@article{fdi:010094297,
  title = {{H}igh-resolution modelling of particulate matter chemical composition over {E}urope : brake wear pollution},
  author = {{U}padhyay, {A}. and {J}iang, {J}. {H}. and {C}heng, {Y}. and {V}asilakos, {P}. and {C}hen, {Y}. and {B}anos, {D}. {T}. and {F}lückiger, {B}. and {M}anousakas, {M}. {I}. and {P}r{\'e}v{\^o}t, {A}. {S}. {H}. and {M}odini, {R}. {L}. and de la {C}ampa, {A}. {S}. and {S}chemmel, {A}. and {A}lastuey, {A}. and {B}ergmans, {B}. and {A}lves, {C}. {A}. and {H}ueglin, {C}. and {C}olombi, {C}. and {R}eche, {C}. and {S}ánchez-{R}odas, {D}. and {M}assabò, {D}. and {D}iapouli, {E}. and {M}azzei, {F}. and {L}ucarelli, {F}. and {U}zu, {G}a{\¨e}lle and {S}alma, {I}. and {J}affrezo, {J}. {L}. and de la {R}osa, {J}. {D}. and {R}eusser, {J}. {E}. and {E}leftheriadis, {K}. and {A}lleman, {L}. {Y}. and {S}cerri, {M}. and {S}everi, {M}. and {F}avez, {O}. and {P}rati, {P}. and {T}raversi, {R}. and {V}ecchi, {R}. and {B}ecagli, {S}. and {N}ava, {S}. and {C}astillo, {S}. and {D}arfeuil, {S}ophie and {G}range, {S}. {K}. and {Q}uerol, {X}. and {K}ert{\'e}sz, {Z}. and {C}iarelli, {G}. and {P}robst-{H}ensch, {N}. and {V}ienneau, {D}. and {K}uenen, {J}. and {V}an {D}er {G}on, {H}. {D}. and {D}aellenbach, {K}. {R}. and {K}rymova, {E}. and de {H}oogh, {K}. and {E}l-{H}addad, {I}.},
  editor = {},
  language = {{ENG}},
  abstract = {{I}n today's rapidly evolving society, the sources of atmospheric particulate matter ({PM}) emissions are shifting significantly. {S}tringent 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 {E}urope. {T}his study analyzes the spatial distribution, temporal trends, and impacts of brake wear {PM} pollution across {E}urope by modeling copper ({C}u) concentrations at a high spatial resolution of-250 m which is a key tracer of brake-wear emissions. {W}e integrated coarse-resolution brake-wear {C}u from {CAM}x chemical transport model and high-resolution land use data into a random forest ({RF}) model to predict {C}u concentrations at-250 m over whole of continental {E}urope. {T}he {RF} model was trained using an unprecedented dataset of over 50,000 daily {C}u measurements from 152 sites. {I}t corrected {CAM}x underestimation and downscaled {C}u to a higher spatial resolution. {I}n validation, the model showed robust spatial and temporal prediction with good {P}earson's correlation coefficients of 0.6 and 0.7, respectively. {W}e generated 10 years (2010-2019) of daily {C}u concentrations over {E}urope, revealing spatial patterns aligned with urbanization and road networks, with peaks in cities and lower values in rural areas. {T}emporal trends reveal that {C}u concentrations generally peak on weekdays and in winter. {D}espite a decline in {PM} across {E}urope over decades, {C}u concentrations showed no decrease in many cities from 2010 to 2019. {C}u levels are strongly correlated with population density with more than 12 million {E}uropeans exposed to levels exceeding 40 ng/m3, equivalent to around 1 mu g/m3 of total {PM}10 from brake wear. {O}ur findings highlight the need for expanded metal measurement for non-exhaust tracers for a better understanding of the health relevance of {PM} composition including {C}u, and more effective regulations of non-exhaust {PM} emissions as included in {EURO} 7 vehicles.},
  keywords = {{B}rake wear ; {N}on-exhaust emissions ; {A}tmospheric {C}u ; {C}opper ; {CAM}x ; {R}andom forest ; {EUROPE}},
  booktitle = {},
  journal = {{E}nvironment {I}nternational},
  volume = {202},
  numero = {},
  pages = {109615 [13 ]},
  ISSN = {0160-4120},
  year = {2025},
  DOI = {10.1016/j.envint.2025.109615},
  URL = {https://www.documentation.ird.fr/hor/fdi:010094297},
}