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New Methods for Urban Heat Assessment and Prediction: From IoT...
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New Methods for Urban Heat Assessment and Prediction: From IoT to Remote Sensing and AI

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Atmospheric Techniques, Instruments, and Modeling".

Deadline for manuscript submissions: closed (31 May 2024) | Viewed by 4780

Special Issue Editor

Dr. António Saraiva Lopes

E-Mail Website
Guest Editor
IGOT—Institute of Geography and Spatial Planning, Center of Geographical Studies, University of Lisbon, Rua Branca Edmée Marques, 1600-276 Lisboa, Portugal
Interests: urban climatology; urban planning; climate guidelines; human comfort and health; thermal remote sensing; climate services
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The extensive information and numerous scientific evidence presented in the six reports of the Intergovernmental Panel on Climate Change, across more than three decades (1990 to 2022), have not transformed actions to the desired extent. The implementation of adaptive measures requires coordinated and collaborative effort from local governments, businesses, civil society, and citizens. Commitment from all sectors of society is also necessary to work together in implementing concrete and effective measures for mitigation and adaptation.

Within this Special Issue, researchers are called upon to submit communications from three perspectives: (i) new research methods in urban climate change, especially related to the new technologies available today (big data, IoT, remote sensing AI, climate walks, etc.), to better understand complex urban climate patterns (heat, humidity, wind, energy balance, etc.); (ii) case studies of good practices that demonstrate the need to include various spatial scales of analysis and intervention in the urban climate system, in an era where it is urgent to prioritize actions for adapting to and mitigating climate risks (droughts, floods, heatwaves, severe storms, etc.); and (iii) studies applied to various sectors of society, for example, urban health and NBS; displaced populations; mobility and urban pollution; and from lessons learned from pandemics worldwide to missed opportunities. In short, this SI will cover everything that may jeopardize the Sustainable Development Goals (SDGs) in the 21st century.

Prof. Dr. António Saraiva Lopes
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • big data
  • Internet of Things (IoT)
  • artificial intelligence (AI)
  • applied remote sensing
  • climate walks
  • urban resilience
  • compared studies for solutions

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Published Papers (3 papers)

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Research

38 pages, 5661 KiB  
Article
Lisbon Urban Climate: Statistical Analysis/Approach for Urban Heat Island Effect Based on a Pioneering Urban Meteorological Network
by Daniel Vilão and Isabel Loupa Ramos
Atmosphere 2024, 15(10), 1177; https://doi.org/10.3390/atmos15101177 - 30 Sep 2024
Viewed by 898
Abstract
The urban heat island (UHI) effect is a widely recognized phenomenon consisting of heat accumulation by dense urban construction and human activities, resulting in higher temperatures across urban areas compared to their surroundings. This article aims to quantify the UHI effect on several [...] Read more.
The urban heat island (UHI) effect is a widely recognized phenomenon consisting of heat accumulation by dense urban construction and human activities, resulting in higher temperatures across urban areas compared to their surroundings. This article aims to quantify the UHI effect on several areas throughout the city of Lisbon, Portugal, with the main goal of validating, evaluating, and reinforcing urban climate adaptation and resilience strategies proposed in the recent scientific literature. A set of nine quality-controlled weather stations from the “Lisboa Aberta” network that are compliant with the World Meteorological Organization (WMO) standards and installation requirements were used to characterize Lisbon’s UHI, in comparison to a reference weather station from the Instituto Português do Mar e da Atmosfera (IPMA), located at Lisbon Airport. By applying a principal component analysis (PCA) in an innovative way to 10 urban indexes, it is shown that the thermal inertia in Lisbon’s urban areas is positively correlated with the UHI intensity and urban density, regardless of the daily heating/cooling cycle. Furthermore, the results show that land use also has an impact on the UHI effect, with continuous, vertical building areas showing the greatest deviations in comparison to the reference, averaging +1.8 °C. Contrastingly, horizontal building areas reveal an average deviation of +1.3 °C, with sparse, discontinuously built areas representing an average UHI effect of +0.2 °C. Finally, through a climatope analysis, it is determined that, across Lisbon, high-density urban areas and ventilation corridors are responsible for inducing average UHI effects of +1.7 °C and +0.2 °C, respectively. Full article
(This article belongs to the Special Issue New Methods for Urban Heat Assessment and Prediction: From IoT to Remote Sensing and AI)
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26 pages, 14766 KiB  
Article
Metrological Evaluation of the Building Influence on Air Temperature Measurements
by Carmen Garcia Izquierdo, Graziano Coppa, Sonia Hernández and Andrea Merlone
Atmosphere 2024, 15(2), 209; https://doi.org/10.3390/atmos15020209 - 7 Feb 2024
Cited by 3 | Viewed by 1635
Abstract
This paper describes the metrological procedure carried out for the evaluation of the building influence on air temperature measurements. This evaluation aims to produce reliable conclusions, information, and data to contribute to the WMO siting classification schemes for air temperature measurements. For this [...] Read more.
This paper describes the metrological procedure carried out for the evaluation of the building influence on air temperature measurements. This evaluation aims to produce reliable conclusions, information, and data to contribute to the WMO siting classification schemes for air temperature measurements. For this purpose, a field experiment was designed, deployed, and carried out. As a result, one-year-lasting air temperature measurements were collected and analyzed. In this field experiment, a 200 m wide building is the unique artificial heat source and the unique object projecting shades over a flat surface (no discernible slope) in an open space bigger than 40,000 m2, covered with short grass. Eight calibrated thermometers, equipped with the same model of artificially ventilated radiation shields, were set up at a height of 1.5 m from the ground and at different distances from a 200 m wide building. This configuration provides the observation of the horizontal air temperature radially distributed from the building and, as a conclusion, it enables the quantification of the building influences on air temperature measurements at different distances from the building. This document describes the field experiment, the analysis procedure, the evolution of the building influence on air temperature measurements along the day, and the impact of other meteorological parameters on this building effect. Two different building effects are observed: the positive building effect, where the air temperature decreases with the distance to the building, and the negative building effect, where the air temperature increases with the distance to the building. It is also noticed that the building influence is higher on clear days and the daily maximum building influence values are directly linked with the corresponding maximum solar irradiance. The influence of wind on the building effect is also analyzed, reaching the conclusion that due to characteristic of local winds, in terms of low speed and direction, the wind impact could be considered as negligible. The maximum values of building influence on air temperature measurements, the associated uncertainty analysis, and the conclusions are presented in this paper. All these points have been addressed using metrological principles with the purpose of giving consistency and robustness to the evidence presented here. Full article
(This article belongs to the Special Issue New Methods for Urban Heat Assessment and Prediction: From IoT to Remote Sensing and AI)
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22 pages, 7270 KiB  
Article
Microclimate Multivariate Analysis of Two Industrial Areas
by Angela Maria de Arruda, António Lopes and Érico Masiero
Atmosphere 2023, 14(8), 1321; https://doi.org/10.3390/atmos14081321 - 21 Aug 2023
Viewed by 1557
Abstract
Most of the existing studies on the increase in air temperature (AT) in industrial neighborhoods (UIs) approach the subject from the analysis of the land surface temperature (LST). Therefore, the objective of this study was to analyze, in addition to LST, the variables [...] Read more.
Most of the existing studies on the increase in air temperature (AT) in industrial neighborhoods (UIs) approach the subject from the analysis of the land surface temperature (LST). Therefore, the objective of this study was to analyze, in addition to LST, the variables of air temperature, relative and specific humidity, wind speed and direction, sky view factor and the albedo of the material surfaces, and to verify which of them has a greater impact on the urban microclimate of the UIs of two cities, Sintra/PT and Uberlândia/BR. To develop this analysis, representative sections of industrial urban areas in the previously mentioned cities were selected and computational simulations were carried out with the ENVI-met software to obtain results related to the studied variables. The results of the simulations, analyzed using multivariate analysis, showed that even though the Udia UI has materials with lower albedo (−45%), lower percentages of vegetation (−20%) and lower WS (−40%) than the Sin UI, the AT inside it may be lower than in the unshaded surroundings around 1.3 °C. For Sin UI, a difference in WS of −1.9 m/s, compared to the control points, caused a peak of +1.5 °C in the industrial environment at 13 h, contrary to what happened in Udia UI. Full article
(This article belongs to the Special Issue New Methods for Urban Heat Assessment and Prediction: From IoT to Remote Sensing and AI)
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