Sustainable Cities and Society最新文献_第3页

Exploring the effect of the architecture morphology on urban ventilation at block scale using CFD-GIS and random forest combined method

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

Sustainable Cities and Society

Pub Date : 2025-02-23 DOI: 10.1016/j.scs.2025.106241

Bin Guo , Miaoyi Chen , Xiaowei Zhu , Zheng Wang , Lu Li , Lin Pei , Hailong Chen , Puhao Chen , Tengyue Guo

Urban ventilation plays a crucial role in dispersing air pollutants and mitigating the urban heat island effect. As a key factor, urban architectural morphology can significantly impact the wind field and ventilation efficiency. This study combines Computational Fluid Dynamics (CFD), Geographic Information System (GIS), and Random Forest (RF) methods to investigate the influence of architectural morphology on urban ventilation at the block scale. First, Remote Sensing (RS) and GIS were used to extract architectural morphology parameters. Second, CFD simulations, guided by in-situ observations, were conducted to model the wind field, with the Standard k-ɛ model validated as the optimal choice. Third, RF analysis was used to rank the importance of architectural morphology parameters on urban ventilation. The results show that architectural morphology has a substantial impact on ventilation, with Degree of Enclosure (DE), Building Coverage Ratio (BCR), Space Openness (SO), Floor Area Ratio (FAR), and Building Dispersion Ratio (BDR) identified as the most influential parameters, ranked in descending order of importance. This study provides valuable insights for enhancing urban wind environments through optimized architectural design at the block scale.

{"title":"Exploring the effect of the architecture morphology on urban ventilation at block scale using CFD-GIS and random forest combined method","authors":"Bin Guo , Miaoyi Chen , Xiaowei Zhu , Zheng Wang , Lu Li , Lin Pei , Hailong Chen , Puhao Chen , Tengyue Guo","doi":"10.1016/j.scs.2025.106241","DOIUrl":"10.1016/j.scs.2025.106241","url":null,"abstract":"<div><div>Urban ventilation plays a crucial role in dispersing air pollutants and mitigating the urban heat island effect. As a key factor, urban architectural morphology can significantly impact the wind field and ventilation efficiency. This study combines Computational Fluid Dynamics (CFD), Geographic Information System (GIS), and Random Forest (RF) methods to investigate the influence of architectural morphology on urban ventilation at the block scale. First, Remote Sensing (RS) and GIS were used to extract architectural morphology parameters. Second, CFD simulations, guided by in-situ observations, were conducted to model the wind field, with the Standard k-ɛ model validated as the optimal choice. Third, RF analysis was used to rank the importance of architectural morphology parameters on urban ventilation. The results show that architectural morphology has a substantial impact on ventilation, with Degree of Enclosure (DE), Building Coverage Ratio (BCR), Space Openness (SO), Floor Area Ratio (FAR), and Building Dispersion Ratio (BDR) identified as the most influential parameters, ranked in descending order of importance. This study provides valuable insights for enhancing urban wind environments through optimized architectural design at the block scale.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"122 ","pages":"Article 106241"},"PeriodicalIF":10.5,"publicationDate":"2025-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143509281","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

Risk-based scheduling of multi-energy microgrids with Power-to-X technology under a multi-objective framework

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

Sustainable Cities and Society

Pub Date : 2025-02-23 DOI: 10.1016/j.scs.2025.106245

Pouya Salyani , Kazem Zare , Nader Javani , Ali Rifat Boynuegri

Power to X (P2X) technologies coupled with energy storage systems serve as a bridge among the various energy vectors to enhance the flexibility of Multi-Energy Microgrids (MEMs). The current research examines a multi-objective approach for scheduling a MEM integrated with P2X conversion technology. The main goal is to minimize three conflicting objectives: operational cost, risk, and CO₂ emissions. The suggested risk-based scheduling is solved through the augmented ε-constraint method to address the economic/environmental aspects of the problem. Two risk management tools of Conditional Value at Risk (CVaR) and a robust approach are proposed to deal with uncertainties in the MEM's scheduling. Besides, the proposed MEM benefits from P2X converters, various storage technologies, demand response resources, renewable resources, and energy market bidding. This enables the MEM to transform the power into other carriers of thermal, hydrogen, and synthetic gas to meet various energy demands, effectively. The simulation results show that adopting a risk-neutral unconservative risk strategy results in an expected operating cost of $7,400 and carbon emission of 58 tCO₂. In this situation, a 21 % reduction in CVaR due to the risk-averse strategy leads to a 24 % increase in operation cost and a 20 % reduction in emission. Moreover, adopting the robust approach to regulation service prices increases the operational cost compared with the corresponding risk-averse unconservative strategy.

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引用次数: 0

Unveiling the nonlinear relationships and co-mitigation effects of green and blue space landscapes on PM2.5 exposure through explainable machine learning

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

Sustainable Cities and Society

Pub Date : 2025-02-22 DOI: 10.1016/j.scs.2025.106234

Wei Cao , Liyan Wang , Rui Li , Wen Zhou , Deshun Zhang

Green-blue spaces are nature-based solutions to mitigate particulate matter pollution. However, the individual and co-mitigation effects of green-blue space landscapes on PM2.5 exposure risk remain poorly understood. This study employed an explainable machine learning framework to investigate the nonlinear relationships, interaction effects, and heterogeneity of green-blue space landscape patterns on population-weighted PM_2.5 exposure (PWP) in the Yangtze River Delta, China. Our findings highlight that (1) Greenspace coverage (G_PLAND), mean greenspace patch size (G_AREA_MN), blue space patch contiguity (W_CONTIG_MN), and mean distance between blue space patches (W_ENN_MN) are the four most influential landscape indicators. (2) G_PLAND and G_AREA_MN negatively influence PWP with thresholds of 40 % and 50 ha, respectively. W_CONTIG_MN (> 0.26) and W_ENN_MN (< 400 m) positively impact PWP. (3) Effects of green-blue space landscapes on PWP vary with different exposure levels: high (blue space is more important), medium (green and blue space are equally important), and low (green-blue spaces are not important). (4) Interactions of green and blue spaces can reinforce PWP mitigation under certain conditions (G_PLAND > 40 %, G_AREA_MN < 12 ha, W_ENN_MN and W_CONTIG_MN with thresholds of 200 m and 0.31, respectively). The findings can facilitate comprehensive planning and optimization of regional green-blue spaces to mitigate PWP.

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引用次数: 0

Unravelling food carbon footprint heterogeneity in metropolitan areas using Tokyo as a case study

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

Sustainable Cities and Society

Pub Date : 2025-02-20 DOI: 10.1016/j.scs.2025.106236

Shun Nakayama , Wanglin Yan

As cities gear up toward carbon neutrality, the food sector can play a crucial role in decarbonization. Food related carbon emissions likely vary across urban areas due to the interplay of urban form, food environments, and dietary habits, affecting the intensity of emissions. Existing consumption-based carbon accounting methods fail to capture spatial heterogeneity effectively and have not fully explored opportunities to enhance spatial resolution in urban contexts. This study proposes a novel Service Point-Based Carbon Accounting (SPBCA) method to systematically understand how these factors influence CO₂ emissions in urban food systems. Unlike traditional approaches, SPBCA focuses on meal provision points rather than consumption locations, allowing for more accurate spatial representation of emissions. We applied SPBCA to census tracts in the Tokyo metropolitan region and validated its effectiveness using LightGBM, an advanced machine learning approach. The model achieved a high validation accuracy (R² = 0.874) through cross-validation, demonstrating SPBCA's capability to capture the heterogeneous nature of urban food-related emissions. This method enables identification of key actors in urban food systems, important for developing effective decarbonization roadmaps for climate policy and urban planning at the urban neighborhood scale.

随着城市逐步实现碳中和，食品行业可以在脱碳过程中发挥关键作用。由于城市形态、食品环境和饮食习惯的相互作用，与食品相关的碳排放在不同城市地区可能有所不同，从而影响排放强度。现有的基于消费的碳核算方法未能有效捕捉空间异质性，也没有充分探索在城市环境中提高空间分辨率的机会。本研究提出了一种新颖的基于服务点的碳核算（SPBCA）方法，以系统地了解这些因素如何影响城市食物系统中的二氧化碳排放。与传统方法不同的是，SPBCA 专注于膳食供应点而非消费地点，从而能够更准确地反映排放量的空间分布。我们将 SPBCA 应用于东京都地区的人口普查区，并使用先进的机器学习方法 LightGBM 验证了其有效性。通过交叉验证，该模型达到了很高的验证精度（R² = 0.874），证明了 SPBCA 能够捕捉城市食品相关排放的异质性。该方法能够识别城市食品系统中的关键参与者，这对于在城市街区范围内为气候政策和城市规划制定有效的去碳化路线图非常重要。

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引用次数: 0

Innovation-driven cities: Reconciling economic growth and ecological sustainability

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

Sustainable Cities and Society

Pub Date : 2025-02-19 DOI: 10.1016/j.scs.2025.106230

Fei Chen , Liling Zhu , Huiqiang Zhang , Yi Li

The innovative city pilot policy (ICPP) presents new solutions to balance economic growth with environmental protection. This paper treats the ICPP as a quasi-natural experiment and employs staggered difference-in-differences (DID) and spatial DID methods to examine its impact on green total factor productivity (GTFP) and its spatial spillover effects from 2008 to 2022. It further analyzes the policy's mechanisms and heterogeneity. The research results indicate that (i) ICPP significantly increased GTFP in pilot cities, accelerating green development by 4.3 % while alleviating environmental issues such as air pollution. (ii) By constructing a moderating effect model, the analysis reveals that the ICPP positively influences GTFP through the moderation of green technological innovation, government support, and intellectual property (IP) protection. (iii) Heterogeneity analysis reveals that while university-based research significantly promotes development, its impact is limited by innovation challenges. Government environmental support increases GTFP, and its effect is more pronounced in regions under greater pollution pressure, where the shift to low-carbon industries presents greater opportunities for improvement.

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引用次数: 0

An indicator-based framework of circular cities focused on sustainability dimensions and sustainable development goal 11 obtained using machine learning and text analytics

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

Sustainable Cities and Society

Pub Date : 2025-02-19 DOI: 10.1016/j.scs.2025.106219

Nadia Falah , Navid Falah , Jaime Solis-Guzman , Madelyn Marrero

The circular economy (CE) serves a practical pathway to facilitate sustainable development (SD) and achieve the Sustainable Development Goals (SDGs). Current frameworks for assessing city sustainability and circularity often lack comprehensibility and multi-dimensional indicator-based approaches, also fail to include city-level CE indicators. This study defines an innovative structure for defining the circular city indicators (CCIs) addressing critical gaps in existing methodologies and CCIs coverage of sustainability and SDGs, especially SDG11. The methodology encompasses an extensive literature review, integrating CE principles, macro level of CE parameters and current CCIs, resulting in a comprehensive list of 241 indicators. Using advanced machine-learning techniques—semi-supervised learning, text analysis, and clustering algorithms—enhances the accuracy, comprehensiveness of the indicator classification. The indicators are categorized into 3D space across environmental, economic, and social dimensions of sustainability. This multi-dimensional approach also reveals the relationships between CCIs and 16 SDG11 classes. The analysis shows 75% of CCIs are multi-dimensional, but, five SDG11 classes show the lowest coverage in the heatmap of CCIs probability distribution across SDG11 classes, indicating a need to revise SDG11 classes and the social indicators of CCIs. The findings offer urban planners and stakeholders a practical list of CCIs to evaluate sustainability and CE level in cities.

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引用次数: 0

A flexible waste bin number allocation plan applied to waste transportation electric fleets in smart cities

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

Sustainable Cities and Society

Pub Date : 2025-02-19 DOI: 10.1016/j.scs.2025.106223

Shuotong Su , Jiawen Hu , Wenjun Li , Domokos Esztergár-Kiss , Tuqiang Zhou

Segregated waste transportation is crucial for the implementation of waste classification. The use of electric vehicles in smart cities to collect and transport waste directly to treatment plants can help to remove waste compacting stations. The amount of each type of generated wastes varies in different locations. However, the current uniform plan for configuring the number of bins is not reasonable, which results in a conflict between the operating costs of the waste collection services and the residents' dissatisfaction with the service. In this study, a plan is proposed to determine the number of waste bins based on the amount of the generated waste. A bi-objective optimization model is developed to solve the optimization of transportation routes with the Internet of Things transport mode. The model is solved by using an improved NSGA-II algorithm. A case study that examines transportation routes in 10 districts is conducted. The results show that the proposed plan is effective in reducing the costs of waste collection services and residents' dissatisfaction with the service. The proposed plan can reduce the operating expenses by ¥5.13 million in three years in 10 districts.

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引用次数: 0

Effect of solar photovoltaics on green roof energy balance and evapotranspiration

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

Sustainable Cities and Society

Pub Date : 2025-02-18 DOI: 10.1016/j.scs.2025.106206

Tej Žižak, Sašo Medved, Ciril Arkar

Photovoltaic green roofs represent an emerging technology that combines on-site renewable energy production with the environmental benefits of green roofs. Detailed models for calculating energy fluxes on photovoltaic green roofs are presented, relying on accessible meteorological data and setup geometry as input data. A key focus is the accurate modelling of longwave radiation, an often-overlooked component of energy balance. Experimental results reveal up to a 100 W m^-² difference in incoming longwave radiation on green roof surface under photovoltaics compared to open-sky conditions, demonstrating the significant impact on the energy balance. The precise modelling of short and longwave radiation is achieved through proposed shading and view factor calculation methods, as well as with a developed parametric model for green roof surface temperature under varying shading factors. Neglecting longwave radiation exchange with photovoltaic modules would result in an 18 % underestimation of daily evapotranspiration. A complete detailed model for evapotranspiration calculation is proposed, achieving a 4.4 % normalized root mean square error for daily predictions. By accurately estimating energy fluxes and evapotranspiration, this study provides tools for quantifying water needs, optimizing the synergy between green roofs and photovoltaics, and assessing their broader impacts on urban microclimates.

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引用次数: 0

How are green spaces associated with chronic disease incidence in Australia? Direct health benefits and interactive effects with socioeconomic status based on multiple green space indicators

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

Sustainable Cities and Society

Pub Date : 2025-02-18 DOI: 10.1016/j.scs.2025.106229

Yunzheng Zhang , Fubin Luo

The health benefits of urban greenery are well-documented, yet findings vary depending on the green space indicators used. Given the limited Australia-based research incorporating both traditional and emerging indicators, this study employs the proportion of parkland, the Normalized Difference Vegetation Index (NDVI), and Google Street View Greenness (SVG), to explore how green spaces and their interactions with socioeconomic status relate to chronic disease incidence rates in Sydney at Statistical Area Levels 1 and 2 (SA1 and SA2). The findings indicate that: (1) While green spaces are not significantly related to overall chronic diseases, they show strong associations with specific diseases, particularly dementia (SA1: Park: coef. = -0.004, p < 0.001; NDVI: coef. = -0.008, p < 0.001; SVG: coef. = -0.009, p < 0.001; SA2: SVG: coef. = -0.005, p < 0.05) and diabetes (SA1: SVG: coef. = -0.013, p < 0.001; SA2: Park: coef. = -0.009, p < 0.05; NDVI: coef. = -0.016, p < 0.01; SVG: coef. = -0.033, p < 0.001), with SVG being the most prevalent predictor. (2) Green spaces, particularly parkland, may mitigate chronic disease risks in lower socioeconomic regions, especially in aging areas (SA1: age#Park: coef. = -0.125, p < 0.001; age#NDVI: coef. = -0.081, p < 0.01; age#SVG: coef. = -0.078, p < 0.01). Additionally, these associations are more pronounced at the neighborhood scale than at the suburb scale. This study examines multiple green space indicators from an Australian perspective, offering insights for international comparisons and public health improvements.

{"title":"How are green spaces associated with chronic disease incidence in Australia? Direct health benefits and interactive effects with socioeconomic status based on multiple green space indicators","authors":"Yunzheng Zhang , Fubin Luo","doi":"10.1016/j.scs.2025.106229","DOIUrl":"10.1016/j.scs.2025.106229","url":null,"abstract":"<div><div>The health benefits of urban greenery are well-documented, yet findings vary depending on the green space indicators used. Given the limited Australia-based research incorporating both traditional and emerging indicators, this study employs the proportion of parkland, the Normalized Difference Vegetation Index (NDVI), and Google Street View Greenness (SVG), to explore how green spaces and their interactions with socioeconomic status relate to chronic disease incidence rates in Sydney at Statistical Area Levels 1 and 2 (SA1 and SA2). The findings indicate that: (1) While green spaces are not significantly related to overall chronic diseases, they show strong associations with specific diseases, particularly dementia (SA1: Park: coef. = -0.004, <em>p</em> < 0.001; NDVI: coef. = -0.008, <em>p</em> < 0.001; SVG: coef. = -0.009, <em>p</em> < 0.001; SA2: SVG: coef. = -0.005, <em>p</em> < 0.05) and diabetes (SA1: SVG: coef. = -0.013, <em>p</em> < 0.001; SA2: Park: coef. = -0.009, <em>p</em> < 0.05; NDVI: coef. = -0.016, <em>p</em> < 0.01; SVG: coef. = -0.033, <em>p</em> < 0.001), with SVG being the most prevalent predictor. (2) Green spaces, particularly parkland, may mitigate chronic disease risks in lower socioeconomic regions, especially in aging areas (SA1: age#Park: coef. = -0.125, <em>p</em> < 0.001; age#NDVI: coef. = -0.081, <em>p</em> < 0.01; age#SVG: coef. = -0.078, <em>p</em> < 0.01). Additionally, these associations are more pronounced at the neighborhood scale than at the suburb scale. This study examines multiple green space indicators from an Australian perspective, offering insights for international comparisons and public health improvements.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"121 ","pages":"Article 106229"},"PeriodicalIF":10.5,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143464196","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

Assessment framework for gaseous pollutant emissions from decentralized pyrolysis units in urban canopies: Case study in Singapore

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

Sustainable Cities and Society

Pub Date : 2025-02-18 DOI: 10.1016/j.scs.2025.106231

Genevieve Soon , Wei Ping Chan , Grzegorz Lisak , Adrian Wing-Keung Law

This study aims to establish an assessment framework for analyzing gaseous emissions from a decentralized pyrolysis unit within an urban environment, with a focus on a case study conducted in Singapore. The framework integrates Computational Fluid Dynamics (CFD) modelling to evaluate pollutant dispersion, considering factors such as emission source characteristics and urban canopy effects. Specifically, we apply this framework on a point source emission within an actual field site, namely the Bishan-Ang Mo Kio Park, Singapore which is surrounded by high-rise buildings. Our findings highlight the significance of emission source characteristics, particularly in conservative scenarios characterized by low wind speeds, reduced emission temperatures, and lower emission heights. Furthermore, the suitability of current industrial emission limits in Singapore for residential settings was evaluated, suggesting adjustments for specific pollutants like PM_2.5. Additionally, guidelines for defining emission source buffer zones based on air quality indexes were proposed, aiding decision-making in the siting of future units amidst multiple options. The assessment framework offers versatility for applications across various regions and waste types, contributing to enhanced air quality management strategies in urban settings.

{"title":"Assessment framework for gaseous pollutant emissions from decentralized pyrolysis units in urban canopies: Case study in Singapore","authors":"Genevieve Soon , Wei Ping Chan , Grzegorz Lisak , Adrian Wing-Keung Law","doi":"10.1016/j.scs.2025.106231","DOIUrl":"10.1016/j.scs.2025.106231","url":null,"abstract":"<div><div>This study aims to establish an assessment framework for analyzing gaseous emissions from a decentralized pyrolysis unit within an urban environment, with a focus on a case study conducted in Singapore. The framework integrates Computational Fluid Dynamics (CFD) modelling to evaluate pollutant dispersion, considering factors such as emission source characteristics and urban canopy effects. Specifically, we apply this framework on a point source emission within an actual field site, namely the Bishan-Ang Mo Kio Park, Singapore which is surrounded by high-rise buildings. Our findings highlight the significance of emission source characteristics, particularly in conservative scenarios characterized by low wind speeds, reduced emission temperatures, and lower emission heights. Furthermore, the suitability of current industrial emission limits in Singapore for residential settings was evaluated, suggesting adjustments for specific pollutants like PM<sub>2.5</sub>. Additionally, guidelines for defining emission source buffer zones based on air quality indexes were proposed, aiding decision-making in the siting of future units amidst multiple options. The assessment framework offers versatility for applications across various regions and waste types, contributing to enhanced air quality management strategies in urban settings.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"122 ","pages":"Article 106231"},"PeriodicalIF":10.5,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143548614","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