The sizing of aerosol particles is commonly carried out by electrical techniques, requiring particles to reach a known charge distribution prior to measurement. This is typically achieved by passing the particles through bipolar diffusion chargers, where the resulting steady-state particle charge distribution depends on the properties of the ions therein. We present new measurements of the charge fractions of sub-20 nm particles after bipolar diffusion charging, along with measurements characterizing the properties of ions generated within the bipolar charger. Our results show that, under steady-state conditions, the particle charge distribution is primarily determined by charger ion properties, which can be influenced even by trace gas contamination. Specifically, the use of commonly employed conductive silicone tubing, which emits trace concentrations of volatile methyl siloxanes (VMS), changes the mean positive ion mobility by 20 %, leading to deviations of up to 25 % in the fraction of singly charged particles relative to measurements without the tubing. We further show that the use of conductive silicone tubing stabilizes the mean positive ion mobility to 1.05 ± 0.1 cm² V^−1 s^−1associated with VMS. The mobility of the negative ions, on the other hand, remains highly dependent on gas composition. Building on the finding that positive ion properties can be readily stabilized to repeatable values, we show that negative ion properties can be approximated through a simple bipolar Mobility Particle Size Spectrometers (MPSS) measurement. Our measurements show good agreement with charge fractions predicted by Hoppel & Frick theory, with relative differences of up to −6.1 % and 0.6 % for positive and negative charge fractions, respectively, supporting the validity of classical charging theory for sub-20 nm particles. In contrast, significant deviations from the commonly used Wiedensohler (1988) approximation highlight the importance of accounting for environment-specific ion properties when predicting particle charge distributions.