Comparative LCA of Municipal Solid Waste Collection and Sorting Schemes Considering Regional Variability

Abstract

Plastic packaging brings safety, hygiene, and comfort to the consumers; however, they also bring a massive problem to the society and to the environment – plastic waste streams. Approximately only one-third of plastic waste is transformed into new recycled goods whereas the rest is incinerated, sent to landfills or, end up in the environment. Therefore, proper management of plastic waste streams has great importance from social, political, and environmental perspectives. Recycling is promoted among the solid waste hierarchy as the most preferred option after waste prevention and reduction. However, only a holistic approach can reveal the advantages, the disadvantages and the hotspots of the waste management structures. Life cycle assessment is a powerful method to understand the environmental impacts of recycling routes. Reaching the end of use and leaving the households, plastic waste undergoes a serial of processes until the recycling facilities. These pre-treatment steps are characterized by a high variability due to technological factors such as collection and sorting scenarios, and spatial factors such as the distance driven by the waste trucks or the electricity mix. This paper investigates (i) the possible advantages of bring point collection compared to door-to-door collection system and (ii) the influence of relevant regional issues. The overarching goal of the study is setting the boundaries to secure an environmentally meaningful chemical recycling process and to quantify the environmental impacts related to the background systems. A comparative LCA is performed to evaluate both systems and subsequently, the influence of regional varying elements is tested through sensitivity analysis. These analyses include different scenarios where the collection, transport and sorting practices are at the scope. The results reveal the advantages of source separation and the importance of regional aspects in LCA modeling.