Contextualizing count data using computational transport modeling

Session: 46. - Plastics in the Great Lakes: Characterizing the Problem and Finding Solutions

Rebecca Knauff, Rochester Inst. of Tech., [email protected]
Matthew Hoffman, Rochester Inst. of Technology, School of Mathematical Sci., [email protected]

Abstract

Numerical modeling has demonstrated the potential to estimate the spatial and temporal patterns of plastic pollution in the Great Lakes. In this way it can be an effective compliment to traditional in situ observations, especially since recent work has highlighted the variability of plastic counts from trawls taken in the same location over time intervals of hours. In this work we use a particle transport model built on current fields from the NOAA operational forecast system to quantify the importance of transport in explaining differences in particle counts collected in different years. We look at data collected from 2012 to 2014 and use both forward and backward particle propagation in the model to investigate differences in particle sources and pathways to the sampling locations. In addition we examine Lagrangian Coherent Structures (LCS) in the flow prior to the sampling times to identify the presence or absence of barriers to transport that could lead to accumulation or dispersion of plastic particles. 

1. Keyword
microplastics

2. Keyword
computer models

3. Keyword
pollutants