Oxidized organic aerosol (OOA) is a major component of ambient particulate matter, substantially impacting climate, human health, and ecosystems. OOA is readily produced in the presence of sunlight, and requires days of photooxidation to reach the levels observed in the atmosphere. High concentrations of OOA are thus expected in the summer; however, our current mechanistic understanding fails to explain elevated OOA during wintertime periods of low photochemical activity that coincide with periods of intense biomass burning. As a result, atmospheric models underpredict OOA concentrations by a factor of 3 to 5. Here we show that fresh emissions from biomass burning exposed to NO2 and O3 (precursors to the NO3 radical) rapidly form OOA in the laboratory over a few hours and without any sunlight. The extent of oxidation is sensitive to relative humidity. The resulting OOA chemical composition is consistent with the observed OOA in field studies in major urban areas. Additionally, this dark chemical processing leads to significant enhancements in secondary nitrate aerosol, of which 50 to 60% is estimated to be organic. Simulations that include this understanding of dark chemical processing show that over 70% of organic aerosol from biomass burning is substantially influenced by dark oxidation. This rapid and extensive dark oxidation elevates the importance of nocturnal chemistry and biomass burning as a global source of OOA.

Abstract.A detailed three-dimensional regional chemical transport model (Particulate Matter Comprehensive Air Quality Model with Extensions, PMCAMx) was applied over Europe, focusing on the formation and chemical transformation of organic matter. Three periods representative of different seasons were simulated, corresponding to intensive field campaigns. An extensive set of AMS measurements was used to evaluate the model and, using factor-analysis results, gain more insight into the sources and transformations of organic aerosol (OA). Overall, the agreement between predictions and measurements for OA concentration is encouraging, with the model reproducing two-thirds of the data (daily average mass concentrations) within a factor of 2. Oxygenated OA (OOA) is predicted to contribute 93 % to total OA during May, 87 % during winter and 96 % during autumn, with the rest consisting of fresh primary OA (POA). Predicted OOA concentrations compare well with the observed OOA values for all periods, with an average fractional error of 0.53 and a bias equal to −0.07 (mean error = 0.9 µg m −3 , mean bias = −0.2 µg m −3 ). The model Published by Copernicus Publications on behalf of the European Geosciences Union. C. Fountoukis et al.: Organic aerosol concentration and composition over Europesystematically underpredicts fresh POA at most sites during late spring and autumn (mean bias up to −0.8 µg m −3 ). Based on results from a source apportionment algorithm running in parallel with PMCAMx, most of the POA originates from biomass burning (fires and residential wood combustion), and therefore biomass burning OA is most likely underestimated in the emission inventory. The sensitivity of POA predictions to the corresponding emissions' volatility distribution is discussed. The model performs well at all sites when the Positive Matrix Factorization (PMF)-estimated low-volatility OOA is compared against the OA with saturation concentrations of the OA surrogate species C * ≤ 0.1 µg m −3 and semivolatile OOA against the OA with C * > 0.1 µg m −3 .

Abstract. The particulate matter source apportionment technology (PSAT) is used together with PMCAMx, a regional chemical transport model, to estimate how local emissions and pollutant transport affect primary and secondary particulate matter mass concentration levels in Paris. During the summer and the winter periods examined, only 13 % of the PM 2.5 is predicted to be due to local Paris emissions, with 36 % coming from mid-range (50-500 km from the center of the Paris) sources and 51 % from long range transport (more than 500 km from Paris).The local emissions contribution to simulated elemental carbon (EC) is significant, with almost 60 % of the EC originating from local sources during both summer and winter. Approximately 50 % of the simulated fresh primary organic aerosol (POA) originated from local sources and another 45 % from areas 100-500 km from the receptor region during summer. Regional sources dominated the secondary PM components. During summer more than 70 % of the simulated sulfate originated from SO 2 emitted more than 500 km away from the center of the Paris. Also more than 45 % of secondary organic aerosol (SOA) was due to the oxidation of VOC precursors that were emitted 100-500 km from the center of the Paris. The model simulates more contribution from long range secondary PM sources during winter because the timescale for its production is longer due to the slower photochemical activity.PSAT results for contributions of local and regional sources were compared with observation-based estimates from field campaigns that took place during the MEGAPOLI project. PSAT simulations are in general consistent (within 20 %) with these estimates for OA and sulfate. The only exception is that PSAT simulates higher local EC contribution during the summer compared to that estimated from observations.

The formation, atmospheric evolution, properties, and removal of organic particulate matter remain some of the least understood aspects of atmospheric chemistry despite the importance of organic aerosol (OA) for both human health and climate change. Here, we summarize our recent efforts to deal with the chemical complexity of the tens of thousands of organic compounds in the atmosphere using the volatility-oxygen content framework (often called the 2D-Volatility Basis Set, 2D-VBS). Our current ability to measure the ambient OA concentration as a function of its volatility and oxygen to carbon (O:C) ratio is evaluated. The combination of a thermodenuder, isothermal dilution and Aerosol Mass Spectrometry (AMS) together with a mathematical aerosol dynamics model is a promising approach. The development of computational modules based on the 2D-VBS that can be used in chemical transport models (CTMs) is described. Approaches of different complexity are tested against ambient observations, showing the challenge of simulating the complex chemical evolution of atmospheric OA. The results of the simplest approach describing the net change due to functionalization and fragmentation are quite encouraging, reproducing both the observed OA levels and O : C in a variety of conditions. The same CTM coupled with source-apportionment algorithms can be used to gain insights into the travel distances and age of atmospheric OA. We estimate that the average age of OA near the ground in continental locations is 1-2 days and most of it was emitted (either as precursor vapors or particles) hundreds of kilometers away. Condensation of organic vapors on fresh particles is critical for the growth of these new particles to larger sizes and eventually to cloud condensation nuclei (CCN) sizes. The semivolatile organics currently simulated by CTMs are too volatile to condense on these tiny particles with high curvature. We show that chemical aging reactions converting these semivolatile compounds to extremely low volatility compounds can explain the observed growth rates of new particles in rural environments.