Aerosol black carbon is a unique primary tracer for combustion emissions. It affects the optical properties of the atmosphere and is recognized as the second most important anthropogenic forcing agent for climate change. It is the primary tracer for adverse health effects caused by air pollution. For the accurate determination of mass equivalent black carbon concentrations in the air and for source apportionment of the concentrations, optical measurements by filter-based absorption photometers must take into account the "filter loading effect". We present a new real-time loading effect compensation algorithm based on a two parallel spot measurement of optical absorption. This algorithm has been incorporated into the new Aethalometer model AE33. Intercomparison studies show excellent reproducibility of the AE33 measurements and very good agreement with post-processed data obtained using earlier Aethalometer models and other filter-based absorption photometers. The real-time loading effect compensation algorithm provides the high-quality data necessary for real-time source apportionment and for determination of the temporal variation of the compensation parameter k.

Equivalent black carbon (EBC) measured by a multi-wavelength Aethalometer can be apportioned to traffic and wood burning. The method is based on the differences in the dependence of aerosol absorption on the wavelength of light used to investigate the sample, parameterized by the source-specific absorption Ångström exponent (α). While the spectral dependence (defined as α values) of the traffic-related EBC light absorption is low, wood smoke particles feature enhanced light absorption in the blue and near ultraviolet. Source apportionment results using this methodology are hence strongly dependent on the α values assumed for both types of emissions: traffic α_TR, and wood burning α_WB. Most studies use a single α_TR and α_WB pair in the Aethalometer model, derived from previous work. However, an accurate determination of the source specific α values is currently lacking and in some recent publications the applicability of the Aethalometer model was questioned. Here we present an indirect methodology for the determination of α_WB and α_TR by comparing the source apportionment of EBC using the Aethalometer model with ¹⁴C measurements of the EC fraction on 16 to 40 h filter samples from several locations and campaigns across Switzerland during 2005–2012, mainly in winter. The data obtained at eight stations with different source characteristics also enabled the evaluation of the performance and the uncertainties of the Aethalometer model in different environments. The best combination of α_TR and α_WB (0.9 and 1.68, respectively) was obtained by fitting the Aethalometer model outputs (calculated with the absorption coefficients at 470 and 950 nm) against the fossil fraction of EC (EC_F ∕ EC) derived from ¹⁴C measurements. Aethalometer and ¹⁴C source apportionment results are well correlated (r = 0.81) and the fitting residuals exhibit only a minor positive bias of 1.6 % and an average precision of 9.3 %. This indicates that the Aethalometer model reproduces reasonably well the ¹⁴C results for all stations investigated in this study using our best estimate of a single α_WB and α_TR pair. Combining the EC, ¹⁴C, and Aethalometer measurements further allowed assessing the dependence of the mass absorption cross section (MAC) of EBC on its source. Results indicate no significant difference in MAC at 880 nm between EBC originating from traffic or wood-burning emissions. Using EC_F ∕ EC as reference and constant a priori selected α_TR values, α_WB was also calculated for each individual data point. No clear station-to-station or season-to-season differences in α_WB were observed, but α_TR and α_WB values are interdependent. For example, an increase in α_TR by 0.1 results in a decrease in α_WB by 0.1. The fitting residuals of different α_TR and α_WB combinations depend on EC_F ∕ EC such that a good agreement cannot be obtained over the entire EC_F ∕ EC range using other α pairs. Additional combinations of α_TR = 0.8, and 1.0 and α_WB = 1.8 and 1.6, respectively, are possible but only for EC_F ∕ EC between ∼ 40 and 85 %. Applying α values previously used in the literature such as α_WB of ∼ 2 or any α_WB in combination with α_TR = 1.1 to our data set results in large residuals. Therefore we recommend to use the best α combination as obtained here (α_TR = 0.9 and α_WB = 1.68) in future studies when no or only limited additional information like ¹⁴C measurements are available. However, these results were obtained for locations impacted by black carbon (BC) mainly from traffic consisting of a modern car fleet and residential wood combustion with well-constrained combustion efficiencies. For regions of the world with different combustion conditions, additional BC sources, or fuels used, further investigations are needed.

We present a new mobile environmental reaction chamber for the simulation of the atmospheric aging of different emission sources without limitation from the instruments or facilities available at any single site. Photochemistry is simulated using a set of 40 UV lights (total power 4 KW). Characterisation of the emission spectrum of these lights shows that atmospheric aging of emissions may be simulated over a range of temperatures (−7 to 25 °C). A photolysis rate of NO₂, JNO₂, of (8.0 ± 0.7) × 10⁻³ s⁻¹ was determined at 25 °C. We demonstrate the utility of this new system by presenting results on the aging (OH = 12 × 10⁶ cm⁻³ h) of emissions from a modern (Euro 5) gasoline car operated during a driving cycle (New European Driving Cycle, NEDC) on a chassis dynamometer in a vehicle test cell. Emissions from the entire NEDC were sampled and aged in the chamber. Total organic aerosol (OA; primary organic aerosol (POA) emission + secondary organic aerosol (SOA) formation) was (369.8–397.5)10⁻³ g kg⁻¹ fuel, or (13.2–15.4) × 10⁻³ g km⁻¹, after aging, with aged OA/POA in the range 9–15. A thorough investigation of the composition of the gas phase emissions suggests that the observed SOA is from previously unconsidered precursors and processes. This large enhancement in particulate matter mass from gasoline vehicle aerosol emissions due to SOA formation, if it occurs across a wider range of gasoline vehicles, would have significant implications for our understanding of the contribution of on-road gasoline vehicles to ambient aerosols.

The relative contributions of eight nitrated aromatic compounds (NACs: nitrophenols and nitrated salicylic acids) to the light absorption of aqueous particle extracts and particulate brown carbon were determined from aerosol particle samples collected in Germany and China. High-volume filter samples were collected during six campaigns, performed at five locations in two seasons: (I) two campaigns with strong influence of biomass-burning (BB) aerosol at the TROPOS institute (winter, 2014, urban background, Leipzig, Germany) and the Melpitz research site (winter, 2014, rural background); (II) two campaigns with strong influence from biogenic emissions at Melpitz (summer, 2014) and the forest site Waldstein (summer, 2014, Fichtelgebirge, Germany); and (III) two CAREBeijing-NCP campaigns at Xianghe (summer, 2013, anthropogenic polluted background) and Wangdu (summer, 2014, anthropogenic polluted background with a distinct BB episode), both in the North China Plain. The filter samples were analyzed for NAC concentrations and the light absorption of aqueous filter extracts was determined. Light absorption properties of particulate brown carbon were derived from a seven-wavelength aethalometer during the campaigns at TROPOS (winter) and Waldstein (summer). The light absorption of the aqueous filter extracts was found to be pH dependent, with larger values at higher pH. In general, the aqueous light absorption coefficient (Abs₃₇₀) ranged from 0.21 to 21.8 Mm⁻¹ under acidic conditions and 0.63 to 27.2 Mm⁻¹ under alkaline conditions, over all campaigns. The observed mass absorption efficiency (MAE₃₇₀) was in a range of 0.10–1.79 m² g⁻¹ and 0.24–2.57 m² g⁻¹ for acidic and alkaline conditions, respectively. For MAE₃₇₀ and Abs₃₇₀, the observed values were higher in winter than in summer, in agreement with other studies. The lowest MAE was observed for the Waldstein (summer) campaign (average of 0.17 ± 0.03 m² g⁻¹), indicating that freshly emitted biogenic aerosols are only weakly absorbing. In contrast, a strong relationship was found between the light absorption properties and the concentrations of levoglucosan, corroborating findings from other studies. Regarding the particulate light absorption at 370 nm, a mean particulate light absorption coefficient b_abs, 370 of 54 Mm⁻¹ and 6.0 Mm⁻¹ was determined for the TROPOS (winter) and Waldstein (summer) campaigns, respectively, with average contributions of particulate brown carbon to b_abs, 370 of 46 % at TROPOS (winter) and 15 % at Waldstein (summer). Thus, the aethalometer measurements support the findings from aqueous filter extracts of only weakly absorbing biogenic aerosols in comparison to the more polluted and BB influenced aerosol at TROPOS (winter). The mean contribution of NACs to the aqueous extract light absorption over all campaigns ranged from 0.10 to 1.25 % under acidic conditions and 0.13 to 3.71 % under alkaline conditions. The high variability among the measurement sites showed that the emission strengths of light-absorbing compounds and the composition of brown carbon were very different for each site. The mean contribution of NACs to the particulate brown carbon light absorption was 0.10 ± 0.06 % (acidic conditions) and 0.13 ± 0.09 % (alkaline conditions) during the Waldstein (summer) campaign and 0.25 ± 0.21 % (acidic conditions) and 1.13 ± 1.03 % (alkaline conditions) during the TROPOS (winter) campaign. The average contribution of NACs to the aqueous extract light absorption over all campaigns was found to be 5 times higher than their mass contribution to water-soluble organic carbon indicating that even small amounts of light-absorbing compounds can have a disproportionately high impact on the light absorption properties of particles.

Aerosol mass spectrometer (AMS) measurements have been successfully used towards a better understanding of non-refractory submicron (PM1) aerosol chemical properties based on short-term campaigns. The recently developed Aerosol Chemical Speciation Monitor (ACSM) has been designed to deliver quite similar artifact-free chemical information but for low cost, and to perform robust monitoring over long-term periods. When deployed in parallel with real-time black carbon (BC) measurements, the combined data set allows for a quasi-comprehensive description of the whole PM1 fraction in near real time. Here we present 2-year long ACSM and BC data sets, between mid-2011 and mid-2013, obtained at the French atmospheric SIRTA supersite that is representative of background PM levels of the region of Paris. This large data set shows intense and time-limited (a few hours) pollution events observed during wintertime in the region of Paris, pointing to local carbonaceous emissions (mainly combustion sources). A non-parametric wind regression analysis was performed on this 2-year data set for the major PM1 constituents (organic matter, nitrate, sulfate and source apportioned BC) and ammonia in order to better refine their geographical origins and assess local/regional/advected contributions whose information is mandatory for efficient mitigation strategies. While ammonium sulfate typically shows a clear advected pattern, ammonium nitrate partially displays a similar feature, but, less expectedly, it also exhibits a significant contribution of regional and local emissions. The contribution of regional background organic aerosols (OA) is significant in spring and summer, while a more pronounced local origin is evidenced during wintertime, whose pattern is also observed for BC originating from domestic wood burning. Using time-resolved ACSM and BC information, seasonally differentiated weekly diurnal profiles of these constituents were investigated and helped to identify the main parameters controlling their temporal variations (sources, meteorological parameters). Finally, a careful investigation of all the major pollution episodes observed over the region of Paris between 2011 and 2013 was performed and classified in terms of chemical composition and the BC-to-sulfate ratio used here as a proxy of the local/regional/advected contribution of PM. In conclusion, these first 2-year quality-controlled measurements of ACSM clearly demonstrate their great potential to monitor on a long-term basis aerosol sources and their geographical origin and provide strategic information in near real time during pollution episodes. They also support the capacity of the ACSM to be proposed as a robust and credible alternative to filter-based sampling techniques for long-term monitoring strategies.

Chemically resolved atmospheric aerosol data sets from the largest intercomparison of the Aerodyne aerosol chemical speciation monitors (ACSMs) performed to date were collected at the French atmospheric supersite SIRTA. In total 13 quadrupole ACSMs (Q-ACSM) from the European ACTRIS ACSM network, one time-of-flight ACSM (ToF-ACSM), and one high-resolution ToF aerosol mass spectrometer (AMS) were operated in parallel for about 3 weeks in November and December~2013. Part 1 of this study reports on the accuracy and precision of the instruments for all the measured species. In this work we report on the intercomparison of organic components and the results from factor analysis source apportionment by positive matrix factorisation (PMF) utilising the multilinear engine 2 (ME-2). Except for the organic contribution of mass-to-charge ratio m/z 44 to the total organics (f₄₄), which varied by factors between 0.6 and 1.3 compared to the mean, the peaks in the organic mass spectra were similar among instruments. The m/z 44 differences in the spectra resulted in a variable f₄₄ in the source profiles extracted by ME-2, but had only a minor influence on the extracted mass contributions of the sources. The presented source apportionment yielded four factors for all 15 instruments: hydrocarbon-like organic aerosol (HOA), cooking-related organic aerosol (COA), biomass burning-related organic aerosol (BBOA) and secondary oxygenated organic aerosol (OOA). ME-2 boundary conditions (profile constraints) were optimised individually by means of correlation to external data in order to achieve equivalent / comparable solutions for all ACSM instruments and the results are discussed together with the investigation of the influence of alternative anchors (reference profiles). A comparison of the ME-2 source apportionment output of all 15 instruments resulted in relative standard deviations (SD) from the mean between 13.7 and 22.7 % of the source's average mass contribution depending on the factors (HOA: 14.3 ± 2.2 %, COA: 15.0 ± 3.4 %, OOA: 41.5 ± 5.7 %, BBOA: 29.3 ± 5.0 %). Factors which tend to be subject to minor factor mixing (in this case COA) have higher relative uncertainties than factors which are recognised more readily like the OOA. Averaged over all factors and instruments the relative first SD from the mean of a source extracted with ME-2 was 17.2 %.