Wind Gusts and Winter Cold Drive Microplastic Pollution in a Pennsylvania Stream, Year-Long Study Finds

Every time a gust of wind sweeps across a small stream in southeastern Pennsylvania, it may be delivering invisible cargo: microscopic plastic fibers shed from the clothes drying in homes across the watershed. That is the striking implication of a new year-long study published in Environmental Monitoring and Assessment, in which researchers from West Chester University tracked microplastic concentrations in Plum Run, a second-order Piedmont stream near West Chester, Pennsylvania, bimonthly from September 2024 to September 2025. Across 49 water column samples, the team found that colder air temperatures and stronger maximum wind gusts were the most robust predictors of microplastic abundance, while precipitation and stream discharge, the variables most often blamed for flushing plastics into rivers, played no significant role at all.

The numbers behind the finding are remarkable. Microplastic concentrations in Plum Run ranged from 1.2 to 23.0 particles per liter, averaging 7.6 particles per liter with a standard deviation of 4.9, meaning the stream’s plastic burden swung wildly from one sampling trip to the next. When the researchers split the year into warm and cool seasons, the pattern was unmistakable: mean concentrations were approximately 4.7 particles per liter between May and September, but 10.6 particles per liter from November through March, roughly a twofold difference. A statistical comparison using Welch’s unequal-variances t test confirmed that winter concentrations were significantly higher than summer values, with a difference of 6.8 particles per liter and a 95 percent confidence interval of 3.1 to 10.5.

What makes this study unusual is not just the seasonal signal but the statistical machinery used to detect it. Rather than relying on a single regression approach, the team built three separate multiple linear regression models: a stepwise selection model guided by the Akaike information criterion, a LASSO regression that shrinks weak predictors to zero, and an elastic net model that balances variable selection with the retention of correlated predictors. All three approaches converged on the same answer. Higher wind gusts were positively associated with microplastic counts, with a coefficient of 0.14 and a p-value of 0.037, while higher temperatures were negatively associated, with a coefficient of -0.34 and a p-value below 0.0002. The stepwise model alone explained roughly 60 percent of the variation in concentrations, with an adjusted R-squared of 0.60.

To guard against overfitting in a dataset of only 49 samples, the researchers subjected their models to repeated tenfold cross-validation, repeating the process 100 times so that every subset of the data served as both training and validation material. The results were strikingly consistent. The stepwise model achieved a cross-validated R-squared of 0.75 with a root mean squared error of 3.1 particles per liter, while the LASSO and elastic net models both reached cross-validated R-squared values of 0.79 with root mean squared errors of 2.9 particles per liter. Taken together, the models explained approximately 80 percent of the variability in microplastic concentrations, an unusually high figure for environmental field data and a strong indication that temperature and wind gusts are the dominant environmental controls on plastic abundance in this stream.

The physical story the researchers propose is one of wind-driven atmospheric delivery. Fibrous microplastics, which made up 96 percent of the particles identified in Plum Run, have high aspect ratios and low effective settling velocities, allowing them to remain suspended in air far longer than fragments or films of equivalent mass. Laboratory and field studies have shown that small fibrous particles are more readily entrained into the atmosphere as wind speeds increase, and short-lived gusts may exceed the threshold velocities needed to lift fibers that stay put under average conditions. Once aloft, these particles can travel considerable distances before turbulence subsides and they settle back to Earth, potentially landing directly on the stream surface or on the riparian corridor beside it. The mean aspect ratio of fibers measured in this study was 14, squarely within the range that model simulations identify as having enhanced atmospheric transport potential.

Two mechanisms may explain why cold weather amplifies the effect. First, vegetation acts as a seasonal filter: deciduous trees trap airborne particulates on their leaves, and the epidermal waxes that enable this trapping peak during spring and summer before declining sharply in autumn and winter. Forested zones in metropolitan areas are estimated to capture roughly 2.2 billion airborne microplastic particles per year, so when leaves fall, the pathway from air to stream becomes far less obstructed. Second, and perhaps more provocatively, cold weather changes human behavior. People wear heavier, more densely woven synthetic garments in winter, wash them more often, and run their tumble dryers more frequently, and mechanical agitation of synthetic textiles in dryers is a known source of airborne microfibers. A single dryer cycle can release more than 500,000 synthetic microfibers into the environment.

The polymer chemistry points in the same direction. Using scanning electron microscopy with energy-dispersive X-ray spectroscopy, the team screened 75 individual particles and found that 93.3 percent were polyester, with the remainder identified as polyvinyl chloride and polyolefins. Because EDS cannot definitively distinguish among carbon-rich polymers, the researchers confirmed a subset of 30 particles with Fourier transform infrared spectroscopy coupled to a diamond attenuated total reflection crystal. Every fiber that had shown oxygen peaks in its EDS spectrum, 28 particles in all, was confirmed as polyester by FTIR, while the two remaining carbon-dominated particles proved to be polypropylene. Polyester fibers are the signature morphotype of synthetic textiles, and with residential land use covering roughly half of the Plum Run watershed, the authors argue that laundering and drying of synthetic clothing is the most plausible dominant source.

To test whether wind-driven delivery is physically plausible rather than merely statistically suggestive, the team regressed wind gust data against daily plastic flux in the stream, obtaining a relationship with an R-squared of 0.42. The wind-sensitive component predicted by this regression averaged 1.28 times ten to the seventh particles per day, closely matching the mean observed stream flux of 1.38 times ten to the seventh particles per day. Scaling this wind-associated export over a 50-meter riparian buffer along the stream’s 19.3-kilometer length, and assuming a conservative one percent same-day delivery ratio, yields an implied atmospheric deposition rate of 663 particles per square meter per day. A sensitivity analysis spanning riparian widths of 10 to 150 meters and delivery ratios of 1 to 10 percent produced deposition rates from 22 to 3,161 particles per square meter per day, all of which fall within the range of atmospheric microplastic deposition previously measured in urban, suburban, and rural settings worldwide.

The authors are careful to frame these results as an indirect inference rather than a proven mechanism. The wind connection rests on statistical association, not on direct measurements of atmospheric deposition, and polymer identification by FTIR was limited to particles larger than 250 micrometers, leaving the smallest fibers characterized only by EDS screening. Still, the study carries a pointed message for anyone who assumes that rain and runoff are the whole story of riverine plastic pollution. In temperate, non-monsoonal catchments like Plum Run, the atmosphere itself may be a major conveyor of microplastics, and the rhythm of pollution may follow the calendar of human comfort: when the wind picks up and the temperature drops, the fibers of our winter wardrobes may be riding the gusts straight into the water.

Subject of Research: Environmental and meteorological controls on microplastic concentrations in a freshwater stream

Article Title: Seasonality and maximum wind gusts correlate with microplastic concentrations in a freshwater stream system

Article References: Mattie, C., Ashman, I., Fork, M., & Arnold, T. E. (2026). Seasonality and maximum wind gusts correlate with microplastic concentrations in a freshwater stream system. Environmental Monitoring and Assessment, 198(11), Article 1173. https://doi.org/10.1007/s10661-026-15985-9

Image Credits: AI Generated

DOI: 10.1007/s10661-026-15985-9

Keywords: microplastics, freshwater streams, atmospheric deposition, wind gusts, polyester fibers, synthetic textiles, seasonality, regression modeling, FTIR spectroscopy, SEM-EDS, urban watershed, Pennsylvania