The presented contributions have varying degrees of specialisation and, in a loose connection to that, their resulting
efficiency. First, the screen-space scattering algorithm simulates scattering in homogeneous media, such as fog and
water, as a fast image filtering process. Next, the amortised photon mapping method focuses on rendering clouds
as arguably one of the most difficult media due to their high scattering anisotropy. Here, interactivity is achieved
through adapting to certain conditions specific to clouds. A generalisation of this approach is principal-ordinates
propagation, which tackles a much wider class of heterogeneous media. The resulting method can handle almost
arbitrary optical properties in such media, thanks to a custom finite-element propagation scheme. Finally, spectral
ray differentials aim at an efficient reconstruction of chromatic dispersion phenomena, which occur in transparent
media such as water, glass and gemstones. This method is based on analytical ray differentiation and as such can
be incorporated to any ray-based rendering framework, increasing the efficiency of reproducing dispersion by
about an order of magnitude. All four proposed methods achieve efficiency primarily by utilizing high-level
mathematical abstractions, building on the understanding of the underlying physical principles that guide light
transport. The methods have also been designed around simple data structures, allowing high execution parallelism
and removing the need to rely on any sort of preprocessing. Thanks to these properties, the presented work is not
only suitable for interactively computing light transport in participating media, but also allows dynamic changes to
the simulated environment, all while maintaining high levels of visual realism.