5:15 PM - 6:45 PM
[MIS09-P05] Spatial distribution and characterization of microplastics in surface sediments in Hakata Bay, Fukuoka, Japan
Keywords:microplastics, sediment, shape, polymer composition, Hakata Bay
To demonstrate the transport and deposit process of microplastics (MP) in the coastal area, this study investigated the distribution and characteristics of MP in sediments in Hakata Bay, Fukuoka Prefecture. The sediments were sampled at three sites from the mouth of the Mikasa River to the mouth of Hakata Bay using the grab sampler in November, 2022. To extract MP from large amount sediment, the collected samples were fractionated using tap water filtered through a 10 µm mesh net and a sieve into three fractions; over 1 mm, 1 mm to 500 µm, and 300-500 µm. These fractionated samples were collected by density separation with 7.8 mol/L NaI solution and then the collected suspension samples were oxidised with 30% H2O2. The solid particulates were measured shape and color and picked using an automatic measuring microscope system equipped with a manipulator (Itaki et al, 2020). The chemical composition of each solid particulates was determined by using a Fourier-transform infrared spectrometer (FT-IR) coupled with an attenuated total reflectance (ATR) accessory.
The number of MP in 1 kg dry sediment was 341.4 particles/kg at the site of the river mouth and showed a decreasing trend towards the mouth of the bay, at 48.7 and 28.4 particles /kg respectively. The maximum lengths of MP at all sites were mainly in the range of 2 mm to 500 µm and finer MP blow 700 µm were observed at the river mouth site. The polymer compositions showed polyethylene (PE) appeared approximately 20% of the plastic composition at all sites. PE and polypropylene (PP) were dominant over 50% in the site of river mouth. In the site of central part, the highest composition was PE for 25%, and then polyamide (PA) for 19% and ethylene-propylene rubber (EPDM) at 13%. Polystyrene (PS) was highest composition for 27% in the bay mouth site, followed PE and polyacrylic, respectively 18%. The concentration of MP was a high at the river mouth and decreased toward the bay mouth indicated that the MP contained in the sediments were mainly derived from the river. The migration process of MP will be discussed by comparing with the characteristics of the sediments.
This research was performed by the Environment Research and Technology Development Fund (JPMEERF20221004) of the Environmental Restoration and Conservation Agency provided by Ministry of the Environment of Japan.
Reference: Itaki et al. (2020) Automated collection of single species of microfossils using a deep learning– micromanipulator system. Progress in Earth and Planetary Science, 7, 19.
The number of MP in 1 kg dry sediment was 341.4 particles/kg at the site of the river mouth and showed a decreasing trend towards the mouth of the bay, at 48.7 and 28.4 particles /kg respectively. The maximum lengths of MP at all sites were mainly in the range of 2 mm to 500 µm and finer MP blow 700 µm were observed at the river mouth site. The polymer compositions showed polyethylene (PE) appeared approximately 20% of the plastic composition at all sites. PE and polypropylene (PP) were dominant over 50% in the site of river mouth. In the site of central part, the highest composition was PE for 25%, and then polyamide (PA) for 19% and ethylene-propylene rubber (EPDM) at 13%. Polystyrene (PS) was highest composition for 27% in the bay mouth site, followed PE and polyacrylic, respectively 18%. The concentration of MP was a high at the river mouth and decreased toward the bay mouth indicated that the MP contained in the sediments were mainly derived from the river. The migration process of MP will be discussed by comparing with the characteristics of the sediments.
This research was performed by the Environment Research and Technology Development Fund (JPMEERF20221004) of the Environmental Restoration and Conservation Agency provided by Ministry of the Environment of Japan.
Reference: Itaki et al. (2020) Automated collection of single species of microfossils using a deep learning– micromanipulator system. Progress in Earth and Planetary Science, 7, 19.