Spatial distribution, morphological characteristics, and risk assessment of microplastics in the beach sediments of Odisha Coast, India

Despite the growing recognition of microplastic (MP) pollution in coastal environments, studies on their spatial distribution along the eastern coastline of India remain limited. The present study examined the prevalence and characteristics of microplastics (MPs) in beach sediments along the Odisha coast, India. Samples were collected from 34 distinct beach locations along the coastline, providing the most spatially extensive baseline dataset currently available for MPs contamination in the region. Additionally, the study evaluated associated environmental risks using multiple risk indices. The average abundance was 948±268 particles/kg. The results revealed spatial variability in MPs abundance across Odisha coast wherein the central coastal region exhibited highest mean concentration, meanwhile the southern region had lowest mean concentration, but the highest variability. The majority particles size ranged from 100-2000µm, with fibres (98.9%) being the predominant form followed by fragments and films. Major polymer types identified by micro-Raman spectroscopy were polyethylene terephthalate (PET), polypropylene (PP), polyethylene (PE) and polyester (PES). Polymer-induced hazard index (PHI) placed the sampling locations in risk categories IV and V, while pollution load index (PLIodisha-2.59) deemed the coast polluted. The potential ecological risk index (PERIodisha- 93206.5) indicated extreme danger. Meanwhile, in 32 places, RQ>1 indicated threat to the ecosystem. As one of the first large scale assessments of MPs along the Odisha coast, this study not only fills a critical regional data gap but also contributes towards the expanding global body of evidence, highlighting urgent policy and conservation responses to MPs pollution.

Highlights

• Evidence of MPs in 100% of sediment samples along the Odisha coastline

• Average MPs abundance estimated was 948 ± 268 particles/kg.

• Smaller MPs (<1,000 μm) were found predominant, and fibres were the most abundant polymer form.

• Polymer type analysis identified PET, PP, PE, PES, and PVC.

• Risk assessment indices indicate potential ecological risk, which needs to be monitored overtime.

1 Introduction

The excellent stability, durability, and beneficial physicochemical features of plastic materials have made them a vital component in a wide range of applications. By the year 2050, the global plastic production is projected to reach 902–1,124 million tons (Dokl et al., 2024). However, with the fact that most of the plastics ultimately end up in landfills, incinerated or disposed of inappropriately, plastic pollution has surfaced as a critical environmental issue globally (Dokl et al., 2024). As reported by OECD (2022), a mere 9% of plastic waste has been processed through global recycling mechanisms; however, 22% of the same has been improperly managed. Furthermore, it has been reported that 46% of plastic waste in India is either inadequately managed or uncollected, whereas 36% is allocated to landfills, 4% is subjected to incineration, and only 13% is processed through recycling (Borah et al., 2024). Plastics, when left in the environment over a longer time period, result in environmental degradation and decompose into smaller particles. Particles measuring less than 5 mm in size have been classified as microplastics (MPs) (Gupta et al., 2024; Shaji et al., 2024), which have become a notable environmental contaminant worldwide. MPs can be synthesised at a microscopic scale for incorporation into personal care products, detergents, and similar, referred to as primary MPs (Luan and Wang, 2024; Suteja et al., 2024). Alternatively, secondary MPs arise from degradation of larger plastic items in the environment due to various environmental factors (Zhang et al., 2024). Understanding the distribution patterns of MPs across various regions and environmental matrices is essential for a rigorous evaluation of their pollution magnitude and the associated environmental risks. MPs research originated within the marine environment (Al-Tarshi et al., 2024; Suteja et al., 2024; Thepwilai et al., 2021; Zhang et al., 2024); however, with growing awareness, the research further expanded to freshwater systems, including rivers and lakes (Choudhary et al., 2025; Kumar et al., 2024) and soils (Li et al., 2024; Liu et al., 2022; Zhou et al., 2023). More recently, the studies have also been documented with regard to atmospheric deposition and biota (Phan et al., 2024; Prarat et al., 2024).

Beaches represent a crucial ecosystem that constitutes nearly 50% of the global ice-free ocean coastline, functioning as a social-ecological system (Mandal et al., 2023). Sandy beaches, in particular, serve as essential habitats for a diverse array of flora and fauna, requiring significant consideration in relation to the pollution caused by MPs (Borah et al., 2024). The occurrence and migration patterns of MPs on beaches are characterised by a multitude of factors, including waves, currents, tides, winds, geomorphology, and human activities, all of which may exhibit variability across distinct geographical regions (Flores-Ocampo and Armstrong-Altrin, 2023; Sunitha et al., 2021; Thepwilai et al., 2021). Tourist beaches are particularly susceptible to heightened risks of MPs pollution, resulting from the mass influx of visitors and the concomitant human activities, including littering and various recreational actions (Mandal et al., 2023; Shaji et al., 2024). Several studies indicate their propensity to concentrate in sediment owing to their buoyant characteristics (Ghanadi et al., 2024; Kumar et al., 2024; Luan and Wang, 2024; Grini et al., 2024). This will ultimately lead to hotspots in areas with considerable human activities, including tourist beaches and urban coastlines. Size, morphology, and polymer content of MPs influence their ecological interactions with marine organisms (Phan et al., 2024; Shaji et al., 2024). Ingestion of MPs can result in the formation of physical blockages, a decrease in the efficiency of feeding, and the introduction of toxic chemicals into the food web (Ghosh et al., 2021; Phan et al., 2024). Furthermore, long-term implications of MP pollution include potential alterations to habitat structures, disruptions of nutrient cycling, and impacts on species resilience.

As noted by UNEP (The Hindu, 2021), India contributes approximately 0.6 million tonnes of plastic waste to the ocean annually. Plastic deposition as well as accumulation on shorelines and coastal sediments have shown a consistent increase over recent decades (Luan and Wang, 2024; Shaji et al., 2024; Soursou et al., 2024). Notwithstanding the increasing awareness associated with the prevalence and adverse effects of MPs on coastal environments, there exists a knowledge gap on the MPs distribution along the eastern coastline of India, particularly concerning the Odisha coast (Veerasingam et al., 2020). The extensive coastline of Odisha along the Bay of Bengal is characterised by a variety of ecological habitats, significant fishing activities, growing coastal tourism, and the presence of industrial centres and ports. Moreover, the region demonstrates an increased vulnerability to recurrent cyclones and riverine discharges, which further facilitate the transport and redistribution of plastic debris within the coastal and sedimentary ecosystems.

This research focuses on the Odisha coastline, providing a more comprehensive investigation compared to previous studies along the Bay of Bengal coast (Mandal et al., 2023; Patchaiyappan et al., 2021). In contrast to earlier studies that have carried out analysis from selected locations, the present research covers 34 different beach locations, providing the most spatially extensive baseline dataset to date, for MPs contamination along the Odisha coast. It also enables benchmarking the MPs contamination levels in the region against other national and international coastal zones, facilitating the development of region-specific mitigation strategies. Additionally, the study provides deeper insights into MPs contamination by evaluating various environmental risk metrics. These include calculating the PLI (pollution load index), PHI (polymer hazard index), PERI (potential ecological risk index), and RQ (risk quotient) for each of the locations within the study area. This holistic approach renders significant insights into the extent of MPs contamination and associated ecological risks along the coast of Odisha.

2 Materials and methods

2.1 Study location

Odisha is a state situated on India’s eastern coast, bordered by the Bay of Bengal to the east, Chhattisgarh to the west, and Andhra Pradesh to the south. It ranks 12th in population and 9th in area, with 485 kilometres of coastline, stretching along the Bay of Bengal. Popularly known as the hexa deltaic region, the coastal plain of Odisha is a cluster of numerous deltas of different sizes and forms created by major rivers including the Subarnarekha, the Mahanadi, the Baitarani, the Rushikulya, the Budhabalanga, and the Brahmani.

In this current study, sample locations of MPs selected include 34 different beaches extending from north to south of the Odisha coast, lying within 19°08′N and 21°33′N latitude and 84°48′E and 87°18′E longitude (Figure 1). The study area spans around 409 km, from Chaumukh beach in the north to Ramayapatnam beach in the south, capturing approximately 85% of Odisha’s total coastal stretch. The selected beaches fall under the following districts: Balasore (BS), Bhadrak (BD), Kendrapara (KP), Jagatsinghpur (JT), Puri (PR), and Ganjam (GM) (Supplementary Table S1). The selected locations include tourist beaches, industrial zones, and remote beaches with minimal human interference, allowing a thorough investigation of human impact on MPs deposition.

Figure 1

Figure 1. Beach sediment sampling locations along the Odisha coast, India.

2.2 Collection of samples

The sediment samples were collected between December 2021 and January 2022, from the high tide line region where MPs are expected to accumulate because of wave action (Shaji et al., 2024). Three sampling sites were chosen at each beach location, with a distance of approximately 100 m between them. Using a 0.5 m × 0.5 m quadrant sample technique, the top 1–2 cm layer was collected, using a stainless steel spatula. The collected samples were transferred to glass bottles to be transported to the laboratory for further analysis (Dutta et al., 2022).

2.3 Extraction and analysis of MPs

The collected sediment samples were oven dried at 60 °C for 24 h and sieved through a 5-mm mesh. MPs extraction was performed with the use of a density separation process wherein supersaturated zinc chloride (ZnCl₂) solution (1.5 g/cc) was mixed thoroughly with the sediment samples (20 g) in a 100-mL glass beaker. This study used ZnCl₂ as it has been reported to have achieved maximum MPs recovery (Sahoo, 2024; Shaji et al., 2024). The mixture was stirred with the use of a magnetic stirrer so as to dislodge any MPs trapped between sand particles and left to stand undisturbed for 5 h (Pradhap et al., 2023). Following this, the supernatant, which contained the suspected MPs, was collected by the overflow method (Le et al., 2023), filtered through Whatman glass fibre filter paper (GF/C, 1.25 μm), and the process was repeated thrice to ensure efficient extraction of MPs from the samples. The suspected MPs on the filter paper were further analysed under a stereo-zoom microscope (SZB-65A, Quasmo, India) supported with a digital camera and an image analysis software (ULTRACAM 3.8) to determine the physical properties (shape, size, and colour).

MPs were first visually inspected and categorised based on their morphology (fibre, fragment, film, and bead), and size was classified into for sub groups, namely (1) 50–500 μm, (2) 500–1,000 μm, (3) 1,000–2,000 μm, and (4) greater than 2,000 μm. Polymer composition of visually discernible MPs was determined using micro-Raman spectroscopy (Renishaw, UK). The analysis was carried out by keeping the suspected MPs on fresh filter paper using stainless steel tweezers. Furthermore, the spectral data were acquired within a range of 100–3,000 cm⁻¹, with a scan duration of 30 s. The resultant spectra were matched with established polymer library references to ascertain the MPs’ polymer composition. Furthermore, the polymer identity was validated by cross-referencing with an open-source database (Open Specy), and only those having a matching factor equal to or higher than 0.6 have been considered (Cowger et al., 2021). This MPs extraction and analysis procedure was adopted from the study by Shaji et al. (2024).

2.4 Environmental risk assessment

Based on parameters, which include PLI, PHI, and PERI, a risk assessment has been conducted comprehensively. PLI has been calculated based on the MPs concentration at the study location, PHI elucidates the chemical toxicity linked to the specific types of MP polymers present at the study location, and PERI quantifies the degree of contamination caused by MPs in the sediments.

PLI is a standardised method for assessing the magnitude of pollution (MPs) in the identified study location based on the concentration of MPs present. Contaminant Factor (CF) (Equation (1)) and PLI have been suggested by Tomlinson et al. (1980) as a metric to evaluate the degree of pollution in natural ecosystems. PLI of a beach was computed as follows:

$\begin{array}{ll}C{F}_i=\frac{C_i}{C_{\mathit{oi}}}& (1)\end{array}$

$\begin{array}{ll}\mathit{PLI}=\sqrt[n]{C{F}_i}=C{F}_i& (2)\end{array}$

$\begin{array}{ll}\mathit{PL}{I}_{\mathit{\text{coast}}}=\sqrt[n]{\mathit{PL}{I}_1\times \mathit{PL}{I}_2\times \mathit{PL}{I}_3\times \dots \mathit{PL}{I}_n}& (3)\end{array}$

The sampling location is represented by “i,” MP concentration at the respective sampling location is denoted as “C_i^,” and the minimal baseline concentration is represented as C_oi (Forero-López et al., 2024; González-Curbelo et al., 2025; Soursou et al., 2024). In the absence of previous background data, the lowest MP concentration observed in this study has been taken as the reference for the minimal baseline level (Soursou et al., 2024). PLI of each beach sample would be equal to CF_i, if MPs were considered as a whole (Equation 2, n = 1) (Picó et al., 2021). PLI of respective locations was used to calculate the PLI for the Odisha coast (PLI coast) using Equation 3 (n = 34). Sampling locations with PLI > 1 are classified as polluted.

PHI was calculated according to Equation (4):

$\begin{array}{ll}\mathit{PHI}=\sum P_n\times S_n& (4)\end{array}$

Here, Pn denotes the proportion of specific MP polymer type identified at each sampling location, and Sn denotes the hazard score for polymer type as outlined in Lithner et al. (2011). In line with the UN Globally Harmonised System (GHS), PLI values were categorised into four levels (I–IV) and PHI values were categorised into five levels (I–V) of increasing hazard as outlined in Supplementary Table S3.

Subsequently, PERI is calculated using Equations (5) and Equation (6):

$\begin{array}{ll}{E}_i=T_i\times C{F}_i& (5)\end{array}$

$\begin{array}{ll}\mathit{RI}=\sum _{i=1}^n{E}_i& (6)\end{array}$

In this context, T_i represents the polymer toxicity coefficient, E_i represents the possible ecological danger from a specific MP polymer, and RI depicts the cumulative ecological risk.

2.5 Risk quotient (RQ)

Risk quotient (RQ) was computed by considering MP abundance and their toxicity level to specific marine organisms (Shaji et al., 2024; Soursou et al., 2024). The ratio of the MPs Measured Environmental Concentration (MEC) to Predicted No-effect Concentration (PNEC) at a particular location is known as the Risk Quotient. The No Observed Effect Concentration (NOEC) of the most sensitive endpoint (Arenicola marina: metabolic rate, 5.4 × 10⁵ particles/kg) was multiplied by an assessment factor (AF) of 1,000. Subsequently, 540 particles/kg was determined as PNEC for sediments in this study. A result of 540 particles/kg was obtained. When the RQ < 1, there is no immediate environmental concern; when it is >1, there may be an environmental risk (Everaert et al., 2018).

2.6 Statistical analysis

MP concentration in sediment is expressed as the number of MPs per gram of dry mass. A comparative analysis of MP concentration across the study location was carried out statistically. Shapiro–Wilk normality test has been performed to check the concentration distribution of MP across the study locations, wherein the coast was divided into three regions: North, Central, and South. Furthermore, one-way ANOVA test has been carried out, followed by a Tukey post-hoc test for region-wise comparison. All data analysis and graphs have been prepared using Microsoft Excel and Origin Pro 2020 software.

2.7 Quality control

Necessary measures have been administered to reduce the likelihood of contamination. All laboratory glassware, sampling apparatus, sieves, and containers were rinsed with Milli-Q water before use. During the experiments, the test beakers were always covered with aluminium foil to avert any possible cross-contamination. All reagents used for this study have been filtered using Whatman GF/C before the analysis. Stainless steel tweezer was used for handling the filters during quantitative and qualitative analysis. Usage of plastic materials has been avoided to the best possible extent throughout the study. During the sample processing and analysis, a cotton lab coat along with nitrile gloves has been worn, and working surfaces have been consistently cleansed using ethanol. Additionally, procedural blank tests were run in tandem with analysis samples to evaluate cross-contamination during laboratory analysis. During the sample collection and analysis, three glass beakers containing Milli-Q water were utilised as blank samples. Following the filtration of control samples, the test filter papers were subsequently analysed using a stereo zoom microscope. The total count of MPs has been corrected by deducting any blank values from it in each of the tested samples.

3 Results

3.1 MPs spatial distribution and abundance

The concentration of MPs exhibited significant variation throughout the sampling locations (Figure 2), ranging between 350 particles/kg and 1,650 particles/kg, with an average abundance along the Odisha coast calculated at 948 ± 268 particles/kg. The maximum and minimum concentrations of MP particles were recorded at locations S30 (1,650 particles/kg) and S13 (350 particles/kg), respectively. It was observed that the MPs concentration at 19 of the 34 sampling locations was greater than the average concentration and follows the order S30 > S1 > S34 = S9 = S8 > S11 > S10 = S6 = S4 > S26 > S32 > S20 > S15 > S18 > S7 > S5 > S2 > S31 > S3. A greater number of locations with MPs abundance higher than the estimated average falls in the BS district, followed by the districts GM, PR, and JT. The BS district had an average MPs concentration of 1,106 particles/kg, with maximum concentration (1,350 particles/kg) being observed at location S1. In the GM district, the mean particle concentration was 985 particles/kg, with location S30 showing the highest concentration (1,650 particles/kg). In the PR district, location S20 recorded the highest MPs concentration (1,050 particles/kg), and the average concentration estimated was 806 particles/kg. The JT district had a mean concentration of 850 particles/kg, with the S11 location showing the highest MP abundance at 1200 particles/kg. While in districts BD and KP, the highest concentration estimated were 1,150 particles/kg and 600 particles/kg, respectively.

Figure 2

Figure 2. Spatial variability of MPs in beach sediments along the Odisha coast.

3.2 MPs morphological characterisation: shape, colour, and size distribution

The shape analysis of MPs in this current study identified a substantial occurrence of fibres in beach sediments of the Odisha coast. Notably, fibres were found in a proportion of 98.9%, followed by fragments (0.63%) and films (0.47%) from all the sediment samples. The microscopic images of the identified MPs are depicted in Figure 3.

Figure 3

Figure 3. Microscopic image of MPs identified in beach sediments along Odisha coast (a,c,e,d) fibre; (b) film; (f) fragment.

Black (36.78%) and transparent/white (28.33%) coloured particles were dominant among the MPs detected, followed by blue (10.02%), red (7.04%), green (6.89%), yellow (5.95%), and pink (5.01%) (Figure 4). This finding aligns with similar research conducted in coastal areas, such as muddy shores of the Gulf of Khambhat (Rabari et al., 2023), sediments along the Gulf of Thailand (Thepwilai et al., 2021), and sea bed sediments of Bay of Bengal (Dhineka et al., 2022), according to which there was also a high percentage of black and transparent MP particles.

Figure 4

Figure 4. MPs color variation in beach sediments along the Odisha coast.

The MPs have been classified into four size groups: (1) 50–500 μm, (2) 500–1,000 μm, (3) 1,000–2,000 μm, and (4) greater than 2,000 μm. MPs ranging from 500 to 1,000 μm constituted the largest proportion (37.27%), followed by 1,000–2,000 μm (31.99%) and 0–500 μm (16.46%). The least proportion of MPs was observed in the size range >2,000 μm (14.29%). Overall, smaller MPs (<1,000 μm) constituted the majority, making up approximately 54% of the total particles. Nevertheless, a relatively significant proportion (46.3%) of MPs were found in size >1,000 μm as well.

A similar higher proportion of large-sized MPs has been reported by Mandal et al. (2023) along the eastern coast of India, wherein 36% of MPs have been identified in the size range of 1,000–2,000 μm. Figure 5 illustrates the percentage variation of MPs within each size group among the sampling locations.

Figure 5

Figure 5. Size variation of MPs in beach sediments along the Odisha coast.

3.3 Polymer composition

Figure 6(i) confirmed the presence of polyethylene terephthalate (PET) polymer as evidenced by peaks at 1,310 cm⁻¹ indicating CH₂ twisting, 1,615 cm⁻¹ associated with the C=C stretching vibrations of the benzene ring, and 1,730 cm⁻¹ corresponding to C-O stretching (Chakraborty et al., 2023). From Figure 6(ii), the peaks at 977 cm⁻¹ (C-C stretching), 1,155 cm⁻¹ (C-C stretching, C-H bending), 1,330 cm⁻¹ (CH₂ twisting), and 1,460 cm⁻¹ (CH₂ and CH₃ bending) confirmed the presence of polypropylene (PP) polymer (Nava et al., 2021). Further peaks at 1,062 cm⁻¹ (C-C stretching), 1,170 cm⁻¹ (C-H bending), 1,295 cm⁻¹ (CH₂ twisting), and 1,417 cm⁻¹ (CH₂ twisting), as depicted in Figure 6(iii), were linked to polyethylene (PE) (Chakraborty et al., 2023). Presence of polyester (PES) was confirmed with peaks at 633 cm⁻¹, 861 cm⁻¹ (aromatic ring deformation), 1,062 cm⁻¹ (C-C stretching), 1,334 cm⁻¹ (CH₂ twisting), 1,615 cm⁻¹ [C-C stretching (ring)], and 1,729 cm⁻¹ (C-O stretching), as outlined in Figure 6(iv) (Chakraborty et al., 2023; Nava et al., 2021). Progressing to Figure 6(v), the spectral peaks at 795 cm⁻¹ (ring deformation), 1,001 cm⁻¹ (C atoms stretching), 1,155 cm⁻¹ and 1,390 cm⁻¹ (CH bending), and 1,583 cm⁻¹ (C-C stretching) are characteristic of polymer polystyrene (PS) (Dhineka et al., 2022; Nava et al., 2021). Meanwhile, the peaks at 838 cm⁻¹ (C-Cl stretching), 1,066 cm⁻¹ (C-C stretching), 1,316 cm⁻¹ (CH₂ twisting), and 1,498 cm⁻¹ (C-C stretching) in Figure 6(vi) denoted polyvinyl chloride (PVC) (Nava et al., 2021). Along with this, smaller concentration of Nylon was also detected.

Figure 6

Figure 6. Raman spectra of identified polymers.

Micro-Raman spectroscopy of the identified MPs samples along the Odisha coast indicated the presence of seven polymer types, with PET being the most prevalent, constituting 34% of the total identified polymers represented in Figure 7. Other predominant polymer types observed were PP, PES, and PE, comprising 21, 17, and 15%, respectively. PVC, PS, and Nylon were also found in lower concentrations, accounting to 5, 6, and 2%, respectively, of the total identified polymers. The polymer types PET and PES, along with nylon, are found in abundance in the BS district, while the districts BD and KP are abundant in PP and PE. PS was found to be more prevalent in the PR and JT districts, while results from the GM district identified the presence of PVC. Studies conducted by Ghanadi et al. (2024) and Lenz et al. (2023) in coastal areas of New Zealand and Northern Germany, respectively, have reported PET as the predominant polymer type in beach sediments. PP was seen in greater concentrations at the muddy coasts of the Gulf of Khambhat (Rabari et al., 2023), followed by PS, PET, PE, and PVC.

Figure 7

Figure 7. MPs polymer composition along the Odisha coast.

3.4 Risk assessment

MPs are made up of a wide variety of polymers that are synthesised through the process of polymerisation processes, which in many cases may not be entirely complete, leaving behind unreacted or residual toxic monomers and hazardous additives. This highlights the need for risk assessment, as MPs have been observed to be consumed by a wide variety of aquatic species, transferring toxic chemicals across trophic levels. The MPs Hazard index calculated along the Odisha coast varied from 200 to 334,067. Based on the PHI values, nine sampling locations (S1, S4, S5, S21, S22, S23, S25, S27, and S28) were categorised under risk category V (i.e., PHI>1,000), indicating a severe pollution threat. Meanwhile, all other sampling locations fell under the risk category IV (PHI between 100 and 1,000). The exceptionally high PHI can be due to the presence of toxic polymers such as PVC and PS, having a very high hazard score due to their potential to leach endocrine-disrupting chemicals and other hazardous additives (Lenz et al., 2023; Liang et al., 2024; Pan et al., 2021). Comparable results have been documented in earlier research along the Bay of Bengal and the Arabian Sea, where high PHI values were associated with industrial discharges and urban runoff (Dhineka et al., 2022; Gupta et al., 2024).

Furthermore, risk assessment of MPs throughout the Odisha coast utilising PLI indicated that all the study locations exhibited PLI ≥ 1 (Figure 8a), signifying that they were categorised as contaminated. The highest PLI (4.7) was recorded at location S30, signifying a fairly greater extent of pollution relative to other assessed locations (Soursou et al., 2024). Simultaneously, S13 displayed the lowest PLI (1), signifying reduced pollution levels. It shall be noted that despite Puri being the most popular tourist beach in Odisha, receiving greater tourist pressure throughout the year, the PLI was comparatively lower. This is in line with the findings reported in the previous study by Barik et al. (2024) on beach litter pollution along the Odisha coast. A lower PLI at Puri suggests a more effective implementation of environmental regulations, including coastal zone management strategies. Moreover, risk level categories proposed by EU GHS (Supplementary Table S2) classify all locations as Category I, with a PLI of less than 10.

Figure 8

Figure 8. Distribution of (a) PLI and (b) RQ for sediments along the Odisha coast.

Considering the PERI of MPs, 22 sampling locations marked a value >1,200, indicating an “extreme danger” category. The calculated average PERI for the Odisha coast (PERI_odisha) was 93206.5. Previous research on ecological risk posed by MPs in coastal environments has reported similarly high PERI values, particularly in regions subjected to heavy anthropogenic pressure, such as the Pearl River Delta in China (PERI = 105,000) and the Mediterranean Sea (PERI = 87,000) (Pan et al., 2021; Soursou et al., 2024).

Meanwhile, RQ was computed based on the obtained results by incorporating the PNEC derived from ecotoxicity investigations. Regarding RQ, among the examined areas, 32 exhibit RQ > 1 (Figure 8b), signifying a “risk” to the environment. This indicates a probable likelihood that the MPs concentration in these areas is higher than the acceptable level. The chances of “high risk” (RQ > 1) are approximately 94% along the Odisha coast, necessitating vigilant monitoring of these areas henceforth.

4 Discussion

4.1 Abundance and morphological characteristics of MPs

The results of this study indicate that MPs are widely distributed in the beach sediments, with notable concentrations detected in all analysed samples. The one-way ANOVA test indicates a significant difference in the mean MPs concentration between the north, central, and south regions (F = 5.11, p = 0.012) (Supplementary Table S5). This indicates that the geographical location has a significant influence on the MPs distribution along the Odisha coast. The Tukey post hoc test further demonstrated that the south region (mean = 860.87 particles/kg) significantly differs from the central region (mean = 1212.5 particles/kg, p = 0.028), but not from the north region (mean = 1085.71 particles/kg) (Supplementary Table S5). The central region, having the highest average concentration, did not significantly differ from the northern zone, indicating potentially similar sources or transport paths. This trend may be ascribed to regional variations in human activity, encompassing population density, tourism impact, industrial effluents, and fishing methods (Bobchev et al., 2024; Dowarah and Devipriya, 2019; Jeyasanta et al., 2020). A boxplot visualisation (Supplementary Figure S1) further demonstrates the mean MPs concentration across the north, central, and south regions of the Odisha coast. These locations of high MPs concentration are relatively well-known beaches popular for frequent tourist visits, fishing, and various recreational activities. Furthermore, rivers are significant pathways for transporting MPs from inland areas (urban litter, agricultural plastic waste, industrial effluents, etc.) to the ocean (Choudhary et al., 2025). The flow is slowed by its confluence with the sea, which results in pollutants and sediments settling (Shaji et al., 2024). As a result, pollutants from inland sources may end up in the coastal zone. Location S1 is a confluence point of the river Subarnarekha into the Bay of Bengal, which could possibly be attributed to the elevated MPs concentration at this region. The findings of this current study thereby indicate that locations proximate to urban agglomerations, industries, or regions with intensive anthropogenic activities exhibited notably higher MPs concentration. This also indicates localised environmental pollution stress with potential adverse effects on marine organisms. The majority of locations in the present study had reported remarkably higher MPs concentration, indicative of significant environmental and ecological challenges, pointing to extensive pollution sources and potential harm to the marine biota. Conversely, beaches located far from urban areas, or with fewer nearby pollution sources, such as industries or heavily populated areas, will have lower MPs inputs (Yaranal et al., 2021). These factors could have possibly contributed to lower MPs concentration in locations S13 and S27. Direct comparisons between the MPs data and the body of previous literature are often challenging due to the varied sampling approaches, extraction techniques, and data presentation styles (Sahoo, 2024). Nevertheless, Supplementary Table S5 provides an overview of studies analogous to the present research.

The concentration of MPs in the sediments in this investigation has been comparable to that stated by Bhattacharya and Chanda (2023), higher than Dowarah and Devipriya (2019) and Patchaiyappan et al. (2020) and lower than Le et al. (2023) and Sunitha et al. (2021). The increased concentration of MPs along coastline can be linked to substantial tourists, continual fishing operations, insufficient solid waste management approaches, and coastal urbanisation (Liang et al., 2024; Phan et al., 2024; Prarat et al., 2024). Moreover, MPs can be transported from adjacent urban areas and rivers to coastal regions by wind and ocean currents. The aggregation of MPs in sediments can also be influenced by plastic debris that is left on beaches or carried ashore by ships (Soursou et al., 2024; Yaranal et al., 2021; Zhang et al., 2024). Various physical factors, including sunlight and wave action, can induce the disintegration of larger plastic objects such as bottles, plastic bags, and fishing gears over time (Bhattacharya and Chanda, 2023). This fragmentation process leads to the formation of smaller MP particles, which subsequently settle into beach sediments. Furthermore, the MPs distribution along the Odisha coast was also likely to be influenced by several water dynamics such as tides, ocean currents, and seasonal changes like monsoons (Veerasingam et al., 2020). These factors contribute towards deposition and transport patterns of MPs, which could be contributing to higher concentrations in less frequented beaches such as S4, S6, S8, S26, and S34. MPs studies conducted along the coastal sediments of Bangladesh (Samrat Hossain et al., 2024) also reported that water dynamics can considerably influence MPs dispersion.

The increased concentration of fibre-shaped MPs in beach sediments can be ascribed to multiple factors, including significant sources from the textile industry (synthetic fibres from clothing), fishing nets, ropes, and gears, effluent from the various industries, including the production and processing of synthetic fibres, etc. (Gupta et al., 2024; Sunitha et al., 2021). Additionally, municipal sewage discharges, primarily from laundry activities, release substantial amounts of fibrous MPs into inland water sources (Shaji et al., 2024). These inland waters can act both as temporary sinks where MPs accumulate in sediments or remain suspended for varying periods and as transport pathways, conveying MPs via rivers and streams from urban areas to the ocean (Goswami et al., 2021; Gupta et al., 2024). Most prior research on beach sands indicated a prevalence of fibres relative to fragments and films. The studies carried out on the south east coast of India (Jeyasanta et al., 2020; Kaviarasan et al., 2022; Sahoo, 2024), the north east coast of the Arabian Sea (Gurjar et al., 2023), the Mediterranean coast transect (Soursou et al., 2024), the south coast of the Yellow Sea, and China (Luan and Wang, 2024) have all reported similar results. Furthermore, sediments from the Arabian Sea shelf indicated over 90% fibrous MPs (Gupta et al., 2024), aligning with the findings of the current study. This similarity can be attributed to comparable source types (domestic wastewater rich in synthetic fibres and intense aquaculture/fishing practices) in both the regions. The second most prevalent shape identified was fragments which originates from disintegration of bigger plastic particles, owing to environmental degradation. Further MP films can originate from disintegration of large plastic products including single-use bags, packaging materials, food wrappers, etc. (Al-Tarshi et al., 2024; Choudhary et al., 2025; Ghanadi et al., 2024). However, contrary to the dominance of fibres in beach sediments fragments are commonly reported shapes in the Marina beach, India (Venkatramanan et al., 2022), Kish Island, Persian Gulf (Petrovic et al., 2022), and Mumbai coastline, India (Dutta et al., 2022).

Variations observed in MPs statistics across various geographies and research findings result from a complex interplay of factors, including differences in pollution sources, environmental and climatic conditions, research methodologies, geographic and geomorphologic features, human activities and management practices, temporal variations, and socioeconomic influences (Flores-Ocampo and Armstrong-Altrin, 2023; Sunitha et al., 2021; Thepwilai et al., 2021). Urbanisation, industrial activity, hydrodynamic conditions, sediment types, waste management practices, and beach clean-up efforts all contribute to these variations (Karthik et al., 2018). Additionally, inconsistencies in sampling techniques, analytical methods, and definitions further complicate comparisons (Bobchev et al., 2024; Randhawa, 2023).

The black MP particles found in abundance in the sediments are a result of multiple sources, including synthetic textiles, fibres from fishing and maritime equipment, household items, urban wastewater, etc. (Atlantic et al., 2024; Gurjar et al., 2023). The majority of the white- and blue-coloured particles seen in this present study may have originated mostly from fishing nets, that commonly manufactured in colours such as blue, white, or translucent (Gupta et al., 2024; Gurjar et al., 2023). Furthermore, coloured particles may originate from ropes, shredded clothing, and urban plastic garbage, while white particles may also originate from plastic carry bags, PET bottles, and other consumer goods (Petrovic et al., 2022; Samrat Hossain et al., 2024). Certain fibres, especially those appearing blue, exhibited discolouration or transparency within the sediments. This is a sign of photooxidative degradation, brought on by extended exposure to the marine environment (Luan and Wang, 2024).

As observed in the present study, the prevalence of small-sized MPs in beach sediments also indicates several key environmental and pollution dynamics (Mandal et al., 2023). It suggests significant degradation and fragmentation of larger plastic debris, likely as a result of extended exposure to UV or mechanical abrasion from waves or microbial activity (Choudhary et al., 2025; Gupta et al., 2024). This abundance also points to substantial local and regional sources of primary MPs, such as synthetic fibres from clothing, entering the marine environment through wastewater discharges and runoff. Additionally, it is highly likely that the smaller MPs are more readily transported and redistributed by hydrodynamic processes, leading to their widespread occurrence across diverse sediment layers (Gurjar et al., 2023). This abundance of small-sized MPs highlights potential ecological risks, as these particles are more readily ingested by a wide range of marine organisms (fish, molluscs, lobsters, shrimps, crabs, etc.) (Phan et al., 2024). In addition to detrimental impacts on the physiological activity of these organisms, the MP particles can get bioaccumulated and eventually result in biomagnification across the food chain (Bhattacharya and Chanda, 2023; Prarat et al., 2024). This further emphasises the potential harmful effects on human health through dietary exposure (Sekar et al., 2024).

4.2 Polymer composition

The elevated PET concentration in coastal sediments can be attributed to multiple interrelated factors. Coastal regions generally undergo heightened urbanisation, tourism, and population density, resulting in elevated usage of PET items, including bottles and packaging, thereby producing additional waste (Robin et al., 2020; Venkatramanan et al., 2022). Inadequate techniques of waste management in these areas frequently lead to inappropriate disposal, permitting PET to reach the marine ecosystem. Furthermore, stormwater runoff can transport plastics from metropolitan regions into adjacent coastal areas, where sediments accumulate them. A similar observation is reported by Mandal et al. (2023) and Mohan et al. (2022). Ocean currents and tides convey PET debris from terrestrial sources, while maritime activities such as fishing and shipping exacerbate its prevalence (Phan et al., 2024; Xu et al., 2024). The current investigation also identified PES and PE alongside PET. Both materials are extensively utilised owing to their adaptability and affordability, with PE being employed in packaging and bags, whereas PES is predominant in textiles and containers (Bobchev et al., 2024; Karthik et al., 2018; Samrat Hossain et al., 2024). The heavy utilisation results in considerable waste production, especially in densely populated coastal areas with substantial tourist traffic. This extensive use leads to significant waste generation, particularly in coastal regions with high population density and tourism (Shaji et al., 2024). The next abundant polymer, PP, is widely utilised in diverse applications, which include plastic packaging, containers, textiles, and automotive parts, while PS is often used for packaging, insulation, and disposable products; PVC finds its application in construction, electrical, medical, and automotive applications, and nylon is applied in diverse areas, ranging from textiles to industrial and medical uses.

4.3 Risk assessment

The computed average PLI for the Odisha coast (PLIodisha) was 2.59. The outcome was in line with other research on the coasts of Northern Chennai (2.83) (Vignesh et al., 2024), the eastern Arabian coast (2.77) (Gupta et al., 2024), and Maharashtra (2.59) (Kumkar et al., 2023). In comparison to global research, the PLI for the Odisha Coast (2.59) is markedly lower than that reported for Riyadh city (20) (Picó et al., 2021), the Changjiang estuary in China (1) (Xu et al., 2018), and Dongshan Bay (14.2) (Pan et al., 2021). Nonetheless, the PLI for Chilika Lake sediments (1.07) (Kumar et al., 2024) was significantly lower than that of the present study, indicating relatively lower levels of pollution. The assessment of ecological risk is critically important, as it can impact both land and aquatic organisms. Nonetheless, the approaches for assessing ecological risk lack standardisation, and as previously noted, there is a dearth of research about the toxicity of various plastic varieties (Soursou et al., 2024).

RQ computation is significant because it estimates risk levels and identifies areas where MP contamination can have a detrimental effect on marine ecosystems. It offers a standardised metric for assessing and comparing risks across diverse locales and situations by comparing ambient concentrations with toxicological thresholds (Kumar et al., 2024). For instance, research conducted along the Yellow Sea and Bohai Sea reported an RQ of 1.2–4.5, with highly industrialised zones exhibiting greater risks (Zhang et al., 2018). The high PHI, PERI, PLI, and RQ values recorded along the Odisha coast indicate that MP pollution poses a significant ecological threat, with certain locations requiring immediate mitigation efforts. The findings emphasise the necessity for stringent waste management policies, enhanced monitoring frameworks, and cross-disciplinary collaborations to safeguard marine biodiversity and coastal ecosystems.

4.4 Study limitations

While this study provides a valuable contribution towards MPs study along the Odisha coastline, it is essential to recognise specific limitations related to the MPs analysis methods employed. The reported concentrations represent average values normalised to sediment dry weight (MPs/kg) in lieu of absolute particle counts. While this approach enables comparability across the study locations as well as the previous studies, it may introduce some degree of variability in the reported concentrations, which is an inherent aspect of MPs quantification studies. Furthermore, the MPs with small size (<50 μm) could be underpresented due to optical resolution limits of the stereomicroscope used for MPs identification—a constraint widely acknowledged in the previous studies (Randhawa, 2023). Another limitation is the lack of seasonal and temporal data. As sampling has been conducted at a specific time, meaning that the influence of monsoonal variations, storm surges, and tidal fluctuations on MPs distribution remains unassessed. Future research should address these constraints by implementing advanced detection methods and seasonal monitoring.

5 Conclusion

This study underscores a significant environmental concern by highlighting the widespread prevalence of MPs in beach sediments of Odisha. Additionally, it helps bridge critical knowledge gaps in MPs research along the eastern coast of India. Our findings indicate that fibres constitute the predominant form of MPs, with PET identified as the most prevalent polymer type. Risk assessment based on the PHI indicates that nine out of the total number of research locations are classified as risk category V, which indicates a significant amount of concern, while the remaining locations are classified under category IV. Additionally, based on the PERI, all 22 locations are categorised as being in extreme danger, further emphasising the critical need of addressing this particular issue. Moreover, the PLI assessments indicate that all locations have a PLI greater than 1, designating them as polluted. The risk quotient analysis suggests that there is approximately 94% risk to biota, highlighting the potential for significant ecological harm. These findings underscore the need for urgent and comprehensive risk assessments to gain a deeper comprehension of the ecological effects that MPs have on coastal ecosystems. It is imperative for policymakers and stakeholders to adopt and execute effective management strategies designed to mitigate MP pollution.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Author contributions

SS: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Visualization, Writing – original draft. YR: Resources, Supervision, Writing – review & editing. BS: Funding acquisition, Project administration, Resources, Supervision, Writing – review & editing.

Funding

The author(s) declared that financial support was received for this work and/or its publication. This research is financially supported by the DST-SERB, Government of India (Grant No. CRG/2022/004343).

Acknowledgments

The corresponding author acknowledges the support of the DST-SERB through the research project funding. The authors also express their gratitude to Miss. T S Sandra, Mr. Binet Monachan, and Miss. Padala Sri Venkata Satya for their support in the preparation of the maps and spectroscopic analysis. The authors are grateful to the Centre for Nanoscience and Nanotechnology, Sathyabama Institute of Science and Technology for facilitating the micro-Raman Spectroscopy of MP samples.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that Generative AI was not used in the creation of this manuscript.

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Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/frwa.2025.1749269/full#supplementary-material

Abbreviations

MPs, microplastics; PET, polyethylene terephthalate; PP, polypropylene; PE, polyethylene; PES, polyester; PVC, polyvinyl chloride; PHI, polymer hazard index; PLI, pollution load index; PHI, polymer hazard index; PERI, potential ecological risk index.

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