Optimization of sampling conditions to minimize sampling errors of both PM_2.5 mass and its semi-volatile inorganic ion concentrations

Abstract

The accurate measurement of PM_2.5 and its inorganic matters (IMs) is crucial for compliance monitoring and understanding particle formation. However, semi-volatile IMs (SVIMs) like NH₄⁺, NO₃⁻, and Cl⁻ tend to evaporate from particles, causing sampling artifacts. The evaporation loss occurs due to many factors making the quantitative prediction difficult. This study aimed to investigate the evaporation loss of SVIMs in PM_2.5 under different sampling conditions. In the field tests, when a normal single Teflon filter (STF) sampler, which is like a Federal Reference Method (FRM) sampler, was used to sample PM_2.5 at ambient conditions, a significant SVIM evaporation loss was observed, resulting in negative biases for total IMs (−25.68 ± 3.25%) and PM_2.5 concentrations (−9.87 ± 4.27%). But if PM_2.5 was sampled by a chilled Teflon filter sampler (CTF) at 4 °C following aerosol dehumidification so that relative humidity (RH) was controlled to within the 10–20% range (RH_d), evaporation loss was minimized with a bias of < ±10% for both total IMs and PM_2.5 based on the reference data. When RH_d is below 10%, both IMs and PM_2.5 are under-measured, but only PM_2.5 is over-measured when RH_d is >20%. A model considering predictable saturation ratios for NH₄⁺, NO₃⁻, and Cl⁻ under various pressure drop, temperature and RH conditions was developed to predict accurately the actual concentrations of PM_2.5 and its SVIMs for the STF. Additionally, the ISORROPIA-II model predicted SVIMs effectively for the CTF. In summary, using the CTF at optimized sampling conditions can achieve accurate measurement of both SVIMs and PM_2.5 concentrations simultaneously.

Copyright © 2023 American Association for Aerosol Research

Graphical abstract

Editor:

• Kihong Park

Disclosure statement

The authors report there are no competing interests to declare.

Additional information

Funding

This work was supported by the Ministry of Science and Technology, Taiwan (contract MOST 111-2221-E-A49-057-MY3), the Ministry of Education, the Higher Education Sprout Project of National Yang Ming Chiao Tung University, and the Academic-Industry Research Hub of People and Earth (AIR HoPE).