本次给大家整理的是《Sustainable Cities and Society》杂志2024年11月第114期的论文的题目和摘要，一共包括77篇SCI论文！由于论文过多，我们将通过两篇文章进行介绍，本篇文章介绍第1--第30篇论文!
论文1
Impact of urbanization on heavy metals in outdoor air and risk assessment: A case study in severe cold regions
城市化对户外空气重金属含量的影响及风险评估：严寒地区的案例研究
【摘要】
Urbanization may result in an accumulation of heavy metals (HMs) in urban air ecosystems, negatively impacting air quality and potentially endangering the health of urban residents. This study utilized Jilin Province, a cold region of China, as a case study. It employed kriging interpolation to unveil heavy metal distribution, Principal Component Analysis (PCA) for source identification, and ecological and health risk assessment methods to evaluate potential health threats. The mean concentrations of HMs were greater than the local background values, indicating that heavy metal pollution in the air in Jilin Province is more serious and may be harmful to the environment and human beings. HMs tend to accumulate in urban areas with high GDP and population density and disperse to neighboring cities with levels of GDP and population density. The study identifies biomass combustion, coal combustion for heating and vehicle emissions as the primary sources of HMs. HMs in the air in Jilin Province pose a risk to both the environment and the human body, with children being particularly vulnerable. These findings emphasize the necessity of implementing comprehensive evaluation and monitoring strategies to mitigate urban air pollution and ensure environmental sustainability.
【摘要翻译】
城市化可能导致重金属（HM）在城市空气生态系统中的积累，负面影响空气质量，并可能危害城市居民的健康。本研究以中国寒冷地区的吉林省为案例。它采用克里金插值法揭示重金属分布，使用主成分分析（PCA）进行源头识别，并利用生态和健康风险评估方法评估潜在的健康威胁。重金属的平均浓度高于当地背景值，表明吉林省空气中的重金属污染更为严重，可能对环境和人类造成危害。重金属倾向于在高GDP和人口密度的城市区域积累，并向具有相似GDP和人口密度的邻近城市扩散。研究识别出生物质燃烧、取暖用煤燃烧和机动车排放是重金属的主要来源。吉林省空气中的重金属对环境和人类健康构成风险，儿童尤其脆弱。这些发现强调了实施全面评估和监测策略的必要性，以减轻城市空气污染，确保环境可持续性。
【doi】
https://doi.org/10.1016/j.scs.2024.105713
【作者信息】
Yongbo Cui, 广州大学土木工程与交通学院，建筑与城市规划学院，广东省广州市510006
Chengliang Fan, 广州大学土木工程与交通学院，建筑与城市规划学院，广东省广州市510006；亚热带建筑科学与城市科学国家重点实验室，广东省广州市510640
Xiaoqing Zhou, 广州大学土木工程与交通学院，建筑与城市规划学院，广东省广州市510006；亚热带建筑科学与城市科学国家重点实验室，广东省广州市510640
Peng Yu，广州大学土木工程与交通学院，建筑与城市规划学院，广东省广州市510006
论文2
Exploring intra-urban thermal stress vulnerability within 15-minute city concept: Example of heat waves 2021 in Moscow
探索15分钟城市概念中的城市内部热应力脆弱性：2021年莫斯科热浪的例子
【摘要】
Heat vulnerability in big cities is important because of the increase in heat wave frequency and thermal stress that is identified by Urban Heat Island. Our study investigated intra-urban heat vulnerability in Moscow, which strongly influenced by historic context in urban planning, with a focus on local disparities. We considered the vulnerability framework in terms of “exposure,” “sensitivity,” and “adaptive capacity,” and adopted the concept of a 15-minute city to evaluate spatial patterns on example of 2021 heat waves. We used high-resolution meteorological data from the regional meteorological model COSMOsingle bondCLM and calculated the Physiologically Equivalent Temperature (PET) to assess thermal stress and define exposure. The data from OSM and other open sources were used to assess sensitivity and adaptive capacity through the proximity of green spaces, cooling centers, healthcare, and premium service facilities. The PET varied from 25.3 °C in the outskirts to 30.2 °C in Moscow centre; however, variations in thermal stress did not have adverse effects on the spatial patterns of vulnerability. The vulnerability indicator in the east was six times higher than in more prosperous areas of the center, north and southwest, due to historical development, mainly the transformation from former industrial areas into residential areas.
【摘要翻译】
大城市的热脆弱性尤为重要，因为热浪频率的增加和城市热岛效应所带来的热压力加剧了这一问题。我们的研究调查了莫斯科市内的热脆弱性，该城市的城市规划受历史背景的强烈影响，研究重点关注了局部差异。我们采用了“暴露”、“敏感性”和“适应能力”这三个维度的脆弱性框架，并结合了“15分钟城市”的概念，评估了2021年热浪期间的空间格局。我们使用了来自区域气象模型COSMO-CLM的高分辨率气象数据，计算了生理等效温度（PET）来评估热压力并确定暴露水平。通过开放街图（OSM）和其他开放数据源，我们评估了绿地、制冷中心、医疗设施和高端服务设施的邻近性，以衡量敏感性和适应能力。生理等效温度在莫斯科郊区为25.3°C，而在市中心则达到了30.2°C；然而，热压力的变化并没有对脆弱性空间格局产生不利影响。由于历史发展（主要是从前工业区向住宅区的转型），东部地区的脆弱性指标是中心、北部和西南部这些较繁荣地区的六倍。
【doi】
https://doi.org/10.1016/j.scs.2024.105729
【作者信息】
N. Shartova, 俄罗斯莫斯科高等经济大学地理与地理信息技术学院，109028；西班牙巴塞罗那全球健康研究所，08003
E. Mironova, 俄罗斯莫斯科国立大学地理学院，119991
M. Varentsov, 俄罗斯莫斯科高等经济大学地理与地理信息技术学院，109028；莫斯科国立大学科研计算中心，119991；俄罗斯国家水文气象大学，圣彼得堡，沃罗涅日大街79号，192007
M. Grischenko, 俄罗斯莫斯科国立大学地理学院，119991
P. Konstantinov，深圳北理莫斯科大学，中华人民共和国广东省深圳市龙岗区，518172；俄罗斯莫斯科国立大学地理学院，119991；俄罗斯国家水文气象大学，圣彼得堡，沃罗涅日大街79号，192007
论文3
Can urban shrinkage contribute to mitigating surface air temperature warming?
城市收缩能否有助于减缓地表空气温度升高？
【摘要】
In recent years, urban areas are increasingly experiencing intense warming. Although urbanization is an important driver of warming in urban environments, it remains unclear whether depopulation trends in shrinking cities mitigate this warming effect. Here, we explored the relationship between shrinking cities and observed warming in China. Of the 356 Chinese cities, 95 were identified as shrinking between 2000 and 2010. We categorized 2419 observation stations into three groups—rural, shrinking, and non-shrinking—and generated a surface air temperature (SAT) anomaly series for each group from 1961 to 2014. Temperature differences between the shrinking and non-shrinking urban stations were investigated. Using segmented generalized least squares regression, the spatiotemporal temperature patterns across the mean (Tmean), maximum (Tmax), and minimum temperatures (Tmin), diurnal temperature range (DTR) indicators, and across seasons—spring, summer, autumn, and winter—were explored. Results revealed a cooling effect in shrinking cities, with decadal decreases of 0.042 °C (–0.078 to –0.005 °C), 0.083 °C (–0.126 to –0.039 °C), and 0.029 °C (–0.062 to –0.005 °C) in regional Tmean, Tmax, and Tmin anomalies, respectively. Moreover, pronounced seasonality was identified in this phenomenon—the cooling effect was most notable for Tmean in spring and Tmax in autumn, less significant in summer, and negligible in winter. These results suggested that the population decline in shrinking cities could alleviate regional warming, having implications that could influence urban planning and climate mitigation policies.
【摘要翻译】
近年来，城市地区的气温持续升高。虽然城市化是城市环境中变暖的重要驱动因素，但在城市收缩过程中，人口减少是否会减缓这一变暖效应仍不明确。在此研究中，我们探讨了中国城市收缩与气温升高之间的关系。在中国的356个城市中，有95个城市在2000年至2010年间被认定为收缩城市。我们将2419个观测站分为三个类别——农村、收缩城市和非收缩城市——并生成了1961年至2014年间每组的地表气温（SAT）异常序列。研究了收缩城市与非收缩城市观测站之间的温度差异。通过分段广义最小二乘回归法，分析了不同时间尺度上的气温变化模式，包括平均温度（Tmean）、最高温度（Tmax）、最低温度（Tmin）、日温差（DTR）指标，以及四季（春、夏、秋、冬）中的温度变化。结果显示，收缩城市中出现了降温效应，区域平均温度（Tmean）、最高温度（Tmax）和最低温度（Tmin）的年代变化分别为每十年下降0.042°C（–0.078°C至–0.005°C）、0.083°C（–0.126°C至–0.039°C）和0.029°C（–0.062°C至–0.005°C）。此外，这一现象存在明显的季节性——降温效应在春季的Tmean和秋季的Tmax中最为显著，在夏季较不明显，而在冬季几乎可以忽略。这些结果表明，城市人口减少可能减缓区域变暖，对城市规划和气候缓解政策具有重要启示。
【doi】
https://doi.org/10.1016/j.scs.2024.105730
【作者信息】
Fengdi Ma, 首尔国立大学景观建筑学跨学科项目，韩国首尔市冠岳区冠岳路1号，08826
Heeyeun Yoon，首尔国立大学农业生命科学学院景观建筑与农村系统工程系，智慧城市全球融合综合专业，农业生命科学研究所，韩国首尔市冠岳区冠岳路1号，08826
论文4
Towards more resilient cities-analyzing the impact of new-type urbanization on urban resilience: Considering spatial spillover boundaries
迈向更具韧性的城市——分析新型城市化对城市韧性的影响：考虑空间溢出边界
【摘要】
This paper examines the New-type Urbanization pilot policy (NTUP) and its influence on urban resilience, offering insights into how NTUP fosters a human-centric, sustainably coordinated, and inclusive model of urban development distinct from traditional approaches. This model plays a key role in enhancing urban capacities to confront economic, social, and environmental challenges, aiding in building more resilient cities. Notably, existing literature scarcely explores the relationship between NTUP and urban resilience, marking a significant gap this research aims to fill. Utilizing a multi-period DID model to examine panel data across 281 Chinese cities from 2006 to 2020, this study delves into NTUP's direct effects on urban resilience, its mechanisms, and spatial spillover boundaries. Findings reveal that: (1) NTUP enhances urban resilience, confirmed by a series of robustness tests. (2) NTUP significantly improves economic, infrastructure, and institutional resilience, while its influence on social resilience is minimal, and it detrimentally impacts ecological resilience. (3) Urban technology innovation and economic agglomeration are the primary mechanisms through which NTUP promotes urban resilience. (4) NTUP has a positive spatial spillover effect on the resilience of neighboring cities up to 350 km, with this effect shifting from a "radiation effect" to a "siphoning effect" as geographical distance increases.
【摘要翻译】
本文探讨了新型城镇化试点政策（NTUP）及其对城市韧性的影响，提供了有关NTUP如何推动以人为本、可持续协调、包容性发展模式的见解，该模式有别于传统的城市发展方法。新型城镇化在提高城市应对经济、社会和环境挑战的能力方面发挥了关键作用，有助于建设更具韧性的城市。值得注意的是，现有文献很少涉及NTUP与城市韧性之间的关系，这正是本研究试图填补的显著空白。本文采用多期双重差分（DID）模型，分析了2006年至2020年间281个中国城市的面板数据，深入探讨了NTUP对城市韧性的直接影响、其作用机制及空间溢出效应。研究结果显示：(1) NTUP增强了城市韧性，并通过一系列稳健性测试得到了验证；(2) NTUP显著改善了经济、基础设施和制度韧性，但对社会韧性的影响较小，且对生态韧性产生了负面影响；(3) 城市技术创新和经济集聚是NTUP促进城市韧性的主要机制；(4) NTUP对邻近城市韧性产生了正向的空间溢出效应，影响范围可达350公里，且随着地理距离的增加，这种效应从“辐射效应”转变为“虹吸效应”。
【doi】
https://doi.org/10.1016/j.scs.2024.105735
【作者信息】
Junzhou Yu, 四川大学公共管理学院，中国四川省成都市610065
Wenzheng Hu,四川大学公共管理学院，中国四川省成都市610065
Lingchun Hou，重庆大学管理科学与房地产学院，中国重庆市400044
论文5
A new methodology for reducing carbon emissions using multi-renewable energy systems and artificial intelligence
一种使用多可再生能源系统和人工智能减少碳排放的新方法
【摘要】
Microgrid cost management is a significant difficulty because the energy generated by microgrids is typically derived from a variety of renewable and non-renewable sources. Furthermore, in order to meet the requirements of freed energy markets and secure load demand, a link between the microgrid and the national grid is always preferred. For all of these reasons, in order to minimize operating expenses, it is imperative to design a smart energy management unit to regulate various energy resources inside the microgrid. In this study, a smart unit idea for multi-source microgrid operation and cost management is presented. The proposed unit utilizes the Improved Artificial Rabbits Optimization Algorithm (IAROA) which is used to optimize the cost of operation based on current load demand, energy prices and generation capacities. Also, a comparison between the optimization outcomes obtained results is implemented using Honey Badger Algorithm (HBA), and Whale Optimization Algorithm (WOA). The results prove the applicability and feasibility of the proposed method for the demand management system in SMG. The price after applying HBA is 6244.5783 (ID). But after applying the Whale Optimization Algorithm, the cost is found 4283.9755 (ID), and after applying the Artificial Rabbits Optimization Algorithm, the cost is found 1227.4482 (ID). By comparing the proposed method with conventional method, the whale optimization algorithm saved 31.396 % per day, and the proposed artificial rabbit's optimization algorithm saved 80.3437 % per day. From the obtained results the proposed algorithm gives superior performance.
【摘要翻译】
微电网的成本管理是一个重大挑战，因为微电网所产生的能量通常来自多种可再生和不可再生能源。此外，为了满足自由能源市场的需求并保障负荷需求，微电网与国家电网的连接是首选。基于以上原因，为了尽量减少运营成本，设计一个智能能源管理单元来调控微电网内部的各种能源资源至关重要。在本研究中，提出了一种用于多源微电网运行和成本管理的智能单元理念。该单元采用改进的人工兔子优化算法（IAROA），根据当前负载需求、能源价格和发电能力来优化运营成本。此外，还通过蜜獾算法（HBA）和鲸鱼优化算法（WOA）对优化结果进行了比较。结果证明了该方法在智能微电网需求管理系统中的可行性和适用性。应用蜜獾算法后的价格为6244.5783（ID），应用鲸鱼优化算法后的成本为4283.9755（ID），应用人工兔子优化算法后的成本为1227.4482（ID）。通过将该方法与传统方法进行比较，鲸鱼优化算法每天节省了31.396％，而人工兔子优化算法每天节省了80.3437％。从获得的结果来看，提出的算法表现优越。
【doi】
https://doi.org/10.1016/j.scs.2024.105721
【作者信息】
Bilal Naji Alhasnawi, 伊拉克库法66001，阿尔弗拉特中部技术大学，阿尔萨马瓦技术学院电力技术系
Sabah Mohammed Mlkat Almutoki, 伊拉克库法66001，阿尔弗拉特中部技术大学，阿尔萨马瓦技术学院电力技术系
Firas Faeq K. Hussain, 伊拉克蒂卡尔，阿尔阿伊恩伊拉克大学工程学院；伊拉克穆萨纳，穆萨纳大学理学院物理系
Ambe Harrison,喀麦隆布埃亚大学科技学院电气与电子工程系，P.O. Box Buea 63
Bahamin Bazooyar, 英国伦敦布鲁内尔大学机械与航空工程系，Uxbridge UB8 3PH
Marek Zanker,捷克共和国赫拉德茨-克拉洛韦大学信息管理学院，50003 Hradec Králové
Vladimír Bureš，捷克共和国赫拉德茨-克拉洛韦大学信息管理学院，50003 Hradec Králové
论文6
Analysing urban local cold air dynamics and climate functional zones using interpretable machine learning: A case study of Tianhe district, Guangzhou
使用可解释机器学习分析城市局部冷空气动力学和气候功能区：广州天河区的案例研究
【摘要】
Deterioration of the thermal environment in built-up areas poses a serious threat to human health, comfort, and urban infrastructure, while also increasing energy consumption and carbon emissions. This underscores the need to optimize wind environments as a key mitigation strategy for urban areas. This paper analyzed the effects of human activities and natural factors on local cold air in Tianhe District, Guangzhou, from the perspective of local ventilation systems. The KLAM_21 (Kaltluft Abfluss Modell) was used to simulate local cold air flow and delineate climate functional zones. A random forest model, interpreted with the SHapley Additive exPlanation (SHAP) method, assessed the impact of various factors on local cold air dynamics. The study found that: (1) The northern mountainous area is a crucial cold source; (2) Some open spaces in the built environment fail to function as effective local cold air corridors; (3) High-intensity urban development hinders local cold air transmission; (4) Water bodies are more effective than green spaces in collecting and transmitting local cold air. This study provided technical methods for identifying climate functional zones and understanding local cold air dynamics, as well as theoretical support for the construction of local ventilation systems in urban areas.
【摘要翻译】
建筑区域热环境的恶化对人类健康、舒适性和城市基础设施构成严重威胁，同时还增加了能源消耗和碳排放。这突显了优化风环境作为城市地区关键缓解策略的必要性。本文从地方通风系统的角度分析了人类活动和自然因素对广州天河区局部冷空气的影响。采用KLAM_21（Kaltluft Abfluss Modell）模拟局部冷空气流动，并划定气候功能区。使用随机森林模型，通过SHapley Additive exPlanation（SHAP）方法解释，评估各种因素对局部冷空气动态的影响。研究发现：(1) 北部山区是重要的冷源；(2) 建筑环境中的某些开放空间未能有效作为局部冷空气走廊；(3) 高强度的城市开发阻碍了局部冷空气的传输；(4) 水体在收集和传输局部冷空气方面比绿地更为有效。该研究为识别气候功能区和理解局部冷空气动态提供了技术方法，也为城市地区局部通风系统的建设提供了理论支持。
【doi】
https://doi.org/10.1016/j.scs.2024.105731
【作者信息】
Shifu Wang, 华南理工大学建筑学院，中国广州市510641；永久地址：中国广州市天河区乌山路381号
Xiangcheng Zeng, 华南理工大学建筑学院，中国广州市510641
Yueyang Huang, 重庆大学建筑与城市规划学院，中国重庆市400045
Xinjian Li，华南理工大学建筑学院，中国广州市510641
论文7
How do driving factors affect the diurnal variation of land surface temperature across different urban functional blocks? A case study of Xi'an, China
驱动因素如何影响不同城市功能区土地表面温度的日变化？以中国西安为案例
【摘要】
A comprehensive and in-depth understanding of the formation mechanisms of the urban thermal environment is the basis for thermal environment regulation, however, there is insufficient knowledge regarding how driving factors influence daytime and nighttime land surface temperature (LST) within urban functional blocks (UFBs). We selected Xi'an, China as a case study, integrating remote sensing data including ECOSTRESS, Landsat-8, and Gaofen-1, along with geographic data including road network, areas of interest, points of interest, building footprint, and mobile phone signaling. It divided 10 types of UFBs, inverted daytime and nighttime LST, calculated 5 types of driving factors, and finally analyzed the contribution and marginal effects of driving factors on day-night LST using boosted regression tree. The results showed that LST and its driving factors differed significantly in different times and UFBs. Industrial blocks and urban villages had higher LST in the daytime, while residential blocks, commercial blocks, and public service blocks had higher LST in nighttime. Industrial blocks were the dominant blocks that drove the overall LST up during the day, while residential blocks were the dominant blocks at night. Location distance (-) and population density (+) affected LST in all UFBs during day and night, NDVI (-), building density (+), and floor area ratio (-) were key factors for most UFBs during daytime, and NDVI (+), surface albedo (-), and point density of interest (+) were key factors during nighttime. Most of the driving factors had significant influence thresholds, but there were small differences across UFBs. This paper aims to elucidate the mechanisms by which driving factors influence urban LST during day and night across different UFBs, thereby providing new support for more targeted thermal environment regulation and diurnal trade-offs at the block scale.
【摘要翻译】
对城市热环境形成机制的全面深入理解是热环境调控的基础，但目前对驱动因素如何影响城市功能区（UFBs）日间和夜间地表温度（LST）的知识仍然不足。我们选择中国西安作为案例研究，整合了包括ECOSTRESS、Landsat-8和高分一号在内的遥感数据，以及道路网络、兴趣区、兴趣点、建筑轮廓和手机信号等地理数据。研究将UFBs分为10种类型，反演了日间和夜间的LST，计算了5种驱动因素，并最终利用提升回归树分析了驱动因素对日夜LST的贡献和边际效应。研究结果表明，不同时间和UFBs中的LST及其驱动因素显著不同。工业区和城中村在白天的LST较高，而住宅区、商业区和公共服务区在夜间的LST较高。工业区是白天整体LST上升的主要驱动区，而住宅区则是夜间的主要驱动区。位置距离（-）和人口密度（+）在日夜间均对LST产生影响，NDVI（-）、建筑密度（+）和容积率（-）是大多数UFBs在白天的关键因素，而NDVI（+）、地表反照率（-）和兴趣点密度（+）是夜间的关键因素。大多数驱动因素具有显著的影响阈值，但在UFBs之间存在小差异。本文旨在阐明驱动因素如何影响不同UFBs日夜间城市LST的机制，从而为更有针对性的热环境调控和块级尺度的昼夜权衡提供新支持。
【doi】
https://doi.org/10.1016/j.scs.2024.105738
【作者信息】
Kaixu Zhao, 西北大学城市与环境科学学院，中国西安710127；西安财经大学公共管理学院，中国西安710100
Zekui Ning, 西安财经大学公共管理学院，中国西安710100
Chen Xu, 西北大学城市与环境科学学院，中国西安710127
Xin Zhao, 西北大学城市与环境科学学院，中国西安710127
Xiaojun Huang，西北大学城市与环境科学学院，中国西安710127；陕西省地表系统与环境承载力重点实验室，中国西安710127；陕西西安城市森林生态系统研究站，中国西安710127
论文8
Passive over active: How low-cost strategies influence urban energy equity
被动优于主动：低成本策略如何影响城市能源公平
【摘要】
This study delves into the energy burden on households, a crucial aspect of energy justice, influenced by urban environment factors and buildings’ passive and active designs. It evaluates the effects of passive and active design features on household energy expenditures at the census tract scale. Applying advanced Machine Learning techniques, including multiple and decision tree regressions, random forests, support vector machines, XGBoost, and Neural Networks, the research assesses the impact of various factors on the energy burden. Findings reveal that passive design elements significantly outweigh active ones in reducing energy costs at the urban scale, as confirmed by a model with a 94.8 % R2 accuracy. The insights provided are vital for policymakers, urban planners, architects, and researchers, pushing for sustainable urban planning and energy justice by prioritizing effective design strategies. This contributes to a broader understanding and implementation of energy-efficient measures in urban development.
【摘要翻译】
这项研究深入探讨了家庭能源负担，这是能源公平的一个重要方面，受到城市环境因素以及建筑的被动和主动设计的影响。研究评估了被动和主动设计特征对家庭能源支出的影响，分析的单位是人口普查区。通过应用先进的机器学习技术，包括多元回归、决策树回归、随机森林、支持向量机、XGBoost 和神经网络，研究评估了各种因素对能源负担的影响。研究结果表明，在城市规模上，被动设计元素在降低能源成本方面的作用显著大于主动设计元素，这一点在一个具有94.8% R²准确度的模型中得到了确认。所提供的见解对于政策制定者、城市规划者、建筑师和研究人员至关重要，推动可持续城市规划和能源公平，优先考虑有效的设计策略。这有助于更广泛地理解和实施城市发展中的节能措施。
【doi】
https://doi.org/10.1016/j.scs.2024.105723
【作者信息】
Siavash Ghorbany, 圣母大学工程学院土木与环境工程及地球科学系，美国印第安纳州诺特丹市46556
Ming Hu, 圣母大学建筑学院副院长，华尔什建筑学院，圣母大学，美国印第安纳州诺特丹市46556；波兰凯尔采市西里西亚学院建筑、土木工程与应用艺术学院，Rolan 43, Katowice 40-555
Matthew Sisk, 圣母大学数据与社会露西家庭研究所实践副教授，美国印第安纳州诺特丹市46556
Siyuan Yao, 圣母大学工程学院计算机科学与工程系，美国印第安纳州诺特丹市46556
Chaoli Wang，圣母大学计算机科学与工程系，美国印第安纳州诺特丹市46556
论文9
A stochastic iterative peer-to-peer energy market clearing in smart energy communities considering participation priorities of prosumers
考虑生产者参与优先权的智能能源社区中随机迭代的点对点能源市场清算
【摘要】
The penetration of distributed energy resources (DERs) has changed the role of a consumer to a prosumer, i.e., producer and consumer. This new role provides the opportunity for peer-to-peer(P2P) energy trading. In this paper, a three-stage iterative framework is proposed to clear the price and quantity of trading in P2P markets while addressing price and DER uncertainties by the Monte Carlo simulation (MCS) method. Initially, bids and offers of customers are determined by implementing an advanced satisfaction-based home energy management system (HEMS) at each home. Subsequently, the market operator prioritizes bids and offers according to the amount of customers’participation in the market. Finally, the P2P market is cleared by application of the alternating direction method of multipliers (ADMM), and the market clearing prices (MCPs) are determined. MCPs are used as a parameter to repeat the three stages, and the procedure is redone until the stopping rule is met. The proposed method's effectiveness has been investigated in communities with 8, 50, and 100 prosumers. Results indicate a 69.51 % cost reduction in a smart energy community with 50 homes through P2P energy market participation. The proposed market clearing method is compared with the common mid-market rate (MMR) and Stackelberg game methods and demonstrates over 25 % reduction in community costs.
【摘要翻译】
分布式能源资源（DERs）的渗透改变了消费者的角色，使其转变为“生产消费者”（prosumers），即既是生产者又是消费者。这一新角色为点对点（P2P）能源交易提供了机会。本文提出了一种三阶段迭代框架，用于清算P2P市场中的交易价格和数量，同时通过蒙特卡洛模拟（MCS）方法解决价格和DER的不确定性。首先，客户的出价和报价通过实施先进的基于满意度的家庭能源管理系统（HEMS）在每个家庭中确定。随后，市场运营商根据客户在市场中的参与程度对出价和报价进行优先排序。最后，通过应用交替方向乘子法（ADMM）清算P2P市场，并确定市场清算价格（MCPs）。MCPs作为参数用于重复这三阶段的过程，直到满足停止规则为止。研究表明，该方法在拥有8个、50个和100个生产消费者的社区中表现出良好的效果。结果显示，通过参与P2P能源市场，一个包含50户家庭的智能能源社区成本降低了69.51%。该市场清算方法与常见的中间市场价格（MMR）和斯塔克尔堡博弈方法进行了比较，显示出社区成本降低超过25%。
【doi】
https://doi.org/10.1016/j.scs.2024.105728
【作者信息】
Abbas Izadi, 伊朗希拉兹，希拉兹大学电力与控制工程系，电气与计算机工程学院
Mohammad Rastegar，伊朗希拉兹，希拉兹大学电力与控制工程系，电气与计算机工程学院
论文10
Unlocking responsive flexibility within local energy communities in the presence of grid-scale batteries
在存在电网规模电池的情况下，释放地方能源社区的响应灵活性
【摘要】
The transition towards a decentralized, decarbonized, and distributed energy infrastructure necessitates techno-economic initiatives to empower local energy communities (LECs) to achieve self-reliance and evolve into self-sustained electricity networks. It is crucial to underscore the significance of network resilience, especially in the context of local power generation, battery storage, and the radial topology of low-voltage (LV) networks. While contemporary LV networks have made significant attempts to integrate distributed energy resources (DERs), the notable deficiency lies in their lack of network redundancy, posing a substantial challenge in the occurrence of high-impact, low-probability (HILP) events. Therefore, to enhance LV network resilience and leverage its capability to withstand unexpected disruptions, the network operator needs to unlock the potential contributions of end-users within the active distribution networks (ADNs). In this paper, a comprehensive model is developed based on multi-temporal optimal power flow (MTOPF) for unbalanced LV networks addressing the technical issues in islanded microgrid operational planning. The contributions of the grid-scale batteries in forming islanded microgrids and the flexibility that can be provided by the end-users in the LEC have been considered in this paper. To demonstrate the performance of the proposed model, the simulation studies have been carried out on a part of medium and low voltage networks, consisting of network reconfiguration and load transferring capability to reduce the service interruptions during HILP events. The energy-not-served (ENS) is chosen as one of the key performance indicators (KPIs) in this study. With the unlocking flexibility potentials and contribution of the DERs, including grid-scale energy storage (GES) units and Photovoltaic (PV) panels, the ENS has been reduced from 700.8 kWh to 447.5 kWh by activating the local resources, proper switching action, and contribution of the flexible loads, for one of the severe HILP events, i.e., the main grid outage. In this case, the full load curtailment index is reduced from 180 to 106 client hours.
【摘要翻译】
向去中心化、脱碳和分布式能源基础设施的转型需要技术经济措施，以赋能地方能源社区（LECs），使其实现自给自足并演变为自维持的电力网络。在地方发电、蓄电池存储和低压（LV）网络的辐射拓扑结构背景下，强调网络韧性的重要性尤为关键。尽管当代LV网络在整合分布式能源资源（DERs）方面做出了重大努力，但其显著不足在于缺乏网络冗余，这在发生高影响、低概率（HILP）事件时构成了重大挑战。因此，为了增强LV网络的韧性并提升其抵御意外干扰的能力，网络运营商需要挖掘活跃配电网络（ADNs）中最终用户的潜在贡献。本文基于多时域最优潮流（MTOPF）模型，针对不平衡的LV网络，解决孤岛微电网的运行规划中的技术问题。本文考虑了电网规模电池在形成孤岛微电网中的贡献，以及LEC中最终用户可以提供的灵活性。为了展示所提模型的性能，模拟研究在一部分中低压网络上进行，包括网络重构和负荷转移能力，以减少HILP事件期间的服务中断。本研究选择未供能（ENS）作为关键绩效指标（KPI）之一。通过释放灵活性潜力和DER的贡献，包括电网规模储能（GES）单元和光伏（PV）面板，ENS在一次严重的HILP事件（即主电网故障）中从700.8 kWh减少至447.5 kWh，通过激活地方资源、适当的切换操作和灵活负荷的贡献。在这种情况下，全面负荷削减指数从180减少到106客户小时。
【doi】
https://doi.org/10.1016/j.scs.2024.105697
【作者信息】
Mohammad Sadegh Javadi，葡萄牙波尔图，系统与计算工程研究所（INESC TEC）
论文11
Effect of urban structure on land surface temperature around elementary schools in Hangzhou based on local climate zones
基于当地气候区的城市结构对杭州小学周围土地表面温度的影响
【摘要】
Changes in land surface temperature (LST) caused by the diversification of urban structures have garnered widespread attention. Elementary school students, the largest group receiving education, are particularly vulnerable. However, few studies have investigated how such changes manifest around elementary schools where students are concentrated. Herein, the urban structure of Hangzhou was identified with the help of local climate zones (LCZs) based on remote sensing to analyze the land use/land cover characteristics around 458 elementary schools. Moreover, a random forest regression model was employed to explore the relation between LCZs and seasonal LST around elementary schools and the relative importance of LCZs. Results indicate the following: (1) The land use intensity and LST around elementary schools were higher. (2) The LST of different LCZs exhibited significant seasonal differences. (3) A nonlinear relationship existed between LCZs and LST around elementary schools, of which compact midrise, open high-rise, dense trees, scattered trees and water were the five most relevant types. (4) The LST around elementary schools was closely related to the urban morphology of artificial surfaces, in which building density was the dominant factor. These findings provide valuable references for land use planning in the surrounding areas of elementary schools.
【摘要翻译】
城市结构多样化导致的地表温度（LST）变化引起了广泛关注。作为接受教育的最大群体，小学生尤其脆弱。然而，关于这种变化在集中学生的小学周围如何表现的研究较少。在本研究中，借助当地气候区（LCZs）和遥感技术，识别了杭州的城市结构，并分析了458所小学周围的土地利用/土地覆盖特征。此外，采用随机森林回归模型探讨了LCZs与小学周围季节性LST之间的关系及其相对重要性。研究结果表明：（1）小学周围的土地利用强度和LST较高；（2）不同LCZ的LST表现出显著的季节差异；（3）LCZ与小学周围LST之间存在非线性关系，其中紧凑中层建筑、开放高层建筑、密集树木、零散树木和水体是五种最相关的类型；（4）小学周围的LST与人工表面的城市形态密切相关，其中建筑密度是主要因素。这些发现为小学周边地区的土地利用规划提供了有价值的参考。
【doi】
https://doi.org/10.1016/j.scs.2024.105724
【作者信息】
Xincheng He,青岛科技大学 iSMART，青岛 266033，中国；北九州大学环境工程学院，日本北九州 808-0135
Weijun Gao , 青岛科技大学 iSMART，青岛 266033，中国；北九州大学环境工程学院，日本北九州 808-0135
Rui Wang，西湖大学西湖研究院，中国杭州 310024
论文12
Quantifying the main and interactive effects of the dominant factors on the diurnal cycles of land surface temperature in typical urban functional zones
定量分析典型城市功能区土地表面温度日循环主导因素的主要和交互效应
【摘要】
The urban heat island (UHI) effect exists both during daytime and nighttime and varies with urban characteristics, such as 2D/3D urban morphology and socio-economics. However, there is a lack of quantitative understanding of the roles of these characteristics in influencing land surface temperature (LST) variations in different urban functional zones (UFZs) throughout the diurnal cycle. In this study, we examined the responses of diurnal LSTs in different UFZs to 2D/3D urban morphology and socio-economic variables. Results showed the following: (1) During daytime, the main drivers of LST varied with not only the UFZs but also the observation times; during nighttime, the LST variations across different UFZs were largely controlled by 3D urban morphology and socio-economic factors. (2) At 10:37, LST declined most rapidly when the percentage of tree cover (PER_Tree) exceeded a certain threshold. The threshold values of PER_Tree were 85%, 70%, 50%, and 60% for the residential, industrial, commercial, and public service zones, respectively. Irrespective of the UFZs, a nighttime cooling effect occurred only when sky view factor (SVF) exceeded 0.8. (3) For locations with high population density (Pop_Den) in the residential zone, whether urban trees induced a cooling effect depended on both the observation time and PER_Tree during daytime; however, a higher SVF tended to result in an increased LST during nighttime. In the public service zone, when Pop_Den exceeded 50, urban trees with high height contributed to nighttime LST cooling, whereas a warming effect occurred with trees with low height. The direct implications of this study suggest that 3D urban morphology and socio-economics are more efficient mitigation strategies for all UFZs at night, and the interactive effects between the dominant drivers of diurnal LSTs should be considered to cool the city most effectively.
【摘要翻译】
城市热岛（UHI）效应在白天和夜间均存在，并且随着城市特征的变化（如二维/三维城市形态和社会经济状况）而有所不同。然而，目前对这些特征在不同城市功能区（UFZs）中影响地表温度（LST）变化的定量理解仍然不足。本研究考察了不同UFZs中昼夜LST对二维/三维城市形态和社会经济变量的响应。研究结果表明：（1）在白天，LST的主要驱动因素不仅因UFZs而异，还受观察时间的影响；而在夜间，不同UFZs之间的LST变化主要受到三维城市形态和社会经济因素的控制。（2）在10:37时，当树冠覆盖率（PER_Tree）超过某一阈值时，LST下降最快。居住区、工业区、商业区和公共服务区的PER_Tree阈值分别为85%、70%、50%和60%。无论UFZs如何，夜间冷却效应仅在天空视域因子（SVF）超过0.8时发生。（3）在居住区，高人口密度（Pop_Den）的位置中，城市树木是否产生冷却效应取决于观察时间和PER_Tree；然而，在夜间，较高的SVF往往会导致LST上升。在公共服务区，当Pop_Den超过50时，高高度的城市树木有助于夜间LST冷却，而低高度的树木则会产生升温效应。本研究的直接意义在于，三维城市形态和社会经济因素在夜间是更有效的减缓策略，并且应考虑昼夜LST的主导驱动因素之间的互动效应，以实现最佳的城市冷却效果。
【doi】
https://doi.org/10.1016/j.scs.2024.105727
【作者信息】
Jike Chen, 南京信息工程大学遥感与测绘工程学院，中国南京210044；自然资源部遥感与导航集成应用技术创新中心，中国南京210044；江苏省协同导航/定位与智能应用工程中心，中国南京210044
Kaixin Wang, 南京信息工程大学遥感与测绘工程学院，中国南京210044
Peijun Du, 江苏省地理信息科学与技术重点实验室，自然资源部土地卫星遥感应用重点实验室，南京大学地理与海洋科学学院，中国南京，江苏210023
Yufu Zang, 南京信息工程大学遥感与测绘工程学院，中国南京210044；自然资源部遥感与导航集成应用技术创新中心，中国南京210044；江苏省协同导航/定位与智能应用工程中心，中国南京210044
Peng Zhang, 安徽大学人工智能学院，中国合肥230601
Junshi Xia, 理研先进智能项目中心，日本东京103-0027
Cheng Chen, 江苏省测绘工程院，中国南京210019
Zhaowu Yu，复旦大学环境科学与工程系，中国上海200438
论文13
Leveraging context-adjusted nighttime light data for socioeconomic explanations of global urban resilience
利用调整背景的夜间灯光数据为全球城市韧性提供社会经济解释
【摘要】
Urban resilience, crucial for achieving sustainable development goals, entails the adaptation and recovery of urban systems from external shocks, such as the recent global pandemic. To investigate the response of urban systems to COVID-19, this study employs context-adjusted nighttime light data to model global urban resilience by combining an evolving urban resilience metric (EURm) with the shape similarity of resilience curves. Random effect analysis and counterfactual explanations are then implemented to explore the socioeconomic impacts on urban resilience during the pandemic, providing strategic insights for improvement. Our results delineate five diverse urban resilience patterns, each characterized by distinct phases of downturn, minimum, and recovery, with examples from Malaysia, Japan, the United States, China, and South Sudan. We also find notable correlations between socioeconomic factors and urban resilience, highlighting that stringent measures may reduce resilience, whereas proactive health and containment strategies could bolster resilience. Meanwhile, economic stress reflected by inflation adversely affects resilience. Furthermore, we delve into strategic socioeconomic modifications to enhance urban resilience using counterfactual explanations, underlining the importance of customized interpretation for varying countries. Overall, this study advances our understanding of urban resilience during global crises, guiding context-specific resilience strategies in urban planning and policy-making.
【摘要翻译】
城市韧性对实现可持续发展目标至关重要，它涉及城市系统对外部冲击（如近期全球疫情）的适应和恢复。为研究城市系统对COVID-19的反应，本研究利用调整过的夜间灯光数据，通过将不断演变的城市韧性指标（EURm）与韧性曲线的形状相似性相结合，建模全球城市韧性。随后，采用随机效应分析和反事实解释探讨疫情期间社会经济因素对城市韧性的影响，为改善提供战略性见解。研究结果描绘了五种不同的城市韧性模式，每种模式都有独特的下行、最低点和恢复阶段，涉及马来西亚、日本、美国、中国和南苏丹等国家的实例。我们还发现社会经济因素与城市韧性之间存在显著相关性，表明严格的防控措施可能会降低韧性，而积极的健康和防控策略可能增强韧性。同时，通货膨胀带来的经济压力对韧性产生不利影响。此外，我们利用反事实解释深入探讨增强城市韧性的战略性社会经济调整，强调不同国家应进行定制化解释的重要性。总体而言，本研究推进了我们对全球危机期间城市韧性的理解，为城市规划和政策制定中的情境特定韧性策略提供指导。
【doi】
https://doi.org/10.1016/j.scs.2024.105739
【作者信息】
Yatao Zhang, 未来韧性系统，新加坡-ETH中心，瑞士联邦理工学院（ETH Zurich），新加坡；制图与地理信息研究所，瑞士联邦理工学院，瑞士苏黎世
Siqi Song, 未来韧性系统，新加坡-ETH中心，瑞士联邦理工学院，新加坡
Xia Li, 地理信息科学重点实验室（教育部），华东师范大学地理科学学院，中国上海
Song Gao, 地理空间数据科学实验室，威斯康星大学麦迪逊分校地理系，美国威斯康星州麦迪逊
Martin Raubal，未来韧性系统，新加坡-ETH中心，瑞士联邦理工学院，新加坡；制图与地理信息研究所，瑞士联邦理工学院，瑞士苏黎世
论文14
Resilient city construction efficiency and its influencing factors in China's Chengdu-Chongqing Economic Circle: Considering both construction input and resilience level of the city
中国成都-重庆经济圈的韧性城市建设效率及其影响因素：同时考虑建设投入和城市韧性水平
【摘要】
The growing expansion of urban centers combined with a deteriorating climatic environment raises the likelihood and severity of urban disasters. Thus, there is an urgent need to accelerate the resilient city construction. Here, we use efficiency theory to structure an assessment indicator system of the resilient city construction efficiency to examine the actual correlation of urban resilience enhancement and urban resource consumption. Specifically, 16 key cities in the Chengdu-Chongqing Economic Circle (CCEC) are investigated using the super-efficient SBM and GTWR models. The findings reveal that the resilient city construction efficiency varies greatly among cities in the region, but most cities have relatively low resilient city construction efficiency, showing high resource consumption and low resilience levels. Also, the lower efficiency of regional resilient city construction is mainly due to the serious ineffectiveness of technical and resource inputs, insufficient outputs of ecological resilience and engineering resilience, and is also greatly influenced by factors such as the economic level and the technological innovation level. Upon this basis, we suggest the development strategies for resilient city construction in CCEC. This study broadens the perspective and scope of urban resilience research, and also provides a realistic reference for accelerating the construction of resilient cities.
【摘要翻译】
这项研究关注城市中心扩张与气候环境恶化的结合，增加了城市灾害的可能性和严重性，因此迫切需要加速韧性城市的建设。我们采用效率理论构建了一套韧性城市建设效率的评估指标体系，以考察城市韧性增强与城市资源消耗之间的实际关联。具体而言，我们研究了成都-重庆经济圈（CCEC）内的16个重点城市，采用超效率SBM和GTWR模型。研究结果显示，该地区韧性城市建设效率在城市之间差异显著，但大多数城市的韧性城市建设效率相对较低，表现为高资源消耗和低韧性水平。此外，该地区韧性城市建设效率低下主要是由于技术和资源投入的严重低效，生态韧性和工程韧性产出不足，同时还受到经济水平和技术创新水平等因素的显著影响。在此基础上，我们建议了CCEC韧性城市建设的发展策略。本研究拓宽了城市韧性研究的视角和范围，并为加速韧性城市建设提供了现实参考。
【doi】
https://doi.org/10.1016/j.scs.2024.105726
【作者信息】
Shan Han, 重庆交通大学 交通与运输学院，中国 重庆 400074
Huaming Wang, 西南科技大学 经济与管理学院，中国 绵阳 621010
Yibin Ao, 成都理工大学 环境与土木工程学院，中国 成都 610059
Bo Wang, 西南科技大学 土木工程与建筑学院，中国 绵阳 621010
Bin Chen, 北京师范大学 环境模拟与污染控制国家重点联合实验室，环境学院，中国 北京 100875；河北工程大学 水污染控制与水生态修复创新中心，中国 邯郸 056038
Igor Martek，迪肯大学 建筑与环境学院，澳大利亚 吉朗 3220
论文15
A bivariate simultaneous pollutant forecasting approach by Unified Spectro-Spatial Graph Neural Network (USSGNN) and its application in prediction of O3 and NO2 for New Delhi, India
通过统一光谱空间图神经网络 (USSGNN) 的双变量同时污染物预测方法及其在印度新德里 O3 和 NO2 预测中的应用
【摘要】
Declining urban air quality affects socioeconomic stability, public health, and ecosystems and is demanding attention of the administration to address environmental sustainability goals. Given the effects of ozone, a greenhouse gas, on local climate and health, this study introduces a Unified Spectro-Spatial Graph Neural Network (USS-GNN) designed for simultaneous 24-hour forecasting of ozone and its precursor, nitrogen-dioxide, while addressing their chemical interactions and spatiotemporal dynamics. This model exploits the graph structure of atmospheric dynamics and mines high-level spatial, spectral, and physical features from atmospheric data through a Dot Product Edge Attention mechanism and a location-aware graph feature rewiring technique. The proposed model is developed for Indian capital city New Delhi, utilizes hourly observations for the years 2021 and 2022 and achieved R2values of 0.650 and 0.618, RMSE of 13.950 and 16.120 μg/m3, MAE of 10.730 and 12.930 μg/m3 for ozone and nitrogen-dioxide respectively, outperforming state-of-the-art models. The model’s forecast analysis identified error-prone areas, effects of local meteorology, and pollutant interdependencies. An ablation study further detailed the impacts of graph operations on forecasts. Moreover, this study promotes the utility of bivariate modeling frameworks in improving urban pollution monitoring and supporting sustainable city management through data-driven policy implementations.
【摘要翻译】
城市空气质量的下降影响社会经济稳定、公共健康和生态系统，迫使管理层关注环境可持续发展目标。考虑到臭氧这一温室气体对地方气候和健康的影响，本研究提出了一种统一光谱时空图神经网络（USS-GNN），旨在同时进行24小时臭氧及其前体二氧化氮的预测，同时考虑它们的化学相互作用和时空动态。该模型利用大气动力学的图结构，通过点积边注意机制和位置感知图特征重连接技术，从大气数据中挖掘高层次的空间、光谱和物理特征。该模型专为印度首都新德里开发，利用2021年和2022年的小时观测数据，取得了臭氧和二氧化氮的R²值分别为0.650和0.618，均方根误差（RMSE）分别为13.950和16.120 µg/m³，平均绝对误差（MAE）分别为10.730和12.930 µg/m³，表现优于现有的先进模型。模型的预测分析识别了易出错区域、局部气象影响及污染物间的相互依赖性。消融研究进一步阐明了图操作对预测的影响。此外，本研究强调了双变量建模框架在改善城市污染监测和通过数据驱动政策实施支持可持续城市管理方面的实用性。
【doi】
https://doi.org/10.1016/j.scs.2024.105741
【作者信息】
Subhojit Mandal, 印度斯里城市信息技术学院计算机科学与工程系，印度安得拉邦萨提亚维杜，Gnan Marg Sricity，邮政编码517646
Suresh Boppani, 印度斯里城市信息技术学院计算机科学与工程系，印度安得拉邦萨提亚维杜，Gnan Marg Sricity，邮政编码517646
Vaibhav Dasari, 印度斯里城市信息技术学院计算机科学与工程系，印度安得拉邦萨提亚维杜，Gnan Marg Sricity，邮政编码517646
Mainak Thakur，印度斯里城市信息技术学院计算机科学与工程系，印度安得拉邦萨提亚维杜，Gnan Marg Sricity，邮政编码517646
论文16
City configurations to optimise pedestrian level ventilation and wind comfort
优化行人级通风和风舒适度的城市配置
【摘要】
Mediterranean coastal cities encounter two conflicting urban environmental challenges. First, strong winds that pose a risk of pedestrian wind discomfort on coastal streets, and second, weak winds that lead to inadequate outdoor ventilation in inner urban fragments. This study aims to optimise pedestrian level ventilation and wind comfort in Izmir, a compact coastal city in the Mediterranean climate. Three hypothetical city configurations were created based on four morphological parameters: street layout, urban street canyon form, tower layout, and tower height variation. Computational fluid dynamics simulations of the city configurations were performed and validated by wind tunnel experiments. The weak, comfortable, and strong winds were determined and mapped at the pedestrian level to assess each city configuration's performance. The results show that using the strategy of a shifted coastal street layout with adding towers on second-row blocks results in a 20 % reduction of the maximum wind velocity ratio on coastal streets compared to a grid street layout without towers. Moreover, positioning step-up towers on step-up city blocks and shifted towers on step-down city blocks can increase pedestrian-level ventilation efficiency by up to 73 %. The research methodology and findings can be transferred to other climates and urban environments and guide urban designers.
【摘要翻译】
地中海沿海城市面临两大相互矛盾的城市环境挑战。首先，强风会导致沿海街道行人感到不适；其次，弱风则造成城市内部片区通风不足。本研究旨在优化土耳其伊兹密尔市这一紧凑型沿海城市的人行通风和风舒适度。基于四个形态参数（街道布局、城市街道峡谷形态、塔楼布局和塔楼高度变化），构建了三种假设城市配置。通过计算流体动力学模拟对这些城市配置进行分析，并通过风洞实验进行验证。研究确定并绘制了弱风、舒适风和强风在行人层面的分布，以评估各城市配置的表现。结果显示，与没有塔楼的网格街道布局相比，采用移位的沿海街道布局并在第二排街区增设塔楼可使沿海街道的最大风速比降低20%。此外，在阶梯式城市街区上设置阶梯塔楼，在降阶式城市街区上设置移位塔楼，可以使行人层的通风效率提高至73%。该研究方法和发现可以推广到其他气候和城市环境，并为城市设计师提供指导。
【doi】
https://doi.org/10.1016/j.scs.2024.105745
【作者信息】
Hakan Baş, 土耳其伊兹密尔凯提普大学工程与建筑学院建筑系，Balatçık, Çiğli, Izmir 35620
Thomas Andrianne, 流体-结构相互作用，实验空气动力学，列日大学，Allée de la Découverte 9 (Bât. B52)，列日 4000，比利时
Sigrid Reiter，LEMA - 本地环境管理与分析，城市与环境工程系，列日大学，Allée de la Découverte 9 (Bât. B52)，列日 4000，比利时
论文17
Microclimate Vision: Multimodal prediction of climatic parameters using street-level and satellite imagery
微气候视觉：使用街道级和卫星影像对气候参数的多模态预测
【摘要】
High-resolution microclimate data is essential for capturing spatio-temporal heterogeneity of urban climate and heat health management. However, previous studies have relied on dense measurements that require significant costs for equipment, or on physical simulations demanding intensive computational loads. As a potential alternative to these methods, we propose a multimodal deep learning model to predict microclimate at a high spatial and temporal resolution based on street-level and satellite imagery. This model consists of LSTM and ResNet-18 architectures, and predicts air temperature (Tair), relative humidity (RH), wind speed (v), and global horizontal irradiance (GHI). For our study area situated at a university campus in Singapore, we collected microclimate data, street-level and satellite imagery. We conducted extensive experiments with our collected dataset to showcase our model’s predictive capabilities and its practical use in generating high-resolution microclimate maps. Our model reported RMSE at 0.95 °C for Tair, 2.57% for RH, 0.31 m/s for v, and 225 W/m2for GHI. Furthermore, we observed a contribution of imagery inputs to higher accuracy by comparing models with and without such inputs. We identified hot spots at a high spatio-temporal resolution, indicating its application for issuing real-time heat alerts. Our models are released openly at the microclimate-vision GitHub repository (https://github.com/kunifujiwara/microclimate-vision).
【摘要翻译】
高分辨率的微气候数据对于捕捉城市气候的时空异质性以及热健康管理至关重要。然而，以往的研究依赖于密集测量，这需要昂贵的设备，或依赖于需要大量计算资源的物理模拟。作为这些方法的潜在替代方案，我们提出了一种多模态深度学习模型，通过街道级和卫星影像预测微气候，达到高空间和时间分辨率。该模型结合了LSTM和ResNet-18架构，能够预测空气温度（Tair）、相对湿度（RH）、风速（v）和全球水平辐射（GHI）。在新加坡的一所大学校园作为研究区域，我们收集了微气候数据、街道级和卫星影像。我们对收集的数据集进行了广泛实验，以展示模型的预测能力及其在生成高分辨率微气候图中的实际应用。模型的均方根误差（RMSE）为：Tair 0.95°C，RH 2.57%，v 0.31 m/s，GHI 225 W/m²。此外，通过比较有影像输入和无影像输入的模型，我们观察到影像输入对提高准确度的贡献。我们在高时空分辨率下识别了热点，表明其在发出实时热警报方面的应用潜力。我们的模型已在microclimate-vision GitHub库（https://github.com/kunifujiwara/microclimate-vision）公开发布。
【doi】
https://doi.org/10.1016/j.scs.2024.105733
【作者信息】
Kunihiko Fujiwara, 国立新加坡大学建筑系，新加坡；竹中工程公司研发院，日本
Maxim Khomiakov, 丹麦技术大学应用数学与计算机科学系，丹麦
Winston Yap, 国立新加坡大学建筑系，新加坡
Marcel Ignatius, 国立新加坡大学建筑系，新加坡
Filip Biljecki,国立新加坡大学建筑系，新加坡；国立新加坡大学房地产系，新加坡
论文18
Operation of smart distribution networks by considering the spatial–temporal flexibility of data centers and battery energy storage systems
考虑数据中心和电池储能系统的时空灵活性，智能配电网络的运行
【摘要】
This paper proposes a new framework for Smart Distribution Networks (SDN) operation by leveraging data centers' spatial–temporal flexibility. Combining this flexibility with Battery Energy Storage Systems (BES) capabilities can create a more robust and practical solution for real-world grid management challenges. Reducing the power exchange with the upstream network during peak hours is critical to reduce total losses. The proposed framework shows a 24.61 % reduction in power exchange with the upstream network during peak hours, resulting in a 39.71 % reduction in total loss compared to normal operation. In addition, managing the uncertainty of renewable energy resource generation and load demand using the robust optimization method has been one of the main goals of this work. Finally, the study utilizes sensitivity analysis to identify the most optimal placement of data centers and BES units within the power grid, maximizing the benefits of this integrated approach. Sensitivity analysis on data centers and BES locations identified optimal locations on buses 15, 25, 33 and 2, 8, 23, 28, respectively. The results show that this strategic placement will reduce total losses by 12 % more than the proposed framework.
【摘要翻译】
这篇论文提出了一种新的智能配电网络（SDN）操作框架，利用数据中心的时空灵活性。将这种灵活性与电池储能系统（BES）的能力相结合，可以为现实中的电网管理挑战提供更稳健、实用的解决方案。减少高峰时段与上游网络的电力交换对于降低总损失至关重要。所提框架在高峰时段与上游网络的电力交换减少了24.61%，相比于正常运行，总损失减少了39.71%。此外，本文还采用稳健优化方法来管理可再生能源发电和负载需求的不确定性，这是本研究的主要目标之一。最后，研究利用敏感性分析确定数据中心和BES单元在电力网中的最佳位置，以最大化这一综合方法的效益。分析结果表明，数据中心的最佳位置在15、25和33号母线，而BES单元的最佳位置在2、8、23和28号母线。结果显示，这种战略性布局将比所提框架进一步减少总损失12%。
【doi】
https://doi.org/10.1016/j.scs.2024.105746
【作者信息】
Kamran Taghizad-Tavana, 伊朗塔布里兹大学电气与计算机工程学院，塔布里兹，伊朗
Mehrdad Tarafdar-Hagh, 伊朗塔布里兹大学电气与计算机工程学院，塔布里兹，伊朗
Sayyad Nojavan, 伊朗博纳布大学电气工程系，博纳布，伊朗
Mohammad Yasinzadeh, 伊朗东阿塞拜疆电力分配公司
Mohsen Ghanbari-Ghalehjoughi，伊朗塔布里兹大学电气与计算机工程学院，塔布里兹，伊朗
论文19
Promoting the sustainable development of CCUS projects: A multi-source data-driven location decision optimization framework
促进 CCUS 项目的可持续发展：多源数据驱动的选址决策优化框架
【摘要】
Carbon Capture, Utilization, and Storage (CCUS) technology is vital for achieving global carbon reduction targets. However, the uncertainties in technology and economic viability are influenced by location. To promote the sustainable development of CCUS technology, the study proposes a data-driven framework for optimizing location decisions. Firstly, the framework considers multiple factors, including geospatial data on resources, risks, power production, transportation, and environment. It also evaluates qualitative and quantitative data across economic, social, environmental, and technological dimensions. Secondly, the two-stage model is conducted as follows: Using Geographic Information System (GIS) technology, the first stage identifies suitable regions for CCUS projects, while the second stage prioritizes these regions using the TODIM method. Further, validated in China, the Junggar Basin, Tarim Basin, Ordos Basin, Sichuan Basin, and Bohai Rim Basin are identified as suitable for CCUS deployment. The Huaneng Luohuang Power Plant is the most conducive location for CCUS projects as pilot demonstrations. Final sensitivity analysis, scenario analysis, and comparative analysis have respectively affirmed the stability, dynamism, and reliability of the model. These analyses have also been instrumental in elucidating the final preferred outcomes under various decision-making preferences and strategic orientations. The framework for decision-making and data-driven priority model for CCUS projects layout proposed in the study can provide technical support and practical evidence for decision-makers in planning CCUS projects and formulating supportive policies.
【摘要翻译】
碳捕集、利用与存储（CCUS）技术对实现全球减碳目标至关重要。然而，技术和经济可行性的变化受地理位置的影响。为促进CCUS技术的可持续发展，本研究提出了一种数据驱动的框架，以优化位置决策。首先，该框架考虑了多个因素，包括资源、风险、电力生产、运输和环境的地理空间数据。此外，它还在经济、社会、环境和技术维度上评估了定性和定量数据。其次，采用两阶段模型进行分析：第一阶段利用地理信息系统（GIS）技术识别适合CCUS项目的区域，第二阶段使用TODIM方法对这些区域进行优先排序。研究在中国进行验证，确定了准噶尔盆地、塔里木盆地、鄂尔多斯盆地、四川盆地和渤海湾盆地适合CCUS部署。其中，华能罗庄电厂被认为是CCUS项目的最佳示范试点位置。最终的敏感性分析、情景分析和比较分析分别确认了模型的稳定性、动态性和可靠性。这些分析对不同决策偏好和战略导向下的最终优选结果的阐明也具有重要意义。本研究提出的CCUS项目决策和数据驱动优先模型的框架为决策者规划CCUS项目和制定支持政策提供了技术支持和实践依据。
【doi】
https://doi.org/10.1016/j.scs.2024.105754
【作者信息】
Jianli Zhou, 新疆大学经济与管理学院, 乌鲁木齐 830046, 中国；西北能源碳中和工程研究中心（ERCNECN），教育部，乌鲁木齐 830046, 中国；新疆宏观经济高质量发展研究院，乌鲁木齐 830046,中国；新疆能源碳中和决策研究中心，新疆大学，乌鲁木齐 830046, 中国
Shuxian Wu, 新疆大学经济与管理学院, 乌鲁木齐 830046, 中国；新疆能源碳中和决策研究中心，新疆大学，乌鲁木齐 830046,中国
Zhuohao Chen, 新疆大学经济与管理学院, 乌鲁木齐 830046, 中国；新疆能源碳中和决策研究中心，新疆大学，乌鲁木齐 830046,中国
Dandan Liu, 新疆大学经济与管理学院, 乌鲁木齐 830046, 中国；新疆能源碳中和决策研究中心，新疆大学，乌鲁木齐 830046,中国
Yaqi Wang, 新疆大学经济与管理学院, 乌鲁木齐 830046, 中国；新疆能源碳中和决策研究中心，新疆大学，乌鲁木齐 830046,中国
Zhiming Zhong, 亚利桑那大学系统与工业工程系, 图森, AZ 85721, 美国
Yunna Wu，北京市新能源与低碳发展重点实验室，华北电力大学，北京 102206, 中国
论文20
Can the resource and environmental dilemma due to water-energy-carbon constraints be solved in the process of new urbanization?
在新型城市化过程中，资源和环境因水-能源-碳约束而产生的困境能否得到解决？
【摘要】
The rapid development of basin resource-based cities (BRCs) in developing countries have led to severe resource and environmental problems centered on the “water-energy-carbon” (WEC) nexus. Based on their spatiotemporal evolution, WEC constraints are evaluated via a multidimensional coupling coordination degree (CCD) mode. Resource-environmental efficiency (REE) under these constraints is measured via the superefficiency SBM model. The path of resource and environmental improvement via new urbanization (NU) is discussed based on the spatial econometric model. Water resource consumption in the BRCs decreased by 12.22 %, but energy consumption and carbon emissions increased by 20.1 % and 70.05 %, respectively, and the CCD of the WEC nexus showed a “highly coordinated - seriously imbalanced” change. Therefore, the REE increase of 44.03 % was unsustainable. NU improved REE and reduced water resource consumption but did not reduce energy consumption or carbon emission, and there is significant regional variability. Scientific and technological innovation, economic agglomeration and land structure diversity contributed to the resource-environmental improvement effects of NU, but optimized industrial structures and environmental governance had masking effects. The policy implication is that during NU, efficiency gains must be combined with policies to promote industrial structure optimization and environmental governance and thus achieve sustainable urban development.
【摘要翻译】
快速发展的资源型城市（BRCs）在发展中国家引发了严重的资源和环境问题，特别是围绕“水-能源-碳”（WEC）之间的关系。基于其时空演变，通过多维耦合协调度（CCD）模式评估WEC约束。在这些约束下，通过超效率SBM模型测量资源环境效率（REE）。此外，基于空间计量经济模型讨论了通过新型城镇化（NU）改善资源和环境的路径。BRCs中的水资源消耗减少了12.22%，但能源消耗和碳排放分别增加了20.1%和70.05%，WEC之间的CCD表现出“高度协调-严重失衡”的变化。因此，REE增加44.03%并不可持续。NU改善了REE并减少了水资源消耗，但未能减少能源消耗或碳排放，并且存在显著的区域差异。科技创新、经济聚集和土地结构多样性促进了NU对资源环境改善的效果，但产业结构优化和环境治理却产生了掩盖效应。政策启示是，在NU过程中，效率提升必须与促进产业结构优化和环境治理的政策结合，从而实现可持续城市发展。
【doi】
https://doi.org/10.1016/j.scs.2024.105748
【作者信息】
Yuanyuan Zhang, 西安工程大学经济与管理学院，中国陕西省西安市阎乡路58号，邮政编码710054
Yi Yang，西安工程大学经济与管理学院，中国西安，邮政编码710054
论文21
The cooling effect of trees in high-rise building complexes in relation to spatial distance from buildings
高层建筑群中树木的降温效果与建筑的空间距离相关
【摘要】
Street trees are vital in mitigating urban heat islands, with their cooling effect significantly influenced by the urban layout. Past studies explored how urban canyon characteristics—aspect ratio, building coverage—affect tree cooling, yet seldom analyzed the impact of distance between trees and buildings. Addressing this, our study evaluates tree cooling effects concerning their proximity to shaded and sunlit walls. The findings highlight that cooling effectiveness varies with the ratio of distance from the shaded wall to building height (Dsha:H), peaking within a ratio range of 0.55 to 0.7. Below a ratio of 0.3, effectiveness decreases to 9–29 %, emphasizing the importance of strategic planting distances. The result shows that when planted at an optimal distance from buildings, small trees can produce similar radiation mitigation effects to those of larger trees. This discovery advocates for thoughtful tree placement in high-density areas, optimally leveraging their shade and evapotranspiration benefits. The study provides actionable insights for urban planners and landscape architects, suggesting that careful consideration of tree placement relative to building shadows can significantly improve urban climates, offering a strategic approach to deploying green infrastructure in high-rise complexes for enhanced climate resilience.
【摘要翻译】
街树在缓解城市热岛效应方面至关重要，其冷却效果受到城市布局的显著影响。以往的研究探讨了城市峡谷特征（如纵横比和建筑覆盖率）对树木冷却的影响，但很少分析树木与建筑之间距离的作用。本研究旨在评估树木冷却效果与其与阴影墙和阳光直射墙的距离之间的关系。研究结果表明，冷却效果与从阴影墙到建筑高度的距离比率（Dsha:H）相关，最佳比率范围为0.55至0.7。在比率低于0.3时，冷却效果降至9%至29%，强调了战略性种植距离的重要性。结果显示，当树木以最佳距离种植于建筑旁时，小树的辐射缓解效果可以与大树相当。这一发现提倡在高密度区域进行合理的树木种植，以最佳利用其遮荫和蒸散效益。研究为城市规划师和景观设计师提供了切实可行的见解，建议仔细考虑树木与建筑阴影的关系，以显著改善城市气候，从而为高层建筑群的绿色基础设施部署提供战略性方法，增强气候适应能力。
【doi】
https://doi.org/10.1016/j.scs.2024.105737
【作者信息】
Ji Yeon Kim, 首尔国立大学景观建筑跨学科项目，韩国首尔；集成智能城市全球融合项目，首尔国立大学，韩国首尔；智能生态科学专业研究生院，首尔国立大学，韩国首尔
SK森林重组团队，韩国首尔
Chae Yeon Park, 环境管理研究所，先进工业科学技术研究院（AIST），日本茨城县筑波
Dong Kun Lee, 首尔国立大学景观建筑跨学科项目，韩国首尔；集成智能城市全球融合项目，首尔国立大学，韩国首尔；首尔国立大学景观建筑与乡村系统工程系，韩国首尔
Seok Hwan Yun, 气候变化适应中心，国立环境研究所，16-2 Onogawa, 日本茨城县筑波，305-8506
Jung Hee Hyun, 系统风险与韧性研究组，应用系统分析国际研究所，奥地利
Eun Sub Kim，低碳与气候影响研究中心，香港城市大学能源与环境学院，九龙塘达志街
论文22
Mapping heterogeneity: Spatially explicit machine learning approaches for urban value uplift characterisation and prediction
映射异质性：城市价值提升特征和预测的空间显式机器学习方法
【摘要】
Understanding urban value uplift is essential for guiding public efforts towards vibrant economies and inclusive communities. Current research, however, often overlooks non-economic dimensions of urban values, resulting in biased socioeconomic outcomes and neglected socio-spatial heterogeneity for sustainable urban planning. This study employs spatially explicit machine learning (ML) approaches to comprehensively investigate the characterisation of urban value uplift and its predictors. Applying GWPCA to the municipality of Shanghai, the results reveal significant heterogeneity in urban value uplift characterisation. While the municipality shows a generally homogeneous polycentric growth pattern, central areas exhibit economic growth, and peripheral areas are enhanced with place value. Additionally, combining a Spatially Enhanced CatBoost algorithm (CTB-S) and SHAPley value, analysis on uplift predictors indicates that urban policy, among many other features, tends to catalyse further economic uplift specifically in central areas. Our findings underscore the inherent heterogeneity in urban change process, necessitating spatially tailored approaches for policymakers to capture urban value uplifts. By addressing the unique needs of different urban areas, policymakers can promote sustainable urban environments that ensure equitable economic and social benefits across all communities.
【摘要翻译】
理解城市价值提升对于指导公共努力实现充满活力的经济和包容性社区至关重要。然而，当前研究常常忽视城市价值的非经济维度，导致社会经济结果的偏差以及可持续城市规划中的社会空间异质性被忽略。本研究采用空间显式的机器学习（ML）方法，全面调查城市价值提升的特征及其预测因素。通过对上海市的GWPCA应用，结果揭示了城市价值提升特征的显著异质性。尽管该市总体表现出均匀的多中心增长模式，但中心区域展现经济增长，而周边区域则在地点价值上有所增强。此外，结合空间增强的CatBoost算法（CTB-S）和SHAPley值的分析显示，城市政策在众多特征中，往往会在中心区域催化进一步的经济提升。我们的发现强调了城市变化过程中的固有异质性，要求政策制定者采用空间量身定制的方法来捕捉城市价值提升。通过满足不同城市区域的独特需求，政策制定者可以促进可持续城市环境，确保所有社区获得公平的经济和社会利益。
【doi】
https://doi.org/10.1016/j.scs.2024.105742
【作者信息】
Xiuning Zhang, 伦敦大学学院巴特利特高级空间分析中心，伦敦 W1T 4TJ，英国
Yumo Zhu, 同济大学建筑与城市规划学院，上海市思平路 1239 号，中国
Wei Gan, 同济大学建筑与城市规划学院，上海市思平路 1239 号，中国
Yixuan Zou, 同济大学智能自主系统研究院，上海市思平路 1239 号，中国
Zhiqiang Wu，同济大学建筑与城市规划学院，上海市思平路 1239 号，中国
深圳市鹏城实验室数学与理论系，中国
论文23
Extension and trend of the London urban heat island under Lamb weather types
倫敦城市热岛效应在兰姆气象类型下的延续与趋势
【摘要】
Understanding and describing how urban heat islands evolve is important, given the noticeable impact they have on people living in cities. This paper considers the London heat island from gridded values with one-arcminute spatial resolution over a 33-year period, from 1990 to 2022. Among the available variables in the database, maximum and minimum air temperatures were used. A cold island was not observed, since temperatures in the city centre were higher than those in the surroundings during the day and at night. However, the urban heat island extension was higher for the maximum temperature, whereas this island was limited to the city centre for the minimum temperature, in line with the area delimited by the congestion charge. Lamb weather types were determined, and it was found that the anticyclonic type prevailed, followed by southwest, west, and cyclonic types. The difference between both temperatures was about 6.8 °C in the city centre, and was particularly defined for anticyclonic and cyclonic types. Moreover, anticyclonic situations were linked with the highest urban heat island intensities for minimum temperature. Finally, the temperature trend was similar for both temperatures –about 0.2–0.3 °C/10 years in the city centre– thereby offering a possible quantification of climate change.
【摘要翻译】
理解和描述城市热岛的演变是非常重要的，因为它们对城市居民的影响显著。本文考虑了伦敦热岛的情况，使用了1990年至2022年间、分辨率为1弧分的网格数据。在可用的变量中，使用了最高和最低气温。没有观察到冷岛现象，因为白天和夜间市中心的温度均高于周围地区。然而，最大气温的热岛扩展范围较大，而最小气温的热岛则仅限于市中心，这与拥堵收费区的边界相符。研究确定了兰姆天气类型，发现反气旋型占主导，其次是西南型、西风型和气旋型。市中心的两种气温差约为6.8 °C，特别是在反气旋和气旋类型中定义明显。此外，反气旋情况下最低气温的城市热岛强度最高。最后，两种气温的趋势相似——市中心约为0.2–0.3 °C/10年，这为气候变化提供了可能的量化依据。
【doi】
https://doi.org/10.1016/j.scs.2024.105743
【作者信息】
Isidro A. Pérez, 西班牙巴利亚多利德大学科学学院应用物理系，地址：Paseo de Belén, 7, 47011 Valladolid, Spain
M. Ángeles García, 西班牙巴利亚多利德大学科学学院应用物理系，地址：Paseo de Belén, 7, 47011 Valladolid, Spain
Saeed Rasekhi, 西班牙巴利亚多利德大学科学学院应用物理系，地址：Paseo de Belén, 7, 47011 Valladolid, Spain
Fatemeh Pazoki, 西班牙巴利亚多利德大学科学学院应用物理系，地址：Paseo de Belén, 7, 47011 Valladolid, Spain
Beatriz Fernández-Duque，西班牙国家研究委员会（IPE-CSIC）比利牛斯生态研究所，地址：Avda. Montañana, 1005, 50059 Zaragoza, Spain
论文24
Secure environmental, social, and governance (ESG) data management for construction projects using blockchain
使用区块链对建筑项目进行安全的环境、社会和治理 (ESG) 数据管理
【摘要】
Environmental, social, and governance (ESG) considerations are increasingly becoming imperative and obligatory across various industries. The ESG performance within the architecture, engineering, and construction (AEC) industry is under heightened market scrutiny. However, current ESG management in construction is still in its infancy due to two limitations: (1) a deficiency in ESG knowledge, such as indicators pertinent to construction activities, and (2) a lack of data security in ESG management, culminating in inefficient and unreliable environmental management practices. Therefore, this paper employs the Design Science Research Method (DSRM) to introduce a Blockchain-ESG Integrated (BESGI) framework, facilitating traceable ESG data management within construction projects. This framework presents three significant contributions. First, it identifies ten AEC-ESG indicators by analyzing ESG methods. Second, it proposes a mapping approach for AEC-ESG indicators to construction projects for key ESG information access and data source identification. Third, it develops a blockchain-based data management mechanism for traceable ESG data management in the BESGI framework. It validates and evaluates the framework in a construction project in Hong Kong. The results show that the framework is usable and can save labor costs by 20.15 % compared to traditional ESG management. This study offers a secure data management solution for ESG analysis of construction projects.
【摘要翻译】
环境、社会和治理（ESG）考虑在各个行业中越来越变得重要和必不可少。在建筑、工程和施工（AEC）行业，ESG表现正受到更高的市场审查。然而，目前施工中的ESG管理仍处于初级阶段，主要受限于两个方面：(1) ESG知识的缺乏，例如与施工活动相关的指标，以及(2) ESG管理中的数据安全性不足，导致环境管理实践低效且不可靠。因此，本文采用设计科学研究方法（DSRM）引入了一个区块链-ESG集成框架（BESGI），以促进施工项目中可追溯的ESG数据管理。该框架有三个重要贡献。首先，通过分析ESG方法，识别出十个AEC-ESG指标。其次，提出了一种将AEC-ESG指标映射到施工项目中的方法，以便访问关键的ESG信息和识别数据源。第三，开发了一种基于区块链的数据管理机制，用于在BESGI框架中实现可追溯的ESG数据管理。该框架在香港的一项施工项目中得到了验证和评估。结果显示，该框架可用，并且与传统ESG管理相比，可以节省20.15%的人工成本。本研究为施工项目的ESG分析提供了一个安全的数据管理解决方案。
【doi】
https://doi.org/10.1016/j.scs.2024.105582
【作者信息】
Xingbo Gong, 香港科技大学土木与环境工程系，香港
Xingyu Tao, 香港科技大学土木与环境工程系，香港
Ming Zhang, 中国建筑工程（香港）有限公司，香港
Yuqing Xu, 香港科技大学土木与环境工程系，香港
Helen H.L. Kwok, 香港科技大学土木与环境工程系，香港
Ji Dai, 中国建筑工程（香港）有限公司，香港
Jack C.P. Cheng，香港科技大学土木与环境工程系，香港
论文25
Profiling residential energy vulnerability: Bayesian-based spatial mapping of occupancy and building characteristics
住宅能源脆弱性剖析：基于贝叶斯的空间占用和建筑特征映射
【摘要】
With global trends in electrification, communities highly dependent on electricity are facing increasing challenges, particularly due to more frequent weather events, which lead to significant surges in electricity demand or result in blackouts. However, the impact is disproportionate across space and time, which raises an urgent need to comprehensively assess residential energy vulnerabilities to ensure energy security for households. Existing methodologies, whether large-scale regional assessments or community-based surveys, predominantly rely on static data. This reliance significantly limits their ability to capture the spatial and temporal dynamics of energy vulnerability, which is particularly important in the face of climate change. This study analyses residential energy vulnerability in the dimensions of social vulnerability, building resilience, and energy burden by innovatively linking occupancy patterns with the built environment through a Bayesian-based spatial mapping methodology. We applied this method through a case study in a Philadelphia census tract area identified for its high vulnerability based on FEMA's National Risk Index. By mapping occupancy with residential buildings, we simulated the energy consumption patterns of approximately 900 residential buildings. The simulations utilized DOE single-family energy prototypes, tailored to account for empirical occupancy and building features, to predict hourly energy consumption and assess indoor thermal comfort during power outages on days with extreme temperatures. The findings reveal disparities across different dimensions of energy vulnerability and illustrate the dynamic nature of energy vulnerability that fluctuates with daily activities. The study also highlights areas with low thermal resilience, suggesting a need for retrofitting older buildings to improve energy efficiency. The implications of this research extend beyond the built environment to the socioeconomic aspects of energy use, advocating for adaptive community planning and the development of resilient energy infrastructures. The results serve as a foundation for stakeholders to implement targeted interventions, prioritize retrofitting efforts, and support equitable access to energy resources, thereby enhancing urban sustainability and resilience.
【摘要翻译】
随着全球电气化趋势的发展，对电力高度依赖的社区面临着日益严峻的挑战，尤其是由于频繁的天气事件，这导致电力需求显著激增或出现停电情况。然而，影响在时间和空间上并不均衡，这迫切需要全面评估住宅能源脆弱性，以确保家庭的能源安全。现有的方法论，无论是大规模区域评估还是基于社区的调查，主要依赖静态数据。这种依赖显著限制了它们捕捉能源脆弱性空间和时间动态的能力，而这种能力在气候变化背景下尤为重要。本研究通过一种基于贝叶斯的空间映射方法，创新性地将占用模式与建筑环境相结合，分析了住宅能源脆弱性，包括社会脆弱性、建筑韧性和能源负担。我们通过对费城一个基于FEMA国家风险指数识别出的高脆弱性普查区进行案例研究，应用了这一方法。通过将占用情况与住宅建筑映射，我们模拟了大约900栋住宅建筑的能源消费模式。模拟使用了DOE单户住宅能量原型，调整以考虑经验占用和建筑特征，预测了每小时的能量消耗，并评估了极端温度天停电期间的室内热舒适度。研究结果揭示了能源脆弱性不同维度之间的差异，并展示了能源脆弱性的动态特性，随着日常活动而波动。研究还突出了低热韧性区域，建议对老旧建筑进行改造以提高能源效率。该研究的影响超越了建筑环境，涉及能源使用的社会经济方面，倡导适应性社区规划和韧性能源基础设施的发展。这些结果为利益相关者提供了实施有针对性的干预、优先改造努力以及支持公平获取能源资源的基础，从而增强城市的可持续性和韧性。
【doi】
https://doi.org/10.1016/j.scs.2024.105667
【作者信息】
Chen Xia, 博士候选人，宾夕法尼亚州立大学建筑工程系，美国宾夕法尼亚州大学公园，邮政编码16802
Yuqing Hu，助理教授，宾夕法尼亚州立大学建筑工程系，美国宾夕法尼亚州大学公园，邮政编码16802
论文26
Tackling the modifiable areal unit problem: Enhancing urban sustainability through improved land surface temperature and its influencing factors analysis
解决可修改区域单元问题：通过改进土地表面温度及其影响因素分析提升城市可持续性
【摘要】
Exploring the modifiable areal unit problem (MAUP) in land surface temperature (LST) and its influencing factors is crucial for understanding LST variation patterns and quantifying the factors' impact. Neglecting the MAUP could lead to an incomplete understanding of LST changes and their driving mechanisms. This study used optimal parameters-based geographical detector and gradient boosting regressor models to investigate the MAUP in LST and its influencing factors. The analysis covered 87 cities across seven climate zones in China, examining MAUP in 12 spatial scales to discern the scale and zoning effects on LST and its influencing factors. The research findings were as follows: (1) The sensitivity of LST influencing factors to spatial scales exhibited both spatial and temporal heterogeneity. Significant differences in the q-values of LST influencing factors were observed across various climate zones and periods (daytime and nighttime), with human factors, particularly those related to residents' work, buildings, life, and rest, showing higher spatial scale dependency than natural factors. (2) Zoning effects significantly impacted the q-values of LST influencing factors and were closely linked to the discretization methods and quantities used, which could alter the trends of these q-values. (3) Across the 12 spatial scales, more than 67.34 % of LST influencing factor interaction types were classified as bi-variable enhancement types. The q-values for LST influencing factor interactions were higher and more stable than those of single factors. LST influencing factor interactions in transitional climate zones exhibited high sensitivity to spatial scales. This research enhances our understanding of LST variations, providing valuable insights for urban climate adaptability planning and the development of climate-resilient cities.
【摘要翻译】
探索可变区域单元问题（MAUP）在地表温度（LST）及其影响因素中的作用对于理解LST变化模式和量化影响因素的影响至关重要。忽视MAUP可能导致对LST变化及其驱动机制的理解不完整。本研究使用基于最优参数的地理探测器和梯度提升回归模型，调查了LST及其影响因素中的MAUP。分析涵盖中国七个气候区的87个城市，考察了12种空间尺度下的MAUP，以辨别尺度和区域划分对LST及其影响因素的影响。研究结果如下：LST影响因素对空间尺度的敏感性表现出空间和时间的异质性。在不同气候区和时间段（白天和夜间），LST影响因素的q值存在显著差异，人为因素，尤其与居民的工作、建筑、生活和休息相关的因素，对空间尺度的依赖性高于自然因素。区域划分效应显著影响LST影响因素的q值，并与所使用的离散化方法和数量密切相关，这可能改变这些q值的趋势。在12种空间尺度中，超过67.34%的LST影响因素交互类型被归类为双变量增强类型。LST影响因素交互的q值高于且比单一因素更稳定。过渡气候区的LST影响因素交互对空间尺度表现出高敏感性。本研究加深了对LST变化的理解，为城市气候适应性规划和气候韧性城市的发展提供了宝贵的见解。
【doi】
https://doi.org/10.1016/j.scs.2024.105747
【作者信息】
Haojian Deng, 广东省城市化与地理模拟重点实验室，广东省公共安全与灾害工程研究中心，中山大学地理与规划学院，中国广州 510006
Kai Liu, 广东省城市化与地理模拟重点实验室，广东省公共安全与灾害工程研究中心，中山大学地理与规划学院，中国广州 510006；南方海洋科学与工程广东实验室，中国珠海 519000
JiaLi Feng, 粤港澳大湾区天气监测预警与预测研究中心（深圳气象创新研究院），中国深圳 518000
Yongzhu Xiong，嘉应学院地理与旅游学院，中国梅州 514015；广东省山区特色农业资源保护与精准利用重点实验室，中国梅州514105
论文27
Efficient message authentication scheme with forward and backward security in Vehicle Cloud Network towards sustainable smart city
面向可持续智慧城市的车辆云网络中的高效消息认证方案，具备前向和后向安全性
【摘要】
The Vehicular Cloud Network (VCN) serves as a crucial component of Intelligent Transportation Systems (ITS), playing an instrumental role in the development of sustainable smart cities. It merges the benefits of both Vehicular Ad Hoc Networks (VANET) and cloud computing. However, VCN faces significant security challenges due to the complexity of communication, the dynamic nature of the environment, and the privacy concerns of data. To address the issues of message security and privacy preservation in VCN, this paper introduces an identity-based key-insulated ring signature (ID-KIRS) scheme for VCN message authentication. Our scheme integrates a secure key update function to address key exposure issues, providing both forward and backward security. The security analysis confirms that our scheme ensures message integrity, unconditional anonymity, and unforgeability. The performance evaluation clearly demonstrates our scheme is efficient, and applicable to vehicle congestion situations, especially car accident scenarios.
【摘要翻译】
车辆云网络（VCN）是智能交通系统（ITS）的关键组成部分，在可持续智能城市的发展中发挥着重要作用。它结合了车辆自组网（VANET）和云计算的优势。然而，由于通信的复杂性、环境的动态性以及数据隐私问题，VCN面临着重大安全挑战。为了解决VCN中的消息安全和隐私保护问题，本文提出了一种基于身份的密钥隔离环签名（ID-KIRS）方案，用于VCN消息认证。我们的方案集成了安全密钥更新功能，以解决密钥暴露问题，提供前向和后向安全性。安全性分析确认我们的方案确保消息的完整性、无条件匿名性和不可伪造性。性能评估清晰地表明，我们的方案高效且适用于车辆拥堵情况，尤其是交通事故场景。
【doi】
https://doi.org/10.1016/j.scs.2024.105732
【作者信息】
Luona Yin, 南京邮电大学，中国南京
Huaqun Wang，南京邮电大学，中国南京
论文28
Traffic assignment optimization to improve urban air quality with the unified finite-volume physics-informed neural network
交通分配优化以改善城市空气质量，结合统一有限体积物理信息神经网络
【摘要】
Emissions by road transportation constitute the major contributor of air pollutants to threat the public health, especially on mega cities with high-rise buildings and growing population. A practicable and economical remedy is assigning the traffic volume judiciously, termed traffic assignment optimization (TAO). Incorporating the computational fluid dynamics (CFD), this method provides precisely optimized traffic volumes under versatile meteorological conditions. However, the high-dimensional degree of freedoms (DoF) involved in CFD hampers its further application toward the large-scale problem where a massive urban area is considered. With the more complicated urban traffic network, the larger decision variable dimension also impedes the time-efficient acquisition of the optimization results. To alleviate this curse-of-dimensionality, the current work proposes an optimization framework with the surrogate model based on the unified finite-volume physics-informed neural networks (UFV-PINN). The UFV-PINN plays the dual role as the partial differential equation (PDE) solver and the surrogate model for pollutant concentration prediction. It reduces the DoF within the PDE solution process and enables the gradient-based optimization. The current work optimizes the average CO concentration and accumulative travel time in Kowloon peninsula of Hong Kong, using the multiple-gradient descent algorithm (MGDA). This optimization framework is tested with various working conditions. Results indicate that the proposed method attain high accuracy solutions, comparable to the heuristic algorithms. This study is the first attempt to incorporate UFV-PINN into the TAO with air quality consideration. Endowed with the differentiability by UFV-PINN, the framework will facilitate the TAO to provide precise suggestions toward large-scale problems.
【摘要翻译】
道路交通排放是空气污染物的主要来源，严重威胁公众健康，尤其是在高层建筑密集和人口增长的特大城市中。一个可行且经济的解决方案是合理分配交通流量，称为交通分配优化（TAO）。结合计算流体动力学（CFD），该方法在多变气象条件下提供精确优化的交通流量。然而，CFD中涉及的高维自由度（DoF）阻碍了其在大规模问题中的进一步应用，特别是在考虑庞大城市区域时。随着城市交通网络的复杂化，决策变量维度的增加也妨碍了优化结果的快速获取。为了解决这一维数诅咒，当前工作提出了一种基于统一有限体积物理信息神经网络（UFV-PINN）的优化框架。UFV-PINN同时充当偏微分方程（PDE）求解器和污染物浓度预测的替代模型，降低了PDE求解过程中的DoF，并支持基于梯度的优化。本研究优化了香港九龙半岛的平均CO浓度和累计旅行时间，使用多梯度下降算法（MGDA）。该优化框架在不同工作条件下进行了测试，结果表明，所提方法在精度上与启发式算法相当。这项研究首次将UFV-PINN纳入考虑空气质量的TAO中，凭借UFV-PINN的可微性，该框架将促进TAO在大规模问题上提供精准建议。
【doi】
https://doi.org/10.1016/j.scs.2024.105750
【作者信息】
Di Mei, 香港大学机械工程系，香港薄扶林道，哈京黄大楼7楼
Ziwei Mo, 中山大学大气科学学院及南方海洋科学与工程广东实验室，中国珠海
Kangcheng Zhou, 香港大学机械工程系，香港薄扶林道，哈京黄大楼7楼
南方科技大学力学与航空航天工程系，中国深圳
Chun-Ho Liu，香港大学机械工程系，香港薄扶林道，哈京黄大楼7楼
论文29
Sectoral carbon emission prediction and spatial modeling framework: A local climate zone-based case study of the Guangdong-Hong Kong-Macao Greater Bay Area
部门碳排放预测和空间建模框架：广东-香港-澳门大湾区的当地气候区案例研究
【摘要】
Understanding the spatio-temporal pattern of carbon emission (CE) is prerequisite for formulating carbon reduction policies. Previous studies emphasized quantitative analysis of CE inventory while ignoring sectoral spatial distribution. This study fills this gap by developing a framework for coupling the CE quantitative prediction model with the sectoral CE spatial model based on the Long-range Energy Alternatives Planning (LEAP) model, spatial proxy data and local climate zone (LCZ). The framework's sectoral CE results reveal a great varied landscape within the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), one of the leading bay areas in the world with rapid urbanization and emphasis on low-carbon development, under four carbon reduction scenarios. By 2060, the CN3 scenario that considers both energy-supply and consumption sides, predicts a drastic emission cut to 35.76 million tons, just 10 % of the business as usual (BAU) scenario's forecast, mainly from transportation (29.45 million tons) and industry (9.34 million tons) sectors. Besides, compared with the common CE spatial products, the spatial simulation results of sectoral CE in our framework present detailed spatial differences at the jurisdictional level. The findings are conducive for governments to formulate accurate CE reduction and optimization strategies of the cities towards to the 2060 carbon neutrality.
【摘要翻译】
了解碳排放（CE）的时空模式是制定减排政策的前提。以往研究强调了CE库存的定量分析，而忽略了行业的空间分布。本研究通过构建一个框架，将CE定量预测模型与基于长期能源替代计划（LEAP）模型、空间代理数据和地方气候区（LCZ）的行业CE空间模型相结合，填补了这一空白。该框架的行业CE结果揭示了粤港澳大湾区（GBA）在四种减碳情景下的显著空间差异，这是一个快速城市化并重视低碳发展的世界领先湾区。到2060年，CN3情景考虑了能源供给和消费两方面，预测排放量将骤降至3576万吨，仅为“照常营业”（BAU）情景预测的10%，主要来自交通（2945万吨）和工业（934万吨）部门。此外，与常见的CE空间产品相比，我们框架的行业CE空间模拟结果在行政区级别上呈现了详细的空间差异。这些发现有助于政府为各城市制定准确的CE减排和优化策略，以实现2060年碳中和目标。
【doi】
https://doi.org/10.1016/j.scs.2024.105756
【作者信息】
RenFeng Wang, 香港大学建筑系景观建筑学部，中国香港
Chao Ren, 香港大学建筑系景观建筑学部
Cuiping Liao, 中国科学院广州能源所，中国广州 510640
Ying Huang, 中国科学院广州能源所，中国广州 510640
Zhen Liu, 中国科学院广州能源所，中国广州 510640
Meng Cai，武汉大学城市设计学院，中国武汉 430072
论文30
Spatial distribution of old neighborhoods based on heat-related health risks assessment: A case study of Changsha City, China
基于热相关健康风险评估的老旧社区空间分布：中国长沙市的案例研究
【摘要】
Assessing the heat-related health risks is crucial for promoting the sustainable development of cities, particularly in the face of extreme climates and urban human settlement governance. Heat health risk assessment serves as a foundational element within the risk governance framework, serving to mitigate heat-related morbidity and mortality rates. The revitalization of old neighborhoods, especially those situated in city centers with deficient facilities, emerges as a critical imperative within this context. This study chose Changsha, a city in Central China that is severely affected by high temperatures and has numerous old neighborhoods, as a case study. We developed a heat risk framework that incorporates city level risk, exposure, vulnerability, and the adaptation of old neighborhoods. Validated through data accessed from medical facilities visit, the framework effectively reflects the distribution of heat risks. By combining qualitative and quantitative methods, we investigated the correlation between heat health risk levels and the behaviors of residents in old neighborhoods. The results indicate that urban planners should prioritize comprehensive renovations in medium-risk neighborhoods, resident behavior management in low-risk neighborhoods, and the indoor thermal environment in high-risk neighborhoods. This framework plays an important role in the assessment of future spatial risk for old neighborhoods renewal.
【摘要翻译】
评估与热相关的健康风险对促进城市的可持续发展至关重要，尤其是在面对极端气候和城市人居治理的背景下。热健康风险评估作为风险治理框架中的基础要素，有助于降低与热相关的发病率和死亡率。老旧社区的 revitalization，特别是在设施不足的市中心，成为当务之急。本研究选择了中央中国的长沙市作为案例，该市高温严重且有众多老旧社区。我们开发了一个热风险框架，涵盖城市级风险、暴露、脆弱性以及老旧社区的适应性。通过访问医疗设施的数据进行验证，该框架有效反映了热风险的分布。结合定性和定量方法，我们研究了热健康风险水平与老旧社区居民行为之间的关联。结果表明，城市规划者应优先考虑中等风险社区的全面改造、低风险社区的居民行为管理，以及高风险社区的室内热环境。该框架在评估未来老旧社区更新的空间风险中发挥了重要作用。
【doi】
https://doi.org/10.1016/j.scs.2024.105740
【作者信息】
Yuquan Xie, 湖南大学建筑与规划学院，中国长沙 410082；湖南省山区城乡人居环境科学重点实验室，中国长沙 410082；湖南省地方建筑科技创新合作基地，中国长沙 410082
Feng Xu, 湖南大学建筑与规划学院，中国长沙 410082；湖南省山区城乡人居环境科学重点实验室，中国长沙 410082；湖南省地方建筑科技创新合作基地，中国长沙 410082
Qiang Ye,湖南大学建筑与规划学院，中国长沙 410082；湖南省山区城乡人居环境科学重点实验室，中国长沙 410082；湖南省地方建筑科技创新合作基地，中国长沙 410082
Zhiqiang Zhai (John), 科罗拉多大学博尔德分校土木、环境与建筑工程系，美国博尔德，CO
Haoran Yang, 湖南大学建筑与规划学院，中国长沙 410082；湖南省山区城乡人居环境科学重点实验室，中国长沙 410082；湖南省地方建筑科技创新合作基地，中国长沙 410082
Xi Feng, 湖南省气象信息中心，中国长沙
Jiachi Shi, 湖南省气象信息中心，中国长沙
Wen Hu，长沙理工大学建筑学院，中国长沙 410076
Projects as game changers for navigating sustainability transitions in societies: Multi-level effects from micro-level decisions
项目作为引导社会可持续转型的游戏改变者：微观决策的多层次影响
【摘要】
Sustainable development and sustainability transitions are becoming increasingly significant in research and practice due to immense challenges that social, economic, and environmental ecosystems are grappling with, such as climate change. Projects as interventions are game-changers in addressing these challenges, as decisions made in projects impact both project success and sustainability transition trajectories in societies. This study developed a conceptual framework through which the cruciality of decisions in different scenarios is evaluated to showcase how the priority of project managers' decisions at the project level (i.e., micro-level) not only impacts the same level but also has butterfly effects on overall sustainability transitions at the broader societal levels (i.e., meso-level and macro-level). To reflect real-world complexities, we drew on various perspectives and theories, namely projects-as-interventions perspective, project-as-practice perspective, socio-technical perspective, actor-network theory, and decision theory, along with comparative analysis. The findings underscored that the project managers' awareness of sustainability transitions throughout the project life cycle (PLC) may change the prioritization and cruciality of decisions, and those can subsequently trigger societal sustainability transitions. Besides, the sensitivity of decision-making in line with sustainability in international and regional projects is more than in national and local projects. Therefore, this study primarily contributes to making sustainable decisions within projects while navigating sustainability transitions at the broader societal levels.
【摘要翻译】
可持续发展和可持续性转型在研究和实践中越来越重要，因为社会、经济和环境生态系统正面临气候变化等巨大挑战。作为干预措施的项目在应对这些挑战中发挥了关键作用，因为项目中所做的决策影响着项目的成功以及社会可持续性转型的轨迹。本研究开发了一个概念框架，通过该框架评估不同情境下决策的重要性，以展示项目经理在项目层面（微观层面）决策的优先级如何不仅影响该层面，还对更广泛社会层面（中观层面和宏观层面）的整体可持续性转型产生蝴蝶效应。为反映现实世界的复杂性，我们借鉴了项目作为干预、项目作为实践、社会技术、行为者网络理论和决策理论等多种视角和理论，并进行了比较分析。研究结果强调了项目经理在项目生命周期（PLC）中对可持续性转型的意识可能会改变决策的优先级和重要性，这些变化可能会触发社会可持续性转型。此外，国际和区域项目中的决策对可持续性的敏感性高于国家和地方项目。因此，本研究主要为在项目中做出可持续决策贡献了理论支持，同时在更广泛的社会层面导航可持续性转型。
【doi】
https://doi.org/10.1016/j.scs.2024.105758
【作者信息】
Amir Bahadorestani, 悉尼大学工程学院项目管理系，澳大利亚新南威尔士州大悉尼，邮政编码2037；悉尼大学约翰·格里尔项目领导力研究所，澳大利亚新南威尔士州大悉尼，邮政编码2037
Nasser Motahari Farimani, 马什哈德福尔多西大学经济与商业管理学院，伊朗马什哈德，邮政编码9177948974
Jan Terje Karlsen，挪威商学院领导与组织行为系，奥斯陆尼达尔斯维恩37号，邮政编码0484
