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.