Particle Charging and Classification: The Mass Mobility Aerosol Spectrometer (M2AS)

Abstract

Quantifying aerosols is essential for understanding their behaviour and assessing their impacts on health, the environment, and industrial applications. Accurate characterisation plays a critical role in evaluating air quality and respiratory health risks, optimising manufacturing processes, and improving climate models. Many aerosol quantification methods rely on particle charging and classification techniques, where particles are charged and classified based on their electrical mobility or mass-to-charge ratio. Diffusion charging is commonly used to impart a known charge to particles, enabling precise classification through instruments such as differential mobility analysers (DMAs) and particle mass analysers (PMAs). These methods provide detailed insights into particle size, mass, and morphology, all of which are crucial for understanding aerosol dynamics and enhancing measurement accuracy across various applications. While the effects of humidity on aerosol behaviour are well-recognised, their influence on particle charging has received limited attention, particularly in the context of charging sensors. In this work, the effect of humidity on particle charging behaviour is investigated, as it is a critical but often overlooked parameter in ambient measurement contexts. It is demonstrated that the ions produced by particle chargers are directly influenced by the presence of water vapour, which, depending on the charging technique, can significantly alter the charging process. This underscores the importance of accounting for humidity effects when interpreting data from charging-based measurement devices, ensuring more accurate and reliable results. Next, the operation of unipolar charger-classifier systems is investigated, specifically the pairing of a unipolar diffusion charger with a Centrifugal Particle Mass Analyser (CPMA). Theoretical models for multiple charge correction in these systems are first experimentally verified, enabling the determination of the average transmitted particle mass. This method proves effective for a wide range of aerosols (mass range of 0.01 fg to 100 fg) and achieves accuracy within ±20% by fitting experimental data to power law functions of mobility diameter for both effective density and average charge. This experimental study highlights a key challenge in unipolar charger-CPMA systems: the inherent uncertainty in relating aerosol mass, charge, and mobility. To address this challenge, the Mobility Separator Electrometer (MSE) is introduced—a new classifier designed to measure average charge and average particle electrical mobility when combined with a condensation particle counter (CPC). The MSE enhances the performance of unipolar charger-classifier systems. Its transfer function is validated through numerical and experimental studies. The integration of the MSE with existing classification systems, such as the CPMA and the Aerodynamic Aerosol Classifier (AAC), is also examined. The influence of particle morphology and system operating conditions on measurements is investigated, further improving classification accuracy. Experimental validation of an AAC–MSE–CPC system using compact aerosols demonstrates good agreement with bulk density measurements, showcasing the system’s accuracy. The MSE’s ability to precisely measure particle charge and mobility significantly enhances the accuracy of unipolar charger–classifier systems. However, challenges remain in accurately measuring particle mass distributions using PMAs due to uncertainties in the relationships between mass, mobility, and charge. A numerical investigation is performed into the determination of number-weighted mass distributions using a unipolar charger–PMA system. It is demonstrated that this approach requires assumptions about particle charge and mobility, which, if incorrect, can introduce errors in the measured mass distribution. Building on the enhanced classification accuracy provided by the MSE, the Mass Mobility Aerosol Spectrometer (M2AS) is introduced. This novel system improves measurement accuracy by incorporating the MSE as a particle classifier. By measuring the average charge and electrical mobility downstream of the CPMA, the M2AS system refines the calculation of the system transfer function, reducing sensitivity to variations in measurement conditions and further advancing aerosol mass characterisation. The final part of this work is the experimental validation of the M2AS system. The M2AS demonstrated good agreement of effective density measurements for DOS and ammonium sulphate, with accuracy within 8.2% for particles smaller than 1 μm, but performed worse for larger particle sizes. Distribution validation of the same aerosols showed good consistency with SMPS measurements, with discrepancies within 10% for geometric mean diameter and standard deviation. However, large overestimations (up to a factor of 2) in total concentration were observed, particularly for smaller particles. Additionally, the system’s measurements of the mass–mobility pre-factor and exponent of non-spherical soot particles were within 10% of CPMA–SMPS results. However, the mobility distribution of M2AS measurements was systematically larger and narrower than the corresponding SMPS distribution. One of the suggested reasons for this systematic disagreement was confirmed by preliminary comparisons with two-dimensional inversion of CPMA–SMPS data, which revealed skew in the effective density measurements, corroborating previously introduced numerical models. These results underscore the potential of the M2AS for precise aerosol characterisation, with further improvements needed to address the identified challenges.