To date, one of the main challenges is the development and application of holistic workflows to fully characterize the “fingerprint” of different environmental samples. The last advances in high resolution mass spectrometry (HRMS) offered the possibility of the simultaneous detection of thousands of compounds in the environmental samples, allowing a comprehensive discovery of chemical space for the first time. Overall, non-target screening (NTS) has shown to be a powerful approach for a successful characterization of environmental systems and identification of contaminants. Over the last decade, we have developed cutting-edge LC-ESI (both RPLC and HILIC) and GC-APCI-HRMS methodologies and workflows (wide-scope target, suspect and non-target screening) for the identification of emerging contaminants (ECs) [1,2] and their transformation products (TPs) [3]. A database of more than 2,400 ECs has been developed for the target screening of the samples, and is continuously being updated, as new compounds are being identified. Moreover, sophisticated software and advanced chemometric tools have been developed, as supporting NTS tools. A Quantitative Structure–Retention Relationship (QSRR) prediction model has been developed [4], for predicting the retention time of new compounds, while the development of Retention Time Indices (RTI) has enabled the harmonization of retention time of ECs in various LC systems at different laboratories at a global scale. Recently, a new in-house developed software has enabled the prioritization of features, through the automated detection of ECs and their TPs that present a trend of detection across the tested samples (trend analysis). Chemical curation workflows have been developed, enabling the development of MS-ready suspect lists. Furthermore, novel steps have been being incorporated into the developed screening workflows for promoting a faster and more accurate identification of unknowns. Screening of samples with a wide-scope regulatory database of more than 68,000 chemicals, automated subtraction of analytical procedural blank from samples, isotopic fitting measurement and modified MS/MS similarity score, are included in an automated workflow [5]. In order to assess the ecotoxicological impact of the detected ECs, a risk assessment algorithm has been developed to predict the acute/growth inhibition toxicity of newly identified compounds towards the three main aquatic organisms (Daphnia magna, Fathead minnow and algae (Selenastrum capricornutum)). Moreover, within NORMAN network activities, we have significantly contributed to the development of “NORMAN SusDat database” available for wide-scope suspect screening [6], through the development of a non-target screening data exchange platform (Digital Sample Freezing Platform). The developed novel methodologies have been applied for the monitoring of Black Sea, during the Joint Danube River survey and in predators and their prey within the LIFE APEX project.

To date, one of the main challenges is the development and application of holistic workflows to fully characterize the “fingerprint” of different environmental samples. The last advances in high resolution mass spectrometry (HRMS) offered the possibility of the simultaneous detection of thousands of compounds in the environmental samples, allowing a comprehensive discovery of chemical space for the first time. Overall, non-target screening (NTS) has shown to be a powerful approach for a successful characterization of environmental systems and identification of contaminants. Over the last decade, we have developed cutting-edge LC-ESI (both RPLC and HILIC) and GC-APCI-HRMS methodologies and workflows (wide-scope target, suspect and non-target screening) for the identification of emerging contaminants (ECs) [1,2] and their transformation products (TPs) [3]. A database of more than 2,400 ECs has been developed for the target screening of the samples, and is continuously being updated, as new compounds are being identified. Moreover, sophisticated software and advanced chemometric tools have been developed, as supporting NTS tools. A Quantitative Structure–Retention Relationship (QSRR) prediction model has been developed [4], for predicting the retention time of new compounds, while the development of Retention Time Indices (RTI) has enabled the harmonization of retention time of ECs in various LC systems at different laboratories at a global scale. Recently, a new in-house developed software has enabled the prioritization of features, through the automated detection of ECs and their TPs that present a trend of detection across the tested samples (trend analysis). Chemical curation workflows have been developed, enabling the development of MS-ready suspect lists. Furthermore, novel steps have been being incorporated into the developed screening workflows for promoting a faster and more accurate identification of unknowns. Screening of samples with a wide-scope regulatory database of more than 68,000 chemicals, automated subtraction of analytical procedural blank from samples, isotopic fitting measurement and modified MS/MS similarity score, are included in an automated workflow [5]. In order to assess the ecotoxicological impact of the detected ECs, a risk assessment algorithm has been developed to predict the acute/growth inhibition toxicity of newly identified compounds towards the three main aquatic organisms (Daphnia magna, Fathead minnow and algae (Selenastrum capricornutum)). Moreover, within NORMAN network activities, we have significantly contributed to the development of “NORMAN SusDat database” available for wide-scope suspect screening [6], through the development of a non-target screening data exchange platform (Digital Sample Freezing Platform). The developed novel methodologies have been applied for the monitoring of Black Sea, during the Joint Danube River survey and in predators and their prey within the LIFE APEX project.

To date, one of the main challenges is the development and application of holistic workflows to fully characterize the “fingerprint” of different environmental samples. The last advances in high resolution mass spectrometry (HRMS) offered the possibility of the simultaneous detection of thousands of compounds in the environmental samples, allowing a comprehensive discovery of chemical space for the first time. Overall, non-target screening (NTS) has shown to be a powerful approach for a successful characterization of environmental systems and identification of contaminants. Over the last decade, we have developed cutting-edge LC-ESI (both RPLC and HILIC) and GC-APCI-HRMS methodologies and workflows (wide-scope target, suspect and non-target screening) for the identification of emerging contaminants (ECs) [1,2] and their transformation products (TPs) [3]. A database of more than 2,400 ECs has been developed for the target screening of the samples, and is continuously being updated, as new compounds are being identified. Moreover, sophisticated software and advanced chemometric tools have been developed, as supporting NTS tools. A Quantitative Structure–Retention Relationship (QSRR) prediction model has been developed [4], for predicting the retention time of new compounds, while the development of Retention Time Indices (RTI) has enabled the harmonization of retention time of ECs in various LC systems at different laboratories at a global scale. Recently, a new in-house developed software has enabled the prioritization of features, through the automated detection of ECs and their TPs that present a trend of detection across the tested samples (trend analysis). Chemical curation workflows have been developed, enabling the development of MS-ready suspect lists. Furthermore, novel steps have been being incorporated into the developed screening workflows for promoting a faster and more accurate identification of unknowns. Screening of samples with a wide-scope regulatory database of more than 68,000 chemicals, automated subtraction of analytical procedural blank from samples, isotopic fitting measurement and modified MS/MS similarity score, are included in an automated workflow [5]. In order to assess the ecotoxicological impact of the detected ECs, a risk assessment algorithm has been developed to predict the acute/growth inhibition toxicity of newly identified compounds towards the three main aquatic organisms (Daphnia magna, Fathead minnow and algae (Selenastrum capricornutum)). Moreover, within NORMAN network activities, we have significantly contributed to the development of “NORMAN SusDat database” available for wide-scope suspect screening [6], through the development of a non-target screening data exchange platform (Digital Sample Freezing Platform). The developed novel methodologies have been applied for the monitoring of Black Sea, during the Joint Danube River survey and in predators and their prey within the LIFE APEX project.

The river Meuse is the source for drinking water production for around 6 million inhabitants in the Netherlands and Belgium. It receives treated wastewater from households and industries, as well as agricultural activities in France, Belgium, North Rhine-Westphalia and the Netherlands, and thereby emissions from a wide range of organic micro-pollutants. Current monitoring programs are not comprehensive and might not include emerging contaminants. To counteract, the revision of the Drinking Water Decree of September 2017 [1] implements a so called risk-based water quality monitoring, tailored to the water source and type of treatment. The design of such a risk-based measurement program requires information on activities and environmental characteristics affecting water quality, as well as an inventory of contaminants relevant for source and drinking water protection. This information can then be used in nontarget screening strategies. These strategies are based on the combination of liquid chromatography (LC) and high resolution mass spectrometry (HRMS) and allow the monitoring of a wide range of compounds in water matrices. The actual detection range depends on the LC column used and the ionization potential of the compounds. Reverse phase (RP) columns (e.g., C18) are suitable for separating semi-polar substances. However, to separate very polar substances, alternatives are needed, such as hydrophilic interaction liquid chromatography (HILIC) [2] or mixed-mode chromatography (MMC) [3]. Here, we combine HRMS based non-target screening using three different chromatographies with suspect lists compiled from existing lists of relevant substances (e.g., SVHC, PMT/vPvM) and dedicated data analysis tools. We show how relevant compounds can be detected, compounds (i.e., features) prioritized and identified. The acquired information allows to update and adapt current monitoring programs, and ultimately leads to improved monitoring of sources of drinking water in the Netherlands.

The river Meuse is the source for drinking water production for around 6 million inhabitants in the Netherlands and Belgium. It receives treated wastewater from households and industries, as well as agricultural activities in France, Belgium, North Rhine-Westphalia and the Netherlands, and thereby emissions from a wide range of organic micro-pollutants. Current monitoring programs are not comprehensive and might not include emerging contaminants. To counteract, the revision of the Drinking Water Decree of September 2017 [1] implements a so called risk-based water quality monitoring, tailored to the water source and type of treatment. The design of such a risk-based measurement program requires information on activities and environmental characteristics affecting water quality, as well as an inventory of contaminants relevant for source and drinking water protection. This information can then be used in nontarget screening strategies. These strategies are based on the combination of liquid chromatography (LC) and high resolution mass spectrometry (HRMS) and allow the monitoring of a wide range of compounds in water matrices. The actual detection range depends on the LC column used and the ionization potential of the compounds. Reverse phase (RP) columns (e.g., C18) are suitable for separating semi-polar substances. However, to separate very polar substances, alternatives are needed, such as hydrophilic interaction liquid chromatography (HILIC) [2] or mixed-mode chromatography (MMC) [3]. Here, we combine HRMS based non-target screening using three different chromatographies with suspect lists compiled from existing lists of relevant substances (e.g., SVHC, PMT/vPvM) and dedicated data analysis tools. We show how relevant compounds can be detected, compounds (i.e., features) prioritized and identified. The acquired information allows to update and adapt current monitoring programs, and ultimately leads to improved monitoring of sources of drinking water in the Netherlands.

The river Meuse is the source for drinking water production for around 6 million inhabitants in the Netherlands and Belgium. It receives treated wastewater from households and industries, as well as agricultural activities in France, Belgium, North Rhine-Westphalia and the Netherlands, and thereby emissions from a wide range of organic micro-pollutants. Current monitoring programs are not comprehensive and might not include emerging contaminants. To counteract, the revision of the Drinking Water Decree of September 2017 [1] implements a so called risk-based water quality monitoring, tailored to the water source and type of treatment. The design of such a risk-based measurement program requires information on activities and environmental characteristics affecting water quality, as well as an inventory of contaminants relevant for source and drinking water protection. This information can then be used in nontarget screening strategies. These strategies are based on the combination of liquid chromatography (LC) and high resolution mass spectrometry (HRMS) and allow the monitoring of a wide range of compounds in water matrices. The actual detection range depends on the LC column used and the ionization potential of the compounds. Reverse phase (RP) columns (e.g., C18) are suitable for separating semi-polar substances. However, to separate very polar substances, alternatives are needed, such as hydrophilic interaction liquid chromatography (HILIC) [2] or mixed-mode chromatography (MMC) [3]. Here, we combine HRMS based non-target screening using three different chromatographies with suspect lists compiled from existing lists of relevant substances (e.g., SVHC, PMT/vPvM) and dedicated data analysis tools. We show how relevant compounds can be detected, compounds (i.e., features) prioritized and identified. The acquired information allows to update and adapt current monitoring programs, and ultimately leads to improved monitoring of sources of drinking water in the Netherlands.

Identification of unknown contaminants encountered in non-target screening analysis of water samples by means of liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) measurements is challenging. In literature, most successful identification attempts are based on the usage of databases for comparisons with the accurate mass, isotopic pattern and fragment ion spectrum [1, 2]. Further approaches for the identification of unknowns based on nuclear magnetic resonance (NMR) spectroscopy, commonly as 1H-NMR and 13C-NMR experiments, are known and were successfully applied for the identification of transformations products (TPs) [3]. In this study the possibilities and limitations for the identification of unknowns are exemplified. Samples from a drinking water production process were investigated by non-target screening analysis. By a prioritization workflow, where a total of nine features were prioritized, one of them could be identified as metoprolol acid/atenolol acid by reference standard and one could be tentatively identified as 1,3-benzothiazole-2sulfonic acid by using the FOR-IDENT database. From measurements of river Rhine samples one feature was encountered, which could not be identified by databases. Therefore, a comprehensive structure elucidation for the characterization of this feature was carried out whereby besides the LC-HRMS data further analytical investigations such, e.g., NMR experiments were accomplished. With the experimental data, functional groups of the unknown feature could be determined.

Identification of unknown contaminants encountered in non-target screening analysis of water samples by means of liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) measurements is challenging. In literature, most successful identification attempts are based on the usage of databases for comparisons with the accurate mass, isotopic pattern and fragment ion spectrum [1, 2]. Further approaches for the identification of unknowns based on nuclear magnetic resonance (NMR) spectroscopy, commonly as 1H-NMR and 13C-NMR experiments, are known and were successfully applied for the identification of transformations products (TPs) [3]. In this study the possibilities and limitations for the identification of unknowns are exemplified. Samples from a drinking water production process were investigated by non-target screening analysis. By a prioritization workflow, where a total of nine features were prioritized, one of them could be identified as metoprolol acid/atenolol acid by reference standard and one could be tentatively identified as 1,3-benzothiazole-2sulfonic acid by using the FOR-IDENT database. From measurements of river Rhine samples one feature was encountered, which could not be identified by databases. Therefore, a comprehensive structure elucidation for the characterization of this feature was carried out whereby besides the LC-HRMS data further analytical investigations such, e.g., NMR experiments were accomplished. With the experimental data, functional groups of the unknown feature could be determined.

Identification of unknown contaminants encountered in non-target screening analysis of water samples by means of liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) measurements is challenging. In literature, most successful identification attempts are based on the usage of databases for comparisons with the accurate mass, isotopic pattern and fragment ion spectrum [1, 2]. Further approaches for the identification of unknowns based on nuclear magnetic resonance (NMR) spectroscopy, commonly as 1H-NMR and 13C-NMR experiments, are known and were successfully applied for the identification of transformations products (TPs) [3]. In this study the possibilities and limitations for the identification of unknowns are exemplified. Samples from a drinking water production process were investigated by non-target screening analysis. By a prioritization workflow, where a total of nine features were prioritized, one of them could be identified as metoprolol acid/atenolol acid by reference standard and one could be tentatively identified as 1,3-benzothiazole-2sulfonic acid by using the FOR-IDENT database. From measurements of river Rhine samples one feature was encountered, which could not be identified by databases. Therefore, a comprehensive structure elucidation for the characterization of this feature was carried out whereby besides the LC-HRMS data further analytical investigations such, e.g., NMR experiments were accomplished. With the experimental data, functional groups of the unknown feature could be determined.

Liquid chromatography coupled with high resolution mass spectrometry (LC-HRMS) did not only provide new possibilities for the analysis of individual water samples, but particularly boosted comparative considerations of multiple samples, such as temporally or spatially related water samples. New application areas for LC-HRMS in water analysis were generated by the integration of metadata during data analysis. An important prerequisite for the establishment of this method is the comparability of analytical results irrespective of the conducting laboratory and the analytical instrument used for LCHRMS analysis. Based on this requirement, the German Water Chemical Society established an expert committee (EC) to summarize the practical experience of the participants in a guideline for non-target screening by LC-ESI-HRMS. [1] The structure of the guideline is based on the general structure of an analytical method. The exact formulation of the task / problem definition is the starting point of each (nontarget) analysis. This results in specific aspects of the sampling strategy and technique, location and timing. From the moment of sampling, the topic of possible blank values (i.e. sample contamination) must always be taken into account. The guideline discusses blank values for sampling, sample preparation and measurement, and states possible ways to minimize them. For a purposeful evaluation of the data and for answering the analytic question, the collection of as much additional information is useful. This metadata may be helpful in interpreting the data. The use of different HRMS devices from different manufacturers with different ion source designs (electrospray ionization, ESI) and various software solutions primarily raises the question of the fundamental comparability of NTS results. Therefore, two comparative studies within the EC were designed and conducted. In the first, possible differences in the detection limit and mass accuracy of the HRMS systems used should be recognized. In the second, the concentration dependence of the identification of spiked substances in a real matrix was considered more closely. From the comparison of the different methods/workflows, the commonalities and problems in data acquisition and data analysis were demonstrated. The results are summarized in the guideline.

Liquid chromatography coupled with high resolution mass spectrometry (LC-HRMS) did not only provide new possibilities for the analysis of individual water samples, but particularly boosted comparative considerations of multiple samples, such as temporally or spatially related water samples. New application areas for LC-HRMS in water analysis were generated by the integration of metadata during data analysis. An important prerequisite for the establishment of this method is the comparability of analytical results irrespective of the conducting laboratory and the analytical instrument used for LCHRMS analysis. Based on this requirement, the German Water Chemical Society established an expert committee (EC) to summarize the practical experience of the participants in a guideline for non-target screening by LC-ESI-HRMS. [1] The structure of the guideline is based on the general structure of an analytical method. The exact formulation of the task / problem definition is the starting point of each (nontarget) analysis. This results in specific aspects of the sampling strategy and technique, location and timing. From the moment of sampling, the topic of possible blank values (i.e. sample contamination) must always be taken into account. The guideline discusses blank values for sampling, sample preparation and measurement, and states possible ways to minimize them. For a purposeful evaluation of the data and for answering the analytic question, the collection of as much additional information is useful. This metadata may be helpful in interpreting the data. The use of different HRMS devices from different manufacturers with different ion source designs (electrospray ionization, ESI) and various software solutions primarily raises the question of the fundamental comparability of NTS results. Therefore, two comparative studies within the EC were designed and conducted. In the first, possible differences in the detection limit and mass accuracy of the HRMS systems used should be recognized. In the second, the concentration dependence of the identification of spiked substances in a real matrix was considered more closely. From the comparison of the different methods/workflows, the commonalities and problems in data acquisition and data analysis were demonstrated. The results are summarized in the guideline.

Liquid chromatography coupled with high resolution mass spectrometry (LC-HRMS) did not only provide new possibilities for the analysis of individual water samples, but particularly boosted comparative considerations of multiple samples, such as temporally or spatially related water samples. New application areas for LC-HRMS in water analysis were generated by the integration of metadata during data analysis. An important prerequisite for the establishment of this method is the comparability of analytical results irrespective of the conducting laboratory and the analytical instrument used for LCHRMS analysis. Based on this requirement, the German Water Chemical Society established an expert committee (EC) to summarize the practical experience of the participants in a guideline for non-target screening by LC-ESI-HRMS. [1] The structure of the guideline is based on the general structure of an analytical method. The exact formulation of the task / problem definition is the starting point of each (nontarget) analysis. This results in specific aspects of the sampling strategy and technique, location and timing. From the moment of sampling, the topic of possible blank values (i.e. sample contamination) must always be taken into account. The guideline discusses blank values for sampling, sample preparation and measurement, and states possible ways to minimize them. For a purposeful evaluation of the data and for answering the analytic question, the collection of as much additional information is useful. This metadata may be helpful in interpreting the data. The use of different HRMS devices from different manufacturers with different ion source designs (electrospray ionization, ESI) and various software solutions primarily raises the question of the fundamental comparability of NTS results. Therefore, two comparative studies within the EC were designed and conducted. In the first, possible differences in the detection limit and mass accuracy of the HRMS systems used should be recognized. In the second, the concentration dependence of the identification of spiked substances in a real matrix was considered more closely. From the comparison of the different methods/workflows, the commonalities and problems in data acquisition and data analysis were demonstrated. The results are summarized in the guideline.