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Urbanization in the Global South is accelerating amid a confluence of ecological, social, and developmental pressures that diverge considerably from those experienced in the Global North. Recent advances in spatial analysis, environmental modeling, and related fields are reshaping scholarly understandings of these multifaceted challenges and the targeted policy responses needed to address them. The Urban Sustainability in the Global South Collection, published in Scientific Reports , compiles interdisciplinary research contributions that elucidate ongoing urban transformations and provide evidence-based insights to inform pathways toward inclusive, safe, resilient, and sustainable urban futures, aligned with Sustainable Development Goal 11 (SDG 11).

Owing to the high energy demand of buildings, which accounted for 36% of the global share in 2020, they are one of the core targets for energy-efficiency research and regulations. Hence, coupled with the increasing complexity of decentralized power grids and high renewable energy penetration, the inception of smart buildings is becoming increasingly urgent. Data-driven building energy management systems (BEMS) based on deep reinforcement learning (DRL) have attracted significant research interest, particularly in recent years, primarily owing to their ability to overcome many of the challenges faced by conventional control methods related to real-time building modelling, multi-objective optimization, and the generalization of BEMS for efficient wide deployment. A PRISMA-based systematic assessment of a large database of 470 papers was conducted to review recent advancements in DRL-based BEMS for different building types, their research directions, and knowledge gaps. Five building types were identified: residential, offices, educational, data centres, and other commercial buildings. Their comparative analysis was conducted based on the types of appliances and systems controlled by the BEMS, renewable energy integration, DR, and unique system objectives other than energy, such as cost, and comfort. Moreover, it is worth considering that only approximately 11% of the recent research considers real system implementations.

Children differ from adults in their physiology and cognitive ability. Thus, they are extremely vulnerable to classroom thermal comfort. However, very few reviews on the thermal comfort of primary school students are available. Further, children-focused surveys have not reviewed the state-of-the-art in thermal comfort prediction using machine learning (AI/ML). Consequently, there is a need for discussion on children-specific challenges in AI/ML-based prediction. This article bridges these research gaps. It presents a comprehensive review of thermal comfort studies in primary school classrooms since 1962. It considers both conventional (non-ML) studies and the recent AI/ML studies performed for children, classrooms, and primary students. It also underscores the importance of AI/ML prediction by analyzing adaptive opportunities for children/students in classrooms. Thereafter, a review of AI/ML-based prediction studies is presented. Through an AI/ML case-study, it demonstrates that model performance for children and adults differs markedly. Performance of classification models trained on ASHRAE-II database and a recent primary students’ dataset shows a 29% difference in thermal sensation and 86% difference in thermal preference, between adults and children. It then highlights three major children-specific AI/ML challenges, viz., “illogical votes”, “multiple comfort metrics”, and “extreme class imbalance”. Finally, it offers several technical solutions and discusses open problems.

Climate change, as a defining issue of the current time, is causing severe heat-related illness in the context of extremely hot weather conditions. In Japan, the remarkable temperature increase in summer caused by an urban heat island and climate change has become a threat to public health in recent years. This study aimed to determine the potential risk factors for heatstroke by analysing data extracted from the records of emergency transport to the hospital due to heatstroke in Fukuoka City, Japan. In this regard, a negative binomial regression model was used to account for overdispersion in the data. Age-structure analyses of heatstroke patients were also embodied to identify the sub-population of Fukuoka City with the highest susceptibility. The daily maximum temperature and wet-bulb globe temperature (WBGT), along with differences in both the mean temperature and time-weighted temperature from those of the consecutive past days were detected as significant risk factors for heatstroke. Results indicated that there was a positive association between the resulting risk factors and the probability of heatstroke occurrence. The elderly of Fukuoka City aged 70 years or older were found to be the most vulnerable to heatstroke. Most of the aforementioned risk factors also encountered significant and positive associations with the risk of heatstroke occurrence for the group with highest susceptibility. These results can provide insights for health professionals and stakeholders in designing their strategies to reduce heatstroke patients and to secure the emergency transport systems in summer.

This study investigated children’s perceptions and adaptive behaviors related to indoor thermal conditions of classrooms in primary schools with no air-conditioning systems during both summer and winter in Dehradun City, Uttarakhand, India. Responses were collected from 5297 school children aged 6–13 years. During the measurement periods, 100% and 94% of the samples were obtained under conditions outside an 80% thermally acceptable comfort range in winter and summer, respectively. The analysis using receiver operating characteristics suggested that the students had the least sensitivity to the temperature variation for all scales of the thermal sensation vote (TSV). Approximately 95.1% of students were “very satisfied”, “satisfied”, or “slightly satisfied” with the thermal conditions under the condition of “extreme caution” or “danger” of heat risk. In contrast, adaptive thermal behaviors, such as adjusting clothing insulation ensembles, opening or closing classroom windows and doors, and utilizing ceiling fans, were found to be the most affordable options for optimizing indoor thermal comfort. Children’s reports of thermal sensations and thermal satisfaction did not correspond to the actual physical environment. This draws attention to the adequacy of applying widely used methods of TSV-based identification of the thermal comfort range in classrooms for children, especially in hot environments. The findings of this study are expected to serve as an evidence-based reference for local governments and authorities to take appropriate measures to mitigate heat risks for schoolchildren in the future.

Rapid urbanization in developing regions presents a critical challenge to the provision of affordable housing. This systematic review, conducted following the PRISMA 2020 guidelines, analyzed 91 studies (2013–2024) from Scopus and Google Scholar to identify cost-effective materials and innovative techniques suitable for the developing context. Findings reveal that achieving affordability in developing regions requires a holistic approach that integrates material innovation with human capacity building. The analysis of critical success factors (CSFs) in the Rumah Unggul Sistem Panel Instant (RUSPIN) system from Indonesia and the Recycled Plastic Formwork (RPF) system from South Africa exemplifies this integration. Both systems show high potential for scalability and technological transfer using local materials and labor training. The review also highlights that materials commonly used in developed countries (e.g., autoclaved aerated concrete, expanded polystyrene, and light steel gauge framing) face adoption barriers in developing regions due to challenges related to supply chains, industry capacity, and regulatory frameworks. Conversely, locally available materials (e.g., earth, bamboo, and recycled waste) require ongoing research to enhance their availability and structural performance. Ultimately, achieving affordable housing depends on an integrated approach that combines locally sourced materials, innovative construction techniques, and the strategic application of critical success factors.

The growing global concern over heat-related health risks, exacerbated by climate change, disproportionately affects low-income populations, particularly in tropical regions like Indonesia. This study investigates indoor thermal conditions in home-based enterprises (HBEs) within the informal urban settlements of Surakarta City, Indonesia, focusing on the struggle for thermal comfort under constrained conditions. By addressing the thermal comfort challenges in low-income urban housing, this research contributes to sustainable development goals, aiming to enhance living conditions in tropical climates. Our methodology included detailed field measurements of thermal comfort using standard indices in these dwellings, complemented by surveys and interviews to understand building designs, occupant behaviors, and adaptation strategies. Findings indicate that temperatures inside the dwellings frequently exceeded 30 °C during 50–60% of working hours, prompting residents to adopt coping strategies such as opening windows, adjusting work schedules, and utilizing shading devices. Space limitations necessitated multifunctional use of dwellings, exacerbating heat and humidity from activities like cooking and ironing. Despite reliance on natural ventilation, ineffective architectural layouts impeded airflow. This study highlights the urgent need for sustainable architectural solutions that accommodate the dual residential and commercial functions of these spaces, aiming to improve living conditions in such challenging environments.

Occupant behavior (OB) has a significant impact on household air-conditioner (AC) energy use. In recent years, bottom-up simulation coupled with stochastic OB modeling has been intensively developed for estimating residential AC consumption. However, a comprehensive analysis of the diverse behavioral preference patterns of occupants regarding AC use is hampered by the limited availability of large-scale residential energy demand data. Therefore, this study aimed to develop a prediction model for the residential household’s AC usage considering various OB-related diversity patterns based on monitoring data of appliance-level electricity use in a residential community of 586 households in Osaka, Japan. First, individual operation schedules and thermal preferences were identified and quantitatively extracted as the two main factors for the diverse behaviors across the whole community. Then, a clustering analysis classified the target households, finding four typical patterns for schedule preferences and three typical patterns for thermal preferences. These results were used, with time and meteorological data in the summer seasons of 2013 and 2014, as inputs for the proposed prediction model using Extreme Gradient Boosting (XGBoost). The optimized XGBoost model showed a satisfactory prediction performance for the on/off state in the testing dataset, with an F1 score of 0.80 and an Area under the Receiver Operating Characteristic (ROC) Curve (AUC) of 0.845.

Rapid urbanization has led to significant demographic shifts and environmental challenges worldwide, with a growing portion of the urban population living in slums. This study investigates the impact of an urban slum upgrading program on pro-environmental behaviors and health-oriented mindsets among residents in Surakarta City, Indonesia. Specifically, it aims to reveal how pro-environmental behaviors, house satisfaction, health-oriented behaviors, and sustainability beliefs manifest within this unique socio-cultural setting. A representative survey was conducted among 327 residents of newly renovated urban slum housing. Additionally, cluster analysis with the Silhouette method was performed to identify distinct demographic and social ‘personalities’ characterized by pro-environmental and health-oriented mindsets within the heterogeneous population across three observed districts. The findings show that while strong beliefs in sustainability are common, there is a gap in translating these beliefs into action, as evidenced by low engagement with recycling and waste-burning avoidance. Furthermore, four clusters with unique profiles emerged: (1) residents dissatisfied with housing but proactive in sustainability (23.3%); (2) health-focused residents satisfied with housing but less engaged in sustainability (5.8%); (3) residents content with housing but low on health awareness and moderate in sustainability beliefs (46.8%); and (4) residents with strong sustainability beliefs but minimal pro-environmental actions (24.1%). This study offers valuable insights for policymakers to guide urban slum upgrading programs with targeted interventions addressing the unique characteristics among the residents. These findings are vital for creating a sustainable urban environment and preventing upgraded areas from reverting to slum conditions.

Courtyard buildings embraced as a passive design paradigm, find wide application in modulating outdoor climatic conditions and fostering energy efficiency. Consequently, exploring passive strategies to mitigate the repercussions of climate change becomes a compelling priority. However, previous studies have predominantly emphasized the daytime performance of traditional courtyards in hot climates, often overlooking their performance throughout the entire day. This oversight includes the impact of courtyards in releasing stored heat into the air during nighttime, commonly referred to as \"the reversed impact of the courtyard.\" This study evaluates the reversed thermal impact of glazed “modernized” courtyard envelope during nighttime and day-exposed radiation. This analysis considers the complex interaction between incoming and outgoing radiation flows. The study employed a combined approach involving onsite measurements and numerical simulations centered upon an educational building within a hot-arid zone. The scope of the study encompasses diverse courtyard geometries and various mitigation strategies, all characterized by heightened proportions of glazed surface areas. The results, depending on prevailing weather conditions, reveal the potential for these factors to reduce heating time from 17 h to just 2 h at the optimum. In contrast, there is an increase in cooling impact, ranging from 7 to 22 h throughout both day and night, with scenarios representing the least and most favorable cases, respectively. For designing processes, optimizing aspect ratio without exceeding 1.6 and glazed façade orientation is essential to control multi-reflection at the modernized courtyard envelope criteria.