Polyethylene Identification in Ocean Water Samples by Means of 50 keV Energy Electron Beam
"> Figure 1
<p>Physical model x-z section of ocean water and polyethylene.</p> "> Figure 2
<p>Geometrical model of x-z section.</p> "> Figure 3
<p>Volumetric cluster cells in 3D.</p> "> Figure 4
<p>Ocean water polyethylene plus microorganisms, x-z section model.</p> "> Figure 5
<p>Carbon total photon cross section as a function of energy.</p> "> Figure 6
<p>Carbon incoherent photon cross section as a function of energy.</p> "> Figure 7
<p>Carbon coherent photon cross section as a function of energy.</p> "> Figure 8
<p>Carbon photoelectric photon cross section as a function of energy.</p> "> Figure 9
<p>Carbon pair production photon cross section as a function of energy.</p> "> Figure 10
<p>Oxygen total photon cross section as a function of energy.</p> "> Figure 11
<p>Oxygen incoherent photon cross section as a function of energy.</p> "> Figure 12
<p>Oxygen coherent photon cross section as a function of energy.</p> "> Figure 13
<p>Oxygen photoelectric photon cross section as a function of energy.</p> "> Figure 14
<p>Oxygen pair production photon cross section as a function of energy.</p> "> Figure 15
<p>Phosphorus total photon cross section as a function of energy.</p> "> Figure 16
<p>Phosphorus incoherent photon cross section as a function of energy.</p> "> Figure 17
<p>Phosphorus coherent photon cross section as a function of energy.</p> "> Figure 18
<p>Phosphorus photoelectric photon cross section as a function of energy.</p> "> Figure 19
<p>Phosphorus pair production photon cross section as a function of energy.</p> "> Figure 20
<p>Ocean water total electron stopping power as a function of energy.</p> "> Figure 21
<p>Ocean water total photon cross section as a function of energy.</p> "> Figure 22
<p>Ocean water incoherent photon cross section as a function of energy.</p> "> Figure 23
<p>Ocean water coherent photon cross section as a function of energy.</p> "> Figure 24
<p>Ocean water photoelectric photon cross section as a function of energy.</p> "> Figure 25
<p>Photon flux—ocean water vs contamination.</p> "> Figure 26
<p>Photon fluxes—spectrum vs contamination.</p> "> Figure 27
<p>30 keV—ocean water vs contamination.</p> "> Figure 28
<p>40 keV—ocean water vs contamination.</p> "> Figure 29
<p>50 keV—ocean water vs contamination.</p> "> Figure 30
<p>Photon flux—polyethylene vs microorganisms.</p> "> Figure 31
<p>30 KeV—polyethylene vs microorganisms.</p> "> Figure 32
<p>40 KeV—polyethylene vs microorganisms.</p> "> Figure 33
<p>50 KeV—polyethylene vs microorganisms.</p> ">
Abstract
:1. Introduction
2. Materials and Methods
3. Results
4. Discussion
- The 10-ppm polyethylene case can be discriminated using the photon flux counts at the detector evaluated on the 30 and 40 keV spectra compared to the standard ocean water.
- The 100-ppm polyethylene case can be discriminated using the photon flux counts at the detector and the 30, 40, and 50 keV spectra compared to the 10 ppm one.
- The 1000-ppm polyethylene case can be discriminated using the photon flux counts at the detector and the 30, 40, and 50 keV spectra compared to the 100 ppm one.
- The 10,000-ppm polyethylene case can be discriminated using the photon flux counts at the detector and the 30, 40, and 50 keV spectra compared to the 1000 ppm one.
- 5.
- The 0.7-ppm microorganisms case can be discriminated using the photon flux counts at the detector evaluated on the 30 and 50 keV spectrum lines compared to the ocean water + 100 ppm polyethylene combination at the same energy conditions.
- 6.
- The 7-ppm microorganisms case can be discriminated using the photon flux counts at the detector evaluated on the 50 keV spectrum line compared to the ocean water + 100 ppm polyethylene + 0.7 ppm microorganisms combination at the same energy condition.
- 7.
- The 70-ppm microorganisms case can be discriminated using the photon flux counts at the detector evaluated on the 40 and 50 keV spectrum lines compared to the ocean water + 100 ppm polyethylene + 7 ppm microorganisms combination at the same energy conditions.
- 8.
- The 700-ppm microorganisms case can be discriminated using the photon flux counts at the detector evaluated on the 40 and 50 keV spectrum lines compared to the ocean water + 100 ppm polyethylene + 70 ppm microorganisms combination at the same energy conditions.
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Parker, L. Microplastics. National Geographic Society. Available online: https://www.nationalgeographic.com/environment/2019/06/microplastics-spread-throughout-deep-sea-monterey-canyon/ (accessed on 20 October 2020).
- Rogers, K. Microplastics “Plastic Particulate”. Britannica. Available online: https://www.britannica.com/technology/microplastic (accessed on 20 October 2020).
- Kane, I.A.; Clare, M.A.; Miramontes, E.; Wogelius, R.; Rothwell, J.J.; Garreau, P.; Pohl, F. Seafloor microplastic hotspots controlled by deep-sea circulation. Science 2020, 368, 1140–1145. [Google Scholar] [CrossRef] [PubMed]
- Smith, M.; Love, D.C.; Rochman, C.M.; Neff, R.A. Microplastics in Seafood and the Implications for Human Health. Curr. Environ. Health Rep. 2018, 5, 375–386. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- National Research Council (US) Safe Drinking Water Committee. Drinking Water and Health; National Academies Press: Washington, DC, USA, 1977. [Google Scholar]
- Wesch, C.; Barthel, A.-K.; Braun, U.; Klein, R.; Paulus, M. No microplastics in benthic eelpout (Zoarces viviparus): An urgent need for spectroscopic analyses in microplastic detection. Environ. Res. 2016, 148, 36–38. [Google Scholar] [CrossRef] [PubMed]
- Prata, J.C.; Da Costa, J.P.; Duarte, A.C.; Rocha-Santos, T. Methods for sampling and detection of microplastics in water and sediment: A critical review. TrAC Trends Anal. Chem. 2019, 110, 150–159. [Google Scholar] [CrossRef]
- Maes, T.; Jessop, R.; Wellner, N.; Haupt, K.; Mayes, A.G. A rapid-screening approach to detect and quantify microplastics based on fluorescent tagging with Nile Red. Sci. Rep. 2017, 7, srep44501. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Araujo, C.F.; Nolasco, M.M.; Ribeiro, A.M.; Ribeiro-Claro, P.J. Identification of microplastics using Raman spectroscopy: Latest developments and future prospects. Water Res. 2018, 142, 426–440. [Google Scholar] [CrossRef] [PubMed]
- Marine & Environmental Research Institute. Guide to Microplastic Identification. 2012. Available online: https://docplayer.net/27438419-Guide-to-microplastic-identification.html (accessed on 20 October 2020).
- Segebade, C.; Starovoitova, V.N.; Borgwardt, T.; Wells, D. Principles, Methodologies, and Applications of Photon Activation Analysis: A Review; Springer: Berlin/Heidelberg, Germany, 2017. [Google Scholar]
- Joseph, A.; Cotruvo, W.H.O. Water, Sanitation and Health Protection and the Human Environment World; WHO: Geneva, Switzerland, 2006. [Google Scholar]
- Fries, E.; Dekiff, J.H.; Willmeyer, J.; Nuelle, M.T.; Ebert, M.; Remy, D. Identification of polymer types and additives in marine microplastic particles using pyrolysis-GC/MS and scanning electron microscopy. Environ. Sci. Process. Impacts 2013, 15, 1949–1956. [Google Scholar] [CrossRef] [Green Version]
- Bar-On, Y.M.; Phillips, R.; Milo, R. The biomass distribution on Earth. Proc. Natl. Acad. Sci. USA 2018, 115, 6506–6511. [Google Scholar] [CrossRef] [Green Version]
- Mann, N.H. The Third Age of Phage. PLoS Biol. 2005, 3, 753–755. [Google Scholar] [CrossRef] [Green Version]
- Wommack, K.E.; Colwell, R.R. Virioplankton: Viruses in Aquatic Ecosystems. Microbiol. Mol. Biol. Rev. 2000, 64, 69–114. [Google Scholar] [CrossRef] [Green Version]
- Suttle, C.A. Viruses in the sea. Nat. Cell Biol. 2005, 437, 356–361. [Google Scholar] [CrossRef]
- Bergh, O.; Børsheim, K.Y.; Bratbak, G.; Heldal, M. High abundance of viruses found in aquatic environments. Nat. Cell Biol. 1989, 340, 467–468. [Google Scholar] [CrossRef]
- Wigington, C.H.; Sonderegger, D.; Brussaard, C.P.D.; Buchan, A.; Finke, J.F.; Fuhrman, J.A.; Lennon, J.T.; Middelboe, M.; Suttle, C.A.; Stock, C.; et al. Re-examination of the relationship between marine virus and microbial cell abundances. Nat. Microbiol. 2016, 1, 15024. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Brum, J.R.; O Schenck, R.; Sullivan, M.B. Global morphological analysis of marine viruses shows minimal regional variation and dominance of non-tailed viruses. ISME J. 2013, 7, 1738–1751. [Google Scholar] [CrossRef] [Green Version]
- Krupovič, M.; Bamford, D.H. Putative prophages related to lytic tailless marine dsDNA phage PM2 are widespread in the genomes of aquatic bacteria. BMC Genom. 2007, 8, 236. [Google Scholar] [CrossRef] [Green Version]
- Xue, H.; Xu, Y.; Boucher, Y.F.; Polz, M.F. High Frequency of a Novel Filamentous Phage, VCYϕ, within an Environmental Vibrio cholerae Population. Appl. Environ. Microbiol. 2011, 78, 28–33. [Google Scholar] [CrossRef] [Green Version]
- Roux, S.; Krupovic, M.; Poulet, A.; Debroas, D.; Enault, F. Evolution and Diversity of the Microviridae Viral Family through a Collection of 81 New Complete Genomes Assembled from Virome Reads. PLoS ONE 2012, 7, e40418. [Google Scholar] [CrossRef]
- Lawrence, C.M.; Menon, S.; Eilers, B.J.; Bothner, B.; Khayat, R.; Douglas, T.; Young, M.J. Structural and Functional Studies of Archaeal Viruses. J. Biol. Chem. 2009, 284, 12599–12603. [Google Scholar] [CrossRef] [Green Version]
- Prangishvili, D.; Forterre, P.; Garrett, R.A. Viruses of the Archaea: A unifying view. Nat. Rev. Microbiol. 2006, 4, 837–848. [Google Scholar] [CrossRef]
- Mainardi, E.; Donahue, R.J.; Wilson, W.E.; Blakely, E.A. Comparison of microdosimetric simulations using PENELOPE and PITS for a 25 keV electron microbeam in water. Radiat. Res. 2004, 162, 326–331. [Google Scholar] [CrossRef] [Green Version]
- Vilhena, M.D.P.S.P.; Da Costa, M.L.; Berrêdo, J.F.; Paiva, R.S.; Almeida, P.D. Chemical composition of phytoplankton from the estuaries of Eastern Amazonia. Acta Amaz. 2014, 44, 513–526. [Google Scholar] [CrossRef] [Green Version]
- Romera-Castillo, C.; Pinto, M.; Langer, T.M.; Álvarez-Salgado, X.A.; Herndl, G.J. Dissolved organic carbon leaching from plastics stimulates microbial activity in the ocean. Nat. Commun. 2018, 9, 1–7. [Google Scholar] [CrossRef]
- Gin, K.Y.-H.; Lin, X.; Zhang, S. Dynamics and size structure of phytoplankton in the coastal waters of Singapore. J. Plankton Res. 2000, 22, 1465–1484. [Google Scholar] [CrossRef]
- Pelowitz, D.B. MCNPX User’s Manual, Version 2.5.0; Report LA-CP-05-0369; Los Alamos National laboratory: Los Alamos, NM, USA, 2005. [Google Scholar]
- White, M.C. Photo Atomic Data Library, MCPLIB04; Los Alamos National Laboratory: Los Alamos, NM, USA, 2003. [Google Scholar]
- Oak Ridge National Laboratory. MCNP-MCNPX Code Collection; Los Alamos national Laboratory: Los Alamos, NM, USA, 2006. [Google Scholar]
Element. | Element (%) | Element | Element (%) |
---|---|---|---|
Oxygen | 85.7 | Molybdenum | 0.000001 |
Hydrogen | 10.8 | Zinc | 0.000001 |
Chlorine | 1.9 | Nickel | 0.00000054 |
Sodium | 1.05 | Arsenic | 0.0000003 |
Magnesium | 0.135 | Copper | 0.0000003 |
Sulfur | 0.0885 | Tin | 0.0000003 |
Calcium | 0.04 | Uranium | 0.0000003 |
Potassium | 0.038 | Chromium | 0.00000003 |
Bromine | 0.0065 | Krypton | 0.00000025 |
Carbon | 0.0028 | Manganese | 0.0000002 |
Strontium | 0.00081 | Vanadium | 0.0000001 |
Boron | 0.00046 | Titanium | 0.0000001 |
Silicon | 0.0003 | Cesium | 0.00000005 |
Fluoride | 0.00013 | Cerium | 0.00000004 |
Argon | 0.00006 | Antimony | 0.000000033 |
Nitrogen | 0.00005 | Silver | 0.00000003 |
Lithium | 0.000018 | Yttrium | 0.00000003 |
Rubidium | 0.000012 | Cobalt | 0.000000027 |
Phosphorus | 0.000007 | Neon | 0.000000014 |
Iodine | 0.000006 | Cadmium | 0.000000011 |
Barium | 0.000003 | Tungsten | 0.00000001 |
Aluminum | 0.000001 | Lead | 0.000000005 |
Iron | 0.000001 | Mercury | 0.000000003 |
Indium | 0.000001 | Selenium | 0.000000002 |
Ocean Water No Contamination | Polyethylene 10 ppm | Polyethylene 100 ppm | Polyethylene 1000 ppm | Polyethylene 10,000 ppm | |
---|---|---|---|---|---|
Bremsstrahlung | 99.1265% | 99.1237% | 99.1182% | 99.1545% | 99.3538% |
1st Fluorescence | 0.8733% | 0.8755% | 0.8812% | 0.8449% | 0.6448% |
2nd Fluorescence | 0.0002% | 0.0008% | 0.0006% | 0.0006% | 0.0015% |
Norm | 100.0000% | 100.0000% | 100.0000% | 100.0000% | 100.0000% |
Element | Ocean Water No Contamination | Polyethylene 10 ppm | Polyethylene 100 ppm | Polyethylene 1000 ppm | Polyethylene 10,000 ppm |
---|---|---|---|---|---|
Oxygen | 76.210% | 76.273% | 76.387% | 73.211% | 52.813% |
Hydrogen | 7.585% | 7.405% | 6.998% | 6.686% | 4.259% |
Chlorine | 12.357% | 12.107% | 12.179% | 11.938% | 8.902% |
Sodium | 1.924% | 1.912% | 1.873% | 1.912% | 1.384% |
Magnesium | 0.306% | 0.325% | 0.316% | 0.370% | 0.244% |
Sulfur | 0.490% | 0.573% | 0.536% | 0.448% | 0.372% |
Calcium | 0.429% | 0.512% | 0.434% | 0.409% | 0.277% |
Potassium | 0.316% | 0.360% | 0.337% | 0.384% | 0.330% |
Bromine | 0.322% | 0.294% | 0.281% | 0.340% | 0.198% |
Carbon | 0.000% | 0.193% | 0.628% | 4.257% | 31.188% |
Strontium | 0.056% | 0.046% | 0.031% | 0.044% | 0.029% |
Silicon | 0.005% | 0.000% | 0.000% | 0.000% | 0.000% |
Argon | 0.000% | 0.000% | 0.000% | 0.000% | 0.004% |
Cluster N | (10 ppm) | (100 ppm) | (1000 ppm) | (10,000 ppm) |
---|---|---|---|---|
ppm perCluster | ppm perCluster | ppm perCluster | ppm perCluster | |
1 | 1 | 10 | 100 | 1000 |
2 | 0.5 | 5 | 50 | 500 |
3 | 2 | 20 | 200 | 2000 |
4 | 1.3 | 13 | 130 | 1300 |
5 | 1.9 | 19 | 190 | 1900 |
6 | 0.3 | 3 | 30 | 300 |
7 | 0.8 | 8 | 80 | 800 |
8 | 0.4 | 4 | 40 | 400 |
9 | 0.2 | 2 | 20 | 200 |
10 | 0.9 | 9 | 90 | 900 |
11 | 0.7 | 7 | 70 | 700 |
Norm | 10 | 100 | 1000 | 10,000 |
Cluster N | (10 ppm) | (10 ppm) | Particles N | Volume (mm3) |
---|---|---|---|---|
ppm per Cluster | % ppm Cluster | per Cluster | per Cluster | |
1 | 1 | 10% | 262 | 1 |
2 | 0.5 | 5% | 131 | 1 |
3 | 2 | 20% | 525 | 2 |
4 | 1.3 | 13% | 341 | 1 |
5 | 1.9 | 19% | 498 | 2 |
6 | 0.3 | 3% | 79 | 0.3 |
7 | 0.8 | 8% | 210 | 1 |
8 | 0.4 | 4% | 105 | 0.4 |
9 | 0.2 | 2% | 52 | 0.2 |
10 | 0.9 | 9% | 236 | 1 |
11 | 0.7 | 7% | 184 | 1 |
Norm | 10 | 100.00% | 2623 | 11 |
Cluster N | (100 ppm) | (100 ppm) | Particles N | Volume (mm3) |
---|---|---|---|---|
ppm per Cluster | % ppm Cluster | per Cluster | per Cluster | |
1 | 10 | 10% | 2623 | 11 |
2 | 5 | 5% | 1311 | 5 |
3 | 20 | 20% | 5245 | 22 |
4 | 13 | 13% | 3409 | 14 |
5 | 19 | 19% | 4983 | 21 |
6 | 3 | 3% | 787 | 3 |
7 | 8 | 8% | 2098 | 9 |
8 | 4 | 4% | 1049 | 4 |
9 | 2 | 2% | 525 | 2 |
10 | 9 | 9% | 2360 | 10 |
11 | 7 | 7% | 1836 | 8 |
Norm | 100 | 100.00% | 26,227 | 110 |
Cluster N | (1000 ppm) | (1000 ppm) | Particles N | Volume (mm3) |
---|---|---|---|---|
ppm per Cluster | % ppm Cluster | per Cluster | per Cluster | |
1 | 100 | 10% | 26,227 | 110 |
2 | 50 | 5% | 13,113 | 55 |
3 | 200 | 20% | 52,454 | 220 |
4 | 130 | 13% | 34,095 | 143 |
5 | 190 | 19% | 49,831 | 209 |
6 | 30 | 3% | 7868 | 33 |
7 | 80 | 8% | 20,981 | 88 |
8 | 40 | 4% | 10,491 | 44 |
9 | 20 | 2% | 5245 | 22 |
10 | 90 | 9% | 23,604 | 99 |
11 | 70 | 7% | 18,359 | 77 |
Norm | 1000 | 100.00% | 262,268 | 1099 |
Cluster N | (10,000 ppm) | (10,000 ppm) | Particles N | Volume (mm3) |
---|---|---|---|---|
ppm per Cluster | % ppm Cluster | per Cluster | per Cluster | |
1 | 1000 | 10% | 262,268 | 1099 |
2 | 500 | 5% | 131,134 | 549 |
3 | 2000 | 20% | 524,535 | 2198 |
4 | 1300 | 13% | 340,948 | 1429 |
5 | 1900 | 19% | 498,308 | 2088 |
6 | 300 | 3% | 78,680 | 330 |
7 | 800 | 8% | 209,814 | 879 |
8 | 400 | 4% | 104,907 | 440 |
9 | 200 | 2% | 52,454 | 220 |
10 | 900 | 9% | 236,041 | 989 |
11 | 700 | 7% | 183,587 | 769 |
Norm | 10,000 | 100.00% | 2,622,676 | 10,989 |
C | H | |
---|---|---|
ppm | (mg/L) | (mg/L) |
10 | 8.57142857 | 1.42857143 |
100 | 85.7142857 | 14.2857143 |
1000 | 857.142857 | 142.857143 |
10,000 | 8571.42857 | 1428.57143 |
Element | Origin Element (%) | Element (ppm) | 10 ppm Polyethylene (ppm) | 100 ppm Polyethylene (ppm) | 1000 ppm Polyethylene (ppm) | 10,000 ppm Polyethylene (ppm) |
---|---|---|---|---|---|---|
Oxygen | 85.70 | 8.57 × 105 | 8.570 × 105 | 8.569 × 105 | 8.561 × 105 | 8.484 × 105 |
Hydrogen | 10.80 | 1.08 × 105 | 1.080 × 105 | 1.080 × 105 | 1.081 × 105 | 1.094 × 105 |
Chlorine | 1.90 | 19,000 | 1.900 × 104 | 1.900 × 104 | 1.898 × 104 | 1.881 × 104 |
Sodium | 1.05 | 10,500 | 1.050 × 104 | 1.050 × 104 | 1.049 × 104 | 1.040 × 104 |
Magnesium | 0.14 | 1350 | 1.350 × 103 | 1.350 × 103 | 1.349 × 103 | 1.337 × 103 |
Sulfur | 0.09 | 885 | 8.850 × 102 | 8.849 × 102 | 8.841 × 102 | 8.762 × 102 |
Calcium | 0.04 | 400 | 4.000 × 102 | 4.000 × 102 | 3.996 × 102 | 3.960 × 102 |
Potassium | 0.04 | 380 | 3.800 × 102 | 3.800 × 102 | 3.796 × 102 | 3.762 × 102 |
Bromine | 0.01 | 65 | 6.500 × 101 | 6.499 × 101 | 6.494 × 101 | 6.435 × 101 |
Carbon | 0.00 | 28 | 3.657 × 101 | 1.137 × 102 | 8.851 × 102 | 8.599 × 103 |
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Adlish, J.I.; Costa, D.; Mainardi, E.; Neuhold, P.; Surrente, R.; Tagliapietra, L.J. Polyethylene Identification in Ocean Water Samples by Means of 50 keV Energy Electron Beam. Instruments 2020, 4, 32. https://doi.org/10.3390/instruments4040032
Adlish JI, Costa D, Mainardi E, Neuhold P, Surrente R, Tagliapietra LJ. Polyethylene Identification in Ocean Water Samples by Means of 50 keV Energy Electron Beam. Instruments. 2020; 4(4):32. https://doi.org/10.3390/instruments4040032
Chicago/Turabian StyleAdlish, John I., Davide Costa, Enrico Mainardi, Piero Neuhold, Riccardo Surrente, and Luca J. Tagliapietra. 2020. "Polyethylene Identification in Ocean Water Samples by Means of 50 keV Energy Electron Beam" Instruments 4, no. 4: 32. https://doi.org/10.3390/instruments4040032
APA StyleAdlish, J. I., Costa, D., Mainardi, E., Neuhold, P., Surrente, R., & Tagliapietra, L. J. (2020). Polyethylene Identification in Ocean Water Samples by Means of 50 keV Energy Electron Beam. Instruments, 4(4), 32. https://doi.org/10.3390/instruments4040032