Migration of (non-) intentionally added substances and microplastics from microwavable plastic food containers

He, Yun; Qin, Yan; Zhang, Tie-Li; Zhu, Yanyan; Wang, Zhaojie; Zhou, Zhong-Shun; Xie, Tian-Zhen; Luo, Xiao-Dong

doi:10.1016/j.jhazmat.2021.126074

Cited by 51 publications

(20 citation statements)

References 33 publications

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“…It is also noticeable that the HQIs of tested particles can reach 0.85–0.89 compared to standard PP, and so these particles could be misassigned as PP MPs since they originated from a PP-based container. This high MP release level is comparable to previous reports on plastic containers (releasing over 1 million MPs per liter 26 , 47 or 1.2–7.6 mg of MPs from a single container 48 ). However, most of these confirmed MPs dissolved away when the filter was placed onto a glass holder and rinsed using ethanol.…”

Section: Resultssupporting

confidence: 86%

“…There were over a million MPs per liter released in the present study and in previous reports. 26 , 47 , 48 However, after an ethanol rinse, the MP level dropped by 5 orders of magnitude in this study. Similarly, while large quantities of MP were reported to be released from plastic baby feeding bottles, 3 , 37 our reassessment based on the new alcohol protocol showed that the levels of MPs decreased from over 1 million per liter to around 100–100,000 per liter, which depends on multiple factors, such as the brand type and duration of use.…”

Section: Discussioncontrasting

confidence: 55%

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Alcohol Pretreatment to Eliminate the Interference of Micro Additive Particles in the Identification of Microplastics Using Raman Spectroscopy

Sheerin

Shi

et al. 2022

Environ. Sci. Technol.

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Raman spectroscopy is an indispensable tool in the analysis of microplastics smaller than 20 μm. However, due to its limitation, Raman spectroscopy may be incapable of effectively distinguishing microplastics from micro additive particles. To validate this hypothesis, we characterized and compared the Raman spectra of six typical slip additives with polyethylene and found that their hit quality index values (0.93–0.96) are much higher than the accepted threshold value (0.70) used to identify microplastics. To prevent this interference, a new protocol involving an alcohol treatment step was introduced to successfully eliminate additive particles and accurately identify microplastics. Tests using the new protocol showed that three typical plastic products (polyethylene pellets, polyethylene bottle caps, and polypropylene food containers) can simultaneously release microplastic-like additive particles and microplastics regardless of the plastic type, daily-use scenario, or service duration. Micro additive particles can also adsorb onto and modify the surfaces of microplastics in a manner that may potentially increase their health risks. This study not only reveals the hidden problem associated with the substantial interference of additive particles in microplastic detection but also provides a cost-effective method to eliminate this interference and a rigorous basis to quantify the risks associated with microplastic exposure.

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Section: Resultssupporting

confidence: 86%

Section: Discussioncontrasting

confidence: 55%

Alcohol Pretreatment to Eliminate the Interference of Micro Additive Particles in the Identification of Microplastics Using Raman Spectroscopy

Sheerin

Shi

et al. 2022

Environ. Sci. Technol.

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“…The remaining plastic waste was either incinerated, accumulated in landfills, or disposed of in natural environments . The impact of plastic waste on the environment and, subsequently, human health is of great concern due to the release of microplastics − and low-molecular-weight (MW) chemicals. − During the production of plastics, a variety of additives are incorporated into the polymeric formulations to enhance favorable characteristics and extend service life. Commonly used additives include plasticizers, flame retardants, lubricants, antioxidants, and UV stabilizers .…”

Section: Introductionmentioning

confidence: 99%

Prediction of Collision Cross-Section Values for Extractables and Leachables from Plastic Products

Song

Dreolin

Canellas

et al. 2022

Environ. Sci. Technol.

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The use of ion mobility separation (IMS) in conjunction with high-resolution mass spectrometry has proved to be a reliable and useful technique for the characterization of small molecules from plastic products. Collision cross-section (CCS) values derived from IMS can be used as a structural descriptor to aid compound identification. One limitation of the application of IMS to the identification of chemicals from plastics is the lack of published empirical CCS values. As such, machine learning techniques can provide an alternative approach by generating predicted CCS values. Herein, experimental CCS values for over a thousand chemicals associated with plastics were collected from the literature and used to develop an accurate CCS prediction model for extractables and leachables from plastic products. The effect of different molecular descriptors and machine learning algorithms on the model performance were assessed. A support vector machine (SVM) model, based on Chemistry Development Kit (CDK) descriptors, provided the most accurate prediction with 93.3% of CCS values for [M + H] + adducts and 95.0% of CCS values for [M + Na] + adducts in testing sets predicted with <5% error. Median relative errors for the CCS values of the [M + H] + and [M + Na] + adducts were 1.42 and 1.76%, respectively. Subsequently, CCS values for the compounds in the Chemicals associated with Plastic Packaging Database and the Food Contact Chemicals Database were predicted using the SVM model developed herein. These values were integrated in our structural elucidation workflow and applied to the identification of plastic-related chemicals in river water. False positives were reduced, and the identification confidence level was improved by the incorporation of predicted CCS values in the suspect screening workflow.

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“…Collectively, this allows for faster and more reliable estimations of identity, thus improving our ability to screen for migration of NIAS into food. Previous nontargeted work has identified various migrants in plastic packaging, − including those shown to exhibit cytotoxicity and endocrine disruption, − as well as chemicals lacking empirical toxicological information . Yet, a large majority of unknown migrants remain uncharacterized. , Screening for and reporting migrants, specifically NIAS, of plastic food packaging is an imperative first step to assessing food packaging safety.…”

Section: Introductionmentioning

confidence: 99%

Assessing Chemical Migration from Plastic Food Packaging into Food Simulant by Gas and Liquid Chromatography with High-Resolution Mass Spectrometry

Taylor

Sapozhnikova

2022

J. Agric. Food Chem.

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Some components of plastic food packaging can migrate into food, and whereas migration studies of known components are required and relatively straightforward, identification of nonintentionally added substances (NIAS; unknowns) is challenging yet imperative to better characterizing food safety. To this aim, migration was investigated across 24 unique plastic food packaging products including plastic wrap, storage bags, vacuum bags, and meat trays. Gas and liquid chromatography separation systems coupled with Orbitrap mass analyzers were used for comprehensive nontargeted screening of migrants. Tentative identifications of features were assigned by searching commercial databases (e.g., NIST, MZCloud, ChemSpider, Extractables and Leachables) and filtering results based on mass accuracy, retention time indices, and mass spectral patterns. Several migrants showed elevated levels in specific food packaging types, particularly meat trays and plastic wrap, and varying degrees of migration over the 10 days. Eleven putative migrants are listed as substances of potential concern or priority hazardous substances. Additionally, migration amounts of an Irgafos 168 degradation product determined by semiquantitation exceeded proposed theoretical maximum migration values.

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Migration of (non-) intentionally added substances and microplastics from microwavable plastic food containers

Cited by 51 publications

References 33 publications

Alcohol Pretreatment to Eliminate the Interference of Micro Additive Particles in the Identification of Microplastics Using Raman Spectroscopy

Alcohol Pretreatment to Eliminate the Interference of Micro Additive Particles in the Identification of Microplastics Using Raman Spectroscopy

Prediction of Collision Cross-Section Values for Extractables and Leachables from Plastic Products

Assessing Chemical Migration from Plastic Food Packaging into Food Simulant by Gas and Liquid Chromatography with High-Resolution Mass Spectrometry

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