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Rapid-Survey Methodology to Assess Litter Volumes along Large River Systems—A Case Study of the Tamsui River in Taiwan

Author

Listed:
  • Falk Schneider

    (Department of Environmental Engineering, National Cheng Kung University, Tainan 701, Taiwan)

  • Alexander Kunz

    (Department of Geosciences, National Taiwan University, Taipei 106, Taiwan)

  • Chieh-Shen Hu

    (IndigoWaters Institute, Kaohsiung City 807, Taiwan)

  • Ning Yen

    (IndigoWaters Institute, Kaohsiung City 807, Taiwan)

  • Hsin-Tien Lin

    (Department of Environmental Engineering, National Cheng Kung University, Tainan 701, Taiwan)

Abstract

Riverbanks are an important source of plastic pollution. However, the current assessment methods for riverbank litter are based on a point-based sampling which is time consuming and limited in scope. To quickly assess hotspot areas and litter compositions in larger areas, this study developed a new citizen science bicycle survey for riverine debris. Covering 281.5 km of the Tamsui river system in Taiwan, the new methodology was tested at one of the most plastics polluted rivers in the world. The results revealed an average litter density of 15.3 m 3 /km at the river mouth and of 0.2 m 3 /km to 2.8 m 3 /km along the riverbanks further upstream. The coastline was mainly polluted by derelict fishing gear whereas single-use plastics and illegally dumped waste dominated the upstream areas. A correlation between litter and population density could not be identified, but it was noted that litter hotspots occur at cut banks and near mangrove vegetation. Overall, the new methodology proved suitable to collect large quantities of data for scientific purposes and to quickly detect litter accumulations prior to clean-up activities.

Suggested Citation

  • Falk Schneider & Alexander Kunz & Chieh-Shen Hu & Ning Yen & Hsin-Tien Lin, 2021. "Rapid-Survey Methodology to Assess Litter Volumes along Large River Systems—A Case Study of the Tamsui River in Taiwan," Sustainability, MDPI, vol. 13(16), pages 1-15, August.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:16:p:8765-:d:609171
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