Community Research and Development Information Service - CORDIS


"As the result of an extensive measurement and analysis exercise, an empirical model has been proposed for calculating noise levels at large distances from elevated noise sources. The work is innovative in that it encompassed a complete experimental study of outdoor noise propagation in relation to wind farms, the results of which have fed into the development of an optimum code for the prediction of wind farm noise radiation.

Most importantly, the work provides a unique, highly empirical approach to solving the propagation problem, being led by observations and measured data rather than starting from a theoretical standpoint. This approach is at odds with models currently available for predicting environmental noise radiation from wind farms which tend to be of a theoretical origin with little or no formal validation against noise levels actually measured around wind farms. Experience has shown that these existing models are inadequate in that only low levels of confidence can be placed on the results obtained from them. This is most often due to their high sensitivity to changes in meteorological parameters.

The output of the model resulting from the present work has been shown from the controlled measurements to be accurate to within 2dB(A) for conditions of strong downwind propagation, with the results being validated for an 8ms-1 component of wind speed blowing from the source to the receiver.

The results of the measurement and analysis exercise have allowed confidence limits to be placed on the calculated long term averaged noise level under varying wind conditions. These confidence limits are based on the typical variation of the measured noise level around the calculated level. This variation is shown to be dependent primarily on the wind speed component blowing from the source to the receiver, with the confidence level increasing for increasing component of vector wind speed blowing from the source to the receiver.

The derived noise calcula

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