ALBERT

Description: 〈p〉Publication date: Available online 25 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society〈/p〉 〈p〉Author(s): Ghasan Alfalah, Tarek Zayed〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Sustainable facility management (SFM) has a positive effect on the three main pillars of sustainable buildings: economic, environmental, and social benefits, thereby adding value to companies, organizations, and governments that integrate SFM into their vision. This paper presents a review of SFM publications, developing a framework for identifying areas of concern regarding SFM systems, as well as identifying and studying research gaps and limitations in the existing body of knowledge. Abstracts from 232 peer-reviewed journal publications from 2007 to 2016 were analyzed according to research discipline, topic studied, and methods used. This analysis suggests that the body of academic knowledge about SFM has reached a certain maturity, and that various research disciplines have contributed to the field from different viewpoints using diverse methods, demonstrating that the SFM research field is an interdisciplinary field. This review demonstrates that the number of SFM publications has decreased over time starting from 2012 until 2016, compared with the highest number of published papers (36) in 2011. This indicates that academic interest in SFM is now driven more by an interest in empirical phenomena rather than SFM as a new research discipline.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 24 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society〈/p〉 〈p〉Author(s): Liang Yi, Xiaofei Wang, Yang Yang, Yixiao Wang, Yang Zhou〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In the previous study, the estimation of gas temperature and velocity in the naturally-ventilated inclined tunnels with vehicle blockage has been well concerned (Y. Zhou et al., Sustain. Cities Soc. 45, 2019, 258-270). In this paper, we continue to pay attention to the prediction of internal gas temperature and velocity under natural smoke extraction in both single-slope and gable-slope tunnel fires, a more hazardous scenario. A series of simplified mathematical models based on the equations of continuity, energy and pressure balance was proposed to estimate the gas temperature and velocity in sloping tunnel fires, in which the influences of fire source location, tunnel slope and tunnel geometry were taken into account. In addition, corresponding numerical simulations based on full-size tilted urban tunnel fires were performed using Computational Fluid Dynamics (CFD) method. The results show that the variation trends between the CFD and analytical results are the same, and the iterative values of gas temperature and velocity coincide well with the simulations. A fast and convenient method for estimation of the gas temperature and velocity in sloping tunnel fires has been proposed, and the results of this work can provide a reference for the optimal design and management of natural smoke extraction systems, and help to ensure the fire safety of single-slope and gable-slope city tunnels.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 23 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society〈/p〉 〈p〉Author(s): Sara Haghifam, Mojtaba Dadashi, Kazem Zare, Heresh Seyedi〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉With utilizing the advanced automation services and communication technologies, distribution systems have been transferred from passive to smart networks. In this regard, owing to widespread and complicated interactions between varied entities, distribution system operators (DSOs) encounter various challenges in terms of energy management. Hence, in this paper, a novel Multi Follower Bi-Level framework is presented for operational scheduling of smart distribution networks (SDNs) in the presence of two players, the Demand Response Aggregator (DRA) and Microgrid Owner (MGO). In the proposed method, the upper-level problem minimizes the DSO's operating costs, while, the lower-levels maximize the MGO and DRA's profits from exchanging power. In this procedure, a non-profit agent, the Distribution-Independent System Operator is introduced to coordinate operational conflicts and interests of the network. The considered model is a non-linear Bi-Level problem which is converted into a linear Single-Level problem through KKT conditions and the Big-M method. The presented scheme is implemented on two modified SDNs. The results demonstrate that the Bi-level technique is appropriate for each entity to promote its benefit without any negative influence on the other players. Finally, to evaluate effectiveness of the proposed model, sensitivity analysis is conducted by transferring the DRA's interest to the upper-level.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 22 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society〈/p〉 〈p〉Author(s): Xilin Zhou, Tsubasa Okaze, Chao Ren, Meng Cai, Yasuyuki Ishida, Hironori Watanabe, Akashi Mochida〈/p〉 〈h5〉ABSTRACT〈/h5〉 〈div〉〈p〉The Local Climate Zone (LCZ) scheme is an urban form and land cover/land use classification system used to study urban heat islands (UHIs). Many studies have evaluated the relationship between LCZs and air temperature. While the intensity and spatial pattern of an UHI can be influenced by the land-sea breeze, especially in coastal cities, few studies have been done to examine this using the LCZ scheme. In this study, Sendai, Japan, has been selected as a case study to evaluate whether the LCZ scheme can be used to study UHIs that are exposed to sea-land breeze since it has two urban-rural areas: mountain side and coastal side. UHI analysis was based on LCZ classes with GIS-derived geometric and land cover properties. By dividing Sendai into two regions along its urban center, the mitigating effects of sea-land breeze on the magnitudes of UHIs in each urban-rural area were demonstrated. Based on the results of this study, two specific UHI mitigation strategies were proposed for Sendai. This study confirmed that the LCZ scheme can be used by urban planners to assess both surface UHI (SUHI) and UHI effects, and proposed a feasible process for developing targeted UHI mitigation strategies.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 22 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society〈/p〉 〈p〉Author(s): Marc Gimenez-Maranges, Viviana Pappalardo, Daniele La Rosa, Jürgen Breuste, Angela Hof〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Sustainable Drainage Systems (SuDS) are solutions which use natural processes to manage storm-water. Having detected the inability of conventional storm-water management to cope alone with e.g. urban flooding, the incorporation of SuDS in action plans can enable a shift towards a more sustainable handling of storm-water. The principles underlying adaptive storm-water management can potentially be realised through the implementation of SuDS. However, the SuDS concept remains undeveloped and poorly researched in Mediterranean countries. This paper explores the extent to which SuDS have been used to manage floods in Italy and Southern France. Examples of SuDS are identified through a review of grey literature and then analysed by a set of socio-technical criteria that evaluate the adoption of the principles of adaptive storm-water management. Findings show an ongoing transition towards an adaptive approach, although mature adaptive storm-water management has been neither supported in policy nor realised in practice. SuDS are fostered in both countries but while a recent increase in their adoption can be observed in Southern France, their implementation is more limited in Italy. However, a conservative and technically focused policy and implementation process has been promoted. Governance practices have, for instance, undergone almost no change.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 55〈/p〉 〈p〉Author(s): Zakaria Yahia, Anup Pradhan〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper addresses the load scheduling problem in residential sector while considering preferences of consumers and reduction of peak load. This study proposes an optimization model using multi-objective mixed integer linear programming considering a time-of-use (ToU) electricity tariff. Furthermore, this study considers the coordinated peak load reduction in a multiple-household environment. The proposed model aims to minimize three objectives: the electricity cost, the scheduling inconvenience and the peak load. Considering three objectives could enable consumers and utility companies to control their priority in minimizing one over the others. Three multi-objective optimization approaches are applied to solve the proposed model: normalized weighted-sum approach, preemptive optimization and compromise optimization. Numerical experiments show that the proposed solutions lead to significant savings in electricity costs, eliminate consumer inconvenience, while reducing the system peak loading. Furthermore, the results show outstanding performance when compared against three schedules from the literature and the consumer’s preferred schedule. Moreover, the coordinated schedules for the multiple-household problem lead to a significant reduction and levelling of the aggregated peak load.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 55〈/p〉 〈p〉Author(s): Loiy Al-Ghussain, Remember Samu, Onur Taylan, Murat Fahrioglu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The hybridization of renewable energy systems (RES) and further integrating them with Energy Storage Systems (ESS) can help improve the RESs’ reliability and reduce the mismatch between energy consumption and generation profiles. The main aim of this study is to suggest a sizing methodology for the RES components with various ESS scenarios in a microgrid through techno-economic feasibility analysis. Although the suggested methodology is flexible to include several RESs and ESSs, the methodology is demonstrated to compare the techno-economic performance of Wind and Photovoltaic (PV) energy systems under four different ESS scenarios; (i) no ESS, (ii) Pumped Hydro Storage (PHS), (iii) Hydrogen Fuel Cell (HFC), and (iv) hybrid ESS (PHS/HFC). The optimal RES configuration is determined by maximizing the RES fraction while equating the Cost of Electricity (COE) to the national utility tariff. However, in the event that there is no feasible system configuration that satisfies the mentioned criteria, the main objective becomes maximizing the RES fraction at the lowest attainable COE. This study outlines that the incorporation of PHS and HFC with the PV/Wind hybrid system increased the demand-supply fraction from 46.5%–89.4% and the RES fraction from 62.6%–91.8% with COE equals to 0.175 USD/kWh.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 21 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society〈/p〉 〈p〉Author(s): Salsabeel Shapsough, Mohannad Takrouri, Rached Dhaouadi, Imran Zualkernan〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉One of the most significant visions to come out of the Internet of Things revolution is Smart Cities. Equipped with sensing and communication technologies and powered by renewable energy, Smart Cities could be the key to protecting environmental resources and ensuring sustainable urbanization as the world population continues to grow. Solar energy is one of the most promising renewable energy sources. However, solar energy is a function of its environment, and sudden changes in meteorological conditions can cause intermittency and disrupt power generation. Furthermore, solar facilities in smart cities are distributed over rooftop installations and parking lots to make use of available space, which represents a challenge to maintenance. This paper presents the design of a solar monitoring system for large-scale and distributed facilities in smart cities. The system uses IoT technologies to remotely assess the performance of individual modules or strings in remote facilities. A prototype was implemented and used to study PV module soiling loss in a harsh desert environment. The prototype was able to successfully and reliably collect data and communicate it to a cloud-based server for researchers to view and analyze. The data is used to enable optimized and preventative maintenance in city-wide solar facilities.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 21 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society〈/p〉 〈p〉Author(s): Zahra Jandaghian, Umberto Berardi〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The modelling of the urban heat island (UHI) phenomenon is becoming critical to allow better prediction and assessment of mitigation strategies. This paper compares different urban canopy models to characterize the UHI in Toronto. In particular, the effects of urban parameterization modeling are investigated using the state-of-the-art Weather Research and Forecasting Model (WRF). The WRF is coupled separately with three Urban Canopy Models (UCMs) to predict the heat and moisture fluxes from the canopies to the atmosphere. The three UCMs are a slab (SB), single-layer (SL), and multi-layer (ML) representation of the canopy. The SB, SL, and ML respectively consider buildings as increased roughness elements, a single orientation of the two-dimensional approximation, and the three-dimensional urban surfaces that also accounts for the vertical exchange of heat, moisture, and momentum. The WRF-UCMs are used to investigate a specific heat wave period. The simulations are evaluated comparing the results of the air temperature, wind speed, relative humidity, and dew point temperature with the measurements from several weather stations. The correlation (r-squared) of the air temperature and dew point temperature was close to 0.9 and 0.85, whereas the correlation of the wind speed and relative humidity was 0.6 and 0.7 respectively. The UHI magnitude is also estimated by the air temperature changes between urban and rural areas. The results illustrate that the daily heat island magnitude is around 1.2 to 1.5 °C, while the daytime is near 0.7 °C. The UHI is magnified during the nighttime and is up to 2 °C. The analysis indicated that the SL is reliable for climate simulations, but for the evaluation of the UHI magnitude and to analyze more sophisticated structures, the ML urban canopy model has to be applied as it is critical to account for the air turbulences and multi-reflections in the urban canopy.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 21 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society〈/p〉 〈p〉Author(s): Ahmad Almuhtady, Marwa Alfaouri〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Heating has been always considered a necessity for humans. Nonetheless, it has always imposed a sustainability challenge, both economically and environmentally. This paper proposes a solution for sustainable residential heating in regions experiencing moderate Winters. The solution integrates the effects of intelligent design and operation. It encompasses minimization of thermal inadequacy, renewable energy incorporation, and optimal policy for the heating controls. Through a case study for an apartment in Jordan, the merits of the proposed solution are highlighted in terms of performance, feasibility, and environmental-friendliness using a detailed physical model. It was found out that thermal inadequacy could double both electricity consumption and generated CO〈sub〉2〈/sub〉. Additionally, despite having global warming potential for their working fluids, utilization of heat pumps instead of electric heaters can reduce CO〈sub〉2〈/sub〉 emissions by 75% with a payback period as short as 15 heating months. Finally, various heating schemes are examined. A proposed policy which represents a hybrid control technique merging threshold controller with demand-based zone heating was found to be capable of handling the trinary trade off resulting from thermal comfort, cost reduction, and minimum number of heating system starts. An optimal set of lower and upper bounds for active and inactive periods were found.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 55〈/p〉 〈p〉Author(s): Zahoor Ahmed, Muhammad Wasif Zafar, Sajid Ali, Danish〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The G7 countries are facing the challenges of high urbanization, growing ecological footprint, and decreasing biocapacity. In these countries, urban areas are the center of economic activities and resource consumption. On this note, current study examines the effect of urbanization and human capital on the ecological footprint in G7 countries. The study uses advanced panel data estimators, such as CUP-FM and CUP-BC on data from 1971 to 2014. The findings reveal that urbanization increases the ecological footprint, whereas human capital reduces it. The reliability of long-run estimates is also examined by using CO〈sub〉2〈/sub〉 emissions as a proxy of environmental impact. The results of causality test disclose unidirectional causality from human capital and urbanization to the ecological footprint. However, the causality between urbanization, human capital, and economic growth is bidirectional. Moreover, energy consumption, economic growth, and import increase environmental degradation, while export and foreign direct investment reduce environmental degradation. Finally, detailed policy options are proposed to combat environmental challenges of G7 countries.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 55〈/p〉 〈p〉Author(s): M. Talaat, Abdulaziz S. Alsayyari, Adel Alblawi, A.Y. Hatata〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this research, a complete vision of using the technology of the smart grid system with a new communication, information technology techniques and devices has been investigated. In addition, a strategy of using a hybrid or private cloud for security, sorting and data storage that is obtained from the power grid has been suggested. The proposed strategy suggested that; construct a wireless sensor network with high reliability and performance for monitoring the various important measurement parameters in the power system grid. All data coming from a large and complicated wireless sensor network spread along the power system can be sorted and classified in the cloud using data processing hardware with high performance and good accuracy. Therefore, an automated decision making in the case of the system outage or fault current condition can be programmed depending on the sorting and analysis of the received data. This will develop the power system design using smart grid architecture to enhance the performance for verifying the various demand applications in power systems (faults, security, monitoring, and control), integrate with available renewable energy sources (wind or solar or biomass or wave energy) and enhance the storage capability and reliability in power system grid to deal with the suddenly change in the power system flow.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 24 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society〈/p〉 〈p〉Author(s): Dachuan Shi, Jiyun Song, Jinxin Huang, Chaoqun Zhuang, Rui Guo, Yafeng Gao〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Both green and blue space are found to be effective for urban heat mitigation and air quality improvement. However, studies on the Synergistic Cooling Effects (SCEs) of green-blue spaces are limited. This paper aims to investigate the SCEs of green-blue spaces in Chongqing, a typical hot humid city in China, through the field measurement and numerical simulation. First, air temperature and relative humidity over different land-use sites (forest, lawn, and impervious pavement) were measured with and without water simultaneously, from July to August, 2018. Experimental results revealed the SCEs of green-blue spaces were obvious in 7–12 m surrounding waterfront areas, where the mean air temperature reduction was 3.3 °C higher than the sums of cooling effect of standalone water and forest. Additionally, an ENVI-met model was validated against the measured data before conducting simulation for the study area in five scenarios, including one control group with no trees and four greening cases with different Leaf Area Index (LAI) values to investigate the importance of green infrastructure on the waterfront thermal environment. Simulation results showed that a decrease of 1.0 LAI can lead to a reduction of average air temperature by 0.19–0.31 °C, possibly owing to the enhanced ventilation flow.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 25 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society〈/p〉 〈p〉Author(s): Edna J. Molina Bacca, Andy Knight, Milana Trifkovic〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In the smart grid environment, optimal placement and sizing of microgrids have attracted a great deal of attention. Here, we propose a multi-scale optimization model for determining microgrid configuration, capacity, and geographical location, and we apply it to a municipality in Southwestern Ontario. The proposed approach accounts for the net present value of the project, power balance of the grid, maximum capacity of the current substations, and the geographic availability for the installation of a microgrid. The problem is tackled in two stages. First, a geographic information system/multicriteria decision analysis (GIS/MCDA) is performed to determine the suitable locations for the installation of distributed energy resources (DERs). Then, a mixed integer optimization model is used to determine the capacities and final installation locations of the DERs based on the results obtained in the GIS/MCDA. Finally, three different scenarios are evaluated to elucidate the influence that retail price, microgrids’ minimum contribution to the demand, and available land have over the final architecture, cost, and allocation of a renewable energy project.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 24 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society〈/p〉 〈p〉Author(s): Lei Zhang, Guochen Sang, Weixiao Han〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This study describes the experimental testing of the hygrothermal properties of the earth brick and the numerical analysis of the hygrothermal behaviour of a residential building in a desert climate in order to evaluate the effect of the earth brick on the indoor environment. The hygrothermal properties, i.e. thermal conductivity, specific heat capacity, equilibrium moisture content and water vapour permeability, were characterized to be used in the following numerical simulation of indoor environment. The numerical analysis was conducted by whole building simulations using EnergyPlus which can be used to simulate the indoor climate in buildings. An existing residential building was monitored for two days in summer in order to validate the accuracy of the model. The simulated results showed that compared with the fired brick, the earth walls reduce the amplitude of both indoor air temperature and relative humidity fluctuations, especially the maximum of relative humidity, due to both thermal inertia and moisture capacity of the earth bricks. Besides, the heating energy consumption results of the earth brick rooms were significantly lower than the fired brick rooms during the heating period.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 24 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society〈/p〉 〈p〉Author(s): Tengfei Huo, Xiaohui Li, Weiguang Cai, Jian Zuo, Fuyuan Jia, Haifeng Wei〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Urbanization is a key driving force for building carbon emissions. However, few studies have explored the relationship between urbanization and urban building carbon emissions. This study comprehensively analyzes the impact of urbanization on urban building carbon emissions from both quantity and structure dimensions based on the STIRPAT model, using the panel data of China’s 30 provinces from 2001 to 2015. Urbanization is measured from the three perspectives: population, economy and space. Results show that the urban population, the added value of tertiary industry and the urban building area contributes positively to the urban building carbon emissions from the quantity dimension, of which the added value of tertiary industry is the main driver. From the structure dimension, the urban population ratio and the proportion of tertiary industry on gross domestic product (GDP) are the driving factors of urban building carbon emissions, but the plot ratio of urban buildings contributes negatively during the study period. This study can help better understand the driving factors of growing urban building carbon emissions under the background of China’s rapid urbanization, and will provide valuable reference for governments’ efforts to set building energy efficiency and carbon emissions mitigation policy.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 24 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society〈/p〉 〈p〉Author(s): Seunghwan Wi, Seong Jin Chang, Sumin Kim〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The use of phase change material as an efficient way to use building energy has recently been discovered as this material occupies 40% of the total carbon emissions through energy used in the building sector. In order to apply phase change materials to buildings, phase stabilization must first be achieved; some researchers have developed shape-stabilized phase change material (SSPCM). In this study, the enthalpy-temperature function based on the thermal properties of 22 types of SSPCMs were analyzed and applied to a dynamic energy simulation program. The SSPCM was applied to improve the low heat storage performance of wooden buildings along with building energy savings. The SSPCM was applied to the inner side of a 20-mm-thick external wall in a case study concerning the inside and outside of an external wall. An analysis of the annual energy consumption of buildings showed that applying SSPCM resulted in average savings of 5%. To confirm the improvement in the heat storage performance of buildings, the indoor temperature behavior during the heating and cooling periods was analyzed. Maintaining the thermal inertia of SSPCM was found to have reduced the peak temperature in summer by 4.1 °C.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 25 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society〈/p〉 〈p〉Author(s): Fernando Lezama, Joao Soares, Bruno Canizes, Zita Vale〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Several initiates have been taken promoting clean energy and the use of local flexibility towards a more sustainable and green economy. From a residential point of view, flexibility can be provided to operators using home-appliances with the ability to modify their consumption profiles. These actions are part of demand response programs and can be utilized to avoid problems, such as balancing/congestion, in distribution networks. In this paper, we propose a model for aggregators flexibility provision in distribution networks. The model takes advantage of load flexibility resources allowing the re-schedule of shifting/real-time home-appliances to provision a request from a distribution system operator (DSO) or a balance responsible party (BRP). Due to the complex nature of the problem, evolutionary computation is evoked and different algorithms are implemented for solving the formulation efficiently. A case study considering 20 residential houses equipped each with seven types of home-appliances is used to test and compare the performance of evolutionary algorithms solving the proposed model. Results show that the aggregator can fulfill a flexibility request from the DSO/BRP by re-scheduling the home-appliances loads for the next 24-hours horizon while minimizing the costs associated with the remuneration given to end-users.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 24 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society〈/p〉 〈p〉Author(s): Jinhan Mo, Enze Tian, Jin Pan〈/p〉 〈h5〉ABSTRACT〈/h5〉 〈div〉〈p〉Influx of ambient particulate matter (PM) to the indoor environment has threatened human health due to its adverse impacts on respiratory, cardiovascular, and neurological systems. Consequently, PM removal devices with high efficiency and low cost like electrostatic precipitator (ESP) are essential for a healthy and sustainable indoor environment. Traditional two-staged ESP includes particle charging and collection part. In this study, we innovated the collection part by coating the repelling electrodes with dielectric films. Four performance influencing parameters were examined: the voltage difference (〈em〉V〈sub〉c〈/sub〉〈/em〉) and distance (〈em〉d〈sub〉c〈/sub〉〈/em〉) between the repelling and collecting electrodes, and both the dielectric material and thickness (〈em〉d〈sub〉e〈/sub〉〈/em〉). The new ESP achieved its best performance when coated with PET (〈em〉d〈sub〉e〈/sub〉〈/em〉 =60 µm) at 〈em〉d〈sub〉c〈/sub〉〈/em〉 =3 mm. The breakdown voltage was promoted from −4 kV (without dielectric film) to −9 kV, and PM removal efficiency was enhanced from 60% to 92%. The new ESP had low net ozone production (3 - 5 ppb), low pressure drop (10 - 13 Pa), and low energy consumption (18 W/m〈sup〉2〈/sup〉), making it an eco-friendly device. Running continuously for one week, the new ESP maintained a single-pass PM removal efficiency of around 90%, notwithstanding changes in ambient air temperature and relative humidity.〈/p〉〈/div〉 〈h5〉Graphic Abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S2210670720300500-ga1.jpg" width="301" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 55〈/p〉 〈p〉Author(s): Wenru Cheng, Yifei Zhang, Peng Wang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Biomass is disadvantageous as it has low energy density and poor fluidity. High transportation costs lead to bottlenecks in the development of biomass. This paper aims to find a spatial distribution model of biomass collection points to effectively control the transportation cost of raw materials. Considering a variety of influencing factors to assess the potential of forestry, agricultural biomass, and domestic waste; and to establish transport cost models with the help of ArcGIS software, the most economical location of biomass thermal power plant is determined and the shortest path and transportation cost from resource point to biomass thermal power plant are obtained. The analysis results show that the transportation cost for a single vehicle has a positive linear relationship with the transportation distance. The transportation cost rapidly increases when the transportation distance reaches 90 km. The total transportation cost and transportation distance within the distance range are positively correlated and follow an S curve. Setting a transportation distance of 22 km as the threshold for the first level raw material collection locations and 63 km as the second level for raw material collection locations. effectively lowered the transportation costs for biomass.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 55〈/p〉 〈p〉Author(s): Yang Lv, Yuwei Zhou, Xi Chen, TongKe Zhao, Tao Liu, Xin He, Jing Liu, Xiao Ye〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉To control severe air pollution and promote cities sustainable development in an old industrial base of severe cold region in China, it obtained indoor and outdoor PM〈sub〉2.5〈/sub〉 permeability coefficients, also bacterial community and source by 16s rDNA gene sequencing technique and BLAST (〈em〉The Basic Local Alignment Search Tool〈/em〉) source apportionment through long-term monitoring of residences in two typical cities of Heilongjiang Province (Harbin and Mudanjiang) in Northeast China during heating and non-heating season. The results showed that the average permeability coefficient of indoor and outdoor fine particles in Harbin is similar to that in Mudanjiang during non-heating season (Harbin: 0.7131, Mudanjiang: 0.7312) mainly due to natural ventilation. In heating season, Harbin (0.5325) was lower than that in Mudanjiang (0.6918) due to the differences in industrial characteristics and building tightness. The dominant bacteria on indoor and outdoor fine particles was Proteobacteria for two cities, accounted for more than 95 % in non-heating season, while for heating season were Proteobacteria, Firmicutes and Bacteroidetes, which were proportional different due to the different average permeability coefficients, intensities of ultraviolet rays and temperature. And no matter which city in different season, their source proportions of indoor human and outdoor soil are larger than others.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 55〈/p〉 〈p〉Author(s): Tanveer Ahmad, Hongcai Zhang, Biao Yan〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The benefits of renewable energy are that it is sustainable and is low in environmental pollution. Growing load requirement, global warming, and energy crisis need energy-intensive management to give sincere attempts to promote high accuracy energy monitoring techniques in order to enhance energy system efficiency and performance. The energy consumption data of domestic, commercial and industrial are becoming accessible to estimate the notable share of various sectors in the energy market. Energy forecasting algorithms play a vital role in energy sector development and policy formulation. Energy prediction and power supply management are the key roots of energy planning. A large number of prediction models have been used in the recent past. The selection of a prediction model usually based on available data, the objectives of the model network mechanism and energy planning operation. In this review, we conduct a critical and systematic review of renewable energy and electricity prediction models applied as an energy planning tool. The forecasting intervals is divided into three sections including: i) short-term; ii) medium-term; iii) and long-term. Three renewable energy resources, i.e. wind, solar, and geothermal energy, and electricity load demand requirement are considered for review forecasting analysis. Three major states-of-art forecasting classifications: i) machine learning algorithms; ii) ensemble-based approaches; iii) and artificial neural networks are analyzed. These approaches are investigated for prediction applicability; accuracy for spatial and temporal forecasting; and relevance to policy and planning objectives. The machine learning models can handle large amount of data with accurate forecasting analysis. Applying ensemble techniques enables us to obtain higher forecasting accuracy by combining different models. Artificial neural networks if used in the right way can contribute a robust choice, given that it is capible to extract and model unseen relationships and features. Furthermore, unlike these conventional techniques, artificial neural networks do not force any limitation on residual and input distributions. Findings from this review would help professionals and researchers in obtaining recognition of the prediction approaches and allow them to choose the relevant methods to satisfy their desired tasks and forecasting requirements.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 55〈/p〉 〈p〉Author(s): Chunping Miao, Shuai Yu, Yuanman Hu, Rencang Bu, Li Qi, Xingyuan He, Wei Chen〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Exposure to near-ground air pollution in urban street canyons poses a serious threat to pedestrian health. To develop design guidelines for air quality improvement, correlations among PM〈sub〉1〈/sub〉, PM〈sub〉2.5〈/sub〉, PM〈sub〉4〈/sub〉, PM〈sub〉10〈/sub〉, TSP, street canyons morphology and climatic conditions were investigated by field experimental studies. The results showed that street canyons morphology and air humidity were two of the most important factors affecting suspended particulate matter concentration in urban street canyons. The concentrations of PM〈sub〉1〈/sub〉 (9.18 ± 0.17 μg/m〈sup〉3〈/sup〉), PM〈sub〉2.5〈/sub〉 (18.12 ± 0.43 μg/m〈sup〉3〈/sup〉), PM〈sub〉4〈/sub〉 (31.66 ± 0.82 μg/m〈sup〉3〈/sup〉), PM〈sub〉10〈/sub〉 (77.57 ± 2.04 μg/m〈sup〉3〈/sup〉) and TSP (104.06 ± 2.85 μg/m〈sup〉3〈/sup〉) in deep canyons were significantly lower than those in medium and wide canyons. The pollutants distributed in E-W or N-S street directions were at a lower concentration compared with those in NE-SW or NW-SE street directions. Moreover, the pollutants showed significantly lower concentration in high-rise building areas than in multilayer building areas. This study provides a reference for future urban planning to reduce suspended particulate matter concentration in street environments.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 55〈/p〉 〈p〉Author(s): Ke Wang, Zhenyu Li, Jianjun Zhang, Xia Wu, Mei Jia, Liu Wu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The optimization of green infrastructure networks (GINs) is an essential part of sustainable urban development, and the expansion of built-up land has to be treated as an important disturbing force of urban GINs. This paper employs morphological spatial pattern analysis (MSPA) to extract the GINs in Wu’an (a resource-dependent city in China), and five factors of production and a three-dimensional digital model are involved in predicting the possibility of built-up land expansion. The entire city is then divided into different eco-sensitive areas, and ecological protected areas with different GIN optimization objects are determined. The main findings indicate that the stability of GINs in Wu’an is reduced. From 1987–2016, the number of large ecological cores increased by 5, but the total area of the large ecological cores decreased by 359.81 km〈sup〉2〈/sup〉, and the number and area of small ecological cores increased by 5 and 26.16 km〈sup〉2〈/sup〉, respectively. The expansion of built-up land leads to disconnection of the GINs, and the possibility of built-up land expansion gradually decreases from the downtown and satellite towns to their surrounding areas. The main contribution of this paper is to provide a new way to optimize the GINs from the perspective of built-up land expansion.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 55〈/p〉 〈p〉Author(s): Bao-Jie He, Lan Ding, Deo Prasad〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The reduction of urban ventilation is one of the significant causes of the urban heat island (UHI) phenomenon. Reasonable urban planning and design can guide cooler wind into cities, thereby mitigating UHI phenomenon. However, existing knowledge of the cooling effect of urban ventilation is mainly at the regional or city scale, while the lack of information on ‘realistic’ precinct ventilation limits the use of wind for UHI mitigation. Therefore, this study aims to understand the precinct ventilation and its associated influences on UHI effects and outdoor thermal comfort. In specific, a case study analysis was performed in summer in a precinct of the coastal Sydney, Australia. Results indicate that in the open low-rise gridiron precinct, the precinct ventilation performance (PVP), precinct outdoor thermal environment (POTE) and precinct outdoor thermal comfort (POTC) significantly varied with the combination of external meteorological conditions and precinct morphological characteristics, while the street orientation made insignificant influence to PVP, POTE and POTC. The PVP exhibited its significant potentials for UHII reduction and POTC improvement. The PVP forced by the sea breeze could further enhance relative humidity for UHII reduction and POTC improvement. Overall, this study presents the understanding of PVP and the associated influence on POTE and POTC under realistic and complicated precinct context. It can further facilitate wind-sensitive urban planning and design for local warming mitigation.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 55〈/p〉 〈p〉Author(s): Yizhou Wu, Tiancheng Zhang, Huan Zhang, Tao Pan, Xueling Ni, Adam Grydehøj, Jianming Zhang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Many island cities have vulnerable ecosystems, yet island ecosystems also present special challenges for research. Ecological footprint analysis is an effective method of evaluating the ability of island cities to engage in regional ecological sustainable development. This study uses ecological footprint analysis combined with the ArcGIS platform to evaluate the ecological security of 14 neighborhoods on Zhoushan Island (Zhejiang Province, China) in 2010, 2013, and 2015. The partial least squares regression model is used to explore factors affecting spatial and temporal differences in ecological security in the island’s neighborhoods and to help optimize the island’s ecological sustainable development. Results reveal that Zhoushan Island’s per capita ecological footprint decreased from 7.355 hm2 in 2010 to 4.662 hm2 in 2015, yet throughout the study period, the per capita ecological footprint remained higher than the per capita ecological carrying capacity in all neighborhoods. Although the island’s ecological security has gradually improved, there continue to be large ecological deficits and ecological pressure. To improve the island city’s ecological security, we should optimize the mode of urban development, develop renewable energy sources, protect ecologically valuable land, improve the scale and quality of urban zones and transportation infrastructure, and improve residents’ industrial and consumption structures.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 55〈/p〉 〈p〉Author(s): Julian Laufs, Hervé Borrion, Ben Bradford〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The implementation of smart technology in cities is often hailed as the solution to many urban challenges such as transportation, waste management, and environmental protection. Issues of security and crime prevention, however, are in many cases neglected. Moreover, when researchers do introduce new smart security technologies, they rarely discuss their implementation or question how new smart city security might affect traditional policing and urban planning processes. This systematic review explores the recent literature concerned with new ‘smart city’ security technologies and aims to investigate to what extent these new interventions correspond with traditional functions of security interventions. Through an extensive literature search we compiled a list of security interventions for smart cities and suggest several changes to the conceptual status quo in the field. Ultimately, we propose three clear categories to categorise security interventions in smart cities: Those interventions that use new sensors but traditional actuators, those that seek to make old systems smart, and those that introduce entirely new functions. These themes are then discussed in detail and the importance of each group of interventions for the overall field of urban security and governance is assessed.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 55〈/p〉 〈p〉Author(s): Veli Yilanci, Seref Bozoklu, Muhammed Sehid Gorus〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The goal of this paper to determine whether the effect of foreign direct investment inflows on the environment is pollutive or pollution-reducing for BRICS countries―Brazil, Russia, India, China, and South Africa―using annual data for the period 1982–2014. For that purpose, this study examines the long-run impact of FDI inflow and energy use on ecological footprint and its components―crop land, grazing land, forest land, fishing ground, built-up land, and carbon footprint―by introducing and utilizing the bootstrap autoregressive distributed lag model with a Fourier function (FARDL) for cointegration. The findings demonstrate that although the effect of FDI inflows on the footprints is mixed in Brazil and Russia, it is positive on environmental degradation regarding ecological footprint and carbon footprint in India. Furthermore, it is found that FDI inflows increase environmental quality in China for cropland and grazing land footprints and in South Africa for crop land, grazing land, fishing ground, and built-up footprints. Furthermore, the long-run effect of energy consumption is mostly pollutive for BRICS countries.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 14 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society〈/p〉 〈p〉Author(s): John Mulrow, Sybil Derrible〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Given the major role that transportation plays in the urgent issue of climate change, as well as technological and societal changes currently underway, a comprehensive evaluation of speed’s role in achieving sustainable transportation goals is needed. This article presents a review of speed’s role in generating climate impacts. The relationships between speed and sustainable transportation factors are reviewed and quantified. Speed is then incorporated as a variable in the ASIF equation, an emissions-projection model used by the IPCC. By applying this model to a United States context, insights are drawn for how transportation speed factors into the achievement of ambitious climate, public transit, and active transportation goals. These insights are crucial for setting sustainable transportation agendas, especially in the nation’s major metropolitan areas, which have become centers of sustainability planning but also hubs of expanding transportation networks, especially via air travel. A motivating question for this study is whether future transportation activity must be slower overall, in order to meet sustainability goals. Importantly, the results do not rule out a faster transportation future but prove that there is far less solution “space” for increasing average mode-speed.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 55〈/p〉 〈p〉Author(s): Ou Han, Ying Zhang, Angui Li, Jianwei Li, Yuwei Li, Huagan Liu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Heavy gases, in particular sulfur hexafluoride (SF〈sub〉6〈/sub〉), are used extensively in the gas insulated substations (GISs) of various industrial buildings, such as nuclear power plants. Although the construction and operation of these facilities are closely monitored and regulated, accidents are possible. A hazardous situation may arise if the SF〈sub〉6〈/sub〉 gas in a GIS leaks without effective measures to remove the contaminants in time. In this study, a chamber experiment and CFD numerical simulation were carried out to study SF〈sub〉6〈/sub〉 gas dispersion characteristics and the optimal ventilation design for its accidental leakage in industrial buildings. The influence of leakage angle (〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"〉〈mrow〉〈mi〉α〈/mi〉〈mo〉=〈/mo〉〈/mrow〉〈/math〉 90°, 45° and 0°) on the SF〈sub〉6〈/sub〉 dispersion and concentration distribution was analyzed. Several different ventilation design parameters, i.e., air outlet layout, size and air change rate, were proposed to evaluate the ventilation performance. The findings indicated that different leakage angles could result in different space concentration distributions of SF〈sub〉6〈/sub〉 and that any leakage angle deviating from 90° could result in an uneven SF〈sub〉6〈/sub〉 concentration distribution; a deviation angle of 45° caused the maximum concentration variation in the lower part of the chamber. The removal of SF〈sub〉6〈/sub〉 was more effective when the air outlets and inlets were arranged on the same side of the wall. Vent openings and air outlets had a remarkable influence on the removal rate of SF〈sub〉6〈/sub〉. It was found that high-efficiency ventilation could be achieved with a 10 h〈sup〉−1〈/sup〉 air change rate, meeting the needs of SF〈sub〉6〈/sub〉 emergency ventilation. The current study can serve as a reference for ventilation design and establishment of standards for the accidental leakage of heavy gas in industrial buildings.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 55〈/p〉 〈p〉Author(s): Jinfei Hu, Guangju Zhao, Xingmin Mu, Georg Hörmann, Peng Tian, Peng Gao, Wenyi Sun〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Understanding the changes in runoff-sediment relationships is a great help for implementing soil and water conservation measures, particularly in regions with severe erosion. We selected a typical coarse sandy catchment on the Loess Plateau to investigate the changes of the runoff-sediment relationships with a data set of 62 years. A change point occurred in 1979, dividing the runoff and sediment load series into a baseline period (1954–1979) and a changing period (1980–2015). A total of 342 flood events were classified into three regimes using hierarchical clustering method. Regime A (162 events) was characterized by the shortest duration, lowest flood crest, and the least flow depth. Regime B (165 events) was characterized by a medium runoff depth, medium flow variability, and medium duration. Regime C merely include fifteen events with longest flood duration, the highest runoff depth, and the largest peak discharge. The sediment yield of flood regime A, B, and C accounted 14.2 % (1.09 × 10〈sup〉8〈/sup〉 t), 51.8 % (3.99 × 10〈sup〉8〈/sup〉 t), and 34.0 % (2.62 × 10〈sup〉8〈/sup〉 t) of the total sediment yield, respectively. The Support vector machines method was applied to established models to predict event sediment yield. It is demonstrated that the performance of models are good for different flood regimes.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 21 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society〈/p〉 〈p〉Author(s): Huang Huanchun, Yang Hailin, Deng Xin, Hao Cui, Liu Zhifeng, Liu Wei, Zeng Peng〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The effects of human activities and land cover changes on urban thermal field patterns are closely related to the land surface temperature (LST) and air temperature. At present, the number of studies on the quantitative relationship between these two indexes and the effect of the observational scale on their influence is insufficient. In this study, spatial analysis methods such as geographic modeling were combined with remote sensing images, meteorological data, and points of insert and used to investigate the composition and scale of the factors influencing the temperature field in Beijing. The results showed that there are differences in the positive and negative correlations between LST and air temperature and various influencing factors. At a spatial resolution of 90 m, LST had a strong linear relationship with the average air temperature. Indicators reflecting elements of human activity, such as buildings, roads, and entertainment, were easily measured by meteorological stations at a small scale, and the natural green space ratio could also be easily captured by satellite thermal sensors at small scales. These results have substantial implications for environmental impact assessments in areas experiencing an increasing urban heat island effect due to rapid urbanization.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 14 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society〈/p〉 〈p〉Author(s): Fakhrii Alam Khan, Muhammad Asif, Awais Ahmad, Mafawez Alharbi, Hanan Aljuaid〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Blockchain technology has gained considerable attention for different types of stakeholders due to its stable implementation in the field of digital currency like Bitcoin. Some users use Bitcoin for payment exchanges against any business while others use the Bitcoin network for earning Bitcoins itself, and there is also another type of user who called hackers those flood different types of attacks to illegally earn some Bitcoins or collapsing overall network. There are also numerous uses of blockchain technology, e.g. health, automation industry, energy sector, security and authentication in smart grids. In this study, we have elaborated on different critical aspects of Blockchain technology like its style of working mechanism, possible improvement suggestions by using Proof-of-Stake, and other custom variations, attempting seven types of challenges by different novel techniques. Moreover, we have also explained the current state-of-the-artwork in blockchain’s non-financial applications like Healthcare in which contribution of four-layered custom blockchain models related to precision medicine and the clinical trial was notable. Moreover, a mobile app model called HDG for the automation of medical records without compromising privacy was also a prominent contribution.〈/p〉〈/div〉

Description: 〈p〉Publication date: February 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 53〈/p〉 〈p〉Author(s): Daniele La Rosa, Viviana Pappalardo〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉There is a rising demand to use nature and natural processes to address a different range of urban issues, especially when looking at the risk of pluvial flood associated with climate changes and urbanization processes. Among the set of Nature-Based Solutions used in urban planning, Sustainable Urban Drainage Systems (SUDS) represent promising solutions to reduce the negative effects of urban water run-offs and to increase urban Ecosystem Services.〈/p〉 〈p〉However, SUDS can impact differently in the urban fabric and generate positive effects only on particular portions of cities. Planning of SUDS should try to consider not only the number of potential beneficiaries but also where beneficiaries are located in the city, as water sensitive approaches to urban planning must deal with distributive, procedural and contextual dimensions of equity.〈/p〉 〈p〉In this paper, we simulate different spatially explicit planning scenarios of SUDS for densely populated catchments in Sicily. Particularly, we evaluate the relation between the quantitative performance of SUDS in terms of reduction of hazard/risk of pluvial flooding and the number and location of beneficiaries -intended here as residents of different social groups. Results suggest that scenarios of SUDS generate benefits that are not equally distributed within the city.〈/p〉 〈/div〉

Description: 〈p〉Publication date: February 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 53〈/p〉 〈p〉Author(s): Baohong Jin, Xiaohong Nan, Xuhao Ning, Zanshe Wang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In the process of tea brick production, the major energy consumption lies in the air-conditioning system of the tea fermentation chamber. Under the condition of satisfying the fermentation process, the energy-saving operation of the air-conditioning system is an effective method to reduce the energy consumption and to improve the economic benefit of the tea brick. However, due to lack of quantitative calculation of the indoor heat and moisture load during the fermentation process, the air conditioning system of the tea brick fermentation chamber is mainly based on the CAS (circulating air system) or the ORCS (One return air conditioning system). Consequently, in this study, the heat and moisture transfer model of the tea brick was built based on the heat and moisture coupling transfer theory for porous media. The COMSOL Multiphysics was implemented to solve the heat and moisture exchange rate between tea bricks and the fermentation environment. Based on the rate and the heat transfer of the envelope structure, the heat and moisture load of the fermentation chamber was calculated under different meteorological parameters. According to the indoor heat and moisture load and outdoor weather parameters, the energy consumption and exergy loss of the two air conditioning systems were analyzed during the fermentation cycle. The results show that the ORCS energy efficiency is 30.8%–55.8% greater than that of the CAS, and the irreversible exergy loss is also reduced by 19.6%–57.0% when the residual heat 〈em〉Q〈/em〉 inside the fermentation chamber is less than zero. On the other hand, when the residual heat 〈em〉Q〈/em〉 is greater than zero, the CAS energy efficiency is 16.1%–22.3% greater than that of the ORCS, and the exergy loss is reduced by 37.8%–43.3%. According to the energy and exergy analyses of the two air-conditioning systems, an energy-saving operation strategies of air conditioning system for brick fermentation were determined in different tea brick production areas.〈/p〉〈/div〉

Description: 〈p〉Publication date: February 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 53〈/p〉 〈p〉Author(s): Woohyun Kim, Srinivas Katipamula, Robert Lutes〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Electricity utilities are faced with the mounting challenge of providing a stable supply of power to meet the growing demand while also integrating rapid growth in distributed variable renewable generation. Traditional means of balancing short- and long-term supply and demand imbalance will be expensive. Alternative approaches of using flexible loads in buildings are needed to mitigate the imbalance at a lower cost. This paper shows how the intelligent load control (ILC) process can be used to manage loads in buildings by dynamically prioritizing loads for curtailment using both quantitative and qualitative criteria. The ILC process can be deployed on low-cost computing platforms without the need for any additional sensing. ILC was first validated in a simulation environment to provide two grid service use cases: (1) managing monthly peak electricity demand and (2) managing buildings’ electricity consumption during a capacity bidding event. After being successfully tested in a simulation environment, ILC was deployed on real buildings to manage electricity consumption to provide two different use cases under different outdoor operating conditions. Both the simulation tests and the real building experiments were deployed using VOLTTRON™, a distributed sensing and control platform. The results from the tests and experiments showed that ILC was able to manage the controllable loads (heat pumps) in the building to maintain the electricity consumption at the desired level without a significant impact on occupant comfort. Overall, the results demonstrate that the ILC allows coordination of the controllable loads and provides a more intelligent means of load management than the traditional duty-cycling approach.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 55〈/p〉 〈p〉Author(s): Ranran Li, Ping Jiang, Hufang Yang, Chen Li〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Electricity demand/load forecasting always plays a vital role in the management and operation of power systems, since it can help develop an optimal action program for power producers, end-consumers and government entities. Inaccurate prediction may cause an additional production or waste of resources due to high operational costs. This paper investigated the benefit of combining data features to produce short-term electricity demand forecast. The nature of the electricity usually presents the complex characteristic and obvious seasonal tendency. In this paper, the advantage of adaptive Fourier decomposition is firstly used to extract the fluctuation characteristics. Then, the condition of the linear and stationary sequence is satisfied and the sub-series are performed to measure and eliminate the seasonal pattern. In the process of seasonal adjustment, the average periodicity length is identified quantitatively. In addition, to realize the generalization performance on real electricity demand data, the sine cosine optimization algorithm is applied to select the penalty and kernel parameters of support vector machine. The empirical study showed that the superior property of the proposed hybrid method profits from the effect of data pretreatment and the findings prove that this hybrid modeling scheme can yield promising prediction results within acceptable computational complexity.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 7 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society〈/p〉 〈p〉Author(s): Tingting Yao, Zelin Huang, Wei Zhao〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉As a new mode of urbanization, smart city both influences the environmental load and economic performance of cities through technology effect, resource allocation effect and industrial structure upgrade effect. So comes the natural question: has smart city construction improved the eco-efficiency of cities In China? How does the impact change over time? Is the impact heterogeneous across cities? Based on Green Solow model, this paper adopts the Super-efficiency SBM model to measure the eco-efficiency of 152 prefecture-level cities in China covering the period 2003-2016, and then DID model is applied to investigate the impact of smart city pilot policy on eco-efficiency. On the whole, the smart city construction significantly improves the eco-efficiency, and the multi-stage DID results reveal that the promotion effect is increasing over time due to the annual superposition. Furthermore, the impact is heterogeneous across cities. Although the promotion effect on medium-sized cities is less than that of large cities, the promotion effect has actually weakened when the urban population size exceeds 5 million. Moreover, the lower the level of city’s economic development, the greater the role of smart city construction in promoting eco-efficiency. The research conclusion is of great practical significance for the reform of urban governance model and the realization of high-quality urban development.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 55〈/p〉 〈p〉Author(s): Laura Romero Rodríguez, José Sánchez Ramos, Francisco José Sánchez de la Flor, Servando Álvarez Domínguez〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉The Urban Heat Island phenomenon is an increasingly important global issue. Understanding the physical characteristics of cities is critical, which is why many studies based on mobile measurements are currently being developed. However, it is highly challenging to compare them due to the various methods that are employed. Therefore, the present work aims to propose an easily replicable methodology for achieving accurate UHI assessments in potentially any city of the world. This is done by finding a representative mobile transect through experimental data, as opposed to previous studies which select routes with a variety of land covers, with the consequent risk of overlooking the truly representative areas. The main urban indicators are also estimated by using public information, including the anthropogenic heat.〈/p〉 〈p〉The methodology was tested in the historic city center of Seville (Spain). The designed mobile transect was repeatedly conducted in July 2019, recording a maximum UHI intensity of 3.1 °C at 22:00 h. A fixed temperature sensor showed that the maximum UHI intensity may be found around 06:00 h, reaching even more than 7 °C. The proposed methodology could be very useful for researchers and policy makers, allowing to direct mitigation strategies and economic investments to areas of particular vulnerability.〈/p〉 〈/div〉

Description: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 55〈/p〉 〈p〉Author(s): Sajida Perveen, Tan Yigitcanlar, Md. Kamruzzaman, Duzgun Agdas〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The urban transport sector is responsible for a considerable portion of the global greenhouse gas emissions, and considered as a primary contributor of environmental pollutants. This study aims to explore ways to compare transport impacts of alternative urban growth scenarios at different spatial and temporal scales. To achieve this aim, alternative policy scenarios and various transport impact indicators were synthesized from a Delphi survey. Four alternative urban growth scenarios (i.e., business-as-usual, environment-focused, economy-focused, balanced scenarios) for the South East Queensland Region of Australia were evaluated by comparing selected indicator values from transportation models developed for three spatial (i.e., region, city, local) and four temporal (i.e., 2016, 2021, 2031, 2041) scales. The results of the analysis disclose that policies under the balanced scenario make the highest contribution towards achieving sustainable urban development—as this scenario generates the least travel time, travel distance, and traffic congestion. The findings reveal that the empirical approach put forward in this paper is useful to inform urban policymaking, and assist urban policymakers, urban/transport planners, practitioners, and stakeholders.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 55〈/p〉 〈p〉Author(s): E. Hoxha, C. Liardet, T. Jusselme〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Generally, the environmental impacts of buildings are benchmarked per square meter as a functional unit. However, this practice prevents developing a user-centered approach in which performance is linked to real usage and not building size. Currently, the less a building is used, the lower the energy consumed during its use and, consequently, the impact per square meter, which does not make sense regarding both usability and environmental performance. Following user-centered design principles, the goal of the present research is to assess the environmental impact of buildings based on novel user-based functional units and to understand the environmental impact consequences of office occupation density. An experiment within the area of an academic office offered the opportunity to test the densification of working spaces and evaluate the resulting environmental and comfort impacts. In the end, the new user-based functional units highlight a reduction of all environmental indicators by almost 50 %. Also, the functional unit "eq-nominal people per effective presence" is introduced as most suitable to evaluate environmental performance according to real building usage, as a complement to square meter function units.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 55〈/p〉 〈p〉Author(s): Liang Zhou, Xuewei Dang, Qinke Sun, Shaohua Wang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The multi-scenario simulation of urban land can effectively reveal the characteristics and trends of changes in urban space and the contradictions of land use in urban sustainable development. By designing a model based on the random forest algorithm and CA-Markov model, we simulated the evolution of urban space in Shanghai from 2015 to 2030 under two distinct scenarios — unconstrained development and development with planning intervention. Results of model validation indicate that the model accurately simulates urban land in 2015. In Shanghai, important factors affecting urban development are population, GDP and distance to subways. Under the unconstrained scenario, urban areas in Shanghai are predicted to increase by 157.79 km〈sup〉2〈/sup〉 between 2015 and 2030, and the spatial expansion of urban areas follows a concentric pattern. Meanwhile, under the scenario with planning intervention, urban expansion is at a lower speed, and more compact because of constraints of ecological, cultivated and cultural protection, and urban areas are predicted to increase by 95.46 km〈sup〉2〈/sup〉 in 2030 compared with 2015. We observe a similar concentric pattern, although significantly smaller in magnitude, in spatial expansion under this scenario. The results show that urban development will be more sustainable under the constraints of ecological and cultivated protection.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 55〈/p〉 〈p〉Author(s): Yue Zhang, Xiaofeng Li〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Tunnel thermal environment has a great impact on the energy consumption and safety in the subway system. Due to the complexity of subway network structure and the influence of piston effect, analytical and numerical methods are limited in showing the real situation. In comparison, full-scale experiments are effective in verifying models and presenting the real situation in subway tunnels. In this study, the experimental method was adopted. The tunnel wall and air temperature were monitored in 5 subway lines in Guangzhou, China for more than 1 year. These selected tunnels have different operation conditions; namely operation year, train density, passenger number, and ventilation form. Based on long-term and multipoint monitoring, the temperature profiles were obtained. In aspect of time-varying features, it was found that the daily temperature profiles present different shapes nder different heat sources and ventilation situations. The temperature profiles in a typical year show 60 and 30–60 days delayed effect compared to outdoor temperature in winter and summer, respectively. In regard to the temperature distribution features, it was revealed that the temperature distribution within a tunnel is not sensitive to the length of tunnel but susceptible to ventilation condition; the tunnel temperature differences between two ends are 0.1-0.8℃ and 1.4-1.6℃ in high-ventilation and low-ventilation tunnels, respectively. Moreover, the possible influencing factors, including operation year, train density, passenger flow, and ventilation condition were analyzed. It was discovered that the factors related to the heat source (train density and passenger flow) have the most important impact, and the ventilation condition takes second place, while the operation years almost have no impact on the thermal environment in subway tunnels. The monitoring data are useful for both analytical and numerical studies and this study provides first-hand research data for subway operators.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 55〈/p〉 〈p〉Author(s): Jiale Chai, Pei Huang, Yongjun Sun〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉A proper system design is crucial for a net-zero energy building (NZEB) to achieve the desired performance during its lifecycle. Most conventional design methods utilize TMY (typical meteorological year) data or multi-year historical data for NZEB system sizing. Due to the climate change, future weather data may differ considerably from these utilized data. Consequently, these designs may not guarantee NZEBs to achieve the expected performance during their lifecycle. Therefore, this study proposes a differential evolution – based system design for NZEBs under climate change. Using the predicted weather data of Hong Kong (including temperature and solar radiation), the proposed system design can optimize building system sizes for minimizing its lifecycle cost with user-defined performance constraints satisfied. Three performance constraints were considered and they were thermal comfort, energy balance and grid interaction. Using the actual weather data, the proposed design has been validated by comparing with two conventional designs (i.e., TMY data-based design and multi-year historical data-based design) in an office building. The results indicated that the proposed design can achieve better performance in terms of lifecycle cost and constraints satisfaction. With improved performance, the proposed design can be used in practice for NZEB system sizing especially as climate change considered.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 14 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society〈/p〉 〈p〉Author(s): Kailiang Huang, Jingxuan Guan, Shuo Zhao, Guohui Feng, Guijun Liu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Air Type-Phase Change Energy Storage Device (AT-PCESD) has great potential in reducing building energy consumption, by storing the coldness at night and releasing it during day. This study established one-dimensional and two-dimensional mathematical models for AT-PCESD, considering pure heat conduction and heat conduction and convection, and compared the error between them and the experimental results. Each group of comparative simulations contained 4,500 pieces of data. Different integration methods for unsteady items were included in the two-dimensional pure heat conduction mathematical model solution. Thereafter, the two-dimensional model was used to analyze the effect of some controllable variables and discover its application effect in typical cold cities in China. According to the mathematical model comparison results, the error for one and two-dimensional mathematical model with natural convection is smaller than the pure heat conduction model, being 6.87%, 5.16%, 2.1%,1.32% for cool storage condition and 2.66%, 2.47%, 1.7%, 1.62% for cool discharge condition respectively. Time-integration method does not affect calculation result clearly under current conditions. The selection condition of step size in forward difference form is put forward through the error influential method. Further, in the simulated application operations, the AT-PCESD has the best effect in Beijing with an electricity saving rate of 27.34%.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 17 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society〈/p〉 〈p〉Author(s): Tianhu Zhang, Xiaopeng Li, Yandi Rao, Yuanjun Liu, Qingxin Zhao〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Indoor formaldehyde (HCHO) has become a big problem for the development of health building in cities. Ventilation and photocatalysis are two efficient tools to remove HCHO. The comparison and integration of the two methods was conducted. Pure titanium dioxide (TiO〈sub〉2〈/sub〉) and Fe/N-TiO〈sub〉2〈/sub〉 were prepared and coated to a glass plate, and experimental and computational fluid dynamics (CFD) method was used to analyze photocatalysis of HCHO. The reaction kinetic of HCHO degradation was studied by experiment, and the efficiency of Fe/N co-doped TiO〈sub〉2〈/sub〉 exhibited 2.3 times than that of pure TiO〈sub〉2〈/sub〉. Then the CFD method was used to study the removal of HCHO by ventilation and photocatalysis in an office. The evaluations were conducted with continuous and transient released HCHO, separately. In the case of continuous release, the average concentration of HCHO was reduced by 27% with the contribution of photocatalyst. In the case of transient release, the removal efficiency was improved by 21% when the photocatalyst was added. This research shows that the CFD method is a convenient tool to explore the effect of novel materials in indoor environment.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 55〈/p〉 〈p〉Author(s): Fang Shi, Xiang Peng, Zheng Liu, Eric Li, Yafei Hu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The health condition of infrastructure including water transmission and distribution mains has a great impact on the quality of human life. The performance of these water infrastructure is affected by the surrounding soil environment as well as the weather or climate changes. To investigate the structural response of water mains to varying soil movements, field data were collected with a sensor monitoring system. This included pipe wall strain in-situ soil water content, soil pressure, and temperature. Combined with weather factors, an automatic variable selection method, i.e., recursive feature elimination, was first applied to identify critical predictors contributing to pipe deformation. Then, a super learning algorithm was employed to characterize the relationship between pipe deformation and environmental factors. Both base and super learners were built to predict three types of pipe deformation which verified the adaptability of two modeling methods to different predictive models. Predictive performance was evaluated through 〈em〉R〈/em〉-squared, root-mean-square error, and mean absolute error values. The performance metrics demonstrate the advantage of the super learning algorithm in comparison with the baseline methods, especially its capability to further incorporate extra base learners and predictors in a more complex setting. This study shows that the pipe structure behavior could be successfully inferred from surrounding soil properties and weather conditions.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 16 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society〈/p〉 〈p〉Author(s): Cheng He, Liguo Zhou, Youru Yao, Weichun Ma, Patrick L. Kinney〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Various anthropogenic heat (AH) emissions that are mainly confined to urban areas have already changed the variability of urban climate. As a major human impact on our global environment, there is a lack of understanding regarding quantification, temporal, and geospatial impacts of AH over large areas. In this study, by using various remote sensing and socioeconomic data, we firstly attempt to quantify the spatial patterns of AH in the Yangtze River Delta (YRD) agglomeration of East China. After that, we organized the agglomeration area into four types (city ​​centre, developed areas, suburbs, and rural areas). We then analyse the temporal and spatial impacts on the urban thermal environment. The results show that: (1) The total amount of AH emissions in the YRD reached 8.19 × 10〈sup〉18〈/sup〉 J per year, with an uneven spatial distribution. There are profound differences in AH total and heat components for each city due to different socioeconomic backgrounds. (2) The correlation between AH distribution and the thermal environment are examined, and higher correlations are observed in the cities that generated large AH emissions. Seasonally, higher correlation exists in summer, while correlation is lower in winter. (3) The correlation between AH flux types and the thermal environment also varied for different human activity types. In the city centre, the thermal environment is related closely to AH fluxes from vehicular traffic; in developed areas there is a close relation to AH fluxes from life and tertiary industry; and in the suburbs it relates closely to AH emissions by industrial activity. Finally, we discussed the important regulatory effects of precipitation, vegetation and water bodies on AH fluxes. Overall, this study proved that the environmental impact of AH sections included herein clearly varies temporally and spatially, and suggest specific strategies for reducing the heat risk due to further urbanization.〈/p〉〈/div〉

Description: 〈p〉Publication date: March 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 54〈/p〉 〈p〉Author(s): Tong Niu, Yimin Chen, Yuan Yuan〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Conventional measurements of urban poverty mainly rely on census data or aggregated statistics. However, these data are produced with a relatively long cycle, and they hardly reflect the built environment characteristics that affect the livelihoods of the inhabitants. Open-access social media data can be used as an alternative data source for the study of poverty. They typically provide fine-grained information with a short updating cycle. Therefore, in this study, we developed a new approach to measure urban poverty using multi-source big data. We used social media data and remote sensing images to represent the social conditions and the characteristics of built environments, respectively. These data were used to produce the indicators of material, economic, and living conditions, which are closely related to poverty. They were integrated into a composite index, namely the Multi-source Data Poverty Index (MDPI), based on the random forest (RF) algorithm. A dataset of the General Deprivation Index (GDI) derived from the census data was used as a reference to facilitate the training of RF. A case study was carried out in Guangzhou, China, to evaluate the performance of the proposed MDPI for measuring the community-level urban poverty. The results showed a high consistency between the MDPI and GDI. By analyzing the MDPI results, we found a significantly positive spatial autocorrelation in the community-level poverty condition in Guangzhou. Compared with the GDI approach, the proposed MDPI could be updated more conveniently using big data to provide more timely information of urban poverty.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 8 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society〈/p〉 〈p〉Author(s): Li Yang, Xiaodong Liu, Feng Qian, Shengnan Niu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The purpose of this paper is to study the wind environment of parallel courtyard in campus which is affected by the yard aspect ratio and wind directions. Research done so far mainly focused on the thermal comfort of courtyards and wind environment at pedestrian level in urban. This article aims to study the wind environment of courtyards under aspect ratios via the high resolution RANS CFD simulation method. Two performance indicators are identified: 1) wind amplified velocity 2) age of air. The evaluation is based on the validation with field measurement. The results show that for single parallel courtyard, the best aspect ratio for air quality and ventilation locates in the range of 1 to 2. Furthermore, for double parallel combined courtyard, 0°and 15°is the most recommended approaching wind angle for ventilation. Contrarily, 75° to 90° are the worst inlet airflow direction for courtyard flow field because of insufficient abounding wind amplified area. Apart from this, only in the range of 0°to 30°, it is possible to enhance the inlet courtyard air quality in double combined yard shape compared to single courtyard.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 55〈/p〉 〈p〉Author(s): Man-Wen Tian, Shu-Rong Yan, Xiao-Xiao Tian, Milad Kazemi, Sayyad Nojavan, Kittisak Jermsittiparsert〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉A single plug-in electric vehicle (PEV) cannot participate in reserve and day-ahead markets as they cannot meet the energy requirements of independent system operators (ISO). However, they can be gathered by a PEV aggregator and play a role in so called markets. On the other hand the PEV aggregators are to deal with the uncertainties that go along with these markets and can highly affect their profit. In order to cover these uncertainties scenario-based stochastic approach can be taken into to account to optimally schedule the PEV aggregators so that the maximum profit is obtained. The main contribution of this paper is to involve risk related uncertainties through the downside risk constraints (DRC) which results in risk-constrained stochastic optimization model. The main advantage of this method is that it can provide the owner of PEV aggregator with decisions that are made by considering various quantities for risk. CPLEX solver of GAMS software is employed to solve the problem which is formulated as mixed-integer linear programming (MILP) model. To investigate the accomplishment of DRC, risk-averse state of model is compared to risk-neutral which in former one the profit is reduced meanwhile that risk-in-profit (RIP) is declined.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 55〈/p〉 〈p〉Author(s): G.R. Bivina, Akshay Gupta, Manoranjan Parida〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The paper investigates the significant factors affecting pedestrians’ satisfaction on walking accessibility to the metro station using Structural equation modelling considering socioeconomic characteristics of pedestrians, microscale, and mesoscale built environment factors measured within the 800-meter buffer area of metro stations. Questionnaire survey conducted within the catchment areas of fifteen metro stations in Delhi, India, consisted of questions regarding socioeconomic characteristics, trip characteristics, and peoples' satisfaction on microscale built environment factors. The mesoscale built environment factors were the spatial indicators measured within the catchment area of each metro station. Models developed in the study determined that microscale factors, rather than macroscale factors, significantly affect pedestrian satisafction in regards to the accessibility of metro stations. Study findings help in better comprehension of factors affecting walking accessibility and suggesting policy interventions for planners in improving walking accessibility to the metro.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 8 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society〈/p〉 〈p〉Author(s): Amirhassan Kermanshah, Hiba Baroud, Mark Abkowitz〈/p〉 〈h5〉ABSTRACT〈/h5〉 〈div〉〈p〉With the growing rate of urbanization, freight transportation systems have become critical in supporting economic and social needs in the United States. In order to achieve efficient and effective operations, freight transportation systems are recognizing the value of using Cyber-Physical (CP) technologies. This research provides a scenario-based assessment of CP technology penetration to improve sustainability in freight transportation systems with a focus on the use of smart GPS technologies by the trucking industry in Tennessee. Based on the case study, CP technologies can result in significant benefits to the economy, environment, and society. A cost-benefit analysis shows that benefits can be more than 7 times the costs in terms of present values. Social benefits can amount to more than $77 M in the period of study when only 3% of the truck population uses smart GPS technologies. Environmental benefits of 1% CP technologies penetration in the truck industry are equivalent to GHG emissions savings from 46,930 passenger vehicles driven for one year. Benefits become more significant with higher penetration rates. For example, at 5% usage rate of GPS technologies in the trucking industry in Tennessee, CO〈sub〉2〈/sub〉 emissions will decrease by more than 1 million metric tons per year.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 14 January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society〈/p〉 〈p〉Author(s): Hong Yuan, Yuan He, Junzheng Zhou, You Li, Xu Cui, Zhongwei Shen〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In order to assess the impact of underground space development on urban compactness, taking Shenzhen Futian Station and Tokyo Station as empirical cases, this paper uses the comprehensive compactness formula to extract influencing factors and to explore the interaction mechanism between underground space utilization and urban compact development. Previous studies have shown that when urban development reaches a certain threshold, the area compactness will be improved. Otherwise, when the development is below the threshold, the area compactness will be reduced. The compactness we discuss in this study is related to the efficiency of underground space development. The average building distance is a core factor affecting urban compactness and the efficiency of underground space development. Increasing total building area of underground space development of rail stations can significantly increase urban compactness.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 55〈/p〉 〈p〉Author(s): D.P. Jenkins, S. Patidar, P. McCallum, K.B. Debnath〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The energy assessment of single buildings and of larger areas of built environment, although exhibiting similarities in terms of technique, have in the past often used different approaches to energy modelling. The growing availability of empirical data and the capability of building modelling software has, more recently, allowed these differences to be reduced. This paper demonstrates, across two very different case-studies in UK and India, that techniques for community energy modelling can be used in a way that maintains detail in energy demand characteristics, thus helping to bridge the gap between detailed building assessment and higher-level energy system modelling. However, understanding the portability of such techniques requires an understanding of energy characteristics that can be specific to a geographic area. This study documents these important differences and proposes a more transferrable approach to detailed community energy modelling.〈/p〉〈/div〉

Description: 〈p〉Publication date: February 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 53〈/p〉 〈p〉Author(s): Allam Zaheer〈/p〉 〈h5〉ABSTRACT〈/h5〉 〈div〉〈p〉A rapid urbanisation rate, coupled with an increasing global population, equates to a surge in energy demand; threatening sustainable transitions from fossil fuel. However, faced with the impacts of climate change and increasing geopolitical accords, cities are turning towards Renewable Energy sources to meet this demand, but this is a complex matter in Megacities where land availability is scarce for the construction of new, or larger, power plants. As the number of Megacities is expected to increase in the near future, the need for decentralised and sustainable solutions that are technically and economically viable for both the state and the private sector need to be sought. This paper dwells into an extensive review of literature studying energy generation in the case of Megacities, and highlight the dimensions required for them to achieve increased sustainability and resilience. A model, inspired from urban complexity theories, aimed at generating decentralised grid networks -based on the dimensions of Energy Diversification, Land Fragmentation and Fiscal Mechanisms, is proposed with a new way at looking at energy grids from a geometrical and morphological perspective while supporting economic dimensions that will encourage its implementation at both policy and project level. This paper is aimed towards Urban and Energy Planners and Policy Makers looking at how to power Megacities as well as cities facing rapid urbanisation.〈/p〉〈/div〉

Description: 〈p〉Publication date: March 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 54〈/p〉 〈p〉Author(s): A. Yazdaninejadi, D. Nazarpour, S. Golshannavaz〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Low inertia time constant of synchronous generator-based distributed energy resources (SGBDERs) makes them more susceptible to faults. Therefore, fast-response protection is of crucial importance to prevent unintentional disconnection of SGBDERs in active distribution networks (DNs) and hence, non-stop electrification in critical infrastructures. To overcome this challenge, the present study aims at devising a new protection coordination strategy (PCS) for directional overcurrent relays (DOCRs) based on numerical relays. In this regard, this paper unveils that time-current characteristics (TCCs) with gentle and steep slopes are suitable for the lines with huge and small differences in fault currents at near-end and far-end fault points, respectively. These characteristics cannot be followed by the conventional approach. Accordingly, some coefficients in the operation function of DOCRs are included in the variables set to present TCCs with steep slopes and some supplementary variables are employed to present TCCs with gentle slopes. Furthermore, to cope with the effect of increment in the number of variables, some controlling parameters are introduced to steer TCCs toward proper slopes. Finally, to provide more flexibility in meeting distributed generation (DG) stability, instantaneous functions are also included in the proposed PCS. Detailed simulation studies are conducted to assess performance of the proposed approach.〈/p〉〈/div〉

Description: 〈p〉Publication date: March 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Sustainable Cities and Society, Volume 54〈/p〉 〈p〉Author(s): Sarkawt M.L. Hama, Prashant Kumar, Roy M. Harrison, William J. Bloss, Mukesh Khare, Sumit Mishra, Anil Namdeo, Ranjeet Sokhi, Paul Goodman, Chhemendra Sharma〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉A key challenge in controlling Delhi’s air quality is a lack of clear understanding of the impacts of emissions from the surrounding National Capital Region (NCR). Our objectives are to understand the limitations of publicly available data, its utility to determine pollution sources across Delhi-NCR and establish seasonal profiles of chemically active trace gases. We obtained the spatiotemporal characteristics of daily-averaged particulate matter (PM〈sub〉10〈/sub〉 and PM〈sub〉2.5〈/sub〉) and trace gases (NO〈sub〉X〈/sub〉, O〈sub〉3〈/sub〉, SO〈sub〉2〈/sub〉, and CO) within a network of 12 air quality monitoring stations located over 2000 km〈sup〉2〈/sup〉 across Delhi-NCR from January 2014 to December 2017. The highest concentrations of pollutants, except O〈sub〉3〈/sub〉, were found at Anand Vihar compared with lowest at Panchkula. A high homogeneity in PM〈sub〉2.5〈/sub〉 was observed among Delhi sites as opposed to a high spatial divergence between Delhi and NCR sites. The bivariate polar plots and k-means clustering showed that PM〈sub〉2.5〈/sub〉 and PM〈sub〉10〈/sub〉 concentrations are dominated by local sources for all monitoring sites across Delhi-NCR. A consequence of the dominance of local source contributions to measured concentrations, except to one site remote from Delhi, is that it is not possible to evaluate the influence of regional pollution transport upon PM concentrations measured at sites within Delhi and the NCR from concentration measurements alone.〈/p〉〈/div〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S2210670719335449-ga1.jpg" width="330" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉