<p><strong>This study presents a one-year assessment of microplastic concentrations in the River Rhine, analyzing samples from three locations and across multiple size fractions using TED-GC/MS. Dominant polymers included polyethylene, polypropylene, polystyrene, styrene–butadiene rubber, and natural rubber.</strong></p><p>Statistical analysis revealed size-dependent distributions, minor seasonal variation, and spatial differences, highlighting the role of sources such as tire abrasion. The findings provide valuable data for environmental monitoring, ecotoxicological research, and regulatory frameworks related to water quality.</p><blockquote><h4><strong>The original article</strong></h4><h4><a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsestwater.5c00530"><strong>One Year Observation of Microplastic Concentrations in the River Rhine</strong></a></h4><p>Yosri Wiesner, Paul Eisentraut, and Korinna Altmann*</p><p>ACS EST Water 2026, 6, 2, 639–648</p><p><a target="_blank" rel="noopener noreferrer" href="https://doi.org/10.1021/acsestwater.5c00530">https://doi.org/10.1021/acsestwater.5c00530</a></p><h6>licensed under <a target="_blank" rel="noopener noreferrer" href="https://creativecommons.org/licenses/by/4.0/"><strong>CC-BY 4.0</strong></a></h6></blockquote><p><strong>Selected sections from the article follow. Formats and hyperlinks were adapted from the original.</strong></p><div><p>As microplastics (MPs) are found all over the world and no comprehensive knowledge is available yet, extensive monitoring campaigns are required to gain a full understanding of their occurrence, transportation and fate. <a href="javascript:void(0);">(1,2)</a> In particular, MP abundance in freshwater systems has still not been sufficiently investigated. <a href="javascript:void(0);">(3,4)</a> Additionally, the question of the toxicological potential of MPs has been the subject of numerous studies for many years, <a href="javascript:void(0);">(5,6)</a> leading to more precise and complex experimental set-ups and results. However, there is still a need for more acurate data on environmental MP concentrations in order to make ecotoxicological tests even more detailed and realistic. The lack of certainty for exposure concentrations in the risk assessment frame of MPs leads to the precautionary principle being applied by politicians and regulators worldwide. Both the EU drinking water directive and the wastewater directive call for monitoring of MPs within the next few years. It is important to establish suitable analytical methods for sampling, sample preparation and detection that must now be fast, robust and fit for purpose in order to obtain representative and valid results depending on mass or particle number. <a href="javascript:void(0);">(7−9)</a></p><p>MPs are solid particles with a size of 1–1000 μm mainly consisting of polymers (ISO/TR 21960, 2020) and can, for example, result from industrial production in the form of small particles that are designed as additives and change the properties of products, or from plastic parts that have been released into the environment. Major sources of MPs today are paints, tires, packaging materials, pellet waste and textiles. <a href="javascript:void(0);">(10−12)</a> These macroplastic products can form MP particles as a result of degradation factors such as photooxidation, hydrolysis and mechanical abrasion. <a href="javascript:void(0);">(13,14)</a></p><p>The River Rhine has its origin in Switzerland and then flows through Liechtenstein, Austria, Germany and France until it discharges into the North Sea in The Netherlands. At 1233 km and a catchment area of about 185&nbsp;000 km<sup>2</sup>, the Rhine is one of the largest river systems in Europe and, due to its expanse, forms the ecological basis for a large number of animal species. Around 30 million people in Germany are supplied with drinking water from the Rhine.</p><p>It is hardly possible to assess the occurrence of MPs if either a limited sampling volume is used or only individual samples are taken. It is therefore essential that different volumes are sampled depending on whether the water to be sampled contains many or few MP particles. It is recommended to sample at least 5 m<sup>3</sup> for drinking water samples and 1 m<sup>3</sup> for surface water, whereas raw wastewater contains so many particles that only a few liters need to be sampled. <a href="javascript:void(0);">(15)</a> Although sampling of these water volumes leads to a representative sample from the analytic point of view, it is questionable, if the result measured is representative for the location. Previous studies have shown that the composition in terms of MP masses in a water body can change at one location with each individual sample independently whether several samples are analyzed in 1 day or spread over several days. <a href="javascript:void(0);">(16)</a> Fractionated filtration and sedimentation boxes as active and passive sampling methods have proven themselves in the sampling of freshwater systems. In active sampling, water is fractionally filtered using a pump and a sieve tower with different mesh sizes. <a href="javascript:void(0);">(17)</a> Passive sampling can be carried out using sedimentation boxes. <a href="javascript:void(0);">(18)</a> In a sedimentation box, the flow velocity of the medium flowing through is reduced by using several baffle plates. Due to the reduced velocity and energy, particles up to a certain size are forced to sediment by the now predominant gravitational force. Such boxes can remain in the water for several weeks and therefore collect a cross-section of the suspended particles including MP over a certain period of time.</p><p>Mass and number-based methods have emerged as suitable detection methods for MPs. <a href="javascript:void(0);">(19)</a> Number-based methods such as μ-Raman, μ-FTIR or LDIR are well advanced to evaluate the polymer identity, particle number concentration and shape, <a href="javascript:void(0);">(20,21)</a> but are still time-consuming in terms of sample preparation. In regulatory approaches or for simulations, usually the MP mass is needed. MP polymer identity and masses can be detected by thermoanalytical methods like pyrolysis-GC/MS (Py-GC/MS) or thermal extraction desorption-GC/MS (TED-GC/MS). Especially TED-GC/MS seems to be suitable for monitoring purses of suspended particulate matter, because there is no need for additional sample preparation others than filtration and homogenization. Up to 50 mg of suspended particulate matter can be directly measured in one run, giving representative subsamples for precise measurements exceeding the limit of quantification. Furthermore, styrene–butadiene rubber (SBR) and natural rubber (NR) as indication for tire wear can be detected in the same sample run next to thermoplastics such as polyethylene (PE), polypropylene (PP), polyethylene terephthalate (PET), polystyrene (PS), polyamide 6 or polyacrylates.</p><p>This work provides a comprehensive data set of MP concentrations of the River Rhine over one year sampling at three different locations starting near the source in Weil via Koblenz and Emmerich. Sampling was done with sedimentation boxes with monthly withdrawal and fractioned filtration of the collected particles afterward. The size fractions 10–50 μm, 50–100 μm and 100–500 μm were provided by the Federal Institute of Hydrology (BfG, Germany) and analyzed at the Federal Institute of Material Research and Testing (BAM, Germany) funded by a national project from the Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection (BMUV, Germany, 3719 22301 0). Detection was performed with TED-GC/MS in routine mode, proven as a fast and robust detection method. <a href="javascript:void(0);">(2,16,22)</a> Data can be used, for example, for water monitoring or as reference values for future risk assessment scenarios and experiments.</p><h4><strong>2. Materials and Methods</strong></h4><h5><strong>2.2. TED-GC/MS</strong></h5><p>TED-GC/MS is a multistage detection technique combining the thermal sample extraction by thermogravimetric analysis (TGA) with chromatographic separation of the individual decomposition gases and detection by trace analysis with gas chromatography/mass spectrometry (GC/MS). Sample material in 150 μL alumina crucibles was pyrolyzed in a <strong>TGA2 thermobalance</strong> (MettlerToledo, Gieβen, Germany) under a nitrogen flow of 30 mL/min from 200 to 500 °C with a heating rate of 10 K/min. Typical sample intake was between 10 to 50 mg depending on the organic content. The decomposition gases were collected on a solid phase (SorbStar, Envea, Vohenstrauβ, Germany) in the typical polymer decomposition temperature range between 200 and 500 °C via a heated coupling module (240 °C, Gerstel, Mülheim an der Ruhr, Germany). The loaded solid phase was transported to the thermodesorption unit (TDU)-GC/MS by an autosampler (<a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?manufacturerItems=8&amp;search=MultiPurposeSampler+2"><strong>MultiPurposeSampler 2</strong></a> (MPS2), Gerstel, Mühlheim an der Ruhr). The desorption of the decomposition products took place in the TDU (50–200 °C, 5 min isothermal, He gas, Gerstel), the cryofocusing in the cold injection system (−100 °C, Gerstel). Injection was carried out from there by rapid heating (−100–270 °C, 12 K/s) onto the separation column (HP5 ms, 1 mL/min He, 40–300 °C, Agilent, Palo Alto, USA) in the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?manufacturerItems=1&amp;search=7890B"><strong>GC system (7890 B Agilent)</strong></a>. After chromatographic separation, detection was performed in a mass spectrometer (EI, 70 eV, scan-mode, <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?manufacturerItems=1&amp;search=5977B"><strong>5977 B, Agilen</strong></a>t).</p><h4><strong>3. Results and Discussion</strong></h4><p>A summary of the identified polymer types and their corresponding mass concentrations per sampling location is provided in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsestwater.5c00530#fig1">Figure 1</a>. All individual results are presented in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acsestwater.5c00530/suppl_file/ew5c00530_si_001.pdf">Table S1</a> of the Supporting Information. With a few exceptions, the polymers PE, PP, PS, SBR and NR were detected. To cope with the large amount of measurement data and to obtain an overview of possible correlations, the data was evaluated using statistical and mathematical algorithms. Only the five polymers named above provide enough input data and are therefore used as the basis for the data analysis. The individual results were sorted according to various aspects that are included in the data set as independent variables:</p><p>(I)&nbsp;&nbsp;&nbsp; Particle size fractions</p><p>(II)&nbsp;&nbsp;&nbsp; Temporal variation</p><p>(III)&nbsp;&nbsp;&nbsp; Spatial variation due to the sampling locations</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_EST_Water_2026_6_2_639_648_Figure_1_Overview_of_sampling_locations_along_the_German_part_of_the_River_Rhine_and_sum_of_identified_median_mass_concentrations_fe570f51b5.jpg" alt="ACS EST Water 2026, 6, 2, 639–648: Figure 1. Overview of sampling locations along the German part of the River Rhine and sum of identified median mass concentrations." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_EST_Water_2026_6_2_639_648_Figure_1_Overview_of_sampling_locations_along_the_German_part_of_the_River_Rhine_and_sum_of_identified_median_mass_concentrations_fe570f51b5.jpg 158w," sizes="100vw" width="1883" height="1860"></p><p>The concentrations of the various polymers in the suspended matter serve as input values. The riverine balancing and material transport based on the total masses (polymer mass in total suspended solids mass) is carried out explicitly and will be published at Umweltbundesamt as part of the project report by the BfG (Ternes, final project report, 2023).</p><h5><strong>3.1. Particle Size Fractions</strong></h5><p>This section describes the possible correlation of the polymer mass concentration with the size of the measured particles regardless of the sampling location. Therefore, the generated samples were sorted by sieving into different size fractions of 10–50, 50–100 and 100–500 μm. The relative mean values of the individual fractions are calculated (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acsestwater.5c00530/suppl_file/ew5c00530_si_001.pdf">Figure S2</a>) to obtain the shares of the different polymer types in the total amount of MP. PE is the dominant polymer in all size fractions with 68–76%, followed by PS (10–15%), SBR (4–13%), PP (2–5%) and NR (2–4%). Obviously, all polymer types are approximately evenly distributed across the size fractions, with SBR being less present in the 100–500 μm fraction.</p><p>In general, it can be determined that PE accounts for the highest proportion of MP. PS makes up the second highest proportion, followed by SBR. Next in line are PP and NR. The polymer findings are in good agreement with previous MP studies of the Rhine. PE, PP and PS in particular are the most frequently detected polymers. <a href="javascript:void(0);">(3)</a> The relative abundance of PE, PP and PS is also relatively similar to Skalska et al., even when the particle number was considered here. <a href="javascript:void(0);">(26)</a> Especially in comparison with the results of Mani et al. significant similarities to the ratios of PE, PP and PS can be found. Data on SBR from tire abrasion in the Rhine is difficult to find in existing studies, as such particles cannot easily be identified using vibrational methods due to the IR absorbing properties and the intense fluorescence of the accompanying soot. However, a comparison with suspended particulate matter samples from the Danube is possible, as here the detection was also carried out using TED-GC/MS. <a href="javascript:void(0);">(2)</a> The relative ratios of PE, PP, PS, SBR and NR are comparable and support the plausibility of the results.</p><p>Total MP mass concentrations are presented in <a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/suppl/10.1021/acsestwater.5c00530/suppl_file/ew5c00530_si_001.pdf">Figure S3</a> for individual polymer types, showing highest mass concentrations in the size fraction 100–500 μm. The median varies from 0.17 to 6.80 μg/mg depending on the polymer type. In absolute terms, the PE mass concentrations are significantly higher than those of all other polymers. PP and PS show a strong mass increase in the 100–500 μm fraction, together with higher uncertainty compared to 10–50 μm and 50–100 μm. With a variation of 0.27–0.32 μg/mg across all particle size fractions, the mass contents of SBR are relatively constant, while NR mass concentration seems to increase more linearly. The high mass concentrations and the strong scattering of the 100–500 μm fractions could be due to the presence or absence of large but few particles. Basically, the larger a particle is, the higher its contribution to the mass concentration. In contrast, the larger a particle is, the lower the probability of an equal distribution in all samples.</p><p>If other regions associated with the Rhine are considered, comparable ratios of mass concentration in the various particle size fractions are found in Rhine floodplains. <a href="javascript:void(0);">(27)</a></p><p>At the beginning of the data analysis, a Principal Component Analysis (PCA) is carried out to identify parameters that have a high influence on the mass content. This analysis identified that the particle size has the greatest influence on the mass concentration (<a target="_blank" rel="noopener noreferrer" href="https://pubs.acs.org/doi/10.1021/acsestwater.5c00530#fig2">Figure 2</a>). The first principal component (PC 1) was identified as the particle size fraction and explains over 50% of the differences in the data.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/ACS_EST_Water_2026_6_2_639_648_Figure_2_PCA_Score_plot_of_mass_concentrations_of_the_different_polymers_be94ae16c4.jpg" alt="ACS EST Water 2026, 6, 2, 639–648: Figure 2. PCA Score plot of mass concentrations of the different polymers." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_ACS_EST_Water_2026_6_2_639_648_Figure_2_PCA_Score_plot_of_mass_concentrations_of_the_different_polymers_be94ae16c4.jpg 184w," sizes="100vw" width="747" height="635"></p><h4><strong>4. Conclusion</strong></h4><p>This study demonstrated that long-term sampling of the Rhine is possible and provides plausible results, which is important for future MP monitoring campaigns, as required by the Urban Waste Water Treatment Directive for the EU. Although the MP concentrations in the Rhine are relatively constant, seasonal and downstream differences were observed. In order to confirm these possible trends, further sampling campaigns are needed to identify possible differences on an annual scale. Furthermore, the influences of urban proximity and land use must be examined in greater detail by increasing the number of measuring points. Additional sample sites are needed to identify possible sources of input. This would be particularly important to clarify the PS concentrations, which show a high correlation between the different particle size fractions in almost all seasons and could indicate a possible common source. SBR is the only polymer to show a relatively constant concentration across all particle sizes and seasons, independent of the river course. Since it is a tire component, constant road traffic could be part of the explanation. However, a different particle ratio must be assumed here compared to the other polymers. The fragmentation mechanism and/or another transport mechanism needs to be clarified.</p><p>Although PE constitutes the majority of the total MP concentration, there may be an overestimation due to false positive signals. To exclude or confirm this, further studies must be conducted to analyze the organic components of the riverine suspended matter in detail.</p><p>A comparison with other studies reveals similar occurrences of the same polymer types and in parts also similar seasonal fluctuations and a slight downstream increase. The differentiated presentation of results in polymer type, particle size fraction and range of mass concentrations can provide a valuable basis for more complex and realistic exposure tests for ecotoxicological studies on freshwater organisms. In particular, the large database for SBR as a tire component could be of special interest, as the toxicity of tire particles due to their chemical composition has already been shown in other studies. In studies using FTIR-based detection methods, these values are usually missing due to the high absorbance of the black tire particles.</p></div>

One Year Observation of Microplastic Concentrations in the River Rhine

<p><strong>In the week of April 6, the following webinars await you in the field of gas / solid phase and especially Raman, FTIR, GC and GC/MS.</strong></p><blockquote><h4><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinars"><strong>👉 DETAILS AND REGISTRATION IN THE WEBINARS SECTION</strong></a></h4><p><strong>👉 Search and filter in the largest global database</strong> with over <strong>5 500 GC, LC, MS and spectroscopy webinars</strong>.</p></blockquote><div><div><div><div><div><div><h5><strong>1. Bruker: Advances in AFM for the Characterization of 2D Materials</strong></h5><ul><li>We, 8.4.2026 17:00 CET</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/6054">Registration</a></li></ul><p>Explore how AFM enables comprehensive nanoscale characterization of 2D materials. Learn about structural, electrical, and chemical mapping, AFM-IR, and nanomanipulation for device fabrication.</p><h5><strong>2. Agilent Technologies: Mastering Gas Sampling: Valve Fundamentals to ASTM Ready RGA &amp; TOGA Analysis</strong></h5><ul><li>Th, 9.4.2026 08:00 CEST</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/webinar/6056">Registration</a></li></ul><p>In this session, learn how to achieve reliable permanent gas analysis, starting from proper valve selection and sampling fundamentals.</p></div></div></div></div></div></div>

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<h4><strong>Introduction&nbsp;</strong></h4><p><strong>Millions of tests, measurements and examinations are made every day in thousands of laboratories around the world. There are innumerable reasons underpinning them, for example: as a way of valuing goods for trade purposes; supporting healthcare and construction; checking the quality and safety of food and feed; and in forensic analysis and environmental monitoring. Virtually every aspect of society is supported in some way by analytical work.&nbsp;</strong></p><p>The cost of carrying out these measurements is high and additional costs may arise from decisions made on the basis of the results. For example, tests showing food to be unfit for consumption may result in compensation claims. In addition, tests confirming the presence of banned drugs could result in fines or imprisonment. Clearly it is important to make a correct measurement and be able to show that the result is correct.</p><h4><strong>The validation/verification process</strong></h4><p>Most analysts know that method validation/verification is important, but exactly why, how and when it should be done is not always clear.&nbsp;</p><p>Method validation/verification is the process whereby the laboratory demonstrates whether or not a method is ‘fit for purpose’ (Fig. 1). This means that the tests carried out should be appropriate with respect to uncertainty, cost, time etc. The final report should present analytical data in such a way that the customer can, readily, interpret it and draw appropriate conclusions.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Eurachem_The_validation_verification_82742c1029.jpg" alt="Eurachem: Fig. 1. The method validation/verification process. The laboratory ‘translates’ the customer’s problem into an analytical requirement, i.e. the method performance required to solve the problem. Method validation/verification includes a stage where various performance characteristics are evaluated and then compared with analytical requirements." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Eurachem_The_validation_verification_82742c1029.jpg 124w," sizes="100vw" width="821" height="1029"></p><h4><strong>The Eurachem Guide&nbsp;</strong></h4><p>A <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/2242"><strong>Guide from Eurachem</strong></a> (Fig. 2) gives practical advice on how method validation/verification can be accomplished. The Guide and its supplements [1-4]:&nbsp;</p><ul><li>Introduce the basic concepts related to method validation and method verification;&nbsp;</li><li>Indicate how to plan, record and report validation and verification studies to best support the statement of ‘fitness for purpose’;&nbsp;</li><li>Provide key definitions and the rationale behind the experiments for assessing the various performance characteristics and related topics (Fig. 3);&nbsp;</li><li>Include quick reference tables that suggest experiments together with the necessary statistical calculations for evaluation and reporting each performance characteristic;&nbsp;</li><li>Provide support to the analyst on how to make the best use of method validation data for setting up an internal quality control plan.</li></ul><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Eurachem_The_Fitness_for_Purpose_of_Analytical_Methods_95fc1a74e3.jpg" alt="Eurachem: Fig. 2. The Eurachem Guide is available free of charge at www.eurachem.org." srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Eurachem_The_Fitness_for_Purpose_of_Analytical_Methods_95fc1a74e3.jpg 135w," sizes="100vw" width="1062" height="1231"></p><h4><strong>How should methods be validated/verified?</strong></h4><p>The guide focuses on a single-laboratory approach to method validation/verification and gives guidance on planning, carrying out and reporting method validation and verification studies. Any method validation or verification study will require the laboratory to investigate several performance characteristics:</p><ul><li>Precision<ul><li>Repeatability&nbsp;</li><li>Intermediate precision</li></ul></li><li>Trueness</li><li>Selectivity</li><li>Working range</li><li>Analytical sensitivity</li><li>Limit of detection</li><li>Limit of quantification</li><li>Ruggedness</li></ul><p>Exactly which characteristics are studied will depend on the analytical application. Verification of the performance of a standard method requires substantially less work than validation of a method developed in-house. Legislative/sectoral requirements must also be considered.&nbsp;</p><p>Sampling and subsampling can be part of the measurement or testing procedure and must, in those cases, be validated.</p>

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<p><strong>Whether you are new to GC or have been performing it for years, you may find that things just aren’t /going the way you want them to. There are many pitfalls that can cause problems and in this talk some of the topics we will discuss include:</strong></p><ul><li>Problematic solvents</li><li>The importance of gas traps</li><li>Syringe hygiene</li><li>Front-end maintenance</li><li>Proper conditioning</li><li>Making connections</li><li>Importance of sample preparation</li></ul><p>Avoiding these pitfalls can help you achieve long-term reliable results.</p><blockquote><p><strong>Presenter:</strong> Alex Ucci (Application Engineer, Agilent Technologies, Inc.)</p><p>In his current position at Agilent, Alex provides application assistance and technical support for sample preparation products as well as GC and LC consumables. Before he joined Agilent in 2014, Alex was a graduate student at the Pennsylvania State University researching the morphology and surface properties of aerosol particles using a wide variety of analytical techniques. He has an MS degree in chemistry.</p></blockquote>

Agilent Technologies: Becoming a Better Chromatographer - Educational Webinar Series

Common Pitfalls in GC Chromatography: What to Avoid

There are many pitfalls that can cause problems and in this talk some of the topics we will discuss 

<div><div container-id="cq-colctrl-lt0" comp-id="A1"><div><p><strong>Join us for an informative webinar where we delve into the intricacies of detection parameters and algorithm options in Chromeleon Chromatography Data System (CDS). This session will enhance your understanding of how to configure and optimize individual detection parameters, as well as explore the various algorithm options available. Whether you are looking to improve your data accuracy or streamline your analysis processes, this webinar will provide you with the insights and techniques needed to master detection in Chromeleon CDS.</strong></p><h5><strong>Key takeaways:</strong></h5><ul><li>Gain a comprehensive understanding of individual detection parameters in Chromeleon CDS</li><li>Learn how to configure and optimize detection settings for accurate results</li><li>Explore the different algorithm options and their applications</li><li>Get answers to your specific questions during the live Q&amp;A session</li></ul><h5><strong>Who should attend:</strong></h5><ul><li>Chromeleon CDS users looking to deepen their knowledge of detection parameters</li><li>Laboratory analysts and technicians seeking to improve data accuracy</li><li>Quality control and assurance professionals interested in optimizing detection settings</li><li>Anyone interested in learning more about detection algorithms in Chromeleon CDS</li></ul><p><i>Don't miss this opportunity to enhance your detection capabilities and achieve more precise results with Chromeleon CDS. Register now to secure your spot!</i></p><blockquote><p><strong>Presenter: </strong>Kimy Young (Senior Manager, Software Product Specialists, Thermo Fisher Scientific)</p><p>Kimy Young is the Senior Manager of software product specialists at Thermo Fisher Scientific. She has been with Thermo Fisher since November 2015. Her background includes administration of Chromeleon CDS, laboratory information management systems (LIMS), Quality Assurance (QA), and IT projects.</p><p><strong>Presenter: </strong>Juan Carmona (Chromeleon CDS Specialist, Thermo Fisher Scientific)</p><p>Juan Carmona is a Chromeleon Specialist at Thermo Fisher Scientific based out of Pflugerville, TX. He has been with Thermo Fisher Scientific for over 15 years. At Thermo Fisher Scientific, he is currently focusing on expanding the customer base using Chromeleon CDS for small networks and enterprise deployments. Prior to joining this group, he was part of the GC/GCMS Center of Excellence team providing support for the product line.</p><p><strong>Presenter: </strong>Monica Driscoll (Regional Marketing Specialist, Thermo Fisher Scientific)</p></blockquote></div></div></div>

Thermo Fisher Scientific: Chromeleon CDS webinar series

Reduce manual integrations: Optimize data processing with detection parameters and algorithms

Explore detection parameters and algorithms in Chromeleon CDS to improve data accuracy and streamline analysis. Live Q&A with Thermo Fisher experts.

Reduce manual integrations: Optimize data processing

<p><strong>Join this webinar to explore how producers can build confidence in Process NIR – across both lab and production – by addressing the technical challenges and team concerns that often stand in the way.</strong></p><p>This webinar explores how food producers can build confidence in Process NIR technology by aligning lab and production teams. It highlights why trust—not hardware—is often the greatest barrier to successful NIR adoption. Attendees will hear expert insights, real-world experiences, and strategies to close the trust gap.</p><p>In modern food production, speed and accuracy in quality control are more critical than ever. As producers adopt Inline, Online, and At-line NIR technologies to meet these demands, many find that technical performance alone is not enough. Trust in the data—especially when it challenges previous lab results or long-standing assumptions—is a major factor in whether these technologies succeed. Lab teams may worry about being sidelined, while production teams may hesitate to act on new real-time insights. Understanding and addressing these human and operational dynamics is essential for building confidence in NIR across the entire process.</p><p>The webinar will address challenges related to scepticism about real-time data, misalignment between lab and process teams, and confusion over different types of NIR setups. Many users experience hesitation when new data contradicts historical norms, or when implementation raises concerns about job roles or reliability. The session will explore how to overcome these challenges through communication, validation, and shared understanding.</p><p>Attendees will learn how to validate and communicate NIR results, align expectations between lab and production teams, and choose the most appropriate NIR setup for their specific process. The session will focus on building trust in the data, handling doubt or resistance, and ensuring that teams work together toward consistent quality outcomes. While not the central focus, broader trends like the shift toward real-time monitoring and smarter quality control systems will be touched on as context for why confidence in Process NIR matters more than ever.</p><p>The webinar will include real-world examples where unexpected results from Process NIR initially caused disbelief but ultimately led to improved process understanding and control. These stories will illustrate how scepticism was turned into confidence and how both lab and production teams were brought along in the journey.</p><p>The speakers will also discuss the importance of calibration and validation, how to handle field objections, and strategies for bridging communication gaps between departments. They will take live questions and share insights from direct conversations with producers navigating the transition to real-time NIR.</p><h5><strong>Key learning points:</strong></h5><ul><li>Clarify the differences between Inline, Online, and At-line NIR, and when to use each</li><li>Understand how trust impacts the success of NIR implementation</li><li>Learn how to validate new NIR data, especially when it challenges expectations</li><li>Gain strategies to align lab and production teams without conflict or fear</li><li>Hear real examples of companies overcoming doubt and building belief in online data</li><li>Leave with practical next steps for integrating NIR into a unified process strategy</li></ul><blockquote><p><strong>Presenter:</strong> David Honigs (Sr. Scientist, PerkinElmer)</p><p>For the last almost 20 years David has worked at Perten (part of Perkin Elmer) on Near Infrared Instrumentation and applications in the food industry. He has 35 research papers as listed on ResearchGate.com. He has 10 issued US patents.</p><p><strong>Presenter: </strong>Stefan Lundgren (Business Leader EMEAI, PerkinElmer)</p><p>Background in Electronics. Working with NIR since 1987. In the early days with another Scandinavian manufacturer but since 2007 working with all aspects of the Perten range of NIR products.</p></blockquote>

New Food Magazine: From Calibration to Confidence: Building Trust in Process NIR

From Calibration to Confidence: Building Trust in Process NIR

Explore how food producers can boost trust in Process NIR across lab and production teams. Learn to validate data, overcome resistance, align for QC success.

Building Trust in Process NIR for Food Production

<div><div container-id="cq-colctrl-lt0" comp-id="A1"><div><p><strong>Therapeutic protein manufacturing faces challenges in maintaining efficiency, reducing costs and ensuring consistent quality while minimizing offline testing.</strong></p><p>Join our speaker as she discusses &nbsp;how precise, non-destructive, real-time insights into protein production empowers teams to make faster, data-driven decisions.</p><p>This webinar will highlight how in-line monitoring strengthens process understanding, supports continuous control strategies and accelerate automation – advancing modern therapeutic protein manufacturing.</p><h5><strong>Attend this webinar to:</strong></h5><ul><li>Understand how <strong>Process Raman </strong>supports automation in biomanufacturing</li><li>Explore practical applications such as protein quantification during clarified harvest and excipient monitoring during ultrafiltration/diafiltration, integrating process control</li><li>Learn how to leverage data-rich insights to optimize workflows, enhance process understanding and address modern biomanufacturing challenges</li></ul><blockquote><p><strong>Presenter: </strong>Michelle Nolasco (Systems Design Engineer at Thermo Fisher Scientific)</p><p>Michelle Nolasco leads innovation initiatives and collaborations for bioproduction at Thermo Fisher Scientific. Michelle specializes in downstream processes and has experience in automation and advanced analytics. Prior to her current role, Michelle was part of the downstream process development team at Patheon Biologics, supporting development and clinical manufacturing for monoclonal antibodies and recombinant enzymes. Michelle holds a bachelor’s degree in chemical engineering from the University of South Florida.</p></blockquote></div></div></div>

Technology Networks: Advancing Therapeutic Protein Production With Real-Time Analysis

Advancing Therapeutic Protein Production With Real-Time Analysis

Join our speaker as she discusses how precise, non-destructive, real-time insights into protein production empowers teams to make faster, data-driven decisions.

Therapeutic Protein Production With Real-Time Analysis

<p><strong>Analysis of sulfur in petroleum products is critical to help prevent corrosion, reduce catalytic reactions, and mitigate SO2 pollution. Gas Chromatography with Sulfur Chemiluminescence Detection (GC-SCD) per ASTM D5623 provides advantages of sensitivity, equimolarity, and speciation over other methods such as EDXRF per ASTM D4294. However, GC-SCD systems can present challenges with complexity and maintenance costs. In this presentation, Alan Cummings of LUMMUS Technology will present theory on sulfur chemiluminescence as well as data collected over a period of several years comparing three commercially available GC-SCD systems for sensitivity and robustness. His research has resulted in optimized GC-SCD system configurations which produce maximize productivity and reliability.</strong></p><h5><strong>Who should attend:</strong></h5><ul><li>Petroleum industry chemists interested in vendor-independent comparison of GC-SCD systems</li><li>Analytical Laboratory professionals interested in learning about sulfur analysis and speciation technologies</li><li>Lab managers seeking to reduce maintenance costs and hardware challenges associated with sulfur analysis in petroleum products by ASTM D5623</li></ul><h5><strong>Learning Objectives:</strong></h5><ul><li>Learn theory of operation as well as optimized conditions for GC-SCD systems for maximum sensitivity and robustness</li><li>Discover tips and tricks for reducing maintenance costs for GC-SCD systems running ASTM D5623</li><li>View data from a long-term evaluation by LUMMUS Technology of three major commercially available GC-SCD systems</li></ul><blockquote><p><strong>Presenter:</strong> Alan Cummings (Senior R&amp;D Analytical Chemist, Lummus Technology)</p><p>Alan T. Cummings is a Senior R&amp;D Analytical Chemist at Lummus Technology in Pasadena, Texas. Alan holds a Bachelor’s degree in Environmental Chemistry from the University of Houston Clear Lake, in Clear Lake Texas. Alan has over 34 years’ experience in analytical chemistry testing, method development, including 23 years in Sulfur Chemiluminescence Detector (SCD) testing. He has been employed by Lummus Technology for 23 years. He supports analytical needs for Lummus Technologies R&amp;D facility and customers including sulfur speciation, titrations, ICP, digestions, LIMS/CDS, GC analysis and method development.</p><p><strong>Presenter: </strong>Jon Peters (Director of Marketing, Shimadzu Scientific Instruments)</p><p>Jon Peters is Director of Marketing Shimadzu Scientific Instruments, a subsidiary of Shimadzu Corporation. For over fifteen years Jon has worked with analytical instrumentation vendors on R&amp;D, product management, vertical marketing, and customer advocacy projects, specializing in spectroscopy, chromatography, physical testing, and X-ray technologies. He applies his experience with a broad range of analytical tools, software, consumables, and sample introduction accessories to create innovative marketing initiatives to support industry, academia, and government laboratories in diverse market spaces.</p></blockquote>

Shimadzu: GC-SCD for Petroleum Products: Comparison of Commercially Available Sulfur Chemiluminescence Detectors by ASTM D5623

GC-SCD for Petroleum Products: Comparison of Commercially Available Sulfur Chemiluminescence Detectors by ASTM D5623

Explore GC-SCD sulfur analysis in petroleum per ASTM D5623. See long-term data on sensitivity, robustness, and optimized conditions to boost productivity.

GC-SCD Comparison for Sulfur in Petroleum (ASTM D5623)

<p><strong>The hydrogen economy is growing across production, storage, distribution, and mobility applications. At every stage, maintaining gas purity is essential to safeguard performance, safety, and international standards. Even trace levels of oxygen, nitrogen, carbon monoxide, or hydrocarbons can affect fuel cell efficiency and infrastructure reliability.</strong></p><p>This session will outline how gas chromatography (GC) solutions support accurate detection of impurities in hydrogen streams. It will cover workflows for monitoring during production, storage, and transport, as well as testing requirements for fuel-cell-grade hydrogen. Focus will be placed on methods that ensure hydrogen quality certification for mobility and industrial use, addressing both current specifications and emerging global frameworks.</p><p>By connecting purity requirements with analytical workflows, the session provides a clear view of how hydrogen can be delivered reliably and safely across the value chain.</p><blockquote><p><strong>Presenter:&nbsp;</strong> Dr. Jie Zhang (Application Development Scientist, Agilent Technologies, China)</p><p>Jie joined Agilent Technologies in 2006. She started as an instrument chemist in the R&amp;D department and participated in new product development of the 7890/7820 GC and the 990 Micro GC. In 2017, she changed her role to a Gas Chromatography Applications Chemist. Currently, she mainly works on application development in energy, new materials, environmental, and food segments. Her educational background includes a BS in Chemistry and a PhD in Analytical Chemistry from Fudan University.</p></blockquote>

Agilent Technologies: Energy Transition Webinar Series

Hydrogen Value Chain: Fueling Green Mobility

Agilent GC solutions for hydrogen purity—trace impurity detection, quality certification, and reliable workflows across the hydrogen value chain.

<div><div id="inner_content_body_text" data-content-id="394785"><p><strong>Ensuring refined fuels and lubricants stay on spec is critical— and direct in-line measurement provides the confidence needed to maintain control throughout production. This webinar explores how a Process Raman Analyzer enables true direct in-line measurement of refined fuels and related products, including diesel, gasoline, jet fuel, and lubricants.</strong></p><p>We’ll share real-world examples of monitoring essential properties such as API gravity, RON, RVP, cetane, and flash point—all aligned with ASTM methods. Unlike other technologies, Process Raman requires no sample conditioning system and eliminates consumables or carrier gases, reducing complexity and costs while delivering continuous, non-destructive analysis.</p><p>With its small footprint and hazardous-location rating, Process Raman integrates seamlessly into production environments—providing operators with peace of mind through reliable, uninterrupted monitoring and immediate detection of deviations. The result: tighter process control, consistent product quality, and lower operating costs.</p><h5><strong>Process Raman Enables:</strong></h5><ul><li>Immediate detection of deviations for faster corrective action</li><li>Lower maintenance and operating costs</li><li>A streamlined path to compliance and consistent quality</li></ul><h5><strong>Who should attend this webinar series?</strong></h5><p>This webinar is designed for professionals in the oil &amp; gas industry looking for hassle-free and reliable in-line fuel quality analysis, including:</p><ul><li>Refinery Managers &amp; Plant Managers – looking to reduce downtime and improve process efficiency</li><li>Process Engineers – wanting to minimize lab delays and bring analysis in-line</li><li>Operations Managers – seeking real-time visibility to drive better decision-making</li><li>Maintenance &amp; Reliability Teams – aiming to lower operating costs and avoid equipment-intensive solutions</li><li>Product Quality Control &amp; Lab Managers – responsible for keeping refined products on spec and compliant</li></ul><p>Join to learn how Process Raman gives refiners and producers the confidence to trust their in-line measurements and keep operations running smoothly.</p><blockquote><p><strong>Presenter:</strong> Janam Pandya, PhD (Application Scientist Measurement Control and Sample Identification, Thermo Fisher Scientific)</p><p>Janam Pandya, PhD is an enthusiastic scientist and spectroscopist with ten years of academic and industry experience. Janam obtained his PhD in food science from the University of Massachusetts Amherst; there his research focused on developing novel analytical methods utilizing cutting-edge Raman spectroscopic techniques. Since 2022, Janam has worked for Thermo Fisher Scientific as an application scientist, advancing the application of Raman Spectroscopy for real-time process measurements. This includes his current focus on implementing process Raman spectroscopy as a PAT tool in the clean-energy sector, among other industries.</p><p><strong>Presenter: </strong>Tom Dearing (Senior Staff Scientist, Thermo Fisher Scientific)</p><p>Tom Dearing received his PhD in Chemometrics from the University of Hull in England, focusing on reaction monitoring utilizing spectroscopy and modeling. Throughout his career, he has held various chemometric positions, all aimed at enhancing decision-making processes through measurements and modeling techniques. In 2022, Tom assumed the role of Director of Chemometrics at MarqMetrix. MarqMetrix became part of Thermo Fisher Scientific in 2023.</p></blockquote></div></div>

Thermo Fisher Scientific: Direct In-Line Fuel & Lubricant Quality Monitoring with Process Raman

Direct In-Line Fuel & Lubricant Quality Monitoring with Process Raman

Join this webinar to see how Process Raman ensures fuel quality with direct in-line analysis, delivering reliable, real-time results without consumables

Fuel & Lubricant Quality Monitoring with Process Raman

<p><strong>Achieving high confidence in analytical results for food fraud investigations is a complex challenge. However, data fusion is revolutionizing the way we detect and deter food fraud—offering greater reliability, accuracy, and cost-effectiveness than single-method approaches. This webinar explores how integrating diverse data sources including elemental and molecular spectroscopic fingerprints through to organic mass spectrometry profiles enhances food authenticity testing.&nbsp;</strong></p><p>You will discover how different fusion strategies, from low- to high-level integration, are applied in real-world case studies, including determining the geographic origin of salmon and soy, and identifying varieties of premium teas. The session will conclude with some thoughts about how the data fusion approach could overcome some of the very big authenticity challenges such as olive oil and honey analysis.</p><h5><strong>Key Learning Objectives:</strong></h5><ul><li>Recognize the financial, political, and legal impacts of global food fraud on producers and consumers.</li><li>Understand the strengths and limitations of molecular spectroscopy and mass spectrometry techniques in detecting food fraud.</li><li>Learn how combining data from multiple techniques can push analytical certainty toward 100%.</li></ul><blockquote><p><strong>Presenter:</strong> Chris Elliott (Inst. for Global Security, Belfast, UK)</p><p>Chris is the founder of the Institute for Global Food Security at Queen’s University Belfast and is a Honorary Professor there now. He is also Professor of Food Security at Thamassat University in Thailand. He has published over 600 peer-reviewed articles on the detection and control of agriculture, food, and environmental-related contaminants. Chris led the independent review of Britain’s food system following the 2013 horsemeat scandal and now acts as a scientific advisor for a range of United Nations Agencies, governments, and industries on a range of food security topics.</p><p>Over the years Chris has developed a high level network of collaborators across Europe, the United States , the Middle East and Asia. He is a recipient of a Winston Churchill Fellowship and is an elected Fellow of the Royal Society of Chemistry and Royal Society of Biology. Chris has received numerous prizes and awards for his work such as the Royal Society of Chemistry Theophilus Redwood Prize and an OBE in 2017. He was elected a member of the Royal Irish Academy in 2020 and became Vice President of the Chartered Institute of Environmental Health in 2021 and Honorary President of the Society of Food Hygiene and Technology in 2023.</p></blockquote>

The Analytical Scientist: Beyond Single Tests: How Data Fusion is Redefining Food Fraud Detection

Beyond Single Tests: How Data Fusion is Redefining Food Fraud Detection

Join webinar to explore data fusion for food fraud detection, enhancing accuracy and reliability across real-world case studies and authenticity challenges.

How Data Fusion is Redefining Food Fraud Detection

<p><strong>Explore the new look and feel of the Data Analysis engine. Become acquainted with Integration Parameters and how to create a calibration curve for quantitation. Investigate new software tools such as Peak Explorer, UV and MS Spectral capabilities, library searching and matching, peak purity and more. Learn how to combine information from multiple results sets to track trends across time and instrumentation.</strong></p><p>OpenLab CDS streamlines your lab operations with a single, secure data system that combines chromatography and mass spectrometry into one software platform. Control your Agilent GC, LC, single quadrupole GC/MS, LC/MS instruments as well as other vendors’ instruments in the lab, and save substantial time managing software and training staff. New tools in OpenLab CDS provide time-saving steps in the analysis, interpretation, and reporting workflows, so you can identify key information and improve turnaround time. Optional built-in technical controls provide peace of mind for analytical labs that need the highest level of data integrity.</p><p>Agilent is offering our valued customers an opportunity to increase their knowledge of OpenLab CDS in a series of live / interactive webinars. Each participant will have their own virtual image with the software loaded, configured and accessed through the web in the safety of your socially distant location. The Agilent expert will lead this virtual seminar and walk participants through a series of interactive laboratories that will allow each attendee to USE the software instead of just view a demonstration. A series of three different sessions each 2 hours in length will be offered. Each will be focused on a different aspect of the software. Feel free to attend all or just one of these seminars.</p><blockquote><p><strong>Presenter: Richard Mutkoski (Laboratory Informatics Application Engineer, Agilent Technologies, Inc.)</strong></p><p>Richard Mutkoski has been a field representative for over 27 years for both hardware and software. In his current role as an informatics application engineer, Rich presents technical solutions of the OpenLab suite of products to customers worldwide. Prior to his tenure at Agilent Rich spent 15 years in a variety of pharma QA/QC and R&amp;D positions, providing him a unique understanding of those workflows, bottlenecks, and challenges.</p></blockquote>

Agilent: OpenLab CDS Seminars - Remote Sessions

Seminar 2 – OpenLab CDS – Data Analysis

Explore the new look and feel of the Data Analysis engine. 

OpenLab CDS – Data Analysis

<div><p><strong>Wiley's KnowItAll software solutions provide a wide range of tools and databases to accelerate spectral identification for Raman, IR, GC-MS, LC-MS, NMR, and UV-Vis workflows. Continuously evolving to meet the demands of today's laboratory, KnowItAll 2026 takes spectral analysis to the next level.</strong></p><p>Join us for a tour of KnowItAll 2026—featuring a newly added application for principal component analysis (PCA), enhanced workflows, &amp; improvements across techniques to enhance your lab's productivity.</p><h4><strong>Key highlights in this release*</strong></h4><ul><li><strong>New Trendfinder application: </strong>Applies Principal Component Analysis (PCA) to uncover patterns in spectra or chromatographic datasets. It's designed to make trend detection intuitive, even if you don't have a background in chemometrics.</li><li><strong>General updates: </strong>MSI deployment, strengthened security, and flexible database installation</li><li><strong>Workflow improvements: </strong>Enhanced database controls, searching, new file format support, and updated applications across the suite</li><li><strong>Enhanced LC-MS, NMR &amp; GC-MS capabilities: </strong>Improved processing, automatic multiplet assignment, retention index searching, and more</li></ul><h4><strong>Who should attend</strong></h4><ul><li><strong>Current KnowItAll users</strong> to take advantage of the new capabilities</li><li><strong>Lab managers </strong>evaluating workflow improvements</li><li><strong>Instrument partners and resellers</strong> wanting to better serve customers</li><li><strong>Anyone interested in KnowItAll’s</strong> latest advances</li></ul><p><i>* Access to features can vary based on the edition of the software you have and options you have licensed. KnowItAll databases require a subscription.</i></p><blockquote><p><strong>Presenter:</strong> Michelle D’Souza, PhD (Product Manager, Software Products, Wiley Science Solutions, Wiley)</p><p>Dr. D’Souza brings years of insight and knowledge in the area of spectral informatics with leadership roles at both Wiley and Bio-Rad Laboratories. In addition to her multiple years as a scientific researcher at Abbott (now AbbVie) and DuPont, she has a Ph.D. in Chemistry from Northern Illinois University and a Masters in Analytical Chemistry from the Chinese Academy of Preventative Medicine. She earned a BS degree from Chemistry Department of Beijing University. &nbsp;</p></blockquote></div>

What’s New in KnowItAll 2026

Tour of KnowItAll 2026—featuring a newly added application for PCA, enhanced workflows, & improvements across techniques

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