本次给大家整理的是《Sustainable Cities and Society》杂志2024年04月第103期的论文的题目和摘要，一共包括36篇SCI论文！
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A fast and multifactor evacuation method considering cumulative fatality rate based on deep reinforcement learning for urban toxic gas leakage
基于深度强化学习，研究城市有毒气体泄露情况下的快速多因素疏散方式对累计致死率的影响
Toxic gas leakage accidents negatively impact human health and the social economy, affecting the sustainability and resilience of cities. It is significant to provide safe evacuation paths timely, but most of the current evacuation methods do not consider the impact of multiple factors and have slow computation speed. In this paper, a fast and multifactor evacuation model based on deep reinforcement learning was proposed to quickly calculate evacuation paths with the lowest cumulative fatality rate. Specifically, the concentration distribution of carbon monoxide was acquired accurately by using a new solver based on buoyantBoussinesqPimpleFoam of OpenFOAM. The evacuation paths were calculated by a novel Double Dueling Deep Q Network, whose reward function was constructed by calculating high-risk areas based on an improved Wells-Riley model. To simplify the training of the model, the pedestrian was divided into leaders and followers, andCellular Automata was coupled to simulate pedestrian collision and congestion. The results demonstrate the proposed method provides safe evacuation paths for urban toxic gas leakage faster. The study identifies the influence mechanism of multiple factors on evacuation, among which wind direction and pre-evacuation time have more significant impacts, providing valuable insights for urban planners to reduce risk and enhance urban sustainability.有毒气体泄漏事故对人类健康和社会经济产生负面影响，影响城市的可持续性和韧性。及时提供安全的疏散路径非常重要，但大多数现有的疏散方法没有考虑多个因素的影响，计算速度也较慢。本文提出了一种基于深度强化学习的快速多因素疏散模型，用于快速计算具有最低累积致死率的疏散路径。具体而言，通过使用基于OpenFOAM的buoyantBoussinesqPimpleFoam的新求解器准确获取一氧化碳的浓度分布。疏散路径由一种新的双决斗深度Q网络（Double Dueling Deep Q Network）计算，其奖励函数通过基于改进的Wells-Riley模型计算高风险区域构建。为了简化模型的训练，将行人分为领队和跟随者，并耦合蜂窝自动机（Cellular Automata）来模拟行人碰撞和拥堵。结果表明，所提出的方法能够更快地提供城市有毒气体泄漏的安全疏散路径。研究确定了多种因素对疏散的影响机制，其中风向和预疏散时间的影响更为显著，为城市规划者提供了有价值的见解，以降低风险并增强城市的可持续性。https://doi.org/10.1016/j.scs.2024.105255
Multi-objective planning of electric bus systems in cities with trolleybus infrastructure networks
具有无轨电车基础设施网络的城市电动公交系统的多目标规划
The deployment of In-Motion-Charging (IMC) trolleybuses is considered a promising approach for efficiently increasing the share of electric public transport modes in urban centers. Indeed, in cities with existing catenary infrastructure hybrid trolleybuses that can charge in motion, yet can also operate in battery mode, can be deployed. In this context, this study investigates the design of transit route networks under the IMC concept and proposes a hybrid multi-objective Variable Neighborhood Search-based (MOVNS) algorithm for this purpose. We combine MOVNS with mixedinteger programming (MIP) for determining supplementary charging station locations. A bi-level bi-objective formulation is adopted to generate non-dominated solutions for passengers and operators. Results show that cities with extensive catenary networks can establish efficient IMC transit systems with minimal investment, and even a 20 % coverage suffices to maintain investment costs low.在城市中心部署动态充电（IMC）无轨电车被认为是有效提高电动公共交通方式份额的有前途的方法。确实，在拥有现有架空线基础设施的城市，可以部署能够在运动中充电但也能在电池模式下运行的混合动力无轨电车。在这种背景下，本研究探讨了IMC概念下的交通路线网络设计，并提出了一种基于混合多目标变邻域搜索（MOVNS）算法的方法。我们将MOVNS与混合整数规划（MIP）结合起来，以确定补充充电站的位置。采用双层双目标公式为乘客和运营商生成非支配解。结果表明，拥有广泛架空线网络的城市可以以最低的投资建立高效的IMC交通系统，即使只有20%的覆盖率也足以保持投资成本低廉。https://doi.org/10.1016/j.scs.2024.105227Christina Iliopoulou, University of Patras Ioannis X. Tassopoulos University of PatrasKonstantinos Kepaptsoglou， National Technical University of Athens
The analysis of the spatio-temporal changes and prediction of built-up lands and urban heat islands using multi-temporal satellite imagery
利用多时相卫星影像分析和预测建设用地和城市热岛的时空变化
Irregular and rapid shifts in built-up lands are among the prime causes of increased Land Surface Temperature (LST) and the subsequent formation of Urban Heat Islands (UHIs). Timely and accurate delineation of built-up lands is fundamental to the understanding of LST variation and environmental changes; however, most of the built-up land maps have coarse resolutions. The present study attempts to develop a combinational index representing the biophysical characteristics of the land surface using exponential functions and Landsat time-series images for accurate built-up land maps on a fine scale. The developed index was used along with the Otsu threshold to categorize different built-up from 2001 to 2021 and then utilized as an input to the CA-Markov model to predict built-up lands in 2031. The corresponding relations between changes in built-up lands and its effects on LST andUHI were also analyzed via partial correlation analysis and bivariate LISA. The accuracy assessments of the proposed model for 2001–2021 revealed an accuracy value of 78 for the period (2001–2021) and a value of 77 when the CA-Markov model was utilized for 2021. The correlation values connecting the built-up land status and LST were also significantly strong and positive (0.86–0.89). The apparent similarities and patterns of clusters linking the built-up lands to UHI were also verified by global bivariate Moran's I index of greater than 0.328, showing how an increase in built-up lands leads to increasing the UHI. These findings are helpful for urban construction planning to minimize the negative environmental impacts of urbanization.不规则和快速的建设用地变化是导致地表温度（LST）升高及其后续形成城市热岛（UHI）的主要原因之一。及时和准确地描绘建设用地对于理解LST变化和环境变化至关重要；然而，大多数建设用地图的分辨率较低。本研究尝试利用指数函数和Landsat时间序列影像开发一个结合地表生物物理特征的指数，以便在细尺度上准确绘制建设用地图。所开发的指数与大津阈值一起用于对2001年至2021年的不同建设用地进行分类，并作为CA-Markov模型的输入预测2031年的建设用地。通过偏相关分析和双变量LISA分析了建设用地变化与LST和UHI影响之间的对应关系。对2001-2021年期间提出模型的准确性评估显示，该期间的准确值为78，当CA-Markov模型用于2021年时准确值为77。建设用地状态与LST之间的相关值也显著强且为正（0.86-0.89）。连接建设用地与UHI的显著相似性和集群模式通过大于0.328的全局双变量Moran's I指数得到验证，显示出建设用地增加如何导致UHI增加。这些发现对城市建设规划有帮助，可以最大限度地减少城市化对环境的负面影响。https://doi.org/10.1016/j.scs.2024.105231Keyvan Ezimand Shahid Beheshti UniversityHossein Aghighi Shahid Beheshti UniversityDavod Ashourloo Shahid Beheshti UniversityAlirezaShakiba Shahid Beheshti University
Assessing urban population exposure risk to extreme heat: Patterns, trends, and implications for climate resilience in China (2000–2020)
评估中国城市人口在极端高温环境中的暴露风险：模式、趋势及对气候韧性的影响（2000–2020）
Urban residents face serious thermal health risks from extreme heat owing to the cumulative effects of urbanization and climate warming. However, the patterns of urban populations exposed to extreme heat and urban extreme heat exposure risks (UEHER) require clarification in China. We determined urban extreme heat and the exposed populations for land surface temperature (LST) in 320 cities from 2000 to 2020 by setting thresholds and assessed the UEHER in China through the “Hazard-Exposure-Vulnerability” framework. Our findings indicated an average extreme LST threshold of 35.24 °C, varying from 29.32 °C to 47.79 °C. Higher extreme LST thresholds were mainly concentrated in Northwest China and developed cities. From 2000 to 2020, the extreme heat-exposed areas have increased by approximately 27.8 km2, equivalent to an average of approximately 321.3 soccer fields per year. The urban population exposed to extreme heat (UPEEH) in China has increased by approximately 115 million in the past 20 years, mainly in more developed cities, especially in eastern and northern China. Notably, the proportion of the UPEEH has decreased more rapidly in the east region. The UEHER index increased 52.5 % over 20 years, with 97.19 % of the cities having a worsening trend. Medium-developed and high-population density regions faced the dual risk of a high UEHER and more rapid increase in extreme heat. In contrast, less-developed regions faced the dual problems of high UEHER and low gross domestic product (GDP). Understanding vulnerable and prioritized areas of urban heat exposure will provide information for the development of adaptive policies that enhance urban climate resilience.由于城市化和气候变暖的累积效应，城市居民面临极端高温带来的严重热健康风险。然而，中国城市人口暴露于极端高温和城市极端高温暴露风险（UEHER）的模式需要澄清。我们通过设定阈值确定了2000年至2020年320个城市的地表温度（LST）中的城市极端高温和暴露人口，并通过“危害-暴露-脆弱性”框架评估了中国的UEHER。我们的研究结果表明，极端LST的平均阈值为35.24℃，范围从29.32℃到47.79℃。较高的极端LST阈值主要集中在中国西北部和发达城市。从2000年到2020年，极端高温暴露区增加了约27.8平方公里，相当于平均每年约321.3个足球场。过去20年，中国暴露于极端高温的城市人口（UPEEH）增加了约1.15亿人，主要集中在东部和北部的发达城市。值得注意的是，东部地区的UPEEH比例下降更为迅速。UEHER指数在20年内增加了52.5%，97.19%的城市呈现恶化趋势。中等发达和高人口密度地区面临高UEHER和极端高温快速增加的双重风险。相反，欠发达地区面临高UEHER和低国内生产总值（GDP）的双重问题。了解城市热暴露的脆弱和优先区域将为制定增强城市气候韧性的适应政策提供信息。https://doi.org/10.1016/j.scs.2024.105260Zhibin Ren 中国科学院, 海南省热带岛屿气候研究国家重点实验室Shengyang Hong 中国科学院, 吉林大学
Prosocial responses in disasters: Zooming out to neighboring regions and uncovering the impact of socioeconomic and built environment features
灾难中的亲社会反应：扩展到邻近地区并揭示社会经济和建成环境特征对其的影响
In recent years, with the escalation of extreme climate events worldwide, prosocial responses from community members, volunteers, and organizations are becoming increasingly important to alleviate the impact of disasters. Nevertheless, the potential for prosocial responses from neighboring regions not immediately impacted by disaster has received limited attention, and particularly, very little is known about the interrelationship between prosocial responses and different socioeconomic and built environment features. This study investigated prosocial responses in regions of Florida not immediately impacted (FNII) during Hurricane Ian in 2022, using Twitter data and empirically assessed their interrelationship with various socioeconomic and built environment features. The correlation results revealed that prosocial responses and sentiments are interrelated with socioeconomic and built environment features and vary on spatial and temporal scales in regions of FNII. Specifically, the findings showed that communities with higher socioeconomic status and improved built environment facilities exhibited more prosocial responses. Moreover, the best-performed regression model, with anR2 value of 0.931, can precisely predict prosocial response-related tweets using socioeconomic and built environment features. Finally, the time series clustering analysis sheds light on socioeconomic and built environment disparities that impact prosocial responses; notably, counties with more advanced educational attainment display increased prosocial responses.近年来，随着全球极端气候事件的升级，社区成员、志愿者和组织的亲社会反应，对于减轻灾害影响变得越来越重要。然而，受灾地区以外的邻近地区潜在的亲社会反应却却没有得到足够的关注，尤其是关于亲社会反应与不同社会经济和建成环境特征之间的相互关系知之甚少。本研究使用推特数据，调查了2022年“伊恩”飓风期间佛罗里达州未受影响地区（FNII）的亲社会反应，并经验性地评估了它们与各种社会经济和建成环境特征之间的相互关系。相关结果显示，FNII地区的亲社会反应和情感与社会经济和建成环境特征相关，并且在空间和时间尺度上有所变化。具体而言，研究结果显示，具有较高社会经济地位和改善的建成环境设施的社区表现出更多的亲社会反应。此外，最佳表现的回归模型具有0.931的R2值，可以精确预测与社会经济和建成环境特征相关的亲社会反应。最后，时间序列聚类分析揭示了影响亲社会反应的社会经济和建成环境差异；值得注意的是，具有更高教育水平的县显示出增加的亲社会反应。https://doi.org/10.1016/j.scs.2024.105245Md Ashiqur Rahman Department of Civil and Environmental Engineering, Florida International University,Runhe Zhu Moss School of Construction, Infrastructure and Sustainability, Florida International University
Dynamic pricing for load shifting: Reducing electric vehicle charging impacts on the grid through machine learning-based demand response
动态定价用于负荷转移：通过机器学习的需求响应，降低电动车充电对电网的影响
A robust smart grid communication network is a critical technology that enables modernized utilities to change power usage in real-time for optimal supply and demand balance. The utility sector must have access to additional power during times of high demand or crises to fulfil the demands of the wholesale market. This paper proposes a dynamic-pricing technique to manage power fluctuations while considering peak and off-peak electricity consumption. The demand for different feeders, overall distribution networks, and end-user power rates decrease throughout the day's peak-hours using proposed dynamic-pricing scheme. Internet of Things (IoT) devices manage price-sensitive loads during peak periods. This article proposed the decision tree regression (DTR)-XGBoost models to analyze short-term electric power consumption forecasting in a dynamic environment. The highest overall distribution substation electric power consumption forecasting accuracy is achieved by DTR-XGBoost in the one-hour interval, with an RMSE of 0.2616MW, MSE of 0.0684 MW, MAE of 0.1270 MW, and R2 of 0.9888. Using demand response to minimize peak demand caused by charging electric vehicles and other high-power devices in distribution networks. Results show that the proposed demand response day ahead dynamic pricing minimizes energy costs and enables smart substation operators to stabilize the power system.一个健壮的智能电网通信网络是一项关键技术，它使现代化的公用事业能够实时调整电力使用，以实现供需平衡。在高需求或危机时期，公用事业部门必须能够获得额外的电力，以满足批发市场的需求。本文提出了一种动态定价技术，以管理电力波动，同时考虑峰值和非峰值电力消耗。通过所提出的动态定价方案，在一天的高峰时段，不同馈线、整体配电网络和最终用户的电力费率需求都会减少。物联网（IoT）设备在高峰期间管理价格敏感的负载。本文提出了决策树回归（DTR）-XGBoost模型，用于分析动态环境下的短期电力消耗预测。在一小时间隔内，DTR-XGBoost实现了最高的整体配电变电站电力消耗预测精度，其均方根误差（RMSE）为0.2616 MW，均方误差（MSE）为0.0684 MW，平均绝对误差（MAE）为0.1270 MW，R2为0.9888。利用需求响应来减少电动车充电和其他高功率设备在配电网络中引起的峰值需求。结果表明，所提出的需求响应提前一天的动态定价可以最小化能源成本，并使智能变电站运营商稳定电力系统。https://doi.org/10.1016/j.scs.2024.105256Balakumar Palaniyappan School of Electrical Engineering, Vellore Institute of Technology, Chennai CampusSenthil Kumar R School of Electrical Engineering, Vellore Institute of Technology, Chennai CampusVinopraba T Department of Electrical and Electronics Engineering, National Institute of Technology PuducherryThe challenges of high-quality development in Chinese secondary cities: A typological exploration
The governmental initiative of high-quality development (HQD) marks a shift in the Chinese development paradigm from prioritizing speed to prioritizing quality towards comprehensive goals of economic growth, social vitality, innovation capacity, industrial upgrading, regional cooperation, and green transformation. This initiative is increasingly discussed within the framework of mega-regions, with prior studies demonstrating that they are critical arenas for promoting HQD visions. However, unevenness within mega-regions has become an important limitation to this vision. Namely, significant disparities exist between mega-regional core cities and the smaller neighboring cities in most HQD indicators. This paper conceptualizes these smaller players as secondary cities. Based on this, this paper aims to understand and differentiate the specific challenges of secondary cities facing intra-regional unevenness in the context of HQD. We build an evaluation framework and employ the TOPSIS method to evaluate 34 core cities and 180 secondary cities. Then, we introduce typological thinking to develop a meaningful classification of secondary cities based on the results of these evaluations. K-means clustering analysis identifies five secondary city types with similar profiles. The analysis supports the discussion of the characteristics and challenges of each type and may contribute to policy recommendations for a balanced HQD in mega-regional secondary cities.政府倡导的高质量发展（HQD）倡议标志着中国发展范式从追求速度转向追求质量，朝着经济增长、社会活力、创新能力、产业升级、区域合作和绿色转型的综合目标迈进。这一倡议在越来越多的讨论中被纳入了超大城市群的框架，先前的研究表明，它们是推动HQD愿景的关键领域。然而，在超大城市群内部的不均衡已成为实现这一愿景的重要局限。具体来说，大多数HQD指标在超大城市群核心城市与较小的邻近城市之间存在显著差异。本文将这些较小的参与者概念化为二线城市。基于此，本文旨在了解和区分在HQD背景下，地区内发展不均衡的二线城市所面临的具体挑战。我们构建了一个评估框架，并采用TOPSIS方法评估了34个核心城市和180个二线城市。然后，我们引入了类型学思维，根据这些评估结果开展了有意义的二线城市分类。K均值聚类分析确定了五种具有相似特征的二线城市类型。该分析对各种类型特征和挑战的讨论提供了支持，且有助于对二线城市所形成的超大城市群的高质量平衡发展提出政策建议。https://doi.org/10.1016/j.scs.2024.105266Yizhao DuDelft University of TechnologyRodrigo V.Cardoso Delft University of TechnologyRobertoRocco Delft University of Technology
Urban economic resilience within the Yangtze River Delta urban agglomeration: Exploring spatially correlated network and spatial heterogeneity
长江三角洲城市群的城市经济韧性：探索空间相关网络和空间异质性
As interconnectivity within urban agglomeration intensifies, enhancing inter-city economic linkages and resilience to uncertainty shocks has become imperative for economic sustainability. This study measured urban economic resilience, and then unveiled its spatial correlation and heterogeneity at urban agglomeration scale. Social network analysis revealed overall network characteristics and nodes' structural features of the delineated spatially correlated network of economic resilience. Factors driving spatial correlations were explored using QAP regression. Additionally, spatial heterogeneity of economic resilience was analysed, and GeoDetector was employed to determine the impacts of various factors and their interactions. The economic resilience of 26 cities within the Yangtze River Delta urban agglomeration was calculated. The spatially correlated network exhibits lower density and efficiency. Some cities play central, bridging, and connected roles, while others have limited connectivity, linked to factors like population mobility, spatial adjacency, economic development difference, and knowledge network. During regional integration strategy promotion, significant global spatial autocorrelation is observed, and local spatial autocorrelation reveals heterogeneity in economic resilience. It could be explained by various factors, with nonlinear enhancement effects of two-factor interactions. Recommendations are proposed for enhancing economic resilience by strengthening connections and coordinating despite differences, thus facilitating resilience shaping economic growth and advancing regional sustainability.随着城市群内部互联互通的加强，增强城市间经济联系和应对不确定性冲击的韧性已成为经济可持续发展的迫切需求。本研究衡量了城市经济韧性，然后揭示了其在城市群尺度上的空间相关性和异质性。社会网络分析揭示了经济韧性空间相关网络的整体网络特征和节点的结构特征。利用QAP回归探讨了驱动空间相关性的因素。此外，分析了经济韧性的空间异质性，并采用GeoDetector确定了各种因素及其相互作用的影响。计算了长江三角洲城市群内26个城市的经济韧性。空间相关网络呈现出较低的密度和效率。一些城市具有中心、桥梁和连接的作用，而其他一些城市连接性有限，与人口流动、空间邻近性、经济发展差异和知识网络等因素相关。在推动区域一体化战略的过程中，观察到了显著的全局空间自相关性，并且局部空间自相关性显示出经济韧性的异质性。这可以通过各种因素来解释，其中两个因素之间的非线性增强效应尤为突出。提出了增强经济韧性的建议，即通过加强连接和协调不同，促进韧性塑造经济增长，推动区域可持续发展。https://doi.org/10.1016/j.scs.2024.105270
Evaluating green space provision development in Shanghai (2012–2021): A focus on accessibility and service efficiency
评估上海绿地供给发展（2012-2021年）：重点关注可达性和服务效率
This study evaluates accessible urban green space (UGS) provision in Shanghai, China (2012–2021), focusing on accessibility and its influencing factors amidst urbanization. We aim to understand if and how UGS provision addresses urban demands effectively and efficiently on limited conditions. Utilizing an improved n-step floating catchment area method, we conducted a comprehensive assessment of UGS locations’ accessibility, integrating comprehensive capacity, population demand, and transport supply. Multidimensional analyses were applied to evaluate changes in UGS accessibility and these three influencing factors. Based on the relationships among these three factors, we investigate the rationality and efficiency of the development of accessible UGS provision. By integrating UGS provision efficiency, the mechanisms driving by the three factors, and the UGSs’ effect on UGS equity citywide, new UGS construction and existing UGSs needing improvement are evaluated from the aspects of feasibility, effectiveness, and justice. Our findings demonstrate that Shanghai effectively developed its UGS accessibility from 2012 to 2021, committing to sustainable urban development and improving residents’ quality of life. Comprehensive capacity emerged as a key driver in UGS provision, highlighting its importance in future policy and planning. This study provides nuanced insights into UGS provision efficiency and optimization, aiding urban planners in enhancing UGSs worldwide.本研究评估了中国上海市（2012年至2021年）的城市绿地供给情况，重点关注可达性及其在城市化进程中的影响因素。我们旨在了解有限条件下城市绿地供给是否有效和高效地满足了城市需求。利用改进的n步浮动捕获区域方法，我们对绿地位置的可达性进行了全面评估，整合了综合容量、人口需求和交通供给。我们运用多维分析方法评估了绿地可达性和这三个影响因素的变化。基于这三个因素之间的关系，我们调查了可达性绿地供给发展的合理性和效率。通过整合绿地供给效率、这三个因素驱动的机制以及绿地对城市范围内绿地公平的影响，从可行性、效果和公正性的角度评估了新绿地建设和需要改进的现有绿地。我们的研究结果表明，上海市在2012年至2021年间有效地提高了其绿地可达性，致力于可持续城市发展并改善居民生活质量。综合容量成为绿地供给的关键驱动因素，突显了其在未来政策和规划中的重要性。本研究提供了对绿地供给效率和优化方式的建议，有助于城市规划者改善全球范围内的绿地供给情况。https://doi.org/10.1016/j.scs.2024.105269
Influence of the built environment on social capital and physical activity in Singapore: A structural equation modelling analysis新加坡建成环境对社会资本和体育活动的影响：一种结构方程建模分析Social well-being and public health have been prominent issues in developing a liveable city, especially in the unique urban context of densely populated Singapore, posing challenges for careful and efficient urban planning. As a result, it is essential to understand the association between the built environment and the social outcomes of local communities. We applied quantitative methods to assess people’s perception on diverse physical features of the built environment, including availability of amenities, public spaces, and transportation options, to understand their complex interplay and collective impact on social outcomes. Data were collected from official open sources and through questionnaire surveys from three selected neighborhoods in Singapore. Structural equation models were developed to study the interactions between various aspects of the built environment and social outcomes that include social capital and physical activity of the residents. The results show that the influence of objective measures of the built environment is not significant, but the perceived built environment aspects of inclusivity and quality have direct positive influence on social capital. Perceived built environment aspects were also found to have an indirect influence on physical activity variables of frequency and mode, with social capital being the mediator.社会福祉和公共健康一直是发展宜居城市的突出问题，尤其是在人口稠密的新加坡这样独特的城市环境中，这给细致高效的城市规划带来了挑战。因此，了解建成环境与当地社区社会结果之间的关联至关重要。我们采用定量方法评估了人们对建成环境的各种物理特征的感知，包括设施的可用性、公共空间和交通选择，以了解它们之间复杂的相互作用及对社会结果的集体影响。数据来源于新加坡三个选定社区的官方开放数据和问卷调查。建立了结构方程模型，研究了建成环境的各个方面与社会结果之间的相互作用，其中包括居民的社会资本和身体活动。结果显示，建成环境客观测量的影响不显著，但感知到的包容性和质量等建成环境方面直接对社会资本产生积极影响。还发现，感知到的建成环境方面对频率和模式等身体活动变量有间接影响，社会资本是中介因素。https://doi.org/10.1016/j.scs.2024.105259Rakhi Manohar Mepparambath Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR) Diem Trinh Thi Le, Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR)Jeremy OonInstitute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR)Jie SongInstitute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR)Hoai Nguyen HuynhInstitute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR)
Post-flood disaster damaged houses classification based on dual-view image fusion and Concentration-Based Attention Module
基于双视图图像融合和注意力机制改进卷积模块，研究洪水灾后受损房屋分类模式
Flood disasters inflict immense devastation upon buildings, and the post-disaster assessment of housing damage levels is of paramount importance in safeguarding resident lives. Conventional assessment methods entail a significant expenditure of human resources, finances, and time. Toward this, a Dual-View Convolutional Neural Network (DV-CNN) model is proposed in this study. The ResNet-50 model is adopted as its backbone, and the transfer learning techniques and the Concentration-Based Attention Module (CBAM) are incorporated into the model to enhance the efficiency and generalization capabilities of the training model. This model can integrate distinct indicators of interior and exterior damage in post-disaster houses to collectively determine the damage levels classification of the houses. Subsequently, this AI model for house damage level classification is validated by training and testing the data of rural house damage caused by the flood triggered by the “July 20 Heavy rainstorm in Zhengzhou”. The analysis of the model’s hyperparameters indicates that the optimal predictive performance is achieved when the learning rate is set to 0.005, the batch size is 16, and the number of epochs is 50. The results of a comparative analysis among the DV-CNN, ResNet-50, ResNet-101, MobileNet-v2, VggNet, and GoogleNet models indicate that the proposed DV-CNN model achieves the highest accuracy of 92.5% in predicting the damage levels of post-flood affected houses. Finally, a visual analysis of the features associated with house risk levels provides a clear understanding of the classification mechanism and the accuracy of the model. Experiments demonstrate that the deep CNN recognition model based on dual-view exhibits greater reliability and generalizability, providing a valuable reference for classification models of post-flood damage levels in rural houses.在洪水灾害中，建筑物遭受了巨大的破坏，对房屋损坏程度进行灾后评估对保障居民生命至关重要。传统的评估方法需要大量的人力、财力和时间投入。因此，本研究提出了一种双视图卷积神经网络（DV-CNN）模型。采用ResNet-50模型作为其主干，并结合了迁移学习技术和注意力机制改进卷积模块（CBAM）来提高训练模型的效率和泛化能力。该模型可以将灾后房屋内部和外部损害的不同指标集成起来，共同确定房屋的损坏程度分类。随后，通过训练和测试“7.20郑州暴雨”引发的洪水造成的农村房屋损坏数据来验证此房屋损坏程度分类的人工智能模型。对模型的超参数进行分析表明，当学习率设定为0.005、批量大小为16、epochs数为50时，可以实现最佳的预测性能。对比分析DV-CNN、ResNet-50、ResNet-101、MobileNet-v2、VggNet和GoogleNet模型的结果表明，所提出的DV-CNN模型在预测洪水影响下房屋损坏程度方面取得了92.5%的最高准确率。最后，对与房屋风险级别相关的特征进行可视化分析，可以清楚地理解分类机制和模型的准确性。实验证明，基于双视图的深度卷积神经网络识别模型具有更高的可靠性和泛化能力，为农村房屋洪水损坏程度分类模型提供了宝贵的参考。https://doi.org/10.1016/j.scs.2024.105234
Synergetic urbanism: a theoretical exploration of a vertical farm as local heat source and flexible electricity user
协同城市主义：垂直农场作为当地热源和灵活用电用户的理论探讨
The urban energy transition requires innovative heating and cooling systems, as well as enhanced flexibility in electricity usage. This paper explores the theoretical potential for vertical farms to contribute to the energy transition by supplying residual heat to local district heat networks and flexible electricity usage. A stepped approach was used to design energy systems that achieve thermal energy balance through heat and cold exchange between a vertical farm and buildings within a specific Dutch neighbourhood. Furthermore, alternative lighting strategies for vertical farms were explored to reduce grid congestion and to respond to electricity price fluctuations, limiting the mismatch between electricity generation and demand. Compared to the baseline scenario, the energy system with an integrated vertical farm reduces overall energy use by 15 %, even when accounting for the farm's electricity use. By adopting intermittent lighting that is better aligned with electricity price fluctuations, the vertical farm obtained annual cost savings of 14 %. The integration of vertical farms into energy systems can, therefore, contribute to the urban energy transition by producing residual heat to balance thermal energy system and save money for growers by optimising LED operations to align with electricity price fluctuations, whilst producing fresh vegetables for the city.城市能源转型需要创新的供热和供冷系统，以及增强电力使用的灵活性。本文探讨了垂直农场在能源转型中的潜在作用，通过向当地的地区供热网络提供余热和灵活使用电力。采用逐步推进的设计方法设计能源系统，通过垂直农场和荷兰特定社区内建筑物之间的热量和冷量交换实现热能平衡。此外，探讨了垂直农场的替代照明策略，以减少电网拥塞并应对电力价格波动，从而限制电力产生和需求之间的不匹配。与基准方案相比，集成了垂直农场的能源系统即使考虑到农场的电力使用，也可以将总能耗降低15%。通过采用与电力价格波动更好对齐的间歇性照明，垂直农场获得了14%的年度成本节约。因此，将垂直农场集成到能源系统中可以通过产生余热来平衡热能系统，并通过优化LED操作以与电力价格波动相一致，为种植者节省资金，同时为城市提供新鲜蔬菜，从而促进城市能源转型。https://doi.org/10.1016/j.scs.2024.105267T. (Tess) Blom Delft University of Technology, Department of Architectural Engineering and TechnologyA. (Andrew)Jenkins University of Salford, School of Science, Engineering and Environment
Enhancing social vulnerability assessment with energy resilience: A comprehensive study of the Netherlands
A comprehensive vulnerability assessment is a scientific basis for the realization of the United Nations' sustainable development goals. Energy resilience plays a crucial role in mitigating social vulnerability due to disaster shocks. Often, energy infrastructure and services collapse after disasters. The recent Russia-Ukraine war has exacerbated Europe's energy crisis and social vulnerabilities, making it even more urgent to add energy resilience to vulnerability assessments. This paper takes the Netherlands as the study area for vulnerability assessment, constructs a new social vulnerability indicator (SVI) system supplemented with the energy element, and compares that with the traditional energy indicator system.The results indicate that: 1) The introduction of energy indicators fills the gap of traditional SVI assessment. 2) Energy indicators reveal regional and spatial differences in potential social vulnerability in the Netherlands. 3) Energy-inclusive SVI demonstrates that uneven urbanization exacerbates risks and inequalities for vulnerable groups, with potential impacts on social vulnerability. Sustainable urban development requires the search for a recognized and coordinated approach to managing vulnerability across regions. The complementarity of energy indicators offers opportunities to provide a more comprehensive assessment of spatial patterns of social vulnerability, identify potentially vulnerable areas, enhance urban disaster resilience, and achieve sustainable urban development.一项全面的脆弱性评估是实现联合国可持续发展目标的科学基础。能源韧性在减轻灾害冲击导致的社会脆弱性方面发挥着关键作用。灾后常常会出现能源基础设施和服务的崩溃。最近的俄罗斯-乌克兰战争加剧了欧洲的能源危机和社会脆弱性，使将能源韧性纳入脆弱性评估更加迫切。本文以荷兰为研究区域进行脆弱性评估，构建了一个新的社会脆弱性指标（SVI）系统，补充了能源元素，并将其与传统的能源指标系统进行了比较。结果表明：1.引入能源指标填补了传统SVI评估的空白。2.能源指标显示了荷兰潜在社会脆弱性的区域和空间差异。3.包含能源的SVI表明不均衡的城市化加剧了对脆弱群体的风险和不平等，可能对社会脆弱性产生影响。可持续的城市发展需要寻求一种公认和协调的方法来跨越地区管理脆弱性。能源指标的互补性提供了更全面地评估社会脆弱性空间模式、识别潜在脆弱区域、增强城市灾害韧性、实现可持续城市发展的机会。https://doi.org/10.1016/j.scs.2024.105251Jun Wu Breda University of Applied Science Nan Jia Michigan State University
Effect of crowd density, wind direction, and air temperature on the formation of individual human breathing zones in a semi-outdoor environment
人群密度、风向和空气温度对处于半露天环境中的个体呼吸区所造成的影响
This paper presents a comprehensive numerical investigation to predict the human breathing zones (BZs) in crowded semi-outdoor environments. The computational domain consisted of a nine-human block array with integrated nasal cavities subjected to the lower part of the atmospheric boundary layer. Five crowding levels, seven wind directions, and inflow ambient air temperatures (ranging from 10 to 31 °C) were tested to examine the horizontal and vertical formations of the BZs. Validation and verification tests were performed through comparisons with experimental results, a grid independence test, and an evaluation of various randomized distribution scenarios to minimize the uncertainties of the computational fluid dynamics analyses. The horizontal extension of the BZs tripled as the crowding level increased from 0.325 to 4.0 m2/capita. However, the lateral extension was insensitive and remained within 10 cm of the nostrils. Human models can inhale air close to the cheek, neck, and shoulders when an oblique flow is assumed. As the air temperature increased, individuals tended to inhale air from the upper regions, which was influenced by the interrelated thermal properties of the human body. Consequently, under high-temperature conditions, there may be an increased probability of gas-phase contaminant inhalation over greater horizontal distances.本文展示了一项全面的数值研究，以预测拥挤的半露天环境中的人体呼吸区（BZs）。计算域包括一个包含九个人体的阵列，具有整合的鼻腔，受大气边界层下部的影响。通过测试五种拥挤水平、七种风向和流入环境空气温度（范围从10到31°C），来检验BZs的水平和垂直形成。通过与实验结果的比较、网格独立性测试以及评估各种随机分布情景来验证和验证测试，以减小计算流体动力学分析的不确定性。随着拥挤水平从0.325增加到4.0 m2/人，BZs的水平延伸增加了三倍。然而，横向延伸不敏感，保持在距离鼻孔约10厘米内。当假定为斜流时，人体模型可以吸入靠近脸颊、颈部和肩膀的空气。随着空气温度的增加，个体倾向于从上部地区吸入空气，这受到人体热性质的相互影响。因此，在高温条件下，可能会增加气态污染物在更大水平距离上的吸入概率。https://doi.org/10.1016/j.scs.2024.105274Islam.M.S.Abouelhamd Kyushu University KazukiKuga Kyushu UniversitySung-JunYoo Kyushu UniversityKazuhideIto Asyut University
Assessing and mapping urban ecological resilience using the loss-gain approach: A case study of Tehran, Iran
利用损益方法评估和绘制城市生态韧性：以伊朗德黑兰为例
In the face of growing urban populations and their increasing demand for land and natural resources, the assessment of urban ecological resilience has emerged as an imperative aspect of sustainable urban governance. This study introduces an assessment framework with the potential to substantially augment urban management practices. It is focused on the formulation of a comprehensive framework for assessing ecological resilience, which is applied to Tehran, the capital of Iran. Our proposed Urban Ecological Resilience Mapping (UERM) framework adopts the Loss-Gain approach, encompassing both environmental risks and capacities related to Tehran's urban landscape. this framework incorporates an array of seven distinct indicators and twenty-five variables meticulously designed to gage the mettle of ecological resilience. The findings underscore that Tehran's central districts exhibit notably low ecological resilience, owing to high population density and the concentration of deteriorated and unstable areas. The localized nature of our assessment framework and its inherent ability to discern spatial dynamics and contributing factors to ecological resilience position it as an indispensable tool for informed urban planning and management decisions. the UERM framework not only facilitates the identification of areas requiring targeted interventions but also empowers urban stakeholders to foster a more resilient and sustainable urban landscape.面对不断增长的城市人口及其对土地和自然资源需求的增加，评估城市生态韧性已成为可持续城市治理的重要方面。本研究介绍了一个评估框架，具有潜力显著增强城市管理实践。重点是制定了一个全面的城市生态韧性评估框架，应用于伊朗首都德黑兰。我们提出的城市生态韧性制图（UERM）框架采用了损益方法，涵盖了德黑兰城市景观的环境风险和能力。该框架包含了七个不同的指标和二十五个变量，精心设计以评估生态韧性的能力。研究结果强调，德黑兰的中心区域表现出明显较低的生态韧性，这归因于高人口密度和恶化不稳定区域的集中。我们评估框架的局部化特性及其固有的区分空间动态和生态韧性贡献因素的能力，使其成为了具有不可或缺性的工具，用于明智的城市规划和管理决策。UERM框架不仅有助于确定需要有针对性干预的区域，而且使城市利益相关者能够促进更具韧性和可持续的城市景观。https://doi.org/10.1016/j.scs.2024.105252AliakbarShamsipour, University of TehranShayestehJahanshahi, University of TehranSeyed SajadMousavi, Municipality of TehranFaezeShoja, University of TehranRoghayehAnsari Golenji, University of TehranSafiyehTayebi, Rutgers the State University of New JerseySeyed AliAlavi, Department of Geography, KU Leuven, AyyoobSharifi, Tehran Sewerage Company
Evaluation of coal-resource-based cities transformation based on CRITIC-TOPSIS model
基于CRITIC-TOPSIS模型，评估煤炭资源的城市转型模式
The transformation of coal-resource-based cities (CRBCs) is one of the important aspect of sustainable development. However, little work has been done on the systematic study of CRBCs. Therefore, this paper constructs a comprehensive evaluation index system from three aspects of economy, society and environment to evaluate the level of transformation and development of 23 CRBCs in China from 2017 to 2021. The proposed model is a multi-criteria decision-making method based on the Criteria Importance Through Inter-criteria Correlation (CRITIC) and the improved Technique in Order of Preference by Similarity to Ideal Solution (TOPSIS). The results show that the comprehensive transformation effects of CRBCs range from 0.308 to 0.660. 13 cities (accounting for 56.5%) demonstrate a slowly growth trend, with the maximum annual growth rate of 1.05%. 10 cities (accounting for 43.5%) show a small downward trend on the comprehensive transformation effect. The main reason for the low transformation is that social development lag behind environmental and economic development. Based on this, provide some suggestions for the transformation of CRBCs.煤炭资源型城市（CRBCs）的转型是可持续发展的重要方面之一。然而，对CRBCs的系统研究工作较少。因此，本文从经济、社会和环境三个方面构建了一个综合评价指标体系，评估了中国23个CRBCs在2017年至2021年间的转型和发展水平。所提出的模型是基于CRITIC（Criteria Importance Through Inter-criteria Correlation）和改进的TOPSIS（Technique in Order of Preference by Similarity to Ideal Solution）的多标准决策方法。结果表明，CRBCs的综合转型效果范围从0.308到0.660不等。13个城市（占56.5%）呈现出缓慢增长趋势，最大年增长率为1.05%。10个城市（占43.5%）的综合转型效果呈现小幅下降趋势。低转型的主要原因是社会发展落后于环境和经济发展。基于此，本文为CRBCs的转型提供了一些建议。https://doi.org/10.1016/j.scs.2024.105271
Assessing Nature-based solutions in the face of urban vulnerabilities: A multi-criteria decision approach
基于自然属性的解决城市脆弱性的方案：一种多标准决策方法Nature-based solutions (NBS) are increasingly employed to address urban challenges. Typically, NBS planning emphasizes environmental impacts and ecosystem services, often overlooking their role in addressing vulnerabilities. Our objective is to develop a framework assessing the extent to which NBS alter urban vulnerabilities. For this, we relate ecosystem service and urban metabolism analyses to spatially explicit vulnerabilities. The framework relies on multi-criteria decision analysis to integrate diverse impacts. It follows a stepwise approach including the development of land-use scenarios, selection of vulnerabilities and indicators, normalization and aggregation of indicators, and stakeholder weighting. We apply the framework to the Metropolitan Area of Barcelona to assess the impacts of increasing (peri‑)urban agriculture in terms of critical vulnerabilities: heat, lack of recreational space, biodiversity loss, and lack of local food. Results show that agricultural expansion decreased the vulnerability of lack of local food, increased the vulnerability of biodiversity loss, and increased the heat vulnerability in terms of night temperatures for sensitive areas. Results reveal diverse spatial outcomes and trade-offs in urban vulnerabilities due to shifts in (peri‑)urban agriculture. The framework innovatively evaluates NBS impacts by linking multiple evaluation methods through spatially explicit vulnerabilities, fostering the strategic planning of NBS at the urban metropolitan scale.面对城市挑战，越来越多地采用基于自然的解决方案（NBS）。通常，NBS规划强调环境影响和生态系统服务，往往忽视了它们在应对脆弱性方面的作用。我们的目标是开发一个框架，评估NBS在改变城市脆弱性方面的程度。为此，我们将生态系统服务和城市新陈代谢分析与具有空间明确性的脆弱性联系起来。该框架依赖于多准则决策分析，以整合不同的影响。它遵循一个分步方法，包括土地利用情景的制定、脆弱性和指标的选择、指标的标准化和聚合，以及利益相关者的权重确定。我们将该框架应用于巴塞罗那大都会区，评估增加（近）城市农业对关键脆弱性的影响：热量、缺乏娱乐空间、生物多样性丧失和缺乏当地食物。结果显示，农业扩张降低了缺乏当地食物的脆弱性，增加了生物多样性丧失的脆弱性，并增加了对敏感地区夜间温度的热量脆弱性。结果显示，由于（城郊）城市农业的转变，城市脆弱性出现了不同的空间结果和权衡。该框架通过将多种评估方法与具有空间明确性的脆弱性联系起来，创新地评估了NBS的影响，促进了在都市大都会尺度上的NBS战略规划。https://doi.org/10.1016/j.scs.2024.105257DavidCamacho-Caballero, Universitat Autònoma de Barcelona (UAB)JohannesLangemeyer, Universitat Autònoma de Barcelona (UAB)RicardSegura-Barrero, Universitat Autònoma de Barcelona (UAB)SergiVentura, Universitat Autònoma de Barcelona (UAB)Angelica MendozaBeltran, Universitat Autònoma de Barcelona (UAB)GaraVillalba, Universitat Autònoma de Barcelona (UAB)
Accessing eye-level greenness visibility from open-source street view images: A methodological development and implementation in multi-city and multi-country contexts
从开源街景图像中获取人视角度的绿色能见度：在多城市和多国家背景下方法论的发展与实践
The urban natural environment provides numerous benefits, including augmenting the aesthetic appeal of urban landscapes and improving mental well-being. While diverse methods have been used to evaluate urban greenery, the assessment of eye-level greenness visibility using street-view level images is emerging due to its greater compatibility with human perception. Many existing studies predominantly rely on proprietary street view images provider such as Google Street View (GSV) data; the usage restrictions and lack of alignment with FAIR (Findability,Accessibility, Interoperability, and Reusability) principles present challenges in using proprietary images at scale. Therefore, incorporating Volunteered Street View Imagery (VSVI) platforms, such as Mapillary, is emerging as a promising alternative. In this study, we present a scalable and reproducible methodological framework for utilising Mapillary images for Green View Index (GVI) assessment using image segmentation approach and evaluate the completeness and usefulness of such data in diverse geographical contexts, including eleven cities (i.e., Amsterdam, Barcelona, Buenos Aires, City of Melbourne, Dhaka, Ho Chi Minh, Kampala, Kobe, Mexico City, Seattle, and Tel Aviv). We also evaluate the use of globally available satellite-based vegetation indices (e.g., Normalised Difference Vegetation Index-NDVI) to estimate GVI in locations where street-view images are unavailable. Our approach demonstrates the applicability of Mapillary data for GVI assessments, although revelling considerable disparities in image availability and usability between cities located in developed and developing countries. We also identified that the NDVI could be used effectively to estimate GVI values in locations where direct street-level imagery is limited. Additionally, the analysis reveals notable differences in greenness visibility across cities, particularly in high-density, lower-income cities in Africa and South Asia, compared to low-density, high-income cities in the USA and Europe.开发和实施基于开源街景图像的眼睛水平绿色能见度评估：在多城市和多国家背景下的方法学发展。城市自然环境提供了众多好处，包括增强城市景观的美感和改善心理健康。尽管已经使用了多种方法来评估城市绿化情况，但使用街景级别图像评估眼睛水平的绿色能见度正在兴起，因为它与人类感知更加兼容。许多现有研究主要依赖于专有的街景图像提供商，如Google Street View（GSV）数据；使用专有图像在规模上存在使用限制和与FAIR（可发现性、可访问性、互操作性和可重用性）原则不符的挑战。因此，将志愿街景图像（VSVI）平台，如Mapillary，纳入其中作为一种有希望的替代方法正在兴起。在本研究中，我们提出了一个可扩展和可重复的方法框架，利用Mapillary图像进行绿色视图指数（GVI）评估，采用图像分割方法，并评估了这些数据在包括阿姆斯特丹、巴塞罗那、布宜诺斯艾利斯、墨尔本市、达卡、胡志明市、坎帕拉、神户、墨西哥城、西雅图和特拉维夫在内的多个城市的不同地理背景下的完整性和实用性。我们还评估了在街景图像不可用的地点使用全球可用的卫星植被指数（例如，归一化差异植被指数-NDVI）来估算GVI的可行性。我们的方法表明了Mapillary数据在GVI评估中的适用性，尽管在发达国家和发展中国家的城市之间，图像可用性和可用性之间存在相当大的差异。我们还确定，NDVI可以有效地用于在直接街景图像有限的地点估算GVI值。此外，分析显示，在不同城市之间存在明显的绿色能见度差异，尤其是在非洲和南亚的高密度、低收入城市与美国和欧洲的低密度、高收入城市相比。https://doi.org/10.1016/j.scs.2024.105262Ilse Abril VázquezSánchez, Utrecht UniversityS.M.Labib, Utrecht University
Data-Driven hierarchical energy management in multi-integrated energy systems considering integrated demand response programs and energy storage system participation based on MADRL approach
基于MADRL方法，考虑综合需求响应方案和能量存储系统参与，探究多集成能源系统的数据驱动分层能源管理模式
In this study, an intelligent and data-driven hierarchical energy management approach considering the optimal participation of renewable energy resources (RER), energy storage systems (ESSs) and the integrated demand response (IDR) programs execution based on wholesale and retail market signals in the multi-integrated energy system (MIES) structure is presented. The proposed objective function is presented on four levels, which include minimizing operating costs, minimizing environmental pollution costs, minimizing risk costs, and reducing the destructive effects of cyberattacks such as false data injection (FDI). The proposed approach is implemented in the structure of the central controller and local controller and is based on the multi-agent deep reinforcement learning method (MADRL). The MADRL model is formulated based on the Markov decision process equations and solved by multi-agent soft actor-critic and deep Q-learning algorithms in two levels of offline training and online operation. The different scenario results show operation cost reduction equivalent to 19.51 %, risk cost equivalent to 19.69 %, cyber security cost equivalent to 24 %, and pollution cost equivalent to 20.24 %. The proposed approach has provided an important step in responding to smart cities challenges and requirements considering advantage of fast response, high accuracy and also reducing the computational time and burden.在本研究中，提出了一种智能和数据驱动的分层能源管理方法，考虑到在多集成能源系统（MIES）结构中根据批发和零售市场信号优化参与可再生能源资源（RER）、能量存储系统（ESSs）和综合需求响应（IDR）方案的执行。所提出的目标函数包括四个层次，包括最小化运营成本、最小化环境污染成本、最小化风险成本和减少虚假数据注入（FDI）等网络攻击的破坏性影响。所提出的方法在中央控制器和本地控制器的结构中实施，并基于多智能体深度强化学习方法（MADRL）。MADRL模型基于马尔可夫决策过程方程式建立，并通过两个级别的离线训练和在线运行来解决，采用多智能体软行为者-评论家和深度Q学习算法。不同的情景结果显示，该方法能够降低运营成本约19.51%，风险成本约19.69%，网络安全成本约24%，以及污染成本约20.24%。所提出的方法为响应智能城市的挑战和需求提供了重要的一步，具有快速响应、高准确性以及减少计算时间和负担的优势。https://doi.org/10.1016/j.scs.2024.105264AminKhodadadi, Islamic Azad University, SaraAdinehpour, Islamic Azad University, RezaSepehrzad, Politecnico di Milano UniversityAhmedAl-Durra, Khalifa UniversityAmjadAnvari-Moghaddam, Aalborg University
Agent-specific, activity-based noise impact assessment using noise exposure cost
使用噪声暴露成本对特定代理人及活动的噪声影响进行评估
This study introduces an agent-specific assessment method of traffic noise exposure in agent mobility simulations. The assessment is achieved through a combination of an energy-based noise exposure impact assessment using noise exposure cost, and the state-of-the-art traffic noise prediction tool NoiseModelling coupled with the activity-based agent mobility simulation software MATSim. The agent-specific noise exposure cost is a measure to evaluate how the noise emissions from the transport of agents relate to the noise-related impact on other agents performing stationary activities. By introducing an agent-specific level, each agent’s individual responsibility for the noise exposure may be estimated. The potential of the agent-specific noise exposure cost concept, combined with the MATSim-NoiseModelling framework, is illustrated through a case study, applying activity-based agent mobility simulations across Nantes, France. The results of the case study highlight, among other considerations, the insights that an agent-specific, activity-based noise exposure cost approach provides by visualizing the noise exposure ” footprint” resulting from an agent’s transportation activities.该研究介绍了一种基于代理人移动模拟的交通噪声暴露的代理人特定评估方法。通过结合基于能量的噪声暴露影响评估，使用噪声暴露成本，以及与最先进的交通噪声预测工具NoiseModelling耦合的基于活动的代理人移动模拟软件MATSim。代理人特定的噪声暴露成本是评估代理人运输所产生的噪声排放与对其他执行静止活动的代理人产生的噪声相关影响的一种衡量标准。通过引入代理人特定水平，可以估计每个代理人对噪声暴露的个人责任。代理人特定的噪声暴露成本概念与MATSim-NoiseModelling框架相结合的潜力通过一项案例研究进行了说明，该案例应用基于活动的代理人移动模拟跨越法国南特市。案例研究的结果突显了代理人特定的、基于活动的噪声暴露成本方法提供的见解，通过可视化代理人交通活动产生的噪声暴露“足迹”等因素。https://doi.org/10.1016/j.scs.2024.105278JohanNygren, KTH Royal Institute of TechnologyValentinLe Bescond, Université Gustave EiffelArnaudCan, Université Gustave EiffelPierreAumond, Université Gustave EiffelPascalGastineau, Université Gustave EiffelSusannBoij, KTH Royal Institute of TechnologyRomainRumpler, KTH Royal Institute of TechnologyCiarán J.O’Reilly, KTH Royal Institute of Technology
Nonlinear trade-off relationship and critical threshold between ecosystem services and climate resilience for sustainable urban development生态系统服务与气候韧性之间的非线性权衡关系和关键阈值，以促进可持续城市发展Metropolitan areas are faced with ecosystem degradation driven by rapid urbanization and climate change. Synergizing ecosystem services (ES) and ecosystem climate resilience (ECR) in ecological restoration programs is essential for sustainable urban and social development. However, it remains unclear whether there is a trade-off relationship between ECR and ES, particularly nonlinear relationships. Here, the Wuhan metropolitan area (WMA) was selected as the study area. First, the entropy theory was used to quantify ECR on multiple timescales using GPP time-series data. Then, the critical ECR timescales of different ES were detected using the GeoDetector model. Finally, restricted cubic spline regression was performed to reveal the nonlinear trade-off relationship and threshold effect between ECR and ES. The results showed that: (1) The critical ECR timescale is 20 years for water yield and grain production services, while one year for habitat quality, water purification, air purification, carbon sequestration, soil retention, and recreational services; (2) The short- and long-term ECR thresholds to ensure the synergistic growth of ECR with multiple ES are 0.38–0.47 and 0.445, respectively; (3) ESB dynamics and ECR thresholds can be integrated as a tool for climate-adaptation ecological restoration zoning.都市地区面临着由快速城市化和气候变化驱动的生态系统退化。在生态修复计划中协同生态系统服务（ES）和生态系统气候韧性（ECR）对于可持续城市和社会发展至关重要。然而，尚不清楚在ECR和ES之间是否存在权衡关系，尤其是非线性关系。本研究选择武汉都市圈作为研究区域。首先，利用GPP时间序列数据，运用熵理论量化了不同时间尺度上的ECR。然后，利用GeoDetector模型检测了不同ES的关键ECR时间尺度。最后，进行了限制性立方样条回归，揭示了ECR和ES之间的非线性权衡关系和阈值效应。结果表明：（1）水量和粮食生产服务的关键ECR时间尺度为20年，而栖息地质量、水净化、空气净化、碳封存、土壤保持和休闲服务的关键ECR时间尺度为一年；（2）确保多种ES与ECR协同增长的短期和长期ECR阈值分别为0.38–0.47和0.445；（3）ESB动态和ECR阈值可以作为气候适应性生态修复分区的工具整合。https://doi.org/10.1016/j.scs.2024.105253
Prevalent underestimation of tree cooling efficiency attributed to urban intrinsic heterogeneity
As cities worldwide grapple with the escalating challenges of extreme heat events, afforestation can serve as an effective adaptation measure to mitigate heat stress. This study presents a comprehensive nationwide assessment of urban tree-induced cooling effects and provides a more accurate and robust methodology that accounts for the influence of spatial heterogeneity within the complex urban environment. Results reveal that the conventional method for assessing cooling efficiency (TCE) is substantially influenced by urban heterogeneity, in terms of both horizontal and vertical structures. The revised tree cooling efficiency (RTCE), designed to minimize the impacts of other land cover types on surface temperature variations, was proved to be a more accurate estimation. In 362 out of 379 cities across China, TCE tended to underestimate the cooling effects as a result of spatial heterogeneity. The nationwide average disparity between RTCE and TCE was approximately 0.047±0.0145 ℃ per percent (95 % confidence interval). The largest differences were observed among high-rise environments, highlighting the undervalued heat mitigation potential of urban trees in compact and densely populated urban settings. This study emphasizes the considerable potential of urban tree-cooling effects in mitigating heat stress in the face of a warming planet.全球各地的城市面临着极端热事件不断加剧的挑战，造林可以作为一种有效的适应措施来减轻热应激。本研究对城市树木引起的降温效应进行了全国范围的综合评估，并提出了一种更准确、更健壮的方法，考虑了复杂城市环境中空间异质性的影响。结果显示，传统的评估降温效率（TCE）的方法受到城市异质性的显著影响，无论是在水平还是垂直结构上。修正后的树木降温效率（RTCE）旨在最小化其他土地覆盖类型对地表温度变化的影响，被证明是更准确的估算方法。在中国379个城市中，有362个城市的TCE往往低估了降温效果，这是由于空间异质性造成的。RTCE和TCE之间的全国平均差异约为0.047±0.0145摄氏度/百分比（95%置信区间）。在高层建筑环境中观察到了最大的差异，突显了在紧凑、人口密集的城市环境中城市树木降温潜力被低估的问题。本研究强调了城市树木降温效应在减轻全球变暖带来的热应激方面的巨大潜力。https://doi.org/10.1016/j.scs.2024.105277
Exploring the seasonal effects of urban morphology on land surface temperature in urban functional zones
Rapid urbanization intensifies the urban heat island (UHI) effect, leading to a multitude of urban challenges. It is important to conduct comprehensive research to understand the underlying mechanisms driving the UHI. Although previous studies have identified the significance of the effects of urban morphology on land surface temperature (LST), the variations in its effects on LST across seasons and different types of urban functional zone (UFZ) remains undefined. Therefore, we explored the seasonal effects of urban morphology, including landscape indicators, building morphology, and surface biophysical parameters, on LST in different types of UFZ by random forest (RF) regression model. Taking the central urban area of Guangzhou as an example, the results indicated that the impacts of urban morphology on LST were strongly dependent on the seasons and UFZs types. The effects of urban morphology on LST were similar across spring, autumn, and winter, with the building morphology showing substantial impacts in commercial and residential zones. In summer, the effects of surface biophysical parameters on LST were significant, especially in industrial, residential, and public service zones. In addition, warming and cooling factors varied across seasons and UFZs. Vegetation was the effective cooling factor during summer, with its fragmented and irregular distribution making a prominent cooling effect in commercial and residential zones, and its coverage crucial for reducing LST in industrial and public service zones. Building height was the dominant cooling factor in spring, autumn, and winter. We consider that these findings can enhance our understanding of the driving mechanism of UHI effect and offer precise references for urban planning in different seasons and UFZs to effectively mitigate the UHI effect.快速城市化加剧了城市热岛效应（UHI），导致了多种城市挑战。开展全面的研究以了解驱动UHI的潜在机制至关重要。尽管先前的研究已经确定了城市形态对地表温度（LST）的影响的重要性，但其在不同季节和不同类型的城市功能区（UFZ）中的影响变化仍然未定义。因此，我们通过随机森林（RF）回归模型，探讨了城市形态，包括景观指标、建筑形态和表面生物物理参数，对不同类型的UFZ中LST的季节影响。以广州市中心城区为例，结果表明城市形态对LST的影响在季节和UFZ类型上强烈依赖。城市形态对LST的影响在春季、秋季和冬季相似，其中建筑形态在商业区和住宅区具有显著影响。在夏季，表面生物物理参数对LST的影响显著，特别是在工业区、住宅区和公共服务区。此外，变暖和降温因素在季节和UFZ之间变化。植被在夏季是有效的降温因素，其分散和不规则分布在商业区和住宅区产生明显的降温效果，在工业区和公共服务区中的覆盖率对降低LST至关重要。建筑高度是春季、秋季和冬季的主导降温因素。我们认为这些发现可以增进我们对UHI效应的驱动机制的理解，并为不同季节和UFZ的城市规划提供精确的参考，以有效缓解UHI效应。https://doi.org/10.1016/j.scs.2024.105268
Solar accessibility in high latitudes urban environments: A methodological approach for street prioritization
高纬度城市环境中的日照覆盖度：街道优先级确定的方法论途径
Streets are the fundamental public space where people move and socialize within cities. Their attractiveness depends on a wide variety of factors, with solar accessibility emerging as crucial in cold climates to guarantee thermal comfort and stimulate the presence of people. This article presents a methodological approach to evaluate and prioritize streets based on solar accessibility in high latitude urban environments (Trondheim, Norway). For this purpose, two novel solar indices, based on hours of direct sunlight and solar irradiation metrics, are introduced, while a calibrated pedestrian model is applied to prioritize streets for solar accessibility based on high predicted pedestrian flows. The results highlight generally favorable solar accessibility in the summer and over the entire year, especially for streets with high predicted pedestrian flows. Urban morphology variables (i.e., street width and building height) impact solar accessibility during mid-season, whereas tree coverage has a significant effect during summer. The presented approach provides public authorities and urban planners with a descriptive and prescriptive planning instrument to prioritize streets for adequate solar accessibility. Moreover, the findings of this study can support the development of urban regulations, policies, and strategies (e.g., street profile changes, management of trees, demolitions, and use of reflective materials) aiming at conserving and restoring solar accessibility in outdoor public spaces over extensive urban areas.高纬度城市环境中的日照覆盖度对保障热舒适度并促进人们活动的重要性日益凸显，而街道是城市中人们移动和社交的基本公共空间。本文提出了一种评估和确定街道日照覆盖度的方法论途径，以挪威特隆赫姆（Trondheim）为例。为此，引入了两个新颖的太阳指标，基于直接阳光照射时间和太阳辐射指标，同时采用校准的行人模型，根据高预测行人流量确定街道的日照覆盖度优先级。结果表明，夏季和整个年份的日照覆盖度普遍良好，特别是对于预测行人流量较高的街道。城市形态变量（例如街道宽度和建筑高度）在中间季节影响太阳可及性，而树木覆盖在夏季具有显著影响。该方法提供了一个描述性和规范性的规划工具，供公共管理机构和城市规划者优先考虑街道的日照覆盖度。此外，本研究的发现可以支持城市规章、政策和战略的制定（例如改变街道剖面、树木管理、拆除和使用反射材料等），旨在保护和恢复室外公共空间的日照覆盖度，覆盖广泛的城市区域。https://doi.org/10.1016/j.scs.2024.105263MatteoFormolli， Norwegian University of Science and Technology NTNUPeterSchön Norwegian University of Science and Technology NTNUTommyKleiven Norwegian University of Science and Technology NTNUGabrieleLobaccaro Norwegian University of Science and Technology NTNU
Exploring the impacts of heterogeneity and stochasticity in air-conditioning behavior on urban building energy models
探讨人工制冷行为中的异质性和随机性对城市建筑能源模型的影响
Heterogeneity and stochasticity, two main aspects of uncertainty in occupant behavior (OB), at the urban scale are not featured in most current urban building energy modeling (UBEM) platforms, and their respective impacts on urban-scale building energy consumption remain unclear. We aimed to introduce OB uncertainty into the UBEM workflow and assess the differences in the impacts of heterogeneity and stochasticity on cooling demand. Different OB models were integrated into the cooling demand simulation of residential building stocks, considering the heterogeneity and stochasticity in both occupancy and energy-use behavior. The impacts of heterogeneity and stochasticity on urban-scale cooling demand and its applications for different purposes in UBEM are discussed. We found that stochasticity in occupancy decreased the peak cooling demand by 54%, whereas the uncertainty in air-conditioning (AC) behavior had little effect. Heterogeneity is the main reason for the diversity in cooling demand, whereas stochasticity better reflects the dynamics of cooling demand., which Occupancy and AC behavior models with higher fidelity are required to obtain results with higher spatial or temporal resolution should be selected according to the UBEM applications. The proposed approach will contribute to the development of appropriate urban-scale occupant behavior models and bridge urban mobility with occupant-centric UBEMs.研究表明，城市尺度上的占用者行为（OB）的异质性和随机性是不确定性的两个主要方面，在大多数当前的城市建筑能源建模（UBEM）平台中并未得到充分考虑，它们对城市尺度建筑能源消耗的影响尚不清楚。我们旨在将OB不确定性引入UBEM工作流程，并评估异质性和随机性对制冷需求的影响差异。不同的OB模型被整合到住宅建筑库的制冷需求模拟中，考虑了占用和能源使用行为中的异质性和随机性。讨论了异质性和随机性对城市尺度制冷需求的影响以及其在UBEM中不同应用目的中的应用。我们发现，占用的随机性会使峰值制冷需求降低54%，而人工智能（AC）行为的不确定性影响较小。异质性是制冷需求差异性的主要原因，而随机性更好地反映了制冷需求的动态性。根据UBEM的不同应用目的，应选择具有较高逼真度的占用和AC行为模型以获得更高的空间或时间分辨率的结果。该方法有助于发展适当的城市尺度占用者行为模型，并将城市流动与以居民为中心的UBEM相结合。https://doi.org/10.1016/j.scs.2024.105285
A novel entropy-based method for quantifying urban energy demand aggregation: Implications for urban planning and policy
基于一种新颖的熵，量化城市能源需求的聚合：探讨其对城市规划和政策的影响
Urban energy demand aggregation (UEDA) is a key aspect of urban sustainability, as it can help to improve the energy efficiency of urban systems and reduce their environmental impacts. However, UEDA is a challenging task, as it involves aggregating heterogeneous and diverse energy demands of individual buildings into a collective demand at a given spatial scale. This paper proposes a novel entropy-based method for UEDA that quantifies the information loss or distortion resulting from this aggregation process. The method also identifies the optimal spatial scale for UEDA that minimizes information loss or distortion, and evaluates the quality and reliability of UEDA results using entropy-based metrics. We apply the method to a case study of Chicago, where we estimate and analyze the energy demand of buildings at 10 spatial scales, ranging from 1.5 km to 15 km, and for different types of energy sources. We calculate the entropy for each spatial scale and energy source, and compare it with building characteristics and ZIP codes. We also assess the quality and reliability of UEDA results using entropy-based metrics, such as information gain ratio and normalized mutual information. Our results show that different spatial scales reveal different patterns and relationships of energy demand, and that choosing an appropriate scale can enhance the accuracy and efficiency of UEDA. Our results also show that there is an optimal spatial scale for UEDA that balances information preservation and reduction, and that this scale may vary depending on the type of energy source and the urban context. Our findings contribute to the field of UEDA and urban sustainability by developing a novel perspective on urban energy dynamics, revealing the complexity and diversity of urban systems, such as population, land use, transportation, and energy demand.城市能源需求聚合（UEDA）是城市可持续性的关键方面，因为它有助于提高城市系统的能源效率并减少其对环境的影响。然而，UEDA是一项具有挑战性的任务，因为它涉及将个体建筑物的异质性和多样化的能源需求聚合到给定空间尺度上的集体需求中。本文提出了一种基于熵的新方法，用于UEDA，该方法量化了由于这一聚合过程而导致的信息损失或失真。该方法还确定了UEDA的最佳空间尺度，以最小化信息损失或失真，并使用基于熵的指标评估UEDA结果的质量和可靠性。我们将该方法应用于芝加哥的案例研究，估算并分析了10个不同空间尺度（从1.5公里到15公里）以及不同能源类型的建筑物能源需求。我们计算了每个空间尺度和能源类型的熵，并将其与建筑特征和邮政编码进行了比较。我们还使用基于熵的指标（如信息增益比和归一化互信息）评估了UEDA结果的质量和可靠性。我们的结果显示，不同的空间尺度揭示了不同的能源需求模式和关系，选择适当的尺度可以提高UEDA的准确性和效率。我们的结果还表明，UEDA存在一个平衡信息保留和减少的最佳空间尺度，这个尺度可能会根据能源类型和城市环境的不同而变化。我们的研究结果为UEDA和城市可持续性领域提供了新的视角，揭示了城市系统的复杂性和多样性，例如人口、土地利用、交通和能源需求。https://doi.org/10.1016/j.scs.2024.105284
Household energy vulnerability evaluation in southern Spain through parametric energy simulation models and socio-economic data
探讨通过参数化能源模拟模型和社会经济数据完成西班牙南部的家庭能源脆弱性评估
When proposing the most suitable strategies for retrofitting the residential stock it is essential to consider energy vulnerability, the current state of stock, users’ economic capacity and climate. This work analyses energy vulnerability on regional and neighborhood scale, applied to the social housing stock in southern Spain. Three key vulnerability indicators are assessed through extensive public databases and validated parametric energy simulation models: 1) buildings energy performance, based on simulated indoor thermal comfort; 2) users’ socio-economic vulnerability, based on their income levels; and 3) climate influence, implementing future climate data into the simulations. The different energy vulnerability levels identified in the research are of great interest for retrofitting the existing stock as they help establish priority action guidelines. It is concluded that social housing in Andalusia currently exhibits a noticeable level of energy vulnerability in winter, with a greater severity of undercooling compared to overheating. In 2050, overheating in summer will significantly worsen, generally surpassing cooling. Despite of the Mediterranean climate, there are noticeable comfort differences between the cities analysed, with Cordoba and Granada being particularly relevant. Finally, a worse thermal performance in winter of the H-block typology was observed, which in summer occur for the linear block buildings.在提出最适合的住宅存量改造策略时，考虑到能源脆弱性、存量的现状、用户的经济能力和气候是至关重要的。本研究分析了南部西班牙社会住房存量的区域和社区规模的能源脆弱性。通过广泛的公共数据库和经过验证的参数化能源模拟模型，评估了三个关键的脆弱性指标：1）建筑能源性能，基于模拟的室内热舒适度；2）用户的社会经济脆弱性，基于他们的收入水平；以及3）气候影响，将未来的气候数据纳入到模拟中。研究确定的不同能源脆弱性水平对于改造现有存量具有很大的意义，因为它们有助于建立优先行动指南。研究得出的结论是，安达卢西亚的社会住房目前在冬季表现出明显的能源脆弱性，低温情况比过热情况更为严重。到2050年，夏季过热情况将显著恶化，通常会超过降温情况。尽管地中海气候，但在分析的城市之间存在明显的舒适度差异，科尔多瓦和格拉纳达尤其引人关注。最后，观察到H型建筑在冬季的热性能较差，在夏季，线性建筑的热性能较差。https://doi.org/10.1016/j.scs.2024.105276Carmen MaríaCalama-González Universidad de SevillaRocíoEscandón Universidad de SevillaRafaelSuárez Universidad de SevillaRafaelSuárez Universidad de SevillaÁngel LuisLeón-Rodríguez Universidad de Sevilla
Unraveling the dynamics of the cyber threat landscape: Major shifts examined through the recent societal events
揭示网络威胁格局动态：通过最近的社会实践研究其主要变化
The continuous expansion of cyberspace offers numerous advantages but also broadens the cybersecurity attack surface, thereby affecting the resilience of critical infrastructure and societal systems. Given the complexity of factors affecting cybersecurity, a data-centric approach is needed, which involves leveraging existing datasets on cyber incidents and utilizing advanced data analytics techniques for enhanced preparedness against evolving cyber threats. In this study, we optimize past cyberattack data for statistical analysis and introduce a methodology for detecting significant shifts in cyberattack patterns through intervention analysis. By applying this approach, we correlate major shifts in the cyber threat landscape over the past six years with critical societal events like COVID-19 and the Russia–Ukraine War, offering insights meaningful for both society and policy formulation. 网络空间不断扩展，带来了许多优势，但也扩大了网络安全攻击面，从而影响了关键基础设施和社会系统的韧性。鉴于影响网络安全的因素复杂，需要采用数据为中心的方法，利用现有的网络事件数据集，并利用先进的数据分析技术，增强对不断演变的网络威胁的准备。在这项研究中，我们优化了过去的网络攻击数据进行统计分析，并引入了一种通过干预分析检测网络攻击模式中重大变化的方法。通过应用这种方法，我们将过去六年来网络威胁格局中的重大变化与COVID-19和俄罗斯-乌克兰战争等重大社会事件相关联，为社会和政策制定提供有意义的见解。https://doi.org/10.1016/j.scs.2024.105265UihyeonSong Korea UniversityGiminHur Korea UniversitySangjinLee Korea UniversityJungheumPark Korea University
Modeling NO2concentrations in real urban areas using computational fluid dynamics: A comparative analysis of methods to assess NO2 concentrations from NOx dispersion results
利用计算流体动力学模型（CFD）模拟真实城市区域中的二氧化氮（NO2）浓度：从NOx分散结果评估NO2浓度的比较分析方法Major cities worldwide constantly deal with health hazards caused by air pollution. Modeling this pollution on an urban scale is essential for assessing the impact of local policies and promoting sustainable urban development. However, there are practical difficulties when using microscale modeling in applied context, and particularly for nitrogen dioxide modeling (NO2). In this study, a Computational Fluid Dynamics (CFD) model was employed to assess monthly NO2concentrations in Antwerp, Belgium, and the results were compared to a one-month measurement campaign using 73 passive samplers. The result showed that using CFD with conventional assumption – such as neutral atmospheric stability consideration and using a turbulent Schmidt number (Sct) set to 0.7 – yield satisfying results according to air quality model acceptance criteria. Optimal outcomes were achieved by considering NO2 background concentration instead of NOx and employing Bachlin et al.’s empirical function to convert modeled NOx concentrations to NO2, dismissing the need for straightforward chemical mechanisms – such as photostationary steady-state equilibrium (PSS) –, or more expensive models in terms of computing resources. This approach yielded an overall error of less than 15 % and a correlation coefficient R of 0.78, affirming its effectiveness in modeling NO2 air quality in applied context.主要城市在全球范围内不断应对由空气污染引起的健康风险。在城市规模上建模这种污染对于评估地方政策影响和促进可持续城市发展至关重要。然而，在应用环境中使用微观尺度建模时存在实际困难，特别是对于二氧化氮（NO2）建模。在这项研究中，采用了计算流体动力学（CFD）模型来评估比利时安特卫普市的月平均NO2浓度，并将结果与一次为期一个月的使用了73个被动式采样器的测量活动进行了比较。结果表明，使用CFD模型与传统假设（如考虑中性大气稳定性和将湍流施密特数（Sct）设定为0.7）产生了令人满意的结果，符合空气质量模型接受标准。通过考虑NO2的背景浓度而不是NOx，并采用Bachlin等人的经验函数将模拟的NOx浓度转换为NO2，可以获得最佳结果，从而摒弃了对于简单的化学机制（如光稳态平衡（PSS））或在计算资源方面更昂贵的模型的需求。这种方法产生的总体误差小于15％，相关系数R为0.78，证实了它在应用环境中建模NO2空气质量的有效性。https://doi.org/10.1016/j.scs.2024.105286NicolasReiminger AIR&D, 32 rue Wimpheling, Strasbourg F-67000, FranceXavierJurado AIR&D, 32 rue Wimpheling, Strasbourg F-67000, FranceLoïcMaurer CNRS, ENGEES, ICube UMR 7357, Département Mécanique, Université de StrasbourgJoséVazquez CNRS, ENGEES, ICube UMR 7357, Département Mécanique, Université de StrasbourgCédricWemmert ICube Laboratory, UMR 7357, CNRS/University of Strasbourg
Spatiotemporal interactions and influencing factors for carbon emission efficiency of cities in the Yangtze River Economic Belt, China
长江经济带城市碳排放效率的时空相互作用和影响因素
Exploring the spatiotemporal evolution and influencing factors of carbon emission efficiency (CEE) is crucial for achieving the goal of urban carbon neutrality. However, most of the existing studies ignore the temporal dependence of the spatial pattern evolution of CEE and the scale variability of the factors influencing CEE. With the help of an exploratory spatiotemporal data analysis framework, this paper examined the spatiotemporal interactions of CEE across 110 cities in the Yangtze River Economic Belt (YREB). In addition, a multiscale geographically weighted regression model was employed to reveal the scale effects of influencing factors on CEE. The main conclusions are as follows: first, the CEE of cities in the YREB shows a fluctuating upward trend, but the overall level is still low, and a certain polarization phenomenon exists. Second, the spatial pattern of the CEE of cities in the YREB is generally relatively stable, with strong spatial integration and path dependence. Finally, the factors influencing CEE exhibit obvious scale variability and spatial heterogeneity. Our findings can provide a basis for localized and differentiated carbon emission reduction decision-making at the city level, as well as new insights for the formulation of sustainable urban spatial planning and low-carbon development strategies.探索碳排放效率（CEE）的时空演变和影响因素对于实现城市碳中和的目标至关重要。然而，大多数现有研究忽略了CEE空间格局演变的时间依赖性以及影响CEE的因素的尺度变异性。本文利用探索性时空数据分析框架，考察了长江经济带（YREB）110个城市的CEE的时空相互作用。此外，采用多尺度地理加权回归模型揭示了影响CEE的因素的尺度效应。主要结论如下：首先，长江经济带城市的CEE呈波动上升趋势，但整体水平仍然较低，并存在一定的极化现象。其次，长江经济带城市CEE的空间格局通常相对稳定，具有较强的空间一体化和路径依赖性。最后，影响CEE的因素表现出明显的尺度变异性和空间异质性。我们的研究结果可以为城市层面的本地化和差异化碳排放减少决策提供依据，同时为制定可持续城市空间规划和低碳发展战略提供新的见解。https://doi.org/10.1016/j.scs.2024.105248
Cost-effective sensor placement optimization for large-scale urban sewage surveillance
Early pandemic outbreak detection in cities is a crucial but challenging task. Complementary to the costly massive individual testing, urban sewage surveillance offers a rare, cost-effective solution for large-scale monitoring of pandemic spread in cities with minimal interference to people’s lives. One emerging question is how to derive a cost-effective sensor placement plan in city-scale sewage networks having complicated topologies. Inspired by remote sensing, we first provide a general multi-objective formulation of the optimal sensor placement problem on directed networks. Then, we introduce a connectivity-based objective evaluation approach and embed it into an NSGA-II algorithm to enable efficient optimization on large-scale directed graphs. The effectiveness of the proposed method is verified on a real-world sewage network in Hong Kong serving more than 500,000 urban residents. Results show that the proposed method efficiently generated optimal sensor placement plans on city-scale networks. Optimized sensor placement plans outperformed human placement heuristics by a significant margin of 102%, highlighting the necessity for data-driven decision support for large-scale urban sensing. Methodologically, this study provides a benchmark problem and datasets for network-based spatial optimization studies. Codes and datasets developed in this study are open-sourced to support future research in a real-world scenario.在城市中及早检测疫情爆发是一项至关重要但具有挑战性的任务。作为对昂贵的大规模个体检测的补充，城市污水监测提供了一种稀有且经济有效的解决方案，可以对城市中的疫情传播进行大规模监测，同时对人们的生活干扰较小。一个新兴的问题是如何在具有复杂拓扑结构的城市污水网络中制定成本效益的传感器布置计划。受遥感启发，我们首先提出了在定向网络上的最优传感器布置问题的一般多目标公式。然后，我们介绍了一种基于连通性的客观评估方法，并将其嵌入到NSGA-II算法中，以实现对大规模定向图的高效优化。该方法的有效性在服务超过50万城市居民的香港实际污水网络上得到了验证。结果显示，所提出的方法有效地生成了城市规模网络上的最优传感器布置计划。优化后的传感器布置计划比人类布置启发式方法的性能提高了102％的显著幅度，突出了对大规模城市感知的数据驱动决策支持的必要性。在方法学上，本研究为基于网络的空间优化研究提供了一个基准问题和数据集。本研究开发的代码和数据集是开源的，以支持未来在实际场景中的研究。https://doi.org/10.1016/j.scs.2024.105250Ke Xu University of California,
Compatibility of integrated physical barriers and personal exhaust ventilation with air distribution systems to mitigate airborne infection risk
集成物理隔离和个人排气通风与空气分配系统的兼容性，以减轻空气传播感染风险
This study investigated the effectiveness of integrating desk partitions and personal exhaust ventilation to mitigate airborne infection risks in areas where people sit closely together. Experiments were conducted in a test chamber equipped with different air distribution systems, including two different mixing and one displacement ventilation. N2O tracer gas was utilized to study airborne transmission between occupants. Results showed effectiveness of preventive measures varied depending on air distributions. In the absence of preventive measures, mixing ventilation systems exhibited higher infection risk compared to displacement ventilation. After the introduction of physical barriers, N2O concentration increased at two measurement points in presence of one of the mixing ventilation systems. In contrast, the other mixing ventilation and displacement ventilation showed a reduction in N2O concentration, up to 63 % and 43 %, respectively, depending on measurement points. Combination of physical barriers and personal exhaust ventilation consistently reduced N2O concentration by 34 % to 83 %, depending on measurement point's location and type of air distribution. Furthermore, higher airflow rates of personal exhaust increased efficiency of proposed strategy in limiting infection risk. This study supports employing physical barriers and personal exhaust ventilation to reduce airborne infection risks. Tailoring preventive measures to specific air distribution system is crucial.这项研究调查了将桌面隔断和个人排气通风集成起来，以减轻人们密集坐在一起的区域中空气传播感染风险的有效性。实验在一个配备了不同空气分配系统的测试室中进行，包括两种不同的混合通风和一种置换通风。使用N2O示踪气体研究了居民之间的空气传播。结果显示，预防措施的有效性因空气分配方式而异。在没有预防措施的情况下，混合通风系统的感染风险比置换通风系统高。在引入物理障碍物后，在一种混合通风系统的情况下，两个测量点的N2O浓度增加。相反，另一种混合通风和置换通风显示出N2O浓度的降低，分别取决于测量点的不同，分别为63％和43％。物理障碍物和个人排气通风的组合一致性地降低了N2O浓度，降低范围为34％至83％，具体取决于测量点的位置和空气分配类型。此外，个人排气的更高风量增加了所提出策略限制感染风险的效率。这项研究支持采用物理障碍物和个人排气通风来降低空气传播感染风险。将预防措施量身定制到特定的空气分配系统是至关重要的。https://doi.org/10.1016/j.scs.2024.105282SeyedkeivanNateghi Silesian University of Technology JanKaczmarczyk Silesian University of Technology
Smart city solutions: Comparative analysis of waste management models in IoT-enabled environments using multiagent simulation
智慧城市解决方案：利用多Agent模拟对物联网环境中的垃圾管理模型进行比较分析
Effective waste management arises as a crucial challenge for smart city development in the current era of rapid urbanization, shifting towards sustainability and public health. Harnessing modern technologies, especially the integration of the Internet of Things (IoT) with intelligent waste bins, can revolutionize urban waste collection, optimizing efficiency and reducing costs. This paper delves into a multiagent simulation-based framework for understanding and assessing the dynamics of an IoT-enabled smart waste management system. Initiating with the intricate process of garbage generation, we shift our focus to the real-time monitoring capabilities of IoT-connected waste bins. The study further explores protocols to regulate bin status, along with timing mechanisms to trigger garbage collection rounds. Subsequently, a predictive routing system is introduced to determine the most efficient garbage collection routes. For the bins’ filled level tracking, the ultrasonic sensors are commonly used that send out sound waves and track their echo return time, whereas weight sensors measure the garbage load in the bin, providing insights into waste production trends. For data transmission from bins to the central system, various communication technologies such as Wi-Fi, cellular networks, and long-distance networks are considered. Through a simulation, we contrast the innovative IoT-enabled sensor-based collection mechanism against the conventional periodic review strategy. Field experiments at the Al Rayyan locale, proximate to Doha, Qatar, facilitate the model demonstration. By leveraging region-specific data, we simulated various aspects including economic factors, environmental impact, public satisfaction, and operational efficiencies. The findings indicate that with an average daily garbage generation of 1.3 kg per individual, the sensor-driven mechanism remarkably outperforms the periodic review approach by covering fewer distances with fewer trucks, while concurrently achieving the key objectives of cost-efficiency, environmental preservation, public satisfaction, and reduced employee workload. This research contributes to the developing field of smart city technology by providing critical insights for urban planners, policymakers, and technologists attempting to build more sustainable, efficiennt, and livable cities.高效的垃圾管理已成为当前快速城市化、向可持续发展和公共卫生转变的智慧城市发展面临的关键挑战。利用现代技术，特别是将物联网（IoT）与智能垃圾箱相结合，可以革新城市垃圾收集，优化效率并降低成本。本文深入研究了基于多Agent模拟的物联网智能垃圾管理系统的动态和评估框架。从垃圾产生的复杂过程开始，我们将焦点转向了物联网连接的智能垃圾箱的实时监测能力。研究进一步探讨了规范垃圾箱状态的协议，以及触发垃圾收集巡回的定时机制。随后，引入了一个预测路由系统，以确定最高效的垃圾收集路线。对于垃圾箱的填充级别跟踪，通常使用超声波传感器，发送声波并跟踪它们的回声返回时间，而重量传感器则测量垃圾箱中的垃圾负载，提供垃圾生产趋势的见解。对于从垃圾箱到中央系统的数据传输，考虑了各种通信技术，如Wi-Fi、蜂窝网络和远程网络。通过模拟，我们将创新的物联网传感器驱动的收集机制与传统的定期检查策略进行了对比。位于卡塔尔多哈附近的阿尔雷扬地区的现场实验促进了模型的演示。通过利用区域特定数据，我们模拟了包括经济因素、环境影响、公众满意度和运营效率在内的各个方面。研究结果表明，平均每人每天产生1.3公斤的垃圾，传感器驱动的机制明显优于定期检查方法，通过更少的车辆覆盖更短的距离，同时实现了成本效益、环境保护、公众满意度和减少员工工作量的关键目标。这项研究为智慧城市技术领域的发展提供了关键见解，为试图建设更可持续、高效和宜居城市的城市规划者、政策制定者和技术专家提供了重要参考。https://doi.org/10.1016/j.scs.2024.105247Dr. IftikharHussain Heriot-Watt UniversityDr. AdelElomri Hamad Bin Khalifa University Dr. LaoucineKerbache Hamad Bin Khalifa UniversityDr. Abdelfatteh ElOmri Hamad Medical Corporation
Unveiling fine-scale urban third places for remote work using mobile phone big data
利用手机大数据打造精细化城市远程办公第三空间
Third places offer a creative alternative for both work from traditional office and home, which are becoming increasingly popular. Previous studies primarily focused on qualitative analyses and survey investigations, lacking quantitative studies exploring remote work in third places. In this study, we proposed a quantitative approach to identify and characterize the fine-scale third places for remote work, with the application in Beijing, China. Initially, we identified knowledge workers who were capable of remote work through mobile office app usage. Subsequently, we delineated the finer-scale distribution of third-place visits of remote workers using mobile phone signaling data and geospatial information. Finally, we utilized the eXtreme Gradient Boosting model and SHapley Additive exPlanations value to explore the association between third-place visits for remote work and the surrounding built environment. The results revealed that (1) approximately 61.43 % of total employees had the potential to work remotely, with 11.27 % opting for remote work in third places and 4.35 % choosing specific commercial third places; and (2) the popularity of these third places was characterized by high-density mixed-use surroundings, proximity to residential communities, and easy accessibility to subway stations. The findings can reinforce the establishment of urban design guidelines for third places, thereby contributing to the development of hybrid work models and sustainable cities.第三空间为传统办公室和家庭办公提供了一种创新的替代方案，越来越受到欢迎。以往的研究主要集中在定性分析和调查调查，缺乏对第三空间中远程工作的定量研究。在本研究中，我们提出了一种定量方法来识别和表征用于远程工作的细粒度第三空间，并将其应用于中国北京。首先，我们通过移动办公应用的使用情况确定了具备远程工作能力的知识工作者。随后，我们利用移动电话信令数据和地理空间信息描绘了远程工作者在第三空间的更细粒度的访问分布。最后，我们利用极限梯度提升模型和Shapley增加解释值来探索第三空间中远程工作与周围建成环境之间的关联。结果显示：（1）大约61.43%的总员工有可能进行远程工作，其中11.27%选择在第三空间远程工作，4.35%选择特定的商业第三空间；（2）这些第三空间的受欢迎程度特征为高密度混合用途周围环境，靠近居民社区，并且易于接近地铁站。这些发现有助于加强第三空间的城市设计准则的制定，从而促进混合工作模式和可持续城市的发展。https://doi.org/10.1016/j.scs.2024.105258
Modeling and spatio-temporal analysis on CO2emissions in the Guangdong-Hong Kong-Macao greater bay area and surrounding cities based on neural network and autoencoder
基于神经网络和自动编码器的广东-香港-澳门大湾区及周边城市二氧化碳排放的建模和时空分析
Significant attention has been given to the issue of CO2 emissions worldwide, especially for China as the largest emitter. Cities, as the main carriers of China's economic development, account for up to 85 % of CO2 emissions from energy use in the country. The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) and surrounding cities play important leading roles in low-carbon development. However, compiling city-level CO2 emissions is challenging due to the limited availability of data. In this paper, a new idea is proposed by using SSA-BP for estimating provincial-level CO2 emissions and downscaling provincial-level CO2 emissions to city-level CO2 emissions by reconstructing missing values of city-level CO2 emissions with an autoencoder. This study compiles a city-level CO2 emissions inventory and conducts a spatio-temporal analysis of CO2 emissions in the GBA and surrounding cities. The results show that CO2 emissions exhibit a spatial distribution pattern with spatial dependence. Furthermore, according to the analysis of spatio-temporal heterogeneity, GDP influenced CO2 emissions the most within the five influencing factors, and the influences of GDP, population, and energy intensity were mainly positive, while the influence of patents was mainly negative, and that of trade was both positive and negative.在全球范围内，二氧化碳排放问题受到了重视，尤其是对中国作为最大排放国的关注。作为中国经济发展的主要载体，城市在国家能源使用中占据了高达85%的二氧化碳排放量。广东-香港-澳门大湾区及周边城市在低碳发展中起着重要的领导作用。然而，由于数据的有限性，编制城市级别的二氧化碳排放清单是具有挑战性的。本文提出了一种新的方法，通过使用SSA-BP来估算省级二氧化碳排放量，并通过使用自动编码器来重建缺失的城市级二氧化碳排放数据，从而将省级二氧化碳排放量下降到城市级。本研究编制了城市级二氧化碳排放清单，并对大湾区及周边城市的二氧化碳排放进行了时空分析。结果表明，二氧化碳排放呈现出具有空间依赖性的空间分布模式。此外，根据时空异质性的分析，GDP对二氧化碳排放的影响最大，在五个影响因素中，GDP、人口和能源强度的影响主要是正向的，专利的影响主要是负向的，而贸易的影响既有正向也有负向。https://doi.org/10.1016/j.scs.2024.105254
Fast prediction of spatial temperature distributions in urban areas with WRF and temporal fusion transformers
使用WRF和时间融合变压器快速预测城市区域的空间温度分布Urban Heat Island (UHI) poses a significant challenge to the sustainable development of global cities. It is of great importance to efficiently characterize the spatiotemporal distribution of urban temperatures for UHI mitigation strategies, such as urban ecosystem planning and control. Numerical Weather Prediction (NWP) methods are used to obtain the urban temperature distribution. However, NWP requires significant hardware resources and long computation time. The development of artificial intelligence approaches have been applied in expediting the weather forecasting, yet their forecasting precision remains significantly inferior to that of NWP. Hence, this study aims to propose a hybrid fast prediction model, considering the accuracy of WRF (Weather Research and Forecasting) and efficiency of Temporal Fusion Transformer (TFT) neural networks. By integrating high-precision temperature time series boundaries generated by WRF into TFT, this method (WRF-TFT) is able to realize the rapid predictions of urban temperature distributions (around 15 times faster compare to WRF) while maintaining the physical characteristics of atmospheric dynamics. With this method, we also conducted for future temperature forecast for cities. It is estimated that the temperature can exceed 35 °C more than 12 hours per day in July 2050. This hybrid model facilitates swift acquisition of urban temperature trends, providing a crucial basis for urban risk management and planning. 城市热岛（UHI）对全球城市的可持续发展构成重大挑战。高效表征城市温度的时空分布对于UHI缓解战略，如城市生态系统规划和控制，具有重要意义。数值天气预报（NWP）方法用于获取城市温度分布。然而，NWP需要大量的硬件资源和长时间的计算。人工智能方法的发展已经应用于加速天气预报，但其预测精度仍然显著低于NWP。因此，本研究旨在提出一种混合快速预测模型，考虑到WRF（Weather Research and Forecasting）的精确性和Temporal Fusion Transformer（TFT）神经网络的效率。通过将WRF生成的高精度温度时间序列边界整合到TFT中，该方法（WRF-TFT）能够实现对城市温度分布的快速预测（比WRF快约15倍），同时保持大气动力学的物理特性。使用这种方法，我们还对未来城市的温度进行了预测。预计到2050年7月，每天超过12小时的时间内温度可能会超过35摄氏度。这种混合模型有助于快速获取城市温度趋势，为城市风险管理和规划提供了重要基础。
https://doi.org/10.1016/j.scs.2024.105249Haocheng Zhu 东南大学
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