Sustainable Cities and Society最新文献_第7页

Scale effect on the relationship between urban landscape patterns and land surface temperature 城市景观模式与地表温度之间关系的规模效应

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

Sustainable Cities and Society

Pub Date : 2024-10-28 DOI: 10.1016/j.scs.2024.105942

Anqi Zhang , Chang Xia

Great efforts have been made to examine the linkages between land surface temperature (LST) and urban landscape patterns (ULPs), which, however, focus on a single spatial scale and linear relationships. This study aims to examine the influence range of four key ULP indicators on LST, namely the sky view factor (SVF) and three indices of built-up area, greens, and blue spaces. The analyses are conducted at the street block level in 38 big cities in China and leverage a multiscalar approach to investigate change patterns of indicators within multiple buffer zones and identify the buffer distance that yields the greatest influence. Results reveal that (1) the greatest local impacts are produced within 0 − 150 m buffer zones in most cities for all key ULP metrics; (2) the maximum impacts of most indicators in summer are greater than in other seasons; and (3) the influence magnitude of key ULP indicators increases after considering the scale effect, and the influence of SVF varies significantly across cities. Results suggest that the consideration of maximum influence ranges of ULP indicators can better explain LST spatial variations. Our findings offer evidence on the local impact of ULPs on LST and contribute to urban design in urban heat mitigation.

人们在研究地表温度（LST）与城市景观格局（ULPs）之间的联系方面做了大量工作，但这些工作主要集中在单一的空间尺度和线性关系上。本研究旨在考察四个主要城市景观格局指标对地表温度的影响范围，即天空视线系数（SVF）以及建筑面积、绿地和蓝地三个指数。研究在中国38个大城市的街区层面进行分析，采用多尺度方法研究多个缓冲区内指标的变化规律，并确定影响最大的缓冲距离。结果表明：（1）在大多数城市中，所有关键ULP指标在0-150米缓冲区内产生的局部影响最大；（2）大多数指标在夏季的最大影响大于其他季节；（3）考虑尺度效应后，关键ULP指标的影响幅度增大，SVF的影响在不同城市之间存在显著差异。结果表明，考虑ULP指标的最大影响范围可以更好地解释LST的空间变化。我们的研究结果为ULP对LST的局部影响提供了证据，有助于城市热量减缓的城市设计。

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引用次数: 0

Dynamic integrated simulation of carbon emission reduction potential in China's building sector 中国建筑行业碳减排潜力的动态综合模拟

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

Sustainable Cities and Society

Pub Date : 2024-10-28 DOI: 10.1016/j.scs.2024.105944

Qiang Du , Zilang Wan , Mengqi Yang , Xiaoyan Wang , Libiao Bai

The building sector has received increasing attention due to its significant contribution to carbon emissions and great reduction potential. With continuous technology implementation, it is critical to identify the trajectories of emissions and potential reduction for China's building sector to achieve carbon peak and carbon neutrality targets. This study develops an integrated model by combining the system dynamics (SD) model and the long-range energy alternatives planning (LEAP) model to estimate energy consumption and carbon emissions of different types of buildings. The LEAP model is constructed based on the predictions from the SD model, which identifies the critical activity level parameters including number of households and building stocks by type. Coupled with scenario analysis, the model is applied to simulate the building emissions reduction potential and the contribution of five mitigation technologies across four scenarios. The results indicate that carbon emissions will peak at 2.80 Billion tons (Bt) in 2032 under the business as usual scenario (BAS). By 2060, reductions of 28.55 %, 59.03 %, and 76.53 % will be achieved under the advanced technology scenario (ATS), intersectoral synergistic scenario (ISS), and continuous improvement scenario (CIS), respectively. Among the five technologies, electrification and efficient end-use device technologies contribute the greatest reductions of 0.16 Bt and 0.23 Bt, respectively. Under the CIS, carbon emissions will advance toward 2024 with a peak of 2.47 Bt. This study not only provides a theoretical tool for energy and emissions analysis but also formulates targeted technology roadmaps for building sector emission mitigation.

建筑行业因其对碳排放的重要贡献和巨大的减排潜力而受到越来越多的关注。随着技术的不断实施，确定中国建筑行业的排放轨迹和减排潜力对于实现碳峰值和碳中和目标至关重要。本研究结合系统动力学（SD）模型和远期能源替代规划（LEAP）模型，建立了一个综合模型，用于估算不同类型建筑的能耗和碳排放。LEAP 模型是根据 SD 模型的预测建立的，该模型确定了关键的活动水平参数，包括家庭数量和不同类型的建筑存量。结合情景分析，该模型用于模拟四种情景下的建筑减排潜力和五种减排技术的贡献。结果表明，在 "一切照旧 "情景（BAS）下，碳排放量将在 2032 年达到峰值 28.0 亿吨（Bt）。到 2060 年，在先进技术情景（ATS）、部门间协同情景（ISS）和持续改进情景（CIS）下，将分别实现 28.55%、59.03% 和 76.53% 的减排。在这五种技术中，电气化和高效终端设备技术的减排量最大，分别为 0.16 Bt 和 0.23 Bt。在 CIS 条件下，碳排放量将在 2024 年达到峰值 24.7 Bt。这项研究不仅为能源和排放分析提供了理论工具，还为建筑行业减排制定了有针对性的技术路线图。

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引用次数: 0

Large language model as parking planning agent in the context of mixed period of autonomous vehicles and Human-Driven vehicles 在自动驾驶车辆和人工驾驶车辆混合使用的情况下，作为停车规划代理的大型语言模型

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

Sustainable Cities and Society

Pub Date : 2024-10-28 DOI: 10.1016/j.scs.2024.105940

Yuping Jin , Jun Ma

Autonomous vehicles (AVs) are anticipated to revolutionize future transportation, necessitating updates to traffic infrastructure, particularly parking facilities, due to the unique characteristics of AVs compared to Human-Driven Vehicles (HDVs). During the transition period in which AVs and HDVs coexist, adaptable infrastructure is essential to accommodate both vehicle types. Traditional research, typically reliant on complex mathematical models and simulations, faces challenges in adapting to diverse urban settings, requiring substantial time and resources. To address these challenges, a government-level framework was developed, enabling urban planners to quickly and accurately evaluate and optimize existing parking facilities for future AV and HDV coexistence scenarios. The framework integrates a Large Language Model (LLM) to enhance flexibility and efficiency in parking planning throughout the transitional period. Structured guidance is incorporated to enhance decision-making precision and reduce LLM hallucination risks. The flexibility, robustness, and accuracy of the framework were validated through step-by-step and end-to-end testing using real-world datasets. Specifically, the framework achieved 91.1 % comprehensiveness and 70.2 % consistency in Indicator Selection Module testing, a 68.9 % success rate in the Single Indicator Calculation Module, and a 66.7 % success rate in end-to-end testing, demonstrating its practical value in supporting cities during AV integration. Finally, the success rates of different LLM agent modules were further explored, along with a comparison of multiple LLMs and an analysis of key issues related to LLM trustworthiness in urban planning applications. The research highlights the potential of LLMs in advancing urban planning processes and optimizing existing infrastructure, contributing to smarter and more adaptable urban environments.

由于自动驾驶汽车（AV）与人类驾驶汽车（HDV）相比具有独特的特点，预计自动驾驶汽车（AV）将彻底改变未来的交通状况，因此有必要更新交通基础设施，特别是停车设施。在自动驾驶汽车与普通汽车共存的过渡时期，适应性强的基础设施对于同时容纳两种类型的车辆至关重要。传统的研究通常依赖于复杂的数学模型和模拟，在适应多样化的城市环境方面面临挑战，需要大量的时间和资源。为了应对这些挑战，我们开发了一个政府层面的框架，使城市规划者能够快速、准确地评估和优化现有停车设施，以适应未来 AV 和 HDV 共存的场景。该框架整合了大型语言模型（LLM），以提高整个过渡时期停车规划的灵活性和效率。结构化指导被纳入其中，以提高决策的准确性并降低 LLM 出现幻觉的风险。该框架的灵活性、稳健性和准确性通过使用真实世界数据集进行的逐步和端到端测试得到了验证。具体而言，该框架在指标选择模块测试中实现了 91.1% 的全面性和 70.2% 的一致性，在单一指标计算模块中实现了 68.9% 的成功率，在端到端测试中实现了 66.7% 的成功率，证明了其在支持城市进行视听集成方面的实用价值。最后，研究人员进一步探讨了不同 LLM 代理模块的成功率，并对多个 LLM 进行了比较，还分析了与 LLM 在城市规划应用中的可信度有关的关键问题。这项研究强调了 LLM 在推进城市规划进程和优化现有基础设施方面的潜力，有助于创造更智能、适应性更强的城市环境。

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引用次数: 0

Exploring the climatic conditions effect on spatial urban photovoltaic systems development using a spatial multi-criteria decision analysis: A multi-city analysis 利用空间多标准决策分析探讨气候条件对城市空间光伏系统开发的影响：多城市分析

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

Sustainable Cities and Society

Pub Date : 2024-10-28 DOI: 10.1016/j.scs.2024.105941

Abouzar Gholamalizadeh , Saman Nadizadeh Shorabeh , Kianoosh Choubineh , Alireza Karimi , Laleh Ghahremani , Mohammad Karimi Firozjaei

Identifying suitable locations for urban photovoltaic systems (UPVS) is crucial for achieving sustainable energy objectives and designing smart, eco-friendly cities. This study assesses the potential for UPVS expansion in eight cities across different climatic zones in Iran using a spatial multi-criteria decision-making method. Two scenarios were analyzed: the first compared spatial potential within each city, and the second compared potential between cities. The findings indicate that rooftops of the tallest buildings in densely populated areas, especially those with high solar energy output and sky view factor, hold the greatest potential for UPVS development. These locations are often near parks, commercial centers, and road networks. In the first scenario, Ardabil (5.70%), Gorgan (4.65%), Mashhad (5.46%), Tehran (8.10%), Kermanshah (5.76%), Shahrekord (3.41%), Kerman (8.67%), and Zahedan (8.56%) show significant potential for photovoltaic development. In the second scenario, cities in hot, dry climates like Zahedan and Kerman exhibit greater potential compared to cities in moderate, humid climates like Ardabil and Gorgan. Based on the analysis of this scenario, Ardabil (0.04%), Gorgan (1.49%), Mashhad (5.58%), Tehran (5.06%), Kermanshah (0.00%), Shaherkord (0.03%), Kerman (21.70%) and Zahedan (39.11%) showed a very high potential for UPVS development. The results of this study offer valuable insights for urban solar energy planning.

确定城市光伏系统（UPVS）的合适位置对于实现可持续能源目标和设计智能、生态友好型城市至关重要。本研究采用空间多标准决策方法，对伊朗不同气候带八个城市的 UPVS 扩展潜力进行了评估。研究分析了两种方案：第一种方案比较了每个城市内部的空间潜力，第二种方案比较了城市之间的潜力。研究结果表明，人口稠密地区最高建筑的屋顶，尤其是太阳能输出和天空视角系数较高的屋顶，具有最大的 UPVS 开发潜力。这些地点通常靠近公园、商业中心和道路网络。在第一种情况下，阿尔达比勒（5.70%）、戈尔甘（4.65%）、马什哈德（5.46%）、德黑兰（8.10%）、克尔曼沙赫（5.76%）、沙雷科德（3.41%）、克尔曼（8.67%）和扎赫丹（8.56%）显示出巨大的光伏发展潜力。在第二种情况下，扎黑丹和克尔曼等气候炎热干燥的城市与阿尔达比勒和戈尔甘等气候温和潮湿的城市相比，表现出更大的潜力。根据对这一情景的分析，阿尔达比勒（0.04%）、戈尔甘（1.49%）、马什哈德（5.58%）、德黑兰（5.06%）、克尔曼沙赫（0.00%）、沙赫科德（0.03%）、克尔曼（21.70%）和扎黑丹（39.11%）显示出极高的 UPVS 发展潜力。这项研究的结果为城市太阳能规划提供了宝贵的启示。

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引用次数: 0

Energy management based on coalitionnal game subdivision applied to energy communities 基于联盟博弈细分的能源管理应用于能源社区

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

Sustainable Cities and Society

Pub Date : 2024-10-24 DOI: 10.1016/j.scs.2024.105911

Adrien Bossu , Benoit Durillon , Arnaud Davigny , Hervé Barry , Fateh Belaïd , Benoît Robyns , Christophe Saudemont

The energy transition requires rethinking how we produce and consume energy. Energy communities (EC) provide a recent legal framework for sharing energy, aiming to reduce energy bills and the environmental footprint of their participants. One of the challenges is adapting economic models to this technological upheaval. In this context, cooperative games, based on game theory, are valuable tools for modeling energy management through cooperation. However, despite their promising characteristics, cooperative games are limited by their computational complexity. The required computation time to solve cooperative games increases exponentially with the number of participants, restricting their application in energy management. This paper aims to propose a solution to apply cooperative game theory tools to larger communities using a multidisciplinary approach. For this purpose, a game subdivision approach based on the specific properties of energy communities is proposed. This methodology will be shown to be efficient in terms of computation time. While the game theory concepts are depreciated by limiting computing time, the sub-games method can become an interesting tool in energy management. Advantages and drawbacks in terms of energy management and game theory are discussed in this paper.

能源转型要求我们重新思考如何生产和消费能源。能源社区（EC）为共享能源提供了一个最新的法律框架，旨在减少能源账单和参与者对环境的影响。其中一项挑战是如何调整经济模式，以适应这一技术变革。在这种情况下，基于博弈论的合作博弈是通过合作进行能源管理建模的重要工具。然而，尽管合作博弈具有良好的特点，但其计算复杂性却限制了合作博弈的发展。解决合作博弈所需的计算时间会随着参与人数的增加而呈指数增长，从而限制了其在能源管理中的应用。本文旨在提出一种解决方案，利用多学科方法将合作博弈论工具应用于更大的社区。为此，本文提出了一种基于能源社区特定属性的博弈细分方法。该方法将被证明在计算时间方面是高效的。虽然由于计算时间的限制，博弈论的概念有所贬值，但子博弈方法可以成为能源管理中一个有趣的工具。本文将讨论能源管理和博弈论的优缺点。

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引用次数: 0

Intersecting social welfare with resilience to streamline urban flood management 将社会福利与抗灾能力相结合，简化城市洪水管理

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

Sustainable Cities and Society

Pub Date : 2024-10-24 DOI: 10.1016/j.scs.2024.105927

Mohammad Reza Hassani , Seyyed Farid Mousavi Janbehsarayi , Mohammad Hossein Niksokhan , Ashish Sharma

Urban policymakers have long searched for stormwater management plans that incentivize stakeholders to adopt Green Infrastructure (GI) while effectively reducing the vulnerability of drainage systems. In this regard, our research introduces a novel framework to develop GI strategies that provide both hydrological resiliency and social acceptance. To achieve this, first, using a coupled Stormwater Management Model (SWMM) and Non-dominated Sorting Genetic Algorithm-II (NSGA-II), optimal alternatives for GI planning were generated. In the optimization process, we used a novel Simple Urban Flood Resilience Index (SUFRI) to consider the internal performance of the system in identifying resilient plans. Derived management strategies warrant runoff volume reduction and resilience improvement up to 31.3% and 55.1%, respectively. In the next step, Utilitarian-based Social Welfare (USW) was employed to clarify the socio-economic behavior of management strategies. Results indicate that while financial incentives significantly motivate developers to implement GI, they cannot guarantee high social welfare, and achieving a sustainable solution requires evaluating both SUFRI and USW layers under different subsidy levels. Visualizing the SUFRI layer revealed a critical failure in the resiliency trend of solutions that cannot be detected by evaluating simpler metrics, such as runoff volume reduction. This highlights the importance of the SUFRI method in conducting deeper evaluations and preventing financial waste. Finally, we navigated the intersection of USW and SUFRI measures to reach an ideal management plan with optimal supporting level. Our findings showed that the selected solution with the highest social acceptability can improve the resiliency of the system by 29 %. This study is a novel combination of the hydrological and social aspects of stormwater management, enabling decision-makers to take significant steps towards sustainable urban development.

长期以来，城市决策者一直在寻找既能激励利益相关者采用绿色基础设施（GI），又能有效降低排水系统脆弱性的雨水管理计划。为此，我们的研究引入了一个新颖的框架，以制定既能提供水文恢复能力又能获得社会认可的绿色基础设施战略。为此，我们首先利用雨水管理模型（SWMM）和非优势排序遗传算法-II（NSGA-II），为 GI 规划生成了最佳替代方案。在优化过程中，我们使用了新颖的简单城市抗洪指数（SUFRI），在确定抗洪计划时考虑了系统的内部性能。得出的管理策略保证了径流量的减少和恢复力的提高，分别达到 31.3% 和 55.1%。下一步，采用基于功利主义的社会福利（USW）来阐明管理策略的社会经济行为。结果表明，虽然经济激励措施能极大地调动开发商实施 GI 的积极性，但并不能保证高社会福利，要实现可持续的解决方案，需要在不同补贴水平下对 SUFRI 层和 USW 层进行评估。对 SUFRI 层的可视化揭示了解决方案恢复力趋势中的一个关键失误，而这一失误无法通过评估径流量减少等更简单的指标来发现。这凸显了 SUFRI 方法在进行更深入评估和防止资金浪费方面的重要性。最后，我们对 USW 和 SUFRI 措施的交叉点进行了导航，以达到具有最佳支持水平的理想管理计划。我们的研究结果表明，所选方案的社会接受度最高，可将系统的恢复能力提高 29%。这项研究新颖地将雨水管理的水文和社会方面结合起来，使决策者能够采取重要措施，实现城市的可持续发展。

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引用次数: 0

Air quality improvement at urban bus stops: Optimal air purification placement using CFD 改善城市公交站台的空气质量：利用 CFD 优化空气净化位置

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

Sustainable Cities and Society

Pub Date : 2024-10-24 DOI: 10.1016/j.scs.2024.105937

Yup Yoo , Junghwan Kim , Jaewon Lee , Hyungtae Cho

Nitrogen dioxide (NO₂) levels are often elevated near roadways due to vehicle emissions, while sulfur dioxide (SO₂) is predominantly found near petrochemical complexes as a result of industrial activities such as oil refining and chemical manufacturing. Considering the detrimental effects of these emissions on the environment and human health, the optimal placement of air purification systems at two bus stops in Ulsan, a heavily industrialized city in South Korea, was investigated in this study to reduce NO₂ and SO₂ concentrations. Computational fluid dynamics (CFD) simulations were performed to identify strategic installation locations, resulting in a significant reduction in pollutant levels. The largest impact was noted for the Deokha Market bus stop, whereby the added health risk (AR) decreased by 1.93 % and the exposure reduction effectiveness (ERE), a measure of air purification system efficiency, increased by 13.8 %. Similarly, at the Hyomun Intersection bus stop, placing the system near the sidewalk led to a significant reduction in AR by 1.60 % and an increase in ERE by 11.63 %. Additionally, air purification systems at Ulsan bus stops are expected to reduce NO2 levels by 9.1 ppb, decreasing mortality risk by 1.44 %, saving 7 lives annually, and yielding an economic benefit of 33.06 million USD.

由于汽车尾气的排放，道路附近的二氧化氮（NO2）含量经常升高，而由于炼油和化工生产等工业活动，石油化工综合体附近的二氧化硫（SO2）含量居高不下。考虑到这些排放物对环境和人类健康的不利影响，本研究调查了在韩国重工业城市蔚山的两个公交站点安装空气净化系统以降低二氧化氮和二氧化硫浓度的最佳方案。通过计算流体动力学（CFD）模拟，确定了最佳安装位置，从而显著降低了污染物水平。影响最大的是德化市场公交车站，增加的健康风险 (AR) 降低了 1.93%，衡量空气净化系统效率的暴露减少效果 (ERE) 提高了 13.8%。同样，在 Hyomun 十字路口公交车站，将空气净化系统安装在人行道附近，可显著降低 1.60% 的健康风险，提高 11.63% 的ERE。此外，蔚山公交车站的空气净化系统预计可将二氧化氮水平降低 9.1 ppb，将死亡风险降低 1.44 %，每年挽救 7 条生命，并产生 3306 万美元的经济效益。

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引用次数: 0

Multi-period Charging Infrastructure Planning under Uncertainty: Challenges and Opportunities 不确定性下的多期充电基础设施规划：挑战与机遇

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

Sustainable Cities and Society

Pub Date : 2024-10-24 DOI: 10.1016/j.scs.2024.105908

Qiming Ye , Prateek Bansal , Bryan Adey

Long-term charging infrastructure planning is imperative to sustain the rapid adoption of electric vehicles (EVs) in line with climate goals. While the literature on spatial planning of charging infrastructure is well documented, the temporal dimension has received limited attention. This paper comprehensively reviews the literature on multi-period charging infrastructure planning under uncertainty. It examines the complex interplay between EV mobility and the energy sector. Four gaps are identified after examining 44 pertinent studies published from January 1990 to March 2024. Firstly, current models are predominantly deterministic and myopic, lacking a forward-looking approach to accommodate future uncertainties. Secondly, most studies rely on EVs’ aggregated mobility and charging patterns, leading to inaccurate charging demand forecasts and suboptimal plans. Addressing this requires integrating vehicle-level agent-based models that accurately depict EVs’ charging patterns, and their interactions with charging stations and the grid. Thirdly, the impact of improved charging infrastructure on EV adoption is generally ignored. Joint consideration of charging demand forecasting with infrastructure planning is essential to incorporate such infrastructure-demand feedback loops. Lastly, current planning frameworks show limited integration of grid expansion, operations, and renewable energy sources To address these gaps, we propose a dynamic programming-based framework and solution approach to this planning problem.

要使电动汽车（EV）的快速普及与气候目标保持一致，就必须进行长期的充电基础设施规划。有关充电基础设施空间规划的文献已被大量引用，但对时间维度的关注却很有限。本文全面回顾了不确定性条件下多期充电基础设施规划方面的文献。它研究了电动汽车流动性与能源部门之间复杂的相互作用。在研究了 1990 年 1 月至 2024 年 3 月期间发表的 44 篇相关研究后，发现了四个差距。首先，目前的模型主要是确定性和近视性的，缺乏前瞻性的方法来考虑未来的不确定性。其次，大多数研究依赖于电动汽车的综合移动性和充电模式，导致充电需求预测不准确和计划不理想。要解决这个问题，需要整合基于车辆级代理的模型，准确描述电动汽车的充电模式，以及它们与充电站和电网之间的互动。第三，改善充电基础设施对电动汽车应用的影响通常被忽视。将充电需求预测与基础设施规划结合起来考虑，对于纳入此类基础设施需求反馈回路至关重要。最后，目前的规划框架对电网扩展、运营和可再生能源的整合有限。为了弥补这些不足，我们针对这一规划问题提出了基于动态编程的框架和解决方法。

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引用次数: 0

Monitoring changes in walkability over time: An environmental exposure change detection framework with implications for equity and social justice 监测步行能力随时间的变化：环境暴露变化检测框架对公平和社会正义的影响

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

Sustainable Cities and Society

Pub Date : 2024-10-24 DOI: 10.1016/j.scs.2024.105808

Lawrence D. Frank , Behram Wali

Evidence suggests that walkability and greenspace impact travel related activity patterns and vehicle emissions which affect sustainability, public health, and equity. Resulting levels of physical activity, active, or sedentary travel time impact obesity, diabetes, and heart disease which impact COVID-19 mortality. It is now possible to track changes in locally controlled land use characteristics known to impact sustainability and health. This information can provide decisionmakers with feedback required to spatially prioritize and better link state and nationally funded transportation investments with locally sanctioned land use actions. Linking the achievement of established benchmarks of health equity-based indicators with funding establishes a more performance-based approach connecting land use with transportation investment. This study longitudinally tracks neighborhood-level walkability features at the census tract level for 2013 and 2020 for the entire USA. Longitudinal volatility-based change detection models are developed to examine how changes in walkability over time correlate with racialization and social justice. Walkability tends to increase over time with significant variations across metro regions and the urban-rural continuum. Largest and smallest increases in walkability were observed in Western Pacific and Northwest states, respectively. Increased racial and social justice disparities were observed in access to more walkable infrastructure by marginalized populations (such as less-educated, older, unemployed, and black individuals). Significant heterogeneity in the spatial distribution of walkability was observed, over the variation captured by observed sociodemographic, regional, and urban/rural factors. The findings highlight the potential for an “environmental surveillance” system to support a “performance-based” approach to transportation funding that prioritizes resource allocation consistent with Justice40 and United Nation's Sustainable Development Goals.

有证据表明，步行能力和绿地会影响与出行相关的活动模式和汽车尾气排放，从而影响可持续性、公共健康和公平性。由此产生的体育活动水平、活跃或久坐不动的出行时间会影响肥胖、糖尿病和心脏病，从而影响 COVID-19 的死亡率。现在可以跟踪当地控制的、已知会影响可持续性和健康的土地使用特征的变化。这些信息可为决策者提供所需的反馈，以便在空间上确定优先次序，并将州和国家资助的交通投资与地方批准的土地使用行动更好地联系起来。将基于健康公平指标的既定基准的实现情况与资金联系起来，可以建立一种更加基于绩效的方法，将土地利用与交通投资联系起来。这项研究纵向跟踪了 2013 年和 2020 年美国全国普查区一级的邻里级步行能力特征。研究开发了基于波动性的纵向变化检测模型，以检验步行能力随时间的变化如何与种族化和社会公正相关联。随着时间的推移，步行能力呈上升趋势，不同城市地区和城乡连续体之间存在显著差异。在西太平洋地区和西北部各州分别观察到步行能力的最大和最小增长。在边缘化人群（如受教育程度较低、年龄较大、失业和黑人）使用更适合步行的基础设施方面，种族和社会公平差异有所扩大。在观察到的社会人口、地区和城乡因素所捕捉到的变化之外，还观察到步行能力空间分布的显著异质性。研究结果凸显了 "环境监测 "系统在支持 "基于绩效 "的交通筹资方法方面的潜力，该方法可根据 "正义 "40 和联合国可持续发展目标确定资源分配的优先次序。

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引用次数: 0

Simulation and prediction of daytime surface urban heat island intensity under multiple scenarios via fully connected neural network 通过全连接神经网络模拟和预测多种情景下的白天地表城市热岛强度

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

Sustainable Cities and Society

Pub Date : 2024-10-23 DOI: 10.1016/j.scs.2024.105922

Jiongye Li , Yingwei Yan , Rudi Stouffs

The intensification of the Surface Urban Heat Island (SUHI), driven by urbanization, land use and land cover (LULC) changes, and population growth, presents significant environmental and public health risks in urban areas. Simulating and predicting SUHI, particularly through the identification of future high SUHI intensity (SUHII) zones, has been recognized as a critical step in mitigating these effects. This study employs a Fully Convolutional Neural Network (FCNN) model, trained on data from four research sites, to simulate the current daytime SUHII across six validation sites in Singapore, utilizing 15 key independent variables identified in previous studies. The model exhibits high validation accuracy, achieving 87.45%. Three projection scenarios, based on projected population growth and LULC changes, predict a decrease in High SUHII across all validation sites, ranging from 98.3% to 9%. This reduction is attributed to the LULC improvements proposed in the 2019 Master Plan. Spatial analysis of the predicted SUHII maps indicates that the majority of High SUHII locations across scenarios remain consistent with the current situation. This research also suggests that the model could be a valuable tool for urban planners, allowing them to assess whether new urban development plans will effectively reduce High SUHII to desired thresholds, thereby mitigating SUHII in urban environments.

城市化、土地利用和土地覆盖（LULC）变化以及人口增长导致城市地表热岛（SUHI）加剧，给城市地区带来了巨大的环境和公共健康风险。模拟和预测 SUHI，特别是通过识别未来的 SUHI 高强度（SUHII）区，已被视为减轻这些影响的关键步骤。本研究采用了一个全卷积神经网络（FCNN）模型，该模型在四个研究地点的数据基础上进行了训练，利用之前研究中确定的 15 个关键独立变量，模拟了新加坡六个验证地点当前的日间 SUHII。该模型的验证准确率很高，达到 87.45%。根据预测的人口增长和土地利用、土地利用的变化，三种预测方案预测所有验证地点的高 SUHII 都会下降，降幅从 98.3% 到 9% 不等。这一下降归因于 2019 年总体规划中提出的 LULC 改善措施。对预测的 SUHII 地图进行的空间分析表明，在各种方案中，大多数 SUHII 偏高的地点与当前情况保持一致。这项研究还表明，该模型可以成为城市规划者的宝贵工具，使他们能够评估新的城市发展计划是否能有效地将高 SUHII 降低到所需的阈值，从而减轻城市环境中的 SUHII。

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