Author, as appears in the article.: Plasencia Sánchez E; Sánchez-Soberón F; Rovira J; Sierra J; Schuhmacher M; Soler A; Torrentó C; Rosell M
Department: Enginyeria Química Ciències Mèdiques Bàsiques
URV's Author/s: Rovira Solano, Joaquim / SÁNCHEZ SOBERÓN, FRANCISCO / Schuhmacher Ansuategui, Marta
Keywords: Tarragona Stable isotopes Pm2.5 Pm10 Pm1 Mixing models Ambient air-pollution tarragona stable isotopes stable carbon pm2 pm1 particulate matter nitrogen isotopes mixing models metropolitan-area main components human health human exposure chemical-characterization atmospheric particles 5
Abstract: Identification of dominant airborne Particulate Matter (PM) sources is essential for maintaining high air quality standards and thus ensuring a good public health. In this study, different approaches were applied for source apportionment of three PM fractions (PM1, PM2.5 and PM10) at the outdoor of 14 schools of a coastal city with a significant land use interweaving such as Tarragona (Spain). PM were collected in 24h-quartz microfiber filters in two seasonal campaigns (cold and warm), together with nine local potential sources, so a total of 84 samples were chemically, mineralogically, and isotopically characterised. Source apportionment was assessed by (i) main chemical components, (ii) Principal Component Analysis (PCA), (iii) dual C and N isotope approach, and (iv) a Bayesian isotope mixing model. When chemical concentrations were grouped into marine, crustal, secondary inorganic aerosols and organic matter + elemental carbon categories, the unaccounted component reached 45% of PM mass. The PCA allowed to identify also traffic and industrial contributions, reducing the unaccounted mass to about 25%. Adding δ13C and δ15N values, secondary organic aerosol could be estimated and a continuous contribution of diesel combustion was identified together with a remarkable use of natural gas in winter. Isotopic values were better understood when considering air masses back trajectories and a possible long-distance contribution from coal-fired electric generating units (EGUs). Finally, using Bayesian dual isotope mixing models, the unaccounted PM mass was reduced up to 5% when adding these EGUs to marine-carbonate related, road traffic, domestic heating, waste incinerator and livestock waste contributions. The added value of the dual isotope approach combined with a Bayesian isotope mixing model, in comparison with conventional chemical approaches, was thus demonstrated for PM source apportionment in an urban and industrial site where many sources and processes converge and can then be applied to other complex cities.
Thematic Areas: Saúde coletiva Química Meteorology & atmospheric sciences Medicina ii Medicina i Materiais Matemática / probabilidade e estatística Interdisciplinar Geografía Geociências General environmental science Farmacia Environmental sciences Environmental science (miscellaneous) Environmental science (all) Engenharias iv Engenharias iii Engenharias ii Engenharias i Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências ambientais Ciências agrárias i Biotecnología Biodiversidade Atmospheric science Astronomia / física
licence for use: https://creativecommons.org/licenses/by/3.0/es/
Author's mail: joaquim.rovira@urv.cat marta.schuhmacher@urv.cat
Author identifier: 0000-0003-4399-6138 0000-0003-4381-2490
Record's date: 2024-08-03
Papper version: info:eu-repo/semantics/publishedVersion
Link to the original source: https://www.sciencedirect.com/science/article/pii/S1352231022005143?via%3Dihub
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Papper original source: Atmospheric Environment. 293 (119449): 119449-
APA: Plasencia Sánchez E; Sánchez-Soberón F; Rovira J; Sierra J; Schuhmacher M; Soler A; Torrentó C; Rosell M (2023). Integrating dual C and N isotopic approach to elemental and mathematical solutions for improving the PM source apportionment in complex urban and industrial cities: Case of Tarragona - Spain. Atmospheric Environment, 293(119449), 119449-. DOI: 10.1016/j.atmosenv.2022.119449
Article's DOI: 10.1016/j.atmosenv.2022.119449
Entity: Universitat Rovira i Virgili
Journal publication year: 2023
Publication Type: Journal Publications
Repositori URV