A Modeling Approach to the Cumulative Noise Effects of Off-Shore Wind Farms in the Canary and North Seas

Offshore wind farms (OWFs) represent an increasingly important and strategically growing renewable energy source. However, their environmental impacts, particularly noise emissions, require further systematic study. Estimating the operational source level (SL) of a single turbine is challenging, and implementing open-source propagation models to predict sound pressure levels (SPL) at vulnerable locations can be tedious. In this study, we integrate a state-of-the-art turbine operational SL prediction algorithm with open-source propagation models in a Jupyter Notebook to streamline cumulative SPL estimation for OWFs. We also incorporate species-specific audiograms and weighting functions to assess the potential biological impacts of received noise levels. The developed tool is applied to four planned OWFs, two in the Canary region and two in the Belgian and German North Seas, under conservative assumptions. Results indicate that at 10 m/s wind speed single turbine’s operational SL reaches 143 dB re 1 µPa in the one-third octave band centered at 160 Hz. Propagation varies notably with bathymetric and seabed character-istics, with maximum SPLs of 112 dB re 1 µPa at 160 Hz within OWFs (exceeding heavy marine traffic noise levels from generic ambient-noise curves), decreasing in some cases to 50 dB re 1 µPa at ~100 km. Weighted SPL against audiograms analyses show that within OWFs, Phocid Carnivores in Water (PCW) and Low-Frequency (LF) cetacean hearing groups are likely to be affected, while outside the farms, only LF groups are impacted.