Demographic disparity in diurnal surface urban Heat Island exposure across local climate zones: A case study of Chongqing, China

Surface urban heat island (SUHI) exposure significantly harms human health during rapid urbanization. Identifying the areas and demographic groups under high SUHI exposure is critical for mitigating heat-related hazards. However, despite broad concern in US-European countries, rare studies discuss the diurnal SUHI exposure of demographic subgroups across Local Climate Zones (LCZs) in Chinese cities. Therefore, taking Chongqing as the case study, we measured the diurnal SUHI exposure of demographic subgroups (e.g., gender, age, and income) across different LCZs (compact, open, and sparsely-built zones) by coupling the ECOSTRESS data and mobile phone signaling data. The results indicated that Chongqing's compact high/middle-rise zones suffered a higher SUHI exposure due to high land surface temperature (LST) and a larger size of population than open zones. Despite a relatively low population density, extremely high LST in compact low-rise zones (e.g., industrial parks) contributes to considerable accumulated SUHI exposure. The SUHI exposure risk exhibited the differences between daytime and nighttime, resulting from SUHI variation and population flow. The demographic analysis showed that Chongqing's demographic subgroups are exposed disproportionately to SUHI. Elderly groups suffered relatively high exposure in compact high-rise zones. Low-incomers witnessed a high exposure in open zones. These findings call for alleviating SUHI exposure risk by targeting vulnerable groups and high-intensity exposure areas.

The extreme heat wave of July-August 2021 in the Athens urban area (Greece): Atmospheric and human-biometeorological analysis exploiting ultra-high resolution numerical modeling and the local climate zone framework

Greece was affected by a prolonged and extreme heat wave (HW) event (July 28-August 05) during the abnormally hot summer of 2021, with the maximum temperature in Athens, the capital of the country, reaching up to 43.9 °C in the city center. This observation corresponds to the second highest maximum temperature recorded since 1900, based on the historical temperature time series of the National Observatory of Athens weather station at Thissio. In the present study, a multi-scale numerical modeling system is used to analyze the urban climate and thermal bioclimate in the Athens urban area (AUA) in the course of the HW event, as well as during 3 days prior to the heat wave and 3 days after the episode. The system consists of the Weather Research and Forecasting model, the advanced urban scheme BEP/BEM (Building Energy Parameterization/Building Energy Model) and the human-biometeorological model RayMan Pro, and incorporates the local climate zone (LCZ) classification scheme. The system's validation results demonstrated a robust modeling set-up, characterized by high capability in capturing the observed magnitude and diurnal variation of the urban meteorological and heat stress conditions. The analysis of two- and three-dimensional fields of near-surface air temperature, humidity and wind unraveled the interplay of geographical factors (surface relief and proximity to the sea), background atmospheric circulations (Etesians and sea breeze) and HW-related synoptic forcing with the AUA's urban form. These interactions had a significant impact on the LCZs heat stress responsiveness, expressed using the modified physiologically equivalent temperature (mPET), between different regions of the study area, as well as at inter- and intra-LCZ level (statistically significant differences at 95 % confidence interval), providing thus, urban design and health-related implications that can be exploited in human thermal discomfort mitigation strategies in AUA.

Urban ventilation corridors and spatiotemporal divergence patterns of urban heat island intensity: a local climate zone perspective

Urban ventilation corridors introduce fresh air into urban interiors and improve urban livability, while mitigating the urban heat island (UHI) effect. However, few studies have assessed the impact of urban ventilation corridors on UHI intensity (UHII) from the perspective of the local climates of different cities. Therefore, this study integrated multisource data to construct ventilation corridors from the perspective of local climate zone (LCZ) and analyzed its impact on UHII. The results showed the following: (1) the average UHII of constructed LCZs was higher than that of natural LCZs, among which the building type LCZ10 (heavy industry) had the highest intensity (5.77 °C); (2) in extracted ventilation corridors, the pixel number of natural LCZs was substantially larger than that of constructed LCZs, among which LCZE (bare soil/paved) was the largest; and (3) for natural LCZs, the average UHII of each LCZ was lower within the ventilated corridors than within the non-ventilated corridors (except for LCZG [water]), with the UHII of LCZB (scattered trees) exhibiting the greatest mitigation effect. Quantitative research on the composition and function of ventilation corridors can not only assess the ability of ventilation corridors to mitigate UHIs, but also provide a reference for urban ventilation corridor planning.

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

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

The urban morphology on our planet - Global perspectives from space

Urbanization is the second largest mega-trend right after climate change. Accurate measurements of urban morphological and demographic figures are at the core of many international endeavors to address issues of urbanization, such as the United Nations' call for "Sustainable Cities and Communities". In many countries - particularly developing countries -, however, this database does not yet exist. Here, we demonstrate a novel deep learning and big data analytics approach to fuse freely available global radar and multi-spectral satellite data, acquired by the Sentinel-1 and Sentinel-2 satellites. Via this approach, we created the first-ever global and quality controlled urban local climate zones classification covering all cities across the globe with a population greater than 300,000 and made it available to the community (https://doi.org/10.14459/2021mp1633461). Statistical analysis of the data quantifies a global inequality problem: approximately 40% of the area defined as compact or light/large low-rise accommodates about 60% of the total population, whereas approximately 30% of the area defined as sparsely built accommodates only about 10% of the total population. Beyond, patterns of urban morphology were discovered from the global classification map, confirming a morphologic relationship to the geographical region and related cultural heritage. We expect the open access of our dataset to encourage research on the global change process of urbanization, as a multidisciplinary crowd of researchers will use this baseline for spatial perspective in their work. In addition, it can serve as a unique dataset for stakeholders such as the United Nations to improve their spatial assessments of urbanization.

An urban energy balance-guided machine learning approach for synthetic nocturnal surface Urban Heat Island prediction: A heatwave event in Naples

Southern European functional urban areas (FUAs) are increasingly subject to heatwave (HW) events, calling for anticipated climate adaptation measures. In the urban context, such adaptation strategies require a thorough understanding of the built-up response to the incoming solar radiation, i.e., the urban energy balance cycle and its implications for the Urban Heat Island (UHI) effect. Despite readily available, diurnal Land Surface Temperature (LST) data does not provide a meaningful picture of the UHI, in these midlatitudes FUAs. On the contrary, the mid-morning satellite overpass is characterized by the absence of a significant surface UHI (SUHI) signal, corresponding to the period of the day when the urban-rural air temperature difference is typically negative. Conversely, nocturnal high-resolution LST data is rarely available. In this study, an energy balance-based machine learning approach is explored, considering the Local Climate Zones (LCZ), to describe the daily cycle of the heat flux components and predict the nocturnal SUHI, during an HW event. While the urban and rural spatial outlines are not visible in the diurnal thermal image, they become apparent in the latent and storage heat flux maps - built-up infrastructures uptake heat during the day which is released back into the atmosphere, during the night, whereas vegetation land surfaces loose diurnal heat through evapotranspiration. For the LST prediction model, a random forest (RF) approach is implemented. RF results show that the model accurately predicts the LST, ensuring mean square errors inferior to 0.1 K. Both the latent and storage heat flux components, together with LCZ classification, are the most important explanatory variables for the nocturnal LST prediction, supporting the adoption of the energy balance approach. In future research, other locations and time-series data shall be trained and tested, providing an efficient local urban climate monitoring tool, where in-situ air temperature observations are not available.

An urban climate-based empirical model to predict present and future patterns of the Urban Thermal Signal

Air temperature is a key aspect of urban environmental health, especially considering population and climate change prospects. While the urban heat island (UHI) effect may aggravate thermal exposure, city-level UHI regression studies are generally restricted to temporal-aggregated intensities (e.g., seasonal), as a function of time-fixed factors (e.g., urban density). Hence, such approaches do not disclose daily urban-rural air temperature changes, such as during heatwaves (HW). Here, summer data from Lisbon's air temperature urban network (June to September 2005-2014), is used to develop a linear mixed-effects model (LMM) to predict the daily median and maximum Urban Thermal Signal (UTS) intensities, as a response to the interactions between the time-varying background weather variables (i.e., the regional/non-urban air temperature, 2-hours air temperature change, and wind speed), and time-fixed urban and geographic factors (local climate zones and directional topographic exposure). Results show that, in Lisbon, greatest temperatures and UTS intensities are found in 'Compact' areas of the city are proportional to the background air temperature change. In leeward locations, the UTS can be enhanced by the topographic shelter effect, depending on wind speed - i.e., as wind speed augments, the UTS intensity increases in leeward sites, even where sparsely built. The UTS response to a future urban densification scenario, considering climate change HW conditions (RCP8.5, 2081-2100 period), was also assessed, its results showing an UTS increase of circa 1.0 °C, in critical areas of the city, despite their upwind location. This LMM empirical approach provides a straightforward tool for local authorities to: (i) identify the short-term critical areas of the city, to prioritise public health measures, especially during HW events; and (ii) test the urban thermal performance, in response to climate change and urban planning scenarios. While the model coefficient estimates are case-specific, the approach can be efficiently replicated in other locations with similar biogeographic conditions.

Socio-spatial inequality and its relationship to thermal (dis)comfort in two major Local Climate Zones in a tropical coastal city

Brazil is the country with the highest social inequality in South America. This socioeconomic disparity reflects not only on the families' income but also on their spatial localization in the city, as well as on the urban design. These urban environments can alter the urban microclimate, and consequently, interfere in dwellers' thermal comfort. This research investigated the relationship between socio-spatial inequalities and thermal comfort in two different Local Climate Zones (LCZ) using a combination of measurement and modeling. Air temperature (Tair) was obtained by on-site measurements in compact high-rise (LCZ1) and compact low-rise buildings (LCZ3) and Mean radiant temperature (Tmrt) was simulated using SOlar and LongWave Environmental Irradiance Geometry (SOLWEIG). The results indicated that in LCZ1 seafront-localized buildings, in which residents have a higher income, the temperature remains in a range classified as comfortable, mainly due to shading and sea breeze. On the other hand, LCZ3, located in the periphery of the city, in which the low-income population is concentrated and is marked by a precariousness urban environment, presented a higher air temperature and Tmrt values, exposing the dwellers to heat stress throughout the year, especially during the summer season. These observations suggested that public and private actions tend to promote better urban designs in areas with a higher concentration of income. Public reforms aimed at improving the urban environment and promoting thermal comfort should be a priority for the warmest LCZ, where the poorest residents live. Public agents should rethink the distribution of environmental resources to promote equitable urban spaces.

Local climate zones classification method from Copernicus land monitoring service datasets: An ArcGIS-based toolbox

Local Climate Zones (LCZ) have become a worldwide standard for identifying land cover classes, according to their climate-relevant morphological parameters. The LCZ's are mostly used to evaluate urban climate performance, particularly the relationship between the urban heat island effect (UHI) and the characteristics of the built-up environment. The World Urban Database and Access Portal Tools (WUDAPT) has provided a supervised LCZ classification method based only on moderate resolution free satellite imagery, mostly Landsat 7 or 8 (30 m pixel size, in the visible spectrum brands); however, its’ results are less accurate for European cities. Conversely, alternative geographic information system (GIS)-based methods developed so far require information that is hardly available to all, such as building footprints or heights. Here, the ArcGIS based LCZ from Copernicus Toolbox (LCZC) provides an alternative classification method that uses only freely accessible information from the Copernicus Land Monitoring Service (CLMS), being possible to replicate it in 800 European urban locations. The method combines Urban Atlas (UA) and Corine Land Cover (CLC) with Tree Cover Density, Dominant Leaf Type and Grassland information, to produce a higher-resolution baseline shapefile that is classified according to each feature's dominant characteristics. The LCZC toolbox output is a LCZ raster map. It has been validated in five European cities: Athens, Barcelona, Lisbon, Marseille, and Naples.•

The LCZC toolbox provides an alternative LCZ GIS-based classification, based on freely accessible CLMS datasets.

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The use of CLMS shapefile higher-resolution inputs, particularly the UA and CLC datasets, ensures an output LCZ map that has greater detail and higher accuracy.

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The availability of CLMS information in 800 European urban areas guarantees that the method can be replicated in those locations.

Spatial relationship between land development pattern and intra-urban thermal variations in Taipei

This paper assesses the influence of land development patterns on intra-urban thermal variation in a densely-developed subtropical city, considering joint effect from greenspace pattern and built-up geometry. Despite growing research on urban climates, research at a scale that can support urban planning with scientificallyinformed strategies is still not as well documented for warm climate cities as for temperate cities. In response, this paper uses land surface temperature and geoinformation to assess the subtropical city of Taipei, Taiwan. Results show cooler environments are not only associated with natural surfaces, but also their interrelation with different spatial arrangement of buildings. An open layout tends to have lower temperature at low- to mid-rise buildings, whereas a compact layout is the coolest form for high-rise buildings. Cooling benefit from open layouts is, however, related to an increase in greenery. Clustering distribution of greenspaces produces more notable cooling. Accordingly, this paper proposes four heat mitigation strategies for Taipei: 1) increasing the amount of water bodies and vegetation, with greater coverage and coherence; 2) taking building height and shadow into account during regeneration/development; 3) increasing spacing and greenery between low- to midrise buildings; and 4) avoiding construction of compact low-rise buildings with corrugated iron steel.

How to quantify the relationship between spatial distribution of urban waterbodies and land surface temperature?

Urban waterbodies can effectively mitigate the increasing UHI effects and thus enhance climate resilience of urban areas. To contribute to our limited understanding in cooling effect of waterbodies on surrounding thermal environments, we examine the quantitative relationship between the spatial distribution of urban waterbodies and the land surface temperature (LST) in Wuhan, China. This paper 1) applies two indicators, the fractional water cover and the gravity water index, for measuring the spatial distribution of urban waterbodies; 2) conducts simple linear regression and spatial regression analyses to explore the LST-water relationship at multiple scales; and 3) compares the individual regression results from different land use types. The results show that the spatial distribution of urban waterbodies affects the LST significantly, and the gravity water index sufficiently explains the LST variation at various scales. Furthermore, the impact of urban waterbody distribution on the LST does vary across different land use types. Conclusions from this study provide insights of the cooling effect of urban waterbodies, which can further assist city planners and decision makers in utilizing cooling effects of waterbodies to improve the thermal environment of urban areas.

Modelled spatiotemporal variability of outdoor thermal comfort in local climate zones of the city of Brno, Czech Republic

This study uses the MUKLIMO_3 urban climate model (in German, Mikroskaliges Urbanes KLImaMOdell in 3-Dimensionen) and measurements from an urban climate network in order to simulate, validate and analyse the spatiotemporal pattern of human thermal comfort outdoors in the city of Brno (Czech Republic) during a heat-wave period. HUMIDEX, a heat index designed to quantify human heat exposure, was employed to assess thermal comfort, employing air temperature and relative humidity data. The city was divided into local climate zones (LCZs) in order to access differences in intra-urban thermal comfort. Validation of the model results, based on the measurement dates within the urban monitoring network, confirmed that the MUKLIMO_3 micro-scale model had the capacity to simulate the main spatiotemporal patterns of thermal comfort in an urban area and its vicinity. The results suggested that statistically significant differences in outdoor thermal comfort exist in the majority of cases between different LCZs. The most built-up LCZ types (LCZs 2, 3, 5, 8 and 10) were disclosed as the most uncomfortable areas of the city. Hence, conditions of great discomfort (HUMIDEX >40) were recorded in these areas, mainly in the afternoon hours (from 13.00 to 18.00 CEST), while some thermal discomfort continued overnight. In contrast, HUMIDEX values in sparsely built-up LCZ 9 and non-urban LCZs were substantially lower and indicated better thermal conditions for the urban population. Interestingly, the model captured a local increase of HUMIDEX values arising out of air humidity in LCZs with the presence of more vegetation (LCZs A and B) and in the vicinity of larger bodies of water (LCZ G).

Evaluation of outdoor human thermal sensation of local climate zones based on long-term database

This study gives a comprehensive picture on the diurnal and seasonal general outdoor human thermal sensation levels in different urban quarters based on long-term (almost 3 years) data series from urban and rural areas of Szeged, Hungary. It is supplemented with a case study dealing with an extreme heat wave period which is more and more frequent in the last decades in the study area. The intra-urban comparison is based on a thermal aspect classification of the surface, namely, the local climate zone (LCZ) system, on an urban meteorological station network and on the utilization of the physiologically equivalent temperature (PET) comfort index with categories calibrated to the local population. The selected stations represent sunlit areas well inside the LCZ areas. The results show that the seasonal and annual average magnitudes of the thermal load exerted by LCZs in the afternoon and evening follow their LCZ numbers. It is perfectly in line with the LCZ concept originally concentrating only on air temperature (T _air) differences between the zones. Our results justified the subdivision of urban areas into LCZs and give significant support to the application possibilities of the LCZ concept as a broader term covering different thermal phenomena.