Forest landscape shield models for assessing audio-visual disturbances of wind turbines.

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.

Effect of increased wood harvesting and utilization on required greenhouse gas displacement factors of wood-based products and fuels.

A displacement factor (DF) may be used to describe the efficiency of using wood-based products or fuels instead of fossil-based ones to reduce net greenhouse gas (GHG) emissions. However, the DFs of individual products and their production volumes could not be used alone to evaluate the climate impacts of forest utilization. For this reason, in this study we have developed a methodology to assess a required displacement factor (RDF) for all wood products and bioenergy manufactured and harvested in a certain country in order to achieve zero CO2 equivalent emissions from increased forest utilization over time in comparison with a selected baseline harvesting scenario. Input data for calculations were produced with the simulation model, Monsu, capable of predicting the carbon stocks of forests and wood-based products. We tested the calculations in Finnish conditions in a 100-year time horizon and estimated the current average DF of manufactured wood-based products and fuels in Finland for the interpretation of RDF results. The results showed that if domestic wood harvesting will be increased by 17-33% compared to the basic scenario, the RDF will be 2.0 to 2.4 tC tC-1 for increased wood use in 2017-2116. However, the estimated average DF of manufactured wood-based products and fuels currently in Finland was less than 1.1 tC tC-1. The results indicate strongly that the increased harvesting intensity from the current situation would represent a challenge for the Finnish forest-based bioeconomy from the viewpoint of climate change mitigation. For this reason, there is an immediate need to improve reliability and applicability of the RDF approach by repeating corresponding calculations in different circumstances and by improving estimations of DFs on country levels.