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- ItemAerosol optical properties in the southeastern United States in summer - Part 2: Sensitivity of aerosol optical depth to relative humidity and aerosol parameters(Katlenburg-Lindau : EGU, 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.
- ItemAerosol hygroscopicity parameter derived from the light scattering enhancement factor measurements in the North China Plain(Göttingen : Copernicus, 2014) Chen, J.; Zhao, C.S.; Ma, N.; Yan, P.The relative humidity (RH) dependence of aerosol light scattering is an essential parameter for accurate estimation of the direct radiative forcing induced by aerosol particles. Because of insufficient information on aerosol hygroscopicity in climate models, a more detailed parameterization of hygroscopic growth factors and resulting optical properties with respect to location, time, sources, aerosol chemistry and meteorology are urgently required. In this paper, a retrieval method to calculate the aerosol hygroscopicity parameter, κ, is proposed based on the in situ measured aerosol light scattering enhancement factor, namely f(RH), and particle number size distribution (PNSD) obtained from the HaChi (Haze in China) campaign. Measurements show that f(RH) increases sharply with increasing RH, and that the time variance of f(RH) is much greater at higher RH. A sensitivity analysis reveals that the f(RH) is more sensitive to the aerosol hygroscopicity than PNSD. f(RH) for polluted cases is distinctly higher than that for clean periods at a specific RH. The derived equivalent κ, combined with the PNSD measurements, is applied in the prediction of the cloud condensation nuclei (CCN) number concentration. The predicted CCN number concentration with the derived equivalent κ agrees well with the measured ones, especially at high supersaturations. The proposed calculation algorithm of κ with the f(RH) measurements is demonstrated to be reasonable and can be widely applied.
- ItemSize-dependent particle activation properties in fog during the ParisFog 2012/13 field campaign(Göttingen : Copernicus, 2014) Hammer, E.; Gysel, M.; Roberts, G.C.; Elias, T.; Hofer, J.; Hoyle, C.R.; Bukowiecki, N.; Dupont, J.-C.; Burnet, F.; Baltensperger, U.; Weingartner, E.Fog-induced visibility reduction is responsible for a variety of hazards in the transport sector. Therefore there is a large demand for an improved understanding of fog formation and thus improved forecasts. Improved fog forecasts require a better understanding of the numerous complex mechanisms during the fog life cycle. During winter 2012/13 a field campaign called ParisFog aiming at fog research took place at SIRTA (Instrumented Site for Atmospheric Remote Sensing Research). SIRTA is located about 20 km southwest of the Paris city center, France, in a semi-urban environment. In situ activation properties of the prevailing fog were investigated by measuring (1) total and interstitial (non-activated) dry particle number size distributions behind two different inlet systems; (2) interstitial hydrated aerosol and fog droplet size distributions at ambient conditions; and (3) cloud condensation nuclei (CCN) number concentration at different supersaturations (SS) with a CCN counter. The aerosol particles were characterized regarding their hygroscopic properties, fog droplet activation behavior and contribution to light scattering for 17 developed fog events. Low particle hygroscopicity with an overall median of the hygroscopicity parameter, κ, of 0.14 was found, likely caused by substantial influence from local traffic and wood burning emissions. Measurements of the aerosol size distribution at ambient RH revealed that the critical wet diameter, above which the hydrated aerosols activate to fog droplets, is rather large (with a median value of 2.6μm) and is highly variable (ranging from 1 to 5μm) between the different fog events. Thus, the number of activated fog droplets was very small and the non-activated hydrated particles were found to contribute significantly to the observed light scattering and thus to the reduction in visibility. Combining all experimental data, the effective peak supersaturation, SSpeak, a measure of the peak supersaturation during the fog formation, was determined. The median SSpeak value was estimated to be in the range from 0.031 to 0.046% (upper and lower limit estimations), which is in good agreement with previous experimental and modeling studies of fog.
- ItemA novel method for deriving the aerosol hygroscopicity parameter based only on measurements from a humidified nephelometer system(Katlenburg-Lindau : EGU, 2017) Kuang, Ye; Zhao, Chunsheng; Tao, Jiangchuan; Bian, Yuxuan; Ma, Nan; Zhao, GangAerosol hygroscopicity is crucial for understanding roles of aerosol particles in atmospheric chemistry and aerosol climate effects. Light-scattering enhancement factor f (RH, λ) is one of the parameters describing aerosol hygroscopicity, which is defined as f (RH, λ) = δsp(RH, λ)=δsp(dry, λ), where δsp(RH, λ) or δsp(dry, λ) represents δsp at wavelength λ under certain relative humidity (RH) or dry conditions. Traditionally, an overall hygroscopicity parameter κ can be retrieved from measured f (RH, λ), hereinafter referred to as κf(RH), by combining concurrently measured particle number size distribution (PNSD) and mass concentration of black carbon. In this paper, a new method is proposed to directly derive κf(RH) based only on measurements from a three-wavelength humidified nephelometer system. The advantage of this newly proposed approach is that κf(RH) can be estimated without any additional information about PNSD and black carbon. This method is verified with measurements from two different field campaigns. Values of κf(RH) estimated from this new method agree very well with those retrieved by using the traditional method: all points lie near the 1 : 1 line and the square of correlation coefficient between them is 0.99. The verification results demonstrate that this newly proposed method of deriving κf(RH) is applicable at different sites and in seasons of the North China Plain and might also be applicable in other regions around the world.
- ItemLong-term cloud condensation nuclei number concentration, particle number size distribution and chemical composition measurements at regionally representative observatories(Katlenburg-Lindau : EGU, 2018) Schmale, Julia; Henning, Silvia; Decesari, Stefano; Henzing, Bas; Keskinen, Helmi; Sellegri, Karine; Ovadnevaite, Jurgita; Pöhlker, Mira L.; Brito, Joel; Bougiatioti, Aikaterini; Kristensson, Adam; Kalivitis, Nikos; Stavroulas, Iasonas; Carbone, Samara; Jefferson, Anne; Park, Minsu; Schlag, Patrick; Iwamoto, Yoko; Aalto, Pasi; Äijälä, Mikko; Bukowiecki, Nicolas; Ehn, Mikael; Frank, Göran; Fröhlich, Roman; Frumau, Arnoud; Herrmann, Erik; Herrmann, Hartmut; Holzinger, Rupert; Kos, Gerard; Kulmala, Markku; Mihalopoulos, Nikolaos; Nenes, Athanasios; O'Dowd, Colin; Petäjä, Tuukka; Picard, David; Pöhlker, Christopher; Pöschl, Ulrich; Poulain, Laurent; Prévôt, André Stephan Henry; Swietlicki, Erik; Andreae, Meinrat O.; Artaxo, Paulo; Wiedensohler, Alfred; Ogren, John; Matsuki, Atsushi; Yum, Seong Soo; Stratmann, Frank; Baltensperger, Urs; Gysel, MartinAerosol-cloud interactions (ACI) constitute the single largest uncertainty in anthropogenic radiative forcing. To reduce the uncertainties and gain more confidence in the simulation of ACI, models need to be evaluated against observations, in particular against measurements of cloud condensation nuclei (CCN). Here we present a data set - ready to be used for model validation - of long-term observations of CCN number concentrations, particle number size distributions and chemical composition from 12 sites on 3 continents. Studied environments include coastal background, rural background, alpine sites, remote forests and an urban surrounding. Expectedly, CCN characteristics are highly variable across site categories. However, they also vary within them, most strongly in the coastal background group, where CCN number concentrations can vary by up to a factor of 30 within one season. In terms of particle activation behaviour, most continental stations exhibit very similar activation ratios (relative to particles 20nm) across the range of 0.1 to 1.0% supersaturation. At the coastal sites the transition from particles being CCN inactive to becoming CCN active occurs over a wider range of the supersaturation spectrum. Several stations show strong seasonal cycles of CCN number concentrations and particle number size distributions, e.g. at Barrow (Arctic haze in spring), at the alpine stations (stronger influence of polluted boundary layer air masses in summer), the rain forest (wet and dry season) or Finokalia (wildfire influence in autumn). The rural background and urban sites exhibit relatively little variability throughout the year, while short-term variability can be high especially at the urban site. The average hygroscopicity parameter, calculated from the chemical composition of submicron particles was highest at the coastal site of Mace Head (0.6) and lowest at the rain forest station ATTO (0.2-0.3). We performed closure studies based on -Köhler theory to predict CCN number concentrations. The ratio of predicted to measured CCN concentrations is between 0.87 and 1.4 for five different types of . The temporal variability is also well captured, with Pearson correlation coefficients exceeding 0.87. Information on CCN number concentrations at many locations is important to better characterise ACI and their radiative forcing. But long-term comprehensive aerosol particle characterisations are labour intensive and costly. Hence, we recommend operating migrating-CCNCs to conduct collocated CCN number concentration and particle number size distribution measurements at individual locations throughout one year at least to derive a seasonally resolved hygroscopicity parameter. This way, CCN number concentrations can only be calculated based on continued particle number size distribution information and greater spatial coverage of long-term measurements can be achieved.