Sông Sài Gòn: Extreme Plastic Pollution Pathways in Riparian Waterways
Plastic pollution in waterways poses a significant global challenge, largely stemming from land-based sources and subsequently transported by rivers to marine environments. With a substantial percentage of marine plastic waste originating from land-based sources, comprehending the trajectory and tem...
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MDPI AG
2025-02-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/25/3/937 |
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| author | Peter Cleveland Ann Morrison |
| author_facet | Peter Cleveland Ann Morrison |
| author_sort | Peter Cleveland |
| collection | DOAJ |
| description | Plastic pollution in waterways poses a significant global challenge, largely stemming from land-based sources and subsequently transported by rivers to marine environments. With a substantial percentage of marine plastic waste originating from land-based sources, comprehending the trajectory and temporal experience of single-use plastic bottles assumes paramount importance. This project designed, developed, and released a plastic pollution tracking device, coinciding with Vietnam’s annual Plastic Awareness Month. By mapping the plastic tracker’s journey through the Saigon River, this study generated high-fidelity data for comprehensive analysis and bolstered public awareness through regular updates on the Re-Think Plastics Vietnam website. The device, equipped with technologies such as drone flight controller, open-source software, embedded computing, and cellular networking effectively captured GPS position, track, and localized conditions experienced by the plastic bottle tracker on its journey. This amalgamation of data contributes to the understanding of plastic pollution behaviors and serves as a data set for future initiatives aimed at plastic prevention in the ecologically sensitive Mekong Delta. By illuminating the transportation of single-use plastic bottles in the riparian waterways of Ho Chi Minh City and beyond, this study plays a role in collective efforts to understand plastic pollution and preserve aquatic ecosystems. By deploying a GPS-enabled plastic tracker, this study provides novel, high-resolution empirical data on plastic transport in urban tidal systems. These findings contribute to improving waste interception strategies and informing environmental policies aimed at reducing plastic accumulation in critical retention zones. |
| format | Article |
| id | doaj-art-ff08c216c0314dc8880e4acb18b28ddc |
| institution | DOAJ |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-ff08c216c0314dc8880e4acb18b28ddc2025-08-20T02:48:05ZengMDPI AGSensors1424-82202025-02-0125393710.3390/s25030937Sông Sài Gòn: Extreme Plastic Pollution Pathways in Riparian WaterwaysPeter Cleveland0Ann Morrison1School of Future Environments Huri Te Ao, Faculty of Design and Creative Technologies, Auckland University of Technology, City Campus, Auckland 1010, New ZealandSchool of Future Environments Huri Te Ao, Faculty of Design and Creative Technologies, Auckland University of Technology, City Campus, Auckland 1010, New ZealandPlastic pollution in waterways poses a significant global challenge, largely stemming from land-based sources and subsequently transported by rivers to marine environments. With a substantial percentage of marine plastic waste originating from land-based sources, comprehending the trajectory and temporal experience of single-use plastic bottles assumes paramount importance. This project designed, developed, and released a plastic pollution tracking device, coinciding with Vietnam’s annual Plastic Awareness Month. By mapping the plastic tracker’s journey through the Saigon River, this study generated high-fidelity data for comprehensive analysis and bolstered public awareness through regular updates on the Re-Think Plastics Vietnam website. The device, equipped with technologies such as drone flight controller, open-source software, embedded computing, and cellular networking effectively captured GPS position, track, and localized conditions experienced by the plastic bottle tracker on its journey. This amalgamation of data contributes to the understanding of plastic pollution behaviors and serves as a data set for future initiatives aimed at plastic prevention in the ecologically sensitive Mekong Delta. By illuminating the transportation of single-use plastic bottles in the riparian waterways of Ho Chi Minh City and beyond, this study plays a role in collective efforts to understand plastic pollution and preserve aquatic ecosystems. By deploying a GPS-enabled plastic tracker, this study provides novel, high-resolution empirical data on plastic transport in urban tidal systems. These findings contribute to improving waste interception strategies and informing environmental policies aimed at reducing plastic accumulation in critical retention zones.https://www.mdpi.com/1424-8220/25/3/937plastic wasteriparian waterwayshidden Markov modelextreme pollution |
| spellingShingle | Peter Cleveland Ann Morrison Sông Sài Gòn: Extreme Plastic Pollution Pathways in Riparian Waterways Sensors plastic waste riparian waterways hidden Markov model extreme pollution |
| title | Sông Sài Gòn: Extreme Plastic Pollution Pathways in Riparian Waterways |
| title_full | Sông Sài Gòn: Extreme Plastic Pollution Pathways in Riparian Waterways |
| title_fullStr | Sông Sài Gòn: Extreme Plastic Pollution Pathways in Riparian Waterways |
| title_full_unstemmed | Sông Sài Gòn: Extreme Plastic Pollution Pathways in Riparian Waterways |
| title_short | Sông Sài Gòn: Extreme Plastic Pollution Pathways in Riparian Waterways |
| title_sort | song sai gon extreme plastic pollution pathways in riparian waterways |
| topic | plastic waste riparian waterways hidden Markov model extreme pollution |
| url | https://www.mdpi.com/1424-8220/25/3/937 |
| work_keys_str_mv | AT petercleveland songsaigonextremeplasticpollutionpathwaysinriparianwaterways AT annmorrison songsaigonextremeplasticpollutionpathwaysinriparianwaterways |