Noise annoyance mapping for wind turbines: a psychoacoustic approach incorporating noise sensitivity

• Psychoacoustic indicators used to predict wind turbine noise annoyance. • Loudness identified as the strongest predictor of annoyance. • Individual noise sensitivity significantly influences annoyance responses. • GIS-based mapping visualises spatial variation in annoyance probability. • Results support sensitivity-informed noise management for wind farms. Wind energy is a clean and renewable resource; however, wind turbine noise (WTN) poses challenges for communities residing near wind farms, with annoyance emerging as a significant concern. This study investigates WTN-induced annoyance through a psychoacoustic approach, with a particular focus on Loudness and individual noise sensitivity. Noise data were collected from 14 locations in proximity to wind farms in County Wexford, Ireland. These audio samples were subsequently used in a controlled laboratory listening experiment involving 46 participants to assess annoyance responses and calculate annoyance probabilities. A generalised linear mixed-effects model was developed incorporating key psychoacoustic indicators, including Loudness, Fluctuation Strength, and Roughness, alongside noise sensitivity scores. A validated relationship between L Aeq,24h and Loudness enabled spatial prediction of perceptual responses. ArcGIS was employed to generate spatial maps of Loudness and predicted annoyance probabilities using Kriging interpolation. The results demonstrate that Loudness is the strongest predictor of annoyance, with responses varying significantly according to individual noise sensitivity. Low-sensitivity individuals exhibited minimal annoyance beyond 500 m, whereas highly sensitive individuals exhibited annoyance probabilities of approximately 0.7 near the 500-metre setback distance. By integrating psychoacoustic modelling with sensitivity-based mapping, this study offers a more inclusive and evidence-based framework for environmental noise management, contributing to the sustainable development of wind energy.