2011, Massling, A., Niedermeier, N., Hennig, T., Fors, E.O., Swietlicki, E., Ehn, M., Hämeri, K., Villani, P., Laj, P., Good, N., McFiggans, G., Wiedensohler, A.

The performance of six custom-built Hygrocopicity-Tandem Differential Mobility Analyser (H-TDMA) systems was investigated in the frame of an international calibration and intercomparison workshop held in Leipzig, February 2006. The goal of the workshop was to harmonise H-TDMA measurements and develop recommendations for atmospheric measurements and their data evaluation. The H-TDMA systems were compared in terms of the sizing of dry particles, relative humidity (RH) uncertainty, and consistency in determination of number fractions of different hygroscopic particle groups. The experiments were performed in an air-conditioned laboratory using ammonium sulphate particles or an external mixture of ammonium sulphate and soot particles. The sizing of dry particles of the six H-TDMA systems was within 0.2 to 4.2% of the selected particle diameter depending on investigated size and individual system. Measurements of ammonium sulphate aerosol found deviations equivalent to 4.5% RH from the set point of 90% RH compared to results from previous experiments in the literature. Evaluation of the number fraction of particles within the clearly separated growth factor modes of a laboratory generated externally mixed aerosol was done. The data from the H-TDMAs was analysed with a single fitting routine to investigate differences caused by the different data evaluation procedures used for each H-TDMA. The differences between the H-TDMAs were reduced from +12/−13% to +8/−6% when the same analysis routine was applied. We conclude that a common data evaluation procedure to determine number fractions of externally mixed aerosols will improve the comparability of H-TDMA measurements. It is recommended to ensure proper calibration of all flow, temperature and RH sensors in the systems. It is most important to thermally insulate the aerosol humidification unit and the second DMA and to monitor these temperatures to an accuracy of 0.2 °C. For the correct determination of external mixtures, it is necessary to take into account size-dependent losses due to diffusion in the plumbing between the DMAs and in the aerosol humidification unit.

2015, Crenn, V., Sciare, J., Croteau, P.L., Verlhac, S., Fröhlich, R., Belis, C.A., Aas, W., Äijälä, M., Alastuey, A., Artiñano, B., Baisnée, D., Bonnaire, N., Bressi, M., Canagaratna, M., Canonaco, F., Carbone, C., Cavalli, F., Coz, E., Cubison, M.J., Esser-Gietl, J.K., Green, D.C., Gros, V., Heikkinen, L., Herrmann, H., Lunder, C., Minguillón, M.C., Močnik, G., O'Dowd, C.D., Ovadnevaite, J., Petit, J.-E., Petralia, E., Poulain, L., Priestman, M., Riffault, V., Ripoll, A., Sarda-Estève, R., Slowik, J.G., Setyan, A., Wiedensohler, A., Baltensperger, U., Prévôt, A.S.H., Jayne, J.T., Favez, O.

As part of the European ACTRIS project, the first large Quadrupole Aerosol Chemical Speciation Monitor (Q-ACSM) intercomparison study was conducted in the region of Paris for 3 weeks during the late-fall – early-winter period (November–December 2013). The first week was dedicated to the tuning and calibration of each instrument, whereas the second and third were dedicated to side-by-side comparison in ambient conditions with co-located instruments providing independent information on submicron aerosol optical, physical, and chemical properties. Near real-time measurements of the major chemical species (organic matter, sulfate, nitrate, ammonium, and chloride) in the non-refractory submicron aerosols (NR-PM1) were obtained here from 13 Q-ACSM. The results show that these instruments can produce highly comparable and robust measurements of the NR-PM1 total mass and its major components. Taking the median of the 13 Q-ACSM as a reference for this study, strong correlations (r2 > 0.9) were observed systematically for each individual Q-ACSM across all chemical families except for chloride for which three Q-ACSMs showing weak correlations partly due to the very low concentrations during the study. Reproducibility expanded uncertainties of Q-ACSM concentration measurements were determined using appropriate methodologies defined by the International Standard Organization (ISO 17025, 1999) and were found to be 9, 15, 19, 28, and 36 % for NR-PM1, nitrate, organic matter, sulfate, and ammonium, respectively. However, discrepancies were observed in the relative concentrations of the constituent mass fragments for each chemical component. In particular, significant differences were observed for the organic fragment at mass-to-charge ratio 44, which is a key parameter describing the oxidation state of organic aerosol. Following this first major intercomparison exercise of a large number of Q-ACSMs, detailed intercomparison results are presented, along with a discussion of some recommendations about best calibration practices, standardized data processing, and data treatment.

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.

2015, Fröhlich, R., Crenn, V., Setyan, A., Belis, C.A., Canonaco, F., Favez, O., Riffault, V., Slowik, J.G., Aas, W., Aijälä, M., Alastuey, A., Artiñano, B., Bonnaire, N., Bozzetti, C., Bressi, M., Carbone, C., Coz, E., Croteau, P.L., Cubison, M.J., Esser-Gietl, J.K., Green, D.C., Gros, V., Heikkinen, L., Herrmann, H., Jayne, J.T., Lunder, C.R., Minguillón, M.C., Močnik, G., O'Dowd, C.D., Ovadnevaite, J., Petralia, E., Poulain, L., Priestman, M., Ripoll, A., Sarda-Estève, R., Wiedensohler, A., Baltensperger, U., Sciare, J., Prévôt, A.S.H.

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 %.

2011, Tsyro, S., Aas, W., Soares, J., Sofiev, M., Berge, H., Spindler, G.

Sea salt aerosol can significantly affect the air quality. Sea salt can cause enhanced concentrations of particulate matter and change particle chemical composition, in particular in coastal areas, and therefore should be accounted for in air quality modelling. We have used an EMEP Unified model to calculate sea salt concentrations and depositions over Europe, focusing on studying the effects of uncertainties in sea salt production and lifetime on calculation results. Model calculations of sea salt have been compared with EMEP observations of sodium concentrations in air and precipitation for a four year period, from 2004 to 2007, including size (fine/coarse) resolved EMEP intensive measurements in 2006 and 2007. In the presented calculations, sodium air concentrations are between 8% and 46% overestimated, whereas concentrations in precipitation are systematically underestimated by 65–70% for years 2004–2007. A series of model tests have been performed to investigate the reasons for this underestimation, but further studies are needed. The model is found to reproduce the spatial distribution of Na+ in air and precipitation over Europe fairly well, and to capture most of sea salt episodes. The paper presents the main findings from a series of tests in which we compare several different sea spray source functions and also look at the effects of meteorological input and the efficiency of removal processes on calculated sea salt concentrations. Finally, sea salt calculations with the EMEP model have been compared with results from the SILAM model and observations for 2007. While the models produce quite close results for Na+ at the majority of 26 measurement sites, discrepancies in terms of bias and temporal correlation are also found. Those differences are believed to occur due to differences in the representation of source function and size distribution of sea salt aerosol, different meteorology used for model runs and the different models' resolution. This study contributes to getting a better insight on uncertainties associated with sea salt calculations and thus facilitates further improvement of aerosol modelling on both regional and global scales.

2016, Madhavan, Bomidi Lakshmi, Kalisch, John, Macke, Andreas

As part of the High Definition Clouds and Precipitation for advancing Climate Prediction Observational Prototype Experiment (HOPE), a high-density network of 99 silicon photodiode pyranometers was set up around Jülich (10 km × 12 km area) from April to July 2013 to capture the small-scale variability of cloud-induced radiation fields at the surface. In this paper, we provide the details of this unique setup of the pyranometer network, data processing, quality control, and uncertainty assessment under variable conditions. Some exemplary days with clear, broken cloudy, and overcast skies were explored to assess the spatiotemporal observations from the network along with other collocated radiation and sky imager measurements available during the HOPE period.

2016, Pfeifer, Sascha, Müller, Thomas, Weinhold, Kay, Zikova, Nadezda, dos Santos, Sebastiao Martins, Marinoni, Angela, Bischof, Oliver F., Kykal, Carsten, Ries, Ludwig, Meinhardt, Frank, Aalto, Pasi, Mihalopoulos, Nikolaos, Wiedensohler, Alfred

Aerodynamic particle size spectrometers are a well-established method to measure number size distributions of coarse mode particles in the atmosphere. Quality assurance is essential for atmospheric observational aerosol networks to obtain comparable results with known uncertainties. In a laboratory study within the framework of ACTRIS (Aerosols, Clouds, and Trace gases Research Infrastructure Network), 15 aerodynamic particle size spectrometers (APS model 3321, TSI Inc., St. Paul, MN, USA) were compared with a focus on flow rates, particle sizing, and the unit-to-unit variability of the particle number size distribution. Flow rate deviations were relatively small (within a few percent), while the sizing accuracy was found to be within 10 % compared to polystyrene latex (PSL) reference particles. The unit-to-unit variability in terms of the particle number size distribution during this study was within 10 % to 20 % for particles in the range of 0.9 up to 3 µm, which is acceptable for atmospheric measurements. For particles smaller than that, the variability increased up to 60 %, probably caused by differences in the counting efficiencies of individual units. Number size distribution data for particles smaller than 0.9 µm in aerodynamic diameter should only be used with caution. For particles larger than 3 µm, the unit-to-unit variability increased as well. A possible reason is an insufficient sizing accuracy in combination with a steeply sloping particle number size distribution and the increasing uncertainty due to decreasing counting. Particularly this uncertainty of the particle number size distribution must be considered if higher moments of the size distribution such as the particle volume or mass are calculated, which require the conversion of the aerodynamic diameter measured to a volume equivalent diameter. In order to perform a quantitative quality assurance, a traceable reference method for the particle number concentration in the size range 0.5–3 µm is needed.

2015, Zhang, Y., Mahowald, N., Scanza, R.A., Journet, E., Desboeufs, K., Albani, S., Kok, J.F., Zhuang, G., Chen, Y., Cohen, D.D., Paytan, A., Patey, M.D., Achterberg, E.P., Engelbrecht, J.P., Fomba, K.W.

Trace element deposition from desert dust has important impacts on ocean primary productivity, the quantification of which could be useful in determining the magnitude and sign of the biogeochemical feedback on radiative forcing. However, the impact of elemental deposition to remote ocean regions is not well understood and is not currently included in global climate models. In this study, emission inventories for eight elements primarily of soil origin, Mg, P, Ca, Mn, Fe, K, Al, and Si are determined based on a global mineral data set and a soil data set. The resulting elemental fractions are used to drive the desert dust model in the Community Earth System Model (CESM) in order to simulate the elemental concentrations of atmospheric dust. Spatial variability of mineral dust elemental fractions is evident on a global scale, particularly for Ca. Simulations of global variations in the Ca / Al ratio, which typically range from around 0.1 to 5.0 in soils, are consistent with observations, suggesting that this ratio is a good signature for dust source regions. The simulated variable fractions of chemical elements are sufficiently different; estimates of deposition should include elemental variations, especially for Ca, Al and Fe. The model results have been evaluated with observations of elemental aerosol concentrations from desert regions and dust events in non-dust regions, providing insights into uncertainties in the modeling approach. The ratios between modeled and observed elemental fractions range from 0.7 to 1.6, except for Mg and Mn (3.4 and 3.5, respectively). Using the soil database improves the correspondence of the spatial heterogeneity in the modeling of several elements (Ca, Al and Fe) compared to observations. Total and soluble dust element fluxes to different ocean basins and ice sheet regions have been estimated, based on the model results. The annual inputs of soluble Mg, P, Ca, Mn, Fe and K associated with dust using the mineral data set are 0.30 Tg, 16.89 Gg, 1.32 Tg, 22.84 Gg, 0.068 Tg, and 0.15 Tg to global oceans and ice sheets.

2018, Dai, Guangyao, Althausen, Dietrich, Hofer, Julian, Engelmann, Ronny, Seifert, Patric, Bühl, Johannes, Mamouri, Rodanthi-Elisavet, Wu, Songhua, Ansmann, Albert

We present a practical method to continuously calibrate Raman lidar observations of water vapor mixing ratio profiles. The water vapor profile measured with the multiwavelength polarization Raman lidar PollyXT is calibrated by means of co-located AErosol RObotic NETwork (AERONET) sun photometer observations and Global Data Assimilation System (GDAS) temperature and pressure profiles. This method is applied to lidar observations conducted during the Cyprus Cloud Aerosol and Rain Experiment (CyCARE) in Limassol, Cyprus. We use the GDAS temperature and pressure profiles to retrieve the water vapor density. In the next step, the precipitable water vapor from the lidar observations is used for the calibration of the lidar measurements with the sun photometer measurements. The retrieved calibrated water vapor mixing ratio from the lidar measurements has a relative uncertainty of 11 % in which the error is mainly caused by the error of the sun photometer measurements. During CyCARE, nine measurement cases with cloud-free and stable meteorological conditions are selected to calculate the precipitable water vapor from the lidar and the sun photometer observations. The ratio of these two precipitable water vapor values yields the water vapor calibration constant. The calibration constant for the PollyXT Raman lidar is 6.56 g kg−1 ± 0.72 g kg−1 (with a statistical uncertainty of 0.08 g kg−1 and an instrumental uncertainty of 0.72 g kg−1). To check the quality of the water vapor calibration, the water vapor mixing ratio profiles from the simultaneous nighttime observations with Raman lidar and Vaisala radiosonde sounding are compared. The correlation of the water vapor mixing ratios from these two instruments is determined by using all of the 19 simultaneous nighttime measurements during CyCARE. Excellent agreement with the slope of 1.01 and the R2 of 0.99 is found. One example is presented to demonstrate the full potential of a well-calibrated Raman lidar. The relative humidity profiles from lidar, GDAS (simulation) and radiosonde are compared, too. It is found that the combination of water vapor mixing ratio and GDAS temperature profiles allow us to derive relative humidity profiles with the relative uncertainty of 10–20 %.

2011, Fountoukis, C., Racherla, P.N., Denier van der Gon, H.A.C., Polymeneas, P., Charalampidis, P.E., Pilinis, C., Wiedensohler, A., Dall'Osto, M., O'Dowd, C., Pandis, S.N.

Sea salt aerosol can significantly affect the air quality. Sea salt can cause enhanced concentrations of particulate matter and change particle chemical composition, in particular in coastal areas, and therefore should be accounted for in air quality modelling. We have used an EMEP Unified model to calculate sea salt concentrations and depositions over Europe, focusing on studying the effects of uncertainties in sea salt production and lifetime on calculation results. Model calculations of sea salt have been compared with EMEP observations of sodium concentrations in air and precipitation for a four year period, from 2004 to 2007, including size (fine/coarse) resolved EMEP intensive measurements in 2006 and 2007. In the presented calculations, sodium air concentrations are between 8% and 46% overestimated, whereas concentrations in precipitation are systematically underestimated by 65–70% for years 2004–2007. A series of model tests have been performed to investigate the reasons for this underestimation, but further studies are needed. The model is found to reproduce the spatial distribution of Na+ in air and precipitation over Europe fairly well, and to capture most of sea salt episodes. The paper presents the main findings from a series of tests in which we compare several different sea spray source functions and also look at the effects of meteorological input and the efficiency of removal processes on calculated sea salt concentrations. Finally, sea salt calculations with the EMEP model have been compared with results from the SILAM model and observations for 2007. While the models produce quite close results for Na+ at the majority of 26 measurement sites, discrepancies in terms of bias and temporal correlation are also found. Those differences are believed to occur due to differences in the representation of source function and size distribution of sea salt aerosol, different meteorology used for model runs and the different models' resolution. This study contributes to getting a better insight on uncertainties associated with sea salt calculations and thus facilitates further improvement of aerosol modelling on both regional and global scales.