Pub Date : 2025-07-01DOI: 10.1016/j.cacint.2025.100222
Elnazir Ramadan , Suliman Abdalla , Ali Al Ahbabi , Tarig Gibreel , Naeema Al Hosani
In arid regions of the Global South, particularly the Gulf Cooperation Council (GCC) states, adopting agricultural technologies is vital for maximizing productivity and achieving sustainability. Despite their demonstrated benefits, adoption rates among small-scale farmers remain low due to water scarcity, environmental degradation, and socio-cultural and institutional barriers. This study explores the factors that influence farmers’ perceptions and decisions to adopt agricultural technologies, in small-scale urban farms in the pre-urban areas., providing valuable insights for enhancing adoption in these challenging environments. By utilizing the Unified Theory of Acceptance and Use of Technology (UTAUT) framework, along with diffusion of innovation, institutional and risk theories, data was gathered through a structured questionnaire and analyzed using ordinal logistic regression (OLR). The analysis identified key drivers of adoption, including performance expectancy, effort expectancy, social influence, facilitating conditions, trust in government and technology providers, and cultural norms. Perceived risk negatively influenced adoption, while compatibility was not statistically significant. The findings highlight the importance of creating supportive environments through transparent communication, infrastructure development, and tailored assistance. Recommendations focus on leveraging social networks, fostering trust, mitigating risks, and aligning technologies with cultural practices to scale up sustainable technology dissemination. This study offers valuable insights for policymakers and practitioners aiming to promote agricultural technology adoption in arid environments, contributing to sustainable development discourse in the Global South.
{"title":"Towards sustainable urban agriculture in the arid GCC states: Drivers of technology adoption among small-scale farmers","authors":"Elnazir Ramadan , Suliman Abdalla , Ali Al Ahbabi , Tarig Gibreel , Naeema Al Hosani","doi":"10.1016/j.cacint.2025.100222","DOIUrl":"10.1016/j.cacint.2025.100222","url":null,"abstract":"<div><div>In arid regions of the Global South, particularly the Gulf Cooperation Council (GCC) states, adopting agricultural technologies is vital for maximizing productivity and achieving sustainability. Despite their demonstrated benefits, adoption rates among small-scale farmers remain low due to water scarcity, environmental degradation, and socio-cultural and institutional barriers. This study explores the factors that influence farmers’ perceptions and decisions to adopt agricultural technologies, in small-scale urban farms in the pre-urban areas., providing valuable insights for enhancing adoption in these challenging environments. By utilizing the Unified Theory of Acceptance and Use of Technology (UTAUT) framework, along with diffusion of innovation, institutional and risk theories, data was gathered through a structured questionnaire and analyzed using ordinal logistic regression (OLR). The analysis identified key drivers of adoption, including performance expectancy, effort expectancy, social influence, facilitating conditions, trust in government and technology providers, and cultural norms. Perceived risk negatively influenced adoption, while compatibility was not statistically significant. The findings highlight the importance of creating supportive environments through transparent communication, infrastructure development, and tailored assistance. Recommendations focus on leveraging social networks, fostering trust, mitigating risks, and aligning technologies with cultural practices to scale up sustainable technology dissemination. This study offers valuable insights for policymakers and practitioners aiming to promote agricultural technology adoption in arid environments, contributing to sustainable development discourse in the Global South.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"28 ","pages":"Article 100222"},"PeriodicalIF":3.9,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144549749","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}
Pub Date : 2025-06-30DOI: 10.1016/j.cacint.2025.100221
Ahmed Marey , Jiwei Zou , Sherif Goubran , Liangzhu Leon Wang , Abhishek Gaur
Urban morphology, defined by the characteristics and spatial arrangement of urban structures, significantly affects urban microclimate in terms of thermal environments, wind dynamics, energy use, and outdoor air quality. Despite extensive research in this field, these effects are intensified by climate change and rapid urbanization, posing challenges to urban sustainability, such as poor air quality, increased energy demands, and pedestrian discomfort. While artificial intelligence (AI) and machine learning (ML) offer promising solutions for addressing these challenges, the field lacks standardized approaches for implementing these technologies. By leveraging urban morphology indicators such as sky view factor, building density, and green space ratio, AI models can analyze complex interactions across various spatiotemporal scales. However, significant variability in methodologies, indicators, and datasets limits the generalizability and applicability of these techniques. By synthesizing 111 studies over the last decade utilizing urban morphology and AI models to predict urban microclimate, this review aims to bridge these gaps and highlight AI’s unique potential to contribute to the field. Analyzed studies reported that key urban morphology indicators, particularly building density and height, explain up to 75% of land surface temperature variance across seasons, while sky view factor accounts for over 67% of heat exposure variations in urban environments, with these findings emerging from multiple independent investigations across diverse urban contexts. Random Forest emerges as the most widely adopted AI technique, demonstrating robust performance across different applications. Emerging trends, such as hybrid approaches combining AI with physics-based models, are highlighted as promising avenues for advancing the field. Our review identifies the need for standardized frameworks and datasets to enhance model applicability. The study presents actionable insights for climate-responsive urban planning and lays the groundwork for interdisciplinary studies, enabling the development of resilient, sustainable urban environments amid the growing challenges of urbanization and climate change.
{"title":"Urban morphology impacts on urban microclimate using artificial intelligence – a review","authors":"Ahmed Marey , Jiwei Zou , Sherif Goubran , Liangzhu Leon Wang , Abhishek Gaur","doi":"10.1016/j.cacint.2025.100221","DOIUrl":"10.1016/j.cacint.2025.100221","url":null,"abstract":"<div><div>Urban morphology, defined by the characteristics and spatial arrangement of urban structures, significantly affects urban microclimate in terms of thermal environments, wind dynamics, energy use, and outdoor air quality. Despite extensive research in this field, these effects are intensified by climate change and rapid urbanization, posing challenges to urban sustainability, such as poor air quality, increased energy demands, and pedestrian discomfort. While artificial intelligence (AI) and machine learning (ML) offer promising solutions for addressing these challenges, the field lacks standardized approaches for implementing these technologies. By leveraging urban morphology indicators such as sky view factor, building density, and green space ratio, AI models can analyze complex interactions across various spatiotemporal scales. However, significant variability in methodologies, indicators, and datasets limits the generalizability and applicability of these techniques. By synthesizing 111 studies over the last decade utilizing urban morphology and AI models to predict urban microclimate, this review aims to bridge these gaps and highlight AI’s unique potential to contribute to the field. Analyzed studies reported that key urban morphology indicators, particularly building density and height, explain up to 75% of land surface temperature variance across seasons, while sky view factor accounts for over 67% of heat exposure variations in urban environments, with these findings emerging from multiple independent investigations across diverse urban contexts. Random Forest emerges as the most widely adopted AI technique, demonstrating robust performance across different applications. Emerging trends, such as hybrid approaches combining AI with physics-based models, are highlighted as promising avenues for advancing the field. Our review identifies the need for standardized frameworks and datasets to enhance model applicability. The study presents actionable insights for climate-responsive urban planning and lays the groundwork for interdisciplinary studies, enabling the development of resilient, sustainable urban environments amid the growing challenges of urbanization and climate change.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"28 ","pages":"Article 100221"},"PeriodicalIF":3.9,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144549748","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}
Pub Date : 2025-06-24DOI: 10.1016/j.cacint.2025.100218
Mari Uemura, Orapin Laosee, Cheerawit Rattanapan, Piyapong Janmaimool
This study aims to evaluate the subjective well-being (SWB) of Japanese immigrant workers residing in Bangkok, Thailand, and to demonstrate how the SWB is affected by urban environments via health-related factors and social support by analyzing a causal relationship model of urban environmental factors affecting SWB. The study used a cross-sectional method based on questionnaire surveys of 389 Japanese residing in Bangkok, Thailand. The surveys were conducted during 15 July-15 August 2024. SWB was divided into two types: 1) cognitive well-being (CWB) measured by the Satisfaction with Life Scale (SWLS), and 2) affective well-being (AWB) measured by the Domain of Affective Well-Being (D-FAW). A measurement model was first tested to examine how much of each indicator’s variance could be explained by its construct and to test the correlation among constructs. The constructs in the model included 1) perceived quality of natural environments (QNE), 2) social neighborhood environmental perception (NEP), 3) access to green spaces (AGS), 4) perceived stress (PS), 5) sleep quality (SQ), 6) social support (SS), and 7) job satisfaction (JS). Subsequently, a partial least squares structural equation modeling (PLS-SEM) was applied to test the causal relationships among constructs to predict CWB and AWB. The results of PLS-SEM revealed that NEP directly and significantly affected AWB, and AGS directly and significantly affected CWB. QNE had indirect effects on CWB and AWB via JS. AGS indirectly affected both SWB via PHS and SS. NEP indirectly affected AWB via SQ and PS. The results point to urban environmental factors as important factors which could affect health-related factors and social factors, and finally constitute to the SWB of Japanese workers residing in Bangkok city, Thailand. Notably, immigrants may construct emotion comparisons regarding urban environments in their current place and in their home country, and these comparisons potentially affect SWB. The workers should be provided with supportive urban environments to improve SWB or trained on how to adjust their living to certain conditions of urban environments to avoid mental challenges.
{"title":"A causal relationship model of urban environmental factors affecting the subjective well-being of Japanese immigrant workers in Thailand","authors":"Mari Uemura, Orapin Laosee, Cheerawit Rattanapan, Piyapong Janmaimool","doi":"10.1016/j.cacint.2025.100218","DOIUrl":"10.1016/j.cacint.2025.100218","url":null,"abstract":"<div><div>This study aims to evaluate the subjective well-being (SWB) of Japanese immigrant workers residing in Bangkok, Thailand, and to demonstrate how the SWB is affected by urban environments via health-related factors and social support by analyzing a causal relationship model of urban environmental factors affecting SWB. The study used a cross-sectional method based on questionnaire surveys of 389 Japanese residing in Bangkok, Thailand. The surveys were conducted during 15 July-15 August 2024. SWB was divided into two types: 1) cognitive well-being (CWB) measured by the Satisfaction with Life Scale (SWLS), and 2) affective well-being (AWB) measured by the Domain of Affective Well-Being (D-FAW). A measurement model was first tested to examine how much of each indicator’s variance could be explained by its construct and to test the correlation among constructs. The constructs in the model included 1) perceived quality of natural environments (QNE), 2) social neighborhood environmental perception (NEP), 3) access to green spaces (AGS), 4) perceived stress (PS), 5) sleep quality (SQ), 6) social support (SS), and 7) job satisfaction (JS). Subsequently, a partial least squares structural equation modeling (PLS-SEM) was applied to test the causal relationships among constructs to predict CWB and AWB. The results of PLS-SEM revealed that NEP directly and significantly affected AWB, and AGS directly and significantly affected CWB. QNE had indirect effects on CWB and AWB via JS. AGS indirectly affected both SWB via PHS and SS. NEP indirectly affected AWB via SQ and PS. The results point to urban environmental factors as important factors which could affect health-related factors and social factors, and finally constitute to the SWB of Japanese workers residing in Bangkok city, Thailand. Notably, immigrants may construct emotion comparisons regarding urban environments in their current place and in their home country, and these comparisons potentially affect SWB. The workers should be provided with supportive urban environments to improve SWB or trained on how to adjust their living to certain conditions of urban environments to avoid mental challenges.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"28 ","pages":"Article 100218"},"PeriodicalIF":3.9,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144481775","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}
Tropical cities like Kuala Lumpur are increasingly vulnerable to urban heat due to rapid urbanization, resulting in greater thermal discomfort, higher energy consumption, and environmental degradation. This study is among the first to comprehensively evaluate the seasonal performance of advanced urban heat mitigation solutions across diverse urban forms in the Greater Kuala Lumpur. We assess city-scale thermal management through high-resolution numerical simulations using the weather research and forecasting (WRF) model coupled with the single-layer urban canopy model (SLUCM), analysing one baseline and five mitigation scenarios: (a) control (no intervention), (b) cool materials (roof albedo 0.80, ground albedo 0.40), (c) super cool materials (roof albedo 0.95), (d) 30 % non-irrigated vegetation, (e) 60 percent non-irrigated vegetation, and (f) a combination of super cool materials with 60 % vegetation. Both monsoon and non-monsoon periods were considered to capture seasonal variability in performance. At 14:00 LT, super cool materials achieved the greatest ambient temperature reductions with 1.8 °C during the monsoon and 2.2 °C during the non-monsoon. Cool materials followed with reductions of 1.5 °C and 1.7 °C. Vegetation at 30 % reduced ambient temperatures by 0.8 to 0.9 °C, while 60 % vegetation achieved 1.2 to 1.5 °C reductions. The combined strategy delivered the highest reductions of 3.1 °C in the monsoon and 3.8 °C in the non-monsoon period. Surface temperature reductions were also most pronounced under the combined strategy, reaching 9.6 °C and 9.8 °C respectively. Individually, super cool materials reduced surface temperatures by up to 6.3 °C, cool materials by up to 5.9 °C, and 60 % vegetation by up to 3.4 °C across both seasons. The effectiveness of each strategy varied seasonally, with super cool and high-albedo surfaces performing best during the dry, high-radiation non-monsoon period, while vegetation offered more consistent cooling during the humid, cloud-covered monsoon season. These contrasts highlight the need for climate-sensitive, integrated mitigation approaches. To assess real-world applicability, these strategies were evaluated across representative local climate zones (LCZs) in Greater Kuala Lumpur. In compact high-rise and mid-rise building areas, it resulted in ambient temperature reductions of up to 4.2 °C, surface temperature drops of 11.0 °C, and universal thermal climate index (UTCI) reductions of 3.5 °C, significantly enhancing outdoor thermal comfort in dense urban areas. This study demonstrates that integrated strategies combining reflective materials with substantial vegetation coverage outperform isolated interventions. The findings provide scalable, context-specific, and seasonally adaptive guidance to support urban planning, climate-sensitive policy, and sustainable urban design in tropical cities, helping to improve long-term livability and resilience against urban heat.
{"title":"Optimizing seasonal performance of advanced heat mitigation solutions for city-scale thermal management in Greater Kuala Lumpur","authors":"Norishahaini Mohamed Ishak , Ansar Khan , Jamalunlaili Abdullah , Siti Aekbal Salleh , Mattheos Santamouris","doi":"10.1016/j.cacint.2025.100219","DOIUrl":"10.1016/j.cacint.2025.100219","url":null,"abstract":"<div><div>Tropical cities like Kuala Lumpur are increasingly vulnerable to urban heat due to rapid urbanization, resulting in greater thermal discomfort, higher energy consumption, and environmental degradation. This study is among the first to comprehensively evaluate the seasonal performance of advanced urban heat mitigation solutions across diverse urban forms in the Greater Kuala Lumpur. We assess city-scale thermal management through high-resolution numerical simulations using the weather research and forecasting (WRF) model coupled with the single-layer urban canopy model (SLUCM), analysing one baseline and five mitigation scenarios: (a) control (no intervention), (b) cool materials (roof albedo 0.80, ground albedo 0.40), (c) super cool materials (roof albedo 0.95), (d) 30 % non-irrigated vegetation, (e) 60 percent non-irrigated vegetation, and (f) a combination of super cool materials with 60 % vegetation. Both monsoon and non-monsoon periods were considered to capture seasonal variability in performance. At 14:00 LT, super cool materials achieved the greatest ambient temperature reductions with 1.8 °C during the monsoon and 2.2 °C during the non-monsoon. Cool materials followed with reductions of 1.5 °C and 1.7 °C. Vegetation at 30 % reduced ambient temperatures by 0.8 to 0.9 °C, while 60 % vegetation achieved 1.2 to 1.5 °C reductions. The combined strategy delivered the highest reductions of 3.1 °C in the monsoon and 3.8 °C in the non-monsoon period. Surface temperature reductions were also most pronounced under the combined strategy, reaching 9.6 °C and 9.8 °C respectively. Individually, super cool materials reduced surface temperatures by up to 6.3 °C, cool materials by up to 5.9 °C, and 60 % vegetation by up to 3.4 °C across both seasons. The effectiveness of each strategy varied seasonally, with super cool and high-albedo surfaces performing best during the dry, high-radiation non-monsoon period, while vegetation offered more consistent cooling during the humid, cloud-covered monsoon season. These contrasts highlight the need for climate-sensitive, integrated mitigation approaches. To assess real-world applicability, these strategies were evaluated across representative local climate zones (LCZs) in Greater Kuala Lumpur. In compact high-rise and mid-rise building areas, it resulted in ambient temperature reductions of up to 4.2 °C, surface temperature drops of 11.0 °C, and universal thermal climate index (UTCI) reductions of 3.5 °C, significantly enhancing outdoor thermal comfort in dense urban areas. This study demonstrates that integrated strategies combining reflective materials with substantial vegetation coverage outperform isolated interventions. The findings provide scalable, context-specific, and seasonally adaptive guidance to support urban planning, climate-sensitive policy, and sustainable urban design in tropical cities, helping to improve long-term livability and resilience against urban heat.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"28 ","pages":"Article 100219"},"PeriodicalIF":3.9,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144571471","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}
Pub Date : 2025-06-16DOI: 10.1016/j.cacint.2025.100217
Tikabo Gebreyesus , Christian Borgemeister , Cristina Herrero- Jáuregui
Urban centers in sub-Saharan Africa face climate vulnerabilities due to rapid urbanization and outdated development strategies that prioritize grey infrastructure over natural elements. In Ethiopia, urban green spaces remain underutilized despite their potential to enhance climate resilience. This study aims to explore the climate mitigation potential of green spaces in Hawassa, Ethiopia, by assessing carbon storage in trees using allometric equations within a customized i-Tree Eco model, complemented by soil and litter carbon analysis for selected parks. We collected data from stratified random sample plots across land uses, along with climate and location information to parameterize the model. Urban trees, soil, and litter carbon pools together stored 78,199 tC, mitigating 286,990.30 tCO2e, with carbon sequestration offsetting 4.9 % of the city’s annual emissions. The highest carbon stock was observed in soil (189.8 ± 8.5 tC ha−1), while litter carbon was the least (1.08 ± 0.12 tC ha−1). Hawassa’s tree carbon density (12.01 tC ha−1) was lower than other Ethiopian cities, influenced by urbanization and methodological variations. In Hawassa, land uses with minimal impervious and greater green space exhibited the highest carbon storage. Carbon sink positively correlated with tree metrics, while urbanization had a negative effect. Spatial mappings revealed an uneven distribution of carbon stocks, with impervious areas dominating low-carbon storage regions. These findings highlight the role of green spaces in climate mitigation and the need to integrate them into spatial planning and carbon policies. Ethiopian cities must balance grey and natural elements to enhance climate resilience and achieve emissions self-sufficiency.
撒哈拉以南非洲的城市中心由于快速城市化和过时的发展战略而面临气候脆弱性，这些战略优先考虑灰色基础设施而不是自然要素。在埃塞俄比亚，尽管城市绿地具有增强气候适应能力的潜力，但仍未得到充分利用。本研究旨在通过在定制的i-Tree生态模型中使用异速生长方程评估树木的碳储量，并对选定的公园进行土壤和凋落物碳分析，探索埃塞俄比亚哈瓦萨绿地的气候缓解潜力。我们从不同土地用途的分层随机样地收集数据，以及气候和位置信息来参数化模型。城市树木、土壤和凋落物碳库共储存了78,199碳当量，减少了286,990.30亿吨二氧化碳当量，碳固存抵消了该市年排放量的4.9%。土壤碳储量最高（189.8±8.5 tC ha - 1），凋落物碳储量最低（1.08±0.12 tC ha - 1）。受城市化和方法差异的影响，哈瓦萨的树木碳密度（12.01 tC ha - 1）低于埃塞俄比亚其他城市。在哈瓦萨，不透水面积最小、绿地面积较大的土地利用表现出最高的碳储量。碳汇与树木指标正相关，城市化对树木指标负相关。碳储量空间分布不均，以不透水区域为主。这些发现突出了绿色空间在减缓气候变化方面的作用，以及将其纳入空间规划和碳政策的必要性。埃塞俄比亚的城市必须平衡灰色和自然因素，以增强气候适应能力，实现排放自给自足。
{"title":"Exploring the role of urban nature in mitigating the climate footprint of urbanization in Ethiopia","authors":"Tikabo Gebreyesus , Christian Borgemeister , Cristina Herrero- Jáuregui","doi":"10.1016/j.cacint.2025.100217","DOIUrl":"10.1016/j.cacint.2025.100217","url":null,"abstract":"<div><div>Urban centers in sub-Saharan Africa face climate vulnerabilities due to rapid urbanization and outdated development strategies that prioritize grey infrastructure over natural elements. In Ethiopia, urban green spaces remain underutilized despite their potential to enhance climate resilience. This study aims to explore the climate mitigation potential of green spaces in Hawassa, Ethiopia, by assessing carbon storage in trees using allometric equations within a customized i-Tree Eco model, complemented by soil and litter carbon analysis for selected parks. We collected data from stratified random sample plots across land uses, along with climate and location information to parameterize the model. Urban trees, soil, and litter carbon pools together stored 78,199 tC, mitigating 286,990.30 tCO<sub>2</sub>e, with carbon sequestration offsetting 4.9 % of the city’s annual emissions. The highest carbon stock was observed in soil (189.8 ± 8.5 tC ha<sup>−</sup>1), while litter carbon was the least (1.08 ± 0.12 tC ha<sup>−</sup>1). Hawassa’s tree carbon density (12.01 tC ha<sup>−</sup>1) was lower than other Ethiopian cities, influenced by urbanization and methodological variations. In Hawassa, land uses with minimal impervious and greater green space exhibited the highest carbon storage. Carbon sink positively correlated with tree metrics, while urbanization had a negative effect. Spatial mappings revealed an uneven distribution of carbon stocks, with impervious areas dominating low-carbon storage regions. These findings highlight the role of green spaces in climate mitigation and the need to integrate them into spatial planning and carbon policies. Ethiopian cities must balance grey and natural elements to enhance climate resilience and achieve emissions self-sufficiency.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"27 ","pages":"Article 100217"},"PeriodicalIF":3.9,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144297693","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}
Pub Date : 2025-06-11DOI: 10.1016/j.cacint.2025.100216
Ermias Debie
Rapid urbanization and environmental degradation in Bahir Dar City underscore the urgent need for integrated urban solutions; however, comprehensive studies on the combined effects of urban agriculture (UA) and green infrastructure (GI) practices—critical for sustainable urban development—remain limited. This study investigates UA-GI integration through surveys and interviews with 99 stakeholders, complemented by participatory observations. The key barriers to integration—based on multiple-response data—include a lack of supportive policies and regulatory frameworks (87%), limited awareness (57%), and space constraints (51%). The multicriteria decision analysis ranked integrated practices as the most effective strategy (score: 16.81), followed by edible tree planting at garden centers (16.18), small gardens (13.83), and fence edge greening (11.46). These practices demonstrate strong synergies across environmental, social, and economic dimensions, making them top priorities for promoting urban sustainability. Structural equation modeling shows that thermal regulation and access to fresh food are critical factors for planning sustainable urban systems. Scaling up the integration of edible trees with vertical farming in residential gardens supported by policy and community engagement is essential to enhance food security, biodiversity, aesthetics, and microclimate regulation. The study underscores integrating nature-based solutions into city planning and provides a replicable framework for other rapidly urbanizing contexts in the Global South.
{"title":"Synergistic integration of urban agriculture and green infrastructure to enhance urban sustainability in Bahir Dar, Ethiopia","authors":"Ermias Debie","doi":"10.1016/j.cacint.2025.100216","DOIUrl":"10.1016/j.cacint.2025.100216","url":null,"abstract":"<div><div>Rapid urbanization and environmental degradation in Bahir Dar City underscore the urgent need for integrated urban solutions; however, comprehensive studies on the combined effects of urban agriculture (UA) and green infrastructure (GI) practices—critical for sustainable urban development—remain limited. This study investigates UA-GI integration through surveys and interviews with 99 stakeholders, complemented by participatory observations. The key barriers to integration—based on multiple-response data—include a lack of supportive policies and regulatory frameworks (87%), limited awareness (57%), and space constraints (51%). The multicriteria decision analysis ranked integrated practices as the most effective strategy (score: 16.81), followed by edible tree planting at garden centers (16.18), small gardens (13.83), and fence edge greening (11.46). These practices demonstrate strong synergies across environmental, social, and economic dimensions, making them top priorities for promoting urban sustainability. Structural equation modeling shows that thermal regulation and access to fresh food are critical factors for planning sustainable urban systems. Scaling up the integration of edible trees with vertical farming in residential gardens supported by policy and community engagement is essential to enhance food security, biodiversity, aesthetics, and microclimate regulation. The study underscores integrating nature-based solutions into city planning and provides a replicable framework for other rapidly urbanizing contexts in the Global South.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"27 ","pages":"Article 100216"},"PeriodicalIF":3.9,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144279916","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}
Pub Date : 2025-06-08DOI: 10.1016/j.cacint.2025.100215
Simona Mannucci, Adriana Ciardiello, Marco Ferrero, Federica Rosso
Urban areas face increasing exposure to climate-induced hazards, including extreme heat and urban flooding, challenges exacerbated by limited green and blue areas. This study presents an integrated parametric workflow for the preliminary evaluation of multi-domain performance of small outdoor spaces, at early design stages, as adaptive interventions for mitigating these issues at the neighborhood scale. Using parametric modelling in Grasshopper with Ladybug Tools and Kangaroo plugins, the novel methodology assesses thermal comfort and surface runoff dynamics in a heat- and flood-prone outdoor space. Thermal stress was evaluated using Ladybug tools via the Universal Thermal Climate Index and the Mediterranean Outdoor Comfort Index, and compared with ENVI-met simulations results to test the reliability of the proposed workflow. Results highlighted significant thermal discomfort during peak summer hours, especially in unshaded areas. Irrigated vegetation, including trees and grass, effectively reduced heat stress, even if in some regions, due to water scarcity, irrigation entails trade-offs. Surface runoff analyses, combining qualitative and quantitative computations, revealed green spaces’ potential to mitigate water accumulation while exposing design inefficiencies, such as impermeable borders restricting infiltration. The findings underscore the critical role of small outdoor urban spaces in enhancing urban resilience. Key design strategies include increasing permeability to reduce runoff, maintaining greenery with irrigation, and integrating shaded elements to improve thermal comfort. The proposed workflow allows rapid scenario-based testing of design solutions during early planning stages, offering practitioners a preliminary tool for adaptive urban design. By addressing hydrological and thermal challenges within a unified workflow, the study highlights the co-benefits of small-scale green infrastructure, advancing climate adaptation and resilience in compact urban settings while promoting equitable and sustainable cities.
{"title":"A parametric integrated workflow to assess multi-domain heat- and flood-related performance of small outdoor urban spaces in a changing climate: A case study in the mediterranean region","authors":"Simona Mannucci, Adriana Ciardiello, Marco Ferrero, Federica Rosso","doi":"10.1016/j.cacint.2025.100215","DOIUrl":"10.1016/j.cacint.2025.100215","url":null,"abstract":"<div><div>Urban areas face increasing exposure to climate-induced hazards, including extreme heat and urban flooding, challenges exacerbated by limited green and blue areas. This study presents an integrated parametric workflow for the preliminary evaluation of multi-domain performance of small outdoor spaces, at early design stages, as adaptive interventions for mitigating these issues at the neighborhood scale. Using parametric modelling in Grasshopper with Ladybug Tools and Kangaroo plugins, the novel methodology assesses thermal comfort and surface runoff dynamics in a heat- and flood-prone outdoor space. Thermal stress was evaluated using Ladybug tools via the Universal Thermal Climate Index and the Mediterranean Outdoor Comfort Index, and compared with ENVI-met simulations results to test the reliability of the proposed workflow. Results highlighted significant thermal discomfort during peak summer hours, especially in unshaded areas. Irrigated vegetation, including trees and grass, effectively reduced heat stress, even if in some regions, due to water scarcity, irrigation entails trade-offs. Surface runoff analyses, combining qualitative and quantitative computations, revealed green spaces’ potential to mitigate water accumulation while exposing design inefficiencies, such as impermeable borders restricting infiltration. The findings underscore the critical role of small outdoor urban spaces in enhancing urban resilience. Key design strategies include increasing permeability to reduce runoff, maintaining greenery with irrigation, and integrating shaded elements to improve thermal comfort. The proposed workflow allows rapid scenario-based testing of design solutions during early planning stages, offering practitioners a preliminary tool for adaptive urban design. By addressing hydrological and thermal challenges within a unified workflow, the study highlights the co-benefits of small-scale green infrastructure, advancing climate adaptation and resilience in compact urban settings while promoting equitable and sustainable cities.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"27 ","pages":"Article 100215"},"PeriodicalIF":3.9,"publicationDate":"2025-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144271405","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}
Pub Date : 2025-06-06DOI: 10.1016/j.cacint.2025.100210
Daniel Jato-Espino , Fabio Capra-Ribero , Vanessa Moscardó , Laura O. Gallardo
Green spaces (GS) are vital for environmental sustainability and public well-being. Understanding public perceptions of GS can promote their distribution aligned with citizens’ preferences. This study explores the alignment between perceptions of GS use, management and availability, captured via a questionnaire in the Valencian Community (Spain), with the objective reality determined through Geographic Information Systems (GIS). Data were collected from 94 participants, with 72 % using GS for relaxation, 54 % for physical exercise and 51 % for walking. Most respondents (78 %) preferred natural reserves as their primary type of GS. While 38 % believed GS were equitably distributed, 41 % disagreed, indicating divided opinions on GS management. Despite 72 % of participants feeling GS availability had remained the same over the past five years, 86 % expressed a desire for more GS. Most respondents accessed GS on foot (65 %), with travel times evenly split between under 5 and 15 min. However, GIS analysis revealed discrepancies between perceived and actual GS proximity, highlighting a mismatch between perception and reality. The responses collected were influenced by contextual factors, with variables such as gender and income level leading to statistically significant differences in perspectives regarding use, visiting habits and availability of GS. These differences, along with the integration of subjective survey data with GIS analysis, underscore the need to incorporate community feedback into urban planning processes to identify specific areas where perceptions diverge from actual GS distribution. The findings suggest that understanding these perceptions can guide policymakers in prioritizing underserved areas, improving GS management and ensuring equitable access.
{"title":"Citizen perceptions on the use, management and availability of green spaces in a Mediterranean region","authors":"Daniel Jato-Espino , Fabio Capra-Ribero , Vanessa Moscardó , Laura O. Gallardo","doi":"10.1016/j.cacint.2025.100210","DOIUrl":"10.1016/j.cacint.2025.100210","url":null,"abstract":"<div><div>Green spaces (GS) are vital for environmental sustainability and public well-being. Understanding public perceptions of GS can promote their distribution aligned with citizens’ preferences. This study explores the alignment between perceptions of GS use, management and availability, captured via a questionnaire in the Valencian Community (Spain), with the objective reality determined through Geographic Information Systems (GIS). Data were collected from 94 participants, with 72 % using GS for relaxation, 54 % for physical exercise and 51 % for walking. Most respondents (78 %) preferred natural reserves as their primary type of GS. While 38 % believed GS were equitably distributed, 41 % disagreed, indicating divided opinions on GS management. Despite 72 % of participants feeling GS availability had remained the same over the past five years, 86 % expressed a desire for more GS. Most respondents accessed GS on foot (65 %), with travel times evenly split between under 5 and 15 min. However, GIS analysis revealed discrepancies between perceived and actual GS proximity, highlighting a mismatch between perception and reality. The responses collected were influenced by contextual factors, with variables such as gender and income level leading to statistically significant differences in perspectives regarding use, visiting habits and availability of GS. These differences, along with the integration of subjective survey data with GIS analysis, underscore the need to incorporate community feedback into urban planning processes to identify specific areas where perceptions diverge from actual GS distribution. The findings suggest that understanding these perceptions can guide policymakers in prioritizing underserved areas, improving GS management and ensuring equitable access.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"27 ","pages":"Article 100210"},"PeriodicalIF":3.9,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144242692","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}
Pub Date : 2025-06-01DOI: 10.1016/j.cacint.2025.100214
Jawoon Gu , Dongwoo Kim , Chulmin Jun , Seungwoo Son
Climate change and urbanization have intensified the urban heat island (UHI) effect, significantly impacting urban living environments. While existing studies have yielded valuable insights into macro-scale thermal environments, this study shifts the focus toward microscale residential contexts, where localized urban form and land use patterns critically shape thermal conditions.
In this study, we analyzed the temporal variations in LST in a residential neighborhood of Okgye-dong, Jung-gu, Daejeon, South Korea. High-resolution thermal imagery captured by unmanned aerial vehicles (UAVs) and interpretable machine learning (ML) techniques were used to model and analyze thermal patterns at the microscale. The study site, adjacent to a river and designated as an Urban Regeneration Area, is particularly vulnerable to summer heat.
Exploratory data analysis (EDA) was conducted to examine statistical characteristics and spatial patterns, followed by confirmatory data analysis (CDA) using nonlinear regression models such as CatBoost, Random Forest, and XGBoost. The results showed that the importance of variables influencing LST varied by time of day. However, meteorological variables such as solar radiation, wind, and humidity were not included due to data limitations.
Among the key findings, alley width, shadow ratio, and distance from the river emerged as dominant variables affecting thermal conditions in residential areas. This study contributes to identifying time-sensitive drivers of urban thermal vulnerability by leveraging UAV-based imagery and ML. Based on these findings, we propose specific policy-oriented strategies for heat mitigation in urban regeneration areas, including improving airflow in narrow alleys by removing obstructions or illegal parking, expanding riverside green spaces to enhance cooling effects, and installing vertical shading elements to reduce localized heat stress and improve thermal comfort.
These results are particularly valuable for urban regeneration projects, where thermal vulnerability is often intensified by high building density and limited green infrastructure. The proposed strategies—such as optimizing alley width, increasing shade coverage, and enhancing riverside green spaces—can be effectively incorporated into localized urban redevelopment plans to improve thermal comfort and resilience.
{"title":"Quantitative assessment of factors that influence heat vulnerability in residential areas using machine learning and unmanned aerial vehicle","authors":"Jawoon Gu , Dongwoo Kim , Chulmin Jun , Seungwoo Son","doi":"10.1016/j.cacint.2025.100214","DOIUrl":"10.1016/j.cacint.2025.100214","url":null,"abstract":"<div><div>Climate change and urbanization have intensified the urban heat island (UHI) effect, significantly impacting urban living environments. While existing studies have yielded valuable insights into macro-scale thermal environments, this study shifts the focus toward microscale residential contexts, where localized urban form and land use patterns critically shape thermal conditions.</div><div>In this study, we analyzed the temporal variations in LST in a residential neighborhood of Okgye-dong, Jung-gu, Daejeon, South Korea. High-resolution thermal imagery captured by unmanned aerial vehicles (UAVs) and interpretable machine learning (ML) techniques were used to model and analyze thermal patterns at the microscale. The study site, adjacent to a river and designated as an Urban Regeneration Area, is particularly vulnerable to summer heat.</div><div>Exploratory data analysis (EDA) was conducted to examine statistical characteristics and spatial patterns, followed by confirmatory data analysis (CDA) using nonlinear regression models such as CatBoost, Random Forest, and XGBoost. The results showed that the importance of variables influencing LST varied by time of day. However, meteorological variables such as solar radiation, wind, and humidity were not included due to data limitations.</div><div>Among the key findings, alley width, shadow ratio, and distance from the river emerged as dominant variables affecting thermal conditions in residential areas. This study contributes to identifying time-sensitive drivers of urban thermal vulnerability by leveraging UAV-based imagery and ML. Based on these findings, we propose specific policy-oriented strategies for heat mitigation in urban regeneration areas, including improving airflow in narrow alleys by removing obstructions or illegal parking, expanding riverside green spaces to enhance cooling effects, and installing vertical shading elements to reduce localized heat stress and improve thermal comfort.</div><div>These results are particularly valuable for urban regeneration projects, where thermal vulnerability is often intensified by high building density and limited green infrastructure. The proposed strategies—such as optimizing alley width, increasing shade coverage, and enhancing riverside green spaces—can be effectively incorporated into localized urban redevelopment plans to improve thermal comfort and resilience.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"27 ","pages":"Article 100214"},"PeriodicalIF":3.9,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144242691","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}
Pub Date : 2025-05-31DOI: 10.1016/j.cacint.2025.100211
Silvia G. Tavares , Majed Abuseif , Karine Dupré
Urban Heat Islands (UHI) pose significant challenges to cities, particularly in tropical climates. This study evaluates various UHI mitigation strategies applied to the Central Business District (CBD) of Townsville using ENVI-met v5.5.1. Air temperature (Ta), relative humidity (RH), wind characteristics, Mean Radiant Temperature (MRT), and Universal Thermal Climate Index (UTCI) were assessed under various scenarios. Strategies investigated include increasing natural and artificial shading, altering pavement albedos, and adding green buildings. Results show that on average, Ta in the proposed scenarios were lower than the input data (up to 3.5 °C) except at 1 pm and 4 pm, due to the differences in the urban morphology between the two dataset locations. Adding buildings generated the worst results and negatively impacted night cooling. The other scenarios positively impacted Ta reduction on average (0 °C to 0.21 °C per hour). The built environment significantly altered wind patterns, and added buildings contributed to increased wind speed (up to 1 m/s during the hottest hours). The median MRT increased during the early hours surpassing the health stress threshold (57.1 °C) at 9am, condition which remained until 2 pm, decreasing afterwards. But importantly, an overestimation of MRT was observed due to the topographical characteristics of the site. This study reveals a misconception that the hottest hours are the most harmful to human well-being, as they may vary based on the local climate patterns. Results also demonstrate that while some strategies contribute to temperature reduction, challenges persist, especially during the hottest hours. This work advances UHI mitigation for tropical savanna climates, guiding sustainable urban planning.
{"title":"Urban Heat Mitigation in a Tropical Climate: A Computer Simulation-Based Study in Townsville, Australia","authors":"Silvia G. Tavares , Majed Abuseif , Karine Dupré","doi":"10.1016/j.cacint.2025.100211","DOIUrl":"10.1016/j.cacint.2025.100211","url":null,"abstract":"<div><div>Urban Heat Islands (UHI) pose significant challenges to cities, particularly in tropical climates. This study evaluates various UHI mitigation strategies applied to the Central Business District (CBD) of Townsville using ENVI-met v5.5.1. Air temperature (Ta), relative humidity (RH), wind characteristics, Mean Radiant Temperature (MRT), and Universal Thermal Climate Index (UTCI) were assessed under various scenarios. Strategies investigated include increasing natural and artificial shading, altering pavement albedos, and adding green buildings. Results show that on average, Ta in the proposed scenarios were lower than the input data (up to 3.5 °C) except at 1 pm and 4 pm, due to the differences in the urban morphology between the two dataset locations. Adding buildings generated the worst results and negatively impacted night cooling. The other scenarios positively impacted Ta reduction on average (0 °C to 0.21 °C per hour). The built environment significantly altered wind patterns, and added buildings contributed to increased wind speed (up to 1 m/s during the hottest hours). The median MRT increased during the early hours surpassing the health stress threshold (57.1 °C) at 9am, condition which remained until 2 pm, decreasing afterwards. But importantly, an overestimation of MRT was observed due to the topographical characteristics of the site. This study reveals a misconception that the hottest hours are the most harmful to human well-being, as they may vary based on the local climate patterns. Results also demonstrate that while some strategies contribute to temperature reduction, challenges persist, especially during the hottest hours. This work advances UHI mitigation for tropical savanna climates, guiding sustainable urban planning.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"27 ","pages":"Article 100211"},"PeriodicalIF":3.9,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144242698","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}
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