Experimental Study of Pollutant Emissions from Biomass Combustion and Modeling of PM Transportation

Experimental measurements and modeling have been performed in the chimney of a biomass boiler to study the gaseous and particulate matter (PM) emissions during the combustion of wood pellets. A 10 kW boiler with an underfeed burner is equipped with different sensors located in the chimney (anemometer, thermocouples). The PM emissions were measured in the chimney through the engine exhaust particle sizer (EEPS) technique. Moreover, the gaseous emissions (CO2, CO, total hydrocarbons THC, O2) were obtained through infrared (IR) spectroscopy and flame ionization detector (FID). The emissions were recorded during the steady phase of the boiler and averaged over several tests. Four locations were investigated in the chimney to evaluate the evolution of the particle size and the potential deposition on the surface. The experimental results were compared with a CFD model with particle transportation. The modeling of turbulent flow in the chimney is based on a Reynolds-averaged Navier–Stokes (RANS) approach with turbulent viscosity closure. To account for flow anisotropy, the v2¯−f turbulence model was selected for this study. The effect of turbulent fluctuations on the discrete phase is considered by the discrete random walk (DRW) turbulent dispersion model. The results obtained provide access to the topology of the carrier phase flow as well as the complete distribution of the particle field within the chimney enclosure. Advanced measurement of pollutant emissions and modeling of the PM transportation are developed for the first time in a domestic biomass boiler operating in real conditions. Experimental results demonstrate several relevant information. The CO and THC emissions show a similar evolution versus time. The PM granulometric distribution measured along the chimney highlights the particle agglomeration phenomena. Moreover, the CFD model and experimental results give similar results in terms of flow characteristics and PM granulometry.