日本地球惑星科学連合2021年大会

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[J] 口頭発表

セッション記号 M (領域外・複数領域) » M-IS ジョイント

[M-IS20] 地球科学としての海洋プラスチック

2021年6月5日(土) 13:45 〜 15:15 Ch.10 (Zoom会場10)

コンビーナ:磯辺 篤彦(九州大学応用力学研究所)、川村 喜一郎(山口大学)、岡崎 裕典(九州大学大学院理学研究院地球惑星科学部門)、土屋 正史(国立研究開発法人海洋研究開発機構 地球環境部門)、座長:磯辺 篤彦(九州大学応用力学研究所)

13:45 〜 14:00

[MIS20-01] 浮遊海洋プラスチックの全球モデリングによる輸送解析

*磯辺 篤彦1 (1.九州大学応用力学研究所)

A particle tracking model (PTM) computing behavior of both plastic debris and microplastics in the upper ocean was established. These particles were carried by surface ocean currents provided by an ocean reanalysis product, Stokes drift computed using a wave model driven by satellite-derived winds, and windage. The generating plastic debris was given from river mouths and fisheries worldwide based on the observed data. The PTM includes the processes of beaching/re-drifting, fragmentation from plastic debris to microplastics on beaches, and removal of microplastics from the model domain. These processes proceed on timescales specified in the model. The timescales for beaching/re-drifting were determined by the field experiments, while other two timescales were chosen through trial and error to be consistent with the actual abundance of oceanic microplastics worldwide. To obtain the actual abundance of oceanic microplastics, a total of 8156 pelagic microplastics samples from the world’s oceans were synthesized to create a dataset composed of raw, calibrated, and processed data. The raw microplastic abundance data were obtained by different research projects using surface net tows or continuous seawater intake. Fibrous microplastics were removed from the calibrated dataset. Microplastic abundance, which fluctuates of microplastic abundance owing to vertical mixing under different oceanic conditions, was standardized in the processed data.
On the basis of the modeled results validated by the observed data, quantities of floating plastic debris, plastic debris washed ashore on beaches, floating microplastics, microplastics on beaches, and removing microplastics from the model domain were computed by reducing the PTM results to a linearized model.