Air pollution and climate change patterns are linked to the abundance of aerosols. However, it is one property of the aerosol particles which is really important with respect to its role in the atmosphere. And that is the particle size. Aerosol particles can have many sizes, starting from small molecular clusters, which dimensions of about one nanometer (a billionth part of a meter) up to the sizes of visible dust particles and raindrops (millimeter). As you can imagine, the physics governing the motion and properties of such differently sized particles can be quite different. Therefore, we describe aerosols often with their so-called particle size-distribution, which expresses how many particles of a certain size (typically expressed by their diameter) are found in a sample. For example, if we find 100 particles smaller than 100 nm and 5 particles larger than 100 nm in 1 cubic centimeter of air, we would already know something about the abundance of large and small particles.
Typical aerosol size-distribution measuring instruments do resolve the question of how many particles of which sizes do we find in a sample on a finer grained grid. The important challenge here is that such instruments need to measure the size of a particle and then count how many of them are found in a sample. This can be especially challenging when we want to assess the size-distribution of very small particles (below 10 nanometer for example). Here both processes are challenging: Measuring the size and counting them. Therefore a variety of different instruments with different approaches exist. However, a recent paper showed that there are still huge discrepancies between these instruments when they measure the same aerosol.
We therefore investigated if it is possible to combine the information of several such instruments in order to better estimate the particle size-distribution in the sub-10 nm range. In this paper published in the Journal of Aerosol Science, we show that mathematical methods can indeed improve the quality of the measured size-distributions when several instruments and their information are combined. With that approach it is therefore possible to better understand the processes related to such small particles, for example how fast they grow and become important for the climate and air quality.