Simultaneous Trace Identification and Quantification of Common

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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 Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b06362 • Publication Date (Web): 09 Apr 2017 Downloaded from http://pubs.acs.org on April 17, 2017

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Environmental Science & Technology

PET Fiber ~ 1µg

3.9*104 1.7*107

m/z 163

Intensity

1 mm

TIC

Intensity

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Simultaneous trace identification and quantification

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of common types of microplastics in environmental

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samples by pyrolysis-gas chromatography-mass

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spectrometry

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Marten Fischer and Barbara M. Scholz-Böttcher*

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Institute for Chemistry and Biology of the Marine Environment (ICBM), Carl von Ossietzky

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University of Oldenburg, P.O. Box 2503, D-26111 Oldenburg, Germany.

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KEYWORDS microplastic, trace analysis, identification, quantification, simultaneous analysis,

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Pyrolysis-GCMS, PE, PP, PET, PS, PVC, PC, PA6, PMMA, environmental samples

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ABSTRACT

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The content of microplastics (MP) in the environment is constantly growing. Since the

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environmental relevance, particularly bioavailability, rises with decreasing particle size, the

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knowledge of the MP proportion in habitats and organisms is of gaining importance. The reliable

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recognition of MP particles is limited and underlies substantial uncertainties. Therefor

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spectroscopically methods are necessary to ensure the plastic nature of isolated particles,

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determine the polymer type and obtain particle count related quantitative data. In this study

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Curie-Point pyrolysis-gas chromatography-mass spectrometry combined with thermochemolysis

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is shown to be an excellent analytical tool to simultaneously identify and optionally quantify MP

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in environmental samples on a polymer specific mass related trace level. The method is

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independent of any optical preselection or particle appearance. For this purpose polymer

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characteristic pyrolysis products and their indicative fragment ions were used to analyze eight

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common types of plastics. Further aspects of calibration, recoveries, and potential matrix effects

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are discussed. The method is exemplarily applied on selected fish samples after an enzymatic-

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chemically pretreatment. This new approach with mass-related results is complementary to

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established FT-IR and Raman methods providing particle counts of individual polymer particles.

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INTRODUCTION

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Since the 1950s around 6.46 billion tons of plastics have been produced worldwide (estimated

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from 1), with 311 million tons in 2014 alone - and the production of MP is still rising.

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Conservative estimates predict that around 10% of all produced plastics will end up in the

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oceans 2. Key reasons for this are insufficient waste management and less reflected end

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consumer habits. Estimations indicate that 2010 alone between 4.8 to 12.7 million tons of land

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based plastic waste entered the oceans 3.

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The attention on plastic litter particularly on microplastics (MP) smaller than 5 mm has risen

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greatly in recent times. The proportion of macro plastics on marine debris has leveled off in

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recent times 4, that of MP increased continuously mostly due to fragmentation processes of

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altered plastic litter and additional input of technical micro particles from different sources. In

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relation to particle numbers it is supposed to be the most prominent plastic fraction today 5.

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World ocean models comparing predicted with measured data show an evident minor presence

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of measured small microplastics (S-MP) below 1 mm and lead to the assumption of a so far

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unknown sink of this fraction 6,7.

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Although the impact of MP on the environment grows with declining particle size 5,8–12, practical

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specific and selective approaches for qualitative and quantitative analysis of individual plastics in

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environmental samples on a sub millimeter scale are still lacking.

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Synthetic polymers are broad in variety in terms of chemical composition and physico-chemical

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characteristics. Identification of macro- and mesoplastics is possible according to their source

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and appearance. These features become less distinctive with decreasing particle sizes. Even

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while using a microscope, an additional, reliable identification method is obligate. For this

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purpose FT-IR and Raman techniques are the most common used for identification of different

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polymer types after optical preselection of conspicuous particles. More recently imaging

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techniques have become popular, which enable an almost automatic scanning of prepared

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samples for characteristic absorption bands of selected polymers. However, this technique is time

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consuming, because analysis time increases substantially with decreasing particle size. In all

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cases particle number related data are generated. The potential of these techniques is reviewed in

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the literature 13–16.

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Pyrolysis-gas chromatography in combination with mass spectrometry (Py-GCMS) can be used

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for reliable identification of isolated plastic particles by analyzing their characteristic thermal

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degradation products e.g. 17–20 and is commonly applied in the polymer industry. However, this

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technique has only rarely been used to detect plastics in environmental samples 21–25 but became

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more popular recently 26–28. In these studies particles, suspected to be plastic, are isolated

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manually and subjected to Py-GCMS.

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In addition, to identification Py-GCMS could also be applied for quantitative trace analysis of

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MP on a polymer specific level if the pyrolysis conditions are highly reproducible to generate a

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consistent composition of pyrolysis products 18,29–31. In environmental samples this was seldom

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done to date and when attempted it was restricted on a few selected polymers (polyvinyl chloride

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(PVC) and polystyrene (PS) 22, PS 30 and modified polyamides32. Very recently a promising

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thermo-gravimetric method for PE determination in environmental samples was introduced.

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Combined with GCMS this technique bears a great potential for polyethylene (PE) detection in

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complex samples even with MP concentration as low as 5w% MP so far tested in spiked

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environmental samples exceed realistic levels in most cases 33.

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Our intention was to develop an analytical setup, which enables a qualitative and quantitative

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polymer specific, weight-related trace analysis of MP in environmental samples with a special

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focus on small MP detracted from optical detection or mechanical particle separation.

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Accordingly, we demonstrate here Curie point (CP)-Py-GCMS combined with

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thermochemolysis (a pyrolytic methylation step 34,35) as an equally reliable and practical

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analytical method for eight relevant common consumer user plastics (PE, polypropylene (PP),

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PS, polyethylene terephthalate (PET), PVC, poly(methyl methacrylate) (PMMA), polycarbonate

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(PC), and polyamide 6 (PA6 detected simultaneously within a single GCMS run. Together they

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represent around 80 % of the actual plastic demand 1 and are prominent in perishables as well as

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disposable packaging. We show that this approach delivers qualitative information and weight-

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related at least semi quantitative data for individual polymers on a trace level independent of

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particle size, shape and a prior optical detection. According to this it is complementary to

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common particle related FT-IR- and Raman techniques for MP analysis. Its successful

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application in combination with complex environmental matrices is exemplarily demonstrated on

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fish samples. Their stomachs and gastro-intestinal (GI) tracts contain a broad spectrum of various

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food related inorganic (e.g. sand, mussel shells) and organic matrix compounds that are

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representative for those expected in environmental samples. The method can be transferred to

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any sample type after an adequate MP preconcentration.

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Concentration ranges to which the method is applicable, detection limits for individual polymers,

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potential interferences of biological matrices with indicator signals selected and recoveries of

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polymers spiked into fish stomach samples in trace amounts are presented and critically

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discussed.

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EXPERIMENTAL SECTION

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CP-Pyrolysis-GCMS/Thermochemolysis. CP-Pyrolysis-GCMS measurements were performed

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with a Curie-Point-Pyrolyzer (CP) Pyromat (GSG Mess- und Analysengeräte, Bruchsal,

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Germany) in a 590°C CP-pyrolytic target cup (GSG). The Pyrolyzer was attached to an Agilent

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6890 N gas chromatograph equipped with a DB-5MS-column linked to an Agilent MSD 5793 N

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mass spectrometer. Additional details on the Py-GCMS conditions are included in the

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Supporting Information (SI), table S1. Thermochemolysis was performed by adding 10 µl of

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tetramethyl ammonium hydroxide (TMAH, 25% in water) to the individual samples directly into

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the CP-pyrolysis targets prior to pyrolysis.

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Polymer identification. To unequivocally identify single polymers in complex natural samples

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specific indicator compounds for each polymer are needed. Therefore a database of different

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polymers (PE, PP, PS, PVC, PA6, PMMA, PET, and PC) was created by measuring polymer

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standards and in some cases additionally polymers of consumer products (for further

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specifications cf. SI Tab. S2) with direct pyrolysis and thermochemolysis, respectively. The

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obtained pyrograms were compared with an in-house database and literature data from Tsuge et

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al. (2011), respectively. The most abundant and/or polymer-specific compounds from TMAH

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pyrograms (cf. results and discussion) were chosen as indicators for polymer specific qualitative

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and quantitative analysis (Tab. 2, and SI Fig. S1 - S8, Tab. S3).

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Calibration. To obtain external calibration curves pyrolysis targets were prepared by adding

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Al2O3 as inert dilution matrix. Between 0.4 and 1070 µg of polymer standards were weighed

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directly into the pyrolysis targets using a Cubis® Ultramicro balance MSE2.7S-000-DM

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(Sartorius, Germany). Finally an Al2O3 cover and in most cases TMAH were added. Polymer

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standards were measured individually and in mixtures. Individual polymers were calibrated

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externally by means of preselected indicator compounds by using the mass chromatograms of

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their respective indicator ions and respective integration results. The bands of confidence and

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prediction at 95% confidence level each were calculated with Origin 2016G (OriginLab

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corporation).

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Fish samples. The applicability of the method to real environmental samples was demonstrated

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by analyzing fishes caught in 2014. Pelagic and demersal fish samples for recovery studies were

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caught in the Jade Bay (North Sea, Germany, stow net) and in two locations from the Baltic Sea

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(Wismar Bay, gillnet, and 35 km north of Rügen Island, demersal trawl). The stomachs (mostly

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pooled in numbers of five) and gastrointestinal (GI)-tracts used for spiking had samples weights

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between one and 20 g. All fishes belong to a sample pool of a pilot study on microplastics in

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fishes; the corresponding data will be published subsequently.

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Sample Clean-up. Sample treatment was adapted and optimized according to existing methods

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SDS, protease, chitinase and H2O2 treatment to remove biological matrix as much as possible

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and to preconcentrate potential microplastic content. Subsequently the vacuum dried samples

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were degreased with a few milliliter of petrol ether (60/80). In case of benthic fish samples a

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high sand content made an additional density separation with sodium iodide solution (~1.6 gL-1)

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necessary. All treatments and washing steps were performed in the same crucible, almost the

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whole time covered with alumina foil to prevent secondary contamination with plastics and

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fibers from the surrounding air. Parallel to the fish samples procedural blanks were conducted to

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follow possible contamination pathways and estimate their extent. At the end of treatment the

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content of crucible was transferred quantitatively to an Anodisc ® filter (0.2 µm) and dried in a

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glass Petri dish. The 6 mm (∅) filter section containing the sample was stamped out and milled

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in a small agate bullet mortar, transferred into a pyrolysis target and pyrolyzed after addition of

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TMAH (25% w/w in water). A detailed clean-up protocol is given in the supplement (SI, S-13).

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Spiking and recovery experiments. The method was verified on fish samples from the same

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type already described, spiked with the respective eight polymers at different stages of sample

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pretreatment (Fig. 2). Around 60 µg (100 µg in case of PE) or less per polymer was spiked, as a

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warranty of fitness for MP trace analysis. Former analysis data from the same fish set (to be

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shown elsewhere) ensure that the MP content of the spiked fishes was far below 20 µg for PE, 6

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µg for PVC as well as PS and 1 µg for PET, PMMA, PA6, and PC, or even lower. PP was not

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detected in this sample set. Therefore a potential impact of these plastics should be negligible to

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the general assessment of the method. To investigate possible effects of any remaining matrix

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(tissue, gastric contents), polymers were added directly to pyrolysis-targets containing the fish

. The samples were enzymatically and chemically digested as a whole via a succession of

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sample. To check the sample digestion procedure polymers were directly spiked to isolated

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stomachs. The influence of the sample homogenization and transfer step into the targets was

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tested by adding the polymers to the prepared sample on dry Anodisc® filter.

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Potential interferences. As potentially interfering compounds which might be present because

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of incomplete sample digestion or due to secondary contamination pyrograms of chitin, (isolated

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from samples and copepods), pine wood, wool and cellulose (fiber and tissue) were reviewed for

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polymer indicator compounds/ions chosen.

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RESULTS AND DISCUSSION

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Polymer identification and indicator compound selection. Since respective polymers underlie

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different decomposition mechanisms e.g. 38,39 their resulting characteristic pyrograms vary

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basically in terms of generated products, signal number and related intensities. Table 1 gives a

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synopsis of the pyrolytic behavior of the studied polymers without and with thermochemolysis.

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The related pyrograms are presented in the supplement (SI Fig. S1 - S8). If pyrolysis is

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performed after TMAH addition the pyrolytic behavior stayed unaffected for PE, PP, PS and

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PVC while that of PET, PMMA, and PA6 changed. Since the intention of this study strives for

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the simultaneous trace detection of the selected polymers, most intensive pyrolysis products are

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desirable for most sensitive polymer detection. Taking this into consideration, thermochemolytic

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pyrolysis with TMAH, an online esterification, transesterification, and methylation process 34,35,

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bears the most benefits.

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Leading to substantially less and specific reaction products, TMAH addition enhances the

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detection sensitivity for PET and PC (cf. SI Fig. S7, S8).

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Table 1. Pyrolytic behavior of polymers with and without TMAH addition Polymer

PE

Direct pyrolysis a, c

Thermochemolysis (TMAH)a

Mechanism

(Main-)Signals

Mechanism (Main-)Signals

RCS

Multiple signals of n-alkanes, n- Unaffected

Unaffected

alkenes and n-alkadienes PP

RCS

Multiple signals of methyl alkenes Unaffected

Unaffected

and alkadienes PS

ECS, RCS

Mono-, di-, tri- and tetramers

Unaffected

Unaffected

PVC

Chain

HCl b, benzene, multiple small

Unaffected

Unaffected

stripping

signals of aromatic compounds

PET

CS,

Multiple signals of benzoate and

PBT

secondary

terephthalate derivatives and

reactions

oligomers

PC

Dimethyl TCTM terephthalate

RCS, cross- Bisphenol A 17; triphenyl

Methylated TCTM

linking PMMA Poly(alkyl

phosphine oxide (flame retardant)a

Bisphenol A Methyl methacrylate

Monomer, smaller signals of ECS

dimers and trimer

TCTM

and

alkyl

methacrylates

metacrylate)s PA 6

Methyl

ECS

ε-Caprolactam, traces of nitriles TCTM and cyanopentyl amides

(partial)

ε-Caprolactam,

N-

methyl-ε-caprolactam

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RCS = random chain scission; ECS = end chain scission; CS = chain scission TCTM = thermochemolytic transmethylation; a For respective pyrograms in detail see supplement; b according to 38,39; c number of signals depending on polymer concentration

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Furthermore advantageous is the inclusion of other less used polyalkylene terephthalates like

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PBT (polybutylene terephthalate) into the measurements due to the generation of the identical

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reaction product, dimethyl terephthalic acid, like PET. This is also appropriate for PMMA and

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poly(alkyl methacrylate)s leading to methyl methacrylate in varying portions due to pyrolytic

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transesterification. For PA6, TMAH treatment leads to a partial methylation of ε-caprolactam.

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The selected indicator compounds for simultaneous detection of the different polymers and

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related information are summarized in table 2 (cf. also SI Fig. S1 - S8). The determination of

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most polymers (PE, PP, PVC, PET, PC, PA6 and PMMA) was unambiguous, with regard to their

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most abundant and selective pyrolysis product(s). For PE n-alkadienes are most indicative

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pyrolysis products 33. However, their signal intensity decreases drastically at concentrations

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below 50 µg and they become unreliable for natural samples with low PE concentrations. Here

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knowing full well that precaution is necessary for forthcoming identification and quantification

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of PE in environmental samples, the more prominent, but matrix interfered n-alkanes and n-

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alkenes are chosen for PE determination. This will be discussed and explained later. For PP all

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three tetramethyl-undecenes and dimethyl heptene, for PET dimethyl terephthalate and for PC

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dimethyl bisphenol A were selected as indicator compounds. For PVC benzene was chosen as an

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indicator since hydrochloric acid is inappropriate for GCMS detection and other compounds do

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not have sufficient sensitivity. PS has two favored indicator compounds, styrene and its trimer

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(5-hexene-1, 3, 5-triyltribenzene), which differ in specificity and abundance. While the former is

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very abundant but nonspecific, the opposite is true for the latter. Therefore, styrene is a perfect

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indicator compound for PS quantification in matrix-free samples such as vehicle paint 30. In

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natural matrices, however, it may be generated from different precursors i.e. chitin as discussed

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later. In these cases the less intensive styrene trimer is more reliable since its generation is

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unequivocally linked to the presence of PS. Spontaneous gas phase polymerization might lead to

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a loss of pyrolytic generated styrene monomer 40 and influence PS quantification. Even no

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indication for this was observed (cf. SI) it favors the trimer as indicator compound as well. ε-

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Caprolactam, indicative for PA6, is partially methylated after thermochemolysis. Either signal is

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very specific for this polymer therefore both are used for identification and the sum of both for

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quantification.

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In summary, the selected characteristic indicator products and their respective ions enable a

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simultaneous detection and identification of the eight selected polymers on a trace level

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whenever samples are pyrolyzed with TMAH. Although the detection of dimethyl terephthalate

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indicates the presence of all poly(alkylene terephthalate)s, we use in the following the term PET,

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the by far main representative, in the following. This applies also to poly(methacrylate)s –

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containing other substituents than methyl. After thermochemolysis they are partially detected as

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methyl methacrylate monomer and summarized as “PMMA” disregarding their former molecular

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weight or substituent. In environmental samples the so-called PMMA signal also includes parts

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of other methacrylate based polymers as well, but points to their anthropogenic impact in

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general. Finally, copolymers that contain at least one of the selected plastic types will be

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determined, too. Thus, the styrene part of, e.g., SAN (styrene acrylonitrile copolymer) will

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contribute to the determined PS content.

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Full scan measurements allow the identification of the respective indicator compounds via their

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mass spectra. Concentration dependent less abundant pyrolysis products enable the identification

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of the individual polymers, too (cf. Tab. 2).

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Calibration. The optimal mass range to use Py-GCMS for quantification is polymer dependent.

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The respective calibration ranges are listed in the SI Tab. S3. Additionally, particle size should

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be as small as possible to enable optimal pyrolysis and, in case of TMAH use, optimal reaction -

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surface.

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Table 2. Polymer related pyrogram information Polymer Characteristic decomposition product(s)

M

Indicator ions

MP amount required

(m/z)

(m/z) a

(µg)

S/N

Alkanes (e.g. C20)

2000

282

99, 85