Increasing urbanization is likely to intensify the urban heat island effect, decrease outdoor thermal comfort, and enhance runoff generation in cities. Urban green spaces are often proposed as a ...mitigation strategy to counteract these adverse effects, and many recent developments of urban climate models focus on the inclusion of green and blue infrastructure to inform urban planning. However, many models still lack the ability to account for different plant types and oversimplify the interactions between the built environment, vegetation, and hydrology.
In this study, we present an urban ecohydrological model, Urban Tethys-Chloris (UT&C), that combines principles of ecosystem modelling with an urban canopy scheme accounting for the biophysical and ecophysiological characteristics of roof vegetation, ground vegetation, and urban trees. UT&C is a fully coupled energy and water balance model that calculates 2 m air temperature, 2 m humidity, and surface temperatures based on the infinite urban canyon approach. It further calculates the urban hydrological fluxes in the absence of snow, including transpiration as a function of plant photosynthesis. Hence, UT&C accounts for the effects of different plant types on the urban climate and hydrology, as well as the effects of the urban environment on plant well-being and performance.
UT&C performs well when compared against energy flux measurements of eddy-covariance towers located in three cities in different climates (Singapore, Melbourne, and Phoenix).
A sensitivity analysis, performed as a proof of concept for the city of Singapore, shows a mean decrease in 2 m air temperature of 1.1 ∘C for fully grass-covered ground, 0.2 ∘C for high values of leaf area index (LAI), and 0.3 ∘C for high values of Vc,max (an expression of photosynthetic capacity). These reductions in temperature were combined with a simultaneous increase in relative humidity by 6.5 %, 2.1 %, and 1.6 %, for fully grass-covered ground, high values of LAI, and high values of Vc,max, respectively. Furthermore, the increase of pervious vegetated ground is able to significantly reduce surface runoff.
Rapid and uncontrolled urbanization in tropical Africa is increasingly leading to unprecedented socio-economical and environmental challenges in cities, particularly urban heat and climate change. ...The latter calls for a better representation of tropical African cities’ properties relevant for urban climate studies. Here, we demonstrate the possibility of collecting urban canopy parameters during a field campaign in the boreal summer months of 2018 for deriving a Local Climate Zone (LCZ) map and for improving the physical representation of climate-relevant urban morphological, thermal and radiative characteristics. The comparison of the resulting field-derived LCZ map with an existing map obtained from the World Urban Data and Access Portal Tool framework shows large differences. In particular, our map results in more vegetated open low-rise classes. In addition, site-specific fieldwork-derived urban characteristics are compared against the LCZ universal parameters. The latter shows that our fieldwork adds important information to the universal parameters by more specifically considering the presence of corrugated metal in the city of Kampala. This material is a typical roofing material found in densely built environments and informal settlements. It leads to lower thermal emissivity but higher thermal conductivity and capacity of buildings. To illustrate the importance of site-specific urban parameters, the newly derived site-specific urban characteristics are used as input fields to an urban parametrization scheme embedded in the regional climate model COSMO-CLM. This implementations decreases the surface temperature bias from 5.34 to 3.97 K. Based on our results, we recommend future research on tropical African cities to focus on a detailed representation of cities, with particular attention to impervious surface fraction and building materials.
To build healthy, resilient, and climate‐responsive cities, planners need ways to understand the local complexities of urban thermal climates. To assist in meeting this need, this study employs the ...simple classification of “local climate zones” (LCZs) to conduct a spatiotemporal thermal climatic analysis of the Toulouse Metropolitan Region (France) under warm and dry summer conditions. Simulations are performed using the mesoscale atmospheric model Méso‐NH. These simulations provide a city‐wide spatial coverage of 2‐m air temperature (T2M), mean radiant temperature (MRT), and Universal Thermal Climate Index (UTCI). Model parameters describing the urban morphology are initialized based on administrative databases and independent of LCZ maps, which allows for an evaluation of whether the distributions of the modelled thermal climatic parameters will differ between LCZs. The results show that different LCZs possess significantly different distributions of T2M and MRT, confirming the suitability of the LCZ scheme for discerning the thermal environment of Toulouse. Compact urban settings (LCZ 1/2/3) show the highest T2M throughout the day and a nocturnal temperature difference of up to 2.8 K compared to rural settings. The MRT of LCZ 1/2/3 in the late afternoon (1700–2000 LST (UTC + 2)) can be as much as 6.3 K lower than it is for LCZs with open settings due to shading by dense urban structures. Additional analysis reveals that the intra‐LCZ variabilities of T2M and MRT may be explained by the distance to the city centre. Finally, the thermal stress in different LCZs is assessed with the modelled UTCI. Among the built LCZs, the probability of strong heat stress is the highest for open high/mid‐rise (LCZ 4/5) and lowest for sparsely built (LCZ 9) and open low‐rise (LCZ 6) settings. For land cover type LCZs, dense trees (LCZ A) are the most favourable for daytime outdoor human thermal comfort.
Distributions of air temperature at 2 m above ground and mean radiant temperature for different local climate zones (LCZs) in Toulouse Metropolitan Region (southern France). Thermal climatic parameters are taken from simulations with the mesoscale atmospheric model Méso‐NH for calm and sunny summer days. Distinct thermal characteristics are identified for different LCZs, notably the warmer built‐up LCZs during the night and the lower mean radiant temperatures for compact LCZ 1/2/3 and dense trees (LCZ A) due to shading in the day.
The urban climate map (UCMap) system has been widely applied in climate-friendly urban design. To facilitate accurate and effective UCMap construction, this study combines the urban energy balance ...calculation model (UDC) and local climate zone (LCZ) parameterization to obtain dynamic block-scale urban climatic parameters. The study area is the Higher Education Mega Center (HEMC) of Guangzhou, and a block-based LCZ classification methodology is proposed to generate an LCZ map of the HEMC. Then a framework is established by integrating the LCZ parameterization and UDC model to obtain a spatiotemporal UCMap atlas of the HEMC. The results show that the overall average local-scale urban heat island intensity (LUHII) and urban wet island intensity (LUWII) vary by 4.99 °C and 3.87 g/kg, respectively, over 24 h. Regarding the spatial distributions, the average LUHII and LUWII reach maximum values of 6.6 °C and 1.3 g/kg, respectively, within the HEMC. Additionally, correlation analysis of the physical property parameters and simulated climatic parameters shows that among the physical parameters, both the sky view factor and pervious surface fraction (PSF) have significant positive effects on the LUHII, whereas only the PSF has a positive effect on the LUWII. Furthermore, quantitative equations describing these relationships are derived, and climate problem zones are defined in terms of temperature and humidity. Identification of these climate problem zones within the HEMC enables appropriate optimization measures to support climate-friendly urban planning.
•A block-based LCZs classification methodology is proposed.•The LCZs parameterization and UDC model is integrated into UCMap making.•Hourly thermal and humid UCMap atlas are displayed.•Spatial morphology optimization strategy for the climate problem zones is presented.
Significance Many case studies of specific cities have investigated factors that contribute to urban energy use and greenhouse-gas emissions. The analysis in this study is based on data from 274 ...cities and three global datasets and provides a typology of urban attributes of energy use. The results highlight that appropriate policies addressing urban climate change mitigation differ with type of city. A global urbanization wedge, corresponding in particular to energy-efficient urbanization in Asia, might reduce urban energy use by more than 25%, compared with a business-as-usual scenario.
The aggregate potential for urban mitigation of global climate change is insufficiently understood. Our analysis, using a dataset of 274 cities representing all city sizes and regions worldwide, demonstrates that economic activity, transport costs, geographic factors, and urban form explain 37% of urban direct energy use and 88% of urban transport energy use. If current trends in urban expansion continue, urban energy use will increase more than threefold, from 240 EJ in 2005 to 730 EJ in 2050. Our model shows that urban planning and transport policies can limit the future increase in urban energy use to 540 EJ in 2050 and contribute to mitigating climate change. However, effective policies for reducing urban greenhouse gas emissions differ with city type. The results show that, for affluent and mature cities, higher gasoline prices combined with compact urban form can result in savings in both residential and transport energy use. In contrast, for developing-country cities with emerging or nascent infrastructures, compact urban form, and transport planning can encourage higher population densities and subsequently avoid lock-in of high carbon emission patterns for travel. The results underscore a significant potential urbanization wedge for reducing energy use in rapidly urbanizing Asia, Africa, and the Middle East.
The scaling of urban climate action and its governance is rapidly becoming a central focus in the urban climate governance literature and policy debates. Building on the broader scaling literature ...and inspired by related initiatives in other fields, this article calls for the development of a systematic “science of scaling” for urban climate governance. Such a science of scaling may help to give a better understanding of how well-performing urban climate action and its governance can be multiplied, accelerated and broadened (ie horizontal and vertical scaling and scaling out, up and down), and it may help to uncover scaling trajectories towards systemic change in cities (ie deep scaling).
Street aspect ratios and urban thermal storage largely determine the thermal environment in cities. By performing scaled outdoor measurements in summer of 2017 in Guangzhou, China, we investigate ...these impacts on spatial/temporal characteristics of urban thermal environment which are still unclear so far. Two types of street canyon models are investigated, i.e. the ‘hollow’ model resembling hollow concrete buildings and the ‘sand’ model consisting of buildings filled with sand attaining much greater thermal storage. For each model, three street aspect ratios (building height/street width, H/W = 1, 2, 3; H = 1.2 m) are considered.
The diurnal variations of air-wall surface temperatures are observed and their characteristics are quantified for various cases. The daily average temperature and daily temperature range (DTR) of wall temperature vary significantly with different aspect ratios and thermal storage. During the daytime, wider street canyon (H/W = 1) with less shading area experiences higher temperature than narrower ones (H/W = 2, 3) as more solar radiation received by wall surfaces. At night, wider street canyon cools down quicker due to stronger upward longwave radiation and night ventilation. For hollow models, H/W = 1 attains DTR of 12.1 °C, which is 1.2 and 2.1 °C larger than that of H/W = 2, 3. Moreover, the sand models experience smaller DTR and a less changing rate of wall temperature than hollow models because larger thermal storage absorbs more heat in the daytime and releases more at night. DTR of hollow models with H/W = 1, 2, 3 is 4.5, 4.6 and 3.8 °C greater than sand models respectively. For both hollow and sand models, wider streets experience a little higher daily average temperature (0.3–0.6 °C) than narrower ones. Our study provides direct evidence in how man-made urban structures influence urban climate and also suggests the possibility to control outdoor thermal environment by optimize urban morphology and thermal storage.
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•Scaled outdoor measurements of urban climate (SOMUCH) in 2D street canyon are tested.•Impact of aspect ratio (H/W = 1,2,3; H = 1.2 m)/thermal storage on T profiles is studied.•Wider street is warmer in daytime and cools down quicker at night than narrower one.•Sand models with more thermal mass get less daily temperature range (DTR) than hollow models.•Upper walls receive more radiation in daytime but cool down quicker than lower walls.
The Local Climate Zone (LCZ) scheme is a classification system providing a standardization framework to present the characteristics of urban forms and functions, especially for urban heat island ...(UHI) research. Landsat-based 100 m resolution LCZ maps have been classified by the World Urban Database and Portal Tool (WUDAPT) method using a random forest (RF) machine learning classifier. Some studies have proposed modified RF and convolutional neural network (CNN) approaches. This study aims to compare CNN with an RF classifier for LCZ mapping in great detail. We designed five schemes (three RF-based schemes (S1–S3) and two CNN-based ones (S4–S5)), which consist of various combinations of input features from bitemporal Landsat 8 data over four global mega cities: Rome, Hong Kong, Madrid, and Chicago. Among the five schemes, the CNN-based one with the incorporation of a larger neighborhood information showed the best classification performance. When compared to the WUDAPT workflow, the overall accuracies for entire land cover classes (OA) and for urban LCZ types (i.e., LCZ1-10; OAurb) increased by about 6–8% and 10–13%, respectively, for the four cities. The transferability of LCZ models for the four cities were evaluated, showing that CNN consistently resulted in higher accuracy (increased by about 7–18% and 18–29% for OA and OAurb, respectively) than RF. This study revealed that the CNN classifier classified particularly well for the specific LCZ classes in which buildings were mixed with trees or buildings or plants were sparsely distributed. The research findings can provide a basis for guidance of future LCZ classification using deep learning.
Urban heat islands (UHI) in a city tend to vary with changes in time and space. To effectively cope with the accelerating intensity of UHI due to global warming and the resulting damage, it is ...essential to accurately analyze and understand the spatial and temporal variations of UHI. This study conducted a systematic literature review (SLR) to better understand how existing studies have classified and analyzed UHI variations. Research trends and limitations related to UHI variation were reviewed focusing on 55 studies extracted through a five-stage protocol to identify critical studies. The selected studies were analyzed and synthesized in detail. The results showed that studies use different research ranges, data collection methods, analysis, and prediction models depending on the type of UHI variation. These results also indicate that studies have not used universal and specific protocols that apply to UHI variations. To address the limitations of these studies, it is necessary to develop more specific UHI research design methods and an analytical model that reflects the three-dimensional elements of the collected data. In addition, researchers should develop indexes to explain the spatial and temporal variations of UHIs. Further studies can help establish policies and planning codes to counter the spatiotemporal variability of UHIs.
•Review of spatial and temporal variations of UHIs using an SLR framework.•Lack of general protocols to set the research scope and determine data collection methods to efficiently study UHI variations.•Need to develop a model and indexes to explain the intensity and magnitude of UHI variations.
Hot weather can exacerbate health conditions such as cardiovascular and respiratory diseases, and lead to heat stroke and death. In built up areas, temperatures are commonly observed to be higher ...than those in surrounding rural areas, due to the Urban Heat Island (UHI) effect. Climate change and increasing urbanisation mean that future populations are likely to be at increased risk of overheating in cities, although building and city scale interventions have the potential to reduce this risk.
We use a regional weather model to assess the potential effect of one type of urban intervention – reflective ‘cool’ roofs – to reduce local ambient temperatures, and the subsequent impact on heat-related mortality in the West Midlands, UK, with analysis undertaken for the summer of 2006, as well as two shorter heatwave periods in 2006 and 2003.
We show that over a summer season, the population-weighted UHI intensity (the difference between simulated urban and rural temperature) was 1.1 °C on average, but 1.8 °C when including only night times, and reached a maximum of 9 °C in the West Midlands. Our results suggest that the UHI contributes up to 40% of heat related mortality over the summer period and that cool roofs implemented across the whole city could potentially offset 18% of seasonal heat-related mortality associated with the UHI (corresponding to 7% of total heat-related mortality).
For heatwave periods, our modelling suggests that cool roofs could reduce city centre daytime 2 m air temperature by 0.5 °C on average, and up to a maximum of ~3 °C. Cool roofs reduced average UHI intensity by ~23%, and reduced heat related mortality associated with the UHI by ~25% during a heatwave. Cool roofs were most effective at reducing peak temperatures during the daytime, and therefore have the potential to limit dangerous extreme temperatures during heatwaves. Temperature reductions were dependent on the category of buildings where cool roofs were applied; targeting only commercial and industrial type buildings contributed more than half of the reduction for heatwave periods. Our modelling suggested that modifying half of all industrial/commercial urban buildings could have the same impact as modifying all high-intensity residential buildings in the West Midlands.
•City centre summer UHI intensity was 2.0 °C (2.6 °C at night) reaching maximum of 9 °C.•Cool roofs reduced population-weighted temperature by 0.3 °C, about 23% of the UHI.•Main impact in the daytime: mean temperature 0.5 °C lower, greatest reduction 3 °C•Cooling effect greatest when implemented in commercial/industrial areas•Cool roofs may offset 25% of heat-related mortality due to the UHI, during heatwaves.
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