American Association for Aerosol Research - Abstract Submission

AAAR 33rd Annual Conference
October 20 - October 24, 2014
Rosen Shingle Creek
Orlando, Florida, USA

Abstract View


Evaporation Loss of PM2.5 during Filter Sampling

CHUEN-JINN TSAI, Chun-Nan Liu, Sih-Fan Lin, Guo-Rui Lee, National Chiao Tung University

     Abstract Number: 80
     Working Group: Aerosol Physics

Abstract
The evaporation loss of PM2.5 in a filter-based sampler was evaluated experimentally by a home-made multi-filter PM10-PM2.5 sampler. Results show that the evaporation loss is severe during sampling process, accounting for 5.8 to 36.0% of the corrected PM2.5 concentration and the percentage increased with decreasing loaded particle mass and increasing filtration velocity. In the present study, this issue was evaluated theoretically. The model of Cheng and Tsai (1997) which can only be used to calculate the evaporation loss of monodisperse NH4NO3 particles was modified allowing for calculating the evaporation loss of PM2.5 particles. In this modified model, the evaporation losses of particles in different particle size ranges below 2.5 µm sampled by the 4th to the after filter stages of the MOUDI were calculated separately and then integrated to obtain the total PM2.5 evaporation loss. Results show that when the collected particles are nearly neutral with a pH equals to 7 to 8, the evaporated concentrations predicted by the present model agree well with the experimental data with an average difference of < 10%. However, for acid aerosols with a pH less than 3.5, the predicted evaporation loss is less than experimental data. This is because in the acid condition, nitrate and chloride particles can also be lost due to chemical interactions between collected particles and strong acids which is not calculated. The theoretical model was used to examine the effect of PM2.5 concentration, ambient temperature and relative humidity on the extent of evaporation loss. Results show that evaporated PM2.5 concentration increases with an increasing temperature and with a decreasing relative humidity and PM2.5 concentration.