Prediction of organic aerosol precursor emission from the pyrolysis of thermally thick wood

Technical Note: Pyrolysis principles explain time-resolved organic aerosol release from biomass burning

“…When heat transfer controls pyrolysis and burning, the difference in the mass loss rate of the wood can be explained using the thermal diffusivity of the wood (Spearpoint and Quintiere, 2001). As demonstrated in this work and modeled (Fawaz et al, 2020), the mass loss rate change as a function of wood type and heat flux can be explained by the heat transfer in the wood. Section S4.2 shows that the mass loss rate of birch and pineR can be predicted by the same global kinetics using Gpyro (Lautenberger and Fernandez-Pello, 2009).…”

“…Figure 1 is a schematic of the experiment. The pyrolysis reactor was described in detail in previous work (Fawaz et al, 2020) and is briefly reviewed here. The reactor was made of a 2.6 kW cylindrical heater controlled by a PID temperature controller.…”

“…Using a pyrolysis model verified experimentally, Fawaz et al (2020) showed that the real-time mass loss rate from thermally thick wood could be predicted, and that internal and external heat transfer govern the thermochemical degradation that produces the gases and PyOM precursors. That work, and other pyrolysis literature of thermally thick wood (Di Blasi et al, 2000;Ding et al, 2018a), show that the two distinct peaks of mass loss rate that appear in Fig 2a-c can be explained by the reactor temperature and thermal diffusivity of a given wood type at a fixed size.…”

Supplementary material to "Technical Note: Pyrolysis principles explain time-resolved organic aerosol release from biomass burning"

“…The EEPS measures number distributions based on the electrical mobility diameter and the AMS measures mass distributions based on the vacuum aerodynamic diameter. The AMS data were converted to number distributions versus mobility diameter using the material density (ρ = 1.72 g/cm 3 for ammonium nitrate) and the Jayne shape factor Jayne et al (2000). The comparison shows that the EEPS accurately sizes particles below 100 nm.…”

“…This problem of the missing size distribution is not encountered at 500 and 600 • C reactor temperature experiments. Using the modeling approach of Fawaz et al (2020), we predict the mass loss rate of the pyrolysis of birch and pineR at 400, 500, and 600…”