TY - JOUR
TI - Forest landscape shield models for assessing audio-visual disturbances of wind turbines
AU - Selkmaki, M
AU - Riippi, J
AU - Rana, P
AU - Lamula, L
AU - Antila, M
AU - Heinonen, T
AU - Tokola, T
T2 - Journal of Environmental Management
AB - Wind power is one of the fastest growing renewable energy sectors and plays a focal role in the transition to a fossil fuel free society in Europe. Technological developments have enabled the construction of turbines within forested areas, which has raised concerns regarding the audio-visual impact on these landscapes. However, there is a paucity of research with regard to the role that forests may play in mitigating the negative impacts of wind farms. In this study, we created a simplified model for noise attenuation based on the ISO 9613-2 and Nord2000 noise models and a visibility model which both relates the audio-visual effect to forest stand structure and applied them in the GIS environment. Our findings suggest that forests can act as effective noise barriers, with the sound attenuation level dependent on the distance that sound travels through the forest, as well as the size and density of the trees. However, in the case of a high elevation sound source (such as wind turbines), the forest begins to act as a noise shield from a distance of between 500 and 1500 m, depending on the height of the forest and the land topography. While current noise models do not consider the impact of tree species, our visibility model accounts for tree size, density and species, as well as understorey and thinning. Our results indicate that spruce trees provide a better visual constraint whereas visibility distances within mature Calluna-type pine forests tend to be more extensive. Both models include variables that can be adjusted by forest management, thereby allowing integration with forest planning software. Overall, this study presents indicative methods for the evaluation of potential forest landscape shields, a concept that could have broad applications, including Landscape Value Trading.   
DA - 2024/02//
PY - 2024
VL - 352
SP - 10
UR - https://www.sciencedirect.com/science/article/pii/S0301479724000562
DO - 10.1016/j.jenvman.2024.120070
LA - English
KW - Wind Energy
KW - Noise
ER -