Inversely tracking indoor airborne particles to locate their release sources

Airborne particles can have numerous adverse effects on human health. Knowing the release locations of airborne particulate sources is helpful in minimizing pollutant exposure. This paper describes a proposal to locate indoor particulate sources by two inverse models: the quasi-reversibility (QR) model and the zone prescription of contaminant sources with the Lagrangian-reversibility (LR) model. The QR model reverses the time marching direction of the Eulerian governing equation and replaces the second-order diffusion term with a fourth-order stabilization term. The zone prescription LR model traces individual particulate motion in a Lagrangian reference frame after reversing the flow field. The particle trajectories are solved backward to the initial release once the conservative forces acting on particles are reversed. The tracked particles are proposed to be placed at the zone boundary of the largest concentration contour within the domain at a given time, which is provided as the initially known information. By connecting all particles at t = 0, a zone is formed that can prescribe the actual contaminant source. This study finds that both models can accurately locate particulate sources released instantaneously at a spot. The QR model performs slightly better than the LR model but is much more computationally demanding.

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► We presented two inverse models to track airborne particles and locate the sources.
► The QR model is applicable for particles if the gravitational settling is included.
► The LR model is efficient to prescribe the source with discrete particles.