EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Leveraging community data to characterize river macroplastic pollution

Lisa Watkins1 and Jordan Yu2
Lisa Watkins and Jordan Yu
  • 1Cornell University, Ithaca, United States of America (
  • 2Chattahoochee Riverkeeper, Atlanta, United States of America

Intercepting mismanaged waste before it reaches the ocean is key to addressing global plastic pollution and its associated ecological effects. A successful strategy for disrupting the transport of macro debris is “trash traps”, cages and booms currently deployed in rivers worldwide to capture floating items. Existing traps are largely managed by NGOs and municipalities, many of whom collect comprehensive data on all captured trash. These community datasets provide a substantial, largely untapped opportunity to advance scientific understanding of riverine plastic pollution.

For this study, we partnered with Chattahoochee Riverkeeper, an NGO in Atlanta, U.S.A. that manages 11 trash traps across 6 rivers spanning a spectrum of urban to agricultural watersheds. After each rainstorm, NGO staff assess all captured debris according to U.S. Environmental Protection Agency Escaped Trash Assessment Protocol (ETAP), noting total volume and weight of the contents, as well as each item’s condition, material-type (e.g. glass, metal), and use (out of 41 item categories).

We analyzed data from each of their 281 trap collections occurring between 2019 and 2021, which captured 8904 items. We found that 80% of collected trash was plastic, with the most common item types being plastic bottles, Styrofoam and plastic bags. Their system of 11 trash traps intercepted 5.7 kg/day of trash from the Chattahoochee River watershed (median: 0.4 kg/day/trap). Though this amounts to 2 tonnes of trash in these tributaries annually, it’s the equivalent of each watershed resident contributing less than a water bottle each year (5.6 g/person/yr), supporting the need for centralized or system-scale pollution intervention strategies over distributed ones. To explore potential drivers of macroplastics, we utilize a general mixed effects model and find rainfall, watershed imperviousness, and local human engagement to be significant predictors of captured quantity. The model coefficients indicate, however, that these factors may be less important to macroplastics than they traditionally are for other river-transported pollutants. We suspect this is due to macroplastics being highly affected by harder-to-capture human activities.

In our presentation we explore these findings in the context of other macroplastic studies worldwide. Through this work, we hope to highlight how collaborative research principles can be used to leverage the local expertise and abundant, underutilized data of NGOs for the advancement of riverine plastic science, while also better engaging local communities around solutions.

How to cite: Watkins, L. and Yu, J.: Leveraging community data to characterize river macroplastic pollution, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-440,, 2022.


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