Uncertainties in source allocation of carbonaceous aerosols in a Mediterranean region.

Understanding the atmospheric processes involving carbonaceous aerosols (CAs) is crucial for assessing air pollution impacts on human health and climate. The sources and formation mechanisms of CAs are not well understood, making it challenging to quantify impacts in models. Studies suggest residential wood combustion (RWC) and traffic significantly contribute to CAs in Europe's urban and rural areas. Here, we used an atmospheric chemistry model (MONARCH) and three different emission inventories (two versions of the European-scale emission inventory CAMS-REG_v4 and the HERMESv3 detailed national inventory for Spain) to assess the uncertainties in CAs simulation and source allocation (from traffic, RWC, shipping, fires and others) in Northeast Spain. For this, black carbon (BC) and organic aerosol (OA) measurements performed at three supersites representing different environments (urban, regional and remote) were used. Our findings show the importance of model resolution and detailed emission input data in accurately reproducing BC/OA observations. Even though emissions of total particulate matter are rather consistent between inventories in Spain, we found discrepancies between them mainly related to the spatiotemporal disaggregation (particularly relevant for traffic and RWC) and the treatment of the condensable fraction of CAs in RWC (changes in the speciation of elemental/organic carbon). The main source contribution to BC concentrations in the urban site is traffic, accounting for 71.1%/65.2% (January/July) in close agreement with the fossil contribution derived from observations (78.8%/84.2%), followed by RWC (12.8%/3%) and shipping emissions (5.4%/13.8%). An over-representation of RWC (winter) and shipping (summer) is obtained with CAMS-REG_v4. Noteworthy uncertainties arise in OA results due to condensables in emissions and a limited secondary aerosol production in the model. These findings offer insights into MONARCH's effectiveness in simulating CAs concentrations and source contribution in Northeast Spain. The study highlights the benefits of combining new datasets and modeling techniques to refine emission inventories and better understand and mitigate air pollution impacts.

Towards a better understanding of fine PM sources: Online and offline datasets combination in a single PMF.

Source apportionment (SA) techniques allocate the measured ambient pollutants with their potential source origin; thus, they are a powerful tool for designing air pollution mitigation strategies. Positive Matrix Factorization (PMF) is one of the most widely used SA approaches, and its multi-time resolution (MTR) methodology, which enables mixing different instrument data in their original time resolution, was the focus of this study. One year of co-located measurements in Barcelona, Spain, of non-refractory submicronic particulate matter (NR-PM1), black carbon (BC) and metals were obtained by a Q-ACSM (Aerodyne Research Inc.), an aethalometer (Aerosol d.o.o.) and fine offline quartz-fibre filters, respectively. These data were combined in a MTR PMF analysis preserving the high time resolution (30 min for the NR-PM1 and BC, and 24 h every 4th day for the offline samples). The MTR-PMF outcomes were assessed varying the time resolution of the high-resolution data subset and exploring the error weightings of both subsets. The time resolution assessment revealed that averaging the high-resolution data was disadvantageous in terms of model residuals and environmental interpretability. The MTR-PMF resolved eight PM1 sources: ammonium sulphate + heavy oil combustion (25%), ammonium nitrate + ammonium chloride (17%), aged secondary organic aerosol (SOA) (16%), traffic (14%), biomass burning (9%), fresh SOA (8%), cooking-like organic aerosol (5%), and industry (4%). The MTR-PMF technique identified two more sources relative to the 24 h base case data subset using the same species and four more with respect to the pseudo-conventional approach mimicking offline PMF, indicating that the combination of both high and low TR data is significantly beneficial for SA. Besides the higher number of sources, the MTR-PMF technique has enabled some sources disentanglement compared to the pseudo-conventional and base case PMF as well as the characterisation of their intra-day patterns.

Compositional changes of PM2.5 in NE Spain during 2009-2018: A trend analysis of the chemical composition and source apportionment.

In this work, time-series analyses of the chemical composition and source contributions of PM2.5 from an urban background station in Barcelona (BCN) and a rural background station in Montseny (MSY) in northeastern Spain from 2009 to 2018 were investigated and compared. A multisite positive matrix factorization analysis was used to compare the source contributions between the two stations, while the trends for both the chemical species and source contributions were studied using the Theil-Sen trend estimator. Between 2009 and 2018, both stations showed a statistically significant decrease in PM2.5 concentrations, which was driven by the downward trends of levels of chemical species and anthropogenic source contributions, mainly from heavy oil combustion, mixed combustion, industry, and secondary sulfate. These source contributions showed a continuous decrease over the study period, signifying the continuing success of mitigation strategies, although the trends of heavy oil combustion and secondary sulfate have flattened since 2016. Secondary nitrate also followed a significant decreasing trend in BCN, while secondary organic aerosols (SOA) very slightly decreased in MSY. The observed decreasing trends, in combination with the absence of a trend for the organic aerosols (OA) at both stations, resulted in an increase in the relative proportion of OA in PM2.5 by 12% in BCN and 9% in MSY, mostly from SOA, which increased by 7% in BCN and 4% in MSY. Thus, at the end of the study period, OA accounted for 40% and 50% of the annual mean PM2.5 at BCN and MSY, respectively. This might have relevant implications for air quality policies aiming at abating PM2.5 in the study region and for possible changes in toxicity of PM2.5 due to marked changes in composition and source apportionment.

Changes in air quality during the lockdown in Barcelona (Spain) one month into the SARS-CoV-2 epidemic.

Lockdown measures came into force in Spain from March 14th, two weeks after the start of the SARS-CoV-2 epidemic, to reduce the epidemic curve. Our study aims to describe changes in air pollution levels during the lockdown measures in the city of Barcelona (NE Spain), by studying the time evolution of atmospheric pollutants recorded at the urban background and traffic air quality monitoring stations. After two weeks of lockdown, urban air pollution markedly decreased but with substantial differences among pollutants. The most significant reduction was estimated for BC and NO2 (-45 to -51%), pollutants mainly related to traffic emissions. A lower reduction was observed for PM10 (-28 to -31.0%). By contrast, O3 levels increased (+33 to +57% of the 8 h daily maxima), probably due to lower titration of O3 by NO and the decrease of NOx in a VOC-limited environment. Relevant differences in the meteorology of these two periods were also evidenced. The low reduction for PM10 is probably related to a significant regional contribution and the prevailing secondary origin of fine aerosols, but an in-depth evaluation has to be carried out to interpret this lower decrease. There is no defined trend for the low SO2 levels, probably due to the preferential reduction in emissions from the least polluting ships. A reduction of most pollutants to minimal concentrations are expected for the forthcoming weeks because of the more restrictive actions implemented for a total lockdown, which entered into force on March 30th. There are still open questions on why PM10 levels were much less reduced than BC and NO2 and on what is the proportion of the abatement of pollution directly related to the lockdown, without meteorological interferences.