Estimating gas-particle partitioning in mixed emissions of plastic and biomass burning thermal degradation products
Abstract
Wildfires at the wildland–urban interface (WUI) generate highly complex and poorly characterized mixtures of gas-phase and condensed-phase pollutants. As the frequency and severity of WUI events increase, evaluating gas–particle partitioning and mixing behavior of these emissions becomes essential for predicting their environmental impact. Experimental characterization of WUI aerosol emissions is particularly challenging due to the diversity of materials and variability in combustion conditions. Thus, practical methods for estimating chemical composition and gas–particle partitioning behavior of mixed-source emissions, with the potential to guide burning experiments with different fuel combinations, are valuable for assessing their atmospheric implications. Here, emission profiles resulting from the thermal degradation of selected plastic reference materials: polyethylene (PE), polypropylene (PP), polystyrene (PS), and polyvinyl chloride (PVC), are investigated using temperature-programmed desorption coupled with direct analysis in real time ionization source and high-resolution mass spectrometry. Combined with established parameterization methods, these measurements enable the construction of VBS distributions for the thermal decomposition products of individual plastics. Plastic-specific VBS distributions are then numerically combined with previously reported biomass burning aerosol properties to evaluate gas-particle partitioning and aerosol-phase viscosity in mixed emissions. Calculations indicate that emissions from PE and PP burning have greater potential to lower volatility and increase particle-phase viscosity in mixed WUI plumes compared to PS and PVC. These emissions may lead to an estimated 20% increase in particle-phase organic mass and induce viscosity changes.
Fields of Study & Subjects
Atmospheric chemistry and aerosols
Toxic Organic Pollutants Impact
Advanced Combustion Engine Technologies
Publication details
- Journal / source
- Figshare
- Publication date
- 13 January 2026