Sustainable Cities and Society最新文献

{"title":"Scale effect on the relationship between urban landscape patterns and land surface temperature","authors":"Anqi Zhang ,&nbsp;Chang Xia","doi":"10.1016/j.scs.2024.105942","DOIUrl":"10.1016/j.scs.2024.105942","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"117 ","pages":"Article 105942"},"PeriodicalIF":10.5,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142593372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic integrated simulation of carbon emission reduction potential in China's building sector","authors":"Qiang Du ,&nbsp;Zilang Wan ,&nbsp;Mengqi Yang ,&nbsp;Xiaoyan Wang ,&nbsp;Libiao Bai","doi":"10.1016/j.scs.2024.105944","DOIUrl":"10.1016/j.scs.2024.105944","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"116 ","pages":"Article 105944"},"PeriodicalIF":10.5,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142554482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Large language model as parking planning agent in the context of mixed period of autonomous vehicles and Human-Driven vehicles","authors":"Yuping Jin ,&nbsp;Jun Ma","doi":"10.1016/j.scs.2024.105940","DOIUrl":"10.1016/j.scs.2024.105940","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"117 ","pages":"Article 105940"},"PeriodicalIF":10.5,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142586994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the climatic conditions effect on spatial urban photovoltaic systems development using a spatial multi-criteria decision analysis: A multi-city analysis","authors":"Abouzar Gholamalizadeh ,&nbsp;Saman Nadizadeh Shorabeh ,&nbsp;Kianoosh Choubineh ,&nbsp;Alireza Karimi ,&nbsp;Laleh Ghahremani ,&nbsp;Mohammad Karimi Firozjaei","doi":"10.1016/j.scs.2024.105941","DOIUrl":"10.1016/j.scs.2024.105941","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"116 ","pages":"Article 105941"},"PeriodicalIF":10.5,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142560857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy management based on coalitionnal game subdivision applied to energy communities","authors":"Adrien Bossu ,&nbsp;Benoit Durillon ,&nbsp;Arnaud Davigny ,&nbsp;Hervé Barry ,&nbsp;Fateh Belaïd ,&nbsp;Benoît Robyns ,&nbsp;Christophe Saudemont","doi":"10.1016/j.scs.2024.105911","DOIUrl":"10.1016/j.scs.2024.105911","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"117 ","pages":"Article 105911"},"PeriodicalIF":10.5,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intersecting social welfare with resilience to streamline urban flood management","authors":"Mohammad Reza Hassani ,&nbsp;Seyyed Farid Mousavi Janbehsarayi ,&nbsp;Mohammad Hossein Niksokhan ,&nbsp;Ashish Sharma","doi":"10.1016/j.scs.2024.105927","DOIUrl":"10.1016/j.scs.2024.105927","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"116 ","pages":"Article 105927"},"PeriodicalIF":10.5,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142554593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Air quality improvement at urban bus stops: Optimal air purification placement using CFD","authors":"Yup Yoo ,&nbsp;Junghwan Kim ,&nbsp;Jaewon Lee ,&nbsp;Hyungtae Cho","doi":"10.1016/j.scs.2024.105937","DOIUrl":"10.1016/j.scs.2024.105937","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"117 ","pages":"Article 105937"},"PeriodicalIF":10.5,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142593371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-period Charging Infrastructure Planning under Uncertainty: Challenges and Opportunities","authors":"Qiming Ye ,&nbsp;Prateek Bansal ,&nbsp;Bryan Adey","doi":"10.1016/j.scs.2024.105908","DOIUrl":"10.1016/j.scs.2024.105908","url":null,"abstract":"<div><div>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. <em>Firstly</em>, current models are predominantly deterministic and myopic, lacking a forward-looking approach to accommodate future uncertainties. <em>Secondly</em>, 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. <em>Thirdly</em>, 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. <em>Lastly</em>, 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.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"116 ","pages":"Article 105908"},"PeriodicalIF":10.5,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142560959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Monitoring changes in walkability over time: An environmental exposure change detection framework with implications for equity and social justice","authors":"Lawrence D. Frank ,&nbsp;Behram Wali","doi":"10.1016/j.scs.2024.105808","DOIUrl":"10.1016/j.scs.2024.105808","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"117 ","pages":"Article 105808"},"PeriodicalIF":10.5,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142703314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simulation and prediction of daytime surface urban heat island intensity under multiple scenarios via fully connected neural network","authors":"Jiongye Li ,&nbsp;Yingwei Yan ,&nbsp;Rudi Stouffs","doi":"10.1016/j.scs.2024.105922","DOIUrl":"10.1016/j.scs.2024.105922","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"116 ","pages":"Article 105922"},"PeriodicalIF":10.5,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142554481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}