LUXTIME: HISTORICAL EXPOSOMICS IN THE MINETT REGION

R-AGR-3703 - IAS - LuxTIME (01/06/2020 - 15/01/2025) - FICKERS Andrea

How can data visualization support interdisciplinary research? LuxTIME: studying historical exposomics in Belval

The Luxembourg Time Machine (LuxTIME) is an interdisciplinary project that studies the historical exposome during the industrialization of the Minett region, located in the south of Luxembourg. Exposome research encompasses all external and internal non-genetic factors influencing the health of the population, such as air pollution, green spaces, noise, work conditions, physical activity, and diet. Due to the wide scope of the interdisciplinary project, the historical study of the exposome in Belval involved the collection of quantitative and qualitative data from the National Archive of Luxembourg, various local archives (e.g., the communes of Esch-sur-Alzette and Sanem), the National Library, the Library of National Statistics STATEC, the National Geoportal of Luxembourg, scientific data from other research centers, and information from newspapers and journals digitized in eluxemburgensia.1 The data collection and the resulting inventory were performed to create a proof of concept to critically test the potential of a multi-layered research design for the study of the historical exposome in Belval. The guiding navigation tool throughout the project was data visualization. It has facilitated the exploration of the data collected (or just the data) and the metadata. It has also been a valuable tool for mapping knowledge and defining the scope of the project. Furthermore, different data visualization techniques have helped us to reflect on the process of knowledge sharing, to understand how the relevance of certain topics changed throughout the project and why, and to learn about the publication process in different journals and the experience of the participants. Data visualization is used not only as a means to an end but also to embrace the idea of sandcastles using a speculative and process-oriented approach to advance knowledge within all research fields involved. LuxTIME has proven to be an ideal case study to explore the possibilities offered by different data visualization concepts and techniques resulting in a data visualization toolbox that could be evaluated and extended in other interdisciplinary projects

How can data visualization support interdisciplinary research? LuxTIME: studying historical exposomics in Belval

peer reviewedThe Luxembourg Time Machine (LuxTIME) is an interdisciplinary project that studies the historical exposome during the industrialization of the Minett region, located in the south of Luxembourg. Exposome research encompasses all external and internal non-genetic factors influencing the health of the population, such as air pollution, green spaces, noise, work conditions, physical activity, and diet. Due to the wide scope of the interdisciplinary project, the historical study of the exposome in Belval involved the collection of quantitative and qualitative data from the National Archive of Luxembourg, various local archives (e.g., the communes of Esch-sur-Alzette and Sanem), the National Library, the Library of National Statistics STATEC, the National Geoportal of Luxembourg, scientific data from other research centers, and information from newspapers and journals digitized in eluxemburgensia.1 The data collection and the resulting inventory were performed to create a proof of concept to critically test the potential of a multi-layered research design for the study of the historical exposome in Belval. The guiding navigation tool throughout the project was data visualization. It has facilitated the exploration of the data collected (or just the data) and the metadata. It has also been a valuable tool for mapping knowledge and defining the scope of the project. Furthermore, different data visualization techniques have helped us to reflect on the process of knowledge sharing, to understand how the relevance of certain topics changed throughout the project and why, and to learn about the publication process in different journals and the experience of the participants. Data visualization is used not only as a means to an end but also to embrace the idea of sandcastles using a speculative and process-oriented approach to advance knowledge within all research fields involved. LuxTIME has proven to be an ideal case study to explore the possibilities offered by different data visualization concepts and techniques resulting in a data visualization toolbox that could be evaluated and extended in other interdisciplinary projects.R-AGR-3703 - IAS - LuxTIME (01/06/2020 - 15/01/2025) - FICKERS Andrea

Non-target screening of surface water samples to identify exposome-related pollutants: a case study from Luxembourg

peer reviewedBackground Non-target screening of surface water samples collected over an extended period can reveal interesting temporal patterns in exposome-related pollutants. Additionally, geographical data on pollution sources close to the sampling sites, chemical classification data and the consideration of flow paths can provide valuable information on the origins and potential threat of tentatively identified chemical compounds. In this study, 271 surface water samples from 20 sampling sites across Luxembourg were analysed using high-resolution mass spectrometry, complementing routine target monitoring efforts in 2019–2022. Data analysis was performed using the open source R-package patRoon, which offers a customizable non-target workflow. By employing open source workflows featuring scoring terms, like spectral match and applying identification levels, tentative identifications can be prioritized, e.g. based on spectral similarity. Furthermore, by utilizing supplementary database information such as PubChemLite annotation categories and classification software such as classyFire, an overall assessment of the potential threats posed by the tentatively identified chemicals was conducted, enabling the prioritization of chemicals for future confirmation through targeted approaches. Results The study tentatively identified 378 compounds associated with the exposome including benzenoids, organoheterocyclic compounds, and organic phosphoric acids and derivatives (11 classyFire superclasses, 50 subclasses). The classification analysis not only revealed temporal variations in agrochemicals, with the majority of identifications occurring in May to July, but also highlighted the prevalence of pharmaceuticals such as venlafaxine in surface waters. Furthermore, potential sources of pollutants, like metallurgic industry or household products were explored by considering common uses and geographical information, as commercial uses of almost 100% of the identified chemicals are known. 41 chemicals were suggested for potential inclusion to governmental monitoring lists for further investigation. Conclusions The findings of this study complement existing knowledge on the pollution status of surface water in Luxembourg and highlight the usefulness of non-target screening for identifying temporal and spatial trends in pollutant levels. This approach, performed in a complementary manner to routine monitoring, can help to tentatively identify chemicals of concern for potential inclusion in target monitoring methods following additional confirmation and quantification efforts.R-AGR-3703 - IAS - LuxTIME (01/06/2020 - 15/01/2025) - FICKERS Andrea

Non-Target Screening of Surface Water Samples to Identify Exposome-Related Pollutants: A Case Study From Luxembourg

peer reviewedTalk given by Dagny Aurich at the ICNTS in Erdin

Chemical Stripes – Visualizing Chemical Trends of the Past Influencing Today

Platform presentation at the SETAC Europe 33rd Annual Meeting, Dublin Session: 3.20 - PMT/vPvM substances: Assessment, Management and Regulation, 04 May 202

Revealing Chemical Trends: Insights from Data-Driven Visualisation and Patent Analysis in Exposomics Research

Understanding historical chemical usage is crucial for assessing current and past impacts on human health and the environment and informing future regulatory decisions. However, past monitoring data is often limited in scope and number of chemicals, while suitable sample types are not always available for remeasurement. Data-driven cheminformatics methods on patent and literature data offer several opportunities to fill this gap. The chemical stripes were developed as an interactive, open source tool for visualising patent and literature trends over time, inspired by the global warming and biodiversity stripes. This paper details the underlying code and datasets behind the visualisation, with a major focus on the patent data sourced from PubChem, including patent origins, uses, and countries. Overall trends and specific examples are investigated in greater detail to explore both the promise and caveats that such data offers in assessing the trends and patterns of chemical patents over time and across different geographic regions. Despite a number of potential artefacts associated with patent data extraction, the integration of cheminformatics, statistical analysis, and data visualisation tools can help generate valuable insights that can both illuminate the chemical past and potentially serve towards an early warning system for the future

Revealing Chemical Trends: Insights from Data-Driven Visualization and Patent Analysis in Exposomics Research

peer reviewedUnderstanding historical chemical usage is crucial for assessing current and past impacts on human health and the environment and for informing future regulatory decisions. However, past monitoring data are often limited in scope and number of chemicals, while suitable sample types are not always available for remeasurement. Data-driven cheminformatics methods for patent and literature data offer several opportunities to fill this gap. The chemical stripes were developed as an interactive, open source tool for visualizing patent and literature trends over time, inspired by the global warming and biodiversity stripes. This paper details the underlying code and data sets behind the visualization, with a major focus on the patent data sourced from PubChem, including patent origins, uses, and countries. Overall trends and specific examples are investigated in greater detail to explore both the promise and caveats that such data offer in assessing the trends and patterns of chemical patents over time and across different geographic regions. Despite a number of potential artifacts associated with patent data extraction, the integration of cheminformatics, statistical analysis, and data visualization tools can help generate valuable insights that can both illuminate the chemical past and potentially serve toward an early warning system for the future.R-AGR-3703 - IAS - LuxTIME - FICKERS Andrea

Avoiding the Next Silent Spring: Our Chemical Past, Present, and Future

Rachel Carson's Silent Spring,1 published just over 60 years ago, outlined how the indiscriminate use of dichlorodiphenyltrichloroethane (DDT), a potent, environmentally persistent insecticide, was damaging the world's ecosystems, animals and food supply. There were many other chemicals more persistent than DDT accumulating in the environment when Carson was writing, including per- and polyfluoroalkyl substances (PFAS). Whilst man-made, PFAS were not intended to cause harm, contrary to pesticides such as DDT. Today, ambient PFAS levels are contaminating rain, soil and drinking water resources worldwide to such an extent that they have caused substantial, irreversible health and environmental damage.2 Like DDT, PFAS were long in use by the time Rachel Carson was writing Silent Spring (see Figure 1). However, their environmental presence went unnoticed by Carson and other contemporary environmental researchers. PFAS were entering the environment under the radar, except to those who were manufacturing and emitting them.

Historical exposomics: a manifesto

peer reviewedThe exposome complements information captured in the genome by covering all external influences and internal (biological) responses of a human being from conception onwards. Such a paradigm goes beyond a single scientific discipline and instead requires a truly interdisciplinary approach. The concept of “historical exposomics” could help bridge the gap between “nature” and “nurture” using both natural and social archives to capture the influence of humans on earth (the Anthropocene) in an interdisciplinary manner. The LuxTIME project served as a test bed for an interdisciplinary exploration of the historical exposome, focusing on the Belval area located in the Minett region in southern Luxembourg. This area evolved from a source of mineral water to steel production through to the current campus for research and development. This article explores the various possibilities of natural and social archives that were considered in creating the historical exposome of Belval and reflects upon possibilities and limitations of the current approaches in assessing the exposome using purely a natural science approach. Issues surrounding significance, visualization, and availability of material suitable to form natural archives are discussed in a critical manner. The “Minett Stories” are presented as a way of creating new historical narratives to support exposome research. New research perspectives on the history of the Anthropocene were opened by investigating the causal relationships between factual evidence and narrative evidence stemming from historical sources. The concept of historical exposome presented here may thus offer a useful conceptual framework for studying the Anthropocene in a truly interdisciplinary fashion