Microplastic contaminants in the sediment of the north coasts of the Persian Gulf and Gulf of Oman

Microplastic contaminants in the sediment of the north coasts of the Persian Gulf and Gulf of Oman | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Microplastic contaminants in the sediment of the north coasts of the Persian Gulf and Gulf of Oman Ali Mehdinia, Zeinab Aghajani, Abbasali Zamani, Younes Khosravi, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6552495/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Abundances and characteristics of microplastics were studied in the coastal area of the Persian Gulf and Oman Sea. Microplastics ranged from 10 to 45 particles per kilogram of sediment. Microplastics were in the size category of 100 µm to 2000 µm. The average concentration of microplastics in selected stations was 655 pieces/kg. In most of the transects, a negative slope of MPs was observed from coastal waters to deeper waters. Black fibers constituted 65.42% of the fibers and high-density polymers were dominant. Also, the type of polymers was identified using Raman analysis and polyethylene terephthalate (PET), nylon and polystyrene (PS) were the three main types of microplastic polymers in coastal surface sediments. In general, the findings reiterated the widespread presence of microplastics. In this study, the spatial outliers and the main deposition locations of microplastics were identified, and as a result, the places where future studies should be focused were determined. Earth and environmental sciences/Environmental sciences Earth and environmental sciences/Environmental sciences/Environmental chemistry Earth and environmental sciences/Environmental sciences/Environmental chemistry/Environmental monitoring Microplastics Persian Gulf Gulf of Oman sediments Pollution fibers Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Plastic waste makes up a significant portion of marine debris, accounting for up to 95 percent of debris on the seabed, sea surface, and coastlines (Yin et al., 2019 ). Plastic debris is persistent and permeates throughout the environment and has been reported from the deepest parts of the ocean to the top of the highest and most remote mountains (Napper et al., 2016). Microplastics can be found in water, soil and even air (Tian et al., 2022 ). In 1950, the production of plastic materials was more than 1.5 Mt, which reached 350 Mt in 2017. Many of these plastic wastes enter the oceans and seas in different shapes and sizes (Duis et al., 2016). The high volume of this plastic waste is related to the production of plastic materials and equipment, the lack of correct collection and recycling methods, the lack of awareness and training of the residents of the region, and cases of this in the hands (Al-Salem et al., 2020 ). Plastics come in a variety of sizes, including macroplastics (greater than 200 mm), mesoplastics (5–200 mm), and microplastics (< 5 mm) (Derraik, 2002 ; Germanov et al., 2018 ). Microplastics (PMs) are persistent solid materials that are created from the breakdown of the larger plastics and are released in marine and coastal environments (Garcés-Ordóñez et al., 2019 ). They have significant adverse effects on ecosystems and marine habitats. (Cordeiro and Costa, 2010 ). They originate from primary or secondary sources. Primary MPs are commonly found in cosmetic products (such as toothpaste, facial cleansers, and cosmetics). On the other hand, it is also used as a drug carrier in medicine. Secondary microplastics are produced as a result of the environmental erosion and degradation of large plastics (Including fishing tackle and food and beverage packaging) through photodegradation, oxidation and mechanical abrasion at sea or on land (Costa e al., 2010; Maghsodian et al. 2021 ; Stockin et al., 2021 ). In general, in various studies, the concentration of microplastics has been estimated at the outlet of sewage, near the mouth of regular rivers and in areas with high levels of fishing and tourism activities (Mehdinia et al., 2020 ; Naji et al., 2021 ). The presence of microplastics in different depths of sediment or seawater depends on various characteristics, including the density of seawater and the density of plastic particles. The density of seawater in the PG&GO is reported to be approximately between 1.02 and 1.03, like seawaters in most parts of the world. However, this density is lower than the density of many plastics (Uddin et al., 2020 ). Therefore, many plastics tend to accumulate on the surface of sediments. Among the types of microplastics, pure microplastics made of low-density polyethylene (LPDE), polypropylene (PP), polyester (PS), high-density polyethylene (HDPE) and some polyethylene terephthalates (PET) have a lower density. And they can stay suspended on the water surface. Pure microplastics made of polyvinyl chloride (PVC), polycarbonate (PC), polyurethane (PU), polystyrene (PES), alkyd and nylon have a higher density than seawater and accumulate on the surface of sediments (Duis et al., 2016). Due to the importance of the PG&GO for Iran and neighboring countries, as well as the persistence of different pollutants in the environment and their damage to organisms, many studies have been conducted in these areas. In one of these studies, Nabizadeh et al. ( 2019 ) studied MPs of sediments in the Persian Gulf shoreline (37 samples from urban highly developed beaches, 10 from rural beaches and 13 from remote beaches mangroves forest, 37 samples from developed urban beaches, 13 examples of remote mangrove forest beaches, and 10 examples of rural beaches). This shows that highly urban areas and human activities have significant effects on the distribution and abundance of microplastics in the coastal area. In another study, (Kor et al., 2020 ), there is information on MPs contamination in coastal sediments of the North Sea of ​​Oman at 10 stations. Based on the results of this study, the presence and distribution of MPs as human pollutants in the region is clear and this makes the importance of management measures and environmental protection education to reduce marine litter. However, it was strongly recommended to establish a monitoring program for microplastics in this area. Based on our knowledge, there is no study on the microplastics distribution in the Iranian coastal area of the PG&GO and this study is the first study that used a large sample compared to that used in other studies conducted in this region. 2. Materials and methods Sampling of the sediments of the studied area was carried out in Bushehr, Hormozgan and Chabahar coasts in 2018 (Fig. 1 ). Five stations were sampled in Bushehr coasts based on the proximity to the tourist area of ​​mangrove forests and Khor Soltani (Table 1 ). Mangrove forests in Bushehr province are among the ecologically sensitive areas that face very high threats such as the entry of industrial pollutants and urban sewage. For this purpose, sampling was performed from stations N1, N2, N3 and N4 near this area. Station M was also chosen for sampling the shore of Bushehr due to its proximity to Khor Soltani, which is one of the most important estuaries of Bushehr and a rich ecosystem exposed to construction debris. Table 1 Geographical locations of Bushehr beach sampling stations Station Longitude Latitude 1 N1 52.655 27.464167 2 N2 52.661389 27.4623 3 N3 52.6689 27.4612 4 N4 52.674165 27.45832 5 N5 50.842304 28.987963 In Hormozgan coasts, 13 stations were sampled (Table 2 ). The stations of Az1, Az3 and Az10 are located between the Azin International Wetland and its mangrove forests, near this wetland, the construction of a wharf and the traffic of fuel smuggling boats have led to pollution including microplastic pollution in this area. The Kh7, Kh12 and Kh16 sampling stations are near the port Khamir, which is the largest marine wetland in the Middle East and has the largest mangrove forests in Iran. This port was chosen for sampling due to its sea transportation connection, plaster and cement factory and an area for tourists. The Ks1, Ks2, Ks4, Ks7, Ks8, Ks9 and Ks11 stations were also sampled due to their proximity to the commercial-industrial port of Shahid Rajai (Fig. 1 ). Table 2 Geographical locations of Hormozgan beach sampling stations Station Longitude Latitude 1 AZ1 57.097192 26.322709 2 AZ3 57.09199 26.31937 3 AZ10 57.09194 26.30511 4 Kh7 55.59341 26.88409 5 Kh12 55.65013 26.88671 6 Kh16 55.66162 26.90643 7 Ks1 56.102244 27.100838 8 Ks2 56.088754 27.098234 9 Ks4 56.07869 27.08715 10 Ks7 56.09859 27.1103 11 Ks8 56.09464 27.11402 12 Ks9 56.09273 27.11537 13 Ks11 56.11118 27.11844 Ten stations were sampled on the coast of Chabahar (Table 3 ). The stations of T1, T2, T4 and T5 are located near the Chabahar Bay, which is the largest bay in Iran with two piers, Shahid Beheshti and Shahid Kalantari. Sampling was performed at the HP1 and HP2 stations due to their proximity to Chabahar beach resorts and White Boat and Ship Wharf in Makran Port. Sampling was performed from BP1 and BP2 stations due to their proximity to Shahid Beheshti Wharf and ST4 and ST9 stations due to their proximity to Iran Gas Press Company and Har Tis Forest (Fig. 1 ). Table 3 Geographical locations of Chabahar beach sampling stations Station Longitude latitude 1 T1 60.6038 25.26985 2 T2 60.53833 25.29749 3 T4 60.50733 25.381 4 T5 60.49091 25.42409 5 HP1 60.62372 25.29828 6 HP2 60.60795 25.31646 7 BP1 60.60566 25.29656 8 BP2 60.59326 25.30863 9 ST4 60.58348 25.39325 10 ST9 60.46035 25.39865 Sediment sampling from the surface layer of the sediment was performed using a Van Veen Grab. For sample preparation, 500 g of sediment samples were weighed and dried in an oven at temperature of 60 ºC. Before separating the microplastics to remove the coating of organic matter, 200 mL of hydrogen peroxide (30%) was added to 200 g of each sample and placed in a shaker at room temperature until the bubbles caused by the reaction disappeared. The samples were stirred several times every day so that the settled organic matter along with the mineral particles on the floor of the beaker were well exposed to the solution. After mixing the samples, the beakers were covered with aluminum foil. After the disappearance of the bubbles, the samples were diluted with distilled water and after settling the suspended solids, the supernatant was passed through the filter paper > 2 µm (S&S5893) with the help of a vacuum pump and under pressure. This part of the work was repeated twice. The remaining particles were washed on filter paper with distilled water and returned to the beaker containing sediment. Then, the samples were placed in an oven at 60°C to dry, so that the remaining water in the containers does not change the density of the added salt. The sodium iodide (NaI) salt solution was used to separate microplastics from the sediments. To prepare this solution, about 1200 g of anhydrous sodium iodide powder (Sigma Aldrich, purity > 97%) was dissolved in one liter of distilled water. This solution was stirred regularly until the complete dissolution of the salt. The density of the prepared solution was more than 1.6 g L − 1 , which was obtained with the help of a glass pycnometer (Densitometer: 25 mL). 150 mL of the prepared solution was added to each sample and stirred gently for at least 5 min. Then the samples were kept without movement for 24 h. After that, the supernatant of the solution was moved on the filter paper and filtered under vacuum with pressure. Then, the filter along with the separated microplastics was stored in glass culture containers (Petri dish). These steps were repeated two times to achieve the maximum percentage of microplastics recovered from the sediment samples. The filter paper containing the sample was dried at room temperature and the particles on the filter were transferred to the petri dishes with the help of a laboratory brush (made of natural hair). To identify the microplastics, a Raman microscope was used. The MPs were characterized using a stereo (binocular) microscope. The microplastic particles were counted using a 250 µm diameter needle and a stereo optical microscope (binoculars) with a maximum magnification of 100 times. The approximate size, shape and color of each particle were recorded after counting the microplastics of each sample. Strict measures were strictly enforced during the work to ensure that contamination was avoided. To prevent contamination of samples, a glassy vacuum filtration system was used, and all solvents and solutions were filtered 3 times before use. All glassware and dissection tools were eluted with triple-filtered distilled water to reduce the potential risk of contamination. The blank analysis was also performed during sample preparation. 3. Results and discussions Based on the samples obtained, the characteristics and details of microplastics of Chabahar, Bushehr and Hormozgan beaches were recorded in terms of color, size, type and abundance. Also, the size of microplastics (in micrometers) is defined in 4 ranges (100 ≤ L < 500) A, (500 ≤ L < 1000) B, (1000 ≤ L < 1500) C and (1500 ≤ L < 2000) D. According to the obtained results, the microplastics of Chabahar, Bushehr and Hormozgan beaches were all of fiber type, and in terms of color, black, blue and red colors were the most abundant, respectively (Fig. 2 &Fig. 3 ). According to Fig. 4 , in Chabahar beach, microplastic samples were recorded at T1 and T4 sampling stations with a frequency of 35 pieces per kilogram of sediment more than other stations and at HP2 station with a frequency of 10 pieces per kilogram of sediment less than other stations. All the microplastics of Chabahar beach were fibers, but the color of the fibers was different. Comparing the color of the fibers of Chabahar beach, it can be said that the black fibers were the most abundant in T1, T2, T4, HP1 stations and the blue fibers were the most abundant in ST9, ST4, BP2, T5 stations. In two stations, HP2 and BP1, the frequency of fibers has been equal. In general, black fibers were more abundant in Chabahar region. In terms of size, the microplastics of Chabahar beach were mostly between 100 and 500 micrometers, which means that the stations often had small microplastics, which could indicate that the plastic particles remained in the environment for a long time and turned into smaller particles (Table 4 ). Table 4 The microplastics data sampled from the Chabahar beach St. Abundance Shape Color Size (µm) - Particle/Kg - Red Black Blue White A B C D T1 35 Fiber 5 20 10 - 20 10 5 - T2 30 Fiber 10 15 - 5 20 10 - - T4 35 Fiber - 20 5 5 15 10 10 - T5 20 Fiber 5 5 10 - 10 10 - - HP1 25 Fiber - 20 5 - 20 5 - - HP2 10 Fiber 5 5 - - 10 - - - ST9 15 Fiber - 15 - - 5 10 - - ST4 20 Fiber - 15 5 - 20 - - - BP2 25 Fiber 10 15 - - 10 10 5 - BP1 15 Fiber 5 5 5 - 10 10 5 - Figure 5 shows that in the Bushehr beach, the highest frequency of microplastic samples is related to station N2 (in the Bushehr beach) with a concentration of 45 pieces per kilogram of sediment. It is due to the proximity of this station to mangrove forests. Station N4 has the lowest abundance of microplastics in this region with an abundance of 20 pieces per kilogram of sediment (Fig. 5 ). According to Table 5 , all the microplastics of Bushehr beach were fibers, but the colors of the fibers were different. Comparing the fibers in Bushehr beach stations, it can be said that the fibers, like Chabahar beach, were mostly between 100 and 500 micrometers in size, and black- colored fibers were the most abundant in all stations. According to Fig. 5 , station N2 had the highest frequency and station N4 had the lowest frequency of microplastics (Table 5 ). Table 5 The data related to microplastics sampled from Bushehr beach St. abundance Shape Color Size (µm) - Particle/Kg - Red Black Blue White A B C D N1 30 Fiber 10 20 - - 20 10 - - M 30 Fiber - 20 10 - 10 15 5 - N3 25 Fiber 5 15 5 - 10 10 5 - N4 20 Fiber - 20 - - 10 5 - 5 N2 45 Fiber 10 25 10 - 25 10 - 10 According to Fig. 6 , station Az3 on the coast of Hormozgan and in the vicinity of mangrove forests and the international wetland of Khor Azini, station Kh7 near Khamir port and station Ks11 near the unloading and loading dock of the special area of ​​the Persian Gulf, with a concentration of 30 pieces of microplastic per Kilogram of sediment was one of the most polluted stations in Hormozgan province. KS9 station also had the least pollution among other stations in this area. Figure 6 also shows that the microplastics in this area are mostly in the form of black fibers, but in station KS11, the amount of black and red fibers are equally recorded and the amount of blue and black fibers in station KS8 were also equal, and the size of most of them is the same as in Bushehr beach stations and Chabahar (about 100 to 500 µm) (Table 6 ). Table 6 The microplastics data of the samples of Hormozgan beach St. Abundance shape Color Size (µm) - Particle/Kg - Red Black Blue White A B C D KS2 20 Fiber 5 15 - - 10 10 - - KH12 25 Fiber - 25 - - 15 5 5 - KH16 15 Fiber - 10 5 - 15 - - - AZ3 30 Fiber 10 20 - - 20 5 5 - KH7 30 Fiber - 20 10 - 20 10 - - KS1 20 Fiber - 15 5 - 15 5 - - KS7 20 Fiber 5 10 5 - 20 - - - KS9 10 Fiber - 10 - - 10 - - - AZ1 25 Fiber - 25 - - 15 10 - - AZ10 15 Fiber - 10 5 - 15 - - - KS11 30 Fiber 15 15 - - 15 10 5 - KS4 20 Fiber - 15 5 - 20 - - - KS8 25 Fiber 5 10 10 - 15 5 5 - Table 7 compares the data obtained from this study with other similar studies. In this study, the amount of microplastics in sensitive coastal sediments of the PG&GO was calculated to be 665 particles/kg. The amount of coastal microplastics in the Sea of ​​Oman is 230 particles/kg, which is almost in the same range as the amount of microplastics in the study by Kor et al. ( 2020 ), but in that study, although the number of stations is less, the amount of microplastics has increased sharply. Also, the amount of microplastics on the shores of the Persian Gulf in this research was 435 particles/kg, which is less than the amount of microplastics on the shores of the Persian Gulf in 2023. Because over time, the amount of microplastics in water and coastal environments increased. All microplastics in this research are in the form of fibers, which shows that fibers are the most abundant microplastics on the shores of the PG&GO. According to Table 7 , in the investigation of microplastics in aquatic and coastal environments, the amount of fibrous microplastics is more than other forms of microplastics. The most common fiber samples are black fibers, like the ones studied by Sheikhi et al. (2023) and Hakim et al. (2020), and these fibers are particles from the wear of tires and roads. But the blue, red and other fibers can be wastes from fishing, recreational activities and the proximity of the beach to the sewage outlet and domestic and industrial effluents in this area. According to the Raman spectra, polyethylene terephthalate, nylon, and polystyrene were the most common types of polymers in plastics. These polymers were similar to the polymers studied by Sheikhi et al. (2023) and Kor et al. ( 2020 ), but the variety of polymers in the study by Hakim et al. (2020). In general, the distribution and variety of polymers in different stations indicate different sources of microplastics in this area. Table 7 Comparison of microplastics data of this study with those of other studies Average Abundance Shape Color Size Type Reference 665 Particles /Kg 100%Fibers 65.42%Black, 16.54% blue, 16.54% red, 1/5% white, 100–1000µm PET, Nylon, PS This work 2019 546.7 ± 172.6 Particles/Kg at depths of (0–5cm:226.2 ± 76.7) (5–15cm:47.1 ± 16.1) (0–15cm:273.4 ± 78.8) 55% fibers 40% Black ˂500 µm PE, PS, PET, Nylon Sheikhi et al., 2023 (Persian Gulf) from 138.3 ± 4.5 to 930.3 ± 49.1 particles /Kg 29.9%Fibers & 32.9%fragments 28.9%White, 20%Blue, 16.1%Black, 12.3%Colorless, 7.5%Red, 5%Green & 10.5% other 1000–5000 µm PE, PP, Nylon Kor et al., 2020 (Oman Sea) 124 to 961 particles/100 g Fragments, fibers and Films black (64%), transparent (55.74%), and red (34.27%) 250–500 µm 75%: Tencel, Bemberg, PTFE, FEP Hakim et al., 2020 (Indian Ocean) The findings of this research showed that human activities, navigation and fishing can be important sources of microplastic pollution in the region. 4. Conclusion A high abundance of microplastics in coastal sediments of the PG&GO (up to 45 pieces of microplastics per kilogram of sediment) was observed. These frequencies are highly variable spatially, highlighting the design of a precise local sampling strategy to capture sample diversity. The wide range of polymer types reflects the diversity of sources and the potential of traveling long distances for plastics. This work shows that local and regional sources are a more important factor that affects the abundance of microplastics and the types of polymers available. This calls for the need to further identify sources to inform development of waste management in the vicinity of vulnerable ecosystems, to further reduce the input of microplastic pollution. The presence of microplastics in all locations of these systems represents a major environmental concern for aquatic ecosystems. Further research is warranted to proactively mitigate potential consequences. Declarations The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Ethical Responsibilities of Authors All authors have read, understood, and have complied as applicable with the statement on "Ethical responsibilities of Authors" as found in the Instructions for Authors”. Ethical Approval Not applicable Funding This work was supported by the Iranian National Institute for Oceanography and Atmospheric Science with Grant number: 399-011-01-028-01. Author Contribution Ali Mehdinia: Conceptualization, writing – review & editing, Funding acquisition, Zeinab Aghajani: Writing original draft, Methodology, Formal analysis, Data curation, Abbasali Zamani: Conceptualization Younes Khosravi: Software, Somayeh Navid: Experiments, Nima Navid: Experiments Acknowledgement The current study was funded by Iranian National Institute for Oceanography and Atmospheric Science (INIOAS) (project grant number 399-011-01-028-01). Data Availability If someone wants to request the data from this study should be contacted to corresponding author. References Al-Salem, S. M., Uddin, S., & Al-Yamani, F. (2020). An assessment of microplastics threat to the marine environment: A short review in context of the Arabian/Persian Gulf, Marine Environmental Research , 159, 104961. Cordeiro, C. A. M. M., & Costa, T. M. (2010). Evaluation of solid residues removed from a mangrove swamp in the São Vicente Estuary, SP, Brazil. Marine Pollution Bulletin , 60(10), 1762-1767. Costa, M. F., Do Sul, J. A. I., Silva-Cavalcanti, J. S., Araújo, M. C. B., Spengler, Â., & Tourinho, P. S. (2010) On the importance of size of plastic fragments and pellets on the strandline: a snapshot of a Brazilian beach. Environmental Monitoring and Assessment , 168, 299-304. Derraik, J. G. (2002) The pollution of the marine environment by plastic debris: a review. Marine Pollution Bulletin , 44, 842–852. Duis, K., & Coors, A. (2016). Microplastics in the aquatic and terrestrial environment: sources (with a specific focus on personal care products), fate and effects. Environmental Sciences Europe, 28(1), 2. Garcés-Ordóñez, O., Castillo-Olaya, V. A., Granados-Briceño, A. F., García, L. M. B., & Díaz, L. F. E. (2019). Marine litter and microplastic pollution on mangrove soils of the Ciénaga Grande de Santa Marta, Colombian Caribbean. Marine Pollution Bulletin . 145, 455-462. Germanov, E. S., Marshall, A. D., Bejder, L., & Fossi, M. C. (2018). Loneragan, N. R. Microplastics: no small problem for filter-feeding megafauna. Trends in Ecology & Evolution . (2018); 33, 227-232. Hakim, L., Asmara, A. A., Priambodo, R.Y & Wong, Y J. (2023). Microplastic Pollution Profile in the Indian Ocean of the Southern Java Island, Indonesia, Environmental Challenges , 100786, 2667-0100. Kor, K., Ghazilou, A., & Ershadifar, H. (2020). Microplastic pollution in the littoral sediments of the northern part of the Oman Sea. Marine Pollution Bulletin , 155, 111166. Maghsodian, Z., Sanati, A.M., Ramavandi, B., Ghasemi, A., & Sorial, G. A. (2021). Microplastics accumulation in sediments and Periophthalmus waltoni fish, mangrove forests in southern Iran, Chemosphere , 264(2 ( , 128543. Mehdinia, A., Dehbandi, R., Hamzehpour, A., & Rahnama, R. (2020). Identification of microplastics in the sediments of southern coasts of the Caspian Sea, north of Iran, Environmental Pollution , 258(4)-113738. Nabizadeh, R., Sajadi, M., Rastkari, N., & Yaghmaeian, K. (2019). Microplastic pollution on the Persian Gulf shoreline: A case study of Bandar Abbas city, Hormozgan Province, Iran, Marine Pollution Bulletin , 145, 536. Naji, A., Azadkhah, S., Farahani, H., Uddin, S., & Khan, F. R. (2021). Microplastics in wastewater outlets of Bandar Abbas city (Iran): a potential point source of microplastics into the Persian Gulf. Chemosphere , 262: 128039. Napper, I. E., & Thompson, R. C. (2016). Release of synthetic microplastic plastic fibres from domestic washing machines: Effects of fabric type and washing conditions. Marine Pollution Bulletin , 112(1-2), 39-45. Sheikhi, H., & Mirzaei, R. (2023). Occurrence and abundance of macro, meso and microplastics along the coasts of the Persian Gulf (case study: Bushehr Province coast). Marine Pollution Bulletin , 194, 115261. Stockin, K. A., Pantos, O., Betty, E. L., Matthew, D. M., Doake, F., Masterton, H., Palmer, E. I., Matthew, R. P., Sarah E. N., & Gabriel, E. M. C. (2021) Fourier transform infrared (FTIR) analysis identifies microplastics in stranded common dolphins (Delphinus delphis) from New Zealand waters, Marine Pollution Bulletin , 173(2), 113084. Tian, L., Cheng, J., Ji, R., Ma, Y., & Yu, X. (2022). Microplastics in agricultural soils: sources, effects, and their fate, Current Opinion in Environmental Science & Health , 25, 100311. Uddin, S., Fowler, S. W., & Saeed, T. (2020). Microplastic particles in the Persian Gulf–a review on sampling and identification. Marine Pollution Bulletin , 154, 111100. Yin, C. S., Chai, Y. J., Carey, D., Yusup, Y., & Gallagher, J. B. (2019). Anthropogenic marine debris and its dynamics across peri-urban and urban mangroves on Penang Island, Malaysia. BioRxiv , 756106. https://doi.org/10.1101/75610. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6552495","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":454397402,"identity":"255c541b-9bdf-4257-ad01-4cb34949920c","order_by":0,"name":"Ali Mehdinia","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyklEQVRIiWNgGAWjYFACHgaJBAYJBn5mBoYDYAFmYrVINpOkBUQZHCDWWbrtvQdvPNxhIW98nPfggQ8MdvIM7LwP8GoxO3Mu2SLxjIThtsN8CQdnMCQbNjCzG+DXciPHTCKxTYJx22Eeg8M8DMwJDMxs+B1mdv8NWIv95mawlnoitNzgAWtJ3MAM1nKYCC1ncowtgFqSZwAddnCGwXHDNoJajp8xvPmzrc62v/+M8YcPFdXy/PzH8GtBA8CwImDHKBgFo2AUjAJiAAA5XDu7wOJCPQAAAABJRU5ErkJggg==","orcid":"","institution":"Iranian National Institute for Oceanography and Atmospheric Science","correspondingAuthor":true,"prefix":"","firstName":"Ali","middleName":"","lastName":"Mehdinia","suffix":""},{"id":454397403,"identity":"54b7222c-5456-455c-b4b1-073910412023","order_by":1,"name":"Zeinab Aghajani","email":"","orcid":"","institution":"University of Zanjan","correspondingAuthor":false,"prefix":"","firstName":"Zeinab","middleName":"","lastName":"Aghajani","suffix":""},{"id":454397404,"identity":"b773d501-1286-4269-9c90-2f92b6c1e5f8","order_by":2,"name":"Abbasali Zamani","email":"","orcid":"","institution":"University of Zanjan","correspondingAuthor":false,"prefix":"","firstName":"Abbasali","middleName":"","lastName":"Zamani","suffix":""},{"id":454397405,"identity":"486796b6-fb35-45a9-991c-78d19245361b","order_by":3,"name":"Younes Khosravi","email":"","orcid":"","institution":"University of Zanjan","correspondingAuthor":false,"prefix":"","firstName":"Younes","middleName":"","lastName":"Khosravi","suffix":""},{"id":454397406,"identity":"59529bf5-d55d-4692-9220-a324b2c2617e","order_by":4,"name":"Somayeh Abedi","email":"","orcid":"","institution":"Iranian National Institute for Oceanography and Atmospheric Science","correspondingAuthor":false,"prefix":"","firstName":"Somayeh","middleName":"","lastName":"Abedi","suffix":""},{"id":454397407,"identity":"e441e720-06a0-46c8-b3fc-9424732b1dab","order_by":5,"name":"Nima Navid","email":"","orcid":"","institution":"Tehran Medical Sciences, Islamic Azad University","correspondingAuthor":false,"prefix":"","firstName":"Nima","middleName":"","lastName":"Navid","suffix":""}],"badges":[],"createdAt":"2025-04-29 04:53:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6552495/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6552495/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82623403,"identity":"944a618e-6cab-4367-86ae-dee3ec5a867c","added_by":"auto","created_at":"2025-05-13 12:41:55","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":52098,"visible":true,"origin":"","legend":"\u003cp\u003eThe location of the sampling stations of the coast of the PG\u0026amp;GO\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6552495/v1/d51d6750519bb78330b69e67.jpg"},{"id":82623401,"identity":"3e2064b1-44ee-4acc-8074-33aa95a2d45a","added_by":"auto","created_at":"2025-05-13 12:41:55","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":119321,"visible":true,"origin":"","legend":"\u003cp\u003eImages of different shapes and colors of microplastic fibers in sediment samples\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6552495/v1/7d5b957fca58e31c992a5d72.jpg"},{"id":82624452,"identity":"9426754e-51a3-45c7-bf42-b80782d4318e","added_by":"auto","created_at":"2025-05-13 12:49:55","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":36175,"visible":true,"origin":"","legend":"\u003cp\u003eShow the approximate abundance of fibers in terms of color\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6552495/v1/df5550ac0996638970f4d24a.jpg"},{"id":82624450,"identity":"9c1a358a-9a3d-4a15-9c5e-afbf790b3ca3","added_by":"auto","created_at":"2025-05-13 12:49:55","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":45068,"visible":true,"origin":"","legend":"\u003cp\u003eThe abundance of microplastics in terms of color in the sampling stations of Chabahar beaches\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6552495/v1/8d387a9247904fbd6d65e78d.jpg"},{"id":82624451,"identity":"a4b36b3e-6cbc-40b3-b436-f201530c07d0","added_by":"auto","created_at":"2025-05-13 12:49:55","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":41380,"visible":true,"origin":"","legend":"\u003cp\u003eThe abundance of microplastics in terms of color in the sampling stations of Bushehr beaches\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6552495/v1/e681e27c5363b7ffbb244497.jpg"},{"id":82623407,"identity":"c0d3ef4d-02c3-47bb-ad14-d614c774cac2","added_by":"auto","created_at":"2025-05-13 12:41:55","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":47470,"visible":true,"origin":"","legend":"\u003cp\u003eThe abundance of microplastics in terms of color in the sampling stations of Hormozgan beaches\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6552495/v1/684f9ed4f94e56e08f520a22.jpg"},{"id":85646615,"identity":"6e776159-b825-4b1b-9767-d44cfc28d221","added_by":"auto","created_at":"2025-06-30 08:39:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1135798,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6552495/v1/4b5f98c1-74fa-461c-9b70-6e84e066174b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Microplastic contaminants in the sediment of the north coasts of the Persian Gulf and Gulf of Oman","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003ePlastic waste makes up a significant portion of marine debris, accounting for up to 95 percent of debris on the seabed, sea surface, and coastlines (Yin et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Plastic debris is persistent and permeates throughout the environment and has been reported from the deepest parts of the ocean to the top of the highest and most remote mountains (Napper et al., 2016). Microplastics can be found in water, soil and even air (Tian et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn 1950, the production of plastic materials was more than 1.5 Mt, which reached 350 Mt in 2017. Many of these plastic wastes enter the oceans and seas in different shapes and sizes (Duis et al., 2016). The high volume of this plastic waste is related to the production of plastic materials and equipment, the lack of correct collection and recycling methods, the lack of awareness and training of the residents of the region, and cases of this in the hands (Al-Salem et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Plastics come in a variety of sizes, including macroplastics (greater than 200 mm), mesoplastics (5\u0026ndash;200 mm), and microplastics (\u0026lt;\u0026thinsp;5 mm) (Derraik, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Germanov et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMicroplastics (PMs) are persistent solid materials that are created from the breakdown of the larger plastics and are released in marine and coastal environments (Garc\u0026eacute;s-Ord\u0026oacute;\u0026ntilde;ez et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). They have significant adverse effects on ecosystems and marine habitats. (Cordeiro and Costa, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). They originate from primary or secondary sources. Primary MPs are commonly found in cosmetic products (such as toothpaste, facial cleansers, and cosmetics). On the other hand, it is also used as a drug carrier in medicine. Secondary microplastics are produced as a result of the environmental erosion and degradation of large plastics (Including fishing tackle and food and beverage packaging) through photodegradation, oxidation and mechanical abrasion at sea or on land (Costa e al., 2010; Maghsodian et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Stockin et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In general, in various studies, the concentration of microplastics has been estimated at the outlet of sewage, near the mouth of regular rivers and in areas with high levels of fishing and tourism activities (Mehdinia et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Naji et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe presence of microplastics in different depths of sediment or seawater depends on various characteristics, including the density of seawater and the density of plastic particles. The density of seawater in the PG\u0026amp;GO is reported to be approximately between 1.02 and 1.03, like seawaters in most parts of the world. However, this density is lower than the density of many plastics (Uddin et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Therefore, many plastics tend to accumulate on the surface of sediments. Among the types of microplastics, pure microplastics made of low-density polyethylene (LPDE), polypropylene (PP), polyester (PS), high-density polyethylene (HDPE) and some polyethylene terephthalates (PET) have a lower density. And they can stay suspended on the water surface. Pure microplastics made of polyvinyl chloride (PVC), polycarbonate (PC), polyurethane (PU), polystyrene (PES), alkyd and nylon have a higher density than seawater and accumulate on the surface of sediments (Duis et al., 2016).\u003c/p\u003e \u003cp\u003eDue to the importance of the PG\u0026amp;GO for Iran and neighboring countries, as well as the persistence of different pollutants in the environment and their damage to organisms, many studies have been conducted in these areas. In one of these studies, Nabizadeh et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) studied MPs of sediments in the Persian Gulf shoreline (37 samples from urban highly developed beaches, 10 from rural beaches and 13 from remote beaches mangroves forest, 37 samples from developed urban beaches, 13 examples of remote mangrove forest beaches, and 10 examples of rural beaches). This shows that highly urban areas and human activities have significant effects on the distribution and abundance of microplastics in the coastal area. In another study, (Kor et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), there is information on MPs contamination in coastal sediments of the North Sea of ​​Oman at 10 stations. Based on the results of this study, the presence and distribution of MPs as human pollutants in the region is clear and this makes the importance of management measures and environmental protection education to reduce marine litter. However, it was strongly recommended to establish a monitoring program for microplastics in this area. Based on our knowledge, there is no study on the microplastics distribution in the Iranian coastal area of the PG\u0026amp;GO and this study is the first study that used a large sample compared to that used in other studies conducted in this region.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cp\u003eSampling of the sediments of the studied area was carried out in Bushehr, Hormozgan and Chabahar coasts in 2018 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFive stations were sampled in Bushehr coasts based on the proximity to the tourist area of ​​mangrove forests and Khor Soltani (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Mangrove forests in Bushehr province are among the ecologically sensitive areas that face very high threats such as the entry of industrial pollutants and urban sewage. For this purpose, sampling was performed from stations N1, N2, N3 and N4 near this area. Station M was also chosen for sampling the shore of Bushehr due to its proximity to Khor Soltani, which is one of the most important estuaries of Bushehr and a rich ecosystem exposed to construction debris.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGeographical locations of Bushehr beach sampling stations\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLongitude\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLatitude\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52.655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.464167\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52.661389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.4623\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52.6689\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.4612\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52.674165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.45832\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.842304\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28.987963\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn Hormozgan coasts, 13 stations were sampled (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The stations of Az1, Az3 and Az10 are located between the Azin International Wetland and its mangrove forests, near this wetland, the construction of a wharf and the traffic of fuel smuggling boats have led to pollution including microplastic pollution in this area. The Kh7, Kh12 and Kh16 sampling stations are near the port Khamir, which is the largest marine wetland in the Middle East and has the largest mangrove forests in Iran. This port was chosen for sampling due to its sea transportation connection, plaster and cement factory and an area for tourists. The Ks1, Ks2, Ks4, Ks7, Ks8, Ks9 and Ks11 stations were also sampled due to their proximity to the commercial-industrial port of Shahid Rajai (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGeographical locations of Hormozgan beach sampling stations\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLongitude\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLatitude\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAZ1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57.097192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.322709\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAZ3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57.09199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.31937\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAZ10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57.09194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.30511\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKh7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55.59341\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.88409\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKh12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55.65013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.88671\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKh16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55.66162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.90643\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKs1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.102244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.100838\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKs2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.088754\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.098234\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKs4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.07869\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.08715\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKs7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.09859\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.1103\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKs8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.09464\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.11402\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKs9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.09273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.11537\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eKs11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.11118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e27.11844\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTen stations were sampled on the coast of Chabahar (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The stations of T1, T2, T4 and T5 are located near the Chabahar Bay, which is the largest bay in Iran with two piers, Shahid Beheshti and Shahid Kalantari. Sampling was performed at the HP1 and HP2 stations due to their proximity to Chabahar beach resorts and White Boat and Ship Wharf in Makran Port. Sampling was performed from BP1 and BP2 stations due to their proximity to Shahid Beheshti Wharf and ST4 and ST9 stations due to their proximity to Iran Gas Press Company and Har Tis Forest (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGeographical locations of Chabahar beach sampling stations\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLongitude\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003elatitude\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.6038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.26985\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.53833\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.29749\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.50733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.381\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.49091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.42409\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHP1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.62372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.29828\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHP2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.60795\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.31646\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBP1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.60566\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.29656\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBP2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.59326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.30863\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eST4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.58348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.39325\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eST9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.46035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.39865\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSediment sampling from the surface layer of the sediment was performed using a Van Veen Grab. For sample preparation, 500 g of sediment samples were weighed and dried in an oven at temperature of 60 \u0026ordm;C. Before separating the microplastics to remove the coating of organic matter, 200 mL of hydrogen peroxide (30%) was added to 200 g of each sample and placed in a shaker at room temperature until the bubbles caused by the reaction disappeared. The samples were stirred several times every day so that the settled organic matter along with the mineral particles on the floor of the beaker were well exposed to the solution. After mixing the samples, the beakers were covered with aluminum foil. After the disappearance of the bubbles, the samples were diluted with distilled water and after settling the suspended solids, the supernatant was passed through the filter paper\u0026thinsp;\u0026gt;\u0026thinsp;2 \u0026micro;m (S\u0026amp;S5893) with the help of a vacuum pump and under pressure. This part of the work was repeated twice. The remaining particles were washed on filter paper with distilled water and returned to the beaker containing sediment. Then, the samples were placed in an oven at 60\u0026deg;C to dry, so that the remaining water in the containers does not change the density of the added salt. The sodium iodide (NaI) salt solution was used to separate microplastics from the sediments. To prepare this solution, about 1200 g of anhydrous sodium iodide powder (Sigma Aldrich, purity\u0026thinsp;\u0026gt;\u0026thinsp;97%) was dissolved in one liter of distilled water. This solution was stirred regularly until the complete dissolution of the salt. The density of the prepared solution was more than 1.6 g L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, which was obtained with the help of a glass pycnometer (Densitometer: 25 mL). 150 mL of the prepared solution was added to each sample and stirred gently for at least 5 min. Then the samples were kept without movement for 24 h. After that, the supernatant of the solution was moved on the filter paper and filtered under vacuum with pressure. Then, the filter along with the separated microplastics was stored in glass culture containers (Petri dish). These steps were repeated two times to achieve the maximum percentage of microplastics recovered from the sediment samples. The filter paper containing the sample was dried at room temperature and the particles on the filter were transferred to the petri dishes with the help of a laboratory brush (made of natural hair). To identify the microplastics, a Raman microscope was used.\u003c/p\u003e \u003cp\u003eThe MPs were characterized using a stereo (binocular) microscope. The microplastic particles were counted using a 250 \u0026micro;m diameter needle and a stereo optical microscope (binoculars) with a maximum magnification of 100 times. The approximate size, shape and color of each particle were recorded after counting the microplastics of each sample.\u003c/p\u003e \u003cp\u003eStrict measures were strictly enforced during the work to ensure that contamination was avoided. To prevent contamination of samples, a glassy vacuum filtration system was used, and all solvents and solutions were filtered 3 times before use. All glassware and dissection tools were eluted with triple-filtered distilled water to reduce the potential risk of contamination. The blank analysis was also performed during sample preparation.\u003c/p\u003e"},{"header":"3. Results and discussions","content":"\u003cp\u003eBased on the samples obtained, the characteristics and details of microplastics of Chabahar, Bushehr and Hormozgan beaches were recorded in terms of color, size, type and abundance. Also, the size of microplastics (in micrometers) is defined in 4 ranges (100\u0026thinsp;\u0026le;\u0026thinsp;L\u0026thinsp;\u0026lt;\u0026thinsp;500) A, (500\u0026thinsp;\u0026le;\u0026thinsp;L\u0026thinsp;\u0026lt;\u0026thinsp;1000) B, (1000\u0026thinsp;\u0026le;\u0026thinsp;L\u0026thinsp;\u0026lt;\u0026thinsp;1500) C and (1500\u0026thinsp;\u0026le;\u0026thinsp;L\u0026thinsp;\u0026lt;\u0026thinsp;2000) D. According to the obtained results, the microplastics of Chabahar, Bushehr and Hormozgan beaches were all of fiber type, and in terms of color, black, blue and red colors were the most abundant, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u0026amp;Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAccording to Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, in Chabahar beach, microplastic samples were recorded at T1 and T4 sampling stations with a frequency of 35 pieces per kilogram of sediment more than other stations and at HP2 station with a frequency of 10 pieces per kilogram of sediment less than other stations. All the microplastics of Chabahar beach were fibers, but the color of the fibers was different. Comparing the color of the fibers of Chabahar beach, it can be said that the black fibers were the most abundant in T1, T2, T4, HP1 stations and the blue fibers were the most abundant in ST9, ST4, BP2, T5 stations. In two stations, HP2 and BP1, the frequency of fibers has been equal. In general, black fibers were more abundant in Chabahar region. In terms of size, the microplastics of Chabahar beach were mostly between 100 and 500 micrometers, which means that the stations often had small microplastics, which could indicate that the plastic particles remained in the environment for a long time and turned into smaller particles (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe microplastics data sampled from the Chabahar beach\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSt.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbundance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eShape\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e \u003cp\u003eColor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c11\" namest=\"c8\"\u003e \u003cp\u003eSize (\u0026micro;m)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParticle/Kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBlack\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBlue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eD\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eT5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHP1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHP2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eST9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eST4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBP2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBP1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows that in the Bushehr beach, the highest frequency of microplastic samples is related to station N2 (in the Bushehr beach) with a concentration of 45 pieces per kilogram of sediment. It is due to the proximity of this station to mangrove forests. Station N4 has the lowest abundance of microplastics in this region with an abundance of 20 pieces per kilogram of sediment (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). According to Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, all the microplastics of Bushehr beach were fibers, but the colors of the fibers were different. Comparing the fibers in Bushehr beach stations, it can be said that the fibers, like Chabahar beach, were mostly between 100 and 500 micrometers in size, and black- colored fibers were the most abundant in all stations. According to Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, station N2 had the highest frequency and station N4 had the lowest frequency of microplastics (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe data related to microplastics sampled from Bushehr beach\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSt.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eabundance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eShape\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e \u003cp\u003eColor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c11\" namest=\"c8\"\u003e \u003cp\u003eSize (\u0026micro;m)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParticle/Kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBlack\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBlue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eD\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAccording to Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, station Az3 on the coast of Hormozgan and in the vicinity of mangrove forests and the international wetland of Khor Azini, station Kh7 near Khamir port and station Ks11 near the unloading and loading dock of the special area of ​​the Persian Gulf, with a concentration of 30 pieces of microplastic per Kilogram of sediment was one of the most polluted stations in Hormozgan province. KS9 station also had the least pollution among other stations in this area. Figure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e also shows that the microplastics in this area are mostly in the form of black fibers, but in station KS11, the amount of black and red fibers are equally recorded and the amount of blue and black fibers in station KS8 were also equal, and the size of most of them is the same as in Bushehr beach stations and Chabahar (about 100 to 500 \u0026micro;m) (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe microplastics data of the samples of Hormozgan beach\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSt.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbundance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eshape\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c7\" namest=\"c4\"\u003e \u003cp\u003eColor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c11\" namest=\"c8\"\u003e \u003cp\u003eSize (\u0026micro;m)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParticle/Kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBlack\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBlue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eD\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKS2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKH12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKH16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAZ3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKH7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKS1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKS7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKS9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAZ1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAZ10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKS11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKS4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKS8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e compares the data obtained from this study with other similar studies. In this study, the amount of microplastics in sensitive coastal sediments of the PG\u0026amp;GO was calculated to be 665 particles/kg. The amount of coastal microplastics in the Sea of ​​Oman is 230 particles/kg, which is almost in the same range as the amount of microplastics in the study by Kor et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), but in that study, although the number of stations is less, the amount of microplastics has increased sharply. Also, the amount of microplastics on the shores of the Persian Gulf in this research was 435 particles/kg, which is less than the amount of microplastics on the shores of the Persian Gulf in 2023. Because over time, the amount of microplastics in water and coastal environments increased.\u003c/p\u003e \u003cp\u003eAll microplastics in this research are in the form of fibers, which shows that fibers are the most abundant microplastics on the shores of the PG\u0026amp;GO. According to Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e, in the investigation of microplastics in aquatic and coastal environments, the amount of fibrous microplastics is more than other forms of microplastics.\u003c/p\u003e \u003cp\u003eThe most common fiber samples are black fibers, like the ones studied by Sheikhi et al. (2023) and Hakim et al. (2020), and these fibers are particles from the wear of tires and roads. But the blue, red and other fibers can be wastes from fishing, recreational activities and the proximity of the beach to the sewage outlet and domestic and industrial effluents in this area.\u003c/p\u003e \u003cp\u003eAccording to the Raman spectra, polyethylene terephthalate, nylon, and polystyrene were the most common types of polymers in plastics. These polymers were similar to the polymers studied by Sheikhi et al. (2023) and Kor et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), but the variety of polymers in the study by Hakim et al. (2020). In general, the distribution and variety of polymers in different stations indicate different sources of microplastics in this area.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of microplastics data of this study with those of other studies\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage Abundance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eShape\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eColor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSize\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eType\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e665 Particles /Kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100%Fibers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65.42%Black, 16.54% blue,\u003c/p\u003e \u003cp\u003e16.54% red,\u003c/p\u003e \u003cp\u003e1/5% white,\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100\u0026ndash;1000\u0026micro;m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePET, Nylon, PS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eThis work\u003c/p\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e546.7\u0026thinsp;\u0026plusmn;\u0026thinsp;172.6 Particles/Kg\u003c/p\u003e \u003cp\u003eat depths of\u003c/p\u003e \u003cp\u003e(0\u0026ndash;5cm:226.2\u0026thinsp;\u0026plusmn;\u0026thinsp;76.7)\u003c/p\u003e \u003cp\u003e(5\u0026ndash;15cm:47.1\u0026thinsp;\u0026plusmn;\u0026thinsp;16.1)\u003c/p\u003e \u003cp\u003e(0\u0026ndash;15cm:273.4\u0026thinsp;\u0026plusmn;\u0026thinsp;78.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55% fibers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40% Black\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e˂500 \u0026micro;m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePE, PS, PET, Nylon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSheikhi et al., 2023\u003c/p\u003e \u003cp\u003e(Persian Gulf)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efrom 138.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.5 to 930.3\u0026thinsp;\u0026plusmn;\u0026thinsp;49.1 particles /Kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29.9%Fibers \u0026amp; 32.9%fragments\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.9%White, 20%Blue, 16.1%Black,\u003c/p\u003e \u003cp\u003e12.3%Colorless, 7.5%Red, 5%Green \u0026amp; 10.5% other\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1000\u0026ndash;5000 \u0026micro;m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePE, PP, Nylon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eKor et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e\u003c/p\u003e \u003cp\u003e(Oman Sea)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e124 to 961 particles/100 g\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFragments, fibers and\u003c/p\u003e \u003cp\u003eFilms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eblack (64%), transparent (55.74%), and red (34.27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e250\u0026ndash;500 \u0026micro;m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75%: Tencel, Bemberg, PTFE, FEP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eHakim et al., 2020\u003c/p\u003e \u003cp\u003e(Indian Ocean)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe findings of this research showed that human activities, navigation and fishing can be important sources of microplastic pollution in the region.\u003c/p\u003e"},{"header":"4. Conclusion","content":"\u003cp\u003eA high abundance of microplastics in coastal sediments of the PG\u0026amp;GO (up to 45 pieces of microplastics per kilogram of sediment) was observed. These frequencies are highly variable spatially, highlighting the design of a precise local sampling strategy to capture sample diversity. The wide range of polymer types reflects the diversity of sources and the potential of traveling long distances for plastics. This work shows that local and regional sources are a more important factor that affects the abundance of microplastics and the types of polymers available. This calls for the need to further identify sources to inform development of waste management in the vicinity of vulnerable ecosystems, to further reduce the input of microplastic pollution. The presence of microplastics in all locations of these systems represents a major environmental concern for aquatic ecosystems. Further research is warranted to proactively mitigate potential consequences.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e \u003cp\u003e \u003cb\u003eEthical Responsibilities of Authors\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAll authors have read, understood, and have complied as applicable with the statement on \"Ethical responsibilities of Authors\" as found in the Instructions for Authors\u0026rdquo;.\u003c/p\u003e\u003cp\u003e \u003ch2\u003eEthical Approval\u003c/h2\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by the Iranian National Institute for Oceanography and Atmospheric Science with Grant number: 399-011-01-028-01.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAli Mehdinia: Conceptualization, writing \u0026ndash; review \u0026amp; editing, Funding acquisition, Zeinab Aghajani: Writing original draft, Methodology, Formal analysis, Data curation, Abbasali Zamani: Conceptualization Younes Khosravi: Software, Somayeh Navid: Experiments, Nima Navid: Experiments\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe current study was funded by Iranian National Institute for Oceanography and Atmospheric Science (INIOAS) (project grant number 399-011-01-028-01).\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eIf someone wants to request the data from this study should be contacted to corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAl-Salem, S. M., Uddin, S., \u0026amp; Al-Yamani, F. (2020). An assessment of microplastics threat to the marine environment: A short review in context of the Arabian/Persian Gulf, \u003cem\u003eMarine Environmental Research\u003c/em\u003e, 159, 104961.\u003c/li\u003e\n\u003cli\u003eCordeiro, C. A. M. M., \u0026amp; Costa, T. M. (2010). Evaluation of solid residues removed from a mangrove swamp in the S\u0026atilde;o Vicente Estuary, SP, Brazil. \u003cem\u003eMarine Pollution Bulletin\u003c/em\u003e, 60(10), 1762-1767.\u003c/li\u003e\n\u003cli\u003eCosta, M. F., Do Sul, J. A. I., Silva-Cavalcanti, J. S., Ara\u0026uacute;jo, M. C. B., Spengler, \u0026Acirc;., \u0026amp; Tourinho, P. S. (2010) On the importance of size of plastic fragments and pellets on the strandline: a snapshot of a Brazilian beach. \u003cem\u003eEnvironmental Monitoring and Assessment\u003c/em\u003e, 168, 299-304.\u003c/li\u003e\n\u003cli\u003eDerraik, J. G. (2002) The pollution of the marine environment by plastic debris: a review. \u003cem\u003eMarine Pollution Bulletin\u003c/em\u003e, 44, 842\u0026ndash;852.\u003c/li\u003e\n\u003cli\u003eDuis, K., \u0026amp; Coors, A. (2016). Microplastics in the aquatic and terrestrial environment: sources (with a specific focus on personal care products), fate and effects. \u003cem\u003eEnvironmental Sciences Europe,\u003c/em\u003e28(1), 2.\u003c/li\u003e\n\u003cli\u003eGarc\u0026eacute;s-Ord\u0026oacute;\u0026ntilde;ez, O., Castillo-Olaya, V. A., Granados-Brice\u0026ntilde;o, A. F., Garc\u0026iacute;a, L. M. B., \u0026amp; D\u0026iacute;az, L. F. E. (2019). Marine litter and microplastic pollution on mangrove soils of the Ci\u0026eacute;naga Grande de Santa Marta, Colombian Caribbean. \u003cem\u003eMarine Pollution Bulletin\u003c/em\u003e. 145, 455-462. \u003c/li\u003e\n\u003cli\u003eGermanov, E. S., Marshall, A. D., Bejder, L., \u0026amp; Fossi, M. C. (2018). Loneragan, N. R. Microplastics: no small problem for filter-feeding megafauna. \u003cem\u003eTrends in Ecology \u0026amp; Evolution\u003c/em\u003e. (2018); 33, 227-232.\u003c/li\u003e\n\u003cli\u003eHakim, L., Asmara, A. A., Priambodo, R.Y \u0026amp; Wong, Y J. (2023). Microplastic Pollution Profile in the Indian Ocean of the Southern Java Island, Indonesia, \u003cem\u003eEnvironmental Challenges\u003c/em\u003e, 100786, 2667-0100.\u003c/li\u003e\n\u003cli\u003eKor, K., Ghazilou, A., \u0026amp; Ershadifar, H. (2020). Microplastic pollution in the littoral sediments of the northern part of the Oman Sea. \u003cem\u003eMarine Pollution Bulletin\u003c/em\u003e, 155, 111166.\u003c/li\u003e\n\u003cli\u003eMaghsodian, Z., Sanati, A.M., Ramavandi, B., Ghasemi, A., \u0026amp; Sorial, G. A. (2021). Microplastics accumulation in sediments and Periophthalmus waltoni fish, mangrove forests in southern Iran, \u003cem\u003eChemosphere\u003c/em\u003e, 264(2\u003cspan dir=\"RTL\"\u003e(\u003c/span\u003e, 128543.\u003c/li\u003e\n\u003cli\u003eMehdinia, A., Dehbandi, R., Hamzehpour, A., \u0026amp; Rahnama, R. (2020). Identification of microplastics in the sediments of southern coasts of the Caspian Sea, north of Iran, \u003cem\u003eEnvironmental Pollution\u003c/em\u003e, 258(4)-113738.\u003c/li\u003e\n\u003cli\u003eNabizadeh, R., Sajadi, M., Rastkari, N., \u0026amp; Yaghmaeian, K. (2019). Microplastic pollution on the Persian Gulf shoreline: A case study of Bandar Abbas city, Hormozgan Province, Iran, \u003cem\u003eMarine Pollution Bulletin\u003c/em\u003e, 145, 536.\u003c/li\u003e\n\u003cli\u003eNaji, A., Azadkhah, S., Farahani, H., Uddin, S., \u0026amp; Khan, F. R. (2021). Microplastics in wastewater outlets of Bandar Abbas city (Iran): a potential point source of microplastics into the Persian Gulf. \u003cem\u003eChemosphere\u003c/em\u003e, 262: 128039.\u003c/li\u003e\n\u003cli\u003eNapper, I. E., \u0026amp; Thompson, R. C. (2016). Release of synthetic microplastic plastic fibres from domestic washing machines: Effects of fabric type and washing conditions. \u003cem\u003eMarine Pollution Bulletin\u003c/em\u003e, 112(1-2), 39-45.\u003c/li\u003e\n\u003cli\u003eSheikhi, H., \u0026amp; Mirzaei, R. (2023). Occurrence and abundance of macro, meso and microplastics along the coasts of the Persian Gulf (case study: Bushehr Province coast). \u003cem\u003eMarine Pollution Bulletin\u003c/em\u003e, 194, 115261.\u003c/li\u003e\n\u003cli\u003eStockin, K. A., Pantos, O., Betty, E. L., Matthew, D. M., Doake, F., Masterton, H., Palmer, E. I., Matthew, R. P., Sarah E. N., \u0026amp; Gabriel, E. M. C. (2021) Fourier transform infrared (FTIR) analysis identifies microplastics in stranded common dolphins (Delphinus delphis) from New Zealand waters, \u003cem\u003eMarine Pollution Bulletin\u003c/em\u003e, 173(2), 113084.\u003c/li\u003e\n\u003cli\u003eTian, L., Cheng, J., Ji, R., Ma, Y., \u0026amp; Yu, X. (2022). Microplastics in agricultural soils: sources, effects, and their fate, \u003cem\u003eCurrent Opinion in Environmental Science \u0026amp; Health\u003c/em\u003e, 25, 100311.\u003c/li\u003e\n\u003cli\u003eUddin, S., Fowler, S. W., \u0026amp; Saeed, T. (2020). Microplastic particles in the Persian Gulf\u0026ndash;a review on sampling and identification. \u003cem\u003eMarine Pollution Bulletin\u003c/em\u003e, 154, 111100.\u003c/li\u003e\n\u003cli\u003eYin, C. S., Chai, Y. J., Carey, D., Yusup, Y., \u0026amp; Gallagher, J. B. (2019). Anthropogenic marine debris and its dynamics across peri-urban and urban mangroves on Penang Island, Malaysia. \u003cem\u003eBioRxiv\u003c/em\u003e, 756106. https://doi.org/10.1101/75610.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Microplastics, Persian Gulf, Gulf of Oman, sediments, Pollution, fibers","lastPublishedDoi":"10.21203/rs.3.rs-6552495/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6552495/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAbundances and characteristics of microplastics were studied in the coastal area of the Persian Gulf and Oman Sea. Microplastics ranged from 10 to 45 particles per kilogram of sediment. Microplastics were in the size category of 100 \u0026micro;m to 2000 \u0026micro;m. The average concentration of microplastics in selected stations was 655 pieces/kg. In most of the transects, a negative slope of MPs was observed from coastal waters to deeper waters. Black fibers constituted 65.42% of the fibers and high-density polymers were dominant. Also, the type of polymers was identified using Raman analysis and polyethylene terephthalate (PET), nylon and polystyrene (PS) were the three main types of microplastic polymers in coastal surface sediments. In general, the findings reiterated the widespread presence of microplastics. In this study, the spatial outliers and the main deposition locations of microplastics were identified, and as a result, the places where future studies should be focused were determined.\u003c/p\u003e","manuscriptTitle":"Microplastic contaminants in the sediment of the north coasts of the Persian Gulf and Gulf of Oman","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-13 12:41:50","doi":"10.21203/rs.3.rs-6552495/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cbe3bdb3-6e5b-4b58-96d1-72e0ceb020e9","owner":[],"postedDate":"May 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":48319753,"name":"Earth and environmental sciences/Environmental sciences"},{"id":48319754,"name":"Earth and environmental sciences/Environmental sciences/Environmental chemistry"},{"id":48319755,"name":"Earth and environmental sciences/Environmental sciences/Environmental chemistry/Environmental monitoring"}],"tags":[],"updatedAt":"2025-06-30T08:38:55+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-13 12:41:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6552495","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6552495","identity":"rs-6552495","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}