An assessment of vapour pressure estimation methods

Area of Science:

• Atmospheric Chemistry
• Chemical Engineering
• Environmental Science

Background:

• Vapor pressure is a key property influencing the formation and behavior of secondary organic aerosol (SOA).
• Accurate estimation of vapor pressure is essential for atmospheric models predicting SOA mass loading and composition.
• Existing vapor pressure estimation methods vary in accuracy and their impact on SOA predictions is not fully understood.

Purpose of the Study:

• To evaluate the accuracy of seven different vapor pressure estimation methods for atmospherically relevant compounds.
• To assess the impact of these estimation methods on the prediction of secondary organic aerosol (SOA) mass loading and composition.
• To identify the most suitable vapor pressure estimation method for SOA modeling.

Main Methods:

• Collated laboratory measurements of vapor pressures for atmospherically relevant compounds.
• Assessed accuracy of seven vapor pressure estimation methods, including Lee-Kesler, Nannoolal et al., and Myrdal and Yalkowsky.
• Utilized an absorptive partitioning equilibrium model to investigate the effect of varying vapor pressure estimation methods on SOA predictions.

Main Results:

• The Lee-Kesler method exhibited the lowest mean absolute error among applicable methods.
• The Nannoolal et al. method showed the lowest mean bias error when using Nannoolal et al. estimated normal boiling points.
• The Myrdal and Yalkowsky method, using Nannoolal et al. normal boiling points, provided the most accurate SOA loading estimation, despite not being the most accurate for vapor pressure alone.

Conclusions:

• Vapor pressure estimation method choice significantly impacts SOA loading predictions.
• The Myrdal and Yalkowsky method, coupled with Nannoolal et al. boiling points, is recommended for accurate SOA loading estimation.
• Further research may refine vapor pressure estimation techniques for improved atmospheric chemistry modeling.