2016, Daellenbach, K.R., Bozzetti, C., Křepelová, A., Canonaco, F., Wolf, R., Zotter, P., Fermo, P., Crippa, M., Slowik, J.G., Sosedova, Y., Zhang, Y., Huang, R.-J., Poulain, L., Szidat, S., Baltensperger, U., El Haddad, I., Prévôt, A.S.H.

Field deployments of the Aerodyne Aerosol Mass Spectrometer (AMS) have significantly advanced real-time measurements and source apportionment of non-refractory particulate matter. However, the cost and complex maintenance requirements of the AMS make its deployment at sufficient sites to determine regional characteristics impractical. Furthermore, the negligible transmission efficiency of the AMS inlet for supermicron particles significantly limits the characterization of their chemical nature and contributing sources. In this study, we utilize the AMS to characterize the water-soluble organic fingerprint of ambient particles collected onto conventional quartz filters, which are routinely sampled at many air quality sites. The method was applied to 256 particulate matter (PM) filter samples (PM1, PM2.5, and PM10, i.e., PM with aerodynamic diameters smaller than 1, 2.5, and 10 µm, respectively), collected at 16 urban and rural sites during summer and winter. We show that the results obtained by the present technique compare well with those from co-located online measurements, e.g., AMS or Aerosol Chemical Speciation Monitor (ACSM). The bulk recoveries of organic aerosol (60–91 %) achieved using this technique, together with low detection limits (0.8 µg of organic aerosol on the analyzed filter fraction) allow its application to environmental samples. We will discuss the recovery variability of individual hydrocarbon ions, ions containing oxygen, and other ions. The performance of such data in source apportionment is assessed in comparison to ACSM data. Recoveries of organic components related to different sources as traffic, wood burning, and secondary organic aerosol are presented. This technique, while subjected to the limitations inherent to filter-based measurements (e.g., filter artifacts and limited time resolution) may be used to enhance the AMS capabilities in measuring size-fractionated, spatially resolved long-term data sets.

2016, Warneke, C., Trainer, M., de Gouw, J.A., Parrish, D.D., Fahey, D.W., Ravishankara, A.R., Middlebrook, A.M., Brock, C.A., Roberts, J.M., Brown, S.S., Neuman, J.A., Lerner, B.M., Lack, D., Law, D., Hübler, G., Pollack, I., Sjostedt, S., Ryerson, T.B., Gilman, J B, Liao, J., Holloway, J., Peischl, J., Nowak, J.B., Aikin, K., Min, K.-E., Washenfelder, R.A., Graus, M.G., Richardson, M., Markovic, M.Z., Wagner, N.L., Welti, A., Veres, P.R., Edwards, P., Schwarz, J.P., Gordon, T., Dube, W.P., McKeen, S., Brioude, J., Ahmadov, R., Bougiatioti, A., Lin, J.J., Nenes, A., Wolfe, G.M., Hanisco, T.F., Lee, B.H., Lopez-Hilfiker, F.D., Thornton, J.A., Keutsch, F.N., Kaiser, J., Mao, J., Hatch, C.

Natural emissions of ozone-and-aerosol-precursor gases such as isoprene and monoterpenes are high in the southeast of the US. In addition, anthropogenic emissions are significant in the Southeast US and summertime photochemistry is rapid. The NOAA-led SENEX (Southeast Nexus) aircraft campaign was one of the major components of the Southeast Atmosphere Study (SAS) and was focused on studying the interactions between biogenic and anthropogenic emissions to form secondary pollutants. During SENEX, the NOAA WP-3D aircraft conducted 20 research flights between 27 May and 10 July 2013 based out of Smyrna, TN. Here we describe the experimental approach, the science goals and early results of the NOAA SENEX campaign. The aircraft, its capabilities and standard measurements are described. The instrument payload is summarized including detection limits, accuracy, precision and time resolutions for all gas-and-aerosol phase instruments. The inter-comparisons of compounds measured with multiple instruments on the NOAA WP-3D are presented and were all within the stated uncertainties, except two of the three NO2 measurements. The SENEX flights included day- and nighttime flights in the Southeast as well as flights over areas with intense shale gas extraction (Marcellus, Fayetteville and Haynesville shale). We present one example flight on 16 June 2013, which was a daytime flight over the Atlanta region, where several crosswind transects of plumes from the city and nearby point sources, such as power plants, paper mills and landfills, were flown. The area around Atlanta has large biogenic isoprene emissions, which provided an excellent case for studying the interactions between biogenic and anthropogenic emissions. In this example flight, chemistry in and outside the Atlanta plumes was observed for several hours after emission. The analysis of this flight showcases the strategies implemented to answer some of the main SENEX science questions.

2019, Neubauer, David, Ferrachat, Sylvaine, Siegenthaler-Le Drian, Colombe, Stier, Philip, Partridge, Daniel G., Tegen, Ina, Bey, Isabelle, Stanelle, Tanja, Kokkola, Harri, Lohmann, Ulrike

The global aerosol–climate model ECHAM6.3–HAM2.3 (E63H23) as well as the previous model versions ECHAM5.5–HAM2.0 (E55H20) and ECHAM6.1–HAM2.2 (E61H22) are evaluated using global observational datasets for clouds and precipitation. In E63H23, the amount of low clouds, the liquid and ice water path, and cloud radiative effects are more realistic than in previous model versions. E63H23 has a more physically based aerosol activation scheme, improvements in the cloud cover scheme, changes in the detrainment of convective clouds, changes in the sticking efficiency for the accretion of ice crystals by snow, consistent ice crystal shapes throughout the model, and changes in mixed-phase freezing; an inconsistency in ice crystal number concentration (ICNC) in cirrus clouds was also removed. Common biases in ECHAM and in E63H23 (and in previous ECHAM–HAM versions) are a cloud amount in stratocumulus regions that is too low and deep convective clouds over the Atlantic and Pacific oceans that form too close to the continents (while tropical land precipitation is underestimated). There are indications that ICNCs are overestimated in E63H23. Since clouds are important for effective radiative forcing due to aerosol–radiation and aerosol–cloud interactions (ERFari+aci) and equilibrium climate sensitivity (ECS), differences in ERFari+aci and ECS between the model versions were also analyzed. ERFari+aci is weaker in E63H23 (−1.0 W m−2) than in E61H22 (−1.2 W m−2) (or E55H20; −1.1 W m−2). This is caused by the weaker shortwave ERFari+aci (a new aerosol activation scheme and sea salt emission parameterization in E63H23, more realistic simulation of cloud water) overcompensating for the weaker longwave ERFari+aci (removal of an inconsistency in ICNC in cirrus clouds in E61H22). The decrease in ECS in E63H23 (2.5 K) compared to E61H22 (2.8 K) is due to changes in the entrainment rate for shallow convection (affecting the cloud amount feedback) and a stronger cloud phase feedback. Experiments with minimum cloud droplet number concentrations (CDNCmin) of 40 cm−3 or 10 cm−3 show that a higher value of CDNCmin reduces ERFari+aci as well as ECS in E63H23.

2019, Heikenfeld, Max, Marinescu, Peter J., Christensen, Matthew, Watson-Parris, Duncan, Senf, Fabian, van den Heever, Susan C., Stier, Philip

We introduce tobac (Tracking and Object-Based Analysis of Clouds), a newly developed framework for tracking and analysing individual clouds in different types of datasets, such as cloud-resolving model simulations and geostationary satellite retrievals. The software has been designed to be used flexibly with any two-or three-dimensional timevarying input. The application of high-level data formats, such as Iris cubes or xarray arrays, for input and output allows for convenient use of metadata in the tracking analysis and visualisation. Comprehensive analysis routines are provided to derive properties like cloud lifetimes or statistics of cloud properties along with tools to visualise the results in a convenient way. The application of tobac is presented in two examples. We first track and analyse scattered deep convective cells based on maximum vertical velocity and the threedimensional condensate mixing ratio field in cloud-resolving model simulations. We also investigate the performance of the tracking algorithm for different choices of time resolution of the model output. In the second application, we show how the framework can be used to effectively combine information from two different types of datasets by simultaneously tracking convective clouds in model simulations and in geostationary satellite images based on outgoing longwave radiation. The tobac framework provides a flexible new way to include the evolution of the characteristics of individual clouds in a range of important analyses like model intercomparison studies or model assessment based on observational data. © 2019 Author(s).