A study claims that atmospheric microplastic emissions may be overestimated

The article presents a critical reassessment of global microplastic emissions to the atmosphere. The authors use a Lagrangian particle dispersion model driven by previously published emission inventories, including both theoretical bottom-up approaches and earlier top-down estimates based on regional data from the United States. These simulations are compared against an extensive dataset of more than 2,000 real-world observations.

The main conclusion is that earlier estimates dramatically overestimated atmospheric microplastic emissions by two to four orders of magnitude—that is, they predicted between 100 and 10,000 times more plastic than is actually present. The study also challenges the notion that the ocean is a major source of plastic particles to the atmosphere. Instead, the results indicate that oceanic emissions are negligible compared with terrestrial sources, and that the ocean effectively acts as a sink for plastic originating on land.

The issue with inventory-based theoretical estimates lies not so much in their conceptual framework as in the highly inflated input values, which stem from large uncertainties in emission factors. Although the study does not introduce new measurements, its strength lies in confronting theory with global observational evidence, demonstrating that scientific estimates—even those that receive significant media attention—can be subject to massive errors and should therefore be interpreted with caution.

This is an article focused on atmospheric microplastic emissions. The topic is highly topical, and the study is commendable for the volume of information analysed and the global scope of its assessment. The article considers measurements taken from various studies over a decade, which are then compared with simulated values. The results reveal a marked contrast between land and sea surfaces, as well as between measured and simulated values, with the latter being noticeably higher.

However, certain limitations indicate that, despite its interest and relevance, this study should be interpreted with caution. For example, the measured data correspond to studies conducted over a period during which emissions may have changed. Some assumptions are made regarding plastic content when treating emissions. Certain results are presented with scaled emissions to facilitate agreement with the measured values. Global values are calculated, but measured values are only available from isolated and unevenly distributed locations, leaving large areas without data. Among the statistics used is the correlation coefficient, which is highly sensitive to outliers and can indicate apparently satisfactory linear relationships even when measured and calculated data differ by orders of magnitude, as is the case here. This suggests that this indicator should be replaced by one that overcomes these limitations. Some mean values notably exceed the third quartile in certain box plots, indicating particularly high values. Figure 3 in the supplementary material is striking because the ranges of measured and simulated values are similar, but the axis scales differ, which may give a misleading impression. A similar issue arises with the colours in supplementary figures 6–14, where the range used masks very different values that are nonetheless represented in the same colour, with only extreme values being distinguishable.

In short, this is an analysis framed within a promising line of research, with numerous aspects yet to be explored in both measurement and modelling applications.