A Build-In Data Inversion Method to Retrieve Aerosol Size Distributions for a Portable Ultrafine Particle Sizer (PUPS)

Abstract

A build-in data inversion method to retrieve aerosol size distributions based on the principle of particle electrical mobility has been introduced, whose required computational effort is low for a portable ultrafine particle sizer (PUPS). The PUPS is cost-effective for the measurements of the fine and ultrafine particles in polluted environments near-source (e.g., cities with high traffic density, freeways, airports or stationary combustion sources). The particle sizer is mainly composed of a unipolar charger, a plate differential mobility analyzer (PDMA), and a Faraday cup electrometer (FCE). The classification efficiencies of the PDMA are strongly dependent on the charging distribution of the unipolar charger, in which multiple charging is more significant than that for a bipolar charger. To reduce the excessive overlap in the kernel function caused by multiple charging, a guidance method for selecting the classification voltages and operating parameters of the PDMA is proposed with the help of MATLAB. Subsequently, a combination of the nonnegative least squares (NNLS) algorithm and post facto smoothing method has been employed to derive the discretized solution of the Fredholm integral equation of the first kind. In the end, the accuracy and stability of the proposed approach are tested under a range of particle size distribution scenarios. The synthesized data results show that for the unimodal aerosol distribution, almost all of the relative errors are less than 20 %, regardless of nonideal operating conditions. The inversion algorithm can be run on Cortex-M3, an ARM embedded chip for low-cost and low-power consumption applications. When a reasonable error range can be permitted, the inversion algorithm can meet the requirements of the PUPS.

Keywords

• Multiple charging
• excessive overlap
• classification voltages
• post facto smoothing
• synthesized data