Urban Air Temperature Research Articles

COVID-19 strict lockdown impact on urban air quality and atmospheric temperature in four megacities of India

COVID-19 pandemic has forced to lockdown entire India starting from 24th March 2020 to 14th April 2020 (first phase), extended up to 3rd May 2020 (second phase), and further extended up to 17th May 2020 (third phase) with limited relaxation in non-hotspot areas. This strict lockdown has severely curtailed human activity across India. Here, aerosol concentrations of particular matters (PM) i.e., PM10, PM2.5, carbon monoxide (CO), nitrogen dioxide (NO2), sulphur dioxide (SO2), ammonia (NH3) and ozone (O3), and associated temperature fluctuation in four megacities (Delhi, Mumbai, Kolkata, and Chennai) from different regions of India were investigated. In this pandemic period, air temperature of Delhi, Kolkata, Mumbai and Chennai has decreased about 3 °C, 2.5 °C, 2 °C and 2 °C respectively. Compared to previous years and pre-lockdown period, air pollutants level and aerosol concentration (−41.91%, −37.13%, −54.94% and −46.79% respectively for Delhi, Mumbai, Kolkata and Chennai) in these four megacities has improved drastically during this lockdown period. Emission of PM2.5 has experienced the highest decrease in these megacities, which directly shows the positive impact of restricted vehicular movement. Restricted emissions produce encouraging results in terms of urban air quality and temperature, which may encourage policymakers to consider it in terms of environmental sustainability.

Future air temperature projection in high-density tropical cities based on global climate change and urbanization – a study in Singapore

Urban air temperature projection is essential to prepare cities for future heat risks. This study aims to anticipate future air temperature increment contributed by climate change and urbanization. First, we identified the rural area in Singapore by historical data, and downscaled global/regional modelling results to investigate climate change at the identified rural area. Representative concentration pathway 8.5 was chosen at the downscaling study for the worst case scenario. Results indicate air temperature at the rural area will increase by 0.4–0.6 °C in 2030s, 1.2–1.6 °C in 2050s, and 2.2–3.8 °C in 2080s. Secondly, we estimated future urbanization based on master planning by planning department, and associated urbanization with air temperature using linear regression. Based on planned plot ratio for future, we calculated sky view factor and site coverage ratio as urban morphology and planning index respectively. Linear regression analysis indicates that air temperature at urban areas could increase 0.05 °C - 0.79 °C in 2030s due to various urbanization in Singapore. This study conducted projections, which are based on global/regional modelling results and associated closely with urban planning. Projection results indicate that pre-emptive urban planning and design strategies are needed at the districts with potential heat risk and enables urban planners to make evidence-based decisions.

Effect of the roadside tree canopy structure and the surrounding on the daytime urban air temperature in summer

As an important component of urban forests, roadside trees provide cooling and humidification effects, thereby improving the microclimate and human thermal comfort during hot summer weather by blocking, reflecting and absorbing solar radiation. However, the complex three-dimensional (3D) structure of roadside trees, diverse planting types and complex landscape heterogeneity complicate efforts to quantify the effects of these factors on above-road air temperatures. In this study, a terrestrial laser scanner (TLS) is used to accurately estimate roadside tree morphological parameters, such as the tree height (TH) and the diameter at breast height (DBH), and canopy structural parameters, such as the canopy thickness (CT), the canopy cover above the road (CCAD), canopy volume over the road (CVAD) and the leaf area index (LAI), to evaluate different 3D canopy geometries (pyramidal, spherical, pileate and cylindrical). A moving meteorological station was used to continuously obtain the horizontal air temperature (AT) distribution to investigate the effects of the canopy structural parameters, the planting types and the land cover types on the above-road AT. The value of ΔAT was positively correlated with TH, CVAD, LAI and CCAD. These structural variables were most significantly correlated with ΔAT under the pileate canopy shape. However, there were no significant correlations between these factors under the cylindrical canopy shape. The physiological equivalent temperature (ΔPET) reached 7.4, 15.8, 4.5 and 17 °C under the cylindrical, spherical, pyramidal and pileate shapes, respectively. The ΔAT of a two-sided planting was approximately 1.7 times greater than that of a one-sided planting; the ΔRH showed a similar trend. Within 230 m of a lake, the ΔAT exhibited a logarithmic relationship with the distance from a given point to the lake. Our study quantifies the influence of the roadside tree structure on the thermal environment, which can serve as a meaningful reference for urban tree species selection and arrangement.

Quantitative-spatial relationships between air and surface temperature, a proxy for microclimate studies in fine-scale intra-urban areas?

Recent studies on fine-scale spatial variations of urban air temperature revealed that urban environments are urban heat "archipelagos", rather than "islands,” and there are locations with higher temperatures which suffer more intensive urban heat, and people in these areas are likely to experience greater heat stress and health risks. However, study of this phenomenon is limited because of insufficient air temperature data at the fine scale. This study attempted to quantify the heterogeneity of air and land surface temperature (LST), and their relationship in a fine-scale urban environment using field-measured air temperature and Landsat 8-based LST data. We found: (1) there was a strong thermal heterogeneity at the fine scale even between the measurement points on the edges of a large urban park. The maximum temperature difference reached 4.2 °C for air temperature and 8 °C for LST in the study area. (2) Air and surface temperatures were positively correlated. However, their cool and hot spots did not always overlap in space. (3) air temperature is more complex than LST, and more parameters in the urban environment can influence air temperature. (4) Urban landscape and climatological parameters can enhance the applicability of LST as a proxy for air temperature from 39% to 57%. The results have theoretical and practical implications for identifying the locations on a fine scale with extreme heat and attracting the attention of urban planners to take adoption measures.

Wind corridor planning and management strategies using cold air characteristics: The application in Korean cities

The urban heat island and air pollution in urban areas due to increased urbanization are becoming serious environmental problems. Urban wind corridor plays a role in solving urban heatwaves and tropical night problems, which worsening at night than during the daytime, and contribute to reducing urban air temperature and improving the urban atmosphere environment. In order to develop active wind corridors in cities, it is necessary to identify the local cold air generated differently according to the spatial characteristics at night. Therefore, we analyzed the characteristics of local cold air formed according to various spatial characteristics using the KALM model targeting three cities in Korea (Cheongju-si, Jeonju-si, and Jinju-si). As results, local cold airflows were the most advantageous in Jeonju-si, where the land use and topographical properties were favorable for the movement and dispersion of cold air. On the other hand, Jinju-si recorded the highest average height of local cold air because it has complex and deep valleys where high layers of local cold air could be accumulated. Based on the analysis, wind corridor planning and management strategies were proposed to maximize the use of local cold air considering to the characteristics and development situation of three different Korean cities.

Comparison of daily and monthly intra-urban thermal reactions based on LCZ classification using surface and air temperature data

Urban air (T a) and surface (T s) temperature patterns depend mainly on the surface cover conditions. WUDAPT methodology was used to create the local climate zone (LCZ) map of Szeged (Hungary) providing detailed information about the structure of the urban area. The seasonal and monthly variations of simultaneous measurements of T a (urban network) and T s (MODIS) in different LCZs were analysed for a four-year period. The results show that the largest differences between T s and T a values occur in late spring and summer. During the day, the monthly mean T s was much higher than the mean T a , while at night, the T a exceeded the T s in all LCZs. Linear statistical relationship was also analysed, which concluded that diurnal and nocturnal T a and T s are strongly correlated in all LCZs in Szeged.

A quantification of classic but unquantified positive feedback effects in the urban-building-energy-climate system

The interaction between urban air temperature (T) and building cooling energy demand (E) generates a well-known positive feedback (PFB), which is mediated by sensible anthropogenic heat (Qfs) and named Qfs-T-E PFB in this study. This PFB could induce self-reinforced warming in urban areas, but its effects have not been completely quantified. Hence, this study aimed to clarify these effects by targeting Osaka, a Japanese major city. Focusing on the from-weekends-to-weekdays increase in urban energy consumption including E increase as an observable trigger of the PFB, its induced T rise due to growth inQfs was estimated with the fed-back additional E gain on weekdays based on observed ground-level T and district-wise electric power consumption during summer. The result indicated that the weekdays–weekends contrast in energy consumption over Osaka could induce the Qfs-T-E PFB effects, which resulted in fed-back E gain reaching 10% on weekdays. Such observational PFB impact on E was found to be roughly reproducible by the proposed urban meteorological model, named WRF-CM-BEM. Thus, the validated modelwasapplied tothequantificationof the climatological PFB impact on T based on feedback gain(gA) which means a percentage of Tvariation caused by the PFB. Anattemptwas madetoquantify gA through the two-cases simulations of the weekdays-run and holidays-run for the months of August in 10 years, focusing again on the weekdays–weekends contrast in urban energy consumption. The simulations provided estimates on gA, whose daytime averages reached nearly 10% in the downtown commercial areas and 20% in the leeward-located residential areas, suggesting the influence of sea breeze heat advection of downtown Qfs. Such estimated impacts on Twere roughly in the same order of magnitude compared to those in a few earlier studies that were not based on observational validations and seemed to be non-negligible, considering the feedback impacts on global surface warming estimated with gA of approximately 50% by the Intergovernmental Panel on Climate Change.

Resolution of the M-shape Pattern of the Outdoor Air Temperature Environmental Kuznets Curve (EKC) for Metropolitan Areas in a Country: Using Long-term Monthly Level Data of Taipei City as Empirical Evidence

In Taiwan, the heat island effect is the most significant in Taipei City. Thus this research provides a causal explanation for why urban outdoor air temperature has an M-shape EKC pattern for metropolitan areas in a country. Results show that the growth rate change in CO2 concentration can induce changes to the periods of the La Nino effect and EI Nino effect, causing high fluctuations in rain accumulation. The amount of rain then alters A-type evaporation, and so the evaporation amount is the top factor for the diffusion of a city’s heat. This fluctuation plays as a cooling and heating source for the V region of the M shape in the outdoor air temperature EKC pattern. In our previous studies, the growth rate change in CO2 concentration correlates to the energy structure. Therefore, a heat sinking model has been proposed to explain the accumulation of heat in a city, in which a proportion process for the solar irradiation source from buildings and remodeling engineering from a public housing policy and the private sector can play as a heating source of the two peaks of the M shape and present long-term linear growth in the outdoor air temperature EKC pattern.

ATLAS: Software for analysing the relationship between urban microclimate and urban morphology in a tropical city

This research applied clustering to unsupervised learning of meteorological data and evaluated the impact of urban morphology on temperature in different weather. Air Temperature Learning Algorithms (ATLAS) was developed for the cluster analysis of urban meteorological data and regression analysis of urban morphology and outdoor air temperature. The case study experiment was conducted on the university campus. Based on principal component analysis (PCA) reduced K-means clustering, this study evaluated the characteristics of reference meteorological data, and local solar irradiance and air temperature. Three weather conditions were identified for the given reference meteorological data. Revised selection criteria for clear, hot, and calm weather in tropical climate were proposed. The mean Raintot shall be less than 0.01 mm, with 25th, 50th and 75th quartile to be 0 mm, respectively. The mean Wavg and its quartiles shall be less than 3 m/s. The mean, 50th and 75th quartile of Stot, Smax, and Savg shall be higher than 5000 Wh/m2, 800 W/m2 and 200 W/m2, respectively. The mean, 50th and 75th quartile of Tavg, Tmax and Tmin shall be higher than 29 °C, 32 °C and 26 °C, respectively. The hourly ground level air temperature models were established in different weather. The results indicate the ground level air temperature in rainy and cool weather conditions are more predictable than hot and dry weather conditions. The sky view factor, exterior wall area, and green plot ratio have a greater impact on air temperature in sunny days than rainy days.

How local climate zones influence urban air temperature: Measurements by bicycle in Dijon, France

This study analyses mobile measurements of urban temperatures in Dijon (eastern France) to quantify the influence of urban form on the micro-scale variability of air temperature. A route was ridden identically on 33 spring and summer evenings on a bike fitted out with measuring instruments (VeloClim). These evenings followed sunny calm days conducive to the formation of thermal contrasts and urban heat islands (UHIs). Two typologies, Corine Land Cover (CLC) and Local Climate Zones (LCZ), are used to assess the impact of urban form and land cover on air temperatures based on ANalysis Of VAriance (ANOVA). ANOVA is applied to the mean of runs to maximize the effect of surface states, and to each run individually to maximize the influence of weather conditions.The results show that both typologies prove relevant and complementary for studying the impact of vegetated and artificialized zones on urban temperature. Temperature variations on intra-urban scales are significantly modulated by urban form and land cover types. Vegetated areas are systematically cooler than impervious surfaces. Independently of meteorological conditions, urban form has a decisive influence on air temperature and each CLC or LCZ category has an original air temperature signature.

Defining local extreme heat thresholds and Indoor Cooling Degree Necessity for vulnerable residential dwellings during the 2020 summer in Ankara – Part I: Air temperature

This study discusses the preliminary assessment of Indoor Cooling Degree Necessity (ICDN) based upon the standard air temperature (Ta) value of 22 °C which is defined to be the standard upper mean temperature limit (Tl) for interior comfort as defined by the WHO. By considering indoor air temperature (TaI), levelled oscillations above Tl are utilised to determine indoor temperature extremes/frequencies at a 10 min temporal resolution during the months of July and August 2020 in Ankara. These recordings were undertaken through the use of an interior in-situ Meteorological Station (MS), simultaneously, an outdoor in-situ MS was also mounted outside the naturally ventilated dwelling with the identical measurement interval period. Moreover, to supplement the encompassing outdoor data collection, two WMO MSs were utilised in the study to account for both encompassing local peri-urban Esenboga (EMS) and Ankara’s urban (AMS) outdoor air temperatures (TaO) at a 1 h temporal resolution.In addition to the ICDN’s identified variation of Tl levels, which frequently remained between +7 °C and +10 °C during periods of accentuated urban outdoor heat stress; their direct/latent cause-and-effect relationship with newly defined local extreme heat thresholds were established. Relative to July and August 2020, a total of 19 Very Hot Days (VHD33), 10 Monthly Tropical Night (MRT20), and 4 Heatwave Events (HWE31) were determined. These thresholds further underlined the growing need to associate indoor and outdoor heat stress during local extreme heat events, particularly in more vulnerable residential contexts; and moreover, in an era of increasing heat stress as result of rapid urbanisation and climate change.

Downscaled night air temperatures between 2030 and 2070: The case of cities with a complex- and heterogeneous-topography

Global and regional climate models tend to underestimate temperatures over urban areas. This limitation is exacerbated in complex-topography regions, where coarse spatial resolutions of climate models fail to detect large apparent change in cities' microclimates. In this study, a night air temperature downscaling approach was proposed in cities with heterogeneous- and complex-topography. It was developed based on six ground-based national weather station datasets along the 1-km remote-sensing-based MODIS land surface temperature (LST) data, between 2000 and 2020. An ordinary least square (OLS) statistical test was applied, including the 1-km MODIS normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), evapotranspiration (ET) and the digital elevation model (DEM) datasets as independent variables. Based on the generated regression relationship and a five-year pixel-based trend analysis, the 25-km NASA NEX-GDDP datasets were downscaled into 1-km spatial resolution night air temperatures between 2030 and 2072 and under two scenarios (i.e. RCP 4.5 and 8.5), averaged from 21 CMIP5 models. Validations were carried out showing good results with an RMSE of 0.49 °C, an AME of 0.42 °C and an R-squared value of 89.5%.Further assessment was made over the largest cities in Lebanon, namely Beirut, Tripoli, Zahle and Baalbeck. Main results showed that, on average, urban night air temperatures under the intermediate RCP 4.5 scenario are expected to increase by 0.12 °C or 0.61% in 2030, 0.36 °C or 1.82% in 2050 and 0.6 °C or 3.07% in 2070. Under the worst-case climate change RCP 8.5 scenario, the average increase would be an overwhelming 7.41 °C or 38.4% by 2070. City and policy makers are invited to implement the proposed straightforward and validated downscaling approach and to use the findings for a more responsive urban planning and design to the particular environemntal and geographic conditions; this isespecially required in cities and agglomorations dominated by complex- and heterogeneous-topographic characteristics.

Crowdsourcing Urban Air Temperature Data for Estimating Urban Heat Island and Building Heating/Cooling Load in London

Urban heat island (UHI) effects significantly impact building energy. Traditional UHI investigation methods are often incapable of providing the high spatial density of observations required to distinguish small-scale temperature differences in the UHI. Crowdsourcing offers a solution. Building cooling/heating load in 2018 has been estimated in London, UK, using crowdsourced data from over 1300 Netatmo personal weather stations. The local climate zone (LCZ) scheme was used to classify the different urban environments of London (UK). Inter-LCZ temperature differences are found to be generally consistent with LCZ temperature definitions. Analysis of cooling degree hours in July shows LCZ 2 (the densest urban LCZ in London) had the highest cooling demand, with a total of 1550 cooling degree hours. The suburban related LCZs 5 and 6 and rural LCZs B and D all had about 80% of the demand of LCZ 2. In December, the rural LCZs A, B and D had the greatest heating demand, with all recording around 5750 heating degree hours. Urban LCZs 2, 5 and 6 had 91%, 86% and 95% of the heating demand of LCZ D, respectively. This study has highlighted both advantages and issues with using crowdsourced data for urban climate and building energy research.

LAND COVER CHANGE ANALYSIS IN THE STATE OF CALIFORNIA USING NLCD DATA

Abstract. Land cover change is critical to be monitored as land cover change has significant impacts on flooding, ground water recharge, and urban air temperature. In this paper, key findings from a land cover change analysis study performed in the State of California are presented. National Land Cover Database (NLCD) data from the Multi-Resolution Land Characteristics Consortium (MRLC) was used for this study. Time series of NLCD data during the time period of 2001 through 2016 was used for the analysis. NLCD data processing was done in ArcMap 10.6.1. This paper includes the methodology in detail, and the results of the analysis. Results of the study indicate a significant increase in impervious surfaces, and a significant decrease in forest land cover.

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.

Spatiotemporal impact of vehicle heat on urban thermal environment: A case study in Hong Kong

Vehicle heat (VH) is a substantial portion of anthropogenic heat and can affect the urban thermal environment. Quantifying the impact of VH has implications for the potential benefits of electric vehicles in cities, yet the spatiotemporal impact of VH has not been investigated separately. This study incorporates VH and urban landscape data into the Weather Research and Forecasting (WRF) model to estimate the VH impacts at a fine spatial resolution over Hong Kong. Results show a strong temporal variation of the VH impact at daily, weekly, and seasonal scales: 1) the warmth of urban canyon air temperature is stronger and more consistent at night than in daytime, 2) increases in sensible heat fluxes are more pronounced during weekdays than weekends, 3) temperature change of 0.35 °C in winter is larger than that of 0.32 °C in summer. Increased air temperature over the land area by VH correlates with urban area fraction and building height positively, but not the aspect ratio. The statistically significant VH impact (90% confidence level) has the broadest spatial coverage in Hong Kong shortly after rush hours. The relative VH impact compared to building heat demonstrates the dominative role of vehicle heat in warming low urbanized areas with highways and circulation roads. The spatiotemporal distributions of the VH impact provide insights into the potential benefits of green transportation technology and policy in mitigating urban heat islands.

RMetS Meteorological Masterclass Series: Anticipating floods, droughts and heatwaves

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Effect of Urban Heat Island and Global Warming Countermeasures on Heat Release and Carbon Dioxide Emissions from a Detached House

Urban air temperature rises induced by the urban heat island (UHIE) effect or by global warming (GW) can be beneficial in winter but detrimental in summer. The SCIENCE-Outdoor model was used to simulate changes to sensible heat release and CO2 emissions from buildings yielded by four UHIE countermeasures and five GW countermeasures. This model can evaluate the thermal condition of building envelope surfaces, both inside and outside. The results showed that water-consuming UHIE countermeasures such as evaporative space cooling and roof water showering provided positive effects (decreasing sensible heat release and CO2 emissions related to space conditioning) in summer. Additionally, they had no negative (unwanted cooling) effects in winter since they can be turned off in the heating season. Roof greening can provide the greatest space- conditioning CO2 emissions reductions among four UHIE countermeasures, and it reduces the amount of heat release slightly in the heating season. Since the effect on reducing carbon dioxide (CO2) emissions by UHIE countermeasures is not very significant, it is desirable to introduce GW countermeasures in order to reduce CO2 emissions. The significance of this study is that it constructed the new simulation model SCIENCE-Outdoor and applied it to show the influence of countermeasures upon both heat release and CO2 emissions.

Evaluation and application of a low-cost measurement network to study intra-urban temperature differences during summer 2018 in Bern, Switzerland

The understanding of intra-urban air temperature variations is crucial to assess strategies for cities' adaptation to impacts of present and future anthropogenic climate change. Depending on extensive measurement networks, high-resolution air temperature measurements in urban environments are challenging due to high instrumentation and maintenance costs. Here, we present a low-cost measurement device (LCD) consisting of a temperature logger and a custom-made, naturally ventilated radiation shield. Besides intercomparisons with automated weather stations (AWS) at three reference sites during record-dry summer 2018, we tested the potential of the devices using a network of 79 LCDs to assess the intra-urban variability of urban heat island (UHI) patterns in the city of Bern, Switzerland. We found positive mean measurement biases between LCDs and AWS of 0.61 to 0.93 K (RMSE: 0.78 to 1.17 K) during daytime, of which up to 82.8% of the variance could be explained statistically by solar irradiance (radiative heating) and wind speed (insufficient ventilation). During night, average measurement biases were markedly lower and eventually negative with −0.12 to 0.23 K (RMSE: 0.19 to 0.34 K). Our results highlight the importance of sensor intercomparisons being conducted at multiple locations with differing urban land-cover, structure, and metabolism given that biases varied considerably between the reference sites. Data retrieved by the city-wide measurement network showed that the LCD approach is well suited for the analysis of spatiotemporal UHI patterns during night and adds considerable value compared to the few existing AWS in detecting fine-scale air temperature variability. In conclusion, the current LCD measurement approach represents a valuable option for cost-effective analyses of urban air temperature variability across multiple scales, which may be of particular value for the development, appliance, and monitoring of adaptation strategies to climate change in cities with restricted financial resources.

A Coupled Modelling Method for the Evaluation of the Impact of Pavement Solar Collector on Urban Air Temperature and Thermal Collection

The Urban Heat Island (UHI) effect is a phenomenon whereby urban areas become warmer than their surrounding rural areas, due to the replacement of vegetation and soil with surfaces such as asphalt and concrete. The asphalt pavement surfaces tend to absorb a large amount of heat through solar radiation and increase the air temperature, which affects the operation of building heating and cooling systems, causing environmental problems and thermal discomfort. However, this energy can be collected by water circulated through buried copper pipes to cool down temperatures and be stored for other usages. This work aims to develop a method for determining the optimum areas to locate pavement solar collector (PSC) systems and simulate the reduction of ambient air and surface temperature by using a coupled computational modelling approach. Discrete ordinate model and solar-ray tracing were utilised for solar radiation effect modelling in the 3D simulation. Furthermore, the PSC prototype was developed, and lab-scale experiments were carried out for validation. Based on the simulated conditions, in the unshaded area, the asphalt slab’s near-surface temperature was reduced by up to 10℃ and the outlet water temperature increased by about 5℃. At the pedestrian height level, the air temperature was reduced up to 4.6℃. This study further expands the investigation of the variation of outdoor conditions such as air temperature and solar radiation. The results showed that the proposed method could be used to optimise the pavement solar collector’s positioning to reduce urban surface and air temperature.