# Will innovation solve the global plastic contamination: how much innovation is needed for that?

Mateo Cordier, Takuro Uehara

► To cite this version:

Mateo Cordier, Takuro Uehara. Will innovation solve the global plastic contamination: how much innovation is needed for that?. 2018. hal-04566023

HAL Id: hal-04566023

https://hal.science/hal-04566023

Preprint submitted on 2 May 2024

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# Will innovation solve the global plastic contamination: how much innovation is needed for that?

Mateo Cordier, Takuro Uehara

► To cite this version:

Mateo Cordier, Takuro Uehara. Will innovation solve the global plastic contamination: how much innovation is needed for that?. 2018. hal-04566023

HAL Id: hal-04566023

https://hal.science/hal-04566023v1

Preprint submitted on 2 May 2024

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
Will innovation solve the global plastic contamination: how much innovation is needed for that?

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5 Mateo Cordier¹, ² and Takuro Uehara³

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16 Corresponding author:

17 Mateo Cordier

18 11 Boulevard d'Alembert, 78280 Guyancourt, France.

19 Email address: mateo.cordier@uvsq.fr

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Will innovation solve the global plastic contamination: how much innovation is needed for that?

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16 Corresponding author:

17 Mateo Cordier

18 11 Boulevard d'Alembert, 78280 Guyancourt, France.

19 Email address: mateo.cordier@uvsq.fr

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40 Abstract

Plastics have become increasingly dominant in the consumer marketplace since their
commercial development in the 1930s and 1940s. Global plastic production reached 335
million tons in 2016, a 640% increase since 1975. In 1960, plastics made up less than 1%
of municipal solid waste by mass in the United States. By 2000, this proportion increased
by one order of magnitude. As a result, plastic contamination is found everywhere in the
world's oceans, coastal areas, freshwater bodies and terrestrial environments. Plastics in
the marine environment are of increasing concern because of their persistence and effects
on the oceans, wildlife, and, potentially, humans. A report by the MacArthur Foundation
published in 2016 claimed that innovation can solve the plastic problem. However, it
does not say how much innovation is needed and does not analyse if it is feasible. In this
working paper, we propose to bring about answers to this question by developing an
ecological-economic world model that simulates plastic waste emission by human
activities, transport from land to the ocean and accumulation into the marine ecosystem.

Innovations will be simulated in an economic sub-model integrated to the ecological-economic world model as one of its components. The model, in its current development stage, is capable of quantifying the impacts of innovations on the total amount of plastics accumulated in the ocean at the world scale. The ecological-economic world model is designed in Powersim following system dynamics programming. In a further work, the economic sub-model will be designed in Excel Following input-output matrix equations.

Our preliminary results suggest that to reach a significant abatement of plastic in the global ocean, a panel of diverse types of solutions is required. One type of environmental measure alone will not succeed. Upstream and downstream solutions must be combined: (i) across the social-ecological system, that is, "at-the-source" but also "middle" and "end-of-pipe" solutions; (ii) as well as across the plastic contamination causal chain as well, that is, "preventive" but also "curative" solutions. Only combined solutions succeed to reduce the amount of plastic stock accumulated in the oceans since the 1950's to the level of 2010. Our model suggests that solutions which would be able to go further and reduce plastic stocks to 50% of 2010's level would require intense ocean cleanup. To achieve such an ambitious environmental target, 11.89% of total plastic wastes should be removed from the ocean every year between 2020 and 2030. The technical feasibility of such a solution is highly questionable knowing that current technologies remove only floating plastic at the surface of the water and that such floating plastic represent a very small percentage of all plastics accumulated in the global ocean at the surface of the water, in the water column and deposited on the seabed.

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40 Abstract

Plastics have become increasingly dominant in the consumer marketplace since their
commercial development in the 1930s and 1940s. Global plastic production reached 335
million tons in 2016, a 640% increase since 1975. In 1960, plastics made up less than 1%
of municipal solid waste by mass in the United States. By 2000, this proportion increased
by one order of magnitude. As a result, plastic contamination is found everywhere in the
world's oceans, coastal areas, freshwater bodies and terrestrial environments. Plastics in
the marine environment are of increasing concern because of their persistence and effects
on the oceans, wildlife, and, potentially, humans. A report by the MacArthur Foundation
published in 2016 claimed that innovation can solve the plastic problem. However, it
does not say how much innovation is needed and does not analyse if it is feasible. In this
working paper, we propose to bring about answers to this question by developing an
ecological-economic world model that simulates plastic waste emission by human
activities, transport from land to the ocean and accumulation into the marine ecosystem.
Innovations will be simulated in an economic sub-model integrated to the ecological-
economic world model as one of its components. The model, in its current development
stage, is capable of quantifying the impacts of innovations on the total amount of plastics
accumulated in the ocean at the world scale. The ecological-economic world model is
designed in Powersim following system dynamics programming. In a further work, the
economic sub-model will be designed in Excel Following input-output matrix equations.
Our preliminary results suggest that to reach a significant abatement of plastic in the
global ocean, a panel of diverse types of solutions is required. One type of environmental
measure alone will not succeed. Upstream and downstream solutions must be combined:
(i) across the social-ecological system, that is, "at-the-source" but also "middle" and
"end-of-pipe" solutions; (ii) as well as across the plastic contamination causal chain as
well, that is, "preventive" but also "curative" solutions. Only combined solutions succeed
to reduce the amount of plastic stock accumulated in the oceans since the 1950's to the
level of 2010. Our model suggests that solutions which would be able to go further and
reduce plastic stocks to 50% of 2010's level would require intense ocean cleanup. To
achieve such an ambitious environmental target, 11.89% of total plastic wastes should be
removed from the ocean every year between 2020 and 2030. The technical feasibility of
such a solution is highly questionable knowing that current technologies remove only
floating plastic at the surface of the water and that such floating plastic represent a very
small percentage of all plastics accumulated in the global ocean at the surface of the
water, in the water column and deposited on the seabed.

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## Introduction

Plastics have become increasingly dominant in the consumer marketplace since their commercial development in the 1930s and 1940s (Jambeck et al., 2015). Global plastic resin production reached 288 million metric tons in 2012 (MT is used hereinafter for Metric Tons), a 620% increase since 1975 (Jambeck et al., 2015; PlasticsEurope, 2013). The largest market sector for plastic resins is packaging (PlasticsEurope, 2013), that is, materials designed for immediate disposal (Jambeck et al., 2015). In 1960, plastics made up less than 1% of municipal solid waste by mass in the United States (EPA, 2011). By 2000, this proportion increased by one order of magnitude (Jambeck et al., 2015).

Plastic contamination is found everywhere in the world's oceans, coastal areas, freshwater bodies and terrestrial environments (Baztan et al., 2017, p. 171). Since 2014, scientists have succeeded to provide gross estimated of their ecological, social and economic impacts (UNEP, 2014; Trasande et al., 2015; Gallo et al., 2018; Jaacks and Prasad, 2017; McIlgorm et al., 2011). Plastics in the marine environment are of increasing concern because of their persistence and effects on the oceans, wildlife, and, potentially, humans (Jambeck et al., 2015; Thompson et al., 2009; Attina et al., 2016; Trasande et al., 2015; Shea and Committee on Environmental Health, 2003; Barnes et al., 2009; Obbard et al., 2014; Baztan et al., 2016; Da Costa et al., 2016).

A report by the MacArthur Foundation (Ellen MacArthur Foundation et al., 2016) claimed that innovation can solve the plastic problem. However, it does not say how much innovation is needed and does not analyse if it is feasible. In this working paper, we propose to bring about answers to this question by developing an ecological-economic world model that simulates plastic waste emission by human activities, transport from land to the ocean and accumulation into the marine ecosystem. Innovations will be simulated in an economic sub-model<fnref n="1" /> integrated to the ecological-economic world model as one of its components. The model, in its current development stage, is capable of quantifying the impacts of innovations on the total amount of plastics accumulated in the ocean at the world scale. The ecological-economic world model is designed in Powersim following system dynamics programming. The economic sub-model will be designed in Excel following input-output matrix equations. We will follow the technique developed in Cordier et al. (2017) were more explanations can be found on the way the architecture of the ecological-economic model and its economic sub-component are built and how they interact one with another.

<footnote n="1">¹ The economic sub-model is a work in progress. It will be finalized in early 2019. Regarding the ecological model used to simulate plastic accumulation in the ocean, the first version is ready and developed in this working paper. Its architectures and its parameters will be further improved in 2019, after discussion with plastic scientists at the Micro 2018 international conference held in Lanzarote (Canary Island, Spain).</footnote>
## Introduction

Plastics have become increasingly dominant in the consumer marketplace since their commercial development in the 1930s and 1940s (Jambeck et al., 2015). Global plastic resin production reached 288 million metric tons in 2012 (MT is used hereinafter for Metric Tons), a 620% increase since 1975 (Jambeck et al., 2015; PlasticsEurope, 2013). The largest market sector for plastic resins is packaging (PlasticsEurope, 2013), that is, materials designed for immediate disposal (Jambeck et al., 2015). In 1960, plastics made up less than 1% of municipal solid waste by mass in the United States (EPA, 2011). By 2000, this proportion increased by one order of magnitude (Jambeck et al., 2015).

Plastic contamination is found everywhere in the world's oceans, coastal areas, freshwater bodies and terrestrial environments (Baztan et al., 2017, p. 171). Since 2014, scientists have succeeded to provide gross estimated of their ecological, social and economic impacts (UNEP, 2014; Trasande et al., 2015; Gallo et al., 2018; Jaacks and Prasad, 2017; McIlgorm et al., 2011). Plastics in the marine environment are of increasing concern because of their persistence and effects on the oceans, wildlife, and, potentially, humans (Jambeck et al., 2015; Thompson et al., 2009; Attina et al., 2016; Trasande et al., 2015; Shea and Committee on Environmental Health, 2003; Barnes et al., 2009; Obbard et al., 2014; Baztan et al., 2016; Da Costa et al., 2016).

A report by the MacArthur Foundation (Ellen MacArthur Foundation et al., 2016) claimed that innovation can solve the plastic problem. However, it does not say how much innovation is needed and does not analyse if it is feasible. In this working paper, we propose to bring about answers to this question by developing an ecological-economic world model that simulates plastic waste emission by human activities, transport from land to the ocean and accumulation into the marine ecosystem. Innovations will be simulated in an economic sub-model<fnref n="1" /> integrated to the ecological-economic world model as one of its components. The model, in its current development stage, is capable of quantifying the impacts of innovations on the total amount of plastics accumulated in the ocean at the world scale. The ecological-economic world model is designed in Powersim following system dynamics programming. The economic sub-model will be designed in Excel following input-output matrix equations. We will follow the technique developed in Cordier et al. (2017) were more explanations can be found on the way the architecture of the ecological-economic model and its economic sub-component are built and how they interact one with another.

<footnote n="1">¹ The economic sub-model is a work in progress. It will be finalized in early 2019. Regarding the ecological model used to simulate plastic accumulation in the ocean, the first version is ready and developed in this working paper. Its architectures and its parameters will be further improved in 2019, after discussion with plastic scientists at the Micro 2018 international conference held in Lanzarote (Canary Island, Spain).</footnote>
117 **Materials & methods**

118
119 *Case study*

120
121 The first estimations of the quantity of plastic entering the ocean from waste generated on
122 land was calculated in 1975. Since then, no recent calculations had been provided until
123 Jambeck et al. (2015) proposed new estimations by linking worldwide data on solid
124 waste, population density, and economic status to estimate the mass of land-based plastic
125 waste entering the ocean. They calculated that 275 million metric tons (MT) of plastic
126 waste was generated in 192 coastal countries in 2010, with 4.8 to 12.7 million MT
127 entering the ocean annually at a global scale. This range might be an underestimate as
128 other studies suggest a range between 10 and 20 MT a year (Raveender Vannela, 2012;
129 European Commission, 2013; UNEP, 2017). However, up to know, there are no
130 estimations of the technological and financial effort required to reduce the annual flow of
131 plastics into the ocean as well as the total stock accumulated in the ocean. And yet, this is
132 quite important since according to Jambeck et al. (2015), without waste management
133 infrastructure improvements, the cumulative quantity of plastic waste available to enter
134 the ocean from land (i.e., mismanaged waste) is predicted to double in 2025 compared to
135 the situation in 2010.
136

136
137 Jambeck et al. (2015, p. 770) use their estimations to evaluate potential mitigation
138 strategies. They propose to apply their mitigation strategies to the 20 top countries ranked
139 by the mass of mismanaged<fnref n="2" /> plastic waste. The top 20 countries' mismanaged plastic
140 waste encompasses 83% of the total in 2010 and include, in order: China, Indonesia,
141 Philippines, Vietnam, Sri Lanka, ..., Morocco, North Korea, and United-States (full list
142 available in Jambeck et al. (2015, p. 769)). If considered collectively, coastal European
143 Union countries (23 total) would rank eighteenth on the list instead of Morocco. Jambeck
144 et al. propose the following mitigation strategies (the categorization below into three
145 categories is ours, see Table 1):
146

146
147 1. Preventive “middle” solutions based on plastic waste management:

148
149 - If the fraction of mismanaged waste were reduced by 50% in the 20 top countries
150 ranked by mass of mismanaged plastic waste, this mass would decrease by 41%
151 by 2025.

152 - This falls to 34% if the reduction is only applied to the top 10 countries.

153 - This falls to 26% if applied to the top 5 countries.

<footnote n="2">² Jambeck et al. (2015) defined mismanaged waste as material that is either littered or inadequately disposed. Inadequately disposed waste is not formally managed and includes disposal in dumps or open, uncontrolled landfills, where it is not fully contained. Mismanaged waste could eventually enter the ocean via inland waterways, wastewater outflows, and transport by wind or tides.</footnote>
117 **Materials & methods**

118
119 *Case study*

120
121 The first estimations of the quantity of plastic entering the ocean from waste generated on
122 land was calculated in 1975. Since then, no recent calculations had been provided until
123 Jambeck et al. (2015) proposed new estimations by linking worldwide data on solid
124 waste, population density, and economic status to estimate the mass of land-based plastic
125 waste entering the ocean. They calculated that 275 million metric tons (MT) of plastic
126 waste was generated in 192 coastal countries in 2010, with 4.8 to 12.7 million MT
127 entering the ocean annually at a global scale. This range might be an underestimate as
128 other studies suggest a range between 10 and 20 MT a year (Raveender Vannela, 2012;
129 European Commission, 2013; UNEP, 2017). However, up to know, there are no
130 estimations of the technological and financial effort required to reduce the annual flow of
131 plastics into the ocean as well as the total stock accumulated in the ocean. And yet, this is
132 quite important since according to Jambeck et al. (2015), without waste management
133 infrastructure improvements, the cumulative quantity of plastic waste available to enter
134 the ocean from land (i.e., mismanaged waste) is predicted to double in 2025 compared to
135 the situation in 2010.
136

136
137 Jambeck et al. (2015, p. 770) use their estimations to evaluate potential mitigation
138 strategies. They propose to apply their mitigation strategies to the 20 top countries ranked
139 by the mass of mismanaged<fnref n="2" /> plastic waste. The top 20 countries' mismanaged plastic
140 waste encompasses 83% of the total in 2010 and include, in order: China, Indonesia,
141 Philippines, Vietnam, Sri Lanka, ..., Morocco, North Korea, and United-States (full list
142 available in Jambeck et al. (2015, p. 769)). If considered collectively, coastal European
143 Union countries (23 total) would rank eighteenth on the list instead of Morocco. Jambeck
144 et al. propose the following mitigation strategies (the categorization below into three
145 categories is ours, see Table 1):
146

146
147 1. Preventive “middle” solutions based on plastic waste management:

148
149 - If the fraction of mismanaged waste were reduced by 50% in the 20 top countries
150 ranked by mass of mismanaged plastic waste, this mass would decrease by 41%
151 by 2025.

152 - This falls to 34% if the reduction is only applied to the top 10 countries.

153 - This falls to 26% if applied to the top 5 countries.

<footnote n="2">² Jambeck et al. (2015) defined mismanaged waste as material that is either littered or inadequately disposed. Inadequately disposed waste is not formally managed and includes disposal in dumps or open, uncontrolled landfills, where it is not fully contained. Mismanaged waste could eventually enter the ocean via inland waterways, wastewater outflows, and transport by wind or tides.</footnote>
154 - To achieve a 75% reduction in the mass of mismanaged plastic waste, waste
155 management would have to be improved by 85% in the 35 top-ranked countries.
156 This strategy would require substantial infrastructure investment primarily in low-
157 and middle-income countries.
158

159 2. Preventive “at-the-source” solutions based on changes in consumer behaviours:

160
161 - A 26% decrease in the amount of mismanaged plastic waste would be achieved by
162 2025 if per capita waste generation were reduced to the 2010 average (1.2
163 kg/day)<fnref n="3" /> in the 91 coastal countries that exceed this average, and the percent
164 plastic in the waste stream were capped at 11% (the 192-country average in 2010).
165 This strategy would target higher-income countries and might require smaller
166 global investments. Changes in consumer behaviours would be required to reduce
167 plastic waste generation, which could encompass awareness rising campaigns on
168 the social and environmental problems caused by the hyper-consumption society,
169 taxes on plastic products to increase purchasing prices and hence to reduce
170 consumption, recycling systems, systems of returnable plastic or glass bottles,
171 online systems designed to help particulars to share, sell, exchange, borrow or rent
172 second-hand products (plastic products included), etc.
173

174 3. Preventive “middle” and “end-of-pipe” based on both, plastic waste management and
175 changes in consumer behaviors:

176
177 - A 77% reduction in the amount of mismanaged plastic waste could be realized
178 with a combined strategy, in which total waste management is achieved (0%
179 mismanaged waste) in the 10 top-ranked countries and plastic waste generation is
180 capped as described above (per capita waste generation reduced to 1.2 kg/day in
181 the 91 coastal countries that exceed this average.

182
183 With the ecological-economic world model developed in this paper, we assess the
184 ecological impact of the three mitigation strategies proposed by Jambeck et al. (2015).
185 Economic impacts will be estimated in a further work once the economic sub-model will
186 be ready. The economic sub-model will also help us to design economic strategies – such
187 as the shared environmental responsibility principle (Cordier et al., 2018) to make
188 affordable plastic solutions that might be disproportionately expensive under the
189 conventional polluter pays principle.
190

190

191

<footnote n="3">³ Average calculated on the world population. It differs from Jambeck et al. (2015, p. 770) – 1.7 kg/day – because they calculated it on a country basis, not on a global population basis.</footnote>
154 - To achieve a 75% reduction in the mass of mismanaged plastic waste, waste
155 management would have to be improved by 85% in the 35 top-ranked countries.
156 This strategy would require substantial infrastructure investment primarily in low-
157 and middle-income countries.
158

159 2. Preventive “at-the-source” solutions based on changes in consumer behaviours:

160
161 - A 26% decrease in the amount of mismanaged plastic waste would be achieved by
162 2025 if per capita waste generation were reduced to the 2010 average (1.2
163 kg/day)<fnref n="3" /> in the 91 coastal countries that exceed this average, and the percent
164 plastic in the waste stream were capped at 11% (the 192-country average in 2010).
165 This strategy would target higher-income countries and might require smaller
166 global investments. Changes in consumer behaviours would be required to reduce
167 plastic waste generation, which could encompass awareness rising campaigns on
168 the social and environmental problems caused by the hyper-consumption society,
169 taxes on plastic products to increase purchasing prices and hence to reduce
170 consumption, recycling systems, systems of returnable plastic or glass bottles,
171 online systems designed to help particulars to share, sell, exchange, borrow or rent
172 second-hand products (plastic products included), etc.
173

174 3. Preventive “middle” and “end-of-pipe” based on both, plastic waste management and
175 changes in consumer behaviors:

176
177 - A 77% reduction in the amount of mismanaged plastic waste could be realized
178 with a combined strategy, in which total waste management is achieved (0%
179 mismanaged waste) in the 10 top-ranked countries and plastic waste generation is
180 capped as described above (per capita waste generation reduced to 1.2 kg/day in
181 the 91 coastal countries that exceed this average.

182
183 With the ecological-economic world model developed in this paper, we assess the
184 ecological impact of the three mitigation strategies proposed by Jambeck et al. (2015).
185 Economic impacts will be estimated in a further work once the economic sub-model will
186 be ready. The economic sub-model will also help us to design economic strategies – such
187 as the shared environmental responsibility principle (Cordier et al., 2018) to make
188 affordable plastic solutions that might be disproportionately expensive under the
189 conventional polluter pays principle.
190

190

191

<footnote n="3">³ Average calculated on the world population. It differs from Jambeck et al. (2015, p. 770) – 1.7 kg/day – because they calculated it on a country basis, not on a global population basis.</footnote>
<table><caption>Table 1. Categorization of plastic solution types</caption><thead><tr><th>Location<br>across<br>the<br>problem<br>causal<br>chain</th><th>Location<br>across the<br>social-<br>ecological<br>system</th><th>Environmental<br>solutions</th><th>Examples of concrete solutions</th></tr></thead><tbody><tr><td rowspan="7">Solutions at the source of<br>the problem</td><td rowspan="7">Preventive<br>measures</td><td>Avoid waste<br>production</td><td>Inciting households to reduce the generation of<br>wastes through awareness rising campaigns aimed<br>at mitigating overconsumption behaviours in<br>general<br>Inciting industries to substitute plastic materials by<br>aluminium or glass for example</td></tr><tr><td>Reuse old<br>products</td><td>Returnable glass or PET bottles</td></tr><tr><td>Recycling</td><td>Recycling in closed cycles (e.g., recycling of plastic<br>bottles, plastic bags, etc.)</td></tr><tr><td>Disposal in<br>landfilling</td><td>Invest in waste management such as landfill sealing<br>to avoid plastic waste leakages through rains,<br>waterways, wind, etc.</td></tr><tr><td>Incineration</td><td>Plastic waste incineration</td></tr><tr><td>Energy recovery</td><td>Plastic waste incineration with energy cogeneration</td></tr><tr><td>Composting<br>biodegradable<br>plastic bottles</td><td>Biodegradable (compostable) plastics made of<br>starch that meet standards for biodegradability and<br>compostability</td></tr><tr><td rowspan="2">Middle solutions</td><td rowspan="2">Curative<br>measures</td><td>Collecting<br>plastics in<br>ecosystems</td><td>Collection of plastic wastes in oceans (e.g., Boyan<br>Slat's Ocean Clean-up Project (Slat, 2014)</td></tr><tr><td>Health measures</td><td>Health care due to plastic chemicals consumption<br>(e.g., Bisphenol-A and other endocrine disruptors)</td></tr><tr><td>End-of-pipe solutions</td><td>Palliative<br>measures</td><td>Averting<br>behaviours to<br>avoid exposure</td><td>Final consumers purchasing glass bottles instead of<br>plastic ones, switching from plastic bottles of<br>mineral water to public tap water, etc.</td></tr></tbody></table>

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<table><caption>Table 1. Categorization of plastic solution types</caption><thead><tr><th>Location<br>across<br>the<br>problem<br>causal<br>chain</th><th>Location<br>across the<br>social-ecological<br>system</th><th>Environmental<br>solutions</th><th>Examples of concrete solutions</th></tr></thead><tbody><tr><td rowspan="7">Solutions at the source of<br>the problem</td><td rowspan="7">Preventive<br>measures</td><td>Avoid waste<br>production</td><td>Inciting households to reduce the generation of<br>wastes through awareness rising campaigns aimed<br>at mitigating overconsumption behaviours in<br>general<br>Inciting industries to substitute plastic materials by<br>aluminium or glass for example</td></tr><tr><td>Reuse old<br>products</td><td>Returnable glass or PET bottles</td></tr><tr><td>Recycling</td><td>Recycling in closed cycles (e.g., recycling of plastic<br>bottles, plastic bags, etc.)</td></tr><tr><td>Disposal in<br>landfilling</td><td>Invest in waste management such as landfill sealing<br>to avoid plastic waste leakages through rains,<br>waterways, wind, etc.</td></tr><tr><td>Incineration</td><td>Plastic waste incineration</td></tr><tr><td>Energy recovery</td><td>Plastic waste incineration with energy cogeneration</td></tr><tr><td>Composting<br>biodegradable<br>plastic bottles</td><td>Biodegradable (compostable) plastics made of<br>starch that meet standards for biodegradability and<br>compostability</td></tr><tr><td rowspan="2">Middle solutions</td><td rowspan="2">Curative<br>measures</td><td>Collecting<br>plastics in<br>ecosystems</td><td>Collection of plastic wastes in oceans (e.g., Boyan<br>Slat's Ocean Clean-up Project (Slat, 2014)</td></tr><tr><td>Health measures</td><td>Health care due to plastic chemicals consumption<br>(e.g., Bisphenol-A and other endocrine disruptors)</td></tr><tr><td>End-of-pipe solutions</td><td>Palliative<br>measures</td><td>Averting<br>behaviours to<br>avoid exposure</td><td>Final consumers purchasing glass bottles instead of<br>plastic ones, switching from plastic bottles of<br>mineral water to public tap water, etc.</td></tr></tbody></table>

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194

195

196

197
198 *Scenarios*

199

200 We simulate three sets of scenarios that describe the evolution of plastic stock in the
201 world's ocean from 2010 to 2030. All scenarios include the evolution of the world
202 population based on forecasts from the UN (The United Nations, n.d.). In a further
203 version of the model, we will also add economic growth rate to take into account that
204 every year, each individual consumes a greater amount of products than previous year.
205 Economic growth explains that even if there were no population growth, plastic product
206 and plastic waste generation would keep increasing. Once the IO sub-model will be
207 coupled to the SD general model displayed in Figure 1, we will test several principles to
208 allocate the implementation cost of plastic solution scenarios to countries and economic
209 sectors (e.g., the polluter pays principle, the shared environmental responsibility
210 principle, the common but differentiate responsibility principle, etc.).

211

212 The first set of scenarios simulates the evolution of plastics as if no environmental
213 measures were implemented in addition to those already undertaken:

214

215 1. *Business as usual scenario (BAU)*: the current trend keeps on up to 2030 with no additional environmental measures addressing plastics than those implemented in the reference year, 2010. At the current stage of the model development, we assume the ocean cleanup effort to be very low since only few cleanup initiatives have been undertaken in the world and at extremely small scales. This is why we arbitrarily set the cleanup effort at annual removal percentage of 0.10 % of the total stock of plastics in the oceans worldwide. This percentage will be estimated more accurately later. Regarding the other variables of the BAU scenario, they have been set based on Jambeck et al. (2015) supplemental materials: the percentage of plastic waste that is littered is set at 2% of plastic waste generation, the plastic waste inadequately managed is set at 30.017% of plastic waste generation, individuals generate 1.216 kg of wastes per day and per person, the share of plastics is set at 11.08 % of waste generation; the world population annual growth rate varies between 1.0% and 1.2%. According to the BAU scenario, if current trends keep on, the 2030's level of plastic in the oceans (floating and deposited plastics on the seabed) will exceed the level of 2020 by 36.5% (Figure 2).

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232

233

234

235

236
198 *Scenarios*

199

200 We simulate three sets of scenarios that describe the evolution of plastic stock in the
201 world's ocean from 2010 to 2030. All scenarios include the evolution of the world
202 population based on forecasts from the UN (The United Nations, n.d.). In a further
203 version of the model, we will also add economic growth rate to take into account that
204 every year, each individual consumes a greater amount of products than previous year.
205 Economic growth explains that even if there were no population growth, plastic product
206 and plastic waste generation would keep increasing. Once the IO sub-model will be
207 coupled to the SD general model displayed in Figure 1, we will test several principles to
208 allocate the implementation cost of plastic solution scenarios to countries and economic
209 sectors (e.g., the polluter pays principle, the shared environmental responsibility
210 principle, the common but differentiate responsibility principle, etc.).
211

212

213 The first set of scenarios simulates the evolution of plastics as if no environmental
214 measures were implemented in addition to those already undertaken:

215

216 1. *Business as usual scenario (BAU)*: the current trend keeps on up to 2030 with no additional environmental measures addressing plastics than those implemented in the reference year, 2010. At the current stage of the model development, we assume the ocean cleanup effort to be very low since only few cleanup initiatives have been undertaken in the world and at extremely small scales. This is why we arbitrarily set the cleanup effort at annual removal percentage of 0.10 % of the total stock of plastics in the oceans worldwide. This percentage will be estimated more accurately later. Regarding the other variables of the BAU scenario, they have been set based on Jambeck et al. (2015) supplemental materials: the percentage of plastic waste that is littered is set at 2% of plastic waste generation, the plastic waste inadequately managed is set at 30.017% of plastic waste generation, individuals generate 1.216 kg of wastes per day and per person, the share of plastics is set at 11.08 % of waste generation; the world population annual growth rate varies between 1.0% and 1.2%. According to the BAU scenario, if current trends keep on, the 2030's level of plastic in the oceans (floating and deposited plastics on the seabed) will exceed the level of 2020 by 36.5% (Figure 2).

217

218

219

220

221

222
237 The second set of scenarios simulates environmental measures aimed at stabilizing the
238 total plastic stock in the oceans by 2020. This means that the stock stops increasing and
239 remains constant after 2020 but it is not reduced (except in scenario 2.5. "Combined
240 strategy"):

241

242 2.1. " Cleanup effort only " scenario : this scenario simulates curative “end-of-pipe”
243 solutions such as collecting plastics in the ecosystem (Table 1), for example the
244 Boyan Slat’s Ocean Cleanup Project (Slat, 2014). The level of cleanup total effort (=  
245 1.91% of the stock of plastic waste in the ocean is removed) 4 has been estimated by  
246 optimization techniques with the world ocean plastic model in Powersim (Figure 1) in  
247 a way to achieve a stabilization of plastic stocks in the world ocean by 2020.
248

248

249 2.2. "Zero inadequately managed waste only" scenario: this scenario simulates
250 preventive "middle" solutions (Table 1) such as developing landfill sealing to avoid
251 plastic leakages taken away by rains and winds, developing collective collect of
252 wastes in low- and middle income countries, installing plastic recycling bins in the
253 streets, etc. This strategy would require substantial infrastructure investment
254 primarily in low- and middle income countries. Without support from high income
255 countries (e.g., financial support) or additional measures (e.g., implementation of
256 additional plastic solutions in high-income countries also – such as in scenario 2.3),
257 this scenario will suffer low social and political acceptability at the international
258 level, which might reduce its likeliness. The level of inadequately managed waste has
259 been estimated by optimization techniques with the model (Figure 1) in a way to
260 achieve a stabilization of plastic stocks in the world ocean by 2020. The optimization
261 results show that the model variable "% Inadequately managed waste" used in the
262 BAU scenario (0.300168 = 30.0168%) 5 must be replaced by 0% (which is the level
263 achieved in developed countries such as France, Sweden, Australia, Japan, United-
264 States, etc.).
265

265

266 2.3. "Reducing by 50% inadequately managed wastes and cleanup effort" scenario: this
267 scenario simulates curative “end-of-pipe” solutions (e.g., cleanup projects to remove
268 plastics from ecosystems) combined to preventive “middle” solutions (e.g.,
269 developing landfill sealing to avoid plastic leakages, development of collective
270 collect of wastes in low- and middle income countries, installing plastic recycling
271 bins in the streets, etc.). This scenario has been designed in two steps:
272

272

<footnote n="4">⁴ Cleanup total effort = baseline cleanup effort (BAU) + optimized cleanup effort = 0.10% + 1.81% = 1.91% of plastic wastes in the ocean are removed.</footnote>

<footnote n="5">⁵ This value has been calculated in Jambeck et al. (2015)'s supplemental materials providing national data for the year 2010 for 192 countries (almost the entire world).</footnote>
237 The second set of scenarios simulates environmental measures aimed at stabilizing the
238 total plastic stock in the oceans by 2020. This means that the stock stops increasing and
239 remains constant after 2020 but it is not reduced (except in scenario 2.5. "Combined
240 strategy"):

241

242 2.1. " Cleanup effort only " scenario : this scenario simulates curative “end-of-pipe”
243 solutions such as collecting plastics in the ecosystem (Table 1), for example the
244 Boyan Slat’s Ocean Cleanup Project (Slat, 2014). The level of cleanup total effort (=  
245 1.91% of the stock of plastic waste in the ocean is removed) 4 has been estimated by  
246 optimization techniques with the world ocean plastic model in Powersim (Figure 1) in  
247 a way to achieve a stabilization of plastic stocks in the world ocean by 2020.
248

248

249 2.2. "Zero inadequately managed waste only" scenario: this scenario simulates
250 preventive "middle" solutions (Table 1) such as developing landfill sealing to avoid
251 plastic leakages taken away by rains and winds, developing collective collect of
252 wastes in low- and middle income countries, installing plastic recycling bins in the
253 streets, etc. This strategy would require substantial infrastructure investment
254 primarily in low- and middle income countries. Without support from high income
255 countries (e.g., financial support) or additional measures (e.g., implementation of
256 additional plastic solutions in high-income countries also – such as in scenario 2.3),
257 this scenario will suffer low social and political acceptability at the international
258 level, which might reduce its likeliness. The level of inadequately managed waste has
259 been estimated by optimization techniques with the model (Figure 1) in a way to
260 achieve a stabilization of plastic stocks in the world ocean by 2020. The optimization
261 results show that the model variable "% Inadequately managed waste" used in the
262 BAU scenario (0.300168 = 30.0168%) 5 must be replaced by 0% (which is the level
263 achieved in developed countries such as France, Sweden, Australia, Japan, United-
264 States, etc.).
265

265

266 2.3. "Reducing by 50% inadequately managed wastes and cleanup effort" scenario: this
267 scenario simulates curative “end-of-pipe” solutions (e.g., cleanup projects to remove
268 plastics from ecosystems) combined to preventive “middle” solutions (e.g.,
269 developing landfill sealing to avoid plastic leakages, development of collective
270 collect of wastes in low- and middle income countries, installing plastic recycling
271 bins in the streets, etc.). This scenario has been designed in two steps:
272

272

<footnote n="4">⁴ Cleanup total effort = baseline cleanup effort (BAU) + optimized cleanup effort = 0.10% + 1.81% = 1.91% of plastic wastes in the ocean are removed.</footnote>

<footnote n="5">⁵ This value has been calculated in Jambeck et al. (2015)'s supplemental materials providing national data for the year 2010 for 192 countries (almost the entire world).</footnote>
273 • First, to simulate the preventive “middle” solution (e.g., developing landfill sealing to avoid plastic leakages), the level of inadequate waste management has been reduced by half, that is, the variable “% Inadequately managed waste” (Figure 1) in the BAU scenario (0.30017)<fnref n="6" /> has been replaced by 0.15008.

276
277
278 • Second, to simulate the curative “end-of-pipe” solution, after setting the variable
279
280 at the first step, we applied an optimization technique in Powersim to the variable
281 “cleanup rate” (Figure 1) in a way that the level of plastic in oceans in 2030 is
282
283 stabilized to the level of 2020. The optimization of the cleanup rate gives the
284 following results: cleanup rate = BAU effort + optimized cleanup effort = 0.10%
285 + 1.0387% = 1.1387% of the stock of plastic waste in the ocean is removed.

284
285
2.4. “Zero plastic litter only” scenario: this scenario simulates preventive “at-the-source-
286
287 of-the-problem” solutions (Table 1) such as awareness rising campaigns to reduce the
288 number of people who litter plastic wastes on the ground, to increase the number of
289 people that put plastic wastes in recycling bins as well as purchase glass bottles and
290 returnable bottles (PET or glass), to mitigate overconsumption behaviours in general
291 and specifically for plastic products, etc. The model shows that even reducing the
292 powersim variable “% Littered waste” (Figure 1) from 2% of plastic waste generation
293 (BAU scenario) to 0% (scenario 2.4) will not succeed to stabilize the level of plastic
294 in the oceans in 2030 to 2020’s level. The 2030’s level of plastic in the oceans will
295 exceed the level of 2020 by 15.4%.
296

295
296
2.5. Combined strategy 2.1 + 2.3 + 2.4: this scenario combines scenarios 2.1, a part of
297
298 2.3 and 2.4, which means the following values are entered in Powersim: baseline
299 cleanup effort (BAU) + optimized cleanup effort = 0.10% + 1.81% = 1.91% (scenario
300 2.1); "% Inadequately managed waste" = 15.008% (environmental measure from
301 scenario 2.3); the % Littered waste = 0% (scenario 2.4).

301
302
303 The third set of scenarios considers cleanup-effort-only scenarios similarly to scenario
304 2.1 except that they are designed to reduce the total plastic stock in the oceans below the
305 level of 2010:
306

305
306
3.1. Cleanup scenario for 25% reduction: this scenario is designed the same way
307
308 scenario 2.1 except that the optimization process is run to achieve in 2030 a level of
309 plastic waste in the ocean that is below 2010’s level by 25%. The optimization results

<footnote n="6">⁶ 0.30017 means that 30.017% of the plastic waste generation in 2010 is inadequately managed (this is the value in 2010 taken from Jambeck’s supplemental materials).</footnote>
273 • First, to simulate the preventive “middle” solution (e.g., developing landfill sealing to avoid plastic leakages), the level of inadequate waste management has been reduced by half, that is, the variable “% Inadequately managed waste” (Figure 1) in the BAU scenario (0.30017)<fnref n="6" /> has been replaced by 0.15008.

276
277
278 • Second, to simulate the curative “end-of-pipe” solution, after setting the variable at the first step, we applied an optimization technique in Powersim to the variable “cleanup rate” (Figure 1) in a way that the level of plastic in oceans in 2030 is stabilized to the level of 2020. The optimization of the cleanup rate gives the following results: cleanup rate = BAU effort + optimized cleanup effort = 0.10% + 1.0387% = 1.1387% of the stock of plastic waste in the ocean is removed.

284
285
286
287
288
289
290
291
292
293
294
295
2.4. “Zero plastic litter only” scenario: this scenario simulates preventive “at-the-source-of-the-problem” solutions (Table 1) such as awareness rising campaigns to reduce the number of people who litter plastic wastes on the ground, to increase the number of people that put plastic wastes in recycling bins as well as purchase glass bottles and returnable bottles (PET or glass), to mitigate overconsumption behaviours in general and specifically for plastic products, etc. The model shows that even reducing the powersim variable “% Littered waste” (Figure 1) from 2% of plastic waste generation (BAU scenario) to 0% (scenario 2.4) will not succeed to stabilize the level of plastic in the oceans in 2030 to 2020’s level. The 2030’s level of plastic in the oceans will exceed the level of 2020 by 15.4%.

296
297
298
299
300
301
3.1. *Combined strategy 2.1 + 2.3 + 2.4:* this scenario combines scenarios 2.1, a part of 2.3 and 2.4, which means the following values are entered in Powersim: baseline cleanup effort (BAU) + optimized cleanup effort = 0.10% + 1.81% = 1.91% (scenario 2.1); “% Inadequately managed waste” = 15.008% (environmental measure from scenario 2.3); the % Littered waste = 0% (scenario 2.4).

302
303
304
305
The third set of scenarios considers cleanup-effort-only scenarios similarly to scenario 2.1 except that they are designed to reduce the total plastic stock in the oceans below the level of 2010:

306
307
308
3.1. *Cleanup scenario for 25% reduction:* this scenario is designed the same way scenario 2.1 except that the optimization process is run to achieve in 2030 a level of plastic waste in the ocean that is below 2010’s level by 25%. The optimization results

<footnote n="6">⁶ 0.30017 means that 30.017% of the plastic waste generation in 2010 is inadequately managed (this is the value in 2010 taken from Jambeck’s supplemental materials).</footnote>
from the model show that to achieve that level, 7.18% of plastic wastes in the ocean must be cleaned up<fnref n="7" />.

311

312 **3.2. Cleanup scenario for 50% reduction:** this scenario is designed the same way
313 scenario 2.1 except that the optimization process is run to achieve in 2030 a level of
314 plastic waste in the ocean that is below 2010's level by 50%. The optimization results
315 from the model show that to achieve that level, 11.89% of plastic wastes in the ocean
316 must be cleaned up<fnref n="8" />.

317

318 [... Other sets of scenarios will be simulated in a further version of this working paper].

319

320 The seventh set of scenarios covers some of the environmental measures proposed by
321 Jambeck et al. (2015, p. 770) in order to assess their potential global impacts on plastics
322 in the ocean:

323

324 **7.1. Reducing by 50% inadequately managed wastes by 2025 in the 20 top countries ranked by mass of mismanaged plastic waste:** it simulates a preventive “middle”
325 solution similar to the one of scenario 2.3 except that in scenario 7.1, inadequately
326 managed wastes<fnref n="9" /> are reduced by half in a limited amount of countries in order to ease
327 the implementation of such an ambitious measure. Scenario 7.1 is thus a preventive
328 “middle” solution since only landfilling techniques are improved (see Table 1 above).
329 It is not a preventive “at-the-source” solution since awareness rising campaigns are
330 not implemented to reduce the number of people littering plastics on the ground. We
331 made this assumption for this scenario because it is difficult (but probably not
332 impossible) to convince all people in every country to never litter plastic products in
333 the street or on the beaches. Thereby, we calculated in the Excel file from Jambeck et
334 al. supplemental material that if the top 20 countries had an “Inadequately managed
335 plastic waste [kg/day]” reduced by 50%, the “% Inadequately managed waste” would
336 be 0.17265 instead of 0.300168 (0.17265 = Inadequately managed plastic waste
337 [kg/day] / Plastic waste generation [kg/day] = 47 077 041.9 kg/day / 272 676 238.6
338 kg/day). So, to simulate scenario 7.1, we modified in Powersim the parameter
339 “Baseline % inadequately mismanaged waste” and replace the value of 0.300168 by
340 0.17265 (starting from 2020, assuming there is a delay between the time the measure
341 is designed and the time it is effectively implemented and result in concrete impacts).
342
343

343

<footnote n="7">⁷ Cleanup total effort = baseline cleanup effort (BAU) + optimized cleanup effort = 0.10% + 7.08% = 7.18% of plastic wastes in the ocean are removed.</footnote>

<footnote n="8">⁸ Cleanup total effort = baseline cleanup effort (BAU) + optimized cleanup effort = 0.10% + 11.79% = 11.89% of plastic wastes in the ocean are removed.</footnote>

<footnote n="9">⁹ Jambeck et al. (2015, p. 770) use the term “waste mismanagement improvements” without specifying what kind of action it encompasses. Thus, we consider in scenario 7.1 that mismanagement improvements address only inadequately managed waste, not littering.</footnote>
from the model show that to achieve that level, 7.18% of plastic wastes in the ocean must be cleaned up<fnref n="7" />.

311

312 **3.2. Cleanup scenario for 50% reduction:** this scenario is designed the same way
313 scenario 2.1 except that the optimization process is run to achieve in 2030 a level of
314 plastic waste in the ocean that is below 2010's level by 50%. The optimization results
315 from the model show that to achieve that level, 11.89% of plastic wastes in the ocean
316 must be cleaned up<fnref n="8" />.

317

318 [... Other sets of scenarios will be simulated in a further version of this working paper].

319

320 The seventh set of scenarios covers some of the environmental measures proposed by
321 Jambeck et al. (2015, p. 770) in order to assess their potential global impacts on plastics
322 in the ocean:

323

324 **7.1. Reducing by 50% inadequately managed wastes by 2025 in the 20 top countries ranked by mass of mismanaged plastic waste:** it simulates a preventive “middle”
325 solution similar to the one of scenario 2.3 except that in scenario 7.1, inadequately
326 managed wastes<fnref n="9" /> are reduced by half in a limited amount of countries in order to ease
327 the implementation of such an ambitious measure. Scenario 7.1 is thus a preventive
328 “middle” solution since only landfilling techniques are improved (see Table 1 above).
329 It is not a preventive “at-the-source” solution since awareness rising campaigns are
330 not implemented to reduce the number of people littering plastics on the ground. We
331 made this assumption for this scenario because it is difficult (but probably not
332 impossible) to convince all people in every country to never litter plastic products in
333 the street or on the beaches. Thereby, we calculated in the Excel file from Jambeck et
334 al. supplemental material that if the top 20 countries had an “Inadequately managed
335 plastic waste [kg/day]” reduced by 50%, the “% Inadequately managed waste” would
336 be 0.17265 instead of 0.300168 (0.17265 = Inadequately managed plastic waste
337 [kg/day] / Plastic waste generation [kg/day] = 47 077 041.9 kg/day / 272 676 238.6
338 kg/day). So, to simulate scenario 7.1, we modified in Powersim the parameter
339 “Baseline % inadequately mismanaged waste” and replace the value of 0.300168 by
340 0.17265 (starting from 2020, assuming there is a delay between the time the measure
341 is designed and the time it is effectively implemented and result in concrete impacts).
342
343

343

<footnote n="7">⁷ Cleanup total effort = baseline cleanup effort (BAU) + optimized cleanup effort = 0.10% + 7.08% = 7.18% of plastic wastes in the ocean are removed.</footnote>

<footnote n="8">⁸ Cleanup total effort = baseline cleanup effort (BAU) + optimized cleanup effort = 0.10% + 11.79% = 11.89% of plastic wastes in the ocean are removed.</footnote>

<footnote n="9">⁹ Jambeck et al. (2015, p. 770) use the term “waste mismanagement improvements” without specifying what kind of action it encompasses. Thus, we consider in scenario 7.1 that mismanagement improvements address only inadequately managed waste, not littering.</footnote>
7.2. *Capping per capita waste generation to 1.2 kg/day*<fnref n="10" /> by 2025 and capping the percentage of plastics in waste stream at 11%<fnref n="11" />: it simulates preventive “at-the-source” solutions (Table 1) based on changes in consumer behaviours. This strategy would mainly target higher-income countries and might require smaller global investments (most of the poor and emerging countries emit an amount of waste per person and per day lower than 1.2 kg whereas rich countries often exceed this amount). Several measures would be needed to motivate consumers to reduce their plastic waste generation: awareness rising campaigns on the social and environmental problems caused by the current consumption society, taxes on plastic products to reduce plastic consumption, recycling systems, systems of returnable plastic or glass bottles, online systems designed to help particulars to share, sell, exchange, borrow or rent second-hand products (including plastic products), etc. This scenario is calculated as follows:

* Calculation for capping the per capita waste generation to 1.2 kg/person/day:
  We calculated in the Excel file from Jambeck et al. supplemental material that if the countries with “waste generation rate” above the world average (1.2 kg/person/day) would reduce it to 1.2 kg/person/day, the world average “waste generation rate” would be 0.92 kg/person/day. So, we simulated this cap by modifying in Powersim the variable “waste generation rate” and replace 1.2 by 0.92 kg/person/day.

* Calculation for capping plastics in the waste stream at to 11%:
  We calculated in the Excel file from Jambeck et al. supplemental material that if the countries with “% Plastic in waste stream” higher than the world average (11.09%) would reduce it to 11.09%, the world average “% Plastic in waste stream” would be 9.88%. So, we simulated this cap by modifying in Powersim the variable “% Plastic in waste stream” and replace 11.09% by 9.88%.

7.3. *Reducing by 100% inadequately managed waste by 2025 in the 10 top countries and capping plastics in waste stream at 11%:* in this scenario, full waste management is achieved (that is, 0% mismanaged waste) in the 10 top-ranked countries ranked in Jambeck et al. (2015, p. 769) by mass of mismanaged plastic waste (poor and emerging countries) and plastic waste generation is capped at 11% as described in scenario 7.2 (rich countries). It simulates a preventive “middle” solution and an “end-of-pipe” one based on both, plastic waste management and changes in consumer behaviors. This scenario is calculated as follows:

<footnote n="10">¹⁰ 1.2 kg/day is the world average in 2010. In that year, 91 coastal countries exceeded that amount.</footnote>

<footnote n="11">¹¹ 11% is the 192-country average in 2010.</footnote>
7.2. *Capping per capita waste generation to 1.2 kg/day*<fnref n="10" /> by 2025 and capping the percentage of plastics in waste stream at 11%<fnref n="11" />: it simulates preventive “at-the-source” solutions (Table 1) based on changes in consumer behaviours. This strategy would mainly target higher-income countries and might require smaller global investments (most of the poor and emerging countries emit an amount of waste per person and per day lower than 1.2 kg whereas rich countries often exceed this amount). Several measures would be needed to motivate consumers to reduce their plastic waste generation: awareness rising campaigns on the social and environmental problems caused by the current consumption society, taxes on plastic products to reduce plastic consumption, recycling systems, systems of returnable plastic or glass bottles, online systems designed to help particulars to share, sell, exchange, borrow or rent second-hand products (including plastic products), etc. This scenario is calculated as follows:

* Calculation for capping the per capita waste generation to 1.2 kg/person/day:
  We calculated in the Excel file from Jambeck et al. supplemental material that if the countries with “waste generation rate” above the world average (1.2 kg/person/day) would reduce it to 1.2 kg/person/day, the world average “waste generation rate” would be 0.92 kg/person/day. So, we simulated this cap by modifying in Powersim the variable “waste generation rate” and replace 1.2 by 0.92 kg/person/day.

* Calculation for capping plastics in the waste stream at to 11%:
  We calculated in the Excel file from Jambeck et al. supplemental material that if the countries with “% Plastic in waste stream” higher than the world average (11.09%) would reduce it to 11.09%, the world average “% Plastic in waste stream” would be 9.88%. So, we simulated this cap by modifying in Powersim the variable “% Plastic in waste stream” and replace 11.09% by 9.88%.

7.3. *Reducing by 100% inadequately managed waste by 2025 in the 10 top countries and capping plastics in waste stream at 11%:* in this scenario, full waste management is achieved (that is, 0% mismanaged waste) in the 10 top-ranked countries ranked in Jambeck et al. (2015, p. 769) by mass of mismanaged plastic waste (poor and emerging countries) and plastic waste generation is capped at 11% as described in scenario 7.2 (rich countries). It simulates a preventive “middle” solution and an “end-of-pipe” one based on both, plastic waste management and changes in consumer behaviors. This scenario is calculated as follows:

<footnote n="10">¹⁰ 1.2 kg/day is the world average in 2010. In that year, 91 coastal countries exceeded that amount.</footnote>

<footnote n="11">¹¹ 11% is the 192-country average in 2010.</footnote>
382 • Calculation to reduce waste mismanagement to 0 % in the top 10 countries:
383 For the same reason as in scenario 7.1, we assume that mismanagement
384 improvements devised by Jambeck et al. address only inadequately managed
385 waste, not littering. This measure is thus a preventive “middle” solution since only
386 landfilling techniques are improved (see Table 1 above). It is not a preventive “at-
387 the-source” solution since awareness rising campaigns are not implemented to
388 reduce the number of people littering plastics on the ground. We calculated in the
389 Excel file from Jambeck et al. supplemental material that if the top 10 countries
390 had an “Inadequately managed plastic waste [kg/day]” reduced to zero percents,
391 the “% Inadequately managed waste” at the global scale would be 8.56% instead
392 of 30.017% (8.56% = 100 * Inadequately managed plastic waste [kg/day] / Plastic
393 waste generation [kg/day] = 100* 23 341 306.0 kg/day / 272676238.6 kg/day).
394 Thus, we simulated this by modifying in Powersim the variable “Baseline %
395 inadequately mismanaged waste” and replace the value of 0.300168 by 0.085601.
396

397 • Calculation for capping plastics in the waste stream at to 11%:
398 Calculations are the same as in the 11% capping described in scenario 7.2
399

400 7.4. Combined strategy: 7.1 + 7.2. + 2.1: this scenario combines scenarios 7.1, 7.2 and
401 2.1, which means it simulates a preventive “middle” solution, a preventive “at-the-
402 source” solution and a curative “end-of-pipe” solution. This scenario consists in
403 entering the following values in Powersim: “Baseline % inadequately mismanaged
404 waste” = 0.17265 (scenario 7.1), “waste generation rate” = 0.92 kg/person/day and
405 “% Plastic in waste stream” = 9.88% (scenario 7.2), cleanup total effort = baseline
406 cleanup effort (BAU) + cleanup scenario effort = 0.10% + 1.81% = 1.91%.

407
408 Model description

409
410 We adopted System dynamics (SD) (Sterman, 2000) for the design of our model to
411 capture the dynamics of marine plastic wastes from their origin (their generation on land)
412 to their fate (when they enter into the ocean). System dynamics is suitable because it
413 describes the complex dynamics of a system with a specific emphasis on flows and
414 stocks. Marine plastic wastes involve complex dynamics of social-ecological systems
415 where stock is a key variable. Indeed, marine plastic wastes flow from the land to the
416 ocean where they accumulate generating a stock of floating plastics in the water and
417 deposited plastic on the seabed. Figure 1 shows the stock and flow diagram of the system
418 dynamics model for marine plastic waste.
419
382 • Calculation to reduce waste mismanagement to 0 % in the top 10 countries:
383 For the same reason as in scenario 7.1, we assume that mismanagement
384 improvements devised by Jambeck et al. address only inadequately managed
385 waste, not littering. This measure is thus a preventive “middle” solution since only
386 landfilling techniques are improved (see Table 1 above). It is not a preventive “at-
387 the-source” solution since awareness rising campaigns are not implemented to
388 reduce the number of people littering plastics on the ground. We calculated in the
389 Excel file from Jambeck et al. supplemental material that if the top 10 countries
390 had an “Inadequately managed plastic waste [kg/day]” reduced to zero percents,
391 the “% Inadequately managed waste” at the global scale would be 8.56% instead
392 of 30.017% (8.56% = 100 * Inadequately managed plastic waste [kg/day] / Plastic
393 waste generation [kg/day] = 100* 23 341 306.0 kg/day / 272676238.6 kg/day).
394 Thus, we simulated this by modifying in Powersim the variable “Baseline %
395 inadequately mismanaged waste” and replace the value of 0.300168 by 0.085601.
396

397 • Calculation for capping plastics in the waste stream at to 11%:
398 Calculations are the same as in the 11% capping described in scenario 7.2
399

400 7.4. Combined strategy: 7.1 + 7.2. + 2.1: this scenario combines scenarios 7.1, 7.2 and
401 2.1, which means it simulates a preventive “middle” solution, a preventive “at-the-
402 source” solution and a curative “end-of-pipe” solution. This scenario consists in
403 entering the following values in Powersim: “Baseline % inadequately mismanaged
404 waste” = 0.17265 (scenario 7.1), “waste generation rate” = 0.92 kg/person/day and
405 “% Plastic in waste stream” = 9.88% (scenario 7.2), cleanup total effort = baseline
406 cleanup effort (BAU) + cleanup scenario effort = 0.10% + 1.81% = 1.91%.

407
408 Model description

409
410 We adopted System dynamics (SD) (Sterman, 2000) for the design of our model to
411 capture the dynamics of marine plastic wastes from their origin (their generation on land)
412 to their fate (when they enter into the ocean). System dynamics is suitable because it
413 describes the complex dynamics of a system with a specific emphasis on flows and
414 stocks. Marine plastic wastes involve complex dynamics of social-ecological systems
415 where stock is a key variable. Indeed, marine plastic wastes flow from the land to the
416 ocean where they accumulate generating a stock of floating plastics in the water and
417 deposited plastic on the seabed. Figure 1 shows the stock and flow diagram of the system
418 dynamics model for marine plastic waste.
419
<figure><img src="image_2.png" /><figcaption>Figure 1. Stock and flow diagram of the system dynamics model for marine plastic waste (designed in Powersim).</figcaption></figure>

420

421

422

423
<figure><img src="image_2.png" /><figcaption>Figure 1. Stock and flow diagram of the system dynamics model for marine plastic waste (designed in Powersim).</figcaption></figure>

420

421

422

423
424 There are two critical stocks in the model: Coastal population and Plastic waste in the
425 ocean (the full model in Powersim format can be provided upon request). The dynamics
426 of coastal population is defined as follows:

$$
\begin{align}
427 \quad \text{Coastal population}^t &= \nonumber \\
428 \quad \int_{t_0}^{t_n} (\text{Changes in coastal population}^t) dt &+ \text{Coastal population}^{t_0} \tag{1} \\
429 \quad & \nonumber
\end{align}
$$

430
431 Following Jambeck et al. (2015), the model focuses on the dynamics of coastal
432 population. Changes in coastal population are assumed to be the same as changes in the
433 world population by using the prediction of population by the United Nations (The
434 United Nations, n.d.).

435 Waste generation is proportional to coastal population and is defined as follows:

$$
\begin{align*}
436 \quad \text{Waste generation}^t &= \text{Waste generation rate} \times \text{Coastal population} \times 365 \text{ days} \\
437 \quad & \tag{2}
\end{align*}
$$

439
440 Plastic waste in the ocean is defined as:

$$
\begin{align*}
441 \quad \text{Plastic waste in the ocean}^t &= \\
442 \quad \int_{t_0}^{t_n} (\text{Entering rate}^t - \text{Cleanup rate}^t) dt &+ \text{Plastic waste in the ocean}^{t_0} \tag{3}
\end{align*}
$$

444
445 The model assumes that plastic waste in the ocean does not decline unless it is cleaned up
446 by people. It does not disappear but stays somewhere in the ocean. Entering rate is
447 determined by mismanaged plastic waste and fractional entering rate (Figure 1). In
448 addition to clean up rate, there are primarily three variables in which environmental
449 policies can intervene to reduce the entering rate: Waste generation rate, % plastic waste
450 in stream, and % Inadequately managed waste (Figure 1). The model allows
451 environmental targets to be set for each of these three variables. The speed required to
452 reach the environmental targets can be modified by changing the variable adjustment
453 time in the model.
454

455 **Results and discussion**

456
457 The first set of scenarios is made of the BAU scenario, which is used as a reference
458 aimed at comparing all other scenarios. This helps us to assess how many environmental
459 measures (scenarios 2 to 7) could help to improve the marine ecosystem compared to a
460 situation without any environmental measures (BAU) other than those already existing in
461 2010.

461
424 There are two critical stocks in the model: Coastal population and Plastic waste in the
425 ocean (the full model in Powersim format can be provided upon request). The dynamics
426 of coastal population is defined as follows:

$$
\begin{align}
427 \quad \text{Coastal population}^t &= \nonumber \\
428 \quad \int_{t_0}^{t_n} (\text{Changes in coastal population}^t) dt &+ \text{Coastal population}^{t_0} \tag{1} \\
429 \quad \text{Following Jambeck et al. (2015), the model focuses on the dynamics of coastal} \nonumber \\
430 \quad \text{population. Changes in coastal population are assumed to be the same as changes in the} \nonumber \\
431 \quad \text{world population by using the prediction of population by the United Nations (The} \nonumber \\
432 \quad \text{United Nations, n.d.).} \nonumber \\
433 \quad \text{Waste generation is proportional to coastal population and is defined as follows:} \nonumber \\
434 \quad \text{Waste generation}^t = \text{Waste generation rate} \times \text{Coastal population} \times 365 \text{ days} \nonumber \\
435 \quad \text{Plastic waste in the ocean is defined as:} \nonumber \\
436 \quad \text{Plastic waste in the ocean}^t &= \nonumber \\
437 \quad \int_{t_0}^{t_n} (\text{Entering rate}^t - \text{Cleanup rate}^t) dt &+ \text{Plastic waste in the ocean}^{t_0} \tag{2} \\
438 \quad \text{The model assumes that plastic waste in the ocean does not decline unless it is cleaned up} \nonumber \\
439 \quad \text{by people. It does not disappear but stays somewhere in the ocean. Entering rate is} \nonumber \\
440 \quad \text{determined by mismanaged plastic waste and fractional entering rate (Figure 1). In} \nonumber \\
441 \quad \text{addition to clean up rate, there are primarily three variables in which environmental} \nonumber \\
442 \quad \text{policies can intervene to reduce the entering rate: Waste generation rate, % plastic waste} \nonumber \\
443 \quad \text{in stream, and % Inadequately managed waste (Figure 1). The model allows} \nonumber \\
444 \quad \text{environmental targets to be set for each of these three variables. The speed required to} \nonumber \\
445 \quad \text{reach the environmental targets can be modified by changing the variable adjustment} \nonumber \\
446 \quad \text{time in the model.} \nonumber \\
447 \quad \textbf{Results and discussion} \nonumber \\
448 \quad The first set of scenarios is made of the BAU scenario, which is used as a reference \nonumber \\
449 \quad aimed at comparing all other scenarios. This helps us to assess how many environmental \nonumber \\
450 \quad measures (scenarios 2 to 7) could help to improve the marine ecosystem compared to a \nonumber \\
451 \quad situation without any environmental measures (BAU) other than those already existing in \nonumber \\
452 \quad 2010. \nonumber \\
453 \quad \nonumber \\
454 \quad \nonumber \\
455 \quad \nonumber \\
456 \quad \nonumber \\
457 \quad \nonumber \\
458 \quad \nonumber \\
459 \quad \nonumber \\
460 \quad \nonumber \\
461 \quad \nonumber
\end{align}
$$

431 Following Jambeck et al. (2015), the model focuses on the dynamics of coastal
432 population. Changes in coastal population are assumed to be the same as changes in the
433 world population by using the prediction of population by the United Nations (The
434 United Nations, n.d.).

435 Waste generation is proportional to coastal population and is defined as follows:

$$
\begin{equation}
\begin{split}
436 \quad \text{Waste generation}^t &= \text{Waste generation rate} \times \text{Coastal population} \times 365 \text{ days} \\
437 \quad & \qquad (2) \\
438 \quad \text{Plastic waste in the ocean is defined as:} \\
439 \quad \text{Plastic waste in the ocean}^t &=
\end{split}
\end{equation}
$$

440 Plastic waste in the ocean is defined as:

$$
\begin{equation}
\begin{split}
441 \quad \text{Plastic waste in the ocean}^t &= \\
442 \quad \int_{t_0}^{t_n} (\text{Entering rate}^t - \text{Cleanup rate}^t) dt &+ \text{Plastic waste in the ocean}^{t_0} \quad (3)
\end{split}
\end{equation}
$$

445 The model assumes that plastic waste in the ocean does not decline unless it is cleaned up
446 by people. It does not disappear but stays somewhere in the ocean. Entering rate is
447 determined by mismanaged plastic waste and fractional entering rate (Figure 1). In
448 addition to clean up rate, there are primarily three variables in which environmental
449 policies can intervene to reduce the entering rate: Waste generation rate, % plastic waste
450 in stream, and % Inadequately managed waste (Figure 1). The model allows
451 environmental targets to be set for each of these three variables. The speed required to
452 reach the environmental targets can be modified by changing the variable adjustment
453 time in the model.
454
455
456
457
458
459
460
461

454
455
**Results and discussion**
456

456 The first set of scenarios is made of the BAU scenario, which is used as a reference
457 aimed at comparing all other scenarios. This helps us to assess how many environmental
458 measures (scenarios 2 to 7) could help to improve the marine ecosystem compared to a
459 situation without any environmental measures (BAU) other than those already existing in
460 2010.
461

461
As expected, without any additional environmental measures (BAU scenario), the stock of plastic wastes accumulated in the ocean at the global scale will be the highest in 2030 reaching 374 million tons (Figure 2). Inciting citizens to stop littering plastic products could theoretically help. However, the model results suggest that such an environmental measure would be far to be enough. If citizens would change their behavior and succeed to never litter plastics on the ground (either because of a spontaneous change of mentalities or thanks to awareness rising campaigns from public authorities or environmental associations), the cumulated stock of plastic waste in the ocean in 2030 would reach an amount of 367 million tons in 2030 (scenario 2.4). This is slightly below the BAU scenario but not much. The amount of plastic waste entering the ocean annually would keep growing quite fast any way. This suggests that focusing all efforts on plastic littering by citizen will never help to solve the plastic problem. Their environmental responsibility is quite limited. Solutions should probably be developed in a collective thinking, not an individual one if we want a significant positive impact to be observed in terms of plastic flow abatement. Results from scenario 2.2 simulations strengthen this assumption. In that scenario, investments are made in every country in all landfills that are inadequately managed to reduce plastic leakages by wind or rains. Plastic recycling bins are also installed in the streets to spur citizen to recycle plastic products, and collective collect of wastes are installed in low- and middle-income countries in all cities and villages where it was lacking. This scenario simulates a future where the world would have achieved zero inadequately managed waste. If such an idealistic future would happen, the model suggests that the amount of cumulated plastic waste in the ocean would stabilize by 2024 at a level of 329 million tons (i.e., 12% below the BAU scenario). Scenarios 2.3 and 2.1 might be more realistic and succeed to stabilize the ocean cumulated plastic stock in 2030 at the level of 2020, that is, 321 million tons. To achieve this environmental target, ocean cleanup must be implemented in addition to improving inadequately managed waste systems. A feasibility study could help to assess if cleaning of 1.14% (scenario 2.3) to 1.91% (scenario 2.1) of ocean plastic waste stock every year is technically and financially achievable. Probably the feasibility study written by Boyan Slat's team (Slat, 2014) could help to answer that question.

However, for more stringent environmental targets such as for example, recovering the situation of 2015, additional measures must be undertaken. Scenario 2.5 (Figure 2) shows that a combining strategy is likelier to achieve that goal. Scenario 2.5 succeeds to reduce plastic wastes in the world ocean in 2030 to a level corresponding to 2015' level (294 million tons), which is 21.2% lower than the BAU scenario. This suggests that combining different kinds of environmental measures across the social-ecological system, downstream and upstream of the social-ecological system ("end-of-pipe" and "at-the-source" solutions) as well as upstream and downstream of the plastic contamination
As expected, without any additional environmental measures (BAU scenario), the stock of plastic wastes accumulated in the ocean at the global scale will be the highest in 2030 reaching 374 million tons (Figure 2). Inciting citizens to stop littering plastic products could theoretically help. However, the model results suggest that such an environmental measure would be far to be enough. If citizens would change their behavior and succeed to never litter plastics on the ground (either because of a spontaneous change of mentalities or thanks to awareness rising campaigns from public authorities or environmental associations), the cumulated stock of plastic waste in the ocean in 2030 would reach an amount of 367 million tons in 2030 (scenario 2.4). This is slightly below the BAU scenario but not much. The amount of plastic waste entering the ocean annually would keep growing quite fast any way. This suggests that focusing all efforts on plastic littering by citizen will never help to solve the plastic problem. Their environmental responsibility is quite limited. Solutions should probably be developed in a collective thinking, not an individual one if we want a significant positive impact to be observed in terms of plastic flow abatement. Results from scenario 2.2 simulations strengthen this assumption. In that scenario, investments are made in every country in all landfills that are inadequately managed to reduce plastic leakages by wind or rains. Plastic recycling bins are also installed in the streets to spur citizen to recycle plastic products, and collective collect of wastes are installed in low- and middle-income countries in all cities and villages where it was lacking. This scenario simulates a future where the world would have achieved zero inadequately managed waste. If such an idealistic future would happen, the model suggests that the amount of cumulated plastic waste in the ocean would stabilize by 2024 at a level of 329 million tons (i.e., 12% below the BAU scenario). Scenarios 2.3 and 2.1 might be more realistic and succeed to stabilize the ocean cumulated plastic stock in 2030 at the level of 2020, that is, 321 million tons. To achieve this environmental target, ocean cleanup must be implemented in addition to improving inadequately managed waste systems. A feasibility study could help to assess if cleaning of 1.14% (scenario 2.3) to 1.91% (scenario 2.1) of ocean plastic waste stock every year is technically and financially achievable. Probably the feasibility study written by Boyan Slat's team (Slat, 2014) could help to answer that question.

However, for more stringent environmental targets such as for example, recovering the situation of 2015, additional measures must be undertaken. Scenario 2.5 (Figure 2) shows that a combining strategy is likelier to achieve that goal. Scenario 2.5 succeeds to reduce plastic wastes in the world ocean in 2030 to a level corresponding to 2015' level (294 million tons), which is 21.2% lower than the BAU scenario. This suggests that combining different kinds of environmental measures across the social-ecological system, downstream and upstream of the social-ecological system ("end-of-pipe" and "at-the-source" solutions) as well as upstream and downstream of the plastic contamination
causal chain (“curative” and “preventive” solutions) is more successful than scenarios where only one type of environmental measure is undertaken.

503

<figure><img src="image_3.png" /></figure>

504

<caption>Figure 2. Scenarios with environmental efforts designed to stabilize the amount of plastic wastes in the ocean at 2020's level by 2030 (floating plastics and deposited on the seabed).</caption>

507

Scenarios 7.1 to 7.3, inspired by Jambeck et al. (2015, p. 770), are interesting because they are intended to be more realistic and achievable. For example, scenario 7.1 proposes to improve only 50% of the inadequately managed waste, not 100%. And this is to be made in only 20 countries, not the entire world. The idea is to obtain a marine ecological improvement with the minimum effort required in order to make plastic solutions more feasible and likelier to happen. However, scenario 7.1 shows poor results in terms of ecological impact. The amount of cumulated plastic waste in the ocean achieves a level of 355 million tons in 2030 (Figure 3), i.e. barely 5.1% below the BAU level. Scenarios 7.2 and 7.3 succeed to stabilize the stock of cumulated plastic wastes in the ocean by 2022 at 327 million tons (Figure 3), i.e., 12% below the BAU in 2030.

518

The combined strategy implemented in Scenario 7.3 – that is, reducing by 100% inadequately managed waste by 2025 in the 10 top countries and capping plastics in waste stream at 11% – could be appreciated by stakeholders in terms of equity as well as social and political acceptability because poor, emerging and rich countries would participate to plastic solutions on the basis of the principle of common but differentiated responsibilities. That is, they would all bear a common environmental responsibility but their contribution to plastic solutions would be differentiated according to their level of responsibility and to their affordability (i.e., their ability to pay for plastic solutions). This makes the implementation of this scenario likelier. However, capping plastics in waste stream at 11% would require changes in consumer behaviours. This is not easy to achieve
causal chain (“curative” and “preventive” solutions) is more successful than scenarios where only one type of environmental measure is undertaken.

503

<figure><img src="image_3.png" /></figure>

504

<caption>Figure 2. Scenarios with environmental efforts designed to stabilize the amount of plastic wastes in the ocean at 2020's level by 2030 (floating plastics and deposited on the seabed).</caption>

505

Scenarios 7.1 to 7.3, inspired by Jambeck et al. (2015, p. 770), are interesting because they are intended to be more realistic and achievable. For example, scenario 7.1 proposes to improve only 50% of the inadequately managed waste, not 100%. And this is to be made in only 20 countries, not the entire world. The idea is to obtain a marine ecological improvement with the minimum effort required in order to make plastic solutions more feasible and likelier to happen. However, scenario 7.1 shows poor results in terms of ecological impact. The amount of cumulated plastic waste in the ocean achieves a level of 355 million tons in 2030 (Figure 3), i.e. barely 5.1% below the BAU level. Scenarios 7.2 and 7.3 succeed to stabilize the stock of cumulated plastic wastes in the ocean by 2022 at 327 million tons (Figure 3), i.e., 12% below the BAU in 2030.

507

The combined strategy implemented in Scenario 7.3 – that is, reducing by 100% inadequately managed waste by 2025 in the 10 top countries and capping plastics in waste stream at 11% – could be appreciated by stakeholders in terms of equity as well as social and political acceptability because poor, emerging and rich countries would participate to plastic solutions on the basis of the principle of common but differentiated responsibilities. That is, they would all bear a common environmental responsibility but their contribution to plastic solutions would be differentiated according to their level of responsibility and to their affordability (i.e., their ability to pay for plastic solutions). This makes the implementation of this scenario likelier. However, capping plastics in waste stream at 11% would require changes in consumer behaviours. This is not easy to achieve
529 unless awareness rising campaigns are designed appropriately to spur cooperation in the
530 mind of consumers and reduce individualistic behaviours. Peculiar designs are required
531 for that – read, inter alia, Benkler (2011) and Ostrom (2010c) – otherwise the change in
532 mentalities and behavior is extremely difficult to achieve.

533
534 Scenario 7.4. is another highly combined strategy since it merges scenarios 7.1, 7.2 and
535 2.1, which involves three categories of solutions: a preventive “middle” solution
536 (scenario 7.1), a preventive “at-the-source” solution (scenario 7.2) and a curative “end-of-
537 pipe” solution (scenario 7.3). Scenario 7.4 follows thus a similar approach as scenario 2.5
538 but it performs better. Figure 3 shows that scenario 7.5 succeed to achieve a level of
539 cumulated plastic waste in the ocean of 277 million tons by 2030, i.e, 26% below the
540 BAU. This means recovering the situation of the year 2011. This strengthen our
541 assumption that combining different kinds of environmental measures downstream and
542 upstream the social-ecological system (“end-of-pipe” and “at-the-source” solutions) as
543 well as upstream and downstream of the plastic contamination causal chain (“curative”
544 and “preventive” solutions) is more successful than scenarios where only one type of
545 environmental measure is undertaken. Keeping on scenario 7.4 up to 2069 would allow
546 the amount of cumulated plastic waste in the ocean to achieve half the value of 2010, i.e.
547 137 million tons. Given the emergency of the situation for marine biodiversity, it might
548 be interesting to test scenarios that are quicker to reduce by 50% the level of 2010. Figure
549 4 is a first attempt in that sense. It shows that cleanup effort only (scenario 3.2) could
550 achieve that goal but would require removing from the ocean 11.89% of plastic every
551 year starting from 2020 up to 2030. Assuming that current levels of plastic annual
552 removal in the ocean is 0.10% (this is a first preliminary assumption that will be
553 improved later), this would require a technological progress 119 times higher than
554 nowadays. Scenario 3.1 is an intent to simulate quite an ambitious ecological target and at
555 the same time a bit more realistic. It shows that to reducing 2010’s level by 25% would
556 require removing from the ocean 7.18% of plastic every year starting from 2020 up to
557 2030 this would require to multiply 72 times current efforts in ocean cleanup
558 technologies. In further versions of this paper, we will assess if such a technological
559 advance is feasible.

560
529 unless awareness rising campaigns are designed appropriately to spur cooperation in the
530 mind of consumers and reduce individualistic behaviours. Peculiar designs are required
531 for that – read, inter alia, Benkler (2011) and Ostrom (2010c) – otherwise the change in
532 mentalities and behavior is extremely difficult to achieve.

533
534 Scenario 7.4. is another highly combined strategy since it merges scenarios 7.1, 7.2 and
535 2.1, which involves three categories of solutions: a preventive “middle” solution
536 (scenario 7.1), a preventive “at-the-source” solution (scenario 7.2) and a curative “end-of-
537 pipe” solution (scenario 7.3). Scenario 7.4 follows thus a similar approach as scenario 2.5
538 but it performs better. Figure 3 shows that scenario 7.5 succeed to achieve a level of
539 cumulated plastic waste in the ocean of 277 million tons by 2030, i.e, 26% below the
540 BAU. This means recovering the situation of the year 2011. This strengthen our
541 assumption that combining different kinds of environmental measures downstream and
542 upstream the social-ecological system (“end-of-pipe” and “at-the-source” solutions) as
543 well as upstream and downstream of the plastic contamination causal chain (“curative”
544 and “preventive” solutions) is more successful than scenarios where only one type of
545 environmental measure is undertaken. Keeping on scenario 7.4 up to 2069 would allow
546 the amount of cumulated plastic waste in the ocean to achieve half the value of 2010, i.e.
547 137 million tons. Given the emergency of the situation for marine biodiversity, it might
548 be interesting to test scenarios that are quicker to reduce by 50% the level of 2010. Figure
549 4 is a first attempt in that sense. It shows that cleanup effort only (scenario 3.2) could
550 achieve that goal but would require removing from the ocean 11.89% of plastic every
551 year starting from 2020 up to 2030. Assuming that current levels of plastic annual
552 removal in the ocean is 0.10% (this is a first preliminary assumption that will be
553 improved later), this would require a technological progress 119 times higher than
554 nowadays. Scenario 3.1 is an intent to simulate quite an ambitious ecological target and at
555 the same time a bit more realistic. It shows that to reducing 2010’s level by 25% would
556 require removing from the ocean 7.18% of plastic every year starting from 2020 up to
557 2030 this would require to multiply 72 times current efforts in ocean cleanup
558 technologies. In further versions of this paper, we will assess if such a technological
559 advance is feasible.

560
<figure><img src="image_4.png" /><figcaption>Figure 3. Impact of scenarios inspired by Jambeck et al. (2015, p. 770) on the amount of plastic wastes in the global ocean (floating plastics and deposited on the seabed).</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>Figure 4. Scenarios with environmental efforts (ocean cleanup effort only) designed to reduce the amount of ocean plastic wastes below 2010 levels (floating plastics and deposited on the seabed).</figcaption></figure>

561
562
563
564
565

566
567
568
569
570
571
572
573
574
575
576
<figure><img src="image_4.png" /><figcaption>Figure 3. Impact of scenarios inspired by Jambeck et al. (2015, p. 770) on the amount of plastic wastes in the global ocean (floating plastics and deposited on the seabed).</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>Figure 4. Scenarios with environmental efforts (ocean cleanup effort only) designed to reduce the amount of ocean plastic wastes below 2010 levels (floating plastics and deposited on the seabed).</figcaption></figure>
577 **Conclusion**

578 Our results suggest that to reach significant abatement of plastic wastes accumulated in
579 the ocean, a panel of diverse types of solutions is required. One type of environmental
580 measure alone will never succeed. Upstream and downstream solutions must be
581 combined across the social-ecological system (i.e., “end-of-pipe” and “at-the-source”
582 solutions from Table 1) as well as across the plastic contamination causal chain (i.e.,
583 “curative” and “preventive” solutions from Table 1). According to Jambeck et al. (2015),
584 long-term solutions will also likely include waste reduction and “downstream” waste
585 management strategies such as expanded recovery systems and extended producer
586 responsibility, i.e., plastic products used by consumers would be recovered by producers
587 for recycling purposes (Braungart, 2013; OECD, 2004; Lifset, 1993; Kalimo et al.,
588 2012). Also, Jambeck et al. assert that improving waste management infrastructure in
589 developing countries is paramount and will require substantial resources and time. While
590 such infrastructure is being developed, industrialized countries can take immediate action
591 by reducing waste and curbing the growth of single-use plastics (Jambeck et al., 2015).

592

593 All these upstream and downstream solutions could either come from the top (political
594 and economic decision makers) or the bottom of the society (citizens, environmental
595 associations, small size enterprises). But in any case, several of these solutions will
596 require a change in mentalities to spur individuals to act collectively. Trying to solve the
597 problem of providing a common good such as a plastic-free ocean is a classic collective
598 action dilemma (Kollock, 1998)<fnref n="12" />. The classic theory of collective action predicts that no
599 one will change behavior and reduce their plastic consumption unless an external
600 authority imposes enforceable rules that change the incentives faced by those involved
601 (Hardin, 1968; Benkler, 2011). This is why many analysts call for a change in institutions
602 at the global level. However, the presumption that a collective action problem that has
603 global effects can only be solved globally is not relying on strong empirical support. A
604 large number of individuals facing collective action problems have self-organized to
605 cooperate and develop solutions to common pool resource problems at a small to medium
606 scale without external top-down authority from national or international levels (Poteete et
607 al., 2010; Agrawal, 2000 ; Schlager et al., 1994 ; Ostrom, 1992, 1994, 2001 ; NRC,
608 2002 ; Dietz, 2003). Plastic as many other problems conceptualized as “global
609 problems” are the cumulative result of actions taken at diverse levels, i.e., at the level of
610 individuals, families, small groups, communities, private firms, and local, regional, and
611 national governments (Ostrom, 2010a). Solving this problem requires collective action
612 and many actors at diverse levels need to change their day-to-day activities to avoid
613 plastics to end up in oceans. At the global level, reducing the threat requires an

<footnote n="12">¹² Plastic contamination is a global environmental problem with impacts at worldwide scale (Baztan et al., 2016, p. 178-179). However, the causes of plastic contamination operate at a much smaller scale. Billions of actors could benefit from reduced plastic emissions into the environment, whether they make any effort toward this goal or not (Ostrom, 2010a,b,c; Kerber, 2017).</footnote>
577 **Conclusion**

578 Our results suggest that to reach significant abatement of plastic wastes accumulated in
579 the ocean, a panel of diverse types of solutions is required. One type of environmental
580 measure alone will never succeed. Upstream and downstream solutions must be
581 combined across the social-ecological system (i.e., “end-of-pipe” and “at-the-source”
582 solutions from Table 1) as well as across the plastic contamination causal chain (i.e.,
583 “curative” and “preventive” solutions from Table 1). According to Jambeck et al. (2015),
584 long-term solutions will also likely include waste reduction and “downstream” waste
585 management strategies such as expanded recovery systems and extended producer
586 responsibility, i.e., plastic products used by consumers would be recovered by producers
587 for recycling purposes (Braungart, 2013; OECD, 2004; Lifset, 1993; Kalimo et al.,
588 2012). Also, Jambeck et al. assert that improving waste management infrastructure in
589 developing countries is paramount and will require substantial resources and time. While
590 such infrastructure is being developed, industrialized countries can take immediate action
591 by reducing waste and curbing the growth of single-use plastics (Jambeck et al., 2015).

592

593 All these upstream and downstream solutions could either come from the top (political
594 and economic decision makers) or the bottom of the society (citizens, environmental
595 associations, small size enterprises). But in any case, several of these solutions will
596 require a change in mentalities to spur individuals to act collectively. Trying to solve the
597 problem of providing a common good such as a plastic-free ocean is a classic collective
598 action dilemma (Kollock, 1998)<fnref n="12" />. The classic theory of collective action predicts that no
599 one will change behavior and reduce their plastic consumption unless an external
600 authority imposes enforceable rules that change the incentives faced by those involved
601 (Hardin, 1968; Benkler, 2011). This is why many analysts call for a change in institutions
602 at the global level. However, the presumption that a collective action problem that has
603 global effects can only be solved globally is not relying on strong empirical support. A
604 large number of individuals facing collective action problems have self-organized to
605 cooperate and develop solutions to common pool resource problems at a small to medium
606 scale without external top-down authority from national or international levels (Poteete et
607 al., 2010; Agrawal, 2000; Schlager et al., 1994; Ostrom, 1992, 1994, 2001; NRC,
608 2002; Dietz, 2003). Plastic as many other problems conceptualized as “global
609 problems” are the cumulative result of actions taken at diverse levels, i.e., at the level of
610 individuals, families, small groups, communities, private firms, and local, regional, and
611 national governments (Ostrom, 2010a). Solving this problem requires collective action
612 and many actors at diverse levels need to change their day-to-day activities to avoid
613 plastics to end up in oceans. At the global level, reducing the threat requires an

<footnote n="12">¹² Plastic contamination is a global environmental problem with impacts at worldwide scale (Baztan et al., 2016, p. 178-179). However, the causes of plastic contamination operate at a much smaller scale. Billions of actors could benefit from reduced plastic emissions into the environment, whether they make any effort toward this goal or not (Ostrom, 2010a,b,c; Kerber, 2017).</footnote>
enforceable global treaty. However, if global solutions negotiated at a global level are not backed up by a variety of efforts at national, regional, and local levels, they are not guaranteed to work well (Ostrom, 2010a, c). Attempts to foster multiple-scale actions and benefits rely on the concept of polycentric governance in which many centers of decision-making are formally independent of each other but can undertake many activities at diverse scales that cumulatively make a difference (Ostrom, 2010a; Gruby and Basuro, 2014). Ostrom (2010c), Benkler (2011) and others have identified about 10 conditions required to create a context in which people are willing to self-organize at multiple levels and collaborate to find a solution to a common problem.

Further research is required to assess the technical and financial feasibility of the solutions proposed to solve plastic contamination of the global ocean. Direct and indirect economic impacts must be assessed to measure social and political feasibility. Economic principle must be designed for financial, social and political difficulties to be overcome (e.g., shared environmental responsibility principle, polluter pays principle, extended producer responsibility, etc.). The SD model must be improved and some parameters made more accurate. We need still to develop and couple the input-output model to the SD model also to assess long term ecological impacts (beyond 2030) of each scenario

## References

Agrawal, A., 2000. Small Is Beautiful, but Is Larger Better? Forest Management Institutions in the Kumaon Himalaya, India. In: C. Gibson, M. McKean, and E. Ostrom (Eds.), 2000. People and Forests: Communities, Institutions, and Governance, pp. 57–86, MIT Press, Cambridge, MA.

Attina, T. M., Hauser, R., Sathyanarayana, S., Hunt, P. A., Bourguignon, J. P., Myers, J. P., DiGangi J., Zoeller R.T Trasande, L., 2016. Exposure to endocrine-disrupting chemicals in the USA: a population-based disease burden and cost analysis. The Lancet Diabetes & Endocrinology, 4(12), 996–1003.

Baztan, J., Bergmann, M., Booth, A., Broglio, E., Carrasco, A., Chouinard, O., Clüsener-Godt, M., Cordier, M., Cozar, A., et al., 2017. Breaking Down the Plastic Age. In: Baztan, J., Jorgensen, B., Pahl, S., Thompson, R. C., & Vanderlinden, J. P. (Eds.), 2017. MICRO 2016: Fate and Impact of Microplastics in Marine Ecosystems: From the Coastline to the Open Sea. Elsevier 2017, Pages 177–181.

Baztan, J., Bergmann, M., Booth, A., Broglio, E., Carrasco, A., Chouinard, O., ... & Enevoldsen, H., 2017. Breaking Down the Plastic Age. In: Baztan, J., Jorgensen, B., Pahl, S., Thompson, R. C., & Vanderlinden, J. P. (Eds.), (2016, pp. 177-181). MICRO 2016: Fate and Impact of Microplastics in Marine Ecosystems: From the Coastline to the Open Sea. Elsevier.
enforceable global treaty. However, if global solutions negotiated at a global level are not backed up by a variety of efforts at national, regional, and local levels, they are not guaranteed to work well (Ostrom, 2010a, c). Attempts to foster multiple-scale actions and benefits rely on the concept of polycentric governance in which many centers of decision-making are formally independent of each other but can undertake many activities at diverse scales that cumulatively make a difference (Ostrom, 2010a; Gruby and Basuro, 2014). Ostrom (2010c), Benkler (2011) and others have identified about 10 conditions required to create a context in which people are willing to self-organize at multiple levels and collaborate to find a solution to a common problem.

Further research is required to assess the technical and financial feasibility of the solutions proposed to solve plastic contamination of the global ocean. Direct and indirect economic impacts must be assessed to measure social and political feasibility. Economic principle must be designed for financial, social and political difficulties to be overcome (e.g., shared environmental responsibility principle, polluter pays principle, extended producer responsibility, etc.). The SD model must be improved and some parameters made more accurate. We need still to develop and couple the input-output model to the SD model also to assess long term ecological impacts (beyond 2030) of each scenario

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731 Ostrom, E., 2010c. A multi-scale approach to coping with climate change and other collective action problems. Solutions, 1(2), 27-36.
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694 Jaacks L.M. and Prasad S., 2017. The ecological cost of continued use of endocrine-disrupting chemicals. The Lancet Diabetes & Endocrinology 5(1), 14-15.

697 Jambeck, J.R., Geyer, R., Wilcox, C., Siegler, T.R., Perryman, M., Andrady, A., Narayan, R., Law, K.L., 2015. Plastic waste inputs from land into the ocean. Science (80-. ). 347, 768-771.

700 Kalimo H., Lifset R., van Rossem C., van Wassenhove L., Atasu A. and Mayers K., 2012. Greening the Economy through Design Incentives: Allocating Extended Producer Responsibility. European Energy and Environmental Law Review, pp. 274-305.

704 Kerber, H., 2017. Marine litter and the commons: How can effective governance be established? Conference paper, presented at the XVI Biennial Conference, 'Practicing the commons: Self-governance, cooperation, and institutional change' of The International Association for the Study of the Commons (IASC), 10-14 July 2017, Utrecht University, the Netherlands.

709 Kollock, P., 1998. Social dilemmas: The anatomy of cooperation. Annual review of sociology, 24(1), 183-214.

711 L. M. Jaacks and S. Prasad, 2017. The ecological cost of continued use of endocrine-disrupting chemicals. Lancet Diabetes Endocrinol; 5: 14-15.

713 Lifset R., 1993. Take it back: Extended producer responsibility as a form of incentive-based environmental policy, J. Resour. Management Technol. 21, 163-175.

716 McIlgorm, A., Campbell, H. F., & Rule, M. J., 2011. The economic cost and control of marine debris damage in the Asia-Pacific region. Ocean & Coastal Management, 54(9), 643-651.

719 NRC (National Research Council), 2002. The Drama of the Commons. Committee on the Human Dimensions of Global Change. E. Ostrom, T. Dietz, N. Dolšak, P. Stern, S. Stonich, and E. Weber (eds). National Academies Press, Washington, DC.

723 OECD, 2004. Economic aspects of extended producer responsibility. Paris, 296 pp.

725 Ostrom, E, Gardner, R and Walker, J., 1994. Rules, Games, and CommonPool Resources. University of Michigan Press, Ann Arbor.

727 Ostrom, E., 2010a. Polycentric systems for coping with collective action and global environmental change. Global Environmental Change 20: 550-557.

729 Ostrom, E., 2010b. Beyond Markets and States: Polycentric Governance of Complex. Economic Systems. American Economic Review 100: 1-33.

731 Ostrom, E., 2010c. A multi-scale approach to coping with climate change and other collective action problems. Solutions, 1(2), 27-36.
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734 Framework for Resource Management in the Americas. Eds. J. Burger, E.

735 Ostrom, R. Norgaard, D. Policansky, and B. Goldstein, 17–41. Island Press,

736 Washington, DC.

737 Ostrom, E., 1992. The Rudiments of a Theory of the Origins, Survival, and

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751 Oceans, 46(15), ENVTL. SCI. & TECH. 7932. Available at

752 https://sustainability.water.ca.gov/documents/18/3334111/Ocean+Pollution.p

753 df.

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755 Organized Institutions for Governing Common Pool Resources. Land

756 Economics 70(3) (August), 294–317.

757 Shea, K. M., and Committee on Environmental Health, 2003. Pediatric exposure

758 and potential toxicity of phthalate plasticizers. Pediatrics, 111(6), 1467-1474.

759 Slat B., 2014. How the oceans can clean themselves. A feasibility study. The

760 Ocean Cleanup (Ed.), The Netherlands, 535 pp.

761 Sterman, J.D., 2000. Business dynamics: Systems thinking and modeling for a complex

762 world. Irwin/McGraw-Hill Boston, Boston, MA.

763 The United Nations, n.d. World population prospects 2017 [WWW Document]. URL

764 https://population.un.org/wpp/Download/Standard/Population/ (accessed 11.3.18).

765 Trasande L., Zoeller R.T., Hass U., Kortenkamp A., Grandjean P., Myers J.P., DiGangi

766 J., M. Bellanger, Hauser R., Legler J., Skakkebaek N.E., and Heindel J.J., 2015.

767 Estimating Burden and Disease Costs of Exposure to Endocrine-Disrupting

768 Chemicals in the European Union. Journal of Clinical Endocrinology and

769 Metabolism 100(4):1245–1255.

770 UNEP (United Nation Environmental Program), 2014. Valuing plastic. The Business

771 Case for Measuring, Managing and Disclosing Plastic Use in the Consumer Goods

772 Industry. 115 pp.
733 Ostrom, E., 2001. Reformulating the Commons. In Protecting the Commons: A

734 Framework for Resource Management in the Americas. Eds. J. Burger, E.

735 Ostrom, R. Norgaard, D. Policansky, and B. Goldstein, 17–41. Island Press,

736 Washington, DC.

737 Ostrom, E., 1992. The Rudiments of a Theory of the Origins, Survival, and

738 Performance of CommonProperty Institutions. In Making the Commons

739 Work: Theory, Practice, and Policy, ed. Daniel W. Bromley et al., 293–318.

740 ICS Press, San Francisco, CA.

741 PlasticsEurope, 2013. Plastics – the facts 2013. Brussels, Belgium. Available at:

742 www.plasticseurope.org/Document/plastics-the-facts-2013.aspx?FolID=2

743 Poteete, A, Janssen, M and Ostrom, E., 2010. Working Together: Collective

744 Action, the Commons, and Multiple Methods in Practice. Princeton

745 University Press, Princeton.

746 Obbard, R. W., Sadri, S., Wong, Y. Q., Khitun, A. A., Baker, I., & Thompson, R.

747 C., 2014. Global warming releases microplastic legacy frozen in Arctic Sea

748 ice. Earth's Future, 2(6), 315-320.

749 Raveender Vannela, 2012. Are We “Digging Our Own Grave” Under the Oceans?

750 Biosphere Level Effects and Global Policy Challenge from Plastic(s) in

751 Oceans, 46(15), ENVTL. SCI. & TECH. 7932. Available at

752 https://sustainability.water.ca.gov/documents/18/3334111/Ocean+Pollution.p

753 df.

754 Schlager, E, Blomquist, W and Tang, SY, 1994. Mobile Flows, Storage and Self

755 Organized Institutions for Governing Common Pool Resources. Land

756 Economics 70(3) (August), 294–317.

757 Shea, K. M., and Committee on Environmental Health, 2003. Pediatric exposure

758 and potential toxicity of phthalate plasticizers. Pediatrics, 111(6), 1467-1474.

759 Slat B., 2014. How the oceans can clean themselves. A feasibility study. The

760 Ocean Cleanup (Ed.), The Netherlands, 535 pp.

761 Sterman, J.D., 2000. Business dynamics: Systems thinking and modeling for a complex

762 world. Irwin/McGraw-Hill Boston, Boston, MA.

763 The United Nations, n.d. World population prospects 2017 [WWW Document]. URL

764 https://population.un.org/wpp/Download/Standard/Population/ (accessed 11.3.18).

765 Trasande L., Zoeller R.T., Hass U., Kortenkamp A., Grandjean P., Myers J.P., DiGangi

766 J., M. Bellanger, Hauser R., Legler J., Skakkebaek N.E., and Heindel J.J., 2015.

767 Estimating Burden and Disease Costs of Exposure to Endocrine-Disrupting

768 Chemicals in the European Union. Journal of Clinical Endocrinology and

769 Metabolism 100(4):1245–1255.

770 UNEP (United Nation Environmental Program), 2014. Valuing plastic. The Business

771 Case for Measuring, Managing and Disclosing Plastic Use in the Consumer Goods

772 Industry. 115 pp.