Fig. 3. Effects plot showing the predicted debris counts based on the generalized linear model. Star added to denote significant difference as per analysis of deviance. From original article.
September 26, 2023 The Conversation
Our beaches are in trouble. Limited recycling programs and a society that throws away so much have resulted in more than 3 million tonnes of plastic polluting the oceans. An estimated 1.5–1.9% of this rubbish ends up on beaches.
So can waste-management strategies such as container deposit schemes make a difference to this 50,000–60,000 tonnes of beach rubbish?
The Queensland government started a container deposit scheme in 2019. We wanted to know if it reduced the rubbish that washed up on beaches in a tourist hotspot, the Whitsundays region.
It turned out that for the types of rubbish included in the scheme – plastic bottles and aluminium cans – the answer was an emphatic yes.
Container deposit schemes work
After the scheme began, there were fewer plastic bottles and aluminium cans on Whitsundays beaches. Volunteer clean-up workers collected an average of about 120 containers per beach visit before the scheme began in 2019. This number fell to 77 in 2020.
Not only that, but those numbers stayed down year after year. This means people continued to take part in the scheme for years.
Rubbish that wasn’t part of the scheme still found its way to the beaches.
However, more types of rubbish such as larger glass bottles are being added to the four-year-old Queensland scheme. Other states and territories have had schemes like this for many years, the oldest in South Australia since 1971.
But we didn’t have access to beach data from before and after those schemes started. So our findings are great news, especially as some of these other schemesare set to expand too. The evidence also supports the creation of new schemes in Victoria this November and Tasmania next year.
These developments give reason to hope we will see further reductions in beach litter.
The data came from the community
To find out whether the scheme has reduced specific sorts of rubbish on beaches we needed a large amount of data from before and after it began.
The unsung heroes of this study are the diligent volunteers who provided us with these data. They have been recording the types and amounts of rubbish found during their cleanups at Whitsundays beaches for years.
Eco Barge Clean Seas Inc has been doing this work since 2009. In taking that extra step of counting and sorting the rubbish, they may not have known it at the time, but they were creating a data gold mine. We would eventually use their data to prove the container deposit scheme works.
The rubbish clean-ups are continuing. This means we’ll be able to see how adding more rubbish types to the scheme will further reduce rubbish on beaches.
The long-term perspective we can gain from such data is testament to this sustained community effort.
There’s still more work to do
So if we recycle our plastics, why do we still get beaches covered in rubbish? The reality is that most plastics aren’t recycled. This is mainly due to two problems:
- technological limitations on the sorting needed to avoid contamination of waste streams
- inadequate incentives for people to reduce contamination by properly sorting their waste, and ultimately to use products made from recycled waste.
Our findings show we can create more sustainable practices and a cleaner environment when individuals are given incentives to recycle.
However, container deposit schemes don’t just provide a financial reward. Getting people directly involved in recycling fosters a sense of responsibility for the environment. This connection between people’s actions and outcomes is a key to such schemes’ success.
Our study also shows how invaluable community-driven clean-up projects are. Not only do they reduce environmental harm and improve our experiences on beaches, but they can also provide scientists like us with the data we need to show how waste-management policies affect the environment.
Waste management is a concern for communities, policymakers and environmentalists around the world. The lessons from our study apply not only in Australia but anywhere that communities can work with scientists and governments to solve environmental problems.
Legacy community science data suggest reduced beached litter in response to a container deposit scheme at a local scale
Anthropogenic litter in the environment is causing undeniable harm (Beaumont et al., 2019; Campbell et al., 2019; Cole et al., 2015; Duncan et al., 2021; Lamb et al., 2018; Vegter et al., 2014). Mitigation strategies include direct removal (e.g. beach clean-ups; Zielinski et al. (2019)), and source reduction strategies including targeted legislation such as bans on individual types of packaging or products (e.g. Muposhi et al., 2022), or recycling incentives, such as material buy-back and container deposit schemes. Container deposit schemes offer a small financial incentive to return a container so that it can be recycled (White et al., 2001). These schemes work in increasing recycling rates (Hopewell et al., 2009; Kosior and Crescenzi, 2020) and reducing litter as a local source (Willis et al., 2022) but there is little published about their effectiveness in reducing observed local debris loads on beaches after implementation (Schuyler et al., 2018).
The accumulation of debris observed on beaches is dictated by natural processes such as supply from the local ocean (Turrell, 2018), the residence time on the beach (Kako et al., 2010), and storms or weather events out of the ordinary (Chubarenko and Stepanova, 2017), but also through anthropogenic processes such as littering behaviour (Campbell et al., 2014) and beach cleaning activities removing litter from beaches (Zielinski et al., 2019). Previous work by Schuyler et al. (2018), suggests that container deposit legislation reduces the amount of observed litter in local systems but focuses on the difference between states with and without container deposit legislation, at a much larger spatial scale than the current work. Willis et al. (2022) used systematic sampling at 100 km intervals around Australia at two-time points to assess the temporal changes in beached litter over that time. They found on average a reduction in litter present on Australian beaches, with a large range and variability across beaches. Here, we use a focused study area over a much longer time frame than either of these studies, with increased sample frequency to further explore litter dynamics in response to management intervention – in this case, the introduction of a container deposit scheme.
Community science data often comes from passionate volunteers who give up their free time because they want to see change or to have an impact on something they care deeply about, this is the case with much of the marine debris data available (e.g. Ambrose et al., 2019; Bauer-Civiello et al., 2018; Gacutan et al., 2023; Nelms et al., 2017). However, due to the nature of volunteer efforts, these schemes rarely have a strategized sampling method through space and time. While it is common that within a beach, methods have been standardised (e.g. the Marine Debris Initiative led by Tangaroa Blue), which beaches they visit and when is often dictated by weather conditions, volunteer availability, and cost. For many of these schemes, collecting the maximum amount of debris is the goal with the data being a useful by-product. However, these schemes have been running in some cases for over a decade, collecting large amounts of information about when and where debris accumulates. In this study, we aim to use this wealth of imperfect data to assess the effectiveness of a container deposit scheme in reducing litter loads in the local environment.
In this study, we will explore a case of the container deposit scheme (CDS) implemented in Queensland, Australia in November 2019. The scheme includes aluminium cans, glass bottles, PET and HDPE, liquid paper, and steel beverage containers between 150 ml and 3 l. The reported uptake of the scheme in Queensland has been good with an estimated 63 % of all eligible containers returned in the 2021–2022 financial year, and a total of 6.2 billion containers diverted from other waste streams since the start of the scheme (Container Exchange, QLD, 2022).
The local management area used for this case study is the Whitsunday region of the Great Barrier Reef World Heritage Area (Fig. 1). The resident population in the local management area is about 37,000 (2021 Census), the region is one of the key tourism areas of the Great Barrier Reef with domestic and international tourist spend approximately 3.5 million nights in the Whitsundays per year (Tourism Research Australia). The region receives two distinct weather seasons, 1) southeast trade windseason from approximately April to September with strong winds from the southeast (Fig. 1C) and 2) the more wind-variable northerly, monsoon wind season that occurs from about October to March (Fig. 1D). Beached litter data for the Whitsundays region was primarily collected and recorded by a local Non-Government Organisation, Eco Barge Clean Seas Inc. During each clean up event, volunteers collected all the debris that can be found from the water up into the vegetation of the back beach. The debris is loaded onto the barge and returned to shore where it is sorted using the Australian Marine Debris Initiative (AMDI) method cataloguing. The AMDI database stores counts of debris items in categories based on the material that the debris item is made of and its use (https://www.tangaroablue.org/resources/how-to-manual.html) and has extensive coverage of the Australian Coastline.
Since Eco Barge Clean Seas began operations in 2009, the amount of debris removed by the Eco Barge team has been 1,991,153 items total and 34,088 total Plastic Drink bottles (debris category: “Plastic drink bottles (water, juice, milk, soft drink)”) alone from the environment (as of June 2023). However, by the nature of the community science data set, sites, visits, and number of volunteers are inconsistent through the years. This is often tied to inconsistent funding for a program such as this, and the non-systematic nature of site selection by volunteer programs. Therefore, standardisation of the data was required. The data were truncated to begin in 2012 as the first few years of the program had too few visits to meaningfully contribute to long-term trends, where there were only 2 visits per year to inconsistent sites in the years 2009–2011. There were no locations that were visited consecutively across all years, therefore we assume that the sites visited in any one year provide a representative sample of the debris load in the Whitsunday region. As community science organisation is run by locals with local knowledge, they go to the sites that accumulate most litter and are accessible on any given sampling day, making this assumption robust at the temporal scale of a year, and spatial scale of the Whitsunday region.
To assess the temporal trends in the long term dataset, we used a multiple before after control impact design (MBACI) (Keough and Mapstone, 1997). We ran a generalized linear mixed effect model (GLMs; lme4 package (Bates et al., 2015), in R programming language; (R Core Team, 2021)) with Analysis of Variance (ANOVA) to indicate significance for explanatory variables and interaction (car package (Fox and Weisberg, 2019)), using the effects package (Fox, 2003), to demonstrate significance. Our model includes Treatment which is the debris covered by the scheme or not which is two levels (CDS and non-CDS), Impact which is the implementation of the CDS with two levels pre-implementation (2012–2019) and post-implementation (2020−2022). We included random effects of site and year in the model to account for spatially explicit differences and the number of visits per site per year as an offset to account for different visitation rates at each site (for summary table, please see supplementary material). We also assume that when volunteers visit a site that the beach is totally cleared of litter regardless of number of volunteers. We justified this assumption by conducting a correlation analysis between the number of volunteers and the observed debris load for each collection event and found no significant correlation (Pearson’s r = 0.0067; p = 0.8905; see S2 in supplementary material).
To assess the impact of the container deposit scheme (CDS), we split the data into the categories that contain items collected by the scheme (“Plastic drink bottles (water, juice, milk, soft drink)” and “Aluminium cans”) and for other common litter items, which became the Treatment of the MBACI analysis. There are considerations when using legacy data, for example the plastic drink bottles category contains bottles that are not currently collected by the scheme and so our results may be diluted by those items. However, this will provide a conservative estimate of change. There are many categories that appear in the data only once, or very infrequently, therefore we selected only categories that appear in the dataset in at least 50 clean ups. We also removed one clean up event that was in response to a boat running ashore that we think did not reflect the normal debris load on the beach. We note that, in previous work, a container-to-lid ratio has been used to assess the effect of container deposit legislation at a national scale (Schuyler et al., 2018), however the community science data does not separate lids from containers that would be covered by the scheme and other lids; therefore we could not replicate that analysis. R code and data used for these analyses are available in an online repository linked with this article (doi:https://doi.org/10.5061/dryad.qjq2bvqn8).
Clean-up events (n = 239) were spread across 90 sites (Fig. 1) in the 11-year study period (mean sites visited per year = 21.7, s.d. = 7.4), and events occurred in all months of each year. There is data from across the region, with site receiving uneven numbers of visits (median visits per year = 1, range 1–5).
The number of debris items collected per visit on Whitsunday beaches for both items covered by the container deposit scheme and those not covered was variable between years (Fig. 2). For CDS debris, there was significantly less debris after the implementation of the scheme (Fig. 2a; Table 1) with a mean of 120.4 (sd 78.4) containers collected per visit before the implementation compared with 77.5 (sd 48.2) after the implementation. The same trend did not exist for non-CDS debris (Fig. 2b; Table 1) with mean items per visit 5162.6 before and 6001.9 after (sd 4046.7, 3475.4 respectively). According to the multiple before after control impact analysis the implementation of the container deposit scheme had a significant effect on the amount of CDS debris present on the Whitsundays region of the Great Barrier Reef Marine Park, seen by the significant interaction between treatment and impact (Table 1) i.e. before and after implementation of the scheme and the debris covered by the scheme and the debris not covered (Fig. 3).
Table 1. Analysis of deviance table (Type II Wald chisquare tests).
|Variable||Z Statistic (Chisq)||Degrees of freedom||P-value|
|Impact (pre and post implementation)||0.485||1||0.4861|
|Treatment ∗ Impact||3051.834||1||<0.001|
COVID-19 impacted the abundance and types of litter in the environment, in most cases there was in increase, especially in instances of personal protective equipment found in the environment (Abedin et al., 2022; Nghiem et al., 2021; Peng et al., 2021; Torres and De-la-Torre, 2021). However, our results indicate there was a reduction in container debris, likely due to increase recycling participation (Schuyler et al., 2018) and compounded by lower levels of littering during “lockdowns” and voluntary periods of reduced socialisation and activities.
The Whitsunday region likely receives litter from local littering, however, with the dramatic drop in both debris classes observed in 2022, when the region received higher than pervious tourist visitation (Tourism Research Australia, 2023), suggests the source of debris on the outer islands is more likely to be from remote sources transported by ocean currents. Buoyant objects transported by the wind (Critchell and Lambrechts, 2016) will likely be transported from the populated areas in the south by the southeast trade winds (Fig. 1). Debris in the Pacific Ocean and Coral Sea could also be a source of debris to the region, however the mechanism of transport is less clear. The fall in observed CDS debris from 2020 to 2022, not seen in the other debris, suggests an impact from the container deposit scheme. This was likely coupled with some lock-down effect, where debris may have been reduced due to restricted movements of people in populated South East Queensland, reducing littering in general in 2020. The dramatic decrease in both classes of debris in 2022, could be a lag effect of the lockdowns in Southeast Queensland, however, data from 2023 and beyond will be necessary to confirm this.
Gacutan et al. (2023) used community science effort to identify drivers of accumulation on beaches, they undertook uniform sampling across Queensland at 17 beaches across three years. Their findings provided unique insights into drivers of accumulation, however, they found no effect of lock downs to the total litter abundance on beaches. They note that the sampling locations were often remote, which may reduce the effect of additional PPE debris and reduction of litter that we observe here. Our data is complemented by Sherow et al. (2023), who found that COVID-19 related lockdowns reduced the abundance of larger plastic items found in storm drains in Melbourne, Australia. Strom drains provide an opportunity to sample very close the potential litter sources, with a short delay between the littering event and the sampling event compared to beach sampling, as we have in this study. The increased time, and distance, between littering and sampling could allow litter to become diffused into the environment making signals of changes in source volume more difficult observe. However, the clear signal observed in this study shows that local action to reduce the amount of plastic lost from the waste management system can have a direct impact on coastal environments. This confirms the finding by Schuyler et al. (2018), who compared states with and without container deposit schemes to assess the effectiveness of the strategy. Here we show the success of a newly implemented scheme in a single region showing that time lag between implementation and evidence in the environment can be short. With schemes about to begin elsewhere, for example in Victoria, Australia, this is a promising opportunity to confirm this with strategic before and after sampling.
Our work shows that legacy clean-up data can be used to effectively see changes brought about by policy changes. It is likely that the effect is diluted due to the broad categories used then quantifying debris, however the signal is present, which should encourage further targeted action towards litter classes at local, state, and national scales. Our statistical analysis was made possible by the effort of the volunteers on the ground in the Whitsunday region. Many of the beaches in the region are relatively small with moderate debris loads which allows volunteers to collect much of the debris (see effort volunteer correlation analysis Sup Mat.), in other regions where beaches are much longer, or debris loads much higher, this may not be the case. We suggest groups attempting to replicate our work conduct their own analysis of effort and observed loads to check that the assumption holds in their region. If effort needs to be considered, we suggest observed debris load be scaled by number of volunteers and time spent on the beach to make the data comparable across beaches and clean up events. The work of Eco Barge Inc. and their dedicated volunteers is not the only example of sustained effort towards quantifying ocean litter, we believe that an approach such as the one presented here could be used on other legacy datasets to detect changes in litter abundance through time. Key decisions around which classes to include should be undertaken so that the analysis is capturing the appropriate data.
Our ability to monitor the success or failure of policy implementation, and schemes such as container deposit schemes, depend on the sampling design and effort. The uptake of the AMDI sampling and cataloguing protocols by Australian and international community science organisations is a great step forward in the ability to use the data collected to answer scientific questions. However, to increase the ability to detect changes in baseline abundance of debris in the environment we recommend that community science organisations visit the same locations at the same time of year. If possible visiting locations multiple times a year will allow for more robust and straightforward comparisons through time. Volunteer effort is such a valuable resource and as data collection efforts continue, we will gain further information on these promising trends.