High-resolution modelling of particulate matter chemical composition over Europe: brake wear pollution

In today's rapidly evolving society, the sources of atmospheric particulate matter (PM) emissions are shifting significantly. Stringent regulations on vehicle tailpipe emissions, in combination with a lack of control of non-exhaust vehicular emissions, have led to an increase in the relative contribution of non-exhaust PM in Europe. This study analyzes the spatial distribution, temporal trends, and impacts of brake wear PM pollution across Europe by modeling copper (Cu) concentrations at a high spatial resolution of ∼250 m which is a key tracer of brake-wear emissions. We integrated coarse-resolution brake-wear Cu from CAMx chemical transport model and high-resolution land use data into a random forest (RF) model to predict Cu concentrations at ∼250 m over whole of continental Europe. The RF model was trained using an unprecedented dataset of over 50,000 daily Cu measurements from 152 sites. It corrected CAMx underestimation and downscaled Cu to a higher spatial resolution. In validation, the model showed robust spatial and temporal prediction with good Pearson's correlation coefficients of 0.6 and 0.7, respectively. We generated 10 years (2010-2019) of daily Cu concentrations over Europe, revealing spatial patterns aligned with urbanization and road networks, with peaks in cities and lower values in rural areas. Temporal trends reveal that Cu concentrations generally peak on weekdays and in winter. Despite a decline in PM across Europe over decades, Cu concentrations showed no decrease in many cities from 2010 to 2019. Cu levels are strongly correlated with population density with more than 12 million Europeans exposed to levels exceeding 40 ng/m<sup>3</sup>, equivalent to around 1 μg/m<sup>3</sup> of total PM<sub>10</sub> from brake wear. Our findings highlight the need for expanded metal measurement for non-exhaust tracers for a better understanding of the health relevance of PM composition including Cu, and more effective regulations of non-exhaust PM emissions as included in EURO 7 vehicles.

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Publication Details

Journal
Environment International
Published
2025-06-22
DOI
https://doi.org/10.1016/j.envint.2025.109615
Citations
3
Primary Topic
Vehicle emissions and performance
Type
article
Field-Weighted Citation Impact
2.05

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article

High-resolution modelling of particulate matter chemical composition over Europe: brake wear pollution

Andrê S. H. Prévôt, Zsófia Kertész, Olivier Favez, Petros Vasilakos et al.
3 citations
Environment International
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High-resolution modelling of particulate matter chemical composition over Europe: brake wear pollution

Andrê S. H. Prévôt, Zsófia Kertész, Olivier Favez, Petros Vasilakos, Jolanda E. Reusser, Ana M. Sánchez de la Campa, Christoph Hueglin, R. Vecchi, Manousos Ioannis Manousakas, Rita Traversi, Nicole M Probst-Hensch, Andrés Alástuey, L. Alleman, Silvia Becagli, Mark M. Scerri, Federico Mazzei, Silvia Nava, Daniel Sánchez-Rodas, Sophie Darfeuil, F. Lucarelli, Sonia Castillo, Jeroen Kuenen, P. Prati, Gaëlle Uzu, Robin L. Modini, Mirko Severi, Kees de Hoogh, Dario Massabò, Xavier Querol, Imre Salma, Jean‐Luc Jaffrezo, Cristina Reche, Jianhui Jiang, Benjamin Flückiger, Benjamin Bergmans, Stuart K. Grange, Giancarlo Ciarelli, Hugo Denier van der Gon, Jesús de la Rosa, Imad El Haddad, Danielle Vienneau, Evangelia Diapouli, Cristina Colombi, Célia Alves, Ying Chen, Abhishek Upadhyay, Yun Cheng, Kaspar R. Daellenbach, Andrea Schemmel, Ekaterina Krymova, Daniel Trejo Banos, Kostas Elefthariadis
article en
3 citations

Abstract

In today's rapidly evolving society, the sources of atmospheric particulate matter (PM) emissions are shifting significantly. Stringent regulations on vehicle tailpipe emissions, in combination with a lack of control of non-exhaust vehicular emissions, have led to an increase in the relative contribution of non-exhaust PM in Europe. This study analyzes the spatial distribution, temporal trends, and impacts of brake wear PM pollution across Europe by modeling copper (Cu) concentrations at a high spatial resolution of ∼250 m which is a key tracer of brake-wear emissions. We integrated coarse-resolution brake-wear Cu from CAMx chemical transport model and high-resolution land use data into a random forest (RF) model to predict Cu concentrations at ∼250 m over whole of continental Europe. The RF model was trained using an unprecedented dataset of over 50,000 daily Cu measurements from 152 sites. It corrected CAMx underestimation and downscaled Cu to a higher spatial resolution. In validation, the model showed robust spatial and temporal prediction with good Pearson's correlation coefficients of 0.6 and 0.7, respectively. We generated 10 years (2010-2019) of daily Cu concentrations over Europe, revealing spatial patterns aligned with urbanization and road networks, with peaks in cities and lower values in rural areas. Temporal trends reveal that Cu concentrations generally peak on weekdays and in winter. Despite a decline in PM across Europe over decades, Cu concentrations showed no decrease in many cities from 2010 to 2019. Cu levels are strongly correlated with population density with more than 12 million Europeans exposed to levels exceeding 40 ng/m<sup>3</sup>, equivalent to around 1 μg/m<sup>3</sup> of total PM<sub>10</sub> from brake wear. Our findings highlight the need for expanded metal measurement for non-exhaust tracers for a better understanding of the health relevance of PM composition including Cu, and more effective regulations of non-exhaust PM emissions as included in EURO 7 vehicles.

Environment InternationalVol. 202
Eötvös Loránd University (HU), Institut polytechnique de Grenoble (FR), Centre National de la Recherche Scientifique (FR), University of Helsinki (FI), Swiss Tropical and Public Health Institute (CH), Universidad de Granada (ES), University of Milan (IT), Utrecht University (NL), University of Malta (MT), HUN-REN Institute for Nuclear Research (HU), National Centre of Scientific Research "Demokritos" (GR), Institut Mines-Télécom (FR), Paul Scherrer Institute (CH), ETH Zurich (CH), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Institut Scientifique de Service Public (BE), Institut des Géosciences de l'Environnement (FR), Swiss Data Science Center (CH), Istituto Nazionale di Fisica Nucleare, Sezione di Genova (IT), Institut national de l'environnement industriel et des risques (FR), German Environment Agency (DE), Agenzia Regionale per la Protezione dell'ambiente ligure (IT), Institute of Environmental Assessment and Water Research (ES), Institut de Recherche pour le Développement (FR), Institute of Nuclear & Radiological Sciences and Technology, Energy & Safety, Azienda Regionale per la protezione dell'ambiente Lombardia (IT), University of Florence (IT), École Polytechnique Fédérale de Lausanne (CH), University of Aveiro (PT), Swiss Federal Institute of Aquatic Science and Technology (CH), East China Normal University (CN), Swiss Federal Laboratories for Materials Science and Technology (CH), Universidad de Huelva (ES), University of Birmingham (GB), Université Grenoble Alpes (FR)
Universidade de Aveiro, San Diego Supercomputer Center, European Commission, National Natural Science Foundation of China, Ministério da Ciência, Tecnologia e Ensino Superior, Agence Nationale pour la Gestion des Déchets Radioactifs, Regione Toscana, Région Normandie, Centro de Estudos Ambientais e Marinhos, Universidade de Aveiro, Fundação para a Ciência e a Tecnologia, National Key Research and Development Program of China
Climate action
Openalex Percentile: Top 13%
Vehicle emissions and performance
2.05
DOIOpen Access PDFOpenAlex
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