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Forecasting plastic waste generation and interventions for environmental hazard mitigation

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F22%3APU141789" target="_blank" >RIV/00216305:26210/22:PU141789 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.sciencedirect.com/science/article/pii/S0304389421022986?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0304389421022986?via%3Dihub</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.jhazmat.2021.127330" target="_blank" >10.1016/j.jhazmat.2021.127330</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Forecasting plastic waste generation and interventions for environmental hazard mitigation

  • Original language description

    Plastic waste and its environmental hazards have been attracting public attention as a global sustainability issue. This study builds a neural network model to forecast plastic waste generation of the EU-27 in 2030 and evaluates how the interventions could mitigate the adverse impact of plastic waste on the environment. The black-box model is interpreted using SHapley Additive exPlanations (SHAP) for managerial insights. The dependence on predictors (i.e., energy consumption, circular material use rate, economic complexity index, population, and real gross domestic product) and their interactions are discussed. The projected plastic waste generation of the EU-27 is estimated to reach 17 Mt/y in 2030. With an EU targeted recycling rate (55%) in 2030, the environmental impacts would still be higher than in 2018, especially global warming potential and plastic marine pollution. This result highlights the importance of plastic waste reduction, especially for the clustering algorithm-based grouped countries with a high amount of untreated plastic waste per capita. Compared to the other assessed scenarios, Scenario 4 with waste reduction (50% recycling, 47.6% energy recovery, 2.4% landfill) shows the lowest impact in acidification, eutrophication, marine aquatic toxicity, plastic marine pollution, and abiotic depletion. However, the global warming potential (8.78 Gt CO(2)eq) is higher than that in 2018, while Scenario 3 (55% recycling, 42.6% energy recovery, 2.4% landfill) is better in this aspect than Scenario 4. This comprehensive analysis provides pertinent insights into policy interventions towards environmental hazard mitigation.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20704 - Energy and fuels

Result continuities

  • Project

    <a href="/en/project/EF15_003%2F0000456" target="_blank" >EF15_003/0000456: Sustainable Process Integration Laboratory (SPIL)</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2022

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Journal of Hazardous Materials

  • ISSN

    0304-3894

  • e-ISSN

    1873-3336

  • Volume of the periodical

    neuveden

  • Issue of the periodical within the volume

    424

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    14

  • Pages from-to

    127330-127330

  • UT code for WoS article

    000703789500008

  • EID of the result in the Scopus database

    2-s2.0-85115951650