Microplastics and nanoplastics in the marine-atmosphere environment

The discovery of atmospheric micro(nano)plastic transport and ocean-atmosphere exchange points to a highly complex marine plastic cycle, with negative implications for human and ecosystem health. Yet, observations are currently limited. In this Perspective, we quantify the processes and fluxes of the marine-atmospheric micro(nano)plastic cycle, with the aim of highlighting the remaining unknowns in atmospheric micro(nano)plastic transport. Between 0.013 and 25 million metric tons per year of micro(nano)plastics are potentially being transported within the marine atmosphere and deposited in the oceans. However, the high uncertainty in these marine-atmospheric fluxes is related to data limitations and a lack of study intercomparability. To address the uncertainties and remaining knowledge gaps in the marine-atmospheric micro(nano)plastic cycle, we propose a future global marine-atmospheric micro(nano)plastic observation strategy, incorporating novel sampling methods and the creation of a comparable, harmonized and global data set. Together with long-term observations and intensive investigations, this strategy will help to define the trends in marine-atmospheric pollution and any responses to future policy and management actions. Atmospheric transport of microplastics could be a major source of plastic pollution to the ocean, yet observations currently remain limited. This Perspective quantifies the known budgets of the marine-atmospheric micro(nano)plastic cycle and proposes a future global observation strategy.Peer reviewe

Validity and limitations of simple reaction kinetics to calculate concentrations of organic compounds from ion counts in PTR-MS

In September 2017, we conducted a proton-transfer-reaction mass-spectrometry (PTR-MS) intercomparison campaign at the CESAR observatory, a rural site in the central Netherlands near the village of Cabauw. Nine research groups deployed a total of 11 instruments covering a wide range of instrument types and performance. We applied a new calibration method based on fast injection of a gas standard through a sample loop. This approach allows calibrations on timescales of seconds, and within a few minutes an automated sequence can be run allowing one to retrieve diagnostic parameters that indicate the performance status. We developed a method to retrieve the mass-dependent transmission from the fast calibrations, which is an essential characteristic of PTR-MS instruments, limiting the potential to calculate concentrations based on counting statistics and simple reaction kinetics in the reactor/drift tube. Our measurements show that PTR-MS instruments follow the simple reaction kinetics if operated in the standard range for pressures and temperature of the reaction chamber (i.e. 1-4 mbar, 30-120 degrees, respectively), as well as a reduced field strength E/N in the range of 100-160 Td. If artefacts can be ruled out, it becomes possible to quantify the signals of uncalibrated organics with accuracies better than +/- 30 %. The simple reaction kinetics approach produces less accurate results at E/N levels below 100 Td, because significant fractions of primary ions form water hydronium clusters. Deprotonation through reactive collisions of protonated organics with water molecules needs to be considered when the collision energy is a substantial fraction of the exoergicity of the proton transfer reaction and/or if protonated organics undergo many collisions with water molecules.Peer reviewe

Analysis of organic matter in surface snow by PTR-MS – implications for dry deposition dynamics in the Alps

This is the repository of the supplementary data for the paper: “Brief communication: Analysis of organic matter in surface snow by PTR-MS – implications for dry deposition dynamics in the Alps”, https://doi.org/10.5194/tc-2018-203 The sampling of the surface snow (2 cm) was performed from 20/03/2017 – 01/04/2017, 8-9 AM each day at Sonnblick Observatory, Austria. The supplementary data include: 1. Raw mass spectra are given for all the measurements including the replicates. The unit expressed is count per second (cps). The corresponding file is “snow mass spectra cps.xlsx” 2. Processed mass spectra (background subtracted, detection of 3-sigma limit applied) for all the measurements including the replicates. The corresponding file is “mass spectra all replicates – ngml.xlsx”. The unit expressed ng/mL. 3. The raw mass-spectra of the field blanks given in the units of counts per second (cps). Field blanks were taken with the goal to expose the blanks to the same impurities as on the time of the sampling, during the storage and further processing. The corresponding file is: “field blanks ms.xlsx”. 4. A summary table of the concentrations (in ng/mL) and atomic ratios (O/C, H/C, N/C) Oxidative State of Carbon (OSC) and the mean number of carbons in the organic molecules (nC). The table also contains a sum of the concentrations of all the organic ions assigned to the groups (see Table 1 of the paper). The corresponding file is: “summary table.xlsx”

SUPPLEMENTARY DATA TO: “Fine micro- and nanoplastics particles (PM2.5) in urban air and their relation to polycyclic aromatic hydrocarbons”

This is the repository of the supplementary data and it contains the following files: • Raw data files as original output of TD-PTR-ToF-MS for field blank measurements and PM2.5 sample measurements of GDB • Raw data files as original output of TD-PTR-ToF-MS for PS spiked measurements • xls Data analysis file including raw data, blank subtraction and LOD correction of all measurements for GDB • Final mass spectra of all experiments (GDB, field blanks, spiked) used for UFMNP fingerprinting • UFMNP fingerprinting results (xls file) for all experiments (GDB, field blanks, spiked) • xls Data analysis file including all macro and micro constituents, i.e. OM, EC, PAHs • Nanoplastics Fingerprint scripts used for the experiments; All “massLibr*” files contain the mass spectra of virgin plastics with molar ratio (ppb) value for each ion detected in the plastics vapours (3 decimal point precision of m/z). The script files were written in PYTHON (compatible with PYTHON 2 and 3 - all versions). “DataFlip.py” is used for formatting the data into the matrix acceptable for the fingerprinting script. “FngClass.py” and “funFunctions.py” are supporting classes used for the main scripts. matchingTest.py is a main script used for comparing a sample mass spectrum to the one from the plastics library (e.g. for PET use “massLibrPET.csv”). matchingLoopQ4.py is a main script used for comparing all the samples with all the plastics from the library (“massLibr*” files). • PTRwid version of software we used for mass spectra and molar ratio extraction

Supplementary data to: Nanoplastics and ultrafine microplastic in the Dutch Wadden Sea – the hidden plastics debris?

Dušan Materić 1,*, Rupert Holzinger1, Helge Niemann2,3 1 Institute for Marine and Atmospheric Research Utrecht, Utrecht University, Princetonplein 5, 3584CC Utrecht, the Netherlands 2 NIOZ Royal Netherlands Institute for Sea Research, Landsdiep 4, 1797 SZ 't Horntje (Texel), the Netherlands 3Department of Earth Sciences, Utrecht University, Princetonplein 5, 3584CC Utrecht, the Netherlands *Correspondence: [email protected] This is the repository of the supplementary, data and it contains: 1. Raw .h5 data files as the original output of TD-PTR-MS for the direct measurement (Site A); 2. Raw .h5 data files as the original output of TD-PTR-MS for the cascade filtering measurements (Site B); 3. Raw .h5 data files as the original output of TD-PTR-MS for the calibration measurements (PS and PET); The folder also contains processing files as the output of PTRwid software used; 4. PTRwid version of software we used for mass spectra and molar ratio extraction; 5. PTRwid associated parameters file that contains the parameters for mass spectra extraction (including the ToF transmissions) 6. Nanoplastics Fingerprint scripts used for the experiments; All “massLibr*” files contain the mass spectra of virgin plastics with molar ratio (ppb) value for each ion detected in the plastics vapours (3 decimal point precision of m/z). The script files were written in PYTHON (compatible with PYTHON 2 and 3 - all versions). “DataFlip.py” is used for formatting the data into the matrix acceptable for the fingerprinting script. “FngClass.py” and “funFunctions.py” are supporting classes used for the main scripts. matchingTest.py is a main script used for comparing a sample mass spectrum to the one from the plastics library (e.g. for PET use “massLibrPET.csv”). matchingLoopQ3.py is a main script used for comparing all the samples with all the plastics from the library (“massLibr*” files). 7. Data analysis of mass spectra: subtraction and limit of detection calculation for “Direct WS*” measurement (Site A

Supplementary data to: Presence of nanoplastics in rural and remote surface waters

This is the repository of the supplementary, data and it contains: 1. Raw .h5 data files as original output of TD-PTR-MS for Swedish measurements; 2. Raw .h5 data files as original output of TD-PTR-MS for Siberian measurements; 3. PTRwid version of software we used for mass spectra and molar ratio extraction; 4. Data analysis of mass spectra: subtraction and limit of detection calculation for Swedish measurements; 5. Data analysis of mass spectra: subtraction and limit of detection calculation for Siberian measurements; 6. Final mass spectra for all the experiment that are used for nanoplastics fingerprinting; 7. Nanoplastics Fingerprint scripts used for the experiments; All “massLibr*” files contain the mass spectra of virgin plastics with molar ratio (ppb) value for each ion detected in the plastics vapours (3 decimal point precision of m/z). The script files were written in PYTHON (compatible with PYTHON 2 and 3 - all versions). “DataFlip.py” is used for formatting the data into the matrix acceptable for the fingerprinting script. “FngClass.py” and “funFunctions.py” are supporting classes used for the main scripts. matchingTest.py is a main script used for comparing a sample mass spectrum to the one from the plastics library (e.g. for PET use “massLibrPET.csv”). matchingLoopQ2.py is a main script used for comparing all the samples with all the plastics from the library (“massLibr*” files). 8. Nanoplastics Fingerprint scores for Sweden site; These are the outputs from the script “matchingLoopQ2.py” for each plastics type and contain the parameters used for running the script. 9. Nanoplastics Fingerprint scores for Siberian site; 10. HYSPLIT trajectory frequencies for Sweden site (monthly, up to one year prior to the sampling); 11. HYSPLIT trajectory frequencies for Siberian site (monthly, up to one year prior to the sampling). 12. HYSPLIT Dispersion model simulations for Siberian and Sweden site

Nanoplastics measurements in Northern and Southern polar ice

It has been established that various anthropogenic contaminants have already reached all the world's pristine locations, including the polar regions. While some of those contaminants, such as lead and soot, are decreasing in the environment, thanks to international regulations, other novel contaminants emerge. Plastic pollution has been shown as a durable novel pollutant, and, since recently, smaller and smaller plastics particles have been identified in various environments (air, water and soil). Considerable research already exists measuring the plastics in the 5 mm to micrometre size range (microplastics). However, far less is known about the plastics debris that fragmented to the sub-micrometre size (nanoplastics). As these small particles are light, it is expected that they have already reached the most remote places on Earth, e.g. transported across the globe by air movement. In this work, we used a novel method based on Thermal Desorption – Proton Transfer Reaction – Mass Spectrometry (TD-PTR-MS) to detect and measure nanoplastics of different types in the water sampled from a Greenland firn core (T2015-A5) and a sea ice core from Antarctica. We identify polyethylene (PE), polypropylene (PP), polyethylene terephthalate (PET), polystyrene (PS), polyvinyl chloride (PVC), and Tire wear nanoparticles in the 14 m deep Greenland firn core and PE, PP and PET in sea ice from Antarctica. Nanoplastics mass concentrations were on average 13.2 ng/mL for Greenland firn samples and 52.3 ng/mL for Antarctic sea ice. We further discuss the possible sources of nanoplastics that we found at these remote locations, which likely involve complex processes of plastic circulation (emission from both land and sea surface, atmospheric and marine circulation).SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Presence of nanoplastics in rural and remote surface waters

It is now established that microplastics are a pervasive presence in aquatic and terrestrial ecosystems. The same is assumed to be true for nanoplastics but data are lacking due to technical difficulties associated with sample analysis. Here, we measured nanoplastics in waterbodies at two contrasting sites: remote Siberian Arctic tundra and a forest landscape in southern Sweden. Nanoplastics were detected in all sampled Swedish lakes (n = 7) and streams (n = 4) (mean concentration = 563 mu g l(-1)) and four polymer types were identified (polyethylene, polyvinyl chloride (PVC), polypropylene, polyethylene terephthalate). In Siberia nanoplastics were detected in 7/12 sampled lakes, ponds and surface flooding, but only two polymer types were detected (PVC and polystyrene) and concentrations were lower (mean 51 mu g l(-1)). Based on back-calculation of air mass trajectories and particle dispersion, we infer that nanoplastics arrive at both sites by aerial deposition from local and regional sources. Our results suggest that nanoplastics may be a near-ubiquitous presence even in remote ecosystems

Presence of nanoplastics in rural and remote surface waters

It is now established that microplastics are a pervasive presence in aquatic and terrestrial ecosystems. The same is assumed to be true for nanoplastics but data are lacking due to technical difficulties associated with sample analysis. Here, we measured nanoplastics in waterbodies at two contrasting sites: remote Siberian Arctic tundra and a forest landscape in southern Sweden. Nanoplastics were detected in all sampled Swedish lakes (n = 7) and streams (n = 4) (mean concentration = 563 mu g l(-1)) and four polymer types were identified (polyethylene, polyvinyl chloride (PVC), polypropylene, polyethylene terephthalate). In Siberia nanoplastics were detected in 7/12 sampled lakes, ponds and surface flooding, but only two polymer types were detected (PVC and polystyrene) and concentrations were lower (mean 51 mu g l(-1)). Based on back-calculation of air mass trajectories and particle dispersion, we infer that nanoplastics arrive at both sites by aerial deposition from local and regional sources. Our results suggest that nanoplastics may be a near-ubiquitous presence even in remote ecosystems