Abstract
To understand the urban environment from a meteorological perspective in order to design better and more sustainable neighbourhoods, an open-source and low-cost meteorological device was developed and tested at the Ecole Polytechnique Fédérale de Lausanne (EPFL). The results underlined, for example, strong temperature gradients on the campus, particularly in built-up areas with a high density of artificial surfaces. Additionally, the outdoor human comfort was evaluated for multiple locations around the campus, underlying the impact of the urban surfaces as well as the city interface and the greening design. Such studies can be seen as crucial to provide information to stakeholders in the evaluation of their planning strategies either for mitigation (such as decrease of the urban heat island effect or greenhouse gas emissions) or for the adaptation (such as improvement of outdoor spaces to face future heat waves).
Highlights
Since 2010, urban areas are home to over 50% of the world population [1]
As urban areas concentrate multiple environmental issues, there is a strong need to cater for the increasing urban population by improving the air quality, the outdoor thermal comfort and the liveability of cities in general [2,3]
The final objective of the study was to create a climatic map of the Ecole Polytechnique Fédérale de Lausanne (EPFL) campus, by interposing the monitoring data performed by the students
Summary
Since 2010, urban areas are home to over 50% of the world population [1]. As urban areas concentrate multiple environmental issues (e.g. urban heat island, air pollution, runoff water, etc.), there is a strong need to cater for the increasing urban population by improving the air quality, the outdoor thermal comfort and the liveability of cities in general [2,3]. The efficient planning of future buildings and districts will only be possible if urban planners and stakeholders have the appropriate tools and information at their disposition. Models are usually used to evaluate urban planning scenarios, but they do not provide long-term analysis of the scenarios. They are computationally very expensive and are seldom used by municipalities and urban planners. There have been several previous attempts to monitor meteorological variables in cities [4,5]. These were performed within the timeframe of a particular project and not extended
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