Article pubs.acs.org/est
Simultaneous Trace Identification and Quantification of Common Types of Microplastics in Environmental Samples by Pyrolysis-Gas Chromatography−Mass Spectrometry Marten Fischer and Barbara M. Scholz-Böttcher*,† Institute for Chemistry and Biology of the Marine Environment (ICBM), Carl von Ossietzky University of Oldenburg, P.O. Box 2503, D-26111 Oldenburg, Germany
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S Supporting Information *
ABSTRACT: The content of microplastics (MP) in the environment is constantly growing. Since the environmental relevance, particularly bioavailability, rises with decreasing particle size, the knowledge of the MP proportion in habitats and organisms is of gaining importance. The reliable recognition of MP particles is limited and underlies substantial uncertainties. Therefore spectroscopic methods are necessary to ensure the plastic nature of isolated particles, determine the polymer type and obtain particle count related quantitative data. In this study Curie-Point pyrolysis-gas chromatography− mass spectrometry combined with thermochemolysis is shown to be an excellent analytical tool to simultaneously identify and optionally quantify MP in environmental samples on a polymer specific mass related trace level. The method is independent of any mechanical preselection or particle appearance. For this purpose polymer characteristic pyrolysis products and their indicative fragment ions were used to analyze eight common types of plastics. Further aspects of calibration, recoveries, and potential matrix effects are discussed. The method is exemplarily applied on selected fish samples after an enzymatic-chemically pretreatment. This new approach with mass-related results is complementary to established FT-IR and Raman methods providing particle counts of individual polymer particles.
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INTRODUCTION Since the 1950s around 6.46 billion tons of plastics have been produced worldwide (estimated from1), with 311 million tons in 2014 alone - and the production of MP is still rising. Conservative estimates predict that around 10% of all produced plastics will end up in the oceans.2 Key reasons for this are insufficient waste management and less reflected end consumer habits. Estimations indicate that 2010 alone between 4.8 and 12.7 million tons of land based plastic waste entered the oceans.3 The attention on plastic litter particularly on microplastics (MP) smaller than 5 mm has risen greatly in recent times. The proportion of macro plastics on marine debris has leveled off in recent times,4 that of MP increased continuously mostly due to fragmentation processes of altered plastic litter and additional input of technical micro particles from different sources. In relation to particle numbers it is supposed to be the most prominent plastic fraction today.5 World ocean models comparing predicted with measured data show an evident minor presence of measured small microplastics (S-MP) below 1 mm and lead to the assumption of a so far unknown sink of this fraction.6,7 Although the impact of MP on the environment grows with declining particle size,5,8−12 practical specific and selective approaches for qualitative and quantitative analysis of individual © 2017 American Chemical Society
plastics in environmental samples on a submillimeter scale are still lacking. Synthetic polymers are broad in variety, in terms of chemical composition and physicochemical characteristics. Identification of macro- and mesoplastics is possible according to their source and appearance. These features become less distinctive with decreasing particle sizes. Even while using a microscope, an additional, reliable identification method is obligate. For this purpose FT-IR and Raman techniques are the most common used for identification of different polymer types after optical preselection of conspicuous particles. More recently imaging techniques have become popular, which enable an almost automatic scanning of prepared samples for characteristic absorption bands of selected polymers. However, this technique is time-consuming, because analysis time increases substantially with decreasing particle size. In all cases particle number related data are generated. The potential of these techniques is reviewed in the literature.13−16 Pyrolysis−gas chromatography in combination with mass spectrometry (Py-GCMS) can be used for reliable identification Received: Revised: Accepted: Published: 5052
December 15, 2016 March 26, 2017 April 8, 2017 April 9, 2017 DOI: 10.1021/acs.est.6b06362 Environ. Sci. Technol. 2017, 51, 5052−5060
Article
Environmental Science & Technology
the Py-GCMS conditions are included in the Supporting Information (SI), Table S1. Thermochemolysis was performed by adding 10 μL of tetramethylammonium hydroxide (TMAH, 25% in water) to the individual samples directly into the CPpyrolysis targets prior to pyrolysis. Polymer Identification. To unequivocally identify single polymers in complex natural samples specific indicator compounds for each polymer are needed. Therefore, a database of different polymers (PE, PP, PS, PVC, PA6, PMMA, PET, and PC) was created by measuring polymer standards and in some cases additionally polymers of consumer products (for further specifications cf. SI Table S2) with direct pyrolysis and thermochemolysis, respectively. The obtained pyrograms were compared with an in-house database and literature data from Tsuge et al. (2011), respectively. The most abundant and/or polymer-specific compounds from TMAH pyrograms (cf. results and discussion) were chosen as indicators for polymer specific qualitative and quantitative analysis (Table 2, and SI Figure S1−S8, Table S3). Calibration. To obtain external calibration curves pyrolysis targets were prepared by adding Al2O3 as inert dilution matrix. Between 0.4 and 1070 μg of polymer standards were weighed directly into the pyrolysis targets using a Cubis Ultramicro balance MSE2.7S-000-DM (Sartorius, Germany). Finally an Al2O3 cover and in most cases TMAH were added. Polymer standards were measured individually and in mixtures. Individual polymers were calibrated externally by means of preselected indicator compounds by using the mass chromatograms of their respective indicator ions and respective integration results. The bands of confidence and prediction at 95% confidence level each were calculated with Origin 2016G (OriginLab corporation). Fish Samples. The applicability of the method to real environmental samples was demonstrated by analyzing fishes caught in 2014. Pelagic and demersal fish samples for recovery studies were caught in the Jade Bay (North Sea, Germany, stow net) and in two locations from the Baltic Sea (Wismar Bay, gill net, and 35 km north of Rügen Island, demersal trawl). The stomachs (mostly pooled in numbers of five) and gastrointestinal (GI)-tracts used for spiking had samples weights between one and 20 g. All fishes belong to a sample pool of a pilot study on microplastics in fishes; the corresponding data will be published subsequently. Sample Clean-Up. Sample treatment was adapted and optimized according to existing methods.36,37 The samples were enzymatically and chemically digested as a whole via a succession of SDS, protease, Chitinase and H2O2 treatment to remove biological matrix as much as possible and to preconcentrate potential microplastic content. Subsequently the vacuum-dried samples were degreased with a few milliliter of petrol ether (60/80). In case of benthic fish samples a high sand content made an additional density separation with sodium iodide solution (∼1.6 g L−1) necessary. All treatments and washing steps were performed in the same crucible, almost the whole time covered with alumina foil to prevent secondary contamination with plastics and fibers from the surrounding air. Parallel to the fish samples procedural blanks were conducted to follow possible contamination pathways and estimate their extent. At the end of treatment the content of crucible was transferred quantitatively to an Anodisc filter (0.2 μm) and dried in a glass Petri dish. The 6 mm (⌀) filter section containing the sample was stamped out and milled in a small agate bullet mortar, transferred into a pyrolysis target and
of isolated plastic particles by analyzing their characteristic thermal degradation products, for example,17−20 and it is commonly applied in the polymer industry. However, this technique has only rarely been used to detect plastics in environmental samples21−25 but became more popular recently.26−28 In these studies particles, suspected to be plastic, are isolated manually and subjected to Py-GCMS. In addition to identification Py-GCMS could also be applied for quantitative trace analysis of MP on a polymer specific level if the pyrolysis conditions are highly reproducible to generate a consistent composition of pyrolysis products.18,29−31 In environmental samples this was seldom done to date and when attempted it was restricted on a few selected polymers (polyvinyl chloride (PVC) and polystyrene (PS),22 PS30 and modified polyamides.32 Very recently a promising thermogravimetric method for PE determination in environmental samples was introduced.33 Combined with GCMS this technique bears a great potential for polyethylene (PE) detection in complex samples although the lowest MP concentration of 5 wt % in spiked environmental samples tested so far exceeds realistic levels in most cases. Our intention was to develop an analytical setup, which enables a qualitative and quantitative polymer specific, weightrelated trace analysis of MP in environmental samples with a special focus on small MP detracted from optical detection or mechanical particle separation. Accordingly, we demonstrate here Curie point (CP)-Py-GCMS combined with thermochemolysis (a pyrolytic methylation step34,35) as an equally reliable and practical analytical method for eight relevant common consumer user plastics (PE, polypropylene (PP), PS, polyethylene terephthalate (PET), PVC, poly(methyl methacrylate) (PMMA), polycarbonate (PC), and polyamide 6 (PA6) detected simultaneously within a single GCMS run. Together they represent around 80% of the actual plastic demand1 and are prominent in perishables as well as disposable packaging. We show that this approach delivers qualitative information and weight-related at least semiquantitative data for individual polymers on a trace level independent of particle size, shape and a prior optical detection. According to this it is complementary to common particle related FT-IR- and Raman techniques for MP analysis. Its successful application in combination with complex environmental matrices is exemplarily demonstrated on fish samples. Their stomachs and gastro-intestinal (GI) tracts contain a broad spectrum of various food related inorganic (e.g., sand, mussel shells) and organic matrix compounds that are representative for those expected in environmental samples. The method can be transferred to any sample type after an adequate MP preconcentration. Concentration ranges to which the method is applicable, detection limits for individual polymers, potential interferences of biological matrices with indicator signals selected and recoveries of polymers spiked into fish stomach samples in trace amounts are presented and critically discussed.
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EXPERIMENTAL SECTION CP-Pyrolysis-GCMS/Thermochemolysis. CP-PyrolysisGCMS measurements were performed with a Curie-PointPyrolyzer (CP) Pyromat (GSG Mess- and Analysengeräte, Bruchsal, Germany) in a 590 °C CP-pyrolytic target cup (GSG). The Pyrolyzer was attached to an Agilent 6890 N gas chromatograph equipped with a DB-5MS-column linked to an Agilent MSD 5793 N mass spectrometer. Additional details on 5053
DOI: 10.1021/acs.est.6b06362 Environ. Sci. Technol. 2017, 51, 5052−5060
Article
Environmental Science & Technology Table 1. Pyrolytic Behavior of Polymers with and Without TMAH Additionc direct pyrolysisa polymer PE PP PS PVC PET & PBT PC PMMA Poly(alkyl metacrylate)s PA 6
b,c
thermochemolysis (TMAH)a d
mechanism
(main-)signals
mechanism
(main-)signals
RCS RCS ECS, RCS chain stripping CS, secondary reactions RCS, cross-linking ECS ECS
multiple signals of n-alkanes, n-alkenes and n-alkadienes multiple signals of methyl alkenes and alkadienes mono-, di-, tri- and tetramers HClb, benzene, multiple small signals of aromatic compounds multiple signals of benzoate and terephthalate derivatives and oligomers bisphenol A;17 triphenyl phosphine oxide (flame retardant)a monomer, smaller signals of dimers and trimer monomer, smaller signals of dimers and trimer
unaffected unaffected unaffected unaffected TCTM
unaffected unaffected unaffected unaffected dimethyl terephthalate
TCTM TCTM TCTM
methylated bisphenol A methyl methacrylate methyl and alkyl methacrylates
ECS
ε-caprolactam, traces of nitriles and cyanopentyl amides
TCTM (partial)
ε-caprolactam, N-methyl-εcaprolactam
a See SI for respective pyrograms in detail. bAccording to refs 38,39. cRCS = random chain scission; ECS = end chain scission; CS = chain scission; TCTM = thermochemolytic transmethylation. dNumber of signals depending on polymer concentration.
Table 2. Polymer Related Pyrogram Informationa polymer
characteristic decomposition product(s)
M
indicator ionsb
RI
(m/z)
(m/z)
MP amount required (μg)
S/N
SI
PE
alkanes (e.g., C20) α-alkenes (e.g., C20) α,ω-alkenes (e.g., C20)
2000 1994 1987
282 280 278
99, 85 97, 83 95, 82
