Abstract. Mobility particle size spectrometers often referred to as DMPS (Differential Mobility Particle Sizers) or SMPS (Scanning Mobility Particle Sizers) have found a wide range of applications in atmospheric aerosol research. However, comparability of measurements conducted world-wide is hampered by lack of generally accepted technical standards and guidelines with respect to the instrumental setup, measurement mode, data evaluation as well as quality control. Technical standards were developed for a minimum requirement of mobility size spectrometry to perform long-term atmospheric aerosol measurements. Technical recommendations include continuous monitoring of flow rates, temperature, pressure, and relative humidity for the sheath and sample air in the differential mobility analyzer.We compared commercial and custom-made inversion routines to calculate the particle number size distributions from the measured electrical mobility distribution. All inversion routines are comparable within few per cent uncertainty for a given set of raw data.Furthermore, this work summarizes the results from several instrument intercomparison workshops conducted within the European infrastructure project EUSAAR (European Supersites for Atmospheric Aerosol Research) and AC-TRIS (Aerosols, Clouds, and Trace gases Research InfraStructure Network) to determine present uncertainties especially of custom-built mobility particle size spectrometers. Under controlled laboratory conditions, the particle number size distributions from 20 to 200 nm determined by mobility particle size spectrometers of different design are within an uncertainty range of around ±10 % after correcting internal particle losses, while below and above this size range the discrepancies increased. For particles larger than 200 nm, the uncertainty range increased to 30 %, which could not be explained. The network reference mobility spectrometers with identical design agreed within ±4 % in the peak particle number concentration when all settings were done carefully. The consistency of these reference instruments to the total particle number concentration was demonstrated to be less than 5 %.Additionally, a new data structure for particle number size distributions was introduced to store and disseminate the data at EMEP (European Monitoring and Evaluation Program). This structure contains three levels: raw data, processed data, and final particle size distributions. Importantly, we recommend reporting raw measurements including all relevant instrument parameters as well as a complete documentation on all data transformation and correction steps. These technical and data structure standards aim to enhance the quality of long-term size distribution measurements, their comparability between different networks and sites, and their transparency and traceability back to raw data.

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Abstract. 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 αTR, and wood burning αWB. Most studies use a single αTR and αWB 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 αWB and αTR 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 αTR and αWB (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 (ECF ∕ 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 αWB and αTR 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 ECF ∕ EC as reference and constant a priori selected αTR values, αWB was also calculated for each individual data point. No clear station-to-station or season-to-season differences in αWB were observed, but αTR and αWB values are interdependent. For example, an increase in αTR by 0.1 results in a decrease in αWB by 0.1. The fitting residuals of different αTR and αWB combinations depend on ECF ∕ EC such that a good agreement cannot be obtained over the entire ECF ∕ EC range using other α pairs. Additional combinations of αTR  =  0.8, and 1.0 and αWB  =  1.8 and 1.6, respectively, are possible but only for ECF ∕ EC between  ∼  40 and 85 %. Applying α values previously used in the literature such as αWB of  ∼  2 or any αWB in combination with αTR  =  1.1 to our data set results in large residuals. Therefore we recommend to use the best α combination as obtained here (αTR  =  0.9 and αWB  =  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.

Abstract. An Analysis of Covariance (ANCOVA) was used to derive the influence of the meteorological variability on the daily maximum ozone concentrations at 12 low-elevation sites north of the Alps in Switzerland during the four seasons in the 1992-2002 period. The afternoon temperature and the morning global radiation were the variables that accounted for most of the meteorological variability in summer and spring, while other variables that can be related to vertical mixing and dilution of primary pollutants (afternoon global radiation, wind speed, stability or day of the week) were more significant in winter. In addition, the number of days after a frontal passage was important to account for ozone build-up in summer and ozone destruction in winter. The statistical model proved to be a robust tool for reducing the impact of the meteorological variability on the ozone concentrations. The explained variance of the model, averaged over all stations, ranged from 60.2% in winter to 71.9% in autumn. The year-to-year variability of the seasonal medians of daily ozone maxima was reduced by 85% in winter, 60% in summer, and 50% in autumn and spring after the meteorological adjustment. For most stations, no significantly negative trends (at the 95% confidence level) of the summer medians of daily O 3 or O x (O 3 +NO 2 ) maxima were found despite the significant reduction in the precursor emissions in Central Europe. However, significant downward trends in the summer 90th percentiles of daily O x maxima were observed at 6 sites in the region around Zürich (on average −0.73 ppb yr −1 for those sites). The lower effect of the titration by NO as a consequence of the reduced emissions could partially explain the significantly positive O 3 trends in the cold seasons (on average 0.69 ppb yr −1 in winter and 0.58 ppb yr −1 in autumn). The increase of O x found for most stations in autumn (on average 0.23 ppb yr −1 ) and winter (on average 0.39 ppb yr −1 ) could be due to increasing European background ozone levCorrespondence to: A. S. H. Prévôt (andre.prevot@psi.ch) els, in agreement with other studies. The statistical model was also able to explain the very high ozone concentrations in summer 2003, the warmest summer in Switzerland for at least ∼150 years. On average, the measured daily ozone maximum was 15 ppb (nearly 29%) higher than in the reference period summer 1992-2002, corresponding to an excess of 5 standard deviations of the summer means of daily ozone maxima in that period.

Particle mobility size spectrometers often referred to as DMPS (Differential Mobility Particle Sizers) or SMPS (Scanning Mobility Particle Sizers) have found a wide application in atmospheric aerosol research. However, comparability of measurements conducted world-wide is hampered by lack of generally accepted technical standards with respect to the instrumental set-up, measurement mode, data evaluation as well as quality control. This article results from several instrument intercomparison workshops conducted within the European infrastructure project EUSAAR (European Supersites for Atmospheric Aerosol Research). Under controlled laboratory conditions, the number size distribution from 20 to 200 nm determined by mobility size spectrometers of different design are within an uncertainty range of ±10% after correcting internal particle losses, while below and above this size range the discrepancies increased. Instruments with identical design agreed within ±3% in the peak number concentration when all settings were done carefully. Technical standards were developed for a minimum requirement of mobility size spectrometry for atmospheric aerosol measurements. Technical recommendations are given for atmospheric measurements including continuous monitoring of flow rates, temperature, pressure, and relative humidity for the sheath and sample air in the differential mobility analyser. In cooperation with EMEP (European Monitoring and Evaluation Program), a new uniform data structure was introduced for saving and disseminating the data within EMEP. This structure contains three levels: raw data, processed data, and final particle size distributions. Importantly, we recommend reporting raw measurements including all relevant instrument parameters as well as a complete documentation on all data transformation and correction steps. These technical and data structure standards aim to enhance the quality of long-term size distribution measurements, their comparability between different networks and sites, and their transparency and traceability back to raw data