RT Journal Article
T1 High-resolution modelling of organic aerosol over Europe: exploring spatial and temporal variability and drivers
A1 Trejo Banos, Daniel
A1 Sánchez de la Campa Verdona, Ana María
A1 Rosa Díaz, Jesús de la
A1 El Haddad, Imad
AB Organic aerosol (OA) is a major component of atmospheric particulate matter (PM), affecting both human health and climate. However, high-resolution estimates of OA exposure needed for exposure analysis remain scarce. Here, we integrate a chemical transport model (CAMx) with a random forest (RF) machine learning approach to bias-correct and downscale daily OA concentrations across Europe. CAMx OA simulations at ∼15 km resolution show moderate agreement with observations (r = 0.55). By combining these outputs with high-resolution land-use data and training the RF model on ∼48,000 daily OA measurements from 137 sites, prediction accuracy improved (r = 0.65), with ∼l5% reduction in root mean square error. The resulting maps provide European daily OA concentrations at ∼250 m resolution for alternate years from 2011 to 2019. The model captures key spatial features, including elevated OA in the Po Valley, Southeastern, and Central Europe, as well as intracity variations due to local hotspots. Seasonal analysis reveals higher concentrations in winter, while long-term trends indicate a general decline in OA levels. Exposure estimates show that half of the European population experiences OA levels above 3 µg/m3, and ∼50 million people are exposed to more than 5 µg/m3, which is the current guideline level recommended by the world health organization for total PM2.5. These high-resolution OA maps offer vital critical support for epidemiological research and air quality policy.
PB Elsevier
SN 0160-4120
SN 1873-6750 (electrónico)
YR 2026
FD 2026
LK https://hdl.handle.net/10272/28151
UL https://hdl.handle.net/10272/28151
LA eng
NO Banos, D. T., Upadhyay, A., Cheng, Y., Jiang, J., Vasilakos, P., Nava, A., Ševera, P., Flueckiger, B., Bougiatioti, A., Sanchez De La Campa Verdona, A. M., Schemmel, A., Alastuey, A., Vasanits, A., Font, A., Tobler, A., Bourin, A., Machon, A., Chazeau, B., Bergmans, B., … Haddad, I. E. (2026). High-resolution modelling of organic aerosol over Europe: exploring spatial and temporal variability and drivers. Environment International, 209, 110143. https://doi.org/10.1016/j.envint.2026.110143
NO We acknowledge all the support for this work. PSI and SDSC team acknowledge funding from Swiss data science centre (SDSC grant C20-08), the Swiss Federal Office of Environment (FOEN), and the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 884104 (PSI-FELLOW-III-3i). Offline data from Swiss sites were sourced from the Swiss National Air Pollution Monitoring Network NABEL, operated by FOEN and Empa. Data from Irish stations were supported by the EU Horizon (grant no. 101081430-PARIS), EPA Ireland and Department of the Environment, Climate and Communications. Data from Czech site were supported by the Ministry of Education, Youth and Sports of the Czech Republic, within the project for support of the national research infrastructure ACTRIS–CZ (LM2023030). Measurements from the Cyprus Atmospheric Observatory were supported financially by the H2020-EMME-CARE (GA 856612) research grants. Measurements from the Athens NOA Air Monitoring Station were supported by the “PANhellenic infrastructure for Atmospheric Composition and climatE change” (MIS 5021516) which is implemented under the Action “Reinforcement of the Research and Innovation Infrastructure”, funded by the Operational Programme “Competitiveness, Entrepreneurship and Innovation” (NSRF 2014-2020) and co-financed by Greece and the European Union (European Regional Development Fund). IDAEA-CSIC acknowledges the funding from Regional Catalan Government (grant no. AGAUR 2021SGR00447). TROPOS measurements were supported by the infrastructure projects ACTRIS (EU FP7; grant no. 262254), ACTRIS-2 (grant no. 654109), and by the German Federal Ministry of Research, Technology and Space (BMFTR) under grant agreements 01LK2002A-G. INOE acknowledge the support of the Core Program within the Romanian National Research Development and Innovation Plan 2022-2027, carried out with the support of MCID, project no. PN 23 05. Samples in France were collected through numerous research and air quality assessment programs, including CARA and MERA (both funded by the Ministry of Environment via LCSQA), DECOMBIO, CAMERA, and QAMECS (all funded by ADEME), ACME and MIAI-Airquality (funded by the University Grenoble Alpes), OPE–Andra (funded by Andra), and multiple initiatives supported by Atmo AuRA, Atmo Sud, Atmo Grand Est, Atmo Hauts de France, Atmo Normandie, IMT Nord Europe, AirBreizh, Atmo Auvergne-Rhône-Alpes, Atmo Grand-Est, Atmo Occitanie, and Lig’Air. We gratefully acknowledge Emmanuel Tison, Nicolas Bonnaire, the many individuals in French AASQA, and staff from several laboratories in France, including IGE and its Air O Sol plateau where a very large fraction of the French samples was analyzed. H. Chebaicheb's PhD was supported by LCSQA (French Ministry of Environment), the Labex CaPPA project (ANR-11-LABX-0005-01), and the CLIMIBIO and ECRIN projects (Hauts-de-France Region & European Regional Development Fund). The ATOLL site, also supported by the Cross-Disciplinary project AREA (R-CDP-24-003-AREA), is part of ACTRIS and contributes to the CARA program of the LCSQA. IMT Nord Europe and INERIS also participated in the COST COLOSSAL Action CA16109. I. Salma acknowledges the support from the Hungarian Research, Development and Innovation Office (contract: Advanced 150835). Ana acknowledgment is given to the Portuguese Foundation for Science and Technology (FCT) for funding UID Centro de Estudos do Ambiente e Mar (CESAM) + LA/P/0094/2020. LCE acknowledges the support of AtmoSud (ToF-ACMS). We acknowledge Dr Anja Tremper and Dr Max Priestman from Imperial College London for their valuable contributions in collecting the ACSM data in London from 2015-2018. Samples in Granada (Spain) were collected through numerous research and air quality assessment programs supported by the Spanish Ministry of Science and Innovation.
DS Repositorio Institucional de la Universidad de Huelva
RD 30 may 2026