Determination of the collision rate coefficient between charged iodic acid clusters and iodic acid using the appearance time method

He, Xu Cheng; Iyer, Siddharth; Sipilä, Mikko; Ylisirniö, Arttu; Peltola, Maija; Kontkanen, Jenni; Baalbaki, Rima; Simon, Mario; Kürten, Andreas; Tham, Yee Jun; Pesonen, Janne; Ahonen, Lauri; Amanatidis, Stavros; Amorim, A.; Baccarini, Andrea; Beck, Lisa; Bianchi, Federico; Brilke, Sophia; Chen, Dexian; Chiu, Randall; Curtius, Joachim; Dada, Lubna; Dias, António; Dommen, Josef; Donahue, Neil M.; Duplissy, Jonathan; Haddad, Imad El; Finkenzeller, Henning; Fischer, Lukas; Heinritzi, Martin; Hofbauer, Victoria; Kangasluoma, Juha; Kim, Changhyuk; Koenig, Theodore K.; Kubečka, Jakub; Kvashnin, A. N.; Lamkaddam, Houssni; Lee, Chuan Ping; Leiminger, Markus; Махмутов, В. С.; Xiao, Mao; Marten, Ruby; Nie, Wei; Onnela, A.; Partoll, Eva; Petäj̈ä, Tuukka; Salo, Vili; Schuchmann, S.; Steiner, Gerhard; Stolzenburg, Dominik; Stozhkov, Yuri; Tauber, Christian; Tomé, António; Väisänen, Olli; Vazquez‐Pufleau, Miguel; Volkamer, Rainer; Wagner, Andrea C.; Wang, Mingyi; Wang, Yonghong; Wimmer, Daniela; Winkler, Paul M.; Worsnop, Douglas R.; Wu, Yusheng; Yan, Chao; Ye, Qing; Lehtinen, K. E. J.; Nieminen, Tuomo; Manninen, Hanna E.; Rissanen, Matti; Schobesberger, Siegfried; Lehtipalo, Katrianne; Baltensperger, Urs; Hansel, Armin; Kerminen, V.-M.; Flagan, Richard C.; Kirkby, J.; Kurtén, Theo; Kulmala, Markku

doi:10.1080/02786826.2020.1839013

Cited by 24 publications

(53 citation statements)

References 43 publications

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“…The measurement site is located on the west campus of the Beijing University of Chemical Technology, which is close to the west 3rd Ring Road of Beijing. The aerosol size distributions were measured using a homemade particle size distribution system (PSD; Liu et al, 2016) and a homemade diethylene glycol scanning mobility particle spectrometer (Jiang et al, 2011a;DEG-SMPS; equipped with a core-sampling apparatus (Fu et al, 2019). The sulfuric acid monomer and dimer concentrations were measured using a long chemical ionization time-of-flight mass spectrometer (ToF-CIMS; Aerodyne Research, Inc.; Jokinen et al, 2012).…”

Section: Measurementsmentioning

confidence: 99%

Impacts of coagulation on the appearance time method for new particle growth rate evaluation and their corrections

Cai

et al. 2021

Atmos. Chem. Phys.

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Abstract. The growth rate of atmospheric new particles is a key parameter that determines their survival probability of becoming cloud condensation nuclei and hence their impact on the climate. There have been several methods to estimate the new particle growth rate. However, due to the impact of coagulation and measurement uncertainties, it is still challenging to estimate the initial growth rate of new particles, especially in polluted environments with high background aerosol concentrations. In this study, we explore the influences of coagulation on the appearance time method to estimate the growth rate of sub-3 nm particles. The principle of the appearance time method and the impacts of coagulation on the retrieved growth rate are clarified via derivations. New formulae in both discrete and continuous spaces are proposed to correct for the impacts of coagulation. Aerosol dynamic models are used to test the new formulae. New particle formation in urban Beijing is used to illustrate the importance of considering the impacts of coagulation on the sub-3 nm particle growth rate and its calculation. We show that the conventional appearance time method needs to be corrected when the impacts of coagulation sink, coagulation source, and particle coagulation growth are non-negligible compared to the condensation growth. Under the simulation conditions with a constant concentration of non-volatile vapors, the corrected growth rate agrees with the theoretical growth rates. However, the uncorrected parameters, e.g., vapor evaporation and the variation in vapor concentration, may impact the growth rate obtained with the appearance time method. Under the simulation conditions with a varying vapor concentration, the average bias in the corrected 1.5–3 nm particle growth rate ranges from 6 %–44 %, and the maximum bias in the size-dependent growth rate is 150 %. During the test new particle formation event in urban Beijing, the corrected condensation growth rate of sub-3 nm particles was in accordance with the growth rate contributed by sulfuric acid condensation, whereas the conventional appearance time method overestimated the condensation growth rate of 1.5 nm particles by 80 %.

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Section: Measurementsmentioning

confidence: 99%

Impacts of coagulation on the appearance time method for new particle growth rate evaluation and their corrections

Cai

et al. 2021

Atmos. Chem. Phys.

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“…O’Dowd and coworkers ( 3 ) demonstrated that new particles can be produced from condensable iodine-containing vapors. Recent studies ( 4 , 51 ) identified that the cluster formation was sustained by sequential addition of HIO 3 , and although the formation mechanism of HIO 3 is still unclear ( 52 ), the elevated HIO 3 is strongly linked to the photochemistry of IO x . Indeed, the observations of ultrafine particle concentrations in coastal locations are strongly correlated with the rapid processing of IO ( 53 ).…”

Section: Atmospheric Impacts Of Icl and Ibrmentioning

confidence: 99%

Direct field evidence of autocatalytic iodine release from atmospheric aerosol

Tham

et al. 2021

Proc. Natl. Acad. Sci. U.S.A.

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Reactive iodine plays a key role in determining the oxidation capacity, or cleansing capacity, of the atmosphere in addition to being implicated in the formation of new particles in the marine boundary layer. The postulation that heterogeneous cycling of reactive iodine on aerosols may significantly influence the lifetime of ozone in the troposphere not only remains poorly understood but also heretofore has never been observed or quantified in the field. Here, we report direct ambient observations of hypoiodous acid (HOI) and heterogeneous recycling of interhalogen product species (i.e., iodine monochloride [ICl] and iodine monobromide [IBr]) in a midlatitude coastal environment. Significant levels of ICl and IBr with mean daily maxima of 4.3 and 3.0 parts per trillion by volume (1-min average), respectively, have been observed throughout the campaign. We show that the heterogeneous reaction of HOI on marine aerosol and subsequent production of iodine interhalogens are much faster than previously thought. These results indicate that the fast formation of iodine interhalogens, together with their rapid photolysis, results in more efficient recycling of atomic iodine than currently considered in models. Photolysis of the observed ICl and IBr leads to a 32% increase in the daytime average of atomic iodine production rate, thereby enhancing the average daytime iodine-catalyzed ozone loss rate by 10 to 20%. Our findings provide direct field evidence that the autocatalytic mechanism of iodine release from marine aerosol is important in the atmosphere and can have significant impacts on atmospheric oxidation capacity.

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“…Note that for different chemical composition of the input particles, the CPC response might be different. Therefore, the kernels used for analysing experiments where particles were formed from oxidised organics (Kirkby et al, 2016) or from iodic acid (He et al, 2021) are different and approximated by the calibration curves for oxidised beta-caryophyllene and sodium chloride from Wlasits et al (2020).…”

Section: Dma-trainmentioning

confidence: 99%

“…We use experiments performed with the differential mobility analyser-train (DMA-train; Stolzenburg et al, 2017) measuring new particle formation and growth at the CERN CLOUD chamber (Duplissy et al, 2016;Kirkby et al, 2011). In addition to testing the method with synthetic DMA-train data (in which the 'correct' results are known), we estimate formation and growth rates from three different formation and growth experiments: sulphuric-ammonia (Stolzenburg et al, 2020), alpha-pinene ozonolysis (Heinritzi et al, 2020) and iodic acid (He et al, 2021;Sipilä et al, 2016). We compare the formation rates with results obtained by using the methodology by Dada et al (2020) based on particle size magnifier (PSM) measurements and the growth rates with the results obtained by the INSIDE method (Pichelstorfer et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Aerosol formation and growth rates from chamber experiments using Kalman smoothing

et al. 2021

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Abstract. Bayesian state estimation in the form of Kalman smoothing was applied to differential mobility analyser train (DMA-train) measurements of aerosol size distribution dynamics. Four experiments were analysed in order to estimate the aerosol size distribution, formation rate, and size-dependent growth rate, as functions of time. The first analysed case was a synthetic one, generated by a detailed aerosol dynamics model and the other three chamber experiments performed at the CERN CLOUD facility. The estimated formation and growth rates were compared with other methods used earlier for the CLOUD data and with the true values for the computer-generated synthetic experiment. The agreement in the growth rates was very good for all studied cases: estimations with an earlier method fell within the uncertainty limits of the Kalman smoother results. The formation rates also matched well, within roughly a factor of 2.5 in all cases, which can be considered very good considering the fact that they were estimated from data given by two different instruments, the other being the particle size magnifier (PSM), which is known to have large uncertainties close to its detection limit. The presented fixed interval Kalman smoother (FIKS) method has clear advantages compared with earlier methods that have been applied to this kind of data. First, FIKS can reconstruct the size distribution between possible size gaps in the measurement in such a way that it is consistent with aerosol size distribution dynamics theory, and second, the method gives rise to direct and reliable estimation of size distribution and process rate uncertainties if the uncertainties in the kernel functions and numerical models are known.

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Determination of the collision rate coefficient between charged iodic acid clusters and iodic acid using the appearance time method

Abstract: Kulmala (2020): Determination of the collision rate coefficient between charged iodic acid clusters and iodic acid using the appearance time method, Aerosol Science and Technology,

Cited by 24 publications

References 43 publications

Impacts of coagulation on the appearance time method for new particle growth rate evaluation and their corrections

Impacts of coagulation on the appearance time method for new particle growth rate evaluation and their corrections

Direct field evidence of autocatalytic iodine release from atmospheric aerosol

Aerosol formation and growth rates from chamber experiments using Kalman smoothing

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