Rapid urbanization has led to drastic land-use/cover changes (LUCCs) and urban heat islands (UHIs), negatively altering the urban climate and air quality. LUCC’s significant impacts on human health and energy consumption have inspired researchers to develop nature-based solutions to mitigate UHIs and improve air quality. However, integrating GIS-CFD modeling for urban heat mitigation towards climate change adaptation was largely neglected for eco-sustainable urban design in rapidly urbanizing areas. In this study, (1) long-term LUCC and meteorological analysis were conducted in the Wuhan metropolitan area from 1980 to 2016; (2) to mitigate the adverse effects of LUCC under a speedy development process, the role and relevance of optimizing building morphology and urban block configuration were discussed; (3) and particular design attention in strategy towards climate change adaptation for environmental performance improvement was paid in Wuhan’s fast-growing zones. The results show that UHII in 1980 was less severe than in 2016. Air temperature (Ta) increased by 0.4 °C on average per decade in developing areas. This increases the severity of UHII in urban fringes. It is found obligatory for a nature-based design to adopt urban morphology indicators (UMIs) such as average building height (μBH), sky view factors (ψ_SVF), and building density (BD/λ_p = % of built area) towards these changes. Further, on-site measurement revealed that λ_p is the most effective indicator for increasing urban heat around the buildings and boosting UHII. Using UMIs and a combined three-in-one regulation strategy based on μBH of common building types of high-rise (BH^A), mid-rise (BH^B), and low-rise (BH^C) buildings can effectively contribute to regulating Ta and air movement within block configuration. As a result of this study’s strategy, urban heat is mitigated via reinforcing wind in order to adapt to climate change, which impacts the quality of life directly in developing areas.

This research addresses the urgent challenges posed by rapid urbanization and climate change through an integrated interdisciplinary approach combining advanced technologies with rigorous scientific exploration. The comprehensive analysis focused on Wuhan, China, spanning decades of meteorological and land-use data to trace extreme urbanization trajectories and reveal intricate temporal and spatial patterns. Employing the innovative 360° radial Fibonacci geometric growth framework, the study facilitated a meticulous dissection of urban morphology at granular scales, establishing a model that combined fixed and mobile observational techniques to uncover climatic shifts and spatial transformations. Geographic information systems and computational fluid dynamics were pivotal tools used to explore the intricate interplay between urban structures and their environments. These analyses elucidated the nuanced impact of diverse morphosectors on local conditions. Furthermore, genetic algorithms were harnessed to distill meaningful relationships from the extensive data collected, optimizing spatial arrangements to enhance urban resilience and sustainability. This pioneering interdisciplinary approach not only illuminates the complex dynamics of urban ecosystems but also offers transformative insights for designing smarter, more adaptable cities. The findings underscore the critical role of green spaces in mitigating urban heat island effects. This highlights the imperative for sustainable urban planning to address the multifaceted challenges of the 21st century, promoting long-term environmental sustainability and urban health, particularly in the context of tomorrow’s climate-adaptive smart cities.

Coronavirus disease has caused city blockades, making people spend longer in residential areas than ever before. Human well-being and health are directly affected by the suppression of the epidemic through residential planning and design. In this regard, scholars from all over the world have made significant efforts to explore the links between COVID-19 and residential planning and design, trying to adjust the states in time to cope with the effects of COVID-19 in the long run. This study is based on Bibliometrix to conduct a scientometric analysis of the literature on “Effects of COVID-19 on residential planning and design (ECRPD)” published in Web of Science and Scopus from 2019 to October 2022. The aim of this study is to comprehensively present the scientific knowledge of ECRPD research through general characteristics’ analysis, citation analysis, and horizontal conceptual structure analysis, and try to summarize how residential planning and design responds to COVID-19, so as to provide support and advice for urban planners, builders, and policy makers. According to the results, ECRPD research is growing significantly, and the scientific productivity of it has increased exponentially. The main effects and feedback are characterized by three aspects: residential environment, residential building space and planning space, and residential traffic and community management. Generally, ECRPD research has expanded beyond the disciplines of architecture and planning. Environmental and energy concerns have attracted the most attention, though practical research into residential building space is relatively limited. To fully deal with COVID-19’s multiple negative facets, it is imperative to promote cross-disciplinary and multi-field collaboration, implement new technologies and methods for traditional disciplines, develop bioclimatic buildings to cope with environmental changes, and strengthen practical research in residential building and planning to ensure that a sustainable and resilient living environment is created in the post-pandemic era.

In rapidly urbanizing environments, environmental stressors—such as air pollution, noise, heat, and green space depletion—substantially exacerbate public health burdens, contributing to the global rise of non-communicable diseases, particularly hypertension, cardiovascular disorders, and mental health conditions. Despite expanding research on green spaces and health (+76.9%, 2019–2025) and optimization and algorithmic approaches (+63.7%), the compounded and synergistic impacts of these stressors remain inadequately explored or addressed within current urban planning frameworks. This study presents a Mixed Methods Systematic Review (MMSR) to investigate the potential of AI-driven urban design optimizations in mitigating these multi-scalar environmental health risks. Specifically, it explores the complex interactions between urbanization, traffic-related pollutants, green infrastructure, and architectural intelligence, identifying critical gaps in the integration of computational optimization with nature-based solutions (NBS). To empirically substantiate these theoretical insights, this study draws on longitudinal 24 h dynamic blood pressure (BP) monitoring (3–9 months), revealing that chronic exposure to environmental noise (mean 79.84 dB) increases cardiovascular risk by approximately 1.8-fold. BP data (average 132/76 mmHg), along with observed hypertensive spikes (systolic > 172 mmHg, diastolic ≤ 101 mmHg), underscore the inadequacy of current urban design strategies in mitigating health risks. Based on these findings, this paper advocates for the integration of AI-driven approaches to optimize urban environments, offering actionable recommendations for developing adaptive, human-centric, and health-responsive urban planning frameworks that enhance resilience and public health in the face of accelerating urbanization.

Natural ventilation can reduce the operational energy consumption of buildings in an energy-saving, environment-friendly and wholesome manner. This paper uses the existing ISO-standardized energy performance calculator and incorporates a dedicated controllable ventilation model to develop a method for the early design assessment of natural-ventilation-driven cooling with the aim of providing a technical support for studying the goal- and performance-oriented design of buildings adaptable to the regional climate. To facilitate application by architects, the normative model applies a certain degree of simplification, requiring only a small set of macroidentifiers for the considered building and assuming generic ventilation provisions in terms of the window opening size and control logic.