please see the response in the supplement file Please also note the supplement to this comment: http://www.atmos-chem-phys-discuss.net/acp-2016-554/acp-2016-554-AC1-supplement.pdf Interactive comment on Atmos. Chem. Phys. Discuss.,
Abstract. Sulfuric acid has been shown to be a key driver for new particle formation and subsequent growth in various environments, mainly due to its low volatility. However, direct measurements of gas-phase sulfuric acid are oftentimes not available, and the current sulfuric acid proxies cannot predict, for example, its nighttime concentrations or result in significant discrepancies with measured values. Here, we define the sources and sinks of sulfuric acid in different environments and derive a new physical proxy for sulfuric acid to be utilized in locations and during periods when it is not measured. We used H2SO4 measurements from four different locations: Hyytiälä, Finland; Agia Marina, Cyprus; Budapest, Hungary; and Beijing, China, representing semi-pristine boreal forest, rural environment in the Mediterranean area, urban environment and heavily polluted megacity, respectively. The new proxy takes into account the formation of sulfuric acid from SO2 via OH oxidation and other oxidation pathways, specifically via stabilized Criegee intermediates. The sulfuric acid sinks included in the proxy are its condensation sink (CS) and atmospheric clustering starting from H2SO4 dimer formation. Indeed, we found that the observed sulfuric acid concentration can be explained by the proposed sources and sinks with similar coefficients in the four contrasting environments where we have tested it. Thus, the new proxy is a more flexible and an important improvement over previous proxies. Following the recommendations in this paper, a proxy for a specific location can be derived.
Abstract. During an intensive field campaign on aerosol, clouds, and ice nucleation in the Eastern Mediterranean in April 2016, we measured the abundance of ice nucleating particles (INPs) in the lower troposphere from unmanned aircraft systems (UASs). Aerosol samples were collected by miniaturized electrostatic precipitators onboard the UASs at altitudes up to 2.5 km. The number of INPs in these samples, which are active in the deposition and condensation modes at temperatures from −20 to −30 °C, were analyzed immediately after collection on site using the ice nucleus counter FRIDGE (FRankfurt Ice nucleation Deposition freezinG Experiment). During the 1-month campaign, we encountered a series of Saharan dust plumes that traveled at several kilometers' altitude. Here we present INP data from 42 individual flights, together with aerosol number concentrations, observations of lidar backscattering, dust concentrations derived by the dust transport model DREAM (Dust Regional Atmospheric Model), and results from scanning electron microscopy. The effect of the dust plumes is reflected by the coincidence of INPs with the particulate matter (PM), the lidar signal, and the predicted dust mass of the model. This suggests that mineral dust or a constituent related to dust was a major contributor to the ice nucleating properties of the aerosol. Peak concentrations of above 100 INPs std L−1 were measured at −30 °C. The INP concentration in elevated plumes was on average a factor of 10 higher than at ground level. Since desert dust is transported for long distances over wide areas of the globe predominantly at several kilometers' altitude, we conclude that INP measurements at ground level may be of limited significance for the situation at the level of cloud formation.
Abstract. Aerosols 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. Furthermore, we applied this methodology to estimate the INP concentration profiles before and after a cloud formation, indicating the seeding role of the particles and their subsequent impact on cloud formation and characteristics. More synergistic datasets are expected to become available in the future from EARLINET (European Aerosol Research Lidar Network) and in the frame of the European ACTRIS-RI (Aerosols, Clouds, and Trace gases Research Infrastructure). Our analysis shows that the developed techniques, when applied on CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) spaceborne lidar observations, are in agreement with the in situ measurements. This study gives us confidence for the production of global 3-D products of cloud-relevant particle number concentrations (n250,dry, Sdry and nINP) using the CALIPSO 13-year dataset. This could provide valuable insight into the global height-resolved distribution of INP concentrations related to mineral dust, as well as possibly other aerosol types.
Abstract. The composition of fine particulate matter (PM) in two major Greek cities (Athens and Patras) was measured during two wintertime campaigns, one conducted in 2013 and the other in 2012. A major goal of this study is to quantify the sources of organic aerosol (OA) and especially residential wood burning, which has dramatically increased due to the Greek financial crisis. A high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) was deployed at both sites. PM with diameter less than 1 µm (PM 1 ) consisted mainly of organics (60-75 %), black carbon (5-20 %), and inorganic salts (around 20 %) in both Patras and Athens. In Patras, during evening hours, PM 1 concentrations were as high as 100 µg m −3 , of which 85 % was OA. In Athens, the maximum hourly value observed during nighttime was 140 µg m −3 , of which 120 µg m −3 was OA. Forty to 60 % of the average OA was due to biomass burning for both cities, while the remaining mass originated from traffic (12-17 %), cooking (12-16 %), and long-range transport (18-24 %). The contribution of residential wood burning was even higher (80-90 %) during the nighttime peak concentration periods, and less than 10 % during daytime. Cooking OA contributed up to 75 % during mealtime hours in Patras, while trafficrelated OA was responsible for 60-70 % of the OA during the morning rush hour.
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