Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/136692
Title: High-resolution modelling of particulate matter chemical composition over Europe : brake wear pollution
Authors: Upadhyay, Abhishek
Jiang, Jianhui
Cheng, Yun
Vasilakos, Petros
Chen, Ying
Trejo Banos, Daniel
Flückiger, Benjamin
Manousakas, Manousos I.
Prévot, André S.H.
Modini, Robin L.
Sanchez de la Campa, Ana
Schemmel, Andrea
Alastuey, Andrés
Bergmans, Benjamin
Alves, Célia A.
Hueglin, Christoph
Colombi, Cristina
Reche, Cristina
Sanchez-Rodas, Daniel
Massabò, Dario
Diapouli, Evangelia
Mazzei, Federico
Lucarelli, Franco
Uzu, Gaëlle
Salma, Imre
Jaffrezo, Jean-Luc
de la Rosa, Jesús D.
Reusser, Jolanda E.
Elefthariadis, Kostas
Alleman, Laurent Y.
Scerri, Mark M.
Severi, Mirko
Favez, Olivier
Prati, Paolo
Traversi, Rita
Vecchi, Roberta
Becagli, Silvia
Nava, Silvia
Castillo, Sonia
Darfeuil, Sophie
Grange, Stuart K.
Querol, Xavier
Kertész, Zsofia
Ciarelli, Giancarlo
Probst-Hensch, Nicole
Vienneau, Danielle
Kuenen, Jeroen
Denier Van Der Gon, Hugo
Daellenbach, Kaspar R.
Krymova, Ekaterina
de Hoogh, Kees
El-Haddad, Imad
Keywords: Copper
Air -- Pollution
Machine learning
Air quality management -- Mathematical models
Brakes -- Environmental aspects
Issue Date: 2025
Publisher: Elsevier Ltd.
Citation: Upadhyay, A., Jiang, J., Cheng, Y., Vasilakos, P., Chen, Y., Banos, D. T.,....El-Haddad, I. (2025). High-resolution modelling of particulate matter chemical composition over Europe: brake wear pollution. Environment International, 109615. DOI: https://doi.org/10.1016/j.envint.2025.109615
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/m3, equivalent to around 1 μg/m3 of total PM10 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.
URI: https://www.um.edu.mt/library/oar/handle/123456789/136692
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