Due to climate change, the increase in electricity demand for building air-conditioning deserves comprehensive investigation during a hot and humid summer. This paper adopted the high-resolution version of the Max Planck Institute Earth System Model (MPI-ESM-1-2-HR) in Phase 6 of the Coupled Model Intercomparison Project (CMIP6) to generate future weather data based on three shared socioeconomic pathways (SSPs), namely SSP1-2.6, SSP2-4.5 and SSP5-8.5. A 1 km × 1 km resolution helped include the micro-climate effect. The resulting impact on a typical high-rise residential building in Hong Kong in the mid- (2040) and end- (2090) centuries was then analyzed. By choosing five district areas with different geographic natures, it was found that the cooling energy demand increased by 9 % and 29 % at most in the mid- and end-centuries. This corresponded to around 10.4 % per degree Celsius increase in the average ambient temperature. The demand was the highest in the district with a higher latitude. Different mitigation strategies were then applied through the modifications of the passive design, with five strategies yielding positive effects. The combined use of these five effective strategies could offer a tangible reduction in the cooling energy demand by at most 4 % as compared to the existing base case, even under SSP5-8.5 in the end-century. The results highlighted the strengths of these passive design strategies for cooling energy resilience under climate change for a sustainable future.

Microclimate research has seen significant growth in recent years, particularly in areas such as outdoor thermal comfort, urban ecology, and urban heat mitigation. However, the short-term nature of many studies in this field presents challenges in ensuring that the collected data accurately represents local climate conditions. This paper introduces a novel method to enhance the quality and applicability of microclimate research by quantifying the representativeness of short-term meteorological data. Our approach employs the Kolmogorov-Smirnov (KS) statistic to compare daily meteorological data from nearby stations against long-term climate trends. Key findings demonstrate that this method effectively identifies representative data periods. This method allows researchers to evaluate the representativeness of each day's data according to their specific study objectives, whether focusing on typical or extreme weather conditions. By implementing this framework, researchers can: (a) Post-filter existing data to identify the most representative samples. (b) Quantify the climate representativeness of their findings, enhancing result interpretation and applicability. (c) More confidently generalize conclusions from short-term studies. The paper also provides simplified alternatives to the full method, making it accessible to a wider range of researchers. By adopting this approach, microclimate studies can achieve greater confidence in their data's representativeness, leading to more robust and generalizable conclusions. Our method addresses a key methodological challenge in microclimate research and provides a flexible data assessment framework. This framework enables researchers to systematically evaluate climate data representativeness, enhancing the reliability and applicability of their findings across various urban climate studies, from thermal comfort assessments to climate adaptation strategies.

Heat-health warning systems and services are important preventive actions for extreme heat, however, global evidence differs on which temperature indicator is more informative for heat-health outcomes. We comprehensively assessed temperature predictors on their summer associations with adverse health impacts in a high-density subtropical city. Maximum, mean, and minimum temperatures were examined on their associations with non-cancer mortality and hospital admissions in Hong Kong during summer seasons 2010–2019 using Generalized Additive Models and Distributed Lag Non-linear Models. In summary, mean and minimum temperatures were identified as strong indicators for mortality, with a relative risk(RR) and 95% confidence interval(CI) of 1.037 (1.006–1.069) and 1.055 (1.019–1.092), respectively, at 95th percentile vs. optimal temperature. Additionally, minimum temperatures captured the effects of hospital admissions, RR1.009 (95%CI: 1.000- 1.018). In stratified analyses, significant associations were found for older adults, female sex, and respiratory-related outcomes. For comparison, there was no association between maximum temperature and health outcomes. With climate change and projected increase of night-time warming, the findings from this comprehensive assessment method are useful to strengthen heat prevention strategies and enhance heat-health warning systems. Other locations could refer to this comprehensive method to evaluate their heat risk, especially in highly urbanized environments and subtropical cities.

The urban heat island (UHI) phenomenon presents pressing challenges for urban sustainability, intersecting urban planning, building design, public health and climate adaptation and mitigation policy. While UHI science has advanced, its knowledge and practice translation into real-life practice remains limited. This paper investigates the processes of how UHI knowledge can support the transition from diagnosing urban climate risks to shaping more thermally resilient cities. It begins by outlining the interdisciplinary significance of urban heat governance and highlights the persistent gap between scientific understanding and actionable outcomes by drawing from five global contexts—Japan, Germany, the United States, Hong Kong and Singapore. The paper explores how scientific insights are integrated into planning instruments, design regulations and environmental performance frameworks. Using an implementation science perspective, the paper examines four key themes: (i) barriers and enablers of science–policy integration, (ii) knowledge co-production, (iii) boundary objects and interfaces, and (iv) policy diffusion across cities. Findings emphasize the importance of institutional coordination, iterative co-production and simple and user-friendly tools for planners. The paper concludes by proposing a forward-looking research agenda focused on integrated modelling, climate-resilient design and community-driven approaches, contributing to a growing discourse on reorienting urban climatology towards practice for more equitable and sustainable cities.

The rising need for urban densification due to population demands and housing shortages has resulted in heightened interest in vertical extension (VE) of buildings. This paper presents a systematic review of 119 peer-reviewed articles analyzing VE research trends. The research employs content analysis, network visualization, and co-occurrence analysis to identify important terminology and definitions, thematic emphasis, and methodological approaches utilized in VE studies, across various temporal and spatial settings. The primary focus areas within the field are structural reinforcement, VE technologies, and suitability/impact considerations. Considering methodologies, the review demonstrates significant dependence on case studies and structural modeling to evaluate the feasibility and practical applicability. The study emphasizes the necessity for standardized VE taxonomy and recommends that future research should broaden its geographical scope to offer a thorough worldwide view on VE. The outcomes offer insights for urban planners, architects, policymakers, and academics, emphasizing key areas of attention and corresponding gaps.

The global concern over the interplay between climate mitigation, urban structures, and city energy usage underscores a pressing need for innovative solutions. This research delves into the relationship between urban layouts, energy dynamics, and the thermal comfort of public spaces between buildings. Focusing on the contrasting climates of Luleå, Sweden, and Limassol, Cyprus, the study employs ENVI-met, a microscale urban climate simulation tool, for a parametric exploration at the city block scale. Assessing eight distinct scenarios across morning, noon, and afternoon timeframes, the research considers the impact of Building-Integrated Photovoltaics (BIPVs) on user thermal comfort. Contrary to expectations, the study reveals that BIPV integration alone may not be the primary driver of improved thermal comfort during peak heat periods. Instead, factors like urban density and urban morphology emerge as influential contributors. For instance, increasing the urban fabric density by doubling the building height resulted in greater PET fluctuations ranging from −3 to +3 degrees, compared to the modest PET fluctuations ranging from 0 to +3 degrees observed with the simple integration of PVs onto buildings. These findings offer valuable insights for urban planners and policymakers, guiding decisions in considering the issue of thermal comfort in public spaces between buildings, while optimizing energy consumption in urban areas.

The ongoing climate crisis and turbulence on the world stage has highlighted the need for sustainability and resilience in the development and maintenance of urban areas regarding climate comfort and energy access. Local production of green energy increases both the sustainability and resilience of an area. Traditionally, photovoltaic (PV) panels are deployed wherever the amount of sunlight is highest but lowering costs for PV panels makes them cost-effective even in colder climates. Within the broader umbrella of positive energy districts, façade mounted building-integrated PV panels in urban areas additionally present unique opportunities and challenges, as factors such as wind, solar irradiance, or nearby obstructions can have either a positive or negative effect on the performance of the PV panels. In this article, we aimed to answer the question: What factors inform the optimization of vertical PV panels? To answer this, we developed a method for the optimization of placement of PV panels. By building upon readily available weather data, local panel conditions were examined, and field-driven aggregation algorithm used to guide panel placement. Performance of the resulting panel configurations were then compared to a baseline case. Results indicate that our developed method helped mitigate negative impacts of the aforementioned factors, and often improved performance over baseline.

The research performed attempts to answer the question of how building integration of active solar systems may affect the thermal comfort in open areas and the interstitial space between buildings in urban environments. This is done by using computer simulation and in-situ observations at the extreme northern and southern geographies of Europe, namely in Luleå, Sweden and in Limassol, Cyprus. A typical example of the urban grid of each city is chosen and active solar systems are integrated on the facades of buildings, respectively foreach case. The thermal conditions at street level are then simulated, using Envi-MET, before and after systems integration, with the aim of assessing the differences between low and high insolation conditions, using the Physiological Equivalent Temperature (PET) indicator. Subsequently, the thermal conditions in the public space between buildings were once again assessed, with reduced emissivity values for the building integrated PV panels. The results point to the fact that the building integration of PVs lacking low emissivity coatings can have an impact in the thermal comfort of users in the locations specified, especially in the summer, wherein it is shown to be negligible in the southern case study but more significant in the northern one.