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The influence of building height on microclimate and human activities in urban open spaces 建筑高度对城市开放空间小气候和人类活动的影响
IF 3.8 Q2 ENVIRONMENTAL SCIENCES Pub Date : 2025-12-14 DOI: 10.1016/j.cacint.2025.100283
Mehrdad Karimimoshaver , Alireza Gerami , Banu Ozkazanc , Amir Mosavi
As urban populations increase and tall residential buildings gradually define city skylines, their impact on microclimate and human activity in open spaces has become a critical matter for sustainable urban design. Despite growing attention to outdoor thermal comfort, most existing studies rely on simulation-based thermal indices with limited connection to real-world behavior. This study addresses this gap through investigating how tall residential structures affect both thermal conditions and actual patterns of human activity, such as walking, cycling, sitting, and socializing, in urban open spaces where both tall and low-rise buildings coexist. The novelty of this research lies in its mixed-methods approach, combining year-round behavioral mapping with microclimatic simulations using Ladybug and Honeybee tools. This study was conducted in Istanbul, which has a temperate Mediterranean climate, from 2023 to2024. The proposed methodology is a combination of experimental observations with software analyses which includes Grasshopper, Ladybug, and Honeybee based on environmental data to evaluate pedestrian comfort and space usability in different urban morphologies. The findings of this study suggest that low-rise areas have better thermal and social performance, while conditions in spaces adjacent to tall buildings are less usable. However, environmental variables such as shade, urban furniture, and wind flow play a role in these effects. Finally, this study provides practical guidelines for urban designers and planners to enhance both thermal resilience and social livability in urban environments.
随着城市人口的增加和高层住宅建筑逐渐定义城市天际线,它们对开放空间小气候和人类活动的影响已成为可持续城市设计的关键问题。尽管人们越来越关注室外热舒适,但大多数现有研究都依赖于基于模拟的热指标,与现实世界的行为联系有限。这项研究通过调查高层住宅结构如何影响热条件和人类活动的实际模式,如步行、骑自行车、坐着和社交,在高层和低层建筑共存的城市开放空间中,解决了这一差距。这项研究的新颖之处在于它的混合方法,将全年行为映射与使用瓢虫和蜜蜂工具的小气候模拟相结合。这项研究于2023年至2024年在伊斯坦布尔进行,那里属于温带地中海气候。提出的方法是将实验观察与软件分析相结合,包括基于环境数据的蚱蜢、瓢虫和蜜蜂,以评估不同城市形态下的行人舒适度和空间可用性。本研究的结果表明,低层建筑具有更好的热性能和社会性能,而与高层建筑相邻的空间条件则不太可用。然而,诸如遮阳、城市家具和气流等环境变量在这些影响中发挥了作用。最后,本研究为城市设计师和规划者提高城市环境的热弹性和社会宜居性提供了实用指南。
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引用次数: 0
Examining inclusive governance of community gardens: lessons from European cities 审视社区花园的包容性治理:来自欧洲城市的经验教训
IF 3.8 Q2 ENVIRONMENTAL SCIENCES Pub Date : 2025-12-14 DOI: 10.1016/j.cacint.2025.100286
Patricia Abrantes , Luís Moreno , Maria Lucinda Fonseca , Burcu Borhan Türeli , Christos Stergiadis , Gábor Szüdi , Martin Felix Gajdusek , Carolin V. Zorell
As urban populations grow and climate pressures intensify, community gardens (CGs) are increasingly recognised as infrastructures that support food sovereignty, resilience, and social inclusion. Yet little is known about how governance, understood here as the structures, relationships, and participatory processes through which actors share decisions, shapes these outcomes. This study addresses this gap by examining how governance influence inclusion and long-term viability in seven CGs located in Portugal, Türkiye, Austria, Hungary, and Greece, all targeting vulnerable communities. Using a qualitative comparative design, we combine semi-structured interviews (n = 65), policy and document analysis, and a cross-case scoring system to assess structural, relational, and procedural governance dimensions through an intersectional gender + lens. Findings show clear patterns: CGs with stronger relational and procedural governance demonstrate higher levels of inclusion, particularly for women, migrants, and low-income residents. Structurally robust CGs, characterised by secure land tenure, formalisation, and institutional support, are crucial for long-term stability and potential scaling. However, weak vertical policy integration across local, national, and European levels in most cases limits their broader systemic impact. Overall, the results suggest that long-term outcomes are best supported by governance frameworks that combine institutional support, citizen co-decision-making, and coherent multilevel policy articulation. These insights contribute to debates on urban governance by identifying practical pathways for municipalities and communities to co-produce more equitable and durable governance arrangements around community gardens.
随着城市人口的增长和气候压力的加剧,社区花园(CGs)越来越被认为是支持粮食主权、恢复力和社会包容的基础设施。然而,人们对治理如何形成这些结果知之甚少,这里将治理理解为参与者分享决策的结构、关系和参与过程。本研究通过考察治理如何影响葡萄牙、土耳其、奥地利、匈牙利和希腊七个社区的包容性和长期生存能力,解决了这一差距,这些社区均以弱势社区为目标。采用定性比较设计,我们结合了半结构化访谈(n = 65)、政策和文件分析以及跨案例评分系统,通过交叉性别+视角评估结构性、关系性和程序性治理维度。研究结果显示了明确的模式:关系性和程序性治理更强的CGs显示出更高的包容性水平,特别是对妇女、移民和低收入居民。结构稳健的CGs,其特点是有保障的土地权属、正规化和制度支持,对长期稳定和潜在规模至关重要。然而,在大多数情况下,地方、国家和欧洲层面的纵向政策整合薄弱,限制了它们更广泛的系统性影响。总体而言,研究结果表明,结合机构支持、公民共同决策和连贯的多层次政策表述的治理框架最能支持长期成果。这些见解通过确定市政当局和社区围绕社区花园共同制定更公平和持久的治理安排的实际途径,促进了关于城市治理的辩论。
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引用次数: 0
Environmental health literacy: an exploratory conceptual redefinition and explanation structuralized from comprehensive multidisciplinary expert perspectives along with public insights 环境健康素养:一种探索性的概念重新定义和解释,从综合多学科专家的角度以及公众的见解结构化
IF 3.8 Q2 ENVIRONMENTAL SCIENCES Pub Date : 2025-12-13 DOI: 10.1016/j.cacint.2025.100285
Leili Mazar , Sakineh Rakhshanderou , Anoushiravan Mohseni-Bandpei , Mohtasham Ghaffari
The environment plays a critical role in public health and sustainable community development. Enhancing Environmental Health Literacy (EHL) is essential for mitigating health risks, improving quality of life, and promoting environmental protection. However, as a relatively new concept, EHL remains conceptually ambiguous and requires further clarification. This study aimed to explore and redefine EHL while identifying its core dimensions. Using an exploratory qualitative approach, we conducted in-depth, semi-structured interviews with 35 experts in public health and environmental sciences, as well as 30 diverse adults from Tehran, capital of Iran. Participants were selected through purposive and snowball sampling between February and October 2024. Data were analyzed using conventional content analysis guided by Graneheim and Lundman’s approach. Analysis resulted in 620 initial codes that were organized into 18 subcategories and six main dimensions of EHL: cognitive, affective, behavioral, media, basic, and communication literacy. Additionally, two overarching conceptual approaches emerged—environment-oriented and content-oriented—reflecting differences in how participants viewed the environments relevant to EHL and the disciplinary domains that inform its content. By integrating multidisciplinary expert insights with lived perspectives from adults, this study provides a comprehensive, contextually grounded conceptualization of EHL. The findings provide a foundation for developing assessment tools, designing targeted educational programs, and formulating policies to enhance EHL across diverse settings. By equipping individuals and communities with EHL to navigate environmental risks, this research underscores its role in shaping effective public health interventions, promoting environmental sustainability, and enhancing resilience in both urban and non-urban contexts.
环境在公共卫生和可持续社区发展方面发挥着关键作用。提高环境卫生素养对于减轻健康风险、提高生活质量和促进环境保护至关重要。然而,作为一个相对较新的概念,EHL在概念上仍然是模糊的,需要进一步澄清。本研究旨在探索和重新定义EHL,并确定其核心维度。采用探索性定性方法,我们对来自伊朗首都德黑兰的35名公共卫生和环境科学专家以及30名不同类型的成年人进行了深入的半结构化访谈。参与者是在2024年2月至10月期间通过有目的的滚雪球抽样选择的。数据分析采用Graneheim和Lundman方法指导下的传统内容分析。分析得出620个初始代码,这些代码被组织成18个子类别和EHL的6个主要维度:认知、情感、行为、媒体、基本和沟通素养。此外,出现了两种主要的概念方法——面向环境和面向内容——反映了参与者如何看待与EHL相关的环境和告知其内容的学科领域的差异。通过将多学科专家的见解与成人的生活观点相结合,本研究提供了一个全面的、基于情境的EHL概念化。研究结果为开发评估工具、设计有针对性的教育项目和制定政策以加强不同环境下的EHL提供了基础。通过为个人和社区提供EHL以应对环境风险,本研究强调了其在形成有效的公共卫生干预措施、促进环境可持续性以及增强城市和非城市环境抵御力方面的作用。
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引用次数: 0
When the sun goes down, heat vulnerability remains 当太阳下山时,热脆弱性仍然存在
IF 3.8 Q2 ENVIRONMENTAL SCIENCES Pub Date : 2025-12-12 DOI: 10.1016/j.cacint.2025.100284
Jiayang Hu , Florence Gignac , Sam Pickard , Paloma Trascasa Castro , Eren Duzenli , Dragana Bojovic
Continuously rising temperatures due to climate change allow extreme heat-related risks to persist throughout the entire day. While daytime and nighttime heat are well distinguished in climate research, the social inequities and adaptation strategies linked to nighttime heat remain overlooked. This short communication proposes a multidimensional perspective to nighttime heat, combining recent climate data, vulnerability analysis and urban adaptation strategies. Using Barcelona, Spain, as a city of reference, we discuss how localized urban heat islands, limited access to climate shelters, and stressors like traffic noise levels intersect to shape heat risk and climate injustice at night. Building an equitable climate resilience to nighttime heat means not only mapping where heat remains at night but also designing strategies for night hours and broadening how heat vulnerability is assessed. This piece calls on both researchers and practitioners to consider climate science, social equity and urban policy through a nighttime lens, and consequently, to ensure a more comprehensive way to support vulnerable population groups.
由于气候变化,气温持续上升,导致与极端高温相关的风险持续一整天。虽然在气候研究中,白天和夜间的热量被很好地区分开来,但与夜间热量相关的社会不平等和适应策略仍然被忽视。这种简短的交流结合了最近的气候数据、脆弱性分析和城市适应策略,提出了夜间高温的多维视角。以西班牙巴塞罗那为例,我们讨论了局部的城市热岛、有限的气候庇护所和交通噪音水平等压力因素如何交叉影响夜间的高温风险和气候不公正。建立对夜间高温的公平的气候适应能力不仅意味着绘制夜间存在热量的地点,还意味着设计夜间策略,并扩大热脆弱性的评估方式。这篇文章呼吁研究人员和实践者通过夜间镜头来考虑气候科学、社会公平和城市政策,从而确保以更全面的方式支持弱势群体。
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引用次数: 0
Leveraging the Self-Attention Mechanism: Cutting-Edge predictive modeling for ozone concentration dynamics 利用自我注意机制:臭氧浓度动力学的前沿预测模型
IF 3.8 Q2 ENVIRONMENTAL SCIENCES Pub Date : 2025-12-10 DOI: 10.1016/j.cacint.2025.100282
Nouar AlDahoul , Haitham Abdulmohsin Afan , Faidhalrahman Khaleel , Ali NajahAhmed , Riyadh Alsultani , Saif Saad Mansoor , Muhammed Basheer Jasser , Mohsen Sherif , Ahmed El-Shafie
Accurate and timely prediction of ozone concentrations is critical for meteorological monitoring and developing effective environmental policies, promoting both resilience and sustainability, as prolonged exposure to elevated pollutant levels poses significant risks to human health and ecosystem integrity. In fact, ozone concentration monitoring and reduction align with global efforts to reduce its negative impact on air pollution (SDG 3: Good Health and Well-being) and enhance urban environmental resilience (SDG 11: Sustainable Cities and Communities). However, the complex physicochemical processes governing tropospheric ozone formation present substantial challenges for precise modeling. Recent advancements in data-driven machine-learning approaches have demonstrated considerable potential in addressing these challenges, particularly in predicting ozone concentrations. Deep learning models, in particular, have been employed to analyze ozone data as time series, leveraging historical concentration values collected over hours or days. Despite these advancements, opportunities remain for enhancing predictive accuracy through the application of state-of-the-art attention-based architectures, such as the Support Vector Machine (SVM), Long Short-Term Memory (LSTM), and Transformer model. This study investigates the efficacy of the self-attention mechanism in predicting ozone concentrations across three monitoring stations in Malaysia: Kuala Lumpur (KL), Putrajaya (PJ), and Klang, using hourly data for the duration between 2012 and 2019, which have been collected from the Department of Environment (DOE). Ministry of Natural Resources and Environmental Sustainability (NRES). The results reveal exceptional performance, with high coefficients of determination (R2) and low mean squared errors (MSE) achieved for PJ, KL, and Klang. Furthermore, the Transformer model significantly reduced both training and inference times (70 s and 1 s, respectively) compared to the LSTM model (110 s and 7.7 s), particularly when long-term historical ozone data is required for prediction. These findings highlight the robust capabilities of self-attention mechanisms in enhancing the accuracy and efficiency of ozone concentration forecasting, warranting further investigation and validation across diverse urban environments globally and contributing to sustainable urban planning and resilience of environmental monitoring systems.
准确和及时地预测臭氧浓度对于气象监测和制定有效的环境政策、促进复原力和可持续性至关重要,因为长期暴露于高水平的污染物对人类健康和生态系统完整性构成重大风险。事实上,监测和减少臭氧浓度与减少其对空气污染的负面影响(可持续发展目标3:良好健康和福祉)和增强城市环境复原力(可持续发展目标11:可持续城市和社区)的全球努力是一致的。然而,控制对流层臭氧形成的复杂物理化学过程对精确建模提出了重大挑战。数据驱动的机器学习方法的最新进展在应对这些挑战方面显示出相当大的潜力,特别是在预测臭氧浓度方面。特别是,深度学习模型已被用于分析臭氧数据作为时间序列,利用在数小时或数天内收集的历史浓度值。尽管取得了这些进步,但通过应用最先进的基于注意力的体系结构,如支持向量机(SVM)、长短期记忆(LSTM)和Transformer模型,仍然有机会提高预测的准确性。本研究利用从马来西亚环境部(DOE)收集的2012年至2019年每小时的数据,调查了自关注机制在预测马来西亚三个监测站(吉隆坡(KL)、布城(PJ)和巴生)臭氧浓度方面的功效。自然资源和环境可持续发展部。结果显示优异的性能,PJ, KL和Klang具有高决定系数(R2)和低均方误差(MSE)。此外,与LSTM模型(分别为110秒和7.7秒)相比,Transformer模型显著减少了训练和推理时间(分别为70秒和1秒),特别是在需要长期历史臭氧数据进行预测时。这些发现突出了自我关注机制在提高臭氧浓度预测的准确性和效率方面的强大能力,值得在全球不同的城市环境中进行进一步的调查和验证,并有助于可持续的城市规划和环境监测系统的复原力。
{"title":"Leveraging the Self-Attention Mechanism: Cutting-Edge predictive modeling for ozone concentration dynamics","authors":"Nouar AlDahoul ,&nbsp;Haitham Abdulmohsin Afan ,&nbsp;Faidhalrahman Khaleel ,&nbsp;Ali NajahAhmed ,&nbsp;Riyadh Alsultani ,&nbsp;Saif Saad Mansoor ,&nbsp;Muhammed Basheer Jasser ,&nbsp;Mohsen Sherif ,&nbsp;Ahmed El-Shafie","doi":"10.1016/j.cacint.2025.100282","DOIUrl":"10.1016/j.cacint.2025.100282","url":null,"abstract":"<div><div>Accurate and timely prediction of ozone concentrations is critical for meteorological monitoring and developing effective environmental policies, promoting both resilience and sustainability, as prolonged exposure to elevated pollutant levels poses significant risks to human health and ecosystem integrity. In fact, ozone concentration monitoring and reduction align with global efforts to reduce its negative impact on air pollution (SDG 3: Good Health and Well-being) and enhance urban environmental resilience (SDG 11: Sustainable Cities and Communities). However, the complex physicochemical processes governing tropospheric ozone formation present substantial challenges for precise modeling. Recent advancements in data-driven machine-learning approaches have demonstrated considerable potential in addressing these challenges, particularly in predicting ozone concentrations. Deep learning models, in particular, have been employed to analyze ozone data as time series, leveraging historical concentration values collected over hours or days. Despite these advancements, opportunities remain for enhancing predictive accuracy through the application of state-of-the-art attention-based architectures, such as the Support Vector Machine (SVM), Long Short-Term Memory (LSTM), and Transformer model. This study investigates the efficacy of the self-attention mechanism in predicting ozone concentrations across three monitoring stations in Malaysia: Kuala Lumpur (KL), Putrajaya (PJ), and <u>Klang</u>, using hourly data for the duration between 2012 and 2019, which have been collected from the Department of Environment (DOE). Ministry of Natural Resources and Environmental Sustainability (NRES). The results reveal exceptional performance, with high coefficients of determination (R<sup>2</sup>) and low mean squared errors (MSE) achieved for PJ, KL, and Klang. Furthermore, the Transformer model significantly reduced both training and inference times (70 s and 1 s, respectively) compared to the LSTM model (110 s and 7.7 s), particularly when long-term historical ozone data is required for prediction. These findings highlight the robust capabilities of self-attention mechanisms in enhancing the accuracy and efficiency of ozone concentration forecasting, warranting further investigation and validation across diverse urban environments globally and contributing to sustainable urban planning and resilience of environmental monitoring systems.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"29 ","pages":"Article 100282"},"PeriodicalIF":3.8,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145797782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Impacts of urbanization and climate change on stormwater drainage efficiency: A PCSWMM 7.5 case study in Dilla Town, Ethiopia 城市化和气候变化对雨水排水效率的影响:埃塞俄比亚Dilla镇PCSWMM 7.5案例研究
IF 3.8 Q2 ENVIRONMENTAL SCIENCES Pub Date : 2025-12-07 DOI: 10.1016/j.cacint.2025.100280
Yohannes Belachew Girma , Daniel Reddythota , Geleta Tilahun Negatu
Rainfall-induced flooding disrupts social urban life, damages infrastructure, and spreads water-borne diseases, primarily due to rapid urbanisation, changing rainfall patterns, and inadequate drainage systems. This study assesses the combined impacts of climate change and urbanisation on the stormwater drainage networks (SWDN) of Dilla town, Ethiopia, using storm-water management models (EPASWMM 5.2, PCSWMM 7.5), ArcGIS, and climate scenarios RCP4.5 and RCP8.5. The average performance of the SWDN) across six kebeles is poor (55.52 %), due to undersized and insufficient infrastructure. Future projections (2022–2053) indicate increased rainfall intensities of 31.34 mm/hr (RCP4.5) and 35 mm/hr (RCP8.5), exceeding the historical baseline. Over the past two decades, impervious surfaces have increased to 38.05 %, and residential areas expanded to 727.53 ha, rising impervious coverage from 27.83 % to 65.88 %. Sub-catchments SC1, SC6, SC7, SC10, SC17, SC25, SC35, and SC37 exhibit the highest peak runoff due to extensive impervious cover. This study uniquely integrates climate projections, urban growth analysis, and hydraulic modelling using PCSWMM to quantify compound flood risks, representing one of the first such applications in an Ethiopian secondary city. The framework and findings from Dilla are transferable to other rapidly growing sub-Saharan cities facing similar hydrological and infrastructural challenges.
降雨引发的洪水扰乱了城市社会生活,破坏了基础设施,并传播了水媒疾病,这主要是由于快速城市化、降雨模式变化和排水系统不足造成的。本研究利用雨水管理模型(EPASWMM 5.2、PCSWMM 7.5)、ArcGIS和气候情景RCP4.5和RCP8.5,评估了气候变化和城市化对埃塞俄比亚Dilla镇雨水排水网络(SWDN)的综合影响。由于规模不足和基础设施不足,六个kebeles的SWDN平均性能较差(55.52%)。未来预估(2022-2053)表明,降水强度将增加至31.34 mm/hr (RCP4.5)和35 mm/hr (RCP8.5),超过历史基线。在过去的二十年中,不透水地表增加到38.05%,住宅面积扩大到727.53公顷,不透水覆盖率从27.83%增加到65.88%。子流域SC1、SC6、SC7、SC10、SC17、SC25、SC35和SC37由于广泛的不透水覆盖而表现出最高的峰值径流。该研究独特地将气候预测、城市增长分析和使用PCSWMM的水力建模整合在一起,量化了复合洪水风险,这是埃塞俄比亚二级城市的首次此类应用之一。Dilla的框架和研究结果可推广到其他面临类似水文和基础设施挑战的快速发展的撒哈拉以南城市。
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引用次数: 0
Balancing positive and negative environmental impacts of urban greening considering future climate: A case study in the Paris region, France 考虑未来气候平衡城市绿化对环境的积极和消极影响:以法国巴黎地区为例
IF 3.8 Q2 ENVIRONMENTAL SCIENCES Pub Date : 2025-12-06 DOI: 10.1016/j.cacint.2025.100277
Robin Monnier , Erwan Personne , Patrick Stella , Laura Ferraz de Paula , Patrick Schalbart , Charlotte Roux , Bruno Peuportier
Urban greening enhances summer thermal comfort in cities; however, vegetation requires watering and reduces solar gains on buildings, potentially increasing energy consumption for heating. A methodology was developed to investigate whether the positive effects of urban trees on human health offset the increased water and energy consumption impacts. This method involves four steps: 1. Modelling the urban microclimate based on regional climatic data, accounting for vegetation effects; 2. Evaluating indoor temperatures and possible overheating using building thermal simulation; 3. Deriving the damage of overheating on human health, and 4. Performing a life cycle assessment.
This process was applied to a case study on an urban greening project, including renovating an existing social housing building. According to the results, urban greening thanks to trees allows a decrease in outdoor air temperature around 1.7 °C (median value, 1.3 °C and 2.0 °C for 10th and 90th percentile, resp.) and a decrease in indoor temperature around 0.4 °C (median value; 0.25 °C and 0.55 for 10th and 90th percentile, resp.) during the five weeks heat wave period. Some life-cycle environmental impacts were reduced, particularly those related to damage to human health (−12.5 %), with limited impact transfer. The impact reduction due to energy savings from building renovation is higher.
While many cities invest in urban greening projects, the importance of energy renovation is often overlooked. This prioritisation may be questioned, and the analysis presented in this article could serve as a valuable tool in guiding decision-making. By using the same indicator (Disability-Adjusted Life Years, DALY) to express life cycle and overheating-related impacts, this approach enables the integration of mitigation and adaptation in decision-making processes.
城市绿化提高城市夏季热舒适性;然而,植被需要浇水,减少了建筑物的太阳能增益,潜在地增加了供暖的能源消耗。开发了一种方法来调查城市树木对人类健康的积极影响是否抵消了水和能源消耗增加的影响。该方法包括四个步骤:1。基于区域气候数据的城市小气候建模,考虑植被效应;2. 使用建筑热模拟评估室内温度和可能的过热;3. 3 .得出过热对人体健康的危害;执行生命周期评估。这一过程被应用于一个城市绿化项目的案例研究,其中包括改造现有的社会住房建筑。结果表明,在为期五周的热浪期内,树木的城市绿化使室外气温下降约1.7°C(中值,第10和第90百分位分别为1.3°C和2.0°C),室内温度下降约0.4°C(中值,第10和第90百分位分别为0.25°C和0.55)。一些生命周期的环境影响减少了,特别是与人类健康损害有关的影响(- 12.5%),影响转移有限。由于建筑改造节省的能源减少的影响更高。虽然许多城市投资城市绿化项目,但能源改造的重要性往往被忽视。这种优先次序可能会受到质疑,本文中提出的分析可以作为指导决策的宝贵工具。通过使用相同的指标(残疾调整生命年,DALY)来表示生命周期和与过热有关的影响,这种方法能够在决策过程中整合缓解和适应。
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引用次数: 0
Development of a PCA-derived water quality index model for monitoring the urban river systems in Dhaka City, Bangladesh 开发pca衍生的水质指数模型,用于监测孟加拉国达卡市的城市河流系统
IF 3.8 Q2 ENVIRONMENTAL SCIENCES Pub Date : 2025-12-04 DOI: 10.1016/j.cacint.2025.100276
Md Mahmud Kamal Bhuiyan , Hridoy Roy , Kazi Saidur Rahman , Bimol Nath Roy , Md. Al Amin Kabir Bhuyan , Md. Rezaul Maksud Jahedi , Md. Shahinoor Islam
In this study, a Water Quality Index (WQI) model was developed to assess the water quality of the major rivers in Dhaka city, including Buriganga, Balu, Turag, and Sitalakhya, based on a comprehensive dataset collected across four seasons (dry, pre-monsoon, monsoon, post-monsoon) in 2024. A total of 144 water samples were analyzed for 16 water quality parameters, and principal component analysis (PCA) combined with correlation analysis was applied to identify eight key parameters: pH, dissolved oxygen (DO), total solids (TS), chemical oxygen demand (COD), chloride, ammonia–nitrogen, E. coli, and total coliform. Sub-indexing was performed using quality rating curves provided by NSF-WQI and a linear interpolation function to transform parameter values into standardized scores. PCA was used again to assign weights based on eigenvalues, a data-driven approach to parameter weighting, with TS (0.215) and ammonia–nitrogen (0.199) contributing most to pollution levels. The final WQI, calculated using a weighted aggregation function, ranged from 29.78 to 77.96, with Buriganga exhibiting the poorest water quality (mean WQI: 46.85) and Sitalakhya the best (mean WQI: 57.10). Seasonal variations revealed that the dry season WQI reached as low as 29.78, while dilution during the monsoon season improved water quality to a maximum of 74.29. Statistical analysis confirmed significant temporal (p < 0.001) and spatial (p < 0.001) variations in water quality. Sensitivity analysis identified TS, COD, and chloride as the most influential parameters. This study presents a robust, data-driven WQI model for efficient monitoring and management of water quality in Dhaka.
在本研究中,基于2024年四个季节(旱季、季风前、季风后)收集的综合数据集,开发了水质指数(WQI)模型,以评估达卡市主要河流的水质,包括Buriganga、Balu、Turag和Sitalakhya。对144份水样的16个水质参数进行了分析,采用主成分分析(PCA)结合相关分析,确定了8个关键参数:pH、溶解氧(DO)、总固体(TS)、化学需氧量(COD)、氯化物、氨氮、大肠杆菌和总大肠菌群。采用NSF-WQI提供的质量评定曲线和线性插值函数进行分标,将参数值转化为标准化分数。再次使用主成分分析法根据特征值分配权重,这是一种数据驱动的参数加权方法,其中TS(0.215)和氨氮(0.199)对污染水平的贡献最大。利用加权聚集函数计算的最终WQI范围为29.78 ~ 77.96,其中Buriganga最差(平均WQI为46.85),Sitalakhya最好(平均WQI为57.10)。季节变化表明,旱季WQI低至29.78,而季风期的稀释使水质改善至74.29。统计分析证实了显著的时间(p < 0.001)和空间(p < 0.001)水质变化。敏感性分析发现TS、COD和氯化物是影响最大的参数。本研究提出了一个强大的、数据驱动的WQI模型,用于达卡水质的有效监测和管理。
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引用次数: 0
Corrigendum to “Citizen perceptions on the use, management and availability of green spaces in a Mediterranean region” [City Environ. Interact. 27 (2025) 100210] “地中海地区市民对绿色空间的使用、管理和可用性的看法”[城市环境]的更正。交互。27 (2025)100210]
IF 3.8 Q2 ENVIRONMENTAL SCIENCES Pub Date : 2025-12-01 DOI: 10.1016/j.cacint.2025.100220
Daniel Jato-Espino , Fabio Capra-Ribeiro , Vanessa Moscardó , Laura O. Gallardo
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引用次数: 0
Inclusive public spaces for vulnerable populations: assessing needs and social implications for Bangkok Metropolitan area 弱势群体的包容性公共空间:评估曼谷大都市区的需求和社会影响
IF 3.8 Q2 ENVIRONMENTAL SCIENCES Pub Date : 2025-12-01 DOI: 10.1016/j.cacint.2025.100272
Warawoot Chuangchai , Wiraporn Pothisiri
Vulnerable populations face increased risks of social violence and discrimination in public spaces, especially in the Global South. Despite growing interest in inclusive design to address these issues, understanding of their experiences and expectations remains inadequate. This study aimed to identify the specific needs for public spaces among people with disabilities in Bangkok, Thailand. A total of 407 individuals with disabilities were contacted and classified into eight disability categories. Of these, 384 participants completed a quantitative survey, and a subset of 23 individuals participated in in-depth interviews to explore their experiences and needs in greater detail. A key finding from the interviews was that many vulnerable individuals expressed a preference for public areas separated from the general public. This preference was voiced by over 60 percent across all gender groups. Beyond physical accessibility challenges, safety concerns related to socially negative behaviors shaped their preferences. Risks of sexual assault (mainly by non-disabled men against women with disabilities), discrimination, and social judgment were identified as threats to public safety. Those willing to share spaces with the general public often expressed hesitance to reveal their impairments publicly, fearing social attention, danger, and stigma. The study argues that providing physical access alone is insufficient; addressing social barriers is essential to creating secure, inclusive environments. The findings underscore the need to prioritize vulnerable populations’ needs in inclusive design, social spaces, and public policy.
弱势群体在公共场所面临越来越大的社会暴力和歧视风险,尤其是在全球南方。尽管人们对解决这些问题的包容性设计越来越感兴趣,但对他们的经历和期望的理解仍然不足。本研究旨在确定泰国曼谷残疾人对公共空间的具体需求。共联系了407名残疾人,并将其分为8类。其中,384名参与者完成了定量调查,另有23人参加了深度访谈,以更详细地探讨他们的经历和需求。访谈的一个重要发现是,许多弱势群体表示,他们更喜欢远离公众的公共区域。在所有性别群体中,超过60%的人表示了这种偏好。除了物理无障碍的挑战,与社会消极行为有关的安全问题影响了他们的偏好。性侵犯(主要是非残疾男性对残疾女性的性侵犯)、歧视和社会评判的风险被认为是对公共安全的威胁。那些愿意与公众分享空间的人往往对公开展示自己的缺陷表示犹豫,担心社会关注、危险和耻辱。该研究认为,仅提供物理通道是不够的;消除社会障碍对于创造安全、包容的环境至关重要。研究结果强调,需要在包容性设计、社会空间和公共政策方面优先考虑弱势群体的需求。
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City and Environment Interactions
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