Simulative prediction of ultrafine particulate matter formation by means of different pyrolysis models

Abstract

In this study, the sensitivity of two different pyrolysis models on the simulative prediction of inorganic ultrafine Particulate Matter (PM) formation is investigated. For consideration of PM formation, the volume-conserved discrete-sectional Population Balance Model (PBM) is used. The volatile release is an input parameter of the PBM and thus influences the calculated PM formation. As a representative of an empirical pyrolysis model, the Fu-Zhang model (FZM) is used. In comparison, the Chemical Percolation Devolatilization model (CPD) is taken as a representative for sophisticated pyrolysis network models. The latter takes influences of fuel composition, heating rate and particle temperature into account. The evaluation of the pyrolysis model impact is determined for a pulverized (dp=65–74μm) Chinese lignite (Zhundong) since this fuel has a relatively high volatile content and thus favors the formation of particulate matter. To investigate the influence of particle heating rate in the models, two different gas temperatures (1200 K and 1500 K, respectively 5.28·104 K s−1 and 7.51 × 104 K s−1 calculated with the energy balance) are considered. Furthermore, these conditions are selected because experimental data of the PM particle size distribution (PSD) from previous studies are available. The modeling of PSD is performed and validated with the existing experimental PSD data. These experimental data were achieved in investigations with a Hencken burner. The results of the two models (FZM and CPD) show recognizable differences in predicting the PSD. This study indicates that the CPD model improves significantly the prediction of ultrafine PM formation.