Urban Thermal Environment Research Articles

Thermal comfort differences between urban villages and formal settlements in Chinese developing cities: A case study in Shenzhen

Rapid urbanization has changed the urban spatial form, which directly leads to the emergence of urban informal settlements, and the impact on ecological environment is manifested as the obvious deterioration of urban thermal environment. The thermal environment of informal settlements, which are called urban villages in China, is seriously deteriorated. In the process of urban renewal, we should pay attention to the thermal environment effect of urban villages and promote the sustainable development of cities. However, at present there are few studies on the differences of thermal comfort among urban settlements. Taking Shenzhen as an example city, this paper distinguished several scopes such as urban villages, formal settlements and non-urban areas, then analyzed the pattern characteristics of urban thermal comfort by using the Modified Temperature and Humidity Index (MTHI), and finally explored the spatial relationship between thermal comfort and various environmental factors through spatial regression models. The results show that (1) thermal comfort has significant spatial autocorrelation and the thermal environment centers are clustered in built-up areas of Shenzhen city. The overall MTHI of urban villages is relatively the highest, and the dominant thermal comfort level in summer is sultry and hot. (2) According to the Spatial Error Model, the green space coverage represented by NDVI has the strongest mitigation effect on urban thermal comfort, and the building density has an obvious aggravating effect on the muggy environment. Both of them have more obvious effects on the thermal comfort of informal settlements. (3) The current thermal environment of urban settlements cannot be ignored, especially in urban villages. In the process of urban renewal, heat dissipation should be considered emphatically. Increasing urban green area and decreasing building density will help to improve urban thermal environment. The study can provide suggestions for urban renewal from the perspective of improving thermal environment.

Quantifying the Relationship between 2D/3D Building Patterns and Land Surface Temperature: Study on the Metropolitan Shanghai

In the context of urban warming associated with rapid urbanization, the relationship between urban landscape patterns and land surface temperature (LST) has been paid much attention. However, few studies have comprehensively explored the effects of two/three-dimensional (2D/3D) building patterns on LST, particularly by comparing their relative contribution to the spatial variety of LST. This study adopted the ordinary least squares regression, spatial autoregression and variance partitioning methods to investigate the relationship between 2D/3D building patterns and summertime LST across 2016–2017 in Shanghai. The 2D and 3D building patterns in this study were quantified by four 2D and six 3D metrics. The results showed that: (1) During the daytime, 2D/3D building metrics had significant correlation with LST. However, 3D building patterns played a significant role in predicting LST. They explained 51.0% and 10.2% of the variance in LST, respectively. (2) The building coverage ratio, building density, mean building projection area, the standard deviation of building height, and mean building height highly correlated with LST. Specifically, the building coverage ratio was the main predictor, which was obviously positively correlated with LST. The correlation of building density and average projected area with LST was positive and significant, while the correlation of building height standard deviation and average building height with LST was negative. The increase in average height and standard deviation of buildings and the decrease in building coverage ratio, average projected area, and density of buildings, can effectively improve the urban thermal environment at the census tract level. (3) Spatial autocorrelation analysis can elaborate the spatial relationship between building patterns and LST. The findings from our research will provide important insights for urban planners and decision makers to mitigate urban heat island problems through urban planning and building design.

Assessing Surface Urban Heat Island Related to Land Use/Land Cover Composition and Pattern in the Temperate Mountain Valley City of Kathmandu, Nepal

Rapid urban growth has coincided with a substantial change in the environment, including vegetation, soil, and urban climate. The surface urban heat island (UHI) is the temperature in the lowest layers of the urban atmosphere; it is critical to the surface’s energy balance and makes it possible to determine internal climates that affect the livability of urban residents. Therefore, the surface UHI is recognized as one of the crucial global issues in the 21st century. This phenomenon affects sustainable urban planning, the health of urban residents, and the possibility of living in cities. In the context of sustainable landscapes and urban planning, more weight is given to exploring solutions for mitigating and adapting to the surface UHI effect, currently a hot topic in urban thermal environments. This study evaluated the relationship between land use/land cover (LULC) and land surface temperature (LST) formation in the temperate mountain valley city of Kathmandu, Nepal, because it is one of the megacities of South Asia, and the recent population increase has led to the rapid urbanization in the valley. Using Landsat images for 2000, 2013, and 2020, this study employed several approaches, including machine learning techniques, remote sensing (RS)-based parameter analysis, urban-rural gradient analysis, and spatial composition and pattern analysis to explore the surface UHI effect from the urban expansion and green space in the study area. The results revealed that Kathmandu’s surface UHI effect was remarkable. In 2000, the higher mean LST tended to be in the city’s core area, whereas the mean LST tended to move in the east, south, north, and west directions by 2020, which is compatible with urban expansion. Urban periphery expansion showed a continuous enlargement, and the urban core area showed a predominance of impervious surface (IS) on the basis of urban-rural gradient analysis. The city core had a lower density of green space (GS), while away from the city center, a higher density of GS predominated at the three time points, showing a lower surface UHI effect in the periphery compared to the city core area. This study reveals that landscape composition and pattern are significantly correlated with the mean LST in Kathmandu. Therefore, in discussing these findings in order to mitigate and adapt to prominent surface UHI effects, this study provides valuable information for sustainable urban planning and landscape design in mountain valley cities like Kathmandu.

Predicting spatial and temporal changes in surface urban heat islands using multi-temporal satellite imagery: A case study of Tehran metropolis

Nowadays, predicting spatial and temporal changes of surface urban heat islands (SUHIs) is both a demanding challenge and a subject of interest for researchers working on urban thermal environments. This study aimed to predict the spatial-temporal changes of SUHI in Tehran city. The research data consisted of Landsat multi-temporal images, MODIS-derived water vapor and land surface temperature (LST) products, as well as climatic data. The cellular automata (CA)-Markov model was used for predicting the spatial and temporal land cover changes. Afterward, based on the statistical and spatial information of the impact of land cover changes on LST changes, maps of the LST and SUHII were procured for future years. The results showed that the area of built-up lands increased by 88% from 1985 to 2019. The built-up lands area is expected to increase to 446.3, 463.9, and 480.1 km2 by 2026, 2032, and 2038, respectively. The mean LST of Tehran city in 1985, 1992, 2000, 2009, and 2019 was 36.45, 41.95, 43.15, 44.95, and 47.25 °C, respectively. By 2026, 2032, and 2038, the mean LST may reach 48.65, 49.95, and 51.15 °C, respectively. Analysis of the SUHI ratio index in Tehran showed an increase from 0.01 in 1985 to 0.34 in 2019, and is expected to reach 0.38, 0.45, and 0.51 by 2026, 2032, and 2038, respectively.

The renew plans of urban thermal environment optimization for traditional districts in Xi'an, China.

During the process of the high-speed urbanization in Chinese cities, the social, economic, and political status and the interaction between each factor have been more focused on urban traditional district renewal. However, the effects on urban microclimate and the residential living conditions in traditional districts are not well discussed, which is strongly related to the living comfort and citizens' well-being. In this study, two typical traditional districts in Xi'an are selected. According to the original situation of building functions and the community characteristics, two renewal plans are proposed by adding vegetation in open spaces (V), and adding vegetation combined with building redevelopment (V&B), in order to balance the living convenience and thermal environment. Via ENVI-met simulation, the effects of the district renewal plans on thermal environment including wind speed, air temperature, and mean radiant temperature are evaluated. This study provides method of environmental evaluation for traditional district renewal, which contributes to sustainable urban planning in historical districts, and provides recommendations for related policy development.

Evaluating the Influence of Different Layouts of Residential Buildings on the Urban Thermal Environment

Urban residential building layouts have an impact on air temperature and thermal comfort. Research has shown that poorly designed building layouts can lead to thermal discomfort. Thus, it is crucial to analyze the relationship between residential building layouts and air temperature. We used the ENVI-met 3D microclimate model to simulate six typical residential building layouts and explore the diurnal and seasonal variations in air temperature. In addition, we used the physiological equivalent temperature (PET) as the evaluation index for the thermal comfort of different building layouts. The diurnal results showed that the air temperature of the parallel layout rose faster and fell faster, and these changes were more significant in summer. The results of the air temperature classifications indicated that the frequency of low-air-temperature areas in the parallel layout is approximately 12% smaller than that of the enclosed and semi-enclosed layouts, and the high-air-temperature area frequency is 11% higher than that of the enclosed and semi-enclosed layouts in summer. In winter, the frequency of low-air-temperature areas in the parallel layout is approximately 7% smaller than that of the enclosed and semi-enclosed layouts, and the high-air-temperature area frequency is 5% higher than that of the enclosed and semi-enclosed layouts. In combination with the PET results, we found that the enclosed layout is the optimal configuration. Moreover, in some cases, increased building height and vegetation lead to a reduction in air temperature.

How Are Land-Use/Land-Cover Indices and Daytime and Nighttime Land Surface Temperatures Related in Eleven Urban Centres in Different Global Climatic Zones?

Improving the urban thermal environment can enhance humans’ well-being. Nevertheless, it was not clear which land-use/land-cover (LU/LC) indices were optimal for explaining land surface temperatures (LSTs) and how they affected LSTs in cities in different climatic zones, especially during the nighttime. Thus, the Aqua/MODIS and Landsat/OLI data were mainly used to explore the optimal indices of building, vegetation, water and bare soil and to analyze their effects on LSTs in eleven urban centers in global distinct climatic regions. Results showed several LU/LC indices had high probabilities of being optimal indices to explain LSTs under different conditions. The daytime LSTs were usually significantly negatively correlated with vegetation indices and positively correlated with building and bare soil indices (p < 0.05). These relationships were stronger in the summer than winter. The nighttime LSTs were usually significantly positively and negatively correlated with building and vegetation indices in the summer, respectively (p < 0.05). These correlations were generally weaker during the nighttime than daytime. The nighttime LSTs were significantly positively and negatively correlated with water and bare soil indices, respectively (p < 0.05). Significant linear multiple regressions commonly existed between daytime and nighttime LSTs and four kinds of LU/LC indices (p < 0.05). These findings helped optimize urban thermal comfort, downscale city LSTs, etc.

Temporal and Spatial Variation of Land Surface Temperature in Recent 20 Years and Analysis of the Effect of Land Use in Jiangxi Province, China

Under the background of global warming, it is of great significance to study the temporal and spatial evolution of land surface temperature (LST) on long-time scale and the impacts of land use in the fields of urban thermal environment and regional climate change. Based on MODIS LST long time series remote sensing data, the temporal and spatial evolution characteristics of pixel-wise LST in Jiangxi Province, the middle inland province of China from 2000 to 2020 were analyzed by using Theil-Sen + Mann-Kendall, coefficient of variation and Hurst index, and the response of LST to land use was identified by combining the contribution and diversity index. The results showed as follows: (1) LST was generally distributed as "high in Middle-East-West-South and low in North-northwest-southeast direction". LST showed an overall downward trend, indicating a weakening of the warming trend. The dynamic trend of LST was characterized by more descending than ascending tendency. The dynamic stability showed a coexistence of high and low fluctuation tendency, with a higher proportion of medium and low fluctuation areas having obvious spatial differences. The overall dynamic sustainability was characterized by uncertainty of future change trend. (2) The LST were strongly affected by land use in the past 20 years. Firstly, the areas of high LST were mostly located in construction land and unused land, while the areas of low LST were mostly in water area and forest land. However, forest land and water area of high temperature were gradually turned to construction land later on. Secondly, the land use structure and pattern had an strong effects on LST. With the increase of the area proportion of different land use, the LST showed significant differences. The more complex the spatial pattern of land use, the more obvious its impact on LST. The research results will provide some reference for the regions with the same characteristics as Jiangxi Province to deal with LST under the background of global climate change.

Spatiotemporal Characteristics of Public Recreational Activity in Urban Green Space under Summer Heat

The urbanization process has contributed to the deterioration of the urban thermal environment and increased the frequency of heat waves in summer that damage public health. Urban green space is the space for the public to escape the summer heat. The cooling effect of urban green space (UGS) can encourage outdoor activities and enhance public health. Analysis of when and how the public utilizes UGS under summer heat can serve as a guide for UGS improvements. In this study, the Hot Spring Park in Fuzhou City, China was utilized as a case study to examine the characteristics of the public recreational behaviors and their influencing factors under summer heat. Results showed the following observations: (1) Canopy density and turf coverage played key roles in regulating the thermal environment. (2) UGS can accommodate multiple summertime behaviors with considerable spatiotemporal variations. (3) In the hot summer, the frequency of recreational activities in UGS was negatively correlated with temperature. Dynamic behaviors were significantly impacted by temperature. Older and younger groups were less heat-tolerant. Based on this, we propose countermeasures and suggestions that are tailored to the needs of urban residents and their behavior characteristics for the planning and management of urban parks in the summer heat.

Study on Urban Thermal Environment in Beijing Based on Local Climate Zone Method

In recent years, with the introduction of the concept of a local climate zone (LCZ), researchers have proved that adding an LCZ to the Weather Research and Forecasting (WRF) Model can improve the simulation effect. However, many existing studies cannot explain whether the improvement of accuracy in the model results is the effect of the refined zone or the effect of urban area correction, so they cannot explain the advantages of LCZ data. Therefore, this paper uses remote sensing images to generate two kinds of land use data sets and introduces them into the Weather Research and Forecasting Model coupled with the building energy model (WRF-BEM). In this paper, the two factors of urban area expansion and fine classification are considered, and three numerical examples are set up to simulate high-temperature weather in August 2019. The research shows that the simulated 2 m temperature of the scheme of correcting only urban area is the closest to the observed data. Although the RMSE in the 2 m temperature simulated by the LCZ scheme is 0.43 °C higher than that of the scheme of correcting only the urban area, it can well reproduce the spatial variation characteristics of 2 m temperature. In addition, different urban morphologies affect the spatial distribution of the surface urban heat islands in Beijing. High surface urban heat island effect zones mainly appear in the compact low-rise, compact mid-rise, and large low-rise types.

Urban form centrality and thermal environment: An empirical study of Chinese megacities

• Concentric urban form leads to the monocentric urban thermal environment. • Intensively concentric urban form has cooling potential on the built-up area. • Stability of urban form centrality significantly impacts LST aggregation. • Restraining urban sprawl could improve urban thermal environment. This paper examines the response of the urban thermal environment to the centrality of urban spatial development. By investigating 27 cases of Chinese megacities, the study quantified the urban form centrality and the spatial pattern of land surface temperature (LST) within built-up areas. Specifically, urban form centrality was measured using the concentric-ring partitioning model, and the landscape metrics and Moran's I were employed to characterize the LST pattern. Then, the correlation between urban form centrality and the LST pattern was examined through ordinary least squares models and global and local bivariate Moran's I. There are three significant findings. First, the urban form centrality dominates the LST centrality along the urban-rural gradient. Second, stably concentric urban forms were inclined toward shape agglomerative and autocorrelated hot areas. Third, enhancing the intensity and reducing the stability of the urban form centrality are preferable to mitigate the urban thermal environment. Fourth, the green space should be embedded around the edge of the built-up area to increase the energy exchange surface. In general, this study has developed a nuanced understanding of the urban form and urban thermal environment and provide climate change adoption strategies for urban planning and public health policies.

Urban thermal environment effects based on visual indices: A case study in Xuzhou City, China

Urban thermal environments are closely related to habitats, citizens' health, and sustainable development. Based on green view index (GVI), we proposed two new visual indices, construction view index (CVI) and imperious surface view index (R&PVI). Mobile observation was used to obtain urban thermal environment data, images and coordinates synchronously in Xuzhou City in late summer, including urban area (U), scenic area (S), exterior of university campus (E), and university campus inside (CUMT). We analyzed the impacts of the urban composition represented by the visual index on the urban thermal environment. The results showed that, along the sampling line, mean air temperature (Ta) was highest (30.42 ℃) and mean relative humidity (RH) was lowest (40.7%) in urban area, while mean Ta was lowest (29.35 ℃) and mean RH was highest (48.4%) in scenic area. The situation of mean wind-chill temperature (TaW) was the highest (32.95 ℃) in the urban area and the lowest (31.93 ℃) in the scenic area. As for CVI, urban area, university campus inside, exterior of university campus and scenic area ranked in descending order, while GVI showed an opposite pattern. CVI was significantly positively correlated to Ta and TaW, but negatively to RH. GVI was significantly negatively correlated to Ta and TaW, but positively to RH. R&PVI was significantly positively correlated to Ta and TaW, but not correlated to RH. CVI and GVI influenced Ta significantly, with the independent effects being 10.4% and 18.9%, and joint effects being 7.8% and 11.3%, respectively. As for RH, CVI and GVI contributed significantly as well, independent effects were 37.5% and 15.7%, and joint effects were 51.4% and 30.2%, respectively. As for TaW, the three visual indices contributed significantly, but independent and joint effects were lower than those on Ta. Moreover, visual indices contributed more on RH than Ta or TaW. The results could provide ideas for optimizing urban thermal environments and mitigating urban heat island effects, and have practical implications for urban renewal and improvement of the quality of human living environment.

Prediction of the future urban heat island intensity and distribution based on landscape composition and configuration: A case study in Hangzhou

• The relationship between landscape patterns and SUHII were detected by SMLR model. • The SUHII in 2030 in Hangzhou were predicted using a RF model. • Implications for mitigating SUHI through landscape optimization were suggested. During rapid urbanization, global land use and land cover change drastically, leading to increasingly severe problems in the urban environment. Among them, the urban heat island effect has attracted much attention owing to its magnification effect on climate change and its negative role in urban livability and sustainable development. In this context, predicting the future surface urban heat island intensity (SUHII) and distribution is important in dealing with the urban thermal environment. In this study, we conducted a prediction of SUHII using a random forest model based on future landscape patterns. According to the results, the built-up area is expected to grow to 3740.67 km 2 , and the non-forest green space (GS2) is estimated to decrease by 1130.96 km 2 by 2030. In the context of urban expansion, the area with SUHII of higher than 5 °C will increase significantly, showing a more concentrated spatial distribution, while the region with SUHII of below −2.5 °C will decrease in coverage. In addition, our results showed that the scattered built-up areas and GS1, as well as concentrated GS2, will contribute to reducing SUHII. The results are expected to help policymakers and urban planners to design reasonable measures for achieving sustainable urban development.

Is the design guidance of color and material for urban buildings a good choice in terms of thermal performance?

In the design of urban buildings, regionality is take into account to ensure that the colors and materials used are consistent with the surrounding environment and urban development. This helps maintain the urban characteristics and local cultural values. However, the effects on the thermal environment are typically not considered in this process. To explore the rationality of the current urban design guidance, a field study was conducted in Xi'an-iHarbour. The surface temperatures of buildings with different colors and materials were investigated, and the solar radiation received by these surfaces was measured. The results show that variations in surface colors can lead to considerable differences in surface temperature, which are strongly and positively correlated with the amount of solar radiation received. In addition, the thermal inertia of the material can significantly influence the daily variation in the surface temperature. The current guidelines for Xi'an urban design have been found to be inappropriate. Low-thermal-inertia materials and light colors have been suggested to improve the urban thermal environment of Xi'an. The findings of this research provide insights on the thermal performance of building surfaces and provide ideas for the architectural design of other cities that also have thermal environmental concerns.

Assessing the thermal environments of parking lots in relation to their shade design characteristics

The conventional surface parking lots lead to prominent urban thermal environment problems. Therefore, it is important to explore the design form of the parking lot that can generate more thermal benefits. In this study, we compared the differences in the thermal environments of eight common urban parking lots in Hangzhou, China, and analyzed their main influencing characteristics. Results show that air temperature and relative humidity differed little among the studied parking lots, with the maximum mean differences during the daytime being only 0.7–0.8 °C and 3.2–3.3%, respectively; however, the globe temperature, surface temperature, and mean radiant temperature had significant differences, with the maximum mean differences of 11.6, 10.6, and 13.6 °C, respectively. Among the factors, shade had an important effect on the thermal environment of the parking lot. We found that the cooling effect of trees was stronger than that of shading devices for the same shaded area. In addition, the combination of trees and mesh enhanced thermal benefits and has great application prospects, especially for the low coverage trees. Increase in grass cover can weaken the negative effects on the air environment of the mesh and more effectively reduce the surface temperature.

A mathematical model for a rapid calculation of the urban canyon albedo and its applications

Urban canyon albedo (UCA) is a primary indicator used to evaluate the impact of urban geometry on radiation absorption. A rapid and effective theoretical calculation for the UCA is helpful in urban design. This research establishes a simplistic but robust mathematical model for calculating the UCA. The model was validated using prior observational studies showing that the maximum root mean square error (RMSE) is 0.03, and the minimum Pearson correlation coefficient (r) is 0.63. The model was then used to evaluate the influence of urban canyon geometry and materials on UCA. The results show that the canyon aspect ratio controls the UCA, especially when the canyon aspect ratio is less than 4. Furthermore, high-albedo facades can effectively increase UCA, and high-albedo pavements are recommended only if the urban canyon aspect ratio is less than 1. Finally, the solar performance of urban canyons on an urban scale was estimated by combining our model with digital elevation model (DEM) data. This study can be used in urban planning to estimate the radiation performance of an urban canyon quickly before full-scale urban thermal environment simulation.

Three-dimensional visualization of thermal environments in urban canyons

Temperature distribution in urban canyons is dynamic, complex, and influenced by a range of heat resources such as radiant heat from reflected sunlight and convective heat from wind flow. While 2D data collection and presentation are the norm for UHI research, we propose using an unmanned aerial vehicle to measure temperatures at different horizontal and vertical locations in urban canyons to develop a 3D visualization of urban thermal environments. We implemented Gestalt laws and transparent and opaque color-coding to improve background recognition and visual closure as well as to better represent the spatiality of temperature data. Our design included grouped color pixels and an interactive temperature slider function. We investigated whether interface usage varied with the flexibility of closure, perceptual speed, and spatial relations of users. Responses from 102 participants indicated that users with flexibility in closure approved of the transparent colors and slider. The primary advantage of this visual model is the elimination of clutter. Visual clutter can cause users to lose their focus when searching a 2D representation of a 3D geographic space. In the proposed model, data hotspots and the boundaries produced by multiple aggregations and clustering enable users to readily and easily find the required information.

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

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

Spatiotemporal variation of urban thermal environment and its relationship with urban expansion types from 2000 to 2020: a case of Huai’an central urban area, Huai’an, China

It is critically important to understand the variation of urban thermal environment since urban heat island (UHI) effect is one of the most worrisome urban environment and impedes urban sustainable development. Taking Huai’an central urban area in China as a case, Landsat images from 2000 to 2020 were used, we first estimated land surface temperature (LST) and land covers based on google earth engineer (GEE) platform. Then explored annual variation of SUHI and urban expansion types using statistics method and urban landscape Analysis tools. Finally, discussed the heat effect of urban expansion types and directions. The results showed that (1) SUHI patches gradually concentrated in Phase I, while in Phase II, concentrated SUHIs spread continuously from urban centre to rural area, changing from two centres to a polycentric pattern. (2) Urban expansion was characterized as a diffusion and coalescence process, extension type is the most dominant urban growth mode, second is leapfrog type, and the smallest is infilling type. (3) Annual trend of NLST shows an increasing trend for all three urban expansion types during the last two decades, which of extension mode was biggest, while, that of infilling growth was smallest. This research can attribute a better understanding for the impact of urban expansion on surface heat island effects.

(Re)Designing Urban Parks to Maximize Urban Heat Island Mitigation by Natural Means

Urban trees play a key role in mitigating urban heat by cooling the local environment. However, the cooling benefit that trees can provide is influenced by differences in species traits and site-specific environmental conditions. Fifteen dominant urban tree species in parks from Mexico City were selected considering physiological traits (i.e., transpiration and stomatal conductance) and aesthetic and morphological characteristics. Species’ physiological performance was measured to explore the potential of trees to reduce urban heat load. Data were collected over a 4-week period in the months of April and May 2020, the warmest and driest months of the year in Mexico City. We used the Thermal UrbaN Environment Energy (TUNEE) balance model to calculate the cooling benefit of each species and the number of individuals necessary to reduce local air temperature. The highest midday transpiration was registered for Liquidambar styraciflua L. (0.0357 g m−2 s−1) and the lowest for Buddleja cordata H.B.K (0.0089 g m−2 s−1), representing an energy consumption and cooling potential of 87.13 and 21.69 J m−2 s−1, respectively. Similarly, the highest stomatal conductance was recorded for L. styraciflua., whereas the lowest was recorded for B. cordata. Based on the species transpiration rates and aesthetic characteristics, we developed a proposal and outline for a 50 × 50 m urban park (i.e., park community) consisting of six species with 19 individuals, and according to the TUNEE model, the proposed arrangement can reduce air temperature up to 5.3 °C. Our results can help urban planners to (re)design urban parks to mitigate urban heat while increasing urban tree diversity in parks.