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Abstract

One of the growing concerns in pollution research is microfiber pollution (≤5 µm). Current research works aim to understand the difference between different household laundry practices and their impact on sheddability. The researcher through an online survey tried to extract consumer knowledge followed by contaminants analysis from the laundry effluent samples collected from 30 households. Three effluent laundry samples were collected and analyzed from each household for a 1-month laundry behavior analysis. Each household sample was properly coded from H1 to H30. The results stated that H26 has the highest sheddability index with 6.70% of the total emission followed by H17 (6.30%). SEM analysis conveyed the presence of nanofibers (≤1 µm), along with an abundance of microfibers (49.16%) of the total fibers released. An average of 5,849,943 MFs/L were released from the 30 households during all three wash trails. FTIR analysis also emphasized the presence of a wide range of fiber contents from cotton, polyester, elastane, and acrylic, to viscose. An attempt to study the optimized laundry variables such as reduced water temperature and wash cycle time showed no significant difference in the overall sheddability, whereas the same conditions were proven effective in reducing the microfiber shedding. The results show conclude that each household has different laundry needs and thus there is a need for a more critical understanding.

Keywords

Consumer Behavior Domestic Laundry Households Microfibers Shedding Textiles

Introduction

Laundry is an integral part of the daily routine. Although several technical and technological advancements have taken place still the total time consumers spend on laundry activities remains the same. According to a study conducted on the “Changing Laundry Practices and Water Conservation” of the Norwegian population, an average family washes up to 300 loads of laundry in a year, consuming up to 155 l of water per wash load. Apart from the energy and water consumption,¹ several researchers are reporting laundry as a one of the potential source of pollution specifically, microfiber pollution.

Microfiber pollution (≤5 µm) is one of the prevalent issues in both aquatic² and terrestrial ecosystems.^3–5 Microfiber pollution is mostly associated with synthetic fibers as they are non-biodegradable.⁶ As plastics and plastic recycling have high demand in modern life, these materials are used in several agro, industrial, food, and textile applications. The intensity of the pollution has increased in recent years with microfibers and microplastics being found in deep sea ocean gyres,⁷ aquatic animals and fishes that are used for human consumption,⁸ and even in the air we breathe.⁹

Previous studies mostly focused on microfiber (MF) release predominantly utilizing controlled conditions, often using similar types of fabrics and standardized laundry routines. However, such controlled settings do not accurately reflect the diversity of laundry practices in real households. This study addresses this gap by analyzing MF release under actual domestic conditions, where laundry routines vary significantly from person to person. Still, the results obtained cannot be standardized in household laundry conditions as every household has its own way of working with laundry. Some of the variables that can affect sheddability during domestic laundry are laundry temperature,² load type,¹⁰ type and quantity of the detergent/fabric softeners,¹¹ and water volume.¹²

The majority of the previous studies were focused on the sheddability of a particular type of garment, laboratory-induced wash conditions, the age of the garment, and the levels of emission. The main objective of the present study is to precisely study the consumer’s knowledge, laundry practices at the domestic level, and microfiber emission levels from 30 selected households in India. Each country has different environmental conditions and practices they follow, and differences in the thought process. The study also aims to observe the different standardized laundry variables to assess whether similar emissions are observed in all the households. This helps to understand the microfiber pollution and reduce the MF emission to a certain percentage.

Methodology

Questionnaire

A Google survey form was designed and circulated on social media platforms to obtain a diverse range of responses by using a snowball sampling technique, due to the prevalence of the Covid pandemic at the time of data collection. However, actual laboratory experimentations were conducted in post post-pandemic period.

Laundry Effluent Collection

Given the diversity of real-world laundry behaviors, it was not feasible to include a conventional control group. Each household’s laundry practices vary widely in terms of detergent use, water temperature, fabric types, and machine settings. Therefore, this study intentionally focuses on the variability of these factors in actual domestic conditions to establish baseline data. After careful consideration and geographical limitations, 30 households were selected for further study. The study is delimited to households that have up to four members with a fully automated washing machine. A consolidated laundry schedule was developed to note different laundry parameters for a period of 1 month. Laundry effluent water was collected three times from each household at random. The laundry rituals were carried out as such and no external influence was put out on respondents.

Quantitative Analysis

It is impossible to study the huge volumes of laundry effluent (40–60 l/wash cycle). So, following up on the previous works in the literature, an aliquots method was obtained. Using the help of large barrels and tubs which were present in the households, the laundry effluents from the wash cycle were collected and then using a wooden log as an agitating agent the effluent was stirred to produce a uniform sample. Then 1-l samples were collected using high-density polyethylene terephthalate. About 200 ml of laundry effluent was filtered using a 50 ml aliquot method. The aliquots were diluted to 100 ml using distilled water, resulting in the dilution of the laundry additives, dust, and other impurities. A stereomicroscope (40–60 × magnification) was employed to identify the microfibers, and a manual counting method was employed after dividing the glass microfiber filtrate into four quadrants to reduce the error rate and recounting of the same fibers twice.

SEM and FTIR Analysis

Advancements in technologies have made the fiber structure so complicated that two different fibers can look unquestionably similar under a micrograph. Thus, to identify the fibers with their true identity, FTIR spectroscopy was taken into consideration, whereas for the dimensional data, SEM analysis was performed.

To prepare the samples for SEM analysis a layer of gold coating was applied on the filter paper. The filter papers were then cut out from the areas that were considered to be the proper areas for analysis, then the cut pieces were mounted on a metallic disk which helped to secure the sample in one place, and then the samples were analyzed on different magnifications to find out the length and width dimensions of the fibers present on the sample. For the FTIR analysis, the samples were directly mounted on the machine and the resulting spectral data were collected, which were then matched with the spectral library to identify the fibers present.

Results and Discussion

Assessment of Consumer Knowledge

After data scrubbing, 273 responses were finalized with predominantly (75%) women respondents. Consumers were surveyed about their clothing preferences, and results showed that 63.70% preferred cotton for apparel, while 37.10% favored cotton for home textiles. However, laundry tests revealed that most apparel and home textiles contained blended fabrics, contradicting respondent’s stated preferences for cotton.

Respondents were asked about their laundry habits, particularly detergent usage. A majority (61.10%) reported using detergent based solely on the quantity of laundry, regardless of how dirty the clothes were. Additionally, 13.80% used a fixed amount of detergent, irrespective of clothing type or load size. Only 24.50% were analyzing their laundry needs and using the detergent based on the uncleanliness of the washing.

When asked about microfiber pollution, 58.80% of respondents were unaware of the issue, while 34.70% claimed some knowledge. However, follow-up questions revealed that only a small number had accurate information on the topic. The results obtained were an indicator that there is a tremendous need for consumer education and awareness, which was not regarded in the previous studies.

Laundry Schedule

A one-month laundry schedule was provided to the respondents to fill out about their laundry procedures such as the number and type of apparel and textiles being washed, the quantity of detergent and fabric softener, usage of bleaching agents, water temperature and volume, wash times, etc. About 420–600 laundry wash cycles were monitored, and enumeration articulated that the cotton program was the most used habituated wash cycle (68.60%), whereas the wool program showed fluctuations, being an indicator of the changing seasons and change in the type of clothing being used. During the winter seasons, a spike was observed which ranged up to 20.40% of all the wash cycles whereas during the summer seasons the cycle rate fell drastically (4.70%). A similar study conducted by Galvão et al.¹³ stated that 68% of the laundry cycles run were cotton cycles.

In India, washing machines typically include a built-in tumble-drying cycle, which most users activate regardless of temperature conditions. This suggests a lack of awareness about its impact on microfiber shedding. A report by the Swedish Agency for Environmental Protection suggested that tumble drying causes up to 3.5 times more added shedding in comparison to the normal wash cycles.

Wash cycle time plays a major role in microfiber shedding. From Figure 1 we can see that the most commonly used wash cycle observed was 30–60 min, followed by a 60–90 min cycle. Volgare et al.⁵ studied laundry variables and stated that water temperature, wash time, and water-to-fabric ratio have a considerable impact on the MF release rate, which varies from one wash cycle to the another.

Figure 1.

Duration of the wash cycles carried out by 30 households.

Quantitative Assessment of Microfibers

Microfibers filtered using glass microfiber filters were manually counted and labeled according to the wash cycle and household number. The highest MF sheddability was observed in H26 consisting of 6.7% of the total emissions followed by H17 with 6.3%. The least amount was observed in the H21 with 1.4%, which might be due to the fact that H21 consists of members opting to reuse garments twice before washing them, thus reducing the overall wash load and thus emission levels. Considering all three samples collected from the thirty households an average of 4,714,641 MFs/L were released from each household. A comparative analysis showed that MF emission is correlated with the number of wash cycles being carried out with R² = 0.3836. Galvão et al.¹³ in their study stated that an average of 2,97,400 MF/l were released during their investigation for 10 wash cycles (Figure 2).

Figure 2.

Percentage emission of MFs from different households.

Apart from the overall estimation, a difference in the front and top load washing machines was also estimated. Figure 3 clearly depicts that a visual difference was observed between the types; however, no statistical significance was found between the emissions. A total of 2,876,277 MFs were found in the range of ≤5 µm comprising 49.16% of the total emissions, whereas 26.95% was the second highest slot with fibers ranging from 50 to 100 µm.

Figure 3.

Difference between top- and front-load washing machine shedding.

Kärkkäinen and Sillanpää¹⁴ also indicate that when Bosch washing machines were tested for the MF release rate, 10–1700 mg/kg fibers were released from the front-loading washing machine, whereas in the top-loading machine the rate increased drastically.

Difference in MFs Shedding Over the Months

Figure 4 presents a clear picture of the MF shedding in top- and front-loading washing machines. Wilcoxon-signed rank test results indicated that there was no significant difference in fiber release between front-loading (median = 159,523.00, n = 7) and top-loading (median = 228,520.00, n = 8) washing machines during the warmer months (z = −0.652, p = 0.515, r = −0.168), suggesting that washing machine type alone did not play a significant role in fiber shedding under these conditions.

Figure 4.

Difference in MF shedding over the months along with top- and front-loading washing machines.

However, during the colder months, a marginally significant difference in fiber release was observed between front-loading (median = 124,975.00, n = 6) and top-loading (median = 133,315.00, n = 9) washing machines (z = −0.560, p = 0.051, r = −0.144). This difference is likely attributable to the increased shedding of thermals, woolens, and fuzzy garments, which are more frequently worn during winter. These fabrics have higher fiber loss rates due to their texture and composition, rather than the washing machine type itself. This finding suggests that seasonal clothing variation plays a crucial role in fiber release dynamics, which must be considered alongside machine type when assessing microfiber pollution (Figure 5).³

Figure 5.

SEM images of the MFs. MF: Microfiber.

Qualitative Assessment of Microfibers

SEM and FTIR analyses were run on the MFs. From the analysis, apart from MFs, several ripped end fibers were also observed which can be due to mechanical stress and agitation. A similar trend was observed in the study conducted by Belzagui et al.,¹⁵ who stated that mechanical agitation and stress imposed on the garments result in this type of imaging. Several lengths and widths of the microfibers were observed in the study along with nano fibers which can attract up to 15–20 times more pollutants than the MFs.¹⁶

From the O-H stretch in the band, we can state the presence of certain fiber structures. The peaks of the C-O bond at 1720 Cm^-1 (polyester) and -C-O-C vibrations at 965 Cm^-1 depict the presence of polyamide fiber (Figure 6). Cellulosic impurities can be observed around 1000–1100 Cm^-1, and the spectral data analysis results showed that 31% of fibers emitted were of cotton origin, and polyester comprised 27%. Some of the fibers (in minute amounts) that were noted in the study were acrylic, viscose, metal fibers, silk, elastane fibers, etc. The abundance of microfiber emissions and the natural to synthetic ratio can be viewed in Table 1, which depicts the main fibers identified during the laundry trials. Mostly households were practicing mixed laundry load cycles; only whites were run in separate cycles. Thus, there is a high chance that synthetics, when abraded with the hydrophilic cellulose fibers, might cause damage to the fiber structure, thereby emitting more MFs.

Figure 6.

FTIR graphs of the MFs. MF: Microfiber.

Table 1.

Abundance ratio and type of fibers released from the households during laundry trials.

Household no.	Abundance (%)	Abundance (MFs/L)	Main fibers identified
H1	Natural: 49	108,209.15	BB, CO, JU, LI, WO
H1	Synthetic: 51	112,625.85	PES, LA, EL, SM
H2	Natural: 89	217,878.23	CO, VI, SE, LI
H2	Synthetic: 11	26,928.77	PE, PES, PAN, UK
H3	Natural: 46	70,917.28	CO, VI, SE
H3	Synthetic: 54	83,250.72	AC, PES, PAN, EL
H4	Natural: 33	31,310.40	CO, VI
H4	Synthetic: 67	63,569.60	PES, PA, PP, SM, EL
H5	Natural: 44	113,381.40	CO, JU, VI, LI, BB
H5	Synthetic: 56	144,303.60	PES, EL, PE, PP, SM
H6	Natural: 77	72,473.94	CO, VI, SE
H6	Synthetic: 23	21,648.06	PES, PP, AC, UK
H7	Natural: 61	157,262.27	CO, VI
H7	Synthetic: 39	100,544.73	AC, PAN, PES, PP, EL
H8	Natural: 41	51,239.75	CO, VI, SE
H8	Synthetic: 59	73,735.25	PES, EL, PAN, UK, SM
H9	Natural: 34	83,589.00	WO, CO, VI
H9	Synthetic: 66	162,261.00	PAN, AC, PES, PP
H10	Natural: 52	158,856.36	WO, CO, JU
H10	Synthetic: 48	146,636.64	PAN, AC, PES, PP, EL, SM
H11	Natural: 22	24,332.00	CO, LI, VI
H11	Synthetic: 78	86,268.00	PES, AC, PA, PAN, PE, EL, SM
H12	Natural: 56	129,958.08	CO, LI, BB, JU, VI, SE
H12	Synthetic: 44	102,109.92	PES, EL, PP, PA, LA
H13	Natural: 45	28,551.60	CO, SE, VI
H13	Synthetic: 55	34,896.40	AC, PA, PE, PES, PP, EL, UK
H14	Natural: 49	66,792.88	CO, JU, LI, VI
H14	Synthetic: 51	69,519.12	PES, PP, EL, SM, PAN, UK
H15	Natural: 38	84,725.18	WO, CO, LI, VI
H15	Synthetic: 62	138,235.82	PAN, PA, AC, PE, PES, UK
H16	Natural: 28	207,484.76	WO, CO, VI
H16	Synthetic: 72	533,532.24	PAN, ME, LA, PES, EL, SM, PE
H17	Natural: 73	239,177.20	WO, CO, VI
H17	Synthetic:27	88,462.80	PAN, PA, PES, PP, EL
H18	Natural: 42	57,206.94	CO, SE, VI, LI
H18	Synthetic: 58	79,000.06	PES, PP, PAN, AC, UK
H19	Natural: 72	122,799.60	CO, VI, UK
H19	Synthetic: 28	47,755.40	PES, EL, AC, PA, PE
H20	Natural: 63	60,535.44	CO, LI, JU, VI
H20	Synthetic: 37	35,552.56	AC, PA, PES, PP, PE, EL, SM
H21	Natural: 53	39,209.40	WO, SE, VI, CO
H21	Synthetic: 47	34,770.60	PAN, PE, PES, PP, EL, UK
H22	Natural: 44	70,190.12	WO, CO, SE, VI
H22	Synthetic: 56	89,332.88	PAN, PES, EL, PE, PP, UK
H23	Natural: 67	153,108.40	WO, JU, LI, CO, SE, VI
H23	Synthetic: 33	75,411.60	PAN, PA, PE, PES, PP, EL
H24	Natural: 51	67,990.65	CO, SE, VI, LI
H24	Synthetic: 49	65,324.35	PE, PES, PA, EL
H25	Natural: 59	93,231.80	CO, SE, VI
H25	Synthetic: 41	64,788.20	AC, PA, PE, PES, PP, EL
H26	Natural: 53	184,512.61	WO, CO, VI, LI
H26	Synthetic: 47	163,624.39	PAN, PA, AC, PES, PE, PP, EL
H27	Natural: 76	83,286.88	WO, CO, VI
H27	Synthetic: 24	26,301.12	PAN, PES, EL, PE, PP, UK
H28	Natural: 35	34,067.95	WO, SE, VI, CO, LI
H28	Synthetic: 65	63,269.05	PAN, PES, PP, PE, EL
H29	Natural: 55	100,772.10	CO, SE, LI, JU
H29	Synthetic: 45	82,449.90	PES, PE, AC, PA PP, UK
H30	Natural: 39	47,105.37	WO, CO, SE, VI, LI
H30	Synthetic: 61	73,677.63	PAN, PE, PES, PP, EL, SM, UK

AC: Acetate; PA: Polyamide; PAN: polyacrylic; PE: polyethylene; PES: polyester; PP: polypropylene; SM: synthetic material; EL: elastane; LA: rubber textile; WO: wool; VI: viscose; CO: cotton; JU: jute; LI: linen; SE: silk; BB: bamboo viscose; ME: metallic fiber; UK: unknown.

Laundry Variables Optimization

Laundry variables were studied under different household conditions. Cesa et al.¹⁷ found a significant difference with and without the usage of laundry detergent with p < 0.001, but in real domestic laundry conditions, it was not possible to run laundry without detergent due to several factors (dust, sweat, stains, etc.). When laboratory studies were conducted, new clothes in sequential washing showed a decline in the MF sheddability, whereas in domestic conditions each cycle was releasing a considerable amount of MFs, which was consistent with a study conducted by Patagonia Inc. Moorhouse and Moorhouse¹⁸ stated that with increased garment age, there is a high chance that it will shed more MFs than new clothes due to the weakening of the fiber structure.

Conclusion

This study provides valuable insights into the release of microfibers (MFs) under real household laundry conditions, highlighting how various behaviors and fabric types influence MF emissions. Unlike controlled studies that focus on standardized materials, this research demonstrates the variability in MF release across different domestic scenarios, reflecting the complexity of real-world laundry routines. While the study does not employ a control group, this approach allows for a more accurate representation of household conditions where textiles and practices vary significantly.

This study also provides a comparative analysis of fiber release from garments washed in front-loading and top-loading washing machines, with a particular focus on the role of seasonal variations and garment composition. Our findings indicate that no significant difference was observed between the two machine types during the warmer months. However, in the colder months, a marginal difference in fiber release was noted, likely due to the increased shedding of thermals, woolens, and fuzzy garments, which are more commonly worn in winter. This highlights the critical role of fabric type in determining microfiber emissions.

Furthermore, the study acknowledges certain limitations, including the sample size and garment diversity, which may have influenced the observed patterns. Increasing the dataset in future research could provide more robust statistical insights and broader applicability of the findings. Additionally, further investigations should explore the effects of washing parameters such as detergent composition, age of the garment and type of the garment to develop more effective fiber-retention strategies in laundry processes. By addressing these factors, future studies can contribute to reducing fiber pollution, thereby promoting more sustainable textile care practices.

Supplemental Material

sj-docx-1-aat-10.1177_24723444251336006 – Supplemental material for Consumers’ Domestic Laundering Behavior in Relation to Microfiber Shedding

Supplemental material, sj-docx-1-aat-10.1177_24723444251336006 for Consumers’ Domestic Laundering Behavior in Relation to Microfiber Shedding by Aligina Anvitha Sudheshna, Meenu Srivastava and Prakash Chidambaram in AATCC Journal of Research

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Prakash Chidambaram

Supplemental material

Supplemental material for this article is available online.

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Supplementary Material

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