Abstract. Urban Heat Islands (UHIs) are a significant urban climate phenomenon, exacerbating energy demand, air pollution, and public health issues. This research highlights the relevance of this approach for civil engineering education, emphasizing the importance of incorporating sustainable studies into curricula. For civil engineers, learning about UHI is not just about understanding the science behind these phenomena but it’s about applying their expertise to create solutions that lead to sustainable, resilient, and livable cities. By integrating UHI mitigation strategies into their projects, civil engineers with their actions and decisions can potentially contribute to reducing the negative impacts of urbanization and climate change. This study employs the knowledge of the Junior Students from the Civil Engineer Program from the Universidad Autónoma de Nuevo León, to apply the Local Climate Zones (LCZ) framework at a Level 1 and a multiscale approach to examine UHI dynamics across various spatial building scales, that go from microscale (building and street level) to mesoscale (neighborhood and city level) and/or regional scales. The findings underscore the potential for Civil Engineers Junior Students to design climate-resilient infrastructures that address UHI impacts, fostering sustainable urban development and better climate adaptation strategies.

ABSTRACT Grounded in a feminist political ecology (FPE) framework, this study investigates how the persistent failure of drainage infrastructure in Karachi, Pakistan’s largest city, unequally burdens low-income women residing in informal settlements. Employing two key concepts from FPE, gendered bodies as living infrastructure and infrastructural violence, the study argues that gender-blind disaster interventions and the selective implementation of anti-encroachment campaigns perpetuate slow violence against marginalized women while intensifying their domestic and community labour. The findings underscore the urgent need to integrate gendered perspectives into urban infrastructure planning and climate adaptation policies to promote more just urban futures.

Abstract. Isoprene, the globally most abundant volatile organic compound, significantly impacts air quality. Determining isoprene concentration variations and their drivers is a persistent challenge. Here, we developed a robust machine learning framework to simulate isoprene concentrations, without requiring localized emission inventories and explicit chemistry. Temperature, radiation, and surface pressure were the primary drivers of short-term isoprene variations across Chinese cities. On climatic timescales, urban greenspace expansion and climate warming drove isoprene increases by 341 pptv in Hong Kong during 1990–2023, but traffic emission reductions in London counteracted the isoprene rise that climate warming would have otherwise caused (−755 pptv vs. +31 pptv). Driven by rising temperatures and isoprene levels, ozone would increase by up to 1.7-fold by 2100 under the high-emission scenario. However, ambitious reduction in nitrogen oxides would alleviate this growth to 1.2-fold. The study has the potential to inform air quality management in a warming climate.

Against the background of the risk of global climate change and the need for urban sustainable development, building systematic, dynamic and adaptive urban climate resilience is an important topic of common concern of the international community. Focusing on three core dimensions (infrastructure, governance models and financial mechanisms), this paper combs through the existing research on urban climate resilience and puts forward a three-dimensional analytical framework. The study finds that cities currently have three challenges in responding to climate risks: infrastructure systems themselves have clear mutual vulnerability; governance with clear cross-level and cross-sectoral coordination mechanism; model not yet to stable and sustainable funding mechanism. This paper further argue that in future resilience building, there is a need to build resilience beyond single domain approaches, but systematically recognize the transportity of engineering measures, institutional design, and financial instruments; to enhance dynamic assessment and digital empowerment; conceive and create differentiated, multi-stakeholder implementation strategies suited for regional characteristics. By incorporating perspectives from multiple disciplines, this study provides a theoretical framework and practical policy insights for urban climate resilience, while also revealing the existing gaps in empirical research, evaluation standards and practices in non-western contexts, indicating directions for further in-depth study.

ABSTRACT This study evaluates eco-friendly roof systems’ potential to mitigate the summertime urban heat island (UHI) effect in Nantong City, China, using an optimized, Python-based energy balance model. Unlike previous single-technology analyses, this research integrates dark membrane, high-albedo, green, and solar-integrated roofing options into one model, leveraging in-situ meteorological and field data from similar coastal cities for local accuracy. Dark membrane and black PV-covered roofs showed the highest peak sensible heat fluxes (320–400 W/m2). While PV panels slightly increased peak flux, they reduced total sensible flux from black roofs by 12%. Converting black membrane roofs to cool (high-albedo) or green roofs decreased the total sensible flux by 48%. Integrating solar panels atop reflective or green roofs achieved a 60% reduction, demonstrating optimal cooling and renewable energy generation. This is the first quantified evaluation of PV-integrated roofing solutions in Nantong’s urban climate, offering a novel framework for modeling heat flux interactions. The findings provide a data-driven basis for UHI mitigation, sustainable urban planning, and offer recommendations for optimizing roof designs in Chinese coastal cities, promoting long-term urban resilience.

Abstract. The urban heat island (UHI), where urban areas experience higher near-surface temperatures than surrounding rural areas, has long been recognized as a serious issue in urban climatology due to global warming and rapid urbanization. This study investigates the key mechanisms of the UHI through a simple theoretical thermodynamic model. Using a simple day-night model based on the surface energy balance (SEB), we demonstrate that the UHI primarily results from two mechanisms: reduced diurnal temperature range (DTR) due to larger heat capacity of urban materials and increased mean temperature due to lower urban albedo. These mechanisms explain why the UHI intensity is stronger at night than during the day. The UHI intensity obtained from the theoretical model shows a qualitatively similar diurnal variation to that found in observations, supporting the applicability of the theoretical model for understanding the UHI. An analysis of temporal dynamics of UHIs in a megacity (Seoul) and a major city (Suwon) in South Korea shows that the long-term changes in the UHI in both cities are significantly correlated with those in the urban-rural difference in DTR, highlighting the role of urban heat storage in the UHI. In particular, this study emphasizes that well-known UHI mechanisms can be explained in a simple and intuitive manner through a time-integrated theoretical framework, underscoring the academic value of simplified models in interpreting complex urban climate processes. Moreover, this approach demonstrates broader applicability beyond UHI research, suggesting that such models can serve as practical tools in diverse climatic and environmental contexts.

Rapid urbanization has driven widespread increases in artificial light at night, intensifying energy use, light pollution, and sustainability challenges. However, its ecological impacts, particularly on vegetation phenological transitions, remain poorly understood. Using 62,994 site-year in situ records and satellite observations across 452 cities from 2001 to 2022, we show that elevated levels of artificial light at night are associated with delayed dates of foliar senescence in urban areas. This delaying effect is spatially heterogeneous and nonlinear, being most pronounced at low light intensities ( < 15 nW cm-2 sr-1) and decreasing or saturating at higher levels. Regional variability in effects of artificial light at night is primarily shaped by urban socioeconomic factors and vegetation traits. Mechanistically, the delaying effect may result from enhanced carbon assimilation and altered climatic responses. We further improve the phenological modeling by incorporating the effects of artificial light at night and project overall later foliar senescence dates than currently predicted. Collectively, our findings highlight a previously underrecognized pathway by which urbanization alters vegetation phenology, with implications for forecasting ecosystem dynamics under continued urban growth and climate change.

Progress of resistance-capacitance modeling in urban climate and building energy simulation

Despite one of the most significant factors reducing photovoltaic (PV) efficiency is still shade of solar panels, the effects of shading vary widely depending on the type, material, and intensity of shading. This study examined the effects of three typical shading materials on the electrical, thermal, and efficiency parameters of an ADH ISO 15 W solar panel erected in Kansanga, Uganda: paper, cloth, and Ficus umbellata leaf. For three months, measurements of current, voltage, irradiance, ambient temperature, and cell temperature were made at 15-min intervals between 9:00 a.m. and 5:00 p.m. Descriptive statistics, efficiency computation, and ANOVA were used to examine the average data. The highest voltage, current, and power output were produced in unshaded situations, according to the results, demonstrating ideal panel performance under full sun exposure. Because of their increased opacity, paper and cloth produced the worst power losses among all shading options; leaf shading, on the other hand, allowed for partial transmission and produced rather moderate savings. More than 94% of the difference in voltage, current, and power was explained by shade, according to an ANOVA, with the paper exhibiting the highest statistical influence across parameters. The results show that even 25% partial shade significantly reduces energy output and modifies thermal behavior, underscoring the vital necessity of minimizing shading and preserving unobstructed panel surfaces in PV installations. These findings offer useful information for PV system installation, design, and shading mitigation techniques in tropical urban settings.

Scalable impact of urban green infrastructure on urban climate: A critical review

High-resolution urban climate spatiotemporal mapping from ERA5 reanalysis: integrating multi-source data with machine learning for the city of Shenzhen

Impacts of urban adaptation on reducing temperatures and heat-related deaths in Belgium

Urban climate action planning case studies: A review of trends, approaches, and reported barriers and drivers.

Local urban climate zones, environmental pollution, disease prevalence and mortality: Evidence from Barcelona

Abstract The Intergovernmental Panel on Climate Change (IPCC) pointed out that climate adaptability should be a major measure to deal with climate change in the future, and cities should be the main areas to cope with the risks. However, cities in severe cold regions are affected by both regional macro-climate and climate changes. Meanwhile the related mechanisms have not been well explored. This paper takes a typical winter city, Harbin, as the research objective. First, the change trend of the urban temperature in Harbin in the last 30 years is analyzed using meteorological and remote sensing data, and then the projection results of the future climate change in Harbin are illustrated according to the global climate system model (BCC_CSM1_1). Second, this paper discusses the relationship between meteorological parameters and some typical urban morphology factors. The results show that the urban temperature in Harbin gradually intensifies in both the summer and the winter, but the regional macro-climate background changes little. Low temperature, frequent snowfall, and insufficient sunshine in winter are still the dominant climatic environmental characteristics in Harbin. Meanwhile, the meteorological parameters have significant relationships with the urban morphology factors, with a big difference between winter and summer. Finally, this paper advances some urban planning and design strategies under the dual background of adapting to climate change and regional severe cold climate based on the analysis.

Climate change is one of the leading challenges confronting urban tourism destinations in the Global South. Nevertheless, this issue is relatively neglected in existing scholarship and most especially in sub-Saharan Africa. Climate change is an integral part of the ‘riskscape’ of contemporary urban Africa. The novel contribution of this article is to investigate climate change adaptation by urban tourism businesses in the setting of Bulawayo, Zimbabwe’s second-largest city. The research uses a quantitative research design to investigate climate adaptation and mitigation of the tourism industry in Bulawayo. In total, 160 responses were obtained using a stratified random sampling technique to ensure representation from the different sub-sectors of the tourism industry. Key findings reveal leading initiatives as the adoption of energy-efficient technologies, the use of renewable energy, training employees in sustainable and green practices, the installation of water - saving systems, climate emergency response systems, collaboration with other stakeholders on climate action, and efforts to integrate climate risks in strategic planning. Overall, the study adds to the limited existing literature in the African context concerning urban tourism and climate adaptation strategies and their challenges.

Abstract. Land Surface Temperature (LST) serves as a critical parameter for evaluating urban climate dynamics and surface energy exchanges. This study examines the relationships between LST and four spectral land cover indices—Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), Normalized Difference Water Index (NDWI), and Normalized Difference Bareness Index (NDBaI)—across four Köppen–Geiger climate zones: Kars (Dfb – Humid Continental), Kilis (Csa – Hot-Summer Mediterranean), Cairo (BWh – Hot Desert), and Malanje (Aw – Tropical Savanna). Using Landsat 8 OLI/TIRS Collection 2 Level-2 imagery acquired in September 2023 (and 2020 for Kars), LST and spectral indices were extracted and analyzed through pixel-based Pearson correlation analysis. The results revealed diverse climatic dependence in the LST–index interactions. In Kars, LST showed a strong positive correlation with NDBI (r = 0.63) and a moderate correlation with NDBaI (r = 0.39). In Kilis, NDVI exhibited a moderate negative relationship with LST (r = −0.47), while NDBI correlated weakly (r = 0.22). Cairo displayed weak overall relationships, with LST–NDBI (r = 0.38) and LST–NDVI (r = −0.22) reflecting the dominance of impervious and arid surfaces. Conversely, Malanje demonstrated the strongest vegetation–temperature interaction, where LST–NDVI correlation reached r = −0.75, LST–NDWI r = 0.72, and LST–NDBI r = 0.53. Across all cities, built-up and bare areas consistently increased LST, while vegetation showed cooling effects that intensified in warmer, more humid climates. These findings highlight that the magnitude and direction of LST–land cover correlations are strongly controlled by regional climate regimes, emphasizing the necessity of climate-specific urban heat mitigation strategies.

ABSTRACT This study adopts an organisational ethnography perspective to assess the impact of integrating document production as a central element of environmental policy. The implementation of urban adaptation plans in Poland from 2007 to 2023 illustrates how EU-inspired, project-based development of environmental documents effectively addresses climate change adaptation as a manageable urban issue, engaging urban administration. However, attempts to go beyond this framework encounter constraints, and emphasising administrative feasibility has introduced challenges in addressing factors hindering policy success. The findings advocate for a critical approach to developing environmental documents, highlighting the multidimensional influence of document production on policy implementation.

Abstract. Land Surface Temperature (LST) is a critical parameter for urban climate analysis, photovoltaic (PV) planning, and environmental monitoring, yet its effective use is hindered by the coarse spatial resolution of thermal sensors like MODIS. This study introduces a two-stage hierarchical Convolutional Neural Network (CNN) framework that integrates multi-sensor satellite data (MODIS, ASTER, Sentinel-2) to generate fine-scale LST products and quantitatively assess scaling effects across heterogeneous landscapes. In the first stage, MODIS LST (1 km) was downscaled to 360 m, 270 m, and 90 m using Sentinel-2–derived scaling factors and validated against ASTER LST. In the second stage, ASTER LST (90 m) was downscaled to 60 m and 30 m and validated with Landsat-based LST. The framework employed spectral indices, topographic parameters, texture features, and sub-pixel land-cover fractions as scaling factors, capturing both spatial and spectral heterogeneity. Comparative evaluation against XGBoost and DisTrad revealed that CNN consistently achieved the highest determination coefficients (R2 = 0.69–0.87) and the lowest RMSE (1.94–2.34 K) and MAE (1.49–1.8 K) values, confirming its superior capacity to model complex nonlinear thermal relationships. Scaling-effect analysis demonstrated that while accuracy naturally decreases with finer resolutions, the CNN model exhibits strong scale stability and resilience to error propagation, outperforming traditional regression and machine-learning approaches. This hierarchical deep-learning design establishes a new paradigm for multi-sensor LST reconstruction, enabling accurate, scalable, and spatially coherent thermal mapping across diverse terrains. The proposed framework offers a generalizable solution for high-resolution thermal monitoring, PV site optimization, and climate-adaptive urban planning.

Background and Aim. Photosynthesis represents the fundamental biological transducer of solar energy into chemical potential, sustaining global ecosystems through carbon sequestration and oxygen (O2) evolution. In the context of rapidly changing urban climates, understanding the physiological performance of diverse tree species, ranging from native foundational species to aggressive invaders, is critical for effective urban forestry management. This study aims to evaluate the efficacy of a modern, cost-effective portable pressure sensor (Globisens Labdisc) for quantifying photosynthetic O₂ evolution and to compare the physiological performance of four distinct woody species under controlled conditions. Materials and Methods. We conducted a comparative physiological analysis of leaves from Quercus robur (Oak), Ulmus spp. (Elm), Ailanthus altissima (Tree of Heaven), and Populus spp. (Poplar). Photosynthetic activity was measured by monitoring the kinetics of pressure increase in a hermetically sealed, CO2-buffered system (1% NaHCO3) under saturating light conditions (450 ± 30 μmol m⁻² s⁻¹). Data were processed to calculate specific photosynthetic rates normalized by fresh weight and time (kPa g⁻¹ min⁻¹), and statistical significance was assessed using one-way ANOVA followed by Tukey’s HSD post-hoc test. Results. The study revealed statistically significant differences in photosynthetic capacity among the species (p &lt; 0.05). Contrary to expectations for an invasive pioneer, Ailanthus altissima exhibited the lowest specific rate of oxygen evolution (0.119 kPa g⁻¹ min⁻¹). The highest activity was observed in Ulmus spp. (0.159 kPa g⁻¹ min⁻¹), followed by Quercus robur (0.149) and Populus spp. (0.141). Conclusion. The results demonstrate that while Populus showed the highest gross pressure change, normalization reveals that Ulmus and Quercus possess superior intrinsic photosynthetic efficiency per unit of biomass under these experimental conditions. The Globisens Labdisc proved to be a robust tool for high-throughput physiological screening, offering a viable alternative to expensive IRGA systems for educational and preliminary ecological monitoring.