Optical trapping and light scattering in atmospheric aerosol science

Aerosol particles are ubiquitous in the atmosphere, and currently contribute a large uncertainty to climate models. Part of the endeavour to reduce this uncertainty takes the form of improving our understanding of aerosol at the microphysical level, thus enabling chemical and physical processes to be more accurately represented in larger scale models. In addition to modeling efforts, there is a need to develop new instruments and methodologies to interrogate the physicochemical properties of aerosol. This perspective presents the development, theory, and application of optical trapping, a powerful tool for single particle investigations of aerosol. After providing an overview of the role of aerosol in Earth's atmosphere and the microphysics of these particles, we present a brief history of optical trapping and a more detailed look at its application to aerosol particles. We also compare optical trapping to other single particle techniques. Understanding the interaction of light with single particles is essential for interpreting experimental measurements. In the final part of this perspective, we provide the relevant formalism for understanding both elastic and inelastic light scattering for single particles. The developments discussed here go beyond Mie theory and include both how particle and beam shape affect spectra. Throughout the entirety of this work, we highlight numerous references and examples, mostly from the last decade, of the application of optical trapping to systems that are relevant to the atmospheric aerosol.

Calculating and fitting morphology-dependent resonances of a spherical particle with a concentric spherical shell

Determining the size and composition of core-shell particles using morphology-dependent resonances (MDRs) is a computationally intensive problem due to the large parameter space that needs to be searched during the fitting process. Very often, it is not even practical to consider a reasonable range of physical parameters due to time constraints, leading to restrictive assumptions concerning the system being studied. The lengthy computational time is so limiting that there has, to date, to the best of our knowledge, been no comprehensive study of fitting measured MDRs for core-shell particles. In this work, we address the issue of fitting speed by developing an algorithm that (i) reduces the multi-dimensional grid search to a one-dimensional search using a least squares method and (ii) implements a new method for calculating MDRs that is much faster than previous methods. With the program presented here, we analyze the best-fits for core-shell MDRs across a large range of physically relevant scenarios using noise levels typical for conventional spectroscopic experiments. For many cases, it has been found that excellent fits can be quickly determined. However, there are also some surprising situations where accurate best-fits are not possible (e.g., if only one mode order is present in the measured MDR set).