| Abstract |
Challenges associated with plastic waste management range from littering to high collection costs to low recycling rates. Effective collection of plastics is obviously an important step in the management of plastic waste and has an impact on recycling rates. For this reason, several countries have transformed their collection systems in recent decades. Collecting more plastic packaging comes at a cost, as the feedstock for the sorting process becomes more complex and leads to cross-contamination within the sorted fractions. Therefore, a balance must be obtained between some elements, such as the design of packaging, collection and recycling rates, and finally, the quality of fractions that have been sorted. Further investment to improve pretreatment, sorting, and recycling technologies and simpler recyclable packaging designs are, therefore, key to further increasing plastic recycling rates. It is essential to possess more data, especially on the type of containers and plastics, and examine how often unsorted waste is collected. The automated waste collection monitoring system is a step forward in automating manual waste collection and sorting. Multi-sensory artificial intelligence (AI) for sorting plastic waste and the blockchain sorting platform for the circular economy of plastic waste are forward-looking activities that will increase the efficiency of recycling plastic waste. This review focuses on the development of collection systems and sorting processes for post-consumer plastic recycling. The focus is on best practices and the best available technology. Separate collection systems for recyclable plastics are presented and discussed along with their respective technical collection and sorting solutions, taking into consideration that progress in separation and sorting systems are implicitly linked to approaches to waste collection. |