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- ItemAerosol Particle and Black Carbon Emission Factors of Vehicular Fleet in Manila, Philippines(Basel, Switzerland : MDPI AG, 2019) Madueño, Leizel; Kecorius, Simonas; Birmili, Wolfram; Müller, Thomas; Simpas, James; Vallar, Edgar; Galvez, Maria Cecilia; Cayetano, Mylene; Wiedensohler, AlfredPoor air quality has been identified as one of the main risks to human health, especially in developing regions, where the information on physical chemical properties of air pollutants is lacking. To bridge this gap, we conducted an intensive measurement campaign in Manila, Philippines to determine the emission factors (EFs) of particle number (PN) and equivalent black carbon (BC). The focus was on public utility jeepneys (PUJ), equipped with old technology diesel engines, widely used for public transportation. The EFs were determined by aerosol physical measurements, fleet information, and modeled dilution using the Operational Street Pollution Model (OSPM). The results show that average vehicle EFs of PN and BC in Manila is up to two orders of magnitude higher than European emission standards. Furthermore, a PUJ emits up to seven times more than a light-duty vehicles (LDVs) and contribute to more than 60% of BC emission in Manila. Unfortunately, traffic restrictions for heavy-duty vehicles do not apply to PUJs. The results presented in this work provide a framework to help support targeted traffic interventions to improve urban air quality not only in Manila, but also in other countries with a similar fleet composed of old-technology vehicles. © 2019 by the authors.
- Item3+2 + X : what is the most useful depolarization input for retrieving microphysical properties of non-spherical particles from lidar measurements using the spheroid model of Dubovik et al. (2006)?(Katlenburg-Lindau : Copernicus, 2019) Tesche, Matthias; Kolgotin, Alexei; Haarig, Moritz; Burton, Sharon P.; Ferrare, Richard A.; Hostetler, Chris A.; Müller, DetlefThe typical multiwavelength aerosol lidar data set for inversion of optical to microphysical parameters is composed of three backscatter coefficients (β) at 355, 532, and 1064 nm and two extinction coefficients (α) at 355 and 532 nm. This data combination is referred to as a 3β C 2α or 3 + 2 data set. This set of data is sufficient for retrieving some important microphysical particle parameters if the particles have spherical shape. Here, we investigate the effect of including the particle linear depolarization ratio (δ) as a third input parameter for the inversion of lidar data. The inversion algorithm is generally not used if measurements show values of d that exceed 0.10 at 532 nm, i.e. in the presence of nonspherical particles such as desert dust, volcanic ash, and, under special circumstances, biomass-burning smoke. We use experimental data collected with instruments that are capable of measuring d at all three lidar wavelengths with an inversion routine that applies the spheroidal light-scattering model of Dubovik et al. (2006) with a fixed axis-ratio distribution to replicate scattering properties of non-spherical particles. The inversion gives the fraction of spheroids required to replicate the optical data as an additional output parameter. This is the first systematic test of the effect of using all theoretically possible combinations of d taken at 355, 532, and 1064 nm as input in the lidar data inversion. We find that depolarization information of at least one wavelength already provides useful information for the inversion of optical data that have been collected in the presence of non-spherical mineral dust particles. However, any choice of d will give lower values of the single-scattering albedo than the traditional 3 + 2 data set. We find that input data sets that include d355 give a spheroid fraction that closely resembles the dust ratio we obtain from using β532 and d532 in a methodology applied in aerosol-type separation. The use of d355 in data sets of two or three d? reduces the spheroid fraction that is retrieved when using d532 and d1064. Use of the latter two parameters without accounting for d355 generally leads to high spheroid fractions that we consider not trustworthy. The use of three d instead of two δ, including the constraint that one of these is measured at 355 nm does not provide any advantage over using 3 + 2 + d355 for the observations with varying contributions of mineral dust considered here. However, additional measurements at wavelengths different from 355 nm would be desirable for application to a wider range of aerosol scenarios that may include non-spherical smoke particles, which can have values of d355 that are indistinguishable from those found for mineral dust. We therefore conclude that - depending on measurement capability - the future standard input for inversion of lidar data taken in the presence of mineral dust particles and using the spheroid model of Dubovik et al. (2006) might be 3+2Cδ355 or 3 + 2 + δ355 + δ532. © 2019 The Author(s).
- ItemA comprehensive characterization of ice nucleation by three different types of cellulose particles immersed in water(Katlenburg-Lindau : EGU, 2019) Hiranuma, Naruki; Adachi, Kouji; Bell, David M.; Belosi, Franco; Beydoun, Hassan; Bhaduri, Bhaskar; Bingemer, Heinz; Budke, Carsten; Clemen, Hans-Christian; Conen, Franz; Cory, Kimberly M.; Curtius, Joachim; DeMott, Paul J.; Eppers, Oliver; Grawe, Sarah; Hartmann, Susan; Hoffmann, Nadine; Höhler, Kristina; Jantsch, Evelyn; Kiselev, Alexei; Koop, Thomas; Kulkarni, Gourihar; Mayer, Amelie; Murakami, Masataka; Murray, Benjamin J.; Nicosia, Alessia; Petters, Markus D.; Piazza, Matteo; Polen, Michael; Reicher, Naama; Rudich, Yinon; Saito, Atsushi; Santachiara, Gianni; Schiebel, Thea; Schill, Gregg P.; Schneider, Johannes; Segev, Lior; Stopelli, Emiliano; Sullivan, Ryan C.; Suski, Kaitlyn; Szakáll, Miklós; Tajiri, Takuya; Taylor, Hans; Tobo, Yutaka; Ullrich, Romy; Weber, Daniel; Wex, Heike; Whale, Thomas F.; Whiteside, Craig L.; Yamashita, Katsuya; Zelenyuk, Alla; Möhler, OttmarWe present the laboratory results of immersion freezing efficiencies of cellulose particles at supercooled temperature (T) conditions. Three types of chemically homogeneous cellulose samples are used as surrogates that represent supermicron and submicron ice-nucleating plant structural polymers. These samples include microcrystalline cellulose (MCC), fibrous cellulose (FC) and nanocrystalline cellulose (NCC). Our immersion freezing dataset includes data from various ice nucleation measurement techniques available at 17 different institutions, including nine dry dispersion and 11 aqueous suspension techniques. With a total of 20 methods, we performed systematic accuracy and precision analysis of measurements from all 20 measurement techniques by evaluating T-binned (1 ∘C) data over a wide T range (−36 ∘C 
- ItemTurbulence-induced cloud voids: Observation and interpretation(Katlenburg-Lindau : EGU, 2019) Karpińska, Katarzyna; Bodenschatz, Jonathan F.E.; Malinowski, Szymon P.; Nowak, Jakub L.; Risius, Steffen; Schmeissner, Tina; Shaw, Raymond A.; Siebert, Holger; Xi, Hengdong; Xu, Haitao; Bodenschatz, EberhardThe phenomenon of "cloud voids", i.e., elongated volumes inside a cloud that are devoid of droplets, was observed with laser sheet photography in clouds at a mountain-top station. Two experimental cases, similar in turbulence conditions yet with diverse droplet size distributions and cloud void prevalence, are reported. A theoretical explanation is proposed based on the study of heavy inertial sedimenting particles inside a Burgers vortex. A general conclusion regarding void appearance is drawn from theoretical analysis. Numerical simulations of polydisperse droplet motion with realistic vortex parameters and Mie scattering visual effects accounted for can explain the presence of voids with sizes similar to that of the observed ones. Clustering and segregation effects in a vortex tube are discussed for reasonable cloud conditions. © Author(s) 2019.
- ItemPolarization lidar: An extended three-signal calibration approach(Katlenburg-Lindau : Copernicus, 2019) Jimenez, Cristofer; Ansmann, Albert; Engelmann, Ronny; Haarig, Moritz; Schmidt, Jörg; Wandinger, UllaWe present a new formalism to calibrate a threesignal polarization lidar and to measure highly accurate height profiles of the volume linear depolarization ratios under realistic experimental conditions. The methodology considers elliptically polarized laser light, angular misalignment of the receiver unit with respect to the main polarization plane of the laser pulses, and cross talk among the receiver channels. A case study of a liquid-water cloud observation demonstrates the potential of the new technique. Long-term observations of the calibration parameters corroborate the robustness of the method and the long-term stability of the three-signal polarization lidar. A comparison with a second polarization lidar shows excellent agreement regarding the derived volume linear polarization ratios in different scenarios: A biomass burning smoke event throughout the troposphere and the lower stratosphere up to 16 km in height, a dust case, and also a cirrus cloud case. © Author(s) 2019.
- ItemDevelopment and validation of a supervised machine learning radar Doppler spectra peak-finding algorithm(Katlenburg-Lindau : Copernicus, 2019) Kalesse, Heike; Vogl, Teresa; Paduraru, Cosmin; Luke, EdwardIn many types of clouds, multiple hydrometeor populations can be present at the same time and height. Studying the evolution of these different hydrometeors in a time-height perspective can give valuable information on cloud particle composition and microphysical growth processes. However, as a prerequisite, the number of different hydrometeor types in a certain cloud volume needs to be quantified. This can be accomplished using cloud radar Doppler velocity spectra from profiling cloud radars if the different hydrometeor types have sufficiently different terminal fall velocities to produce individual Doppler spectrum peaks. Here we present a newly developed supervised machine learning radar Doppler spectra peak-finding algorithm (named PEAKO). In this approach, three adjustable parameters (spectrum smoothing span, prominence threshold, and minimum peak width at half-height) are varied to obtain the set of parameters which yields the best agreement of user-classified and machine-marked peaks. The algorithm was developed for Ka-band ARM zenith-pointing radar (KAZR) observations obtained in thick snowfall systems during the Atmospheric Radiation Measurement Program (ARM) mobile facility AMF2 deployment at Hyytiälä, Finland, during the Biogenic Aerosols - Effects on Clouds and Climate (BAECC) field campaign. The performance of PEAKO is evaluated by comparing its results to existing Doppler peak-finding algorithms. The new algorithm consistently identifies Doppler spectra peaks and outperforms other algorithms by reducing noise and increasing temporal and height consistency in detected features. In the future, the PEAKO algorithm will be adapted to other cloud radars and other types of clouds consisting of multiple hydrometeors in the same cloud volume. © 2019 Copernicus GmbH. All rights reserved.
- ItemNew particle formation and its effect on cloud condensation nuclei abundance in the summer Arctic: A case study in the Fram Strait and Barents Sea(Katlenburg-Lindau : EGU, 2019) Kecorius, Simonas; Vogl, Teresa; Paasonen, Pauli; Lampilahti, Janne; Rothenberg, Daniel; Wex, Heike; Zeppenfeld, Sebastian; van Pinxteren, Manuela; Hartmann, Markus; Henning, Silvia; Gong, Xianda; Welti, Andre; Kulmala, Markku; Stratmann, Frank; Herrmann, Hartmut; Wiedensohler, AlfredIn a warming Arctic the increased occurrence of new particle formation (NPF) is believed to originate from the declining ice coverage during summertime. Understanding the physico-chemical properties of newly formed particles, as well as mechanisms that control both particle formation and growth in this pristine environment, is important for interpreting aerosol-cloud interactions, to which the Arctic climate can be highly sensitive. In this investigation, we present the analysis of NPF and growth in the high summer Arctic. The measurements were made on-board research vessel Polarstern during the PS106 Arctic expedition. Four distinctive NPF and subsequent particle growth events were observed, during which particle (diameter in a range 10-50 nm) number concentrations increased from background values of approx. 40 up to 4000 cm-3. Based on particle formation and growth rates, as well as hygroscopicity of nucleation and the Aitken mode particles, we distinguished two different types of NPF events. First, some NPF events were favored by negative ions, resulting in more-hygroscopic nucleation mode particles and suggesting sulfuric acid as a precursor gas. Second, other NPF events resulted in less-hygroscopic particles, indicating the influence of organic vapors on particle formation and growth. To test the climatic relevance of NPF and its influence on the cloud condensation nuclei (CCN) budget in the Arctic, we applied a zero-dimensional, adiabatic cloud parcel model. At an updraft velocity of 0.1 m s-1, the particle number size distribution (PNSD) generated during nucleation processes resulted in an increase in the CCN number concentration by a factor of 2 to 5 compared to the background CCN concentrations. This result was confirmed by the directly measured CCN number concentrations. Although particles did not grow beyond 50 nm in diameter and the activated fraction of 15-50 nm particles was on average below 10 %, it could be shown that the sheer number of particles produced by the nucleation process is enough to significantly influence the background CCN number concentration. This implies that NPF can be an important source of CCN in the Arctic. However, more studies should be conducted in the future to understand mechanisms of NPF, sources of precursor gases and condensable vapors, as well as the role of the aged nucleation mode particles in Arctic cloud formation. © Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License.
- ItemThe importance of the representation of air pollution emissions for the modeled distribution and radiative effects of black carbon in the Arctic(Katlenburg-Lindau : EGU, 2019) Schacht, Jacob; Heinold, Bernd; Quaas, Johannes; Backman, John; Cherian, Ribu; Ehrlich, Andre; Herber, Andreas; Huang, Wan Ting Katty; Kondo, Yutaka; Massling, Andreas; Sinha, P.R.; Weinzierl, Bernadett; Zanatta, Marco; Tegen, InaAerosol particles can contribute to the Arctic amplification (AA) by direct and indirect radiative effects. Specifically, black carbon (BC) in the atmosphere, and when deposited on snow and sea ice, has a positive warming effect on the top-of-atmosphere (TOA) radiation balance during the polar day. Current climate models, however, are still struggling to reproduce Arctic aerosol conditions.We present an evaluation study with the global aerosol-climate model ECHAM6.3-HAM2.3 to examine emission-related uncertainties in the BC distribution and the direct radiative effect of BC. The model results are comprehensively compared against the latest ground and airborne aerosol observations for the period 2005-2017, with a focus on BC. Four different setups of air pollution emissions are tested. The simulations in general match well with the observed amount and temporal variability in near-surface BC in the Arctic. Using actual daily instead of fixed biomass burning emissions is crucial for reproducing individual pollution events but has only a small influence on the seasonal cycle of BC. Compared with commonly used fixed anthropogenic emissions for the year 2000, an up-to-date inventory with transient air pollution emissions results in up to a 30% higher annual BC burden locally. This causes a higher annual mean all-sky net direct radiative effect of BC of over 0.1Wm-2 at the top of the atmosphere over the Arctic region (60-90° N), being locally more than 0.2Wm-2 over the eastern Arctic Ocean. We estimate BC in the Arctic as leading to an annual net gain of 0.5Wm-2 averaged over the Arctic region but to a local gain of up to 0.8Wm-2 by the direct radiative effect of atmospheric BC plus the effect by the BC-in-snow albedo reduction. Long-range transport is identified as one of the main sources of uncertainties for ECHAM6.3-HAM2.3, leading to an overestimation of BC in atmospheric layers above 500 hPa, especially in summer. This is related to a misrepresentation in wet removal in one identified case at least, which was observed during the ARCTAS (Arctic Research of the Composition of the Troposphere from Aircraft and Satellites) summer aircraft campaign. Overall, the current model version has significantly improved since previous intercomparison studies and now performs better than the multi-model average in the Aerosol Comparisons between Observation and Models (AEROCOM) initiative in terms of the spatial and temporal distribution of Arctic BC. © Author(s) 2019.
- ItemRetrieval of ice-nucleating particle concentrations from lidar observations and comparison with UAV in situ measurements(Katlenburg-Lindau : EGU, 2019) Marinou, Eleni; Tesche, Matthias; Nenes, Athanasios; Ansmann, Albert; Schrod, Jann; Mamali, Dimitra; Tsekeri, Alexandra; Pikridas, Michael; Baars, Holger; Engelmann, Ronny; Voudouri, Kalliopi-Artemis; Solomos, Stavros; Sciare, Jean; Groß, Silke; Ewald, Florian; Amiridis, VassilisAerosols that are efficient ice-nucleating particles (INPs) are crucial for the formation of cloud ice via heterogeneous nucleation in the atmosphere. The distribution of INPs on a large spatial scale and as a function of height determines their impact on clouds and climate. However, in situ measurements of INPs provide sparse coverage over space and time. A promising approach to address this gap is to retrieve INP concentration profiles by combining particle concentration profiles derived by lidar measurements with INP efficiency parameterizations for different freezing mechanisms (immersion freezing, deposition nucleation). Here, we assess the feasibility of this new method for both ground-based and spaceborne lidar measurements, using in situ observations collected with unmanned aerial vehicles (UAVs) and subsequently analyzed with the FRIDGE (FRankfurt Ice nucleation Deposition freezinG Experiment) INP counter from an experimental campaign at Cyprus in April 2016. Analyzing five case studies we calculated the cloud-relevant particle number concentrations using lidar measurements (n250,dry with an uncertainty of 20 % to 40 % and Sdry with an uncertainty of 30 % to 50 %), and we assessed the suitability of the different INP parameterizations with respect to the temperature range and the type of particles considered. Specifically, our analysis suggests that our calculations using the parameterization of Ullrich et al. (2017) (applicable for the temperature range −50 to −33 ∘C) agree within 1 order of magnitude with the in situ observations of nINP; thus, the parameterization of Ullrich et al. (2017) can efficiently address the deposition nucleation pathway in dust-dominated environments. Additionally, our calculations using the combination of the parameterizations of DeMott et al. (2015, 2010) (applicable for the temperature range −35 to −9 ∘C) agree within 2 orders of magnitude with the in situ observations of INP concentrations (nINP) and can thus efficiently address the immersion/condensation pathway of dust and nondust particles. The same conclusion is derived from the compilation of the parameterizations of DeMott et al. (2015) for dust and Ullrich et al. (2017) for soot.
- ItemEARLINET evaluation of the CATS Level 2 aerosol backscatter coefficient product(Katlenburg-Lindau : EGU, 2019) Proestakis, Emmanouil; Amiridis, Vassilis; Marinou, Eleni; Binietoglou, Ioannis; Ansmann, Albert; Wandinger, Ulla; Hofer, Julian; Yorks, John; Nowottnick, Edward; Makhmudov, Abduvosit; Papayannis, Alexandros; Pietruczuk, Aleksander; Gialitaki, Anna; Apituley, Arnoud; Szkop, Artur; Muñoz Porcar, Constantino; Bortoli, Daniele; Dionisi, Davide; Althausen, Dietrich; Mamali, Dimitra; Balis, Dimitris; Nicolae, Doina; Tetoni, Eleni; Liberti, Gian Luigi; Baars, Holger; Mattis, Ina; Stachlewska, Iwona Sylwia; Voudouri, Kalliopi Artemis; Mona, Lucia; Mylonaki, Maria; Perrone, Maria Rita; Costa, Maria João; Sicard, Michael; Papagiannopoulos, Nikolaos; Siomos, Nikolaos; Burlizzi, Pasquale; Pauly, Rebecca; Engelmann, Ronny; Abdullaev, Sabur; Pappalardo, GelsominaWe present the evaluation activity of the European Aerosol Research Lidar Network (EARLINET) for the quantitative assessment of the Level 2 aerosol backscatter coefficient product derived by the Cloud-Aerosol Transport System (CATS) aboard the International Space Station (ISS; Rodier et al., 2015). The study employs correlative CATS and EARLINET backscatter measurements within a 50km distance between the ground station and the ISS overpass and as close in time as possible, typically with the starting time or stopping time of the EARLINET performed measurement time window within 90min of the ISS overpass, for the period from February 2015 to September 2016. The results demonstrate the good agreement of the CATS Level 2 backscatter coefficient and EARLINET. Three ISS overpasses close to the EARLINET stations of Leipzig, Germany; Évora, Portugal; and Dushanbe, Tajikistan, are analyzed here to demonstrate the performance of the CATS lidar system under different conditions. The results show that under cloud-free, relative homogeneous aerosol conditions, CATS is in good agreement with EARLINET, independent of daytime and nighttime conditions. CATS low negative biases are observed, partially attributed to the deficiency of lidar systems to detect tenuous aerosol layers of backscatter signal below the minimum detection thresholds; these are biases which may lead to systematic deviations and slight underestimations of the total aerosol optical depth (AOD) in climate studies. In addition, CATS misclassification of aerosol layers as clouds, and vice versa, in cases of coexistent and/or adjacent aerosol and cloud features, occasionally leads to non-representative, unrealistic, and cloud-contaminated aerosol profiles. Regarding solar illumination conditions, low negative biases in CATS backscatter coefficient profiles, of the order of 6.1%, indicate the good nighttime performance of CATS. During daytime, a reduced signal-to-noise ratio by solar background illumination prevents retrievals of weakly scattering atmospheric layers that would otherwise be detectable during nighttime, leading to higher negative biases, of the order of 22.3%. © Author(s) 2019.