plastic waste management case study

Plastic Waste Management: A Case Study From Dehradun, India

To enhance the Plastic Waste Management at Dehradun, India, Earth5R , an Environmental Organization based in India initiated a project called ‘ Know Your Plastics ’. The project aims at raising awareness about plastic waste and also aspires to increase recycling rates of products.

Clean-Up And Classification Of Plastic Waste 

As part of the project, volunteers visited 10 locations in their neighborhood to collect the maximum amount of plastic waste possible. A time limit was dedicated to segregating waste into six different categories:   MLP(multi-layer packaging), PET( Polyethylene terephthalate) plastics, LDPE(Low Density Polyethylene), HDPE(High Density Polyethylene), Tetra packs and Synthetic fibers. Any other kind of waste that was found was included in the ‘other’ category.

After the waste was segregated, the data put together is analyzed to figure out what category contributes to most of the pollution. It also assists in finding out which companies are generating most of the plastic waste.

Waste Data Utilised For Research Work And Creating Awareness 

As an effort to bring into perspective the ongoing issue of plastic waste and how it hinders the implementation of sustainable development goals and environmental growth, some data has been represented below:

• The Changing Markets  Foundation stated that as of 2020, Coca-Cola was the largest plastic footprint on earth with 2.9 million metric tonnes of plastic packaging produced annually. While Pepsico, came second with 2.3 millon metric tonnes of plastic waste.
• A Central Pollution Control Board ( CPCB ) report from 2018-19 puts the total annual plastic waste generation in India at a humongous 3.3 million metric tonnes per year.
• More than half of the plastic waste (approx.60%) goes in for recycling whereas the rest of it goes unpicked in the natural environment.
• The current situation of the COVID-19 pandemic has aggravated the issue with large amounts of plastic and medical waste being disposed of carelessly.
• As per data from 2019, metropolitan cities like Chennai, Bengaluru and Delhi contribute to more than 50% of the plastic waste deposition.

Recklessly increasing dependency on plastics simply because of their durability is choking our waterways and is becoming an immeasurable threat to the terrestrial as well as the aquatic ecosystem!

Predictions  say that the amount of plastic waste in the environment will only keep increasing if no strict action is taken against it.

Plastic Waste Management Initiative At Dehradun, India

Arya Mitra ,  an   Earth5R volunteer   from Dehradun took the initiative to go about the Global Plastic Waste Crisis from his hometown. He conducted a sequence of 10 cleanup sessions, analysed the waste collected and provided the material.

His views on why he wanted to join the project were, “I wanted to join the ‘Know Your Plastics’ project because I wanted to understand the types of waste and how I could help in achieving  a long term goal, not only by picking up waste right now but actually encouraging the society around me to assist in accomplishing the objective of sustainable development. With the help of Earth5R, I would like to raise awareness about plastic waste not only in my city but outside the boundaries too and also do the required steps that need to be implemented in order to bring the crisis under control and gradually solve it.”

With the help of Earth5R, I would like to raise awareness about plastic waste not only in my city but outside the boundaries too and also do the required steps that need to be implemented in order to bring the crisis under control and gradually solve it-ARYA MITRA, EARTH5R VOLUNTEER @DEHRADUN, INDIA

Plastic Waste Data Collected In Dehradun

Cleanup and segregation of data was carried out in 10 different locations by Arya Mitra in his locality.

He collected and analyzed the data, the results are as follows:

• A total of 246 plastic waste items were collected.
• 150 Multi-Layer Packaging(MLP)Products constituted the highest amount of the plastic waste i.e. 60.9%.
• This was followed by 48 Low Density Polyethylene Products  (LDPE) waste which made up 19.5% of the total.
• 19 Tetra Packs were found which formed 7.7% of the total.
• 9 High Density Plastic (HDPE) Products were found forming 3.6% of the total plastic waste.
• 5 Polyethylene terephthalate (PET)Products were found which made up 2.03% of the total plastic waste.

Lack of proper waste management leads to waste being found at places which are harmful for the environment. Arya also stated, “According to my findings, most of the waste was found near school boundaries and comparatively lesser around the residential areas. I also wanted to mention that most of the plastic waste material consisted of things which are usually tabooed in the society for example: pregnancy test kits other contraceptives and packets of tobacco. Maybe people are not comfortable with disposing these off at home and so unfortunately, they happen to litter the streets outside!”

I also wanted to mention that most of the plastic waste material consisted of things which are usually tabooed in the society for example: pregnancy test kits other contraceptives and packets of tobacco. Maybe people are not comfortable with disposing these off at home and so unfortunately, they happen to litter the streets outside!– ARYA MITRA, EARTH5R VOLUNTEER

Burning Of Plastic Waste

Due to lack of management in the city, all the waste is littered on the roads and is highly hazardous for the environment. As an outcome of lack of segregation and recycling, plastic is left in the soil to decompose or to be burnt which again poses detrimental effects on the environment.

Another important point that Arya brings up is “I am positive that the rate of plastic consumption in my city is very high. People are not even responsible enough to throw their plastic waste in segregated dustbins that have been set up. Due to their careless behaviour, the entire ecosystem has to bear the consequences.” 

This behavior highlights the lack of education and awareness of the people belonging to the city. 

How To Solve The Global Plastic Waste Issue?

The responsibility of solving the Plastic Waste Crisis falls directly on the shoulders of the people. They must switch to recyclable and reusable plastics or things that do not pose a threat to the environment. 

The government must make policies or laws encouraging plastic ban, use economic incentives to stimulate manufacturers to adopt alternatives to plastic or create revenue that can fund plastic waste cleanup efforts.

As Sylvia Earle, a marine biologist says,  “It is the worst of times but it is the best of times because we still have a chance,”  we must not let go of that chance to protect our ecosystem and the environment around us. Instead, we must work together towards a brighter plastic-free future leading us on the road to sustainable development. It is all in the hands of those in power after all and as citizens of the world we must be responsible enough to give back to Mother Earth for she has granted to us the gift of life.

Reported by Arya Mitra; Edited by Krishangi Jasani

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• Published: 29 January 2019

Future scenarios of global plastic waste generation and disposal

• Laurent Lebreton 1 , 2 &
• Anthony Andrady 3  

Palgrave Communications volume  5 , Article number:  6 ( 2019 ) Cite this article

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• Environmental studies

The accumulation of mismanaged plastic waste (MPW) in the environment is a global growing concern. Knowing with precision where litter is generated is important to target priority areas for the implementation of mitigation policies. In this study, using country-level data on waste management combined with high-resolution distributions and long-term projections of population and the gross domestic product (GDP), we present projections of global MPW generation at ~1 km resolution from now to 2060. We estimated between 60 and 99 million metric tonnes (Mt) of MPW were produced globally in 2015. In a business-as-usual scenario, this figure could triple to 155–265 Mt y −1 by 2060. The future MPW load will continue to be disproportionately high in African and Asian continents even in the future years. However, we show that this growth in plastic waste can be reduced if developing economies significantly invest in waste management infrastructures as their GDP grows in the future and if efforts are made internationally to reduce the fraction of plastic in municipal solid waste. Using our projections, we also demonstrate that the majority of MPW (91%) are transported via watersheds larger than 100 km 2 suggesting that rivers are major pathways for plastic litter to the ocean.

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Introduction.

Commercial production of plastics that started around 1950’s has enjoyed exceptional growth, to reach the present global annual production of 330 million metric tonnes (Mt) for 2016 (Plastics Europe, 2017 ). Including the resin used in spinning textile fibres (Lenzing Group, 2016 ), this figure is closer to 393 Mt, a value that interestingly matches the global human biomass. At the present rate of growth, plastics production is estimated to double within the next 20 years. This impressive success of plastics is unparalleled by any competing materials used in packaging or construction, the two major applications areas of plastics. Plastics production is energy intensive with resins having an embodied energy of 62–108 MJ kg −1 (inclusive of feedstock energy) much higher than for paper, wood, glass or metals (except for Aluminium) (Hammond and Jones, 2008 ). About 4% of fossil-fuel extracted annually is presently used as raw materials for plastics (British Plastics Federation, 2008 ) and it is the natural gas liquid fraction or low-value gaseous fraction from petroleum refining that is mostly used to make plastics. The demand on fossil fuel, energy, as well as the associated carbon emissions by the industry, will increase as the future consumer demand for plastics increases. By year 2050 plastics manufacturing and processing may account for as much as 20% of petroleum consumed globally and 15% of the annual carbon emissions budget (World Economic Forum, 2016 ). There is considerable interest in switching to biomass feedstock to make bioplastics that include the most-used synthetic plastic, polyethylene.

It is the considerable societal benefits of plastics (Andrady and Neal, 2009 ) that account for its popularity as a material. Plastics represent a low-cost, easily formable, high-modulus, hydrophobic, bio-inert material that finds use in a bewildering range of consumer products. It is often the preferred, and with some products an indispensable, choice in consumer packaging that accounts for 42% of the global annual resin production (Geyer et al., 2017 ). Transparent packaging films that are both strong and impermeable to gases and moisture, facilitate conformal packaging (vacuum packs) or controlled-environment packaging (as in red-meat packs). The exceptional thermal insulation of expanded polystyrene foam has ensured its lead in hot-food service applications (Andrady and Neal, 2009 ). The handful of resins that dominate packaging and food service applications are also the most frequently found in municipal solid waste as well as in marine debris (Andrady, 2011 ): these are polyethylene, polypropylene, polyethylene terephthalate, and polystyrene. Generally, the lighter, more durable and less expensive plastics (especially polyvinyl chloride) have replaced metal and even wood in building applications that accounts for about 20% of global production (Plastics Europe, 2017 ). The same is true for comfort fibres in fabric and in carpeting where plastic has replaced natural fibres such as wool, cotton or silk, for the most part. Plastic products are indispensable in medical applications that require sterility and microbial inertness.

Projected increase in future plastic use will result in a concomitant increase in post-consumer plastic waste. For instance, by 2025 the global urban population is estimated to generate > 6 Mt of solid waste daily (Hoornweg et al. 2013 ). Even using the present fraction of ~10% plastics in the solid waste stream, this amounts to over 200 Mt of waste plastics: this was the entire global plastic resin production in 2002 (Plastics Europe, 2014 ). The discouragingly slow growth in recycling rates and the likely increase in single-use products, both exacerbate this situation. Packaging products are almost always discarded with their functional characteristics virtually intact, permitting both facile re-use and recycling, however only about 9.4% of plastics (E.P.A., 2016 ) is presently recycled in the US mainly due to collection costs, lack of requisite infrastructure and poor demand by processors for recycled plastic granulate.

Adding to risks of local flooding by clogging drains and degradation of air quality from open dumps, a serious concern is where mismanaged waste located near inland waterways or in coastal regions serves as an input of plastics into rivers and the oceans. Microplastics or small fragments (<5 mm in size), mostly derived by surface weathering degradation of plastic debris (Andrady, 2017 ), now ubiquitous in soil (Rillig, 2012 ), rivers and lakes (Lebreton et al., 2017 ) as well as in the oceans (Barnes et al., 2009 ). Virgin pellets and some manufactured products such as microbeads, also find their way into oceans (Mason et al., 2016 ). The smaller the dimension of the microplastic, the wider will be the range of marine organisms that are able to ingest or otherwise interact with them. Microplastics absorb and concentrate hydrophobic pollutants present in sea water at very low concentrations and these can be bioavailable to the ingesting species. Over 660 species (Secretariat of the Convention on Biological Diversity, 2012 ), ranging from seabirds, fish, bivalves to the zooplanktons at the bottom of the marine food chain, are known to be affected by plastic debris (Ivar do Sul and Costa, 2014 ; Van Cauwenberghe and Janssen, 2014 ) and there is credible evidence of the bioavailability of pollutants concentrated in the plastic (Heskett et al., 2012 ; Chen et al., 2017 ) to the ingesting organisms. Potential trophic transfer of the plastics and pollutants along the food chain (Au et al., 2017 ) and their potential tainting of human seafood (Santillo et al., 2017 ) are particularly serious concerns.

However, broad estimates of global plastic production or MPW generation are inadequate to assess the regional impacts of plastic waste on the ecosystem that would dictate the need for mitigation. Future increase in population density and therefore regional or even country-level plastic waste generation are spatially heterogeneous. For instance, while the global population is predicted to increase to over 9.5 billion in 2025 over 97% of this growth will be in Asia and Africa (United Nations, 2015 ). Coastal communities in those regions will place a disproportionate plastic waste burden on the environment and especially the ocean. Understanding this spatial variation in plastics influx into the ocean requires the development of a high-resolution map of global plastic usage that would indicate geographic bias in future plastic waste trends.

Generally, plastics in the global ecosystem is distributed between three fractions: plastics in use, post-consumer managed plastic waste, and a mismanaged plastic waste (MPW) fraction, the last of which includes urban litter (Geyer et al., 2017 ). Packaging-related plastics have a particularly short in-use phase and therefore dominate municipal plastic waste and subsequently the mismanaged waste as well. In addition to urban litter, mismanaged waste also includes inadequately contained waste such as open dumps and are therefore transportable via runoff and wind. Some mismanaged waste may be collected by street sweepers and concerned citizen groups and be re-introduced in one of the two first categories. Managed waste is accounted for and is typically disposed of by incineration or landfilling. Both per capita use of plastics and the population density at a given location determines the local plastic demand by consumers, reflected in the in-use fraction. The former generally scales with the local gross domestic product (GDP) (Hoornweg et al., 2013 ) with the more affluent countries using as much as over 100 kg/pp/year (Waste Atlas, 2016 ). But in populous countries such as India or China a relatively low per capita use of plastics coupled with a high population density can still yield large tonnage of plastic waste. A recent study (Jambeck et al., 2015 ) based on a World Bank dataset (Hoornweg and Bhada-Tata, 2012 ) on country-specific waste generation and management concluded that the fraction of this waste that is reaching the oceans represented 4.8 to 12.7 Mt of plastics in 2010 from populations living within 50 km from the coastline.

The present effort is aimed at examining the possibility of improving the granularity of country-level plastic waste generation data, using reasonable assumptions based on population density and affluence. A comprehensive dataset of municipality-level waste generation data for different countries is not presently available. While we appreciate the limitations of evolving country-level waste generation data into higher-resolution maps of finer granularity, we believe the exercise is important as it yields likely global ‘hot spots’ for plastic waste at present and progressed into the near future. An important trend is the increased migration into urban areas that in general would tend to exacerbate the developing hot-spots. We therefore employ high-resolution (30 × 30 arc seconds) population density and GDP distributions to model waste data at cells in a finer geographic grid. The use of these two indicators allows to represent plastic waste generation near large urban areas but also to possibly predict the likely accumulation near major transportation axes such as roads and railways which may not be represented by municipality-level data.

Consumer demand for plastics and per capita GDP relation

We use data distributed by Waste Atlas ( 2016 ) for per capita municipal solid waste generation (expressed in kg y −1 ), mismanaged fraction (expressed in %) and plastic fraction in municipal solid waste (expressed in %). Hitherto, models of plastic waste generation had relied on the data set compiled by the World Bank (Hoornweg and Bhada-Tata, 2012 ). In this effort we use an alternative source, the Waste Atlas, a resource compiled using country-level data submitted by individual experts from each country. More recent and detailed data are available from this source compared to the World Bank dataset. A comparison between the two datasets is provided in Supplementary Figure 1 . Unfortunately, this collection is non-exhaustive, and information is provided for some countries only. Data is available for n  = 160 countries for per capita municipal solid waste generation, n  = 95 countries for unsound disposal fraction and n  = 105 countries for plastic proportion in municipal solid waste.

When data was available, we compared these variables with per capita GDP provided by the International Monetary Fund (IMF, 2016 ). We performed a Pearson product-moment correlation test for the three waste variables against per capita GDP (Table 1 ). Both per capita municipal solid waste generation and mismanaged fraction showed a statistically significant correlation with per capita GDP. The correlation was expectedly positive for waste generation reflecting the higher consumption levels in rich country and negative for the mismanaged fraction showing a greater amount of waste unsoundly disposed for developing countries (Fig. 1 ). However, per capita GDP and the proportion of plastic in municipal solid waste did not demonstrate a statistically significant relationship. This suggests that the proportion of plastic in solid waste is generally independent of the per capita GDP of a country. The proportion of plastic in municipal solid waste for countries provided by Waste-Atlas was homogeneously distributed when compared against per capita GDP with an average value of 10.9% and standard deviation of 4.5% ( n  = 105).

Per capita municipal solid waste (MSW) generation a and mismanaged fraction b for different per capita GDP categories of country. Red line shows the median, the blue box extends from the 25th to 75th percentile, the black whisker extends from minimum and maximum non-outliers and red crosses shows outliers

The statistically significant correlations between per capita municipal solid waste generation, mismanaged fraction and per capita GDP allow us to predict these quantities when they are not reported by Waste Atlas ( n  = 160 countries reported). When the proportion of plastic in municipal solid waste is not reported we used the global reported average.

Model formulation

Current per capita plastic waste generation is calculated by multiplying per capita municipal solid waste generation by the fraction of plastic found within waste. When waste generation data for a country was missing, we derived per capita municipal solid waste generation ( Ms c ) from per capita GDP ( X c , in 2016 USD) by introducing an empirical function:

Where a  = 11.434 (lower: 11.218, upper: 11.953) and b  = 0.3433 (lower: 0.3565, upper: 0.3298), best fit parameters for n  = 160 countries (Supplementary Figure 2a ). The production rates reported by Waste Atlas completed with estimations from this relation allowed us to draw an exhaustive list of per capita municipal solid waste generation at national level, worldwide. For any country, an estimate of total plastic waste produced ( A) could then be formulated:

Where p is the average proportion of plastic in solid waste and Y is the country’s total population. When p was not reported by Waste Atlas, we used the global average of 10.9 ± 0.85% (95% C.I., n  = 105). Value of p is assumed to be the same for all unmanaged waste including litter. This method for estimating global plastic waste generation has a drawback, however, in that it does not account for spatial heterogeneity within a country. Furthermore, when integrating national plastic waste generation at global scale, the total was estimated to range between 212 and 229 Mt y −1 for 2015. A figure higher than the predicted amount derived from production data, assuming conservatively that 50% of plastic production goes to packaging and household items (i.e., ~50% of 380 Mt in 2015 is 190 Mt). A similar overestimation was found using the World Bank dataset with which the same method resulted in 212 Mt of global plastic waste for 2015. We explain these results by a bias in estimating solid waste generation in rural areas. Waste management data is mainly reported for urban centres and we trust that levels of per capita use may not be representative of rural areas.

An important model assumption here, is that per capita solid waste generation scales with GDP inside a country. We used high resolution (30 by 30 arc seconds, ~1 km) gridded population density data (Landscan, 2014 ) and sub-national GDP data (UNEP/DEWA/GRID-Geneva, 2012 ). The global GDP dataset distinguishes between rural and urban population and allows the mapping of per capita GDP at sub-national scale. We combined these two datasets to estimate per capita solid waste generation derived from computed per capita GDP. For a model grid cell i , inside a given country, we computed the plastic waste generation:

Where x(i) is GDP and y(i) is population in cell i . The additional correction term allows to scale generation between urban and rural zones. If per capita GDP in cell i is lower than the national average X c , the per capita waste generation, term is reduced from the national value. We computed national and global generation by integrating over land cells. Our global estimated municipal plastic waste generation of 181 Mt for 2015 is closer to predictions from production data and confirms our assumptions.

For future projections we used country-scale population projections distributed by the United Nations ( 2015 ) from 2015 to 2060. We sourced national GDP projections for 2015 to 2021 from the IMF ( 2016 ) and long-term growth rate projections for 2022 to 2060 from the Organisation for Economic Cooperation and Development (OECD, 2014 ). Since the gridded distribution of population and GDP used in this study are representative of the current situation, we scaled the distribution in time using the country scale projections. As such we neglected the possible migration of population or variations in domestic product inside countries for our future projections as we considered the relative distribution to remain the same over time. For time t and in model cell i of a given country, we computed the plastic waste generation A(i,t) following:

Where Ms c (t 0 ) and X c (t 0 ) are the current national value for respectively per capita solid waste generation and per capita GDP. x(i) and y(i) are the current GDP and population in cell i . Xc(t) and Y(t) are the respective national projections of per capita GDP and population at time t . This model allowed us to produce high resolution maps of future plastic waste generation from 2015 to 2060, every five years. An additional map was created for 2010 to compare results with previous estimates (Supplementary Figure 3 ).

Municipal waste management scenarios

We derived mismanaged plastic waste generation from fraction of unsound disposal per country reported by Hoornweg and Bhada-Tata ( 2012 ) as proposed in a previous assessment (Jambeck et al. 2015 ). When data was not reported (50% of countries) we proposed an empirical formulation to estimate the fraction of mismanaged waste K from per capita GDP ( X c in 2016 USD) based on the correlation introduced earlier:

With e  = −3.13 10 −3 and f  = 104 (lower: 70, upper: 138), best fit parameters for n  = 95 countries (Supplementary Figure 2b ). Many countries with a high GDP per capita had a reported mismanaged fraction of 0%. To account for accidental and deliberate littering in these countries, Jambeck et al. ( 2015 ) used a minimum threshold of 2% of mismanaged waste. In this study, we conservatively considered a minimum of 1% for our mid-point estimates. However, as a significant degree of uncertainty is associated with this value, we considered using an upper and lower threshold by varying orders of magnitude from 0.1 to 10% minimum mismanaged waste. As some countries reported 100% of mismanaged waste, we also applied a threshold on the upper limit to account for opportunistic recycling and waste picking. The upper threshold for mismanaged waste was respectively set to 90, 99 and 99.9% for lower, mid and upper estimates.

Reported and estimated mismanaged fractions K were associated to plastic waste generation per country A to produce quantities of MPW B :

For future projections, we assumed three scenarios. For scenario A, we considered the case of business-as-usual where the mismanaged fraction reported by Waste Atlas ( 2016 ) were maintained into the future years (estimated from equation ( 5 ) at 2015 levels when not reported). In scenario B, we varied the mismanaged fraction K(t) for each country over time from an initial value K(t 0 ) using the following:

Since e is negative, a growth in per capita GDP ( Xc ) from t 0 to t results in the decrease of mismanaged fraction (i.e., as the economy grows, waste management infrastructure improves). A minimum threshold ranging from 0.1 to 10% and maximum from 90 to 99.9% were also applied to this relation. Finally, in scenario C, we used the same assumption as in scenario B and further reduced the input of individual countries by capping the fraction p of plastic in solid waste to 10% by 2020 and to 5% by 2040.

Plastic waste and watersheds

We introduced a spatial indicator representing the size of the watershed of which a model cell belongs to. Starting from the HydroSHEDS database (Lehner et al., 2008 ) regrouping global watershed boundaries as polygonal features, we computed the area covered by individual watersheds and created a 30 arc second resolution global grid to match with our plastic waste generation maps. Individual grid cells were associated to the watershed they belonged to and assigned the watershed’s surface area as value. If a grid cell was not located in any watershed, it was considered as oceanic cell. We categorised grid cells from small watersheds (<10 km 2 ) to continental rivers (>1,000,000 km 2 ) by orders of magnitude of surface area (7 categories in total). The main motivation behind this analysis was to identify the fraction of global plastic waste generated in coastal areas against the fraction generated inland that may reach the marine environment via rivers. The surface area of watersheds naturally decreases while approaching the coast from land. Some smaller watershed may be found in land generally in arid regions such as desert or mountains. As the waste generation in these areas is very small since they are generally unpopulated, we neglected the contribution of these regions from inland inputs.

Global plastic waste generation

Combining country-level data on self-reported per capita municipal solid waste (Waste Atlas, 2016 ) generation with high resolution (30 arc seconds) distributions of global population (Landscan, 2014 ) and GDP (UNEP/DEWA/GRID-Geneva, 2012 ), we estimated plastic waste generation at local level. The estimate reflects differences in consumption within a country, differentiating between consumption rates in urban and rural areas. Based on self-reported levels of inadequate disposal, we estimated between 60 and 99 (mid-point: 80) million metric tonnes (Mt) of municipal plastic waste were inadequately disposed globally into the environment during 2015 (Fig. 2 ). The quantity represents about 47% of the global annual municipal plastic waste generation (mid-point estimate of 181 Mt for n  = 188 countries).

Global mismanaged plastic waste (MPW) generation in 2015. Plastic waste generation is computed globally on a 30 by 30 arc seconds resolution reflecting geographical heterogeneity based on population and GDP distributions. National data on waste management reported per countries (Waste Atlas, 2016 ) is derived to estimate the mismanaged fraction at local scale. The 10 largest producing urban centres are labelled on the map with Manila, Cairo and Kolkata as the leading agglomerations

Hosting 60% of the global population (United Nations, 2015 ), the Asian continent was in 2015 the leading generating region of plastic waste with 82 Mt, followed by Europe (31 Mt) and Northern America (29 Mt). Latin America (including the Caribbean) and Africa each produced 19 Mt of plastic waste while Oceania generated about 0.9 Mt. However, the proportion of produced waste that was inadequately disposed varied across regions (Waste Atlas, 2016 ). We derived quantities of MPW from reported waste management data per countries and per capita GDP. As a significant level of uncertainty is associated with the data on municipal waste management, we introduced lower and upper ranges along with our midpoint estimate and thereafter reported the ranges in brackets. With an average of 63% of inadequately disposed waste for 2015, Asia released 52 (42–58) Mt of plastic waste into the environment, representing 65% of the global MPW generation. Africa, however, had the highest rate of unsound waste disposal with an average of 88.5% resulting in a total of 17 (10–20) Mt of unsoundly disposed plastic waste despite the low levels of resin production. Latin America and the Caribbean were the third generating region with 7.9 (6.7–8.3) Mt, followed by Europe with 3.3 (1.3–9.1) Mt, Northern America with 0.3 (0.03–3.0) Mt, and Oceania with 0.14 (0.05–0.32) Mt. Interestingly, except with Asia, the regions with unsoundly disposed plastics, do not correspond to production volumes of plastics in these regions; the Middle East and Africa account for only 7% of resin production while US and Europe each account for ~20% of global plastics production. The unfair practice of importing waste, especially e-waste, from developed nations, is to a large part responsible for this problem in Africa for example (Schmidt, 2006 ).

We ranked contributors by mid-point estimate of MPW generation at regional and national scale (Table 2 ). The generation of waste from the Asian continent was distributed between Southern, Eastern and South-East Asia with respectively 18.4, 17.4 and 11.7 Mt y −1 of annual MPW generation. Inputs from China with 17.2 Mt y −1 , and India with 14.4 Mt y −1 dominated the waste generation figures for Asia. These two countries provide over a third of the global MPW generation. The Philippines were the third generating country with 4.52 Mt y −1 but Manila, its capital, was predicted as the largest urban centre for the generation of MPW with at least 0.81 Mt y −1 for the agglomeration, the same annual amount as produced by countries like Sudan or Algeria. Five of the top 10 countries for mismanaged plastic waste identified by this model include only 5 of the top ten countries identified by Jambeck et al. ( 2015 ) for 2010. Except for Tanzania, all ten were identified in the top 20 countries in this previous work. However, at least a part of this discrepancy might be due to differences in methodology adopted in previous and present studies. The finer granularity of the present model allows us to predict local scale accumulation. Solid waste is mostly an urban phenomenon (Hoornweg et al., 2013 ) and our model confirms this by predicting substantial accumulation around cities and near axes of transportation with 89% of global MPW produced over 10% of the total modelled landmass, and 64% over less than 1.5% (Fig. 3 ). High resolution renderings of MPW generation on land are presented in Supplementary Figure 4 . We ranked global urban centres by MPW generation. Manila, the largest contributor predicted by our model, was followed by Cairo and Kolkata with 0.53 and 0.48 Mt y −1 . Sao Paolo in Brazil was ranked fourth with 0.47 Mt y −1 . The rest of the top 10 cities were in Asia with Bangkok (0.45 Mt y −1 ), New Delhi (0.41 Mt y −1 ), Shanghai (0.5 Mt y −1 ), Kuala Lumpur (0.29 Mt y −1 ), Beijing (0.28 Mt y −1 ) and Guangzhou (0.27 Mt y −1 ).

Distribution of annual MPW generation over total land surface area. Modelled cells were classified by rate of MPW generation (0–1, 1–10, …, >10k kg y −1 ). Total land surface area (blue, expressed in % of total modelled surface) and total MPW generation (grey, expressed in % of total generation) are represented for each cell category

Future scenarios

We predicted future plastic waste generation by considering population (United Nations, 2015 ) and GDP (IMF, 2016 ; OECD, 2014 ) growth rates per country. By 2020, under a business-as usual-scenario for plastic consumption, our predictive model suggested the world will produce above 200 Mt of municipal plastic waste annually and around 230 Mt by 2025. This is in good agreement with previous projections of solid waste generation (Hoornweg et al., 2013 ) with daily estimates above 6 Mt in 2025. Considering global average proportion of plastic in municipal solid waste (10.9%, lower: 8.3%, upper: 13.2%), a daily input of 6 Mt of solid waste may represent around 239 (182–290) Mt of annual generation of municipal plastic waste. Based on long term projections of population and GDP per countries, we estimated the global municipal plastic waste generation could reach 300 Mt annually by 2040 and 380 Mt by 2060. This increase is also in good agreement with municipal solid waste generation projections which are not expected to peak within this century (Hoornweg et al., 2013 ). To predict the total mismanaged fraction (MPW) of future plastic production, we initially considered two scenarios. In scenario A, we assumed the case of business-as-usual where the level of waste management remains at the current status in different countries worldwide. In scenario B, we assumed waste management efforts will improve with increased investment in infrastructure as the economies in individual countries grow in the future.

Following a growing demand of plastic by end-users, the MPW generation in scenario A would nearly triple from the present value of 80 (60–99) Mt y −1 to 213 (155–265) Mt y −1 by 2060. Midpoint plastic demand by end-users in Asia was projected to steadily increase from 99 Mt y −1 in 2020 to 151 Mt y −1 in 2040 and 193 Mt in 2060. If no efforts are made in waste management, generation of MPW in Asia could double from 52 (42–58) Mt y −1 in 2020 to 129 (104–150) Mt y −1 in 2060. India would become the largest MPW generating country by 2035 and would reach 46.3 (38.6–52.0) Mt y −1 by 2060, followed by China with 33.3 (28.1–36.8) Mt y −1 and the Philippines with 11.6 (10.1–12.4) Mt y −1 . According to scenario A, cities like Manila, Cairo, Kolkata or New Delhi would reach the 1 Mt y −1 mark for annual MPW generation before 2060. However, if we assume a gradual improvement of waste management infrastructures with scenario B, we estimated that global MPW generation could peak before 2020 and decrease to 50 (22–94) Mt y −1 by 2060. In this case, the decrease of global MPW generation would mainly be driven by the rapid economic development in Asia. We found that the continent could reduce MPW generation below 30 Mt y −1 by 2040 and below 10 Mt y −1 by 2060. This scenario would mean reducing mismanaged waste below 10% of total generated waste by around 2030 for current major contributors such as China, Thailand, Indonesia or Turkey, and around 2060 for countries like India, the Philippines, or Vietnam. Our model shows how the main contribution to global MPW production would then shift from Asia to Africa. Our projections suggested that African demand by consumers for plastic will increase exponentially in the future decades from 23 Mt y −1 of municipal plastic waste in 2010 to 72 Mt y −1 in 2060. The demand for plastic by end-users in Africa was projected higher than in Northern America or Europe by 2035. Under this scenario, by 2060, 8 out of the 10 generating country will be an African country with Nigeria (3.08–6.46 Mt y −1 ), Congo (2.22–6.33 Mt y −1 ), Tanzania (1.16–6.42 Mt y −1 ), Ethiopia (1.01–4.10 Mt y −1 ), Niger (0.88–2.69 Mt y −1 ), Sudan (0.38–2.00 Mt y −1 ), Mozambique (0.82–1.64 Mt y −1 ) and Mali (0.47–1.78 Mt y −1 ).

Finally, we investigated an alternative option where demand of plastic per capita would substantially decrease in the future. We introduced a third scenario C, where waste management efforts improve as the economy of a country grows like in scenario B, but also where plastic use by households is reduced to 10% of municipal solid waste by 2020 and to 5% by 2040, reflecting willingness from country to curb waste generation and ban single-use plastics. This objective is reachable as some developed economies already demonstrates such low rate. Notably Denmark, first country to introduce a tax on plastic bags in 1993 for example, now reporting 1% of municipal waste composed of plastic (Waste Atlas, 2016 ). We found no significant relation between fraction of plastic in solid waste and per capita GDP. Some strong economies for example reported large fractions such as The Netherlands, largest reported figure for a developed economy with 19% of plastic in municipal solid waste. Under a scenario where countries would align to reduce fraction of plastic in municipal waste to below 5%, the global plastic waste generation would drop to around 140 Mt per year by 2040 but increase again to 2015 levels with nearly 180 Mt per year in 2060 as global population grows. Combined with a gradual investment in waste management infrastructure however, the global MPW generation could be reduced to a third of current value with annual average generation below 25 Mt y −1 before 2060 including 74% generated in Africa and 21% in Asia. Long term projections for global MPW generation for scenario A, B and C are presented in Fig. 4 as well as distributions per continent. A full breakdown of results per sub-region with confidence interval for 2020, 2040 and 2060 is given for scenario A, B and C in Supplementary Tables 2 , 3 and 4 .

Future projections of global mismanaged plastic waste (MPW) generation and distribution per continent under three scenarios. Scenario A corresponds to a business-as-usual case where the level of waste management corresponds to data for 2015 and consumer demand for plastic increases with economy. Scenario B considers that waste management infrastructures improve as per capita GDP grows. Scenario C reflects a reduction in plastic demand per capita with fraction of plastic in municipal solid waste capped at 10% by 2020 and 5% by 2040, waste management gradually improves as in scenario B. (Top, graph) The global midpoint estimates for MPW generation are represented with thick lines while the shaded areas represent our confidence interval. (Bottom, maps) Continental distribution of MPW generation in 2020, 2040 and 2060 under the three investigated scenarios

Sources to ocean

The rapid accumulation of MPW on land can result in the contamination of waterways and eventually the marine environment. Through runoff, winds, and gravity, plastic debris slowly makes its way downhill and enters the sea from coastal environments (Jambeck et al., 2015 ) and through rivers (Lebreton et al., 2017 ). A first global estimate of plastic inputs from land to the sea for 2010 (Jambeck et al., 2015 ) proposed to consider municipal plastic waste generation for population living within 50 km from the coastline and assumed 25% (15–40%) of plastic waste from this population enters the ocean. Under this condition, we predicted a total of 20.5 Mt of MPW for coastal population in 2010. Following the study, this quantity may be converted to an annual global input into sea of 5.1 (3.1–8.2) Mt. The fraction of plastic waste entering the ocean may vary between locations, however. The magnitude and timing of plastic waste displacement on land is poorly known (Horton et al., 2017 ) and may be a function of topography, land use, climate, vegetation and, particle shape and size (e.g., microplastics may be more easily transported than larger, more complexly shaped debris).

Considering populations living within a fixed distance from the coastline may not always be representative of land-based sources to the ocean as plastic waste generated inland can be transported by rivers. Predicted accumulation of plastic waste on land can be distributed into watersheds (Lebreton et al., 2017 ). Here, we categorised watersheds by surface area considering that small watersheds are located directly at the coastline while larger watersheds may expand in land and form streams and rivers (Fig. 5 ). We grouped watersheds by orders of magnitude in surface area from coastal watersheds (<10 km 2 ) to continental rivers (>1,000,000 km 2 ). From our global distribution of mismanaged plastic waste for 2015, we estimated that 5% of waste was discarded directly near the coastline (watershed surface area < 10 km 2 ) and 4% at proximity to the coastline (10 to 100 km 2 ). This result shows that the majority (91%) of MPW was generated inside larger watersheds (>100 km 2 ) and suggests that rivers may be a major vector of transport of plastic waste from land into the ocean. Over a quarter of the global waste was discarded into the watersheds of only 14 continental rivers (>1,000,000 km 2 , namely the Mississippi, the Nelson, the St Lawrence, the Amazon, the Paraná, the Congo, the Niger, the Nile, the Zambezi, the Volga, the Lena, the Amur, the Yangtze and the Ganges rivers).

Distribution of global mismanaged plastic waste (MPW) generation in 2015 by watershed size categories. The surface area of a watershed is a good indicator to differentiate coastal watersheds from large rivers. An example (top) is shown for the Mississippi river mouth with watersheds of different size categories. The global generation of mismanaged waste was binned into surface area categories (bottom) from coastal watersheds (<10 km 2 ) to continental rivers (>1,000,000 km 2 )

Here we present for the first time, spatial distributions of mismanaged municipal plastic waste generation at an order of 1 km resolution, worldwide from now to 2060. As synthetized in this study, these results can be interpreted at global, regional, national and local scale. This information at this level of resolution for GDP and population density, even with the limitation of low-resolution waste generation data, is important as it can help policy makers target priority areas for mitigation and development of waste management infrastructures. Furthermore, projected into the future, this dataset can assist countries, regions and municipalities in fixing objectives to reduce generation of plastic waste and limit releases into the environment. China and India currently contribute to above a third of the global MPW generation, with GDP growth rate projected above 4% until mid-2020s and early 2040 s respectively (OECD, 2014 ). Under a business-as-usual scenario, it is fair to expect that consumer demand for plastic will dramatically increase in these countries. According to the World Bank (Hoornweg and Bhada-Tata, 2012 ), 70 and 85% of municipal waste is currently mismanaged in China and India, respectively. It is crucial for cities and municipalities in these countries to invest in waste management and prepare for the surge in consumer plastic demand predicted for the future decades and the associated waste management needs. A scenario where China and India reduce the fraction of mismanaged waste to 50% by respectively 2020 and 2030, and to the current western standard by 2035 and 2050, along with other countries in similar economic transition, shows that we could reach peak generation of MPW at global scale in the next decade. Our results highlight the urgency of the situation and the necessity of an international law-abiding agreement between countries on the management of plastic waste as we could be generating twice the current amount of MPW per year, globally, by mid-century if the situation remains unchanged. These should focus on anti-dumping of waste in developing countries, developing better recycling architectures and standardising technologies to prevent escape of microplastics from land-based sources into the ocean.

However, our results also suggest that gradual increase in waste management infrastructure may not be enough for some parts of the world. Our projections show some countries, particularly in Africa, that may not reach this transition before 2060. The consumer demand for plastic in Africa was projected to grow by 375% from the current demand by 2060, the highest growth for a continent, the global average being 210%. This exponential increase in demand for plastics by the end-user is fuelled by GDP growth but also by a substantial increase of population. Africa’s demographic is expected to reach 2.9 billion by 2060 (United Nations, 2015 ) representing a population growth of 245% from 2015, much higher than any other continents (global average: 138%). As a result, despite GDP growth, the per capita GDP remains sufficiently low for our model to consider a large portion of produced waste to be likely mismanaged. These assumptions may have to be further questioned however it is an indication that resolving the global issue of plastic contamination in the environment may require cooperation between cities and countries as well as the promotion of further international aid for waste management in the future. But more importantly, it shows that GDP-fuelled demand for plastics by end-users is not sustainable at global scale and support the necessity to introduce quotas in plastic use. In a scenario where the plastic fraction in municipal solid waste is capped to 10% by 2020 and to 5% by 2040, the release of plastic into the environment could be efficiently reduced to a third of the current level, assuming significant improvement are also made in terms of waste management to compensate for population growth. Prohibition of single-use plastics is currently being proposed in policies of cities, countries and regions around the world. To efficiently mitigate the release of plastic waste into the environment in the future, our results emphasise two aspects with (1) the improvement of waste management infrastructure as well as our capacity of recycling waste and (2) the introduction of a limit on fraction of plastic in solid waste per capita reflecting reduction in demand for single-use plastics.

The analysis of our results may not only be constrained to political boundaries as in this study, we show how considering physical boundaries may help in understanding the generation of plastic waste in watersheds and indirectly sources of plastic to the ocean (Lebreton et al., 2017 ; Schmidt et al., 2017 ). Our data is made available to assist hydrologist and geologist in quantifying sources of plastic litter in rivers and soils (Gonzalez et al., 2016 ; van Emmerik et al., 2018 ). This is an important aspect as we also show that most of the produced MPW each year is located inside larger watersheds characterised by a river and several confluents. Understanding the geography of waste generation can help targeting rivers for mitigation and eventually reduce the source of plastic waste to the ocean. The transport of plastic litter on land is poorly understood and additional site-specific work may be required to quantify the portion of litter that is stored in soils and the portion that enters waterways, and subsequently the ocean. Other physical boundaries of interest are the average ultraviolet radiation levels received by unit of surface area or the average ground air temperature as these environmental parameters may dictate degradation processes for plastic waste on land and therefore microplastics generation rate. Well outside the scope of this study, we noticed however that the current plastic demand by end-users is dominantly distributed in regions with a temperate climate, but our projections shows that this demand will shift towards lower latitude, in much warmer climate, within the course of this century with predicted major consumers in Southern Asia, South-Eastern Asia or in Africa. The foregoing discussion was based on MPW in general. However, recent research specifically points to ecological impacts of meso-plastics, micro-plastics and nano-plastics in the ocean environment (Avio et al., 2017 ). These smaller fragments are generated by weathering degradation of plastic debris in the outdoor environment, especially beaches, followed by mechanical action of wind and waves fragmenting the degraded plastics (Andrady, 2017 ). A combination of solar UV radiation and high sample temperatures are well known to control the rates of degradation and therefore the fragmentation of MPW into micro-particles (Abdelhafidia et al., 2015 ). Fragmentation of common plastics into micro- and nano-sized particles has been demonstrated in laboratory (Wohlleben and Neubauer, 2016 ; Kalogerakis et al., 2017 ). It is difficult to accurately quantify the rates of potential micro-plastics generation at a given location as the fraction of MPW exposed to solar radiation cannot be easily assessed. But those locations of high solar irradiance and high ambient temperatures might be qualitatively expected to promote faster weathering and fragmentation of exposed plastics waste. Considering the already developed hotspots, those in African continent will experience both high downward solar UV flux as well as high ambient temperatures followed by those in India and East Asia. The significance of these hotspots is therefore magnified because of the increased propensity to generate micro-plastics at a faster rate. Accordingly, they demand more stringent efforts at plastic waste management to avoid the load of micro- and nano-plastics they may generate via weathering.

It is important to note that some uncertainties are associated to our estimates. To reflect these, we introduced lower and upper ranges along our mid-point projections. The calculations of these confidence intervals include the uncertainties related to per capita municipal solid waste generation, proportion of plastic in waste and proportion of waste that is mismanaged. This data was reported at national level. However, values may vary inside countries. As local information is unavailable, we proposed a model to consider sub-national variations of plastic consumption. This approach naturally yields uncertainties which are also included in the calculation of our confidence interval. The confidence interval for our projections naturally increase as we progress in the future. For example, our projections neglect sub-national change of population distribution since population density was assumed to grow at the same rate as the national average. This assumption may introduce a bias in our projections. Rural exodus may further reinforce urban influences on waste production in the future. Also, our projections do not consider plastic waste exports or imports for reprocessing: in 2012, for instance, 15 Mt was traded, mainly between Europe and China. The import of waste for recycling has recently been shut down from China however and many countries now face difficulties to handle the accumulated plastic from curb-side collection. Similarly, our model cannot account for future exceptional economic, societal or financial events. Advances in technology, consumer product design, and behaviour patterns may change the per capita GDP-consumption relationship as well as conversion rates of waste to MPW. Generally, we encourage the systematic reporting of waste management data at sub-national scale by countries to reduce some of the uncertainties introduced above. Better reporting of waste management practices could lead to the development of a national plastic waste emission, similarly to the creation of carbon emission index by climate scientists (Le Quéré et al., 2018 ). Such index would foster international cooperation and assist countries and municipalities in setting objectives to reduce plastic waste releases into natural environments.

Data availability

Gridded distributions of total and mismanaged municipal plastic waste generation are available on Figshare in.tif format as well as a country scale results summary spreadsheet (Lebreton and Andrady, 2018 ).

Abdelhafidia A, Babaghayoua IM, Chabiraa SF, Sebaaa M (2015) Impact of solar radiation effects on the physicochemical properties of polyethylene (PE) plastic film. Procedia Social Behav Sci 195:2922–2929

Article   Google Scholar  

Andrady AL (2011) Microplastics in the marine environment. Mar Pollut Bull 62(8):1596–1605

Article   CAS   Google Scholar  

Andrady AL (2017) The plastic in microplastics: a review. Mar Pollut Bull 119(1):12–22

Andrady AL, Neal MA (2009) Applications and societal benefits of plastics. Philos Trans R Soc B 364(1526):1977–1984

Au SY, Lee CM, Weinstein JE, van den Hurk P, Klaine SJ (2017) Trophic transfer of microplastics in aquatic ecosystems: Identifying critical research needs. Integr Environ Assess Manag 13(3):505–509

Avio C, Gorbi S, Regoli F (2017) Plastics and microplastics in the oceans: from emerging pollutants to emerged threat. Mar Env Res 128:2–11

Barnes D, Galgani F, Thompson R, Barlaz M (2009) Accumulation and fragmentation of plastic debris in global environments. Philos Trans R Soc B: Biol Sci 364(1526):1985–1998

British Plastics Federation (2008) Oil consumption. British Plastics Federation. http://www.bpf.co.uk/press/Oil_Consumption . Accessed 20 Apr 2018

Chen Q, Reisser J, Cunsolo S, Kwadijk C, Kotterman M, Proietti M, Slat B, Ferrari FF, Schwarz A, Levivier A, Yin D, Hollert H, Koelmans AA (2017) Pollutants in plastics within the North Pacific subtropical gyre. Environ Sci Technol 52(2):446–456

Article   ADS   Google Scholar  

Secretariat of the Convention on Biological Diversity and the Scientific and Technical Advisory Panel—GEF (2012) Impacts of marine debris on biodiversity: current status and potential solutions. Montreal, Technical Series No. 67. Secretariat of the Convention on Biological Diversity.

E.P.A. (2016) Advancing sustainable materials management: 2014 fact sheet. Assessing trends in material generation, recycling, composting, combustion with energy recovery and landfilling in the United States. United States Environmental Protection Agency, Office of Land and Emergency Management, Washington DC

Geyer R, Jambeck J, Law KL (2017) Production, use, and fate of all plastics ever made. Sci Adv 3(7):e1700782

Gonzalez FD, Hanke G, Tweehuysen G, Bellert B, Holzhauer M, Palatinus A, Hohenblum P, Oosterbaan L (2016) Riverine litter monitoring—options and recommendations. MSFD GES TG Marine Litter Thematic Report, JRC Technical Report, EUR 28307. https://doi.org/10.2788/461233 . Accessed 10 Oct 2018

Hammond GP and Jones CI (2008) Embodied energy and carbon in construction materials. Proc Inst Civil Eng Energ 161(2): 87–98

Heskett M et al. (2012) Measurement of persistent organic pollutants (POPs) in plastic resin pellets from remote islands: toward establishment of background concentrations for International Pellet Watch. Mar Pollut Bull 64(2):445–448

Hoornweg D and Bhada-Tata P (2012) What a waste: a global review of solid waste management. World Bank. http://hdl.handle.net/10986/17388 . Accessed 28 Feb 2016

Hoornweg D, Bhada-Tata P, Kennedy C (2013) Environment: waste production must peak this century. Nature 502:615–616

Horton AA, Walton A, Spurgeon DJ, Lahive E, Svendsen C (2017) Microplastics in freshwater and terrestrial environments: Evaluating the current understanding to identify the knowledge gaps and future research priorities Sci Total Environ 586:127–141

Article   ADS   CAS   Google Scholar  

IMF (2016) World Economic Outlook Database. I nternational Monetary Fund. https://www.imf.org/external/pubs/ft/weo/2016/02/weodata/index.aspx . Accessed 28 Nov 2016

Ivar do Sul JA, Costa MF (2014) The present and future of microplastic pollution in the marine environment. Environ Pollut 185:352–364

Jambeck JR, Geyer R, Wilcox C, Siegler TR, Perryman M, Andrady A, Narayan R, Law KL (2015) Plastic waste inputs from land into the ocean. Science 347(6223):768–771

Kalogerakis N, Karkanorachaki K, Kalogerakis G, Triantafyllidi EI, Gotsis AD, Partsinevelos P, Fava FH (2017) Microplastics generation: onset of fragmentation of polyethylene films in marine environment mesocosms. Front Mar Sci 4:84

Landscan (2014) Global population database. Oak Ridge National Laboratory. http://web.ornl.gov/sci/landscan . Accessed 26 June 2017

Le Quéré C, Andrew RM, Friedlingstein P, Sitch S, Pongratz J, Manning AC, Korsbakken JI, Peters GP, Canadell JG, Jackson RB, Boden TA, Tans PP, Andrews OD, Arora VK, Bakker DCE, Barbero L, Becker M, Betts RA, Bopp L, Chevallier F, Chini LP, Ciais P, Cosca CE, Cross J, Currie K, Gasser T, Harris I, Hauck J, Haverd V, Houghton RA, Hunt CW, Hurtt G, Ilyina T, Jain AK, Kato E, Kautz M, Keeling RF, Klein Goldewijk K, Körtzinger A, Landschützer P, Lefèvre N, Lenton A, Lienert S, Lima I, Lombardozzi D, Metzl N, Millero F, Monteiro PMS, Munro DR, Nabel JEMS, Nakaoka S-I, Nojiri Y, Padin XA, Peregon A, Pfeil B, Pierrot D, Poulter B, Rehder G, Reimer J, Rödenbeck C, Schwinger J, Séférian R, Skjelvan I, Stocker BD, Tian H, Tilbrook B, Tubiello FN, van der Laan-Luijkx IT, van der Werf GR, van Heuven S, Viovy N, Vuichard N, Walker AP, Watson AJ, Wiltshire AJ, Zaehle S, Zhu D (2018) Global Carbon Budget 2017. Earth Syst Sci Data 10:405–448

Lebreton L and Andrady A (2018) Supplementary data for 'Future scenarios of global plastic waste generation and disposal'. figshare. https://doi.org/10.6084/m9.figshare.5900335

Lebreton L, van der Zwet J, Damsteeg JW, Slat B, Andrady A, Reisser J (2017) River plastic emissions to the world’s oceans. Nat Commun 8:15611

Lehner B, Verdin K, Jarvis A (2008) New global hydrography derived from spaceborne elevation data. Eos, Trans, AGU 89(10):93–94

Lenzing Group (2016) Factsheet. Lenzing Group. http://www.lenzing.com/en/investors/factsheet.html . Accessed 12 Dec 2017

Mason SA, Garneau D, Sutton R, Chu Y, Ehmann K, Barnes J, Fink P, Papazissimos D, Rogers DL (2016) Microplastic pollution is widely detected in US municipal wastewater treatment plant effluent. Environ Pollut 218:1045–1054

OECD (2014) Economic outlook no 95. Long-term baseline projections. Organisation for Economic Co-operation and Development. http://stats.oecd.org/Index.aspx?DataSetCode=EO95_LTB . Accessed 28 Nov 2016

Plastics Europe (2014) Plastics—The facts. Plastic Europe. https://www.plasticseurope.org/en/resources/publications/95-plastics-facts-2014 . Accessed 12 Dec 2017

Plastics Europe (2017) Plastics—The facts. Plastic Europe. https://www.plasticseurope.org/en/resources/publications/274-plastics-facts-2017 . Accessed 20 Apr 2018

Rillig MC (2012) Microplastic in terrestrial ecosystems and the soil. Environ Sci Technol 46(12):6453–6454

Santillo D, Miller K, Johnston P (2017) Microplastics as contaminants in commercially important seafood species. Integr Environ Assess Manag 13:516–521

Schmidt C, Krauth T, Wagner S (2017) Export of plastic debris by rivers into the sea. Environ Sci Technol 51(21):12246–12253

Schmidt CW (2006) Unfair Trade e-Waste in Africa. Environ Health Perspect 114(4):232–235

UNEP/DEWA/GRID-Geneva (2012) Gross domestic product 2010. United Nations Environment Program. https://preview.grid.unep.ch/ . Accessed 22 Dec 2016

United Nations (2015) Probabilistic population projections based on the world population prospects: the 2015 revision. United Nations Department of Economic and Social Affairs. https://esa.un.org/unpd/wpp/publications/Files/WPP2015_Volume-I_Comprehensive-Tables.pdf . Accessed 28 Nov 2016

Van Cauwenberghe L, Janssen CR (2014) Microplastics in bivalves cultured for human consumption. Environ Polut 193:65–70

van Emmerik T, Kieu-Le TC, Loozen M, van Oeveren K, Strady E, Bui XT, Egger M, Gaspéri J, Lebreton L, Nguyen PD, Schwarz A, Slat B, Tassin B (2018) A methodology to characterize riverine macroplastic emission into the ocean. Front Mar Sci 5:372

Waste Atlas (2016) D-waste. Waste Atlas. http://www.atlas.d-waste.com/ . Accessed 4 Aug 2016

Wohlleben W, Neubauer N (2016) Quantitative rates of release from weathered nanocomposites are determined across 5 orders of magnitude by the matrix, modulated by the embedded nanomaterial. NanoImpact 1:39–45

World Economic Forum (2016) The new plastics economy. Rethinking the future of plastics. World Economic Forum, Geneva, Switzerland

Google Scholar  

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Acknowledgements

This study was made possible thanks to the open-access distribution of several global dataset including the Waste Atlas, the LandScan 2014 High Resolution Global Population Data, the GDP distribution by UNEP/DEWA/GRID-Geneva and the HydroSHEDS by USGS/WWF. We would like to thank the donors of The Ocean Cleanup Foundation who helped funding this study, as well as Dr Tim van Emmerik for reviewing this manuscript. The authors would also like to thank the participants of GESAMP Working Group 40 on Sources, Fate and Effects of Microplastics in the Marine Environment, for the valuable exchanges in the early stage of this study.

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Lebreton, L., Andrady, A. Future scenarios of global plastic waste generation and disposal. Palgrave Commun 5 , 6 (2019). https://doi.org/10.1057/s41599-018-0212-7

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1 Department of Natural Resources and Environmental Management, IPB University, Bogor, Indonesia

5 Natural Resources and Environmental Management , IPB University, Jl. Raya Pajajaran, Secretariat Study Program 2nd Floor Campus IPB Baranangsiang, Bogor, Jawa Barat, 16144 Bogor, Indonesia

2 Department of Aquatic Resources Management, Faculty of Fisheries and Marine Sciences, IPB University, Bogor, Indonesia

4 Center for Coastal and Marine Resources Studies, IPB University, Bogor, Indonesia

3 Technology Industry of Agriculture Department, IPB University, Bogor, Indonesia

Sigid Hariyadi

The accumulation of plastic waste in the marine environment has increased the global risk of marine pollution due to its negative impact on land, ecosystems, and especially the food chain and marine organisms. Ineffective plastic waste management has reduced the quality of the coastal environment including community sanitation and health, landscapes, and coastal views, and influenced economic sectors such as tourism, fisheries, and shipping. The economic and public activities within coastal areas have consistently as the source of plastic waste leakage either directly or indirectly. Various variables involved and connected each other, some influential and other existing variables were not working effectively and do not support each other optimally in the system. The policy without limitation on the plastic production and certain type of plastic such as packaging or single-use, bags, and a lack of management capacity have led to the establishment of a burden on current plastic waste management within the coastal and marine of Jakarta Bay. Therefore, the study aims to analyze the roles and interrelation of variables that influence plastic waste management in Jakarta Bay. Public participation through group discussion, interview, and Micmac analysis method was used to identify, map, and analyze their interrelationships, roles, and hierarchy in the plastic waste management system. The results showed that the dynamics of variables’ interaction affect their level of performance and contribution. The variables with strong influence have the potential to strengthen others, while some had a high dependence which was vulnerable to have ineffective performance in the waste management system as their stability relied on other variables’ performance. A group of variables were greatly affected by others and indicates that they had lower influence and higher dependence, while the rest of the variables were relatively disconnected from the system. The key to better waste management is to improve the performance and the quality of relationships of variables that were found in the influential and intermediate quadrants. Furthermore, the indirect influence variables also need to be considered as they have the potential to contribute to the future system strategy or scenario planning.

Introduction

The increasing crisis of marine plastic waste has become a global concern due to its significant negative impact on humans and the environment. The improper management that leads to rapid plastic pollution in the marine and coastal areas has threatened the quality of the ecosystem, coastal sanitation and aesthetics, and human health due to seafood consumption containing microplastics. Kaza et al. ( 2018 ) have estimated that about 2 billion tons of solid waste are not managed properly, and the number may increase to 3.4 billion tons by 2050. WWF ( 2019 ) also estimated that in 2016 plastic waste had reached 396 million metric tons (MMT) or 53 kg of plastic/person, and by 2030 there will be a 40% increase. Other research shows that 150 million tons (MT) of plastics worldwide are in the ocean and will increase by 250 MT if the trends of urbanization, production, and consumption continue (Shuker and Chapman, 2018 ). Jambeck et al. ( 2015 ) also reported that 275 MMT were produced by 192 coastal countries in 2010, and approximately 4.8 to 12.7 MMT/year entered the sea. While Lebreton et al. ( 2017 ) estimated that 1.15 to 2.41 MT amount of plastic flows from global riverine areas into the oceans annually.

Nearly 80% of the world’s plastic waste is from land-based sources, shorelines, and the sea contains 60 to 90% combinations of different plastic polymers (Andrady 2015 ; Derraik 2002 ; Galgani et al. 2015 ; UNEP 2016 ; WWF 2019 ). In Indonesia, the Ministry of Environment and Forestry (KLHK) reported that the national waste production has reached an amount of 67.8 MT/year with 18.5% or 12.54 MT is plastic waste (KLHK 2021 ). Shuker and Chapman ( 2018 ) also reported that an average of 3.22 MT produced waste that was not managed properly resulted in an amount of 0.48 to 1.29 MMT plastic waste leaks into the oceans/year. This range is consistent with other studies conducted by Shuker and Chapman ( 2018 ), Cordova et al. ( 2019 ), and KLHK ( 2017 ) with the amount of 400,000 tons/year, 268.740 to 594.558 tons/year, and 488.096 tons/year respectively.

Plastic waste negatively disrupts marine ecosystems and environmental sustainability including marine food webs, fish, other biotas, and humans’ health that consume seafood containing microplastics. The negative impact is widespread and harmful because it is transboundary, persistent at sea, contains hazardous substances, and takes time to decompose. Furthermore, marine biota is also entangled by plastic materials, or plastic waste contaminates coastal vegetation, soil, water, and air (waste burning) with its toxic substances and will have wider damage on marine habitats and ecosystems. These negative impacts have directly affected economic activities such as shipping, fishing, aquaculture, tourism, and recreation (Vince and Hardesty 2016 ; Shuker and Chapman 2018 ; UNEP 2017 ).

The characteristics of semi-enclosed waters with various activities surrounding made Jakarta Bay vulnerable to receiving dumped plastic waste from various sources, such as river outlets, households or settlements, offices, industry, fisheries, ports, and marine transportation. The bay is vulnerable to being a dumping ground of waste leakages from land and sea that are carried by tides into the bay or estuaries, and the Thousand Islands. The observation conducted in 15 stations of the bay indicates the plastic waste leakage and accumulation occurred in the river mouth and port area (Fig.  1 ). Dadap, Muara Kali Adem, and Banjir Kanal Timur rivers were the highest, while Angke Fishing Port is highest in the port areas. The type of plastic waste found was dominated by plastic packaging, bags, styrofoam, and bottles respectively (Fig.  2 ).

The type of plastic waste found in Jakarta Bay

The packaging like single-use and plastic bags that are significantly found in the bay area is closely related to plastic production policy and the innovation of plastic types. The critical issues, for example, no limitations on the production and use, the comfortable use of plastics by consumers with a lack of awareness on how to treat plastic waste properly, and limited capacity of the authority in the implementation of prevention and handling instrument are all lead to the establishment of crisis in the plastic waste management in Jakarta Bay. This complexity needs to be unraveled from upstream to downstream to provide an understanding of gaps, what is the most influential variables, and their roles, including their relationship in the management of plastic waste.

The government has declared a 70% reduction of marine debris through the 2018 to 2025 action plan (Presidential Decree 83/2018 concerning Marine Debris Handling), and the National Policy and Strategy (Jakstranas) for the Management of Household Waste and Similar Types of Household Waste (Presidential Decree 97/2017) with the targets of 30% reduction and 70% waste handling through its action plan. These policies derivatives are being followed up by the DKI Jakarta Government Decree 108/2018 at the Regional Policy and Strategy (Jakstrada) level. Ideally, regulatory effectiveness has played an important role in dealing with the complexity of current plastic waste management because it ensures the target can be achieved optimally and effectively. In addition, the majority of variables are reflected in these action plans and become a guideline for related institutions including Jakarta Bay authorities. However, it seems that the implementation of the action plans including its institutional arrangements has not been effective. Hence, the crisis and gaps component then needs to be addressed in the management of plastic waste. It needs the initiative to map the most influential and other existing variables, and their level of relationships, analyze gaps in the implementation of policies, action plans, and instruments, and anticipate the need for policy and scenarios as recommendations for strengthening and improving future management.

Materials and methods

Case study site.

As the condition in Jakarta Bay could not be separated from the national context, the study focused on management system both at the national level and in Jakarta Bay. Location of study is presented in Fig. ​ Fig.3. Their 3 . Their dynamic relationships were analyzed because the improvement at the national level directly affects the management at the regional level and vice versa.

The study case site of the research in Jakarta Bay

Solid waste photoes are shown in Fig. ​ Fig.4, 4 , showing condition of river mouths and traditional fishing ports which are polluted by solid waste. Composition of solid waste in the west, middle and east zones of Jakarta Bay and its volume is shown in ​ in5. 5 . In the middle part mostly fishing and public ports, the plastic waste is not only coming from the estuary and enters the port area by tidal influence, but also significant waste is produced from inside the port by anchored ships, shops, and visitors. Other sources are from outside the estuaries such as marine transportation and floating plastic waste that is carried from other territory seas like Thousand Islands water into the bay waters, estuaries, and ports. The most significant plastic waste found in the eastern part of the bay, followed by the western and middle parts is the least.

Waste leakage and accumulation in the river mouth of Dadap (top left) Banjir Kanal Timur (top right), Cakung Drain/Cilincing Fisher Village (bottom left), and in the port area of Muara Angke Fishing Port (bottom right)

Composition of plastic waste in the west, middle and east zones of Jakarta Bay

Data collection and analysis

The scope of analysis was to identify, map, and classify variables, and to describe their relationship which later provides essential information for system improvements. The Micmac (matrix of cross-impact multiplications applied to a classification) method was used to performs structural analysis through (i) determining key variables, (ii) mapping the relationship between influence (Y) and dependence (X) variables, and (iii) explaining their relevance and causal chain in the system, which among others is used as a reference to unravel and reduce the complexity (Fauzi 2019 ; Tiwari 2013 ). The principle of Micmac analysis is mapping the interactions to obtain an integrated picture of variables that have a direct or indirect impact and a detailed display of relationships between elements (Veltemeyer and Sahin 2014). In addition, the key variables are the main or essential factors that affect the system. In the study of the interrelationships between elements, the Micmac method identifies the main influential, dependent variables and explains the evolution of the system through the combination of ideas using a matrix (Godet 2000 ).

Data were collected through a series of public participation or focus group discussions (FGD) and interviews where experts’ and stakeholders’ opinions were examined. The participants were representatives from the government (national, regional), experts (academicians, researchers), industries, non-government organizations, associations, and community groups (Table  1 ). They had various expertise and relevant experiences in plastic waste management such as in the recycling plastic and packaging industry, advocation, community empowerment, researchers, government officials at the national or regional level in handling day-to-day plastic waste management, particularly in Jakarta Bay.

FGD participants

The explored opinions of experts and stakeholders were used as information for Micmac in analyzing the relationship between variables. The analysis results can be used by policymakers to intervene in the system and to look for alternative strategies as well as action plan formulations (Sahin et al. 2013 ). In this case, Micmac provides the ranking of variables by measuring the level of influence and dependence and how they interact as a system (Veltmeyer and Sahin 2014 ). In Fig.  6 , the data from FGD (stages 1–2) was analyzed by Micmac (stages 3–4). The identified variables (Table  3 ) were scored and the outcomes were presented through the MDI matrix (Table  4 ). The score used to evaluate the influence between variables was 0 = no relationship, 1 = weak relationship, 2 = average, 3 = strong, P = potential influence in the future. Based on the Matrix of Direct Influences (MDI) analysis, the Micmac method classified variables into certain quadrants (Fig.  7 ) based on their level of influence-dependence (Godet 1994 ; Fauzi 2019 ), and its description as shown in Table  2 .

The stages of analisis using Micmac method

Variable characteristic and position based on influence and dependence level

The description of variables and quadrants

(Saxena et al. 1990 ; Godet and Durrance 2011 ; Fauzi 2019 )

Identified variables in the plastic waste management systems

The level of influence between variables (MDI Matrix)

The result shows a map of variables that describes the influence and dependence level based on MDI matrix, variables position changes (displacement map) based on indirect relationships, and a hierarchy diagram of variables which both are based on the matrix of direct and indirect influence (MDII). Each variable of the marine plastic waste management system was ranked either by the direct influence and dependence level or indirect influence factor.

Results and discussion

The variables of the plastic waste management.

Thirty relevant variables were identified in the management system of plastic waste and agreed by FGD as shown in Table  3 , and all were categorized into five dimensions namely environment, economy, governance, socio-cultural, dan technology based on Micmac method (Godet 1994 ; Fauzi 2019 ).

The roles and interrelation of the variables

The characteristic of variables in quadrant 1 with high influence and low dependence is influential and has the potential of being a determinant factor in the system (Godet and Durrance 2011 ). Therefore, their acceleration or performance will greatly affect other variables in quadrants 2 and 3, and on all other variables in the system (Fig.  8 or Table ​ Table5). For 5 ). For example, the variable Product that tends to increase annually would directly increase the number of uses, distributions, and plastic waste in the community and the environment. The variable Product along with the limitations of Facility, Fund and government capacity (Intergov) affect variables in quadrant 2 such as the significant volume of plastic waste (Volume), weak consolidation of interests between pro-industry and pro-environment actors, gaps in the implementation of the waste reduction roadmap (Roadmap), and other related regulations (Policy) including the circular economy (Circular). Product design also represents consumers’ culture and their high dependence on the use of plastic containers including single-use and bags in situations where low public awareness occurred (Behavior). However, the performance of variables in quadrant 2 may also have an effect (positive/negative) on other variables in the system, depending on the extent of influence received.

The variable mapping based on the direct influence and dependence level

The group of variables based on their position at each quadrant

The variables in quadrant 2 with higher influence are also important but their dependence is relatively high such as Roadmap which is essential for waste reduction from the industrial side. On the other side, it is also a challenge for the Actor’s solidity in the implementation which sometimes raises questions about the commitment in implementing Roadmap, a package of Policies or instruments. The performance of other variables like Behavior, number of waste in the environment (Volume), Circular economy as an alternative waste reduction strategy, and law enforcement (Lawnforce) are greatly influenced by other variables. Saxena et al. ( 1990 ), and Godet and Durrance ( 2011 ) identified it as an unstable variable with the potential of becoming a source of conflicts. The possible conflict may arise from the two sides of the Actors’ (institutions/companies) interest either to prioritize their mission or show the commitment and responsibility on plastic waste reduction mandated by regulations. The variable with dependence both in quadrants 2 and 3 are affected by these situations. However, some variables in quadrant 2 have the potential of making a positive impact on the system when they run effectively, namely Actors, Behavior, Roadmap, Policy, Circular, and Lawnforce.

The leakage from various sources of waste in Jakarta Bay enables plastic waste to accumulate and spread (Volume), resulting in reduced Quality of the environment. The existing use of technology (Techno) such as fleets of ships, waste collection vessels, and waste nets have not been sufficient for optimal waste handling. The same non-optimal situation occurred on several variables, such as inadequate community knowledge-skill (Capacity) in prevention and handling waste, gaps in the implementation of SOPs, and Guidelines on handling waste from homes and in the environment (coastal, seas, islands, and ports), and inadequate of waste Data. In addition, other variables in the waste management system still need improvements such as the increase of the added value of plastic waste innovation (Innovate), to design easy-to-manage products (Recyclable), empowering and strengthening small-middle-micro business through partnerships (Business), and monitoring and evaluation systems (Monev).

The pros and cons of plastic bag taxation and reduction are an indication of the lack of solidity between stakeholders. The continuous accumulation and spread of plastic waste from various sources of leakages made Jakarta Bay vulnerable close to a critical stage of management. A symptom of slow achievement performance is seen from the unfinished ministerial regulation on plastic bags taxation, stakeholders’ conflict of interest, continuous plastic waste leakage into the sea and coastal area. This is a challenge that requires immediate responses, otherwise, permanent burdens will continue to create ineffectiveness in management, which may lead to a millennium ‘tragedy of the common’ as illustrated by Vince and Hardesty ( 2018 ). It needs a systems approach as Eriyatno ( 2012 ) with a framework to seek the integration between elements or variables function through a complete understanding of their structure and complex processes, or a cross-scale interaction between element or subsystem that enables communication and cooperation, and also involve actors, information, facilities, techniques, programs, and other support elements (Jackson and Ferris 2012 ; INCOSE 2006 ).

As variables in quadrant 2 are strategic, they require maximum management attention. At Cilincing fishing village (Fig.  4 ), the plastic waste accumulates and spreads in the riverbanks and village environment and the impacts are mainly from some activities such as households, shops, river outlets, and fisheries (fishers, fish market and auction, loading-unloading, docking). The volume of waste is increasing and the environment is filled with litter, among other things because the availability of facilities (trash cans, waste vessels, nets, grinding machines) is not enough for intensive waste collection. The condition also contributed by the role of some variables such as (i) Behavior that disposes of waste improperly, (ii) the insufficient number of personnel and budget (Intergov), (iii) lack of stakeholder engagement in the sea (Actor), (iv) inadequate community participation and capacity (Capacity), and (v) lack of sanctions or fines (Lawnforce). The fishers also argued that inadequate facilities and the low capacity of local authorities were the main sources of the problems. All variables in quadrant 2 were unable to solve the problem independently and required support from other variables, especially from quadrant 1. Therefore, the ignorance of existing conditions will have an impact on the system, and this will lead to dynamics and complexity in management, as well as system instability. At this point, the system may lead to the low accountability of the marine plastic waste management as WWF ( 2019 ). However, as Saxena et al. ( 1990 ), these variables have the potential to establish a positive contribution to better future management when handled properly and also create a beneficial reverse chain process for the system.

The complexity of the wastes management system requires an approach that examines problems and the behavior of subsystems as it has the potential of being a determinant variable such as Govreg, Actor, Policy, Intergov, Behaviour, and Lawnforce. However, the performance of behavioral change cannot be measured in a short period but rather requires evolution. BPS ( 2018 ) reported the Environmental Awareness Index on the waste management category, where 72% of the community have indifferent interest in waste management. Plastic bags taxation has also received rejections from producers/associations due to the presence of multi-agencies with different missions and interests. The decision-maker needs to work on preventing the instability in the waste management system and the actor variables may be used as important instruments to achieve solidity and effective collaboration.

The millennium of ‘tragedy of the commons’ in Jakarta Bay can not be avoided if the plastic waste production through various sources of leakages is faster than an existing handling efforts performance, such as producer waste reduction, recyclable products or circular economy, stakeholder cooperation, law enforcement, existing handling capacity, and behavior change. The leakages have not been handled optimally by existing technologies, facilities, application of SOPs and guidelines, community support, law enforcement, and adequate funding. The solution to this condition depends on the ability to fix the performance of highly influenced variables which are mostly in quadrants 1 and 2. In the meantime, as the performance of dependent variables in quadrant 3 will be influenced by their achievement, for example, most variable in quadrant 3 is a part of the variable Govreg action plan (Presidential Decree 83/2018 on Marine Debris Handling). The ability of the National Coordination Task Force on Marine Debris Handling to ensure its effectiveness during implementation is essential, and their success will provide a wider impact to the whole variables in the system.

The government and its hierarchies are the keys to the complexity, system instability, and low accountability as they are connected to all variables. Their effective leadership and responses through coordination, facilitation, assistance, and partnership are needed, and it may be started from the ‘government’ variable such as Policy, Support, Intergov, Govreg, Facility, Fund, Roadmap, Lawnforce, Pilot, and Incentive. These variables are the key including government support and regulations (Saxena et al. 1990 ). All efforts that are expected to succeed in its implementation are in a race against time as all sources of leakage continue to produce waste and the amount of plastic waste steadily increases. Pressure on environmental quality continues to grow, while some handling and reduction efforts are still being implemented ineffectively. Therefore, the variables in quadrant 1 with the potential of driving power need to be a priority when considering strategic plans of action (Godet and Durrance 2011 ), namely Support, Integrated, Intergov, Fund, and Facility as well as Govreg. The strategy may also consider moving their potential influence to another important variable in quadrant 2 for further improvements as they are a potential determinant factor in achieving a sustainable marine plastic waste management system.

The variables in quadrant 4 have relatively less significant effects on others and the system as a whole. With the low influence-dependence, it tends to be disconnected from the system (Saxena et al. 1990 ; Godet and Durrance 2011 ), unless several variables are intensified with widespread effects, such as enforcing Incentives for industries to design easy-to-manage plastic products, the application of management-product certifications (Certified), and the use of local community Wisdom. In Jakarta Bay, these variables have not shown a significant effect as instruments but may have the potential to be developed and strengthened. Furthermore, high influence variables may be used to promote the development of the local wisdom approaches through social sanctions or restricting people from throwing garbage into rivers-seas. In the case of Pandemic, the variable is seen by stakeholders as a new situation or a temporary variable where its influence probably will not last permanently and may likely disappear from the system in the future. However, its effects have been seen recently, for example, the limitations on implementing programs that previously involved a large number of participants, like beach clean-up, budget re-focusing policies, and research findings which indicates that there are additional types of plastic waste in Jakarta Bay that come from medical waste. Though this has the potential to slow down the progress of action plans, the implementation of other programs continued even in the midst of the pandemic.

The Level of Relationship Between Variables

The relationship between variables in plastic waste management (Fig.  9 a) showed a very strong direct influence of some influential variables such as Govreg, Product, Intergov, and Integrated to the majority of variables in intermediate and dependent quadrant (thick red lines and arrows pointing out). The level of influence showed the existing management greatly accelerated by the dynamic coordination in the implementation of the Presidential Decree of marine debris handling, the consolidation of the actor on the volume of plastic production and the wider impact of waste to the environment, and the efforts on integrated land-sea based approaches. In addition, some variables (thick red lines and arrows pointing in) such as Volume, Roadmap, Innovate, Lawnforce, Behavior, and Quality that strongly influenced by other variables. This condition was indicating that the implementation of several action plans and waste management targets has not been effective. Prevention of waste accumulation, the effectiveness of reduction roadmaps, product innovation, law enforcement, behavioral change, and environmental health cannot be achieved optimally as planned due to their highly dependent nature.

The relationship level of variables based on direct (a) and indirect (b) influence

The impact of indirect relationships also needs to be considered as useful information for proper system management. It confirms the importance of certain variables and discovers their potentials, and also their indirect actions which have an important role that is not identifiable through direct classification (Godet et al. 2004 ). Figure  9 b shows variable Support has a very strong indirect influence with future potentials of contributing to accelerate circular economy policies, industry compliance on waste reduction roadmaps, effective policy implementation, and restoration of environmental function and quality, including the achievement of several management targets as mandated by Govreg, Jakstranas, and Jakstrada DKI Jakarta. As the impact of indirect relationships (Fig.  10 a), seven variables (ranks 1–7) with high influence remained at the same rank after the indirect factor was included in the calculation. Their stability indicates that in the future these variables are still important in the management system. Eight variables increased in rank namely Fund, Volume, Lawnforce, Research, Data, Guideline, Pandemic and Innovate. The increased influence of these variables indicates their influence level as they receive a positive impact indirectly from other variables and they have the potential to be considered in future scenarios. In addition, eight variables also experienced a decrease in ranking. On the other side (Fig.  10 b), no change of position at the top six rankings, eight variables increased and nine decreased of their dependence rank after the indirect factor was included in the calculation. The increased rank indicates the performance of variables become more dependent on others especially variable Certified, while the decrease indicates the opposite situation, as shown by the performance of variable SOP.

The shifting order of variables based on influence (a) and dependence (b) after the consideration of indirect relationship

Figure  11 is a replacement map showing the position change of variables in Fig.  10 after the indirect influences were calculated. Furthermore, there were changes in the initial position of the variables in Fig.  8 and this was indicated by the change from a bigger to a smaller circle. Some variables had a change of position in their quadrant, while others shifted to another quadrant. For example, Lawnforce (increase in influence) and Facility (increase in dependency) both shifted to quadrant 2. The displacement indicates that Lawnforce has more potential influence in the future with support from certain variables in quadrants 1 and 2. While the Facility variable had more future potential dependence value as the current availability of infrastructure and facilities for plastic waste management mostly relied on the support and facilitation from the national-regional government including some support from other stakeholders such as the private sector and non-government organizations.

The shifting of variables position based on indirect influences

Variables improvement and strengthening the systems

The results of the Micmac analysis may be used as a reference to identify areas for intervention or improvement, and this could be carried out in the following ways. First, to analyze some selected variables for further treatment, making improvements, strengthening capacity, and effectiveness. Secondly, to improve the performance of driver-determinant variables in quadrant 1 to increase their effective influence on others, including some important variables in quadrant 2, and enable optimal performance as expected and gradually provide consistent impact to the system. Thirdly, particular attention is needed to explore the hidden potential of indirect influence and dependence variables for their future essential contribution. Fourth, it is necessary to focus more on critical variables and those with high influence and dependence as they are vulnerable to having an impact from other variables (quadrant 2). However, as Godet et al. ( 2004 ), these improvement plans may only fit certain parts of the analyzed system that lead to the adjustment of partial improvements. This method of analysis needs to be seen as an indicative approach of illustrating system changes and their essential information, and enable a certain number of potential actions that are planned for further improvements and better plastic waste management in Jakarta Bay. Therefore, as Vince and Hardesty ( 2018 ), a single approach may not effectively solve the complexities of environmental pollution and social challenges in the management of marine plastic waste, but rather a comprehensive approach that includes a common will by the public, effective policies, and coordination in the community (global, regional, national, local, and individual levels) including various instruments of action, programs, and regulations.

Learning the roles and interrelation of variables and understanding their influence on the waste management system is an important part of institutional arrangements. As Kooiman et al. ( 2005 ), it involves the whole process of public and private interaction to solve problems and create opportunities, including formulating and applying principles that guide the interaction process and encourage institutions to work effectively. Marine plastic waste has continued to increase in recent decades and shows no signs of decreasing or ending, thereby causing difficulties in reforming existing governance of the variables’ dimensions (Dauvergne 2018 ) as shown in Table  3 . Furthermore, the process of environmental recovery and the implementation of resource management is hindered by poor management of plastic waste (Vince and Hardesty 2016 ) due to the nature of its widespread and transboundary pollution with complexity management. In the long term, it has great potential to reduce the carrying capacity of the environment and threaten the sustainability of marine and coastal resources.

The variables in quadrants 1 and 2 are relatively influential to other variables and the system (all quadrants). They include Support, Integrated, Intergov, Govreg, Product, Fund, and Facilities (quadrant 1), and Actor, Roadmap, Behavior, Volume, Policy, and Circular (quadrant 2). Most of them are government variables or some have received an impact from government intervention. It shows that even though the government efforts are in place but some variables indicated ineffective symptoms due to the performance that is depending on influential or other variables performance. This interdependence and impacted variables can be seen in quadrants 2 and 3 where ineffectiveness is seen through the gap that existed in the policy implementation, inadequate infrastructure, and handling capacity, and low awareness and participation. The plastic production policy with no limitations and ineffective prevention and handling instrument has contributed significantly to an increase in plastic waste in marine and coastal environments. The continued accumulation of plastic waste in Jakarta Bay originating from active sources of leakage indicates the Integrated approach by combining management of waste from land-sea as well as inter-government coordination and capacity still needs an improvement.

As the impact of interdependence and impacted variables, the performance of variables needs support from influential variables. For the higher dependence variables, the solidity of actors in the implementation of management strategy is challenged by different interests, goals, or capacities, for example, the organization’s target on profit that influence the commitment, or lack of capacities (facilities, fund, technical knowledge, innovation). It then affects the performance of the roadmap on plastic waste reduction by producers where only a few of them has involved and participated in the proposal submission. The performance of behavior programs is also depending on the performance of other variables such as Actor awareness including consumer, Fund sufficiency, effective Support, Policy, and Lawnforce. Though the design of plastic produced like single-use packaging and bags are comfortable for consumers as it is cheap and practical, the lack of awareness and wisdom on the use of plastic made production contributes indirectly to the accumulation of waste. The Circular Economy approach that is expected to combine both reducing wastes in the environment and offering economic value from waste seems its performance still depends on the support of other variables. Though they are influential, the variables in quadrant 2 tend to be unstable as they perform a high dependence on other variables and are also vulnerable to being influenced by other variable performance.

The main sources of the dynamics of the system are from these quadrants, and their dynamics interaction is also seen in the pros and cons of some prevention or reduction instruments. Therefore, the key to better system management is quadrants 1 and 2 through the improvements of variable performance strategies. The improvements may focus on higher dependence and impacted variables and the effective influence of influential variables. The impact of indirect relationships also needs to be considered as reference information for future system strategy or scenario planning as their potential and importance can be discovered. The Support variable shows a very strong indirect influence on (i) Circular, (ii) Volume, (iii) Quality, (iv) Policy, and (v) Roadmap, and shows the influence and role of government are still very dominant and still needed in the system. In the future, better sustainable management requires a holistic and integrated understanding of performance and the interrelationships between variables.

Some recommendations that may be used as follow-up research include the study of i) the implementation of gaps in some policies particularly those directly related to marine and coastal areas of Jakarta Bay, and ii) stakeholder role, capacity, and solidity in the plastic waste management system. The results of this study can be used as scientific generic inputs for better future marine plastic pollution management in the bay, which is part of the integrated coastal management of Jakarta Bay. As a tropical bay, Jakarta Bay urgently needs recuperative actions in managing its coastal environment for better bay ecosystem health.

The authors did not receive support from any organization for the submitted work. No funding was received to assist with the preparation of this manuscript. No funding was received for conducting this study. No funds, grants, or other support was received.

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• Andrady AL (2015) Persistence of plastic litter in the oceans. M. Bergmann, M. Klages, L. Gutow (eds.) Marine Anthropogenic Litter pp. 57–72. Springer. 10.1007/978-3-319-16510-3_3
• BPS (2018) Statistik Lingkungan Hidup Indonesia. Pengelolaan Sampah di Indonesia. Badan Pusat Statistik. https://www.bps.go.id/publication/download
• Cordova MR, Falahudin D, Puspitasari R, Purbonegoro T, Wulandari I, Iskandar MR, Rositasari R(2019) Naskah Akademik Inisiasi Data Sampah Laut Indonesia Untuk Melengkapi Rencana Aksi Nasional Penanganan Sampah Laut Sesuai Peraturan Presiden RI No. 83 Tahun 2018. Pusat Penelitian Oseanografi - Lembaga Ilmu Pengetahuan Indonesia. https://sampahlaut.id/wp-content/uploads/2020/02/Naskah-Akademik-Inisiasi-Data-Sampah-Laut-Lembaga-Ilmu-Pengetahuan-Indonesia-LIPI.pdf
• Dauvergne P(2018) The power of environmental norms: marine plastic pollution and the politics of microbeads. Environmental Politics 27 (4), pp 579–597. 10.1080/09644016. 2018.1449090
• Derraik JG. The pollution of the marine environment by plastic debris: a review. Mar Pollut Bull. 2002; 44 (9):842–852. doi: 10.1016/S0025-326X(02)00220-5. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Eriyatno (2012) Ilmu Sistem jilid satu, 4th edn. Surabaya, Penerbit Guna Widya
• Fauzi A. Teknis Analisis Keberlanjutan. Jakarta: PT Gramedia Pustaka Utama; 2019. [ Google Scholar ]
• Galgani F, Hanke G, Maes T (2015) Global distribution, composition and abundance of marine litter. Marine anthropogenic litter. Springer, pp 29–56. 10.1007/978-3-319-16510-3_2
• Godet M, Durance P(2011) Strategic Foresight for Corporate and Regional Development. pp 84–90. Unesco. http://www.laprospective.fr/dyn/traductions/2dunod-unesco-strategic-foresight-ext-veng.pdf
• Godet M, Monti R, Meunier F, Roubelat F(2004) Scenarios and Strategies: A Toolbox for Scenario Planning. 3rd Issue. LIPSOR – Laboratory for Investigation in Prospective and Strategy. http://en.laprospective.fr/dyn/anglais/articles/bo-lips-en.pdf
• Godet M(2000) The Art of Scenarios and Strategic planning: Tools and Pitfalls. Technological Forecasting and Social Change 65, 3–22. https://doi.org/S0040-1625(99)00120-1
• Godet M (1994) From anticipation to action: A handbook of strategic prospective. Paris Unesco Publishing, pp 83–103
• INCOSE (2006) Systems engineering handbook: A guide for life cycle processes and activities, version 3 edition, C. Haskins (Editor), International Council on Systems Engineering. http://www.las.inpe.br/~perondi/21.06.2010/SEHandbookv3.pdf
• Jackson S, Ferris TLJ(2012) Resilience Principles for Engineered Systems. Systems Engineering · July 2013 Wiley Periodicals Inc. 10.1002/sys.21228
• Jambeck JR, Geyer R, Wilcox C, Siegler TR, Perryman M, Andrady A, Narayan R, Law KL. Plastic waste inputs from land into the ocean. Sciencemag org Science. 2015; 347 :768–770. doi: 10.1126/science.1260352. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kaza S, Yao L, Tata PB, Woerden FV(2018) What a Waste 2.0: A Global Snapshot of Solid Waste Management to 2050. Urban Development Series. Washington DC. World Bank. 10.1596/978-1-4648-1329-0
• KLHK (2021) Sistem informasi pengelolaan sampah nasional (SIPSN). Capaian kinerja pengelolaan sampah. Kementerian Lingkungan Hidup dan Kehutanan. https://sipsn.menlhk.go.id/sipsn
• KLHK (2017) Pemantauan Sampah Laut Indonesia. Direktorat Pengendalian Pencemaran dan Kerusakan Pesisir dan Laut, Direktorat Jenderal Pengendalian dan Kerusakan Lingkungan, Kementerian Lingkungan Hidup dan Kehutanan. https://ppkl.menlhk.go.id/website/filebox/274/180703160900REKAP%20SAMPAH%20LAUT%20INDONESIA%202017.pdf
• Kooiman J, Bavinck M, Jentoft S, Pullin R(2005) Fish for Life: Interactive Governance for Fisheries. MARE Publication Series 3. Amsterdam University Press. https://www.ssoar.info/ssoar/bitstream/handle/document/31640/ssoar-2005-kooiman_et_al - Fish_for_Life__Interactive.pdf?sequence = 1&isAllowed = y&lnkname = ssoar-2005-kooiman_et_al-Fish_for_Life__Interactive.pdf
• Lebreton LCM, Van Der Zwet J, Damsteeg JW, Slat B, Andrady A, Reisser J. River plastic emissions to the world’s oceans. Nat Commun Vol. 2017; 8 :15611. doi: 10.1038/ncomms15611. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Sahin O, Richards R, Sano M. Integrated Modelling Approach for Climate Change Adaptation: The Case of Surf Life Saving Australia, Griffith School of Engineering. Australia: Griffith University, Gold Coast; 2013. [ Google Scholar ]
• Saxena JP, Sushil, Vrats P(1990) Impact of Indirect Relationships in Classification of Variables-a Micmac Analysis for Energy Conservation Systems Research Vol 7. No 4. pp 245–253. International Federation for System Research. 10.1002/sres.3850070404
• Shuker IG, Cadman CA(2018) Indonesia marine debris hotspot rapid assessment: Synthesis report. Washington,. http://documents.worldbank.org/curated/en/983771527663689822/Indonesia-Marine-debris-hotspot-rapid-assessment-synthesis-report
• Tiwari RK. Identification of factors affecting reverse chain performance in relation to customer satisfaction using ISM Modelling & Micmac. Anal Uncertain Supply Chain Manage. 2013; 1 :237–252. doi: 10.5267/j.uscm.2013.08.005. [ CrossRef ] [ Google Scholar ]
• UNEP (2016) Marine Litter, Vital Graphics UNEP Programme and GRID-Arendal. Nairobi and Arendal. www.unep.org, www.grida.no
• UNEP (2017) Marine litter: socio-economic study United Nations Environment Programme, Nairobi. Kenya. https://wedocs.unep.org/bitstream/handle/20.500.11822/26014/Marinelitter_socioeco_study.pdf?sequence
• Veltmeyer J, Sahin O(2014) Modelling climate change adaptation using cross-impact analysis: an approach for integrating qualitative and quantitative data. Griffith university, Queensland Australia. https://scholarsarchive.byu.edu/iemssconference/2014/Stream-H/72
• Vince J, Hardesty BD. Governance Solutions to the Tragedy of the Commons That Marine Plastics Have Become. Front Mar Sci. 2018; 5 :214. doi: 10.3389/fmars.2018.00214. [ CrossRef ] [ Google Scholar ]
• Vince J, Hardesty BD. Plastic pollution challenges in marine and coastal environments: from local to global governance. Restoration Ecology. J Soc Ecol restorations. 2016 doi: 10.1111/rec.12388. [ CrossRef ] [ Google Scholar ]
• WWF (2019) Solving plastic pollution through accountability. Report. Dalberg Advisors. https://www.worldwildlife.org/publications/solving-plastic-pollution-through-accountability

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Case Study: Marine Plastic Debris and Solid Waste Management in Peru

The negative impact of plastic debris on marine ecosystems and species is a global challenge. While the causes vary by region, most scientists agree that poor solid waste management is a leading factor.

Click here to open the Spanish version of the Case Study

 Introduction

The negative impact of plastic debris on marine ecosystems and species is a global challenge. While the causes vary by region, most scientists agree that poor solid waste management is a leading factor. This is particularly true in the developing world, where infrastructure has not kept pace with economic growth. For the past several years, a range of public and private sector partners in Peru have worked to improve solid waste management—for human well-being and to reduce threats to marine ecosystems. Their work offers insight into effective strategies while also illuminating gaps in key data on the impact of plastic pollution on marine biodiversity. This case study includes a look at the challenges facing Peru, the strategies undertaken to date, and the types of additional data and interventions required to address this global issue at the local and national level.

The Global Challenge

Plastic debris is a persistent and ubiquitous global issue threatening marine life throughout the world’s oceans (Thevenon, Carroll and Sousa 2014; Jambeck, et al. 2015; Boucher and Friot 2017; The CADMUS Group 2018). Global plastic production has increased significantly, with more than 300 million metric tons of plastics currently produced annually, compared to 1.5 million metric tons in 1950 (Boucher and Friot 2017). As plastic consumption increases, so does solid waste and, ultimately, marine debris. Currently, plastic debris can be found in a wide range of sizes: from nanoplastics and microplastics, such as the ones used in synthetic textiles and tires (Ibid), to macroplastics, such as plastic bags.

A significant portion of marine plastic pollution is generated inland and transported to the coastal areas through rivers (Lebreton et al. 2017) and runoff (Boucher and Friot 2017). Industrial fisheries also contribute to marine plastic debris (Luna-Jorquera et al. 2019). On a global scale, the most significant polluting rivers are located in Asia (Lebreton, et al. 2019). Rivers in South America account for an estimated 4.8 percent of the river mass plastic input to the oceans (Ibid).

Most plastic debris remains near coastal areas for years, degrading ecosystems key to economic and human health. Over time, debris can be degraded and transported by ocean currents to open waters and gyres, where particles accumulate and create “garbage patches” (Lebreton, Egger, and Slat 2019; Thiel, et al. 2018). Plastics in the South Pacific Subtropical Gyre (SPSG) largely originate from debris in the coastal waters of the Humboldt Current, spanning across the coast of Chile and Peru (Thiel, et al. 2018). Marine protected areas located near the five oceanic gyres and garbage accumulation points are at risk of receiving large amounts of marine plastic debris, undermining efforts to protect local wildlife (Luna-Jorquera, et al. 2019).

Plastic debris has negative effects on marine wildlife, including entanglement, ingestion, the transport of invasive species, and toxic pollutants (Thevenon, Carroll, and Sousa 2014). Microplastics have been reported in a wide range of marine taxa, including amphipods living in six of the deepest marine ecosystems on Earth (Thiel et al., 2018; Jamieson, et al. 2019), pointing at the ubiquitous distribution of these particles. However, a nuanced understanding of the impact of plastic on the biology of specific marine species is still poorly understood. The risk of exposure to plastics and microplastics depends on the distribution and abundance of the plastics and the biology of the species (Thiel et al. 2018).

Until scientists collect more data on the impact of marine debris on species and ecosystems, public and private sector institutions are focusing on better solid waste management upstream to reduce the flow of plastic pollution. Of the 6,300 million metric tons of plastic waste produced globally as of 2015, 9 percent has been recycled, 12 percent has been incinerated, and about 79 percent has accumulated in landfills or in the natural environment (Geyer et al. 2017). At the current trend, 12 billion tons of plastic waste will accumulate in landfills and the natural environment by 2050 (Idem).

In many developing countries, the consumption of disposable goods has increased at a higher rate than the development of proper waste management practices and infrastructure (Jambeck, et al. 2015). Developing sustainable waste management systems requires several key strategies, including strengthening the capacity of public waste management authorities; closing the infrastructure gap; partnering with and building the capacity of the private sector and civil society organizations; and implementing adequate laws, regulations, and standards (The Cadmus Group 2018). Countries, including Peru, are increasingly taking bold measures to tackle plastic pollution. With over 3,000 km of coastline and home to some of the most polluted beaches in Latin America, Peru provides a model to better understand the relationship between marine plastic debris and solid waste management, and the types of interventions having a positive impact.

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The plastic pollution crisis

Plastics only began to be produced in large quantities following the second world war – but plastic pollution has since become one of the most serious threats humanity faces. By 2015, 60% of all plastic ever produced had become plastic waste, and in today’s world, plastic waste is ubiquitous – it’s in the air, in the soil, in freshwater, and in the sea.  

Much of the world’s plastic waste – from large items down to barely visible microplastic particles – ends up in the ocean, where it can persist for hundreds of years. Here it has negative effects on marine life of all kinds, and ultimately causes harm to humans too. Up to 12 million tonnes of plastic debris is entering the global ocean every year:  2  the UN calls it ‘a planetary crisis’.

Photo: ID 164267024 © Evgeniy Parilov Dreamstime.com

The highly populated, semi-enclosed Mediterranean basin is one of the global hotspots for marine plastic pollution. Urgent and wide-ranging action is required to radically reduce the amounts of plastic that reach the sea and bring the situation under control – but for this to happen, we need to build as full a picture as possible of what’s actually going on.

Photo: ID 144605122 © Jakub Gojda Dreamstime.com

 Where does ocean plastic come from? 

Overall, 80% of marine plastic debris comes from land, and 20% is produced by ocean-based sources such as fishing, shipping and aquaculture.  3  Much of it is comprised of industrial and domestic waste from metropolitan and urban areas with poorly managed collection and disposal systems. Rubbish finds its way into rivers and other waterways, sometimes through storm drains and sewage outfalls, and these take it all the way to the sea. It’s estimated that 94% of the plastic pollution that enters the Mediterranean comes in the form of macroplastics, but microplastic pollution is significant too. Land-based sources of microplastics include agricultural polyethylene sheets that fragment from weathering, biosolids and sewage sludge from wastewater treatment plants, and grey water from washing clothes made with synthetic fibres.  4  Sewage entering municipal treatment systems is high in microfibres from textiles, microplastics from personal care products, and degraded consumer products.

Between 80 and 90 percent of microplastics entering treatment systems remain in residual sewage sludge. This sludge is often used as fertilizer in agriculture, resulting in plastic being deposited on agricultural fields where it can remain for long periods of time – or be washed into the rivers and out to sea. Based on a recent study, microplastics can persist in soils for more than 100 years, due to low light and oxygen conditions 5 .    

The plastics life cycle

Plastic pollution is a design, production, consumption and disposal challenge that must be tackled across plastic’s entire life cycle. Many factors contribute to the issue, most obviously unsustainable consumption patterns, non-existent or ineffective legislation, inefficient waste management systems, and a lack of coordination between different sectors.

The impacts of plastic pollution on biodiversity and human health

Plastic pollution has adverse impacts on ocean ecosystems, the integrity of food supplies, and people’s livelihoods.

Entanglement and ingestion are the most common hazards for marine species, almost all of which – from microscopic zooplankton to the largest marine mammals – will come into contact with plastic waste during their lives. Entanglement in plastic ropes, lines and discarded fishing gear injures and kills all kinds of marine animals; while ingestion at every stage of the food chain can cause fatalities or have major impacts on physiological functions including nutrition, growth, behaviour and reproduction.  

 Once microplastics and nanoplastics are ingested by marine animals they become part of the food web, and can ultimately enter the human food chain.  

Confronting the issue: a harmonised methodology and a global agreement

Plastic leakage is a complex issue, involving multiple sources and actors, and addressing it requires stakeholders to join forces and intervene at various levels. Before this can happen, though, countries and cities face an initial knowledge gap: they need to establish the magnitude of the challenge they face, and gain an understanding of the processes involved.  Resolution No. 6 on marine plastic litter and micro-plastics  adopted at the  Fourth Session of the UN Environment Assembly (UNEA-4)  in 2019 highlighted the importance of a h armonised methodology to measure plastic flows and leakage along the value chain, and generate actionable data.

 Once these facts are established, countries need practical and legislative tools to address the root sources of the problem. With this in mind, the  Fifth UN Environment Assembly (UNEA-5)  created an expert group on marine litter and microplastics. The group is “reviewing the present situation and analysing the effectiveness of existing and potential response options related to marine plastic litter and microplastics”. It developed and signed “a new global agreement , to provide a legal framework of global response and to facilitate national responses especially for those countries with limited resources and capacities that could contain either legally binding and/or non-binding elements”.

The  Programme for the Assessment and Control of Marine Pollution in the Mediterranean (MEDPOL)  of the   United Nations Environment Programme (UNEP)   is responsible for the implementation of the Integrated Monitoring and Assessment Programme (IMAP) for the Pollution and Litter and Noise clusters.   MED POL supports the Contracting Parties in the formulation and implementation of pollution control and prevention policies as well as regulatory measures. MED POL also undertakes regular activities to promote capacity-building and provides technical assistance on monitoring and assessment, implementation and enforcement. Its purpose is to assist Mediterranean countries in the implementation of three major protocols of the  Barcelona Convention:

•  The Protocol for the Protection of the Mediterranean Sea against Pollution from Land-Based Sources 
•  The Protocol for the Prevention of Pollution in the Mediterranean Sea by Dumping from Ships and Aircraft 
•  The Protocol on the Prevention of Pollution of the Mediterranean Sea by Transboundary Movements of Hazardous Wastes and their Disposal

The Mediterranean: plastic pollution hotspot

The Mediterranean Sea is a global hotspot for plastic pollution, its semi-enclosed basin concentrating marine litter at levels comparable to those found in the five subtropical gyres  7  ,the most notorious being the ‘Great Garbage Patch’ of the North Pacific.

The need for knowledge: PlastiMed project

In order to improve knowledge of the origins, distribution and leakage of plastic waste in the Mediterranean, a quantitative study on the impact of microplastics in the Mediterranean ecosystem was conducted. The research was based on samples collected during two main expeditions,  ExpeditionMED  and  Tara Méditerranée 2014  . In the latter, 75,000 microplastic particles were collected and analysed, making it the largest study of this kind in the Mediterranean to date. Following the expeditions, a database of Mediterranean plastic polymer types, including their geographical distribution, was completed, and a modelling study of the circulation of plastic debris in the Mediterranean was developed.

 The recent IUCN report   Mare Plasticum :  The Mediterranean   provides information about the quantity of plastics leaking into the Mediterranean Sea every year, also highlighting the countries and cities with the highest plastic leakage rates. This map is a combination of both studies, merging information gathered through fieldwork and desk-based analysis.

Photo: john-jerome-ganzon-dreamstime.com

Photo: john-jerome-ganzon-dreamstime

Taking action

The  Beyond Plastic Med  (BeMed) initiative was launched in 2019 to develop and support a network of stakeholders committed to implementing concrete solutions for the prevention of plastic pollution in the Mediterranean. By raising awareness of the issue, bringing together companies and organisations who can contribute to the project’s aims, and spreading best practices in the field, BeMed is an important umbrella for much of the work going on in the Mediterranean today.

In 2019, IUCN-Med launched the   Plastic Waste-Free Islands Mediterranean   project, as part of its global   Close the Plastic Tap   programme. The initiative’s overarching goal is to drive the circular economy agenda forward and to reduce plastic waste generation and leakage from islands. The programme of work focuses on tackling plastic pollution at its source by engaging a wide range of stakeholders – including governments, industries and society – and on addressing plastic pollution knowledge gaps. 

Surfrider Europe has been advocating for enhanced environmental policies to tackle plastic pollution and raising awareness among citizens to change their behaviour.

Tara Foundation conducted a 2019 expedition along nine major European rivers to research the origins and flux of microplastic waste, using its scientific expertise to raise awareness and educate the general public, as well as mobilise political decision-makers at the highest level.

In 2017, Région Sud (Provence-Alpes-Côte d’Azur) established the Zero Plastic Waste Pledge to enable local authorities, companies and associations to commit to reducing plastic waste at sea and on land. Région Sud and the IUCN signed a   joint declaration   at the World Conservation Congress, reflecting strong engagement and the beginning of coordinated action against plastic pollution.

Co-developed by the United Nations Environment Programme (UNEP) and the IUCN, the   National Guidance on Plastic Pollution Hotspotting and Shaping Action   contributes to filling gaps in knowledge. It provides a methodological framework and practical tools applicable at national level. Beyond the quantification and qualification of plastic pollution, the guidance offers an effective interface between science-based assessments and policy-making. The guidance maps plastic leakage and its impacts across the value chain by collecting and analysing data on plastic production, consumption, waste management and disposal, and prioritises hotspots for action. It enables governments to collaborate with key stakeholders to identify and implement corresponding interventions and instruments in these hotspots, ensuring that action takes place in the areas that need it most. Once decision-makers are equipped with reliable knowledge through use of the guidance, they can set targets, agree and implement actions, and monitor progress.

• Geyer, R., Jambeck, J. R., & Law, K. L. (2017). Production, use, and fate of all plastics ever made.  Science advances ,  3 (7), e1700782.  DOI: 10.1126/sciadv.1700782 
• Boucher, J., & Friot, D. (2017).    Primary microplastics in the oceans: a global evaluation of sources    (Vol. 43). Gland, Switzerland: IUCN. 43pp.
• Mendenhall, E. (2018). Oceans of plastic: a research agenda to propel policy development. Marine Policy, 96 , 291-298.  DOI: 10.1016/j.marpol.2018.05.005 
• Horton, A. A., Walton, A., Spurgeon, D. J., Lahive, E., & Svendsen, C. (2017). Microplastics in freshwater and terrestrial environments: evaluating the current understanding to identify the knowledge gaps and future research priorities.  Science of the total environment ,  586 , 127-141.  DOI: 10.1016/j.scitotenv.2017.01.190 
• Azoulay, D., Villa, P., Arellano, Y., Gordon, M. F., Moon, D., Miller, K. A., & Thompson, K. (2019).    Plastic & health: the hidden costs of a plastic planet .  Geneva: CIEL;
• Peng, L., Fu, D., Qi, H., Lan, C. Q., Yu, H., & Ge, C. (2020). Micro-and nano-plastics in marine environment: Source, distribution and threats—A review.  Science of the Total Environment ,  69 8.  DOI: 10.1016/j.scitotenv.2019.134254 
• Cózar, A., Sanz-Martín, M., Martí, E., González-Gordillo, J. I., Ubeda, B., Gálvez, J. Á., ... & Duarte, C. M. (2015). Plastic accumulation in the Mediterranean Sea.  PloS one ,  10 (4).  DOI:10.1371/journal.pone.0121762 
• Kedzierski, M., Palazot, M., Soccalingame, L., Falcou-Préfol, M., Gorsky, G., Galgani, F., ... & Pedrotti, M. L. (2022). Chemical composition of microplastics floating on the surface of the Mediterranean Sea.  Marine pollution bulletin ,  174 , 113284.  DOI:10.1016/j.marpolbul.2021.113284 
• Pedrotti Maria Luiza, Lomard Fabien, Baudena Alberto, Galgani François, Kedzierski Mikaël, Elineau Amanda, Henry Maryvonne, Bruzeau Stéphane, Reverdin Gilles, Boss Emmanuel, & Gorsky Gabriel. (2021). Tara Mediterranean surface plastic quantitative dataset [Data set]. Zenodo.  DOI: 10.5281/zenodo.5538238  .
• Boucher, J., Billard, G., Simeone, E. and Sousa, J. (2020). The marine plastic footprint. Gland, Switzerland: IUCN. viii+69 pp.
• Boucher, J. & Bilard, G. (2020). The Mediterranean: Mare plasticum. Gland, Switzerland: IUCN. x+62 pp.

Acknowledgements

This web story has been edited by IUCN Med and its partners, with financial support from the   Prince Albert II of Monaco Foundation   .

Produced and designed by   Swim2Birds   &   IUCN Centre for Mediterranean Cooperation.

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THE EFFECTS OF INCENTIVIZING PLASTIC WASTE MANAGEMENT ON ENVIRONMENTAL SUSTAINABILITY: A CASE STUDY OF COCA-COLA COMPANY IN NAMAVE WAKISO DISTRICT NAME: OTIM IVAN

2020, Otim Ivan

Plastic waste management is increasingly becoming a global challenge that has affected social- economic and environmental realities with significant bearing on environmental sustainability in Wakiso district. The population patterns and rapid urbanization have driven production, distribution, and consumption of PET plastic packaged products and beverages like soda and water further causing plastic pollution on land and swamps surrounding Lake Victoria. This prompted the researcher to investigate the impact of incentivizing plastic waste management on environmental sustainability a case study of the Coca-Cola Company in Namave Wakiso district. The general objective examined the impact of incentivizing plastic waste management on environmental sustainability in the Wakiso district. The other objectives explored the practices of plastic waste management by Coca-Cola Company in Namanve Wakiso district, assess the implications of plastic waste management on environmental sustainability in the Wakiso district, and explore the possible practices of incentivizing plastic waste management by Coca-Cola Company, Wakiso district. The study took a case study research design adopting both qualitative and quantitative approaches (mixed method) to investigate the issues that revolved around plastic waste management. The qualitative research design helped to capture qualitative data, based on qualitative aspects not quantified. The other methods were interviews, observation, questionnaires, and desk reviews as data collection methods. The study found out that the practice of plastic management at production, distribution, and consumption level has contributed to an increase in PET plastic waste due to urbanization and population dynamics as driving factors. This has tremendously had an impact economically, socially, and environmentally The study summary findings indicated that the practice of plastic management is not managed with a clear plan of managing the wastes and plastic distribution and consumption predisposes factors to poor plastic waste management and yet they can be targeted for incentivized plastic waste recovery The plastic waste management practices are inclined toward commercialization practices and not focused on incentivizing approaches. This has made plastic waste management practice ineffective and no sustainable due to the limitation of the technical and financial resources. Therefore, the research recommended that sustainable waste management practice should integrate technology, policy, administrative and legal actions to address the challenge of plastic waste management through an incentivized mechanism. The focus of the incentivized approach of legal &policy framework for enforcement, establish aa a comprehensive database from production, distribution, and consumption to support plastic waste recovery, refocus plastic waste through an incentivize recovery approach and increase awareness on waste management practices for effecting the trademark “Please recycle.

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Studies of informal waste recovery have described and characterized the process without a conceptual framework for the explanation of the observed behavior of the different participants. This makes extrapolation and comparison of results difficult. This paper provides a conceptual framework for describing and explaining the behavior of participants in plastic waste recovery in Kano metropolis. Twenty-five copies of unstructured questionnaire were administered to each category of the participants involved who were selected by random sampling. The researcher&#39;s observation and direct participation in some of the activities of the participants also provided additional data for the study. Gidden&#39;s structuration theory was used to provide conceptualization to describe and explain the organization and interrelationship of those involved in plastic waste recovery in Kano metropolis. The study indicates that social action is never an individual egocentric pursuit, but it takes place ...

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A critical review and analysis of plastic waste management practices in Rwanda

• Review Article
• Published: 10 August 2024

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• Gratien Twagirayezu 1 , 2 ,
• Hongguang Cheng 1 ,
• Olivier Irumva 3 ,
• Jean Claude Nizeyimana 2 , 4 ,
• Ildephonse Nizeyimana 5 ,
• Philippe Bakunzibake 6 ,
• Abias Uwimana 7 &
• Christian Sekomo Birame 8  

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Plastic products are now essential commodities, yet their widespread disposal leads to environmental and human health effects, particularly in developing nations. Therefore, developing nations require comprehensive studies to assess the current state of plastic and plastic waste production to enhance plastic waste management practices. This review analyzes the import and export of plastic and the production of plastic waste in Rwanda, aiming to improve waste management practices. This review used open-access papers, reports, and websites dealing with plastic waste management. In this review, 58 articles from the Web of Science and 86 from other search engines were consulted to write this review. The findings revealed that the daily estimated plastic waste produced per person ranges between 0.012 and 0.056 kg. The estimated amount of plastic waste generated per person per year in Rwanda could be between 4.38 and 20.44 kg. Plastic waste accounts for between 1 and 8% of the total municipal solid waste produced per person per day in the country, which ranges from 219 to 255.5 kg. The average annual amount of imported plastics could reach 568.2881 tons, whereas the average quantity of exported plastics could reach 103.7414 tons. This shows that plastic management practices have not yet adopted technically advanced or improved practices, which should concern efforts to protect our environment. This study suggests approaches that can vastly improve plastic waste management and potentially open massive opportunities for the people of Rwanda.

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• Environmental Chemistry

Adarsh UK, Kartha VB, Santhosh C, Unnikrishnan VK (2022) Spectroscopy: a promising tool for plastic waste management. TrAC Trends Anal Chem 149:116534. https://doi.org/10.1016/j.trac.2022.116534

Addor JA, Wiah EN, Alao FI (2022) Mathematical model for the cyclical dynamics of plastic waste management: a two-state closed model. J Mater Sci Res 9:15–36. https://journaljmsrr.com/index.php/JMSRR/article/view/193

Afroz R, Rahman A, Masud MM, Akhtar R (2017) The knowledge, awareness, attitude and motivational analysis of plastic waste and household perspective in Malaysia. Environ Sci Pollut Res 24:2304–2315. https://doi.org/10.1007/s11356-016-7942-0

Article   Google Scholar  

Al-Maaded M, Madi NK, Kahraman R et al (2012) An overview of solid waste management and plastic recycling in Qatar. J Polym Environ 20:186–194. https://doi.org/10.1007/s10924-011-0332-2

Al-Salem SM (2019) Energy production from Plastic Solid Waste (PSW). In: Plastics to energy. Elsevier, pp 45–64. https://doi.org/10.1016/B978-0-12-813140-4.00003-0

Anani OA, Adetunji CO (2021) Bioremediation of polythene and plastics using beneficial microorganisms. Microb Rejuvenation Polluted Environ 3:281–302.  https://doi.org/10.1007/978-981-15-7459-7_13

Anastasopoulou A, Fortibuoni T (2019) Impact of plastic pollution on marine life in the Mediterranean Sea. In: Plastics in the aquatic environment-part I: current status and challenges, vol 1, pp 135–196. https://doi.org/10.1007/698_2019_421

Antelava A, Damilos S, Hafeez S et al (2019) Plastic Solid Waste (PSW) in the context of Life Cycle Assessment (LCA) and sustainable management. Environ Manag 64:230–244.  https://doi.org/10.1007/s00267-019-01178-3

Bagai A, Henam SD (2021) Beating plastic pollution: UNEP’s priorities and partnership in India. Environ Policy Law 51:265–269. https://doi.org/10.3233/EPL-201069

Bates A (2019) Transforming plastic: from pollution to evolution. GroundSwell Books.  https://www.sanmin.com.tw/product/index/007251442 . Accessed 21 Aug 2023

Baumgarten LG, Freitas AA, Santana ER et al (2023) Graphene and gold nanoparticle-based bionanocomposite for the voltammetric determination of bisphenol A in (micro) plastics. Chemosphere 334:139016.  https://doi.org/10.1016/j.chemosphere.2023.139016

Bening CR, Pruess JT, Blum NU (2021) Towards a circular plastics economy: interacting barriers and contested solutions for flexible packaging recycling. J Clean Prod 302:126966.  https://doi.org/10.1016/j.jclepro.2021.126966

Bishop G, Styles D, Lens PNL (2021) Environmental performance comparison of bioplastics and petrochemical plastics: a review of Life Cycle Assessment (LCA) methodological decisions. Resour Conserv Recycl 168:105451. https://doi.org/10.1016/j.resconrec.2021.105451

Cao X, Liang Y, Jiang J et al (2023) Organic additives in agricultural plastics and their impacts on soil ecosystems: compared with conventional and biodegradable plastics. TrAC Trends Anal Chem. 166:117212. https://doi.org/10.1016/j.trac.2023.117212

Celis-Hernández O, Ávila E, Ward RD et al (2021) Microplastic distribution in urban vs pristine mangroves: using marine sponges as bioindicators of environmental pollution. Environ Pollut 284:117391. https://doi.org/10.1016/j.envpol.2021.117391

Chacko S (2021) Plastic pollution in aquatic systems may triple by 2040: UNEP. https://www.downtoearth.org.in/environment/plastic-pollution-in-aquatic-systems-may-triple-by-2040-unep-79822 . Accessed 12 Aug 2023

Chauhan V, Kärki T, Varis J (2022) Review of natural fiber-reinforced engineering plastic composites, their applications in the transportation sector and processing techniques. J Thermoplast Compos Mater 35:1169–1209. https://doi.org/10.1177/0892705719889095

Article   CAS   Google Scholar  

Chen Q, Reisser J, Cunsolo S et al (2018) Pollutants in plastics within the North Pacific subtropical gyre. Environ Sci Technol 52:446–456. https://doi.org/10.1021/acs.est.7b04682

Chen HL, Nath TK, Chong S et al (2021) The plastic waste problem in Malaysia: management, recycling and disposal of local and global plastic waste. SN Appl Sci 3:1–15. https://doi.org/10.1007/s42452-021-04234-y

Da Costa JP, Avellan A, Mouneyrac C et al (2023) Plastic additives and microplastics as emerging contaminants: mechanisms and analytical assessment. TrAC Trends Anal Chem 158:116898. https://doi.org/10.1016/j.trac.2022.116898

Davidson MG, Furlong RA, McManus MC (2021) Developments in the life cycle assessment of chemical recycling of plastic waste–a review. J Clean Prod 293:126163. https://doi.org/10.1016/j.jclepro.2021.126163

De Kock L, Sadan Z, Arp R, Upadhyaya P (2020) A circular economy response to plastic pollution: current policy landscape and consumer perception. S Afr J Sci 116:1–2.  https://doi.org/10.17159/sajs.2020/8097

der Vegt AK (2002) From polymers to plastics. Dup Blue Print, Delft Univ Press Netherlands. https://lib.ugent.be/en/catalog/rug01:001268065 . Accessed 27 Sept 2023

Domenech T, Bleischwitz R, Doranova A et al (2019) Mapping industrial symbiosis development in Europe_typologies of networks, characteristics, performance and contribution to the Circular Economy. Resour Conserv Recycl 141:76–98. https://doi.org/10.1016/j.resconrec.2018.09.016

Drzyzga O, Prieto A (2019) Plastic waste management, a matter for the ‘community.’ Microb Biotechnol 12:66.  https://doi.org/10.1111/1751-7915.13328

Du L, Jin X, Qian G et al (2022) Lignin-based vitrimer for circulation in plastics, coatings, and adhesives with tough mechanical properties, catalyst-free and good chemical solvent resistance. Ind Crops Prod 187:115439.  https://doi.org/10.1016/j.indcrop.2022.115439

Encyclopedia (2023) Geography of Rwanda. https://en.wikipedia.org/wiki/Geography_of_Rwanda . Accessed 02 Jul 2024

EuRIC (2020) Recycling: bridging circular economy & climate policy. https://euric-aisbl.eu/images/Positionpapers . Accessed 20 Jun 2024

European Commission (2018) Plastics in a circular economy. https://research-andinnovation.ec.europa.eu/research-area/environment/circular-economy/plastics-circular-economy_en . Accessed 18 Jun 2024

Faraca G, Martinez-sanchez V, Astrup TF (2019) Resources, conservation & recycling environmental life cycle cost assessment : recycling of hard plastic waste collected at Danish recycling centres. Resour Conserv Recycl 143:299–309. https://doi.org/10.1016/j.resconrec.2019.01.014

Flaws J, Damdimopoulou P, Patisaul HB et al (2020) Plastics, EDCs and health. Endocr Soc, Washington https://www.endocrine.org/-/media/endocrine/files/topics/edc_guide_2020_v1_6bhqen.pdf . Accessed 24 Jun 2024

Fobil JN, Hogarh JN (2006) The dilemmas of plastic wastes in a developing economy: proposals for a sustainable management approach for Ghana. West African J Appl Ecol 10:1–8. https://doi.org/10.4314/wajae.v10i1.45716

Gall SC, Thompson RC (2015) The impact of debris on marine life. Mar Pollut Bull 92:170–179. https://doi.org/10.1016/j.marpolbul.2014.12.041

Geyer R, Jambeck JR, Law KL (2017) Production, use, and fate of all plastics ever made. Sci Adv 3:e1700782.  https://doi.org/10.1126/sciadv.1700782

Geyer R (2020a) A brief history of plastics. Mare Plast Plast Sea Combat Plast Pollut Through Sci Art 31–47. https://doi.org/10.1007/978-3-030-38945-1_2

Geyer R (2020b) Production, use, and fate of synthetic polymers. In: Plastic waste and recycling. Elsevier, 13–32. https://doi.org/10.1016/B978-0-12-817880-5.00002-5

Ghisellini P, Cialani C, Ulgiati S (2016) A review on circular economy: the expected transition to a balanced interplay of environmental and economic systems. J Clean Prod 114:11–32. https://doi.org/10.1016/j.jclepro.2015.09.007

Giuliani A, Zuccarini M, Cichelli A et al (2020) Critical review on the presence of phthalates in food and evidence of their biological impact. Int J Environ Res Public Health 17:5655. https://doi.org/10.3390/ijerph17165655

Global Green Growth Institute (2019) Solid waste management in secondary cities of Rwanda - Muhanga & Huye Situation assessment and potential intervention areas.  https://gggi.org/wp-content/uploads/2019/08 . Accessed 18 Jun 2024

Google Scholar  

Gourmelon G (2015) Global plastic production rises, recycling lags. Vital Signs 22:91–95.  http://www.plastic-resource-center.com . Accessed 19 Jun 2024

Government of Canada (2018) Ocean Plastics Charter. https://www.canada.ca/en/environment-climate-change/services/managing-reducing-waste/international-commitments/ocean-plastics-charter.html . Accessed 20 Jun 2024

Halog A, Anieke S (2021) A review of circular economy studies in developed countries and its potential adoption in developing countries. Circ Econ Sustain 1:209–230. https://doi.org/10.1007/s43615-021-00017-0

Hammer J, Kraak MHS, Parsons JR (2012) Plastics in the marine environment: the dark side of a modern gift. Rev Environ Contam Toxicol. 1–44. https://doi.org/10.1007/978-1-4614-3414-6_1

Hermabessiere L, Dehaut A, Paul-Pont I et al (2017) Occurrence and effects of plastic additives on marine environments and organisms: a review. Chemosphere 182:781–793. https://doi.org/10.1016/j.chemosphere.2017.05.096

Hikmath JT, Arachchige USPR (2020) Future strategies in plastic waste management in Sri Lanka. J Res Technol Eng 62–71. https://www.jrte.org/2020/01/25/future-strategies-in-plastic-waste-management-in-sri-lanka . Accessed 25 Sept 2023

Hoellein TJ, Rochman CM (2021) The “plastic cycle”: a watershed-scale model of plastic pools and fluxes. Front Ecol Environ 19:176–183. https://doi.org/10.1002/fee.2294

Huang Q, Chen G, Wang Y et al (2020) Modelling the global impact of China’s ban on plastic waste imports. Resour Conserv Recycl 154:104607.  https://doi.org/10.1016/j.resconrec.2019.104607

Hurley R, Horton A, Lusher A, Nizzetto L (2020) Plastic waste in the terrestrial environment. Plastic waste and recycling, pp 163–193. https://doi.org/10.1016/B978-0-12-817880-5.00007-4

Iacovidou E, Geyer R, Kalow J et al (2021) Toward a circular economy for plastics. One Earth 4:591–594. https://doi.org/10.1016/j.oneear.2021.04.023

Iraguha F, Handono Ramelan A, Setyono P (2022) Assessment of current solid waste management practices, community perceptions, and contributions in the City of Kigali, Rwanda. IOP Conf Ser Earth Environ Sci 1016. https://doi.org/10.1088/1755-1315/1016/1/012056

Iyamu HO, Anda M, Ho G (2020) A review of municipal solid waste management in the BRIC and high-income countries: a thematic framework for low-income countries. Habitat Int 95:102097.  https://doi.org/10.1016/j.habitatint.2019.102097

Jambeck J, Hardesty BD, Brooks AL et al (2018) Challenges and emerging solutions to the land-based plastic waste issue in Africa. Mar Policy 96:256–263. https://doi.org/10.1016/j.marpol.2017.10.041

Jeswani H, Krüger C, Russ M et al (2021) Life cycle environmental impacts of chemical recycling via pyrolysis of mixed plastic waste in comparison with mechanical recycling and energy recovery. Sci Total Environ 769:144483.  https://doi.org/10.1016/j.scitotenv.2020.144483

Joshi S (1999) Product environmental life-cycle assessment using input-output techniques. J Ind Ecol 3:95–120. https://doi.org/10.1162/108819899569449

Junaid M, Siddiqui JA, Liu S et al (2023) Adverse multigeneration combined impacts of micro (nano) plastics and emerging pollutants in the aquatic environment. Sci Total Environ 882:163679.  https://doi.org/10.1016/j.scitotenv.2023.163679

Kabera T, Wilson DC, Nishimwe H (2019) Benchmarking performance of solid waste management and recycling systems in East Africa: comparing Kigali Rwanda with other major cities. Waste Manag Res 37:58–72. https://doi.org/10.1177/0734242X18819752

Karasik R, Bering J, Griffin M et al (2022) Annual trends in plastic policy: a brief. NI PB 1–22. https://nicholasinstitute.duke.edu . Accessed 25 Jun 2024

Kaza S, Yao L, Bhada-Tata P, Van Woerden F (2018) What a waste 2.0: a global snapshot of solid waste management to 2050. World Bank Publications.  https://doi.org/10.1596/978-1-4648-1329-0

Kehinde O, Ramonu OJ, Babaremu KO, Justin LD (2020) Plastic wastes: environmental hazard and instrument for wealth creation in Nigeria. Heliyon 6(e05131):1–7. https://doi.org/10.1016/j.heliyon.2020.e05131

Khan R, Kumar S, Srivastava AK et al (2021) Machine learning and IoT-based waste management model. Comput Intell Neurosci 2021:1–11. https://doi.org/10.1155/2021/5942574

Khan AH, López-Maldonado EA, Khan NA et al (2022) Current solid waste management strategies and energy recovery in developing countries-state of art review. Chemosphere 291:133088. https://doi.org/10.1016/j.chemosphere.2021.133088

Kibria MG, Masuk NI, Safayet R et al (2023) Plastic waste: challenges and opportunities to mitigate pollution and effective management. Int J Environ Res 17:20. https://doi.org/10.1007/s41742-023-00507-z

Kumar R, Verma A, Shome A et al (2021) Impacts of plastic pollution on ecosystem services, sustainable development goals, and need to focus on circular economy and policy interventions. Sustainability 13:9963. https://doi.org/10.3390/su13179963

Kumar V, Singh E, Singh S et al (2023) Micro-and nano-plastics (MNPs) as emerging pollutant in ground water: environmental impact, potential risks, limitations and way forward towards sustainable management. Chem Eng J 459:141568.  https://doi.org/10.1016/j.cej.2023.141568

Kurniawan TA, Maiurova A, Kustikova M et al (2022) Accelerating sustainability transition in St. Petersburg (Russia) through digitalization-based circular economy in waste recycling industry: a strategy to promote carbon neutrality in era of Industry 4.0. J Clean Prod 363:132452.  https://doi.org/10.1016/j.jclepro.2022.132452

Lambert S, Wagner M (2017) Environmental performance of bio-based and biodegradable plastics: the road ahead. Chem Soc Rev 46:6855–6871. https://doi.org/10.1039/c7cs00149e

Leal Filho W, Saari U, Fedoruk M et al (2019) An overview of the problems posed by plastic products and the role of extended producer responsibility in Europe. J Clean Prod 214:550–558. https://doi.org/10.1016/j.jclepro.2018.12.256

Lebreton L, Andrady A (2019) Future scenarios of global plastic waste generation and disposal. Palgrave Commun 5:1–11. https://doi.org/10.1057/s41599-018-0212-7

Lee M-Y, Cho N-H, Lee S-J et al (2021) Application of material flow analysis for plastic waste management in the Republic of Korea. J Environ Manage 299:113625. https://doi.org/10.1016/j.jenvman.2021.113625

Lehel J, Murphy S (2021) Microplastics in the food chain: food safety and environmental aspects. Rev Environ Contam Toxicol 259:1–49. https://doi.org/10.1007/398_2021_77

Li WC, Tse HF, Fok L (2016) Plastic waste in the marine environment: a review of sources, occurrence and effects. Sci Total Environ 566:333–349. https://doi.org/10.1016/j.scitotenv.2016.05.084

Maheswaran B, Al-Ansari M, Al-Humaid L et al (2023) In vivo degradation of polyethylene terephthalate using microbial isolates from plastic polluted environment. Chemosphere 310:136757.  https://doi.org/10.1016/j.chemosphere.2022.136757

Martinez Sanz V, Morales Serrano A, Schlummer M (2022) A mini-review of the physical recycling methods for plastic parts in end-of-life vehicles. Waste Manage Res 40:1757–1765. https://doi.org/10.1177/0734242X221094917

McGlade J, Samy Fahim I, Green D et al (2021) From pollution to solution: a global assessment of marine litter and plastic pollution. https://www.unep.org/resources/pollution-solution-global-assessment-marine-litter-and-plastic-pollution . Accessed 26 Jun 2024

MIA (2023) Rwanda-economic growth through mining. https://idrc-crdi.ca/sites/default/files/openebooks/450-5/ . Accessed 20 Sept 2023

Millet H, Vangheluwe P, Block C et al (2018) The nature of plastics and their societal usage. Plast Environ 2018:1–20. https://doi.org/10.1039/9781788013314-00001

MINICOM (2011) Rwanda national export strategy (NES). https://rwandatrade.rw/media/2011%20MINICOM%20National%20Export%20Strategy%20(NES).pdf . Accessed 28 Aug 2023

Mülhaupt R (2013) Green polymer chemistry and bio-based plastics: dreams and reality. Macromol Chem Phys 214:159–174. https://doi.org/10.1002/macp.201200439

Mulvaney D, Richards RM, Bazilian MD et al (2021) Progress towards a circular economy in materials to decarbonize electricity and mobility. Renew Sustain Energy Rev 137:110604.  https://doi.org/10.1016/j.rser.2020.110604

Muzeza C, Ngole-Jeme V, Msagati TAM (2023) The mechanisms of plastic food-packaging monomers’ migration into food matrix and the implications on human health. Foods 12:3364.  https://doi.org/10.3390/foods12183364

Natesan U, Vaikunth R, Kumar P et al (2021) Spatial distribution of microplastic concentration around landfill sites and its potential risk on groundwater. Chemosphere 277:130263.  https://doi.org/10.1016/j.chemosphere.2021.130263

NISR (2020) National Institute of Statistics of Rwanda: Gross Domestic Product First Quarter 2020. https://www.statistics.gov.rw/publication/gdp-national-accounts-first-quarter-2020

Nikuze MJ, Munderere E, Uliho A et al (2021) Quantification of solid waste destined in Kigali City Nduba dumpsite. Oalib 08:1–15. https://doi.org/10.4236/oalib.1106627

Ocean conservancy (2023) Fighting for trash free seas. https://oceanconservancy.org/trash-free-seas/ . Accessed 08 Oct 2023

OEC (2023) Economic complexity.  https://oec.world/en/profile/country/rwa . Accessed 06 Oct 2023

Ormsby MJ, White HL, Metcalf R et al (2024) Enduring pathogenicity of African strains of Salmonella on plastics and glass in simulated peri-urban environmental waste piles. J Hazard Mater 461:132439.  https://doi.org/10.1016/j.jhazmat.2023.132439

Page MJ, McKenzie JE, Bossuyt PM et al (2021) The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Int J Surg 88. https://doi.org/10.1016/j.ijsu.2021.105906

Pathak DR, Mainali B, Abuel-Naga H et al (2020) Quantification and characterization of the municipal solid waste for sustainable waste management in newly formed municipalities of Nepal. Waste Manage Res 38:1007–1018. https://doi.org/10.1177/0734242X20922588

Peiris MTOV, Dayarathne GLN (2023) Application of life cycle framework for municipal solid waste management: a circular economy perspective from developing countries. Circ Econ Sustain 3:899–918. https://doi.org/10.1007/s43615-022-00200-x

Phadke G, Rawtani D (2022) Impact of waste generated due to COVID-19. In: COVID-19 in the Environment. Elsevier, pp 251–276. https://doi.org/10.1016/B978-0-323-90272-4.00005-1

Phuong NN, Zalouk-Vergnoux A, Poirier L et al (2016) Is there any consistency between the microplastics found in the field and those used in laboratory experiments? Environ Pollut 211:111–123. https://doi.org/10.1016/j.envpol.2015.12.035

Plastic oceans (2018) Rwanda plastic bag ban. https://plasticoceans.org/rwanda-plastic-bag-ban/ . Accessed 02 Oct 2023

Powers H, Renner K, Prowse V (2024) Plastic pollution and environmental education through artwork. Cambridge Prism Plast 2. https://doi.org/10.1017/plc.2024.7

Prisandani UY, Amanda AL (2019) The importance of regulating plastic marine pollution for the protection of Indonesian marine environment. Yuridika 35:171.  https://doi.org/10.20473/ydk.v35i1.10962

Rajashekar A, Bowers A, Sebarenzi GA (2019) Assessing waste management services in Kigali. Int Growth Cent 73. https://www.theigc.org/sites/default/files/2019/11/Rajashekar-et-al-2019-paper.pdf . Accessed 19 Sept 2023

RDB (2020) Rwanda development board: manufacturing sector. https://rdb.rw/investment-opportunities/manufacturing/ . Accessed 27 Sept 2023

Reddy MS, Reddy PS, Subbaiah GV, Subbaiah HV (2014) Effect of plastic pollution on environment. J Chem Pharm Sci 14:28–29. https://www.naturefund.de . Accessed 19 Sept 2023

REMA (2021) State of environment and outlook report. Rwanda Environ Manag Auth 88. https://www.rema.gov.rw . Accessed 06 Oct 2023

Ren Z, Gui X, Xu X et al (2021) Microplastics in the soil-groundwater environment: aging, migration, and co-transport of contaminants–a critical review. J Hazard Mater 419:126455.  https://doi.org/10.1016/j.jhazmat.2021.126455

Rillig MC, Kim SW, Kim T-Y, Waldman WR (2021) The global plastic toxicity debt. Environ Sci Technol 55:2717–2719.  https://doi.org/10.1021/acs.est.0c07781

Ross S, Evans D (2003) The environmental effect of reusing and recycling a plastic-based packaging system. J Clean Prod 11:561–571. https://doi.org/10.1016/S0959-6526(02)00089-6

Rothman R, Ryan AJ (2023) The history and future of plastics. In: Plastic pollution in the global ocean, pp 21–46. https://doi.org/10.1142/9789811259111-0002

Roy P, Mohanty AK, Wagner A et al (2021) Impacts of COVID-19 outbreak on the municipal solid waste management: now and beyond the pandemic. ACS Environ Au 1:32–45. https://doi.org/10.1021/acsenvironau.1c00005

Ruiz A (2023) 25 plastic waste statistics that will shock you. https://theroundup.org/plastic-waste-statistics/ . Accessed 10 Oct 2023

Santillo D, Miller K, Johnston P (2017) Microplastics as contaminants in commercially important seafood species. Integr Environ Assess Manag 13:516–521. https://doi.org/10.1002/ieam.1909

Sarwar F, Ali S, Bhatti SH, urRehman S (2021) Legal approaches to reduce plastic marine pollution: challenges and global governance. Ann Soc Sci Perspect 2:15–20.  https://doi.org/10.52700/assap.v2i1.32

Shen M, Huang W, Chen M et al (2020a) (Micro) plastic crisis: un-ignorable contribution to global greenhouse gas emissions and climate change. J Clean Prod 254:120138.  https://doi.org/10.1016/j.jclepro.2020.120138

Shen M, Song B, Zeng G et al (2020b) Are biodegradable plastics a promising solution to solve the global plastic pollution? Environ Pollut 263:114469.  https://doi.org/10.1016/j.envpol.2020.114469

Shruti VC, Pérez-Guevara F, Elizalde- I, Martínez K-MG (2020) First study of its kind on the microplastic contamination of soft drinks, cold tea and energy drinks-Future research and environmental considerations. Sci Total Environ 726:138580.  https://doi.org/10.1016/j.scitotenv.2020.138580

Silva ALP, Prata JC, Walker TR et al (2020) Rethinking and optimising plastic waste management under COVID-19 pandemic: policy solutions based on redesign and reduction of single-use plastics and personal protective equipment. Sci Total Environ 742:140565.  https://doi.org/10.1016/j.scitotenv.2020.140565

Simon N, Raubenheimer K, Urho N et al (2021) A binding global agreement to address the life cycle of plastics. Science 80(373):43–47. https://doi.org/10.1126/science.abi9010

Smith RL, Takkellapati S, Riegerix RC (2022) Recycling of plastics in the United States: plastic material flows and polyethylene terephthalate (PET) recycling processes. ACS Sustain Chem Eng 10:2084–2096. https://doi.org/10.1021/acssuschemeng.1c06845

Sri Sasi Jyothsna T, Chakradhar B (2020) Current scenario of plastic waste management in India: way forward in turning vision to reality. Urban Min Sustain waste Manag 203–218. https://doi.org/10.1007/978-981-15-0532-4_21

Statista (2023) Annual production of plastics worldwide from 1950 to 2021. https://www.statista.com/statistics/282732/global-production-of-plastics-since-1950/ . Accessed 18 Sept 2023

Statista (2024) Rwanda: Gross domestic product (GDP) in current prices from 1989 to 2029. https://www.statista.com/statistics/452123/gross-domestic-product-gdp-in-rwanda/ . Accessed 18 Jun 2024

Stöfen-O A, Naji A, Brooks AL et al (2022) Marine plastic debris in the Arabian/Persian Gulf: challenges, opportunities and recommendations from a transdisciplinary perspective. Mar Policy 136:104909.  https://doi.org/10.1016/j.marpol.2021.104909

Sun Y, Liu S, Wang P et al (2022) China’s roadmap to plastic waste management and associated economic costs. J Environ Manage 309:114686. https://doi.org/10.1016/j.jenvman.2022.114686

Talukdar A, Bhattacharya S, Bandyopadhyay A, Dey A (2023) Microplastic pollution in the Himalayas: occurrence, distribution, accumulation and environmental impacts. Sci Total Environ 874:162495.  https://doi.org/10.1016/j.scitotenv.2023.162495

Tan J, Tan FJ, Ramakrishna S (2022) Transitioning to a circular economy: a systematic review of its drivers and barriers. Sustainability 14:1757. https://doi.org/10.3390/su14031757

Tian W, Song P, Zhang H et al (2022) Microplastic materials in the environment: problem and strategical solutions. Prog Mater Sci 132:101035. https://doi.org/10.1016/j.pmatsci.2022.101035

Trust Magazine (2023) Confronting ocean plastic pollution. https://www.pewtrusts.org/en/trust/archive/fall-2020/confronting-ocean-plastic-pollution . Accessed 20 Jun 2024

Tulebayeva N, Yergobek D, Pestunova G et al (2020) Green economy: waste management and recycling methods. In: E3S web of conferences, vol 159, p 1012. https://doi.org/10.1051/e3sconf/202015901012

Twagirayezu G, Irumva O, Huang K et al (2022) Environmental effects of electrical and electronic waste on water and soil: a review. Polish J Environ Stud. 31:2507–2525.  https://doi.org/10.15244/pjoes/144194

Twagirayezu G, Huang K, Xia H (2023a) Effects of bio-contaminants in organic waste products on the soil environment. In: Fate of biological contaminants during recycling of organic wastes, vol 1. Elsevier, pp 187–212. https://doi.org/10.1016/B978-0-323-95998-8.00013-3

Twagirayezu G, Uwimana A, Kui H et al (2023b) Towards a sustainable and green approach of electrical and electronic waste management in Rwanda: a critical review. Environ Sci Pollut Res 30:77959–77980. https://doi.org/10.1007/s11356-023-27910-5

Twagirayezu G, Huang K, Cheng H et al (2024) Electrical and electronic waste: an emerging global contaminant. In: Occurrence and behavior of emerging contaminants in organic wastes and their control strategies, vol 1, pp 53–70. https://doi.org/10.1016/B978-0-443-13585-9.00008-2

UNEP (2021) From pollution to solution: a global assessment of marine litter and plastic pollution. Grid Arendal.  https://www.grida.no/resources/15043 . Accessed 20 Sept 2023

UNEP (2018a) Africa waste management outlook. UN Environment Programme, Nairobi. https://www.unep.org/ietc/resources/publication/africa-waste-management-outlook . Accessed 10 Oct 2023

UNEP (2018b) Single use plastics: a roadmap for sustainability. https://www.unep.org/resources/report/single-use-plastics-roadmap-sustainability . Accessed 26 Sept 2023

Vanapalli KR, Sharma HB, Ranjan VP et al (2021) Challenges and strategies for effective plastic waste management during and post COVID-19 pandemic. Sci Total Environ 750:141514.  https://doi.org/10.1016/j.scitotenv.2020.141514

Velis CA, Cook E (2021) Mismanagement of plastic waste through open burning with emphasis on the global south: a systematic review of risks to occupational and public health. Environ Sci Technol 55:7186–7207. https://doi.org/10.1021/acs.est.0c08536

Verma R, Vinoda KS, Papireddy M, Gowda ANS (2016) Toxic pollutants from plastic waste-a review. Procedia Environ Sci 35:701–708. https://doi.org/10.1016/j.proenv.2016.07.069

Villanueva A, Eder P (2014) End-of-waste criteria for waste plastic for conversion. Inst Prospect Technol Stud. https://doi.org/10.2791/13033

Virdin J, Karasik R, Vegh T et al (2020) 20 years of government responses to the global plastic pollution problem: the plastics policy inventory. https://nicholasinstitute.duke.edu/sites/default/files/publications . Accessed 20 Sept 2023

Wang Y, Zhu Y, Lv W et al (2023) Tough while recyclable plastics enabled by monothiodilactone monomers. J Am Chem Soc 145:1877–1885. https://doi.org/10.1021/jacs.2c11502

Wiah EN, Addor JA, Alao FI (2022) Transitional probabilities for plastic waste management and implication on sustainability. Sustain Environ 8:1–16. https://doi.org/10.1080/27658511.2022.2118654

Wilson DC, Velis CA (2015) Waste management–still a global challenge in the 21st century: an evidence-based call for action. Waste Manage Res. 33:1049–1051.  https://doi.org/10.1177/0734242X15616055

Wojnowska-Baryła I, Bernat K, Zaborowska M (2022) Plastic waste degradation in landfill conditions: the problem with microplastics, and their direct and indirect environmental effects. Int J Environ Res Public Health 19:13223.  https://doi.org/10.3390/ijerph192013223

Wordometer (2024) Rwanda Population (LIVE). https://www.worldometers.info/world-population/rwanda-population . Accessed 21 Jun 2024

World Bank (2022) Tackling plastic pollution: toward experience-based policy guidance. https://documents.worldbank.org/en . Accessed 28 Sept 2023

World Population Review (2024) Kigali Population 2023. https://worldpopulationreview.com/world-cities/kigali-population . Accessed 28 Jun 2024

Worldometer (2024) Rwanda Population (Live). https://www.worldometers.info/world-population/rwanda-population/ . Accessed 27 Jun 2024

Wu H-H (2022) A study on transnational regulatory governance for marine plastic debris: trends, challenges, and prospect. Mar Policy 136:103988.  https://doi.org/10.1016/j.marpol.2020.103988

Zheng J, Tian L, Bayen S (2023) Chemical contaminants in canned food and can-packaged food: a review. Crit Rev Food Sci Nutr 63:2687–2718. https://doi.org/10.1111/raq.12496

Zhou A, Zhang Y, Xie S et al (2021) Microplastics and their potential effects on the aquaculture systems: a critical review. Rev Aquac 13:719–733

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Acknowledgements

The authors deeply acknowledge the National Key Research and Development Program of China, the “Light of West China” Program, and the Opening Fund of the State Key Laboratory of Environmental Geochemistry for funding. Gratien Twagirayezu would like to acknowledge the ANSO Scholarship for Young Talents in China.

This research was financed by the National Key Research and Development Program of China (2018YFC1802601), The “Light of West China” Program, Opening Fund of the State Key Laboratory of Environmental Geochemistry (SKLEG 2022216).

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The research concept and methodology were developed through collaboration among all authors. Gratien Twagirayezu, Hongguang Cheng, Olivier Irumva, and Jean Claude Nizeyimana conducted the data collection and analysis. After Gratien Twagirayezu wrote the work, it was reviewed by Ildephonse Nizeyimana, Bakunzibake Philippe, Abias Uwimana, and Christian Sekomo Birame. All authors have reviewed and approved the final manuscript.

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Twagirayezu, G., Cheng, H., Irumva, O. et al. A critical review and analysis of plastic waste management practices in Rwanda. Environ Sci Pollut Res (2024). https://doi.org/10.1007/s11356-024-34572-4

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Application of machine learning in plastic waste detection and classification: a systematic review.

1. Introduction

2. materials and methods, 2.1. search strategy, 2.2. systematic search, 3. results and discussion, 3.1. studies developed without using the considered ml models, 3.2. studies based on the considered ml models, 3.3. performance analysis, 4. conclusions, 5. challenges and future research directions, author contributions, data availability statement, conflicts of interest.

• Environment Programme. We’re Gobbling up the Earth’s Resources at an Unsustainable Rate. Available online: https://www.unep.org/news-and-stories/story/were-gobbling-earths-resources-unsustainable-rate (accessed on 17 December 2023).
• d’Ambrières, W.; Plastics Recycling Worldwide: Current Overview and Desirable Changes. December 2019. Available online: https://journals.openedition.org/factsreports/5102 (accessed on 17 December 2023).
• Geyer, R.; Jambeck, J.R.; Production, K.L.L. Production use, and fate of all plastics ever made. Sci. Adv. 2017 , 3 , e1700782. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Smulian, M. OECD Finds Only 9% of Plastic Recycled Worldwide. Available online: https://www.mrw.co.uk/news/oecd-finds-only-9-of-plastic-recycled-worldwide-22-02-2022/ (accessed on 17 December 2023).
• Ozdemir, M.E.; Ali, Z.; Subeshan, B.; Asmatulu, E. Applying machine learning approach in recycling. J. Mater. Cycles Waste Manag. 2021 , 23 , 855–871. [ Google Scholar ] [ CrossRef ]
• Garello, R. Plastics: A Threat to our Oceans. Available online: https://ieeeoes.org/oes-beacon/june-2019-beacon/plastics-a-threat-to-our-oceans/ (accessed on 17 December 2023).
• Jason, C. AI-Guided Robots Are Ready to Sort Your Recyclables. Available online: https://spectrum.ieee.org/ai-guided-robots-are-ready-to-sort-your-recyclables (accessed on 17 December 2023).
• Chidepatil, A.; Bindra, P.; Kulkarni, D.; Qazi, M.; Kshirsagar, M.; Sankaran, K. From Trash to Cash: How Blockchain and Multi-Sensor-Driven Artificial Intelligence Can Transform Circular Economy of Plastic Waste? Adm. Sci. 2020 , 10 , 23. [ Google Scholar ] [ CrossRef ]
• Grand View Research. Plastic Waste Management Market Size, Share & Trends Analysis Report by Service (Collection, Recycling, Incineration, Landfills), by Polymer (PP, PET, PVC), by Source, by End Use, by Region, and Segment Forecasts, 2020–2027. Available online: https://www.grandviewresearch.com/industry-analysis/plastic-waste-management-market (accessed on 17 December 2023).
• Flower, W. What Operation Green Fence Has Meant for Recycling. Available online: https://www.waste360.com/waste-management-business/what-operation-green-fence-has-meant-for-recycling (accessed on 17 December 2023).
• Recycling Today. China Announces Import Ban on an Additional 32 Scrap Materials. 2023. Available online: https://www.recyclingtoday.com/article/china-bans-solid-waste-imports/ (accessed on 17 December 2023).
• Page, M.J.; McKenzie, J.E.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Shamseer, L.; Tetzlaff, J.M.; Akl, E.A.; Brennan, S.E.; et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. Int. J. Surg. 2021 , 88 , 105906. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Hua, D.; Gao, J.; Mayo, R.; Smedley, A.; Puranik, P.; Zhan, J. Segregating Hazardous Waste Using Deep Neural Networks in Real-Time Video. In Proceedings of the 2020 10th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA, 6–8 January 2020; Charkrabarti, S., Paul, R., Eds.; IEEE: Piscataway, NJ, USA, 2020; pp. 1016–1022. [ Google Scholar ] [ CrossRef ]
• Kumar, N.M.; Mohammed, M.A.; Abdulkareem, K.H.; Damasevicius, R.; Mostafa, S.A.; Maashi, M.S.; Chopra, S.S. Artificial intelligence-based solution for sorting COVID related medical waste streams and supporting data-driven decisions for smart circular economy practice. Process Saf. Environ. Prot. 2021 , 152 , 482–494. [ Google Scholar ] [ CrossRef ]
• Altikat, A.; Gulbe, A.; Altikat, S. Intelligent solid waste classification using deep convolutional neural networks. Int. J. Environ. Sci. Technol. 2022 , 19 , 1285–1292. [ Google Scholar ] [ CrossRef ]
• Menaka, S.; Gayathri, A. To Improving the Performance of Identification and Segregation of Liquid and Solid from Municipal Waste Using Adam Optimization Algorithm. In Proceedings of the 2023 International Conference on Self Sustainable Artificial Intelligence Systems (ICSSAS), Erode, India, 18–20 October 2023; pp. 1515–1520. [ Google Scholar ] [ CrossRef ]
• Thibuy, K.; Thokrairak, S.; Jitngernmadan, P. Holistic Solution Design and Implementation for Smart City Recycle Waste Management Case Study: Saensuk City. In Proceedings of the 2020—5th International Conference on Information Technology (InCIT), Chonburi, Thailand, 21–22 October 2020; pp. 233–237. [ Google Scholar ] [ CrossRef ]
• Viswanadham, Y.K.; Rani, R.S.; Mai, V.M.S.L.S.; Krishna, V.N.V.; Vamsi, Y.V. An Identification and Categorization of Plastic Material using Deep Learning Approach. In Proceedings of the 2023 3rd International Conference on Pervasive Computing and Social Networking (ICPCSN), Salem, India, 19–20 June 2023; pp. 289–294. [ Google Scholar ] [ CrossRef ]
• Tamin, O.; Moung, E.G.; Dargham, J.A.; Yahya, F.; Omatu, S.; Angeline, L. Machine Learning for Plastic Waste Detection: State-of-the-art, Challenges, and Solutions. In Proceedings of the 2022 International Conference on Communications, Information, Electronic and Energy Systems (CIEES), Veliko Tarnovo, Bulgaria, 24–26 November 2022; pp. 1–6. [ Google Scholar ] [ CrossRef ]
• Shravani, N.; Vigneshwari, S. Optimizing Waste Management through Intelligent Machine Learning Systems: A Comparative Study. In Proceedings of the 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT), Delhi, India, 6–8 July 2023; pp. 1–6. [ Google Scholar ] [ CrossRef ]
• Rahman, N.; Das, S.K. A Fusion of Three Custom-Tailored Deep Learning Architectures for Waste Classification. In Proceedings of the 2022 4th International Conference on Sustainable Technologies for Industry 4.0 (STI), Dhaka, Bangladeshc, 17–18 December 2022; pp. 1–6. [ Google Scholar ] [ CrossRef ]
• Alzyoud, F.Y.; Maqableh, W.; Al Shrouf, F. A Semi Smart Adaptive Approach for Trash Classification. Int. J. Comput. Commun. Control 2021 , 16 , 4172. [ Google Scholar ] [ CrossRef ]
• Abdu, H.; Noor, M.H.M. A Survey on Waste Detection and Classification Using Deep Learning. IEEE Access 2022 , 10 , 128151–128165. [ Google Scholar ] [ CrossRef ]
• Kang, Z.; Yang, J.; Li, G.; Zhang, Z. An Automatic Garbage Classification System Based on Deep Learning. IEEE Access 2020 , 8 , 140019–140029. [ Google Scholar ] [ CrossRef ]
• Luo, Q.; Yang, G.; Zhao, X. An Edge-Cloud Framework Equipped with Deep Learning Model for Recyclable Garbage Detection. In Proceedings of the 2020 Eighth International Conference on Advanced Cloud and Big Data (CBD), Taiyuan, China, 5–6 December 2020; pp. 248–252. [ Google Scholar ] [ CrossRef ]
• Sheng, T.J.; Islam, M.S.; Misran, N.; Baharuddin, M.H.; Arshad, H.; Islam, R.; Chowdhury, M.E.H.; Rmili, H. An Internet of Things Based Smart Waste Management System Using LoRa and Tensorflow Deep Learning Model. IEEE Access 2020 , 8 , 148793–148811. [ Google Scholar ] [ CrossRef ]
• Huang, J.; Koroteev, D.D. Artificial intelligence for planning of energy and waste management. Sustain. Energy Technol. Assess. 2021 , 47 , 101426. [ Google Scholar ] [ CrossRef ]
• Bhattacharya, S.; Sai, K.B.; Puvirajan, H.S.; Peera, H.; Jyothi, G. Automated Garbage Classification using Deep Learning. In Proceedings of the 2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC), Salem, India, 4–6 May 2023; pp. 404–410. [ Google Scholar ] [ CrossRef ]
• Tseng, M.-L.; Ha, H.M.; Tran, T.P.T.; Bui, T.-D.; Chen, C.-C.; Lin, C.-W. Building a data-driven circular supply chain hierarchical structure: Resource recovery implementation drives circular business strategy. Bus. Strategy Environ. 2022 , 31 , 2082–2106. [ Google Scholar ] [ CrossRef ]
• Nafiz, M.S.; Das, S.S.; Morol, M.K.; Al Juabir, A.; Nandi, D. ConvoWaste: An Automatic Waste Segregation Machine Using Deep Learning. In Proceedings of the 2023 3rd International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST), Dhaka, Bangladesh, 7–8 January 2023; pp. 181–186. [ Google Scholar ] [ CrossRef ]
• Shennib, F.; Schmitt, K. Data-driven technologies and artificial intelligence in circular economy and waste management systems: A review. In Proceedings of the 2021 IEEE International Symposium on Technology and Society (ISTAS), Waterloo, ON, Canada, 28–31 October 2021; pp. 1–5. [ Google Scholar ] [ CrossRef ]
• Wu, H.; Zhang, H.; Liang, J.; Yang, Z.; Wang, X. Design of New Intelligent Dustbin for Garbage Classification based on Machine Learning. In Proceedings of the 2022 International Joint Conference on Information and Communication Engineering (JCICE), Seoul, Republic of Korea, 20–22 May 2022; pp. 171–176. [ Google Scholar ] [ CrossRef ]
• Yu, K.H.; Zhang, Y.; Li, D.; Montenegro-Marin, C.E.; Kumar, P.M. Environmental planning based on reduce, reuse, recycle and recover using artificial intelligence. Environ. Impact Assess. Rev. 2021 , 86 , 106492. [ Google Scholar ] [ CrossRef ]
• Carrera, B.; Mata, J.B.; Pinol, V.L.; Kim, K. Environmental sustainability: A machine learning approach for cost analysis in plastic recycling classification. Resour. Conserv. Recycl. 2023 , 197 , 107095. [ Google Scholar ] [ CrossRef ]
• Maraveas, C.; Kotzabasaki, M.I.; Bartzanas, T. Intelligent Technologies, Enzyme-Embedded and Microbial Degradation of Agricultural Plastics. Agriengineering 2023 , 5 , 85–111. [ Google Scholar ] [ CrossRef ]
• Tripathi, R.; Shetty, H.; Patil, K.; Ingawale, P.; Trivedi, M. Intelligent Waste Material Classification Using EfficientNet-B3 Convolutional Neural Network for Enhanced Waste Management. In Proceedings of the 2023 International Conference on Self Sustainable Artificial Intelligence Systems (ICSSAS), Erode, India, 18–20 October 2023; pp. 132–137. [ Google Scholar ] [ CrossRef ]
• Seyyedi, S.R.; Kowsari, E.; Ramakrishna, S.; Gheibi, M.; Chinnappan, A. Marine plastics, circular economy, and artificial intelligence: A comprehensive review of challenges, solutions, and policies. J. Environ. Manag. 2023 , 345 , 118591. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Zia, H.; Jawaid, M.U.; Fatima, H.S.; Hassan, I.U.; Hussain, A.; Shahzad, S.; Khurram, M. Plastic Waste Management through the Development of a Low Cost and Light Weight Deep Learning Based Reverse Vending Machine. Recycling 2022 , 7 , 70. [ Google Scholar ] [ CrossRef ]
• Salim, A.A.; Karnadi, I.; Williamdy, W.; Bastiaan, T.; Steven, E. PLEESE—Plastic Reuse Reminder System using Computer Vision Deep Learning. In Proceedings of the 2022 1st International Conference on Technology Innovation and Its Applications (ICTIIA), Tangerang, Indonesia, 23 September 2022; pp. 1–6. [ Google Scholar ] [ CrossRef ]
• Kumar, J.N.A.; Chimmani, S. Proposal of smart home resource management for waste reduction and sustainability using AI and ML. In Proceedings of the 2019 International Conference on Communication and Electronics Systems (ICCES), Coimbatore, India, 17–19 July 2019; pp. 992–998. [ Google Scholar ] [ CrossRef ]
• Imran; Ahmad, S.; Kim, D.H. Quantum GIS Based Descriptive and Predictive Data Analysis for Effective Planning of Waste Management. IEEE Access 2020 , 8 , 46193–46205. [ Google Scholar ] [ CrossRef ]
• Pan, Y. Research on image classification algorithm of domestic garbage based on deep learning method. In Proceedings of the 2023 IEEE 3rd International Conference on Power, Electronics and Computer Applications (ICPECA), Shenyang, China, 29–31 January 2023; pp. 1237–1244. [ Google Scholar ] [ CrossRef ]
• Liang, Z.; Gumabay, M.V.N. Smart Household Waste Classification System using Artificial Intelligence. In Proceedings of the 2022 5th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE), Wuhan, China, 22–24 April 2022; pp. 766–771. [ Google Scholar ] [ CrossRef ]
• Chopde, A.; Bharate, N.; Bhattar, S.; Kunvar, A.; Bhadwal, S. Trash Can! An AI system for automatic classification of waste. In Proceedings of the 2022 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES), Greater Noida, India, 20–21 May 2022; pp. 167–171. [ Google Scholar ] [ CrossRef ]
• Togacar, M.; Ergen, B.; Comert, Z. Waste classification using AutoEncoder network with integrated feature selection method in convolutional neural network models. Measurement 2020 , 153 , 107459. [ Google Scholar ] [ CrossRef ]
• Ghatkamble, R.; Parameshachari, B.D.; Pareek, P.K. YOLO Network Based Intelligent Municipal Waste Management in Internet of Things. In Proceedings of the 2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT), Mandya, India, 26–27 December 2022; pp. 1–10. [ Google Scholar ] [ CrossRef ]
• Chu, Y.; Huang, C.; Xie, X.; Tan, B.; Kamal, S.; Xiong, X. Multilayer hybrid deep-learning method for waste classification and recycling. Comput. Intell. Neurosci. 2018 , 2018 , 5060857. [ Google Scholar ] [ CrossRef ]
• Wang, Y.; Zhang, X. Autonomous garbage detection for intelligent urban management. MATEC Web Conf. 2018 , 232 , 01056. [ Google Scholar ] [ CrossRef ]
• Faria, R.; Ahmed, F.; Das, A.; Dey, A. Classification of organic and solid waste using deep convolutional neural networks. In Proceedings of the 2021 IEEE 9th Region 10 Humanitarian Technology Conference (R10-HTC), Bangalore, India, 30 September–2 October 2021; pp. 1–6. [ Google Scholar ]
• Nnamoko, N.; Barrowclough, J.; Procter, J. Solid waste image classification using deep convolutional neural network. Infrastructures 2022 , 7 , 4. [ Google Scholar ] [ CrossRef ]
• Shi, C.; Tan, C.; Wang, T.; Wang, L. A waste classification method based on a multilayer hybrid convolution neural network. Appl. Sci. 2021 , 11 , 18. [ Google Scholar ] [ CrossRef ]
• Narayan, Y. DeepWaste: Applying Deep Learning to Waste Classification for a Sustainable Planet. In Proceedings of the 34th Conference on Neural Information Processing Systems (NeurIPS 2020), Vancouver, BC, Canada, 6–12 December 2020. [ Google Scholar ]
• Adedeji, O.; Wang, Z. Intelligent Waste Classification System Using Deep Learning Convolutional Neural Network. Procedia Manuf. 2019 , 35 , 607–612. [ Google Scholar ] [ CrossRef ]
• Ramsurrun, N.; Suddul, G.; Armoogum, S.; Foogooa, R. Recyclable Waste Classification Using Computer Vision and Deep Learning. In Proceedings of the 2021 Zooming Innovation in Consumer Technologies Conference (ZINC), Novi Sad, Serbia, 26–27 May 2021; pp. 11–15. [ Google Scholar ]
• Yuan, Z.; Liu, J. A Hybrid Deep Learning Model for Trash Classification Based on Deep Transfer Learning. J. Electr. Comput. Eng. 2022 , 2022 , 1–9. [ Google Scholar ] [ CrossRef ]
• Liu, W.; Ouyang, H.; Liu, Q.; Cai, S.; Wang, C.; Xie, J.; Hu, W. Image recognition for garbage classification based on transfer learning and model fusion. Math. Probl. Eng. 2022 , 2022 , 1–12. [ Google Scholar ] [ CrossRef ]
• Liu, F.; Xu, H.; Qi, M.; Liu, D.; Wang, J.; Kong, J. Depth-wise separable convolution attention module for garbage image classification. Sustainability 2022 , 14 , 3099. [ Google Scholar ] [ CrossRef ]
• Bobulski, J.; Piatkowski, J. PET waste classification method and plastic waste database—WaDaBa. In Advances in Intelligent Systems and Computing ; Springer Verlag: Berlin/Heidelberg, Germany, 2018; Volume 681, pp. 57–64. [ Google Scholar ]
• Wu, Y.; Shen, X.; Liu, Q.; Xiao, F.; Li, C. A garbage detection and classification method based on visual scene understanding in the home environment. Complexity 2021 , 2021 , 1–14. [ Google Scholar ] [ CrossRef ]
• Chen, Y.; Han, W.; Jin, J.; Wang, H.; Xing, Q.; Zhang, Y. Clean our city: An automatic urban garbage classification algorithm using computer vision and transfer learning technologies. J. Phys. Conf. Ser. 2021 , 1994 , 012022. [ Google Scholar ] [ CrossRef ]
• Sun, A.; Xiao, H. ThanosNet: A novel trash classification method using metadata. In Proceedings of the 2020 IEEE International Conference on Big Data (Big Data), Atlanta, GA, USA, 10–13 December 2020; pp. 1394–1401. [ Google Scholar ]
• Vo, A.H.; Son, L.H.; Vo, M.T.; Le, T. A novel framework for trash classification using deep transfer learning. IEEE Access 2019 , 7 , 178631–178639. [ Google Scholar ] [ CrossRef ]
• Hossain, S.; Debnath, B.; Anika, A.; Junaed-Al-Hossain, M.; Biswas, S.; Shahnaz, C. Autonomous trash collector based on object detection using deep neural network. In Proceedings of the TENCON 2019–2019 IEEE Region 10 Conference (TENCON), Kochi, India, 17–20 October 2019; pp. 1406–1410. [ Google Scholar ]
• Tiyajamorn, P.; Lorprasertkul, P.; Assabumrungrat, R.; Poomarin, W.; Chancharoen, R. Automatic trash classification using convolutional neural network machine learning. In Proceedings of the 2019 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM), Bangkok, Thailand, 18–20 November 2019; pp. 71–76. [ Google Scholar ]
• Lin, W. YOLO-green: A real-time classification and object detection model optimized for waste management. In Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), Orlando, FL, USA, 15–18 December 2021; pp. 51–57. [ Google Scholar ]
• Panwar, H.; Gupta, P.K.; Siddiqui, M.K.; Morales-Menendez, R.; Bhardwaj, P.; Sharma, S.; Sarker, I.H. AquaVision: Automating the detection of waste in water bodies using deep transfer learning. Case Stud. Chem. Environ. Eng. 2020 , 2 , 100026. [ Google Scholar ] [ CrossRef ]
• Ma, W.; Wang, X.; Yu, J. A lightweight feature fusion single shot multibox detector for garbage detection. IEEE Access 2020 , 8 , 188577–188586. [ Google Scholar ] [ CrossRef ]
• Fulton, M.; Hong, J.; Islam, M.J.; Sattar, J. Robotic detection of marine litter using deep visual detection models. In Proceedings of the 2019 International Conference on Robotics and Automation (ICRA), Montreal, QC, Canada, 20–24 May 2019; pp. 5752–5758. [ Google Scholar ]
• Sousa, J.; Rebelo, A.; Cardoso, J.S. Automation of waste sorting with deep learning. In Proceedings of the 15th Workshop on Computer Vision, (WVC), São Bernardo do Campo, Brazil, 9–11 September 2019; pp. 43–48. [ Google Scholar ]
• Gruber, F.; Grählert, W.; Wollmann, P.; Kaskel, S. Classification of black plastics waste using fluorescence imaging and machine learning. Recycling 2019 , 4 , 40. [ Google Scholar ] [ CrossRef ]
• Seredkin, A.V.; Tokarev, M.P.; Plohih, I.A.; Gobyzov, O.A.; Markovich, D.M. Development of a method of detection and classification of waste objects on a conveyor for a robotic sorting system. J. Phys. Conf. Ser. 2019 , 1359 , 012127. [ Google Scholar ] [ CrossRef ]
• Sreelakshmi, K.; Akarsh, S.; Vinayakumar, R.; Soman, K.P. Capsule neural networks and visualization for segregation of plastic and non-plastic wastes. In Proceedings of the 2019 5th International Conference on Advanced Computing and Communication Systems (ICACCS), Coimbatore, India, 15–16 March 2019; pp. 631–636. [ Google Scholar ]
• Costa, B.S.; Bernardes, A.C.S.; Pereira, J.V.A.; Zampa, V.H.; Pereira, V.A.; Matos, G.F.; Soares, E.A.; Soares, C.L.; Silva, A.F.B. Artificial intelligence in automated sorting in trash recycling. In Proceedings of the 2018: Anais do Xv Encontro Nacional de Inteligência Artificial e Computacional, São Paulo, Brazil, 22–25 October 2018; pp. 198–205. [ Google Scholar ]
• Sakr, G.E.; Mokbel, M.; Darwich, A.; Khneisser, M.N.; Hadi, A. Comparing deep learning and support vector machines for autonomous waste sorting. In Proceedings of the 2016 International Multidisciplinary Conference on Engineering Technology (IMCET), Beirut, Lebanon, 2–4 November 2016; pp. 207–212. [ Google Scholar ]
• Li, X.; Su, J.; Wang, H.; Boczkaj, G.; Mahlknecht, J.; Singh, S.V.; Wang, C. Bibliometric analysis of artificial intelligence in wastewater treatment: Current status, research progress, and future prospects. J. Environ. Chem. Eng. 2024 , 12 , 113152. [ Google Scholar ] [ CrossRef ]
• Su, J.; Zhang, F.; Yu, C.; Zhang, Y.; Wang, J.; Wang, C.; Wang, H.; Jiang, H. Machine learning: Next promising trend for microplastics study. J. Environ. Manag. 2023 , 344 , 118756. [ Google Scholar ] [ CrossRef ]

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Ramos, E.; Lopes, A.G.; Mendonça, F. Application of Machine Learning in Plastic Waste Detection and Classification: A Systematic Review. Processes 2024 , 12 , 1632. https://doi.org/10.3390/pr12081632

Ramos E, Lopes AG, Mendonça F. Application of Machine Learning in Plastic Waste Detection and Classification: A Systematic Review. Processes . 2024; 12(8):1632. https://doi.org/10.3390/pr12081632

Ramos, Edgar, Arminda Guerra Lopes, and Fábio Mendonça. 2024. "Application of Machine Learning in Plastic Waste Detection and Classification: A Systematic Review" Processes 12, no. 8: 1632. https://doi.org/10.3390/pr12081632

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