scholarly journals Source apportionment of fine particulate matter in Houston, Texas: insights to secondary organic aerosols

2018 ◽  
Vol 18 (21) ◽  
pp. 15601-15622 ◽  
Author(s):  
Ibrahim M. Al-Naiema ◽  
Anusha P. S. Hettiyadura ◽  
Henry W. Wallace ◽  
Nancy P. Sanchez ◽  
Carter J. Madler ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Molecular Marker ◽  
Source Apportionment ◽  
Diesel Engines ◽  
Organic Aerosol ◽  
Anthropogenic Sources ◽  
Motor Vehicles ◽  
Ship Emissions ◽  
Gasoline Engines ◽  
Primary Emissions

Abstract. Online and offline measurements of ambient particulate matter (PM) near the urban and industrial Houston Ship Channel in Houston, Texas, USA, during May 2015 were utilized to characterize its chemical composition and to evaluate the relative contributions of primary, secondary, biogenic, and anthropogenic sources. Aerosol mass spectrometry (AMS) on nonrefractory PM1 (PM ≤ 1 µm) indicated major contributions from sulfate (averaging 50 % by mass), organic aerosol (OA, 40 %), and ammonium (14 %). Positive matrix factorization (PMF) of AMS data categorized OA on average as 22 % hydrocarbon-like organic aerosol (HOA), 29 % cooking-influenced less-oxidized oxygenated organic aerosol (CI-LO-OOA), and 48 % more-oxidized oxygenated organic aerosol (MO-OOA), with the latter two sources indicative of secondary organic aerosol (SOA). Chemical analysis of PM2.5 (PM ≤ 2.5 µm) filter samples agreed that organic matter (35 %) and sulfate (21 %) were the most abundant components. Organic speciation of PM2.5 organic carbon (OC) focused on molecular markers of primary sources and SOA tracers derived from biogenic and anthropogenic volatile organic compounds (VOCs). The sources of PM2.5 OC were estimated using molecular marker-based positive matric factorization (MM-PMF) and chemical mass balance (CMB) models. MM-PMF resolved nine factors that were identified as diesel engines (11.5 %), gasoline engines (24.3 %), nontailpipe vehicle emissions (11.1 %), ship emissions (2.2 %), cooking (1.0 %), biomass burning (BB, 10.6 %), isoprene SOA (11.0 %), high-NOx anthropogenic SOA (6.6 %), and low-NOx anthropogenic SOA (21.7 %). Using available source profiles, CMB apportioned 41 % of OC to primary fossil sources (gasoline engines, diesel engines, and ship emissions), 5 % to BB, 15 % to SOA (including 7.4 % biogenic and 7.6 % anthropogenic), and 39 % to other sources that were not included in the model and are expected to be secondary. This study presents the first application of in situ AMS-PMF, MM-PMF, and CMB for OC source apportionment and the integration of these methods to evaluate the relative roles of biogenic, anthropogenic, and BB-SOA. The three source apportionment models agreed that ∼ 50 % of OC is associated with primary emissions from fossil fuel use, particularly motor vehicles. Differences among the models reflect their ability to resolve sources based upon the input chemical measurements, with molecular marker-based methods providing greater source specificity and resolution for minor sources. By combining results from MM-PMF and CMB, BB was estimated to contribute 11 % of OC, with 5 % primary emissions and 6 % BB-SOA. SOA was dominantly anthropogenic (28 %) rather than biogenic (11 %) or BB-derived. The three-model approach demonstrates significant contributions of anthropogenic SOA to fine PM. More broadly, the findings and methodologies presented herein can be used to advance local and regional understanding of anthropogenic contributions to SOA.

scholarly journals Source apportionment of fine particulate matter in Houston, Texas: Insights to secondary organic aerosols

2018 ◽  
Author(s):  
Ibrahim M. Al-Naiema ◽  
Anusha P. S. Hettiyadura ◽  
Henry W. Wallace ◽  
Nancy P. Sanchez ◽  
Carter J. Madler ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Molecular Marker ◽  
Source Apportionment ◽  
Diesel Engines ◽  
Fine Particulate Matter ◽  
Organic Aerosol ◽  
Ship Emissions ◽  
Gasoline Engines ◽  
Fine Particulate ◽  
Primary Emissions

Abstract. Online and offline measurements of fine particulate matter (PM) near the urban and industrial Houston Ship Channel in Houston, Texas, USA during May 2015 were utilized to characterize its chemical composition and to evaluate the relative contributions of primary, secondary, biogenic, and anthropogenic sources. Aerosol mass spectrometry (AMS) on non-refractory PM1 (PM ≤ 1 µm) indicated major contributions from sulfate (averaging 50 %), organic aerosol (OA, 40 %), and ammonium (14 %). Positive matrix factorization (PMF) of AMS data categorized OA on average as 22 % hydrocarbon-like organic aerosol (HOA), 29 % cooking influenced semi-volatile oxygenated organic aerosol (CI-SV-OOA), and 48 % low-volatility oxygenated organic aerosol (LV-OOA), with the latter two sources indicative of secondary organic aerosol (SOA). Chemical analysis of PM2.5 (PM ≤ 2.5 µm) filter samples agreed that organic matter (35 %) and sulfate (21 %) were the most abundant components. Organic speciation of PM2.5 organic carbon (OC) focused on molecular markers of primary sources and SOA tracers derived from biogenic and anthropogenic volatile organic compounds (VOC). The sources of PM2.5 OC were estimated using molecular marker-based positive matric factorization (MM-PMF) and chemical mass balance (CMB) models. MM-PMF resolved 9 factors that were identified as diesel engines (11.5 %), gasoline engines (24.3 %), non-tailpipe vehicle emissions (11.1 %), ship emissions (2.2 %), cooking (1.0 %), biomass burning (BB, 10.6 %), isoprene SOA (11.0 %), high-NOx anthropogenic SOA (6.6 %), and low-NOx anthropogenic SOA (21.7 %). Using available source profiles, CMB apportioned 41 % of OC to primary fossil sources (gasoline engines, diesel engines, and ship emissions), 5 % to BB, 15 % to SOA (including 7.4 % biogenic and 7.6 % anthropogenic), and 39 % to other sources that were not included in the model and are expected to be secondary. This study presents the first application of in situ AMS-PMF, MM-PMF, and CMB for OC source apportionment and the integration of these methods to evaluate the relative roles of biogenic, anthopogenic, and BB-SOA. The three source apportionment models agreed that ~ 50 % of OC is associated with primary emissions from fossil fuel use, particularly motor vehicles. Differences among the models reflect their ability to resolve sources based upon the input chemical measurements, with molecular marker-based methods providing greater source specificity and resolution for minor sources. By combining results from MM-PMF and CMB, BB was estimated to contribute 11 % of OC, with 5 % of primary emissions and 6 % BB-SOA. SOA was dominantly anthropogenic (28 %) compared to biogenic (11 %) or BB-derived. The three-model approach demonstrates significant contributions of anthropogenic SOA to fine PM. More broadly, the findings and methodologies presented herein can be used to advance local and regional understanding of anthropogenic contributions to SOA.

scholarly journals Primary sources of PM<sub>2.5</sub> organic aerosol in an industrial Mediterranean city, Marseille

2010 ◽  
Vol 10 (11) ◽  
pp. 25435-25490 ◽  
Author(s):  
I. El Haddad ◽  
N. Marchand ◽  
H. Wortham ◽  
C. Piot ◽  
J.-L. Besombes ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Ultrafine Particles ◽  
Organic Aerosol ◽  
Submicron Particles ◽  
Anthropogenic Sources ◽  
Primary Sources ◽  
Motor Vehicles ◽  
Accurate Estimation ◽  
Special Focus ◽  
Industrial Emissions

Abstract. Marseille, the most important port of the Mediterranean Sea, represents a challenging case study for source apportionment exercises, combining an active photochemistry and multiple emission sources, including fugitive emissions from industrial sources and shipping. This paper presents a Chemical Mass Balance (CMB) approach based on organic markers and metals to apportion the primary sources of organic aerosol in Marseille, with a special focus on industrial emissions. Overall, the CMB model accounts for the major primary anthropogenic sources including motor vehicles, biomass burning, and the aggregate emissions from three industrial processes (HFO combustion/shipping, coke production and steel manufacturing) as well as some primary biogenic emissions. This source apportionment exercise is well corroborated by 14C measurements. Primary OC estimated by the CMB accounts on average for 22% and is dominated by the vehicular emissions that contribute on average for 17% of OC mass concentration (17% of PM2.5). Even though, industrial emissions contribute for only 2.3% of the total OC (7% of PM2.5), they are associated with ultrafine particles (Dp<80 nm) and high concentrations of Polycyclic Aromatic Hydrocarbons (PAH) and heavy metals such as Pb, Ni and V. On one hand, given that industrial emissions governed key primary markers, their omission would lead to substantial uncertainties in the CMB analysis performed in areas heavily impacted by such sources, hindering accurate estimation of non-industrial primary sources and secondary sources. This result implies that CMB modelling should not be a straightforward exercise and one have to carefully investigate the marker behaviours and trends beforehand, especially in complex environments such as Marseille. On the other hand, being associated with bursts of submicron particles and carcinogenic and mutagenic components such as PAH, these emissions are most likely related with acute health outcomes and should be regulated despite their small contributions to OC. Another important result is the fact that 78% of OC mass cannot be attributed to the major primary sources and thus remains un-apportioned. We have consequently critically investigated the uncertainties underlying our CMB apportionments. While we have provided some evidence for photochemical decay of hopanes, this decay does not appear to significantly alter the CMB estimates of the total primary OC. Sampling artefacts and unaccounted primary sources also appear to marginally influence the amount of un-apportioned OC. Therefore, this significant amount of un-apportioned OC is mostly attributed to secondary organic carbon that appears to be the major component of OC, during the whole period of study.

scholarly journals Organic aerosol source apportionment by offline-AMS over a full year in Marseille

2017 ◽  
Author(s):  
Carlo Bozzetti ◽  
Imad El Haddad ◽  
Dalia Salameh ◽  
Kaspar Rudolf Daellenbach ◽  
Paola Fermo ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Mediterranean Sea ◽  
Source Apportionment ◽  
Organic Aerosol ◽  
Aerodynamic Diameter ◽  
Aerosol Mass Spectrometer ◽  
Aerosol Mass ◽  
Aerosol Source

Abstract. We investigated the seasonal trends of OA sources affecting the air quality of Marseille (France) which is the largest harbor of the Mediterranean Sea. This was achieved by measurements of nebulized filter extracts using an aerosol mass spectrometer (offline-AMS). PM2.5 (particulate matter with an aerodynamic diameter

scholarly journals Mass spectral characterization of primary emissions and implications in source apportionment of organic aerosol

2020 ◽  
Vol 13 (6) ◽  
pp. 3205-3219 ◽  
Author(s):  
Weiqi Xu ◽  
Yao He ◽  
Yanmei Qiu ◽  
Chun Chen ◽  
Conghui Xie ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Spectral Characteristics ◽  
Organic Aerosol ◽  
Water Soluble ◽  
Spectral Characterization ◽  
Rural Site ◽  
Spectral Features ◽  
Mass Spectral ◽  
Spectral Profiles ◽  
Primary Emissions

Abstract. Source apportionment of organic aerosol (OA) from aerosol mass spectrometer (AMS) or aerosol chemical speciation monitor (ACSM) measurements relies largely upon mass spectral profiles from different source emissions. However, the changes in mass spectra of primary emissions from AMS–ACSM with the newly developed capture vaporizer (CV) are poorly understood. Here we conducted 21 cooking, crop straw, wood, and coal burning experiments to characterize the mass spectral features of OA and water-soluble OA (WSOA) using SV-AMS and CV-ACSM. Our results show overall similar spectral characteristics between SV-AMS and CV-ACSM for different primary emissions despite additional thermal decomposition in CV, and the previous spectral features for diagnostics of primary OA factors are generally well retained. However, the mass spectral differences between OA and WSOA can be substantial for both SV-AMS and CV-ACSM. The changes in f55 (fraction of m∕z 55 in OA) vs. f57, f44 vs. f60, and f44 vs. f43 in CV-ACSM are also observed, yet the evolving trends are similar to those of SV-AMS. By applying the source spectral profiles to a winter CV-ACSM study at a highly polluted rural site in the North China Plain, the source apportionment of primary OA was much improved, highlighting the two most important primary sources of biomass burning and coal combustion (32 % and 21 %). Considering the rapidly increasing deployments of CV-ACSM and WSOA studies worldwide, the mass spectral characterization has significant implications by providing essential constraints for more accurate source apportionment and making better strategies for air pollution control in regions with diverse primary emissions.

scholarly journals Primary emissions versus secondary formation of fine particulate matter in the most polluted city (Shijiazhuang) in North China

2019 ◽  
Vol 19 (4) ◽  
pp. 2283-2298 ◽  
Author(s):  
Ru-Jin Huang ◽  
Yichen Wang ◽  
Junji Cao ◽  
Chunshui Lin ◽  
Jing Duan ◽  
...  
Keyword(s):  
Particulate Matter ◽  
North China ◽  
Fine Particulate Matter ◽  
Mass Range ◽  
Organic Aerosol ◽  
Average Mass ◽  
Episodic Events ◽  
Secondary Formation ◽  
Primary Emissions ◽  
Pollution Events

Abstract. Particulate matter (PM) pollution is a severe environmental problem in the Beijing–Tianjin–Hebei (BTH) region in North China. PM studies have been conducted extensively in Beijing, but the chemical composition, sources, and atmospheric processes of PM are still relatively less known in nearby Tianjin and Hebei. In this study, fine PM in urban Shijiazhuang (the capital of Hebei Province) was characterized using an Aerodyne quadrupole aerosol chemical speciation monitor (Q-ACSM) from 11 January to 18 February in 2014. The average mass concentration of non-refractory submicron PM (diameter <1 µm, NR-PM1) was 178±101 µg m−3, and it was composed of 50 % organic aerosol (OA), 21 % sulfate, 12 % nitrate, 11 % ammonium, and 6 % chloride. Using the multilinear engine (ME-2) receptor model, five OA sources were identified and quantified, including hydrocarbon-like OA from vehicle emissions (HOA, 13 %), cooking OA (COA, 16 %), biomass burning OA (BBOA, 17 %), coal combustion OA (CCOA, 27 %), and oxygenated OA (OOA, 27 %). We found that secondary formation contributed substantially to PM in episodic events, whereas primary emissions were dominant (most significant) on average. The episodic events with the highest NR-PM1 mass range of 300–360 µg m−3 were comprised of 55 % of secondary species. On the contrary, a campaign-average low OOA fraction (27 %) in OA indicated the importance of primary emissions, and a low sulfur oxidation degree (FSO4) of 0.18 even at RH >90 % hinted at insufficient oxidation. These results suggested that in Shijiazhuang in wintertime fine PM was mostly from primary emissions without sufficient atmospheric aging, indicating opportunities for air quality improvement by mitigating direct emissions. In addition, secondary inorganic and organic (OOA) species dominated in pollution events with high-RH conditions, most likely due to enhanced aqueous-phase chemistry, whereas primary organic aerosol (POA) dominated in pollution events with low-RH and stagnant conditions. These results also highlighted the importance of meteorological conditions for PM pollution in this highly polluted city in North China.

scholarly journals Chemical transport model simulations of organic aerosol in southern California: model evaluation and gasoline and diesel source contributions

2017 ◽  
Vol 17 (6) ◽  
pp. 4305-4318 ◽  
Author(s):  
Shantanu H. Jathar ◽  
Matthew Woody ◽  
Havala O. T. Pye ◽  
Kirk R. Baker ◽  
Allen L. Robinson
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Southern California ◽  
Transport Model ◽  
Chemical Transport ◽  
Organic Aerosol ◽  
Production Model ◽  
Anthropogenic Sources ◽  
Chemical Transport Model ◽  
Mobile Sources

Abstract. Gasoline- and diesel-fueled engines are ubiquitous sources of air pollution in urban environments. They emit both primary particulate matter and precursor gases that react to form secondary particulate matter in the atmosphere. In this work, we updated the organic aerosol module and organic emissions inventory of a three-dimensional chemical transport model, the Community Multiscale Air Quality Model (CMAQ), using recent, experimentally derived inputs and parameterizations for mobile sources. The updated model included a revised volatile organic compound (VOC) speciation for mobile sources and secondary organic aerosol (SOA) formation from unspeciated intermediate volatility organic compounds (IVOCs). The updated model was used to simulate air quality in southern California during May and June 2010, when the California Research at the Nexus of Air Quality and Climate Change (CalNex) study was conducted. Compared to the Traditional version of CMAQ, which is commonly used for regulatory applications, the updated model did not significantly alter the predicted organic aerosol (OA) mass concentrations but did substantially improve predictions of OA sources and composition (e.g., POA–SOA split), as well as ambient IVOC concentrations. The updated model, despite substantial differences in emissions and chemistry, performed similar to a recently released research version of CMAQ (Woody et al., 2016) that did not include the updated VOC and IVOC emissions and SOA data. Mobile sources were predicted to contribute 30–40 % of the OA in southern California (half of which was SOA), making mobile sources the single largest source contributor to OA in southern California. The remainder of the OA was attributed to non-mobile anthropogenic sources (e.g., cooking, biomass burning) with biogenic sources contributing to less than 5 % to the total OA. Gasoline sources were predicted to contribute about 13 times more OA than diesel sources; this difference was driven by differences in SOA production. Model predictions highlighted the need to better constrain multi-generational oxidation reactions in chemical transport models.

scholarly journals Source apportionment of submicron organic aerosol at an urban background and a road site in Barcelona, Spain

2013 ◽  
Vol 13 (4) ◽  
pp. 11167-11211 ◽  
Author(s):  
M. Alier ◽  
B. L. van Drooge ◽  
M. Dall'Osto ◽  
X. Querol ◽  
J. O. Grimalt ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Organic Compounds ◽  
Organic Aerosol ◽  
Oxidation Products ◽  
Anthropogenic Sources ◽  
Multivariate Curve Resolution ◽  
Monitoring Site ◽  
Atmospheric Conditions ◽  
Urban Background ◽  
Air Mass

Abstract. This study investigates the contribution of potential sources to the sub-micron (PM1) organic aerosol (OA) simultaneously detected at an urban background (UB) and a road site (RS) in Barcelona during the 30 days of the intensive field campaign of SAPUSS (Solving Aerosol Problems by Using Synergistic Strategies, September–October 2010). 103 filters at 12 h sampling time resolution were collected at both sites. Thirty-six neutral and polar organic compounds of known emission sources and photo-chemical transformation processes were analyzed by Gas Chromatography-Mass Spectrometry (GC-MS). The concentrations of the trace chemical compounds analyzed are herein presented and discussed. Additionally, OA source apportionment was performed by Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) and six OA components were identified at both sites: two were of primary anthropogenic OA origin, three of secondary OA origin while a sixth one was not clearly defined. Primary organics from emissions of local anthropogenic activities (Urban primary organic aerosol, Urban POA) contributed for 43% (1.5 μg OC m−3) and 18% (0.4 μg OC m−3) to OA in RS and UB, respectively. A secondary primary source – biomass burning (BBOA) – was found in all the samples (average values 7% RS; 12% UB; 0.3 μg OC m−3), but this component was substantially contributing to OA only when the sampling sites were under influence of regional air mass circulation. Three Secondary Organic Aerosol (SOA) components (describing overall 60% of the variance) were observed in the urban ambient PM1. Products of isoprene oxidation (SOA ISO), i.e. 2-methylglyceric acid, C5 alkene triols and 2-methyltetrols, showed the highest abundance at both sites when the city was under influence of inland air masses. The overall concentrations of SOA ISO were similar at both sites (0.4 and 0.3 μg m−3, 16% and 7%, at UB and RS, respectively). By contrast, a SOA biogenic component attributed to α-pinene oxidation (SOA BIO PIN) presented average concentrations of 0.5 μg m−3 at UB (24% of OA) and 0.2 μg m−3 at RS (7%), respectively, suggesting that this SOA component did not impact the two monitoring site at the same level. A clear anti correlation was observed between SOA ISO and SOA PIN during nucleation days, surprisingly suggesting that some of the growth of urban freshly nucleating particles may be driven by biogenic α-pinene oxidation products but inhibited by isoprene organic compounds. A third SOA component was formed by a mixture of aged anthropogenic and biogenic secondary organic compounds (Aged SOA) that accumulated under stagnant atmospheric conditions, contributing for 12% to OA at RS (0.4 μg OC m−3) and for 18% at UB (0.4 μg OC m−3). A sixth component, formed by C7–C9 dicarboxylic acids and detected especially during daytime, was called "urban oxygenated organic aerosol" (Urban OOA) due to its high abundance in urban RS (23%; 0.8 μg OC m−3) vs. UB (10%; 0.2 μg OC m−3), with a well-defined daytime maximum. This temporal trend and geographical differentiation suggests that local anthropogenic sources were determining this component. However, the changes of these organic molecules were also influenced by the air mass trajectories, indicating that atmospheric conditions had an influence on this component although the specific origin on this component remains unclear. It points to a secondary organic component driven by primary urban sources including cooking and traffic (mainly gasoline) activities.

scholarly journals Source Apportionment of Fine Organic Particulate Matter (PM2.5) in Central Addis Ababa, Ethiopia

2021 ◽  
Vol 18 (21) ◽  
pp. 11608
Author(s):  
Worku Tefera ◽  
Abera Kumie ◽  
Kiros Berhane ◽  
Frank Gilliland ◽  
Alexandra Lai ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Source Apportionment ◽  
Biomass Burning ◽  
Addis Ababa ◽  
Atmospheric Particulate Matter ◽  
Motor Vehicles ◽  
Soil Dust ◽  
Rain Season ◽  
The Impact

The development of infrastructure, a rapidly increasing population, and urbanization has resulted in increasing air pollution levels in the African city of Addis Ababa. Prior investigations into air pollution have not yet sufficiently addressed the sources of atmospheric particulate matter. This study aims to identify the major sources of fine particulate matter (PM2.5) and its seasonal contribution in Addis Ababa, Ethiopia. Twenty-four-hour average PM2.5 mass samples were collected every 6th day, from November 2015 through November 2016. Chemical species were measured in samples and source apportionment was conducted using a chemical mass balance (CMB) receptor model that uses particle-phase organic tracer concentrations to estimate source contributions to PM2.5 organic carbon (OC) and the overall PM2.5 mass. Vehicular sources (28%), biomass burning (18.3%), plus soil dust (17.4%) comprise about two-thirds of the PM2.5 mass, followed by sulfate (6.5%). The sources of air pollution vary seasonally, particularly during the main wet season (June–September) and short rain season (February–April): From motor vehicles, (31.0 ± 2.6%) vs. (24.7 ± 1.2%); biomass burning, (21.5 ± 5%) vs. (14 ± 2%); and soil dust, (11 ± 6.4%) vs. (22.7 ± 8.4%), respectively, are amongst the three principal sources of ambient PM2.5 mass in the city. We suggest policy measures focusing on transportation, cleaner fuel or energy, waste management, and increasing awareness on the impact of air pollution on the public’s health.

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

2020 ◽  
Vol 20 (1) ◽  
pp. 409-429 ◽  
Author(s):  
Marco Pandolfi ◽  
Dennis Mooibroek ◽  
Philip Hopke ◽  
Dominik van Pinxteren ◽  
Xavier Querol ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Coal Combustion ◽  
Road Traffic ◽  
Cold Season ◽  
Western Mediterranean ◽  
Anthropogenic Sources ◽  
Mineral Matter ◽  
Ship Emissions ◽  
Maritime Shipping ◽  
Source Contributions

Abstract. Here 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.

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