Health and environmental impacts: how wind turbines are responsible?

Wind energy has significantly advanced over recent decades and is pivotal in transitioning to a net zero energy system. However, the rise in wind farms has increased concerns about the noise they generate and associated health impacts. It is a crucial concern that needs to be addressed from an environmental, human health and social acceptance perspective.

Within the Work Package (WP) 2 of the Horizon Europe project WIMBY (Wind In My BackYard), PSI explores the sound propagation from wind turbines and its impact on human health.

We have developed an open-source Python library that will be integrated into a Geographic Information System (GIS) interface. This interface will showcase wind turbine sound emissions, assist in pinpointing optimal locations for turbines and provide human health impacts information to Life Cycle Assessment (LCA) model, also developed in WP2 of WIMBY. Users can input turbine specifications such as power output, hub height and diameter to calculate location-specific sound emissions and propagation over the time of the day.

First, the tool simulates sound emissions from wind turbines as a function of the wind speed (fetched from climate re-analysis databases, such as Copernicus’ ERA5) and the wind turbines’ specifications (e.g., height, rotor diameter, nominal power). These emissions are expressed in A-weighted Decibels (i.e., using a set of coefficients to consider the relative loudness perceived by the human ear). This generates a sound versus wind speed curve (see Figure 1).

Maxime Balandret, Master student,
Romain Sacchi, Scientist, Paul Scherrer Institute

Figure 1 – Noise emissions of five wind turbines relative to the wind speed. Each wind turbine’s noise level was simulated given their main characteristics: blade diameter, hub height and maximum power output.

Secondly, the tool calculates sound levels at specific locations and delineates sound contours around wind turbines, which provides a clear acoustic landscape. In Figure 2, wind turbines are denoted by black points, while red points indicate noise receivers, or listening points. This visualization aims to clarify wind turbine sound emissions, potentially improving wind energy acceptance.

Maxime Balandret, Master student,
Romain Sacchi, Scientist, Paul Scherrer Institute

Figure 2 – Noise contour levels in dB(a) based on user-adjustable wind speed (m/s). Red dots are listening points (e.g., residents); black points represent noise emitters (i.e., wind turbines). The noise levels are shown with coloured surfaces on the right side of the map according to the scale.

Finally, our tool is designed to compute Lden values. Lden is a recognized noise indicator representing average sound pressure levels over a full day, accounting for the varying sensitivity to noise during day, evening, and night. By aligning with the World Health Organization (WHO) guidelines, our tool ensures accurate noise exposure assessments for wind turbine installations (WHO, 2022 update). Figure 3 shows operating wind turbines near La Chaux-de-Fonds, in Switzerland, and buildings exposed to Lden levels above the WHO-recommended level of 45 dB(a).

Figure 3 – Location of wind turbines and residence buildings exposed to noise near La Chaux-de-Fonds, Neuchâtel, Switzerland. Residence buildings not within the noise-perceptible range are not shown on the map.

The WIMBY project aims to translate research insights into real-world impacts by providing a holistic understanding of wind energy impacts and providing solutions for the affected communities. For this purpose, the tool empowers communities, policymakers, and wind energy stakeholders to make informed decisions.

Reference: WHO, 2022 update