塑料消费及其报废管理造成了巨大的环境足迹,并且是能源密集型的。作为对策,欧洲已广泛推广了废物转化资源和预防战略;但是,其有效性仍不确定。本研究旨在通过探索性数据分析,揭示欧盟成员国(EU-27)塑料价值链的环境足迹模式。降维和分组。评估了九个变量,从社会经济和人口到环境影响。根据一系列特征的相似性形成三个簇(九个),环境影响被确定为确定集群的主要影响变量。大多数国家属于第0组,2014年由17个国家和2019年由18个国家组成。它们代表全球变暖潜势(GWP)相对较低的集群,2014年的平均值为2.64tCO2eq/cap,2019年为4.01tCO2eq/cap。在所有评估国家中,在EU-27的特征内评估时,丹麦显示出显着变化,从2014年的集群1(高GWP)到2019年的集群0(低GWP)。2019年塑料包装废弃物统计数据分析(2022年数据发布)显示,尽管欧盟27国内部的回收率有所提高,但全球升温潜能值并没有降低,暗示反弹效应。GWP倾向于与较高的塑料废物量相关地增加。相比之下,其他环境影响,比如富营养化,非生物和酸化潜力,被确定为通过恢复有效地缓解,抑制塑料废物产生增加的不利影响。五年间隔的数据分析在一组模式中确定了不同的集群,根据它们的相似性对它们进行分类。分类和见解是制定重点缓解策略的基础。
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 CO2eq/cap in 2014 and 4.01 t CO2eq/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.