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Application of GIS in forecasting ocean plastic waste in the South Central Coast, Vietnam (Case study in Da Nang City)

Science & Technology Development Journal - Social Sciences & Humanities 2023
Huan Duc Vu, Thị Bích Ngọc Phạm

Summary

Researchers applied GIS-based modeling to forecast the transport and distribution of plastic waste entering the ocean along Vietnam's South Central Coast, demonstrating how spatial data can support policymakers in targeting plastic waste reduction interventions.

Study Type Environmental

Plastic waste in the marine environment has become a major concern due to its persistence in the oceans, and its detrimental consequences for marine life and human health. To propose strategic policies to reduce plastic waste, policymakers must be updated with quantitative information on ocean plastic waste sources. Garbage arising from activities in each individual's life, if not collected and managed, will be leaked and carried by wind, rain, to slope areas, and canals, then drifted along rivers and discharged into the sea. This study aims to present a method using a geographic information system (GIS) to analyze secondary data of plastic waste from the discharge sources to the ocean based on socio-demographic data, secondary statistics, the weights of plastic waste density, and topographical characteristics such as rivers and hydrology, including spatial and temporal variation. The simulated results of the research provide a comparison and correction to the survey data reported by the World Bank (WB), the United Nations Environment Program (UNEP), and local government environmental offices regarding the distribution of plastic waste in Da Nang’s rivers. The simulation estimates that an average density of 304,5 kg/month/1km2 (in 2021) is currently flowing into the ocean from rivers in the study area. The results of the model are further evaluated by interpreting high-resolution satellite images at 10 hotspots. The findings of this study improve the existing model with more detail and localization for estimating ocean plastic waste volumes and provide data for future strategic policies to monitor and reduce plastic debris.

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