Sustainable Process Integration Laboratory - SPIL, NETME Centre, Faculty of Mechanical Engineering, Brno University of Technology, Technická 2896/2, 616 69 Brno, Czech Republic.
Faculty of Chemistry and Chemical Engineering, University of Maribor, Smetanova 17, Maribor, Slovenia.
Environ Res. 2024 Jan 15;241:117581. doi: 10.1016/j.envres.2023.117581. Epub 2023 Nov 14.
Plastic consumption and its end-of-life management pose a significant environmental footprint and are energy intensive. Waste-to-resources and prevention strategies have been promoted widely in Europe as countermeasures; however, their effectiveness remains uncertain. This study aims to uncover the environmental footprint patterns of the plastics value chain in the European Union Member States (EU-27) through exploratory data analysis with dimension reduction and grouping. Nine variables are assessed, ranging from socioeconomic and demographic to environmental impacts. Three clusters are formed according to the similarity of a range of characteristics (nine), with environmental impacts being identified as the primary influencing variable in determining the clusters. Most countries belong to Cluster 0, consisting of 17 countries in 2014 and 18 countries in 2019. They represent clusters with a relatively low global warming potential (GWP), with an average value of 2.64 t COeq/cap in 2014 and 4.01 t COeq/cap in 2019. Among all the assessed countries, Denmark showed a significant change when assessed within the traits of EU-27, categorised from Cluster 1 (high GWP) in 2014 to Cluster 0 (low GWP) in 2019. The analysis of plastic packaging waste statistics in 2019 (data released in 2022) shows that, despite an increase in the recovery rate within the EU-27, the GWP has not reduced, suggesting a rebound effect. The GWP tends to increase in correlation with the higher plastic waste amount. In contrast, other environmental impacts, like eutrophication, abiotic and acidification potential, are identified to be mitigated effectively via recovery, suppressing the adverse effects of an increase in plastic waste generation. The five-year interval data analysis identified distinct clusters within a set of patterns, categorising them based on their similarities. The categorisation and managerial insights serve as a foundation for devising a focused mitigation strategy.
塑料消费及其生命周期末端的管理对环境造成了重大影响,而且能源密集度高。废物转化为资源和预防策略在欧洲得到了广泛推广,作为应对措施;然而,其效果仍不确定。本研究旨在通过降维和分组的探索性数据分析,揭示欧盟成员国(EU-27)塑料价值链的环境足迹模式。评估了九个变量,范围从社会经济和人口统计到环境影响。根据一系列特征(九个)的相似性形成了三个聚类,其中环境影响被确定为确定聚类的主要影响变量。大多数国家属于聚类 0,其中包括 2014 年的 17 个国家和 2019 年的 18 个国家。它们代表了全球变暖潜力(GWP)相对较低的聚类,2014 年的平均 GWP 值为 2.64t COeq/cap,2019 年为 4.01t COeq/cap。在所评估的所有国家中,丹麦在 2014 年被归类为聚类 1(高 GWP),而在 2019 年被归类为聚类 0(低 GWP),其在 EU-27 中的特征评估中发生了显著变化。对 2019 年(2022 年发布)塑料包装废物统计数据的分析表明,尽管欧盟-27 的回收率有所增加,但 GWP 并未降低,表明存在回弹效应。GWP 往往会随着塑料废物量的增加而增加。相比之下,其他环境影响,如富营养化、非生物和酸化潜力,通过回收得到有效缓解,抑制了塑料废物产生增加带来的不利影响。五年间隔数据分析确定了一组模式内的不同聚类,根据它们的相似性对它们进行分类。分类和管理见解为制定有针对性的缓解策略提供了基础。