Heat risk of residents in different types of communities from urban heat-exposed areas

Personalized heat stress early warning system for an urban area

Extreme heat events have led to significant human mortality and morbidity across all regions of the world, with the risk of heat stress among residents steadily increasing. In response, there is a growing need for early warning systems to help individuals plan their activities to mitigate these risks. This study aims to develop a Heat Stress Risk Index Forecast (HSRIF) system, currently being prototyped for the municipal boundary of Delhi (India). HSRIF is a novel Universal Thermal Climate Index (UTCI)-based personalised early warning system, developed to provide customized heat stress risk value to the user for the upcoming 5 days. The system leverages a novel approach by utilizing meteorological data generated through an open source numerical weather prediction model 'Weather Research and Forecasting model's Urban Canopy Model (WRF-UCM)' to calculate the UTCI at a high resolution of 333 m over the study area. The calculated UTCI is then categorically normalized to derive a hazard index. This hazard index is layered over a personalized vulnerability and exposure index tailored to individual users. The vulnerability and exposure indices are designed based on personal user information, categorized into three levels of severity derived from the literature. These parameters are further refined through expert opinions from both medical and non-medical fields, incorporating their insights using the Bayesian Best-Worst Method (BBWM). By amalgamating the hazard, vulnerability, and exposure indices, the system forms the UTCI-based HSRIF. This forecast is presented to users via an interactive dashboard, providing a detailed assessment of their heat stress risk over the upcoming five days.

Heat health assessment and risk simulation prediction in eastern China: a geospatial analysis

Background

High temperatures pose significant health risks and societal challenges in China, with spatial variations in heat health risks. Furthermore, due to the constraint imposed by heat health risk assessment on the construction of the public health security framework, it is necessary to explore the heat health risk pattern of spatial distribution and the trend of future risk development in eastern China.

Methods

Based on the Intergovernmental Panel on Climate Change (IPCC) and Risk Triangle framework which is combined with natural and socio-economic factors, the heat health risk assessment index system of eastern China is established in this paper. This paper enhances the accuracy of risk maps with the aid of high-resolution imagery. It also focuses specifically on the exposure of construction workers in urban areas and agricultural workers in rural areas. This paper also evaluates the heat health risk of eastern China from 2010 to 2019 by using ArcGIS and the CA-Markov model.

Results

The heat health risk in most areas of eastern China is predominantly highest risk, with the proportion of highest and medium risk areas increasing steadily from 2010 to 2019. The spatial distribution pattern reveals that high-risk areas are concentrated in the central urban areas, while low-risk areas are primarily in the mountainous regions, suburbs, rural areas, and water source areas. The conversion of heat health risk areas mainly occurs between adjacent levels, with no mutation process. From 2010 to 2025, the heat health risk of eastern China has been improving, and the overall distribution pattern of risk levels remains consistent.

Conclusion

The research findings provide a basis for us to gain a deeper understanding of the vulnerability of different groups. This study not only presents spatial distribution maps of health risks, but offers a new perspective for us to comprehend the complexity and diversity of these risks. The research findings also establish a foundation for optimizing monitoring and warning systems. Furthermore, this study provides scientific evidence for policymakers to develop comprehensive heatwave mitigation plans. Nevertheless, we must acknowledge the limitations of the research and recognize that there is room for improvement in the future.

Tailored green and blue infrastructure for heat mitigation under renewal planning of urban blocks in Beijing

Urban heat island has become increasingly prominent, posing significant social risks and challenges to contemporary human health and well-being. Understanding the green and blue infrastructure (GBI) is crucial to support equitable climate mitigation and adaptation efforts in urban renewal process. We found three types of high-temperature blocks account for 35.53% in Beijing's Fifth Ring Road, with a mean land surface temperature of 34.13 °C. Land surface temperature antagonizing with the increase of Point GBI Area_MN, the proportion of Point GBI, and Plane GBI PD act as the major heat mitigation measures in three types of hightemperature blocks, respectively. Tailored GBI, such as alternated greening and urban forest parks, can reduce average temperature from 0.09 °C to 5.34 °C. Our study establishes a tight link between nature-based solutions and urban heat mitigation within urban renewal planning and construction to address the disparities of heat mitigation.

Feeling hot is being hot? Comparing the mapping and the surveying paradigm for urban heat vulnerability in Vienna

With rising global temperatures, cities increasingly need to identify populations or areas that are vulnerable to urban heat waves; however, vulnerability assessments may run into ecological fallacy if data from different scales are misconstrued as equivalent. We assess the heat vulnerability of 1983 residents in Vienna by measuring heat impacts, exposure, sensitivity and adaptive capacity with mirrored indicators in the mapping paradigm (i.e. census tract data referring to the geographic regions where these residents live) and the surveying paradigm (i.e. survey data referring to the residents' individual households). Results obtained in both paradigms diverge substantially: meteorological indicators of hot days and tropical nights are virtually unrelated to self-reported heat strain. Meteorological indicators are explained by mapping indicators (R2 of 15-40 %), but mostly not by surveying indicators. Vice versa, experienced heat stress and subjective heat burden are mostly unassociated with mapping indicators but are partially explained by surveying indicators (R2 of 2-4 %). The results suggest that the two paradigms do not capture the same components of vulnerability; this challenges whether studies conducted in the respective paradigms can complement and cross-validate each other. Policy interventions should first define which heat vulnerability outcome they target and then apply the paradigm that best captures the specific drivers of this outcome.

Modification effects of immigration status and comorbidities on associations of heat and heatwave with stroke morbidity

BACKGROUND

Heat and heatwave have been associated with stroke morbidity, but it is still unclear whether immigrants from different geographic regions and patients with comorbidity are more vulnerable to heat and heatwave.

METHODS

Time-stratified case-crossover design combined with generalized additive quasi-Poisson models were used to quantify the relative risks (RRs) of heat and heatwave on first-ever stroke morbidity during 0-7 lag days. Attributable fractions (AFs) were estimated to assess the first-ever stroke morbidity burden due to heat and heatwave. Stratified analyses for sex, age, disease subtypes, resident characteristics, and comorbidity type were performed to identify potential modification effects.

RESULTS

Heat and heatwave were associated with first-ever stroke morbidity, with the AF of 2.535% (95% empirical confidence interval (eCI) = 0.748, 4.205) and 2.409% (95% confidence interval (CI) = 1.228, 3.400), respectively. Among northern and southern immigrants, the AF for heat was 2.806% (0.031, 5.069) and 2.798% (0.757, 4.428), respectively, and the AF for heatwave was 2.918% (0.561, 4.618) and 2.387% (1.174, 3.398), respectively, but the effects of both on natives were statistically insignificant. Among patients with hypertension, dyslipidemia, or diabetes, the AF for heat was 3.318% (1.225, 5.007), 4.237% (1.037, 6.770), and 4.860% (1.171, 7.827), respectively, and the AF for heatwave was 2.960% (1.701, 3.993), 2.771% (0.704, 4.308), and 2.652% (0.653, 4.185), respectively. However, the effects of both on patients without comorbidity were statistically insignificant.

CONCLUSION

Heat and heatwave are associated with an increased risk of first-ever stroke morbidity among immigrants and those with comorbid hypertension, dyslipidemia, or diabetes, with the effects primarily due to non-native individuals.

DATA ACCESS STATEMENT

The author(s) are not authorized to share the data.

Enhancing human resilience against climate change: Assessment of hydroclimatic extremes and sea level rise impacts on the Eastern Shore of Virginia, United States

Coastal regions face climate-induced threats that have likely increased over the past four decades. In this work, we quantify the future climate impacts on hydroclimatic extremes in the risk-prone, 15-m-above-sea-level Eastern Shore of Virginia (ESVA) region, utilizing the Sixth International Coupled Model Intercomparison Project (CMIP6) Assessment Report 6 (AR6) and General Circulation Models (GCMs). We incorporate historical data on demographics and disasters, land use land cover (LULC), Landsat imagery, and sea level rise (SLR) to better understand and highlight the correlation between hydroclimatic extremes and societal components in this region. The hydrological model Soil and Water Assessment Tool (SWAT), Standardized Precipitation Index (SPI), Normalized Difference Water Index (NDWI), and Interquartile Range (IQR) method have been used to evaluate the intensity and frequency of projected climate extremes, in which SLR projections under different greenhouse gas emission pathways are temporally and spatially quantified. Our findings include (1) a trend towards wetter conditions is found with an increase in the number of flood events and up to an 8.9 % rise in the severity of flood peaks compared to the 2003-2020 period; (2) current coastal high-risk regions, identified using historical data of natural disasters, demographics, and LULC, are projected to be more susceptible to future climate impacts; and (3) low-lying coastal towns and regions are identified as currently vulnerable to coastal and SLR-induced flooding and are projected to become even more susceptible by 2100. This is the first effort that provides a valuable scientific basis for anticipated shifts in future climate patterns, essential for natural hazard prevention in ESVA. It highlights the need for authorities and decision-makers to plan and implement adaptive strategies and sustainable policies for the ESVA region and other coastal areas across the United States.

Demographic disparity in diurnal surface urban Heat Island exposure across local climate zones: A case study of Chongqing, China

Surface urban heat island (SUHI) exposure significantly harms human health during rapid urbanization. Identifying the areas and demographic groups under high SUHI exposure is critical for mitigating heat-related hazards. However, despite broad concern in US-European countries, rare studies discuss the diurnal SUHI exposure of demographic subgroups across Local Climate Zones (LCZs) in Chinese cities. Therefore, taking Chongqing as the case study, we measured the diurnal SUHI exposure of demographic subgroups (e.g., gender, age, and income) across different LCZs (compact, open, and sparsely-built zones) by coupling the ECOSTRESS data and mobile phone signaling data. The results indicated that Chongqing's compact high/middle-rise zones suffered a higher SUHI exposure due to high land surface temperature (LST) and a larger size of population than open zones. Despite a relatively low population density, extremely high LST in compact low-rise zones (e.g., industrial parks) contributes to considerable accumulated SUHI exposure. The SUHI exposure risk exhibited the differences between daytime and nighttime, resulting from SUHI variation and population flow. The demographic analysis showed that Chongqing's demographic subgroups are exposed disproportionately to SUHI. Elderly groups suffered relatively high exposure in compact high-rise zones. Low-incomers witnessed a high exposure in open zones. These findings call for alleviating SUHI exposure risk by targeting vulnerable groups and high-intensity exposure areas.

Increased moist heat stress risk across China under warming climate

Heatwaves have afflicted human health, ecosystem, and socioeconomy and are expected to intensify under warming climate. However, few efforts have been directed to moist heat stress (MHS) considering relative humidity and wind speed, and moist heat stress risk (MHSR) considering exposure and vulnerability. Here we showed MHS and MHSR variations across China during 1998-2100 using China Meteorological Administration Land Data Assimilation System datasets, the 6th Coupled Model Intercomparison Project (CMIP6) merged datasets, Gross Domestic Product, population and leaf area index. We detected increased MHS across China under different Shared Socioeconomic Pathways (SSPs). Specifically, the historical MHS occurred mostly during mid-July to mid-August. We found increasing trends of 0.08%/year, 0.249%/year, and 0.669%/year in the MHS-affected areas under SSP126, SSP245, and SSP585, respectively. Furthermore, we observed the highest increasing rate of MHSR in Northwest and Southwest China, while the MHSR across Northeast and North China under SSP126 shifted from increasing to decreasing trends. Noteworthy is that the increasing trend of MHSR under SSP585 is 1.5-2.6 times larger than that under SSP245, especially in North and South China. This study highlights spatiotemporal evolutions of MHS and MHSR and mitigation to moisture heat stress in a warming climate.

Exploring surface urban heat island (SUHI) intensity and its implications based on urban 3D neighborhood metrics: An investigation of 57 Chinese cities

Excessive urban temperature exerts a substantially negative impact on urban sustainability. Three-dimensional (3D) landscapes have a great impact on urban thermal environments, while their heat conditions and driving factors still remain unclear. This study mapped urban 3D neighborhoods and their associated SUHI (surface urban heat island) intensities in summer daytime across 57 Chinese cities, and then explored their relationships, driving factors as well as implications. Nine categories of urban 3D neighborhoods existed in Chinese cities and the 3D neighborhood of High Density & Medium Rise (HDMR) contributed the largest share of urban areas. The distribution of 3D neighborhoods varied among cities due to their distinct natural and economic traits. The average SUHI intensity can amount to 4.27 °C across all Chinese 3D neighborhoods. High Density & Low Rise (HDLR) and HDMR presented higher SUHI intensities than other 3D neighborhoods in China. Urban green space (UGI) and building height (BH) had great influences on SUHI intensities. The relative contribution of UGI decreased with the increase of building density and building height, but BH presented the opposite trend. The interaction of urban 3D landscapes and function zones led to highly complicated urban thermal environments, with higher SUHI intensities in industrial zones. Besides, the SUHI intensities of 3D neighborhoods presented great diurnal and seasonal variations, with higher SUHI intensities in HDHR and HDMR at nighttime in winter and summer. What's more, urban residents may suffer unequal heat risk inside cities due to the deviations of SUHI intensities among different 3D neighborhoods. It could be a highly effective way to mitigate SUHI effects in cities by increasing urban greening and improving urban ventilation.

Analysis of heat stress and heat wave in the four metropolitan cities of India in recent period

Cities are becoming hotter day-by-day because heat is trapped near the earth's surface due to a decrease in green cover, rapid urbanization, energy-intensity activities, and concrete structures. The four major metropolitan cities of India, i.e. Kolkata, Chennai, Delhi and Mumbai, have experienced heat waves and heat stress frequently during the summer season. This study analyses heat wave and heat stress patterns in these cities using 30 years of data from 1990 to 2019 during the summer season. We used daily maximum temperature, relative humidity, wind speed and solar radiation datasets for the above mentioned period in this study. To understand the episode of a heat wave, we have used the 95th percentile method. Furthermore, we have also used Humidity Index (HD) to evaluate the degree of discomfort and the Universal Thermal Climate Index (UTCI) to categorize the level of heat stress. The analysis indicates that the number of heat wave events in the Delhi region is 26.31%, 31.58% and 63.16% higher than Kolkata, Chennai, and Mumbai regions respectively. It is also seen that the risks of extreme heat stress and dangerous-heat stroke events in the Chennai region during heat wave periods are higher than that experienced in other metropolitan cities because of high temperature with higher values of relative humidity. The risk of extreme heat stress is less in Delhi because of lower relative humidity compared to other metropolitan cities although temperature is higher in this region. However, the risk of extreme heat stress is lower in Mumbai region because of relatively lower temperature than Chennai during summer season. The likelihood of experiencing great discomfort during heat wave periods in Kolkata city is higher than that experienced in other metropolitan cities in India, however, during non-heat wave periods the probability of extreme discomfort is higher in Chennai.

Exploring Adaptive UHI Mitigation Solutions by Spatial Heterogeneity of Land Surface Temperature and Its Relationship to Urban Morphology in Historical Downtown Blocks, Beijing

Heat stress brought on by the intensification of urban heat island (UHI) has caused many negative effects on human beings, which were found to be more severe in highly urbanized old towns. With the inconsistent findings on how urban spatial morphological characteristics influence land surface temperature (LST) and gaps between design practices being found, we chose Beijing Old Town (BOT) as the study area and took the basic planning implementation module “block” as a study to reveal the spatial heterogeneity of LST and its relationship to multiple urban morphological characteristics with higher spatial resolution calculated via WorldView3. Our results have shown that (1) UHI effect was significant and spatially heterogeneous in BOT, and significant hot areas with high LST value and small LST differences were found, as cold areas were the exact opposite. (2) The proportion of vegetated area, water, impervious surface, and urban spatial structure indicators i.e., building coverage ratio, mean height, highest building index, height fluctuation degree, space crowd degree and sky view factor were identified as significantly affecting the LST of blocks in BOT. (3) The effects of GBI components and configuration on LST varied within different block types; generally, blocks with GBI with larger patches that were more complex in shape, more aggregated, and less fragmented were associated with lower LST. Finally, in the context of integrating our study results with relevant planning and design guidelines, a strategy sample of adaptive GBI planning and vegetation design for blocks with different morphological features was provided for urban planners and managers to make a decision on UHI mitigation in the renewal process of BOT.

Retrospection of heatwave and heat index

The frequency and intensity of extreme events especially heat waves (HW) are growing all around the world which ultimately poses a serious threat to the health of individuals. To quantify the effects of extreme temperature, appropriate information, and the importance of HW and heat index (HI) are carefully discussed for different parts of the world. Varied definitions of the HW and HI formula proposed and used by different countries are carried out systematically continent-wise. Different studies highlighted the number of definitions of HW; however, mostly used Steadman's formulae, which was developed in the late 1970s, for the calculation of HI that uses surface air temperature and relative humidity as climatic fields. Since then, dramatic changes in climatic conditions have been observed as evident from the ERA5 datasets which need to be addressed; likewise, the definition of HW, which is modified by the researchers as per the geographic conditions. It is evident from the ERA5 data that the temperature has increased by 1-2 °C as compared to the 1980s. There is a threefold increase in the number of heatwave days over most of the continents in the last 40 years. This study will help the researcher community to understand the importance of HW and HI. Furthermore, it opens the scope to develop an equation based on the present scenario keeping in mind the basics of an index as considered by Steadman.

Combined Effect of Hot Weather and Outdoor Air Pollution on Respiratory Health: Literature Review

Association between short-term exposure to ambient air pollution and respiratory health is well documented. At the same time, it is widely known that extreme weather events intrinsically exacerbate air pollution impact. Particularly, hot weather and extreme temperatures during heat waves (HW) significantly affect human health, increasing risks of respiratory mortality and morbidity. Concurrently, a synergistic effect of air pollution and high temperatures can be combined with weather–air pollution interaction during wildfires. The purpose of the current review is to summarize literature on interplay of hot weather, air pollution, and respiratory health consequences worldwide, with the ultimate goal of identifying the most dangerous pollution agents and vulnerable population groups. A literature search was conducted using electronic databases Web of Science, Pubmed, Science Direct, and Scopus, focusing only on peer-reviewed journal articles published in English from 2000 to 2021. The main findings demonstrate that the increased level of PM10 and O3 results in significantly higher rates of respiratory and cardiopulmonary mortality. Increments in PM2.5 and PM10, O3, CO, and NO2 concentrations during high temperature episodes are dramatically associated with higher admissions to hospital in patients with chronic obstructive pulmonary disease, daily hospital emergency transports for asthma, acute and chronic bronchitis, and premature mortality caused by respiratory disease. Excessive respiratory health risk is more pronounced in elderly cohorts and small children. Both heat waves and outdoor air pollution are synergistically linked and are expected to be more serious in the future due to greater climate instability, being a crucial threat to global public health that requires the responsible involvement of researchers at all levels. Sustainable urban planning and smart city design could significantly reduce both urban heat islands effect and air pollution.