five

CLiP Solomon Islands Microplastics in sediment 2017

收藏
DataCite Commons2026-03-24 更新2024-07-13 收录
下载链接:
https://www.cefas.co.uk/data-and-publications/dois/clip-solomon-islands-microplastics-in-sediment-2017/
下载链接
链接失效反馈
官方服务:
资源简介:
This dataset contains 2 csv files. One file contains data on microplastic abundance expressed in number of particles per 5g dried sediment from 6 riverine, transitional and coastal locations on Guadalcanal Island (Solomon Islands) in 2017. One file contains spectrum analysis for some of the particles carried out with a ATR-FTIR. A READ-ME text file contains description of columns content for these two csv files. There is a .zip file that includes a csv file with the description of the plastic particles larger than 5mm (macroplastic) found in the samples and their pictures. Microplastics are plastic particles with size less than 5 mm in diameter (Arthur et al., 2008). The Commonwealth Litter Project (CLiP) supported Solomon Islands to take action on plastics entering the oceans. The assessment of microplastics in seawater was part of the action plan to define scientific baselines for future monitoring purposes and comparison. Samples were dried for 3 days (less than 50 degrees centigrade) and weighted. Density separation using NaCl solution and a centrifuge, filtering the supernatant. This was followed by a chemical digestion with a KOH:NaClO solution for 3 days at 50 degrees centigrade whilst shaking. Plastic particles were then stained with Nile Red dye and a digital image was acquired through a microscope. Microplastic particles were then counted and a subsample of particles (between 1 and 10 percent) was processed through a ATR—FTIR to identify particle composition comparing their spectrum to a polymers library. The presence and number of particles of plastic more than 5mm was also noted for each sample.
提供机构:
Centre for Environment, Fisheries and Aquaculture Science, Lowestoft, UK
创建时间:
2019-04-15
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作