Acoustic Agglomeration of PM2.5 Enhanced by Additional Particles

The acoustic agglomeration model of suspended PM 2.5 subjected to a standing-wave sound field is established based on the direct simulation Monte Carlo (DSMC) method. The particle motion and agglomeration are numerically investigated, and the simulated result is compared with experiment to validate the agglomeration model and the algorithm. The results show that the dynamic behaviors of sub micron particles and micron particles under the effect of sound field are very different, and that the removal efficiency of PM 2.5 by acoustic agglomeration can be greatly improved by adding large particles into the gas stream. In a typical case, the PM 2.5 removal efficiency can be increased from 21.5% to 47.4% with additional particles.