NO2 Suppression of Autoxidation–Inhibition of Gas-Phase Highly Oxidized Dimer Product Formation

Atmospheric autoxidation of volatile organic compounds (VOC) leads to prompt formation of highly oxidized multifunctional compounds (HOM) that have been found crucial in forming ambient secondary organic aerosol (SOA). As a radical chain reaction mediated by oxidized peroxy (RO2) and alkoxy (RO) radical intermediates, the formation pathways can be intercepted by suitable reaction partners, preventing the production of the highest oxidized reaction products, and thus the formation of the most condensable material. Commonly, NO is expected to have a detrimental effect on RO2 chemistry, and thus on autoxidation, whereas the influence of NO2 is mostly neglected. Here it is shown by dedicated flow tube experiments, how high concentration of NO2 suppresses cyclohexene ozonolysis initiated autoxidation chain reaction. Importantly, the addition of NO2 ceases covalently bound dimer production, indicating their production involving acylperoxy radical (RC(O)OO•) intermediates. In related experiments NO was also shown to strongly suppress the highly oxidized product formation, but due to possibility for chain propagating reactions (as with RO2 and HO2 too), the suppression is not as absolute as with NO2. Furthermore, it is shown how NOx reactions with oxidized peroxy radicals lead into indistinguishable product compositions, complicating mass spectral assignments in any RO2 + NOx system. The present work was conducted with atmospheric pressure chemical ionization mass spectrometry (CIMS) as the detection method for the highly oxidized end-products and peroxy radical intermediates, under ambient conditions and at short few second reaction times. Specifically, the insight was gained by addition of a large amount of NO2 (and NO) to the oxidation system, upon which acylperoxy radicals reacted in RC(O)O2 + NO2 → RC(O)O2NO2 reaction to form peroxyacylnitrates, consequently shutting down the oxidation sequence. Keywords: acylperoxy radicals; Autoxidation; dimers; Highly oxidized multifunctional compounds; Highly oxygenated molecules; HOM; nitrogen oxides; peroxyacylnitratePeer reviewe

Reaction between Peroxy and Alkoxy Radicals Can Form Stable Adducts

Peroxy (RO2) and alkoxy (RO) radicals are prototypical intermediates in any hydrocarbon oxidation. In this work, we use computational methods to (1) study the mechanism and kinetics of the RO2 + OH reaction for previously unexplored “R” structures (R = CH(O)CH2 and R = CH3C(O)) and (2) investigate a hitherto unaccounted channel of molecular growth, R′O2 + RO. On the singlet surface, these reactions rapidly form ROOOH and R′OOOR adducts, respectively. The former decomposes to RO + HO2 and R(O)OH + O2 products, while the main decomposition channel for the latter is back to the reactant radicals. Decomposition rates of R′OOOR adducts varied between 103 and 0.015 s–1 at 298 K and 1 atm. The most long-lived R′OOOR adducts likely account for some fraction of the elemental compositions detected in the atmosphere that are commonly assigned to stable covalently bound dimers.Peer reviewe

MDL Convergence Speed for Bernoulli Sequences

The Minimum Description Length principle for online sequence estimation/prediction in a proper learning setup is studied. If the underlying model class is discrete, then the total expected square loss is a particularly interesting performance measure: (a) this quantity is finitely bounded, implying convergence with probability one, and (b) it additionally specifies the convergence speed. For MDL, in general one can only have loss bounds which are finite but exponentially larger than those for Bayes mixtures. We show that this is even the case if the model class contains only Bernoulli distributions. We derive a new upper bound on the prediction error for countable Bernoulli classes. This implies a small bound (comparable to the one for Bayes mixtures) for certain important model classes. We discuss the application to Machine Learning tasks such as classification and hypothesis testing, and generalization to countable classes of i.i.d. models.Comment: 28 page

Kinetics of the Reactions of CH2Cl, CH3CHCl, and CH3CCl2 Radicals with Cl2 in the Temperature Range 191-363 K

Peer reviewe

Multi-scheme chemical ionization inlet (MION) for fast switching of reagent ion chemistry in atmospheric pressure chemical ionization mass spectrometry (CIMS) applications

A novel chemical ionization inlet named the Multi-scheme chemical IONization inlet (MION), Karsa Ltd., Helsinki, Finland) capable of fast switching between multiple reagent ion schemes is presented, and its performance is demonstrated by measuring several known oxidation products from much-studied cyclohexene and alpha-pinene ozonolysis systems by applying consecutive bromide (Br-) and nitrate (NO3-) chemical ionization. Experiments were performed in flow tube reactors under atmospheric pressure and room temperature (22 degrees C) utilizing an atmospheric pressure interface time-of-flight mass spectrometer (APi-ToF-MS, Tofwerk Ltd., Thun, Switzerland) as the detector. The application of complementary ion modes in probing the same steady-state reaction mixture enabled a far more complete picture of the detailed autoxidation process; the HO2 radical and the least-oxidized reaction products were retrieved with Br- ionization, whereas the highest-oxidized reaction products were detected in the NO3- mode, directly providing information on the first steps and on the ultimate endpoint of oxidation, respectively. While chemical ionization inlets with multiple reagent ion capabilities have been reported previously, an application in which the charging of the sample occurs at atmospheric pressure with practically no sample pretreatment, and with the potential to switch the reagent ion scheme within a second timescale, has not been introduced previously. Also, the ability of bromide ionization todetect highly oxygenated organic molecules (HOM) from atmospheric autoxidation reactions has not been demonstrated prior to this investigation.Peer reviewe

A new determination of the orbit and masses of the Be binary system delta Scorpii

The binary star delta Sco (HD143275) underwent remarkable brightening in the visible in 2000, and continues to be irregularly variable. The system was observed with the Sydney University Stellar Interferometer (SUSI) in 1999, 2000, 2001, 2006 and 2007. The 1999 observations were consistent with predictions based on the previously published orbital elements. The subsequent observations can only be explained by assuming that an optically bright emission region with an angular size of > 2 +/- 1 mas formed around the primary in 2000. By 2006/2007 the size of this region grew to an estimated > 4 mas. We have determined a consistent set of orbital elements by simultaneously fitting all the published interferometric and spectroscopic data as well as the SUSI data reported here. The resulting elements and the brightness ratio for the system measured prior to the outburst in 2000 have been used to estimate the masses of the components. We find Ma = 15 +/- 7 Msun and Mb = 8.0 +/- 3.6 Msun. The dynamical parallax is estimated to be 7.03 +/- 0.15 mas, which is in good agreement with the revised HIPPARCOS parallax.Comment: 8 pages, 4 figs. Accepted for publication in MNRA

Nonparametric Hierarchical Clustering of Functional Data

In this paper, we deal with the problem of curves clustering. We propose a nonparametric method which partitions the curves into clusters and discretizes the dimensions of the curve points into intervals. The cross-product of these partitions forms a data-grid which is obtained using a Bayesian model selection approach while making no assumptions regarding the curves. Finally, a post-processing technique, aiming at reducing the number of clusters in order to improve the interpretability of the clustering, is proposed. It consists in optimally merging the clusters step by step, which corresponds to an agglomerative hierarchical classification whose dissimilarity measure is the variation of the criterion. Interestingly this measure is none other than the sum of the Kullback-Leibler divergences between clusters distributions before and after the merges. The practical interest of the approach for functional data exploratory analysis is presented and compared with an alternative approach on an artificial and a real world data set

(Semi-)Predictive Discretization During Model Selection

In this paper, we present an approach to discretizing multivariate continuous data while learning the structure of a graphical model. We derive the joint scoring function from the principle of predictive accuracy, which inherently ensures the optimal trade-off between goodness of fit and model complexity (including the number of discretization levels). Using the so-called finest grid implied by the data, our scoring function depends only on the number of data points in the various discretization levels. Not only can it be computed efficiently, but it is also independent of the metric used in the continuous space. Our experiments with gene expression data show that discretization plays a crucial role regarding the resulting network structure