A Modeling Approach to Aggregated Noise Effects of Offshore Wind Farms in the Canary and North Seas

Journal Article

Title: A Modeling Approach to Aggregated Noise Effects of Offshore Wind Farms in the Canary and North Seas

Author:

Urtiaga-Chasco, I.; Hernández-Guerra, A.

Publication Date:

December 19, 2025

Journal:

Journal of Marine Science and Engineering

Volume:

Issue:

Pages:

1-16

Publisher:

MDPIRSS

Affiliation

Universidad de Las Palmas de Gran Canaria

Technology:

Wind Energy, Fixed Offshore Wind, Floating Offshore Wind

Stressor:

Noise

Receptor:

Marine Mammals

Language:

English

Document Access

Website:

External Link

Attachment:

Access File

Citation

APA
BibTex
RIS

Urtiaga-Chasco, I.; Hernández-Guerra, A. (2025). A Modeling Approach to Aggregated Noise Effects of Offshore Wind Farms in the Canary and North Seas. Journal of Marine Science and Engineering, 14(1), 1-16. https://doi.org/10.3390/jmse14010002

@article{Urtiaga-Chasco-2025-2114635,
author = {Urtiaga-Chasco, I and Hernández-Guerra, A},
title = {A Modeling Approach to Aggregated Noise Effects of Offshore Wind Farms in the Canary and North Seas},
journal = {Journal of Marine Science and Engineering},
year = {2025},
month = {dec},
publisher = {MDPIRSS},
volume = {14},
number = {1},
pages = {1--16},
doi = {10.3390/jmse14010002},
url = {https://www.mdpi.com/2077-1312/14/1/2},
keywords = {Wind Energy, Fixed Offshore Wind, Floating Offshore Wind, Noise, Marine Mammals},
}

Export Citation to BibTex

TY - JOUR
TI - A Modeling Approach to Aggregated Noise Effects of Offshore Wind Farms in the Canary and North Seas
AU - Urtiaga-Chasco, I
AU - Hernández-Guerra, A
T2 - Journal of Marine Science and Engineering
AB - Offshore wind farms (OWFs) represent an increasingly important renewable energy source, yet their environmental impacts, particularly underwater noise, require systematic study. Estimating the operational source level (SL) of a single turbine and predicting sound pressure levels (SPLs) at sensitive locations can be challenging. Here, we integrate a turbine SL prediction algorithm with open-source propagation models in a Jupyter Notebook (version 7.4.7) to streamline aggregated SPL estimation for OWFs. Species-specific audiograms and weighting functions are included to assess potential biological impacts. The 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, a single turbine’s SL reaches 143 dB re 1 µPa in the one-third octave band centered at 160 Hz. Sensitivity analyses indicate that variations in wind speed can cause the operational source level at 160 Hz to increase by up to approximately 2 dB re 1 µPa2/Hz from the nominal value used in this study, while differences in sediment type can lead to transmission loss variations ranging from 0 to on the order of 100 dB, depending on bathymetry and range. Maximum SPLs of 112 dB re 1 µPa are predicted within OWFs, decreasing to ~50 dB re 1 µPa at ~100 km. Within OWFs, Low-Frequency (LF) cetaceans and Phocid Carnivores in Water (PCW) would likely perceive the noise; National Marine Fisheries Service (NMFS) marine mammals’ auditory-injury thresholds are not exceeded, but behavioral-harassment thresholds may be crossed. Outside the farms, only LF audiograms are crossed. In high-traffic North Sea regions, OWF noise is largely masked, whereas in lower-noise areas, such as the Canary Islands, it can exceed ambient levels, highlighting the importance of site-specific assessments, accurate ambient noise monitoring and propagation modeling for ecological impact evaluation.
DA - 2025/12//
PY - 2025
PB - MDPIRSS
VL - 14
IS - 1
SP - 1
EP - 16
UR - https://www.mdpi.com/2077-1312/14/1/2
DO - 10.3390/jmse14010002
LA - English
KW - Wind Energy
KW - Fixed Offshore Wind
KW - Floating Offshore Wind
KW - Noise
KW - Marine Mammals
ER -

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Abstract

Offshore wind farms (OWFs) represent an increasingly important renewable energy source, yet their environmental impacts, particularly underwater noise, require systematic study. Estimating the operational source level (SL) of a single turbine and predicting sound pressure levels (SPLs) at sensitive locations can be challenging. Here, we integrate a turbine SL prediction algorithm with open-source propagation models in a Jupyter Notebook (version 7.4.7) to streamline aggregated SPL estimation for OWFs. Species-specific audiograms and weighting functions are included to assess potential biological impacts. The 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, a single turbine’s SL reaches 143 dB re 1 µPa in the one-third octave band centered at 160 Hz. Sensitivity analyses indicate that variations in wind speed can cause the operational source level at 160 Hz to increase by up to approximately 2 dB re 1 µPa²/Hz from the nominal value used in this study, while differences in sediment type can lead to transmission loss variations ranging from 0 to on the order of 100 dB, depending on bathymetry and range. Maximum SPLs of 112 dB re 1 µPa are predicted within OWFs, decreasing to ~50 dB re 1 µPa at ~100 km. Within OWFs, Low-Frequency (LF) cetaceans and Phocid Carnivores in Water (PCW) would likely perceive the noise; National Marine Fisheries Service (NMFS) marine mammals’ auditory-injury thresholds are not exceeded, but behavioral-harassment thresholds may be crossed. Outside the farms, only LF audiograms are crossed. In high-traffic North Sea regions, OWF noise is largely masked, whereas in lower-noise areas, such as the Canary Islands, it can exceed ambient levels, highlighting the importance of site-specific assessments, accurate ambient noise monitoring and propagation modeling for ecological impact evaluation.