🎤Francis Femi OloyIn this episode of Concentrating on Chromatography, David speaks with Francis Femi Oloy about using chromatography to uncover hidden pollutants in real-world water systems.Femi’s team analyzed polychlorinated biphenyls (PCBs) in six major rivers in southwestern Nigeria — compounds that were banned decades ago but still persist in the environment. Using a workflow that many analytical labs will recognize — liquid–liquid extraction, cleanup, rotary evaporation, nitrogen blowdown, and GC-ECD detection — they quantified 25 PCB congeners at trace levels and linked the results to ecological and human health risk.<h4>In this conversation, we cover:</h4><ul><li>Why legacy pollutants like PCBs still show up today</li><li>Choosing GC-ECD vs LC-MS for halogenated compounds</li><li>Liquid–liquid extraction and matrix cleanup strategies</li><li>Why sample concentration is critical for dilute environmental samples</li><li>How rotovap + nitrogen blowdown work together without losing volatile analytes</li><li>Seasonal trends (why wet season levels were higher)</li><li>Translating concentration data into meaningful risk assessments</li></ul><h3>Video Transcription</h3><section><div><div><div><div><div><div>Persistent organic pollutants such as polychlorinated biphenyls (PCBs) remain a significant environmental concern despite decades of regulatory restrictions. In this interview, Francais Femi Oloy discusses the environmental and analytical challenges associated with monitoring PCB contamination in rivers of southwestern Nigeria, a rapidly industrializing region where urban growth, industrial activity, agriculture, and dense populations intersect with extensive aquatic systems.Oloy explains that his interest in environmental contaminant analysis emerged from observing unexplained health problems and environmental degradation while growing up in Nigeria. This motivated his transition into organic and environmental chemistry, with a focus on identifying pollutants present in drinking water, agricultural soils, and food systems. Southwestern Nigeria, particularly the Lagos region, represents a critical environmental monitoring area due to intense industrial development, shipping activity, and widespread human dependence on rivers for domestic use, agriculture, and fishing.Although PCBs are considered “legacy pollutants” and are no longer intentionally produced, the interview highlights why they continue to persist in aquatic environments. Old electrical transformers and aging industrial equipment still contain PCB residues, while historical contamination stored in river sediments can become remobilized during flooding, dredging, or sediment disturbance. Because PCBs are hydrophobic and resistant to degradation, they preferentially accumulate in sediments and bioaccumulate through aquatic food chains, creating long-term environmental and human exposure risks.A major focus of the discussion centers on the analytical workflow used for PCB determination in environmental water samples. Composite river water samples were collected in amber glass bottles to avoid contamination and photodegradation, preserved with sodium azide to minimize microbial activity, and stored under cooled conditions prior to extraction. The analytical protocol employed liquid–liquid extraction using dichloromethane (DCM) and hexane to recover both polar and nonpolar PCB congeners. Oloy emphasizes that liquid–liquid extraction was selected over solid-phase extraction (SPE) because of concerns about congener retention within sorbent materials and clogging issues associated with large-volume environmental samples.Following extraction, concentration and cleanup represented critical analytical stages due to the trace-level occurrence and volatility of PCBs. Silica and alumina cleanup procedures were used to remove matrix interferences prior to instrumental analysis. The concentration workflow combined rotary evaporation for bulk solvent reduction with nitrogen blowdown for final volume reduction to less than 1 mL, while carefully avoiding excessive temperature or complete dryness to minimize analyte loss. Oloy repeatedly stresses that improper concentration procedures are among the most common causes of analytical failure in PCB analysis.For instrumental determination, the study utilized gas chromatography coupled with electron capture detection (GC-ECD) rather than LC-MS or GC-MS. According to Oloy, GC was preferred because PCBs are sufficiently volatile for gas chromatographic separation, while ECD provided superior sensitivity and selectivity for chlorinated compounds at environmentally relevant concentrations. The interview also discusses analytical validation strategies, including the use of surrogate standards to assess recoveries, which ranged from approximately 85% to 114%, and signal-to-noise-based determination of detection limits.The study further examined seasonal variations in PCB concentrations, revealing higher levels during the wet season. This observation was attributed to rainfall-driven runoff from contaminated infrastructure, sediment resuspension, and lower temperatures that reduce volatilization losses. To communicate toxicological relevance beyond simple concentration reporting, the researchers also calculated toxic equivalency values (TEQs), converting mixtures of PCB congeners into biologically meaningful toxicity estimates comparable to dioxin toxicity metrics.Beyond environmental monitoring, Oloy highlights broader research interests focused on pollutant remediation and sustainable environmental protection. His group is also involved in developing catalytic materials capable of degrading or removing persistent contaminants from environmental systems. Throughout the discussion, he emphasizes that analytical chemistry plays a central role not only in detecting pollutants, but also in enabling prevention, remediation, and long-term environmental management strategies.</div></div></div></div></div></div></section><blockquote>This text has been automatically transcribed from a video presentation using AI technology. It may contain inaccuracies and is not guaranteed to be 100% correct.</blockquote><blockquote><h4>Concentrating on Chromatography Podcast</h4>Dive into the frontiers of chromatography, mass spectrometry, and sample preparation with host David Oliva. Each episode features candid conversations with leading researchers, industry innovators, and passionate scientists who are shaping the future of analytical chemistry. From decoding PFAS detection challenges to exploring the latest in AI-assisted liquid chromatography, this show uncovers practical workflows, sustainability breakthroughs, and the real-world impact of separation science. Whether you’re a chromatographer, lab professional, or researcher you'll discover inspiring content!You can find Concentrating on Chromatography Podcast in podcast apps:<ul><li><a target="_blank" rel="noopener noreferrer" href="https://open.spotify.com/show/1wZg67rCjoGju4yhqxI3tL">Spotify</a></li><li><a target="_blank" rel="noopener noreferrer" href="https://podcasts.apple.com/tz/podcast/concentrating-on-chromatography/id1788429185">Apple podcast</a></li><li><a target="_blank" rel="noopener noreferrer" href="https://podscan.fm/podcasts/concentrating-on-chromatography">podscan</a></li></ul>and on <a target="_blank" rel="noopener noreferrer" href="https://www.youtube.com/@ChromatographyTalk/videos">YouTube channel</a></blockquote>

Tracking Toxic PCBs in River Water using Gas Chromatography–Electron Capture Detection

This study presents a high-temperature GC-APCI-MS/MS method for detecting large polycyclic aromatic hydrocarbons in pyroplastics and environmental samples. The approach enables sensitive analysis of PAHs with molecular weights from 314–424 Da without extensive cleanup or fractionation.Application to pyroplastics from the M/V X-Press Pearl fire revealed substantially elevated levels of large PAHs compared to unburnt plastics. Several compounds, including 1,3,5-triphenylbenzene, emerged as promising markers for identifying pyroplastic contamination, supporting future monitoring of plastic burning, fires, and microplastic pollution.<blockquote><h4>The original article</h4><h4><a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c11703">Gas Chromatography-Atmospheric Pressure Chemical Ionization (GC-APCI) Expands the Analytical Window for Detection of Large PAHs (≥24 Ringed-Carbons) in Pyroplastics and Other Environmental Matrices</a></h4>Cara Megill, Douglas M. Stevens*, Christopher M. Reddy, Bryan D. James*, Robert K. Nelson, and Frank L. DormanACS Omega 2026, 11, 7, 12321–12329<a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1021/acsomega.5c11703">https://doi.org/10.1021/acsomega.5c11703</a><h6>licensed under <a target="_blank" rel="noopener noreferrer" href="https://creativecommons.org/licenses/by/4.0/">CC-BY 4.0</a></h6></blockquote>Selected sections from the article follow. Formats and hyperlinks were adapted from the original.<div>The measurement and reporting of polycyclic aromatic hydrocarbons (PAHs) are routine practices in environmental monitoring and risk assessment. <a href="javascript:void(0);">(1−3)</a> However, of the thousands of PAHs, only the 16 designated as Priority Pollutants by the U.S. Environmental Protection Agency (EPA16) are typically reported. <a href="javascript:void(0);">(4,5)</a> These span two to six ringed parent PAHs, ranging in molecular weight from 128 to 278 Da. It is well recognized that this limited analyte list drastically simplifies and misses a significant fraction of PAHs. <a href="javascript:void(0);">(4)</a> For example, the concentration of C1–C4 alkylated PAHs can be greater than or equal to the concentration of the EPA16 in crude oils and fuels. <a href="javascript:void(0);">(6)</a> Expanding the analytical window of PAHs has proven valuable for forensic analysis of oil spills (e.g., alkylated and heterocycle-containing PAHs) and relevant for toxicological evaluation(e.g., oxygen-, nitrogen-, and sulfur-containing PAHs). <a href="javascript:void(0);">(3,7)</a> Moreover, the sources of PAHs have distinct compositions of PAHs, <a href="javascript:void(0);">(1,8)</a> which enables the use of PAHs for source apportionment. <a href="javascript:void(0);">(2,7)</a> Including alkylated and sulfur-containing PAHs (those beyond the EPA16) in the investigation of environmental samples and other matrices provides greater discriminating power between potential sources (using extracted ion chromatograms). <a href="javascript:void(0);">(3,7,9)</a> Additionally, monitoring the compositional changes of PAHs in the environment can inform about the fate and environmental processing of the matrix (e.g., oil weathering). <a href="javascript:void(0);">(2)</a> While these efforts have made strides in considering other PAHs, an environmentally relevant fraction of PAHs remains underutilized.PAHs with more than six rings have been reported in diverse environmental matrices. <a href="javascript:void(0);">(10,11)</a> These large PAHs (≥24 ringed-carbons <a href="javascript:void(0);">(10)</a>) have been found in combustion-derived particulate matter, <a href="javascript:void(0);">(12−19)</a> urban dust, <a href="javascript:void(0);">(20−23)</a> refinery deposits, <a href="javascript:void(0);">(11)</a> coal tars and pitches, <a href="javascript:void(0);">(24−27)</a> cokes, <a href="javascript:void(0);">(28)</a> soils, <a href="javascript:void(0);">(20,22)</a> sediments, <a href="javascript:void(0);">(20−23)</a> and deep-sea hydrothermal vent bitumen. <a href="javascript:void(0);">(29)</a> Most reports of large PAHs in environmental matrices have been from analyses of U.S. National Institute of Standards and Technology (NIST) standard reference materials (SRMs); <a href="javascript:void(0);">(18,21−23,25,26,30)</a> a few 302 Da isomers have been certified in three SRM. <a href="javascript:void(0);">(31)</a> Nonetheless, isomers ranging from 326 to 374 Da have been reported in SRMs for urban dust (1649a/b), diesel particulate (1650b and 2975), coal tar (1597a), and marine sediment (1941b), displaying qualitative differences between the sources in their large PAH compositions; <a href="javascript:void(0);">(18,20,22,23,27)</a> thus, large PAHs should offer forensic utility.Recent advances in soft ionization within an atmospheric pressure chemical ionization source for gas chromatography–mass spectrometry (GC-APCI) are well-suited for the analysis of large PAHs. Two contributing factors for this are the tolerance for high carrier gas flow rates by GC-APCI and the sensitivity of charge exchange APCI for aromatic species. <a href="javascript:void(0);">(48)</a> Increasing the carrier gas flow rate reduces the elution temperature of analytes, making many higher mass analytes accessible using a conventional GC and column, although poor thermal stability may still pose challenges for some analytes. <a href="javascript:void(0);">(49)</a> Classic vacuum-source GC/MS systems using electron ionization (EI) restrict the upper carrier gas flow allowed from the GC, and therefore, cannot fully utilize high GC carrier gas flows. The sensitivity of GC-APCI for components of petroleum, such as PAHs, has been previously reported. <a href="javascript:void(0);">(48)</a> Furthermore, unlike LC-APCI, which commonly exhibits protonation of analytes in positive ion mode, <a href="javascript:void(0);">(50)</a> GC-APCI+ can operate with dry source conditions. These conditions result in nitrogen-mediated charge exchange ionization and ions of the form M+•, the same form of molecular ion created using EI. As a result, because the charge site location on an ion dictates which product ions will be stable, the same multiple reaction monitoring (MRM) transitions can be used for both GC-APCI MS/MS and EI MS/MS. <a href="javascript:void(0);">(51)</a>Herein, a GC-APCI method was developed for the detection of large PAHs. Due to the limited availability of pure standards, previously characterized NIST SRMs were used in method development as sources of large PAHs. The values of the method and detection of large PAHs were demonstrated by analyzing environmental plastic samples collected after the M/V X-Press Pearl ship fire and plastic spill.<h4>Materials and Methods</h4><h5>GC-APCI</h5>The solvent extracts and dilutions were analyzed by GC-APCI on a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/554">Xevo TQ Absolute</a> (Waters Corporation) tandem quadrupole mass spectrometer (TQ-MS/MS). The atmospheric pressure gas chromatography (APGC) ionization source was operated in charge transfer mode using dry N2 as the reagent gas. Dry N2 reagent gas creates molecular ions of the form M+• with no significant adduct formation for large PAHs. The high reagent gas flow rate of 350 mL/min into the ionization chamber, combined with low energies applied to the transfer optics from the atmospheric pressure region to the first quadrupole, leads to a high molecular ion survival rate. Furthermore, the use of MS/MS with quadrupoles operating at unit mass resolution prevents potential effects on response caused by adduct formation. Acquisitions were performed in positive ion, MRM mode. Two MRM transitions were used for each of the 16 precursor masses, ranging from 314 to 424 Da (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acsomega.5c11703/suppl_file/ao5c11703_si_001.pdf">Table S1</a>). No optimization of source conditions specific to the analysis of large PAHs was required. The list of 16 specific precursor masses targeted in this range was developed using multiple sources reporting large PAHs in NIST SRMs and samples from deep-sea hydrothermal vents. <a href="javascript:void(0);">(18,29,30)</a> The two transitions represented constant neutral losses of 2 and 4 Da at high collision energies of 60–100 eV, using N2 as the collision gas.For 1,3,5-TPB analysis, the APGC ionization source was operated in charge transfer mode using N2 as the collision gas. Acquisitions were performed in positive ion, MRM mode, yielding six MRM transitions for analysis (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acsomega.5c11703/suppl_file/ao5c11703_si_001.pdf">Table S2</a>). Similar to the large PAHs, this analyte also shows neutral losses of 2 and 4 Da, reflecting behavior like that of the more condensed structures.The <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=8890+GC">8890 GC (Agilent Technologies)</a> was configured with N2 as the carrier gas and an <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=7&amp;search=Rxi-5HT">Rxi-5HT column (Restek)</a> of 15 m in length, 0.25 mm inner diameter, and 0.10 μm film thickness. The split/splitless (SSL) injection port was operated at a 10:1 split ratio with a temperature of 380 °C. A 1 μL injection volume was used for all analyses. The temperature program was 30.8 min; it started by holding at 40 °C for 0.5 min, then ramped to 160 °C at 14 °C/min, followed by a ramp to 395 °C at 22 °C/min and a hold at the temperature for 11 min. The flow rate of the N2 carrier gas was initially 0.60 mL/min, then ramped at 0.015 mL/min2 to 0.90 mL/min, followed by a ramp at 0.150 mL/min2 to 3.0 mL/min. To adapt the system for high-temperature work, the SSL was configured with a high-temperature septum (400 °C maximum), a 100% graphite liner O-ring, and a straight 4 mm inner diameter, wool-packed liner (450 °C maximum). Additional instrument and method details are included in the <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acsomega.5c11703/suppl_file/ao5c11703_si_001.pdf">Supporting Information</a>.<h4>Results</h4><h5>Analysis of Large PAHs in Pyroplastic Samples by GC-APCI</h5>Macroplastic and microplastic debris from the M/V X-Press Pearl ship fire and plastic spill were investigated for the presence and distribution of large PAHs. The field samples included white, unburnt polyethylene nurdles and two types of pyroplastic, termed burnt plastic and combustion remnant (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c11703#fig1">Figure 1</a>), both of which were polyethylene. <a href="javascript:void(0);">(43)</a> The types of pyroplastics were previously operationally defined based on the size and shape of the pieces. <a href="javascript:void(0);">(43)</a>Investigation of the 302 Da isomers revealed profiles similar to those of the SRMs; however, unique differences were observed (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acsomega.5c11703/suppl_file/ao5c11703_si_001.pdf">Figure S2</a>). Eighteen to twenty-one peaks were detected across the plastic samples. Compared with the SRMs, the pyroplastics showed decreases in the relative abundance of dibenzo[a,e]fluoranthene and increases in dibenzo[a,h]pyrene (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acsomega.5c11703/suppl_file/ao5c11703_si_001.pdf">Figure S2</a>). This trend was not the case for the white nurdle sample. Starting at a retention time of 16.80 min, two peaks were unique to the pyroplastic samples (not present in the SRMs and especially minor in the white nurdles). These peaks followed that for dibenzo[a,h]pyrene, which had previously been reported as the last detected 302 Da isomer compound in the SRMs, <a href="javascript:void(0);">(21)</a> supporting their novelty as marker compounds of pyroplastics.The plastic samples displayed similarities and differences in the presence and distribution of large PAHs (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsomega.5c11703#fig3">Figure 3</a>). The white nurdles, burnt plastic, and combustion remnant all contained high-intensity peaks at 20.50 min for 398 Da and 19.55 min for 374 Da. Peaks between 20.00 and 20.25 min of 398 Da and the 19.35 min peak of 374 Da were reduced in intensity for the pyroplastics compared to the white nurdles (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acsomega.5c11703/suppl_file/ao5c11703_si_001.pdf">Figure S3</a>). Conversely, the peaks between 18.50 and 18.75 min of 350 Da were more intense in the pyroplastics compared to the white nurdles.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_Omega_2026_11_7_12321_12329_Figure_3_Comparison_of_the_resolved_isomers_for_398_374_and_350_Da_of_the_white_nurdles_burnt_plastic_and_combustion_remnant_pieces_ec390ebae3.jpg" alt="ACS Omega 2026, 11, 7, 12321–12329: Figure 3. Comparison of the resolved isomers for 398, 374, and 350 Da of the white nurdles, burnt plastic, and combustion remnant pieces collected from Pamunugama Beach, Sri Lanka, following the 2021 M/V X-Press Pearl ship fire and plastic spill." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_Omega_2026_11_7_12321_12329_Figure_3_Comparison_of_the_resolved_isomers_for_398_374_and_350_Da_of_the_white_nurdles_burnt_plastic_and_combustion_remnant_pieces_ec390ebae3.jpg 232w," sizes="100vw" width="1600" height="1077">The levels of all the targeted large PAHs were at least 2 orders of magnitude higher in the pyroplastics than in the white nurdles. These levels included the individual PAHs that were common to the pyroplastics. This trend mirrored that observed for smaller PAHs and the solvent-extractable content of the sample types. <a href="javascript:void(0);">(39,43,46)</a> There were also slight differences in the signatures of the large PAHs found in the pyroplastics. The 398 Da peak at 20.24 min, along with the 374 Da peak at 19.31 min and the 350 Da peak at 18.61 min, were more prominent in the combustion remnant compared to the burnt plastic (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acsomega.5c11703/suppl_file/ao5c11703_si_001.pdf">Figure S3</a>).Similar to the differences in large PAH signatures between the SRMs, the plastic samples had different signatures. Such qualitative interpretation of extracted ion chromatograms is forensically accepted for distinguishing sources. <a href="javascript:void(0);">(3)</a> This feature can potentially be utilized to differentiate between plastic types (e.g., virgin, weathered, and partially combusted) as well as to identify sources of the large PAHs and the combustion temperature.<h4>Conclusions</h4>GC-APCI-MS/MS proved a useful technique for detecting large PAHs in diverse environmental matrices, including extracts from pyroplastic field samples. Despite a lack of widely available analytical standards for large PAHs, NIST SRMs provided ample material for method development for their detection. Nonetheless, with the increasing research on microplastics in the environment and their relevance to human health, an environmental SRM with certified values for large PAHs is needed, and pyroplastics may provide such a source of material. Large PAHs and 1,3,5-TPB were detected in pyroplastic field samples and hold promise as chemical markers for pyroplastics, complementing other means for their detection in environmental samples (e.g., appearance and physical properties). Due to the accessibility of GC-APCI, the detection of large PAHs can be integrated into workflows for evaluating environmental samples, including those for microplastics.</div>

Gas Chromatography-Atmospheric Pressure Chemical Ionization (GC-APCI) Expands the Analytical Window for Detection of Large PAHs (≥24 Ringed-Carbons) in Pyroplastics and Other Environmental Matrices

In the week of May 11, the following webinars await you in the field of gas / solid phase and especially Raman, FTIR, GC and GC/MS.<blockquote><h4><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinars">👉 DETAILS AND REGISTRATION IN THE WEBINARS SECTION</a></h4>👉 Search and filter in the largest global database with over 5 500 GC, LC, MS and spectroscopy webinars.</blockquote><h5>1. Thermo Fisher Scientific: Uncovering Microplastics: Identification, Quantification, and Exposure Assessment</h5><ul><li>Tu, 12.5.2026 08:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/6136">Registration</a></li></ul>In this webinar, we will explore complementary analytical solutions for comprehensive microplastics characterization.<h5>2. AZoM: From Lab to Line: Leveraging GC and Process MS for Petrochemical Gas Analysis</h5><ul><li>We, 13.5.2026 16:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/6171">Registration</a></li></ul>Explore how GC and process MS work together in petrochemical workflows, combining detailed lab analysis with real-time gas monitoring for faster decisions.<h5>3. Milestone: Modern Sample Prep for Organic Contaminants: PAHs, PFAS, MOSH/MOAH in Food</h5><ul><li>We, 13.5.2026 16:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/5822">Registration</a></li></ul>Learn how microwave-assisted extraction streamlines food analysis of PAHs, PFAS, and MOSH/MOAH, improving recoveries, reducing solvents, and meeting regulatory demands.<h5>4. Thermo Fisher Scientific: End-to-end automation in GC/GC-MS: Trends, tools, and practical implementation</h5><ul><li>We, 13.5.2026 18:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/6186">Registration</a></li></ul>In this GC/GC-MS power hour session, we’ll explore how automation is transforming laboratories by helping teams do more with less time, fewer resources, and greater confidence.<h5>5. GERSTEL: Automating Food Safety Workflows for the Analysis of Edible Oils and Fats</h5><ul><li>We, 13.5.2026 20:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/6168">Registration</a></li></ul>Learn how automated workflows improve data quality in edible oil testing, including FAMEs, MOSH/MOAH, and 3-MCPD analysis with real-world insights.

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LECO ChromaTOF Identification Grading System

ChromaTOF Identification Grading System assigns confidence scores to GC×GC-HRTOFMS identifications using accurate mass, spectra, fragments, and retention indices for faster, defensible results.

<h3>Bring the power of accurate mass and confidence to compound identification</h3>The LECO Identification Grading System™ (IGS™) is designed to simplify and accelerate data review by clearly indicating how confident you can be in each compound identification. By consolidating all available chemical evidence into a single, intuitive grading metric, IGS enables users to quickly justify identifications, report results with confidence, and make informed decisions on next analytical steps.IGS is tightly integrated with data generated by the Pegasus GC-HRT 4D platform and is especially powerful for non-targeted workflows, where large numbers of unknown or partially known compounds must be evaluated efficiently and objectively.<h3>Key Features</h3>The Identification Grading System leverages the full chemical information content produced by GC×GC-HRTOFMS to strengthen confidence in “unknown unknown” identification.Each compound identification is assigned a grade based on four independent criteria:<ul><li>Presence and accurate mass of the molecular ion</li><li>Presence and strong spectral similarity score from a curated reference library</li><li>Accurate mass agreement of chemically reasonable fragment ion formulae associated with the library hit</li><li>Retention index agreement with the corresponding library entry</li></ul>The resulting numerical grade provides an immediate, transparent indicator of identification confidence—the higher the grade, the stronger the supporting evidence.<h3>Theory of Operation</h3>The full potential of confident identification is realized through the combined capabilities of comprehensive two-dimensional gas chromatography (GC×GC) and high-resolution time-of-flight mass spectrometry (TOFMS).GC×GC separates co-eluting species that would otherwise interfere with spectral interpretation, producing significantly cleaner mass spectra. High-resolution TOFMS delivers accurate, unskewed mass spectra across the entire chromatographic peak, including extremely narrow second-dimension peaks. When combined with advanced deconvolution, this results in exceptionally high-quality spectral information.Developed in response to the challenges highlighted by the U.S. EPA’s Non-Targeted Analysis Collaborative Trial (ENTACT), IGS directly addresses the time-consuming and subjective nature of traditional data review. It provides a systematic, evidence-based approach to filtering large result sets and focusing attention on the most reliable identifications.<h4>Practical Impact in Non-Target Analysis</h4>In GC×GC-TOFMS datasets from the EPA ENTACT challenge, unfiltered deconvolution can yield thousands of tentative identifications. Applying the IGS filter dramatically reduces this number, immediately highlighting the most confident matches and allowing analysts to focus on true unknowns with high priority.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/LECO_Identification_Grading_System_3_9b33a4d091.jpg" alt="LECO: Identification Grading System" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_LECO_Identification_Grading_System_3_9b33a4d091.jpg 245w," sizes="100vw" width="513" height="120">In blind ENTACT samples, IGS correctly identified approximately 80% of known compounds introduced into the sample, demonstrating that the combination of GC×GC separation and high-resolution TOFMS is essential for high-confidence non-target identification.

LECO ChromaTOF Sync

ChromaTOF Sync co-processes Pegasus BT GC–MS sample sets to generate a single unified peak table, enabling cleaner deconvolution, trend analysis, and confident non-target data interpretation.

ChromaTOF Sync is an advanced peak-finding and data alignment solution designed for sample sets acquired on LECO Pegasus BT series GC–MS systems. By extending ChromaTOF’s proven peak-finding algorithms and deconvolution capabilities, Sync enables multiple samples to be processed together, generating a single, unified peak table for the entire sample set.This collective approach allows laboratories to move beyond isolated sample evaluation toward true sample-set intelligence. Compiled chemical information supports comprehensive non-target data review, making it easier to identify similarities, differences, and trends across complex datasets.<h4>How ChromaTOF Sync Works</h4>The Pegasus GC–MS platform produces exceptionally information-rich datasets. However, extracting meaningful insights from large sample sets can be challenging without specialized tools. ChromaTOF Sync addresses this by co-processing BT data, leveraging shared chemical information across all samples to align peaks, refine deconvolution, and generate one consolidated peak table.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/LECO_Chroma_TOF_Sync_Analyza_dat_GC_TOFMS_1eeb398516.jpg" alt="LECO: ChromaTOF Sync" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_LECO_Chroma_TOF_Sync_Analyza_dat_GC_TOFMS_1eeb398516.jpg 245w," sizes="100vw" width="1133" height="555">By using the full context of the dataset, Sync delivers results that are greater than the sum of individual analyses. Users benefit from cleaner deconvoluted spectra, improved peak alignment, clearer trend identification, and integrated statistical tools that accelerate confident data interpretation.<h4>Advanced Data Processing and Visualization</h4>ChromaTOF Sync was developed and validated using real-world experimental datasets. Retention time shifts, difficult peak shapes, and wide analyte dynamic ranges are automatically corrected and aligned, simplifying downstream review.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/LECO_Chroma_TOF_Sync_Analyza_dat_GC_TOFMS_2_aeb513cd50.jpg" alt="LECO: ChromaTOF Sync" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_LECO_Chroma_TOF_Sync_Analyza_dat_GC_TOFMS_2_aeb513cd50.jpg 245w," sizes="100vw" width="416" height="150">The interactive application interface provides:<ul><li>Combined peak tables for the full sample set</li><li>Overlaid chromatograms for direct comparison</li><li>High-quality deconvoluted mass spectra</li><li>Interactive plots highlighting peak shape, repeatability, and trends</li><li>Spectral filters and visualization tools for monitoring chemical behavior across samples</li></ul>These features enable efficient exploration of complex datasets without manual reconciliation of individual files.

LECO ChromaTOF® Tile analytical software

ChromaTOF Tile enables rapid, statistically robust GC×GC-TOFMS data comparison using tiled heatmaps, reducing false positives and cutting data mining from days to minutes.

Turn Your Data into ChemistryThe volume of GC×GC-TOFMS data can quickly become overwhelming. Thousands of analytes across multiple tables may require months of pixel-level data mining, often complicated by false positives caused by normal chromatographic variation.ChromaTOF Tile fundamentally changes how GC×GC data are compared and interpreted. Instead of evaluating individual pixels, the software statistically compares tiled regions of chromatograms. Truly significant differences rise immediately to the surface—allowing you to focus on chemical meaning rather than data hunting.<blockquote>“ChromaTOF Tile is an enabling technology that has reduced our peak picking time from 10 days to 10 minutes.”</blockquote><h3>Designed for Sample Group Differentiation</h3>Integrated heatmap tables provide instant visual feedback on relative intensities and variance. ChromaTOF Tile highlights differences between two or more sample classes, including:<ul><li>Biomarkers distinguishing healthy vs. diseased samples</li><li>Off-odor detection in food quality control</li><li>Environmental samples upstream/downstream of contamination sources</li><li>Petroleum samples from different geographic origins</li><li>Any complex GC×GC comparison where class differentiation matters</li></ul><h3>Key Features</h3><ul><li>Stand-alone software designed to work in conjunction with <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/41">ChromaTOF</a></li><li>Rapid statistical comparison of GC×GC data sets</li><li>Exportable tables and plots for efficient reporting</li><li>Clean, library-searchable spectra generated from tiling</li><li>Approximate trend quantification using tile areas</li><li>Reduced false positives from chromatographic misalignment</li></ul><h3>Theory of Operation</h3>The challenge: Comparing large sets of GC×GC chromatograms is slow and alignment-sensitive, often taking weeks or months even with automated tools.The solution: In collaboration with Robert Synovec, ChromaTOF Tile applies Fisher ratios to partition chromatograms into regions (“tiles”). Instead of pixel-by-pixel comparison, corresponding tiles are averaged and statistically evaluated.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/LECO_Chroma_TOF_Tile_analytical_software_816a8a7705.jpg" alt="LECO ChromaTOF® Tile analytical software" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_LECO_Chroma_TOF_Tile_analytical_software_816a8a7705.jpg 245w," sizes="100vw" width="854" height="462">The result is a set of intuitive heatmaps that immediately direct attention to regions of high variance and high analytical relevance—without altering the underlying data.<img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/LECO_Chroma_TOF_Tile_analytical_software_2_c3c8abd476.jpg" alt="LECO ChromaTOF® Tile analytical software" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_LECO_Chroma_TOF_Tile_analytical_software_2_c3c8abd476.jpg 245w," sizes="100vw" width="1045" height="566">

LECO ChromaTOF Software

ChromaTOF is LECO’s advanced GC and GC×GC analytical software, offering fully integrated instrument control, powerful deconvolution, and high-end qualitative and quantitative analysis for TOFMS data.

ChromaTOF is proprietary analytical software developed by LECO specifically for GC-TOFMS and GC×GC-TOFMS workflows. It is purpose-built to handle the extremely large datasets generated by time-of-flight mass spectrometers and to fully support multidimensional chromatography (GC×GC) in a single, integrated data system.ChromaTOF provides seamless instrument and accessory control, highly integrated qualitative and quantitative data processing, and an intuitive user interface. It was the first mass spectrometry data system to natively accommodate GC×GC data and remains a reference platform for advanced GC and GC×GC analysis.<h3>What Makes ChromaTOF Unique</h3><ul><li>Automatic saving of all data processing steps directly within the file system</li><li>Integrated storage and management of metadata and instrument data</li><li>All standard features included in a single software package</li><li>Built-in control for compatible options, activated only when needed</li><li>Easy-to-use yet powerful, efficient, and robust environment</li><li>Frequent updates for maintenance improvements and new functionality</li></ul>ChromaTOF combines advanced qualitative and quantitative capabilities in one user-friendly platform and supports both <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products?category=21&amp;manufacturerItems=24&amp;search=bt">Pegasus BT</a> and <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/38">Pegasus GC-HRT</a> instrument families.<h3>What Can ChromaTOF Do</h3><ul><li>Automatic tuning with report generation</li><li>Absolute quantitation using calibration curves</li><li>Relative quantitation based on reference or analyte curves</li><li>Quantitation using single-channel detectors (FID)</li><li>Importable workspace templates to speed up setup</li><li>Spectral deconvolution with library searches (NIST, Wiley, or user libraries)</li><li>Semi-quantitative analysis of non-calibrated compounds</li><li>Integrated control of LECO and Agilent sample handling systems</li><li>Automatic export to CSV, ANDI MS, NETCDF, or LECO formats</li><li>Compatibility with liquid nitrogen and consumable-free <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/44">GC×GC thermal modulators</a></li><li>GC×GC classification and method development tools</li><li>Integrated GC control</li><li>Unknown-unknown discovery using ChemSpider</li><li>Advanced calculation tools:<ul><li>Monoisotopic mass from molecular formula</li><li>Formula generation from measured mass</li><li>Required mass resolution for separating close masses</li></ul></li></ul>Licensing options: 90-day free trial, 1-year subscription, or perpetual license.<h3>Exclusive Features for Pegasus High-Resolution Models</h3><ul><li>Automated unknown identification using High-Resolution Deconvolution</li><li>Automatic fragment formula generation with mass accuracy reporting</li><li>Accurate <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/application::paper.paper/SEP_SCI_ACCURATE_MASS_LIBRARY_209-272.pdf">Mass Spectral Libraries</a> with AML Rank similarity scoring</li><li>User-scalable mass defect plots (e.g., Kendrick mass defect)</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/application::paper.paper/SPECTRAL_ANALYSIS_TOOL_SAT_209-262.pdf">Optional Spectral Analysis Tool</a> with Van Krevelen and CN vs. RDBE plots</li></ul><h3>Features for Pegasus Benchtop Models</h3><ul><li>Automated unknown identification using Non-Target Deconvolution</li><li>Full profile mass spectra acquisition at 35 kHz with better-than-nominal resolution</li></ul>

LECO Simply GC×GC®

Simply GC×GC from LECO guides users through the steps of creating an optimized GC×GC method or converting an existing 1D GC method for complex samples.

Simply GC×GC from LECO is a free tool designed to walk users through the steps of creating an optimized GC×GC method for complex samples.The tool allows users to create a GC×GC method from scratch or convert an existing 1D GC method to GC×GC.Simply GC×GC provides logical, step-by-step instructions, for example for:<ul><li>setting the secondary oven offset,</li><li>setting the second-dimension column length,</li><li>experimentally evaluating stationary phases and peak capacity.</li></ul>Simply GC×GC takes a simple approach to GC×GC and helps users avoid unnecessary testing while streamlining the method development cycle.

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