The urban heat island and its impact on heat waves and human health in Shanghai

On urban microclimate spatial-temporal dynamics: Evidence from the integration of fixed and wearable sensing and mapping techniques

Urban Heat Island (UHI) is acknowledged to generate harmful consequences on human health, and it is one of the main anthropogenic challenges to face in modern cities. Due to the urban dynamic complexity, a full microclimate decoding is required to design tailored mitigation strategies for reducing heat-related vulnerability. This study proposes a new method to assess intra-urban microclimate variability by combining for the first time two dedicated monitoring systems consisting of fixed and mobile techniques. Data from three fixed weather stations were used to analyze long-term trends, while mobile devices (a vehicle and a wearable) were used in short-term monitoring campaigns conducted in summer and winter to assess and geo-locate microclimate spatial variations. Additionally, data from mobile devices were used as input for Kriging interpolation in the urban area of Florence (Italy) as case study. Mobile monitoring sessions provided high-resolution spatial data, enabling the detection of hyperlocal variations in air temperature. The maximum air temperature amplitudes were verified with the wearable system: 3.3 °C in summer midday and 4.3 °C in winter morning. Physiological Equivalent Temperature (PET) demonstrated to be similar when comparing green areas and their adjacent built-up zone, showing up the microclimate mitigation contribution of greenery in its surrounding. Results also showed that mixing the two data acquisition and varied analysis techniques succeeded in investigating the UHI and the site-specific role of potential mitigation actions. Moreover, mobile dataset was reliable for elaborating maps by interpolating the monitored parameters. Interpolation results demonstrated the possibility of optimizing mobile monitoring campaigns by focusing on targeted streets and times of day since interpolation errors increased by 10% only with properly reduced and simplified input samples. This allowed an enhanced detection of the site-specific granularity, which is important for urban planning and policymaking, adaptation, and risk mitigation actions to overcome the UHI and anthropogenic climate change effects.

Heat exposure impacts on urban health: A meta-analysis

The escalating health risks posed by warm weather in urban areas have become a pressing global public health issue. This study undertakes a meta-analysis to evaluate the impact of warm weather on health in urban settings. We comprehensively searched PubMed, Embase, Scopus, and Web of Science for literature published before September 6, 2023, evaluating evidence quality using the Navigation Guide Criteria. We included original studies utilizing high temperatures or heatwaves as exposure metrics and employing observational designs. A meta-analysis was carried out to assess the relative risk (RR) of the association between high temperatures (or heatwaves) and disease outcomes. Out of 12,893 studies identified, 188 met the inclusion criteria for meta-analysis. Results demonstrate a statistically significant association between a 1 °C temperature increase and a 2.1 % elevation in disease-related mortality (RR 1.021 [95 % CI 1.018-1.023]), alongside a 1.1 % increase in morbidity (RR 1.011 [95 % CI 1.007-1.016]). Heatwaves also showed associations with increased total mortality (RR 1.224 [95 % CI 1.186-1.264]) and morbidity (RR 1.038 [95 % CI 1.010-1.066]). Subgroup analyses for diseases, sex, age, climatic zones, countries, and time periods consistently indicated heightened disease-related mortality and morbidity linked to high temperatures. Notably, China's urban population faced an elevated mortality risk (RR 1.027 [95 % CI 1.018-1.036]) compared to other countries (RR 1.021 [95 % CI 1.019-1.024]). Mortality associated with high temperatures after 2007 (RR 1.022 [95 % CI 1.015-1.029]) was higher than before 2007 (RR 1.017 [95 % CI 1.013-1.021]), reflecting increased health risks as the global warming accelerates. Our findings underscore the positive association between rising temperatures and/or heatwaves and adverse health outcomes in urban populations. The widespread exposure to high temperatures amplifies health risks across various diseases, demographics, climates, and countries, with potential exacerbation under ongoing global warming. Further research is imperative to delineate factors influencing altered heat exposure impacts.

The effects of brightness and prominent colors on outdoor thermal perception in Chongqing, China

Outdoor thermal comfort has become an important factor affecting human mental and physical health due to rapid urbanization. This study aimed to investigate the influence of brightness and prominent colors on thermal perception in hot summer and cold winter regions. Meteorological measurements were conducted accompanied by subjective thermal and visual questionnaires (n = 2020) during summer and winter. The physiological equivalent temperature (PET) was applied as thermal indices to evaluate the influence of visual conditions on thermal perception. The results showed that (1) the neutral PET is 20.2 °C with a range of 14.8 ~ 25.7 °C in Chongqing and neutral illumination range is 0 ~ 8663 lx. (2) Thermal sensitivity is most great in neutral brightness than bright and too bright groups. The influence of outdoor prominent colors in winter supports hue-heat hypothesis. However, in summer, result only supports the hypothesis under low thermal stress. Both cool and warm colors can reduce the thermal sensitivity of visitors compared to neutral colors (gray and white). (3) The interactions between colors and brightness are more obvious under low thermal stress levels. (4) Thermal perceptions of females are more greatly affected by brightness and prominent colors compared with males. These results could help landscape designers better understand the correlation between the thermal and visual environments and provide a reference for comprehensive designs of urban open spaces.

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.

Grid-based climate variability analysis of Addis Ababa, Ethiopia

Climate change is an intricate global environmental concern. However, its impact is more pervasive in developing nations such as Ethiopia. Hence, this manuscript examines temperature variability and the magnitude of change over 38 years in the specific case of Addis Ababa, Ethiopia. Gridded meteorological data consisting of minimum and maximum temperatures on a monthly time scale ranging from 1981 to 2018 was obtained from the National Meteorological Agency of Ethiopia. The coefficient of variation (CV) and standardized anomaly index (SAI) were used to examine the rate and extent of temperature anomalies. Geostatistical models, particularly ordinary kriging, are presented as a means of spatially interpolating temperature data. Modified Mann-Kendall test (MMK), Sen's Slope (SS) estimator, principal component analysis (PCA), and T-test were employed to determine the monthly, annual, and seasonal trends using Geospatial technologies, "R" programming, and statistical software. The findings revealed substantial spatial and temporal variation in Addis Ababa's annual and seasonal maximum and minimum temperatures. The long-term mean annual maximum and minimum temperatures were 25.8 °C and 12.6 °C, respectively. The monthly, annual, and seasonal temperatures accrued significantly except in the months of January and September. It is noteworthy that the decadal maximum temperature has risen by 2.7 °C, while minimum temperatures have displayed comparatively minor fluctuations. Moreover, the findings also exhibited that the average maximum and minimum temperatures increased by 1.88 °C and 1.72 °C, correspondingly and the highest temperature occurred during the spring (Belg) season. The first two PCAs (Annual and Kiremt Tmax) account for 90% of the temperature variation. In conclusion, the findings underscore the pressing need for the implementation of climate adaptation strategies and policy measures, which can strengthen the city's resilience to imminent climate change-induced hazards. The mounting temperature presents substantial challenges across various sectors within the city, emphasizing the urgency of preemptive actions to mitigate potential repercussions.

Improving the green space arrangement in residential areas from the perspective of tree leaf temperature utilizing scenario simulation in ENVI-met

Studying the differences in leaf temperature and their mechanisms can help us accurately understand the microenvironment in which plants are located. In this paper, typical residential areas in Jianye District, Nanjing, Jiangsu Province, China, are selected as the research area, we investigated the suitability of green space configurations from the perspective of tree leaf temperature of residential areas based on the scenario simulation in ENVI-met. Firstly, twenty abstract models were constructed, including four kinds of aspect ratio of trees (ARTs) which can be used to indicate the different green space arrangement and two typical tree species, camphora tree and platanus tree. And then three aspects were discussed including impacts of different Aspect Ratio of Trees (ART), different house-side configurations on tree leaf temperature and the relationship between temperature of tree leaves and land surface temperature (ΔSurfT) and the thermal comfort index of physiological equivalent temperature (ΔPET). The results showed that B-1 (camphor tree, ART = 2) demonstrates the most effective cooling effect in summer, with ΔPET of 3.09 °C and ΔSurfT of 3.34 °C. In winter, A-1 (platanus tree, ART = 2) proves to be the most effective in enhancing thermal comfort (ΔPET = -0.15 °C), while B-1 excels in improving surface temperature (ΔSurfT = 0.55 °C). In all, for residential area, especially in summer, planting dense camphora trees is better than platanus trees and house-side green space was very necessary. This research can help to determine appropriate tree species and green space configuration strategies for future residential areas to enhance thermal comfort.

Methods to Advance Climate Science in Respiratory Health: Satellite-Based Environmental Modeling for Temperature Exposure Assessment in Epidemiological Studies

Climate change is a major concern with significant impacts on human health including respiratory outcomes, particularly through changes in air temperature. The rise in global temperature has led to an increase in heat waves and extreme weather events, which pose serious risks to respiratory health. Accurately assessing the effects of air temperature on respiratory health requires a comprehensive approach that incorporates fine-scale exposure assessment to characterize the geospatial environment impacting population health. Recent advances in open-source earth observation data have allowed for improved exposure assessment through temperature modeling.

Intensification of compound temperature extremes by rapid urbanization under static and dynamic Urban-rural division: A comparative case study in Hunan Province, Central-South China

Climate extremes, notably compound extremes, pose significant risks to human society and environmental systems. These extremes, heightened by urbanization-a hallmark of modern socioeconomic progression-inflict persistent, intense thermal conditions. The comprehension of urbanization's impact on compound temperature extremes, particularly in Central-South China, a region with rapid urbanization and a subtropical climate, remains limited. In addition, most existing studies relied on static urban-rural division, and few used dynamic division, with no research yet juxtaposing findings from both methods. Against this backdrop, this study provided an unprecedented assessment of urbanization's impact on both individual and compound temperature extremes in Central South China, focusing on Hunan Province during long-time period of 1960-2022 under both static and dynamic urban-rural divisions. In both urban and rural stations, a pronounced warming trend was evident across individual and compound temperature extremes. Besides, a tendency of independent day/night extremes shifting towards extremes spanning both was observed. Notably, the escalation of heat compound extreme temperature indices (ETIs) outpaces that of cold ones, with a larger urban-rural discrepancy under dynamic classifications. Urbanization intensifies temperature extremes, particularly affecting the reduction of independent cold days (30.97 %-33.94 %) and the increase in compound hot events (23.91 %-24.87 %). Interestingly, urbanization's impact is more substantial on independent daytime extremes than on independent nighttime ones. Urbanization's influence on ETIs was consistently observed under both static and dynamic classifications, with the latter revealing a more pronounced contribution (1 %-3 %), and the contribution to compound ETIs is 6 %-8 % higher than to individual ETIs. These findings emphasize the importance of considering urbanization's multifaceted impacts on climate strategies and underscore the need for adaptive infrastructure and sustainable practices to mitigate escalating climate risks.

Using a novel strategy to identify the clustered regions of associations between short-term exposure to temperature and mortality and evaluate the inequality of heat- and cold-attributable burdens: A case study in the Sichuan Basin, China

BACKGROUND

Few studies have focused on the spatially clustered regions in the association between short-term exposure to temperature and mortality, which is important for identifying high-susceptibility population and enhancing the prevention of high/low temperatures. Previous studies have explored the association inequality, but no study has evaluated the inequalities of temperature-attributable burdens, which may be more meaningful for reducing temperature-related regional inequality.

METHODS

Taking the Sichuan Basin (SCB), an economically imbalanced area with high humidity and four distinctive seasons, as an example, we used a novel multi-stage strategy to investigate the two issues. First, distributed lag nonlinear models were independently constructed to obtain the county-level associations between daily temperature and cardiorespiratory mortality. Then, an estimation-error-based spatial scan statistic was used to detect the association-clustered regions. Third, multivariate meta-regression incorporating the identified clustered regions and socioeconomic and natural factors was used to obtain stable county-specific associations, based on which the heat- and cold-attributable deaths were mapped and their inequalities were evaluated using concentration indices and Lorenz curves.

RESULTS

On average, a U-shaped temperature-mortality association was examined. A significantly association-clustered region was detected (P = 0.017), in which heat and cold temperatures presented significantly stronger associations than those in the non-clustered region, particularly for heat temperatures. The cold-attributable deaths (3.5%) were substantially more than the heat-attributable deaths (0.5%). Both presented severe inequalities over counties. Significant temperature-attributable inequalities were also found over per-capital public budget, urbanization rate, employment rate and per-capital GDP. The directions of inequalities over GDP and urbanization rate were opposite between heat and cold temperatures.

CONCLUSIONS

Our analysis provided the first evidence about the clustering of temperature-mortality associations and the inequality of cold- and heat-attributable burdens. Significantly association-clustered regions and heavy temperature-attributable inequalities were found in the SCB. Rural people bore heavier cold-attributable but less heat-attributable mortality risk than urban people, suggesting that different policies should be designed to reduce the temperature-attributable inequalities for heat and cold temperatures and different regions. This novel strategy can provide an interesting new perspective in the association between environmental exposure and human health.

Heat impacts on human health in the Western Pacific Region: an umbrella review

Background

High temperatures and heatwaves are occurring more frequently and lasting longer because of climate change. A synthesis of existing evidence of heat-related health impacts in the Western Pacific Region (WPR) is lacking. This review addresses this gap.

Methods

The Scopus and PubMed databases were searched for reviews about heat impacts on mortality, cardiovascular morbidity, respiratory morbidity, dehydration and heat stroke, adverse birth outcomes, and sleep disturbance. The last search was conducted in February 2023 and only publications written in English were included. Primary studies and reviews that did not include specific WPR data were excluded. Data were extracted from 29 reviews.

Findings

There is strong evidence of heat-related mortality in the WPR, with the evidence concentrating on high-income countries and China. Associations between heat and cardiovascular or respiratory morbidity are not robust. There is evidence of heat-related dehydration and stroke, and preterm and still births in high-income countries in the WPR. Some evidence of sleep disturbance from heat is found for Australia, Japan and China.

Interpretation

Mortality is by far the most studied and robust health outcome of heat. Future research should focus on morbidity, and lower income countries in continental Asia and Pacific Island States, where there is little review-level evidence.

Funding

Funded by the World Health Organization WPR Office.

Land surface and air temperature dynamics: The role of urban form and seasonality

Due to the scarcity of air temperature (Ta) observations, urban heat studies often rely on satellite-derived Land Surface Temperature (LST) to characterise the near-surface thermal environment. However, there remains a lack of a quantitative understanding on how LST differs from Ta within urban areas and what are the controlling factors of their interaction. We use crowdsourced air temperature measurements in Sydney, Australia, combined with urban landscape data, Local Climate Zones (LCZ), high-resolution satellite imagery, and machine learning to explore the influence of urban form and fabric on the interaction between Ta and LST. Results show that LST and Ta have distinct spatiotemporal characteristics, and their relationship differs by season, ecological infrastructure, and building morphology. We found greater seasonal variability in LST compared to Ta, along with more pronounced intra-urban spatial variability in LST, particularly in warmer seasons. We also observed a greater temperature difference between LST and Ta in the built environment compared to the natural LCZs, especially during warm days. Natural LCZs (areas with mostly dense and scattered trees) showed stronger LST-Ta relationships compared to built areas. In particular, we observe that built areas with higher building density (where the heat vulnerability is likely more pronounced) show insignificant or negative relationships between LST- Ta in summer. Our results also indicate that surface cover, distance from the ocean, and seasonality significantly influence the distribution of hot and cold spots for LST and Ta. The spatial distribution for Ta hot spots does not always overlap with LST. We find that relying solely on LST as a direct proxy for the urban thermal environment is inappropriate, particularly in densely built-up areas and during warm seasons. These findings provide new perspectives on the relationship between surface and canopy temperatures and how these relate to urban form and fabric.

The association of heatwave with drowning mortality in five provinces of China

Drowning is a serious public health problem in the world. Several studies have found that ambient temperature is associated with drowning, but few have investigated the effect of heatwave on drowning. This study aimed to explore the associations between heatwave and drowning mortality, and further estimate the mortality burden of drowning attributed to heatwave in China. Drowning mortality data were collected in 71 prefectures in China during 2013-2018 from provincial vital register system. Meteorological data at the same period were collected from European Centre for Medium-Range Weather Forecasts (ECMWF). A distributed lag non-linear model (DLNM) was first to explore the association between heatwave and drowning mortality in each prefecture. Secondly, the prefecture-specific associations were pooled using meta-analysis. Finally, attributable fractions (AFs) of drowning deaths caused by heatwave were estimated. Compared to normal day, the mortality risk of drowning significantly increased during heatwave (RR = 1.20, 95%CI: 1.18-1.23). Higher risks were observed in males (RR = 1.23, 95%CI: 1.20-1.27) than females (RR = 1.18, 95%CI: 1.13-1.23), in children aged 5-14 years old (RR = 1.24, 95%CI: 1.15-1.33) than other age groups, in urban city (RR = 1.32, 95%CI: 1.28-1.36) than rural area (RR = 1.09, 95%CI: 1.07-1.12) and in Jilin province (RR = 2.85, 95%CI: 1.61-5.06) than other provinces. The AF of drowning deaths due to heatwave was 11.4 % (95%CI: 10.0 %-12.9 %) during heatwave and 1.0 % (95%CI: 0.9 %-1.1 %) during study period, respectively. Moreover, the AFs during study period were higher for male (1.2 %, 95%CI: 1.0 %-1.3 %), children 5-14 years (1.1 %, 95%CI: 0.7 %-1.6 %), urban city (1.6 %, 95%CI: 1.4 %-1.8 %) than their correspondents. These differences were also observed in AFs during heatwave. We found that heatwave may significantly increase the mortality risk of drowning mortality, and its mortality burden attributable to heatwave was noteworthy. Targeted intervention should be carried out to decrease drowning mortality during heatwave.

Space-time clusters of cardiovascular mortality and the role of heatwaves and cold spells in the city of São Paulo, Brazil

The effects extreme air temperature events are related with an increase in cardiovascular mortality among vulnerable groups worldwide. Therefore, we identify spatiotemporal mortality clusters associated with diseases of the cardiovascular system among people ≥ 65 years in São Paulo, from 2006 to 2015, and investigate whether high-risk mortality clusters occurred during or following extreme air temperature events. To detect the clusters, we used daily mortality data and a retrospective space-time scan analysis with a discrete Poisson model. Extreme air temperature events were defined by daily mean temperatures, below the 10th percentile for cold spells and above the 90th percentile for heatwaves, with two or more consecutive days. We found statistically significant high-risk mortality clusters located in the peripheral areas. The spatiotemporal clusters of risk areas for cardiovascular and ischemic heart disease occurred during or following cold spell events, whereas those for stroke and ischemic stroke events were related to heatwaves.

Vulnerability assessment of urban agglomerations to the risk of heat waves in China since the 21st century

In the context of global warming, frequent heat wave disasters have seriously threatened the safety of human life and property. The urban agglomeration, as the main region with a high concentration of population and economy, is susceptible to heat weaves due to the existing urban heat island effect. In this study, we investigated the temporal and spatial characteristics of heat waves (heat index, HI) in China from 2000 to 2020 and assess the vulnerability of 19 urban agglomerations to heat waves from the perspective of exposure, sensitivity and adaptability. The results show that: (1) In the past 20 years, the frequency and intensity of HI (greater than 26.67 °C) both showed an upward trend. (2) Shandong Peninsula, Central Henan, Yangtze River Delta, Middle Reaches of Yangtze River, and Mid-southern Liaoning urban agglomerations always maintain a high vulnerability. (3) From 2000 to 2020, the vulnerability of Beijing-Tianjin-Hebei, Yangtze River Delta, Chengdu-Chongqing, Middle reaches of Yangtze River, Guangdong-Fujian-Zhejiang, Harbin-Changchun and Mid-southern Liaoning urban agglomerations were always dominated by exposure. The vulnerability of Shandong Peninsula, Beibu Gulf and Central Henan urban agglomeration has always been dominated by sensitivity. The vulnerability of North Tianshan Mountain, Lanzhou-Xining, Guanzhong and Hu-Bao-E-Yu urban agglomeration has always been dominated by inadequate adaptability. (4) Recently, the factors that contributed most to exposure, sensitivity and adaptability were population density, the proportion of outdoor workers and water supply, with contribution rates of 38%, 55% and 26%, respectively. This study can provide a scientific basis for the rational allocation of resources among urban agglomerations, effectively formulating policies and guiding population migration from high temperature disasters.

Machine learning analysis and risk prediction of weather-sensitive mortality related to cardiovascular disease during summer in Tokyo, Japan

Climate-sensitive diseases developing from heat or cold stress threaten human health. Therefore, the future health risk induced by climate change and the aging of society need to be assessed. We developed a prediction model for mortality due to cardiovascular diseases such as myocardial infarction and cerebral infarction, which are weather or climate sensitive, using machine learning (ML) techniques. We evaluated the daily mortality of ischaemic heart disease (IHD) and cerebrovascular disease (CEV) in Tokyo and Osaka City, Japan, during summer. The significance of delayed effects of daily maximum temperature and other weather elements on mortality was previously demonstrated using a distributed lag nonlinear model. We conducted ML by a LightGBM algorithm that included specified lag days, with several temperature- and air pressure-related elements, to assess the respective mortality risks for IHD and CEV, based on training and test data for summer 2010-2019. These models were used to evaluate the effect of climate change on the risk for IHD mortality in Tokyo by applying transfer learning (TL). ML with TL predicted that the daily IHD mortality risk in Tokyo would averagely increase by 29% and 35% at the 95th and 99th percentiles, respectively, using a high-level warming-climate scenario in 2045-2055, compared to the risk simulated using ML in 2009-2019.

Temperature extremes and infectious diarrhea in China: attributable risks and effect modification of urban characteristics

Studies about the role of urban characteristics in modifying the health effect of temperature extremes are still unclear. This study is aimed at quantifying the morbidity risk of infectious diarrhea attributable to temperature extremes and the modified effect of a range of city-specific indicators. Distributed lag non-linear model and multivariate meta-regression were applied to estimate fractions of infectious diarrhea morbidity attributable to temperature extremes and to explore the effect modification of city-level characteristics. Extreme heat- and extreme cold-related infectious diarrhea amounted to 0.99% (95% CI: 0.57-1.29) and 1.05% (95% CI: 0.64-1.24) of the total cases, respectively. The attributable fraction of temperature extremes on infectious diarrhea varied between southern and northern China. Several city characteristics modified the association of extreme cold with infectious diarrhea, with a higher morbidity impact related to increased water consumption per capita and decreased latitude. Regions with higher levels of latitude or GDP per capita appeared to be more sensitive to extreme hot. In conclusion, exposure to temperature extremes was associated with increased risks of infectious diarrhea and the effect can be modified by urban characteristics. This finding can inform public health interventions to decrease the adverse effects of temperature extremes on infectious diarrhea.

The unrelenting global expansion of the urban heat island over the last century

The past century has seen dramatic increases in global temperatures and mounting urbanization. As a result of these events, the urban heat island (UHI) effect has received growing attention in scientific research worldwide. A global search was initially conducted using a scientific literature database to collect all available relevant publications to understand how the UHI has been expanding worldwide and affecting more cities across different latitudes and altitudes. Subsequently, a semantic analysis was performed to extract city names. The literature search and analysis combined resulted in 6078 publications in which UHI was investigated in 1726 cities worldwide in the 1901 to 2022 time period. The cities were grouped into 'first appearance' and 'recurrent appearance'. Results show that UHI was studied in only 134 cities during the 90-year period from 1901 to 1992, with a remarkable growth over time in the number of cities where interest in UHI increased. Interestingly, the number of first appearances was always notably higher than the number of recurrent appearances. The Shannon evenness index was employed to identify the spatial locations (hotspots) across the globe where UHI-related research has been concentrated in multiple cities over the last 120 years. Finally, Europe was selected as a testbed for conducting an analysis to shed light on how economic, demographic, and environmental factors can impact UHI. Our study is unique for having demonstrated not only the rapid growth of cities affected by UHI globally but also the increasing and unrelenting expansion of UHI occurrences across different latitudes and altitudes over time. These novel findings will undoubtedly be of interest to scientists investigating the UHI phenomenon and its trends. Stakeholders will acquire a broader perspective and deeper understanding of UHI in order to engage in more effective urban planning to offset and mitigate the phenomenon's adverse effects in the context of increasing climate change and urbanization.

How does tourism affect the urban heat island effect? A case study of the tourism heat footprint in Macao

This paper uses the tourism heat footprint (THF) and a structural vector autoregressive model to investigate how tourism has affected the urban heat island effect in Macao, a typical urban tourism destination. The dynamic relationships between the THF, heat island intensity (HII), and quarterly average temperature (QAT) are investigated. The impulse response function and variance decomposition analysis are used to assess if a long-term causal relationship exists between the three indicators. The results show the following. (1) The hotel industry in Macao is the source of energy consumption and heat release. (2) A Granger causality relationship exists between the THF and QAT but not between the THF and HII. (3) The interaction effect between the growth rate of the THF and QAT is manifested as shocks with the same frequency and regular periodic fluctuations. (4) The heat island effect of this tourism destination is reflected in an increase in local temperature due to the energy consumption and heat release by tourists. Based on the results, policy implications for a sustainable tourism city are provided.

Using buffer analysis to determine urban park cooling intensity: Five estimation methods for Nanjing, China

Urban parks are part of the blue-green infrastructure of urban ecosystems. Although the cooling effect of urban parks has been widely recognized, the understanding of park cooling intensity (PCI) and its mechanisms remains incomplete. Applicable and accurate quantification could facilitate better design and management of urban parks. We used five methods (equal area method [EAM], equal radius method [ERM], fixed radius method [FRM], turning point method-maximum perspective [TPM-M], and turning point method-accumulation perspective [TPM-A]) to estimate PCI, and established the method selection mechanism, which we evaluated in terms of PCI amplitudes, spatial heterogeneity, and interactions with park landscape features. Using Nanjing as a case study, we employed spatial and statistical analyses to further assess the autocorrelation of PCI and its relationship with park landscape features. The results indicate the following: (1) 62.38 % of Nanjing's urban parks are located above the 90 % confidence level in cold spot areas. (2) Different methods had significant effects on the estimated PCI, were positively correlated, and had similar spatial heterogeneity. (3) All methods revealed that park area (PA), water area proportion (WAP), and the normalized difference vegetation index (NDVI) of the vegetated area (NDVI_veg) were the three dominant factors that influenced PCI; WAP and NDVI_veg that achieved more effective cooling. (4) The quantification of PCI using the ERM and TPM is recommended over other methods. These findings are essential for landscape planners to understand the formation of PCI and design cooler parks to mitigate the urban heat island (UHI) effect more systematically.

A geographic information systems and remote sensing-based approach to assess urban micro-climate change and its impact on human health in Bartin, Turkey

Increasing land surface temperature (LST) is one of the major urban climatology problems arising in urban development. In this paper, the impact of vegetation and built-up areas on the LST and impact of LST on human health are assessed using the Landsat thermal data in Bartin, Turkey. The results show that there is a constant change in the share of vegetation and built-up areas due to rapid urbanization in Bartin. Strong positive correlation has been found between NDBI and LST while strong negative correlation has been found between NDVI and LST, suggesting their strong impacts on land surface temperatures. Similarly, a strong positive correlation has been observed between LST, sleep deprivation, and heat stress. This study provides precise information on effects of urbanization and man-made activities, which cause major changes in micro-climate and human health in the city. This study can assist decision-makers or planners to plan future developments sustainably.

Thermal responses of face-masked pedestrians during summer: An outdoor investigation under tree-shaded areas

During the SARS-CoV-2 (COVID-19) pandemic, most citizens were cooperative towards the face-masking policy; however, undeniably, face masking has increased complaints of thermal discomfort to varying degrees and resulted in potential health hazards during summer. Thus, a thermal comfort survey was conducted under tree-shaded areas generally preferred by pedestrians to explore the thermal response of face-masked pedestrians. Thirty-two subjects, with and without masks, participated in walking experiments, and their thermal parameters and physiological indicators were recorded; moreover, the subjects were asked to fill in subjective questionnaires. The results showed that although tree shades significantly reduced the average radiant temperature, dampness in the mask may cause some discomfort symptoms, among which intense sweating (54.55%) and tachycardia (42.18%) accounted for the largest proportion. Based on thermal indices, it could be concluded that face-masking does not significantly affect the thermal comfort of subjects walking in shaded areas. Notably, a 30-min walk in tree-shaded areas with face masking does not adversely affect human health or quality of life. Thus, the present assessment of the thermal safety of humans in shaded environments provides reference data for determining thermal comfort levels during outdoor walking with face masking.

Identifying and characterizing frequency and maximum durations of surface urban heat and cool island across global cities

Surface urban heat island (SUHI) has been widely reported from a local to global scale. However, variations and controls of temporal indicators for SUHI and SUCI (surface urban cool island) remain unclear. This paper firstly reconstructed the seamless daily LST (land surface temperature) based on ATC-SKT (annual temperature cycle-skin temperature) and comprehensively validated for SUHI applications across 1112 global cities. Based on the seamless daily LST, this paper further characterized the spatiotemporal variations of the frequency (SUHIF and SUCIF) and maximum duration (SUHID and SUCID) and investigated the impacts from related factors, inconsideration of the different characteristics of SUHI and SUCI. There are five major findings. (1) The seamless daily LST reconstructed based on ATC-SKT is validated through pixel-based temperature and city-based SUHII accuracy assessments. (2) The selection of the frequency threshold is based on robustness for LST accuracy, approximation to SUHII global average, and mitigation of frequency saturation. (3) The average daytime SUHIF is 214 days/year, with 44 % of cities exhibiting SUHI occurrences for almost every day in summer. The nighttime SUHIF is 175 days/year, with increasing latitudinal variations from equatorial to polar regions. The daytime SUCIF is 41 days/year, with the greatest average frequency of 172 days/year exhibited in arid regions. (4) The average SUHID is 147 days at daytime and 58 days at nighttime, with relatively opposite geographical distributions between day and night. (5) Greater vegetation difference at daytime and greater albedo difference at nighttime result in more occurrences and longer consecutive durations of SUHI, with opposite effects on the temporal indicators of SUCI. Furthermore, the improvements in daily SUHII and impacts from the maximum duration were discussed. This paper aims to identify and highlight the period with significant SUHI and SUCI effects across global cities for further mitigation.

Urban heat island effect-related mortality under extreme heat and non-extreme heat scenarios: A 2010-2019 case study in Hong Kong

The urban heat island (UHI) effect exacerbates the adverse impact of heat on human health. However, while the UHI effect is further intensified during extreme heat events, prior studies have rarely mapped the UHI effect during extreme heat events to assess its direct temperature impact on mortality. This study examined the UHI effect during extreme heat and non-extreme heat scenarios and compared their temperature-mortality associations in Hong Kong from 2010 to 2019. Four urban heat island degree hour (UHIdh) scenarios were mapped onto Hong Kong's tertiary planning units and classified into three levels (Low, Moderate, and High). We assessed the association between temperature and non-external mortality of populations living in each UHIdh level for the extreme heat/non-extreme heat scenarios during the 2010-2019 hot seasons. Our results showed substantial differences between the temperature-mortality associations in the three levels under the UHIdh extreme heat scenario (UHIdh_EH). While there was no evidence of increased mortality in Low UHIdh_EH areas, the mortality risk in Moderate and High UHIdh_EH areas were significantly increased during periods of hot temperature, with the High UHIdh_EH areas displaying almost double the risk (RR: 1.08, 95%CI: 1.03, 1.14 vs. RR: 1.05, 95 % CI: 1.01, 1.09). However, other non-extreme heat UHI scenarios did not demonstrate as prominent of a difference. When stratified by age, the heat effects were found in Moderate and High UHIdh_EH among the elderly aged 75 and above. Our study found a difference in the temperature-mortality associations based on UHI intensity and potential heat vulnerability of populations during extreme heat events. Preventive measures should be taken to mitigate heat especially in urban areas with high UHI intensity during extreme heat events, with particular attention and support for those prone to heat vulnerability, such as the elderly and poorer populations.

Study on the Correlation between Life Expectancy and the Ecological Environment around the Cities along the Belt and Road

The impact of building the Belt and Road on the ecological environment and the health of the related cities along this belt deserves more attention. Currently, there are few relevant pieces of research in this area, and the problem of a time lag between the ecological environment and health (e.g., life expectancy, LE) has not been explored. This paper investigates the aforementioned problem based on five ecological indicators, i.e., normalized difference vegetation index, leaf area index, gross primary production (GPP), land surface temperature (LST), and wet, which were obtained from MODIS satellite remote-sensing products in 2010, 2015, and 2020. The research steps are as follows: firstly, a comprehensive ecological index (CEI) of the areas along the Belt and Road was calculated based on the principle of component analysis; secondly, the changes in the trends of the five ecological indicators and the CEI in the research area in the past 11 years were calculated by using the trend degree analysis method; then, the distributions of the cold and hot spots of each index in the research area were calculated via cold and hot spot analysis; finally, the time lag relationship between LE and the ecological environment was explored by using the proposed spatiotemporal lag spatial crosscorrelation analysis. The experimental results show that ① there is a positive correlation between LE and ecological environment quality in the study area; ② the ecological environment has a lagging impact on LE, and the impact of ecological indicators in 2010 on LE in 2020 is greater than that in 2015; ③ among the ecological indicators, GPP has the highest impact on LE, while LST and Wet have a negative correlation with LE.

Spatio-temporal development of the urban heat island in a socioeconomically diverse tropical city

Urban heat islands, where temperatures are elevated relative to non-urban surrounds, are near-ubiquitous in cities globally. Yet, the magnitude and form of urban heat islands in the tropics, where heat has a large morbidity and mortality burden, is not well understood, especially for those of urban informal settlements. We used 29 years of Landsat satellite-derived surface temperature, corroborated by in situ temperature measurements, to provide a detailed spatial and temporal assessment of urban heat islands in Makassar, Indonesia, a city that is representative of rapidly growing urban settlements across the tropics. Our analysis identified surface urban heat islands of up to 9.2 °C in long-urbanised parts of the city and 6.3 °C in informal settlements, the seasonal patterns of which were driven by change in non-urban areas rather than in urban areas themselves. In recently urbanised areas, the majority of urban heat island increase occurred before land became 50% urbanised, whereas the established heat island in long-urbanised areas remained stable in response to urban expansion. Green and blue space protected some informal settlements from the worst urban heat islands observed across the city and maintenance of such space will be essential to mitigate the growing heat burden from urban expansion and anthropogenic climate change. Settlements further than 4 km from the coast and with Normalised Difference Vegetation Index (NDVI) less than 0.2 had higher surface temperatures, with modelled effects of more than 5 °C. Surface temperature measurements were representative of in situ heat exposure, measured in a subset of 12 informal settlements, where mean indoor temperature had the strongest relationship with surface temperature (R² = 0.413, P = 0.001). We advocate for green space to be prioritised in urban planning, redevelopment and informal settlement upgrading programs, with consideration of the unique environmental and socioeconomic context of tropical cities.

The influence of heat and cold waves on mortality in Russian subarctic cities with varying climates

Publications on ambient temperature-related mortality among Arctic or subarctic populations are extremely rare. While circumpolar areas cover large portions of several European countries, Canada, and the USA, the population of these territories is relatively small, and the data needed for statistical analysis of the health impacts of extreme temperature events are frequently insufficient. This study utilizes standard time series regression techniques to estimate relative increases in cause- and age-specific daily mortality rates during heat waves and cold spells in four Russian cities with a subarctic climate. The statistical significance of the obtained effect estimates tends to be greater in the continental climate than in the marine climate. A small meta-analysis was built around the obtained site-specific health effects. The effects were homogeneous and calculated for the selected weather-dependent health outcomes. The relative risks of mortality due to ischemic heart disease, all diseases of the circulatory system, and all non-accidental causes during cold spells in the age group ≥ 65 years were 1.20 (95% CI: 1.11-1.29), 1.14 (1.08-1.20), and 1.12 (1.07-1.17), respectively. Cold spells were more harmful to the health of the residents of Murmansk, Archangelsk, and Magadan than heat waves, and only in Yakutsk, heat waves were more dangerous. The results of this study can help the public health authorities develop specific measures for the prevention of excess deaths during cold spells and heat waves in the exposed subarctic populations.

Heat-induced health impacts and the drivers: implications on accurate heat-health plans and guidelines

Urban heat challenges are increasingly severe, along with climate change and urbanisation. Despite significant environmental, economic, and social consequences, limited actions have been conducted to address urban heat challenges. To support the formulation of heat-health plans and guidelines at the city and community scale, this study presented results, through a questionnaire survey among 584 respondents in Shanghai, China, on heat-induced physiological and psychological impacts and analysed the variability of them with demographic characteristics. The results indicate that psychological impacts were more severe than physiological impacts in severity and susceptible people. Skin heat damage and digestive system diseases were ignored in previous studies, compared with fatal cardiovascular and respiratory diseases. Emotional irritability and difficulty in controlling temper were the two most prominent psychological symptoms. The elderly and health-vulnerable groups were more susceptible to heat-induced physiological and psychological impacts than other groups. Among different demographic groups, the most critical physiological and psychological symptoms could vary significantly. Afterwards, suggestions for heat-health plans or guidelines have been proposed. Overall, this study provides a reference for the understanding of heat-induced impacts and enhancing the capacity to cope with urban heat challenges.

Fine-scale monitoring and mapping of biodiversity and ecosystem services reveals multiple synergies and few tradeoffs in urban green space management

Urban watersheds can play a critical role in supporting biodiversity and ecosystem services in a rapidly changing world. However, managing for multiple environmental and social objectives in urban landscapes is challenging, especially if the optimization of one ecosystem service conflicts with another. Urban ecology research has frequently been limited to a few indicators - typically either biodiversity or ecosystem service indices - making tradeoffs and synergies difficult to assess. Through a recently established watershed-scale monitoring network in Central Texas, we address this gap by evaluating biodiversity (flora and fauna), habitat quality, and ecosystem service indices of urban green spaces across the watershed. Our results reveal substantial heterogeneity in biodiversity and ecosystem service levels and multiple synergies (stacked benefits or "win-wins"). For example, we found that carbon sequestration positively correlated with tree species richness and the proportion of native trees in a green space, indicating that biodiversity goals for increased tree diversity can also provide carbon sequestration benefits. We also documented correlations between green spaces with greater riparian forest cover and lower particulate matter (PM_2.5) concentrations and cooler temperatures. In addition, we found that bee and wasp species richness was positively correlated with carbon sequestration and human visitation rates, meaning that urban green spaces can optimize carbon sequestration goals without losing pollinator habitat or access opportunities for city residents. Overall, our results indicate that many aspects of habitat quality, biodiversity, and ecosystem services can be simultaneously supported in urban green spaces. We conclude that urban design and management can optimize nature-based solutions and strategies to have distinct positive impacts on both people and nature.

Climate change impacts on thermal stress in four climatically diverse European cities

The thermal conditions that prevail in cities pose a number of challenges to urban residents and policy makers related to quality of life, health and welfare as well as to sustainable urban development. However, the changes in thermal stress due to climate change are probably not uniform among cities with different background climates. In this work, a comparative analysis of observed and projected thermal stress (cold stress, heat stress, no thermal stress) across four European cities (Helsinki, Rotterdam, Vienna, and Athens), which are representative of different geographical and climatic regions of the continent, for a recent period (1975 - 2004) and two future periods (2029 - 2058, 2069 - 2098) has been conducted. Applying a rational thermal index (Universal Thermal Climate Index) and considering two models of the EURO-CORDEX experiment (RCA4-MOHC, RCA4-MPI) under two Representative Concentration Pathways (RCP4.5, RCP8.5), the projected future changes in thermal conditions are inspected. The distribution of thermal stress in the current climate varies greatly between the cities, reflecting their climatic and urban heterogeneity. In the future climate, a reduction in the frequency of cold stress is expected across all cities, ranging between - 2.9% and - 16.2%. The projected increase in the frequency of optimal thermal conditions increases with increasing latitude, while the projected increase in the frequency of heat stress (ranging from + 0.2 to + 14.6%) decreases with increasing latitudes. Asymmetrical changes in cold- and heat-related stress between cities were found to affect the annual percentage of optimal (no thermal stress) conditions in future. Although future projections are expected to partly bridge the gap between the less-privileged cities (with respect to annual frequency of optimal thermal conditions) like Helsinki and Rotterdam and the more privileged ones like Athens, the former will still lag behind on an annual basis.

Urbanization promotes specific bacteria in freshwater microbiomes including potential pathogens

Freshwater ecosystems are characterized by complex and highly dynamic microbial communities that are strongly structured by their local environment and biota. Accelerating urbanization and growing city populations detrimentally alter freshwater environments. To determine differences in freshwater microbial communities associated with urbanization, full-length 16S rRNA gene PacBio sequencing was performed in a case study from surface waters and sediments from a wastewater treatment plant, urban and rural lakes in the Berlin-Brandenburg region, Northeast Germany. Water samples exhibited highly habitat specific bacterial communities with multiple genera showing clear urban signatures. We identified potentially harmful bacterial groups associated with environmental parameters specific to urban habitats such as Alistipes, Escherichia/Shigella, Rickettsia and Streptococcus. We demonstrate that urbanization alters natural microbial communities in lakes and, via simultaneous warming and eutrophication and creates favourable conditions that promote specific bacterial genera including potential pathogens. Our findings are evidence to suggest an increased potential for long-term health risk in urbanized waterbodies, at a time of rapidly expanding global urbanization. The results highlight the urgency for undertaking mitigation measures such as targeted lake restoration projects and sustainable water management efforts.

Influence of view factors on intra-urban air temperature and thermal comfort variability in a temperate city

Urban geometry is known to be one of the major factors in explaining the intra-urban temperature variations. A commonly used indicator to describe the urban geometry is the sky view factor. However, the existing studies have shown that the relationship between SVF and urban temperature is quite contradictory. This suggests that a single SVF cannot accurately quantify the urban geometry. For comparison, we here propose to use view factors, including sky, building and tree view factors (SVF, BVF, and TVF, respectively), to accurately quantify the three-dimensional urban geometry. Based on microclimate measurements conducted in Beijing Olympic Park and its surrounding urban environment in Beijing, China, the impact of view factors on intra-urban air temperature and thermal comfort was evaluated. Measurements were conducted along a selected path during hot summer days with clear skies and light winds by mobile traverses. The obtained results showed that SVF was positively correlated with air temperature during the day but negatively correlated with air temperature at night. BVF mainly played a warming role in both daytime and nighttime. Especially at night, BVF was the main geometric warming factor. TVF had a significant cooling effect during the day but did not have a negative effect at night due to reduced SVF. There was a strong point-to-point correlation between SVF and outdoor thermal comfort in the daytime. The mean differences in Mean Radiant Temperature and Physiologically Equivalent Temperature between shaded and unshaded sites were 12.0 °C and 6.8 °C, respectively, which suggested that providing effective shading is extremely important for improving outdoor daytime thermal comfort.

Compound Risk of Air Pollution and Heat Days and the Influence of Wildfire by SES across California, 2018-2020: Implications for Environmental Justice in the Context of Climate Change

Major wildfires and heatwaves have begun to increase in frequency throughout much of the United States, particularly in western states such as California, causing increased risk to public health. Air pollution is exacerbated by both wildfires and warmer temperatures, thus adding to such risk. With climate change and the continued increase in global average temperatures, the frequency of major wildfires, heat days, and unhealthy air pollution episodes is projected to increase, resulting in the potential for compounding risks. Risks will likely vary by region and may disproportionately impact low-income communities and communities of color. In this study, we processed daily particulate matter (PM) data from over 18,000 low-cost PurpleAir sensors, along with gridMET daily maximum temperature data and government-compiled wildfire perimeter data from 2018-2020 in order to examine the occurrence of compound risk (CR) days (characterized by high temperature and high PM2.5) at the census tract level in California, and to understand how such days have been impacted by the occurrence of wildfires. Using American Community Survey data, we also examined the extent to which CR days were correlated with household income, race/ethnicity, education, and other socioeconomic factors at the census tract level. Results showed census tracts with a higher frequency of CR days to have statistically higher rates of poverty and unemployment, along with high proportions of child residents and households without computers. The frequency of CR days and elevated daily PM2.5 concentrations appeared to be strongly related to the occurrence of nearby wildfires, with over 20% of days with sensor-measured average PM2.5 > 35 μg/m3 showing a wildfire within a 100 km radius and over two-thirds of estimated CR days falling on such days with a nearby wildfire. Findings from this study are important to policymakers and government agencies who preside over the allocation of state resources as well as organizations seeking to empower residents and establish climate resilient communities.

Background climate modulates the impact of land cover on urban surface temperature

Cities with different background climates experience different thermal environments. Many studies have investigated land cover effects on surface urban heat in individual cities. However, a quantitative understanding of how background climates modify the thermal impact of urban land covers remains elusive. Here, we characterise land cover and their impacts on land surface temperature (LST) for 54 highly populated cities using Landsat-8 imagery. Results show that urban surface characteristics and their thermal response are distinctly different across various climate regimes, with the largest difference for cities in arid climates. Cold cities show the largest seasonal variability, with the least seasonality in tropical and arid cities. In tropical, temperate, and cold climates, normalised difference built-up index (NDBI) is the strongest contributor to LST variability during warm months followed by normalised difference vegetation index (NDVI), while normalised difference bareness index (NDBaI) is the most important factor in arid climates. These findings provide a climate-sensitive basis for future land cover planning oriented at mitigating local surface warming.

An integrated cyberGIS and machine learning framework for fine-scale prediction of Urban Heat Island using satellite remote sensing and urban sensor network data

Due to climate change and rapid urbanization, Urban Heat Island (UHI), featuring significantly higher temperature in metropolitan areas than surrounding areas, has caused negative impacts on urban communities. Temporal granularity is often limited in UHI studies based on satellite remote sensing data that typically has multi-day frequency coverage of a particular urban area. This low temporal frequency has restricted the development of models for predicting UHI. To resolve this limitation, this study has developed a cyber-based geographic information science and systems (cyberGIS) framework encompassing multiple machine learning models for predicting UHI with high-frequency urban sensor network data combined with remote sensing data focused on Chicago, Illinois, from 2018 to 2020. Enabled by rapid advances in urban sensor network technologies and high-performance computing, this framework is designed to predict UHI in Chicago with fine spatiotemporal granularity based on environmental data collected with the Array of Things (AoT) urban sensor network and Landsat-8 remote sensing imagery. Our computational experiments revealed that a random forest regression (RFR) model outperforms other models with the prediction accuracy of 0.45 degree Celsius in 2020 and 0.8 degree Celsius in 2018 and 2019 with mean absolute error as the evaluation metric. Humidity, distance to geographic center, and PM2.5 concentration are identified as important factors contributing to the model performance. Furthermore, we estimate UHI in Chicago with 10-min temporal frequency and 1-km spatial resolution on the hottest day in 2018. It is demonstrated that the RFR model can accurately predict UHI at fine spatiotemporal scales with high-frequency urban sensor network data integrated with satellite remote sensing data.

Impact of urban land use and land cover change on urban heat island and urban thermal comfort level: a case study of Addis Ababa City, Ethiopia

The increase in the urban heat island is caused by the replacement of vegetation cover by impervious surfaces. As the population of Addis Ababa City has increased dramatically, the vegetation cover and other land cover classes have been converted into built-up areas. This study attempted to examine the relationship between urban heat islands and urban thermal comfort (UTCL) and land use and land cover (LULC) change using geospatial technologies in Addis Ababa City, Ethiopia. Landsat TM 1991, Landsat ETM + 2005, and Landsat OLI/TIRS 2021 data were used in this study. During the study period, LULC change, land surface temperature (LST), and urban heat island were calculated using the multispectral and thermal infrared bands (1991-2021). Results revealed that the built-up area in 1991 was 96.6 km² (18.3%), and increased to 165.4 km² (31.4%) and 277.2 km² (52.6%) by 2005 and 2021, respectively. In contrast, agriculture and vegetation land cover classes were declined by 66.8 km² and 25.7 km², respectively between 1991 and 2021. Rapid conversion of LULC change increases the mean LST of Addis Ababa City by 8.3 °C over the last three decades. According to the results, a high LST was recorded over built-up regions and areas with little vegetative cover. Furthermore, the central areas of the study area suffered a greater UHI effect than the surrounding areas. The results of the urban thermal field variance index (UTFVI) revealed that the UHI varies greatly across the city. Strong, stronger, and strongest urban heat islands dominated the central, southwestern, and southeastern suburbans of the study area, respectively. The excellent comfort level has declined from 16.3 km² (3.1%) in 1991 to 12.1 km² (2.3%) in 2021. The study proposed that local community awareness needs to be raised for environmental conservation through the establishment of urban green spaces that reduce UHI and increase comfort in Addis Ababa City.

A review on the influencing factors of pavement surface temperature

Pavement surface temperature is of great significance to pavement performance and pavement design, as well as the development of cool pavements. The variation of a pavement surface temperature is complicated as it is jointly affected by various factors, including air temperature, solar irradiance, wind speed, and pavement texture. This study overviews the internal and external factors that affect the pavement surface temperature in the field. It is found that air temperature is the main external climatic factor affecting the pavement surface temperature during the course of a day. Although solar radiation dictates the thermal partition at the pavement surface, it mainly influences daytime pavement temperature but vanishes at night. Pavements in calm weather can be 3-10 °C hotter than those in windy weather, depending on the time of the day and the season. Other external factors such as passing vehicles also influence the pavement surface temperature at a degree 1-3 °C. Also, the shading effect of urban trees can affect pavement surface temperature and urban microclimate. Internal factors that vary pavement surface temperature include albedo, thermal conductivity, heat capacity, and emissivity. Among them, albedo controls the pavement surface temperature while other factors play a secondary role. The results of this review provide a scope of research for developing sustainable and advanced solutions for future municipal pavement construction and urban heat island (UHI) mitigation.

Developing a method for assessing environmental sustainability based on the Google Earth Engine platform

Environmental sustainability is the foundation and of great significance for the sustainable development of urban agglomerations. Taking the Beijing-Tianjin-Hebei urban agglomeration as an example, we developed a method to effectively assess long-term regional environmental sustainability based on the Google Earth Engine (GEE) platform. We used the GEE to obtain 5206 Landsat remote sensing images in the region from 1983 to 2016 and developed the comprehensive environmental index (CEI) to assess regional environmental sustainability based on the theme-oriented framework proposed by the United Nations Commission on Sustainable Development. We found that the environmental sustainability of the urban agglomeration showed a trend of first rising, then falling, and then rising again in the past 30 years. The average CEI increased from 0.621 to 0.631 from 1985 to 1990, dropped to the lowest value of 0.618 in 2000, and then rose to the highest value of 0.672 in 2015. In particular, the extent of areas in which environmental sustainability improved (56% of the region) was greater than the extent of areas in which environmental deterioration occurred. The environmental sustainability of Hengshui, Xingtai, and Cangzhou in the southeast of the region has been significantly improved. The method proposed in this study provides an automatic, rapid, and extensible way to assess regional environmental sustainability and provides a scientific reference for improving the sustainability of the regional environment.

Socioeconomic inequalities and the surface heat island distribution in Santiago, Chile

Surface urban heat islands (SUHIs) are an important socio-environmental problem associated with large cities, such as the Santiago Metropolitan Area (SMA), in Chile. Here, we analyze daytime and nighttime variations of SUHIs for each season of the year during the period 2000-2020. To evaluate socioeconomic inequities in the distribution of SUHIs, we establish statistical relationships with socioeconomic status, land price, and urban vegetation. We use the MODIS satellite images to obtain the land surface temperatures and the normalized difference vegetation index (NDVI) through the Google Earth Engine platform. The results indicate more intense SUHIs during the nighttime in the eastern sector, coinciding with higher socioeconomic status and larger green areas. This area during the day is cooler than the rest of the city. The areas with lower and middle socioeconomic status suffer more intense SUHIs (daytime and nighttime) and match poor environmental and urban qualities. These results show the high segregation of SMA. Urban planning is subordinated to land prices with a structure maintained over the study period. The lack of social-climate justice is unsustainable, and such inequalities may be exacerbated in the context of climate change. Thus, these results can contribute to the planning of the SMA.

Investigation of Spatio–Temporal Changes in Land Use and Heat Stress Indices over Jaipur City Using Geospatial Techniques

Heat waves are expected to intensify around the globe in the future, with a potential increase in heat stress and heat-induced mortality in the absence of adaptation measures. India has high current exposure to heat waves, and with limited adaptive capacity, impacts of increased heat waves might be quite severe. This paper presents a comparative analysis of urban heat stress/heatwaves by combining temperature and vapour pressure through two heat stress indices, i.e., Wet Bulb Globe Temperature (WBGT) and humidex index. For the years 1970–2000 (historical) and 2041–2060 (future), these two indicators were estimated in Jaipur. Another goal of this research is to better understand Jaipur land use changes and urban growth. For the land use study, Landsat 5 TM and Landsat 8 OLI satellite data from the years 1993, 2010, and 2015 were examined. During the research period, urban settlement increased and the majority of open land is converted to urban settlements. In the coming term, all months except three, namely July to September, have seen an increase in the WBGT index values; however, these months are classified as dangerous. Humidex’s historical value has been 21.4, but in RCP4.5 and RCP8.5 scenarios, it will rise to 25.5 and 27.3, respectively, and slip into the danger and extreme danger categories. The NDVI and SAVI indices are also used to assess the city’s condition during various periods of heat stress. The findings suggest that people’s discomfort levels will rise in the future, making it difficult for them to work outside and engage in their usual activities.

Exploring Methods for Developing Local Climate Zones to Support Climate Research

Meteorological and climate prediction models at the urban scale increasingly require more accurate and high-resolution data. The Local Climate Zone (LCZ) system is an initiative to standardize a classification scheme of the urban landscape, based mainly on the properties of surface structure (e.g., building, tree height, density) and surface cover (pervious vs. impervious). This approach is especially useful for studying the influence of urban morphology and fabric on the surface urban heat island (SUHI) effect and to evaluate how changes in land use and structures affect thermal regulation in the city. This article will demonstrate three different methodologies of creating LCZs: first, the World Urban Database and Access Portal Tools (WUDAPT); second, using Copernicus Urban Atlas (UA) data via a geographic information system (GIS) client directly; and third via Google Earth Engine (GEE) using Oslo, Norway as the case study. The WUDAPT and GEE methods incorporate a machine learning (random forest) procedure using Landsat 8 imagery, and offer the most precision while requiring the most time and familiarity with GIS usage and satellite imagery processing. The WUDAPT method is performed principally using multiple GIS clients and image processing tools. The GEE method is somewhat quicker to perform, with work performed entirely on Google’s sites. The UA or GIS method is performed solely via a GIS client and is a conversion of pre-existing vector data to LCZ classes via scripting. This is the quickest method of the three; however, the reclassification of the vector data determines the accuracy of the LCZs produced. Finally, as an illustration of a practical use of LCZs and to further compare the results of the three methods, we map the distribution of the temperature according to the LCZs of each method, correlating to the land surface temperature (LST) from a Landsat 8 image pertaining to a heat wave episode that occurred in Oslo in 2018. These results show, in addition to a clear LCZ-LST correspondence, that the three methods produce accurate and similar results and are all viable options.

Long-Term Spatiotemporal Patterns and Evolution of Regional Heat Islands in the Beijing–Tianjin–Hebei Urban Agglomeration

With the continuous development of urbanization, the urban heat island (UHI) phenomenon is becoming increasingly prominent. Especially with the development of various large urban agglomerations and the shrinking distance between cities, the regional thermal environment has attracted extensive attention. Therefore, we used Modis land surface temperature (LST) data and employed least squares, standard deviation and spatial autocorrelation analysis methods to analyze the spatiotemporal patterns and characteristics of summer daytime regional urban heat islands (RHI) in the Beijing–Tianjin–Hebei (BTH) urban agglomeration. Our results indicated that the relative land surface temperature (RLST) in the southeastern part of BTH with a relatively high level of urbanization showed a significant and continuous upward trend. With the continuous development of the level of urbanization in the southeast, the center of gravity (GC) of RHI gradually moved to the southeast, and the development direction of RHI changed from northwest–southeast to northeast–southwest. The area transfer of RHI was concentrated in no change and little change, indicating that the evolution trend of RHI was relatively stable. The high-high aggregation areas were mainly located in the more developed areas in the southeast. In addition, the methods and results of this study can provide reasonable and effective insights into the future development and planning of the BTH.

Supporting urban ecosystem services across terrestrial, marine and freshwater realms

The terrestrial, freshwater and marine realms all provide essential ecosystem services in urban environments. However, the services provided by each realm are often considered independently, which ignores the synergies between them and risks underestimating the benefits derived collectively. Greater research collaboration across these realms, and an integrated approach to management decisions can help to support urban developments and restoration projects in maintaining or enhancing ecosystem services. The aim of this paper is to highlight the synergies and trade-offs among ecosystem services provided by each realm and to offer suggestions on how to improve current practice. We use case studies to illustrate the flow of services across realms. In our call to better integrate research and management across realms, we present a framework that provides a 6-step process for conducting collaborative research and management with an Australian perspective. Our framework considers unifying language, sharing, and understanding of desired outcomes, conducting cost-benefit analyses to minimise trade-offs, using multiple modes of communication for stakeholders, and applying research outcomes to inform regulation. It can be applied to improve collaboration among researchers, managers and planners from all realms, leading to strategic allocation of resources, increased protection of urban natural resources and improved environmental regulation with broad public support.

Effects of Altitude, Plant Communities, and Canopies on the Thermal Comfort, Negative Air Ions, and Airborne Particles of Mountain Forests in Summer

Forest bathing is considered an economical, feasible, and sustainable way to solve human sub-health problems caused by urban environmental degradation and to promote physical and mental health. Mountain forests are ideal for providing forest baths because of their large area and ecological environment. The regulatory mechanism of a mountain forest plant community in a microenvironment conducive to forest bathing is the theoretical basis for promoting physical and mental health through forest bathing in mountain forests. Based on field investigations and measurements, differences in the daily universal thermal climate index (UTCI), negative air ion (NAI), and airborne particulate matter (PM2.5 and PM10) levels in nine elevation gradients, six plant community types, and six plant community canopy parameter gradients were quantitatively analyzed. In addition, the correlations between these variables and various canopy parameters were further established. The results showed the following: (1) Altitude had a significant influence on the daily UTCI, NAI, PM2.5, and PM10 levels in the summer. The daily UTCI, NAI, PM2.5, and PM10 levels gradually decreased with the increase in altitude. For every 100 m increase in altitude, the daily UTCI decreased by 0.62 °C, the daily NAI concentration decreased by 108 ions/cm3, and the daily PM2.5 and PM10 concentrations decreased by 0.60 and 3.45 µg/m3, respectively. (2) There were significant differences in the daily UTCI, NAI, PM2.5, and PM10 levels among different plant communities in the summer. Among the six plant communities, the Quercus variabilis forest (QVF) had the lowest daily UTCI and the best thermal comfort evaluation. The QVF and Pinus tabuliformis forest (PTF) had a higher daily NAI concentration and lower daily PM2.5 and PM10 concentrations. (3) The characteristics of the plant community canopy, canopy density (CD), canopy porosity (CP), leaf area index (LAI), and sky view factor (SVF), had significant effects on the daily UTCI and NAI concentration, but had no significant effects on the daily PM2.5 and PM10 concentrations in the summer. The plant community with higher CD and LAI, but lower CP and SVF, showed a higher daily UTCI and a higher daily NAI concentration. In conclusion, the QVF and PTF plant communities with higher CD and LAI but lower CP and SVF at lower elevations are more suitable for forest bathing in the summer in mountainous forests at lower altitudes. The results of this study provide an economical, feasible, and sustainable guide for the location of forest bathing activities and urban greening planning to promote people’s physical and mental health.

Exploring Urban Forms Vulnerable to Urban Heat Islands: A Multiscale Analysis

Understanding urban forms vulnerable to urban heat islands provides urban planning measures to improve urban heat islands and offering insight into different sustainable urban forms. The purpose of this study was to investigate the relationship between the urban heat island effect and urban forms, to explore which urban forms are vulnerable to this effect, and to present urban planning measures to alleviate urban heat islands. This study also conducted an analysis on two scales, the macro- and micro-dimensions, to develop policy suggestions for urban heat island mitigation. In the macro-scale analysis, the relationship between urban shape and urban heat islands was investigated through a statistical approach using a regression equation, and in the micro-scale analysis, a spatial analysis method using urban climate zones (LCZs) was used.

Seasonal Contrast and Interactive Effects of Potential Drivers on Land Surface Temperature in the Sichuan Basin, China

Little is known about the seasonal heterogeneity of land surface temperature (LST) and the interaction relationship between potential drivers in Sichuan Basin, China. In this study, based on exploring the spatial heterogeneity of LST in Sichuan Basin, China, multi-source remote sensing data as potential drivers were selected and a Geo-detector model was applied to analyze the main drivers and the interactive relationship between drivers on LST during different seasons. The results showed that the high-temperature areas in Sichuan Basin in different seasons all appeared in the cities near the high mountains on the edge of the basin. This phenomenon was summarized as “sinking heat island” by us. From the driving factors, the biophysical parameters (DEM, SLOPE and NDVI) had the greatest impact on LST in each season, reaching the peak in the transition season. The climate parameters (WIND, HUM, PRE and TEM) and socioeconomic parameters (LIGHT, POP and ROAD) also had a certain impact on LST. The influence of a single landscape parameter (SHDI, PD, LPI, ED and LSI) on LST is limited. From the effect of factor interaction on LST, the interaction of biophysical parameters, climatic parameters and landscape parameters from summer to the transitional season was strengthened obviously, and it showed a downward trend in the winter; in contrast, the socioeconomic parameters showed the opposite characteristics, indicating that the interaction between human activities and other factors affected LST more obviously in the winter. The results of this study are not only valuable for understanding the spatial features of LST but also important for formulating mitigation strategies and sustainable development of urban heat island in Sichuan Basin.

Concurrent Heat Waves and Extreme Ozone (O3) Episodes: Combined Atmospheric Patterns and Impact on Human Health

More recurrent heat waves and extreme ozone (O₃) episodes are likely to occur during the next decades and a key question is about the concurrence of those hazards, the atmospheric patterns behind their appearance, and their joint effect on human health. In this work, we use surface maximum temperature and O₃ observations during extended summers in two cities from Morocco: Casablanca and Marrakech, between 2010 and 2019. We assess the connection between these data and climate indices (North Atlantic Oscillation (NAO), Mediterranean Oscillation (MO), and Saharan Oscillation (SaO)). We then identify concurrent heat waves and O₃ episodes, the weather type behind this concurrence, and the combined health risks. Our findings show that the concurrence of heat waves and O₃ episodes depends both on the specific city and the large-scale atmospheric circulation. The likely identified synoptic pattern is when the country is under the combined influence of an anticyclonic area in the north and the Saharan trough extending the depression centered in the south. This pattern generates a warm flow and may foster photochemical pollution. Our study is the first step toward the establishment of an alert system. It will help to provide recommendations for coping with concurrent heat waves and air pollution episodes.

Application of Remote Sensing Tools to Assess the Land Use and Land Cover Change in Coatzacoalcos, Veracruz, Mexico

Land use and land cover (LULC) change has become an important research topic for global environmental change and sustainable development. As an important part of worldwide land conservation, sustainable development and management of water resources, developing countries must ensure the use of innovative technology and tools that support their various decision making systems. This study provides the most recent LULC change analysis for the last six years (2015–2021) of Coatzacoalcos, Veracruz, Mexico, one of the most important petrochemical cities in the world and host of the ongoing Interoceanic Corridor project. The analysis was carried out using Landsat 8 Operational Land Imager (OLI) satellite images, ancillary data and ground-based surveys and the Normalized Difference Vegetation Index (NDVI) to identify and to ameliorate the discrimination between four main macro-classes and fourteen classes. The LULC classification was performed using the maximum likelihood classifier (MLC) to produce maps for each year, as it was found to be the best approach when compared to minimum distance (MDM) and spectral angle mapping (SAM) methods. The macro-classes were water, built-up, vegetation and bare soil, whereas the classes were an improved classification within those. Our study achieved both user accuracy (UA) and producer accuracy (PA) above 90% for the proposed macro-classes and classes. The average Kappa coefficient for macro-classes was 0.93, while for classes it was 0.96, both comparable to previous studies. The results from the LULC analysis show that residential, industry and commercial areas slowed down their growth throughout the study period. These changes were associated with socio-economical drivers such as insecurity and lack of economic investments. Groves and trees presented steady behaviors, with small increments during the five-year period. Swamps, on the other hand, significantly degraded, being about 2% of the study area in 2015 and 0.93% in 2021. Dunes and medium and high vegetation densities (∼80%) transitioned mostly to low vegetation densities. This behavior is associated with rainfall below the annual reference and increments of surface runoff due to the loss of vegetation cover. Lastly, the present study seeks to highlight the importance of remote sensing for a better understanding of the dynamics between human–nature interactions and to provide information to assist planners and decision-makers for more sustainable land development.

Perceived impacts of Urban Heat Island phenomenon in a tropical metropolitan city: Perspectives from stakeholder dialogue sessions

The stakeholders' perceptions on the impacts of Urban Heat Island (UHI) are critical for reducing exposure and influencing their response to interventions that are aimed at encouraging a behaviour change. A proper understanding of the UHI impacts on the society, economy and environment is deemed an essential motivating factor for the stakeholders to work towards UHI mitigations in the local context. This study adopted an inductive qualitative approach using Stakeholder Dialogue Sessions (SDSs) to assess the perceived impacts of UHI among various stakeholders, comprising policy makers, academicians, developers and Non-Governmental Organizations (NGO), in a tropical metropolitan city. The results revealed five themes such as deterioration of public health, acceleration of urban migration patterns and spending time in cooler areas, reduction of workers' productivity, increased energy consumption by the households and deterioration of environmental quality and natural resources that were categorized into social, economic and environmental impacts. Although most of the stakeholders were quite unfamiliar with the term UHI, they still display a good understanding of the potential impacts of UHI due to their posteriori knowledge and ability to rationalize the physical condition of the environment in which they live. The findings provide useful insights and valuable information to the local authorities to tailor necessary actions and educational campaigns to increase UHI awareness among the stakeholders. Being among the earlier studies to use a qualitative approach to attain the aforementioned objective, the findings are crucial to determine the level of understanding of the stakeholders on the impact of UHI. Through this study, the authors have highlighted the gaps and needs for knowledge improvements aimed at behaviour change among the stakeholders.

Fierce Heat and Players’ Health: Examining the View on Japan High School Baseball

A summer high school baseball tournament is held every mid-summer in Koshien Stadium. “Koshien Baseball” is very popular in Japan; however, it faces the problem of extremely high temperatures during games. Thus, high school players are threatened by harsh environmental conditions. For this reason, two Internet surveys were distributed to the same individuals. Then, their views regarding the Koshien tournament before and after the provision of information regarding environmental change in Japan were gathered. Using these data, this study examined how their views changed after being introduced to the information. Compared with their previous views, it was found that (1) respondents were more likely to agree that the management rules of the Koshien tournament should be altered to protect players’ health, and (2) the impact of providing information is greater for female respondents, young respondents, and highly educated respondents. This study provides evidence that the effect of information provision varies according to gender, age, and educational background. However, the mechanism causing this difference has not yet been analyzed. It would be valuable to consider this mechanism in future research.