Packaging Environmental Sensors for an Internet-of-Things Solution for Urban-Microclimate Studies

2019 ◽  
Author(s):  
Shuv Dey ◽  
Yogendra Joshi ◽  
J. Michael Brown
Keyword(s):  
Rural Areas ◽  
Low Cost ◽  
Urban Environments ◽  
Environmental Data ◽  
Sensor Data ◽  
Heat Island ◽  
Environmental Sensors ◽  
Negative Effects ◽  
Air Temperatures ◽  
Urban Heat

Abstract Cities are experiencing a number of negative effects caused by increasing urbanization. For decades, the effects of pollution have been recognized and studied and steps have been taken attempting to control this problem. Many urban environments are also experiencing the effect of the Urban Heat Island (UHI). UHIs are metropolitan areas that have measurably warmer average air temperatures during several periods during the year, than their surrounding rural areas. There is a great interest in studying UHI and pollution and its effects on the environment as well as urban residents. However, in order to study these phenomena, we need more information than we currently have. Thus, an IoT based low cost sensor network can be used to collect the data necessary to study UHI and pollution. There are several key challenges associated with an IoT based solution to environmental data monitoring. This study explores these challenges by looking at what effect the packaging has on the deployed environmental sensors, and how and where to deploy sensor modules. Sensor data collected over a few months’ timeframe are analyzed and presented.

Packaging Environmental Sensors for Monitoring Urban-Microclimates

2020 ◽  
Vol 1 (3) ◽  
Author(s):  
Shuv Dey ◽  
J. Michael Brown ◽  
Yogendra Joshi
Keyword(s):  
Low Cost ◽  
Environmental Data ◽  
Data Monitoring ◽  
Cfd Modeling ◽  
Heat Island ◽  
Environmental Sensors ◽  
Cfd Model ◽  
Advanced Packaging ◽  
Urban Heat ◽  
Urban Microclimates

Abstract An internet-of-things (IoT)-based low-cost sensor network can be used to collect the data necessary to study both Urban Heat Island (UHI) and air pollution. There are several key challenges associated with an IoT-based solution to environmental data monitoring, including packaging and deployment. This study explores these challenges by looking at effects the packaging has on the deployed environmental sensors. Several packaging designs are numerically studied using a computation fluid dynamics (CFD) model. Two sensor designs are chosen using results obtained from CFD modeling and then experimentally deployed. The findings conclude that the IoT sensors chosen for this study are not significantly affected by flow velocities or require advanced packaging designs when paired with street-side outdoor digital displays.

Using localised weather files to assess overheating in naturally ventilated offices within London's urban heat island

2011 ◽  
Vol 33 (4) ◽  
pp. 351-369 ◽  
Author(s):  
C Demanuele ◽  
A Mavrogianni ◽  
M Davies ◽  
M Kolokotroni ◽  
I Rajapaksha
Keyword(s):  
Urban Heat Island ◽  
Rural Areas ◽  
Urban Environments ◽  
Policy Implications ◽  
Weather Data ◽  
Heat Island ◽  
Urban Buildings ◽  
Air Temperatures ◽  
Urban Heat ◽  
The Impact

Urban environments typically experience increased average air temperatures compared to surrounding rural areas – a phenomenon referred to as the Urban Heat Island (UHI). The impact of the UHI on comfort in naturally ventilated buildings is the main focus of this article. The overheating risk in urban buildings is likely to be exacerbated in the future as a result of the combined effect of the UHI and climate change. In the design of such buildings in London, the usual current practice is to view the use of one generic weather file as being adequate to represent external temperatures. However, the work reported here demonstrates that there is a considerable difference between the overheating performance of a standard building at different sites within London. This implies, for example, that a building may wrongly pass or fail criteria used to demonstrate compliance with building regulations as a result of an inappropriate generic weather file being used. The work thus has important policy implications. Practical application: The Greater London Authority has recently developed, with the Chartered Institute of Building Services Engineers, guidance for developers to address the risk of overheating in buildings via the provision of weather files for London relating to three zones. While such an initiative is welcomed, it may be that a weather file tailored to the building location would be preferable. Of course, this would add further complexity to the process and a view would have to be taken as the viability of such an approach. The work presented in this article, however, suggests that serious consideration should be given to the use of tailored weather data for regulatory purposes.

scholarly journals Evaluating the roles of green and built-up areas in reducing a surface urban heat island using remote sensing data

Urbani izziv ◽  
2019 ◽  
Vol 2 (30) ◽  
pp. 105-112
Author(s):  
Gordana Kaplan
Keyword(s):  
Urban Heat Island ◽  
Rural Areas ◽  
Land Surface ◽  
Remote Sensing Data ◽  
Heat Island ◽  
Negative Effects ◽  
Rapid Urbanization ◽  
Green Areas ◽  
Urban Heat ◽  
Surface Urban Heat Island

Rapid urbanization has several negative effects on both the environment and human health. Urbanization has also become an important contributor to global warming. One of these effects is the urban heat island (UHI), which is caused by human activities and defined as the temperature difference between urban and surrounding rural areas. With rapid urbanization in the past few decades, Skopje has experienced remarkable UHI effects. To investigate the roles of built-up and green areas in a surface UHI, this article uses satellite data from Landsat ETM+ to analyse the land surface temperature and high-resolution Planet Scope DOVE data to analyse built-up and green areas. For geostatistical analyses, seventeen randomly selected subareas in Skopje were used. The results show a significant correlation between the UHI and built-up areas, and strong correlation between green areas and areas not affected by the UHI, indicating that the UHI effect can be significantly weakened with additional green areas. One of the significant findings in the study is the ideal proportion of built-up (40%) and green areas (60%), where the UHI effect is weak, or in some cases prevented. For future studies, investigating other factors that may contribute to the UHI phenomenon is suggested.

Automated detection of urban heat islands based on satellite imagery, digital surface models, and a low-cost sensor network                                     

2021 ◽  
Author(s):  
Sebastian Schlögl ◽  
Nico Bader ◽  
Julien Gérard Anet ◽  
Martin Frey ◽  
Curdin Spirig ◽  
...  
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Rural Areas ◽  
Urban Areas ◽  
Low Cost ◽  
Urban Heat Islands ◽  
Heat Islands ◽  
Micro Scale ◽  
Air Temperatures ◽  
Urban Heat

<p>Today, more than half of the world’s population lives in urban areas and the proportion is projected to increase further in the near future. The increased number of heatwaves worldwide caused by the anthropogenic climate change may lead to heat stress and significant economic and ecological damages. Therefore, the growth of urban areas in combination with climate change can increase future mortality rates in cities, given that cities are more vulnerable to heatwaves due to the greater heat storage capacity of artificial surfaces towards higher longwave radiation fluxes.</p><p>To detect urban heat islands and resolve the micro-scale air temperature field in an urban environment, a low-cost air temperature network, including 450 sensors, was installed in the Swiss cities of Zurich and Basel in 2019 and 2020. These air temperature data, complemented with further official measurement stations, force a statistical air temperature downscaling model for urban environments, which is used operationally to calculate hourly micro-scale air temperatures in 10 m horizontal resolution. In addition to air temperature measurements from the low-cost sensor network, the model is further forced by albedo, NDVI, and NDBI values generated from the polar-orbiting satellite Sentinel-2, land surface temperatures estimated from Landsat-8, and high-resolution digital surface and elevation models.</p><p>Urban heat islands (UHI) are processed averaging hourly air temperatures over an entire year for each grid point, and comparing this average to the overall average in rural areas. UHI effects can then be correlated to high-resolution local climate zone maps and other local factors.</p><p>Between 60-80 % of the urban area is modeled with an accuracy below 1 K for an hourly time step indicating that the approach may work well in different cities. However, the outcome may depend on the complexity of the cities. The model error decreases rapidly by increasing the number of spatially distributed sensor data used to train the model, from 0 to 70 sensors, and then plateaus with further increases. An accuracy below 1 K can be expected for more than 50 air temperature measurements within the investigated cities and the surrounding rural areas. </p><p>A strong statistical air temperature model coupled with atmospheric boundary layer models (e.g. PALM-4U, MUKLIMO, FITNAH) will aid to generate highly resolved urban heat island prediction maps that help decision-makers to identify local heat islands easier. This will ensure that financial resources will be invested as efficiently as possible in mitigation actions.</p>

scholarly journals Comparison of Temperatures and Spatial Resolutions between Urban Sensors and National Weather Observations (ASOS, AWS) for Urban Heat Island Intensity Analysis

2021 ◽  
Vol 21 (3) ◽  
pp. 39-48
Author(s):  
Haekyung Park
Keyword(s):  
Urban Heat Island ◽  
Urban Environments ◽  
Sensor Data ◽  
Heat Island ◽  
Heat Islands ◽  
The Public ◽  
Weather Observations ◽  
Urban Heat ◽  
The Difference ◽  
Weather Observation

Urban temperatures have become more important because the frequency and intensity of heatwaves will increase with the worsening urban heat island effects due to climate change. Recently, urban sensors are emerging as a new means of heat island analysis, and urban sensor data including temperatures were opened to the public in Seoul in 2020. However, there are insufficient cases of analysis and the differences from national weather observation are unknown. Accordingly, this study introduces the S⋅DoT (Smart Seoul Data of Things), an urban sensor in Seoul, and compared S⋅DoT temperatures with national weather observation (such as ASOS and AWS) temperature in order to facilitate heat island analysis using urban sensors. The result shows the S⋅DoT temperature is about 1-1.15 ℃ higher than ASOS⋅AWS during May to August 2020, which is due to differences in the height and installation environment, not in the performance of the equipment. S⋅DoT is installed in the urban environments at the height of approximately 3 m and measures the actual living temperature, whereas ASOS measures temperature in the controlled environment and AWS measures temperature from the higher position due to being installed on the top of a building. Therefore, we suggest that when using S⋅DoT together with rural AWS temperature to analyze the intensity of heat islands, calibration should be considered taking into account the difference between the two observations, and a better method is to calculate the heat island intensity only using S⋅DoT temperature in urbanized and non-urbanized areas without using rural temperature.

Use of Satellite Images for Observational and Quantitative Analysis of Urban Heat Islands Around the World

2012 ◽  
Author(s):  
Kaufui V. Wong ◽  
Sarmad Chaudhry
Keyword(s):  
Urban Heat Island ◽  
Temperature Difference ◽  
Rural Areas ◽  
Urban Areas ◽  
Urban Environments ◽  
Urban Heat Islands ◽  
Heat Island ◽  
The World ◽  
Urban Heat ◽  
Landsat Satellite

Urban Heat Island Intensity (UHII) is calculated as the spatially-averaged temperature difference between an urban and its surrounding rural area. This concept, however, provides an umbrella for a range of diversified ideas that include the temperature difference between the densely developed urban area and least developed area or between two different built-up areas. There are also averages for the season, for the year, for multiple years, etc. and UHII quoted for the day and another for the night. The objective of this work is to examine the urban heat island effect for cities around the world, using readily available data. The innovation is in using data from the Landsat satellites for different cities previously not studied. Thermal images of the Earth were obtained and analyzed to produce surface temperature maps. These maps showed that the temperature in the urban environments were significantly higher than the temperature in the surrounding countryside, a defining characteristic of urban heat island. Furthermore, the urban and rural areas in the images were separated and analyzed individually to quantitatively measure the temperature difference. It was found that the UHII could be 0.3–5.1°C for the eleven cities investigated. Miami and Shenzen are two cities which seem to have been missed in previous studies because they were limited in their scope and responsibilities, and their methods required much more resources for the longer term studies. It is not the claim here that a UHI is definitively established by the analysis presented of the Landsat satellite data. The present work demonstrates the use of a possible planning tool in terms of understanding where urban areas may be subjected to additional heat. Our use of the method shows that a UHI is probably taking place at the time of observation, and precautionary notices should be sent out to the community to take preventative measures to ensure their health and wellbeing. The minimal resources required is the demonstration shown by our work of the usefulness of this method.

scholarly journals The Impact of the Urban Heat Island during an Intense Heat Wave in Oklahoma City

2010 ◽  
Vol 2010 ◽  
pp. 1-10 ◽  
Author(s):  
Jeffrey B. Basara ◽  
Heather G. Basara ◽  
Bradley G. Illston ◽  
Kenneth C. Crawford
Keyword(s):  
Urban Heat Island ◽  
Heat Wave ◽  
Rural Areas ◽  
Oklahoma City ◽  
Apparent Temperature ◽  
Heat Island ◽  
Atmospheric Conditions ◽  
Urban Heat ◽  
The Impact ◽  
Intense Heat

During late July and early August 2008, an intense heat wave occurred in Oklahoma City. To quantify the impact of the urban heat island (UHI) in Oklahoma City on observed and apparent temperature conditions during the heat wave event, this study used observations from 46 locations in and around Oklahoma City. The methodology utilized composite values of atmospheric conditions for three primary categories defined by population and general land use: rural, suburban, and urban. The results of the analyses demonstrated that a consistent UHI existed during the study period whereby the composite temperature values within the urban core were approximately C warmer during the day than the rural areas and over C warmer at night. Further, when the warmer temperatures were combined with ambient humidity conditions, the composite values consistently revealed even warmer heat-related variables within the urban environment as compared with the rural zone.

scholarly journals Microclimate Evaluation of the Hradec Králové City using HUMIDEX

2017 ◽  
Vol 47 (3) ◽  
pp. 231-246 ◽  
Author(s):  
Jaroslav Rožnovský ◽  
Tomáš Litschmann ◽  
Hana Středová ◽  
Tomáš Středa ◽  
Petr Salaš ◽  
...  
Keyword(s):  
Radiation Balance ◽  
Negative Effects ◽  
Environment Analysis ◽  
Surface Areas ◽  
Air Temperatures ◽  
Green Areas ◽  
Urban Heat ◽  
Surrounding Landscape ◽  
The City ◽  
Very High

Abstract Urban environment differs from the surrounding landscape in terms of the values of meteorological parameters. This is often referred to as the urban heat island (UHI), which in simple terms means higher air temperatures in cities. The cause of these changes lies in the different active surfaces in cities, which subsequently results in a different radiation balance. The higher temperatures, however, also affect the living conditions in the city and during very high temperature periods can have negative effects on the health of the city inhabitants. The results presented in this paper are based on measurements taken over several years at locations near Hradec Králové, which is surrounded by different surface areas. Environment analysis was performed using the Humidex index. The obtained results show that replacing green areas with built-up areas affects temperatures in the city, when air temperatures are very high they significantly increase the discomfort of the inhabitants. Differences in the frequency of discomfort levels are observed especially during periods of high temperatures, at lower temperatures these differences are not significant. Higher frequencies of discomfort are observed at locations with artificial surfaces (asphalt, cobblestones, concrete) and in closed spaces. In contrast, locations with lots of green areas almost always have the value of this index lower or more balanced. The results should therefore be a valid argument for maintaining and extending green areas in cities.

scholarly journals Urban heat island in Bloemfontein during winter

2013 ◽  
Vol 32 (1) ◽  
Author(s):  
Pieter Snyman ◽  
A. Stephen Steyn
Keyword(s):  
Maximum Intensity ◽  
Urban Heat Islands ◽  
Urban Air ◽  
Heat Island ◽  
Heat Islands ◽  
Air Temperatures ◽  
Local Topography ◽  
Urban Heat ◽  
The Difference ◽  
The City

Urban heat islands (UHIs) are characterised by warmer urban air temperatures compared to rural air temperatures, and the intensity is equal to the difference between the two. Air temperatures are measured at various sites across the city of Bloemfontein and then analysed to determine the UHI characteristics. The UHI is found to have a horseshoe shape and reaches a maximum intensity of 8.2 °C at 22:00. The UHI is largely affected by the local topography.

A comparative study of urban heat island effects in two Belarusian cities from satellite and ground-based observations

2021 ◽  
Author(s):  
Heorhi Burchanka ◽  
Yahor Prakopchyk ◽  
Tsimafei Schlender ◽  
Aleh Baravik ◽  
Siarhei Barodka
Keyword(s):  
Urban Heat Island ◽  
Rural Areas ◽  
City Planning ◽  
Thermal Characteristics ◽  
Data Availability ◽  
Eastern Bloc ◽  
Temperature Fields ◽  
Landsat 8 ◽  
Heat Island ◽  
Urban Heat

<p>This study is devoted to analysis of urban development effects on surface thermal characteristics for the case of Belarusian cities of Minsk and Mahiloŭ. Both cities being situated on the same latitude (53.90 N) and not far from each other (~180 km distance), while also sharing a number of similar features typical for cities in Belarus (and in some other former Eastern Bloc countries as well), Minsk and Mahiloŭ nevertheless differ significantly in terms of their population, size and structure. It is therefore of interest to perform urban climate studies for these two cities in parallel.</p><p>First, we use geoinformation systems (QGIS), centralized city planning databases and Open Street Maps (OSM) vector data to implement description of Minsk and Mahiloŭ urban territories in terms of functional zones, taking into account such features as buildings density and urban area category (industrial, residential, business, recreational and other types).</p><p>Furthermore, we perform analysis of surface temperature fields for both cities from satellite data (Landsat-8) and ground-based observations, the latter including both regular meteorological stations (in urban as well as surrounding rural areas) and a volunteer network of weather and air quality sensors distributed in both cities as part of the AirMQ project [1]. We analyze observations for several months in the 2019-2021 period (depending on data availability), paying special attention to days with specific weather conditions (e.g. blocking anticyclones).</p><p>Analysis demonstrates clear evidence of significant urban heat island effects in thermal regimes of both cities, with specific areas of increased temperature related to urban zoning, industrial and green areas, buildings heights and density. However, the selected method of surface urban heat island (SUHI) detection turns out to be somewhat limited for the purposes of studying the effects of blocking anticyclones on urban heat island phenomena development, thereby calling for application of atmospheric numerical modelling techniques.</p><p>[1] AirMQ project, URL: https://airmq.by/</p>

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