different vehicle technologies and the optimal fleet composition for small-scale car sharing. The model is applied to car sharing system VAMO, located in Fortaleza (Brazil), and the decision variables comprise pure electric (BEV), plug-in hybrid (PHEV) and internal combustion engine (ICEV) vehicles. Baseline results are strongly influenced by the economic dimension, showing that existing infrastructure and well-established technology are great advantages for ICEVs and major barriers for EVs. In that sense, ethanol arises as a balanced alternative between costs and emissions. However, EVs represent a strong environmental appeal considering global emissions and local pollutants and even with economic losses in the short-term, investments in electromobility could come out as a positioning strategy in a future business with strong perspectives of growth, be it technological or in market share. The results suggest that all vehicle technologies will play an important role during this transition period to a desired sustainable mobility.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 67〈/p〉 〈p〉Author(s): J. Semeijn, C.J. Gelderman, J.M.C. Schijns, R. van Tiel〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Although it is often assumed that physically disabled people have different environmental attitudes and behavior, there has been very little empirical evidence supporting this claim. This study is the first to shed light upon the determinants of physically disabled consumers’ pro environmental purchase intentions. We gathered survey data from (net) 118 physically disabled consumers about their purchase intentions for environmentally friendly cars. Structural equation modeling is used for the analysis. The results show that attitude and social norms are important predictors of environmentally friendly purchase intentions. Both hedonic and functional motivation have an indirect effect, while attitude has a direct effect on physically disabled people’s purchase intentions for environmentally friendly cars. Apparently, physically disabled people value the opinions of others in their living and working environment. Notably, we did not observe an expected impact of behavioral control or lack thereof on the purchase intention of environmentally friendly cars. The study offers insights that can be helpful to marketing managers and policymakers in tailoring their strategies to the purchase intentions of physically disabled consumers.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 2 December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society〈/p〉 〈p〉Author(s): Nuno D. Cortiços〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The building sector — following tech's development — favor buildings' short-term replacement. This demands substantial construction operations, especially if implies the demolition of superstructures, before reaching their potential lifespan: up to 120 years for modern solutions. With high costs for societies, due to the complex logistics and the risks involved: public health, GHG emissions, energy waste, noise, light particles pollution, excessive water consumption, urban restrictions, delays in traffic, et cetera. This research aims to extend building’s life with desirable gains in performance, considering the superstructure longevity, supported by technologies on renovation to meet the requirements set for new buildings, as nZEBs. Supported by maintenance methodology to assess actual performance and a Tool to simulate each underperforming system renovation, limited to passive solutions of the building envelope, quantifying the energy savings to favor the shortest investment reimbursement in decennial periods. Buildings were assessed, and a renovation plan simulated, concluding that the rehabilitation is only justified if under 10% (decennial period) of renovation cost, and if able to recover the initial performance. Renovation showed the potential to increase building performance 〉10% and energy savings 〈45% or 811 kWh/m〈sup〉2〈/sup〉.year for acclimatization only, under 9,6 kWh/m〈sup〉2〈/sup〉.year, set for Lisbon’s nZEBs.〈/p〉〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 67〈/p〉 〈p〉Author(s): Federico Perrotta, Tony Parry, Luis C. Neves, Thomas Buckland, Emma Benbow, Mohammad Mesgarpour〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉This paper presents an assessment of the accuracy of the HDM-4 fuel consumption model calibrated for the United Kingdom and evaluates the need for further calibration of the model. The study focuses on HGVs and compares estimates made by HDM-4 to measurements from a large fleet of vehicles driving on motorways in England. The data was obtained from the telematic database of truck fleet managers (SAE J1939) and includes three types of HGVs: light, medium and heavy trucks. Some 19,991 records from 1645 trucks are available in total. These represent records of trucks driving at constant speed along part of the M1 and the M18, two motorways in England.〈/p〉 〈p〉These conditions have been simulated in HDM-4 by computing fuel consumption for each truck type driving at a constant speed of 85 km/h on a flat and straight road segment in good condition.〈/p〉 〈p〉Estimates are compared to real measurements under two separate sets of assumptions. First, the HDM-4 model calibrated for the UK has been used. Then, the model was updated to take into account vehicle weight and frontal area specific to the considered vehicles.〈/p〉 〈p〉The paper shows that the current calibration of HDM-4 for the United Kingdom already requires recalibration. The quality of the model estimates can be improved significantly by updating vehicle weight and frontal area in HDM-4. The use of HGV fleet and network condition data as described in this paper provides an opportunity to verify HDM-4 continuously.〈/p〉 〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 45〈/p〉 〈p〉Author(s): Wangtu (Ato) Xu, Linchuan Yang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This study proposes a measure to evaluate the urban land use plan with transit accessibility, more specifically, the spatial accessibility of transit stations. The spatial accessibility of transit stations is measured with the number of effective reachable grids, and the influence of transfer on reduction in spatial accessibility is considered. A geographically weighted regression model is used to determine the correlation between transit accessibility and urban land use characteristics. Moreover, the methodology is applied to Xiamen, China and the corresponding results demonstrate the usefulness and effectiveness of the proposed methodology. Researchers can adopt the proposed approach to evaluate urban land use plan, particularly in transit-dominated and car-lite contexts.〈/p〉〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 67〈/p〉 〈p〉Author(s): Dafeng Xu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉More than 50 bikeshare programs have been launched in the U.S. since 2010. In this paper, I estimate the effects of bikeshare programs on the prevalence of obesity at the county level. To do so, I merge bikeshare system data with obesity data released by Centers for Disease Control and Prevention, and construct a county-level panel covering the period of 2007–2013. I employ a difference-in-differences empirical framework, in which I compare the obesity rate before and after the introduction of the bikeshare programs in counties that have ever launched bikeshare programs, and use counties that have never introduced bikeshare programs as the control group. Difference-in-differences estimates suggest the significant public health effect of bikeshare programs: the introduction of the bikeshare programs leads to moderate declines in obesity rates; a possible mechanism is its impacts on leisure-time physical activities. I also conduct various additional tests to check the robustness of the above findings. These tests show that the conclusion of this paper is robust to changes to samples and empirical models.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 45〈/p〉 〈p〉Author(s): Eduard Oró, Paolo Taddeo, Jaume Salom〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The heating and cooling sector in Europe aims to increase the share of thermal energy provided by district heating (DH) and cooling networks, from the current 13% to 50% by 2050. To reach this ambitious goal, it is needed to create the scientific evidence required to support the decarbonisation of the sector in Europe by combining energy efficiency and local waste heat. A vast amount of waste heat is produced in urban areas from a range of local sources such as data centres. These unique infrastructures are a rapidly growing industry generating heat that could potentially be recovered for heating applications, and in particular for DH networks. This manuscript evaluates numerically the energy and economic feasibility of the implementation of heat reuse solutions in air-cooled data centres to increase the energy efficiency of DH networks. Even though the primary energy reused in such installations can be above 50%, the economic analysis performed for a specific 1000 kW data centre located in Barcelona (Spain) demonstrates the non-viability of heat recovery integration in most of the conventional air-cooled data centres. However, for some cooling configurations, in particular in rear door cooling technology, the results prove the economic viability of heat reuse options.〈/p〉〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 67〈/p〉 〈p〉Author(s): Na Chen, Greg Lindsey, Chih-Hao Wang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Transportation, parks, and health organizations are collaborating to develop multiuse trail networks that meet the needs of metropolitan residents for utilitarian travel, recreation, and fitness. This paper describes how trails are used and explores correlates of trail use in the Greater Cincinnati region. Drawing on a systematic survey of users, we use ordinary probit and spatial models to explore the effects of socio-demographics, trip characteristics, attitudes, and the built environment, on recreational and utilitarian use. Most (89%) respondents report using trails for recreation; just 8.8% say they use trails for utilitarian purposes. Ordinary probit models show that users reporting recreational use are significantly more likely to be female, have incomes greater than $120,000, and travel longer distances on trails, but less likely to bike or walk to access trails. Transit connectivity is negatively correlated with recreational use. Trail users reporting utilitarian purposes are disproportionately male, significantly less likely to have incomes greater than $120,000, and more likely to take short trips on trails and to access trails by cycling or walking. They say they would commute more by cycling if connectivity were improved. Spatial probit model indicates negative spatial relationships among recreational users, implying the absence of a spatially-based common culture of trail use. Trail planners in this region can use these findings to strengthen the planning and design of trail networks and to meet the needs of different users. Given the finding most trail use is for recreational purposes, additional studies of the needs of utilitarian users are warranted.〈/p〉〈/div〉 〈/div〉