scholarly journals On the composition of ammonia–sulfuric-acid ion clusters during aerosol particle formation

2015 ◽  
Vol 15 (1) ◽  
pp. 55-78 ◽  
Author(s):  
S. Schobesberger ◽  
A. Franchin ◽  
F. Bianchi ◽  
L. Rondo ◽  
J. Duplissy ◽  
...  

Abstract. The formation of particles from precursor vapors is an important source of atmospheric aerosol. Research at the Cosmics Leaving OUtdoor Droplets (CLOUD) facility at CERN tries to elucidate which vapors are responsible for this new-particle formation, and how in detail it proceeds. Initial measurement campaigns at the CLOUD stainless-steel aerosol chamber focused on investigating particle formation from ammonia (NH3) and sulfuric acid (H2SO4). Experiments were conducted in the presence of water, ozone and sulfur dioxide. Contaminant trace gases were suppressed at the technological limit. For this study, we mapped out the compositions of small NH3–H2SO4 clusters over a wide range of atmospherically relevant environmental conditions. We covered [NH3] in the range from < 2 to 1400 pptv, [H2SO4] from 3.3 × 106 to 1.4 × 109 cm−3 (0.1 to 56 pptv), and a temperature range from −25 to +20 °C. Negatively and positively charged clusters were directly measured by an atmospheric pressure interface time-of-flight (APi-TOF) mass spectrometer, as they initially formed from gas-phase NH3 and H2SO4, and then grew to larger clusters containing more than 50 molecules of NH3 and H2SO4, corresponding to mobility-equivalent diameters greater than 2 nm. Water molecules evaporate from these clusters during sampling and are not observed. We found that the composition of the NH3–H2SO4 clusters is primarily determined by the ratio of gas-phase concentrations [NH3] / [H2SO4], as well as by temperature. Pure binary H2O–H2SO4 clusters (observed as clusters of only H2SO4) only form at [NH3] / [H2SO4] < 0.1 to 1. For larger values of [NH3] / [H2SO4], the composition of NH3–H2SO4 clusters was characterized by the number of NH3 molecules m added for each added H2SO4 molecule n (Δm/Δ n), where n is in the range 4–18 (negatively charged clusters) or 1–17 (positively charged clusters). For negatively charged clusters, Δ m/Δn saturated between 1 and 1.4 for [NH3] / [H2SO4] > 10. Positively charged clusters grew on average by Δm/Δn = 1.05 and were only observed at sufficiently high [NH3] / [H2SO4]. The H2SO4 molecules of these clusters are partially neutralized by NH3, in close resemblance to the acid–base bindings of ammonium bisulfate. Supported by model simulations, we substantiate previous evidence for acid–base reactions being the essential mechanism behind the formation of these clusters under atmospheric conditions and up to sizes of at least 2 nm. Our results also suggest that electrically neutral NH3–H2SO4 clusters, unobservable in this study, have generally the same composition as ionic clusters for [NH3] / [H2SO4] > 10. We expect that NH3–H2SO4 clusters form and grow also mostly by Δm/Δn > 1 in the atmosphere's boundary layer, as [NH3] / [H2SO4] is mostly larger than 10. We compared our results from CLOUD with APi-TOF measurements of NH3–H2SO4 anion clusters during new-particle formation in the Finnish boreal forest. However, the exact role of NH3–H2SO4 clusters in boundary layer particle formation remains to be resolved.

2014 ◽  
Vol 14 (9) ◽  
pp. 13413-13464 ◽  
Author(s):  
S. Schobesberger ◽  
A. Franchin ◽  
F. Bianchi ◽  
L. Rondo ◽  
J. Duplissy ◽  
...  

Abstract. The formation of particles from precursor vapors is an important source of atmospheric aerosol. Research at the Cosmics Leaving OUtdoor Droplets (CLOUD) facility at CERN tries to elucidate which vapors are responsible for this new particle formation, and how in detail it proceeds. Initial measurement campaigns at the CLOUD stainless-steel aerosol chamber focused on investigating particle formation from ammonia (NH3) and sulfuric acid (H2SO4). Experiments were conducted in the presence of water, ozone and sulfur dioxide. Contaminant trace gases were suppressed at the technological limit. For this study, we mapped out the compositions of small NH3-H2SO4 clusters over a wide range of atmospherically relevant environmental conditions. We covered [NH3] in the range from <2 to 1400 pptv, [H2SO4] from 3.3 × 106 to 1.4 × 109 cm−3, and a temperature range from −25 to +20 °C. Negatively and positively charged clusters were directly measured by an atmospheric pressure interface time-of-flight (APi-TOF) mass spectrometer, as they initially formed from gas-phase NH3 and H2SO4, and then grew to larger clusters containing more than 50 molecules of NH3 and H2SO4, corresponding to mobility-equivalent diameters greater than 2 nm. Water molecules evaporate from these clusters during sampling and are not observed. We found that the composition of the NH3-H2SO4 clusters is primarily determined by the ratio of gas-phase concentrations [NH3] / [H2SO4], as well as by temperature. Pure binary H2O-H2SO4 clusters (observed as clusters of only H2SO4) only form at [NH3] / [H2SO4]<0.1 to 1. For larger values of [NH3] / [H2SO4], the composition of NH3-H2SO4 clusters was characterized by the number of NH3 molecules m added for each added H2SO4 molecule n (Δm / Δn), where n is in the range 4–18 (negatively charged clusters) or 1–17 (positively charged clusters). For negatively charged clusters, Δm / Δn saturated between 1 and 1.4 for [NH3] / [H2SO4]>10. Positively charged clusters grew on average by Δm / Δn = 1.05 and were only observed at sufficiently high [NH3] / [H2SO4]. The H2SO4 molecules of these clusters are partially neutralized by NH3, in close resemblance to the acid-base bindings of ammonium bisulfate. Supported by model simulations, we substantiate previous evidence for acid-base reactions being the essential mechanism behind the formation of these clusters under atmospheric conditions and up to sizes of at least 2 nm. Our results also suggest that yet unobservable electrically neutral NH3-H2SO4 clusters grow by generally the same mechanism as ionic clusters, particularly for [NH3] / [H2SO4]>10. We expect that NH3-H2SO4 clusters form and grow also mostly by Δm / Δn>1 in the atmosphere's boundary layer, as [NH3] / [H2SO4] is mostly larger than 10. We compared our results from CLOUD with APi-TOF measurements of NH3-H2SO4 anion clusters during new particle formation in the Finnish boreal forest. However, the exact role of NH3-H2SO4 clusters in boundary layer particle formation remains to be resolved.


2017 ◽  
Author(s):  
Andreas Kürten ◽  
Chenxi Li ◽  
Federico Bianchi ◽  
Joachim Curtius ◽  
António Dias ◽  
...  

Abstract. A recent CLOUD (Cosmics Leaving OUtdoor Droplets) chamber study showed that sulfuric acid and dimethylamine produce new aerosols very efficiently, and yield particle formation rates that are compatible with boundary layer observations. These previously published new particle formation (NPF) rates are re-analyzed in the present study with an advanced method. The results show that the NPF rates at 1.7 nm are more than a factor of 10 faster than previously published due to earlier approximations in correcting particle measurements made at larger detection threshold. The revised NPF rates agree almost perfectly with calculated rates from a kinetic aerosol model at different sizes (1.7 nm and 4.3 nm mobility diameter). In addition, modeled and measured size distributions show good agreement over a wide range (up to ca. 30 nm). Furthermore, the aerosol model is modified such that evaporation rates for some clusters can be taken into account; these evaporation rates were previously published from a flow tube study. Using this model, the findings from the present study and the flow tube experiment can be brought into good agreement. This confirms that nucleation proceeds at rates that are compatible with collision-controlled (a.k.a. kinetically-controlled) new particle formation for the conditions during the CLOUD7 experiment (278 K, 38 % RH, sulfuric acid concentration between 1 × 106 and 3 × 107 cm−3 and dimethylamine mixing ratio of ~ 40 pptv). Finally, the simulation of atmospheric new particle formation reveals that even tiny mixing ratios of dimethylamine (0.1 pptv) yield NPF rates that could explain significant boundary layer particle formation. This highlights the need for improved speciation and quantification techniques for atmospheric gas-phase amine measurements.


2007 ◽  
Vol 7 (1) ◽  
pp. 211-222 ◽  
Author(s):  
M. Ehn ◽  
T. Petäjä ◽  
H. Aufmhoff ◽  
P. Aalto ◽  
K. Hämeri ◽  
...  

Abstract. The hygroscopic growth of aerosol particles present in a boreal forest was measured at a relative humidity of 88%. Simultaneously the gas phase concentration of sulfuric acid, a very hygroscopic compound, was monitored. The focus was mainly on days with new particle formation by nucleation. The measured hygroscopic growth factors (GF) correlated positively with the gaseous phase sulfuric acid concentrations. The smaller the particles, the stronger the correlation, with r=0.20 for 50 nm and r=0.50 for 10 nm particles. The increase in GF due to condensing sulfuric acid is expected to be larger for particles with initially smaller masses. During new particle formation, the changes in solubility of the new particles were calculated during their growth to Aitken mode sizes. As the modal diameter increased, the solubility of the particles decreased. This indicated that the initial particle growth was due to more hygroscopic compounds, whereas the later growth during the evening and night was mainly caused by less hygroscopic or even hydrophobic compounds. For all the measured sizes, a diurnal variation in GF was observed both during days with and without particle formation. The GF was lowest at around midnight, with a mean value of 1.12–1.24 depending on particle size and if new particle formation occurred during the day, and increased to 1.25–1.34 around noon. This can be tentatively explained by day- and nighttime gas-phase chemistry; different vapors will be present depending on the time of day, and through condensation these compounds will alter the hygroscopic properties of the particles in different ways.


2018 ◽  
Vol 18 (3) ◽  
pp. 1835-1861 ◽  
Author(s):  
Johannes Größ ◽  
Amar Hamed ◽  
André Sonntag ◽  
Gerald Spindler ◽  
Hanna Elina Manninen ◽  
...  

Abstract. This paper revisits the atmospheric new particle formation (NPF) process in the polluted Central European troposphere, focusing on the connection with gas-phase precursors and meteorological parameters. Observations were made at the research station Melpitz (former East Germany) between 2008 and 2011 involving a neutral cluster and air ion spectrometer (NAIS). Particle formation events were classified by a new automated method based on the convolution integral of particle number concentration in the diameter interval 2–20 nm. To study the relevance of gaseous sulfuric acid as a precursor for nucleation, a proxy was derived on the basis of direct measurements during a 1-month campaign in May 2008. As a major result, the number concentration of freshly produced particles correlated significantly with the concentration of sulfur dioxide as the main precursor of sulfuric acid. The condensation sink, a factor potentially inhibiting NPF events, played a subordinate role only. The same held for experimentally determined ammonia concentrations. The analysis of meteorological parameters confirmed the absolute need for solar radiation to induce NPF events and demonstrated the presence of significant turbulence during those events. Due to its tight correlation with solar radiation, however, an independent effect of turbulence for NPF could not be established. Based on the diurnal evolution of aerosol, gas-phase, and meteorological parameters near the ground, we further conclude that the particle formation process is likely to start in elevated parts of the boundary layer rather than near ground level.


2018 ◽  
Vol 18 (2) ◽  
pp. 845-863 ◽  
Author(s):  
Andreas Kürten ◽  
Chenxi Li ◽  
Federico Bianchi ◽  
Joachim Curtius ◽  
António Dias ◽  
...  

Abstract. A recent CLOUD (Cosmics Leaving OUtdoor Droplets) chamber study showed that sulfuric acid and dimethylamine produce new aerosols very efficiently and yield particle formation rates that are compatible with boundary layer observations. These previously published new particle formation (NPF) rates are reanalyzed in the present study with an advanced method. The results show that the NPF rates at 1.7 nm are more than a factor of 10 faster than previously published due to earlier approximations in correcting particle measurements made at a larger detection threshold. The revised NPF rates agree almost perfectly with calculated rates from a kinetic aerosol model at different sizes (1.7 and 4.3 nm mobility diameter). In addition, modeled and measured size distributions show good agreement over a wide range of sizes (up to ca. 30 nm). Furthermore, the aerosol model is modified such that evaporation rates for some clusters can be taken into account; these evaporation rates were previously published from a flow tube study. Using this model, the findings from the present study and the flow tube experiment can be brought into good agreement for the high base-to-acid ratios (∼ 100) relevant for this study. This confirms that nucleation proceeds at rates that are compatible with collision-controlled (a.k.a. kinetically controlled) NPF for the conditions during the CLOUD7 experiment (278 K, 38 % relative humidity, sulfuric acid concentration between 1 × 106 and 3 × 107 cm−3, and dimethylamine mixing ratio of ∼ 40 pptv, i.e., 1 × 109 cm−3).


2020 ◽  
Author(s):  
Anna Shcherbacheva ◽  
Tapio Helin ◽  
Heikki Haario ◽  
Hanna Vehkamäki

&lt;p&gt;Atmospheric new particle formation and successive cluster growth to aerosol particles is an important field of research, in particular due to climate change phenomena and air quality monitoring. Recent developments in the instrumentation have enabled quantification of ionic clusters formed in the gas phase at the first steps of particle formation under atmospherically relevant mixing ratios. However, electrically neutral clusters are prevalent in atmospheric conditions, and thus must be charged prior to detection by mass spectrometer. The charging process can lead to cluster fragmentation and thus alter the measured cluster composition.&lt;/p&gt;&lt;p&gt;Even when the cluster composition can be measured directly, this does not quantify individual cluster-level properties, such as cluster collision and evaporation rates. Collision rates contain relatively small uncertainties in comparison to evaporation rates, which are computed using detailed balance assumption together with the free energies of cluster formation, which can in turn be obtained from Quantum chemistry (QC) methods. As evaporation rates depend exponentially on the free energies, even difference by several kcal/mol between different QC methods results in orders of magnitude differences in evaporation rates.&lt;/p&gt;&lt;p&gt;On the other hand, in spite of the error margins associated with the evaporation rates, simulations of cluster populations, which incorporate collision and evaporation rates as free parameters (such as Becker-D&amp;#246;ring models), have demonstrated good qualitative agreement with experimental data. The Becker-D&amp;#246;ring equations are a system of Ordinary Differential equations (ODE) which account for cluster birth and death processes, as well as external sinks and sources. In mathematical terms, prediction of cluster concentrations using kinetic simulations with given cluster collision and evaporation rates is called a forward problem.&lt;/p&gt;&lt;p&gt;In the present study, we focus on the so-called inverse problem of how to derive the evaporation rates and thermodynamic data (enthalpy change and entropy change due to addition or removal of molecule) from available measurements, rather than on the forward problem. We do this by Delayed Rejection Adaptive Monte Carlo (DRAM) method for the system containing sulfuric acid and ammonia with the maximal size of the pentamer. Initially, we tested the method on the synthetic data created from Atmospheric Cluster Dynamic Code (ACDC) simulations. By so doing, we identify the combination of fitted parameters and concentration measurements, which leads to the best identification of the evaporation rates. Additionally, we demonstrated that the temperature-dependent data yield better estimates of the evaporation rates as compared to the time-dependent data measured before the system has reached the steady state.&lt;/p&gt;&lt;p&gt;Next, we apply the technique to improve the identification of the evaporation rates from CLOUD chamber data, which contain cluster concentrations and new particle formation rates measured at different temperatures and a wide range of atmospherically relevant sulfuric acid and ammonia concentrations. As a result, we were able to obtain the probability density functions (PDFs) that show small standard variations for thermodynamic data. By using the values from the PDFs as parameters in the ACDC model, we achieve a fair agreement with the measured NPFs and cluster concentrations for a wide range of temperatures.&lt;/p&gt;


2020 ◽  
Author(s):  
Vitus Besel ◽  
Jakub Kubečka ◽  
Theo Kurtén ◽  
Hanna Vehkamäki

&lt;div&gt; &lt;p&gt;The bulk of aerosol particles in the atmosphere are formed by gas-to-particle nucleation (Merikanto et al., 2009). However, the exact process of single molecules forming cluster, which subsequently can grow into particles, remains largely unknown. Recently, sulfuric acid has been identified to play a key role in this new particle formation enhanced by other compounds such as organic acids (Zhang, 2010) or ammonia (Anttila et al., 2005). To identify the characteristics of cluster formation and nucleation involving sulfuric acid and ammonia in neutral, positive and negative modes, we conducted a computational study. We used a layered approach for configurational sampling of the molecular clusters starting from utilizing a genetic algorithm in order to explore the whole potential energy surface (PES) with all plausible geometrical minima, however, with very unreliable energies. The structures were further optimized with a semi-empirical method and, then, at the &amp;#969;B97X-D DFT level of theory. After each step, the optimized geometries were filtered to obtain the global minimum configuration. Further, a high level of theory (DLPNO-CCSD(T)) was used for obtaining the electronic energies, in addition to performing DFT frequency analysis, to calculate the Gibbs free energies of formation. These were passed to the Atmospheric Cluster Dynamics Code (ACDC) (McGrath et al., 2012) for studying the evolution of cluster populations. We determined the global minima for the following sulfuric acid - ammonia clusters: (H&lt;sub&gt;2&lt;/sub&gt;SO&lt;sub&gt;4&lt;/sub&gt;)&lt;sub&gt;m&lt;/sub&gt;(NH&lt;sub&gt;3&lt;/sub&gt;)&lt;sub&gt;n&lt;/sub&gt; with m=n, m=n+1 and n=m+1 for neutral clusters, (H&lt;sub&gt;2&lt;/sub&gt;SO&lt;sub&gt;4&lt;/sub&gt;)&lt;sub&gt;m&lt;/sub&gt;(HSO&lt;sub&gt;4&lt;/sub&gt;)&lt;sup&gt;&amp;#8722;&lt;/sup&gt;(NH&lt;sub&gt;3&lt;/sub&gt;)&lt;sub&gt;n&lt;/sub&gt; with m=n and n=m+1 for positively charged clusters, and (H&lt;sub&gt;2&lt;/sub&gt;SO&lt;sub&gt;4&lt;/sub&gt;)&lt;sub&gt;m&lt;/sub&gt;(NH&lt;sub&gt;4&lt;/sub&gt;)&lt;sup&gt;+&lt;/sup&gt;(NH&lt;sub&gt;3&lt;/sub&gt;)&lt;sub&gt;n&lt;/sub&gt; with m=n and m=n+1 for negatively charged clusters. Further, we present the formation rates, steady state concentrations and fluxes of these clusters calculated using ACDC and discuss how a new configurational sampling procedure, more precise quantum chemistry methods and parameters, such as symmetry and a quasiharmonic approach, impact these ACDC results in comparison to previous studies.&lt;/p&gt; &lt;/div&gt;&lt;div&gt; &lt;p&gt;&lt;em&gt;References:&lt;br&gt;&lt;/em&gt;&lt;em&gt;J. Merikanto, D. V. Spracklen, G. W. Mann, S. J. Pickering, and K. S. Carslaw (2009). Atmos. Chem.&amp;#160; Phys., 9, 8601-8616. &lt;br&gt;R. Zhang (2010). Science, 328, 1366-1367. &lt;br&gt;T. Anttila, H. Vehkam&amp;#228;ki, I. Napari, M. Kulmala (2005). Boreal Env. Res., 10, 523. &lt;br&gt;M.J. McGrath, T. Olenius, I.K. Ortega, V. Loukonen, P.&amp;#160; Paasonen, T. Kurten, M. Kulmala (2012). Atmos. Chem. Phys., 12, 2355. &lt;br&gt;&lt;/em&gt;&lt;/p&gt; &lt;/div&gt;


2019 ◽  
Author(s):  
Andreas Kürten

Abstract. Understanding new particle formation and growth is important because of the strong impact of these processes on climate and air quality. Measurements to elucidate the main new particle formation mechanisms are essential; however, these mechanisms have to be implemented in models to estimate their impact on the regional and global scale. Parameterizations are computationally cheap ways of implementing nucleation schemes in models but they have their limitations, as they do not necessarily include all relevant parameters. Process models using sophisticated nucleation schemes can be useful for the generation of look-up tables in large-scale models or for the analysis of individual new particle formation events. In addition, some other important properties can be derived from a process model that implicitly calculates the evolution of the full aerosol size distribution, e.g., the particle growth rates. Within this study, a model (SANTIAGO, Sulfuric acid Ammonia NucleaTIon And GrOwth model) is constructed that simulates new particle formation starting from the monomer of sulfuric acid up to a particle size of several hundred nanometers. The smallest sulfuric acid clusters containing one to four acid molecules and varying amount of base (ammonia) are allowed to evaporate in the model, whereas growth beyond the pentamer (5 sulfuric acid molecules) is assumed to be entirely collision-controlled. The main goal of the present study is to derive appropriate thermodynamic data needed to calculate the cluster evaporation rates as a function of temperature. These data are derived numerically from CLOUD (Cosmics Leaving OUtdoor Droplets) chamber new particle formation rates for neutral sulfuric acid-water-ammonia nucleation at temperatures between 208 K and 292 K. The numeric methods include an optimization scheme to derive the best estimates for the thermodynamic data (dH and dS) and a Monte Carlo method to derive their probability density functions. The derived data are compared to literature values. Using different data sets for dH and dS in SANTIAGO detailed comparison between model results and measured CLOUD new particle formation rates is discussed.


2019 ◽  
Vol 19 (7) ◽  
pp. 5033-5050 ◽  
Author(s):  
Andreas Kürten

Abstract. Understanding new particle formation and growth is important because of the strong impact of these processes on climate and air quality. Measurements to elucidate the main new particle formation mechanisms are essential; however, these mechanisms have to be implemented in models to estimate their impact on the regional and global scale. Parameterizations are computationally cheap ways of implementing nucleation schemes in models, but they have their limitations, as they do not necessarily include all relevant parameters. Process models using sophisticated nucleation schemes can be useful for the generation of look-up tables in large-scale models or for the analysis of individual new particle formation events. In addition, some other important properties can be derived from a process model that implicitly calculates the evolution of the full aerosol size distribution, e.g., the particle growth rates. Within this study, a model (SANTIAGO – Sulfuric acid Ammonia NucleaTIon And GrOwth model) is constructed that simulates new particle formation starting from the monomer of sulfuric acid up to a particle size of several hundred nanometers. The smallest sulfuric acid clusters containing one to four acid molecules and a varying amount of base (ammonia) are allowed to evaporate in the model, whereas growth beyond the pentamer (five sulfuric acid molecules) is assumed to be entirely collision-controlled. The main goal of the present study is to derive appropriate thermodynamic data needed to calculate the cluster evaporation rates as a function of temperature. These data are derived numerically from CLOUD (Cosmics Leaving OUtdoor Droplets) chamber new particle formation rates for neutral sulfuric acid–water–ammonia nucleation at temperatures between 208 and 292 K. The numeric methods include an optimization scheme to derive the best estimates for the thermodynamic data (dH and dS) and a Monte Carlo method to derive their probability density functions. The derived data are compared to literature values. Using different data sets for dH and dS in SANTIAGO detailed comparison between model results and measured CLOUD new particle formation rates is discussed.


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