Top PDF Oxidation of SO<sub>2</sub> by stabilized Criegee intermediate (sCI) radicals as a crucial source for atmospheric sulfuric acid concentrations

Oxidation of SO<sub>2</sub> by stabilized Criegee intermediate (sCI) radicals as a crucial source for atmospheric sulfuric acid concentrations

Oxidation of SO<sub>2</sub> by stabilized Criegee intermediate (sCI) radicals as a crucial source for atmospheric sulfuric acid concentrations

action rate for the monoterpene-originated sCIs by one and two orders of magnitude (D1 and D2, respectively) and then decreased the rate for formaldehyde oxide plus water by one and two orders of magnitude (D3 and D4, respectively). The results, presented in Table 5, show the contribution of the ox- idation of sulfur dioxide by the sCI for the single cases when all the other rates kept constant as described in scenario D. The results point out that the knowledge of this reaction rate is crucial. An increase of the reaction rate for the sCIs from monoterpenes by 10 will decrease the overall formation rate of sulfuric acid down to 39.8 % and 63.4 % for Hyyti¨al¨a and Hohenpeissenberg, respectively, when compared to the mea- surements. On the other side an increase in the reaction rate for formaldehyde oxide by 10 would improve the situation for Hyyti¨al¨a but lead to an overestimation for Hohenpeis- senberg by more than 34 %. One way to investigate the re- action rates for the sCI with water and with sulfur dioxide could be a very detailed long-term sensitivity study by taking the changes of the relative humidity as one factor to research when the best agreement between the simulations and mea- surements are achieved. This could improve our knowledge in the reaction rates for the Criegees with water and sulfur dioxide but will still leave a lot of uncertainties on the for- mation of the stabilized Criegee intermediates.
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Enhancement of atmospheric H<sub>2</sub>SO<sub>4</sub> / H<sub>2</sub>O nucleation: organic oxidation products versus amines

Enhancement of atmospheric H<sub>2</sub>SO<sub>4</sub> / H<sub>2</sub>O nucleation: organic oxidation products versus amines

gas monitor (Thermo Environmental Instruments 49C). The concentrations of the olefins were detected with the help of a quadrupole proton transfer reaction mass spectrometer (PTR-MS, Ionicon Analytik GmbH) (Lindinger et al., 1998). Sulfuric acid was measured at the IfT-LFT outlet by means of a Chemical Ionization Mass spectrometer, CI-MS (Eisele and Tanner, 1993; Mauldin et al., 1998; Petäjä et al., 2009) using (NO − 3 ) as the reagent ion. The reagent ions were gen- erated by nitric acid and a 241 Am alpha source and mixed in a drift tube utilizing concentric sheath and sample flows together with electrostatic lenses. The sulfuric acid concen- tration is determined by the ratio between the signals at mass 97 amu (HSO − 4 ) and the reagent ion at mass 62 amu (NO − 3 ) multiplied by the setup dependent calibration factor. The cal- ibration factor was determined by photolysis of water vapour with a mercury lamp to generate a defined amount of OH rad- icals in front of the inlet (e.g. Mauldin et al., 2001). The pro- duced OH radicals subsequently convert isotopically labeled
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Reactivity of stabilized Criegee intermediates (sCIs) from isoprene and monoterpene ozonolysis toward SO<sub>2</sub> and organic acids

Reactivity of stabilized Criegee intermediates (sCIs) from isoprene and monoterpene ozonolysis toward SO<sub>2</sub> and organic acids

as biogenic terpenes in the atmosphere (Atkinson, 2000). Al- though the reactivity of these oxidants toward a large va- riety of atmospheric trace gases is well established, ambi- ent observations have revealed major ambiguities in atmo- spheric oxidation chemistry, especially related to OH in lo- cations having high emissions of biogenic volatile organic compounds (BVOCs) (Di Carlo et al., 2004; Lou et al., 2010; Nölscher et al., 2012; Lelieveld et al., 2008; Hofzumahaus et al., 2009; Taraborrelli, et al., 2012). Recently, two ad- ditional major processes contributing to the complexity of atmospheric oxidation have been revealed: firstly, the auto- oxidation mechanism producing highly oxidized condens- able organic vapours in the gas phase discovered by Ehn et al. (2014) – such vapours are shown to be essential for for- mation of secondary organic aerosol (Kulmala et al., 1998; Riipinen et al., 2011); secondly, the suggestion that stabi- lized Criegee intermediates (sCIs), formed by ozonolysis of biogenic alkenes (Criegee, 1975), might add to the oxidation capacity of the atmosphere – at least from the point of view of SO 2 oxidation and subsequent formation of sulfuric acid,
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Observations of volcanic SO<sub>2</sub> from MLS on Aura

Observations of volcanic SO<sub>2</sub> from MLS on Aura

observed by MLS is at 100 and 147 hPa, where we would ex- pect the MLS observations to be reasonably good. However, Nabro is at a rather low latitude, where the ability of MLS to observe at lower altitudes is more likely to be adversely affected by high levels of water vapour in the upper tropo- sphere. A more recent paper (Clarisse et al., 2014) gives a mass of 650 Gg above 10 km for the initial phase of the erup- tion; this is in somewhat better agreement with the MLS es- timate. It should be noted that all of the eruptions during the Aura mission to date have been small compared to the erup- tion of Mount Pinatubo in 1991; Read et al. (1993) give a to- tal mass of M t = 17 000 Gg for that eruption. The e-folding
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Observations of volcanic SO<sub>2</sub> from MLS on Aura

Observations of volcanic SO<sub>2</sub> from MLS on Aura

Table 2. Total injected SO 2 mass M 0 and decay time τ for a selection of the volcanic events observed by MLS. Estimates of M 0 from other sources are shown for comparison. Krotkov et al. (2010) also give an estimate of τ = 9days for Kasatochi. For Sarychev we show two estimates for two choices of highest pressure used (p max ). The 215 hPa result is more use for comparison with nadir-sounder data but is less satisfactory as it proved difficult to remove the seasonal background for this case.

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Direct detection of OH formation in the reactions of HO<sub>2</sub> with CH<sub>3</sub> C(O)O<sub>2</sub> and other substituted peroxy radicals

Direct detection of OH formation in the reactions of HO<sub>2</sub> with CH<sub>3</sub> C(O)O<sub>2</sub> and other substituted peroxy radicals

In a recent Max-Planck-Institute field campaign (GABRIEL), OH was for the first time directly monitored over the Amazonian rainforest. The results (see elsewhere in this issue) clearly demonstrate that large [OH] ≈1×10 7 molecule cm −3 were maintained, despite a large (∼1 ppb) isoprene loading in otherwise clean air (NO∼15 ppt). The largest discrepancies (up to a factor of 10) between measured and modelled [OH] were

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Coastal upwelling fluxes of O<sub>2</sub>, N<sub>2</sub>O,  and CO<sub>2</sub> assessed from continuous atmospheric observations at Trinidad,California

Coastal upwelling fluxes of O<sub>2</sub>, N<sub>2</sub>O, and CO<sub>2</sub> assessed from continuous atmospheric observations at Trinidad,California

vided computer programming and data analysis, B. Paplawski, engineering and chemical ex- pertise, A. Cox, gas cylinder preparation and handling, J. Cooper, data processing, and A. Hartounian, PC and instrument fabrication and software support. N 2 O data were provided by the AGAGE program at S.I.O. headed by R. Weiss. P. Salameh and C. Harth provided AGAGE data support. Trinidad Station support was provided by W. Snible and R. Dickau. Shipboard

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Gaseous (DMS, MSA, SO<sub>2</sub>, H<sub>2</sub>SO<sub>4</sub> and DMSO) and particulate (sulfate and methanesulfonate) sulfur species over the northeastern coast of Crete

Gaseous (DMS, MSA, SO<sub>2</sub>, H<sub>2</sub>SO<sub>4</sub> and DMSO) and particulate (sulfate and methanesulfonate) sulfur species over the northeastern coast of Crete

Concurrent field data both on the oxidants involved in the DMS oxidation and including at least the major oxidation products of DMS in gaseous and particulate phase are clearly needed to validate the laboratory results. Such data is par- ticularly difficult to obtain since the levels of free radicals and DMS oxidation products are often very low (in sub- pmol·mol −1 level) and state-of-the-art analytical techniques are needed. To our knowledge only few studies have ful- filled all the above requirements. Especially in the marine boundary layer only one study has been performed so far (the SCATE experiment in coastal Antarctica; Berresheim and Eisele, 1998). The MINOS campaign conducted in Crete in July-August 2001, provides the first comprehen- sive dataset to understand the factors controlling the distri- bution and the fate of DMS oxidation products under moder- ately polluted marine conditions. Intensive measurements of gaseous DMS, DMSO, SO 2 , H 2 SO 4 and MSA and particu-
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TransCom N<sub>2</sub>O model inter-comparison – Part 2:  Atmospheric inversion estimates of N<sub>2</sub>O emissions

TransCom N<sub>2</sub>O model inter-comparison – Part 2: Atmospheric inversion estimates of N<sub>2</sub>O emissions

The number of degrees of freedom in the inversion is an important factor for determining how closely the poste- rior fluxes resemble the prior ones. For MOZART4-I and ACTMt42l67-I, which solve the inversion using coarse re- gions, the number of degrees of freedom is substantially re- duced, representing a strong constraint on the inversion as only the mean flux in each region is optimized and the flux pattern within each region remains as described a priori. On the other hand, solving for fine regions i.e. at the resolution of the transport model, as in TM5-I, TM3-I and LMDZ4- I, benefits from additional regularization constraints, such as spatial correlations of the prior flux errors (used in the defini- tion of B). For TM5-I the spatial correlation length (200 km) means that the grid cells are only weakly correlated to one another resulting in a weak constraint, whereas in LMDZ4-I, longer scale lengths are used (500 km for land and 1000 km for ocean) resulting in a stronger constraint (see Table 2).
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Observations of SO<sub>2</sub> and NO<sub>2</sub> by mobile DOAS in the Guangzhou Eastern Area during the Asian Games 2010

Observations of SO<sub>2</sub> and NO<sub>2</sub> by mobile DOAS in the Guangzhou Eastern Area during the Asian Games 2010

Acknowledgements. The authors would like to thank the Guangzhou Environmental Center for supporting the experiment. We also want to thank our two drivers, Shaoli Wang and Zongmao Xu, whose skillful driving ensured that the experiment could be carried out successfully and safely. This work was also made possible by the support of Special research funding for the pub- lic industry sponsored by Ministry of Environmental Protection of PRC (Grant No: 201109007)

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Spatiotemporal variations of air pollutants (O<sub>3</sub>, NO<sub>2</sub>, SO<sub>2</sub>, CO, PM<sub>10</sub>, and VOCs) with land-use types

Spatiotemporal variations of air pollutants (O<sub>3</sub>, NO<sub>2</sub>, SO<sub>2</sub>, CO, PM<sub>10</sub>, and VOCs) with land-use types

The hourly observations of the pollutants, except for the VOCs, during the 12-year period were utilized for the tem- poral cycle and trend analyses over the land-use types. The hourly data were arranged into 144 monthly anomaly val- ues in order to remove the annual cycle in the time series. The anomaly value was computed by substracting the cli- matology (i.e., 12-year monthly mean in this study) from the monthly average in a given month. The 95 % confidence intervals for the trends were calculated using the bootstrap method (Wilks, 1995). For each air pollutant anomaly data set, 10 000 new data sets were created to produce 10 000 lin- ear trends through random sampling (e.g., Lee et al., 2013). The random sampling was conducted by drawing data out of the respective original records of the air pollutant anomalies, allowing repetition. The ± values in the trend analysis de- fined the 95 % confidence intervals, while they stood for 1σ (standard deviation) in the concentration averages.
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Observations of SO<sub>2</sub and NO<sub>2</sub> by mobile DOAS in the Guangzhou eastern area during the Asian Games 2010

Observations of SO<sub>2</sub and NO<sub>2</sub> by mobile DOAS in the Guangzhou eastern area during the Asian Games 2010

VOCs, and fine particulates are emitted. Regional studies in- vestigated that area sources have a very strong influence on air quality through the regional transport of air pollutants, possibly causing severe pollution events to the area and its neighbors (Melamed et al., 2009; Takashima et al., 2011). The temporal and spatial scale of transport can range from a few days to several weeks and from a few kilometers to hundreds of kilometers. Therefore, understanding the spa- tial and temporal distribution as well as the emission sources of air pollutants in GEA was important for environmental management during the Guangzhou Asian Games. Air pol- lutants were routinely monitored by the local environmental protection agency using a network of ground-level monitors. However, data from this network were insufficient for spatial distribution and transportation processes as well as emission sourcing.
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The effect of coal-fired power-plant SO<sub>2</sub> and NO<sub>x</sub> control technologies on aerosol nucleation in the source plumes

The effect of coal-fired power-plant SO<sub>2</sub> and NO<sub>x</sub> control technologies on aerosol nucleation in the source plumes

Measurements of high concentrations of ultrafine particles have been found in the plumes of coal-fired power plants despite the reduction of emissions from installed pollution- control technology (Junkermann et al., 2011a, b). Junker- mann et al. (2011b) compared the aerosol size distributions measured in plumes from modern power plants with pol- lution controls to those from older plants without controls. They found the modern plants to have significantly more ul- trafine particles (and total particle number) than the older plants. Their hypothesis as to the source of these ultrafine aerosols is explained by in-stack formation from pollution- control technology byproducts (Srivastava et al., 2004). A fraction of these additional ultrafine particles evolve into CCN and may ultimately affect clouds and climate (Adams and Seinfeld, 2003; Pierce and Adams, 2009a; Konwar et al., 2010; Junkermann et al., 2011a, b). Junkermann et al. (2011b) describes how the shift to cleaner power plants may lead to more CCN that can impact climate. Thus, it is important to understand the various processes that affect the net number of particles formed due to power plants that are affected by pollution-control technologies. Along with the in-stack formation of new particles, changes in plume chem- istry and microphysics due to the changes in emissions of sulfur dioxide (SO 2 ) and nitrogen oxides (NO x = NO + NO 2 )
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Importance of including ammonium sulfate ((NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub>) aerosols for ice cloud parameterization in GCMs

Importance of including ammonium sulfate ((NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub>) aerosols for ice cloud parameterization in GCMs

Several simulations, listed in Table 1, were conducted to un- derstand and eliminate the biases in the ice clouds. The con- trol experiment, conducted with the SCM, simulated the en- tire atmospheric column with liquid and ice clouds for the 3-year period of the Atmospheric Radiation Measurement (ARM) – Southern Great Plain (SGP) as a driver data pro- vided by the ARM-SGP Working Group (Xie et al., 2004). The driver data contain lateral and surface fluxes at hourly intervals based on the analysis of observations (Zhang et al., 2001). The simulations were performed for three continuous years (1999–2001); it is the only continuous period for which the ARM-SCM data were available. The model simulations were compared with available satellite and ground observa- tions. Ground measurements of liquid water path were taken from Microwave Radiometer Retrieval (MWRRET) (Gaus- tad and Turner, 2007) measurements from 1999–2005, which were then compared with MODIS total column liquid water (Collection 5) data from 2000 to 2007 (Levy et al., 2007). We also performed additional SCM simulations in which all the simulations were repeated with (NH 4 ) 2 SO 4 allowed to
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Latitude-time variations of atmospheric column-average dry air mole fractions of CO<sub>2</sub>, CH<sub>4</sub> and N<sub>2</sub>O

Latitude-time variations of atmospheric column-average dry air mole fractions of CO<sub>2</sub>, CH<sub>4</sub> and N<sub>2</sub>O

For quantitative evaluation of the model-observation agreement, we prepared follow- ing statistics: correlation coefficient R, model bias b[=Σ(X ACTM −X TCCON )/N]; where N is the number of data points in the time series), and model-data root mean squared (RMS) difference d [=sqrt{Σ(X ACTM −X TCCON ) 2 /N}]. We use the digital filtering method described in Nakazawa et al. (1997) for decomposing the daily averaged original time

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Zeeman effect in atmospheric O<sub>2</sub> measured by ground-based microwave radiometry

Zeeman effect in atmospheric O<sub>2</sub> measured by ground-based microwave radiometry

measured by TEMPERA. We can observe that, in general, there is a very good agreement between the measurements and the model. Both simulations and measurements show higher ratio values (> 1), which indicate a smaller broaden- ing regarding the averaged spectrum for the smallest azimuth angles and a larger broadening (ratios < 1) for the largest an- gles. The relative differences between both ratios are lower than 1 % for all the azimuth angles. We observe that the ra- tios for some azimuth angles are almost identical while some discrepancies are observed for other ones. The errors for the TEMPERA measurements have been estimated by evaluat- ing the uncertainties associated with the different terms of the tropospheric correction (Eq. 11). The error bars shown in Fig. 13 have been calculated using error propagation theory and they presented values very similar (∼ 0.01) for all the ob- servational angles. The errors associated with the simulations were obtained by evaluating the ratio of the simulated spectra plus Gaussian white noise. The calculated uncertainties pre- sented values much smaller than the ones found for the mea- surements (maximum value of 4.6 × 10 −4 ). It is important to note that the differences found between measurements and simulations are within the measurement uncertainties. From this comparison we can conclude that the agreement between measurements and model is clear. These results show the po- larized state of the radiation due to the Zeeman effect, which is revealed for a different broadening in the spectra when the angle of the Earth magnetic field and the observational path is changed.
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Effects of increased atmospheric CO<sub>2</sub> on small and intermediate sized osmotrophs during a nutrient induced phytoplankton bloom

Effects of increased atmospheric CO<sub>2</sub> on small and intermediate sized osmotrophs during a nutrient induced phytoplankton bloom

vealed that diatoms accounted for most of the chlorophyll during the main bloom (Riebesell et al., 2007; Schultz et al., 2008). The flow cytometry results presented here revealed a much more varied dynamic among the various osmotrophic populations: The initial nutrient pulse resulted in a com- munity shift from small sized (=picoplankton: heterotrophic bacteria, Synechococcus and picoeukaryotes) to intermediate (Emiliania huxleyi and other eukaryotic nanoflagellates) in addition to the big sized (diatoms) osmotrophs. On a compe- tition to defence specialist axis (Thingstad et al., 2005) inter- mediate/big osmotrophs represent defence specialists char- acterized by features (e.g. size, silicate scale) making them less vulnerable for grazing (Thingstad, 1998; Hamm, 2000; Hamm et al., 2003) and/or infection (Raven and Waite, 2004), whereas the small osmotrophs are thought to out- compete bigger ones when nutrients are low (Kuenen et al., 1977; Smith and Kalff, 1982; Bratbak and Thingstad, 1985; Thingstad et al., 2005). The observed shift thus represents a change from competition specialists, which dominated the mesocosm water before nutrient addition, to defence spe- cialists taking advantage of the nutrient replete conditions brought about by the initial nutrient pulse.
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Atmospheric deuterium fractionation: HCHO and HCDO yields in the CH<sub>2</sub>DO+O<sub>2</sub> reaction

Atmospheric deuterium fractionation: HCHO and HCDO yields in the CH<sub>2</sub>DO+O<sub>2</sub> reaction

reaction. In some cases when the reactivity of a deuterated species was not known a best estimate was made, for example the rate of H abstraction will scale with the num- ber of H atoms, and a C–D bond’s reactivity is 1/8 that of C–H, based on the reactivity of deuterated methanes. Since there is some unavoidable uncertainty in this process, it is reassuring that the model only indicated a minor correction; the final result is largely

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Retrieval of near-surface sulfur dioxide (SO<sub>2</sub>) concentrations at a global scale using IASI satellite observations

Retrieval of near-surface sulfur dioxide (SO<sub>2</sub>) concentrations at a global scale using IASI satellite observations

column are shown, separately for the morning (blue) and evening (red) overpasses of IASI. The averages have been calculated in a circle of 125 and 75 km radius around re- spectively Beijing and Sar Cheshmeh. As before, only observations with less than 20 % cloud fraction and with available meteorological level 2 have been taken into account and only those with sufficiently low retrieval errors are considered (same thresholds as

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Uptake of HO<sub>2</sub> radicals on Arizona test dust surface

Uptake of HO<sub>2</sub> radicals on Arizona test dust surface

sample was introduced into the main reactor along its axis. The coated tube could be moved relative to the outer tube of the injector that allowed the variation of the solid film length exposed to gas phase reactant and consequently of the reaction time. The walls of the main reactor as well as of the outer tube of the movable injector (in contact with HO 2 ) were coated with halocarbon wax in order to minimize the heterogeneous

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