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Nucleation of jet engine oil vapours is a large source of aviation-related ultrafine particles
(2022)
Large airports are a major source of ultrafine particles, which spread across densely populated residential areas, affecting air quality and human health. Jet engine lubrication oils are detectable in aviation-related ultrafine particles, however, their role in particle formation and growth remains unclear. Here we show the volatility and new-particle-formation ability of a common synthetic jet oil, and the quantified oil fraction in ambient ultrafine particles downwind of Frankfurt International Airport, Germany. We find that the oil mass fraction is largest in the smallest particles (10-18 nm) with 21% on average. Combining ambient particle-phase concentration and volatility of the jet oil compounds, we determine a lower-limit saturation ratio larger than 1 × 105 for ultra-low volatility organic compounds. This indicates that the oil is an efficient nucleation agent. Our results demonstrate that jet oil nucleation is an important mechanism that can explain the abundant observations of high number concentrations of non-refractory ultrafine particles near airports.
Size-resolved measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted at the remote Amazon Tall Tower Observatory (ATTO) in the central Amazon Basin over a full seasonal cycle (Mar 2014–Feb 2015). In a companion part 1 paper, we presented an in-depth CCN characterization based on annually as well as seasonally averaged time intervals and discuss different parametrization strategies to represent the Amazonian CCN cycling in modelling studies (M. Pöhlker et al., 2016b). The present part 2 study analyzes the aerosol and CCN variability in original time resolution and, thus, resolves aerosol advection and transformation for the following case studies, which represent the most characteristic states of the Amazonian atmosphere:
1. Near-pristine (NP) conditions, defined as the absence of detectable black carbon (< 0.01 µg m−3), showed their highest occurrence (up to 30 %) in the wet season (i.e., Mar–May). On average, the NP episodes are characterized by a bimodal aerosol size distribution (strong Aitken mode: DAit = 70 nm, NAit = ~ 200 cm−3 vs. weaker accumulation mode: Dacc = 170 nm, Nacc = ~ 60 cm−3), a mostly organic particle composition, and relatively low hygroscopicity levels (κAit = 0.12 vs. κacc = 0.18). The NP CCN efficiency spectrum shows that the CCN population is sensitive to changes in supersaturation (S) over a wide S range.
2. Long-range transport (LRT) conditions frequently mix Saharan dust, African combustion smoke, and sea spray aerosols into the Amazonian wet season atmosphere. The LRT episodes (i.e., Feb–Apr) are characterized by an accumulation mode dominated size distribution (DAit = 80 nm, NAit = 120 cm−3 vs. Dacc = 180 nm, Nacc = 300 cm−3), a clearly increased abundance of dust and salt compounds, and relatively high hygroscopicity levels (κAit = 0.18, κacc = 0.34). The LRT CCN efficiency spectrum shows that the CCN population is highly sensitive to changes in S in the low S regime.
3. Biomass burning (BB) conditions dominate the Amazonian dry season. A selected characteristic BB episode shows a very strong accumulation mode (DAit = 70 nm, NAit = ~ 140 cm−3 vs. Dacc = 170 nm, Nacc = ~ 3400 cm−3), particles with very high organic fractions (> 90 %), and correspondingly low hygroscopicity levels (κAit = 0.14, κacc = 0.17). The BB CCN efficiency spectrum shows that the CCN population is highly sensitive to changes in S in the low S regime.
4. Mixed pollution conditions show the superposition of African (i.e., volcanic) and Amazonian (i.e., biomass burning) aerosol emissions during the dry season. The African aerosols showed a broad monomodal distribution (D = 130 nm, N = ~ 1300 cm−3), with very high sulfate fractions (20 %), and correspondingly high hygroscopicity (κAit = 0.14, κacc = 0.22). This was superimposed by fresh smoke from nearby fires with one strong mode (D = 113 nm, Nacc = ~ 2800 cm−3), an organic-dominated aerosol, and sharply decreased hygroscopicity (κAit = 0.10, κacc = 0.20). These conditions underline the rapidly changing pollution regimes with clear impacts on the aerosol and CCN properties.
Overall, this study provides detailed insights into the CCN cycling in relation to aerosol-cloud interaction in the vulnerable and climate-relevant Amazon region. The detailed analysis of aerosol and CCN key properties and particularly the extracted CCN efficiency spectra with the associated fit parameters provide a basis for an in-depth analysis of aerosol-cloud interaction in the Amazon and beyond.
Size-resolved long-term measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted at the remote Amazon Tall Tower Observatory (ATTO) in the central Amazon Basin over a 1-year period and full seasonal cycle (March 2014–February 2015). The measurements provide a climatology of CCN properties characteristic of a remote central Amazonian rain forest site.
The CCN measurements were continuously cycled through 10 levels of supersaturation (S = 0.11 to 1.10 %) and span the aerosol particle size range from 20 to 245 nm. The mean critical diameters of CCN activation range from 43 nm at S = 1.10 % to 172 nm at S = 0.11 %. The particle hygroscopicity exhibits a pronounced size dependence with lower values for the Aitken mode (κAit = 0.14 ± 0.03), higher values for the accumulation mode (κAcc = 0.22 ± 0.05), and an overall mean value of κmean = 0.17 ± 0.06, consistent with high fractions of organic aerosol.
The hygroscopicity parameter, κ, exhibits remarkably little temporal variability: no pronounced diurnal cycles, only weak seasonal trends, and few short-term variations during long-range transport events. In contrast, the CCN number concentrations exhibit a pronounced seasonal cycle, tracking the pollution-related seasonality in total aerosol concentration. We find that the variability in the CCN concentrations in the central Amazon is mostly driven by aerosol particle number concentration and size distribution, while variations in aerosol hygroscopicity and chemical composition matter only during a few episodes.
For modeling purposes, we compare different approaches of predicting CCN number concentration and present a novel parametrization, which allows accurate CCN predictions based on a small set of input data.
Size-resolved long-term measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations as well as hygroscopicity were conducted at the remote Amazon Tall Tower Observatory (ATTO) in the central Amazon Basin over a one-year period and full seasonal cycle (March 2014 - February 2015). The presented measurements provide a climatology of CCN properties for a characteristic central Amazonian rain forest site.
The CCN measurements were continuously cycled through 10 levels of supersaturation (S = 0.11 to 1.10 %) and span the aerosol particle size range from 20 to 245 nm. The observed mean critical diameters of CCN activation range from 43 nm at S = 1.10 % to 172 nm at S = 0.11 %. The particle hygroscopicity exhibits a pronounced size dependence with lower values for the Aitken mode (κAit = 0.14 ± 0.03), elevated values for the accumulation mode (κAcc = 0.22 ± 0.05), and an overall mean value of κmean = 0.17 ± 0.06, consistent with high fractions of organic aerosol.
The hygroscopicity parameter κ exhibits remarkably little temporal variability: no pronounced diurnal cycles, weak seasonal trends, and few short-term variations during long-range transport events. In contrast, the CCN number concentrations exhibit a pronounced seasonal cycle, tracking the pollution-related seasonality in total aerosol concentration. We find that the variability in the CCN concentrations in the central Amazon is mostly driven by aerosol particle number concentration and size distribution, while variations in aerosol hygroscopicity and chemical composition matter only during a few episodes.
For modelling purposes, we compare different approaches of predicting CCN number concentration and present a novel parameterization, which allows accurate CCN predictions based on a small set of input data.
Seven different instruments and measurement methods were used to examine the immersion freezing of bacterial ice nuclei from Snomax® (hereafter Snomax), a product containing ice active protein complexes from non-viable Pseudomonas syringae bacteria. The experimental conditions were kept as similar as possible for the different measurements. Of the participating instruments, some examined droplets which had been made from suspensions directly, and the others examined droplets activated on previously generated Snomax particles, with particle diameters of mostly a few hundred nanometers and up to a few micrometers in some cases. Data were obtained in the temperature range from −2 to −38 °C, and it was found that all ice active protein complexes were already activated above −12 °C. Droplets with different Snomax mass concentrations covering 10 orders of magnitude were examined. Some instruments had very short ice nucleation times down to below 1 s, while others had comparably slow cooling rates around 1 K min−1. Displaying data from the different instruments in terms of numbers of ice active protein complexes per dry mass of Snomax, nm, showed that within their uncertainty the data agree well with each other as well as to previously reported literature results. Two parameterizations were taken from literature for a direct comparison to our results, and these were a time dependent approach based on a contact angle distribution Niedermeier et al. (2014) and a modification of the parameterization presented in Hartmann et~al.~(2013) representing a time independent approach. The agreement between these and the measured data were good, i.e. they agreed within a temperature range of 0.6 K or equivalently a range in nm of a factor of 2. From the results presented herein, we propose that Snomax, at least when carefully shared and prepared, is a suitable material to test and compare different instruments for their accuracy of measuring immersion freezing.
Seven different instruments and measurement methods were used to examine the immersion freezing of bacterial ice nuclei from Snomax® (hereafter Snomax), a product containing ice-active protein complexes from non-viable Pseudomonas syringae bacteria. The experimental conditions were kept as similar as possible for the different measurements. Of the participating instruments, some examined droplets which had been made from suspensions directly, and the others examined droplets activated on previously generated Snomax particles, with particle diameters of mostly a few hundred nanometers and up to a few micrometers in some cases. Data were obtained in the temperature range from −2 to −38 °C, and it was found that all ice-active protein complexes were already activated above −12 °C. Droplets with different Snomax mass concentrations covering 10 orders of magnitude were examined. Some instruments had very short ice nucleation times down to below 1 s, while others had comparably slow cooling rates around 1 K min−1. Displaying data from the different instruments in terms of numbers of ice-active protein complexes per dry mass of Snomax, nm, showed that within their uncertainty, the data agree well with each other as well as to previously reported literature results. Two parameterizations were taken from literature for a direct comparison to our results, and these were a time-dependent approach based on a contact angle distribution (Niedermeier et al., 2014) and a modification of the parameterization presented in Hartmann et al. (2013) representing a time-independent approach. The agreement between these and the measured data were good; i.e., they agreed within a temperature range of 0.6 K or equivalently a range in nm of a factor of 2. From the results presented herein, we propose that Snomax, at least when carefully shared and prepared, is a suitable material to test and compare different instruments for their accuracy of measuring immersion freezing.
Immersion freezing is the most relevant heterogeneous ice nucleation mechanism through which ice crystals are formed in mixed-phase clouds. In recent years, an increasing number of laboratory experiments utilizing a variety of instruments have examined immersion freezing activity of atmospherically relevant ice nucleating particles (INPs). However, an inter-comparison of these laboratory results is a difficult task because investigators have used different ice nucleation (IN) measurement methods to produce these results. A remaining challenge is to explore the sensitivity and accuracy of these techniques and to understand how the IN results are potentially influenced or biased by experimental parameters associated with these techniques.
Within the framework of INUIT (Ice Nucleation research UnIT), we distributed an illite rich sample (illite NX) as a representative surrogate for atmospheric mineral dust particles to investigators to perform immersion freezing experiments using different IN measurement methods and to obtain IN data as a function of particle concentration, temperature (T), cooling rate and nucleation time. Seventeen measurement methods were involved in the data inter-comparison. Experiments with seven instruments started with the test sample pre-suspended in water before cooling, while ten other instruments employed water vapor condensation onto dry-dispersed particles followed by immersion freezing. The resulting comprehensive immersion freezing dataset was evaluated using the ice nucleation active surface-site density (ns) to develop a representative ns(T) spectrum that spans a wide temperature range (−37 °C < T < −11 °C) and covers nine orders of magnitude in ns.
Our inter-comparison results revealed a discrepancy between suspension and dry-dispersed particle measurements for this mineral dust. While the agreement was good below ~ −26 °C, the ice nucleation activity, expressed in ns, was smaller for the wet suspended samples and higher for the dry-dispersed aerosol samples between about −26 and −18 °C. Only instruments making measurement techniques with wet suspended samples were able to measure ice nucleation above −18 °C. A possible explanation for the deviation between −26 and −18 °C is discussed. In general, the seventeen immersion freezing measurement techniques deviate, within the range of about 7 °C in terms of temperature, by three orders of magnitude with respect to ns. In addition, we show evidence that the immersion freezing efficiency (i.e., ns) of illite NX particles is relatively independent on droplet size, particle mass in suspension, particle size and cooling rate during freezing. A strong temperature-dependence and weak time- and size-dependence of immersion freezing efficiency of illite-rich clay mineral particles enabled the ns parameterization solely as a function of temperature. We also characterized the ns (T) spectra, and identified a section with a steep slope between −20 and −27 °C, where a large fraction of active sites of our test dust may trigger immersion freezing. This slope was followed by a region with a gentler slope at temperatures below −27 °C. A multiple exponential distribution fit is expressed as ns(T) = exp(23.82 × exp(−exp(0.16 × (T + 17.49))) + 1.39) based on the specific surface area and ns(T) = exp(25.75 × exp(−exp(0.13 × (T + 17.17))) + 3.34) based on the geometric area (ns and T in m−2 and °C, respectively). These new fits, constrained by using an identical reference samples, will help to compare IN measurement methods that are not included in the present study and, thereby, IN data from future IN instruments.
In this study we show how size-resolved measurements of aerosol particles and cloud condensation nuclei (CCN) can be used to characterize the supersaturation of water vapor in a cloud. The method was developed and applied during the ACRIDICON-Zugspitze campaign (17 September to 4 October 2012) at the high-Alpine research station Schneefernerhaus (German Alps, 2650 m a.s.l.). Number size distributions of total and interstitial aerosol particles were measured with a scanning mobility particle sizer (SMPS), and size-resolved CCN efficiency spectra were recorded with a CCN counter system operated at different supersaturation levels.
During the evolution of a cloud, aerosol particles are exposed to different supersaturation levels. We outline and compare different estimates for the lower and upper bounds (Slow, Shigh) and the average value (Savg) of peak supersaturation encountered by the particles in the cloud. A major advantage of the derivation of Slow and Savg from size-resolved CCN efficiency spectra is that it does not require the specific knowledge or assumptions about aerosol hygroscopicity that are needed to derive estimates of Slow, Shigh, and Savg from aerosol size distribution data. For the investigated cloud event, we derived Slow ≈ 0.07–0.25%, Shigh ≈ 0.86–1.31% and Savg ≈ 0.42–0.68%.
In the present work, three different techniques are used to separate ice-nucleating particles (INP) and ice particle residuals (IPR) from non-ice-active particles: the Ice Selective Inlet (ISI) and the Ice Counterflow Virtual Impactor (Ice-CVI), which sample ice particles from mixed phase clouds and allow for the analysis of the residuals, as well as the combination of the Fast Ice Nucleus Chamber (FINCH) and the Ice Nuclei Pumped Virtual Impactor (IN-PCVI), which provides ice-activating conditions to aerosol particles and extracts the activated ones for analysis. The collected particles were analyzed by scanning electron microscopy and energy-dispersive X-ray microanalysis to determine their size, chemical composition and mixing state. Samples were taken during January/February 2013 at the High Alpine Research Station Jungfraujoch. All INP/IPR-separating techniques had considerable abundances (median 20–70%) of contamination artifacts (ISI: Si-O spheres, probably calibration aerosol; Ice-CVI: Al-O particles; FINCH + IN-PCVI: steel particles). Also, potential measurement artifacts (soluble material) occurred (median abundance < 20%). After removal of the contamination particles, silicates and Ca-rich particles, carbonaceous material and metal oxides were the major INP/IPR particle types separated by all three techniques. Minor types include soot and Pb-bearing particles. Sea-salt and sulfates were identified by all three methods as INP/IPR. Lead was identified in less than 10% of the INP/IPR. It was mainly present as an internal mixture with other particle types, but also external lead-rich particles were found. Most samples showed a maximum of the INP/IPR size distribution at 400 nm geometric diameter. In a few cases, a second super-micron maximum was identified. Soot/carbonaceous material and metal oxides were present mainly in the submicron range. ISI and FINCH yielded silicates and Ca-rich particles mainly with diameters above 1 μm, while the Ice-CVI also sampled many submicron particles. Probably owing to the different meteorological conditions, the INP/IPR composition was highly variable on a sample to sample basis. Thus, some part of the discrepancies between the different techniques may result from the (unavoidable) non-parallel sampling. The observed differences of the particles group abundances as well as the mixing state of INP/IPR point to the need of further studies to better understand the influence of the separating techniques on the INP/IPR chemical composition.