City and Environment Interactions最新文献

{"title":"Advancing groundwater quality assessment in Siliguri City of India through the RMS-WQI model incorporating the data-driven approaches","authors":"Samsad Parween ,&nbsp;Agnieszka I. Olbert ,&nbsp;Apoorva Bamal ,&nbsp;Abdul Majed Sajib ,&nbsp;Mir Talas Mahammad Diganta ,&nbsp;Md Abu Hasan ,&nbsp;Yunus Ahmed ,&nbsp;Md Moniruzzaman ,&nbsp;Azizur Rahman ,&nbsp;Md Galal Uddin","doi":"10.1016/j.cacint.2025.100270","DOIUrl":"10.1016/j.cacint.2025.100270","url":null,"abstract":"<div><div>As a vital renewable resource, groundwater is significant and safeguarded source of drinking water for city population. Therefore, continuous assessment of the groundwater quality (GWQ) is required to maintain the good status of the GWQ. The current research focused on assessing the GWQ of Siliguri City, eastern India, utilizing the root mean squared water quality index (RMS-WQI) model. Furthermore, the research incorporated the eXtreme Gradient Boosting (XGB) algorithm with Optuna (OPT) (XGB-OPT) hyperparameter optimization technique to enhance the accuracy of predictions and reduce potential errors within the RMS-WQI model. The computed WQI scores ranged from 66.4 to 94.0, with most sampling locations falling within the ‘Good’ to ‘Fair’ classification. Moreover, the XGB-OPT model showed high accuracy in both the training and testing period (Training RMSE = 3.27, Testing RMSE = 1.50; Training MSE = 9.74, Testing MSE = 2.25; Training MAE = 3.01, Testing MAE = 0.69; and Training PABE = 3.41 and Testing PABE = 0.79) in terms of WQI score prediction. Additionally, the developed model showed high sensitivity (R² = 0.94) and low uncertainty (&lt; 1 %) in terms of WQI score prediction with the least prediction error at each sampling sites (PREI = 0.096; NSE = 0.816; MEF = 0.815). These results collectively demonstrated the robustness and reliability of the RMS-WQI model in assessing the GWQ. The findings highlighted the effectiveness of the RMS-WQI model in the GWQ assessment. The research outcome presents critical insights for the stakeholders, including policymakers, environmental regulators, and scientific researchers, facilitating more informed and strategic decision-making for sustainable groundwater management. By demonstrating the reliability and precision of the RMS-WQI model, this research contributed to improve the existing GWQ monitoring approach, which could ultimately support long-term water security scheme and provide safeguard to public health in Siliguri City.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"29 ","pages":"Article 100270"},"PeriodicalIF":3.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145658601","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}

{"title":"How weather variability, seasonality, and temporal scale interact to shape urban heat island intensity in Madison, Wisconsin","authors":"Elizabeth Berg ,&nbsp;Christopher Kucharik","doi":"10.1016/j.cacint.2026.100321","DOIUrl":"10.1016/j.cacint.2026.100321","url":null,"abstract":"<div><div>Due to differences in energy balance, urban areas typically experience greater temperatures than surrounding rural areas, a phenomenon known as the urban heat island (UHI) effect. This urban–rural temperature difference can vary greatly, and the magnitude of the UHI depends on the time of day, season, and weather conditions. This study used 12 years of observational records from an extensive sensor network in Madison, Wisconsin, to explore patterns in short- and long-term variability of the local UHI, as well as the meteorological drivers of this variability. We identified a statistically significant year-round inverse correlation between wind speed and UHI magnitude. For other meteorological variables, correlation with the UHI varied seasonally, with the strongest dependence on temperature occurring during the winter and the strongest dependence on precipitation occurring during summer and fall. We also observed a greater frequency of inverted heat islands – days when urban temperatures dropped below rural temperatures – than previously documented in Madison or climatically similar cities. Additionally, we identified marked differences between spring and fall conditions that point to the role of prior seasons in shaping the UHI. Overall, the trends documented here have the potential to inform the development and evaluation of heat mitigation efforts in the Madison area. More broadly, the degree of variability observed in this study relative to prior analyses highlights the benefits that long-term, year-round monitoring can provide to urban climate planning throughout the world.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"29 ","pages":"Article 100321"},"PeriodicalIF":3.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147395953","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}

{"title":"Improving Blue-Green Transversal Connectivity in Cities: A Case Study of Munich and the Isar River","authors":"Pia Schmitzer ,&nbsp;Artan Hysa ,&nbsp;Carla Sofia Santos Ferreira ,&nbsp;Juergen Geist","doi":"10.1016/j.cacint.2026.100311","DOIUrl":"10.1016/j.cacint.2026.100311","url":null,"abstract":"<div><div>Urbanization and the associated transport infrastructure, particularly roads, reduce connectivity between vegetated areas (green) and surface water systems (blue), fragmenting blue-green landscapes and limiting ecosystem functions and services. Enhancing blue-green infrastructure (BGI) connectivity is therefore essential for strengthening urban resilience to climate change impacts. Focusing on the city of Munich in Bavaria, Germany, and its Isar River, this study explores strategies to strengthen the transversal connection of the river to surrounding urban green spaces, aiming to establish a more integrated and expansive blue-green network, supported by different landscape planning strategies. This study uses the Transversal Connectivity Index (TCI) as a methodological approach to improve BGI connectivity in the transversal (extended lateral) dimension. Using open-source geospatial data (e.g., Urban Atlas, Tree Cover Density, Street Trees), we generate connectivity scenarios that highlight potential core areas for connectivity. The results reveal that up to 74 existing green urban areas are potentially connectable to BGI adjacent to the Isar River. Of these, 26 are small patches under 0.8 ha, which can perform as stepping stones and play a crucial role in facilitating connectivity. The methodological approach used demonstrates the possibilities of exploring BGI expansions and transversal connectivity for positively influencing ecosystem services in urban settings, such as biodiversity conservation, climate regulation and improved human well-being. Its application to other metropolitan areas may provide a basis for supporting urban BGI planning and management for sustaining and improving ecosystem services and benefits to human societies.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"29 ","pages":"Article 100311"},"PeriodicalIF":3.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147395957","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}

{"title":"Mass rapid transit systems and sustainable urban development: a review of impacts and implications","authors":"Vinod Kumar ,&nbsp;Bijay Kumar Das ,&nbsp;Adheesh Kumar Vivek","doi":"10.1016/j.cacint.2026.100318","DOIUrl":"10.1016/j.cacint.2026.100318","url":null,"abstract":"<div><div>The rapid expansion of mass rapid transit systems (MRTS) has profoundly transformed urban morphology, functionality, and sustainability across the globe. As cities face mounting challenges related to rapid urbanization, congestion, and environmental degradation, MRTS have emerged as essential infrastructures fostering economic vitality, social inclusion, and ecological balance. This review paper critically examines the multidimensional relationships between metro systems and sustainable urban development, emphasizing their economic, social, environmental, and spatial impacts. It explores how MRT networks enhance employment accessibility, stimulate local economies, increase property values, and support compact, transit-oriented urban growth. Additionally, metro systems play a vital role in advancing environmental sustainability by reducing greenhouse gas emissions, promoting shifts toward public transport, lowering automobile dependency, and improving urban air quality.</div><div>Methodologically, the study employs a systematic literature review integrated with bibliometric analysis using VOSviewer software to map the intellectual landscape, identify influential authors and journals, and visualize thematic and citation networks within the global research domain. The bibliometric analysis provides quantitative insights into the evolution of MRT-related research, while the qualitative synthesis of empirical and case-based studies contextualizes regional variations and planning implications.</div><div>MRTS drive sustainable urban transformation by enhancing mobility, land-use efficiency, and compact city planning. However, benefits vary across contexts, requiring adaptive and inclusive planning. The study advances perspectives for policymakers, planners, and researchers, highlighting the need to align MRT investments with social equity, environmental stewardship, and economic resilience goals.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"29 ","pages":"Article 100318"},"PeriodicalIF":3.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147395876","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}

{"title":"A computational framework for analyzing urban data usage patterns in African cities: a 25-year data-driven review using natural language processing and machine learning","authors":"Rida Azmi ,&nbsp;Jérôme Chenal ,&nbsp;El Bachir Diop ,&nbsp;Seyid Abdellahi Ebnou Abdem ,&nbsp;Mariem Bounabi ,&nbsp;Mohammed Hlal ,&nbsp;Meriem Adraoui ,&nbsp;Tarik Chafiq","doi":"10.1016/j.cacint.2026.100296","DOIUrl":"10.1016/j.cacint.2026.100296","url":null,"abstract":"<div><div>This study provides a scoping review of urban data usage in African cities over the past 25 years, leveraging advanced Natural Language Processing − NLP, Machine Learning − ML, and hybrid approaches to classify urban data. The fine-tuned classification framework demonstrated robust performance, achieving an accuracy of 91.76 % in classifying relevant abstracts, with calibrated confidence scores ensuring reliable and evidence-aligned predictions. Topic modeling analysis is used combined with a personalized dictionary to extract five urban data typologies: Spatial, Digital, Commercial, Public Sector, and Sensor Data. These typologies are mapped to 15 urban contexts, revealing significant regional disparities that offer deeper insights into local practices, successes, and deficiencies. The model’s ability to capture well-defined contexts, such as Urban Settlement &amp; Housing, highlights its strength, while lower confidence in overlapping themes, such as Urban Environment &amp; Climate, underscores the complexity of these categories. Rigorous validation, including stratified k-fold cross-validation and stability testing of topic modeling parameters, ensures the replicability and generalizability of the framework.</div><div>To move beyond descriptive comparisons, we conducted a chi-square analysis, which revealed a statistically significant but modest association between geographic regions and urban research themes across Africa (χ² = 219.88, df = 36, p &lt; 0.001; Cramér’s V = 0.120), confirming that observed regional disparities reflect genuine differences in research priorities rather than random variation. The analysis reveals three continental patterns in urban research: Environment &amp; Climate dominates overall but is unevenly distributed, with strong concentration in Southern and North Africa, while Health &amp; Sanitation shows a clear East/West versus North/South divide. Infrastructure research exhibits the greatest regional inequality, with relative specialization in Southern Africa and under-representation in East and West Africa, likely to reflect differences in research capacity, funding, and development trajectories.</div><div>These findings not only provide actionable insights into regional urban research priorities but also establish a replicable methodology for systematically analyzing urban data in diverse and resource-constrained settings.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"29 ","pages":"Article 100296"},"PeriodicalIF":3.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976661","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}

{"title":"Development of a PCA-derived water quality index model for monitoring the urban river systems in Dhaka City, Bangladesh","authors":"Md Mahmud Kamal Bhuiyan ,&nbsp;Hridoy Roy ,&nbsp;Kazi Saidur Rahman ,&nbsp;Bimol Nath Roy ,&nbsp;Md. Al Amin Kabir Bhuyan ,&nbsp;Md. Rezaul Maksud Jahedi ,&nbsp;Md. Shahinoor Islam","doi":"10.1016/j.cacint.2025.100276","DOIUrl":"10.1016/j.cacint.2025.100276","url":null,"abstract":"<div><div>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 (<em>p</em> &lt; 0.001) and spatial (<em>p</em> &lt; 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.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"29 ","pages":"Article 100276"},"PeriodicalIF":3.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145749052","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}

{"title":"Are smart technologies enough to build climate-resilient cities? A bibliometric assessment of global trends and research gaps","authors":"Chané de Bruyn ,&nbsp;Foued Ben Said ,&nbsp;Marius Venter ,&nbsp;Rui Alexandre Castanho","doi":"10.1016/j.cacint.2026.100306","DOIUrl":"10.1016/j.cacint.2026.100306","url":null,"abstract":"<div><div>Cities around the world are facing unprecedented challenges related to climate change, demanding innovative solutions and strategic adaptation. This study carries out an in-depth bibliometric analysis of the growing research on smart cities and climate change adaptation, exploring how technological advances can improve urban resilience and sustainability. By analyzing 1348 documents from the Scopus and Web of Science databases (2009–2024), we identify the main research trends, influential authors and journals, as well as the main thematic groups. Our results reveal a growing attention paid to the integration of artificial intelligence, the Internet of Things and big data analysis in urban planning and governance for climate change mitigation and adaptation. In particular, we identify critical gaps in research, including the need for holistic evaluation frameworks, improved citizen participation strategies and reducing the gap between technological potential and actual implementation. This analysis provides an essential roadmap for future research and policy development, guiding the transition to climate-resilient smart cities.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"29 ","pages":"Article 100306"},"PeriodicalIF":3.8,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146188128","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}

{"title":"Corrigendum to “Citizen perceptions on the use, management and availability of green spaces in a Mediterranean region” [City Environ. Interact. 27 (2025) 100210]","authors":"Daniel Jato-Espino ,&nbsp;Fabio Capra-Ribeiro ,&nbsp;Vanessa Moscardó ,&nbsp;Laura O. Gallardo","doi":"10.1016/j.cacint.2025.100220","DOIUrl":"10.1016/j.cacint.2025.100220","url":null,"abstract":"","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"28 ","pages":"Article 100220"},"PeriodicalIF":3.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145736092","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}

{"title":"Air pollution exceedance events in Melbourne and Sydney, Australia, between 2000 and 2024","authors":"Simon William Mkasimongwa ,&nbsp;Stephen J. Livesley ,&nbsp;Robert G. Ryan ,&nbsp;Robyn Schofield","doi":"10.1016/j.cacint.2025.100239","DOIUrl":"10.1016/j.cacint.2025.100239","url":null,"abstract":"<div><div>Air pollution events pose significant challenges to public health in Melbourne and Sydney, Australia’s most populous cities. This study evaluates publicly available data to understand the frequency of air pollution exceedance events beyond World Health Organization (WHO) guidelines, as well as national and state standards. The air quality of both cities generally complies with national standards but consistently fails to meet WHO air quality guidelines. Since 2000, Sydney recorded single-pollutant events on 43% of monitored days and multi-pollutant events on 14% of monitored days. In Melbourne, single-pollutant events were recorded on 42% of monitored days, and multi-pollutant events on 8%. In Sydney, NO₂ exceeded WHO guidelines on 52% of monitored days, PM_2.5 on 13%, PM₁₀ on 4%, and O₃ on 6%. In Melbourne, NO₂ exceeded on 47% of monitored days, PM_2.5 on 4%, PM₁₀ on 6%, and O₃ on 2%. Evaluating long-term, city-scale air quality is challenging due to significant variations in spatial and temporal data coverage, especially in Melbourne. Many monitoring stations have limited temporal coverage and do not consistently monitor all key pollutants, meaning the true extent of air pollution is likely not fully captured. Since 2017, Melbourne has had only five active monitoring stations, compared to over 15 in Sydney. This study demonstrates the urgent need for expanded air pollution monitoring networks in Australia’s largest cities and highlights the need for ongoing research into the impacts of multi- as well as single-pollutant exceedance events.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"28 ","pages":"Article 100239"},"PeriodicalIF":3.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144896158","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}

{"title":"Capital city status and policy influence on land dynamics: a case study of Sofifi, North Maluku Archipelago, Indonesia","authors":"Hayati Sari Hasibuan ,&nbsp;Mari Eko Mulyani ,&nbsp;Muhammad Attorik Falensky ,&nbsp;Muhammad Fadel Aginda ,&nbsp;Rudy Parluhutan Tambunan","doi":"10.1016/j.cacint.2025.100253","DOIUrl":"10.1016/j.cacint.2025.100253","url":null,"abstract":"<div><div>As the world’s largest archipelagic nation, comprising 17,024 islands, Indonesia faces distinct challenges in managing urban expansion within its island cities, particularly given that 90% of its urban areas are situated along the coastlines. This study provides a critical analysis of Sofifi the designated as capital of North Maluku Province three decades ago, with the aim of informing scholarly debates and policy considerations surrounding the ongoing development of Indonesia’s new national capital Nusantara. By examining landscape changes in Sofifi between 1994 and 2024, the research assess the extent to which its administrative status as the provincial capital influenced urbanisation. It addresses a gap in global scholarship on landscape transformation in island-based cities as most existing literature focuses on mainland contexts. The analysis utilised satellite imagery from the Google Earth Engine (GEE) platform. In addition to multitemporal Landsat imagery field surveys were conducted in early October 2024 to collect land cover samples. These data were processed through land cover classification and transformation analysis using the Change Detection Wizard in ArcGIS Pro. Findings revealed that despite administrative designation Sofifi experienced no significant urbanisation over the three decades. Lessons learned for Indonesia’s New National Capital (Nusantara) include the critical need to address the evident reluctance of populations to migrate to newly established capitals, which underscore the importance of inclusive planning and infrastructure readiness to ensure urban vibrancy.</div></div>","PeriodicalId":52395,"journal":{"name":"City and Environment Interactions","volume":"28 ","pages":"Article 100253"},"PeriodicalIF":3.8,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145361542","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}