Magnitude of urban heat islands largely explained by climate and population

Spectrally engineered textile for radiative cooling against urban heat islands

Radiative cooling textiles hold promise for achieving personal thermal comfort under increasing global temperature. However, urban areas have heat island effects that largely diminish the effectiveness of cooling textiles as wearable fabrics because they absorb emitted radiation from the ground and nearby buildings. We developed a mid-infrared spectrally selective hierarchical fabric (SSHF) with emissivity greatly dominant in the atmospheric transmission window through molecular design, minimizing the net heat gain from the surroundings. The SSHF features a high solar spectrum reflectivity of 0.97 owing to strong Mie scattering from the nano-micro hybrid fibrous structure. The SSHF is 2.3°C cooler than a solar-reflecting broadband emitter when placed vertically in simulated outdoor urban scenarios during the day and also has excellent wearable properties.

Evidence of plasticity, but not evolutionary divergence, in the thermal limits of a highly successful urban butterfly

Despite the generally negative impact of urbanization on insect biodiversity, some insect species persist in urban habitats. Understanding the mechanisms underpinning the ability of insects to tolerate urban habitats is critical given the contribution of land-use change to the global insect decline. Compensatory mechanisms such as phenotypic plasticity and evolutionary change in thermal physiological traits could allow urban populations to persist under the altered thermal regimes of urban habitats. It is important to understand the contributions of plasticity and evolution to trait change along urbanization gradients as the two mechanisms operate under different constraints and timescales. Here, we examine the plastic and evolutionary responses of heat and cold tolerance (critical thermal maximum [CTmax] and critical thermal minimum [CTmin]) to warming among populations of the cabbage white butterfly, Pieris rapae, from urban and non-urban (rural) habitats using a two-temperature common garden experiment. Although we expected populations experiencing urban warming to exhibit greater CTmax and diminished CTmin through plastic and evolutionary mechanisms, our study revealed evidence only for plasticity in the expected direction of both thermal tolerance traits. We found no evidence of evolutionary divergence in either heat or cold tolerance, despite each trait showing evolutionary potential. Our results suggest that thermal tolerance plasticity contributes to urban persistence in this system. However, as the magnitude of the plastic response was low and comparable to other insect species, other compensatory mechanisms likely further underpin this species' success in urban habitats.

Ecosystem service mismatches evidence inequalities in urban heat vulnerability

Exposure to heat poses a pressing challenge in cities, with uneven health and environmental impacts across the urban fabric. To assess disparities in heat vulnerability and its environmental justice implications, we model supply-demand mismatches for the ecosystem service (ES) urban temperature regulation. We integrated remote sensing, health, and socio-demographic data with Artificial Intelligence for Environment and Sustainability (ARIES) and geographical information system tools. We computed composite indicators at the census tract level for urban cooling supply, and vulnerability to heat as a measure of demand. We do so in the context of the mid-size city of Vitoria-Gasteiz, Basque Country (Europe). We mapped relative mismatches after identifying and analysed their relationship with socio-demographic and health factors. Our findings show disparities in heat vulnerability, with increased exposure observed among socio-economically disadvantaged communities, the elderly, and people with health issues. Areas associated with higher income levels show lower ES mismatches, indicating higher temperature regulation supply and reduced heat vulnerability. The results point at the need for nature-based heat mitigation interventions that especially focus on the more socio-economically disadvantaged communities.

Persistent urban heat

Urban surface and near-surface air temperatures are known to be often higher than their rural counterparts, a phenomenon now labeled as the urban heat island effect. However, whether the elevated urban temperatures are more persistent than rural temperatures at timescales commensurate to heat waves has not been addressed despite its importance for human health. Combining numerical simulations by a global climate model with a surface energy balance theory, it is demonstrated here that urban surface and near-surface air temperatures are significantly more persistent than their rural counterparts in cities dominated by impervious materials with large thermal inertia. Further use of these materials will result in even stronger urban temperature persistence, especially for tropical cities. The present findings help pinpoint mitigation strategies that can simultaneously ameliorate the larger magnitude and stronger persistence of urban temperatures.

Exploring the spatial and seasonal heterogeneity of cooling effect of an urban river on a landscape scale

Urban water bodies can effectively mitigate the urban heat island effect and thus enhance the climate resilience of urban areas. The cooling effect of different water bodies varies, however, the cooling heterogeneity of different sections of a single watercourse or river network is rarely considered. Based on various satellite images, geospatial approaches and statistical analyses, our study confirmed the cooling heterogeneity from spatial and seasonal perspectives of the Suzhou Outer-city River in detail in the urban area of Suzhou, China. The cooling effect of the river was observed in the daytime in four seasons, and it is strongest in summer, followed by spring and autumn, and weakest in winter. The combination of the width of the river reach, the width and the NDVI value of the adjacent green space can explain a significant part of the cooling heterogeneity of the different river sections in different seasons. Land surface temperature (LST) variations along the river are more related to the width of the river reach, but the variations of the cooling distance are more related to the adjacent green space. The cooling effect of a river reach could be enhanced if it is accompanied by green spaces. In addition, the cooling effect of a looping river is stronger on the inside area than on the outside. The methodology and results of this study could help orient scientific landscape strategies in urban planning for cooler cities.

Cooling Effect of Green Spaces on Urban Heat Island in a Chinese Megacity: Increasing Coverage versus Optimizing Spatial Distribution

Enhancing the cooling effectiveness of green spaces (GSs) is crucial for improving urban thermal environments in the context of global warming. Increasing GS coverage and optimizing its spatial distribution individually proved to be effective urban cooling measures. However, their comparative cooling effectiveness and potential interaction remain unclear. Here, using the moving window approach and random forest algorithm, we established a robust model (R2 = 0.89 ± 0.01) to explore the relationship between GS and land surface temperature (LST) in the Chinese megacity of Guangzhou. Subsequently, the response of LST to varying GS coverage and its spatial distribution was simulated, both individually and in combination. The results indicate that GS with higher coverage and more equitable spatial distribution is conducive to urban heat mitigation. Increasing GS coverage was found to lower the city's average LST by up to 4.73 °C, while optimizing GS spatial distribution led to a decrease of 1.06 °C. Meanwhile, a synergistic cooling effect was observed when combining both measures, resulting in additional cooling benefits (0.034-0.341 °C). These findings provide valuable insights into the cooling potential of GS and crucial guidance for urban green planning aimed at heat mitigation in cities.

The angiogenic growth of cities

Describing the space-time evolution of urban population is a fundamental challenge in the science of cities, yet a complete theoretical treatment of the underlying dynamics is still missing. Here, we first reconstruct the evolution of London (UK) over 180 years and show that urban growth consists of an initial phase of diffusion-limited growth, followed by the development of the railway transport network and a consequential shift from central to suburban living. Such dynamics-which are analogous to angiogenesis in biological systems-can be described by a minimalist reaction-diffusion model coupled with economic constraints and an adaptive transport network. We then test the generality of our approach by reproducing the evolution of Sydney, Australia, from 1851 to 2011. We show that the rail system coevolves with urban population, displaying hierarchical characteristics that remain constant over time unless large-scale interventions are put in place to alter the modes of transport. These results demonstrate that transport schemes are first-order controls of long-term urbanization patterns and efforts aimed at creating more sustainable and healthier cities require careful consideration of population-transport feedbacks.

The great urban shift: Climate change is predicted to drive mass species turnover in cities

Human experiences with nature are important for our culture, economy, and health. Anthropogenically-driven climate change is causing widespread shifts in biodiversity and resident urban wildlife are no exception. We modelled over 2,000 animal species to predict how climate change will impact terrestrial wildlife within 60 Canadian and American cities. We found evidence of an impending great urban shift where thousands of species will disappear across the selected cities, being replaced by new species, or not replaced at all. Effects were largely species-specific, with the most negatively impacted taxa being amphibians, canines, and loons. These predicted shifts were consistent across scenarios of greenhouse gas emissions, but our results show that the severity of change will be defined by our action or inaction to mitigate climate change. An impending massive shift in urban wildlife will impact the cultural experiences of human residents, the delivery of ecosystem services, and our relationship with nature.

Mesoscale structure of the atmospheric boundary layer across a natural roughness transition

The structure and intensity of turbulence in the atmospheric boundary layer (ABL) drive fluxes of sediment, contaminants, heat, moisture, and CO[Formula: see text] at the Earth's surface. Where ABL flows encounter changes in roughness-such as cities, wind farms, forest canopies, and landforms-a new mesoscopic flow scale is introduced: the internal boundary layer (IBL), which represents a near-bed region of transient flow adjustment that develops over kilometers. Measurement of this new mesoscopic scale lies outside present observational capabilities of ABL flows, and simplified models fail to capture the sensitive dependence of turbulence on roughness geometry. Here, we use large-eddy simulations, run over high-resolution topographic data and validated against field observations, to examine the structure of the ABL across a natural roughness transition: the emergent sand dunes at White Sands National Park. We observe that development of the IBL is triggered by the abrupt transition from smooth playa surface to dunes; however, continuous changes in the size and spacing of dunes over several kilometers influence the downwind patterns of boundary stress and near-bed turbulence. Coherent flow structures grow and merge over the entire [Formula: see text]10 km distance of the dune field and modulate the influence of large-scale atmospheric turbulence on the bed. Simulated boundary stresses in the developing IBL counter existing expectations and explain the observed downwind decrease in dune migration, demonstrating a mesoscale coupling between flow and form that governs landscape dynamics. More broadly, our findings demonstrate the importance of resolving both turbulence and realistic roughness for understanding fluid-boundary interactions in environmental flows.

Different explanations for surface and canopy urban heat island effects in relation to background climate

The background climatic conditions and urban morphology greatly influence urban heat island effects (UHIs), but one-size-fits-all solutions are frequently employed to mitigate UHIs. Here, attribution models for surface UHIs (SUHIs) and canopy UHIs (CUHIs) were developed to describe UHI formation. The contribution of factors to SUHIs and CUHIs shows similar dependencies on background climate and urban morphology. Furthermore, the factors that mainly contributed to CUHIs were more complex, and anthropogenic heat was the more critical factor. Influence from urban morphology also highlights that there is no one-size-fit-all solution for heat mitigation at the neighborhood. In particular, maintaining a low building density should be prioritized, especially mitigating CUHIs. Moreover, it is more effective to prioritize urban irrigation maintenance over increasing green cover in arid regions but the opposite in humid regions. The work can provide scientific evidence to support developing general and regional guidelines for urban heat mitigation.

Imprint of urbanization on snow precipitation over the continental USA

Urbanization can alter the local climate through modifications in land-atmosphere feedback. However, a continental scale evaluation of its influence on precipitation phase remains unknown. Here, we assess the difference in the likelihood of snow dominated events (SDEs) over 7,415 urban and surrounding non-urban (buffer) regions across the continental United States. Among 4,856 urban-buffer pairs that received at least five SDEs per year, 81% of urban regions are characterized by a smaller snow probability, 99% by a lower frequency of SDEs, and 57% by faster declining trends in SDEs compared to their buffer counterparts. Notably, urban (buffer) regions with lower snow probability are often characterized by higher net incoming and sensible energy fluxes as compared to buffer (urban) regions, thus highlighting the influence of land-energy feedback on precipitation phase. Results highlight a clear imprint of urbanization on precipitation phase and underscore the need to consider these influences while projecting hydro-meteorological risks.

Intensifying urban imprint on land surface warming: Insights from local to global scale

Increasing urbanization exacerbates surface energy balance perturbations and the health risks of climate warming; however, it has not been determined whether urban-induced warming and attributions vary from local, regional, to global scale. Here, the local surface urban heat island (SUHI) is evidenced to manifest with an annual daily mean intensity of 0.99°C-1.10°C during 2003-2018 using satellite observations over 536 cities worldwide. Spatiotemporal patterns and mechanisms of SUHI tightly link with climate-vegetation conditions, with regional warming effect reaching up to 0.015°C-0.138°C (annual average) due to surface energy alterations. Globally, the SUHI footprint of 1,860 cities approximates to 1% of the terrestrial lands, about 1.8-2.9 times far beyond the urban impervious areas, suggesting the enlargements of the imprint of urban warming from local to global scales. With continuous development of urbanization, the implications for SUHI-added warming and scaling effects are considerably important on accelerating global warming.

Urban heat mitigation by green and blue infrastructure: Drivers, effectiveness, and future needs

The combination of urbanization and global warming leads to urban overheating and compounds the frequency and intensity of extreme heat events due to climate change. Yet, the risk of urban overheating can be mitigated by urban green-blue-grey infrastructure (GBGI), such as parks, wetlands, and engineered greening, which have the potential to effectively reduce summer air temperatures. Despite many reviews, the evidence bases on quantified GBGI cooling benefits remains partial and the practical recommendations for implementation are unclear. This systematic literature review synthesizes the evidence base for heat mitigation and related co-benefits, identifies knowledge gaps, and proposes recommendations for their implementation to maximize their benefits. After screening 27,486 papers, 202 were reviewed, based on 51 GBGI types categorized under 10 main divisions. Certain GBGI (green walls, parks, street trees) have been well researched for their urban cooling capabilities. However, several other GBGI have received negligible (zoological garden, golf course, estuary) or minimal (private garden, allotment) attention. The most efficient air cooling was observed in botanical gardens (5.0 ± 3.5°C), wetlands (4.9 ± 3.2°C), green walls (4.1 ± 4.2°C), street trees (3.8 ± 3.1°C), and vegetated balconies (3.8 ± 2.7°C). Under changing climate conditions (2070-2100) with consideration of RCP8.5, there is a shift in climate subtypes, either within the same climate zone (e.g., Dfa to Dfb and Cfb to Cfa) or across other climate zones (e.g., Dfb [continental warm-summer humid] to BSk [dry, cold semi-arid] and Cwa [temperate] to Am [tropical]). These shifts may result in lower efficiency for the current GBGI in the future. Given the importance of multiple services, it is crucial to balance their functionality, cooling performance, and other related co-benefits when planning for the future GBGI. This global GBGI heat mitigation inventory can assist policymakers and urban planners in prioritizing effective interventions to reduce the risk of urban overheating, filling research gaps, and promoting community resilience.

Study on spatiotemporal dynamic characteristics of precipitation and causes of waterlogging based on a data-driven framework

The discernible alterations in regional precipitation patterns, influenced by the intersecting factors of urbanization and climate change, exert a substantial impact on urban flood disasters. Based on multi-source precipitation data, a data-driven model fusion framework was constructed to analyze the spatial and temporal dynamic distribution characteristics of precipitation in Beijing. Wavelet analysis method was used to reveal the periodic variation characteristics and multi-scale effects of precipitation, and the machine learning method was used to characterize the spatiotemporal dynamic change pattern of precipitation. Finally, geographical detector was used to explore the causes of waterlogging in Beijing. The research outcomes reveal a disparate distribution of precipitation across the year, with 78 % of the total precipitation occurring during the flood season. The principal periodic cycles observed in annual cumulative precipitation (ACP) were identified at 21, 13, and 9-year intervals. Spatially, while a decreasing trend in precipitation was observed in most areas of Beijing, 63.4 % of the region exhibited an escalating concentration trend, thereby heightening the risk of urban waterlogging. Machine learning model clustering elucidated three predominant spatial dynamic distribution patterns of precipitation in Beijing. The utilization of web crawler technology to acquire water accumulation data addressed challenges in obtaining urban waterlogging data, and validation through Landsat8 images enhanced data reliability and authenticity. Factor detection shows that road network density, topography, and precipitation were the main factors affecting urban waterlogging. These findings hold significant implications for informing flood control strategies and emergency management protocols in urban areas across China.

The effects of urban thermal heterogeneity and feather coloration on oxidative stress and metabolism of pigeons (Columba livia)

Urbanization stands out as a significant anthropogenic factor, exerting selective pressures on ecosystems and biotic components. A notable outcome of urbanization is thermal heterogeneity where the emergence of Urban Heat Islands is characterized by elevated air and surface temperatures compared to adjacent rural areas. Investigating the influence of thermal heterogeneity on urban animals could offer insights into how temperature variations can lead to phenotypic shifts. Urban pigeons (Columba livia) serve as an excellent model for studying urban thermal effects, given the melanism variations, which are associated with the pleiotropy of the melanocortin system. To examine the development of physiological plasticity in response to urban thermal variations, we conducted a study on pigeons in Santiago, Chile, during the rainy season. We assessed the influence of habitat on physiological traits related to metabolism and antioxidant capacities, which are theoretically affected by feather coloration. Our findings reveal that variations in melanism significantly impact pigeon physiology, affecting both antioxidant capacities and the mitochondrial activity of red blood cells. It was found that higher urban temperatures, from both the current sampling month and the prior sampling month (from CRU TS dataset), were negatively and strongly associated with lower antioxidant and metabolic activities. This suggests that elevated urban temperatures likely benefit the energetic budgets of pigeon populations and mitigate the negative effects of oxidative metabolism, with differential effects depending on feather colorations.

Street trees provide an opportunity to mitigate urban heat and reduce risk of high heat exposure

Climate change is exacerbating the need for urban greening and the associated environmental and human well-being benefits. Trees can help mitigate urban heat, but more detailed understanding of cooling effects of green infrastructure are needed to guide management decisions and deploy trees as effective and equitable climate adaptation infrastructure. We investigated how urban trees affect summer air temperature along sidewalks within a neighborhood of Tacoma, Washington, USA, and to what extent urban trees reduce risks of high summer temperatures (i.e., the levels regulated by state outdoor heat exposure rules intended to reduce heat-related illnesses). Air temperature varied by 2.57 °C, on average, across our study area, and the probability of daytime temperatures exceeding regulated high temperature thresholds was up to five times greater in locations with no canopy cover within 10 m compared to those with 100% cover. Air temperatures decreased linearly with increasing cover within 10 m, suggesting that every unit of added tree cover can help cool the air. Our findings highlight the value of trees in mitigating urban heat, especially given expected warming with climate change. Protecting existing urban trees and increasing tree cover (e.g., by planting street trees), are important actions to enhance climate change resilience of urban areas.

Greater local cooling effects of trees across globally distributed urban green spaces

Urban green spaces (UGS) are an effective mitigation strategy for urban heat islands (UHIs) through their evapotranspiration and shading effects. Yet, the extent to which local UGS cooling effects vary across different background climates, plant characteristics and urban settings across global cities is not well understood. This study analysed 265 local air temperature (TA) measurements from 58 published studies across globally distributed sites to infer the potential influence of background climate, plant and urban variables among different UGS types (trees, grass, green roofs and walls). We show that trees were more effective at reducing local TA, with reductions 2-3 times greater than grass and green roofs and walls. We use a hierarchical linear mixed effects model to reveal that background climate (mean annual temperature) and plant characteristics (specific leaf area vegetation index) had the greatest influence on cooling effects across UGS types, while urban characteristics did not significantly influence the cooling effects of UGS. Notably, trees dominated the overall local cooling effects across global cities, indicating that greater tree growth in mild climates with lower mean annual temperatures has the greatest mitigation potential against UHIs. Our findings provide insights for urban heat mitigation using UGS interventions, particularly trees across cities worldwide with diverse climatic and environmental conditions and highlight the essential role of trees in creating healthy urban living environments for citizens under extreme weather conditions.

Spatiotemporal patterns and drivers of the urban air pollution island effect for 2273 cities in China

Air pollution levels tend to be higher in urban areas than in surrounding rural areas, and this air pollution has a negative effect on human health. However, the spatiotemporal patterns of urban-rural air pollution differences and the determinants of these differences remain unclear. Here, we calculate the Urban Air Pollution Island (UAPI) intensity for PM2.5 and PM10 on a monthly, seasonal, and annual scale for 2273 cities in China from 2000 to 2020. Subsequently, we analyze the influence of urban characteristics using a combined approach of a two-way fixed effects model and a spatial Durbin model. Results show a strong downward trend in the UAPI intensity since 2013, with reductions ranging from 42 % to 61 % until 2020, for both pollutants and in summer as well as winter. Consistently, the proportion of the cities experiencing the UAPI phenomenon decreased from 94.5 % to 77.3 % for both PM2.5 and PM10. We find a significant influence of urban morphology on UAPI. Specifically, urban sprawl, polycentric development, and an increase in urban green spaces are associated with a reduction in UAPI, while dense urban areas intensify it. Our study also reveals a robust inverted U-shaped relationship between stages of economic development and UAPI. Moreover, economic development and air pollution itself show spillover effects that oppose their direct impacts. These results suggest that urban and regional planning and more ambitious climate change mitigation policies could be more effective strategies for mitigating air pollution in cities than end-of-pipe control.

Diurnal variation in the urban thermal environment and its relationship to human activities in China: a Tencent location-based service geographic big data perspective

The main factor of the formation and deterioration in China's urban thermal environment is human activity, which is difficult to describe and measure. A new perspective on the effect of human activity on the urban thermal environment can be obtained by examining the interaction between location-based service (LBS) data and the urban thermal environment in China. However, relevant research is still limited. In this study, we used Tencent LBS data, Terra/Aqua MODIS land surface temperature (LST) data, and land use data to investigate the relationship between LBS and the urban thermal environment, specifically the LST and surface urban heat island intensity (SUHII) across China and its provinces. Our results showed that (1) in summer, the heat island effect was an issue in 94% of the urban areas in China, which was worse during the day. The high- and low-value periods of LBS data on a given day coincided with the acquisition times of MODIS LST products during the day and at night, respectively. (2) During both the day and at night, there was a significant connection between LBS data and the urban thermal environment in China. The highest correlation coefficient (r) between LBS data and the LST could reach 0.55 (p < 0.01) at the provincial level, and the highest correlation coefficient (r) between LBS data and the SUHII could reach 0.78 (p < 0.01) at the provincial level. (3) The urban thermal environment diurnal difference and LBS data exhibited a significant relationship. The ΔLBS diurnal differences were significantly positively related to the SUHII diurnal differences in China. The overall study findings revealed that LBS data constitute an important parameter to represent the human activity intensity when investigating the formation of the urban thermal environment in China.

Heterogeneous effects of the availability and spatial configuration of urban green spaces on their cooling effects in China

The impacts of the availability and spatial configuration of urban green spaces (UGS) on their cooling effects can vary with background climate conditions. However, large-scale studies that assess the potential heterogeneous relationships of UGS availability and spatial configuration with urban thermal environment are still lacking. In this study, we investigated the impacts of UGS availability and spatial configuration on urban land surface temperature (LST) taking 306 cities in China as a case study covering a multi-biome-scale. We first calculated the availability of surrounding UGS for urban built-up pixels in each city using a distance-weighted approach, and its spatial configuration was quantified through the Gini coefficient. Then, we employed various regression models to explore how the impacts of UGS availability and the Gini coefficient on LST varies across different LST quantiles and between day- and nighttime. The results revealed that UGS availability was negatively associated with both daytime and nighttime LST, while the Gini coefficient showed a positive impact solely on daytime LST, indicating that an adequate and equally distributed UGS contributes to lower environmental temperatures during the daytime. Furthermore, the impact of UGS availability on LST decreased during both day- and nighttime with increased background LST quantiles. Whereas the impact of the Gini coefficient increased only with daytime LST quantile levels, with its effect remaining almost insignificant during the night. Our findings provide new insights into the impacts of UGS on urban thermal environment, offering significant implications for urban green infrastructure planning aiming at lowering the urban heat island.

Mapping impervious surface area increase and urban pluvial flooding using Sentinel Application Platform (SNAP) and remote sensing data

Expansion of urban impervious surface (UIA) and increased urban pluvial flooding (UPF) have an impact on urban dynamics, socioeconomic activities, and our environment. Therefore, monitoring the increase in UIS and its effect on UPF is essential. The notion of this research is based on the mapping of impervious surface area increase in three major cities of Pakistan. There were two key objectives: (i) Mapping impervious surface area growth using the global impervious surface area index (GISAI) on Google Earth Engine from 1992 to 2022 and (ii) mapping the pluvial flood extent in selected urban areas using Sentinel-1 Ground Range Detected (GRD) data. Thus, we have utilized the GISAI for mapping urban impervious surface area (UISA) using Landsat time-series data on GEE. Our research findings revealed that about 16.8%, 23.5%, and 16.4% of the impervious surface have been increased in Islamabad, Lahore, and Karachi, respectively. Also, Lahore city has the highest overall accuracy, aiming at the GISAI of 93%, followed by Karachi and Islamabad with an overall accuracy of 86% and 85%, respectively. The results indicated that urban flooding has occurred in those areas where the ISA has grown during the last three decades. It shows significant changes in the impervious surface area that cause enhanced urban pluvial flooding in major cities of Pakistan. Also, Sentinel-1 data and the SNAP tool significantly mapped flooded areas in the selected zones. So, providing cities and local governments with increased quick flood detection capabilities is essential. It can also provide feasible policy recommendations for Pakistan decision-makers in city management. Therefore, we suggest a modeling-based solution to identify high-risk locations in major cities for upcoming UPF events.

Economic valuation of temperature-related mortality attributed to urban heat islands in European cities

As the climate warms, increasing heat-related health risks are expected, and can be exacerbated by the urban heat island (UHI) effect. UHIs can also offer protection against cold weather, but a clear quantification of their impacts on human health across diverse cities and seasons is still being explored. Here we provide a 500 m resolution assessment of mortality risks associated with UHIs for 85 European cities in 2015-2017. Acute impacts are found during heat extremes, with a 45% median increase in mortality risk associated with UHI, compared to a 7% decrease during cold extremes. However, protracted cold seasons result in greater integrated protective effects. On average, UHI-induced heat-/cold-related mortality is associated with economic impacts of €192/€ - 314 per adult urban inhabitant per year in Europe, comparable to air pollution and transit costs. These findings urge strategies aimed at designing healthier cities to consider the seasonality of UHI impacts, and to account for social costs, their controlling factors, and intra-urban variability.

Urban Versus Lake Impacts on Heat Stress and Its Disparities in a Shoreline City

Shoreline cities are influenced by both urban-scale processes and land-water interactions, with consequences on heat exposure and its disparities. Heat exposure studies over these cities have focused on air and skin temperature, even though moisture advection from water bodies can also modulate heat stress. Here, using an ensemble of model simulations covering Chicago, we find that Lake Michigan strongly reduces heat exposure (2.75°C reduction in maximum average air temperature in Chicago) and heat stress (maximum average wet bulb globe temperature reduced by 0.86°C) during the day, while urbanization enhances them at night (2.75 and 1.57°C increases in minimum average air and wet bulb globe temperature, respectively). We also demonstrate that urban and lake impacts on temperature (particularly skin temperature), including their extremes, and lake-to-land gradients, are stronger than the corresponding impacts on heat stress, partly due to humidity-related feedback. Likewise, environmental disparities across community areas in Chicago seen for skin temperature are much higher (1.29°C increase for maximum average values per $10,000 higher median income per capita) than disparities in air temperature (0.50°C increase) and wet bulb globe temperature (0.23°C increase). The results call for consistent use of physiologically relevant heat exposure metrics to accurately capture the public health implications of urbanization.

Water-energy-vegetation nexus explain global geographical variation in surface urban heat island intensity

Surface urban heat island (SUHI) is a key climate risk associated with urbanization. Previous case studies have suggested that precipitation (water), radiation (energy), and vegetation have important effects on urban warming, but there is a lack of research that combines these factors to explain the global geographic variation in SUHI intensity (SUHII). Here, we utilize remotely sensed and gridded datasets to propose a new water-energy-vegetation nexus concept that explains the global geographic variation of SUHII across four climate zones and seven major regions. We found that SUHII and its frequency increase from arid zones (0.36 ± 0.15 °C) to humid zones (2.28 ± 0.10 °C), but become weaker in the extreme humid zones (2.18 ± 0.15 °C). We revealed that from semi-arid/humid to humid zones, high precipitation is often coupled with high incoming solar radiation. The increased solar radiation can directly enhance the energy in the area, leading to higher SUHII and its frequency. Although solar radiation is high in arid zones (mainly in West, Central, and South Asia), water limitation leads to sparse natural vegetation, suppressing the cooling effect in rural areas and resulting in lower SUHII. In extreme humid regions (mainly in tropical areas), incoming solar radiation tends to flatten out, which, coupled with increased vegetation as hydrothermal conditions become more favorable, leads to more latent heat and reduces the intensity of SUHI. Overall, this study offers empirical evidence that the water-energy-vegetation nexus highly explains the global geographic variation of SUHII. The results can be used by urban planners seeking optimal SUHI mitigation strategies and for climate change modeling work.

Grading surface urban heat island and investigating factor weight based on interpretable deep learning model across global cities

Significant urbanization resulted in increasing surface urban heat island (SUHI) that caused negative impacts on urban ecological environment, and residential comfort. Accurately monitoring the spatiotemporal variations and understanding controls of SUHI were essential to propose effective mitigation measurements. However, SUHI grades across global cities remained unknown, which cloud greatly support for global mitigations. Additionally, quantitative evaluating factor weights for different SUHI indicators and grades worldwide remained further investigations. Therefore, this paper proposed SUHI grading based on agglomerative hierarchical clustering, and further quantified factor weights for different indicators and grades based on an interoperable machine learning named TabNet. There were three major findings. (1) Global cities were grouped into five grades, including SUCI (surface urban cool island), insignificant, low-value, medium-value, and high-value SUHI grades, indicating significant differences among different grades. SUHI grades showed significant climate-based variations, wherein the arid climate was dominated by the SUCI grade at daytime but the high-value grade at nighttime. (2) Vegetation difference was an important factor for daytime SUHII accounting for 27%. Daytime frequency of SUHI was controlled by vegetation difference, temperature, evaporation and nighttime light, accounting for 78%. The major factors for nighttime frequency were albedo differences and nighttime light, accounting for 45%. (3) Related factors contributed differently to various SUHI grades. The weight of △EVI for daytime SUHII gradually increased with grades, while it for daytime frequency and maximum duration of SUHI decreased with grades. The nighttime SUHII of the low-value grade was greatly affected by the background climate, while that of the medium-value and high-value grades were strongly impacted by anthropogenic heat flux. The diurnal contrast of grades and coupling effects with heat wave were further discussed. This paper aimed to provide information on grades and controls of SUHI for further mitigation proposal.

Inequality in behavioural heat adaptation: an empirical study with mobility data from the transport system in New York City, NY, USA

BACKGROUND

Heat exposure, which can negatively affect human health and wellbeing, is heterogeneous within US cities. However, little is known about who can avoid heat stress by adjusting their everyday behaviour. We aimed to analyse the effect of ambient temperature on mobility, specifically subway (ie, the underground railway system) use, in New York City, NY, USA, during 2014-19.

METHODS

For this empirical study, subway use across New York City was measured with turnstile data from the New York City Metropolitan Transportation Authority between Jan 1, 2014, and Dec 31, 2019. Passenger numbers were then aggregated to the zip code tabulation area (ZCTA) level. Daily observational climate data were obtained from the US National Weather Service between Jan 1, 2014, and Dec 31, 2019. Socioeconomic data at the ZCTA level originated from the American Community Survey 2019. We extracted data on population age, ethnicity, commuting, employment, median household income, rent, and health-insurance coverage. We used a fixed-effects panel-regression model to assess the influence of temperature on subway use in New York City, which was the main outcome of our study.

FINDINGS

We obtained data for 438 subway stations across New York City. After data cleaning and preprocessing, the final aggregated data sample consisted of 238 508 instances of subway use in 1955 days across 6 years for 122 ZCTAs, with 168 days missing in the raw data and 67 days removed as outliers. The results of the fixed-effects panel-regression analysis showed a strong, non-linear effect of daily maximum temperature on subway use. Subway use was highest at 11·5°C and substantially decreased for temperatures that were colder and warmer than that, with reductions reaching 6·5% (95% CI 2·5-10·5) for the coldest temperature (ie, -6·5°C) and 10·5% (6·0-14·0) for the hottest temperature (ie, 34·5°C). Reductions differed between weekdays and weekends, when residents generally had more freedom to adjust their behaviour. Neighbourhoods that were at a socioeconomic disadvantage experienced smaller or no reductions in mobility in heat; mobility increased in neighbourhoods with beach access.

INTERPRETATION

Our study showed that temperature had a strong, non-linear effect on subway use, but the magnitude of the effect on subway use was heterogeneous across areas of the city on warm days. Weaker avoidance of heat stress correlated with less privilege, indicating compounding health risks. Everyday behavioural adaptation to heat is therefore an effect pathway that contributes to unequal heat effects and should be explored in future research.

FUNDING

The Volkswagen Foundation and the Werner Siemens Foundation.

Global mapping of urban thermal anisotropy reveals substantial potential biases for remotely sensed urban climates

Urban thermal anisotropy (UTA) drastically impacts satellite-derived urban surface temperatures and fluxes, and consequently makes it difficult to gain a more comprehensive understanding of global urban climates. However, UTA patterns and associated biases in observed urban climate variables have not been investigated across an adequate number of global cities with diverse contexts; nor is it known whether there are globally measurable factors that are closely related to the UTA intensity (UTAI, quantified as the maximum difference between the nadir and off-nadir urban thermal radiation). Here we investigate the UTAI over more than 5500 cities worldwide using multi-angle land surface temperature (LST) observations from 2003 to 2021 provided by Moderate Resolution Imaging Spectroradiometer (MODIS). The results show that the global mean UTAI can reach 5.1, 2.7, 2.4, and 1.7 K during summer daytime, winter daytime, summer nighttime, and winter nighttime, respectively. Using nadir LST observations as a reference, our analysis reveals that UTA can lead to an underestimation of satellite-based urban surface sensible heat fluxes (H) by 45.4% and surface urban heat island intensity (Is) by 43.0% when using LST observations obtained from sensor viewing zenith angles (VZAs) of ±60°. Practitioners can limit the biases of H and Is within ±10% by using LSTs from sensor VZAs within ±30°. We also find that UTAI is closely related to urban impervious surface percentage and surface air temperature across global cities. These findings have implications for angular normalization of satellite-retrieved instantaneous LST observations across cities worldwide.

Climatic and Economic Background Determine the Disparities in Urbanites' Expressed Happiness during the Summer Heat

Climate-change-induced extreme weather events increase heat-related mortality and health risks for urbanites, which may also affect urbanites' expressed happiness (EH) and well-being. However, the links among EH, climate, and socioeconomic factors remain unclear. Here we collected ∼6 million geotagged tweets from 44 Chinese prefecture-level cities based on Sina Weibo and performed a quadratic regression model to explore the relationships between summer heat and EH. A three-stage analysis was developed to examine spatiotemporal heterogeneity and identify factors contributing to disparities in urbanites' EH. Results show that all cities exhibited a similar hump-shaped relationship, with an overall optimal temperature (OT) of 22.8 °C. The estimated OT varied geographically, with 25.3, 23.8, and 20.0 °C from north to south. Moreover, a 1 standard deviation increase in heatwave intensity was associated with a 0.813 (95% CI: 0.177, 1.449) standard deviation decrease in EH. Notably, within the geographic scope of this study, it was observed that urbanites in northern China and economically underdeveloped cities faced significantly lower heat risks during the summer heat. This research provides insight for future studies and practical applications concerning extreme weather events, urbanites' mental health, and sustainable urban development goal.

Global future population exposure to heatwaves

The increasing exposure to extreme heatwaves in urban areas from both climate change and the urban heat island (UHI) effect poses multiple threats and challenges to human society. Despite a growing number of studies focusing on extreme exposure, research advances are still limited in some aspects such as oversimplification of human exposure to heatwaves and neglect of perceived temperature as well as actual body comfort, resulting in unreliable and unrealistic estimates of future results. In addition, little research has performed comprehensive and fine-resolution global analyses in future scenarios. In this study, we present the first global fine-resolution projection of future changing urban population exposure to heatwaves by 2100 under four shared socioeconomic pathways (SSPs) considering urban expansion at global, regional, and national scales. Overall, global urban population exposure to heatwaves is rising under the four SSPs. Temperate and tropical zones predictably have the greatest exposure among all climate zones. Coastal cities are projected to have the greatest exposure, followed closely by cities at low altitudes. Middle-income countries have the lowest exposure and the lowest inequality of exposure among countries. Individual climate effects contributed the most (approximately 46.4%) to future changes in exposure, followed by the interactive effect between climate and urbanization (approximately 18.5%). Our results indicate that more attention needs to be paid to policy improvements and sustainable development planning of global coastal cities and some low-altitude cities, especially in low- and high-income countries. Meanwhile, this study also highlights the impact of continued future urban expansion on population exposure to heatwaves.

Measuring the relationships between various urban green spaces and local climate zones

Urban green spaces (UGS) improve living conditions in cities by mitigating the Urban Heat Island effect. While the cooling effect of UGS seems unequivocal, the relationship between the types of UGS and types of residential areas has not yet been well explored. In this study, we systematically analysed the cooling effect of 71 UGS in Prague, a central European city, on residential areas within 400 m of the UGS. The UGS are classified according to their spatial characteristics (size, shape, and tree density), and the residential areas according to three Local Climate Zones (LCZ 2, 5, 6) typical for European cities. The cooling effect is evaluated using a regression model of the Land Surface Temperature (LST) in residential zones according to the LCZ type and distance from the various UGS. The results show that compact UGS of 10-25 ha with dense trees have the most pronounced cooling effect. This type of UGS was associated with a mean decrease in LST within 400 m of 2.3 °C compared to the least effective UGS type (long with sparse trees) across LCZs. The results of the presented study can be applied in urban planning and urban design to improve microclimates in cities.

Variations in land surface temperatures in small-scale urban areas in Vietnam during Covid-19 restrictions: Case studies from Da Nang, Hue and Vinh City

Land surface temperature (LST) is an important variable in urban microclimate research. At the end of 2019, the emergence of Covid-19 pandemic has changed the world in a manner that forced many countries to impose restrictions in human activities. As a measure to prevent the expansion of Covid-19 infections, most of the major cities have entered a prolonged lockdown period and reduction in human activities between the early 2020 and the late 2021. These restrictions were strict in most of the cities in Southeast Asia, particularly in Vietnam. The present study investigated the variations in LST and NDVI observed in three rapidly growing urban areas, namely Da Nang, Hue and Vinh, in Vietnam using Landsat-8 imagery acquired between 2017 and 2022. There has been a slight reduction in LST in the study sites, particularly in Da Nang City, during the lockdown period but not as high as observed in recently conducted studies from big metropolitan cities, including in Vietnam. It is also observed that LST estimated from built-up areas and other impervious surfaces remained relatively stable during the study period which is similar to the results from recent studies.

Increased heat risk in wet climate induced by urban humid heat

Cities are generally warmer than their adjacent rural land, a phenomenon known as the urban heat island (UHI). Often accompanying the UHI effect is another phenomenon called the urban dry island (UDI), whereby the humidity of urban land is lower than that of the surrounding rural land^1-3. The UHI exacerbates heat stress on urban residents^4,5, whereas the UDI may instead provide relief because the human body can cope with hot conditions better at lower humidity through perspiration^6,7. The relative balance between the UHI and the UDI-as measured by changes in the wet-bulb temperature (T_w)-is a key yet largely unknown determinant of human heat stress in urban climates. Here we show that T_w is reduced in cities in dry and moderately wet climates, where the UDI more than offsets the UHI, but increased in wet climates (summer precipitation of more than 570 millimetres). Our results arise from analysis of urban and rural weather station data across the world and calculations with an urban climate model. In wet climates, the urban daytime T_w is 0.17 ± 0.14 degrees Celsius (mean ± 1 standard deviation) higher than rural T_w in the summer, primarily because of a weaker dynamic mixing in urban air. This T_w increment is small, but because of the high background T_w in wet climates, it is enough to cause two to six extra dangerous heat-stress days per summer for urban residents under current climate conditions. The risk of extreme humid heat is projected to increase in the future, and these urban effects may further amplify the risk.

Did the Covid-19 restrictions influence land surface temperatures in Southeast Asia? A study from Ho Chi Minh City, Vietnam

There have been a prolonged lockdown period and reduction in human activities in most of the major cities in the world during the Covid-19 pandemic period between the early 2020 and the late 2021. Such a reduction in human activities was believed to have influenced pollution levels and land surface temperatures (LST) in urban areas. This paper describes the variations in LSTs before, during and after the Covid-19 lockdown in Ho Chi Minh City in southern Vietnam, which is the economic hub of the country. For this purpose, Landsat-8 OLI and TIRS images acquired between 2015 and 2022 were used. It is observed that there was a significant reduction of 1 to 1.8 °C in LST in open areas, excepting impervious surfaces and built-up areas, during the strict lockdown period in Ho Chi Minh City, and an increase in LST since then. The observed reduction in LST during the lockdown period in Ho Chi Minh City is in agreement with the reduction in greenhouses gases during the same period in recent studies. Human mobility and industrial activities have been restored in November 2021 in the study area which would explain the regain in LST in the post-lockdown period.

Urban insect bioarks of the 21st century

Insects exhibit divergent biodiversity responses to cities. Many urban populations are not at equilibrium: biodiversity decline or recovery from environmental perturbation is often still in progress. Substantial variation in urban biodiversity patterns suggests the need to understand its mechanistic basis. In addition, current urban infrastructure decisions might profoundly influence future biodiversity trends. Although many nature-based solutions to urban climate problems also support urban insect biodiversity, trade-offs are possible and should be avoided to maximize biodiversity-climate cobenefits. Because insects are coping with the dual threats of urbanization and climate change, there is an urgent need to design cities that facilitate persistence within the city footprint or facilitate compensatory responses to global climate change as species transit through the city footprint.

Tropical surface urban heat islands in east Africa

The horn of Africa is susceptible to droughts because of the persistent heat waves and insufficient precipitation. The growth of urban population and built-up urban environments exacerbate the overheating problems due to the urban heat island effects. Understanding the impacts of anthropogenic activities in such dry environments is important to control or mitigate extreme heat leading to droughts. This is required to preserve soil moisture, pothole waters, lakes and rivers that are required for pasture and drinking water. Nonetheless, the intensity and duration of the urban heat island effects have not been investigated in this region resulting in the underestimation of the intensity and severity of the extreme heat events. This study therefore performs the quantitative analyses of the intensity, duration and causality of the tropical surface urban heat islands (TSUHIs) for the first time using earth observation information at a regional to local scale. It also identifies the factors that control TSUHIs, considering background climate, population, vegetation and the impervious urban fractions. Results showed that the TSUHI in the capital cities of tropical east Africa varies from 1 [Formula: see text]C in Dodoma to 4 [Formula: see text]C in Kampala and reaches up to 8 [Formula: see text]C in Khartoum. The mean temperature contribution to regional climate from 2000 to 2020 is 0.64 [Formula: see text]C during the day and 0.34 [Formula: see text]C during the night, a mean total of around 0.5 [Formula: see text]C, a 0.25 [Formula: see text]C increase per decade. This is a quarter of the increase in global surface temperature, which is [Formula: see text] 1.09 [Formula: see text]C from 2011 to 2020 compared to the 1850-1900 level. Most of these capital cities in this region exhibited high TSUHIs from late summer to winter and are dependent on mainly population, vegetation, evapotranspiration and soil moisture in different proportions. This urban induced additional temperature has been intensifying droughts in tropical east Africa. Therefore, urban planners are advised to consider the impacts of TSUHIs to reduce the severity of droughts in the tropical east Africa region.

Can retro-reflective materials replace diffuse highly reflective materials for urban buildings’ wall to improve outdoor thermal comfort?

In recent years, there have been numerous studies on the application of retroreflective (RR) materials to exterior building walls to relieve the urban heat island (UHI) phenomenon and save building energy consumption instead of diffuse highly reflective (DHR) materials. Experimental measurements were undertaken to investigate the impact of applying DHR and RR materials to building exterior walls on the outdoor thermal environment. DHR and RR walls were tested with three canyon aspect ratios ( H / D ) of 0.5, 1.0, and 1.5, respectively, with seven environmental indexes recorded and compared, including air temperature ( T a ), relative humidity ( R H ), sol-air temperature ( S A T ), operative temperature ( O T ), standard effective temperature ( S E T * ), change in operative temperature ( C O T ), and real-time solar reflectance ( ρ ). The results show that the RR wall is more effective in improving the outdoor thermal environment, where S A T decreased by 4.5 °C, S E T * decreased by 0.5 °C, and COT decreased by 1.2 °C, on average, while it can also improve the real-time solar reflectance ( ρ ) by 12% on average compared to the DHR wall. Moreover, it gets more effective in scenarios with a higher canyon aspect ratio.

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.

Integrating CFD-GIS modelling to refine urban heat and thermal comfort assessment

Constant urban growth exacerbates the demand for residential, commercial and traffic areas, leading to progressive surface sealing and urban densification. With climate change altering precipitation and temperature patterns worldwide, cities are exposed to multiple risks, demanding holistic and anticipatory urban planning strategies and adaptive measures that are multi-beneficial. Sustainable urban planning requires comprehensive tools that account for different aspects and boundary conditions and are capable of mapping and assessing crucial processes of land-atmosphere interactions and the impacts of adaptation measures on the urban climate system. Here, we combine Computational Fluid Dynamics (CFD) and Geographic Information System (GIS) capabilities to refine an existing 2D urban micro- and bioclimatic modelling approach. In particular, we account for the vertical and horizontal variability in wind speed and air temperature patterns in the urban canopy layer. Our results highlight the importance of variability of these patterns in analysing urban heat development, intensity and thermal comfort at multiple heights from the ground surface. Neglecting vertical and horizontal variability, non-integrated CFD modelling underestimates mean land surface temperature by 7.8 °C and the Universal Thermal Climate Index by 6.9 °C compared to CFD-integrated modelling. Due to the strong implications of wind and air temperature patterns on the relationship between surface temperature and human thermal comfort, we urge caution when relying on studies solely based on surface temperatures for urban heat assessment and hot spot analysis as this could lead to misinterpretations of hot and cool spots in cities and, thus, mask the anticipated effects of adaptation measures. The integrated CFD-GIS modelling approach, which we demonstrate, improves urban climate studies and supports more comprehensive assessments of urban heat and human thermal comfort to sustainably develop resilient cities.

A comparison study on the role of urbanization in altering the short-duration and long-duration intense rainfall

Urbanization has significantly changed the regional hydrological cycle and energy balance. However, the different roles of urbanization on intense rainfall with short and long persistence need a better understanding, particularly in coastal mega cities with complex terrains. In this study, we compared the spatial and diurnal characteristics of intense rainfall across two coastal cities with different degrees of urbanization with 70 meteorological stations. The effects of anthropogenic and geographical factors on short-duration intense rainfall (SDIR) and long-duration intense rainfall (LDIR) were investigated using the statistical method. SDIR and LDIR events show different spatial patterns that SDIR events center in the highly urbanized regions while LDIR events center in the coastal mountainous regions. In terms of diurnal features, it is found that the higher occurrence frequency of SDIR in the dense urban region than that in suburbs occurs over the period with strong urban heat island intensity (UHII). It indicated that thermal contrast between urban and suburbs breeds an atmospheric environment for inspiriting the convection and SDIR events. The urban-induced increase in SDIR events depended on urbanization stages, with only dense urban regions showing a significant influence. The results of geographical detector model (GDM) also demonstrated that the synergy of build-up area and population explained 48 %-51 % of spatial heterogeneity of SDIR. Nevertheless, urbanization has little effect in modifying the diurnal features of LDIR events, while it might influence spatial rainfall patterns by enhancing rainfall peaks. The GDM results indicated that terrain positively dominates the spatial distribution for LDIR events, and the interactions of multi-factors (terrain, urbanization, or distance to the coast et al.) have enhanced explanatory power (q values up to 0.70). The results provide a fundamental understanding for the effects of anthropogenic and geographical factors on different types of rainfall events in coastal mega cities.

Intraday adaptation to extreme temperatures in outdoor activity

Linkages between climate and human activity are often calibrated at daily or monthly resolutions, which lacks the granularity to observe intraday adaptation behaviors. Ignoring this adaptation margin could mischaracterize the health consequences of future climate change. Here, we construct an hourly outdoor leisure activity database using billions of cell phone location requests in 10,499 parks in 2017 all over China to investigate the within-day outdoor activity rhythm. We find that hourly temperatures above 30 °C and 35 °C depress outdoor leisure activities by 5% (95% confidence interval, CI 3-7%) and by 13% (95% CI 10-16%) respectively. This activity-depressing effect is larger than previous daily or monthly studies due to intraday activity substitution from noon and afternoon to morning and evening. Intraday adaptation is larger for locations and dates with time flexibility, for individuals more frequently exposed to heat, and for parks situated in urban areas. Such within-day adaptation substantially reduces heat exposure, yet it also delays the active time at night by about half an hour, with potential side effect on sleep quality. Combining empirical estimates with outputs from downscaled climate models, we show that unmitigated climate change will generate sizable activity-depressing and activity-delaying effects in summer when projected on an hourly resolution. Our findings call for more attention in leveraging real-time activity data to understand intraday adaptation behaviors and their associated health consequences in climate change research.

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.

A multi-perspective study of atmospheric urban heat island effect in China based on national meteorological observations: Facts and uncertainties

The atmospheric urban heat island (AUHI) effect, traditionally measured by in-situ sensors mounted on fixed meteorological stations, has been extensively studied by different and imperfect methods. However, facts and uncertainties of the AUHI estimates revealed by the different methods are not well understood at a large scale. Here we examined the spatial-temporal variations of the AUHI effects from multiple perspectives in China's 86 large cities as revealed by national-level meteorological observations at 2-m height from 1981 to 2017. We find relatively consistent patterns of larger urban heating effects in daily minimum temperature, winter, and Northeast China than their counterparts in terms of multiyear mean intensity (AUHII), long-term trend (△AUHII), and contribution to local warming (according to the CTRUMR "urban minus rural" and CTROMR "observation minus reanalysis" methods). Concurrently, a cooling impact or a reduction in the heating effect has been observed in some cities randomly, especially in daily maximum temperature. On average across cities, the AUHII, △AUHI, CTRUMR, and CTROMR for the daily mean temperature amount to 0.33 °C, 0.013 °C 10a-1, 53 %, and 23 % at an annual mean time scale, respectively. Nevertheless, the poor representativeness of weather stations, discrepancies among the quantification methods, nonlinearity of the long-term tendencies, and coupling effects with rural crop land use activities lead to large uncertainties of the AUHI estimates. Our results emphasize the limitations of national-level meteorological stations in characterizing AUHI in China and suggest that the urban heat island remains a "well described but rather poorly understood" phenomenon warranting further investigation by a combined uses of multiple techniques like high-density sensor networks, remote sensing techniques, and high-resolution numerical models.

Regional thermal environment changes: Integration of satellite data and land use/land cover

Land surface temperature (LST) is subject to location and environmental influences, which makes quantification difficult in terms of timeliness. Based on 10-d geostationary satellite LST TCI products, we quantitatively evaluated the thermal environment differentiation of various ground objects in North, South, and Northwest China from 2017 to 2021. We found that the thermal condition index (TCI) in Northwest China decreased, whereas it increased in North and South China. In contrast, Moran's I index increased in Northwest and South China, with strong spatial agglomeration. The TCI for artificial surfaces decreased from North (0.633) to Northwest (0.554) and South China (0.384). The bare land TCI was always the lowest among the land use/land cover (LULC) types in each region. Our results reflect the LULC thermal environment of China against the background of new urbanization and provide theoretical support for scientific planning to improve the ecological environment.

Does city-water layout matter? Comparing the cooling effects of water bodies across 34 Chinese megacities

As most cities are located around or near waterbodies, it is essential to assess the thermal effect of these waterbodies. This research focuses on 34 Chinese megacities as case studies to examine the spatial relationship between city-water layout and the thermal effect of waterbodies. Landsat-8 remote-sensing images acquired around noontime in summer were used to retrieve land surface temperatures (LST) and classify land cover. The results show that there are three types of city-water layout. For most cities, waterbodies have a cooling effect, and their mean cooling distance (ΔL_max) ranges from 431 m to 1350 m, with the maximum temperature difference (ΔT_max) ranging from - 2.21 °C to 7.83 °C. The cooling effect of waterbodies is also influenced by their spatial distribution, size, location, and background climate regions. The larger the percentage or area of waterbodies in a city, the shorter ΔL_max and the bigger ΔT_max. Waterbodies have the longest ΔL_max and the smallest ΔT_max when they are dispersed within the city, whereas they have the shortest ΔL_max and the largest ΔT_max when they are flowing through the city. The results suggest that the thermal effects of waterbodies should be seriously considered by urban planners to improve the urban microclimate.

Anthropogenic effects on the body size of two neotropical orchid bees

To accommodate an ever-increasing human population, agriculture is rapidly intensifying at the expense of natural habitat, with negative and widely reported effects on biodiversity in general and on wild bee abundance and diversity in particular. Cities are similarly increasing in area, though the impact of urbanisation on wild bees is more equivocal and potentially positive in northern temperate regions. Yet agriculture and urbanisation both lead to the loss and alteration of natural habitat, its fragmentation, a potential reduction in floral availability, and warmer temperatures, factors thought to be drivers of wild bee decline. They have also been shown to be factors to which wild bee populations respond through morphological change. Body size is one such trait that, because of its relation to individual fitness, has received growing attention as a morphological feature that responds to human induced modification in land use. Here, we investigated the change in body size of two sympatric orchid bee species on the Yucatan Peninsula of Mexico in response to urbanization and agricultural intensification. By measuring 540 male individuals sampled from overall 24 sites, we found that Euglossa dilemma and Euglossa viridissima were on average smaller in urban and agricultural habitats than in natural ones. We discuss the potential role of reduced availability of resources in driving the observed body size shifts. Agricultural and urban land management in tropical regions might benefit wild bees if it encompassed the planting of flowering herbs and trees to enhance their conservation.

Natural-anthropogenic environment interactively causes the surface urban heat island intensity variations in global climate zones

The inconstant climate change and rapid urbanization substantially disturb the global thermal balance and induce severe urban heat island (UHI) effect, adversely impacting human development and health. Existing literature has revealed the UHI characteristics and driving factors at an urban scale, but interactions between the main factors of a global grid scale assessment on the context of climate zones remain unclear. Therefore, based on the multidimensional climatic and socio-economic statistical datasets, the multi-time scale of surface urban heat island intensity (SUHI) characteristics was investigated in this study to analyze how natural-anthropogenic drivers affect the variance of SUHI and vary in their importance for the changes of other interaction factors. The results show that the mean value of SUHI in summer is higher than in winter, and in daytime is higher than in nighttime on a seasonal and daily scale. SUHIs in different global climate zones have significant differences. When analyzing drivers' contributions and interactions with LightGBM model and SHAP algorithm, we know that monthly precipitation (PREC), the estimated population (POP) and surface pressure (PRES) are the three major drivers of daytime SUHI. The nighttime SUHI is mainly PREC, POP and anthropogenic heat emission (AHE), the influence rules of the natural driversare mostly opposite to that of daytime. This study highlights the fundamental role of background climate for designing strategies. Irrigation or artificial rainfall will be effective to mitigate SUHI in low rainfall areas, while it is more effective to reduce AHE in high rainfall areas. In where greening can be difficult in the most developed cities, reducing AHE, increasing per capita GDP and controlling the population scale may also contribute to alleviating the SUHI. This study provides ideas for developing responsive urban heat island mitigation policies in a more realistic setting.

Crown dieback and mortality of urban trees linked to heatwaves during extreme drought

Cities have been described as 'heat islands' and 'dry islands' due to hotter, drier air in urban areas, relative to the surrounding landscape. As climate change intensifies, the health of urban trees will be increasingly impacted. Here, we posed the question: Is it possible to predict urban tree species mortality using (1) species climate envelopes and (2) plant functional traits? To answer these, we tracked patterns of crown dieback and recovery for 23 common urban tree and shrub species in Sydney, Australia during the record-breaking austral 2019-2020 summer. We identified 10 heat-tolerant species including five native and five exotic species, which represent climate-resilient options for urban plantings that are likely to continue to thrive for decades. Thirteen species were considered vulnerable to adverse conditions due to their mortality, poor health leading to tree removal, and/or extensive crown dieback. Crown dieback increased with increasing precipitation of the driest month of species climate of origin, suggesting that species from dry climates may be better suited for urban forests in future climates. We effectively grouped species according to their drought strategy (i.e., tolerance versus avoidance) using a simple trait-based framework that was directly linked with species mortality. The seven most climate-vulnerable species used a drought-avoidance strategy, having low wood density and high turgor loss points along with large, thin leaves with low heat tolerance. Overall, plant functional traits were better than species climate envelopes at explaining crown dieback. Recovery after stress required two mild, wet years for most species, resulting in prolonged loss of cooling benefits as well as economic losses due to replacement of dead/damaged trees. Hotter, longer, and more frequent heatwaves will require selection of more climate-resilient species in urban forests, and our results suggest that future research should focus on plant thermal traits to improve prediction models and species selection.

An Ethical Framework for Artificial Intelligence and Sustainable Cities

The digital revolution has brought ethical crossroads of technology and behavior, especially in the realm of sustainable cities. The need for a comprehensive and constructive ethical framework is emerging as digital platforms encounter trouble to articulate the transformations required to accomplish the sustainable development goal (SDG) 11 (on sustainable cities), and the remainder of the related SDGs. The unequal structure of the global system leads to dynamic and systemic problems, which have a more significant impact on those that are most vulnerable. Ethical frameworks based only on the individual level are no longer sufficient as they lack the necessary articulation to provide solutions to the new systemic challenges. A new ethical vision of digitalization must comprise the understanding of the scales and complex interconnections among SDGs and the ongoing socioeconomic and industrial revolutions. Many of the current social systems are internally fragile and very sensitive to external factors and threats, which lead to unethical situations. Furthermore, the multilayered net-like social tissue generates clusters of influence and leadership that prevent communities from a proper development. Digital technology has also had an impact at the individual level, posing several risks including a more homogeneous and predictable humankind. To preserve the core of humanity, we propose an ethical framework to empower individuals centered on the cities and interconnected with the socioeconomic ecosystem and the environment through the complex relationships of the SDGs. Only by combining human-centered and collectiveness-oriented digital development will it be possible to construct new social models and interactions that are ethical. Thus, it is necessary to combine ethical principles with the digital innovation undergoing in all the dimensions of sustainability.