Sustainable Cities and Society最新文献_第8页

Association between urban agglomerations and total non-exhaust particulate matter emissions from electric vehicles: A case study from urban and non-urban cities in Taiwan

IF 10.5 1区工程技术

Sustainable Cities and Society Pub Date : 2025-03-10 DOI: 10.1016/j.scs.2025.106289

Sultan F.I. Abdillah , Sheng-Jie You , Ya-Fen Wang

{"title":"Association between urban agglomerations and total non-exhaust particulate matter emissions from electric vehicles: A case study from urban and non-urban cities in Taiwan","authors":"Sultan F.I. Abdillah , Sheng-Jie You , Ya-Fen Wang","doi":"10.1016/j.scs.2025.106289","DOIUrl":"10.1016/j.scs.2025.106289","url":null,"abstract":"<div><div>Many countries are adopting vehicle electrification policies to achieve net-zero goals and sustainable transport sector. However, varying levels of urban development and socio-economic conditions can influence the transition and its environmental impact. This study explored the interplay between urban agglomerations and non-exhaust particulate matters (NE PMs) emission from electric vehicles (EVs) by identifying urban and non-urban cluster, agglomeration index, spatial variation, and EVs emission share of 22 cities in Taiwan. Three urban agglomeration clusters were identified in the northern, central, and southern areas with Taipei, Chiayi city, and Tainan as the center cities of each cluster. High spatial resolution analysis for NE PMs has revealed intensified emissions from EVs in the urban agglomeration clusters, with center cities having higher emissions compared to other cities. Urban cities such as Taipei and Tainan have 6 – 14 times higher emissions from EVs (2.97 – 3.44 t<sub>TSP</sub>/y) than non-urban cities (0.30 – 0.33 t<sub>TSP</sub>/y). Multi-linear regression (MLR) and principal component analysis (PCA) fitting models revealed that socio-economic indicators such as adult population, immigrant numbers, road area, and regular income are significantly associated with NE PM emissions from EVs <em>(p</em> <em><</em> <em>0.01)</em>. These findings provide further insights into the importance of targeted net-zero policies in city-level perspective.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"123 ","pages":"Article 106289"},"PeriodicalIF":10.5,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143601743","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}

引用次数: 0

Spatiotemporal analysis of heat-related emergency department visits and hospitalizations in Florida (2005–2021): A Bayesian change point detection approach

IF 10.5 1区工程技术

Sustainable Cities and Society Pub Date : 2025-03-09 DOI: 10.1016/j.scs.2025.106288

Ehsan Foroutan , Saeid Niazmardi , Tao Hu

{"title":"Spatiotemporal analysis of heat-related emergency department visits and hospitalizations in Florida (2005–2021): A Bayesian change point detection approach","authors":"Ehsan Foroutan , Saeid Niazmardi , Tao Hu","doi":"10.1016/j.scs.2025.106288","DOIUrl":"10.1016/j.scs.2025.106288","url":null,"abstract":"<div><div>The rise in global temperatures poses significant health risks, underscoring the need for decision-makers to understand the spatiotemporal patterns of heat-related health issues as part of efforts to advance sustainability in cities. However, many existing studies rely on statistical methods and limited time frames, failing to capture full temporal dynamics and trend changepoints. This study addresses these gaps by proposing a novel method using the Bayesian Estimator of Abrupt Change, Seasonality, and Trend (BEAST) algorithm to analyze heat-related emergency department visits (EDVs) and hospitalizations across 67 Florida counties from 2005 to 2021. The method decomposes time series data into trend and seasonality components, with significant trend changes analyzed to determine associations with demographic, health, environmental, and meteorological variables. Results indicated relatively stable or slightly increasing trends in heat-related EDVs and hospitalizations in most counties. Among the 14 analyzed variables, pre-existing health conditions, populations aged 5 years or younger, and those aged 65 years or older were most strongly linked to trend changes, while environmental and meteorological factors played a lesser role. These findings contribute to the understanding of heat-related health vulnerabilities, offering valuable insights for fostering resilience and adaptability in sustainable cities.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"123 ","pages":"Article 106288"},"PeriodicalIF":10.5,"publicationDate":"2025-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143628851","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}

引用次数: 0

Post-tornado automated building damage evaluation and recovery prediction by integrating remote sensing, deep learning, and restoration models

IF 10.5 1区工程技术

Sustainable Cities and Society Pub Date : 2025-03-08 DOI: 10.1016/j.scs.2025.106286

Abdullah M. Braik , Maria Koliou

{"title":"Post-tornado automated building damage evaluation and recovery prediction by integrating remote sensing, deep learning, and restoration models","authors":"Abdullah M. Braik , Maria Koliou","doi":"10.1016/j.scs.2025.106286","DOIUrl":"10.1016/j.scs.2025.106286","url":null,"abstract":"<div><div>This study introduces a novel methodology that integrates remote sensing, deep learning, and restoration models to streamline building damage assessment and recovery time predictions following tornado events. In contrast to existing research primarily focused on pre-hazard mitigation and preparedness, this study advances the field by extending the application of engineering models to the post-hazard emergency response and recovery phase. The novelty lies in utilizing remote sensing and deep learning to automate the generation of large-scale maps for tornado damage. Then, building damage evaluation is integrated with restoration models for rapid estimations of post-disaster restoration time and cost. Through a comprehensive application study focused on the 2011 Joplin Tornado, the methodology is demonstrated to be fully automated. The predictions were validated against historical reports, highlighting the methodology's effectiveness in generating accurate damage evaluation and restoration predictions. This study stands out as the first to leverage remote sensing imagery-based damage evaluation to extend the utility of regional risk assessment beyond pre-tornado planning, thus enhancing post-tornado disaster response and recovery efforts.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"123 ","pages":"Article 106286"},"PeriodicalIF":10.5,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143594124","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}

引用次数: 0

Multi-source data fusion-driven urban building energy modeling

IF 10.5 1区工程技术

Sustainable Cities and Society Pub Date : 2025-03-08 DOI: 10.1016/j.scs.2025.106283

Sebin Choi , Dong Hyuk Yi , Deuk-Woo Kim , Sungmin Yoon

{"title":"Multi-source data fusion-driven urban building energy modeling","authors":"Sebin Choi , Dong Hyuk Yi , Deuk-Woo Kim , Sungmin Yoon","doi":"10.1016/j.scs.2025.106283","DOIUrl":"10.1016/j.scs.2025.106283","url":null,"abstract":"<div><div>The energy efficiency of buildings is important for creating sustainable cities. In this context, urban building energy modeling (UBEM) is essential for comprehending and predicting building energy consumption and the patterns from a city-wide perspective. This study proposes a multi-source data-fusion-driven UBEM and its real-world applications in Seoul, South Korea. Unlike existing models that utilize energy data as input variables, models based solely on building features play a crucial role in various projects in which energy consumption data is unavailable, such as new building projects, retrofitting projects, and new city developments. In this modeling scenario, data fusion using multi-source data is crucial for developing highly accurate and robust models because of the limited availability of input features. In this study, the utilization of multi-source open data, along with simulated data such as shading factor, enables the fusion of these datasets to derive building features. These features are subsequently utilized to train the prediction model, leading to accurate and robust modeling outcomes. Thus, five case studies were conducted for 47,391 buildings, located in Seoul, South Korea, to demonstrate how and how much data fusion-driven features enhance the performance of UBEM. Discussions in each case provide insights into feature selection and effective utilization tailored to each modeling context. Finally, the developed model was tested in two additional regions, and it was observed that adding features to the model training improved the model performance in both regions. These findings emphasize the importance of data fusion for robust UBEM in the context of sustainable cities.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"123 ","pages":"Article 106283"},"PeriodicalIF":10.5,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143628793","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}

引用次数: 0

Pathways to urban net zero energy buildings in Canada: A comprehensive GIS-based framework using open data

IF 10.5 1区工程技术

Sustainable Cities and Society Pub Date : 2025-03-08 DOI: 10.1016/j.scs.2025.106263

Yang Li, Haibo Feng

{"title":"Pathways to urban net zero energy buildings in Canada: A comprehensive GIS-based framework using open data","authors":"Yang Li, Haibo Feng","doi":"10.1016/j.scs.2025.106263","DOIUrl":"10.1016/j.scs.2025.106263","url":null,"abstract":"<div><div>While policies outline ambitious Urban Net Zero Energy Buildings (UNEZB) strategies, the lack of available Canadian-specific archetypes and data complexity has limited spatial and quantitative validation of these strategies. In this study, a simplified 3D building model (LoD 100) was developed using footprint and Digital Surface Model (DSM) data. An archetype database, based on ASHRAE 90.1 and NECB 2011, was created to classify urban-level energy use intensity across various building types and HVAC systems. This research explores three pathways to net-zero energy: electrification transitions, energy efficiency retrofits, and renewable energy integration. A case study was conducted by developing the urban-scale 3D building models for the City of Richmond at BC Canada, and the spatial energy analysis revealed significant disparities in energy consumption across urban and suburban areas. Key findings from the case study indicate that electrification and solar energy adoption in commercial districts, along with targeted retrofitting in residential zones, can significantly reduce energy use. This study provides a physics-based framework and robust methodology for Canadian cities to achieve net-zero energy goals, which offers valuable insights for policymakers, urban planners, and energy engineers to support decision-making and urban sustainability.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"122 ","pages":"Article 106263"},"PeriodicalIF":10.5,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143580386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Effects of complex skyscraper geometries on wind energy potentials of high-density urban central business district: A case study of the Lujiazui blocks

IF 10.5 1区工程技术

Sustainable Cities and Society Pub Date : 2025-03-08 DOI: 10.1016/j.scs.2025.106287

Jing Wen , Zhengyu Fan , Jiaping Liu

{"title":"Effects of complex skyscraper geometries on wind energy potentials of high-density urban central business district: A case study of the Lujiazui blocks","authors":"Jing Wen , Zhengyu Fan , Jiaping Liu","doi":"10.1016/j.scs.2025.106287","DOIUrl":"10.1016/j.scs.2025.106287","url":null,"abstract":"<div><div>The wind energy resources of high-rise buildings have been increasingly becoming one of the most important sources for achieving zero-carbon buildings and cities. However, due to the lack of understanding regarding the relationship between the wind energy potential and the complex geometries of the central business district (CBD), the developments of wind energy utilizations were severely limited. Employing validated CFD simulations, this research has studied the core skyscraper representatives of the Lujiazui CBD in Shanghai to reveal the correlations between the aforementioned complex geometries and key indicators of wind energy resources. The potential locations of wind turbine installations hadd been analyzed in detail. It has been found that to achieve higher wind power potentials, the representative floor planes should opt for rounded or smoothly chamfered shapes rather than sharp-edged polygons or rectangles. Besides, the roof profile should favor conical and semi-circular shapes over a flat roof, and the outer edges of extended planes are more suitable for installing wind turbines. For twin skyscrapers, the excessive angles between internal clamping channels and the prevailing wind directions should be avoided. The results can provide scientific and practical references for the optimizations of complex forms of skyscrapers in urban CBD blocks.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"124 ","pages":"Article 106287"},"PeriodicalIF":10.5,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143642112","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}

引用次数: 0

Towards high-resolution pollutant mapping in narrow spaces: Integrating fixed sensors, mobile robots, and enhanced reconstruction techniques

IF 10.5 1区工程技术

Sustainable Cities and Society Pub Date : 2025-03-08 DOI: 10.1016/j.scs.2025.106280

Yaohua Jiang , Suwan Zhou , Wei Xiang , Shilong Chen , Hao Cai , Yan Tong , Zhenglong Zhou

{"title":"Towards high-resolution pollutant mapping in narrow spaces: Integrating fixed sensors, mobile robots, and enhanced reconstruction techniques","authors":"Yaohua Jiang , Suwan Zhou , Wei Xiang , Shilong Chen , Hao Cai , Yan Tong , Zhenglong Zhou","doi":"10.1016/j.scs.2025.106280","DOIUrl":"10.1016/j.scs.2025.106280","url":null,"abstract":"<div><div>Narrow spaces—including underground tunnels, subway platforms, corridors, overpasses, and public transportation vehicles—are prone to pollutant accumulation due to spatial constraints and limited ventilation, posing significant health and safety risks. Achieving high-resolution mapping of pollutant distribution patterns is crucial for mitigating these risks, yet traditional monitoring methods often fail to adequately address the trade-offs between temporal and spatial resolution. This study introduces an innovative monitoring and analysis framework designed for the efficient dispersion of pollutants in ventilated narrow spaces. It integrates fixed sensors for high temporal resolution data acquisition, mobile robots for enhanced spatial coverage, and advanced field reconstruction methods—specifically, Kernel DM+V/W+ and Kernel DM+V/W++ methods—to extrapolate limited sampling data into high-resolution concentration fields. The efficacy of this framework is demonstrated through meticulous ethanol and methane dispersion experiments conducted in a long corridor and a scaled-down utility tunnel model, respectively. The results underscore the framework’s capability to precisely depict pollutant distributions, effectively extrapolate concentrations to unmonitored areas, and produce comprehensive environmental distribution maps. This novel approach not only significantly enhances the precision of pollutant distribution reconstruction but also optimizes sampling strategies and improves overall monitoring efficiency.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"124 ","pages":"Article 106280"},"PeriodicalIF":10.5,"publicationDate":"2025-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683912","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}

引用次数: 0

Revisiting urban heat island effects in China: Multi-satellite evidence from the ESA-CCI land surface temperature product

IF 10.5 1区工程技术

Sustainable Cities and Society Pub Date : 2025-03-07 DOI: 10.1016/j.scs.2025.106281

Xing Li , Xiao Li , Hedi Ma , Juan Zhou , Fei Ge , Wanxin Zhang , Yan Yan , Yijing Zhou

{"title":"Revisiting urban heat island effects in China: Multi-satellite evidence from the ESA-CCI land surface temperature product","authors":"Xing Li , Xiao Li , Hedi Ma , Juan Zhou , Fei Ge , Wanxin Zhang , Yan Yan , Yijing Zhou","doi":"10.1016/j.scs.2025.106281","DOIUrl":"10.1016/j.scs.2025.106281","url":null,"abstract":"<div><div>Rapid urbanization affects local and regional climates, yet uncertainties in multi-satellite-derived surface urban heat island intensity (SUHII) remain poorly understood. This study reassessed China's multi-scale SUHII (2000–2020) and its uncertainties using seven satellite products from the European Space Agency's Climate Change Initiative Land Surface Temperature (LST) dataset via a dynamic-size sliding window method. Results showed that daytime SUHII exhibited a north-south gradient (−0.5 to 0 °C in north; 1.0–1.5 °C in south) with pronounced seasonal variations, whereas nighttime values remained uniform (0.3–1.0 °C) with minor seasonal fluctuations. Substantial inter-satellite discrepancies emerged during summertime in southern China (spreads up to 3.62 °C). Analysis of three long-term satellite records revealed increasing daytime SUHII trends in the south (>1.5 °C/10a), weak decreases in the north (<0.5 °C/10a) and moderate nighttime warming trends countrywide (0.5–1.0 °C/10a). Interannual SUHII variations are smaller than seasonal and diurnal variations. Assessment of data quality metrics suggested that both region-specific climate conditions-induced inherent uncertainties (e.g., clear-sky pixel availability and LST total uncertainty) and varying satellite overpass times are probably the primary drivers of inter-satellite discrepancies. Our findings underscore the importance of considering inter-satellite uncertainties when interpreting urban SUHII patterns, informing urban planning and climate change adaptation strategies.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"123 ","pages":"Article 106281"},"PeriodicalIF":10.5,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143611001","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}

引用次数: 0

Impact mechanisms of 2D and 3D spatial morphologies on urban thermal environment in high-density urban blocks: A case study of Beijing's Core Area

IF 10.5 1区工程技术

Sustainable Cities and Society Pub Date : 2025-03-07 DOI: 10.1016/j.scs.2025.106285

Guangxi Tang , Xintong Du , Siyuan Wang

{"title":"Impact mechanisms of 2D and 3D spatial morphologies on urban thermal environment in high-density urban blocks: A case study of Beijing's Core Area","authors":"Guangxi Tang , Xintong Du , Siyuan Wang","doi":"10.1016/j.scs.2025.106285","DOIUrl":"10.1016/j.scs.2025.106285","url":null,"abstract":"<div><div>Amid global warming, thermal issues in high-density urban areas have become increasingly severe. This study developed an integrated framework combining artificial neural networks, machine learning, and spatial regression to assess how urban morphology impacts the thermal environment in high-density urban areas. Using 2D and 3D building morphology indicators, we applied self-organizing maps (SOM) to classify urban blocks. Boosted regression trees (BRT) model identified key urban morphology indicators influencing land surface temperature (LST), evaluated their contributions, and analyzed marginal effects. Generalized additive models (GAM) explored nonlinear relationships and threshold effects between LST and morphology metrics, while geographically weighted regression (GWR) captured spatial heterogeneity. Results showed that Dense Low-rise Zone (DLZ) and Dense Mid-rise Zone (DMZ) are predominant in Beijing's core area, with DLZ averaging 50.2 °C, significantly impacting the thermal environment. Building patch density (PD_B) and building number density (BND) are primary indicators affecting LST, with 3D indicators showing the strongest influence. ISF, HRE and POID exhibit significant nonlinear relationships with LST. These findings provide a scientific basis for thermal environment planning and management strategies in high-density urban settings, offering guidance for mitigating urban heat island effects.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"123 ","pages":"Article 106285"},"PeriodicalIF":10.5,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143594125","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}

引用次数: 0

Optimizing productive green roofs for urban food self-sufficiency in Amsterdam

IF 10.5 1区工程技术

Sustainable Cities and Society Pub Date : 2025-03-07 DOI: 10.1016/j.scs.2025.106284

Pengxuan Xie , José M. Mogollón , Jan Willem Erisman , Valerio Barbarossa

{"title":"Optimizing productive green roofs for urban food self-sufficiency in Amsterdam","authors":"Pengxuan Xie , José M. Mogollón , Jan Willem Erisman , Valerio Barbarossa","doi":"10.1016/j.scs.2025.106284","DOIUrl":"10.1016/j.scs.2025.106284","url":null,"abstract":"<div><div>Fulfilling urban dietary demand often hinges on importing food from rural areas, leaving the local food supply chain and food security vulnerable to disruptions. Productive green roofs have the potential to partially address this challenge by supplying food locally and therefore mitigating sudden disruptions in the urban food supply chain. However, increasing urban food self-sufficiency requires an understanding of urban food production potential and the optimal planting structures for crop rotation planning. In this study, we modeled various crop rotations spatially and temporally to assess the potential for urban productive green roof food production to meet the local dietary demand of specific crop groups. We estimated urban food self-sufficiency considering average productive green roof crop yields and climatic variability (2003–2021) within the city of Amsterdam. We find that Amsterdam's potential productive green roofs can achieve urban food self-sufficiency of 52 % for selected crops (41–54 % when accounting for climatic and spatial variability). When optimizing the planting structure, this number rises to 71 % (50–71 %). Our results highlight that productive green roofs in Amsterdam have the potential to strengthen the local food supply chain, especially if a strategic approach to the planting structure is adopted.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"123 ","pages":"Article 106284"},"PeriodicalIF":10.5,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143629303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0