Modelling of atmospheric copper, iron, and manganese over Europe
Although the adverse health effects of particulate matter (PM) are often considered in terms of mass and particle size, a growing number of studies now focus on new health metrics such as the oxidative potential (OP) of PM, highlighting the role of certain metals, among them copper (Cu), iron (Fe),...
| Autores: | , , , , , , , , , , , , , , , , , , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2026 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/421733 |
| Acceso en línea: | http://hdl.handle.net/10261/421733 https://api.elsevier.com/content/abstract/scopus_id/105030661205 |
| Access Level: | acceso abierto |
| Palabra clave: | Copper Iron Manganese Particulate matter (PM) Health risks http://metadata.un.org/sdg/9 http://metadata.un.org/sdg/12 http://metadata.un.org/sdg/6 http://metadata.un.org/sdg/11 http://metadata.un.org/sdg/17 http://metadata.un.org/sdg/3 Ensure healthy lives and promote well-being for all at all ages Ensure availability and sustainable management of water and sanitation for all Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation Make cities and human settlements inclusive, safe, resilient and sustainable Ensure sustainable consumption and production patterns Strengthen the means of implementation and revitalize the Global Partnership for Sustainable Development |
| Sumario: | Although the adverse health effects of particulate matter (PM) are often considered in terms of mass and particle size, a growing number of studies now focus on new health metrics such as the oxidative potential (OP) of PM, highlighting the role of certain metals, among them copper (Cu), iron (Fe), and manganese (Mn) for their capacity to impact OP levels in ambient air. In this study, we built on a previously-developed European anthropogenic emission inventory for Cu, Fe and Mn to simulate PM<inf>10</inf> concentrations of these metals within PM<inf>10</inf> during a two-year period with the WRF-CHIMERE chemistry transport model, applying a source-tagging method. We also estimated the contribution of erosion dust (mostly of African origin) and urban dust (mostly road and construction dust) as significant sources for each of these metals. For validation purpose, we compared the simulation results with a large database of measurements collected from various sources and locations. The medians of the fractional mean biases for Cu are close to zero for both rural and urban background sites, indicating that the emission in the inventory adequately represent atmospheric Cu concentrations. However, the biases are highly negative for Fe and Mn in a simulation when only considering anthropogenic emissions. The correlation coefficients obtained for (rural and urban) background stations range from 0.4 to 0.6, with urban sites showing slightly higher correlations for Fe but slightly lower ones for Cu and Mn. The inclusion of desert dust sources improves the correlation for some rural stations, while including local urban dust has a less pronounced effect. However, neither source fully explains the significant biases for Fe and Mn concentrations. Overall, this study calls for further works to try and elucidate the missing sources of Fe and Mn, revisit our previously developed emission inventory, and refine the share of PM resuspension to ambient air concentrations of key metallic compounds. |
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