Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
1 Quantifying the contribution of marine organic gases to atmospheric 2 iodine: Supporting Material - further method details 3 4 Further details of ambient VOIC analysis 5 Both GC/MS instruments incorporated a 50 m x 0.32 mm internal diameter SGE BPX5 6 capillary column, and detection by electron impact ionisation quadrupole mass 7 spectrometry. Calibration of the GC/MS instruments for ambient VOIC analysis was 8 achieved based upon a permeation oven based technique described fully in Wevill and 9 Carpenter [2004]. Permeation tubes containing pure liquid halocarbons (>97%, Aldrich) 10 maintained in a thermostated oven with a constant nitrogen flow rate were used to deliver 11 a constant calibration gas output containing dilute levels of halocarbons. Sequential 10 μl 12 volumes of permeation gas were injected into a stream of nitrogen (BOC, CP grade) in 13 order to generate a linear calibration of each halocarbon at pptv levels. Full permeation 14 oven calibrations were performed at the beginning and end of each cruise, whilst day-to 15 day variability in instrument sensitivity was accounted for using an in-house prepared gas 16 standard, containing pptv-levels of all VOICs studied. 17 During the MAP cruise the air sample inlet was located on the foredeck to the port side of 18 the ship and during RHaMBLe the inlet was sited on the port side. During both cruises 19 ambient air was pumped through a PFA Teflon line (50 m length for the MAP cruise, 20 20 m length for RHaMBLe, both ½ i.d) using a diaphragm pump at a rate of ~30 l min-1, 21 and clean air was sub-sampled diverted upstream of the diaphragm pump via a metal 22 bellows pump (Senior Aerospace Limited) and delivered to a cold trap at -30 °C within 23 the thermal desorption unit to pre-concentrate volatile components prior to GC/MS 24 analysis. 25 26 Sea-air flux calculations 27 Sea-air fluxes were calculated as a function of the concentration difference across the sea- 28 air boundary (ΔC, mol cm-3) and the total gas transfer velocity k (cm h-1, which 29 incorporates both the waterside and airside transfer velocities - kw and ka, respectively), 30 according to Equation (1). We used the Nightingale et al. [2000] parameterization for the 31 waterside transfer velocity, (kw = {0.222u2 + 0.333u}{SC/660}-1/2) and the McGillis et al. 32 [2000] expression to include the airside resistance (k = kw {1 – γa}) (where γa is the 33 airside gradient function), with minute averaged wind speeds u (in m s-1), and the 34 dimensionless Henry’s law coefficients (H) from Moore et al. [1995]. The Khalil et al. 35 [1999] approximation was used to derive the temperature dependent Schmidt numbers 36 (Sc) for each gas (Equation 2), where T is seawater temperature and M is the relative 37 molecular mass. Sea-air fluxes were also calculated according to the Liss and Merlivat 38 [1986] and Wanninkhof [1992] 39 parameterizations resulted in mean average CH3I, CH2ICl and CH2I2 fluxes for both 40 cruises which differed by ±25-30%. parameterizations for kw, and the three different kw 41 42 F = kΔC (1) Sc = 335.6M1/2 (1-0.065T + 0.002043T2 - (2.6x10-5)T3) (2) 43 44 45 46 47 Further details of the Ocean Mixed Layer Model 48 The ocean mixed layer (OML) model contains explicit parameterisations of the 49 mechanisms which drive mixing within the surface ocean. Mixing in surface waters 50 occurs as a response to two broad categories of forcing: wind-driven forced convection 51 (caused by surface and internal waves, shear instabilities, secondary circulations - e.g. 52 Langmuir cells - and various interactions between them) and density instability-driven 53 free convection. Buoyancy instabilities driving pure free convection may be a result of 54 surface cooling or evaporation. Free convection is usually combined with some degree of 55 forced convection. A model aiming to accurately reproduce the behaviour of physical 56 properties in oceanic surface waters must therefore explicitly describe or parameterise the 57 above mechanisms adequately. The OML model is based on Large et al. [1994] and uses 58 a parameterisation for the depth-resolved eddy diffusivity profile based on criteria 59 consistent with the conservation equations in their primitive form. The model uses a non- 60 local eddy diffusivity (K) profile parameterisation (KPP) after Troen & Mahrt [1986] 61 with local parameterisations for the three mixing processes in the interior added by Large 62 et al. [1994], as well as adaptations of the rules for matching boundary layer properties at 63 the ocean interior, and of the boundary conditions at the surface and bottom. 64 The model was validated for physical property prediction by running with a standard set 65 of initialisations and external forcings, and comparing predicted physical properties such 66 as the mixed layer depth with those obtained by six other turbulent vertical mixing 67 models reported in Martin [1985, 1986] under the same synthetic forcing conditions. 68 Having validated the model skill in reproducing physical properties, it was modified and 69 extended to integrate the vertical production, destruction and transport of dissolved 70 gaseous CH2I2 and CH2ICl. The depth-dependent biological production terms were 71 equivalent in structure to a typical Chl a profile (based on in-situ measured depth profiles 72 of Chl a for MAP) maximising at the bottom of the predicted mixed layer, and were 73 simply scaled to approximately reproduce the observed CH2ICl and CH2I2 concentrations 74 at 2 or 6 m depth. Maximum production rates (at the Chl a maximum) were ~6 pmol dm- 75 3 76 photolysis rates were calculated using wavelength-resolved solar irradiance from 77 NASA’s 78 (http://snowdog.larc.nasa.gov/jin/rtset.html) combined with absorption cross-sections and 79 quantum yields for photolysis of dihalomethanes in seawater from Jones and Carpenter 80 [2006]. Sea–air exchange losses are parameterised using the wind speed dependent gas 81 transfer velocities used in sea-air flux calculations (described above). Initialising the 82 model with vertical salinity, temperature and velocity profiles (temperature and salinity 83 from in-situ profile measurements during MAP and from archived BODC data from the 84 same region and time of year for RHaMBLe; initial velocity profiles were based on 85 acoustic doppler current profiler (ADCP) measurements from previous studies in similar 86 regions) and forcing it with in-situ ship-board meteorological observations (~10 m above 87 sea level), the physical properties and VOIC vertical profile evolution were predicted. d-1 and ~1.5 pmol dm-3 d-1 for CH2I2 and CH2ICl, respectively. Depth-dependent Coupled Ocean Atmosphere Radiative Transfer (COART) model 88 89 Further details of the MISTRA 1D Atmospheric Model 90 The one-dimensional Lagrangian MISTRA model, which contains detailed treatment of 91 the thermodynamics and microphysics and explicit gas and aqueous phase chemical 92 mechanisms, was used to simulate iodine sources to the MBL. The gas-phase chemical 93 mechanism used in the MISTRA model was updated to the latest IUPAC 94 recommendation (June 2006), with a revised DMS mechanism mainly based upon Barnes 95 et al. [2006]. The chemistry of hydrocarbons and halogenated hydrocarbons was revised 96 by including more explicit treatment of the intermediates, based on the Master Chemical 97 Mechanism protocol [Saunders et al., 2003]. Besides chlorine and bromine inorganic 98 chemistry, the model includes a detailed iodine mechanism, similar to the one described 99 in Pechtl et al. [2006], with some minor revisions and updates. 100 The model is initialised with ozone mixing ratios typical of clean sub-tropical MBL air 101 that has travelled for at least 3 days in the boundary layer from the mid-latitude to the 102 sub-tropical Atlantic Ocean (30-40 ppbv, Read et al., [2008]). The model was initially 103 run for 1.5 days to spin-off the meteorology and the microphysics, after which the 104 chemistry was reinitialized and the model run for 3 days. 105 106 Although the total organic iodine flux derived from our measurements is similar to that of 107 the Vogt et al. [1999] base case fluxes used in the model (which were based on coastal 108 studies), the relative abundance of each gas is different, with lower CH2I2 and higher 109 CH3I fluxes from the measurements; the net effect being much slower release of reactive 110 iodine using the measured fluxes. 111 112 Sensitivity tests on MISTRA model 113 Sensitivity tests were carried out on the iodine mechanism in the model, in an attempt to 114 resolve the discrepancy between the modeled and measured concentrations of IO 115 (average measured IO was ~1.4 pptv, compared to the maximum modelled value of ~0.3 116 pptv). Rate coefficients and/or products and branching ratios of selected reactions were 117 altered, including: mass accommodation coefficients of HOI and HIO3, photolysis rates 118 of OIO, I2O2 and CH2I2, products of the decomposition reaction of I2O2, products of the 119 OH+IBr, I+INO3 reactions and of the IO self-reaction, formation of HIO3 and I2O3, 120 photolysis of iodinated oxygenates formed by peroxy radicals self- and cross-reactions 121 and addition of a speculative HIO3 loss term. However, none of these reactions impacted 122 the modelled concentrations of IO by more than a few percent, except when HIO3 123 formation was set to zero or when a loss term for HIO3 (with a pseudo first-order rate 124 coefficient of 1.0x10-3 s-1) was added to the mechanism, but even in this case the model 125 still underestimated the observed IO mixing ratios by up to a factor of 3. Even doubling 126 the measured VOIC fluxes did not provide an iodine source sufficient to produce the 127 observed IO concentrations (doubling the upwelling VOIC fluxes resulted in IO 128 concentrations of ~0.6 pptv). 129 The model was also run with an iodine mechanism similar to that used by Gomez-Martin 130 et al. [2009], which resulted in higher modeled IO (~0.6 pptv compared to ~0.3 pptv with 131 the initial mechanism). Although a direct comparison between the two models is not 132 straightforward, we believe that the main reasons for the differences are (i) the Gomez- 133 Martin et al. [2009] mechanism does not include the IO+CH3O2 reaction, (ii) the rate 134 coefficient of the OIO+OH reaction used by Gomez-Martin et al. [2009] is 6x10-12 cm-3 135 molecule-1 s-1 and the product is HOI, while in our mechanism the rate coefficient is 136 5x10-10 cm-3 molecule-1 s-1 (at 298 K, Plane et al. [2006]) and the product is HIO3, and 137 (iii) mass accommodation coefficients for inorganic iodine species are a factor of 2 (HI) 138 and up to a factor of 50 (HOI) lower than those used in the present work. The differences 139 in the gas-phase mechanism may or may not be significant (the reaction IO+CH3O2 is, in 140 fact, extremely uncertain), although the model is very sensitive to HIO3 formation and 141 loss. The ultimate fate of iodine is accumulation in particles in the form of iodide and 142 iodate [Pechtl et al., 2006] and this typically occurs by uptake of inorganic iodine (mostly 143 INOx, HIO3 and IxOy); therefore all processes that reduce the formation rate of these 144 species and/or their uptake onto particles (such as OIO+OH and the mass accommodation 145 coefficients) will result in higher concentrations of inorganic iodine in the gas-phase. 146 147 148 Supporting references 149 Barnes, I., J. Hjorth and N. Mihalopoulos (2006), Dimethyl sulfide and dimethyl 150 sulfoxide and their oxidation in the atmosphere, Chemical Reviews, 106, 940-975. 151 Gomez-Martin, J. C., S. H. Ashworth, A. S. Mahajan and J. M. C. Plane (2009), 152 Photochemistry of OIO: laboratory study and atmospheric implications, Geophys. 153 Res. Lett., 36, L09802. 154 Jones, C. E. and L. J. Carpenter (2006), Solar photolysis of CH2I2, CH2ICI, and 155 CH2IBr in water, saltwater, and seawater, Environ. Sci. Technol., 40(4), 1372, 156 doi:10.1021/es058022e. 157 Khalil, M. A. K., R. M. Moore, D. B. Harper, J. M. Lobert, D. J. Erickson, V. 158 Koropalov, W. T. Sturges and W. C. Keene (1999), Natural emissions of chlorine- 159 containing gases: Reactive Chlorine Emissions Inventory, J. Geophys. Res. - Atmos., 160 104(D7), 8333-8346. 161 Large, W. G., J. C. McWilliams and S. C. Doney (1994), Oceanic vertical mixing: a 162 review and a model with a non-local boundary layer parameterization, Rev. of 163 Geophys., 32, 363-403. 164 Liss, P. S. and L. Merlivat (1986), Air-sea gas exchange rates: Introduction and 165 synthesis, in The Role of Air-Sea Exchange in Geochemical Cycling, edited by P. 166 Buat-Menard, pp. 113 – 127 D. Reidel, Norwell, Mass. 167 Martin, P. J. (1985), Simulation of the mixed layer at OWS N and P with several 168 models, J. Geophys. Res., 90, 903-916. 169 Martin, P. J. (1986), Testing and comparison of several mixed-layer models, U. S. 170 Naval Ocean Research and Development Activity Report 143. 171 McGillis, W. R., J. W. H. Dacey, N. M. Frew, E. J. Bock and R. K. Nelson (2000), 172 Water-air flux of dimethylsulfide, J. Geophys. Res., 105(C1), 1187-1193. 173 Moore, R. M., C. E. Geen and V. K. Tait (1995), Determination of Henry Law 174 Constants for a suite of naturally-occurring halogenated methanes in seawater, 175 Chemosphere, 30(6), 1183-1191. 176 Mössinger, J. C., D. E. Shallcross and R. A. Cox (1998), UV-VIS absorption cross- 177 sections and atmospheric lifetimes of CH2Br2, CH2I2 and CH2BrI, J. Chem. Soc. 178 Faraday Trans., 94, 1391-1396. 179 Nightingale, P. D., G. Malin, C. S. Law, A. J. Watson, P. S. Liss, M. I. Liddicoat, J. 180 Boutin and R. C. Upstill-Goddard (2000), In situ evaluation of air-sea gas exchange 181 parameterizations using novel conservative and volatile tracers, Global Biogeochem. 182 Cy., 14(1) 373-387. 183 Pechtl, S., E. R. Lovejoy, J. B. Burkholder and R. von Glasow (2006), Modeling the 184 possible role of iodine oxides in atmospheric new particle formation, Atmos. Chem. 185 Phys., 6, 505-523. 186 Plane, J. M. C., D. M. Joseph, B. J. Allan, S. H. Ashworth and J. S. Francisco (2006), 187 An experimental and theoretical study of the reactions OIO + NO and OH + OH, J. 188 Phys. Chem. A, 110(1), 93-100 doi: 10.1021/jp055364y. 189 Rattigan, O. V., D. E. Shallcross and R. A. Cox (1997), UV absorption cross-sections 190 and atmospheric photolysis rates of CF3I, CH3I, C2H5I and CH2ICl, J. Chem. Soc. 191 Faraday Trans., 93, 2839-2846. 192 Read, K. A., et al. (2008), Extensive halogen-mediated ozone destruction over the 193 tropical Atlantic Ocean, Nature, 453, 1232-1235 doi:10.1038/nature07035. 194 Saunders, S. M., M. E. Jenkin, R. G. Derwent and M. J. Pilling (2003), Protocol for 195 the development of the Master Chemical Mechanism, MCM v3 (Part A): tropospheric 196 degradation of non-aromatic volatile organic compounds, Atmos. Chem. Phys., 3, 197 161-180. 198 Vogt, R., R. Sander, R. von Glasow and P. J. Crutzen (1999), Iodine chemistry and its 199 role in halogen activation and ozone loss in the marine boundary layer: A model 200 study, J. Atmos. Chem., 32(3), 375-395. 201 Troen, I. and L. Mahrt (1986), A simple model of the atmospheric boundary layer - 202 sensitivity to surface evaporation, Boundary-Layer Meteorology, 37, 1-2, 129-148. 203 Wanninkhof, R. (1992), Relationship between wind-speed and gas-exchange over the 204 ocean, J. Geophys. Res. - Oceans, 97(C5), 7373-7382. 205 Wevill, D. J. and L. J. Carpenter (2004), Automated measurement and calibration of 206 reactive volatile halogenated organic compounds in the atmosphere, The Analyst, 129, 207 634-638. 208 209 210 Supporting Material Figure S1. Rate of iodine atom release from VOICs within the 211 atmospheric boundary layer, based upon the open ocean sea-air fluxes (ocean) and 212 upwelling fluxes (upwell). Total VOICs corresponds to iodine atom production from all 213 measured VOICS (CH3I, C2H5I, 1-C3H7I, CH2IBr, CH2ICl and CH2I2). 214 215 216