Modelling particle deposition onto surfaces in historic buildings

A comprehensive model of indoor particle deposition onto surfaces of historic interiors was developed. The model takes into account the most important deposition processes observed in historic buildings: Brownian and turbulent diffusion, gravitational settling, turbophoresis, and thermophoresis. The developed model is expressed as a function of important parameters characterizing historic interiors: the friction velocity - capturing the effect of the indoor airflow intensity, the difference between the temperature of the air and the surface, and surface roughness. In particular, a new form of the thermophoretic term was proposed to account for an important mechanism of surface soiling driven by frequent large temperature differences between indoor air and surfaces in historic buildings. The form adopted allowed the temperature gradients to be calculated down to low distances from the surfaces and showed insignificant dependence of the temperature gradient on the diameter of particles, which yielded a meaningful physical description of the process. The predictions of the developed model agreed with the outcome of the previous models, in turn correctly interpreting the experimental data. The model was used in simulating the total deposition velocity in a small-size church taken as an example of a historic building, heated in the cold period. The model adequately predicted the deposition processes and proved to be able to map magnitudes of deposition velocities for specific surface orientations. The crucial effect of the surface roughness on the deposition paths was documented.

Automated summary

A comprehensive model for indoor particle deposition in historic interiors was developed, considering important processes such as Brownian diffusion, turbulent diffusion, gravitational settling, turbophoresis, and thermophoresis. The model is expressed as a function of parameters characterizing historic interiors, including friction velocity, temperature difference, and surface roughness. The model successfully predicted deposition processes and deposition velocities for specific surface orientations by accounting for the effect of surface roughness.