Air absorption effects lead to significant attenuation in high frequencies over long distances and this is critical to model in wide-band virtual acoustic simulations. Air absorption is commonly modelled using filter banks applied to an impulse response or to individual impulse events (rays or image sources) arriving at a receiver. Such filter banks require non-trivial fitting to air absorption attenuation curves, as a function of time or distance, in the case of IIR approximations, or may suffer from overlap-add artefacts in the case of FIR approximations. In this study, a filter method is presented which avoids the aforementioned issues. The proposed approach relies on a time-varying diffusion kernel that is found in an approximate Green’s function solution to Stokes’ equation in free space. This kernel acts as a low-pass filter that is parametrised by physical constants, and can be applied to an impulse response using time-varying convolution. Numerical examples are presented demonstrating the utility of this approach for adding air absorption effects to room impulse responses simulated using geometrical acoustics or wave-based methods.

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