scholarly journals Pet Welfare in Municipal Adaptation Plans: Case of Poland

2021 ◽  
Vol 30 (3) ◽  
pp. 95-107
Author(s):  
Anna Haładyj ◽  
Katarzyna Kułak-Krzysiak
Keyword(s):  
Climate Change ◽  
Heat Stress ◽  
Thermal Comfort ◽  
Urban Heat Islands ◽  
Adaptation Measures ◽  
Main Hypothesis ◽  
Heat Islands ◽  
Starting Point ◽  
Legal Nature ◽  
Urban Heat

The aim of the article was to explore pet welfare in Municipal Adaptation Plans (MAPs), based on a literature review and case studies of 40 MAPs accepted in Poland as part of the “Let’s Feel the Climate” project, supported by the Polish Ministry of Environment in 2017–2019. The study summarizes the concept of climate change and the importance of adaptation measures with particular emphasis on urban heat islands and heat stress, acknowledged by climate change literature, and outlines pet welfare in the context of thermal comfort and threats caused by heat stress. Because the authors subsequently presented an empirical study of the 40 accepted MAPs, they also discussed the role and legal nature of MAPs. The main hypothesis of this survey of Polish MAPs was that pet welfare in the context of their thermal comfort is an example of the adaptive measures clearly stipulated in Polish MAPs, which was examined after presenting the MAPs’ findings. The starting point was the assumption that the welfare of pets should also be assessed from the perspective of their thermal comfort – a new element of broadly understood animal welfare. This is due to the fact that pets are exposed to the risk of heat stress resulting from urban heat islands and, just like people, have to endure the inconvenience of extreme weather phenomena, which is impossible without the support of amenities such as drinkers or water shelters and the development of green and blue infrastructure.

scholarly journals Use of remote sensing in the identification of Urban Heat Islands and in the evaluation of Human Thermal Comfort

2018 ◽  
Vol 7 (7) ◽  
pp. 408
Author(s):  
Rafaela Lisboa Costa
Keyword(s):  
Remote Sensing ◽  
Heat Stress ◽  
Surface Temperature ◽  
Thermal Comfort ◽  
Urban Areas ◽  
Satellite Images ◽  
Urban Heat Islands ◽  
Heat Islands ◽  
Human Thermal Comfort ◽  
Urban Heat

The objective of this study was to identify heat islands and to evaluate the degree of thermal comfort / discomfort in selected urban areas. Landsat 5 and 8 satellite images were use in the thermal bands and, as a complement, observed data from meteorological stations present in the chosen cities. In order to evaluate heat islands and the degree of thermal comfort / discomfort, the surface temperature was obtain and the Kawamura Discomfort Index (IDK) was use. By means of surface temperature images, it was possible to identify the heat islands in these areas. For IDK, in spite of this index, in general, to present the situation of comfort, for some areas were observe situations of discomfort and heat stress due to the heat, mainly in the year of 2016, considered one of the hottest of this century. The use of observed data was necessary in order to corroborate with the information of the satellites.

(Re)presenting urban heat islands in Australian cities: A study of media reporting and implications for urban heat and climate change debates

Urban Climate ◽  
2019 ◽  
Vol 27 ◽  
pp. 420-429 ◽  
Author(s):  
Alexander Iping ◽  
Juliette Kidston-Lattari ◽  
Alice Simpson-Young ◽  
Elizabeth Duncan ◽  
Phil McManus
Keyword(s):  
Climate Change ◽  
Urban Heat Islands ◽  
Media Reporting ◽  
Heat Islands ◽  
Urban Heat

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>

Sign in / Sign up

Export Citation Format

Share Document