Stratifying the Shoreline: A Modified OSPAR Framework to Monitor Event-Driven Beach Litter

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S. Carvalho, Carlos Gonçalves, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7767950/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 10 Apr, 2026 Read the published version in Environmental Monitoring and Assessment → Version 1 posted 9 You are reading this latest preprint version Abstract Urban beaches are increasingly vulnerable to litter accumulation, especially during large-scale coastal events that create short-lived but intense pollution pulses. Despite growing interest in marine litter monitoring, traditional methods often lack the spatial and temporal sensitivity required to capture such episodic surges. This study presents a methodological adaptation of the OSPAR beach litter monitoring protocol, applying a stratified sampling framework to a high-use coastal site during the RFM SOMNII festival in Figueira da Foz, Portugal, one of Europe’s largest beach music festivals. Over a five-year period (2019–2023), including pre- and post-COVID-19 seasons, 17 seasonal surveys were conducted across three functional zones (STAGE, VIP, CHILLOUT) to assess the spatiotemporal dynamics of litter accumulation. Results indicate clear spatial heterogeneity, with litter densities peaking in high-traffic areas and artificial polymer materials, particularly single-use plastics, accounting for over 90% of all debris. Temporal trends show sharp declines in 2020–2021 during festival cancellations, with subsequent rebounds following the event’s return, and further reductions after targeted cleanup measures in 2023. The stratified sampling approach revealed patterns and hotspots that would likely be overlooked by conventional OSPAR layouts, highlighting the potential for this framework to enhance marine litter monitoring in event-prone coastal zones. Findings also inform broader sustainability strategies, reinforcing the need for adaptive cleanup planning, reusable alternatives to single-use items, and coordinated engagement between researchers, event organizers, and policymakers. The approach offers a replicable blueprint for improving beach litter assessments under dynamic, high-pressure conditions worldwide. Marine litter monitoring Stratified sampling OSPAR methodology Coastal events Single-use plastics Beach pollution hotspots Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction Marine litter represents a pressing global environmental challenge with broad implications for marine ecosystems, human health, and local economies. Plastics, which dominate marine debris, often accumulate on shorelines (Garcés-Ordóñez et al., 2020 ; Grelaud & Ziveri, 2020 ), reducing aesthetic value, threatening wildlife, and interfering with human activities (Browne et al., 2015 ). Although just ~ 0.1% of global plastic production enters the ocean annually (Cózar et al., 2014 ), this still amounted to an estimated 5.5–14.5 million metric tons in 2018 (Wayman & Niemann, 2021 ), highlighting the persistent and growing magnitude of the problem. Among various pressures, urban beaches experience heightened litter inputs due to high visitation, tourism, and recreational events (Garcés-Ordóñez et al., 2020 ). Notably, large coastal festivals contribute episodic surges in litter loads, the impacts of which are poorly characterized and often underestimated (Oliveira et al., 2022 ). Beaches serve as dynamic interfaces between terrestrial and marine systems, functioning simultaneously as sinks and sources for anthropogenic debris (Gallitelli et al., 2023 ; Jambeck et al., 2015 ), making beach litter one of the most visible indicators of environmental pollution. Urban beaches, in particular, face increased littering pressures due to their accessibility, popularity among tourists, and high foot traffic (Garcés-Ordóñez et al., 2020 ; Grelaud & Ziveri, 2020 ). Seasonal increases in litter pollution have been widely documented on beaches across the globe, from Spain and China to Brazil and the Mediterranean (Ali & Shams, 2015 ; Asensio-Montesinos et al., 2019 ; Grelaud & Ziveri, 2020 ; Pervez et al., 2020 ; Ribeiro et al., 2021 ). Beyond these pressures, large coastal events contribute episodic surges in litter loads, the impacts of which are poorly characterized and often underestimated (Oliveira et al., 2022 ). While promoting cultural and recreational engagement, these events draw large crowds, generating substantial waste that, if not managed effectively, can cause long-term environmental degradation (Browne et al., 2015 ). To ensure sustainable management of such events, the environmental impacts of litter accumulation must be thoroughly understood and addressed (Williams & Rangel-Buitrago, 2019 ). Despite the recognition of these hotspots, there is a methodological gap in understanding how event-driven litter deposition unfolds over space and time. Traditional beach monitoring protocols - though standardized - often lack the spatial resolution and temporal sensitivity needed to detect short-lived yet intense pollution episodes. In this context, methodological innovations are essential to develop monitoring strategies capable of capturing dynamic littering phenomena with sufficient granularity. This study addresses that gap by adapting the OSPAR methodology to a stratified sampling framework tailored to high-traffic, event-prone coastal areas. Specifically, the research applies this design to the case of RFM SOMNII - one of Europe’s largest beach music festivals, held annually in Figueira da Foz, Portugal. With over 100,000 participants each year (RFM SOMNII Festival, n.d.), this site offers a valuable testbed to examine the performance and utility of stratified monitoring in capturing event-driven litter fluctuations. Over a five-year period - including pre- and post-COVID-19 seasons - this study conducted seasonal and festival-time monitoring at Praia do Relógio, generating a detailed dataset on litter abundance, composition, and distribution. Rather than focusing solely on regional impacts, the goal is to evaluate how stratified OSPAR-based protocols can enhance the detection and interpretation of marine litter patterns linked to large-scale events - contributing to broader efforts to refine international monitoring frameworks and inform adaptive coastal management. Methodology Study Site and beach music festival The study was conducted at Praia do Relógio, an urban beach in Figueira da Foz ( 40°149161 N, 8° 871150 W ), on the North Atlantic Portuguese coast (Fig. 1 ). The beach has an average width of 500 meters and extends approximately 2 kilometers in a North-South orientation. The city experiences high levels of tourism during the summer months (mainly July and August), and the beach is public and freely accessible. However, the sampling area is not as popular with sunbathers compared to other areas in the same beach, likely due to a combination of three factors: the beach's large width, its southern boundary being marked by a jetty (Ponte Lira et al., 2016 ), and the western boundary being limited by dunes (Andriolo & Gonçalves, 2023 ), which restrict direct access to the area. The sampling area is located at the site of the RFM SOMNII Beach Music Festival ( RFM SOMNII Festival , n.d.), which held its first edition in 2013. Since then, the festival has taken place annually at the beginning of July (summer season), except for the years 2020 and 2021, when it was cancelled due to the COVID-19 pandemic (Fig. 2 ). This festival, recognized as the largest beach music festival in Portugal and one of the biggest in Europe, typically attracts around 100,000 attendees for 72 hours of music during the afternoons and nights. In 2023, the SOMNII producers organized a second festival, BR FEST, just one week later, at the same location and using the same infrastructure. BR FEST was described as the “biggest ever event dedicated to Brazilian music in Portugal,” with “thousands” of participants ( BR FEST 2023 , n.d.). Field Sampling design The OSPAR guidelines for monitoring marine litter on beaches (Wenneker et al., 2010 ) specify a standard sampling unit of 100 meters, measured as a straight line parallel to the back of the beach. However, while OSPAR guidelines cover the area between the swash zone and the backshore, this study defined three parallel sampling units, each measuring 100 m x 50 m, within the festival area (total festival area = 110 000 m 2 ) (Fig. 1 ). This adapted methodology was necessary to implement a stratified sampling design representative of the main festival areas: the VIP zone, the STAGE zone, and the CHILLOUT zone. The VIP zone featured a carpeted floor and was located on the east side of the enclosure, at the backshore. The STAGE zone was the middle area where a large number of visitors congregated for long periods. The CHILLOUT zone was located between the food and drink tents and the swash zone, and was mainly used for resting during the festival ( https://vimeo.com/rfmsomnii ). Field campaigns were conducted from summer 2019, shortly after the SOMNII festival of 2019, through summer 2023, following the SOMNII festival of 2023. A total of 17 seasonal campaigns were carried out, with one campaign per season (spring, summer, autumn, winter). Each sampling campaign began approximately two hours before low tide. During sampling, two to three individuals surveyed each designated unit (VIP, STAGE, CHILLOUT) along transects. Macro-litter sampling and identification On average, one to two months after sampling, beach litter was sorted, counted, measured (when relevant), and assigned to one of the 112 predefined OSPAR litter types (Wenneker et al., 2010 ). The latest OSPAR guidelines classify cigarette butts under the artificial polymer material category, aligning with their plastic composition. As a result, we did not adopt the approach used in previous studies (Araújo & Costa, 2021 ; Bettencourt et al., 2023 ), which had categorized cigarette butts as a separate group. Those studies relied on earlier OSPAR guidelines that inaccurately placed cigarette butts in the paper/cardboard category, necessitating a workaround to account for their unique nature. Four individuals participated in the categorization process, with the project coordinator supervising to ensure consistent decision-making criteria for ambiguous items. All items were classified according to the following criteria: a) Material composition, as defined in the MSFD recommendations (MSFD Technical Group on Marine Litter, 2013): Artificial polymer material (also known as plastic), Rubber, Cloth/Textile, Paper/Cardboard, Processed/Worked wood, Metal, Glass/Ceramics, Undefined. b) Single-use plastics (SUP) and maritime-related plastics (SEA): The SUP category follows the definitions in the MSFD recommendations (MSFD Technical Group on Marine Litter, n.d.). The SEA category is derived from the FISH category in the MSFD recommendations (Hanke et al., 2019 ), excluding non-plastic items. c) Litter types targeted by existing measures: Specifically, items addressed in the OSPAR Marine Litter Regional Action Plan (OSPAR Commission, 2022 ) or the EU SUP Directive (Directive (EU) 2019 /904 on the Reduction of the Impact of Certain Plastic Products on the Environment., 2019). d) SOMNII items and OTHER items: This classification is based on the presumed source of the items. SOMNII items are those confidently identified as left behind by festival participants or staff, such as plastic cups with the festival logo, festival tickets, bracelets and zip ties (Supplementary Material - Images). Cigarette butts were also included in the SOMNII category due to their significant presence during post-festival sampling, especially in the STAGE zone, where the highest attendee concentration is observed (Fig. 3 ). OTHER items include all remaining debris not linked to the festival or whose source could not be determined. Data Analysis The Pearson’s Chi-square test of independence was initially performed to evaluate the association between litter categories and the predictor variables: ‘source’, sampling unit’, ‘season’, and ‘year’. This non-parametric test was selected due to its appropriateness for categorical data and its ability to assess whether observed frequencies significantly deviate from expected frequencies. The test was performed at a 5% significance level, and the results were interpreted based on the calculated Chi-square values and their corresponding p-values. The Chi-test was carried out using the R Stats package (R Core Team and contributors worldwide, n.d.). Abundances were assessed by calculating the median of items at the zone scale (for each sampling unit) and aggregated at the site scale (total sampling area) (Table 1 ). Median-based statistical methods were chosen because they are well-suited for handling skewed distributions in beach litter data (Schulz et al., 2017 , 2019 ). It is worth noting that median values are typically lower than mean (average) values, as they exclude extreme outliers, making them more appropriate for decision-making purposes. To calculate percentages, the median of each litter group was divided by the total sum of the medians across all litter groups considered (e.g., the percentage of artificial polymer material is obtained by dividing its median by the total sum of the medians of all material categories). The top 15 litter types were ranked based on the median values of individual litter types. Trends were assessed using the median-based Theil-Sen method, that calculates slopes and associated p-value. Analyses were performed using the litteR package (Walvoort & van Loon, 2021 ) and Microsoft Excel. Table 1 List of statistical indicators calculated at the zones and site geographical scales and corresponding calculation methods. Beach litter indicator SOMNII zones scale SOMNII site scale Abundance Median of sampling unit data for the four seasons sampled, within the five-year period from Summer 2019 to Summer 2023. Median of sampling units’ medians Percentage 100 × median of the category considered divided by the sum of medians of the different categories. Top 15 Ranking of medians of individual litter types and presentation of the 15 highest ranking types. Trend Theil-Sen slope of sampling unit data for the five-year period from 2019 to 2023. p-value of Theil-Sen slope. Median of sampling units’ slopes. p-value of aggregated sampling units. The relationship between the number of items collected per litter type and the predictor variables - ‘category,’ ‘source,’ ‘sampling unit,’ ‘season,’ and ‘year’ - was explored to identify the predictors that most strongly influence the number of items collected. Preliminary analysis revealed data overdispersion (variance significantly higher than the mean) (Fig. 4 ) indicating the need for a Negative Binomial distribution model. Additionally, it was assumed that the dataset includes structural count zeros arising from two distinct processes: sampled areas that were cleaned beforehand and litter types deemed irrelevant to the festival context. As such, a Zero-Inflated Negative Binomial (ZINB) model was implemented, using the pscl package from R software (Jackman S, 2024 ; Zeileis A et al., 2008 ). The ZINB model assumes that excess zeros arise from a separate process, independent of the count data, and models these zeros separately. It consists of two components: the logit model to predict the “certain zero” cases, identifying whether a variable belongs to this group; and a Negative Binomial model to predict counts for data not classified as "certain zeros". In this study, particular interest lies in understanding which variables are predictors of the excess zeros, to support the hypotheses that certain items are absent because they are not from SOMNII sources. In other words, during festival years, certain items are highly more expected than others. All statistical analyses were performed using R Software version 4.4.2. Results Spatial and temporal distribution of beach litter Statistically significant associations (p < 0.05) were found between litter categories and their source, sampling units, seasons, and years, indicating that litter composition varied meaningfully with these factors (Table 2 ) (Supplementary Material_Chi-SquareTest). Table 2 Pearson's Chi-squared test of independence to evaluate the association between litter categories and the categorical variables source (SOMNII/OTHER), sampling unit (VIP, STAGE and CHILLOUT zones), sampling season (winter, spring, summer, autumn) and sampling year (2019, 2020, 2021, 2022, 2023). Chi-square value df p-value Litter categories VS Source 4075.6 7 < 2.2e-16 * Litter categories VS Sampling Unit 655.06 14 < 2.2e-16 * Litter categories VS Season 1052.9 21 < 2.2e-16 * Litter categories VS Year 1358.5 28 < 2.2e-16 * * p-value < 0.05 (statistically significant) The number of items found in the study area is high and well above the European Threshold Value (EU TV) of 20 items/100 m (van Loon et al., 2020 ). A total of 26742 items were collected in the SOMNII festival sampling site from 2019 to 2023, with a total count median of 329 items/100 m. Overall, the median is lower for items that have a SOMNII source (94 items/100m) compared to OTHER sources (235 items/100 m). Higher for items found at the STAGE zone (532 items/100 m), followed by the VIP zone (329 items/100m) and then by the CHILLOUT zone (70 items/100m). Higher for items collected in the summer (569 items/100 m) and lower in the winter (184 items/100 m). The magnitude of beach litter pollution from SOMNII sources shows a different trend over the years compared to OTHER sources. Items from SOMNII sources showed a sharp decrease between 2019 and 2021, a time period without festival editions that covers the COVID19 pandemic, followed by an increase in 2022 when the festival returned, and a subsequent decrease in 2023 when massive cleanups were implemented by the festival organization (Fig. 5 ). Despite the trends observed, no significant decreases in both total counts and plastic items have been observed for items from SOMNII sources, at the site and at the zone scales (Table 3 ). Items from OTHER sources experienced an increase between 2019 and 2020, before the COVID 19 lockdown, followed by a sharp decrease between 2020 and 2021 (COVID19), a slight decrease until 2022 (after COVID19) and another sharp decrease until 2023 (massive cleanups related to the SOMNII festival) (Fig. 5 ). Table 3 Median total and plastic counts (from 2019 to 2023), and associated trends, for items from SOMNII sources, in the site area and zones. TOTAL PLASTIC (Artificial Polymer materials) Geographical scale Median Count (items/100 m) Trend (slope in items/100 m per year) p-value Median Count (items/100 m) Trend (slope in items/100 m per year) p-value Site area 329 -24.46 0.0875 282 -36.42 0.0875 Zones VIP 329 -24.46 0.2712 282 -36.42 0.3575 STAGE 532 -86.12 0.2167 457 -80.55 0.2448 CHILLOUT 70 -10.97 0.1715 56 -10.8 0.1006 Note: All p-values are not significant. The analysis of litter composition shows a predominance of items made of artificial polymer materials, also known as plastics (Fig. 6 ). At the site scale (SOMNII Festival area scale), plastic items represent 90.38% of the pollution, with a median of 282 items/100 m whereas other materials do not exceed 14 items/100 m. Similar results are observed at the VIP (88.68%), the STAGE (89.78%) and the CHILLOUT (96.55%) zones. When analyzing litter composition by source, the medians indicate that items from SOMNI sources belong only to four categories: Artificial polymer materials, Metal, Paper/Cardboard and Cloth. Artificial Polymer Materials are dominant, but those for which we are certain come from the SOMNII festival (SOMNII sources) show the highest counts in the STAGE zone, where most participants gather during the festival. The remaining plastic items show the highest counts in the VIP zone, which is farther away from the swash zone and closer to the dunes. Predicting the number of items There is a statistically significant probability that all category items, except for Paper/Cardboard, appear less frequently than Artificial polymer materials (Table 4 ). For instance, cloth items are 1.67 times less likely to appear than artificial polymer items. Items from the SOMNII festival are 1.05 times more likely to appear than items from OTHER sources. This does not imply a greater number of SOMNII items overall, but rather that these items have a higher probability of occurrence within a specific category and zone. Additionally, SOMNII items are 0.76 times more likely to be collected in the STAGE zone than in the VIP zone, but 1.16 times less likely to be collected in the CHILLOUT zone. This is in line with the intensity of festival-goers expected in each of three sampling units. The zero-inflation part of the model indicates that some litter categories, the zone and the years have a meaningful impact on the probability of an observation being an excess zero. An increase in the predictor variable (positive estimates) is associated with a higher probability of an observation being an excess zero. In other words, and for the specific case of this study, there is a statistically significant lower probability of collecting Cloth, Metal, Paper and Rubber items. This information is consistent with the fact that most of the items are artificial polymers. For each item found there is a significant lower probability of collecting items from the CHILLOUT zone than from the VIP zone, suggesting several items were actually more frequently released in this zone. This is in accordance with what we know from the festival SOMNII, that the CHILLOUT zone had the lower number of festival goers and hence, less litter. Additionally, there was a significant lower probability of collecting items in 2020 up to 2023 than in 2019, which is again consistent with known events that may result in less litter: festival cancellation, COVID19 and massive clean-ups, after 2019. Table 4 Zero-inflated model fitted to the variables ‘category’, ‘source’ and ‘sampling unit’ to model the count in the negative binomial part. The variables ‘category’, ‘source’, ‘sampling unit and ‘year’ model the logit part. This model fits the data significantly better than the null model (intercept-only), with a p-value of 8.937496e-232 (df = 27). Model formula: nr ~ cat + source + samplingunits | source + samplingunits + year + season Count model (negative binomial) coefficients Estimate Std. Error z value Pr(>|z|) (Intercept) 1.00874 0.09641 10.463 < 2.00E-16 *** Cloth -1.66619 0.26623 -6.258 3.89E-10 *** Glass and ceramics -1.21497 0.24856 -4.888 1.02E-06 *** Metal -1.64681 0.1612 -10.216 0.65759 *** Paper/Cardboard -0.08986 0.20273 -0.443 0.01721 Processed / Worked Wood -0.67395 0.28291 -2.382 1.28E-12 * Rubber -2.17006 0.30578 -7.097 0.00126 *** Undefined -1.36214 0.42241 -3.225 3.16E-11 ** SOMNII source 1.04711 0.15773 6.639 3.11E-09 *** STAGE 0.76317 0.12879 5.926 < 2.00E-16 *** CHILLOUT -1.15969 0.12766 -9.084 < 2.00E-16 *** Log(theta) -2.74007 0.03893 -70.391 |z|) (Intercept) -45.5334 5.71E + 04 -0.001 0.99936 Cloth 1.3557 4.94E-01 2.747 0.00601 ** Glass and ceramics 17.4494 1.03E + 03 0.017 0.98649 Metal 0.6282 2.57E-01 2.442 0.01462 * Paper/Cardboard 1.3063 3.30E-01 3.956 7.61E-05 *** Processed / Worked Wood 43.2256 5.71E + 04 0.001 0.9994 Rubber 1.7047 6.63E-01 2.573 0.01009 * Undefined 19.0714 4.09E + 03 0.005 0.99628 SOMNII source 45.0296 5.71E + 04 0.001 0.99937 STAGE zone 0.1627 1.82E-01 0.896 0.37009 CHILLOUT zone 1.1992 2.21E-01 5.429 5.67E-08 *** 2020 0.8892 2.96E-01 3.003 0.00267 ** 2021 1.1892 3.00E-01 3.96 7.48E-05 *** 2022 0.8084 2.96E-01 2.734 0.00626 ** 2023 0.9713 3.12E-01 3.116 0.00183 ** Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Theta = 0.0622. Number of interations = 67. Log-likelihood: -7989(df = 21) Maritime-related plastic items (SEA), Single-use plastics (SUP) and measures coverage The “Maritime-related plastic items” (SEA) and the “Single-use Plastics” (SUP) categories represent 39.46% of litter items. SEA materials represent 1.08% of litter items, and, as expected, do not have a SOMNII source. Their presence is higher in the CHILLOUT zone (2.56%). These results were expected since this sampling unit is closer to the sea shore where fishing-related items, such as lobster/fish tags, octopus pots, nets, and strings and cords (which can come from different sources but are often mainly related to fishing), are potentially more prone to be found (Ouyang & Yang, 2022 ; Watson et al., 2022 ). SUP materials represent 38.38% of litter items, 17.54% being attributed to the RFM SOMNII Festival. Median counts were higher at the STAGE zone (183 items/100 m from SOMNII festival and 25 items/100m from OTHER sources (Fig. 7 ). The trend of SUP from the SOMNII source over the years (Fig. 7 ) follows the same general trend (Fig. 5 ), indicating a correct classification of these items. However, the trend over the years of both SUP and Other items, from OTHER sources, with increasing trends once the festival returns in 2022, indicates that SOMNII items are potentially sub-accounted. 50% of the litter items collected are targeted either by the OSPAR Regional Action Plan on Marine Litter (ML RAP) 2014–2020 or the EU SUP Directive 2019 /904. Top litter types The top 15 litter types are dominated by non-identifiable items, such as plastic/polystyrene pieces (0–2.5 cm and 2.5–50 cm) and other plastic/polystyrene fragments, with median values exceeding 50 litter items per 100 meters at the VIP and STAGE zones (Fig. 8 ). These, along with “String and cord (diameter less than 1 cm)”, consist of fragments of artificial polymer materials with untraceable sources. The presence of these items suggests a potential underestimation of the median of items originating from SOMNII sources. Among the top 15 litter types, six are Single-Use Plastics (SUP): cigarette butts, caps/lids, cotton bud sticks, crisp/sweet packets and lolly sticks, cutlery/trays/straws, and drink-related items (e.g. bottles). The median for cigarette butts stands out at 117 items per 100 meters in the STAGE zone, the area with the highest concentration of festival-goers. Other SUP items, such as caps/lids, crisp/sweet packets and lolly sticks, cutlery/trays/straws, and drink-related items, are typical of these types of events. Drink-related items rank among the top 15 in the CHILLOUT zone, whereas cutlery/trays/straws appear in the top 15 only within the VIP and STAGE zones, which is logical given their proximity to meal areas. Given the European ban on plastic plates, cutlery, straws, drink stirrers and containers made of expanded polystyrene, in July 2021 (Currie et al., 2023 ; Souza Filho et al., 2023 ), it is relevant to look upon the trend of these items over time (Fig. 9 ). They still show an increase once the festival returned, but at lower median counts. Zip ties also deserve attention. Absent from the top 15 at the CHILLOUT zone, their median values reach 33 items per 100 meters in the VIP zone and 32 items per 100 meters in the STAGE zone. Zip ties are commonly used for bundling and securing musical equipment during transportation and setup, organizing electrical and audio cables, and stabilizing temporary structures like protective barriers. Discussion Context-Specific Observations The results of this study reveal event-specific debris characteristics. For instance, higher densities of litter in zones with intense human activity, such as the STAGE zone, corroborate findings from studies on event-related waste, where human presence and dynamics strongly correlates with litter accumulation (Asensio-Montesinos et al., 2019 ; Garcés-Ordóñez et al., 2020 ; Grelaud & Ziveri, 2020 ). The correlation between human density and waste generation in events is potentially related to behavioral and event-specific factors that play a pivotal role in waste accumulation. There is a tendency of attendees to discard items on the ground, particularly during performances or in crowded areas (Rangoni & Jager, 2017 ). This behavior is highly consistent with the distribution of cigarette butts in the SOMNII festival. Cigarette butts are recognized as one the most common forms of personal litter around the world (Araújo & Costa, 2021 ) and in the festival area are the most frequent item in the STAGE zone. The behavior to discard items to the ground is influenced by demographic variables, with disparities between anti‑litter attitudes, willingness to act, and individual accountability (Lev et al., 2023 ), but also by the availability and accessibility of waste disposal facilities (Rangoni & Jager, 2017 ). For instance, inadequate placement or an insufficient number of bins can lead to an increase in improper disposal practices (Rangoni & Jager, 2017 ). Another context-specific finding is the significant presence of zip ties in the VIP and STAGE zones and which reflects logistical practices specific to festival setups, such as the transportation and organization of equipment. This contrasts with urban beach studies, where such items are reported less frequently (Fernández García et al., 2024 ; Fernández-Enríquez et al., 2024 ). Additionally, the ease of attributing certain litter items to SOMNII sources is linked to brand marketing strategies involving the distribution of branded cups, wristbands, and other promotional materials. These strategies are commonplace at festivals, and, while they directly contribute to the volume of waste generated, they also present an opportunity for improved waste management strategies. The significant differences observed between festival zones (VIP, STAGE, CHILLOUT) are also characteristic of such events. Spatial variations in items like cigarette butts and food- and drinks-related litter reflect the movement of the crowd. Although these items are not new in event monitoring and management, the stratified sampling approach employed in this study is uncommon in beach litter monitoring and should be considered for events held on beaches. Findings from stratified sampling improve accuracy and representativeness (Bravo et al., 20 C.E.; Ramos et al., 2016 ) and may offer valuable insights into the spatial variability of litter accumulation and into crowd behavior in large-scale events, enabling the implementation of targeted waste management strategies. Alignment with global patterns of beach litter composition Beach litter composition observed is consistent with global patterns. The predominance of artificial polymer materials, which constitute over 90% of the litter, is in line with global trends that identify plastics as the primary marine pollutant (Ali & Shams, 2015 ; Fernández-Enríquez et al., 2024 ; Garcés-Ordóñez et al., 2020 ; Pervez et al., 2020 ). The prevalence of artificial polymer materials from sources not related to the festival in zones away from the shoreline and near dune plants is also consistent with global-scale studies suggesting dune plants as sinks for marine litter (Gallitelli et al., 2023 ). The presence of maritime-related items in the CHILLOUT zone, closer to the shoreline, is also consistent with global research indicating that fishing-related debris is more likely to accumulate in areas near the swash zone (Ouyang & Yang, 2022 ; Watson et al., 2022 ). Debris can be transported to the coastal region from the oceans by nearshore currents, tidal cycles, regional-scale topography, intentional or accidental disposal (Ouyang & Yang, 2022 ; UNEP, 2009 ). The pattern observed over time is also aligned with global studies. The waste accumulation in the summer season is consistent with the increase of people in tourist seasons (Asensio-Montesinos et al., 2019 ; Garcés-Ordóñez et al., 2020 ) and with the role of large-scale events in exacerbating coastal pollution (Oliveira et al., 2022 ). The sharp reduction in litter during festival-free years (2020–2021) is consistent with the role of the COVID19 pandemic lockdowns in reducing beach litter from terrestrial sources (Currie et al., 2023 ; Souza Filho et al., 2023 ). The slight litter decrease in 2023, when a massive clean-up regime was implemented after the festival, is consistent with the expected positive impact of waste management strategies (Rangoni & Jager, 2017 ). These findings reinforce the importance of conducting long-term studies as they allow for the identification of trends that may not be apparent in short-term studies. In the particular case of this study, a decrease in litter suggests a relationship with the COVID19 pandemic and with post-event clean-ups. In other situations, it may suggest the effectiveness of broader environmental policies and public awareness campaigns (Dodds et al., 2022 ; Gration et al., 2011 ; Williams & Rangel-Buitrago, 2019 ). These temporal variations offer critical insights for designing mitigation strategies (Oliveira et al., 2022 ) and contribute to broader discussions on the environmental impact of large-scale coastal gatherings (Gallagher A & Pike K, 2011 ). Advancing monitoring methodologies: A stratified OSPAR framework for event-driven litter dynamics Despite increasing recognition of beaches as critical monitoring sites for marine litter, standardized methodologies, including OSPAR’s, remain optimized for long-term, low-frequency monitoring across broad spatial units (Wenneker et al., 2010 ). These designs often struggle to capture acute, short-lived pollution events associated with high-density, high-tempo activities like beach festivals (Gallagher A & Pike K, 2011 ). This study addresses that methodological blind spot by adapting the OSPAR monitoring protocol into a stratified, high-resolution sampling framework tailored to the spatiotemporal dynamics of a large-scale beach event. By partitioning the SOMNII festival site into three functionally distinct zones - VIP, STAGE, and CHILLOUT - each sampled using fixed 100 m × 50 m plots, this approach enabled fine-scale detection of litter accumulation and composition. Stratification revealed significant spatial differences: STAGE areas averaged around seven times more litter than CHILLOUT zones, and litter composition varied by zone and source. Without this zoning, such detail would likely have been obscured under a conventional 100 m transect model (Asensio-Montesinos et al., 2019 ). Importantly, the method uncovered clear temporal shifts in litter dynamics, driven by external events such as COVID-19-related festival cancellations and the introduction of intensive post-festival cleanups in 2023. The results indicate that stratified OSPAR monitoring not only enhances the sensitivity of event-driven litter detection but also improves hotspot identification, informing better spatial targeting of waste prevention measures (van Loon et al., 2020 ). These insights offer a scalable monitoring template for other tourist-intensive coastal environments, where functional zoning (e.g., event spaces, recreational zones, food/beverage areas) can vary but follow broadly similar patterns (Dodds et al., 2022 ). Event organizers and coastal managers may adopt this framework to create “event-specific litter response plans”, combining real-time monitoring with targeted interventions such as bin placement, signage, and reusable item programs (Prasuhn et al., 2017 ). While the approach is broadly applicable and logistically feasible - it leverages standard OSPAR analysis protocols and tools (e.g., the R package litterR) - it is not without limitations. Zone-specific monitoring requires coordination with event planners and local authorities to ensure access and optimal timing. Though not more labor-intensive than traditional approaches, increased temporal frequency may impact resource needs. Moreover, the classification of items by source, while grounded in site-specific observations and item characteristics, inevitably involves some uncertainty, particularly for unbranded plastic fragments and cross-purpose items like zip ties (van Loon et al., 2020 ). Lastly, the transferability of the zonation scheme must account for the spatial layouts of other events, as direct replication is not always viable. Nonetheless, the insights gained from this stratified approach justify its added complexity, offering a replicable and scientifically robust enhancement to conventional marine litter monitoring. By integrating functional spatial analysis into existing frameworks, this method supports both regulatory evaluation (e.g., OSPAR’s RAP ML and the EU SUP Directive 2019 /904) and the design of targeted, evidence-based waste mitigation strategies (Gallagher A & Pike K, 2011 ). Policy leverage and collaborative strategies for event-driven litter mitigation Large-scale coastal events present a valuable opportunity to evaluate the effectiveness of mitigation efforts and shape future waste management strategies. Following the 2023 edition of the RFM SOMNII festival, extensive cleanup operations led to marked reductions in litter density, particularly in high-traffic areas. This decrease, most pronounced in the STAGE and VIP zones, highlights the effectiveness of targeted cleanup interventions in reducing the environmental footprint of such events (Rangoni & Jager, 2017 ). At the same time, the high prevalence of artificial polymer fragments reveals the limitations of cleanup operations, which primarily address visible waste while overlooking less conspicuous pollutants (Galgani et al., 2015 ; Santillán et al., 2023 ). Plastic fragments are of particular concern because they often exhibit inherent weaknesses that make them more susceptible to degradation (Baby et al., 2024 ). This poses additional biological risks, as smaller particles are ingested by marine organisms, entering the food chain with potential consequences for ecosystem health and human wellbeing (Browne et al., 2015 ). Moreover, the unidentifiable nature of litter fragments (Zielinski et al., 2022 ) rises litter categorization issues, that skew conclusions (Watts et al., 2017 ) and make the implementation of targeted measures more challenging. In the context of litter monitoring events, it also exacerbates the problem of distinguishing between event-related waste and pre-existing litter. While branded items like cups or wristbands can be directly linked to an event, a significant portion of the litter consists of non-branded or fragmented items that are harder to trace. The findings provide empirical support for the implementation and enhancement of policies such as the EU Single-Use Plastics (SUP) Directive (Directive (EU) 2019 /904 on the Reduction of the Impact of Certain Plastic Products on the Environment., 2019)) and the OSPAR Regional Action Plan on Marine Litter (RAP ML 2) 2022–2030 (OSPAR Commission, 2022 ). Both frameworks aim to reduce plastic pollution through measures such as the restriction or elimination of SUP items, improved waste management, and public education. The SOMNII festival seems to be itself evidence of the success of such policies. In Europe, the European Union has banned the commercialization of single-use plastics, including plastic straws and cutlery, as of July 2021. As a consequence, the presence of these items was reduced in 2022 and 2023, compared to 2019 (previous festival edition). However, these banned items, along with other SUP items, such as cigarette butts and food-related packaging, persisted, especially in high-density areas and despite the cleaning efforts. Could these policies be strengthened during public events by introducing bans on specific items or mandating reusable alternatives (Williams & Rangel-Buitrago, 2019 )? Waste management practices implemented in large-scale events in Portugal (Interreg Europe, 2022 ) and Málaga (Interreg Europe, 2025 ) seem to corroborate this possibility. Stricter regulations on waste management for event organizers could also include the requirement for comprehensive cleanup plans (Rangoni & Jager, 2017 ; Williams & Rangel-Buitrago, 2019 ). Rangoni & Jager ( 2017 ), for instance, suggest adaptive/dynamical cleaning regimes, which seem to be more effective and cheaper than pre-defined cleaning. This could also reduce issues related to festival peak hours that often lead to litter dispersing into adjacent areas due to crowds’ movement, complicating collection efforts and reducing cleanup efficiency. Other sustainable practices for waste management of large-scale events could include the increase of recycling opportunities through the deployment of smart bins and AI-driven waste sorting systems to improve the efficiency of waste segregation and processing (Ramasawmy & Nagowah, 2023 ). Public awareness campaigns represent another essential component of waste management strategies, especially those that foster behavioral changes that contribute to long-term reductions in litter generation (Bär et al., 2022 ). Educating festival-goers about the environmental impacts of improper waste disposal, through both digital platforms and on-site initiatives, could foster a sense of shared responsibility among attendees. Signage promoting responsible waste disposal, accompanied by clear instructions on waste segregation, could also foster environmentally conscious behavior. In high-impact zones, interactive campaigns, such as reward systems for proper waste segregation, could effectively engage attendees and incentivize responsible behavior. The findings point to the necessity of proactive collaboration of event organizers with researchers, industry and local decision-makers. Collaboration with researchers would support the identification and tracking of specific items more efficiently (Zielinski et al., 2022 ). This could support the identification of potential waste hotspots within the event site, helping organizers to implement targeted waste collection strategies (e.g. strategically placing bins or staff deployment), translated into cost savings. It could identify problematic waste sources, enabling organizers to adopt sustainable practices and comply with environmental regulations, such as reducing single-use plastics or promoting reusable alternatives. It could also provide valuable data on attendee behavior and waste generation patterns, which can inform future event planning and layout optimization (Martinho et al., 2018 ). One collaboration approach could involve authorizations for pre- and post-event litter composition surveys to establish clearer baselines for monitoring the effectiveness of interventions over time (Zielinski et al., 2022 ). Another collaboration could involve tagging branded items distributed during the events with advanced technologies such as QR codes (Aparna et al., 2022 ), enabling researchers to trace the origins of specific items more efficiently. This would also need to rely on collaboration with industry to provide such technologies. Other collaborations with industry could focus on developing and adopting alternatives for problematic items, such as zip ties, for which sustainable options, on paper, bio-based plastics, and recycled PET, are already available. Collaboration with decision-makers plays a pivotal role in implementing targeted solutions for environmental sustainability at events. Such partnerships can take various forms. For example, event organizers and decision-makers can coordinate the installation of adequate waste management infrastructures, such as recycling bins, composting stations, and waste collection points, to address the unique challenges of coastal environments (Oliveira et al., 2022 ). Joint efforts can also be directed towards public awareness campaigns that educate attendees on the environmental impacts of littering and foster responsible waste disposal behaviors (Mair & Laing, 2013 ). Furthermore, collaborative initiatives can extend to reward systems, such as discounts or tokens, to encourage attendees to engage in proper waste segregation and recycling (Yang et al., 2024 ). Additionally, local authorities can play a key role in establishing or promoting adherence to sustainability certifications for events, which serve as benchmarks for effective waste management and environmental responsibility (Nygaard, 2023 ). They can also incentivize the redirection of reusable or repurposable waste through the implementation of donation programs benefiting local institutions (Oliveira et al., 2022 ). Conclusions This study demonstrates the value of adapting established monitoring frameworks - specifically the OSPAR methodology - to better capture the spatial and temporal complexities of marine litter generated during large-scale coastal events. By implementing a stratified sampling design across functionally distinct zones of the RFM SOMNII festival site, the research revealed clear patterns of litter accumulation and material composition that would likely have been missed using conventional beach monitoring protocols. These insights not only advance our understanding of event-driven pollution dynamics but also highlight the potential of tailored methodologies to inform more targeted and effective waste management interventions. While the dominance of artificial polymer materials and single-use plastics (SUP) remains a consistent challenge, the study demonstrates that refined sampling approaches can support hotspot detection and improve attribution, critical steps for prevention and mitigation. The unique context of the COVID-19 pandemic further enabled a contrast between festival-active and inactive periods, providing rare empirical evidence on the direct influence of human activity. Beyond the case study, the stratified monitoring framework offers a replicable blueprint for enhancing marine litter assessments under similarly dynamic and high-pressure coastal conditions. Its application can improve decision-making by identifying pollution hotspots, refining litter source analysis, and supporting compliance with policy frameworks such as the EU SUP Directive and OSPAR’s Regional Action Plan. Future research should explore how integrating traceability technologies, automated detection tools, and stakeholder collaboration can further strengthen attribution accuracy and operational efficiency. Together, these innovations can accelerate progress toward more sustainable coastal event management and marine environmental protection. Declarations Human Ethics and Consent to Participate declarations not applicable Declaration of Interests 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. Funding Declaration This work was supported by the FCT – Fundação para a Ciência e Tecnologia [grant numbers UIDB/04292/2020 ( https://doi.org/10.54499/UIDB/04292/2020 ); UIDP/04292/2020 ( https://doi.org/10.54499/UIDP/04292/2020 ); LA/P/0069/2020 ( https://doi.org/10.54499/LA/P/0069/2020 ); UID/04292/MARE-Centro de Ciências do Mar e do Ambiente; UIDB/04035/2020 ( https://doi.org/10.54499/UIDB/04035/2020 ); CEECINST/00152/2018/CP1570/CT0007 ( https://doi.org/10.54499/CEECINST/00152/2018/CP1570/CT0007 ); CEECINSTLA/00018/2022/CP2967/CT0001 ( https://doi.org/10.54499/CEECINSTLA/00018/2022/CP2967/CT0001 ); UI/BD/150952/2021 ( http://dx.doi.org/10.13039/501100001871 ); SFRH/BD/147777/2019 ( http://dx.doi.org/10.13039/501100005727 ); and 2022.12166.BD; 2023.04308.BDANA]. Author Contribution Z.T. and C.M. defined the overarching research goals and the design of the methodology. Z.T., A.C., and P.C. ensured data curation for both initial use and future reuse. C.G., C.M., A.B., D.P., D.M., and L.R. made substantial contributions to data collection throughout the five-year field campaigns. Z.T., A.C., and C.M. collaborated on the statistical analysis.Z.T. drafted the original manuscript, prepared the final figures and tables for publication, and was primarily responsible for planning and executing the research activities, as well as securing the main financial support. C.M. supervised the planning and execution of the research activities and provided mentorship beyond the core team.All authors critically reviewed the manuscript, approved the final version for publication, and agree to be accountable for all aspects of the work, ensuring that any questions related to its accuracy or integrity are thoroughly investigated and resolved. Acknowledgement The authors gratefully acknowledge the invaluable additional contributions of the following researchers and students during fieldwork: Patrícia Rita, Bárbara Camarão, Daniela Silva, Duarte, Juliana Spitz, Marta Ressurreição, Sofia Cunha, Amani Abusaid, Ana Gomes, Diogo Costa, Eunice, Irene Gutierrez, Jonas, Juan Flores, Rafael, Tiago Miguel Cerqueira, Tiago Verdelhos, and Vera Lamas. We would also like to thank the Municipality of Figueira da Foz and local authorities for authorizing sampling during COVID-19 lockdowns. Data Availability Data is available at https://zenodo.org/records/15303685 under the title "Dataset Seasonal Data on Beach Litter from a Massive Music Festival in Portugal (2019–2023)" (Anonymous). The dataset is available in raw and processed formats. References Ali, R., & Shams, Z. I. (2015). Quantities and composition of shore debris along Clifton Beach, Karachi, Pakistan. 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Supplementary Files SupplementaryMaterialChiSquareTest.pdf SupplementaryMaterialImages.pdf Cite Share Download PDF Status: Published Journal Publication published 10 Apr, 2026 Read the published version in Environmental Monitoring and Assessment → Version 1 posted Editorial decision: Revision requested 24 Nov, 2025 Reviews received at journal 21 Nov, 2025 Reviews received at journal 07 Nov, 2025 Reviewers agreed at journal 05 Nov, 2025 Reviewers agreed at journal 31 Oct, 2025 Reviewers invited by journal 30 Oct, 2025 Editor assigned by journal 21 Oct, 2025 Submission checks completed at journal 21 Oct, 2025 First submitted to journal 02 Oct, 2025 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. 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18:56:16","extension":"xml","order_by":47,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":214869,"visible":true,"origin":"","legend":"","description":"","filename":"2ac1f49b15044e759fb38c0d0b7465391structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7767950/v1/f9c9f65196138f879e065992.xml"},{"id":95677321,"identity":"24c23901-f56c-4249-8879-7a57f61d60ea","added_by":"auto","created_at":"2025-11-11 18:56:15","extension":"html","order_by":48,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":234411,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7767950/v1/8b5e86c734a9183e1eed86ce.html"},{"id":95677269,"identity":"eb6f1703-9c74-4470-b462-3e6082020578","added_by":"auto","created_at":"2025-11-11 18:56:14","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":545419,"visible":true,"origin":"","legend":"\u003cp\u003eLocation of RFM SOMNII Beach Music Festival at Praia do Relógio, Figueira da Foz, Portugal, with stratified sampling units categorized into VIP, STAGE, and CHILLOUT zones.\u003c/p\u003e","description":"","filename":"Fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7767950/v1/ff0403085f43bd6b17bc2069.jpg"},{"id":95797413,"identity":"160c752f-ab17-44ee-a6ce-27b38efdd8b4","added_by":"auto","created_at":"2025-11-13 08:04:48","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":91799,"visible":true,"origin":"","legend":"\u003cp\u003eTimeline illustrating key events in the history of the RFM SOMNII festival and related occurrences from 2019 to 2023. The timeline highlights significant milestones, including the cancellation of the festival in 2020 and 2021 due to the COVID-19 pandemic and the first and last field campaigns conducted after SOMNII’19 and BR FEST’23. BR FEST’23 was a second festival held at the same location, using the same infrastructure. Post-festival field campaigns were conducted one to two weeks after the complete dismantling of the infrastructure.\u003c/p\u003e","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7767950/v1/1a4191b7d623388068a2469a.jpg"},{"id":95798810,"identity":"feabd61a-b3dd-46cf-97eb-941688a2c404","added_by":"auto","created_at":"2025-11-13 08:17:54","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":39593,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal variation in cigarette butt accumulation across the three festival zones: VIP, STAGE, and CHILLOUT. Peaks in litter counts are observed in the STAGE zone during campaigns conducted immediately after festival editions, whereas the CHILLOUT and VIP zones show relatively stable and consistently lower counts of cigarette butts across all sampling dates.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7767950/v1/7fbcb5ab278650bda4274fb0.jpg"},{"id":95677274,"identity":"2d7822bd-b0f8-42be-a95e-34fcbb2a7eb2","added_by":"auto","created_at":"2025-11-11 18:56:14","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":55870,"visible":true,"origin":"","legend":"\u003cp\u003eHistograms illustrating the frequency distribution of litter items by material composition: Artificial Polymer Materials (plastic), Cloth, Glass/Ceramics, Metal, Paper (Paper/Cardboard), Processed/Worked Wood, Rubber and Undefined. Mean and variance values are provided for each category, highlighting the variability in item counts. Artificial Polymer Materials exhibit the highest mean and variance.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7767950/v1/fd265cebd2327bef394d1bd7.jpg"},{"id":95677275,"identity":"03334a8c-58a8-4b17-9692-4200b25342a4","added_by":"auto","created_at":"2025-11-11 18:56:14","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":196172,"visible":true,"origin":"","legend":"\u003cp\u003eTrends in the median number of litter items per 100 meters, per litter category, from 2019 to 2023 for two distinct sources: \"SOMNII sources” (top) and \"OTHER sources” (bottom). From SOMNI sources (top), with the exception of the Artificial Polymer Materials, Paper/Cardboard, and Metal categories, the medians for all other categories consistently remained at 0 across all years.\u003c/p\u003e","description":"","filename":"F3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7767950/v1/68d8cae63c10a5ffecb9aad9.jpg"},{"id":95799350,"identity":"e4bffe52-f415-4d20-a12a-fd145384c05e","added_by":"auto","created_at":"2025-11-13 08:19:41","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":150049,"visible":true,"origin":"","legend":"\u003cp\u003eMedian number of litter items per 100 meters, per litter category, across three festival zones: VIP, STAGE, and CHILLOUT, for two distinct sources: \"SOMNII sources\" (top) and \"Other sources\" (bottom). Artificial Polymer Materials are dominant, but those for which we are certain come from the SOMNII festival (SOMNII sources) show the highest counts in the STAGE zone. The remaining plastic items show the highest counts in the VIP zone.\u003c/p\u003e","description":"","filename":"F4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7767950/v1/c3763056bdbf580c00268205.jpg"},{"id":95798879,"identity":"9722f76a-be26-455e-b8de-a5bfbc534c5d","added_by":"auto","created_at":"2025-11-13 08:18:06","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":93256,"visible":true,"origin":"","legend":"\u003cp\u003eBar Chart (Left): median number of items per 100 meters, categorized by type - Single-use plastics (SUP), Maritime-related plastic items (SEA) and other -, across three festival zones: VIP, STAGE, and CHILLOUT, from two distinct sources: \"SOMNII sources\" and \"OTHER sources\". SUP medians from the SOMNII festival are higher than from OTHER sources and SEA items are absent. Line Graph (Right): Trends of Single-use plastics (SUP) items per 100 meters from SOMNII sources across sampling years (2019 to 2023) which highlights the decline in SUP items during festival cancellations in 2020 and 2021.\u003c/p\u003e","description":"","filename":"F5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7767950/v1/de8f89e29b98a76238d21379.jpg"},{"id":95677284,"identity":"d59e4153-cca2-49f5-94d8-a4bd82084aa3","added_by":"auto","created_at":"2025-11-11 18:56:15","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":812927,"visible":true,"origin":"","legend":"\u003cp\u003eMedian number of top 15 litter types (Items/100m) in the VIP, CHILLOUT, and STAGE zones. The VIP zone shows high prevalence of small plastic/polystyrene pieces (0–2.5 cm), the CHILLOUT zone shows a large median number of plastic/polystyrene pieces (2.5–50 cm), and the STAGE zone features a high median number of cigarette butts.\u003c/p\u003e","description":"","filename":"F6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7767950/v1/4ca9d27542de173a0ecb4e5b.jpg"},{"id":95799627,"identity":"f16bd427-89f1-4289-bcc7-2413c757f407","added_by":"auto","created_at":"2025-11-13 08:20:26","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":86750,"visible":true,"origin":"","legend":"\u003cp\u003eMedian number of cutlery/trays/straws per 100 meters, across three festival zones: VIP, STAGE, and CHILLOUT, from 2019 to 2023. The data shows the impact of COVID-19 lockdowns and festival cancellations in 2020 and 2021, and the potential impact of EU restrictions on single-use plastics (SUP) introduced in 2021.\u003c/p\u003e","description":"","filename":"F7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7767950/v1/3a1cd1ebb11400ee4da1952c.jpg"},{"id":106809529,"identity":"819e218a-9d24-498d-94cb-92395cde27da","added_by":"auto","created_at":"2026-04-13 16:11:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3099034,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7767950/v1/a1b223fb-415e-4ab7-b3f1-0f61fb979166.pdf"},{"id":95798897,"identity":"5598cfef-5595-49db-a75e-9618c9a65866","added_by":"auto","created_at":"2025-11-13 08:18:09","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":199042,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterialChiSquareTest.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7767950/v1/0bb6979d2b052971f082fb60.pdf"},{"id":95677289,"identity":"c789ffc4-5101-420c-af8a-f9f96a865d6f","added_by":"auto","created_at":"2025-11-11 18:56:15","extension":"pdf","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":495655,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterialImages.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7767950/v1/5710a98bc7a49d3a68ec4e30.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Stratifying the Shoreline: A Modified OSPAR Framework to Monitor Event-Driven Beach Litter","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMarine litter represents a pressing global environmental challenge with broad implications for marine ecosystems, human health, and local economies. Plastics, which dominate marine debris, often accumulate on shorelines (Garc\u0026eacute;s-Ord\u0026oacute;\u0026ntilde;ez et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Grelaud \u0026amp; Ziveri, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), reducing aesthetic value, threatening wildlife, and interfering with human activities (Browne et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Although just\u0026thinsp;~\u0026thinsp;0.1% of global plastic production enters the ocean annually (C\u0026oacute;zar et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), this still amounted to an estimated 5.5\u0026ndash;14.5\u0026nbsp;million metric tons in 2018 (Wayman \u0026amp; Niemann, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), highlighting the persistent and growing magnitude of the problem.\u003c/p\u003e\u003cp\u003eAmong various pressures, urban beaches experience heightened litter inputs due to high visitation, tourism, and recreational events (Garc\u0026eacute;s-Ord\u0026oacute;\u0026ntilde;ez et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Notably, large coastal festivals contribute episodic surges in litter loads, the impacts of which are poorly characterized and often underestimated (Oliveira et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eBeaches serve as dynamic interfaces between terrestrial and marine systems, functioning simultaneously as sinks and sources for anthropogenic debris (Gallitelli et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Jambeck et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), making beach litter one of the most visible indicators of environmental pollution. Urban beaches, in particular, face increased littering pressures due to their accessibility, popularity among tourists, and high foot traffic (Garc\u0026eacute;s-Ord\u0026oacute;\u0026ntilde;ez et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Grelaud \u0026amp; Ziveri, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Seasonal increases in litter pollution have been widely documented on beaches across the globe, from Spain and China to Brazil and the Mediterranean (Ali \u0026amp; Shams, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Asensio-Montesinos et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Grelaud \u0026amp; Ziveri, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Pervez et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Ribeiro et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Beyond these pressures, large coastal events contribute episodic surges in litter loads, the impacts of which are poorly characterized and often underestimated (Oliveira et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). While promoting cultural and recreational engagement, these events draw large crowds, generating substantial waste that, if not managed effectively, can cause long-term environmental degradation (Browne et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). To ensure sustainable management of such events, the environmental impacts of litter accumulation must be thoroughly understood and addressed (Williams \u0026amp; Rangel-Buitrago, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDespite the recognition of these hotspots, there is a methodological gap in understanding how event-driven litter deposition unfolds over space and time. Traditional beach monitoring protocols - though standardized - often lack the spatial resolution and temporal sensitivity needed to detect short-lived yet intense pollution episodes. In this context, methodological innovations are essential to develop monitoring strategies capable of capturing dynamic littering phenomena with sufficient granularity.\u003c/p\u003e\u003cp\u003eThis study addresses that gap by adapting the OSPAR methodology to a \u003cem\u003estratified sampling framework\u003c/em\u003e tailored to high-traffic, event-prone coastal areas. Specifically, the research applies this design to the case of RFM SOMNII - one of Europe\u0026rsquo;s largest beach music festivals, held annually in Figueira da Foz, Portugal. With over 100,000 participants each year (RFM SOMNII Festival, n.d.), this site offers a valuable testbed to examine the performance and utility of stratified monitoring in capturing event-driven litter fluctuations.\u003c/p\u003e\u003cp\u003eOver a five-year period - including pre- and post-COVID-19 seasons - this study conducted seasonal and festival-time monitoring at Praia do Rel\u0026oacute;gio, generating a detailed dataset on litter abundance, composition, and distribution. Rather than focusing solely on regional impacts, the goal is to evaluate how stratified OSPAR-based protocols can enhance the detection and interpretation of marine litter patterns linked to large-scale events - contributing to broader efforts to refine international monitoring frameworks and inform adaptive coastal management.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cp\u003eStudy Site and beach music festival\u003c/p\u003e\u003cp\u003eThe study was conducted at Praia do Rel\u0026oacute;gio, an urban beach in Figueira da Foz (\u003cem\u003e40\u0026deg;149161 N, 8\u0026deg; 871150 W\u003c/em\u003e), on the North Atlantic Portuguese coast (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The beach has an average width of 500 meters and extends approximately 2 kilometers in a North-South orientation. The city experiences high levels of tourism during the summer months (mainly July and August), and the beach is public and freely accessible. However, the sampling area is not as popular with sunbathers compared to other areas in the same beach, likely due to a combination of three factors: the beach's large width, its southern boundary being marked by a jetty (Ponte Lira et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), and the western boundary being limited by dunes (Andriolo \u0026amp; Gon\u0026ccedil;alves, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), which restrict direct access to the area.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe sampling area is located at the site of the RFM SOMNII Beach Music Festival (\u003cem\u003eRFM SOMNII Festival\u003c/em\u003e, n.d.), which held its first edition in 2013. Since then, the festival has taken place annually at the beginning of July (summer season), except for the years 2020 and 2021, when it was cancelled due to the COVID-19 pandemic (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This festival, recognized as the largest beach music festival in Portugal and one of the biggest in Europe, typically attracts around 100,000 attendees for 72 hours of music during the afternoons and nights. In 2023, the SOMNII producers organized a second festival, BR FEST, just one week later, at the same location and using the same infrastructure. BR FEST was described as the \u0026ldquo;biggest ever event dedicated to Brazilian music in Portugal,\u0026rdquo; with \u0026ldquo;thousands\u0026rdquo; of participants (\u003cem\u003eBR FEST 2023\u003c/em\u003e, n.d.).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eField Sampling design\u003c/p\u003e\u003cp\u003eThe OSPAR guidelines for monitoring marine litter on beaches (Wenneker et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) specify a standard sampling unit of 100 meters, measured as a straight line parallel to the back of the beach. However, while OSPAR guidelines cover the area between the swash zone and the backshore, this study defined three parallel sampling units, each measuring 100 m x 50 m, within the festival area (total festival area\u0026thinsp;=\u0026thinsp;110 000 m\u003csup\u003e2\u003c/sup\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This adapted methodology was necessary to implement a stratified sampling design representative of the main festival areas: the VIP zone, the STAGE zone, and the CHILLOUT zone. The VIP zone featured a carpeted floor and was located on the east side of the enclosure, at the backshore. The STAGE zone was the middle area where a large number of visitors congregated for long periods. The CHILLOUT zone was located between the food and drink tents and the swash zone, and was mainly used for resting during the festival (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://vimeo.com/rfmsomnii\u003c/span\u003e\u003cspan address=\"https://vimeo.com/rfmsomnii\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eField campaigns were conducted from summer 2019, shortly after the SOMNII festival of 2019, through summer 2023, following the SOMNII festival of 2023. A total of 17 seasonal campaigns were carried out, with one campaign per season (spring, summer, autumn, winter). Each sampling campaign began approximately two hours before low tide. During sampling, two to three individuals surveyed each designated unit (VIP, STAGE, CHILLOUT) along transects.\u003c/p\u003e\u003cp\u003eMacro-litter sampling and identification\u003c/p\u003e\u003cp\u003eOn average, one to two months after sampling, beach litter was sorted, counted, measured (when relevant), and assigned to one of the 112 predefined OSPAR litter types (Wenneker et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The latest OSPAR guidelines classify cigarette butts under the artificial polymer material category, aligning with their plastic composition. As a result, we did not adopt the approach used in previous studies (Ara\u0026uacute;jo \u0026amp; Costa, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Bettencourt et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), which had categorized cigarette butts as a separate group. Those studies relied on earlier OSPAR guidelines that inaccurately placed cigarette butts in the paper/cardboard category, necessitating a workaround to account for their unique nature.\u003c/p\u003e\u003cp\u003eFour individuals participated in the categorization process, with the project coordinator supervising to ensure consistent decision-making criteria for ambiguous items. All items were classified according to the following criteria:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003ea) Material composition, as defined in the MSFD recommendations (MSFD Technical Group on Marine Litter, 2013): Artificial polymer material (also known as plastic), Rubber, Cloth/Textile, Paper/Cardboard, Processed/Worked wood, Metal, Glass/Ceramics, Undefined.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eb) Single-use plastics (SUP) and maritime-related plastics (SEA): The SUP category follows the definitions in the MSFD recommendations (MSFD Technical Group on Marine Litter, n.d.). The SEA category is derived from the FISH category in the MSFD recommendations (Hanke et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), excluding non-plastic items.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003ec) Litter types targeted by existing measures: Specifically, items addressed in the OSPAR Marine Litter Regional Action Plan (OSPAR Commission, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) or the EU SUP Directive (Directive (EU) \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e/904 on the Reduction of the Impact of Certain Plastic Products on the Environment., 2019).\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003ed) SOMNII items and OTHER items: This classification is based on the presumed source of the items. SOMNII items are those confidently identified as left behind by festival participants or staff, such as plastic cups with the festival logo, festival tickets, bracelets and zip ties (Supplementary Material - Images). Cigarette butts were also included in the SOMNII category due to their significant presence during post-festival sampling, especially in the STAGE zone, where the highest attendee concentration is observed (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). OTHER items include all remaining debris not linked to the festival or whose source could not be determined.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eData Analysis\u003c/h2\u003e\u003cp\u003eThe Pearson\u0026rsquo;s Chi-square test of independence was initially performed to evaluate the association between litter categories and the predictor variables: \u0026lsquo;source\u0026rsquo;, sampling unit\u0026rsquo;, \u0026lsquo;season\u0026rsquo;, and \u0026lsquo;year\u0026rsquo;. This non-parametric test was selected due to its appropriateness for categorical data and its ability to assess whether observed frequencies significantly deviate from expected frequencies. The test was performed at a 5% significance level, and the results were interpreted based on the calculated Chi-square values and their corresponding p-values. The Chi-test was carried out using the R Stats package (R Core Team and contributors worldwide, n.d.).\u003c/p\u003e\u003cp\u003eAbundances were assessed by calculating the median of items at the zone scale (for each sampling unit) and aggregated at the site scale (total sampling area) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Median-based statistical methods were chosen because they are well-suited for handling skewed distributions in beach litter data (Schulz et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). It is worth noting that median values are typically lower than mean (average) values, as they exclude extreme outliers, making them more appropriate for decision-making purposes. To calculate percentages, the median of each litter group was divided by the total sum of the medians across all litter groups considered (e.g., the percentage of artificial polymer material is obtained by dividing its median by the total sum of the medians of all material categories). The top 15 litter types were ranked based on the median values of individual litter types. Trends were assessed using the median-based Theil-Sen method, that calculates slopes and associated p-value. Analyses were performed using the litteR package (Walvoort \u0026amp; van Loon, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and Microsoft Excel.\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\u003e\u0026nbsp;List of statistical indicators calculated at the zones and site geographical scales and corresponding calculation methods.\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=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBeach litter indicator\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eSOMNII zones scale\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSOMNII site scale\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAbundance\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eMedian of sampling unit data for the four seasons sampled, within the five-year period from Summer 2019 to Summer 2023.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMedian of sampling units\u0026rsquo; medians\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePercentage\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003e100 \u0026times; median of the category considered divided by the sum of medians of the different categories.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTop 15\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\u003cp\u003eRanking of medians of individual litter types and presentation of the 15 highest ranking types.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTrend\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTheil-Sen slope of sampling unit data for the five-year period from 2019 to 2023. p-value of Theil-Sen slope.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eMedian of sampling units\u0026rsquo; slopes.\u003c/p\u003e\u003cp\u003ep-value of aggregated sampling units.\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 relationship between the number of items collected per litter type and the predictor variables - \u0026lsquo;category,\u0026rsquo; \u0026lsquo;source,\u0026rsquo; \u0026lsquo;sampling unit,\u0026rsquo; \u0026lsquo;season,\u0026rsquo; and \u0026lsquo;year\u0026rsquo; - was explored to identify the predictors that most strongly influence the number of items collected.\u003c/p\u003e\u003cp\u003ePreliminary analysis revealed data overdispersion (variance significantly higher than the mean) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) indicating the need for a Negative Binomial distribution model. Additionally, it was assumed that the dataset includes structural count zeros arising from two distinct processes: sampled areas that were cleaned beforehand and litter types deemed irrelevant to the festival context. As such, a Zero-Inflated Negative Binomial (ZINB) model was implemented, using the pscl package from R software (Jackman S, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Zeileis A et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The ZINB model assumes that excess zeros arise from a separate process, independent of the count data, and models these zeros separately. It consists of two components: the logit model to predict the \u0026ldquo;certain zero\u0026rdquo; cases, identifying whether a variable belongs to this group; and a Negative Binomial model to predict counts for data not classified as \"certain zeros\". In this study, particular interest lies in understanding which variables are predictors of the excess zeros, to support the hypotheses that certain items are absent because they are not from SOMNII sources. In other words, during festival years, certain items are highly more expected than others.\u003c/p\u003e\u003cp\u003eAll statistical analyses were performed using R Software version 4.4.2.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eSpatial and temporal distribution of beach litter\u003c/p\u003e\u003cp\u003eStatistically significant associations (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were found between litter categories and their source, sampling units, seasons, and years, indicating that litter composition varied meaningfully with these factors (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) (Supplementary Material_Chi-SquareTest).\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\u003ePearson's Chi-squared test of independence to evaluate the association between litter categories and the categorical variables source (SOMNII/OTHER), sampling unit (VIP, STAGE and CHILLOUT zones), sampling season (winter, spring, summer, autumn) and sampling year (2019, 2020, 2021, 2022, 2023).\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=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" 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\u003eChi-square value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003edf\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLitter categories VS Source\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4075.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;2.2e-16 *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLitter categories VS Sampling Unit\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e655.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;2.2e-16 *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLitter categories VS Season\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1052.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;2.2e-16 *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLitter categories VS Year\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1358.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;2.2e-16 *\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e* p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (statistically significant)\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 number of items found in the study area is high and well above the European Threshold Value (EU TV) of 20 items/100 m (van Loon et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). A total of 26742 items were collected in the SOMNII festival sampling site from 2019 to 2023, with a total count median of 329 items/100 m. Overall, the median is lower for items that have a SOMNII source (94 items/100m) compared to OTHER sources (235 items/100 m). Higher for items found at the STAGE zone (532 items/100 m), followed by the VIP zone (329 items/100m) and then by the CHILLOUT zone (70 items/100m). Higher for items collected in the summer (569 items/100 m) and lower in the winter (184 items/100 m).\u003c/p\u003e\u003cp\u003eThe magnitude of beach litter pollution from SOMNII sources shows a different trend over the years compared to OTHER sources. Items from SOMNII sources showed a sharp decrease between 2019 and 2021, a time period without festival editions that covers the COVID19 pandemic, followed by an increase in 2022 when the festival returned, and a subsequent decrease in 2023 when massive cleanups were implemented by the festival organization (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Despite the trends observed, no significant decreases in both total counts and plastic items have been observed for items from SOMNII sources, at the site and at the zone scales (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Items from OTHER sources experienced an increase between 2019 and 2020, before the COVID 19 lockdown, followed by a sharp decrease between 2020 and 2021 (COVID19), a slight decrease until 2022 (after COVID19) and another sharp decrease until 2023 (massive cleanups related to the SOMNII festival) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\u003cp\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\u003eMedian total and plastic counts (from 2019 to 2023), and associated trends, for items from SOMNII sources, in the site area and zones.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e\u003cp\u003eTOTAL\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e\u003cp\u003ePLASTIC (Artificial Polymer materials)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGeographical scale\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003eMedian Count\u003c/b\u003e\u003c/p\u003e\u003cp\u003e(items/100\u0026nbsp;m)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003eTrend\u003c/b\u003e\u003c/p\u003e\u003cp\u003e(slope in items/100\u0026nbsp;m per year)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003eMedian Count\u003c/b\u003e (items/100\u0026nbsp;m)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003eTrend\u003c/b\u003e\u003c/p\u003e\u003cp\u003e(slope in items/100\u0026nbsp;m per year)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSite area\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e329\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003e-24.46\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003e0.0875\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e282\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e-36.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003e0.0875\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eZones\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eVIP\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003e329\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003e-24.46\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003e0.2712\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003e282\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003e-36.42\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003e0.3575\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eSTAGE\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003e532\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003e-86.12\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003e0.2167\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003e457\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003e-80.55\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003e0.2448\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eCHILLOUT\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cem\u003e70\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003e-10.97\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003e0.1715\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003e56\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003e-10.8\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cem\u003e0.1006\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003eNote: All p-values are not significant.\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 analysis of litter composition shows a predominance of items made of artificial polymer materials, also known as plastics (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). At the site scale (SOMNII Festival area scale), plastic items represent 90.38% of the pollution, with a median of 282 items/100 m whereas other materials do not exceed 14 items/100 m. Similar results are observed at the VIP (88.68%), the STAGE (89.78%) and the CHILLOUT (96.55%) zones.\u003c/p\u003e\u003cp\u003eWhen analyzing litter composition by source, the medians indicate that items from SOMNI sources belong only to four categories: Artificial polymer materials, Metal, Paper/Cardboard and Cloth. Artificial Polymer Materials are dominant, but those for which we are certain come from the SOMNII festival (SOMNII sources) show the highest counts in the STAGE zone, where most participants gather during the festival. The remaining plastic items show the highest counts in the VIP zone, which is farther away from the swash zone and closer to the dunes.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003ePredicting the number of items\u003c/p\u003e\u003cp\u003eThere is a statistically significant probability that all category items, except for Paper/Cardboard, appear less frequently than Artificial polymer materials (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). For instance, cloth items are 1.67 times less likely to appear than artificial polymer items. Items from the SOMNII festival are 1.05 times more likely to appear than items from OTHER sources. This does not imply a greater number of SOMNII items overall, but rather that these items have a higher probability of occurrence within a specific category and zone. Additionally, SOMNII items are 0.76 times more likely to be collected in the STAGE zone than in the VIP zone, but 1.16 times less likely to be collected in the CHILLOUT zone. This is in line with the intensity of festival-goers expected in each of three sampling units.\u003c/p\u003e\u003cp\u003eThe zero-inflation part of the model indicates that some litter categories, the zone and the years have a meaningful impact on the probability of an observation being an excess zero. An increase in the predictor variable (positive estimates) is associated with a higher probability of an observation being an excess zero. In other words, and for the specific case of this study, there is a statistically significant lower probability of collecting Cloth, Metal, Paper and Rubber items. This information is consistent with the fact that most of the items are artificial polymers. For each item found there is a significant lower probability of collecting items from the CHILLOUT zone than from the VIP zone, suggesting several items were actually more frequently released in this zone. This is in accordance with what we know from the festival SOMNII, that the CHILLOUT zone had the lower number of festival goers and hence, less litter. Additionally, there was a significant lower probability of collecting items in 2020 up to 2023 than in 2019, which is again consistent with known events that may result in less litter: festival cancellation, COVID19 and massive clean-ups, after 2019.\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\u003eZero-inflated model fitted to the variables\u0026nbsp;\u0026lsquo;category\u0026rsquo;, \u0026lsquo;source\u0026rsquo; and \u0026lsquo;sampling unit\u0026rsquo; to model the count in the negative binomial part. The variables\u0026nbsp;\u0026lsquo;category\u0026rsquo;, \u0026lsquo;source\u0026rsquo;, \u0026lsquo;sampling unit and \u0026lsquo;year\u0026rsquo; model the logit part. This model fits the data significantly better than the null model (intercept-only), with a p-value of 8.937496e-232 (df\u0026thinsp;=\u0026thinsp;27).\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\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eModel formula: nr\u0026thinsp;~\u0026thinsp;cat\u0026thinsp;+\u0026thinsp;source\u0026thinsp;+\u0026thinsp;samplingunits | source\u0026thinsp;+\u0026thinsp;samplingunits\u0026thinsp;+\u0026thinsp;year\u0026thinsp;+\u0026thinsp;season\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eCount model (negative binomial)\u0026nbsp;coefficients\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEstimate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStd. Error\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ez value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePr(\u0026gt;|z|)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Intercept)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.00874\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.09641\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.463\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;2.00E-16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCloth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1.66619\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.26623\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-6.258\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.89E-10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGlass and ceramics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1.21497\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.24856\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-4.888\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.02E-06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMetal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1.64681\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.1612\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-10.216\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.65759\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePaper/Cardboard\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.08986\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.20273\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.443\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.01721\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProcessed / Worked Wood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.67395\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.28291\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-2.382\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.28E-12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRubber\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-2.17006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.30578\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-7.097\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.00126\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUndefined\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1.36214\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.42241\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-3.225\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.16E-11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSOMNII source\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.04711\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.15773\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.639\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.11E-09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSTAGE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.76317\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.12879\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.926\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;2.00E-16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCHILLOUT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-1.15969\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.12766\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-9.084\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;2.00E-16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLog(theta)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-2.74007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.03893\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-70.391\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;2.00E-16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eZero-inflation model (logit) coefficients\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLogg-odds\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStd. Error\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ez value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePr(\u0026gt;|z|)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Intercept)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-45.5334\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.71E\u0026thinsp;+\u0026thinsp;04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.99936\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCloth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.3557\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.94E-01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.747\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.00601\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGlass and ceramics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17.4494\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.03E\u0026thinsp;+\u0026thinsp;03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.98649\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMetal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.6282\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.57E-01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.442\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.01462\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePaper/Cardboard\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.3063\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.30E-01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.956\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.61E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProcessed / Worked Wood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e43.2256\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.71E\u0026thinsp;+\u0026thinsp;04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.9994\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRubber\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.7047\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.63E-01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.573\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.01009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUndefined\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19.0714\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.09E\u0026thinsp;+\u0026thinsp;03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.99628\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSOMNII source\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e45.0296\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.71E\u0026thinsp;+\u0026thinsp;04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.99937\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSTAGE zone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.1627\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.82E-01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.896\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.37009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCHILLOUT zone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.1992\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.21E-01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.429\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.67E-08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.8892\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.96E-01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.00267\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.1892\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.00E-01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.48E-05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.8084\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.96E-01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.734\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.00626\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.9713\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.12E-01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.116\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.00183\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003eSignif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eTheta\u0026thinsp;=\u0026thinsp;0.0622. Number of interations\u0026thinsp;=\u0026thinsp;67. Log-likelihood: -7989(df\u0026thinsp;=\u0026thinsp;21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eMaritime-related plastic items (SEA), Single-use plastics (SUP) and measures coverage\u003c/p\u003e\u003cp\u003eThe \u0026ldquo;Maritime-related plastic items\u0026rdquo; (SEA) and the \u0026ldquo;Single-use Plastics\u0026rdquo; (SUP) categories represent 39.46% of litter items.\u003c/p\u003e\u003cp\u003eSEA materials represent 1.08% of litter items, and, as expected, do not have a SOMNII source. Their presence is higher in the CHILLOUT zone (2.56%). These results were expected since this sampling unit is closer to the sea shore where fishing-related items, such as lobster/fish tags, octopus pots, nets, and strings and cords (which can come from different sources but are often mainly related to fishing), are potentially more prone to be found (Ouyang \u0026amp; Yang, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Watson et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSUP materials represent 38.38% of litter items, 17.54% being attributed to the RFM SOMNII Festival. Median counts were higher at the STAGE zone (183 items/100 m from SOMNII festival and 25 items/100m from OTHER sources (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). The trend of SUP from the SOMNII source over the years (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e) follows the same general trend (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), indicating a correct classification of these items. However, the trend over the years of both SUP and Other items, from OTHER sources, with increasing trends once the festival returns in 2022, indicates that SOMNII items are potentially sub-accounted.\u003c/p\u003e\u003cp\u003e50% of the litter items collected are targeted either by the OSPAR Regional Action Plan on Marine Litter (ML RAP) 2014\u0026ndash;2020 or the EU SUP Directive \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e/904.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTop litter types\u003c/p\u003e\u003cp\u003eThe top 15 litter types are dominated by non-identifiable items, such as plastic/polystyrene pieces (0\u0026ndash;2.5 cm and 2.5\u0026ndash;50 cm) and other plastic/polystyrene fragments, with median values exceeding 50 litter items per 100 meters at the VIP and STAGE zones (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). These, along with \u0026ldquo;String and cord (diameter less than 1 cm)\u0026rdquo;, consist of fragments of artificial polymer materials with untraceable sources. The presence of these items suggests a potential underestimation of the median of items originating from SOMNII sources.\u003c/p\u003e\u003cp\u003eAmong the top 15 litter types, six are Single-Use Plastics (SUP): cigarette butts, caps/lids, cotton bud sticks, crisp/sweet packets and lolly sticks, cutlery/trays/straws, and drink-related items (e.g. bottles). The median for cigarette butts stands out at 117 items per 100 meters in the STAGE zone, the area with the highest concentration of festival-goers. Other SUP items, such as caps/lids, crisp/sweet packets and lolly sticks, cutlery/trays/straws, and drink-related items, are typical of these types of events. Drink-related items rank among the top 15 in the CHILLOUT zone, whereas cutlery/trays/straws appear in the top 15 only within the VIP and STAGE zones, which is logical given their proximity to meal areas. Given the European ban on plastic plates, cutlery, straws, drink stirrers and containers made of expanded polystyrene, in July 2021 (Currie et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Souza Filho et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), it is relevant to look upon the trend of these items over time (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). They still show an increase once the festival returned, but at lower median counts.\u003c/p\u003e\u003cp\u003eZip ties also deserve attention. Absent from the top 15 at the CHILLOUT zone, their median values reach 33 items per 100 meters in the VIP zone and 32 items per 100 meters in the STAGE zone. Zip ties are commonly used for bundling and securing musical equipment during transportation and setup, organizing electrical and audio cables, and stabilizing temporary structures like protective barriers.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eContext-Specific Observations\u003c/p\u003e\u003cp\u003eThe results of this study reveal event-specific debris characteristics. For instance, higher densities of litter in zones with intense human activity, such as the STAGE zone, corroborate findings from studies on event-related waste, where human presence and dynamics strongly correlates with litter accumulation (Asensio-Montesinos et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Garc\u0026eacute;s-Ord\u0026oacute;\u0026ntilde;ez et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Grelaud \u0026amp; Ziveri, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The correlation between human density and waste generation in events is potentially related to behavioral and event-specific factors that play a pivotal role in waste accumulation. There is a tendency of attendees to discard items on the ground, particularly during performances or in crowded areas (Rangoni \u0026amp; Jager, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This behavior is highly consistent with the distribution of cigarette butts in the SOMNII festival. Cigarette butts are recognized as one the most common forms of personal litter around the world (Ara\u0026uacute;jo \u0026amp; Costa, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and in the festival area are the most frequent item in the STAGE zone. The behavior to discard items to the ground is influenced by demographic variables, with disparities between anti‑litter attitudes, willingness to act, and individual accountability (Lev et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), but also by the availability and accessibility of waste disposal facilities (Rangoni \u0026amp; Jager, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). For instance, inadequate placement or an insufficient number of bins can lead to an increase in improper disposal practices (Rangoni \u0026amp; Jager, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAnother context-specific finding is the significant presence of zip ties in the VIP and STAGE zones and which reflects logistical practices specific to festival setups, such as the transportation and organization of equipment. This contrasts with urban beach studies, where such items are reported less frequently (Fern\u0026aacute;ndez Garc\u0026iacute;a et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Fern\u0026aacute;ndez-Enr\u0026iacute;quez et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Additionally, the ease of attributing certain litter items to SOMNII sources is linked to brand marketing strategies involving the distribution of branded cups, wristbands, and other promotional materials. These strategies are commonplace at festivals, and, while they directly contribute to the volume of waste generated, they also present an opportunity for improved waste management strategies. The significant differences observed between festival zones (VIP, STAGE, CHILLOUT) are also characteristic of such events. Spatial variations in items like cigarette butts and food- and drinks-related litter reflect the movement of the crowd. Although these items are not new in event monitoring and management, the stratified sampling approach employed in this study is uncommon in beach litter monitoring and should be considered for events held on beaches. Findings from stratified sampling improve accuracy and representativeness (Bravo et al., 20 C.E.; Ramos et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) and may offer valuable insights into the spatial variability of litter accumulation and into crowd behavior in large-scale events, enabling the implementation of targeted waste management strategies.\u003c/p\u003e\u003cp\u003eAlignment with global patterns of beach litter composition\u003c/p\u003e\u003cp\u003eBeach litter composition observed is consistent with global patterns. The predominance of artificial polymer materials, which constitute over 90% of the litter, is in line with global trends that identify plastics as the primary marine pollutant (Ali \u0026amp; Shams, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Fern\u0026aacute;ndez-Enr\u0026iacute;quez et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Garc\u0026eacute;s-Ord\u0026oacute;\u0026ntilde;ez et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Pervez et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The prevalence of artificial polymer materials from sources not related to the festival in zones away from the shoreline and near dune plants is also consistent with global-scale studies suggesting dune plants as sinks for marine litter (Gallitelli et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The presence of maritime-related items in the CHILLOUT zone, closer to the shoreline, is also consistent with global research indicating that fishing-related debris is more likely to accumulate in areas near the swash zone (Ouyang \u0026amp; Yang, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Watson et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Debris can be transported to the coastal region from the oceans by nearshore currents, tidal cycles, regional-scale topography, intentional or accidental disposal (Ouyang \u0026amp; Yang, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; UNEP, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe pattern observed over time is also aligned with global studies. The waste accumulation in the summer season is consistent with the increase of people in tourist seasons (Asensio-Montesinos et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Garc\u0026eacute;s-Ord\u0026oacute;\u0026ntilde;ez et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and with the role of large-scale events in exacerbating coastal pollution (Oliveira et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The sharp reduction in litter during festival-free years (2020\u0026ndash;2021) is consistent with the role of the COVID19 pandemic lockdowns in reducing beach litter from terrestrial sources (Currie et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Souza Filho et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The slight litter decrease in 2023, when a massive clean-up regime was implemented after the festival, is consistent with the expected positive impact of waste management strategies (Rangoni \u0026amp; Jager, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). These findings reinforce the importance of conducting long-term studies as they allow for the identification of trends that may not be apparent in short-term studies. In the particular case of this study, a decrease in litter suggests a relationship with the COVID19 pandemic and with post-event clean-ups. In other situations, it may suggest the effectiveness of broader environmental policies and public awareness campaigns (Dodds et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Gration et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Williams \u0026amp; Rangel-Buitrago, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). These temporal variations offer critical insights for designing mitigation strategies (Oliveira et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and contribute to broader discussions on the environmental impact of large-scale coastal gatherings (Gallagher A \u0026amp; Pike K, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAdvancing monitoring methodologies: A stratified OSPAR framework for event-driven litter dynamics\u003c/p\u003e\u003cp\u003eDespite increasing recognition of beaches as critical monitoring sites for marine litter, standardized methodologies, including OSPAR\u0026rsquo;s, remain optimized for long-term, low-frequency monitoring across broad spatial units (Wenneker et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). These designs often struggle to capture acute, short-lived pollution events associated with high-density, high-tempo activities like beach festivals (Gallagher A \u0026amp; Pike K, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). This study addresses that methodological blind spot by adapting the OSPAR monitoring protocol into a stratified, high-resolution sampling framework tailored to the spatiotemporal dynamics of a large-scale beach event.\u003c/p\u003e\u003cp\u003eBy partitioning the SOMNII festival site into three functionally distinct zones - VIP, STAGE, and CHILLOUT - each sampled using fixed 100 m \u0026times; 50 m plots, this approach enabled fine-scale detection of litter accumulation and composition. Stratification revealed significant spatial differences: STAGE areas averaged around seven times more litter than CHILLOUT zones, and litter composition varied by zone and source. Without this zoning, such detail would likely have been obscured under a conventional 100 m transect model (Asensio-Montesinos et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Importantly, the method uncovered clear temporal shifts in litter dynamics, driven by external events such as COVID-19-related festival cancellations and the introduction of intensive post-festival cleanups in 2023.\u003c/p\u003e\u003cp\u003eThe results indicate that stratified OSPAR monitoring not only enhances the sensitivity of event-driven litter detection but also improves hotspot identification, informing better spatial targeting of waste prevention measures (van Loon et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). These insights offer a scalable monitoring template for other tourist-intensive coastal environments, where functional zoning (e.g., event spaces, recreational zones, food/beverage areas) can vary but follow broadly similar patterns (Dodds et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Event organizers and coastal managers may adopt this framework to create \u0026ldquo;event-specific litter response plans\u0026rdquo;, combining real-time monitoring with targeted interventions such as bin placement, signage, and reusable item programs (Prasuhn et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWhile the approach is broadly applicable and logistically feasible - it leverages standard OSPAR analysis protocols and tools (e.g., the R package litterR) - it is not without limitations. Zone-specific monitoring requires coordination with event planners and local authorities to ensure access and optimal timing. Though not more labor-intensive than traditional approaches, increased temporal frequency may impact resource needs. Moreover, the classification of items by source, while grounded in site-specific observations and item characteristics, inevitably involves some uncertainty, particularly for unbranded plastic fragments and cross-purpose items like zip ties (van Loon et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Lastly, the transferability of the zonation scheme must account for the spatial layouts of other events, as direct replication is not always viable.\u003c/p\u003e\u003cp\u003eNonetheless, the insights gained from this stratified approach justify its added complexity, offering a replicable and scientifically robust enhancement to conventional marine litter monitoring. By integrating functional spatial analysis into existing frameworks, this method supports both regulatory evaluation (e.g., OSPAR\u0026rsquo;s RAP ML and the EU SUP Directive \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e/904) and the design of targeted, evidence-based waste mitigation strategies (Gallagher A \u0026amp; Pike K, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePolicy leverage and collaborative strategies for event-driven litter mitigation\u003c/p\u003e\u003cp\u003eLarge-scale coastal events present a valuable opportunity to evaluate the effectiveness of mitigation efforts and shape future waste management strategies. Following the 2023 edition of the RFM SOMNII festival, extensive cleanup operations led to marked reductions in litter density, particularly in high-traffic areas. This decrease, most pronounced in the STAGE and VIP zones, highlights the effectiveness of targeted cleanup interventions in reducing the environmental footprint of such events (Rangoni \u0026amp; Jager, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). At the same time, the high prevalence of artificial polymer fragments reveals the limitations of cleanup operations, which primarily address visible waste while overlooking less conspicuous pollutants (Galgani et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Santill\u0026aacute;n et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Plastic fragments are of particular concern because they often exhibit inherent weaknesses that make them more susceptible to degradation (Baby et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This poses additional biological risks, as smaller particles are ingested by marine organisms, entering the food chain with potential consequences for ecosystem health and human wellbeing (Browne et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Moreover, the unidentifiable nature of litter fragments (Zielinski et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) rises litter categorization issues, that skew conclusions (Watts et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and make the implementation of targeted measures more challenging. In the context of litter monitoring events, it also exacerbates the problem of distinguishing between event-related waste and pre-existing litter. While branded items like cups or wristbands can be directly linked to an event, a significant portion of the litter consists of non-branded or fragmented items that are harder to trace.\u003c/p\u003e\u003cp\u003eThe findings provide empirical support for the implementation and enhancement of policies such as the EU Single-Use Plastics (SUP) Directive (Directive (EU) \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e/904 on the Reduction of the Impact of Certain Plastic Products on the Environment., 2019)) and the OSPAR Regional Action Plan on Marine Litter (RAP ML 2) 2022\u0026ndash;2030 (OSPAR Commission, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Both frameworks aim to reduce plastic pollution through measures such as the restriction or elimination of SUP items, improved waste management, and public education. The SOMNII festival seems to be itself evidence of the success of such policies. In Europe, the European Union has banned the commercialization of single-use plastics, including plastic straws and cutlery, as of July 2021. As a consequence, the presence of these items was reduced in 2022 and 2023, compared to 2019 (previous festival edition). However, these banned items, along with other SUP items, such as cigarette butts and food-related packaging, persisted, especially in high-density areas and despite the cleaning efforts. Could these policies be strengthened during public events by introducing bans on specific items or mandating reusable alternatives (Williams \u0026amp; Rangel-Buitrago, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)? Waste management practices implemented in large-scale events in Portugal (Interreg Europe, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and M\u0026aacute;laga (Interreg Europe, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) seem to corroborate this possibility. Stricter regulations on waste management for event organizers could also include the requirement for comprehensive cleanup plans (Rangoni \u0026amp; Jager, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Williams \u0026amp; Rangel-Buitrago, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Rangoni \u0026amp; Jager (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), for instance, suggest adaptive/dynamical cleaning regimes, which seem to be more effective and cheaper than pre-defined cleaning. This could also reduce issues related to festival peak hours that often lead to litter dispersing into adjacent areas due to crowds\u0026rsquo; movement, complicating collection efforts and reducing cleanup efficiency. Other sustainable practices for waste management of large-scale events could include the increase of recycling opportunities through the deployment of smart bins and AI-driven waste sorting systems to improve the efficiency of waste segregation and processing (Ramasawmy \u0026amp; Nagowah, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePublic awareness campaigns represent another essential component of waste management strategies, especially those that foster behavioral changes that contribute to long-term reductions in litter generation (B\u0026auml;r et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Educating festival-goers about the environmental impacts of improper waste disposal, through both digital platforms and on-site initiatives, could foster a sense of shared responsibility among attendees. Signage promoting responsible waste disposal, accompanied by clear instructions on waste segregation, could also foster environmentally conscious behavior. In high-impact zones, interactive campaigns, such as reward systems for proper waste segregation, could effectively engage attendees and incentivize responsible behavior.\u003c/p\u003e\u003cp\u003eThe findings point to the necessity of proactive collaboration of event organizers with researchers, industry and local decision-makers. Collaboration with researchers would support the identification and tracking of specific items more efficiently (Zielinski et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This could support the identification of potential waste hotspots within the event site, helping organizers to implement targeted waste collection strategies (e.g. strategically placing bins or staff deployment), translated into cost savings. It could identify problematic waste sources, enabling organizers to adopt sustainable practices and comply with environmental regulations, such as reducing single-use plastics or promoting reusable alternatives. It could also provide valuable data on attendee behavior and waste generation patterns, which can inform future event planning and layout optimization (Martinho et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). One collaboration approach could involve authorizations for pre- and post-event litter composition surveys to establish clearer baselines for monitoring the effectiveness of interventions over time (Zielinski et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Another collaboration could involve tagging branded items distributed during the events with advanced technologies such as QR codes (Aparna et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), enabling researchers to trace the origins of specific items more efficiently. This would also need to rely on collaboration with industry to provide such technologies. Other collaborations with industry could focus on developing and adopting alternatives for problematic items, such as zip ties, for which sustainable options, on paper, bio-based plastics, and recycled PET, are already available.\u003c/p\u003e\u003cp\u003eCollaboration with decision-makers plays a pivotal role in implementing targeted solutions for environmental sustainability at events. Such partnerships can take various forms. For example, event organizers and decision-makers can coordinate the installation of adequate waste management infrastructures, such as recycling bins, composting stations, and waste collection points, to address the unique challenges of coastal environments (Oliveira et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Joint efforts can also be directed towards public awareness campaigns that educate attendees on the environmental impacts of littering and foster responsible waste disposal behaviors (Mair \u0026amp; Laing, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Furthermore, collaborative initiatives can extend to reward systems, such as discounts or tokens, to encourage attendees to engage in proper waste segregation and recycling (Yang et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Additionally, local authorities can play a key role in establishing or promoting adherence to sustainability certifications for events, which serve as benchmarks for effective waste management and environmental responsibility (Nygaard, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). They can also incentivize the redirection of reusable or repurposable waste through the implementation of donation programs benefiting local institutions (Oliveira et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study demonstrates the value of adapting established monitoring frameworks - specifically the OSPAR methodology - to better capture the spatial and temporal complexities of marine litter generated during large-scale coastal events. By implementing a stratified sampling design across functionally distinct zones of the RFM SOMNII festival site, the research revealed clear patterns of litter accumulation and material composition that would likely have been missed using conventional beach monitoring protocols. These insights not only advance our understanding of event-driven pollution dynamics but also highlight the potential of tailored methodologies to inform more targeted and effective waste management interventions.\u003c/p\u003e\u003cp\u003eWhile the dominance of artificial polymer materials and single-use plastics (SUP) remains a consistent challenge, the study demonstrates that refined sampling approaches can support hotspot detection and improve attribution, critical steps for prevention and mitigation. The unique context of the COVID-19 pandemic further enabled a contrast between festival-active and inactive periods, providing rare empirical evidence on the direct influence of human activity.\u003c/p\u003e\u003cp\u003eBeyond the case study, the stratified monitoring framework offers a replicable blueprint for enhancing marine litter assessments under similarly dynamic and high-pressure coastal conditions. Its application can improve decision-making by identifying pollution hotspots, refining litter source analysis, and supporting compliance with policy frameworks such as the EU SUP Directive and OSPAR\u0026rsquo;s Regional Action Plan. Future research should explore how integrating traceability technologies, automated detection tools, and stakeholder collaboration can further strengthen attribution accuracy and operational efficiency. Together, these innovations can accelerate progress toward more sustainable coastal event management and marine environmental protection.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eHuman Ethics and Consent to Participate declarations\u003c/h2\u003e\u003cp\u003enot applicable\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eDeclaration of Interests\u003c/strong\u003e\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\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eDeclaration\u003c/p\u003e\u003cp\u003eThis work was supported by the FCT \u0026ndash; Funda\u0026ccedil;\u0026atilde;o para a Ci\u0026ecirc;ncia e Tecnologia [grant numbers UIDB/04292/2020 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.54499/UIDB/04292/2020\u003c/span\u003e\u003cspan address=\"10.54499/UIDB/04292/2020\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e); UIDP/04292/2020 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.54499/UIDP/04292/2020\u003c/span\u003e\u003cspan address=\"10.54499/UIDP/04292/2020\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e); LA/P/0069/2020 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.54499/LA/P/0069/2020\u003c/span\u003e\u003cspan address=\"10.54499/LA/P/0069/2020\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e); UID/04292/MARE-Centro de Ci\u0026ecirc;ncias do Mar e do Ambiente; UIDB/04035/2020 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.54499/UIDB/04035/2020\u003c/span\u003e\u003cspan address=\"10.54499/UIDB/04035/2020\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e); CEECINST/00152/2018/CP1570/CT0007 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.54499/CEECINST/00152/2018/CP1570/CT0007\u003c/span\u003e\u003cspan address=\"10.54499/CEECINST/00152/2018/CP1570/CT0007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e); CEECINSTLA/00018/2022/CP2967/CT0001 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.54499/CEECINSTLA/00018/2022/CP2967/CT0001\u003c/span\u003e\u003cspan address=\"10.54499/CEECINSTLA/00018/2022/CP2967/CT0001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e); UI/BD/150952/2021 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.13039/501100001871\u003c/span\u003e\u003cspan address=\"10.13039/501100001871\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e); SFRH/BD/147777/2019 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.13039/501100005727\u003c/span\u003e\u003cspan address=\"10.13039/501100005727\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e); and 2022.12166.BD; 2023.04308.BDANA].\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eZ.T. and C.M. defined the overarching research goals and the design of the methodology. Z.T., A.C., and P.C. ensured data curation for both initial use and future reuse. C.G., C.M., A.B., D.P., D.M., and L.R. made substantial contributions to data collection throughout the five-year field campaigns. Z.T., A.C., and C.M. collaborated on the statistical analysis.Z.T. drafted the original manuscript, prepared the final figures and tables for publication, and was primarily responsible for planning and executing the research activities, as well as securing the main financial support. C.M. supervised the planning and execution of the research activities and provided mentorship beyond the core team.All authors critically reviewed the manuscript, approved the final version for publication, and agree to be accountable for all aspects of the work, ensuring that any questions related to its accuracy or integrity are thoroughly investigated and resolved.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors gratefully acknowledge the invaluable additional contributions of the following researchers and students during fieldwork: Patr\u0026iacute;cia Rita, B\u0026aacute;rbara Camar\u0026atilde;o, Daniela Silva, Duarte, Juliana Spitz, Marta Ressurrei\u0026ccedil;\u0026atilde;o, Sofia Cunha, Amani Abusaid, Ana Gomes, Diogo Costa, Eunice, Irene Gutierrez, Jonas, Juan Flores, Rafael, Tiago Miguel Cerqueira, Tiago Verdelhos, and Vera Lamas. We would also like to thank the Municipality of Figueira da Foz and local authorities for authorizing sampling during COVID-19 lockdowns.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData is available at https://zenodo.org/records/15303685 under the title \"Dataset Seasonal Data on Beach Litter from a Massive Music Festival in Portugal (2019\u0026ndash;2023)\" (Anonymous). The dataset is available in raw and processed formats.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAli, R., \u0026amp; Shams, Z. I. (2015). 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MDPI. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/su141911994\u003c/span\u003e\u003cspan address=\"10.3390/su141911994\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"environmental-monitoring-and-assessment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"emas","sideBox":"Learn more about [Environmental Monitoring and Assessment](http://link.springer.com/journal/10661)","snPcode":"10661","submissionUrl":"https://submission.nature.com/new-submission/10661/3","title":"Environmental Monitoring and Assessment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Marine litter monitoring, Stratified sampling, OSPAR methodology, Coastal events, Single-use plastics, Beach pollution hotspots","lastPublishedDoi":"10.21203/rs.3.rs-7767950/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7767950/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eUrban beaches are increasingly vulnerable to litter accumulation, especially during large-scale coastal events that create short-lived but intense pollution pulses. Despite growing interest in marine litter monitoring, traditional methods often lack the spatial and temporal sensitivity required to capture such episodic surges. This study presents a methodological adaptation of the OSPAR beach litter monitoring protocol, applying a stratified sampling framework to a high-use coastal site during the RFM SOMNII festival in Figueira da Foz, Portugal, one of Europe\u0026rsquo;s largest beach music festivals. Over a five-year period (2019\u0026ndash;2023), including pre- and post-COVID-19 seasons, 17 seasonal surveys were conducted across three functional zones (STAGE, VIP, CHILLOUT) to assess the spatiotemporal dynamics of litter accumulation. Results indicate clear spatial heterogeneity, with litter densities peaking in high-traffic areas and artificial polymer materials, particularly single-use plastics, accounting for over 90% of all debris. Temporal trends show sharp declines in 2020\u0026ndash;2021 during festival cancellations, with subsequent rebounds following the event\u0026rsquo;s return, and further reductions after targeted cleanup measures in 2023. The stratified sampling approach revealed patterns and hotspots that would likely be overlooked by conventional OSPAR layouts, highlighting the potential for this framework to enhance marine litter monitoring in event-prone coastal zones. Findings also inform broader sustainability strategies, reinforcing the need for adaptive cleanup planning, reusable alternatives to single-use items, and coordinated engagement between researchers, event organizers, and policymakers. The approach offers a replicable blueprint for improving beach litter assessments under dynamic, high-pressure conditions worldwide.\u003c/p\u003e","manuscriptTitle":"Stratifying the Shoreline: A Modified OSPAR Framework to Monitor Event-Driven Beach Litter","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-11 18:56:09","doi":"10.21203/rs.3.rs-7767950/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-25T01:21:52+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-21T16:59:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-07T07:50:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"275019602150463154963745801670597340302","date":"2025-11-05T08:15:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"61315783170129734653140429546668410682","date":"2025-10-31T08:34:47+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-30T23:29:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-21T05:10:57+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-21T05:10:20+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Monitoring and Assessment","date":"2025-10-02T16:09:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"environmental-monitoring-and-assessment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"emas","sideBox":"Learn more about [Environmental Monitoring and Assessment](http://link.springer.com/journal/10661)","snPcode":"10661","submissionUrl":"https://submission.nature.com/new-submission/10661/3","title":"Environmental Monitoring and Assessment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"1927230c-53f4-4a55-9d19-7e4bc070e1cd","owner":[],"postedDate":"November 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-04-13T16:07:40+00:00","versionOfRecord":{"articleIdentity":"rs-7767950","link":"https://doi.org/10.1007/s10661-026-15260-x","journal":{"identity":"environmental-monitoring-and-assessment","isVorOnly":false,"title":"Environmental Monitoring and Assessment"},"publishedOn":"2026-04-10 15:58:10","publishedOnDateReadable":"April 10th, 2026"},"versionCreatedAt":"2025-11-11 18:56:09","video":"","vorDoi":"10.1007/s10661-026-15260-x","vorDoiUrl":"https://doi.org/10.1007/s10661-026-15260-x","workflowStages":[]},"version":"v1","identity":"rs-7767950","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7767950","identity":"rs-7767950","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}