Plastic Pollution in the Oceans: Characterization and Modeling
|
P.F.J. Lermusiaux, A. Gupta, C.S. Kulkarni, M. Doshi Massachusetts Institute of Technology
|
G.R. Flierl, J. Marshall, T. Peacock, S.J. Levang Massachusetts Institute of Technology
|
Project Summary Ongoing MIT-MSEAS Research Additional Links MSEAS Project-supported Publications Background Information
|
|
| This research is sponsored by the MIT Environmental Solutions Initiative. | |||
Project Summary
Since the 19th and early-20th century, plastics have become ubiquitous in the world. Plastics have outgrown most man-made materials: their global volume production has surpassed that of steel production in the late 1980s (Fernandez et al., 2018). The MIT Environmental Solutions Initiative (MIT-ESI) aims to tackle this challenge through the expertise of our interdisciplinary faculty, ranging from materials, to manufacturing and design, to smart sensing and advanced computational modeling and data-driven learning. Through our approaches and collaborations, our long-term goal is to develop a plastic free environment that will ensurethe health of our planet.
Background information is available below.
| Top of page |  |
Ongoing MIT-MSEAS Research
Specific Objectives:
- Utilize existing and formulate new models of a series of processes for marine plastic transports, dynamics, and relative motions with respect to the ocean water
- Complete a set of regional multiscale simulations and sensitivity studies. This includes modeling and simulations at coastal, regional, and basin scales.
- Use particle tracking models applied to the MIT-GCM and other global model outputs to investigate the global distributions, concentrations, and transport of plastics
- Further develop our MSEAS capability of predicting and characterizing the uncertainty of 3D material-plastic transports solving stochastic PDEs, instead of using a large ensemble of trajectories for a large number of sample ocean flow conditions.
- Utilize our MSEAS PDE-based Bayesian inference schemes for the assimilation of marine plastic data and model learning
- Utilize Observation System Simulation Experiments (OSSEs) to optimize the sensing, collection, and cleaning of marine plastics
- Demonstrate our probabilistic predictions and analyses of marine plastics transports and dynamics in our local Massachusetts Bay and Cape Cod region and its estuaries, possibly extending the modeling to the New England Shelf and Middle Atlantic Bight ocean region.
Publications
MSEAS Project-supported Publications
| Top of page | |
Additional Links
| Top of page | |
Background Information
Plastic production continues to increase and undesirable impacts from plastic pollution have proliferated throughout the world, in our lands, rivers and oceans, as well as in animals and human foods. It is time for the world to solve this problem. Banning plastics is not sufficient nor immediately practical. Just as for CFCs, we need to engineer alternatives, but in the plastic case, we also need to clean the environment due to the long plastic lifetimes. Some of the needs include: design and manufacture plastic alternatives for varied applications, from packaging to automotive and fishing; understand, model, and forecast plastic transports and dispersion in our estuaries and oceans, combining fundamental dynamics with uncertainty quantification, data assimilation, and machine learning; develop and build intelligent autonomous robots for optimized plastic sensing and cleaning, on land and at sea; harvest energy or other useful by-products from plastic waste without new pollution; integrate all of these systems into practical world and regional solutions.
| Top of page | |
