Semi-volatile organic compounds (SVOC) exist in indoor air at very low concentrations (usually less than 100 mu g/m(3)), but do great harm to human health. SVOC pollutants transfer in indoor air with suspended particles so complicatedly that traditional experimental methods are hardly to reveal the mass-transfer mechanism. This study employs Lattice Boltzmann method (LBM) to investigate the mass transfer behaviours of two-phase SVOC pollutants (gas- and particle-phase), and compare two widely-used gas/particle partition models (the instantaneous equilibrium model and the dynamic model). LBM is used to simulate the fluid flows and SVOC mass transfer, and the cell automation (CA) probabilistic model is applied to simulate the particle transport. The interaction between the gas- and particle-phase of SVOC is considered in the source term of the Lattice Boltzmann equations. One particle is firstly simulated in order to focus on the particle-phase concentration, then a large number of particles are simulated to focus on the effect of particles on the concentration field of SVOC. The simulation results show: (i) particles in the instantaneous equilibrium model for gas/particle partition always help gas-phase SVOC transport in indoor air by particle-mediation effect, while such an effect in the dynamic model is greatly determined by K-p and residence time of particles; (ii) particle-mediation effect can also increase the emission rate, and a non-uniform distribution of particles predicted by our numerical model indicates that such an additional emission rate increases exponentially with particle concentration, because a small number of particles have little possibility of approaching emission surface. (iii) Our numerical model can effectively estimate SVOC concentration in the presence of airborne particles by tracking each particle. These results highlight the roles of airborne particles in the transport of indoor SVOC pollutants, and are expected to be useful to consider dust deposition and resuspension when particles are in a realistic size distribution. (C) 2019 Published by Elsevier Ltd.