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- ItemLong-range and local air pollution: What can we learn from chemical speciation of particulate matter at paired sites?(Katlenburg-Lindau : EGU, 2020) Pandolfi, Marco; Mooibroek, Dennis; Hopke, Philip; van Pinxteren, Dominik; Querol, Xavier; Herrmann, Hartmut; Alastuey, Andrés; Favez, Olivier; Hüglin, Christoph; Perdrix, Esperanza; Riffault, Véronique; Sauvage, Stéphane; van der Swaluw, Eric; Tarasova, Oksana; Colette, AugustinHere we report results of a detailed analysis of the urban and non-urban contributions to particulate matter (PM) concentrations and source contributions in five European cities, namely Schiedam (the Netherlands, NL), Lens (France, FR), Leipzig (Germany, DE), Zurich (Switzerland, CH) and Barcelona (Spain, ES). PM chemically speciated data from 12 European paired monitoring sites (one traffic, five urban, five regional and one continental background) were analysed by positive matrix factorisation (PMF) and Lenschow's approach to assign measured PM and source contributions to the different spatial levels. Five common sources were obtained at the 12 sites: sulfate-rich (SSA) and nitrate-rich (NSA) aerosols, road traffic (RT), mineral matter (MM), and aged sea salt (SS). These sources explained from 55 % to 88 % of PM mass at urban low-traffic-impact sites (UB) depending on the country. Three additional common sources were identified at a subset of sites/countries, namely biomass burning (BB) (FR, CH and DE), explaining an additional 9 %-13 % of PM mass, and residual oil combustion (V-Ni) and primary industrial (IND) (NL and ES), together explaining an additional 11 %-15 % of PM mass. In all countries, the majority of PM measured at UB sites was of a regional+continental (R+C) nature (64 %-74 %). The R+C PM increments due to anthropogenic emissions in DE, NL, CH, ES and FR represented around 66 %, 62 %, 52 %, 32 % and 23 %, respectively, of UB PM mass. Overall, the R+C PM increments due to natural and anthropogenic sources showed opposite seasonal profiles with the former increasing in summer and the latter increasing in winter, even if exceptions were observed. In ES, the anthropogenic R+C PM increment was higher in summer due to high contributions from regional SSA and V-Ni sources, both being mostly related to maritime shipping emissions at the Spanish sites. Conversely, in the other countries, higher anthropogenic R+C PM increments in winter were mostly due to high contributions from NSA and BB regional sources during the cold season. On annual average, the sources showing higher R+C increments were SSA (77 %-91 % of SSA source contribution at the urban level), NSA (51 %-94 %), MM (58 %-80 %), BB (42 %-78 %) and IND (91 % in NL). Other sources showing high R+C increments were photochemistry and coal combustion (97 %-99 %; identified only in DE). The highest regional SSA increment was observed in ES, especially in summer, and was related to ship emissions, enhanced photochemistry and peculiar meteorological patterns of the Western Mediterranean. The highest R+C and urban NSA increments were observed in NL and associated with high availability of precursors such as NOx and NH3. Conversely, on average, the sources showing higher local increments were RT (62 %-90 % at all sites) and V-Ni (65 %-80 % in ES and NL). The relationship between SSA and V-Ni indicated that the contribution of ship emissions to the local sulfate concentrations in NL has strongly decreased since 2007 thanks to the shift from high-sulfur-to low-sulfur-content fuel used by ships. An improvement of air quality in the five cities included here could be achieved by further reducing local (urban) emissions of PM, NOx and NH3 (from both traffic and non-traffic sources) but also SO2 and PM (from maritime ships and ports) and giving high relevance to non-urban contributions by further reducing emissions of SO2 (maritime shipping) and NH3 (agriculture) and those from industry, regional BB sources and coal combustion. © 2020 Copernicus GmbH. All rights reserved.
- ItemAerosol activation characteristics and prediction at the central European ACTRIS research station of Melpitz, Germany(Katlenburg-Lindau : EGU, 2022) Wang, Yuan; Henning, Silvia; Poulain, Laurent; Lu, Chunsong; Stratmann, Frank; Wang, Yuying; Niu, Shengjie; Pöhlker, Mira L.; Herrmann, Hartmut; Wiedensohler, AlfredUnderstanding aerosol particle activation is essential for evaluating aerosol indirect effects (AIEs) on climate. Long-term measurements of aerosol particle activation help to understand the AIEs and narrow down the uncertainties of AIEs simulation. However, they are still scarce. In this study, more than 4 years of comprehensive aerosol measurements were utilized at the central European research station of Melpitz, Germany, to gain insight into the aerosol particle activation and provide recommendations on improving the prediction of number concentration of cloud condensation nuclei (CCN, NCCN). (1) The overall CCN activation characteristics at Melpitz are provided. As supersaturation (SS) increases from 0.1% to 0.7%, the median NCCN increases from 399 to 2144cm-3, which represents 10% to 48% of the total particle number concentration with a diameter range of 10-800nm, while the median hygroscopicity factor (κ) and critical diameter (Dc) decrease from 0.27 to 0.19 and from 176 to 54nm, respectively. (2) Aerosol particle activation is highly variable across seasons, especially at low-SS conditions. At SSCombining double low line0.1%, the median NCCN and activation ratio (AR) in winter are 1.6 and 2.3 times higher than the summer values, respectively. (3) Both κ and the mixing state are size-dependent. As the particle diameter (Dp) increases, κ increases at Dp of 1/440 to 100nm and almost stays constant at Dp of 100 to 200nm, whereas the degree of the external mixture keeps decreasing at Dp of 1/440 to 200nm. The relationships of κ vs. Dp and degree of mixing vs. Dp were both fitted well by a power-law function. (4) Size-resolved κ improves the NCCN prediction. We recommend applying the κ-Dp power-law fit for NCCN prediction at Melpitz, which performs better than using the constant κ of 0.3 and the κ derived from particle chemical compositions and much better than using the NCCN (AR) vs. SS relationships. The κ-Dp power-law fit measured at Melpitz could be applied to predict NCCN for other rural regions. For the purpose of improving the prediction of NCCN, long-term monodisperse CCN measurements are still needed to obtain the κ-Dp relationships for different regions and their seasonal variations.