Aerosols are found in almost all indoor or outdoor environments, and have significant impacts on climate, environment and human health. These implications and prevalence have driven rapid growth in aerosol research and led to a variety of particle instruments being developed over the past seven decades. The Aerodynamic Aerosol Classifier (AAC) is a relatively new instrument, which selects aerosol particles based on their relaxation times or aerodynamic diameters. This dissertation demonstrates that the novel operating principle of the AAC has the potential to address a variety of challenges facing the field of aerosol science.

To explore the potential, this work advances the development and knowledge of the AAC, resulting in novel methodologies for measuring the aerodynamic size and bipolar charge distributions of an aerosol. First, the performance of the AAC is determined by characterising its transfer function experimentally using tandem AACs. These results demonstrate that the transmission efficiency of the AAC is 2.6 to 5.1 times higher (which corresponds to higher measurement signals) than that of a neutraliser-Differential Mobility Analyser (DMA), a system that is widely-used in aerosol research. However, the AAC transfer function is 1.3 to 1.9 times broader than predicted by theory.

Using this characterised transfer function, the deconvolution theory to accurately measure the aerodynamic size distribution of an aerosol by stepping the AAC setpoint whilst in series with a particle detector is developed and validated experimentally against commercial instruments. While this approach overcomes the low classification resolutions and set measurement ranges (which focus on larger particles) of previous methodologies for aerodynamic sizing, it requires the AAC setpoint to be stepped and stabilised before each measurement, which forces trade-offs between measurement time and step resolution. To overcome this limitation, this thesis is the first to develop and validate the transfer function and its corresponding deconvolution theory to allow the AAC setpoint to be scanned continuously, rather than stepped, during size distribution measurements. This approach is validated experimentally against the stepping AAC (agreement within 2% if aerosol source stability is considered) and calibration particles (agreement within 8.7%). Scanning the AAC is also shown to reduce its measurement time (1.1 to 2.6 times faster), while increasing the resolution of the measured size distribution (6.1 to 9.0 times higher classes per decade).

This work is also the first to leverage the advantages of the AAC to develop improved methodologies for measuring the bipolar charge distribution of spherical particles. It is demonstrated that using an AAC in tandem with a DMA overcomes significant limitations of the commonly used tandem DMA system (such as multiply-charged particle artefacts and low measurement signals). This approach is used to quantify the significant charging effects (up to a 0.084 difference in a charge fraction) of different sample flow rates through a radioactive neutraliser, free-ions downstream of the neutraliser, or different neutralisers. To study non-spherical particles, this approach is then expanded by demonstrating an AAC and DMA in tandem can select homogeneous, non-spherical particles. The bipolar charge distribution of the homogeneous particles is then measured using another DMA downstream. The bipolar charging of non-spherical, soot aggregates is shown to deviate significantly (up to a 0.069 difference in a charge fraction) from widely-used charging theory, but can be accounted for using a charging equivalent diameter.

The novel AAC methodologies developed and validated in this thesis are intended to allow others to further characterise the sizing and bipolar charging of aerosols. There are also opportunities to expand the AAC to other applications based on the foundational theory developed in this work. Ultimately, these outcomes will lead to a greater understanding of aerosol science.