This readme.txt file was generated on 2020/04/08 by Sarah W. Grosshuesch ------------------- GENERAL INFORMATION ------------------- 1. Title of Dataset An Analysis of Microlitterand Microplastics from Lake Superior Beach Sand and Surface-Water 2. Author Information Principal Investigator Contact Information Name: Elizabeth C. Minor Institution: Large Lakes Observatory and Department of Chemistry and Biochemistry, University of Minnesota Duluth Address: 2205 East 5th St., Duluth, MN 55812, USA Email: eminor@d.umn.edu ORCID: 0000-0001-6930-9338 Co-investigator Contact Information Name: Roselynd Lin Institution: Department of Chemistry and Biochemistry, University of Minnesota Duluth Address: 1039 University Drive and 2205 East 5th St, Duluth, MN 55812 USA Email: ORCID: Contact Information Name: Alvin Burrows Institution: Department of Chemistry and Biochemistry, University of Minnesota Duluth Address: 1039 University Drive and 2205 East 5th St, Duluth, MN 55812 USA Email: ORCID: Contact Information Name: Ellen M. Cooney Institution: Large Lakes Observatory, University of Minnesota Duluth Address: 1039 University Drive and 2205 East 5th St, Duluth, MN 55812 USA Email: ORCID: Contact Information Name: Sarah Grosshuesch Institution: Large Lakes Observatory, University of Minnesota Duluth Address: 1039 University Drive and 2205 East 5th St, Duluth, MN 55812 USA Email: ORCID: Contact Information Name: Brenda LaFrancois Institution: National Park Service, Interior Regions 3, 4, and 5 (Great Lakes, Mississippi, and Missouri Basins) Address: 2800 Lake Shore Drive East, Ashland, WI 54806 Email: ORCID: 3. Date of data collection: 2018-05-21 to 2018-07-25 4. Geographic location of data collection: Data was collected primarily within the Apostle Islands National Lakeshore. Other data was collected from sites in close proximity to the Lakeshore on Lake Superior and adjacent waters. 5. Information about funding sources that supported the collection of the data: The project was funded by a cooperative agreement between theNational Park Service and the University of Minnesota with support from the Great Lakes Restoration Initiative and the National Park Service Water Resources Division. -------------------------- SHARING/ACCESS INFORMATION -------------------------- 1. Licenses/restrictions placed on the data: none 2. Links to publications that cite or use the data: none at present, paper submitted for publication 3. Links to other publicly accessible locations of the data: none 4. Links/relationships to ancillary data sets: none 5. Was data derived from another source? no If yes, list source(s): 6. Recommended citation for the data: Minor, Elizabeth C; Lin, Roselynd; Burrows, Alvin; Cooney, Ellen M; Grosshuesch, Sarah; LaFrancois, Brenda. (2020). An Analysis of Microlitter and Microplastics from Lake Superior Beach Sand and Surface-Water. Retrieved from the Data Repository for the University of Minnesota, https://doi.org/10.13020/7c7w-9m80. --------------------- DATA & FILE OVERVIEW --------------------- 1. File List A. Filename: Plastics for STOTEN_R1_062620_changes accepted & figs and tables separate.pdf Short description: Report B. Filename: Plastics for STOTEN_Appendix_revised_062620.pdf Short description: Appendix C. Filename: Highlights for STOTEN_revised_062620.pdf Short description: Highlights D. Filename: Graphic abstract_062620.pdf Short description: Graphic abstract E. Filename: Fig 1_070620.tif Short Description: Figure 1 F. Filename: Fig 2_070620.tif Short Description: Figure 2 G. Filename: Fig 3_070620_labeled.tif Short Description: Figure 3 H. Filename: Fig 4_070620.tif Short Description: Figure 4 I. Filename: Fig 5_070620.tif Short Description: Figure 5 J. Filename: Fig 6_070620.pdf Short Description: Figure 6 K. Filename: NPSAI –Samples.csv Short description:Spreadsheet detailing sample collection date, sample type, sample IDs, site number, site name, oxidation information, py-GCMS filenames. (.csv) L. Filename: NPS AI -Particle Morphology Definitions.pdf Short description: definition of shape of particles listed in microscopy files (.pdf) M. Folder Name: NPS AI -Py-GCMS-20200413T162231Z-001.zipS hort description: py-GCMS spectra (.jpg) N. Folder Name: NPS AI -Images-20200413T162347Z-001.zip Short description: Images (.jpg) of samples. O. Folder Name: NPS AI -Microscopy-20200413T162302Z-001.zip Short description: spreadsheets for each sample, count blank, field blank included in the report 2. Relationship between files: explains type of particle in OK-samples in the reportM, N, O-data collected on samples listed in K 3. Additional related data collected that was not included in the current data package: none that was covered in report 4. Are there multiple versions of the dataset? no --------------------- METHODOLOGICAL INFORMATION -------------------------- 1. Description of methods used for collection/generation of data: Discussed in report(Plastics for STOTEN_R1_062620_changes accepted & figs and tables separate.pdf). 2. Methods for processing the data: Discussed in report(Plastics for STOTEN_R1_062620_changes accepted & figs and tables separate.pdf).Microscopy was obtained with the use of Optical Microscopes (details in the report). py-GCMS data was collected on Agilent/Gerstel instrumentation (details in the report) and converted to acceptable format for archiving. Excel spreadsheets were used for data compilation. Statistics were calculated (details in the report). 3. Instrument-or software-specific information needed to interpret the data: none Discussed in report. Spectra from the Py-GCMS were analyzed using software discussed in the report. 4. Standards and calibration information, if appropriate: none required 5. Environmental/experimental conditions: samples collected from the natural environment; sample processing/analysis conducted in laboratory setting 6. Describe any quality-assurance procedures performed on the data: Field blanks were collected and processed/analyzed under the same conditions as samples. Count blanks representing the time corresponding samples were open to ambient conditions were examined under microscopy. These quality assurance procedures are discussed in the report. "As a positive control, sand from Park Point, MN (near Site 11) was collected, sieved through a 4 mm metal sieve and ashed in a combustion oven at 450 °C for four hours to remove any previous microplastic burden. Thermogravimetric analysis has shown that onset of plastic loss occurs just above 200 °C and that 450 °C efficiently removes polystyrene, polymethyl methacrylate, PVC and PE (Zhou et al., 2019). The ashed sand was then split into two equal aliquots, which were each spiked with ten polyethylene (PE) spheres (Cospheric CPB-0.96, 600-710 µm) and ten polypropylene (PP) fragments, created with a lab grinder and approximately 3 mm in length. These spiked sand aliquots (Controls A and B) and a blank without sand but spiked with the same number of PE and PP particles were then subjected to density extraction, filtration, and microscopy as described above for the spring 2018 samples. Recoveries in each of the spiked sand samples were 9/10 PE and 10/10 PP particles. The recovery in the spiked blank was also 9/10 PE and 10/10 PP particles. To expand the positive control to include oxidation, we resuspended the particles from the density positive control samples described above. In the spiked blank out of the original 10 PE and 10 PP particles, 5 PE whole spheres and 5 (probable, identified by microscopy and melt testing) PE fragments were found along with 10/10 PP particles. In Control A, 7 PE spheres and 6 probable PE fragments out of 10 original particles were found along with 11 PP particles. In Control B, 9/10 PE spheres and 10/10 PP particles were found. The results from the spiked blank and control A indicate that in some cases, the oxidation step appears to fragment the original plastic particles." 7. People involved with sample collection, processing, analysis and/or submission: Elizabeth Minor, Roselynd Lin, Alvin Burrows, Ellen Cooney, Sarah Grosshuesch, Brenda LaFrancois, Ted Gostomoski, Julie Van Stappen, Tom Frantti, Julia Agnich. ----------------------------------------- DATA-SPECIFIC INFORMATION FOR: NPS AI -Samples.csv ----------------------------------------- 1. Number of variables: 7 2. Number of cases/rows: 58 3. Missing data codes: none Codes are explained in the file. 4. Variable List Type of sample: beach sand or water Sample Code: AI (stands for Apostle Islands), 1(May sampling) or 2(July sampling)-number(site number)-sample collection position-blank OR ox(sample oxidized) OR CB (count blank) (these are explainedon the spreadsheet) Date Sampled: month.date.year format Site Number: ranges from 1-12, water samples do not have a site number Site Name: text describing collection location Fenton oxid ?: if x, sample was oxidized, if -, no oxidation Py-gcms files: -if no py-gs/ms file, if py_yymm### then spectra is in Py-GCMS files ----------------------------------------- DATA-SPECIFIC INFORMATION FOR: NPS AI -Images-20200413T162347Z-001.zip ----------------------------------------- 1. These files are .jpg images of various particles encountered in microscopy. There are no variables to describe. ----------------------------------------- DATA-SPECIFIC INFORMATION FOR: NPS AI -Py-GCMS-20200413T162231Z-001 ----------------------------------------- 1. These files are .jpg spectra obtained from analysis of particles. No variables to detail. ----------------------------------------- DATA-SPECIFIC INFORMATION FOR: NPS AI -Microscopy-20200413T162302Z-001.zip ----------------------------------------- 1. Number of variables: this varies depending on the number and type of particles found in the sampleParticle morphology definitions found in separate pdf file(NPS AI -Particle Morphology Definitions.pdf).