Long range and local air pollution: what can we learn from chemical speciation of particulate matter at paired sites?

Abstract

<p><strong>Abstract.</strong> We report here results of a detailed analysis of the urban and non-urban contributions to PM concentrations and source contributions in 5 European cities, namely: Shiedam (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 (1 traffic, 5 urban, 5 regional and 1 continental background) were analyzed by Positive Matrix Factorization (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: <i>sulfate-rich</i> (SSA) and <i>nitrate-rich</i> (NSA) aerosols, <i>road traffic</i> (RT), <i>mineral matter</i> (MM), and <i>sea salt</i> (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 detected at a subset of sites/countries, namely: <i>biomass burning</i> (BB) (FR, CH, and DE), explaining an additional 9–13 % of PM mass, <i>residual oil combustion</i> (V-Ni), and <i>primary industrial</i> (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 regional + continental (R + C) nature (64–74 %). The R + C PM increments due to anthropogenic emissions were in the range 10–11 μg/m<sup>3</sup> in CH, NL and DE (52 %, 62 % and 66 %, respectively, of UB PM mass), followed by ES (8 g/m<sup>3</sup>; 32 %) and FR (5 g/m<sup>3</sup>; 23 %). 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 urban level), NSA (51–94 %), MM (58–80 %), BB (42–78 %), IND (91 % in the Netherlands). Other sources showing high R + C increments were photochemistry (PHO) and coal combustion (CC) (97–99 %; detected 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 NO<sub>x</sub> and NH<sub>3</sub>. 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 strongly decreased from 2007 thanks to the shift from high-sulfur to low-sulfur content fuel used by ships. Based on the present analysis, an improvement of air quality in the 5 cities included here could be achieved by further reducing local (urban) emissions of PM, NO<sub>x</sub> and NH<sub>3</sub> (from both traffic and non-traffic sources) but also SO<sub>2</sub> and PM (from maritime ships and ports) and giving high relevance to non-urban contributions by further reducing emissions of SO<sub>2</sub> (maritime shipping) and NH<sub>3</sub> (agriculture) and those from industry, regional BB sources and coal combustion.</p>

Disparities in particulate matter (PM<sub>10</sub>) origins and oxidative potential at a city scale (Grenoble, France) – Part 1: Source apportionment at three neighbouring sites

“…Figure 4 presents a comparison of the source contributions in each site based on mass concentration (in µg m −3 ). These results are in line with recent studies leading to anthropogenic and SOA sources heavily influencing urban air pollution in western Europe (Daellenbach et al, 2019;Pandolfi et al, 2020;Srivastava et al, 2018b;Weber et al, 2019). The most notable difference across all sites is the sharp decrease in mineral dust in Vif compared to the other two urban sites, and this is discussed further in Sect.…”

“…Investigating the PM oxidative potential (OP) in light of its major emission sources in various urban environments can then provide valuable information to instigate air pollution abatement policies limiting health outcomes. However, spatially resolved PM source apportionment at a city scale remains a challenging task (Dai et al, 2020a, b;Pandolfi et al, 2020).…”

Global review of recent source apportionments for airborne particulate matter

“…The sulfate may not appear clearly in the “diesel” profile since the variations in sulfate can be fully subsumed by the “sulfate” factor. However, the relationship with the primary emissions can be observed in the g-space plots ( Kim and Hopke, 2008 : Pandolfi et al, 2020 ) and adds to the total impact of the primary source.…”

Discovering Oxidative Potential (Op) Drivers of Atmospheric Pm10, Pm2.5, and Pm1 Simultaneously in North-Eastern Spain

“…To improve the robustness of our PMF model, a multisite solution was used by aggregating the BCN and MSY data into a single dataset for each PM size. Previous research has shown the feasibility of applying a multisite PMF to PM 10 and PM 2.5 in the same study area (in 't Veld et al, 2021;Pandolfi et al, 2020). Applying the multisite solution did not, however, result in an adequate solution.…”

“…A considerable amount of previous research has been performed in the study area regarding sources of PM 10 , PM 2.5 , and PM 1 (Amato et al, 2009b(Amato et al, , 2016Brines et al, 2019;in 't Veld et al, 2021;Minguillón et al, 2011;Moreno et al, 2011;Pandolfi et al, 2016Pandolfi et al, , 2020Pérez et al, 2016;Querol et al, 2007;Reche et al, 2012;Viana et al, 2013). This extensive research, which has applied PMF for all PM sizes, has separately identified the same sources for all PM sizes.…”