Abstract
Abstract. Source apportionment of organic aerosols (OAs) is of great importance to better understand the health impact and climate effects of particulate matter air pollution. Air quality models are used as potential tools to identify OA components and sources at high spatial and temporal resolution; however, they generally underestimate OA concentrations, and comparisons of their outputs with an extended set of measurements are still rare due to the lack of long-term experimental data. In this study, we addressed such challenges at the European level. Using the regional Comprehensive Air Quality Model with Extensions (CAMx) and a volatility basis set (VBS) scheme which was optimized based on recent chamber experiments with wood burning and diesel vehicle emissions, and which contains more source-specific sets compared to previous studies, we calculated the contribution of OA components and defined their sources over a whole-year period (2011). We modeled separately the primary and secondary OA contributions from old and new diesel and gasoline vehicles, biomass burning (mostly residential wood burning and agricultural waste burning excluding wildfires), other anthropogenic sources (mainly shipping, industry and energy production) and biogenic sources. An important feature of this study is that we evaluated the model results with measurements over a longer period than in previous studies, which strengthens our confidence in our modeled source apportionment results. Comparison against positive matrix factorization (PMF) analyses of aerosol mass spectrometric measurements at nine European sites suggested that the modified VBS scheme improved the model performance for total OA as well as the OA components, including hydrocarbon-like (HOA), biomass burning (BBOA) and oxygenated components (OOA). By using the modified VBS scheme, the mean bias of OOA was reduced from −1.3 to −0.4 µg m−3 corresponding to a reduction of mean fractional bias from −45 % to −20 %. The winter OOA simulation, which was largely underestimated in previous studies, was improved by 29 % to 42 % among the evaluated sites compared to the default parameterization. Wood burning was the dominant OA source in winter (61 %), while biogenic emissions contributed ∼ 55 % to OA during summer in Europe on average. In both seasons, other anthropogenic sources comprised the second largest component (9 % in winter and 19 % in summer as domain average), while the average contributions of diesel and gasoline vehicles were rather small (∼ 5 %) except for the metropolitan areas where the highest contribution reached 31 %. The results indicate the need to improve the emission inventory to include currently missing and highly uncertain local emissions, as well as further improvement of VBS parameterization for winter biomass burning. Although this study focused on Europe, it can be applied in any other part of the globe. This study highlights the ability of long-term measurements and source apportionment modeling to validate and improve emission inventories, and identify sources not yet properly included in existing inventories.
Highlights
Pollution by atmospheric fine particulate matter (PM) exerts significant impacts on human health (Ciarelli et al, 2019; Cohen et al, 2017; Lelieveld et al, 2015; Tuet et al, 2017) and climate (Kanakidou et al, 2005), where organic aerosols (OAs) contribute 20 %–90 % (Jimenez et al, 2009; Kanakidou et al, 2005)
Using the regional Comprehensive Air Quality Model with Extensions (CAMx) and a volatility basis set (VBS) scheme which was optimized based on recent chamber experiments with wood burning and diesel vehicle emissions, and which contains more source-specific sets compared to previous studies, we calculated the contribution of OA components and defined their sources over a wholeyear period (2011)
In order to improve the model performance for the organic aerosol which is generally underestimated by air quality models, we updated the VBS parameterization based on recent findings in chamber experiments with biomass burning and diesel vehicles (CAMx-NEW)
Summary
Pollution by atmospheric fine particulate matter (PM) exerts significant impacts on human health (Ciarelli et al, 2019; Cohen et al, 2017; Lelieveld et al, 2015; Tuet et al, 2017) and climate (Kanakidou et al, 2005), where organic aerosols (OAs) contribute 20 %–90 % (Jimenez et al, 2009; Kanakidou et al, 2005). Unlike the single-component pollutants such as ozone and sulfur dioxide, organic aerosols are composed of numerous compounds from different sources with distinct physical, chemical and toxicological properties (Hallquist et al, 2009; Shrivastava et al, 2017). Positive matrix factorization (PMF) analysis is often applied to aerosol mass spectrometer data to classify the measured organic mass spectra into different factors. Recent studies with long-term offline aerosol mass spectrometer (AMS) measurements were able to further split the OOA component into biogenic SOA and anthropogenic SOA according to their seasonal variability (Daellenbach et al, 2016, 2017; Vlachou et al, 2018)
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