scholarly journals Heat Waves and Human Well-Being in Madrid (Spain)

Atmosphere ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 288 ◽  
Author(s):  
Domingo Rasilla ◽  
Fernando Allende ◽  
Alberto Martilli ◽  
Felipe Fernández
Keyword(s):  
Air Quality ◽  
Thermal Comfort ◽  
Land Surface ◽  
Heat Waves ◽  
Well Being ◽  
Urban Heat Islands ◽  
Canopy Layer ◽  
Physiological Equivalent Temperature ◽  
Human Thermal Comfort ◽  
The City

Heat waves pose additional risks to urban spaces because of the additional heat provided by urban heat islands (UHIs) as well as poorer air quality. Our study focuses on the analysis of UHIs, human thermal comfort, and air quality for the city of Madrid, Spain during heat waves. Heat wave periods are defined using the long-term records from the urban station Madrid-Retiro. Two types of UHI were studied: the canopy layer UHI (CLUHI) was evaluated using air temperature time-series from five meteorological stations; the surface UHI (SUHI) was derived from land surface temperature (LST) images from MODIS (Moderate Resolution Imaging Spectroradiometer) products. To assess human thermal comfort, the Physiological Equivalent Temperature (PET) index was applied. Air quality was analyzed from the records of two air quality networks. More frequent and longer heat waves have been observed since 1980; the nocturnal CLUHI and both the diurnal and nocturnal SUHI experience an intensification, which have led to an increasing number of tropical nights. Conversely, thermal stress is extreme by day in the city due to the lack of cooling by winds. Finally, air quality during heat waves deteriorates because of the higher than normal amount of particles arriving from Northern Africa.

scholarly journals Urban Heat Islands and Thermal Comfort: A Case Study of Zorrotzaurre Island in Bilbao

2021 ◽  
Vol 13 (11) ◽  
pp. 6106
Author(s):  
Irantzu Alvarez ◽  
Laura Quesada-Ganuza ◽  
Estibaliz Briz ◽  
Leire Garmendia
Keyword(s):  
Thermal Comfort ◽  
Heat Waves ◽  
Urban Environments ◽  
Urban Heat Islands ◽  
Extreme Weather Events ◽  
Climate Index ◽  
Physiological Equivalent Temperature ◽  
Heat Islands ◽  
The North ◽  
The Impact

This study assesses the impact of a heat wave on the thermal comfort of an unconstructed area: the North Zone of the Island of Zorrotzaurre (Bilbao, Spain). In this study, the impact of urban planning as proposed in the master plan on thermal comfort is modeled using the ENVI-met program. Likewise, the question of whether the urbanistic proposals are designed to create more resilient urban environments is analyzed in the face of increasingly frequent extreme weather events, especially heat waves. The study is centered on the analysis of temperature variables (air temperature and average radiant temperature) as well as wind speed and relative humidity. This was completed with the parameters of thermal comfort, the physiological equivalent temperature (PET) and the Universal Temperature Climate Index (UTCI) for the hours of the maximum and minimum daily temperatures. The results demonstrated the viability of analyzing thermal comfort through simulations with the ENVI-met program in order to analyze the behavior of urban spaces in various climate scenarios.

scholarly journals Empirical Model of Human Thermal Comfort in Subtropical Climates: A First Approach to the Brazilian Subtropical Index (BSI)

Atmosphere ◽  
2018 ◽  
Vol 9 (10) ◽  
pp. 391 ◽  
Author(s):  
João Gobo ◽  
Marlon Faria ◽  
Emerson Galvani ◽  
Fabio Goncalves ◽  
Leonardo Monteiro
Keyword(s):  
Thermal Comfort ◽  
Empirical Model ◽  
Thermal Sensation ◽  
Meteorological Data ◽  
Well Being ◽  
Global Solar Radiation ◽  
Coefficient Of Determination ◽  
Subtropical Climate ◽  
Human Thermal Comfort ◽  
The City

The bioclimatic well-being of individuals is associated with the environmental characteristics of where they live. Knowing the relationships between local and regional climatic variables as well as the physical characteristics of a given region and their implications on thermal comfort is important for identifying aspects of thermal sensation in the population. The aim of this study is to develop an empirical model of human thermal comfort based on subjective and individual environmental patterns observed in the city of Santa Maria, located in the state of Rio Grande do Sul, Brazil (Subtropical climate). Meteorological data were collected by means of an automatic meteorological station installed in the city center, which contained sensors measuring global solar radiation, air temperature, globe temperature (via a grey globe thermometer), relative humidity and wind speed and direction. A total of 1720 people were also interviewed using a questionnaire adapted from the model recommended by ISO 10551. Linear regressions were performed to obtain the predictive model. The observed results proposed a new empirical model for subtropical climate, the Brazilian Subtropical Index (BSI), which was verified to be more than 79% accurate, with a coefficient of determination of 0.926 and an adjusted R2 value of 0.924.

scholarly journals Impact of Land Cover Changes on Land Surface Temperature and Human Thermal Comfort in Dhaka City of Bangladesh

2021 ◽  
Author(s):  
H. M. Imran ◽  
Anwar Hossain ◽  
A. K. M. Saiful Islam ◽  
Ataur Rahman ◽  
Md Abul Ehsan Bhuiyan ◽  
...  
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Surface Temperature ◽  
Thermal Comfort ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Dhaka City ◽  
Human Thermal Comfort ◽  
The City

AbstractUrbanization leads to the construction of various urban infrastructures in the city area for residency, transportation, industry, and other purposes, which causes major land use change. Consequently, it substantially affects Land Surface Temperature (LST) by unbalancing the surface energy budget. Higher LST in city areas decreases human thermal comfort for the city dwellers and affects the urban environment and ecosystem. Therefore, a comprehensive investigation is needed to evaluate the impact of land use change on the LST. Remote Sensing (RS) and Geographic Information System (GIS) techniques were used for the detailed investigation. RS data for the years 1993, 2007 and 2020 during summer (March–May) in Dhaka city were used to prepare land cover maps, analyze LST, generate hazard maps and relate the land cover change with LST by using GIS. The results show that the built-up area in Dhaka city increased by 67% from 1993 to 2020 by replacing lowland mainly, followed by vegetation, bare soil and water bodies. LSTs found in the study area were ranged from 23.26 to 39.94 °C, 23.69 to 43.35 °C and 24.44 to 44.58 °C for the years 1993, 2007 and 2020, respectively. The increases of spatially distributed maximum and mean LST were found 4.62 °C and 6.43 °C, respectively, for the study period of 27 years while the change in minimum LST was not substantial. LST increased by around 0.24 °C per year and human thermal discomfort shifted from moderate to strong heat stress for the total study period due to the increase of built-up and bare lands. This study also shows that normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were negatively correlated with LST while normalized difference built-up Index (NDBI) and normalized difference built-up Index (NDBAI) were positively correlated with LST. The methodology developed in this study can be adapted to other cities around the globe.

scholarly journals Beyond Singular Climatic Variables—Identifying the Dynamics of Wholesome Thermo-Physiological Factors for Existing/Future Human Thermal Comfort during Hot Dry Mediterranean Summers

2018 ◽  
Vol 15 (11) ◽  
pp. 2362 ◽  
Author(s):  
Andre Santos Nouri ◽  
Ioannis Charalampopoulos ◽  
Andreas Matzarakis
Keyword(s):  
Thermal Comfort ◽  
Heat Waves ◽  
Physiological Stress ◽  
Climatic Variables ◽  
Climatic Data ◽  
Equivalent Temperature ◽  
Physiological Equivalent Temperature ◽  
Human Thermal Comfort ◽  
Physiological Indices ◽  
Typical Summer

Centered on hot dry Mediterranean summer climates, this study assesses the climatic data that was extracted from Lisbon’s meteorological station between the years of 2012 and 2016. Focused on the summer period, existing outdoor human thermal comfort levels that are already prone to extreme heat stress thresholds were evaluated. Such an assessment was rooted around identifying the relationship and discrepancies between singular climatic variables (e.g., air Temperature (Ta)); and adapted thermos-physiological indices (e.g., the modified physiologically equivalent temperature (mPET)), which also consider the influence of radiation fluxes over the human body. In addition, default urban canyon case studies (UCCs) were utilized to supplement how both differ and influence one another, especially under extreme weather conditions including heat waves events (HWE), and very hot days (VHD). Through the use of wholesome thermo-physiological indices, the study revealed that while human health and thermal comfort is already prone to extreme physiological stress (PS) grades during one of the hottest months of the year, the current extremes could be drastically surpassed by the end of the century. Within the examined UCCs, it was identified that the projected PET could reach values of 58.3 °C under a projected climate change RCP8.5/SRES A1FI scenario. Similarly, and in terms of thermo-physiological stress loads, the following could happen: (i) a future “cooler summer day” could present similar conditions to those currently found during a ‘typical summer day; (ii) a future ‘typical summer day’ could present hourly physiological equivalent temperature load (PETL) that recurrently surpassed those currently found during a “very hot day”; and, (iii) a future “very hot day” could reveal severe hourly PETL values that reached 35.1 units beyond the established “no thermal stress” class.

scholarly journals Remotely Sensed Derived Land Surface Temperature (LST) as a Proxy for Air Temperature and Thermal Comfort at a Small Geographical Scale

Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 410
Author(s):  
Ran Goldblatt ◽  
Abdullah Addas ◽  
Daynan Crull ◽  
Ahmad Maghrabi ◽  
Gabriel Gene Levin ◽  
...  
Keyword(s):  
Thermal Comfort ◽  
Land Surface ◽  
Remotely Sensed ◽  
Urban Heat Islands ◽  
Remotely Sensed Data ◽  
Physiological Equivalent Temperature ◽  
Heat Islands ◽  
Geographical Scale ◽  
Urban Heat

Urban Heat Islands (UHIs) and Urban Cool Islands (UCIs) can be measured by means of in situ measurements and interpolation methods, which often require densely distributed networks of sensors and can be time-consuming, expensive and in many cases infeasible. The use of satellite data to estimate Land Surface Temperature (LST) and spectral indices such as the Normalized Difference Vegetation Index (NDVI) has emerged in the last decade as a promising technique to map Surface Urban Heat Islands (SUHIs), primarily at large geographical scales. Furthermore, thermal comfort, the subjective perception and experience of humans of micro-climates, is also an important component of UHIs. It remains unanswered whether LST can be used to predict thermal comfort. The objective of this study is to evaluate the accuracy of remotely sensed data, including a derived LST, at a small geographical scale, in the case study of King Abdulaziz University (KAU) campus (Jeddah, Saudi Arabia) and four surrounding neighborhoods. We evaluate the potential use of LST estimates as proxy for air temperature (Tair) and thermal comfort. We estimate LST based on Landsat-8 measurements, Tair and other climatological parameters by means of in situ measurements and subjective thermal comfort by means of a Physiological Equivalent Temperature (PET) model. We find a significant correlation (r = 0.45, p < 0.001) between LST and mean Tair and the compatibility of LST and Tair as equivalent measures using Bland-Altman analysis. We evaluate several models with LST, NDVI, and Normalized Difference Built-up Index (NDBI) as data inputs to proxy Tair and find that they achieve error rates across metrics that are two orders of magnitude below that of a comparison with LST and Tair alone. We also find that, using only remotely sensed data, including LST, NDVI, and NDBI, random forest classifiers can detect sites with “very hot” classification of thermal comfort nearly as effectively as estimates using in situ data, with one such model attaining an F1 score of 0.65. This study demonstrates the potential use of remotely sensed measurements to infer the Physiological Equivalent Temperature (PET) and subjective thermal comfort at small geographical scales as well as the impacts of land cover and land use characteristics on UHI and UCI. Such insights are fundamental for sustainable urban planning and would contribute enormously to urban planning that considers people’s well-being and comfort.

Human Thermal Comfort and Indoor Air Quality

2016 ◽  
pp. 67-98
Author(s):  
T. Agami Reddy ◽  
Jan F. Kreider ◽  
Peter S. Curtiss ◽  
Ari Rabl
Keyword(s):  
Air Quality ◽  
Thermal Comfort ◽  
Indoor Air Quality ◽  
Indoor Air ◽  
Human Thermal Comfort

scholarly journals The Effects of Green Roofs on Outdoor Thermal Comfort, Urban Heat Island Mitigation and Energy Savings

Atmosphere ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 123 ◽  
Author(s):  
Guglielmina Mutani ◽  
Valeria Todeschi
Keyword(s):  
Surface Temperature ◽  
Thermal Comfort ◽  
Urban Heat Island ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Green Roofs ◽  
Heat Island ◽  
Urban Context ◽  
Urban Heat ◽  
The City

There is growing attention to the use of greenery in urban areas, in various forms and functions, as an instrument to reduce the impact of human activities on the urban environment. The aim of this study has been to investigate the use of green roofs as a strategy to reduce the urban heat island effect and to improve the thermal comfort of indoor and outdoor environments. The effects of the built-up environment, the presence of vegetation and green roofs, and the urban morphology of the city of Turin (Italy) have been assessed considering the land surface temperature distribution. This analysis has considered all the information recorded by the local weather stations and satellite images, and compares it with the geometrical and typological characteristics of the city in order to find correlations that confirm that greenery and vegetation improve the livability of an urban context. The results demonstrate that the land-surface temperature, and therefore the air temperature, tend to decrease as the green areas increase. This trend depends on the type of urban context. Based on the results of a green-roofs investigation of Turin, the existing and potential green roofs are respectively almost 300 (257,380 m2) and 15,450 (6,787,929 m2). Based on potential assessment, a strategy of priority was established according to the characteristics of building, to the presence of empty spaces, and to the identification of critical areas, in which the thermal comfort conditions are poor with low vegetation. This approach can be useful to help stakeholders, urban planners, and policy makers to effectively mitigate the urban heat island (UHI), improve the livability of the city, reduce greenhouse gas (GHG) emissions and gain thermal comfort conditions, and to identify policies and incentives to promote green roofs.

scholarly journals Monitoring the Interannual Spatiotemporal Changes in the Land Surface Thermal Environment in Both Urban and Rural Regions from 2003 to 2013 in China Based on Remote Sensing

2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Yuanzheng Li ◽  
Lan Wang ◽  
Liping Zhang ◽  
Qing Wang
Keyword(s):  
Land Surface ◽  
Thermal Environment ◽  
Well Being ◽  
Urban Heat Islands ◽  
Central China ◽  
Human Reproduction ◽  
Night Time ◽  
Rural And Urban ◽  
Significance Levels ◽  
Moderate Resolution Imaging Spectroradiometer

The thermal environment is closely related to human well-being. Diurnal and seasonal variations in surface urban heat islands (SUHIs) have been extensively studied. Nevertheless, interannual changes in SUHIs as well as in land surface temperatures (LSTs) in cities and their corresponding villages remain poorly understood, particularly using data from several continuous years to analyse change rates and corresponding significance levels. Using Aqua/Terra moderate resolution imaging spectroradiometer (MODIS) data for 2003–2013, we explored not only the interannual changes in annual and seasonal mean LSTs in rural and urban regions which were identified based on modified criteria, but also the SUHI intensities (SUHIIs) for these cities. The results showed that most of LSTs and SUHIIs did not change significantly (p≥0.05). Their changes exhibited clear spatiotemporal agglomeration and variation laws. The rural region LST change rates, which exhibited significant changes, were generally highest in the summer, with most of values of 0.1–0.5°C (yr−1) during the daytime across China, except for the Xinjiang autonomous regions, and 0.1–0.2°C (yr−1) during the night-time. The rates were lowest in the winter, with most of values of −0.4 to −0.1°C (yr−1). The rates of daytime SUHIIs with significant changes were generally highest in the summer, with most of values of 0.1–0.3°C (yr−1), and lowest in the winter, even with most of values of −0.4 to −0.1°C (yr−1) in northern central China. During the night-time, most of rates were 0.0–0.1°C (yr−1). In China, most of the changes in the surface thermal environment were harmful to humans at both large national and local urban scales. The changes could lower thermal comfort levels, harm human health, affect human reproduction rates and lives, and increase the energy consumed for refrigeration or heating, thereby increase emissions of greenhouse gases.

scholarly journals Night Thermal Unmixing for the Study of Microscale Surface Urban Heat Islands with TRISHNA-Like Data

2019 ◽  
Vol 11 (12) ◽  
pp. 1449 ◽  
Author(s):  
Carlos Granero-Belinchon ◽  
Aurelie Michel ◽  
Jean-Pierre Lagouarde ◽  
Jose A. Sobrino ◽  
Xavier Briottet
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Image Resolution ◽  
Urban Heat Islands ◽  
Land Uses ◽  
Regression Kriging ◽  
Heat Islands ◽  
Urban Heat ◽  
Land Covers ◽  
The City

Urban Heat Islands (UHIs) at the surface and canopy levels are major issues in urban planification and development. For this reason, the comprehension and quantification of the influence that the different land-uses/land-covers have on UHIs is of particular importance. In order to perform a detailed thermal characterisation of the city, measures covering the whole scenario (city and surroundings) and with a recurrent revisit are needed. In addition, a resolution of tens of meters is needed to characterise the urban heterogeneities. Spaceborne remote sensing meets the first and the second requirements but the Land Surface Temperature (LST) resolutions remain too rough compared to the urban object scale. Thermal unmixing techniques have been developed in recent years, allowing LST images during day at the desired scales. However, while LST gives information of surface urban heat islands (SUHIs), canopy UHIs and SUHIs are more correlated during the night, hence the development of thermal unmixing methods for night LSTs is necessary. This article proposes to adapt four empirical unmixing methods of the literature, Disaggregation of radiometric surface Temperature (DisTrad), High-resolution Urban Thermal Sharpener (HUTS), Area-To-Point Regression Kriging (ATPRK), and Adaptive Area-To-Point Regression Kriging (AATPRK), to unmix night LSTs. These methods are based on given relationships between LST and reflective indices, and on invariance hypotheses of these relationships across resolutions. Then, a comparative study of the performances of the different techniques is carried out on TRISHNA synthesized images of Madrid. Since TRISHNA is a mission in preparation, the synthesis of the images has been done according to the planned specification of the satellite and from initial Aircraft Hyperspectral Scanner (AHS) data of the city obtained during the DESIREX 2008 capaign. Thus, the coarse initial resolution is 60 m and the finer post-unmixing one is 20 m. In this article, we show that: (1) AATPRK is the most performant unmixing technique when applied on night LST, with the other three techniques being undesirable for night applications at TRISHNA resolutions. This can be explained by the local application of AATPRK. (2) ATPRK and DisTrad do not improve significantly the LST image resolution. (3) HUTS, which depends on albedo measures, misestimates the LST, leading to the worst temperature unmixing. (4) The two main factors explaining the obtained performances are the local/global application of the method and the reflective indices used in the LST-index relationship.

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