A two-dimensional gas chromatography-time-of-flight/mass spectrometry (GC×GC-TOF/MS) suspect screening analysis method was used to rapidly characterize chemicals in 100 consumer products-which included formulations (e.g., shampoos, paints), articles (e.g., upholsteries, shower curtains), and foods (cereals)-and therefore supports broader efforts to prioritize chemicals based on potential human health risks. Analyses yielded 4270 unique chemical signatures across the products, with 1602 signatures tentatively identified using the National Institute of Standards and Technology 2008 spectral database. Chemical standards confirmed the presence of 119 compounds. Of the 1602 tentatively identified chemicals, 1404 were not present in a public database of known consumer product chemicals. Reported data and model predictions of chemical functional use were applied to evaluate the tentative chemical identifications. Estimated chemical concentrations were compared to manufacturer-reported values and other measured data. Chemical presence and concentration data can now be used to improve estimates of chemical exposure, and refine estimates of risk posed to human health and the environment.

Recycled materials are found in many consumer products as part of a circular economy; however, the chemical content of recycled products is generally uncharacterized. A suspect screening analysis using twodimensional gas chromatography time-of-flight mass spectrometry (GC × GC-TOFMS) was applied to 210 products (154 recycled, 56 virgin) across seven categories. Chemicals in products were tentatively identified using a standard spectral library or confirmed using chemical standards. A total of 918 probable chemical structures identified (112 of which were confirmed) in recycled materials versus 587 (110 confirmed) in virgin materials. Identified chemicals were characterized in terms of their functional use and structural class. Recycled paper products and construction materials contained greater numbers of chemicals than virgin products; 733 identified chemicals had greater occurrence in recycled compared to virgin materials. Products made from recycled materials contained greater numbers of fragrances, flame retardants, solvents, biocides, and dyes. The results were clustered to identify groups of chemicals potentially associated with unique chemical sources, and identified chemicals were prioritized for further study using high-throughput hazard and exposure information. While occurrence is not necessarily indicative of risk, these results can be used to inform the expansion of existing models or identify exposure pathways currently neglected in exposure assessments.

Non-targeted analysis (NTA) encompasses a rapidly evolving set of mass spectrometry techniques aimed at characterizing the chemical composition of complex samples, identifying unknown compounds, and/or classifying samples, without prior knowledge regarding the chemical content of the samples. Recent advances in NTA are the result of improved and more accessible instrumentation for data generation and analysis tools for data evaluation and interpretation. As researchers continue to develop NTA approaches in various scientific fields, there is a growing need to identify, disseminate, and adopt community-wide method reporting guidelines. In 2018, NTA researchers formed the Benchmarking and Publications for Non-Targeted Analysis Working Group (BP4NTA) to address this need. Consisting of participants from around the world and representing fields ranging from environmental science and food chemistry to 'omics and toxicology, BP4NTA provides resources addressing a variety of challenges associated with NTA. Thus far, BP4NTA group members have aimed to establish a consensus on NTA-related terms and concepts and to create consistency in reporting practices by providing resources on a public Web site, including consensus definitions, reference content, and lists of available tools. Moving forward, BP4NTA will provide a setting for NTA researchers to continue discussing emerging challenges and contribute to additional harmonization efforts.

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Masks constructed of a variety of materials are in widespread use due to the COVID-19 pandemic, and people are exposed to chemicals inherent in the masks through inhalation. This work aims to survey commonly available mask materials to provide an overview of potential exposure. A total of 19 mask materials were analyzed using a nontargeted analysis twodimensional gas chromatography (GCxGC)−mass spectrometric (MS) workflow. Traditionally, there has been a lack of GCxGC− MS automated high-throughput screening methods, resulting in trade-offs with throughput and thoroughness. This work addresses the gap by introducing new machine learning software tools for high-throughput screening (Floodlight) and subsequent pattern analysis (Searchlight). A recursive workflow for chemical prioritization suitable for both manual curation and machine learning is introduced as a means of controlling the level of effort and equalizing sample loading while retaining key chemical signatures. Manual curation and machine learning were comparable with the mask materials clustering into three groups. The majority of the chemical signatures could be characterized by chemical class in seven categories: organophosphorus, long chain amides, polyethylene terephthalate oligomers, n-alkanes, olefins, branched alkanes and long-chain organic acids, alcohols, and aldehydes. The olefin, branched alkane, and organophosphorus components were primary contributors to clustering, with the other chemical classes having a significant degree of heterogeneity within the three clusters. Machine learning provided a means of rapidly extracting the key signatures of interest in agreement with the more traditional time-consuming and tedious manual curation process. Some identified signatures associated with plastics and flame retardants are potential toxins, warranting future study to understand the mask exposure route and potential health effects.