This Annex provides more details on the methodological framework employed to obtain the estimates and projections of plastics use, waste and environmental impacts presented in the report. These have been generated by building on the methodology employed in the OECD Global Plastics Outlook publications (2022[1]; 2022[2]).
Policy Scenarios for Eliminating Plastic Pollution by 2040
The OECD’s in-house dynamic computable general equilibrium (CGE) model ENV-Linkages is used as the basis to project the economic activities that drive plastics use. ENV-Linkages is a multi-sectoral, multi-regional model that links economic activities to energy and environmental issues. A more comprehensive model description is given in Chateau, Dellink and Lanzi (2014[3]). The sectoral and regional aggregation of the model as used in the simulations are given in Table A A.1 and Table A A.2, respectively.
Production in ENV Linkages is assumed to operate under cost minimisation with perfect markets and constant returns-to-scale technology. The production technology is specified as nested Constant Elasticity of Substitution (CES) production functions in a branching hierarchy. This structure is replicated for each output, while the parameterisation of the CES functions may differ across sectors. The model adopts a putty/semi-putty technology specification, where substitution possibilities among factors are assumed to be higher with new vintage capital than with old vintage capital. In the short run this ensures inertia in the economic system, with limited possibilities to substitute away from more expensive inputs, but in the longer run this implies a relatively smooth adjustment of quantities to price changes. Capital accumulation is modelled as in the traditional Solow/Swan neo classical growth model, where economic growth is assumed to stem from the combination of labour, capital accumulation and technological progress.
Household consumption demand is the result of static maximisation behaviour which is formally implemented as an “Extended Linear Expenditure System”. A representative consumer in each region – who takes prices as given – optimally allocates disposal income among the full set of consumption commodities and savings. Saving is considered as a standard good in the utility function and does not rely on forward looking behaviour by the consumer. The government in each region collects various kinds of taxes in order to finance government expenditures. Assuming fixed public savings (or deficits), the government budget is balanced through the adjustment of the income tax on consumer income. In each period, investment net-of-economic depreciation is equal to the sum of government savings, consumer savings and net capital flows from abroad.
International trade is based on a set of regional bilateral flows. The model adopts the Armington specification, assuming that domestic and imported products are not perfectly substitutable. Moreover, total imports are also imperfectly substitutable between regions of origin. Allocation of trade between partners then responds to relative prices at the equilibrium.
Market goods equilibria imply that, on the one side, the total production of any goods or services is equal to the demand addressed to domestic producers plus exports; and, on the other side, the total demand is allocated between the demands (both final and intermediary) by domestic producers and the import demand.
ENV Linkages is fully homogeneous in prices and only relative prices matter. All prices are expressed relative to the numéraire of the price system that is arbitrarily chosen as the index of OECD manufacturing exports prices. Each region runs a current account balance, which is fixed in terms of the numéraire.
As ENV-Linkages is recursive-dynamic and does not incorporate forward-looking behaviour, price-induced changes in innovation patterns are not represented in the model. The model does, however, entail technological progress through an annual adjustment of the various productivity parameters, including e.g. autonomous energy efficiency and labour productivity improvements. Furthermore, as production with new capital has a relatively large degree of flexibility in choice of inputs, existing technologies can diffuse to other firms. Thus, within the CGE framework, firms choose the least-cost combination of inputs, given the existing state of technology. The capital vintage structure also ensures that such flexibilities are larger in the long run than in the short run.
The ENV-Linkages model has been extended to include plastics production and use, for both primary and secondary (recycled) plastics. The plastics production and use data is presented in million metric tonnes (Mt) and plastics use is split by region, polymer and application. Figure A A.1 presents estimates for plastics use by polymer and application in 2020. Waste estimates and end-of-life fates are derived based on average lifespans by application and country-specific end-of-life shares. Further information on the data sources used to derive the estimates for plastic flows, from production to disposal and mismanagement, is presented in (OECD, 2022[1]).
Polymer use shares by application, global, 2020
Source: OECD ENV-Linkages model. Estimates and projections for plastic leakage to the aquatic environment.
The projections on the leakage of waste plastics to aquatic environments are made by L. Lebreton (2024[4]), employing a methodology that estimates the amount of plastic waste entering aquatic environments (by region). As explained in more detail in (OECD, 2022[2]), the methodology employs results from a previous study by Borrelle et al. (2020[5]) which estimated leakage of mismanaged plastic waste into rivers, lakes, and the ocean at a global scale. The model computes the probability of releases of plastics (from mismanaged plastic waste produced in a certain region or country) to reach an aquatic environment (rivers, lakes, and oceans).
The model also assesses the mobility of plastics in aquatic environments as well as degradation. The whole-ocean plastic mass budget model presented in (Lebreton and Andrady, 2019[6]) is expanded to a simplified representation of the global aquatic environment. The model differentiates between annual inputs in freshwater and the ocean, allowing floating plastic waste to circulate from one compartment to the other over time. The model also differentiates inputs by polymer types using the OECD ENV-Linkages model estimates and waste projections presented in this report. The likely fate of emitted plastics is determined depending on their density. Additionally, the degradation rates vary across polymers based on laboratory results (Gerritse et al., 2020[7]). The general model framework is presented in Figure A A.2. The methodology is explained in more detail in (OECD, 2022[2]).
Note: Mass inputs by modelled region, characterised by polymer types, are accumulated from 1951 to 2060 into the plastic fate model. Plastics with a density higher than water sink and accumulate in riverbed, lakebed and seabed. Floating plastics (density lower than water) are transported between different aquatic compartments and are allowed to degrade into microplastics over time from contact with sunlight. The region-specific parameter ‘i’ is the ratio between plastics remaining in freshwater and the plastics entering the marine environment. The parameters ‘s’ and ‘r’ represent the fraction of stranding and release from the global shoreline. The parameter ‘t’ is the fraction of floating plastic circulating from the coastal to the offshore ocean. Finally, ‘d’ is the mass fraction degrading into microplastics annually and varies with polymer types.
Source: (OECD, 2022[2]).
The methodology and parameters employed to generate projections on the contribution of the lifecycle of plastics to GHG emissions, on a global level, are detailed in (OECD, 2022[2]). Plastics-related GHG emissions are calibrated based on emission factors for the year 2015 provided by Zheng and Suh (2019[8]), and calibrated over time as described in (OECD, 2022[2]). Only GHG emissions from production and conversion, recycling, landfilling and incineration are quantified. GHG emissions from other stages of the lifecycle of plastics, such as those generated from the open pit burning of plastic waste or from plastics in the environment, are not estimated due to a lack of underlying data.
References
[5] Borrelle, S. et al. (2020), “Predicted growth in plastic waste exceeds efforts to mitigate plastic pollution”, Science, Vol. 369/6510, pp. 1515-1518, https://doi.org/10.1126/science.aba3656.
[3] Château, J., R. Dellink and E. Lanzi (2014), “An Overview of the OECD ENV-Linkages Model: Version 3”, OECD Environment Working Papers, No. 65, OECD Publishing, Paris, https://doi.org/10.1787/5jz2qck2b2vd-en.
[7] Gerritse, J. et al. (2020), “Fragmentation of plastic objects in a laboratory seawater microcosm”, Scientific Reports, Vol. 10/1, p. 10945, https://doi.org/10.1038/s41598-020-67927-1.
[4] Lebreton, L. (2024), Quantitative analysis of aquatic leakage for multiple scenarios based on ENV-Linkages, unpublished.
[6] Lebreton, L. and A. Andrady (2019), “Future scenarios of global plastic waste generation and disposal”, Palgrave Communications, Vol. 5/1, p. 6, https://doi.org/10.1057/s41599-018-0212-7.
[1] OECD (2022), Global Plastics Outlook: Economic Drivers, Environmental Impacts and Policy Options, OECD Publishing, Paris, https://doi.org/10.1787/de747aef-en.
[2] OECD (2022), Global Plastics Outlook: Policy Scenarios to 2060, OECD Publishing, Paris, https://doi.org/10.1787/aa1edf33-en.
[8] Zheng, J. and S. Suh (2019), “Strategies to reduce the global carbon footprint of plastics”, Nature Climate Change, Vol. 9/5, pp. 374-378, https://doi.org/10.1038/s41558-019-0459-z.