Background: Heatwaves present a significant health risk and the hazard is likely to escalate with the increased future temperatures presently predicted by climate change models. The impact of heatwaves is often felt strongest in towns and cities where populations are concentrated and where the climate is often unintentionally modified to produce an urban heat island effect; where urban areas can be significantly warmer than surrounding rural areas. The purpose of this interdisciplinary study is to integrate remotely sensed urban heat island data alongside commercial social segmentation data via a spatial risk assessment methodology in order to highlight potential heat health risk areas and build the foundations for a climate change risk assessment. This paper uses the city of Birmingham, UK as a case study area.
Results: When looking at vulnerable sections of the population, the analysis identifies a concentration of "very high" risk areas within the city centre, and a number of pockets of "high risk" areas scattered throughout the conurbation. Further analysis looks at household level data which yields a complicated picture with a considerable range of vulnerabilities at a neighbourhood scale.
Conclusions: The results illustrate that a concentration of "very high" risk people live within the urban heat island, and this should be taken into account by urban planners and city centre environmental managers when considering climate change adaptation strategies or heatwave alert schemes. The methodology has been designed to be transparent and to make use of powerful and readily available datasets so that it can be easily replicated in other urban areas.
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http://dx.doi.org/10.1186/1476-072X-10-42 | DOI Listing |
Nat Commun
January 2025
Institute of Carbon Neutrality, Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China.
Proc Natl Acad Sci U S A
January 2025
Laboratoire de Géologie, Ecole Normale Supérieure, CNRS, Institut Pierre-Simon Laplace, Université Paris Sciences et Lettres, Paris 75005, France.
The insulative properties of soil organic carbon (SOC) and surface organic layers (moss, lichens, litter) regulate surface-atmosphere energy exchanges in the Arctic through a coupling with soil temperatures. However, a physical description of this process is lacking in many climate models, potentially biasing their high-latitude climate predictions. Using a coupled surface-atmosphere model, we identified a strong feedback loop between soil insulation, surface air temperature, and snowfall.
View Article and Find Full Text PDFEnviron Res
January 2025
School of Remote Sensing & Geomatics Engineering, Nanjing University of Information Science & Technology, No.219, Ningliu Road, Nanjing, 210044, Jiangsu, China.
Heat extremes become increasingly frequent and severe, posing adverse risks to public health and environment. Previous research on extreme heat mostly used meteorological observations or reanalysis data, which cannot well capture detailed spatial patterns. This study developed a seamless air temperature (T) dataset from remote sensing data to characterize the spatio-temporal variations of heat extremes in the Yangtze River Delta (YRD) from 2001 to 2023.
View Article and Find Full Text PDFActa Pharm
December 2024
University of Zagreb Faculty of Pharmacy and Biochemistry, Department of Pharmacognosy 10000 Zagreb, Croatia.
Biowaste produced in urban parks is composed of large masses of organic matter that is only occasionally used economically. In this work, extracts of six plants widely distributed in urban parks in Central Europe (, , , , , and ), prepared using 10 % and 50 % ethanol, were screened for their antidiabetic and related properties. HPLC and UV-Vis analysis revealed the presence of caffeic acid, quercetin, luteolin, and apigenin derivatives.
View Article and Find Full Text PDFEnviron Monit Assess
January 2025
College of Earth and Environmental Sciences, University of the Punjab, Lahore, 54000, Pakistan.
Rapid urbanization in Lahore has dramatically transformed land use and land cover (LULC), significantly impacting the city's thermal environment and intensifying climate change and sustainable development challenges. This study aims to examine the changes in the urban landscape of Lahore and their impact on the Urban thermal environment between 1990 and 2020. The previous studies conducted on Lahore lack the application of Geospatial artificial intelligence (GeoAI) to quantify land use and land cover, which is successfully covered in this study.
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