Understanding the sources of atmospheric microplastics

A direct consequence of the increasing number of atmospheric micro- and nanoplastic observations is the need for designing reliable atmospheric modelling, capable of describing their emission processes and transport. At the current state of the art, one of the main uncertainties lies in the identification of source regions and their relative contributions to observed atmospheric concentrations. In this work, we aim at comparing different atmospheric concentration studies in urban, periurban and remote locations, and their associated atmospheric transport analysis. The objective is to determine whether current source knowledge is sufficient to explain the observed variability, and whether any contribution (e.g. oceans, populated areas, agricultural activities) emerges as dominant.

The analysis covers a collection of data from literature, including total mass concentrations from Thermal Desorption–Proton Transfer Reaction–Mass Spectrometry (TD-PTR-MS) and particle-counting data from µ-Raman and Fourier Transform Infrared (FTIR) spectroscopy. Backward simulations from FLEXPART v11 (Bakels et al. 2024) are used to evaluate the consistency between observed MP variability and candidate source regions. For some datasets, statistically significant correlations (up to ~80%) are found between modelled source sensitivities and observed concentrations, indicating that some source contributions are well captured, particularly in free-tropospheric regimes. However, in the cases in which a greater variety of sources was potentially involved, the analysis showed weak or absent correlations, highlighting both gaps in the current emission inventories hypothesis and limitations in the comparability of available observations.

Overall, our results indicate that no dominant single source can explain atmospheric microplastic observations across all environments. In the free troposphere, oceanic and mineral dust-related sources often emerge as main contributors, while near-surface and urban observations display more complex and site-specific signatures. These findings underscore the need for case-by-case source attribution, improved emission characterisation, and closer integration between modelling and measurement strategies to robustly constrain the atmospheric microplastic budget.