An evidence-based model to design plastic waste management solution for emerging and developing countries

Abstract

As of today, undeniably plastic pollution is a global problem and all the more alarming in fast-emerging regions where the consumption exceeds by far the system’s capacity to handle the generated waste. As a result, by 2040, if we continue the business as usual, there will be twice as much macroplastic generated and three times more plastic leakage into the ocean every year. It is also important to picture that today, only five countries are responsible for half of the plastic in the ocean, all located in Asia: China, Indonesia, The Philippines, Viet Nam and Thailand (25% of the world population). As such, finding local solutions to plastic pollution is essential. However, local organizations and project leaders willing to do so are usually lacking technical or technological knowledge, struggling in understanding what would be the relevant business model to implement in their particular situation, lacking access to sufficient funding, have few or no contacts related to the waste management sector. In this thesis, a two-year R&D process of screening, surveying, and analyzing 350+ local-scale recycling centers has been designed to lead to the creation of an innovative solution, applying this research into a marketable business. NP Analytics is a software-based decision-making tool for local plastic waste management projects design. With NP Analytics, local recycling initiatives will be best advised on (1) suitable technologies and business models to implement, (2) viable funding opportunities and (3) connection with the relevant regional and international network. This solution aims to foster social entrepreneurship, and to create profitable and sustainable plastic recycling centers in developing and emerging countries. Like any model, an iterative process will help refine it along the way with the development of concrete projects, especially the understanding of various social contexts to find the best way to integrate the identified solutions.

Date of Award	2021
Original language	English
Awarding Institution	The Hong Kong University of Science and Technology
Supervisor	Benjamin STEUER (Supervisor)