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A clean-coast index (CCI) was developed and is suggested as a tool for evaluation of the actual coast cleanliness. It measures plastic debris as a beach cleanliness indicator, in an easy way precluding bias by the assessor. Furthermore, the CCI is the measuring tool of the ''Clean Coast'' program-a new, long-term approach for cleaner beaches by var...
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Context 1
... the first two weeks of June 2005, inspectors of the Marine and Coastal Environment Division in the Ministry of the Environment performed 35 CCI measurements on 26 unauthorized beaches along the Israeli Mediterranean coast. On each beach, 1-3 measurements were made, depending on the length of the beach. Baseline CCI results are presented in Fig. ...
Context 2
... the first two weeks of June 2005, inspectors of the Marine and Coastal Environment Division in the Ministry of the Environment performed 35 CCI measurements on 26 unauthorized beaches along the Israeli Mediterranean coast. On each beach, 1-3 measurements were made, depending on the length of the beach. Baseline CCI results are presented in Fig. ...
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Citations
... We employed CCI as the first index that gives the number of litter parts/ m 2 , taking into account the existing relation between the number of litter items and the total area of the sample unit as a product of the length, width, and a constant value (K = 20). According to the scale presented by Alkalay et al. (2007), the CCI enables measuring beach cleanliness in five different levels as, very clean (0 < CCI < 2), clean (2.1 < CCI < 5), moderate (5.1 < CCI < 10), dirty (10.1 < CCI < 20), and extremely dirty (20 < CCI). ...
Marine debris accumulation and contamination have become escalating yet disastrous environmental impacts in marine ecosystems at present Sri Lanka context. Thus, we conducted this study to assess the marine debris abundance and density in randomly selected sites (n = 6) of Kandakuliya beach, Negombo, Sri Lanka. Marine debris density was used to explore the extent of beach pollution from marine debris. 13 types of marine debris were found including sub types of marine debris. Higher abundance of fragment marine debris can be seen rather than whole marine debris in each site. Moreover, a significant difference of mean abundance of hard plastic was observed among 6 sites as spatial variation of hazardous marine debris. According to Clean Coast Index (CCI), site 1 was classified as the “extremely dirty”, while site 2 - site 4 were classified as “dirty”. As per the Hazardous Items Index (HII), site 1 - site 4 were grouped under the category (IV). Further according to Plastic Abundance Index (PAI) categories, site 1 was grouped as “high level of plastic contamination”, while site 2 and site 4 were grouped as “high to moderate level of plastic contamination”. Accumulation of hazardous and non-degradable waste carried away by wind and ocean current from unsustainable fishing practices, mismanagement of solid waste, destructive recreational activities have been recorded as main sources for observed marine debris on the beach. In conclusion, study showed that there exists a substantial need in incorporating marine beach and coastal management framework to preserve these ecosystems. Despites raising awareness and education, and beach cleanup initiatives, we suggest introduction of new waste management methods (especially, gears and boat waste) through innovation, strengthening legislation and regulations, corporate responsibility, and advanced research and development as further management steps must be taken to conserve the beach in Kandakuliya.
Keywords
Clean coast index (CCI)Hazardous and non-hazardous debrisKandakuliya beachMarine debris abundance and densityPlastic abundance index (PAI)
... The analyzed beaches' cleanliness was investigated using the Clean Coast Index (CCI) developed by Alkalay et al. (2007). This index serves as a comprehensive measure, encompassing both the abundance and density of macrolitter pollution. ...
... Since the study spanned a period of five years and was conducted in the same designated assessment areas, it provides reliable insights into the dynamics of litter density and distribution. The analysis revealed that the majority of the assessed beaches fell into three classes: "a lot of waste on the shore" (30 %), "a few pieces of litter can be detected" (30 %), and "no litter is seen over a large area" (30 %), according to density description of Alkalay et al. (2007). The average litter density across all assessment areas on beaches was estimated to be 0.44 ± 0.04 items/m 2 , corresponding to the classification of "a few pieces of litter can be detected". ...
... It provides an opportunity to compare cleanliness results over time, across seasons, and between different countries. In this particular research, we were able to gather comprehensive data for the entire coast, including the impact of force majeure circumstances like travel restrictions during the COVID-19 pandemic, which indirectly subjected the beaches to maximum Table 1 Density and C a CI classes, according to Alkalay et al. (2007). ...
Over the years, the Black Sea has been impacted by the issue of marine litter, which poses ecological and health threats. A mid-term monitoring program initiated in 2018 assessed the abundance, density, and composition of beach litter (BL) on 40 frequently visited beaches. From 2018 to 2022, there was a significant increase in average abundance, rising by 261 %. Artificial polymer materials accounted for the majority (84 %) of the litter. Land-based sources dominated 77 % of the litter. The Clean Coast Index (CCI) categorized the beaches as “moderate” with an average value of 8.9 for the period between 2018 and 2022. However, the years 2021 and 2022, during the COVID-19 epidemic, were identified as the “dirtiest period” with 11 beaches classified as “extremely dirty” due to high domestic tourist pressure. The study demonstrates a successful combination of standard in situ visual assessment supported by unmanned aerial systems for beach litter surveys.
... The result is reported in items per square meter and grams per square meter, respectively. The Clean Coast Index (CCI), created by Alkalay et al. (2007), was used to assess the level of cleanliness of the beaches due to litter. The index rates the cleanliness of the beach according to the amount of trash on it, and the results are divided into five categories: very clean (0-2), clean (2-5), moderate (5-10), dirty (10-20), and extremely dirty (> 20). ...
... The litter density (number of items) and the coefficient factor, K (=20), are multiplied to determine the CCI. For practical reasons and to prevent the CCI values from falling between 0 and 1, the coefficient factor is used as a multiplier (Alkalay et al., 2007;Sajorne et al., 2021). Some studies have only used the CCI for plastic litter because it makes up the majority of marine litter (Alkalay et al., 2007;Paler et al., 2019;Akarsu et al., 2022;da Silva et al., 2022), whereas others have used it for all types of litter (Rangel-Buitrago et al., 2019;Terzi et al., 2020;Pervez and Lai, 2022). ...
... For practical reasons and to prevent the CCI values from falling between 0 and 1, the coefficient factor is used as a multiplier (Alkalay et al., 2007;Sajorne et al., 2021). Some studies have only used the CCI for plastic litter because it makes up the majority of marine litter (Alkalay et al., 2007;Paler et al., 2019;Akarsu et al., 2022;da Silva et al., 2022), whereas others have used it for all types of litter (Rangel-Buitrago et al., 2019;Terzi et al., 2020;Pervez and Lai, 2022). Additionally, Akarsu et al. (2022) estimated the CCI values using the diameters of plastic trash and discovered a substantial variation in the outcomes. ...
Marine litter in coastal areas can bring economic, social, and environmental damage, especially the loss of aesthetic value of a tourist site. Therefore, research on the composition of marine litter to identify its sources is important for planning strategic action to minimize the problem. This study analyzed beach litter composition on five beaches (Kondangmerak, Balekambang, Ungapan, Ngudel, and Goa Cina) along the Indian Ocean coastline in the eastern part of the south Java region, Indonesia. All the beaches are known as the famous touristic beaches of Malang City, and receive many visitors, especially during the holiday season. Beach litter composition was obtained by collecting different types of litter in a 5 x 5 m square transect. Five square transects were placed along the beach strandline at each beach, and intervals of 20 m separated each transect. In each transect, the litter was collected and counted based on its category (plastic, paper, rubber, fabric, processed wood, metal, glass, ceramic, and hazardous items) and size (0.5–2.5cm, 2.5–5cm, 5–10 cm, and > 10 cm). There was a statistically significant variation in the number of litters among the sizes (p<0.05). However, the distribution of beach litter remained consistent across beaches regardless of its size. In general, beach litter with a size > 10 cm was found least on all beaches (< 15%), while the other three size categories were found in similar numbers (in the range of 20% to 50%). Plastic was the dominating type of litter on all beaches. Based on the Clean Coastal Index, all beaches were considered dirty to extremely dirty. All litter on the beaches was the product of tourism activities, and littering habits play a significant role as the source of marine litter in the study areas. Since this is the first study on the marine litter composition in the eastern part of south Java, the results of this study can be used as a baseline for future studies to prevent marine debris pollution and to develop management strategies for reducing the impact of marine debris on the environment.
... The marine litter samples on the beaches were described in studies [10,11] and adjusted for the actual conditions of the study area. The sampling locations ensured the following criteria: the sampled areas had a beach length greater than 100 m; the sampled beaches had slopes ranging from 8o to 20o; the sampling units were not affected by wave barriers or ports; and the research team's sampling units had access to the entire year. ...
Marine debris is a prevalent problem that affects oceans and coastal regions worldwide, particularly beaches. The problem of marine litter pollution is also severe on beaches in Nha Trang. In this study, marine debris with a size ≥ 5 mm was collected at seven locations along the coastline of Nha Trang during both dry and rainy seasons, accruing a total of 4436 items. During the rainy season, most beaches had more debris than that in the dry season, and marine debris density ranged between 0.009 items/m2 to 0.418 items/m2. Results from the beach cleanliness index (CCI) assessment showed that CCI values ranged from 0.2 to 4.4 during the dry season, with beaches classified as either very clean or clean. Meanwhile, during the rainy season, CCI values ranged from 0.36 to 8.35, resulting in beaches being categorized as very clean, clean, or average. The Plastic Abundance Index (PAI) showed that the PAI ranged from 0.004 to 0.061 during the dry season, while during the rainy season, it ranged from 0.006 to 0.118. PAI values for both seasons indicated low levels of plastic debris distribution on the beaches. However, local authorities and managers need to pay attention to potential sources of pollution, such as waste from food service activities in restaurants, ports and unsustainable waste from aquaculture activities.
... Los residuos sólidos se contabilizaron, a partir del número total de residuos se determinó el índice de contaminación (IC) por zona, mediante la Ecuación 1 (Alkalay et al., 2007). ...
Las playas son de gran importancia debido a los servicios ambientales que prestan; sin embargo, se encuentran sujetas a alteraciones a causa de actividades antropogénicas, siendo la presencia de residuos marinos una de las mayores afectaciones. Dentro de estos residuos, los materiales plásticos presentan las
mayores proporciones. Éstos, al estar expuestos a la intemperie, se degradan y con ello forman microplásticos (MP) los cuales afectan al medio marino. En el presente trabajo se evaluaron las concentraciones de residuos y microplásticos en tres zonas de una playa de Oaxaca, México. La metodología empleada consistió en primero delimitar un transecto de 100 m paralelo a la pleamar, posteriormente la recolección de residuos se realizó en cinco secciones elegidas aleatoriamente para después cuantificarlos y clasificarlos. El muestreo de microplásticos se llevó a cabo con un muestreador cilíndrico en 10 puntos, también seleccionados de manera aleatoria. Las muestras se analizaron mediante a un proceso secuencial de tamizado y flotación. Los resultados evidenciaron la presencia de residuos sólidos y microplásticos en todas las zonas de playa, presentando un intervalo de concentración de residuos sólidos de 0,009 – 0,019 piezas/m2, en donde la mayor proporción fueron de material plástico; de estos los residuos más comunes fueron las tapas de botellas de bebidas. Se encontró un intervalo de concentración de MP de 59,9- 76,3 MP/m2 y mayor proporción de MP del tipo fragmento (92 %) y color
blanco (78 %). Se recomienda futuros estudios en distintas temporadas, permitiendo la observación de posibles cambios que surgieran de factores externos.
... In order to assess the level of solid waste contamination in the mangrove and on the Santos beaches, the Clean Coast Index (CCI) was used, which quantifies plastic and styrofoam residues as an indicator of ecosystem cleanliness (Alkalay et al., 2007). Data on the amount of plastic and styrofoam items collected were recorded based on the equation proposed by Alkalay et al. (2007), to obtain the CCI according to the numerical index of each sampled location, establishing the following levels of cleanliness: Very clean: from 0 to 2; Clean: from 2 to 5; Moderate: from 5 to 10; Dirty: from 10 to 20, and Extremely dirty: > 20. ...
... In order to assess the level of solid waste contamination in the mangrove and on the Santos beaches, the Clean Coast Index (CCI) was used, which quantifies plastic and styrofoam residues as an indicator of ecosystem cleanliness (Alkalay et al., 2007). Data on the amount of plastic and styrofoam items collected were recorded based on the equation proposed by Alkalay et al. (2007), to obtain the CCI according to the numerical index of each sampled location, establishing the following levels of cleanliness: Very clean: from 0 to 2; Clean: from 2 to 5; Moderate: from 5 to 10; Dirty: from 10 to 20, and Extremely dirty: > 20. ...
The present study investigated the hypothesis that the marine litter found on the beaches of Santos, in Brazil, may have originated from the mangrove located in the adjacent estuary, acting as a hotspot. To this end, we performed quali-quantitative analyses of the waste found in the beach environments (beached and discarded litter) and the mangrove, as well as hydrodynamic modeling, to verify the influence of the tides on waste transport and the level of contamination according to the Clean Coast Index (CCI). The beached waste presented a similar composition to the items found in the mangrove, corroborated by multivariate analyses and Spearman’s correlation. The hydrodynamic conditions revealed that tidal currents transport waste from the interior of the mangrove to the beaches through the Santos Channel, therefore indicating that the mangrove itself acts as a marine litter hotspot. This problem needs to be managed on a macro-scale by public management agencies, not just locally.
... For each beach, the Clean-Coast Index (CCI) was estimated using the method described by Alkalay et al. (2007). The Clean-Coast Index CCI is the product of the density of macrodebris per m 2 (CM) and K is a constant equal to 20 with CCI ¼ CM x K. ...
... Marine litter density was calculated for each transect area (four per sampling day) and nally considered the mean marine density for each study site. The cleanliness level of the beach was assessed based on the Clean Coast Index(Alkalay, et al., 2017) Beach cleanliness (CCI) was calculated as followCCI = C M * K Where CM is the number of marine litter densities per m 2 , K is a constant that equals 20 (Marin, C.B, et al., 2019 ...
Marine plastic debris has become a major concern on the northern coast of Jaffna, Sri Lanka, where it poses a threat to marine resources. A preliminary study was conducted to investigate the abundance and characteristics of marine plastic debris at four major fish landing sites in the northern coast of Jaffna, using the Clean Coast Index (CCI) and Plastic Abundance Index (PAI). The results revealed that the average abundance of marine debris and plastic debris were 1.71 ± 0.42 items/m ² and 1.66 ± 0.57 items/m ² , respectively. The most common types of plastic debris were plastic rope and net pieces (23.2%), followed by unidentified weathered plastic fragments (16.7%), beverage bottles (16.2%), bottle caps and lids (13%), and styrofoam (14.1%). The recognized sources of plastic debris were mainly fishing-based activities, recreation activities, transboundary sources, and unidentified sources. The cleanliness level of the fish landing sites were categorized as extremely dirty, with high levels of plastic debris, resulting in a CCI above 10 and a PAI value over 8. This study realized the consequence of implementation of a proper plastic waste management framework in the northern coast of Jaffna and highlights the necessity to address buoyant debris on the northern Indian Ocean.
... Other publications used different units of measuring plastic debris density and needed to be converted to match the standard reporting unit. Acot et al. (2022) (2022) and Sajorne et al. (2021) used the clean-coast index (CCI) to classify sites according to cleanliness (Alkalay et al., 2007). The CCI multiplies a fixed constant of 20 to the macro-plastics debris density in items/m 2 to allow for convenience in comparison. ...
Despite the consistent tagging of countries in Southeast Asia as among the top polluters of plastics in the oceans and the increasing local literature documenting the presence and abundance of plastics in marine environments, there still lacks a comprehensive, open, and accessible repository for marine plastics pollution data in the region. As such, this study presents the development of the PlastiCount Pilipinas portal in line with the call for a common data repository by the Philippines’ National Plan of Action for the Prevention, Reduction, and Management of Marine Litter and the ASEAN Regional Action Plan for Combating Marine Debris in the ASEAN Member States. A total of 14 existing databases were reviewed to identify key features for the online portal implemented to promote ease of access and diversified functionality. For the database, a total of 38 publications, 2 reports, 1 scientific poster, and 3 baselining studies were used to develop the initial ground-truthed baseline for marine plastic pollution, covering 23 provinces and 14 regions across the Philippines. The challenges presented by an observed variation across different methodologies and reporting styles emphasize the critical need to harmonize methods toward generating a more refined national baseline for marine litter. The initial baseline data and other resources such as manuals, information sheets, photographs, news, and publications are uploaded onto a public online portal for viewing and download (https://plasticount.ph/). Data and resource submissions from the public are also accepted and considered for inclusion in the database. The insights gained from developing the online portal and database for the Philippines can be used to inform the development of a regional database for Southeast Asia towards reducing marine litter.
... The environmental impact of ML in the mangrove forest of the CM was assessed employing two indexes: The Clean-Coast Index (CCI) modified in this study going from using the total number of articles to their density (not overestimating the results due to the small sample area used on each point), and the Hazardous Items Index (HII). The modified CCI was calculated by quantifying the ML in each mangrove forest study site, based on the index proposed by Alkalay et al. (2007), using the following equation: ...
... where CCI determines the state of cleanliness (absence of ML) and the habits required to achieve and maintain that state (Rangel-Buitrago et al., 2019a, 2019b, estimated by total items quantified, divided by the total sampling area (m 2 ) and multiplied by the K coefficient equal to 20. Based on the scale provided by Alkalay et al. (2007), resulting values are grouped into five different classes, ranging from I 'very clean' to V 'extremely dirty'. ...
The Ciénaga de Mallorquín is a unique coastal lagoon close to Barranquilla City. It is the first study on this topic in the Ciénaga de Mallorquín that evaluated the state of pollution based on marine litter inside the mangrove forest in the Ciénaga de Mallorquín. A total of 860 items and 77.9 kg of litter were collected, equivalent to an average density of 23.89 items*m-2 and 2.16 kg*m-2. Plastic was the main litter item (43.55 %), followed by polystyrene, rubber, and processed wood, most of which comes from inland sources such as dumping and recreational and urban activities and is transported mainly by local streams. Of the litter collected, 87.3% was characterized as persistent buoyancy items. The mangrove forest is classified in a dirty state (Class IV), with a considerable number of hazardous items (Class III). The CM needs an urgent, integral, and proactive management plan to reduce litter at its sources, adopting and improving measures such as education and public awareness, good management practices, recycling, and reuse.
