Generation of microplastics from the opening and closing of disposable plastic water bottles

There has recently been a significant increase in interest regarding the prevalence of microplastics in bottled water. Previous studies have shown that the composition of many of the microplastics in bottled water is consistent with the materials of the bottle and bottle cap. The focus of this study is to quantify microplastic particle generation from the cap and bottle interaction during open and close cycles. Nile Red dye was used for the detection of microplastics >4.7 μm in size. Microplastic contamination levels in the water were found to increase as the bottle cap is opened and closed repeatedly. The rate of generation of particles with bottle opening and closing cycles (553± 202 microplastics/L/cycle) is adequate to account for the total particle density in the water. This clearly demonstrates that the abrasion between the bottle cap and bottleneck is the dominantmechanism for the generation of microplastic contamination detected in bottled water. A large spread between the maximum andminimum levels of microplastic contamination for bottles from the same lot, regardless of the number of times the cap is opened and closed, suggests that mechanical tolerances in the manufacturing of bottles and caps might play an important role in microplastic generation.


INTRODUCTION
The rapid growth in the prevalence and production of plastics demands research into the risks posed by microplastics (MPs), to understand and avoid any health concerns.
Microplastics are plastic pieces that are smaller than or equal to 5 mm in size (Bergmann et al. ). The existence of microplastics has been reported for decades, going back to the 1970s (Carpenter & Smith ). Microplastics are often detected in the environment, but a lack of standardized methodology and the variability in composition and concentration of the particles make it difficult to determine the risks posed by the microplastics' existence (Koelmans et al. ).
With the ubiquity of microplastics comes the question of pollution in drinking water and food. Concerns about microplastics in our diet from consuming fish and seafood have been raised (Davison & Asch ). Recently, many studies (including Mason et al. ; Schymanski et al. ; Zuccarello et al. ) have pushed microplastics into the spotlight, when they detected microplastic particles in bottled drinking water. In addition to drinking water, studies have found microplastic contamination in German beers (Liebezeit & Liebezeit ), honey and sugar (Liebezeit & Liebezeit ), and table salts (Karami et al. ).
The implications of microplastics on human health have been examined (Wright & Kelly ); however, the effect on humans is still unknown. There is limited data from animal studies, suggesting that the accumulation of microplastics in the body could induce an immune response, causing particle toxicity (Deng et al. ). The particles may also cause damage to the gastrointestinal system of animals (Wright & Kelly ), and small particles may transfer to tissues and penetrate organs (ESFA ). Chemical toxicity could also occur from the chemical additives and toxins in the plastic, which are used to alter the properties of the plastic polymers (Hammer et al. ). Some of these additives have been classified as hazardous to human health and the environment and can even be mutagenic and/or carcinogenic (Lithner et al. ). This makes research into the type and amount of microplastic consumed exceptionally important.
There have been various methods for separating and counting microplastics across the multiple fields microplastics research is conducted in. In studies about microplastics in sediment and other aqueous environments, density separation, filtration, and visual identification have been the most prevalent (Hidalgo-Ruz et al. ). In studies pertaining to food, particles are usually separated by filtration, and particle analysis is performed on the filter's surface. Particles can also be identified through micro-Fourier transform infrared spectroscopy (Erni-Cassola et al. ) or micro-Raman spectroscopy (Karami et al. ; Schymanski et al. ).
The quality of microplastic research has recently been discussed (Burton ). Using a microscope to visually identify microplastics is difficult for small, transparent, or fiber-like particles (Lenz et al. ). Fourier transform infrared and Raman spectroscopy do offer the precision to detect microplastics only tens of microns in size, but repeated trials and expensive equipment are often required to obtain reliable spectra (Lenz et al. ). There have been studies into automating infrared-microscopy procedures for a less labor-intensive approach, but this method is slow, costly, and has a poor spectral resolution (Maes et al. ).
Several recent studies have successfully used Nile Red (NR) dye as an accurate stain, to rapidly detect and count microplastics (Maes et al. ; Mason et al. ; Chen et al. ). NR selectively absorbs and fluoresces; both characteristics that make it an efficient technique to identify and quantify microplastics. NR's selective absorption has been tested for common organic and inorganic environmental contaminants (Maes et al. ), and NR's efficiency and reliability was further confirmed through analysis using

Sample collection and processing
Two cases of 0.5 L, single use (disposable) plastic water bottles of a major bottled water brand were purchased simultaneously in California, USA, for this study. Each case contained 24 single use polyethylene terephthalate (PET) plastic water bottles. Bottles from the two cases were used randomly in this study to ensure that case-tocase variation does not impact the results of this study. is minimized.

Imaging and excitation-emission wavelengths
The filters were inspected with a trinocular optical microscope (AmScope SM-1TNZ, 3.5-90X) fitted with a longpass (LP) filter (Omega Optical Rapidedge), and imaged with a 10M pixel integrated camera (AmScope MU1000). Six images were taken for each filter. Each 10 M pixel image has a field of view of 17 mm × 13 mm, making 1 pixel equal to 4.7 μm. Therefore, this study can detect >4.7 μm particles. There is no size upper bound limitation on particles detected by this method (though particles >1 mm were not observed in this study). Filters were placed on a manual X-Y stage mounted on the microscope base, allowing for easy and precise positioning of the filters for imaging. were tested in combination with three emission wavelengths using LP filters (Omega Optical Rapidedge LP: 560, 580, and 600 nm). The light sources were operated at 15 W power using a DC power supply (Tekpower TP3005T).

Particle counting
Fluorescent particles in all the images were counted using 'Galaxy Count' software (Faltas )

Excitation and emission wavelength selection
The top-left), whereas >600 nm emission wavelengths cut out most small particles. Based on these findings, the combination of excitation wavelengths of 520-525 nm and emission wavelengths >580 nm was used for the rest of this study.

Positive control
The effectiveness of MP detection for this study was and counts noise as particles for thresholds below 0.5 (as shown in Figure 3(b)). The reported particle counts grow rapidly when the threshold setting is reduced below the optimal value, due to the prevalence of image noise. Therefore, the optimal value for the threshold setting in the Galaxy Count software can easily be found from the 'knee' of the particle count vs. threshold setting curve. This method provides a repeatable and rigorous method for setting the threshold value and measuring the number of particles in images. The optimal value for the threshold setting was validated by the author for each image, and the total particle count for each sample is reported in (MPs/L) units.

Impact of open-close cycles on MP generation
The total particle counts for the experiments are plotted in     give the y-intercept value.
Comparing the y-intercept mean value of 358 MPs/L in Figure 5 to the average lab blank particle density of 506 MPs/L leads to the conclusion that on average experimental contamination (lab blanks) can completely account for y-intercept since the difference of y-intercept and lab blanks is À148 MPs/L. Therefore, the particles observed during all these tests (corrected for lab blanks) are likely generated during bottle cap open-close cycles.
Microplastic particle density in this study is taken to be 553 ± 202 (SE) MPs/L when the cap is opened once based on the slope of mean particle density in Figure 5.

Comparison to previous studies
As noted previously, significant variation in particle levels reported in various studies remains a concern for MP research (Koelmans et al. ). MP levels reported in this study (553 MPs/L) for particles sizes >4.7 μm are higher than those reported in previous studies. Mason et al. () reported an average of 325 MPs/L for particles >6.5 μm The procedure used in this study for detecting MPs with NR tagging is based on the method used by Mason et al.
(). Two procedural improvements in this study are also likely to explain the higher level of MPs detected in this study compared with previous studies. The first of these improvements is related to the orientation of the bottle during the NR incubation period. Figure 6 shows the most  The data in Figure 5 show that the average, maximum, and minimum particles trend up with increasing cap cycles (though at different rates). Since neither external sources of variation (e.g. contamination, measurement MPs after many open-close cycles, as observed in Figure 5.

Impact of airborne MP contamination
Concerns about airborne MP contamination in studies of after water filtration has been completed will not be detected in our study as these contaminants will not be tagged by NR dye.

CONCLUSIONS
In this study, two cases of single use bottled water from a major brand were used to study the contribution of bottle cap opening and closing on the levels of microplastic particles found in the water. NR dye was used to specifically stain microplastic particles, and tagged particles were

DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.