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Urban climate

The climate of many cities is heavily burdened by urban heat islands (UHI). Densely built-up areas, dark sealed surfaces and a lack of vegetation cause temperatures in the districts to rise by up to 10 °C above those in the surrounding areas in summer. Air congestion between the buildings also prevents cooling at night.

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The consequences range from an increased health burden, particularly for vulnerable groups, excessive peak energy loads and heat-related damage to infrastructure, such as road surfaces, railways and electronics. At the same time, climate change and demographic change are increasing the frequency and impact of heatwaves, making climate-adapted urban development an urgent necessity. This is currently presenting many municipalities with challenges.

However, existing measurements and conventional weather stations only provide a rough representation of these microclimatic extremes. As a result, municipalities run the risk of prioritizing resources incorrectly or allowing measures to be ineffective or even aggravating due to data that is too coarse.

Causes of urban heat islands

Sealed surfaces

Asphalt and concrete store heat and release it slowly at night.

Little green

The lack of parks and trees prevents evaporative cooling and shade.

Anthropogenic heat sources

Traffic, industry and air conditioning systems continue to drive up temperatures.

Measure locally - decide locally: Building efficient sensor networks

From From our point of view, the technically correct construction of a high-performance sensor network (e.g. LoRa) and a sensor kit to measure the local urban climate is always the first step. The next is the Strategic selection of sensor locations to avoid interferences such as direct sunlightradiation or wind shading. In addition to classic air temperature sensors, measuring devices for humidity and surface temperature are often used to obtain a comprehensive picture of the microclimate.

Live monitoring of the urban climate

As soon as the raw data is automatically transferred to an IoT platform, such as IoTnovaThe data was transferred to and validated at the University of Applied Sciences, where interactive maps are generated that illustrate temperature gradients and show hotspots at district level. Based on this data, measures such as greening projects or cooling passages can be planned efficiently and their effectiveness monitored over time.