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Global warming and rapid urban growth, compounded by the urban heat island (UHI) effect, are posing substantial challenges for urban populations and ecological well-being due to increased heat stress risks. This study aimed to analyze the spatiotemporal patterns of land surface temperature (LST), UHI, and potential heat stress risk areas (PHSRA) in two distinct cities, an inland city, Nakhon Ratchasima, and a coastal city, Si Racha, during the summer. Geoinformatics techniques and Crichton’s Risk Triangle method were employed, using updated demographic data and Sentinel-3 data from 2017 to 2022. The findings indicate that the inland city daytime average LST values were higher than in the coastal city, while the opposite was true at nighttime. Additionally, high daytime UHI patterns in the inland city were observed on the outskirts, and nighttime UHI concentrated in the urban center. The coastal city exhibited a strong daytime and nighttime UHI compared to the inland city, with daytime UHI peaking in the inner area and nighttime UHI near the coastline. The PHSRA was categorized into five risk levels (very high: > 0.8, high: 0.8–0.6, moderate: 0.6–0.4, low: 0.4–0.2 and very low: ≤ 0.2). During the daytime the highest risk areas, the high and very high levels of PHSRA in the inland city (23.84%) were greater than those in the coastal city (16.46%). Conversely, at nighttime, the coastal city (16.46%) exhibited higher levels than the inland city (5.26%). In nighttime conditions, all levels of PHSRA occurred more significantly than during the daytime in these cities. Understanding the spatiotemporal variations in PHSRA is vital for pinpointing places at risk of heat stress accidents in summer. This data is a goldmine for city planners and healthcare authorities, helping them plan interventions and effective measures for the future.

Abstract The thermal profile of the urban built-up area is essential for reducing the impact of built-up areas on urban heat stress. This study quantifies the variations in the outdoor thermal profile of built forms in a heterogeneous urban area. A two-step process was adopted to quantify built form induced heat stress. The build form typologies referred to as Urban Built Form (UBF X) were clustered based on parameterised build form indices (sky view factor, built height etc.) using statistical data reduction. The heat stress of the categorised UBFs was then examined through field measurements and radiation simulation model. Variations in thermal variables were assessed using three indices - Cooling Potential (CP), Humidex (Hx) and Mean Radiant Temperature (Tmrt) that collectively define the thermal profile of each UBF. A novel Heat Stress Risk Index (HSRI) was conceptualised and computed to represent the aggregate risk of a particular UBF towards heat stress. It was found that among the UBFs, the medium-rise compact (UBF 4) show lowest rate of cooling, exposure to high Tmrt, and high discomfort levels throughout the day and therefore exhibit thermally stressed profile. High rise-open typologies (UBF1) have high Tmrt and Hx during the noon (12:00 to 14:00 h), but their high cooling potential reduces the thermal impact of its built form during the cooling hours (18:00 to 20:00 h). Three thermal indices provide varied aspects of thermal performance of UBFs and HSRI cumulatively represents the heat stress risk of the UBFs. This study is a proof of concept, that uses empirical evidence to demonstrate thermal variations in urban built forms during calm and clear weather conditions. Results indicate the significance of built form indices as a policy variable for framing climate sensitive urban development regulations that aim to achieve a thermally efficient built environment. Graphical abstract Unlabelled Image Highlights • Aims to investigate thermal variations within heterogeneous urban built forms (UBFs). • Three thermal performance indicators describe the thermal characteristics of an UBF. • The indicator-based assessment of Heat Stress Risk in UBFs • Mid-rise compact UBFs found to have the highest risk of heat stress (HSRI). • HSRI provides a thermally informed approach for framing urban development guidelines. [ABSTRACT FROM AUTHOR]

Energy retrofitting the existing building stock is crucial to reduce thermal discomfort, energy consumption, and carbon emissions. However, insulating and enhancing the thermal mass of an existing building wall using traditional methods is a very challenging and expensive task. There is a need to develop a material that can be applied easily in an existing occupied building without much interruption to occupants' daily life while also having high thermal resistance and heat storage capacity. This study aimed to investigate a potential building wall retrofit strategy combining aerogel render and Phase change materials (PCM) because aerogel render is highly resistive to heat and PCM has high thermal mass. While a number of studies investigated the thermal and energy-saving performances of aerogel render and PCM separately, no study has been done on the thermal and energy-saving performance of the combination of PCM and aerogel render. In this study, the performance of 12 different retrofit strategies, including aerogel and PCM, were evaluated numerically in terms of heat stress, energy savings, peak cooling, emission, and lifecycle cost using a typical single-story Australian house. The results showed that applying aerogel render and PCM on the outer side of the external walls and PCM and insulation in ceilings is the best option considering all performance indicators and ease of application. Compared to the baseline, this strategy reduced severe discomfort hours by 82% in a free-running building. In an air-conditioned building, it also decreased energy use, peak cooling demand, CO2 emission, and operational energy cost by 40%, 65%, 64%, and 35%, respectively. Although the lifecycle cost savings for this strategy were lower than the "insulated ceiling and rendered wall without PCM" case, the former one was considered the best option for its superior energy, emission, and comfort performance. Parametric analysis showed that 0.025 m is the optimum thickness for both PCM and aerogel render, and the 25 °C melting point PCM was optimum to achieve the best results amongst all performance indicators for a typical Australian house in Melbourne climate. [ABSTRACT FROM AUTHOR]

Hanoi City has been greatly reshaped owing to its "Master Plan by 2030 and a vision to 2050 by Decision 1259/QD-TTg of Vietnam" (called Hanoi Master Plan thereafter). This Hanoi Master Plan results in multi-challenges for the Hanoi City in terms of conserving urban greenspace (UGS). This study pursues to (1) investigate the changing environmental spatial patterns of UGS, (2) identity the areas at high risk due to heat stress based on abnormal land surface temperature (LST) distribution and demographic vulnerability, and (3) suggest mitigation strategies to the authorities by using the proposed UGS management platform. Sentinel-2 multispectral instrument (MSI) data was used to examine the evolution of UGS in relation to LST derived from Landsat 8 OLI thermal band that was subsequently utilized to create heat stress risk patterns. The study region is the inner Hanoi City. The UGS was investigated during the timeframe from Oct. 2016 to Oct. 2018. Accuracy assessment was performed by using Google Earth and field survey data. Results showed that UGS in inner Hanoi City is much declined by 1.3% for woodland and by 4.4% for shrub land, while grass-cover is increased by 2.4% in recent 2 years. Overall accuracies are of 96% and 88% with Kappa coefficients of 0.92 and 0.78 for land cover classification in 2018 and 2016, respectively. Urban heat stress index patterns showed a higher risk in the central inner-city areas of dense residential regions characterized by dense built-up. The identification of environmental heat stress risk patterns provides useful information for calling more attention of urban planners, authorities and health organizations. [Display omitted] • Urban greenspace (UGS) spatial patterns are altered due to the Hanoi Master Plan. • High heat stress areas are identified via land surface temperature (LST) monitoring. • Evolution of UGS in relation to LST was examined by using Sentinel-2 MSI data. • Heat stress index pattern showed higher risks in urban areas with denser residents. [ABSTRACT FROM AUTHOR]

l Predicting heat stress to climate change is needed at individual level. l A method of the Comprehensive Deviation Coefficient (CDC) is proposed. l Subjects' Tsk, Tre and HR to heat exposure are analyzed by multi-dimensional metrics. l Individual differences of physiological responses are quantified via CDC values. l High-risk hot environments and vulnerable individual are identified using CDC method. With increasing global warming, a method to identify individual heat exposure risk and conduct interventions is essential, in order to mitigate impacts of extreme climates on people's health. This paper aims to examine the differences of individual's physiological response in hot environments and consequently proposes a personal-based method to identify potentially vulnerable populations with high risk. A heat exposure experiment was carried out in a climate chamber to build datasets, with nine conditions combining air temperature (35 °C/38 °C/40 °C) and relative humidity (25%/40% /60%). The rectal temperature (Tre), skin temperature (Tsk) and heart rate (HR) of 10 subjects were monitored. Data were analyzed using multiple-dimensional metrics of average deviation(AD), coefficient of variation(CV) and skewness(SKEW). The study introduced the Moment of Inertia (MI) and the Simulated Mass System (MS) in a multidimensional coordinate system and developed a Comprehensive Deviation Coefficient (CDC) method. Using various combinations of AD/CV/SKEW, the values of CDC Tre , CDC Tsk , CDC HR were calculated; the high-risk thermal environment (40 °C/60%) and subject were thus identified. The proposed CDC method enables to distinguish the individual's physiological response differences, under different hot environments and personal characteristics. The equations in this method can be programed in computer and integrated with smart sensor technology, contributing to identify the high-risk environments and provide precautions for susceptible populations, to mitigate the heat exposure hazards on people' health and safety. [ABSTRACT FROM AUTHOR]