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    A statistical proxy for sulphuric acid concentration
    (München : European Geopyhsical Union, 2011) Mikkonen, S.; Romakkaniemi, S.; Smith, J.N.; Korhonen, H.; Petäjä, T.; Plass-Duelmer, C.; Boy, M.; McMurry, P.H.; Lehtinen, K.E.J.; Joutsensaari, J.; Hamed, A.; Mauldin III, R.L.; Birmili, W.; Spindler, G.; Arnold, F.; Kulmala, M.; Laaksonen, A.
    Gaseous sulphuric acid is a key precursor for new particle formation in the atmosphere. Previous experimental studies have confirmed a strong correlation between the number concentrations of freshly formed particles and the ambient concentrations of sulphuric acid. This study evaluates a body of experimental gas phase sulphuric acid concentrations, as measured by Chemical Ionization Mass Spectrometry (CIMS) during six intensive measurement campaigns and one long-term observational period. The campaign datasets were measured in Hyytiälä, Finland, in 2003 and 2007, in San Pietro Capofiume, Italy, in 2009, in Melpitz, Germany, in 2008, in Atlanta, Georgia, USA, in 2002, and in Niwot Ridge, Colorado, USA, in 2007. The long term data were obtained in Hohenpeissenberg, Germany, during 1998 to 2000. The measured time series were used to construct proximity measures ("proxies") for sulphuric acid concentration by using statistical analysis methods. The objective of this study is to find a proxy for sulfuric acid that is valid in as many different atmospheric environments as possible. Our most accurate and universal formulation of the sulphuric acid concentration proxy uses global solar radiation, SO2 concentration, condensation sink and relative humidity as predictor variables, yielding a correlation measure (R) of 0.87 between observed concentration and the proxy predictions. Interestingly, the role of the condensation sink in the proxy was only minor, since similarly accurate proxies could be constructed with global solar radiation and SO2 concentration alone. This could be attributed to SO2 being an indicator for anthropogenic pollution, including particulate and gaseous emissions which represent sinks for the OH radical that, in turn, is needed for the formation of sulphuric acid.
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    A concept of an automated function control for ambient aerosol measurements using mobility particle size spectrometers
    (München : European Geopyhsical Union, 2014) Schladitz, A.; Merkel, M.; Bastian, S.; Birmili, W.; Weinhold, K.; Löschau, G.; Wiedensohler, A.
    An automated function control unit was developed to regularly check the ambient particle number concentration derived from a mobility particle size spectrometer as well as its zero-point behaviour. The function control allows unattended quality assurance experiments at remote air quality monitoring or research stations under field conditions. The automated function control also has the advantage of being able to get a faster system stability response than the recommended on-site comparisons with reference instruments. The method is based on a comparison of the total particle number concentration measured by a mobility particle size spectrometer and a condensation particle counter while removing diffusive particles smaller than 20 nm in diameter. In practice, the small particles are removed by a set of diffusion screens, as traditionally used in a diffusion battery. Another feature of the automated function control is to check the zero-point behaviour of the ambient aerosol passing through a high-efficiency particulate air (HEPA) filter. The performance of the function control is illustrated with the aid of a 1-year data set recorded at Annaberg-Buchholz, a station in the Saxon air quality monitoring network. During the period of concern, the total particle number concentration derived from the mobility particle size spectrometer slightly overestimated the particle number concentration recorded by the condensation particle counter by 2 % (grand average). Based on our first year of experience with the function control, we developed tolerance criteria that allow a performance evaluation of a tested mobility particle size spectrometer with respect to the total particle number concentration. We conclude that the automated function control enhances the quality and reliability of unattended long-term particle number size distribution measurements. This will have beneficial effects for intercomparison studies involving different measurement sites, and help provide a higher data accuracy for cohort health and climate research studies.
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    Mobility particle size spectrometers: Harmonization of technical standards and data structure to facilitate high quality long-term observations of atmospheric particle number size distributions
    (München : European Geopyhsical Union, 2012) Wiedensohler, A.; Birmili, W.; Nowak, A.; Sonntag, A.; Weinhold, K.; Merkel, M.; Wehner, B.; Tuch, T.; Pfeifer, S.; Fiebig, M.; Fjäraa, A.M.; Asmi, E.; Sellegri, K.; Depuy, R.; Venzac, H.; Villani, P.; Laj, P.; Aalto, P.; Ogren, J.A.; Swietlick, E.; Williams, P.; Roldin, P.; Quincey, P.; Hüglin, C.; Fierz-Schmidhauser, R.; Gysel, M.; Weingartner, E.; Riccobono, F.; Santos, S.; Grüning, C.; Faloon, K.; Beddows, D.; Harrison, R.; Monahan, C.; Jennings, S.G.; O'Dowd, C.D.; Marinoni, A.; Horn, H.-G.; Keck, L.; Jiang, J.; Scheckman, J.; McMurry, P.H.; Deng, Z.; Zhao, C.S.; Moerman, M.; Henzing, B.; de Leeuw, G.; Löschau, G.; Bastian, S.
    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 set-up, 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 ACTRIS (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.