Of the 10 sites studied, a total of 4,227 items were collected and classified. The composition of the litter was 84.54% plastic (Fig. 2), with the other litter categories together not surpassing 15.46% (cloths (7.64%), glass (4.35%), and rubber (3.47%). The high quantity of plastic found in this study is in accordance with previous studies conducted in the Indian coast [17, 35–38] but surpasses the global average of 75% reported by [39]. Similar percentages have been reported in other coastal regions; 71% on the Moroccan Mediterranean coast [29], 72.80% on the beaches of China [40], 98.9% in Cape Town, South Africa [41], 83.4% in the Adriatic Sea [42], and 87% on the islands of the North Atlantic [43]. The PV Pattinam beach have highest number of plastic items (94%), followed by Namputhalai (92%) and Passipattinam beach (88%) while the low percentage observed on Theerthandam beach (37%). In this study, we found 51 face masks on five beaches. These types of litter related to COVID-19 are already reported by [44] from beaches in Tamil Nadu, India. The density of face masks in this study (0.017 items/m2) is comparable with the density reported by [44] on fishing beaches in India. This region already faces existing waste management issues, and the litter created by the COVID-19 pandemic phase has made the already-existing issues worse [44–46].
The top 10 items represented 90% of all items collected in this study (Table 2), which is similar to other previous studies where a few items categories of litter comprise the largest number of total items recorded [17, 29, 35, 36, 47, 48]. The main items of litter found along the Palk Bay coast were polythene covers (carry bags) (17.12%), plastic cups (14.85%), drinks bottles (12.75%), string and cord (8.54%), clothing (7.64%) and fishing line (7.59%). Other plastics items (5.91%), foams (thermocol) (5.92%), nets and pieces of net (5.46%) and other bottles (5.34%) are also abundant on the beaches surveyed. The most common marine litter in India reported in other studies are not observed in this study [17, 35–38]. Caps/lids, cigarette butts and filters, plastic/polystyrene pieces, small plastic bags, and crisp/sweet packets were the most abundant plastic items on Indian beaches, which is different from our study results. This difference in composition probably reflects the type of activity practiced on the beach.
Table 2
Top 10 litter items observed on the ten beaches surveyed.
S. No
|
Material type
|
OSPAR
ID
|
Items name
|
Items counts
|
% Items
|
1
|
Plastics
|
2
|
Plastic cover (carry bags)
|
724
|
17.12
|
2
|
Plastics
|
21
|
Plastic cups
|
628
|
14.85
|
3
|
Plastics
|
4
|
Drinks bottles
|
539
|
12.75
|
4
|
Plastics
|
32
|
String and cord
|
361
|
8.54
|
5
|
Plastics
|
54
|
Clothing
|
323
|
7.64
|
6
|
Plastics
|
35
|
Fishing line
|
321
|
7.59
|
7
|
Plastics
|
48
|
Other plastics items
|
250
|
5.91
|
8
|
Foam
|
45
|
Foam (thermocol)
|
242
|
5.92
|
9
|
Plastics
|
116
|
Nets and pieces of net > 50 cm
|
231
|
5.46
|
10
|
Plastics
|
12
|
Other bottles
|
226
|
5.34
|
The mean litter abundance was determined to be 0.70 items/ m2, varying from 0.45 items/m2 to 1.49 items/ m2 (Table 3). The mean litter abundance in this study was lower than recently recorded in other Indian beaches, e.g., Marina Beach (1.37 items/m2 [35]), Tuticorin beaches 1.38 ± 78 to 6.16 ± 94 items/ m2 [36], along the Hooghly estuary during the monsoon (1.10 ± 0.39 items/ m2) and after the monsoon (0.86 ± 0.32 items/ m2) [17] and Gopalpur coast (0.98 items/m2 [49]. It is also less than the global average (∼1 item/m2) [50]. The mean density is of the same order of magnitude as densities reported along the southeast coast of India [51], Morocco [52], Northern Mediterranean countries [48], Italy [53], North Atlantic Islands [43] and Caspian Sea [54]. In this comparison, it is important to take into account the beach typology studied. [55] pointed out that beaches utilized for a diverse range of activities had a higher density of marine litter than those used only for recreational activities or fishing. The high density reported in this study may be explained by the lack of cleaning of sites and the proximity of rivers, which facilitates the accumulation of marine litter. [51] reported that fishing villages result in greater accumulation of litter.
Table 3
The number and density of marine litter (items/m2) collected at each site and the CCI values and their grade (Alkalay et al., 2007).
S. No
|
Number items
|
Density (item/m2)
|
CCI
|
Grade
|
S1
|
372
|
0.62
|
10
|
Moderately clean
|
S2
|
498
|
0.83
|
6.26
|
Dirty
|
S3
|
433
|
0.72
|
12.8
|
Dirty
|
S4
|
312
|
0.52
|
6.46
|
Moderately clean
|
S5
|
326
|
0.54
|
10.3
|
Dirty
|
S6
|
408
|
0.68
|
11.16
|
Dirty
|
S7
|
894
|
1.49
|
25.7
|
Extremely dirty
|
S8
|
367
|
0.61
|
11.36
|
Moderately clean
|
S9
|
346
|
0.57
|
9.6
|
Moderately clean
|
S10
|
271
|
0.45
|
7.36
|
Moderately clean
|
As shown in Table 3, the highest litter abundance was recorded in Thondi (1.49 items/m2), followed by Theerthandam (0.83 items/m2), Passipattinam (0.72 items/m2) and MR Pattinam (0.68 items/m2). Relatively high litter abundances were observed also in SP Pattinam (0.62 items/m2), Namputhalai (0.61 items/m2) and Soliyankudi (0.57 items/m2). The lowest abundances were recorded PV Pattinam (0.54 items/m2), Vattanam (0.52 items/m2) and Karankadu (0.45 items/m2). Variation in the abundance of litter from place to place could be the result of many factors. This disparity was caused by anthropogenic and physical factors, such as beach morphology, winds, waves, orientation, number of beach visitors, beach cleaning programs, etc. Fishing effort is another factor. For example, the high density of marine litter on Thondi beach coincides with the large number of fishing vessels (150), which explains the high density in this site compared to others.
The cleanliness of Palk Bay beaches was assessed using the CCI [28]. In this study, SP Pattinam, Vattanam, Namputhalai, Karankadu and Soliyankudi beaches were "moderately clean" (Table 3). MR Pattinam, PV Pattinam, Theerthandam and Passipattinam beaches were classified as dirty and Thondi beach were classified as "extremely dirty" (Table 3). No "very clean" beaches were found. Taking into consideration the entire study area (6000 m2), the Palk Bay score achieves an overall CCI value of 11 which allows to be classified this region as "dirty". Similarly, [30] and [51] used the same index in Indian beaches and determined that most beaches were classified as "clean" to "dirty". Similar findings have been reported for sandy beaches in Bangladesh [56] and in Philippines [57] where beaches were listed as "moderately clean", "dirty," and "extremely dirty. Same index was used in the Indonesian coasts and the beach was found "clean" to "dirty" [31].
Concerning the sources, this present study clearly highlights that these depend on the activities carried out on the beach. The ten beaches are less influenced by tourism and litter from shoreline/recreational activities constitutes only 28.69% of the total litter collected. This value is lower than the international data [58], the value recorded in the Mediterranean [59] and also the value reported on Indian beaches [35, 38, 49]. 17] recorded a small percentage of litter related to recreational activities on Indian beaches (48%). These types of litter may be discarded by fishermen or by residents who regularly visit the beaches in the study area. Dumping activities, which account for 49.46% of all the litter recorded along the surveyed beaches, are the primary source. The main items dumped are cloths, footwear (flip-flops), plastic cup, foam (thermocol) and shopping bags. The domination of these types of marine litter is caused by litter spilling or deposition in river basins and surrounding streets, which eventually builds along Palk Bay's beaches [60]. This litter is likely transported by rain events, river and wind to the beach. Studies by [61] and [62] have indicated that litter found on beaches is carried from land-based origins via rivers and drainage systems.
On the other hand, fishing activities play a major role in beach pollution (Fig. 3). The mean abundance of litter related to fishing activities in this study was 0.15 items/m2. This result is lower than that reported by [16] along the beaches of northeast India (6.3 items/m2). The most common are string and cord, fishing lines, fishing gear, floats and buoys. Majority of these litter had been washed up from traditional fishing in the near shore zone. Several studies have documented the dominance of litter related to fishing activities on Asian beaches. [63] reported that 70% of marine litter comes from derelict fishing gear in East Asia. Also, [16] identified plastic items related to fishing as one of the major sources of litter along the beaches of northeast India. Similarly, [51] determined that litter from fishing is the second most prevalent source along India's southeast coast. Particularly, 21.85% of the overall litter collected is made of items connected to fishing, as reported in our study. This value exceeds the 5% estimated for the Mediterranean [64], the 11-19.4% reported by [47] for the North western Adriatic beaches, 21% in India [17], 19.6–36.7% in Oman [65], 25.1% in Brazil [62], 20% in Sri Lanka [66], 13% in China [67] and 12% in Japanese beaches [68]. On the contrary, the percentage of litter related to fishing activities in this study is lower than the value obtained by in India by [69], 45% in Lakshadweep Islands, Arabian Sea [51], 48% in the beaches of Thailand [70], 46% in the Great Pacific [71] and 46% along the coast of Brazil [72]. Fishing activities, such as commercial fishing and marine aquaculture (51.3%), were discussed by [73] as the main sources of marine litter in Korea. Thanur Beach was reported to have the highest fishing-related litter. This difference can be explained by the number of fishing vessels operating on each beach (n = 150). Similarly, [74] also observed a correlation between litter abundance and proximity to fishing areas on British beaches. These authors found that beaches close to active fishing areas tend to have greater overall litter loads, which included both litter from fishing and other sources.
In addition, the large amount of plastic litter related to fishing encountered along the study area suggests the potential for these items to be discarded into the ocean, where they pose a risk to marine life through entanglement and ingestion. This is particularly relevant due to the number of harbors that generate large amounts of litter. Fishing litter that are lost or left in the marine environment represent a serious threat to marine biota and are commonly found on beaches Indian [18, 21, 75]. Each year, more than 640,000 t of fishing gear is lost or discarded into the marine environment and drifts into the ocean. This gear, also known as "ghost nets" [76], is discarded in the ocean by the fishermen and are then swept by the tide to coastal areas. Fishing-related plastics remain in the ecosystem for a prolonged period [77].
A total of 28 cases of interactions between marine wildlife and marine litter have been recorded in the last five years (2018–2022). Olive turtles (Lepidochelys olivacea) are most affected by entanglement (n = 25, 89.28%) followed by crabs (n = 2, 7.15%) and fish (n = 1, 3.57%). Fishing related litter is responsible for most of the registered entanglements. For turtles, most reported entanglements were from discarded or lost fishing gear (Fig. 4). [69] have already highlighted the entanglement of sea turtles in discarded gillnets. Similarly, [78] documented that discarded fishing nets constituted the majority of sea turtle entanglements. Entanglement is identified as one of the major sources of mortality for sea turtles worldwide [18, 78, 79]. The cases of entanglement cited here are probably a very small fraction of the total entanglements that have happened in Indian waters. However, this study suggest that Indian waters is a hotspot interaction between sea turtles and fishing litter. The high presence of discarded and lost fishing gear in Indian waters may lead to more pressure on the population of marine fauna that had been heavily affected by human activities in this region. The olive turtle is a vulnerable species according to the list of threatened species of the IUCN. This type of litter has affected other animals such as seabird. [80] recorded the entanglement of seabirds in marine litter associated with fishing activities in coastal Kerala, India.
This study offers some recommendations for improving the quality of these beaches. Poor municipal garbage collection systems, lack of waste management infrastructure, illegal dumping sites, and poorly managed defunct landfills can contribute to marine litter. The majority of the reduction can be done at the source detected in this study. It is important to organize ongoing clean-up programs on these types of sites in order to reduce the accumulation of litter on these beaches. Specifically, it is important to involve fishermen in clean-up operations and to make them aware of the problem of plastic pollution. In addition, the awareness of the fishermen's association on the impact of debris related to fishing activities in the marine ecosystem and for marine fauna are also necessary.