Studies have shown that washing and drying clothes contribute microfiber contamination to the environment. However, many of the previous studies on clothes drying were conducted under idealized conditions. To better understand microfiber emissions from clothes dryers during normal household use, we recruited participatory volunteer scientists to install a mesh on their dryer vents for three weeks. During that time, the volunteers used a mobile application to record the item dried (e.g., pants, shirt, etc.) and the material composition (e.g., cotton, acrylic, silk). The mesh was then returned and the accumulated material was removed, weighed, and analyzed. The results showed that the items dried were primarily comprised of cotton, followed by polyester. The textile-derived microfibers on the mesh were primarily cellulose, followed by polyethylene terephthalate/polyester and other plastics. When we compared the microfibers on the mesh to the textiles dried, we found that the relative percentage of cellulosic microfibers on the mesh was higher than the percentage of cellulosic textiles dried. This suggests that cellulosic textiles released more microfibers than synthetic textiles. On average, 138 mg of material was emitted per dryer load. When scaled to the number of electric clothes dryers in the United States and the average number of dryer loads per household per year, we estimated dryers release ~3,543.6 metric tons of microfibers per year. The results indicate that clothes dryers are potentially a significant source of cellulosic and synthetic microfibers being released into the air, and steps should be taken to reduce these emissions. The methods outlined here can be applied to other studies to assess microfiber emissions from dryers under normal household use.

Project design and participant recruitment

This study was a participatory science project, during which volunteers were asked to participate by either: 1) installing a mesh over their dryer vent to collect microfiber emissions, submitting information about their dryer habits during the three weeks the mesh was installed, and mailing the mesh back to DRI or 2) only submitting information about their dryer habits without installing the mesh to collect microfibers. We recruited volunteers through the League to Save Lake Tahoe, a nonprofit organization located in South Lake Tahoe, California. The project began in April of 2020 and ended in August of 2020.

To recruit participants, the League to Save Lake Tahoe emailed information about the project to their list of volunteers. The email directed potentially interested individuals to fill out a Google form, which asked about their dryer system, their household, and their interest in installing the mesh outside their home (see the supplementary materials). Individuals interested in installing the mesh over their dryer vent were then invited to an online video conference, during which we reviewed the research questions and goals, methodologies, and expectations of the project. This meeting was also used to confirm participant interest. Seven individuals agreed to participate by installing the mesh over their dryer vent. Individuals who did not want to participate by installing the mesh were invited to submit data on their drying habits (see section below).

Dryer vent mesh

To create the mesh that would sit over the dryer vent exhaust, we first purchased a plastic dryer vent guard (these are typically used to keep animals from entering the dryer vent). Inside the dryer vent guard, we installed a custom-fit mesh with 1 mm x 1 mm openings made from screening material (vinyl-coated fiberglass). The dryer vent guard provided the mesh stability during transport and allowed for easy installation by the volunteers. Each mesh was numbered and weighed. The mesh was then mailed with the dryer vent guard and instructions to the citizen volunteers.

Installation of the mesh and data reporting

Volunteers were asked to install the mesh and dryer vent guard by July 12, 2020, and to begin recording their clothes drying habit data once it was installed. Installation instructions were provided during the initial online video meeting, as well as through written instructions. To our knowledge, no issues arose during installation.

After installation, the volunteers were asked to record data every time they used their dryer. The data collection survey was hosted on the existing Citizen Science Tahoe (CST) smartphone application platform. Zach Lyon Creative developed the CST app in 2015 in collaboration with three regional groups: the University of California Davis Tahoe Environmental Research Center, the League to Save Lake Tahoe, and DRI. In 2020, the CST app hosted six different citizen science surveys used by CST partners, with a total network of 1,970 registered users. We have successfully used the CST app for other participatory science projects (Arienzo et al., 2021). The “DRI: Clothes Drying Habits” survey included a series of screens for the users to submit data. The first screen asked the users to enter the number on their assigned dryer mesh or to enter zero if they did not have a mesh on their dryer vent. Since the CST app is publicly available, we wanted users to enter their dryer number because potentially anyone using the app could submit to the survey. The following screens included questions about the dryer setting, the two largest items dried (e.g., pants, towel, or sheet), and the composition of the two largest items (e.g., nylon, polypropylene, etc.). The date and time of the data submission was recorded automatically by the CST app. To remind volunteers to submit data during the experiment, we followed up with emails and text messages to ensure data submission and answer any questions volunteers had. After three weeks of the mesh being installed in the dryer vent, we asked the volunteers to return the mesh to DRI using a prepaid return envelope.

Laboratory processes

Once DRI received the mesh, it was reweighed in the laboratory to calculate the weight of the accumulated microfibers (weight data are available in the manuscript text). All the material from the mesh was then collected and stored in a glass jar labeled with the number of the associated mesh. Subsamples of microfibers were taken from the collected material, and then analyzed for chemical composition using microscope-enable Fourier Transform Infrared (mFTIR) spectroscopy (Thermo Nicolet iN10 MX). The subsample was placed on a zinc selenium (ZnSe) IR transparent window (13 mm diameter by 2 mm window, Pike Technologies, Madison, WI, USA). We ensured that the particles on the ZnSe slide were not overlapping and one quarter of the slide was imaged by the instrument. We then used the particle identification tool to select the particles of interest, and the instrument collected data for each identified particle. The spectra were collected using spectral resolution of 8 cm⁻¹ (from 4000 to 715 cm⁻¹ ) and 64 scans. The Norton−Beer strong apodization function was applied by the instrument software. The particle identification tool automatically collected the background spectra using the same settings as part of the particle analysis. The particle identification tool also automatically collected length and width estimates of the analyzed microfibers. We compiled the microfiber length and width data for dryer vents 1, 2, 4, 5, and 7.

The resulting spectra were processed using Open Specy (Cowger et al., 2021). We applied an absolute derivative transformation of the first order and smoothed the data using a polynomial order 3 and a moving window of 11 data points (88 cm⁻¹). The processed spectra were then compared against the derivative corrected library in Open Specy and matched with library spectra using the built-in Pearson correlation search algorithm. A match percent ≥70% was used to identify the chemical composition. All matches ≥70% were also verified by the instrument user. Particles that had a match <70% were not considered in the analysis. This has been previously shown to be a robust data processing approach (Kozloski et al., 2024). To aid in comparison with the volunteer data, microfibers that were identified as either polyethylene terephthalate (PET) or polyester (PEST) were categorized together (PET/PEST) because for textiles, most PEST is PET (Geyer et al., 2017).