Sustainable Cities and Society最新文献

Collaborative planning of regional integrated energy system in the era of EV penetration: A comprehensive review

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-11-26 DOI: 10.1016/j.scs.2024.106013

Qinshan Yang , Yingjun Ruan , Fanyue Qian , Hua Meng , Yuting Yao , Tingting Xu , Chaoliang Wang , Wei Liu

The widespread adoption of electric vehicles (EVs) significantly increases the uncertainty and complexity of regional integrated energy system (RIES), leading to substantial changes in their structure and characteristics. This paper reviews the challenges and proposes strategies for collaborative RIES planning in the context of EV. Firstly, the evolution of RIES is analyzed, including its structural changes and characteristics. Secondly, the influence of EV penetration on the source-network-load-storage links within RIES is analyzed. Reviews of literature indicate that under certain conditions, EV even has the potential to replace around 20% of energy storage demand, reducing transportation costs by over 20% while also minimizing energy losses. This paper then summarizes various planning methods for RIES, including the siting and sizing of energy stations, the layout planning of energy networks, and the siting and sizing of EV charging stations. Based on the literature survey conducted in this study, only around 10% of station-network collaborative planning papers consider the impact of EVs, and this paper categorizes these findings into three main methods. This paper aims to provide a solid theoretical foundation and practical guidance for RIES planning in the era of EV penetration.

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引用次数: 0

Predicting origin-destination flows by considering heterogeneous mobility patterns

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-11-26 DOI: 10.1016/j.scs.2024.106015

Yibo Zhao , Shifen Cheng , Song Gao , Peixiao Wang , Feng Lu

The accurate prediction of origin-destination (OD) flows is essential for advancing sustainable urban mobility and supporting resilient urban planning. However, the inherent heterogeneity of mobility patterns results in complex geographic unit relations, diverse spatial organizational structures, and the long-tailed effect on OD flow distribution. This study proposes a novel OD flow prediction method based on graph-based deep learning (named as HMCG-LGBM). Specifically, 1) a modularity-based graph reconstruction strategy is presented for geographic unit relation augmentation by eliminating weak connections; 2) the heterogeneous spatial organization of OD flows is captured by combining the community detection approach and graph attention mechanism with the introduction of socio-economic and spatial features; and 3) a weighted loss function with distribution smoothing paradigm is developed to enhance the prediction for low-probability mobility events, addressing the challenges posed by long-tailed distributions. Extensive experiments conducted on real-world datasets show that the predictive performance of the proposed method is significantly improved, with the RMSE and MAE reduced from the baselines by 11.1%–33.3% and 14.1%–22.2%, respectively. The results also demonstrate the robustness of the proposed method for dealing with imbalanced OD flow distributions, providing valuable insights for spatial interaction predictive modeling in the context of sustainable urban systems.

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引用次数: 0

Nonlinear relationships between canopy structure and cooling effects in urban forests: Insights from 3D structural diversity at the single tree and community scales

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-11-24 DOI: 10.1016/j.scs.2024.106012

Jia Jia , Lei Wang , Yunlong Yao , Zhongwei Jing , Yalin Zhai , Zhibin Ren , Xingyuan He , Ruonan Li , Xinyu Zhang , Yuanyuan Chen , Zhiwei Ye

Three-dimensional structural diversity (3SD) directly influences the distribution and flow of heat within the canopy. However, the nonlinear effects of 3SD of different species on the cooling effects remain unclear. Here, we proposed an analytical framework to explore this relationship at the single tree and community scales. Results indicated that: (1) A benchmark dataset for individual tree segmentation was established, with the best-performing algorithm achieving an accuracy of 77.36% (F-score=0.75), the UAV-based LiDAR, multispectral and thermal infrared imagery using a data fusion approach achieved a better species classification accuracy of 80.41% (kappa=0.78); (2) At the single tree scale, the cooling effects are controlled by vertical structure, heterogeneity, and leaf density (15.36%<rel.inf<26.84%). Entropy, VAI, and H_max exhibited the largest seasonal relative importance change rates (7%<|Δrel.inf|<11%); (3) At the community scale (10m × 10m), VAI contributed the most to coniferous cooling in summer, while H_max had the greatest impact on broadleaf cooling in winter. Species’ spatial connectivity had a significantly greater impact on the cooling effects in broadleaf in summer and coniferous in winter compared to structural diversity. This study supports optimizing urban forestry by demonstrating UAV-based data fusion for species classification and highlighting structural diversity's role in regulating temperature across scales and seasons.

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引用次数: 0

Identification of urban thermal properties by combining urban microclimate modeling and thermal infrared satellite data 结合城市小气候建模和热红外卫星数据识别城市热特性

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-11-23 DOI: 10.1016/j.scs.2024.105995

Thaïs Keravec-Balbot , Auline Rodler , Laure Roupioz , Marjorie Musy , Teddy Gresse , Xavier Briottet

Climate models are increasingly used to predict urban climate, but uncertainties in urban surface properties, such as thermal conductivity and capacity, lead to inaccuracies in comfort indices calculations. The forthcoming TRISHNA satellite mission will provide a unique dataset of thermal infrared imagery (TIR) to study urban area, with a planned spatial resolution of 57 meters and a revisit schedule of three times every eight days.

This study aims to develop a novel method to identify urban thermal properties based on prior knowledge by combining urban microclimate modeling and high spatial resolution satellite TIR, to provide input to microclimate urban models, for outdoor summer comfort assessment. Using a Bayesian approach, the method compares observed satellite-derived land surface temperatures (LST) with simulated LST from a combination of microclimate (Solene micro-climate) and radiative (DART) models. In this present work, as TRISHNA not yet operational, simulated data also serves as the observations.

An ideal street canyon model, representing typical urban structures, was used to validate the method. The approach improved the accuracy of thermal property estimates for horizontal surfaces by up to three times compared to random estimations within prior intervals. Best results were achieved with daytime TIR images acquired during the hottest days.

气候模型越来越多地用于预测城市气候，但城市地表属性（如热传导率和热容量）的不确定性会导致舒适度指数计算的不准确性。即将执行的 TRISHNA 卫星任务将提供独特的热红外图像（TIR）数据集来研究城市地区，计划的空间分辨率为 57 米，重访计划为每八天三次。本研究旨在开发一种新方法，通过结合城市微气候建模和高空间分辨率卫星热红外图像，在先验知识的基础上识别城市热属性，为城市微气候模型提供输入，用于室外夏季舒适度评估。该方法采用贝叶斯方法，将观测到的卫星地表温度（LST）与结合微气候（Solene 微气候）和辐射（DART）模型模拟的地表温度（LST）进行比较。在本研究中，由于 TRISHNA 尚未投入使用，模拟数据也可作为观测数据。与先前区间内的随机估算相比，该方法提高了水平表面热属性估算的准确性达三倍。在最炎热的白天获取的昼间红外图像取得了最佳效果。

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引用次数: 0

Enhancing urban emergency response: A Euclidean distance-based framework for optimizing rescue facility layouts

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-11-23 DOI: 10.1016/j.scs.2024.106006

Chengye Ma , Mingxing Song , Weitao Zeng , Xinuo Wang , Tao Chen , Shihai Wu

This study presents a Euclidean distance-based framework for optimizing the layout of urban emergency rescue facilities. Traditional precinct-based (Type 1) and dynamic time-based (Type 2) models are compared with the proposed Euclidean distance-based (Type 3) model. The analysis uses geospatial and statistical methods to evaluate accessibility, variability, and fairness across different times of the day. The results indicate that the Euclidean distance-based model enhances rescue response efficiency and maintains a more equitable service distribution relative to traditional models. The study identifies a “threshold effect” in rescue times, emphasizing the critical distance beyond which rescue efficiency declines. By leveraging real-time traffic data and integrating Euclidean distance principles, the proposed framework offers a robust and practical approach for urban planners to improve emergency response capabilities and urban resilience. This research underscores the importance of considering both geometric proximity and dynamic traffic conditions in the strategic placement of rescue facilities, providing valuable insights for future urban emergency management and planning.

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引用次数: 0

Susceptibility and risk to inhalation of pathogen-laden aerosol in large public spaces: Evidence from Fangcang Shelter Hospitals under multiple ventilation rates 大型公共场所吸入病原体气溶胶的易感性和风险：多种通风率下芳草地医院的证据

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-11-22 DOI: 10.1016/j.scs.2024.106003

Chuan Jiang , Zhijian Liu , Yongxin Wang , Guangpeng Yao , Junzhou He , Shiyue Li , Rui Rong , Zhenyu Liang , Jiaqi Chu , Jingwei Liu

To enhance the prevention and control of pandemic respiratory infections, we constructed an infection risk prediction model for pathogen inhalation based on the dose-response relationship with reference to the long-distance transmission chain of the SARS-CoV-2 pathogen, applying it to the Fangcang Shelter Hospital (FSH). The model quantitatively describes key processes of pathogens shedding, airborne transmission, suspension, inhalation by susceptible individuals, and lung deposition, thus improving the resolution and accuracy of the results. This study considered four ventilation rates and quantitatively assessed their impact on inhalation infection risk. Results indicate that the infection risk within the multi-patient shelter unit is unevenly distributed, with the maximum probability (3.66 %) being more than 30 times higher than the minimum probability (0.10 %) at a ventilation rate of 8 ACH. Poor ventilation (6 ACH) significantly increases average infection probability, with a rise of 35.96 % compared to the average probability (1.14 %) at 8 ACH. However, excessive ventilation (12 ACH) led to diminishing returns on ventilation performance. Lastly, we also found that poor ventilation was a sufficient and non-essential condition for higher infection probability. Our findings can be extended to similar large-scale scenarios, offering positive support for the sustainable development of society.

为加强对大流行性呼吸道传染病的防控，我们参考 SARS-CoV-2 病原体的远距离传播链，基于剂量-反应关系构建了病原体吸入感染风险预测模型，并将其应用于芳草地避难所医院（FSH）。该模型定量描述了病原体脱落、空气传播、悬浮、易感人群吸入和肺沉积等关键过程，从而提高了结果的分辨率和准确性。本研究考虑了四种通风率，并定量评估了它们对吸入感染风险的影响。结果表明，多病人收容单元内的感染风险分布不均，通风率为 8 ACH 时，最大感染概率（3.66%）是最小感染概率（0.10%）的 30 多倍。通风不良（6 ACH）会显著增加平均感染概率，与 8 ACH 时的平均概率（1.14 %）相比，增加了 35.96 %。然而，过度通气（12 ACH）会导致通气性能的收益递减。最后，我们还发现，通风不良是导致感染概率升高的充分条件，但并非必要条件。我们的研究结果可以推广到类似的大规模场景中，为社会的可持续发展提供积极的支持。

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引用次数: 0

PM2.5 reduces the daytime/nighttime urban heat island intensity over mainland China PM2.5 可降低中国大陆白天/夜间城市热岛强度

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-11-22 DOI: 10.1016/j.scs.2024.106001

Zihao Feng , Xuhong Wang , Mengqianxi Yu , Yimei Yuan , Bingqian Li

PM_2.5 pollution severely threatens people's living environment and health, significantly affect urban heat island (UHI). In this study, in-situ observed data were combined with satellite data via refined pollution intensity classification methods, and the relationships between PM_2.5 and canopy/surface UHI (CUHI/SUHI) were analyzed. PM_2.5 reduced the UHI in nearly all the environments, with more pronounced effects during clear-sky daytime and winter (-0.33 °C for the SUHI) and less pronounced effects at all-sky nights and in summer. For the former, PM_2.5 primarily diminishes the UHI intensity (UHII) by weakening incident radiation; this radiative forcing effect is exacerbated by the combination of PM_2.5 and high humidity, which is further amplified by winter pollution peaks. At night, the UHII primarily influenced by the initial temperature conditions during the day. Less intake of surface energy on high-pollution days, which in turn affects longwave radiation from the surface/canopy at night. Additionally, PM_2.5 has been found to significantly influence UHI through its interaction with potential influential factors and its filtering effect (different PM_2.5 levels correspond to varying conditions of these factors). This study with new insights into the impact of PM_2.5 on UHI could aid in the design of strategies to improve urban heat and pollution environments.

PM2.5 污染严重威胁着人们的生活环境和健康，对城市热岛（UHI）有显著影响。本研究通过改进的污染强度分类方法，将现场观测数据与卫星数据相结合，分析了 PM2.5 与冠层/地表 UHI（CUHI/SUHI）之间的关系。几乎在所有环境中，PM2.5都降低了UHI，在晴朗天空的白天和冬季效果更明显（SUHI为-0.33 °C），而在晴朗天空的夜晚和夏季效果不明显。对于前者，PM2.5 主要通过减弱入射辐射来降低超高气温影响强度（UHII）；PM2.5 和高湿度的结合加剧了这种辐射强迫效应，而冬季污染高峰又进一步放大了这种效应。在夜间，UHII 主要受白天初始温度条件的影响。在高污染日，地表能量摄入较少，这反过来又会影响夜间地表/树冠的长波辐射。此外，研究还发现，PM2.5 通过与潜在影响因素的相互作用及其过滤效应（不同的 PM2.5 水平对应于这些因素的不同条件），对 UHI 有显著影响。这项研究对 PM2.5 对 UHI 的影响有了新的认识，有助于设计改善城市热量和污染环境的策略。

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引用次数: 0

The impacts and thresholds detection of 2D/3D urban morphology on the heat island effects at the functional zone in megacity during heatwave event 热浪事件中二维/三维城市形态对特大城市功能区热岛效应的影响及阈值检测

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-11-19 DOI: 10.1016/j.scs.2024.106002

Yicong Chen , Weibo Ma , Yamei Shao , Nan Wang , Zhaowu Yu , Haidong Li , Qingwu Hu

The contributions of urban morphology (UM) and their key thresholds to urban heat island (UHI) intensity during heatwave events lack clarity. In response to this problem, the impacts and thresholds of UM on summer daytime land surface temperature (LST) in megacity, Shanghai, during the heatwave event were quantified by high-resolution remote sensing and GIS data, including 57 2D/3D UM indices associated with building volumes, vegetation volumes and so on, using stepwise multiple linear regression (SMLR), and XGBoost-based SHAP interpretable methods. The results show that increasing the proportion of tree cover within urban functional zones (UFZs) no longer effectively mitigates UHI; instead, reducing the difference in building and vegetation volume is the key cooling factor related to vegetation. The 3D building-vegetation integrated morphology indices, we proposed, show a fine explanatory on LST, and predominantly govern LST variations in UFZs together with the 2D UM indices (29 %-44 %). Threshold effects are also observed in the impacts of UM during the heatwave event, and the proportion and cohesion of built-up generally has a low impact on LST, when their values are lower than 11.9 % and 98.9 % respectively. Based on these findings, we proposed that the reduction of the volume difference between buildings and vegetation depending on ecological construction of tree species with large canopy may serve as an effective approach to mitigate UHI in UFZs during heatwave events.

城市形态（UM）及其关键阈值对热浪事件期间城市热岛（UHI）强度的贡献尚不明确。针对这一问题，利用高分辨率遥感和地理信息系统数据，包括与建筑体积、植被体积等相关的 57 个二维/三维城市形态指数，采用逐步多元线性回归（SMLR）和基于 XGBoost 的 SHAP 可解释方法，量化了热浪事件期间城市形态对上海特大城市夏季白天地表温度（LST）的影响和阈值。结果表明，增加城市功能区（UFZs）内的树木覆盖率不再能有效缓解 UHI；相反，减少建筑物与植被体积的差异才是与植被相关的关键降温因素。我们提出的三维建筑-植被综合形态指数对低温热量有很好的解释作用，与二维城市功能区指数（29%-44%）一起主要控制城市功能区的低温热量变化。在热浪事件期间，UM 的影响也出现了阈值效应，当其值分别低于 11.9 % 和 98.9 % 时，堆积物的比例和内聚力一般对 LST 的影响较小。基于这些研究结果，我们建议，在热浪事件期间，根据大冠层树种的生态建设情况来减少建筑物与植被之间的体积差，可作为减缓 UFZ 中 UHI 的有效方法。

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引用次数: 0

Knowledge co-creation during urban simulation computation to enable broader participation 在城市仿真计算过程中共同创造知识，实现更广泛的参与

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-11-17 DOI: 10.1016/j.scs.2024.105994

Zaiyang Ma , Hengyue Li , Kai Zhang , Jin Wang , Songshan Yue , Yongning Wen , Guonian Lü , Min Chen

Preparing knowledge on urban simulation computation is necessary to help participants build consensus, reduce expertise gaps, and guide participatory sustainable urban planning. Knowledge co-creation is an effective way to prepare the needed knowledge related to urban simulation computation. However, the procedural and operational information that can help instruct the implementation of urban simulation is extensively hidden in the implementation processes of urban simulation in various forms (e.g., dialog records, configuration parameters, and model operations). Difficulties remain in extracting this implicit information and synthesizing the related knowledge. Therefore, a strategy is proposed to support the co-creation of knowledge during the urban simulation computation. In this strategy, the structural knowledge expression methods are first designed to support information extraction and knowledge synthesis. Based on interaction tracking and natural language understanding techniques, the related information can be obtained from simulation computation processes. Using this information, four main types of knowledge can be generated, optimized and visualized to assist collaborative urban simulation practices. This strategy was implemented in an online collaboration prototype system and verified with two sustainable urban case studies involving the simulation of urban noise environments and solar radiation assessment of photovoltaic noise barriers in cities. The results show that the knowledge co-creation can be effectively implemented by using the information extracted from simulation computation processes, which can benefit broader collaboration in urban simulation and sustainable urban planning.

为帮助参与者达成共识、减少专业知识差距并指导参与式可持续城市规划，有必要准备有关城市仿真计算的知识。知识共创是准备城市仿真计算相关所需知识的有效途径。然而，有助于指导城市仿真实施的程序和操作信息以各种形式（如对话记录、配置参数和模型操作）广泛隐藏在城市仿真的实施过程中。提取这些隐含信息并综合相关知识仍然存在困难。因此，我们提出了一种支持在城市仿真计算过程中共同创造知识的策略。在这一策略中，首先设计了结构性知识表达方法，以支持信息提取和知识合成。基于交互跟踪和自然语言理解技术，可以从模拟计算过程中获取相关信息。利用这些信息，可以生成、优化和可视化四种主要类型的知识，以协助城市仿真协作实践。这一策略已在一个在线协作原型系统中实施，并通过两个可持续城市案例研究进行了验证，涉及城市噪声环境模拟和城市光伏隔音屏障的太阳辐射评估。结果表明，通过使用从模拟计算过程中提取的信息，可以有效地实现知识共创，从而有利于城市模拟和可持续城市规划领域的更广泛合作。

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引用次数: 0

Effects of carbon tax policy on vehicle pollution control and carbon reduction based on the availability heuristic and system dynamics 基于可用性启发式和系统动力学的碳税政策对汽车污染控制和碳减排的影响

IF 10.5 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2024-11-17 DOI: 10.1016/j.scs.2024.105990

Shuwei Jia, Wanminghao Zhu

Emissions from motor vehicles are major contributors to air pollution in China. This article establishes a system dynamics management model for the urban road transport system that aims to reduce emissions and pollution. Further, to broaden the carbon tax's emission-reduction effect, we propose an integration algorithm for vehicle travel decision-making based on the availability heuristic and system dynamics. The results of our study show that (1) in Beijing's road transport system, passenger vehicles and trucks are the main sources of CO₂ and PM_2.5 emissions, respectively. The surge in emissions from trucks is a key contributor to the observed increase in PM_2.5. (2) The application of carbon tax policy to road transport is subject to substitution, synergy and projection effects. Using heuristics to optimize the carbon tax system can help control taxpayers’ psychological expectations and increase the emission-reduction effect. (3) The principle of taxation limits the effect of carbon taxes. (4) Compared with a standard carbon tax, a heuristic carbon tax can increase the reduction of CO₂ and PM_2.5 emissions by 8.47 % and 8.38 %, respectively. Under the joint green scenario, the degree of pollution loss and the influence on health can be reduced by 20.44 % and 19.14 %, respectively.

机动车排放是造成中国空气污染的主要因素。本文为城市道路交通系统建立了一个系统动力学管理模型，旨在减少排放和污染。此外，为了扩大碳税的减排效果，我们提出了一种基于可用性启发式和系统动力学的车辆出行决策集成算法。研究结果表明：(1) 在北京的道路交通系统中，客运车辆和货车分别是二氧化碳和 PM2.5 的主要排放源。卡车排放量的激增是导致 PM2.5 上升的主要原因。(2) 对公路运输实施碳税政策会产生替代效应、协同效应和预测效应。利用启发式方法优化碳税制度，有助于控制纳税人的心理预期，提高减排效果。(3）税收原则限制了碳税的效果。(4）与标准碳税相比，启发式碳税可使二氧化碳和 PM2.5 的减排量分别增加 8.47%和 8.38%。在联合绿色情景下，污染损失程度和对健康的影响可分别减少 20.44 % 和 19.14 %。

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引用次数: 0