Abundance of microlitter (including microplastics) in riverine samples (sediment, surface waters and biota) at selected locations across the Orange-Senqu River basin and associated land use data 2021
Abundance data of microlitter (including microplastics) in riverine samples (sediment, surface waters and biota) were collected at selected locations across the Orange-Senqu River basin and associated land use in 2021. The file entitled 'List microlitter biota' presents the abundance of microplastics in riverine biota at selected locations across the Orange-Senqu River basin. The file entitled 'List microlitter sediment' presents the abundance of microplastics in riverine sediments at selected locations across the Orange-Senqu River basin. The file entitled 'List microlitter surface waters' presents the abundance of microplastics in riverine surface waters at selected locations across the Orange-Senqu River basin. The file entitled 'LU' summarises the local watershed traits including population density, land use, rainfall and flows.
dataset
https://data.cefas.co.uk/view/22014
name: Cefas Data Portal
description: The Cefas Data Portal contains metadata records and data sets available to download and connect to in support of our commitment to open science. Data is available in the following formats: Binary download, CSV, ESRI Shapefile. The data can also be accessed via the WFS and WMS protocols.
function: download
CEFAS22014
https://data.cefas.co.uk
eng
environment
revision
2011-03-25
publication
2008-06-01
revision
2011-03-25
publication
2008-06-01
revision
2010-05-18
publication
2012-01-11
publication
2012-01-11
10.00
30.00
-20.00
-40.00
2021-10-04
2021-10-15
publication
2024-08-23
revision
2024-08-23
creation
2024-08-22
notPlanned
The riverine sediment samples were analysed using a LUMOS II Fourier transform infrared spectroscopy (FTIR) microscope with focal plane array (FPA) detector (Bruker, UK) at the Cefas microplastics laboratory. Dried sediments were digested using the dropwise addition of filtered (0.2 μm) H2O2 (30%). Following digestion, density separation used a 1.5 g.mL-1 solution of ZnCl2 . Centrifugated supernatant was transferred to a previously cleaned filtration unit and filtered using a 25 mm diameter 0.2 μm porosity Whatman Anodisc (VWR, UK). Each filter was then carefully transferred to previously cleaned glass petri dish and transported to a drying cabinet for drying under 50 °C prior to analysis using a LUMOS II micro-FTIR with FPA detector (Bruker, UK). FTIR spectra were collected using FPA detector in transmission mode using a single scan in the range 4000-1300 cm-1 at a resolution of 8 cm-1 using a 4x4 binning (limit of detection [LOD] ~20 μm). Spectra were converted using a macro in Bruker OPUS (version 8.5) and particle identification was carried out using the siMPle software developed by Aalborg University (Denmark). The riverine water samples were vacuum filtered and stained with Nile Red solution for 30 minutes. Visual examination of filters under a Leica MZ10F with GXCAM-U3PRO-20 camera attachment microscope using both blue and white light was conducted. A subset of suspected microlitter was identified for confirmation and polymer identification using a LUMOS II micro-FTIR. The riverine biota samples were chemically digested using a 30% KOH:NaClO v:v solution. Beakers were sonicated for 5 minutes (VWR ultrasonic cleaner, T2020SX26782) and placed in an incubator shaker (VWR incubating mini shaker, 980151UK) at 40 °C, 50 rpm for three days. On the fourth day, 40 mL of degreaser (Elbow Grease all-purpose degreaser) was added to each beaker and incubated for a further 24 hours. Following digestion, filtration, visual examination, and FTIR analysis of digested fish was completed in the same manner as surface water samples. Each item was imaged in GXCapture-T software (version x64, 4.10.16968.20200415). The second file (LU) containing the most recent land cover data (updated in 2020) for South Africa were extracted from the Department of Forestry, Fisheries, and the Environment (DFFE) open source South African National Land Cover database ( `https://egis.environment.gov.za/sa_national_land_cover_datasets`_). The database has 73 land cover classes which were reclassified using the ‘reclass’ tool in ArcGIS into six land use types: agriculture, industrial, natural and plantation, semi-urban, urban, and waterbody .. _`https://egis.environment.gov.za/sa_national_land_cover_datasets`: https://egis.environment.gov.za/sa_national_land_cover_datasets
publication
2013-12-10
false
See the referenced specification
publication
2010-12-08
true
See the referenced specification
Unknown
Centre for Environment, Fisheries and Aquaculture Science, Lowestoft Laboratory (CEFAS)
Cefas Lowestoft Laboratory
Pakefield Road
Lowestoft
NR33 0HT
UK
originator
Centre for Environment, Fisheries and Aquaculture Science, Lowestoft Laboratory (CEFAS)
Cefas Lowestoft Laboratory
Pakefield Road
Lowestoft
NR33 0HT
UK
custodian
Centre for Environment, Fisheries and Aquaculture Science, Lowestoft Laboratory (CEFAS)
Cefas Lowestoft Laboratory
Pakefield Road
Lowestoft
NR33 0HT
UK
distributor
Department for Environment, Food and Rural Affairs (DEFRA)
owner
Centre for Environment, Fisheries and Aquaculture Science, Lowestoft Laboratory (CEFAS)
Cefas Lowestoft Laboratory
Pakefield Road
Lowestoft
NR33 0HT
UK
pointOfContact
2024-08-23T03:00:53