Primary plastic polymers: Urgently needed upstream reduction - Volume 2

Plastic pollution has attracted the attention of the media, public, and government worldwide. Analysis of the inverted U-shaped environmental Kuznets curve (EKC) relationship between economic development and plastic pollution is crucial because economic growth is a critical driver of plastic pollution. In this study, for the first time, we (i) used the stochastic impacts of regression on population, affluence, and technology (STIRPAT) model to investigate the EKC relationship; (ii) performed a comprehensive analysis of the effects of sociodemographic factors on plastic pollution; and (iii) used a panel dataset of 128 countries for empirical analyses. The STIRPAT model was used to conduct scenario analyses to explore the impacts of sociodemographic driving forces on future plastic pollution by 2050 on a national (217 countries) and global scale. The empirical results confirmed the EKC relationship and revealed that changes in population structure and urbanization could substantially affect plastic pollution. Global plastic pollution was projected to reach 66.1 MT/y by 2050 under the business-as-usual scenario. Low-income countries and sub-Saharan Africa are projected to become major contributors to plastic pollution, leading to a global trend of increasing plastic pollution. These findings will help policymakers identify targets to effectively reduce future global plastic pollution.

We reviewed economic and environmental studies on global plastic pollution and we estimate the global cost of actions toward zero plastic pollution in all countries by 2040 to be US$ 18.3–158.4 trillion (cost of a 47% reduction of plastic production included). If no actions are undertaken, we estimate the cost of damages caused by plastic pollution from 2016 to 2040 to be US$ 13.7–281.8 trillion. These ranges suggest it is possible that the costs of inaction are significantly higher than those of action. Plastic product sales will also generate a global benefit in the form of incomes (salaries, dividends etc.) estimated to be US$ 38.0 trillion over 2016–2040 in the case of inaction, and US$ 32.7–33.1 trillion in case of action. Calculating benefit minus costs provides the net benefits: US$ −120.4 to 19.7 trillion in case of action and US$ −243.8 to 24.3 trillion in case of inaction. Net benefit ranges suggest action and inaction will both be beneficial when considering the high estimates. However, the low estimates show net benefits might be negative, which suggests inaction might generate a net cost for society that will be twice the cost of action. Our estimates are preliminary (several cost and benefit data are lacking).

The complexity of ecological-economic systems significantly reduces our ability to investigate their behavior and propose policies aimed at various environmental and/or economic objectives. Following recent suggestions for integrating nonlinear dynamic modeling with input-output (IO) modeling, we develop a fully dynamic ecological-economic model by integrating IO with system dynamics (SD) for better capturing critical attributes of ecological-economic systems. We also develop and evaluate various scenarios using policy impact and policy sensitivity analyses. The model and analysis are applied to the degradation of fish nursery habitats by industrial harbors in the Seine estuary (Haute-Normandie region, France). The modeling technique, dynamization, and scenarios allow us to show trade-offs between economic and ecological outcomes and evaluate the impacts of restoration scenarios and water quality improvement on the fish population.