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Aerosol optical properties in the southeastern United States in summer - Part 2: Sensitivity of aerosol optical depth to relative humidity and aerosol parameters

2016, Brock, Charles A., Wagner, Nicholas L., Anderson, Bruce E., Attwood, Alexis R., Beyersdorf, Andreas, Campuzano-Jost, Pedro, Carlton, Annmarie G., Day, Douglas A., Diskin, Glenn S., Gordon, Timothy D., Jimenez, Jose L., Lack, Daniel A., Liao, Jin, Markovic, Milos Z., Middlebrook, Ann M., Ng, Nga L., Perring, Anne E., Richardson, Matthews S., Schwarz, Joshua P., Washenfelder, Rebecca A., Welti, Andre, Xu, Lu, Ziemba, Luke D., Murphy, Daniel M.

Aircraft observations of meteorological, trace gas, and aerosol properties were made between May and September 2013 in the southeastern United States (US). Regionally representative aggregate vertical profiles of median and interdecile ranges of the measured parameters were constructed from 37 individual aircraft profiles made in the afternoon when a well-mixed boundary layer with typical fair-weather cumulus was present (Wagner et al., 2015). We use these 0–4 km aggregate profiles and a simple model to calculate the sensitivity of aerosol optical depth (AOD) to changes in dry aerosol mass, relative humidity, mixed-layer height, the central diameter and width of the particle size distribution, hygroscopicity, and dry and wet refractive index, while holding the other parameters constant. The calculated sensitivity is a result of both the intrinsic sensitivity and the observed range of variation in these parameters. These observationally based sensitivity studies indicate that the relationship between AOD and dry aerosol mass in these conditions in the southeastern US can be highly variable and is especially sensitive to relative humidity (RH). For example, calculated AOD ranged from 0.137 to 0.305 as the RH was varied between the 10th and 90th percentile profiles with dry aerosol mass held constant. Calculated AOD was somewhat less sensitive to aerosol hygroscopicity, mean size, and geometric standard deviation, σg. However, some chemistry–climate models prescribe values of σg substantially larger than we or others observe, leading to potential high biases in model-calculated AOD of  ∼  25 %. Finally, AOD was least sensitive to observed variations in dry and wet aerosol refractive index and to changes in the height of the well-mixed surface layer. We expect these findings to be applicable to other moderately polluted and background continental air masses in which an accumulation mode between 0.1–0.5 µm diameter dominates aerosol extinction.

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Characterization and source apportionment of organic aerosol using offline aerosol mass spectrometry

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.

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Immersionmode ice nucleationmeasurements with the new Portable Immersion Mode Cooling chAmber (PIMCA)

2016, Kohn, Monika, Lohmann, Ulrike, Welti, André, Kanji, Zamin A.

The new Portable Immersion Mode Cooling chAmber (PIMCA) has been developed for online immersion freezing of single-immersed aerosol particles. PIMCA is a vertical extension of the established Portable Ice Nucleation Chamber (PINC). PIMCA immerses aerosol particles into cloud droplets before they enter PINC. Immersion freezing experiments on cloud droplets with a radius of 5–7 μm at a prescribed supercooled temperature (T) and water saturation can be conducted, while other ice nucleation mechanisms (deposition, condensation, and contact mode) are excluded. Validation experiments on reference aerosol (kaolinite, ammonium sulfate, and ammonium nitrate) showed good agreement with theory and literature. The PIMCA-PINC setup was tested in the field during the Zurich AMBient Immersion freezing Study (ZAMBIS) in spring 2014 in Zurich, Switzerland. Significant concentrations of submicron ambient aerosol triggering immersion freezing at T > 236 K were rare. The mean frozen cloud droplet number concentration was estimated to be 7.22·105 L−1 for T < 238 K and determined from the measured frozen fraction and cloud condensation nuclei (CCN) concentrations predicted for the site at a typical supersaturation of SS = 0.3%. This value should be considered as an upper limit of cloud droplet freezing via immersion and homogeneous freezing processes. The predicted ice nucleating particle (INP) concentration based on measured total aerosol larger than 0.5 μm and the parameterization by DeMott et al. (2010) at T = 238 K is INPD10=54 ± 39 L−1. This is a lower limit as supermicron particles were not sampled with PIMCA-PINC during ZAMBIS.