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Author: Pöschl, U. × Subject: atmospheric chemistry ×

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    Scanning supersaturation condensation particle counter applied as a nano-CCN counter for size-resolved analysis of the hygroscopicity and chemical composition of nanoparticles
    (München : European Geopyhsical Union, 2015) Wang, Z.; Su, H.; Wang, X.; Ma, N.; Wiedensohler, A.; Pöschl, U.; Cheng, Y.
    Knowledge about the chemical composition of aerosol particles is essential to understand their formation and evolution in the atmosphere. Due to analytical limitations, however, relatively little information is available for sub-10 nm particles. We present the design of a nano-cloud condensation nuclei counter (nano-CCNC) for measuring size-resolved hygroscopicity and inferring chemical composition of sub-10 nm aerosol particles. We extend the use of counting efficiency spectra from a water-based condensation particle counter (CPC) and link it to the analysis of CCN activation spectra, which provides a theoretical basis for the application of a scanning supersaturation CPC (SS-CPC) as a nano-CCNC. Measurement procedures and data analysis methods are demonstrated through laboratory experiments with monodisperse particles of diameter down to 2.5 nm, where sodium chloride, ammonium sulfate, sucrose and tungsten oxide can be easily discriminated by different characteristic supersaturations of water droplet formation. A near-linear relationship between hygroscopicity parameter κ and organic mass fraction is also found for sucrose-ammonium sulfate mixtures. The design is not limited to the water CPC, but also applies to CPCs with other working fluids (e.g. butanol, perfluorotributylamine). We suggest that a combination of SS-CPCs with multiple working fluids may provide further insight into the chemical composition of nanoparticles and the role of organic and inorganic compounds in the initial steps of atmospheric new particle formation and growth.
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    The Global Aerosol Synthesis and Science Project (GASSP): Measurements and Modeling to Reduce Uncertainty
    (Boston, Mass. : ASM, 2017) Reddington, C.L.; Carslaw, K.S.; Stier, P.; Schutgens, N.; Coe, H.; Liu, D.; Allan, J.; Browse, J.; Pringle, K.J.; Lee, L.A.; Yoshioka, M.; Johnson, J.S.; Regayre, L.A.; Spracklen, D.V.; Mann, G.W.; Clarke, A.; Hermann, M.; Henning, S.; Wex, H.; Kristensen, T.B.; Leaitch, W.R.; Pöschl, U.; Rose, D.; Andreae, M.O.; Schmale, J.; Kondo, Y.; Oshima, N.; Schwarz, J.P.; Nenes, A.; Anderson, B.; Roberts, G.C.; Snider, J.R.; Leck, C.; Quinn, P.K.; Chi, X.; Ding, A.; Jimenez, J.L.; Zhang, Q.
    The largest uncertainty in the historical radiative forcing of climate is caused by changes in aerosol particles due to anthropogenic activity. Sophisticated aerosol microphysics processes have been included in many climate models in an effort to reduce the uncertainty. However, the models are very challenging to evaluate and constrain because they require extensive in situ measurements of the particle size distribution, number concentration, and chemical composition that are not available from global satellite observations. The Global Aerosol Synthesis and Science Project (GASSP) aims to improve the robustness of global aerosol models by combining new methodologies for quantifying model uncertainty, to create an extensive global dataset of aerosol in situ microphysical and chemical measurements, and to develop new ways to assess the uncertainty associated with comparing sparse point measurements with low-resolution models. GASSP has assembled over 45,000 hours of measurements from ships and aircraft as well as data from over 350 ground stations. The measurements have been harmonized into a standardized format that is easily used by modelers and nonspecialist users. Available measurements are extensive, but they are biased to polluted regions of the Northern Hemisphere, leaving large pristine regions and many continental areas poorly sampled. The aerosol radiative forcing uncertainty can be reduced using a rigorous model–data synthesis approach. Nevertheless, our research highlights significant remaining challenges because of the difficulty of constraining many interwoven model uncertainties simultaneously. Although the physical realism of global aerosol models still needs to be improved, the uncertainty in aerosol radiative forcing will be reduced most effectively by systematically and rigorously constraining the models using extensive syntheses of measurements.