Background Sound Variability Distance from source Noise level, dB critical region Source Sound Variability Potentially critical assessment region

Further considerations Potential causes of variation in measured background noise levels: Rain, both at the time of measurement and for the period afterwards Wind direction, are there any systematic trends in the level of background noise with wind direction ? The time of day, some locations are influenced by temporal variations You can’t reduce variability in environmental noise, but understanding the cause of the variations is key to a successful noise assessment

Dominant flow noise in streams

Noise variation with distant roads Across & downwind of motorway Upwind of motorway

Relevant assessment conditions Scenario 1 – Receiver down wind of both busy road and wind turbines

Relevant assessment conditions Scenario 2 – Receiver down wind of turbines but upwind of busy road

Choice of polynomial – linear A linear regression may be appropriate for a receptor where the dominant noise is generally independent of wind speed, such as a busy road or stream

Choice of polynomial – 2 nd 3 rd and 4 th order The choice of order for a polynomial best fit line between 2 nd, 3 rd and 4 th will often result in a small change in the typical noise level at the critical wind speeds, often between 6 ms -1 and 8 ms -1 Typically a polynomial fit provides the most appropriate trend for the expression of background noise at locations where this data is clearly influenced by wind speed

‘typical’ noise levels should be used to inform noise limits baseline noise data is inherently variable due to a broad range of factors essential that site specific variability is taken into account best practice is not a singular, prescriptive strategy must be prepared to accommodate practical considerations may involve the use of a wide range of measurement strategies understand the inherent variability in baseline noise data to ensure typical conditions are represented Summary

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