Summary

The urbanization and growing urban population has exacerbated the Urban Heat Island (UHI) effect. To better understand the extent of exposure and the spatial distribution of health risks associated with the UHI effect, this study assessed the spatial distribution of UHI intensity and vulnerable population across three Swiss cities (Bern, Basel, and Zurich).

We used publicly available simulated night-time temperature in the summer of year 2020 in fine scales. The UHI intensity was calculated as the temperature difference between urban area and rural reference station for each city. Then we identified vulnerable populations having higher mortality risks to extreme heat and UHI effect utilizing existing evidence from previous studies. Based on the exsiting evidence, we identified older adults (aged > 64 years), females and individuals with the lowest socio-economic status as vulnerable population to UHI effect in Switzerland.

The key feature of this study is to identify at-risk neighbourhoods to UHI effect by using census data and publicly available temperature data. This comprehensive method can be potentially extended to other cities and give insights for indentifying vulnerable neighbourhoods and determinants exacerbating heat risks at the district level.

Data

Demographic and socio-economic data

We collected individual-level population and hosehold statistics, referred to as 'STATPOP' from the Swiss Federal Statistical Office for the years of 2012 to 2021. For this study, we used the STATPOP data in the year of 2020 to ensure temporal consistency with the temperature data employed in this study.Furthermore, we integrated the Swiss-SEP Index into this study, which is an area-based indicator reflecting the socio-economic position in Switzreland (Panczak et al. 2023).

For the information on the number of workers, we collected statistics on the Swiss economy so-called 'STATENT' for the year of 2020 collected from the Swiss Federal Office. Through STATENT, we calculated the number of employees by economic sectors (agricultural, industrial, and sevice sectors) by districts.

Temperature data

We used simulated night-time (4 a.m) air temperature at 2m above ground in year 2020. This data is based on FITNAH 3D model for the modelling process, incorporating data on terrain height, usage structure, and vegetation height (Gross 1989; Gross 1993; Gross 2002). The spatial resolution of the temperature varied depending on the city: Bern (5m x 5m), Basel(10m x 10m), and Zurich (25m x 25m).

Methods

UHI intensity was calculated as the temperature difference between urban area and rural reference point. Then, we calculated district-mean UHI intensity and identify 'High UHI area' and 'Extreme UHI area', where districts experience higher UHI intensity than city-wide average and 90th perecentile.

You can refer to the NCCS-Impacts website for detailed information on mmethods of exposure assessment and the development of heat vulnerability index.

Information

This website is designed to interactively explore the spatial distribution of vulnerable population and infrastructures to UHI effect in Swiss cities. The temperature and demographic data that appear in the website are based on the year of 2020.

The webiste provides content soley for information purposes, and does not reflect the most up-to-date on the matters addressed.

This webiste was created as part of NCCS-Impacts Programme - Health. This website is developed by Sujung Lee, and if you have any questions or feedback, please contact to: sujung.lee@unibe.ch