Can we identify the dominant sources of atmospheric microplastic?

Despite the increasing numbers of observations of atmospheric microplastic (MP), including at the poles, the marine boundary layer, clouds, high mountains snow, and the atmospheric fallout of densely populated areas, the identification of the main sources of emissions in the atmosphere remains complicated. Their emissions are still not well characterized and there are high uncertainties in the attempts of estimating their relative contributions. In this work, we apply to atmospheric microplastic observations a widespread method for source apportionment of air pollutants, based on Lagrangian modelling. We will specifically use the latest version of the state-of-the-art model, FLEXPART-v11 (Bakels et al., 2024), which incorporates the ability to simulate the transport patterns of irregular particles, such as fibers. These particles are characterized by higher drag coefficients (Tatsii et al., 2023) compared to the values typically assumed in conventional settling schemes, usually based on the assumption of spherical particles. The method will be applied to different time series of microplastic concentrations from literature, including data from Thermal Desorption - Proton Transfer Reaction - Mass Spectrometry (TD-PTR-MS) describing the total mass of MP, and data from micro-Raman and Fourier transform infrared spectroscopy (FT-IR), which instead provides information on particles counts, size, shape and composition. Among the results, the analysis suggests that ocean sources may be dominant in certain regions of the free troposphere, and that the total microplastic atmospheric emissions are not directly related to the population density, as instead often assumed.

References:

Bakels, L., Tatsii, D., Tipka, A., Thompson, R., Dütsch, M., Blaschek, M., Seibert, P., Baier, K., Bucci, S., Cassiani, M., Eckhardt, S., Zwaaftink, C. G., Henne, S., Kaufmann, P., Lechner, V., Maurer, C., Mulder, M. D., Pisso, I., Plach, A., . . . Stohl, A. (2024). Flexpart version 11: Improved accuracy, efficiency, and flexibility. Geoscientific Model Development, 17, 7595–7627.  https://doi.org/10.5194/gmd-17-7595-2024

Tatsii, D., Bucci, S., Bhowmick, T., Guettler, J., Bakels, L., Bagheri, G., & Stohl, A. (2023). Shape matters: Long-range transport of microplastic fibers in the atmosphere. Environmental Science Technology.  https://doi.org/10.1021/acs.est.3c08209