Source apportionment of PM10 based on offline chemical speciation data at 24 European sites

This study applied Positive Matrix Factorization (PMF) to PM10 speciation datasets from 24 urban sites across six European countries (France, Greece, Italy, Portugal, Spain, and Switzerland) to perform a detailed source apportionment (SA) analysis. By using a consistent source apportionment tool for all datasets, the study enhances the comparability of PM10 SA results across urban Europe. The results identified seven major PM10 sources including road traffic, biomass burning, crustal/mineral sources, secondary aerosols, industrial emissions, sea salt, and heavy oil combustion (HOC). Road traffic emerged as the predominant source of PM10 in urban areas, with contributions varying by location, but representing as much as 41% in high-traffic zones. Biomass burning was detected at 23 sites, contributing 8% to 41% on yearly averages, with substantial increase in winter. Crustal sources were present at all sites (3–33%). Industrial sources contributed relatively less PM10 mass, which was identified at 10 sites with contributions ranging from 2% to 14%. Secondary inorganic and organic aerosol, consisting primarily of ammonium nitrates and sulfates, and organic matter, formed a portion of the PM10 mass (5–41%). These secondary factors are primarily influenced by anthropogenic emissions, including the various combustion processes. Sea salt, predominantly found in coastal areas, contributed between 4% and 21%, reflecting the impact of the marine environments on air quality. This source was very often ‘aged’ (mixed with anthropogenic pollutants from different origins). Additionally, HOC, especially emits from shipping activities, and traced by V and Ni, was also a frequent contributing source (2–15% for 9 sites), indicating a need for more stringent emission controls. The chemical comparison is performed which indicates road traffic and secondary aerosols, showed consistent chemical profiles across sites, while industrial, HOC, and crustal sources displayed significant site-specific variability. These findings underscore the need for tailored air quality strategies according to local sources of emissions and the importance of long-term PM speciation monitoring for effective pollution control.

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Publication Details

Journal
npj Climate and Atmospheric Science
Published
2025-07-05
DOI
https://doi.org/10.1038/s41612-025-01097-7
Citations
8
Primary Topic
Air Quality and Health Impacts
Type
article
Field-Weighted Citation Impact
9.60

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article

Source apportionment of PM10 based on offline chemical speciation data at 24 European sites

Olivier Favez, S. Nava, Sébastien Conil, Christoph Hueglin et al.
8 citations
npj Climate and Atmospheric Science
Air Quality and Health Impacts
9.60
article

Source apportionment of PM10 based on offline chemical speciation data at 24 European sites

Olivier Favez, S. Nava, Sébastien Conil, Christoph Hueglin, Maria I. Gini, Giulia Calzolai, Andrés Alástuey, Roy M. Harrison, Siyuan Qian, Sophie Darfeuil, Sonia Castillo, Gaëlle Uzu, Evangelia Diapouli, Xavier Querol, Jean‐Luc Jaffrezo, Cristina Reche, Stuart K. Grange, Nicolas Marchand, Konstantinos Eleftheriadis, Manousos-Ioannis Manousakas, Jesús de la Rosa, Vy Dinh Ngoc Thuy, Philip Karl Hopke, Célia Alves, Xiansheng Liu, Pamela Dominutti, Tao Wang, Jin Zou, Marta Monge, Bowen Jin, Xun Zhang
article en
8 citations

Abstract

This study applied Positive Matrix Factorization (PMF) to PM10 speciation datasets from 24 urban sites across six European countries (France, Greece, Italy, Portugal, Spain, and Switzerland) to perform a detailed source apportionment (SA) analysis. By using a consistent source apportionment tool for all datasets, the study enhances the comparability of PM10 SA results across urban Europe. The results identified seven major PM10 sources including road traffic, biomass burning, crustal/mineral sources, secondary aerosols, industrial emissions, sea salt, and heavy oil combustion (HOC). Road traffic emerged as the predominant source of PM10 in urban areas, with contributions varying by location, but representing as much as 41% in high-traffic zones. Biomass burning was detected at 23 sites, contributing 8% to 41% on yearly averages, with substantial increase in winter. Crustal sources were present at all sites (3–33%). Industrial sources contributed relatively less PM10 mass, which was identified at 10 sites with contributions ranging from 2% to 14%. Secondary inorganic and organic aerosol, consisting primarily of ammonium nitrates and sulfates, and organic matter, formed a portion of the PM10 mass (5–41%). These secondary factors are primarily influenced by anthropogenic emissions, including the various combustion processes. Sea salt, predominantly found in coastal areas, contributed between 4% and 21%, reflecting the impact of the marine environments on air quality. This source was very often ‘aged’ (mixed with anthropogenic pollutants from different origins). Additionally, HOC, especially emits from shipping activities, and traced by V and Ni, was also a frequent contributing source (2–15% for 9 sites), indicating a need for more stringent emission controls. The chemical comparison is performed which indicates road traffic and secondary aerosols, showed consistent chemical profiles across sites, while industrial, HOC, and crustal sources displayed significant site-specific variability. These findings underscore the need for tailored air quality strategies according to local sources of emissions and the importance of long-term PM speciation monitoring for effective pollution control.

npj Climate and Atmospheric ScienceVol. 8(1)
Institut polytechnique de Grenoble (FR), École de l'air et de l'espace (FR), Centre National de la Recherche Scientifique (FR), Guangdong University of Technology (CN), Clarkson University (US), Universidad de Granada (ES), Beijing Technology and Business University (CN), National Centre of Scientific Research "Demokritos" (GR), Fudan University (CN), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Instituto Andaluz de Ciencias de la Tierra (ES), Beijing Academy of Artificial Intelligence (CN), Xinjiang Institute of Engineering (CN), École des Métiers de l’Environnement (FR), Institut des Géosciences de l'Environnement (FR), Institut national de l'environnement industriel et des risques (FR), Agence Nationale pour la Gestion des Déchets Radioactifs (FR), Institute of Environmental Assessment and Water Research (ES), Beijing Municipal Education Commission (CN), Institut de Recherche pour le Développement (FR), University of Florence (IT), University of Rochester (US), University of Aveiro (PT), Swiss Federal Laboratories for Materials Science and Technology (CH), Universidad de Huelva (ES), University of Birmingham (GB), Université Grenoble Alpes (FR)
Universidade de Aveiro, Fondation Université Grenoble Alpes, European Commission, Agence Nationale de la Recherche, National Natural Science Foundation of China, Generalitat de Catalunya, Ministry of Environment, Ministerio de Ciencia e Innovación, Ministério da Ciência, Tecnologia e Ensino Superior, State Key Laboratory of Resources and Environmental Information System, Région Normandie, Centro de Estudos Ambientais e Marinhos, Universidade de Aveiro, Fundação para a Ciência e a Tecnologia, Agència de Gestió d'Ajuts Universitaris i de Recerca, Agencia Estatal de Investigación
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Openalex Percentile: Top 2%
Air Quality and Health Impacts
9.60
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