Seasonality and wind-driven atmospheric deposition predict microplastic concentrations in a Pennsylvania stream

We evaluate how meteorological and environmental variables relate to stream microplastic concentrations using regression-based models. Sixty-six duplicate water-column samples were collected over an annual cycle from a stream in southeastern Pennsylvania, USA. Microplastic particles were isolated and quantified by light microscopy, and polymer types were characterized using scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM–EDS) and Fourier transform infrared spectroscopy (FTIR). Modeling results demonstrate high variability in microplastic counts, including pronounced within-day variability (mean = 7.1 particles L⁻¹, n = 66, 1σ = 4.9 particles L⁻¹). All regression approaches evaluated (stepwise selection, LASSO, and elastic net) identify colder temperatures and stronger wind gusts as significant predictors of elevated microplastic concentrations. When scaled by riparian area, the wind-sensitive component of the stream plastic flux is consistent with physically plausible atmospheric deposition rates. These results suggest that environmental factors enhance transport of microplastics into waterways. Qualitative data from EDS and FTIR spectra indicate that polyester fibers comprise the majority of microplastic pollution in Plum Run. From this, we infer that increased laundering and shedding of synthetic clothing during winter may be a primary reason for higher pollution in winter months.