Urban heat island: Aerodynamics or imperviousness?

Urban development pattern's influence on extreme rainfall occurrences

Growing urban population and the distinct strategies to accommodate them lead to diverse urban development patterns worldwide. While local evidence suggests the presence of urban signatures in rainfall anomalies, there is limited understanding of how rainfall responds to divergent urban development patterns worldwide. Here we unveil a divergence in the exposure to extreme rainfall for 1790 inland cities globally, attributable to their respective urban development patterns. Cities that experience compact development tend to witness larger increases in extreme rainfall frequency over downtown than their rural surroundings, while the anomalies in extreme rainfall frequency diminish for cities with dispersed development. Convection-permitting simulations further suggest compact urban footprints lead to more pronounced urban-rural thermal contrasts and aerodynamic disturbances. This is directly responsible for the divergent rainfall responses to urban development patterns. Our analyses offer significant insights pertaining to the priorities and potential of city-level efforts to mitigate the emerging climate-related hazards, particularly for countries experiencing rapid urbanization.

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.

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.

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.

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.

Effects of landscape on thermal livability at the community scale based on fine-grained geographic information: A case study of Shenzhen

In the current research, the question of how to modify the microclimate through landscape planning to create a livable thermal environment within a residential community area has not been clarified. Therefore, this study investigated the effects of landscape on thermal livability in 2980 communities in Shenzhen, and obtained the following findings: (1) the proportion of trees and the average building height were key indicators to determine the average land surface temperature (LST) of a community, while the two-dimensional building characteristics, particularly shape, similarity, and patch dominance, were mainly responsible for regulating the spatial distribution of LST within a community; (2) at the community scale, the cooling intensity of buildings was strongest when their average height was around 40-60 m, and cooling effect of trees was most pronounced when their proportion achieved 20 %; and (3) the LST threshold for thermal livability in Shenzhen was around 35 °C. In summer, a higher proportion of trees and grass, as well as buildings with higher average heights, larger volume ratios, and more complex three-dimensional structures were favorable to maintain a livable community thermal environment, while in winter, a lower proportion of trees was more encouraged. In addition, a smaller average sky view factor can achieve a community thermal environment that warm in winter and cool in summer. These results are expected to facilitate urban planners to develop community renewal from the perspective of thermal livability.

Vegetation-induced asymmetric diurnal land surface temperatures changes across global climate zones

Unprecedented global vegetation greening during past decades is well known to affect annual and seasonal land surface temperatures (LST). However, the impact of observed vegetation cover change on diurnal LST across global climatic zones is not well understood. Using global climatic time-series datasets, we investigated the long-term growing season daytime and nighttime LST changes globally and explored associated dominant contributors including vegetation and climate factors including air temperature, precipitation, and solar radiation. Results revealed asymmetric growing season mean daytime and nighttime LST warming (0.16 °C/10a and 0.30 °C/10a, respectively) globally from 2003 to 2020, as a result, the diurnal LST range (DLSTR) declined at 0.14 °C/10a. The sensitivity analysis indicated the LST response to changes in LAI, precipitation, and SSRD mainly concentrated during daytime instead of nighttime, however, which showed comparable sensitivities for air temperature. Combining the sensitivities results and the observed LAI and climate trends, we found rising air temperature contributes to 0.24 ± 0.11 °C/10a global daytime LST warming and 0.16 ± 0.07 °C/10a nighttime LST warming, turns to be the dominant contributor to the LST changes. Increased LAI cooled global daytime LST (-0.068 ± 0.096 °C/10a) while warmed nighttime LST (0.064 ± 0.046 °C/10a); hence LAI dominates declines in DLSTR trends (-0.12 ± 0.08 °C/10a), despite some day-night process variations across climate zones. In Boreal regions, reduced DLSTR was due to nighttime warming from LAI increases. In other climatic zones, daytime cooling, and DLSTR decline, was induced by increased LAI. Biophysically, the pathway from air temperature heats the surface through sensible heat and increased downward longwave radiation during day and night, while the pathway from LAI cools the surface by enhancing energy redistribution into latent heat rather than sensible heat during the daytime. These empirical findings of diverse asymmetric responses could help calibrate and improve biophysical models of diurnal surface temperature feedback in response to vegetation cover changes in different climate zones.

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.

Urban dynamics through the lens of human mobility

The urban spatial structure represents the distribution of public and private spaces in cities and how people move within them. Although it usually evolves slowly, it can change quickly during large-scale emergency events, as well as due to urban renewal in rapidly developing countries. Here we present an approach to delineate such urban dynamics in quasi-real time through a human mobility metric, the mobility centrality index ΔKS. As a case study, we tracked the urban dynamics of eleven Spanish cities during the COVID-19 pandemic. The results revealed that their structures became more monocentric during the lockdown in the first wave, but kept their regular spatial structures during the second wave. To provide a more comprehensive understanding of mobility from home, we also introduce a dimensionless metric, KSHBT, which measures the extent of home-based travel and provides statistical insights into the transmission of COVID-19. By utilizing individual mobility data, our metrics enable the detection of changes in the urban spatial structure.

Comparing the cooling effectiveness of operationalisable urban surface combination scenarios for summer heat mitigation

Extreme summer heat in cities exacerbates the vulnerability of urban communities to heatwaves. Vegetative and reflective urban surfaces can help reduce urban heat. This study investigated the impacts of urban trees, green roofs and cool roofs on heat mitigation during average and extreme summer conditions in temperate oceanic Melbourne, Australia. We simulated the city climate using 'The Air Pollution Model' (TAPM) at a 1 km spatial resolution over 10 years, which according to our review of the literature, was the most prolonged period for simulation in Melbourne. During a widespread heatwave event, some of the tested scenarios with combined surface parameters could reduce the extreme values of the energy budget components- sensible heat, latent heat, and storage heat fluxes up to seasonal averages compared to the existing situation for Melbourne (control). The scenario with the highest (reasonable maximum) ground-level vegetation, green roofs, and cool roofs could reduce air temperatures up to 2.4 °C. The simulations suggest that a combined strategy with vegetative and high-albedo surfaces will deliver higher effectiveness with maximum cooling benefits and cost-effectiveness than individual strategies in cities. These results suggest the importance of collaborative strategic planning of urban surfaces to make cities healthier, sustainable, and liveable.

Urban green space and albedo impacts on surface temperature across seven United States cities

Extreme heat represents a growing threat to public health, especially across the densely populated, developed landscape of cities. Climate adaptation strategies that aim to manage urban microclimates through purposeful design can reduce the heat exposure of urban populations, however, it is unclear how the temperature impacts of urban green space and albedo vary across cities and background climate. This study quantifies the sensitivity of surface temperature to landcover characteristics tied to two widely used climate adaptation strategies, urban greening and albedo manipulation (e.g. white roofs), by combining long-term remote sensing observations of land surface temperature, albedo, and moisture with high-resolution landcover datasets in a spatial regression analysis at the census block scale across seven United States cities. We find tree cover to have an average cooling impact of -0.089 K per % cover, which is approximately four times stronger than the average grass cover cooling impact of -0.021 K per % cover. Variability in the magnitude of grass cover cooling impacts was primarily a function of vegetation moisture content, with the Land Surface Water Index (LSWI) explaining 89 % of the variability in grass cover cooling impacts across cities. Variability in tree cover cooling impacts was primarily a function of sunlight and vegetation moisture content, with solar irradiance and LSWI explaining 97 % of the cooling variability across cities. Albedo cooling impacts were consistent across cities with an average cooling impact of -0.187 K per increase of 0.01. While these interventions are broadly effective across cities, there are critical regional trade-offs between vegetation cooling efficiency, irrigation requirements, and the temporal duration and evolution of the cooling benefits. In warm, arid cities, high albedo surfaces offer multifaceted benefits such as cooling and water conservation, whereas temperate, mesic cities likely benefit from a combination of strategies, with greening efforts targeting highly paved neighborhoods.

Characteristics of Urban Heat Island in China and Its Influences on Building Energy Consumption

Urban heat island (UHI) draws more attention as it affects not only the health of residents but also the energy consumption of buildings at the city scale. To achieve carbon neutrality goals, it is crucial to better understand the mechanism of the UHI influences on building energy consumption. The characteristics of urban heat island intensity (UHII) and the relationship between the UHII effect and building electricity and related coal consumption were analyzed, based on the long period of monitoring data with hourly weather data from 1 January to 31 December 2019. Results show that a strong correlation between the annual mean UHII and the median daily mean UHII exists. The synthetic diurnal UHII of most cities presents a U-shaped variation trend. In different building climate zones in China, namely, severe cold region (SCR), cold region (CR), hot summer cold winter region (HSCWR), hot summer and warm winter region (HSWWR), and mild region (MR), the influences of UHII on building energy consumption were analyzed. The existence of UHI reduces building energy consumption in 96.7% of SCR cities and 60.8% of CR cities, while in HSCWR, HSWWR, and MR cities, the percentage of cities where the building energy consumption is increased by UHI is 69.4%, 80%, and 63.6%, respectively. Urban climate strongly influences building energy consumption, indicating that it should be considered and analyzed in detail for making future urban development or carbon emission reduction strategies.

Analysis of Domestic and International Green Infrastructure Research Trends from the ESG Perspective in South Korea

Government-level ESG (environmental, social, and governance) institutionalization and active ESG activation in the private sector are being discussed for the first time this year in Korea, spurred by increased national interest since the COVID-19 pandemic crisis and the declaration of a carbon-neutral society by 2050, and ESG discussion in many fields is spreading rapidly. In addition, global awareness of the crisis caused by environmental pollution and natural disasters has highlighted the importance of green infrastructure (GI) as a new conceptual alternative to improve public value. Based on sustainability, which is a common goal of ESG and green infrastructure, this study aimed to examine the research targets and techniques of green infrastructure from the perspective of ESG. This study selected and analyzed 98 domestic and international academic journal papers published over the past 10 years in the Web of Science academic journal database literature collection. Focusing on the research subjects, the focus on green infrastructure, and research keywords, we examined the aspects of the green infrastructure plan that have been focused on from the ESG perspective and compared domestic and international research trends. In addition, implications for how each research topic is connected to the concept of ESG according to its function and purpose were derived. By examining the domestic and international research trends of green infrastructure from the ESG perspective, we identified the need for a wider range of research on the diversity and relationship between humans and the ecological environment; policies and systems; and technical research that does not focus only on a specific field. In this regard, we intend to increase the contribution to ESG management in the public sector through the establishment of green infrastructure plans and policies in the future, as they account for a large portion of public capital.

The Seasonality of Surface Urban Heat Islands across Climates

In this work, we investigate how the seasonal hysteresis of the Surface Urban Heat Island Intensity (SUHII) differs across climates and provide a detailed typology of the daytime and nighttime SUHII hysteresis loops. Instead of the typical tropical/dry/temperate/continental grouping, we describe Earth’s climate using the Köppen–Geiger system that empirically maps Earth’s biome distribution into 30 climate classes. Our thesis is that aggregating multi-city data without considering the biome of each city results in temporal means that fail to reflect the actual SUHII characteristics. This is because the SUHII is a function of both urban and rural features and the phenology of the rural surroundings can differ considerably between cities, even in the same climate zone. Our investigation covers all the densely populated areas of Earth and uses 18 years (2000–2018) of land surface temperature and land cover data from the European Space Agency’s Climate Change Initiative. Our findings show that, in addition to concave-up and -down shapes, the seasonal hysteresis of the SUHII also exhibits twisted, flat, and triangle-like patterns. They also suggest that, in wet climates, the daytime SUHII hysteresis is almost universally concave-up, but they paint a more complex picture for cities in dry climates.

Urban Warming of the Two Most Populated Cities in the Canadian Province of Alberta, and Its Influencing Factors

Continuous urban expansion transforms the natural land cover into impervious surfaces across the world. It increases the city’s thermal intensity that impacts the local climate, thus, warming the urban environment. Surface urban heat island (SUHI) is an indicator of quantifying such local urban warming. In this study, we quantified SUHI for the two most populated cities in Alberta, Canada, i.e., the city of Calgary and the city of Edmonton. We used the moderate resolution imaging spectroradiometer (MODIS) acquired land surface temperature (LST) to estimate the day and nighttime SUHI and its trends during 2001–2020. We also performed a correlation analysis between SUHI and selected seven influencing factors, such as urban expansion, population, precipitation, and four large-scale atmospheric oscillations, i.e., Sea Surface Temperature (SST), Pacific North America (PNA), Pacific Decadal Oscillation (PDO), and Arctic Oscillation (AO). Our results indicated a continuous increase in the annual day and nighttime SUHI values from 2001 to 2020 in both cities, with a higher magnitude found for Calgary. Moreover, the highest value of daytime SUHI was observed in July for both cities. While significant warming trends of SUHI were noticed in the annual daytime for the cities, only Calgary showed it in the annual nighttime. The monthly significant warming trends of SUHI showed an increasing pattern during daytime in June, July, August, and September in Calgary, and March and September in Edmonton. Here, only Calgary showed the nighttime significant warming trends in March, May, and August. Further, our correlation analysis indicated that population and built-up expansion were the main factors that influenced the SUHI in the cities during the study period. Moreover, SST indicated an acceptable relationship with SUHI in Edmonton only, while PDO, PNA, and AO did not show any relation in either of the two cities. We conclude that population, built-up size, and landscape pattern could better explain the variations of the SUHI intensity and trends. These findings may help to develop the adaptation and mitigating strategies in fighting the impact of SUHI and ensure a sustainable city environment.

A Scale-Separating Framework for Fusing Satellite Land Surface Temperature Products

The trade-off between spatial and temporal resolutions of satellite imagery is a long-standing problem in satellite remote sensing applications. The lack of daily land surface temperature (LST) data with fine spatial resolution has hampered the understanding of surface climatic phenomena, such as the urban heat island (UHI). Here, we developed a fusion framework, characterized by a scale-separating process, to generate LST data with high spatiotemporal resolution. The scale-separating framework breaks the fusion task into three steps to address errors at multiple spatial scales, with a specific focus on intra-scene variations of LST. The framework was experimented with MODIS and Landsat LST data. It first removed inter-sensor biases, which depend on season and on land use type (urban versus rural), and then produced a Landsat-like sharpened LST map for days when MOIDS observations are available. The sharpened images achieved a high accuracy, with a RMSE of 0.91 K for a challenging heterogeneous landscape (urban area). A comparison between the sharpened LST and the air temperature measured with bicycle-mounted mobile sensors revealed the roles of impervious surface fraction and wind speed in controlling the surface-to-air temperature gradient in an urban landscape.

Estimating ecological sustainability in the Guangdong-Hong Kong-Macao Greater Bay Area, China: Retrospective analysis and prospective trajectories

In recent decades, rapid urbanization and intensified global climate change have resulted in a significant difference of environment and resources distribution on space, which would cause trouble for accurate assessment of regional ecological sustainable development, especially in the large urban agglomerations. The parameters used in previous assessment methods have normally ignored spatial heterogeneity, leading to deviations in the evaluation accuracies against the context above. By incorporating remote sensing technology, this study proposed an improved emergy ecological footprint (EEF) method and a novel ecological sustainability index to comprehensively analyze the variability of ecological security states (ESS) from 1994 to 2018 in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) and to predict its sustainable growth potential based on a combined factorial decomposition and scenario analysis. Results showed that the pixel-based emergy analysis revealed significant heterogeneity over time and space under the impact of climate change and intense land use activities during the study period. The emergy carrying capacity per capita (ecc) and the emergy ecological footprint per capita (eef) also showed a significant difference between the nine cities in the GBA. In addition, the traditional EEF method, which does not consider the spatiotemporal variation, has indeed overestimated the GBA's ecc by 15% compared with our results. The ESS of the GBA gradually worsened from slight insecurity in the 1990s to moderate insecurity in 2018. If the current trends in socio-economic activities and climate change continue according to the RCP8.5 scenario in the IPCC, the ESS of the GBA will reach the extreme insecurity state in 2050. However, our scenarios show that industrial structure adjustment, energy structure optimization, and especially biological resource conservation can reduce the EFI by approximately 6.52%, 23.4%, and 30.6%, respectively. Consequently, effective implementation of the above measures can limit the increase both in emergy ecological deficit and emergy ecological footprint intensity (EFI) and, together, contribute to a higher security status in the GBA in 2050.

Global climate-driven trade-offs between the water retention and cooling benefits of urban greening

Urban greening can potentially help mitigate heat-related mortality and flooding facing the >4 billion urban population worldwide. However, the geographical variation of the relative combined hydrological and thermal performance benefits of such interventions are unknown. Here we quantify globally, using a hydrological model, how climate-driven trade-offs exist between hydrological retention and cooling potential of urban greening such as green roofs and parks. Using a Budyko framework, we show that water retention generally increases with aridity in water-limited environments, while cooling potential favors energy-limited climates. Our models suggest that common urban greening strategies cannot yield high performance simultaneously for addressing both urban heat-island and urban flooding problems in most cities globally. Irrigation, if sustainable, may enhance cooling while maintaining retention performance in more arid locations. Increased precipitation variability with climate change may reduce performance of thinner green-infrastructure more quickly compared to greened areas with thicker soils and root systems. Our results provide a conceptual framework and first-order quantitative guide for urban development, renewal and policymaking.

Urbanization Impact on Regional Climate and Extreme Weather: Current Understanding, Uncertainties, and Future Research Directions

Urban environments lie at the confluence of social, cultural, and economic activities and have unique biophysical characteristics due to continued infrastructure development that generally replaces natural landscapes with built-up structures. The vast majority of studies on urban perturbation of local weather and climate have been centered on the urban heat island (UHI) effect, referring to the higher temperature in cities compared to their natural surroundings. Besides the UHI effect and heat waves, urbanization also impacts atmospheric moisture, wind, boundary layer structure, cloud formation, dispersion of air pollutants, precipitation, and storms. In this review article, we first introduce the datasets and methods used in studying urban areas and their impacts through both observation and modeling and then summarize the scientific insights on the impact of urbanization on various aspects of regional climate and extreme weather based on more than 500 studies. We also highlight the major research gaps and challenges in our understanding of the impacts of urbanization and provide our perspective and recommendations for future research priorities and directions.

Decrease in the residents' accessibility of summer cooling services due to green space loss in Chinese cities

Urban green spaces (UGSs) reduce the surrounding temperature and create cooling areas as a buffer between people and high temperatures, thus helping residents adapt to the warming climate. However, the accessibility of UGS cooling services to the residents of cities remains largely unknown, which hinders decision-making regarding the formulation of climate adaptation and urban greening schemes. In the present study, we estimated the number of residents who accessed UGSs for cooling by analyzing the annual changes in such cooling areas during summer across 315 Chinese cities from 2003 to 2015. Approximately 93.3% of the cities showed significant decreasing trends (p < 0.05) of the total UGS area; as such the UGS coverage dropped from 12.23 ± 0.32% in 2003 to 7.69 ± 0.22% in 2015. Consequently, with the prevalent loss of UGS, the coverage of cooling spaces decreased from 32.55 ± 0.76% in 2003 to 24.39 ± 0.60% in 2015. This has formed a spatial mismatch between the growing urban population and the remaining UGSs. Accordingly, the number of residents of areas outside these cooling spaces increased by 4.23 million per year. In particular, the shortage of cooling services was more significant in cities with < 20,000 USD gross domestic product per capita and < 5 million residents than in the rest of the cities. To minimize the adverse impacts of increasing temperatures, focused greening plans are warranted, specifically in underdeveloped cities.

Estimating Heat-Related Exposures and Urban Heat Island Impacts: A Case Study for the 2012 Chicago Heatwave

Accelerated urbanization increases both the frequency and intensity of heatwaves (HW) and urban heat islands (UHIs). An extreme HW event occurred in 2012 summer that caused temperatures of more than 40°C in Chicago, Illinois, USA, which is a highly urbanized city impacted by UHIs. In this study, multiple numerical models, including the High Resolution Land Data Assimilation System (HRLDAS) and Weather Research and Forecasting (WRF) model, were used to simulate the HW and UHI, and their performance was evaluated. In addition, sensitivity testing of three different WRF configurations was done to determine the impact of increasing model complexity in simulating urban meteorology. Model performances were evaluated based on the statistical performance metrics, the application of a multi-layer urban canopy model (MLUCM) helps WRF to provide the best performance in this study. HW caused rural temperatures to increase by ∼4°C, whereas urban Chicago had lower magnitude increases from the HW (∼2-3°C increases). Nighttime UHI intensity (UHII) ranged from 1.44 to 2.83°C during the study period. Spatiotemporal temperature fields were used to estimate the potential heat-related exposure and to quantify the Excessive Heat Factor (EHF). The EHF during the HW episode provides a risk map indicating that while urban Chicago had higher heat-related stress during this event, the rural area also had high risk, especially during nighttime in central Illinois. This study provides a reliable method to estimate spatiotemporal exposures for future studies of heat-related health impacts.

Quantifying the response of surface urban heat island to urban greening in global north megacities

Urban heat island, a phenomenon that urban temperature is higher than the rural area nearby, affects directly citizens' human health and well-being. However, the cooling effect from urban green space (UGS) and the attribution of the different land processes to surface urban heat island intensity (SUHI) under different background climates remains unclear. The coarse-grained model was used to estimate summer SUHI in three different background climatic zones and for seven agglomerations (BTH, JP, LD, NAAC, NAGL, YZ, UQ). Results indicate that (1) the temperate zone had the highest daytime SUHI (0-10 °C), while the arid zone has the lowest daytime SUHI (-1-2 °C). In both temperate and cold zone, the daytime SUHI was higher than the nighttime SUHI. The SUHI in downtown was higher (more than 2 °C) than in the suburbs. (2) The increasing precipitation can enhance daytime SUHI while can weaken nighttime SUHI in all three climatic zones. The increasing temperature tends to enhance SUHI in both daytime and nighttime (exclude UQ). (3) The cooling effects of UGS in daytime SUHI were highly dependent on the background climate (cold > temperate > arid). (4) The nighttime SUHI could be effectively offset when UGSFs were greater than 0.48, 0.82, 0.97, 0.95 in NAAC, NAGL, YZ, and UQ. This article highlights the different feedback of urban green space to UHII and supports green infrastructure intervention as an effective means of reducing urban heat stress at urban agglomeration scales.

The role of urban trees in reducing land surface temperatures in European cities

Urban trees influence temperatures in cities. However, their effectiveness at mitigating urban heat in different climatic contexts and in comparison to treeless urban green spaces has not yet been sufficiently explored. Here, we use high-resolution satellite land surface temperatures (LSTs) and land-cover data from 293 European cities to infer the potential of urban trees to reduce LSTs. We show that urban trees exhibit lower temperatures than urban fabric across most European cities in summer and during hot extremes. Compared to continuous urban fabric, LSTs observed for urban trees are on average 0-4 K lower in Southern European regions and 8-12 K lower in Central Europe. Treeless urban green spaces are overall less effective in reducing LSTs, and their cooling effect is approximately 2-4 times lower than the cooling induced by urban trees. By revealing continental-scale patterns in the effect of trees and treeless green spaces on urban LST our results highlight the importance of considering and further investigating the climate-dependent effectiveness of heat mitigation measures in cities.

Urban Heat Island and Its Interaction with Heatwaves: A Review of Studies on Mesoscale

With rapid urbanization, population growth and anthropogenic activities, an increasing number of major cities across the globe are facing severe urban heat islands (UHI). UHI can cause complex impacts on the urban environment and human health, and it may bring more severe effects under heatwave (HW) conditions. In this paper, a holistic review is conducted to articulate the findings of the synergies between UHI and HW and corresponding mitigation measures proposed by the research community. It is worth pointing out that most studies show that urban areas are more vulnerable than rural areas during HWs, but the opposite is also observed in some studies. Changes in urban energy budget and major drivers are discussed and compared to explain such discrepancies. Recent studies also indicate that increasing albedo, vegetation fraction and irrigation can lower the urban temperature during HWs. Research gaps in this topic necessitate more studies concerning vulnerable cities in developing countries. Moreover, multidisciplinary studies considering factors such as UHI, HW, human comfort, pollution dispersion and the efficacy of mitigation measures should be conducted to provide more accurate and explicit guidance to urban planners and policymakers.

Plant Species Composition and the Perception of the Afforestation in Urban Public Green Spaces in a Municipality in Eastern Brazilian Amazon

The plant composition is a fundamental element in public green spaces, improving the environment and people’s quality of life. The executing of floristic inventories can contribute to better understanding and management of these spaces. Here, we sought to know the plants used in the afforestation of the main public green spaces in the town of Oriximiná, eastern Brazilian Amazon, as well as to perform a brief analysis of the population’s perception regarding the afforestation of these environments. The plants were collected and identified using specific literature and dichotomous keys, in addition to consultations in virtual herbariums. The analysis of the population’s perception took place through interviews, with questionnaires collected in each public green space. We registered 1616 individuals from the flora of the squares, distributed in 16 families, 24 genera, and 28 species. Exotic plants are predominant in number species and of individuals. The interviewees demonstrated that they are aware of the importance of plants in the squares and providing shade stands out as the most cited benefit. The afforestation of the squares shows some irregularities, highlighting the need for better planning which includes the use of native species and the participation of the local community in the management of these green areas. Finally, we provide a list of native species, naturally occurring in the Amazon region, that can be used in urban afforestation.

Urban-Scale Evaluation of Cool Pavement Impacts on the Urban Heat Island Effect and Climate Change

We implemented a context-sensitive and prospective framework to assess the global warming potential (GWP) impacts of cool pavement strategies on specific roads for different cities. The approach incorporates several interconnections among different elements of the built environment, such as buildings and urban road segments, as well as the transportation fleet, using specific building and pavement information from an urban area. We show that increasing pavement albedo lowers urban air temperatures but can adversely affect the building energy demand in the areas with high incident radiation exposure. The heating energy savings and the radiative forcing effect improve the GWP savings in cold and humid climate conditions. The total GWP savings intensity is sensitive to the city morphology and road traffic. The probabilistic results show that cool pavement strategies can offset 1.0-3.0% and 0.7-6.0% of the total GHG emissions of the U.S. cities Boston and Phoenix, respectively, for a 50-year analysis period. The worldwide range of savings can be as large as 5.0-44.7 Gt of CO₂ eq. A paradigm shift in pavement strategy selection is required in most neighborhoods.

A Satellite-Based Model for Estimating Latent Heat Flux From Urban Vegetation

The impacts of extreme heat events are amplified in cities due to unique urban thermal properties. Urban greenspace mitigates high temperatures through evapotranspiration and shading; however, quantification of vegetative cooling potential in cities is often limited to simple remote sensing greenness indices or sparse, in situ measurements. Here, we develop a spatially explicit, high-resolution model of urban latent heat flux from vegetation. The model iterates through three core equations that consider urban climatological and physiological characteristics, producing estimates of latent heat flux at 30-m spatial resolution and hourly temporal resolution. We find strong agreement between field observations and model estimates of latent heat flux across a range of ecosystem types, including cities. This model introduces a valuable tool to quantify the spatial heterogeneity of vegetation cooling benefits across the complex landscape of cities at an adequate resolution to inform policies addressing the effects of extreme heat events.

Highly efficient evaporative cooling by all-day water evaporation using hierarchically porous biomass

We developed a 3D solar steam generator with the highest evaporation rate reported so far using a carbonized luffa sponge (CLS). The luffa sponge consisted of entangled fibers with a hierarchically porous structure; macropores between fibers, micro-sized pores in the fiber-thickness direction, and microchannels in the fiber-length direction. This structure remained after carbonization and played an important role in water transport. When the CLS was placed in the water, the microchannels in the fiber-length direction transported water to the top surface of the CLS by capillary action, and the micro-sized pores in the fiber-thickness direction delivered water to the entire fiber surface. The water evaporation rate under 1-sun illumination was 3.7 kg/m2/h, which increased to 14.5 kg/m2/h under 2 m/s wind that corresponded to the highest evaporation rate ever reported under the same condition. The high evaporation performance of the CLS was attributed to its hierarchically porous structure. In addition, it was found that the air temperature dropped by 3.6 °C when the wind passed through the CLS because of the absorption of the latent heat of vaporization. The heat absorbed by the CLS during water evaporation was calculated to be 9.7 kW/m2 under 1-sun illumination and 2 m/s wind, which was 10 times higher than the solar energy irradiated on the same area (1 kW/m2).

Deficient endoplasmic reticulum translocon-associated protein complex limits the biosynthesis of proinsulin and insulin

The conserved endoplasmic reticulum (ER) membrane protein TRAPα (translocon-associated protein, also known as signal sequence receptor 1, SSR1) has been reported to play a critical but unclear role in insulin biosynthesis. TRAPα/SSR1 is one component of a four-protein complex including TRAPβ/SSR2, TRAPγ/SSR3, and TRAPδ/SSR4. The TRAP complex topologically has a small exposure on the cytosolic side of the ER via its TRAPγ/SSR3 subunit, whereas TRAPβ/SSR2 and TRAPδ/SSR4 function along with TRAPα/SSR1 largely on the luminal side of the ER membrane. Here, we have examined pancreatic β-cells with deficient expression of either TRAPβ/SSR2 or TRAPδ/SSR4, which does not perturb mRNA expression levels of other TRAP subunits, or insulin mRNA. However, deficient protein expression of TRAPβ/SSR2 and, to a lesser degree, TRAPδ/SSR4, diminishes the protein levels of other TRAP subunits, concomitant with deficient steady-state levels of proinsulin and insulin. Deficient TRAPβ/SSR2 or TRAPδ/SSR4 is not associated with any apparent defect of exocytotic mechanism but rather by a decreased abundance of the proinsulin and insulin that accompanies glucose-stimulated secretion. Amino acid pulse labeling directly establishes that much of the steady-state deficiency of intracellular proinsulin can be accounted for by diminished proinsulin biosynthesis, observed in a pulse-labeling as short as 5 minutes. The proinsulin and insulin levels in TRAPβ/SSR2 or TRAPδ/SSR4 null mutant β-cells are notably recovered upon re-expression of the missing TRAP subunit, accompanying a rebound of proinsulin biosynthesis. Remarkably, overexpression of TRAPα/SSR1 can also suppress defects in β-cells with diminished expression of TRAPβ/SSR2, strongly suggesting that TRAPβ/SSR2 is needed to support TRAPα/SSR1 function.

Water, energy and climate benefits of urban greening throughout Europe under different climatic scenarios

Urban greening is an effective mitigation option for climate change in urban areas. In this contribution, a European Union (EU)-wide assessment is presented to quantify the benefits of urban greening in terms of availability of green water, reduction of cooling costs and CO₂ sequestration from the atmosphere, for different climatic scenarios. Results show that greening of 35% of the EU’s urban surface (i.e. more than 26,000 km²) would avoid up to 55.8 Mtons year⁻¹ CO₂ equivalent of greenhouse gas emissions, reducing energy demand for the cooling of buildings in summer by up to 92 TWh per year, with a net present value (NPV) of more than 364 billion Euro. It would also transpire about 10 km³ year⁻¹ of rain water, turning into “green” water about 17.5% of the “blue” water that is now urban runoff, helping reduce pollution of the receiving water bodies and urban flooding. The greening of urban surfaces would decrease their summer temperature by 2.5–6 °C, with a mitigation of the urban heat island effect estimated to have a NPV of 221 billion Euro over a period of 40 years. The monetized benefits cover less than half of the estimated costs of greening, having a NPV of 1323 billion Euro on the same period. Net of the monetized benefits, the cost of greening 26,000 km² of urban surfaces in Europe is estimated around 60 Euro year⁻¹ per European urban resident. The additional benefits of urban greening related to biodiversity, water quality, health, wellbeing and other aspects, although not monetized in this study, might be worth such extra cost. When this is the case, urban greening represents a multifunctional, no-regret, cost-effective solution. 

Impacts of the evolving urban development on intra-urban surface thermal environment: Evidence from 323 Chinese cities

Urban development has significantly modified the surface thermal environment in urban areas. This study provides the first attempt to characterize the urban development imprint on surface thermal environment for 323 cities across the entire country of China, using an intra-urban perspective. Specifically, it investigates the variation of surface thermal environment in terms of land surface temperature (LST) difference triggered by significant urban evolution of intra-urban division containing two primary classes: old urban areas developed by 1992 and new ones expanded in the 1992-2015 period. Under this "old-new" dichotomy, the relationship between urban development and the LST difference is explored through Multi-scale Geographically Weighted Regression (MGWR). Results reveal that urban development is closely related to the difference in LST between old and new urban areas in 2015, which varies from -2.66 °C to 2.46 °C, up to -6.27 °C in western China. 264 cities manifest relatively "cooler" urban environments in the generally larger-sized new urban areas. The seven selected urban development indicators can explain 75% of the variance in the LST difference through MGWR. Among them, the old-new elevation difference, the normalized difference vegetation index (NDVI) difference, and Gini coefficient are found to influence the LST difference in various spatially varying manners. The elevation difference, a generally underestimated nature-driven indicator, is found dominant in explaining the LST difference for 252 cities, among which 216 cities demonstrate higher LSTs in the urban areas with lower elevations. Overall, this study provides valuable information of human-environment interaction across many cities in a generalized way, which complements similar studies at local level, and helps to depict a complete picture of environmental impacts of urban development. The integrated workflow can also be promoted to other periods or other countries to examine the corresponding urbanization imprint on intra-urban surface warming.

Crowdsourced air temperatures contrast satellite measures of the urban heat island and its mechanisms

The ubiquitous nature of satellite data has led to an explosion of studies on the surface urban heat island (SUHI). Relatively few have simultaneously used air temperature measurements to compare SUHI with the canopy UHI (CUHI), which is more relevant to public health. Using crowdsourced citizen weather stations (>50,000) and satellite data over Europe, we estimate the CUHI and SUHI intensity in 342 urban clusters during the 2019 heat wave. Satellites produce a sixfold overestimate of UHI relative to station measurements (mean SUHI 1.45°C; CUHI 0.26°C), with SUHI exceeding CUHI in 96% of cities during daytime and in 80% at night. Using empirical evidence, we confirm the control of aerodynamic roughness on UHI intensity, but find evaporative cooling to have a stronger overall impact during this time period. Our results support urban greening as an effective UHI mitigation strategy and caution against relying on satellite data for urban heat risk assessments.

Study of Urban Heat Islands Using Different Urban Canopy Models and Identification Methods

This work aims to compare the performance of the single‑(SLUCM) and multilayer (BEP-Building effect parameterization) urban canopy models (UCMs) coupled with the Weather Research and Forecasting model (WRF), along with the application of two urban heat island (UHI) identification methods. The identification methods are: (1) the “classic method”, based on the temperature difference between urban and rural areas; (2) the “local method” based on the temperature difference at each urban location when the model land use is considered urban, and when it is replaced by the dominant rural land use category of the urban surroundings. The study is performed as a case study for the city of Lisbon, Portugal, during the record-breaking August 2003 heatwave event. Two main differences were found in the UHI intensity (UHII) and spatial distribution between the identification methods: a reduction by half in the UHII during nighttime when using the local method; and a dipole signal in the daytime and nighttime UHI spatial pattern when using the classic method, associated with the sheltering effect provided by the high topography in the northern part of the city, that reduces the advective cooling in the lower areas under prevalent northern wind conditions. These results highlight the importance of using the local method in UHI modeling studies to fully isolate urban canopy and regional geographic contributions to the UHII and distribution. Considerable improvements were obtained in the near‑surface temperature representation by coupling WRF with the UCMs but better with SLUCM. The nighttime UHII over the most densely urbanized areas is lower in BEP, which can be linked to its larger nocturnal turbulent kinetic energy (TKE) near the surface and negative sensible heat (SH) fluxes. The latter may be associated with the lower surface skin temperature found in BEP, possibly owing to larger turbulent SH fluxes near the surface. Due to its higher urban TKE, BEP significantly overestimates the planetary boundary layer height compared with SLUCM and observations from soundings. The comparison with a previous study for the city of Lisbon shows that BEP model simulation results heavily rely on the number and distribution of vertical levels within the urban canopy.

Quantification of the Environmental Impacts of Highway Construction Using Remote Sensing Approach

Highways provide key social and economic functions but generate a wide range of environmental consequences that are poorly quantified and understood. Here, we developed a before–during–after control-impact remote sensing (BDACI-RS) approach to quantify the spatial and temporal changes of environmental impacts during and after the construction of the Wujing Highway in China using three buffer zones (0–100 m, 100–500 m, and 500–1000 m). Results showed that land cover composition experienced large changes in the 0–100 m and 100–500 m buffers while that in the 500–1000 m buffer was relatively stable. Vegetation and moisture conditions, indicated by the normalized difference vegetation index (NDVI) and the normalized difference moisture index (NDMI), respectively, demonstrated obvious degradation–recovery trends in the 0–100 m and 100–500 m buffers, while land surface temperature (LST) experienced a progressive increase. The maximal relative changes as annual means of NDVI, NDMI, and LST were about −40%, −60%, and 12%, respectively, in the 0–100m buffer. Although the mean values of NDVI, NDMI, and LST in the 500–1000 m buffer remained relatively stable during the study period, their spatial variabilities increased significantly after highway construction. An integrated environment quality index (EQI) showed that the environmental impact of the highway manifested the most in its close proximity and faded away with distance. Our results showed that the effect distance of the highway was at least 1000 m, demonstrated from the spatial changes of the indicators (both mean and spatial variability). The approach proposed in this study can be readily applied to other regions to quantify the spatial and temporal changes of disturbances of highway systems and subsequent recovery.

The impacts of existing and hypothetical green infrastructure scenarios on urban heat island formation

Urban Heat Island (UHI) is posing a significant challenge due to growing urbanisations across the world. Green infrastructure (GI) is popularly used for mitigating the impact of UHI, but knowledge on their optimal use is yet evolving. The UHI effect for large cities have received substantial attention previously. However, the corresponding effect is mostly unknown for towns, where appreciable parts of the population live, in Europe and elsewhere. Therefore, we analysed the possible impact of three vegetation types on UHI under numerous scenarios: baseline/current GI cover (BGI); hypothetical scenario without GI cover (HGI-No); three alternative hypothetical scenarios considering maximum green roofs (HGR-Max), grasslands (HG-Max) and trees (HT-Max) using a dispersion model ADMS-Temperature and Humidity model (ADMS-TH), taking a UK town (Guildford) as a case study area. Differences in an ambient temperature between three different landforms (central urban area, an urban park, and suburban residential area) were also explored. Under all scenarios, the night-time (0200 h; local time) showed a higher temperature increase, up to 1.315 °C due to the lowest atmospheric temperature. The highest average temperature perturbation (change in ambient temperature) was 0.563 °C under HGI-No scenario, followed by HG-Max (0.400 °C), BGI (0.343 °C), HGR-Max (0.326 °C) and HT-Max (0.277 °C). Furthermore, the central urban area experienced a 0.371 °C and 0.401 °C higher ambient temperature compared with its nearby suburban residential area and urban park, respectively. The results allow to conclude that temperature perturbations in urban environments are highly dependent on the type of GI, anthropogenic heat sources (buildings and vehicles) and the percentage of land covered by GI. Among all other forms of GI, trees were the best-suited GI which can play a viable role in reducing the UHI. Green roofs can act as an additional mitigation measure for the reduction of UHI at city scale if large areas are covered.

Biophysical impacts of Earth greening largely controlled by aerodynamic resistance

Satellite observations show widespread increasing trends of leaf area index (LAI), known as the Earth greening. However, the biophysical impacts of this greening on land surface temperature (LST) remain unclear. Here, we quantify the biophysical impacts of Earth greening on LST from 2000 to 2014 and disentangle the contributions of different factors using a physically based attribution model. We find that 93% of the global vegetated area shows negative sensitivity of LST to LAI increase at the annual scale, especially for semiarid woody vegetation. Further considering the LAI trends (P ≤ 0.1), 30% of the global vegetated area is cooled by these trends and 5% is warmed. Aerodynamic resistance is the dominant factor in controlling Earth greening's biophysical impacts: The increase in LAI produces a decrease in aerodynamic resistance, thereby favoring increased turbulent heat transfer between the land and the atmosphere, especially latent heat flux.

Fundamental Concepts of Human Thermoregulation and Adaptation to Heat: A Review in the Context of Global Warming

The international community has recognized global warming as an impending catastrophe that poses significant threat to life on earth. In response, the signatories of the Paris Agreement (2015) have committed to limit the increase in global mean temperature to <1.5 °C from pre-industry period, which is defined as 1850–1890. Considering that the protection of human life is a central focus in the Paris Agreement, the naturally endowed properties of the human body to protect itself from environmental extremes should form the core of an integrated and multifaceted solution against global warming. Scholars believe that heat and thermoregulation played important roles in the evolution of life and continue to be a central mechanism that allows humans to explore, labor and live in extreme conditions. However, the international effort against global warming has focused primarily on protecting the environment and on the reduction of greenhouse gases by changing human behavior, industrial practices and government policies, with limited consideration given to the nature and design of the human thermoregulatory system. Global warming is projected to challenge the limits of human thermoregulation, which can be enhanced by complementing innate human thermo-plasticity with the appropriate behavioral changes and technological innovations. Therefore, the primary aim of this review is to discuss the fundamental concepts and physiology of human thermoregulation as the underlying bases for human adaptation to global warming. Potential strategies to extend human tolerance against environmental heat through behavioral adaptations and technological innovations will also be discussed. An important behavioral adaptation postulated by this review is that sleep/wake cycles would gravitate towards a sub-nocturnal pattern, especially for outdoor activities, to avoid the heat in the day. Technologically, the current concept of air conditioning the space in the room would likely steer towards the concept of targeted body surface cooling. The current review was conducted using materials that were derived from PubMed search engine and the personal library of the author. The PubMed search was conducted using combinations of keywords that are related to the theme and topics in the respective sections of the review. The final set of articles selected were considered “state of the art,” based on their contributions to the strength of scientific evidence and novelty in the domain knowledge on human thermoregulation and global warming.

Dramatic uneven urbanization of large cities throughout the world in recent decades

The world has experienced dramatic urbanization in recent decades. However, we still lack information about the characteristics of urbanization in large cities throughout the world. After analyzing 841 large cities with built-up areas (BUAs) of over 100 km² from 2001 to 2018, here we found an uneven distribution of urbanization at different economic levels. On average, large cities in the low-income and lower-middle-income countries had the highest urban population growth, and BUA expansion in the upper-middle-income countries was more than three times that of the high-income countries. Globally, more than 10% of BUAs in 325 large cities showed significant greening (P < 0.05) from 2001 to 2018. In particular, China accounted for 32% of greening BUAs in the 841 large cities, where about 108 million people lived. Our quantitative results provide information for future urban sustainable development, especially for rational urbanization of the developing world.

Assessing the coordination between economic growth and urban climate change in China from 2000 to 2015

The balance between economic growth and environmental protection has been a critical concern for sustainable urban development. However, among the multiple research efforts exploring the coordination between the two aspects, the widespread urban climate change has rarely been considered. This study encompasses urban climate change into the cross-system coupling analysis framework to assess its coordination with economic growth using the Coupling Coordination Degree (CCD) model. The two aspects are respectively represented using indicators of Surface Urban Heat Island Intensity (SUHII) and Gross Domestic Product (GDP). Specifically, China is selected as case study, and a total of 259 cities from the 2000-2015 period are analyzed. The spatio-temporal patterns of CCD are investigated through time series clustering to uncover its performance under diversified economic and climatic contexts. The regional inequality and spatial agglomeration effects are also examined. Results reveal significant spatio-temporal heterogeneity of CCD. Geographically, CCD varies from uncoordinated to high-level coordination. Wealthier cities in the eastern coastal region are significantly better coordinated than their inland counterparts. Temporally, the uptrend of CCD is not significant for most cities due to the relatively insufficient emphasis on urban heat island (UHI) mitigation in previous efforts. Evident spatial inequality and agglomeration patterns are also observed with slight downtrends. The spatio-temporal patterns of CCD revealed in this study indicate great necessity for the central government to develop policies suiting cities' special characteristics and contexts, and more efforts should be targeted on reducing regional imbalance. Hence, a nation-city-community policy skeleton is last outlined to enhance the pursuit of a more climate-friendly urban environment under rapid economic development. Overall, this study advances the understanding of economy-urban climate interactions and facilitates the future pursuit of better sustainable cities. The proposed workflow can be utilized for other countries with diversified urbanization processes and potentially used for comparison among different countries.

Tree Transpiration and Urban Temperatures: Current Understanding, Implications, and Future Research Directions

The expansion of an urban tree canopy is a commonly proposed nature-based solution to combat excess urban heat. The influence trees have on urban climates via shading is driven by the morphological characteristics of trees, whereas tree transpiration is predominantly a physiological process dependent on environmental conditions and the built environment. The heterogeneous nature of urban landscapes, unique tree species assemblages, and land management decisions make it difficult to predict the magnitude and direction of cooling by transpiration. In the present article, we synthesize the emerging literature on the mechanistic controls on urban tree transpiration. We present a case study that illustrates the relationship between transpiration (using sap flow data) and urban temperatures. We examine the potential feedbacks among urban canopy, the built environment, and climate with a focus on extreme heat events. Finally, we present modeled data demonstrating the influence of transpiration on temperatures with shifts in canopy extent and irrigation during a heat wave.

Assessment of Urban Heat Risk in Mountain Environments: A Case Study of Chongqing Metropolitan Area, China

For urban climatic environments, the urban heat island (UHI) effect resulting from land use and land cover change (LUCC) caused by human activities is rapidly becoming one of the most notable characteristics of urban climate change due to urban expansion. UHI effects have become a significant barrier to the process of urbanization and sustainable development of the urban ecological environment. Predicting the spatial and temporal patterns of the urban heat environment from the spatial relationship between land use and land surface temperature (LST) is key to predicting urban heat environment risk. This study established an Urban Heat Environment Risk Model (UHERM) as follows. First, the urban LST was normalized and classified during three different periods. Second, a Markov model was constructed based on spatio-temporal change in the urban heat environment between the initial year (2005) and middle year (2010), and then a cellular automata (CA) model was used to reveal spatial relationships between the urban heat environments of the two periods and land use in the initial year. The spatio-temporal pattern in a future year (2015) was predicted and the accuracy of the simulation was verified. Finally, the spatio-temporal pattern of urban heat environment risk was quantitatively forecasted based on the decision rule for the urban heat environment risk considering both the present and future status of the spatial characteristics of the urban heat environment. The MODIS LST product and LUCC dataset retrieved from remote sensing images were used to verify the accuracy of UHERM and to forecast the spatio-temporal pattern of urban heat environment risk during the period of 2015–2020. The results showed that the risk of urban heat environment is increasing in the Chongqing metropolitan area. This method for quantitatively evaluating the spatio-temporal pattern of urban heat environment risk could guide sustainable growth and provide effective theoretical and technical support for the regulation of urban spatial structure to minimize urban heat environment risk.

Impact of Biophysical Mechanisms on Urban Heat Island Associated with Climate Variation and Urban Morphology

The rapid development of urban areas can potentially alter hydro-meteorological fluxes and lead to the Urban Heat Island (UHI) phenomenon. In this study, UHI intensity and its driving factors were estimated using the Community Land Model (CLM) in cities of Tokyo, Phoenix, Bandung, and Quito, with different landscapes and climates, as a step in risk assessment of urbanization phenomena. The UHI magnitude increased along with the ratio of the height to width (H/W) of urban canyons in cities with the same latitude, especially during the daytime, when Quito (Tokyo) had a higher UHI than Bandung (Phoenix). El Niño-Southern Oscillation (ENSO) events, such as El Niño and La Niña, contributed to UHI variability, during which the cities in the western (eastern) part of Pacific Ocean experienced a higher UHI during El Niño (La Niña). The UHI differences from total biophysical drivers between these events were highest in Tokyo during the daytime as a result of convection process, and in Phoenix during the nighttime due to the hot arid climate of the city. Our results suggest the need to consider climate variation beyond local site characteristics when mitigating heat stress and making decisions regarding urban development.

Quantifying the biophysical effects of forests on local air temperature using a novel three-layered land surface energy balance model

The well-documented energy balance dynamics within forest ecosystems are poorly implemented in studies of the biophysical effects of forests. This results in limitations to the accurate quantification of forest cooling/warming on local air temperature. Taking into consideration the forest air space, this study proposes a three-layered (canopy, forest air space and soil [CAS]) land surface energy balance model to simulate air temperature within forest spaces (T_af) and subsequently to evaluate its biophysical effects on forest cooling/warming, i.e., the air temperature gradient (∆T_a) between the T_af and air temperature of open spaces (T_ao) (∆T_a = T_af - T_ao). We test the model using field data for 23 sites across 10 cities worldwide; the model shows satisfactory performance with the test data. High-latitude forests show greater seasonal dynamics of ∆T_a, generating considerable cooling of local air temperatures in warm seasons but minimal cooling or even warming effects during cool seasons, while low-latitude tropical forests always exert cooling effects with less interannual variability. The interannual dynamics of ∆T_a are significantly related to the seasonality of solar geometry and canopy leaf phenology. The differences between forest canopy temperature (T_c) and T_ao, which are the two most important terms attributed by the CAS model in impacting T_af, explain a large part of forest cooling and warming (May-July: R² = 0.35; November-January: R² = 0.51). The novel CAS model provides a feasible way to represent the energy balance within forest ecosystems and to assess its impacts on local air temperatures globally.

Investigating the urbanization process and its impact on vegetation change and urban heat island in Wuhan, China

Rapid urbanization significantly changes vegetation coverage and heat distribution, which threatens the sustainable development and the quality of life. As the largest developing city in Central China, Wuhan was chosen as the experimental region. This study investigated the urbanization process of Wuhan from 1989 to 2917 based on Landsat data. Combined with MODIS EVI (Enhanced Vegetation Index) and LST (Land Surface Temperature) data, vegetation disturbance and surface urban heat island (SUHI) caused by urbanization were discussed for 2001-2017. Furthermore, correlation between ∆EVI (urban EVI minus rural EVI) and ∆LST (urban LST minus rural LST) was also conducted. The results were as follows: (1) Wuhan experienced a strong urbanization over the past 29 years, with an increasing urban expansion rate and the altered dominant urban expansion pattern (edge expansion and infilling). After the enhanced vegetation functions and urban increased structures, the urbanization finally caused the fragmented patches and irregular urban shapes. (2) Urbanization had a positive effect on LST but a negative effect on EVI. From 2001 to 2017, the highest increasing rate of ∆LST for the old urban area (OUA) and urbanized area (UA) was both observed in summer daytime (OUA, 0.106 °C/a; UA, 0.207 °C/a). The decreasing rate of ∆EVI reached the highest value in summer (OUA, 0.00697/a; UA, 0.00298/a). (3) There was a strong negative correlation (except spring and winter for OUA) between ∆EVI and ∆LST in daytime, which proved that the activity of vegetation in daytime could relieve LST to a certain extent. This study clarifies the dynamic urbanization process of Wuhan and discusses its impacts on vegetation change and SUHI. Efficiently investigating urbanization process and quantifying its impacts on urban environment are critical for regional ecological conservation.

Magnitude of urban heat islands largely explained by climate and population

Urban heat islands (UHIs) exacerbate the risk of heat-related mortality associated with global climate change. The intensity of UHIs varies with population size and mean annual precipitation, but a unifying explanation for this variation is lacking, and there are no geographically targeted guidelines for heat mitigation. Here we analyse summertime differences between urban and rural surface temperatures (ΔT_s) worldwide and find a nonlinear increase in ΔT_s with precipitation that is controlled by water or energy limitations on evapotranspiration and that modulates the scaling of ΔT_s with city size. We introduce a coarse-grained model that links population, background climate, and UHI intensity, and show that urban-rural differences in evapotranspiration and convection efficiency are the main determinants of warming. The direct implication of these nonlinearities is that mitigation strategies aimed at increasing green cover and albedo are more efficient in dry regions, whereas the challenge of cooling tropical cities will require innovative solutions.

Using Remote Sensing Based Metrics to Quantify the Hydrological Response in a City

We propose a remote-sensing based metric approach to evaluate the hydrological response of highly urbanized areas and apply it to the city of Brussels. The model is set-up using 2 m resolution hyperspectral data. Next, it is upscaled to the city level, using multi-spectral Sentinel-2 data with 20 m resolution. We identify the total impervious area, the vegetation cover and the leaf area index as important metrics to derive a timeseries of spatially distributed net rainfall, runoff and infiltration from rainfall data. For the estimation of the actual evapotranspiration we use the potential evapotranspiration and the available water storage based on the interception, the depression storage and the infiltration. Additionally, we route the runoff to the outlet of selected sub-catchments. An important metric for the routing is the timing to the outlet which is approximated using the total impervious area and the hydrological distance to the outlet. We compare our approach to WetSpa model simulations and reach R 2 values of 98% for net rainfall, 95% for surface runoff, 99% for infiltration and 97% for cumulative evapotranspiration. The routing in the Watermaelbeek catchment is evaluated with discharge observations and reaches NSE values of 0.89 at a 2 m resolution and 0.88 at a 20 m resolution using an hourly timestep. At the timestep of 10 min and a 20 m resolution the NSE is reduced to 0.76. For the Roodebeek catchment we reach an NSE of 0.73 at a spatial resolution of 20 m and an hourly timestep. The results presented in this paper are optimistic for using spatial and temporal metrics retrieved from remote sensing data to quantify the water balance of urban catchments.

A Statistically Rigorous Approach to Experimental Design of Vertical Living Walls for Green Buildings

Living walls (LW) have been widely proposed as a form of green infrastructure to improve aesthetics, energy consumption, and microclimate in urban environments by adding densely-planted vegetation to the outside walls of buildings. Scientific studies using multiple treatments in a single LW face challenges due to the close physical proximity of different treatments, particularly the potential for plants above to influence those below. A study on a west-facing LW was undertaken to investigate 36 unique treatments in Adelaide, South Australia, for nine months. The LW comprised combinations of six native plant species, three soil substrates and two irrigation volumes. The LW consisted of 144 modular trays mounted on a wall in a 12 × 12 grid with four replicates of each treatment. The location of each treatment was designed to account for a cascading carry-over effect that may be present when one plant is placed above another. Carry-over effect of the model designed showed mixed results among the plant groups identified. It was also found that long-form plants can significantly shade smaller plants below them. Experimental research into the performance of plants in mixed species LW should consider the carry-over effect to account for this.

Land Use Change and Climate Variation in the Three Gorges Reservoir Catchment from 2000 to 2015 Based on the Google Earth Engine

Possible environmental change and ecosystem degradation have received increasing attention since the construction of Three Gorges Reservoir Catchment (TGRC) in China. The advanced Google Earth Engine (GEE) cloud-based platform and the large number of Geosciences and Remote Sensing datasets archived in GEE were used to analyze the land use and land cover change (LULCC) and climate variation in TGRC. GlobeLand30 data were used to evaluate the spatial land dynamics from 2000 to 2010 and Landsat 8 Operational Land Imager (OLI) images were applied for land use in 2015. The interannual variations in the Land Surface Temperature (LST) and seasonally integrated normalized difference vegetation index (SINDVI) were estimated using Moderate Resolution Imaging Spectroradiometer (MODIS) products. The climate factors including air temperature, precipitation and evapotranspiration were investigated based on the data from the Global Land Data Assimilation System (GLDAS). The results indicated that from 2000 to 2015, the cultivated land and grassland decreased by 2.05% and 6.02%, while the forest, wetland, artificial surface, shrub land and waterbody increased by 3.64%, 0.94%, 0.87%, 1.17% and 1.45%, respectively. The SINDVI increased by 3.209 in the period of 2000-2015, while the LST decreased by 0.253 °C from 2001 to 2015. The LST showed an increasing trend primarily in urbanized area, with a decreasing trend mainly in forest area. In particular, Chongqing City had the highest LST during the research period. A marked decrease in SINDVI occurred primarily in urbanized areas. Good vegetation areas were primarily located in the eastern part of the TGRC, such as Wuxi County, Wushan County, and Xingshan County. During the 2000–2015 period, the air temperature, precipitation and evapotranspiration rose by 0.0678 °C/a, 1.0844 mm/a, and 0.4105 mm/a, respectively. The climate change in the TGRC was influenced by LULCC, but the effect was limited. What is more, the climate change was affected by regional climate change in Southwest China. Marked changes in land use have occurred in the TGRC, and they have resulted in changes in the LST and SINDVI. There was a significantly negative relationship between LST and SINDVI in most parts of the TGRC, especially in expanding urban areas and growing forest areas. Our study highlighted the importance of environmental protection, particularly proper management of land use, for sustainable development in the catchment.