PM10 chemical fingerprints and source assessment guiding air quality improvements by 2030 in Andalusia, southern Spain
This study focuses on the evaluation of 2021–2023 PM10 concentrations, chemical speciation and source apportionment (with receptor modelling) of samples collected at 21 air quality monitoring stations (urban, urban-industrial, traffic hotspots and rural) from Andalusia (southern Spain). After subtra...
| Autores: | , , , , , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2026 |
| País: | España |
| Institución: | Universidad de Huelva (UHU) |
| Repositorio: | Arias Montano. Repositorio Institucional de la Universidad de Huelva |
| Idioma: | inglés |
| OAI Identifier: | oai:ariasmontano.uhu.es:10272/28039 |
| Acceso en línea: | https://hdl.handle.net/10272/28039 |
| Access Level: | acceso abierto |
| Palabra clave: | Air pollution Air quality policy Air quality standards Receptor modelling Source apportionment 2509.02 Contaminación Atmosférica 3308.01 Control de la Contaminación Atmosférica |
| Sumario: | This study focuses on the evaluation of 2021–2023 PM10 concentrations, chemical speciation and source apportionment (with receptor modelling) of samples collected at 21 air quality monitoring stations (urban, urban-industrial, traffic hotspots and rural) from Andalusia (southern Spain). After subtracting the natural dust contribution, 9/21 sites would exceed the annual PM10 limit value of 20 μg m−3 set by the new Ambient Air Quality Directive (EU) 2024/2881. Source apportionment analysis carried out with PMF identified six major sources of PM10: Crustal, Marine, Combustion (biomass burning and traffic mix), Traffic, Regional and Industrial. The main anthropogenic source was Combustion, with the exception of those stations located in cities with a high road traffic density, where Traffic was the dominant anthropogenic source. To comply with the objectives of the Directive (EU) 2024/2881, a reduction of 5–50 % in anthropogenic sources is proposed, based on the sum of their interannual mean concentrations at the nine potentially non-compliance sites. The study evidences the complexity of separating specific source contributions of PM10, highlighting the need to conduct higher time resolution studies to better identify and quantify source contributions and their temporal variations, as well as the need to combine deterministic and receptor modelling for a complete source apportionment, specially of secondary PM contributions. |
|---|