Cambodia and Myanmar

plastic according to weight and product and how they are handled allows for (a) an estimation in turn of the commercial viability of individual activities in the waste management system and (b) an understanding of where the broken links are in the downstream plastic value chain, their origins, and therefore possible means of addressing them through policies. • Last, mapping the stakeholders involved in the plastic life cycle, to identify all economic actors, their role and possible influence, how they may be affected by plastic pollution, and the possible avenues to address it.

The basic diagnostics of how plastic flows through the economy and environment enables the consequences of inaction to be predicted. Plastic pollution baseline studies should estimate how plastic pollution would increase under different assumptions about population growth and future per capita consumption of plastic. Using material flow assessment tools allows spatial simulation of the additional burden on waste management systems if no action is taken.

BOX 2.1 Identifying the 10 Plastic Products Most Commonly Found in the Environment Using Drones and Artificial Intelligence in Cambodia and Myanmar

The methodology used in Cambodia and Myanmar was based on the European Union strategy that informed the development of the European Commission’s Directive on Reduction of the Impact of Certain Plastic Products on the Environment (commonly referred to as the Single-Use Plastics Directive). The 10 plastic products most commonly found in the environment were identified; various policy options to address leakage of those 10 plastics were assessed; and the applicability of those options was considered in terms of factors such as pragmatism, affordability, and availability of alternatives. Two surveys were initiated between October 2019 and April 2020. The first focused on field sampling following international marine plastics survey guidelines. The second involved a highly innovative approach of remote sensing and automated detection, quantification, and classification of plastics using a machine-learning process (figure B2.1.1). Drones were used to collect images of rivers, beaches, and urban canals at different height levels, which were automatically analyzed to show pollution hot spots, waste area coverage, and volume of plastics, and, most importantly, to classify the most common types of plastics found in and along the waterways being studied. This information can be used as the basis for targeted measures against specific plastic types or in specific areas.

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