Pollen characterization and identification by elastically scattered light

Development and application of a method to classify airborne pollen taxa concentration using light scattering data

Although automated pollen monitoring networks using laser optics are well-established in Japan, it is thought that these methods cannot distinguish between pollen counts when evaluating various pollen taxa. However, a method for distinguishing the pollen counts of two pollen taxa was recently developed. In this study, we applied such a method to field evaluate the data of the two main allergens in Japan, Chamaecyparis obtusa and Cryptomeria japonica. We showed that the method can distinguish between the pollen counts of these two species even when they are simultaneously present in the atmosphere. This result indicates that a method for automated and simple two pollen taxa monitoring with high spatial density can be developed using the existing pollen network.

Laboratory evaluation of the (VIS, IR) scattering matrix of complex-shaped ragweed pollen particles

Ragweed or Ambrosia artemisiifolia pollen is an important atmospheric constituent affecting the Earth's climate and public health. The literature on light scattering by pollens embedded in ambient air is however rather sparse: polarization measurements are limited to the sole depolarization ratio and pollens are beyond the reach of numerically exact light scattering models mainly due to their tens of micrometre size. Also, ragweed pollen presents a very complex shape, with a small-scale external structure exhibiting spikes that bears some resemblance with coronavirus, but also apertures and micrometre holes. In this paper, to face such a complexity, a controlled-laboratory experiment is proposed to evaluate the scattering matrix of ragweed pollen embedded in ambient air. It is based on a newly-built polarimeter, operating in the infra-red spectral range, to account for the large size of ragweed pollen. Moreover, the ragweed scattering matrix is also evaluated in the visible spectral range to reveal the spectral dependence of the ragweed scattering matrix within experimental error bars. As an output, precise spectral and polarimetric fingerprints for large size and complex-shaped ragweed pollen particles are then provided. We believe our laboratory experiment may interest the light scattering community by complementing other light scattering experiments and proposing outlooks for numerical work on large and complex-shaped particles.

Feasibility Study for a Chemical Process Particle Size Characterization System for Explosive Environments Using Low Laser Power

The industrial particle sensor market lacks simple, easy to use, low cost yet robust, safe and fast response solutions. Towards development of such a sensor, for in-line use in micro channels under continuous flow conditions, this work introduces static light scattering (SLS) determination of particle diameter using a laser with an emission power of less than 5 µW together with sensitive detectors with detection times of 1 ms. The measurements for the feasibility studies are made in an angular range between 20° and 160° in 2° increments. We focus on the range between 300 and 1000 nm, for applications in the production of paints, colors, pigments and crystallites. Due to the fast response time, reaction characteristics in microchannel designs for precipitation and crystallization processes can be studied. A novel method for particle diameter characterization is developed using the positions of maxima and minima and slope distribution. The novel algorithm to classify particle diameter is especially developed to be independent of dispersed phase concentration or concentration fluctuations like product flares or signal instability. Measurement signals are post processed and particle diameters are validated against Mie light scattering simulations. The design of a low cost instrument for industrial use is proposed.

Principles and methods for automated palynology

Pollen grains are microscopic so their identification and quantification has, for decades, depended upon human observers using light microscopes: a labour-intensive approach. Modern improvements in computing and imaging hardware and software now bring automation of pollen analyses within reach. In this paper, we provide the first review in over 15 yr of progress towards automation of the part of palynology concerned with counting and classifying pollen, bringing together literature published from a wide spectrum of sources. We consider which attempts offer the most potential for an automated palynology system for universal application across all fields of research concerned with pollen classification and counting. We discuss what is required to make the datasets of these automated systems as acceptable as those produced by human palynologists, and present suggestions for how automation will generate novel approaches to counting and classifying pollen that have hitherto been unthinkable.

Towards an integrated optical single aerosol particle lab

We present a manipulation and characterization system for single airborne particles which is integrated onto a microscope slide. Trapped particles are manipulated by means of radiation pressure and characterized by cavity enhanced Raman spectroscopy. Optical fibers are used to deliver the trapping laser light as well as to collect the Raman scattered light, allowing for a flexible usage of the device. The system features a sample chamber which is separated from an aerosol-flooded injection chamber by means of a light guiding glass-capillary. The coupling of this device with an aerosol optical tweezers setup to selectively load its trapping sites is demonstrated. Finally, a route towards chip-integrated handling and processing of multiple particles is shown and the first results are presented.