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Dataset on mesoplastics and microplastics abundances and characteristics from sandy beaches before and after typhoon events in northern Taiwan.
Kunz, Alexander; Löwemark, Ludvig; Yang, Joshua.
Afiliação
  • Kunz A; Research Center for Environmental Changes, Academia Sinica, No. 128, Sec. 2, Academia Road, 115201 Taipei City, Taiwan.
  • Löwemark L; Department of Geosciences, National Taiwan University, No. 1, Section 4, Roosevelt Road, 106216 Taipei City, Taiwan.
  • Yang J; Department of Geosciences, National Taiwan University, No. 1, Section 4, Roosevelt Road, 106216 Taipei City, Taiwan.
Data Brief ; 49: 109317, 2023 Aug.
Article em En | MEDLINE | ID: mdl-37600133
ABSTRACT
A comprehensive dataset is presented, which describes the abundance, shapes, and colors of meso- and microplastic particles collected from two sandy beaches situated on the north coast of Taiwan. The sampling of beach sand was conducted repetitively at fixed locations over a time period of 20 months, commencing from April 2018 to November 2019, with the aim of monitoring the variations in distribution and composition of plastic particles. A total of three adjacent transects perpendicular to the waterline were sampled, with bulk sand samples collected from 50 × 50 cm quadrats. The samples were subjected to drying, weighing, and sieving to obtain mesoplastic fractions (5-25 mm) and microplastic fractions (1-5 mm). Visual identification was employed to extract mesoplastic particles, while density separation using a saturated NaCl solution was utilized to extract microplastic particles. The particles were counted visually under a stereo microscope, and subsequently classified based on their shape and color. Any unknown particles were subjected to FTIR spectroscopy. Particle count data are presented as particles per unit area (0.25 m2) but can be converted to particles per kg d.w. by employing the weight of dry sand, as provided in the tables. The dataset encompasses a time series and delineates the changes in particle distribution and composition following extreme weather events. It can be utilized for further research by reanalyzing the data from different perspectives or by incorporating other factors.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Data Brief Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Taiwan

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Data Brief Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Taiwan