Presentation on theme: "Atmospheric Chemistry: Overview and Future Challenges Allan Gross Danish Meteorological Institute, Lyngbyvej 100, 2100 Copenhagen Ø, Denmark. & University."— Presentation transcript:
Atmospheric Chemistry: Overview and Future Challenges Allan Gross Danish Meteorological Institute, Lyngbyvej 100, 2100 Copenhagen Ø, Denmark. & University of Copenhagen, Scientific Computing Chemistry Group, Universitetsparken 5, 2100 Copenhagen Ø, Denmark. CITES 2005, March 20-23, 2005, Novosibirsk, Russia.
Background There is a critical need for improving the available mechanistic data in Atmospheric Chemical Transport Models (ACTM), examples: –the chemistry of higher molecular weight organic compounds (e.g. aromatic and biogenic compounds), –radical reactions (e.g. peroxy – peroxy radical reactions), –photo-oxidation processes (quantum yields and absorption cross sections), –heterogeneous processes. Furthermore, due to experimental difficulties most rates are measured best near 298 K, i.e. temperature dependence of many reactions is not well characterised (see NIST, IUPAC and NASA).
Contents With a description of the new European project GEMS as starting point, the following aspects will be outlined: –an overview of atmospheric chemistry (boundary layer and free-troposphere), –show important areas where future studies are needed, e.g.: aromatic chemistry, alkene chemistry. –a comparison of some of the most frequently used lumped atmospheric chemistry mechanisms will be given (EMEP, RADM2, RACM). Examples of atmospheric environments where these lumped mechanism need to be improved: –biogenic environment, –marine environment.
Objectives of GEMS (EU-project, 2005-09) Some components of the system: 1.combines “all available” remotely sensed and in-situ data to achieve global tropospheric and stratospheric monitoring of the composition and dynamics of the atmosphere from global to regional scale covering the tropospheric and stratosphere: Satellite data, and near-real time measurements. 2.global data assimilation. 3.Point 1 will deliver current and operational forecasted 3-dim. global distributions. These distributions will be used for regional air quality modelling. Develop and implement at ECMWF a new validated, comprehensive and operational global data assimilation/forecasting system for atmospheric composition and dynamics.
GEMS Global System Data input (Assimilation, Satellite, Real-time) Global Greenhouse Gasses Global Reactive Gasses Regional Air Quality Global Aerosols Products, User Service GEMS Global System Coordination System Integration oxidants green house gasses boundary conditions oxidants optical properties Schematic illustration of the GEMS strategy to build an integrated operational system for monitoring and forecasting the atmospheric chemistry environment: Greenhouse gasses, global reactive gasses, global aerosols and regional air quality. Global Reac- tive Gasses (UV- forecast) Regional Air Quality (RAQ modelling)
Operational deliverables Current and forecasted 3-dim. global distributions of atmospheric key compounds (horizontal resolution 50 km): –greenhouse gases (CO 2, CH 4, N 2 O and SF 6 ), –reactive gases (O 3, NO 3, SO 2, HCHO and gradually expanded to more species), –aerosols (initially a 10-parameter representation, later expanded to app. 30 parameters). The global assimilation/forecast system will provide initial and boundary conditions for operational regional air-quality and ‘chemical weather’ forecast systems across Europe: –provide a methodology for assessing the impact of global climate changes on regional air quality. –provide improved operational real-time air-quality forecasts.
CLRTAP: UN Convertion on Long-Range Trans-boundary Air Polluton
GEMS Regional Air-Quality Monotoring and Forecastning Partners Individual20 Institutes V.-H. Peuch (co.), A. DufourMETEO-FR (Météo-France, Centre National de Recherches Météorologiques) A. ManningMETO-UK (The Met Office, Exeter, Great-Britain) R. Vautard, J.-P. Cammas, V. Thouret, J.-M. Flaud, G. Bergametti CNRS-LMD (Laboratoire de Météorologie Dynamique, CNRS-LA (Laboratoire d'Aérologie, CNRS-LISA (Laboratoire Inter-Universitaire des Systèmes Atmosphériques) D. Jacob, B. LangmannMPI-M (Max-Planck Institut für Meteorologie) H. EskesKNMI (Koninklijk Nederlands Meteorologisch Instituut) J. Kukkonen, M. SofievFMI (Finnish Meteorological Institute) A. Gross, J.H SørensenDMI (Danmarks Meteorologiske Institut) M. BeekmannSA- UPMC (Université Pierre et Marie Curie Service d’Aéronomie) C. Zerefos, D. MelasNKUA (Laboratory of Climatology and Atmospheric Environment, University of Athens) M. Deserti, E. MinguzziARPA-SM (ARPA Emilia Romagna, Servizio IdroMeteorologico) F. Tampieri, A. BuzziISAC (Institute of Atmospheric Sciences and Climate Consiglio Nazionale delle Ricerche) L. Tarrason, L.-A. BreivikDNMI (Det Norske Meteorologisk Institutt) H. Elbern, H. JakobsFRIUUK (Rheinisches Institut für Umweltforschung, Universität Köln) L. RouilINERIS (Institut National de l’Environnement Industriel et des Risques) J.Keder, J.SantrochCHMI (Czech Hydrometeorological Institute) F.McGovern B.KellyEPAI (Irish Environmental Protection Agency) W.MillPIEP (Polish Institute of Environmental Protection) D.BriggsICSTM (Imperial College of Science, Technology and Medicine, London)
Models Within RAQ Sub-Project Contribution Models and Partners Target speciesData assimilationNRT Forecast E / P * Re-analyses simul. E / P * MOCAGEMETEO-FROzone and precursors (RACM); aerosol components (ORISAM); ENVISAT; MOPITT; OMI; IASI; surface data P and EE BOLCHEMCNR-ISACOzone and precursors (CB-IV or SAPRC90). Surface and profile data. P, then EP, case studies EURADFRIUUKOzone and precursors (RACM); aerosol components (MADE). SCIAMACHY; MOPITT; surface data. P, then E_____ CHIMERECNRS and SA_UPMC Ozone and precursors (EMEP or SAPRC90); aerosol components (ORISAM). SCIAMACHY; Surface and profile data. PP SILAMFMIChemically inert aerosols of arbitrary size spectrum _____PP, year 2000 MATCHFMIOzone and precursors (EMEP); aerosol components (MONO32). _____PP, year 2000 CACDMIOzone and precursors (RACM) and sulphur/DMS; aerosol components. _____PP, case studies MM5-UAMVNKUAOzone and precursors (CB-IV)._____PP, case studies EMEPmet.noOzone and precursors (EMEP); aerosol components (MM32). MERIS and MODIS for PM information PP, 2005 REMOMPI-MOzone and precursors (RADM2)._____ P UMAQ-UKCAUKMOOzone and precs.; aerosol comp._____P * E : run at ECMWF ; P : run at partner institute
Chemical Schemes in USA-models WORF-CHEM: RADM2 CMAQ: CB-IV, RADM2, RACM, ”SAPRC99” CAMX: CB-IV with improved isoprene chemistry, SAPRC99
RAQ Interfaces and Communication between ECMWF and Partner Institutes
GEMS, Summary The GEMS project will develop state-of-the-art variational estimates of –many trace gases and aerosols, –the sources/sinks, and –inter-continental transports. Later on operational analyses will be designed to meet policy makers' key requirements to –the Kyoto protocol, –the Montreal protocol, and –the UN Convention on Long-Range Trans-boundary Air Pollution.
Gas-Phase Chemistry Need to be Solved in Regional Air Quality Models Formation of: 1.ozone, 2.nitrogen oxides, 3.peroxyacetyl nitrate (PAN), 4.hydrogen peroxide, 5.atmospheric acids..... Need to understand chemical reactions of: 1.nitrogen oxides, 2.VOC.....
Chemistry of the free-troposphere: 1.nitrogen oxides and its connection with, 2.carbon monoxide, and 3.simplest alkane – methane. Polluted environment we have high NO X, and VOC chemistry shall also be included.
Reaction Cycle of HO X and NO x, only VOC – methane +H 2 O O3O3 HO Hydrocarbons hνhν HCHO HO 2 products, RCHO RO 2 NO NO 2 O3O3 hνhν RONO 2 RO+NO 2 ROOH RO 3 NO 2 RO 2 NO 2 H2O2H2O2 H2O2H2O2 hνhν HNO 3 O( 3 P) Hydrocarbons O3O3 H 2 O 2, CO RNO 3 CH 4 NO 3 CH 3 O 2 CO CH 3 OOH Reaction Cycle of HO X and NO x, high VOCs Nighttime chem. HCHO
Oxidation Steps of Hydrocarbons RH HO H2OH2O R·R· O2O2 RO 2 HO 2 R(ONO 2 ) HO O2O2 HO 2 NO ROOH RO· HO R’CHO hνhν HO NO R’─R O2O2 NO 3 NO 3 +O 2 NO 2 RO 3 NO 2 NO 3 NO 2 NO 3 HNO 3 hν+O 2 RO 2 HO 2 R’O 2 R(-H)O+R’OH+O 2 RO + R’O+ O 2 ROOR’+O 2 ROOH+R’O 2 Green: only alkene path Red: also other end products but these react further to the given end product R’─R OO R’CHO O O3O3 C5H12 C4H10 C6H14 CH3C5H11 CH3CH3CH4H8 C7H16 CH3C6H13 C3H8 C9H20 CH3C8H17 C10H22 CH3C9H19 C11H24 C12H26 C2H4 C3H6 C4H8 C5H10 CH3C4H7 C4H6 C2H2 C6H6 CH3C6H5 C2H5C6H5 (CH3)3C6H3 HCHO C2H5CHO (CH3)2CHCHO C3H7CHO CH3CHO CH3C6H4C2H5 C3H7C6H5 C4H9CHO CH3COCH3 CH3COC4H9 CH3OH CH3CO2CH3 CH7CH3CO2 CH3CCl C2Cl4 CH3Cl C2H5CO2CH3 C2H5OH CH3COC2H5 C6H5CHO CH4 C2H6 RO 3
Gaps in Atmospheric Chemistry, High Priorities Inorganic chemistry is relatively well known Problems: alkenes monocyclic aromatic hydrocarbons polycyclic aromatics hydrocarbons (PAH)
The Chemistry of Alkenes Reasonable Established. Rate coefficients for HO-alkene reactions of most of the alkenes which have been studies appears to be reasonable accurate. Gaps, Highest Priorities the data base for RO 2 + R’O 2, RO 2 + HO 2, RO 2 +NO 2,RO 2 + NO reactions and their products are very limited and complex. –E.g. system with only 10 RO 2 (no NO X ) results in approximately 165 reactions. ozonolysis of alkenes are important in urban polluted area. Example: O 3 + H 2 C CH 2 → →HCHO + H 2 COO * O O O H 2 COO 37% CO+H 2 O 38% CO 2 +H 2 13% primary ozonide Criegee biradical The rate and product yields of the stable Criegee biradical with NO, NO 2 and H 2 O have only been studied for the simplest carbonhydrids. Higher order carbonhyrids should be investigated
Many of the unsaturated dicarbonyl products appear to be very photochemically active. Absorption cross sections only determined from highly uncertain gas-phase measurements. Examples of compounds it is important to determine the spectra of trans-butenedial 4-oxo-2-pentanal 3-hexene-2,5-dione 4-hexadienedials O O O O O O O O (Atmospheric oxidation products from aromatics)
The Chemistry of Aromatics Still Highly Uncertain Gaps is related both to the rate constant the of aromatic chemistry and the yields of the formed products
Rate coefficients for HO-reactions with monocyclic aromatics –only 23 aromatics have been studied: only studied by one lab. p-cymene tetralin α-methyl-styrene β-methyl-styrene β-β-dimethyl-styrene iso-propyl-benzene o- m- p-ethyl-toluene tert-butyl-benzene indan indene studied by more than one lab. but with over all uncertainties greater than 30% –rate constants for only 20 of the many aromatics products of the oxidation of aromatics have been determined, 14 of these are single studies.
Rate coefficients for HO-reactions with polycyclic aromatics (PAHs) –only 16 aromatics have been studied: only studied by one lab. 1-: 2-methyl-naphthalene 2, 3-dimethyl-naphthalene acenaphthalene flouranthene 1-: 2-nitronaphthalene 2-methyl-1-nitron-aphthalene NO 2
HO +PAH studied by more than one lab., rate constant uncertainties for seven PAHs biphenyl (30%) fluorene (fac. of 1.5) acenaphthene (fac. of 2) phenanthrene (fac. of 2) dibenzo-p-dioxin(fac. of 1.5) dibenzofuran (30%) O O anthracene: one of the most abundant and important PAH in the atmosphere anthracene Rate highly uncertain: range (18 to 289) × 10 -12 cm 3 molecule -1
3-methyl-phenanthrene pyrene benzo[a]flouorene Rate coefficients for PAHs with vapor pressures greater than app. 10 -5 Torr (298 K) should be determined since their reaction with HO may be an improtant removal process, three examples are: HO +PAH
NO 3 + aromatics appear unimportant in the atmosphere Exceptions: a group attached to the atomatic ring have a double bound (ex. indene, styrene), have an –OH group attached to the aromatic ring (ex. phenols, cresols). Only studies: NO 3 + & & phenol o-: m-: p-cresol m-nitro-phenol NO 2 OH
O 3 + aromatics: have gaps but these reactions are not highly important in atmospheric chemistry. O( 3 P) + aromatics: unimportant in urban atmosphere. Atmospheric chemistry of organic compounds sorbed on particles (heterogeneous reactions) and its reactions in aerosols even more uncertain. Important. PAHs oxidation sorbed on particles. Important. PAHs + HO more studies are needed.
Non-aromatic products from the oxidation of aromatic compounds – additional kinetic and mechanics studies of the rates are needed: –Especially the HO initiated reactions, –Product studies of HO + aromatics from chamber experiments shows carbon mass losses from 30% to 50%, i.e. quite possible that some yet unidentified reactions pathways. That means the overall atmospheric oxidation mechanism of aromatics is still rather uncertain. Highest priority, a study the products from the oxidation of most important aromatics: toluene, xylenes, and trimethyl-substituted benzenes.
Application of Chemistry in Atmospheric –Chemical Transport Models Problems: A “Complete Mechanism” would require tens of thousands of chemical species and reactions. The reaction mechanisms and rates are not known for most of these. The ordinary differential equation for chemical mechanisms is very stiff, i.e. numerical standard methods are not applicable. Way of solving it: Using lumped chemical mechanism. Make special ad hoc adjustments to the rate equation to remove stiffness in the lumped mechanism → use a fast solver.
Correlation of the rates for NO 3 with O( 3 P) Correlation of the rates for NO 3 with HO □ (line c): addition reactions Δ (lines a & b): abstraction reacs
Correlation of Peroxy ─ Peroxy Radical Reactions Function fit depend on number of carbons Function fit depend on the rates from the and the alkyl-alkoxy substitution reactants peroxy-self-reaction rates
Lumped Atmospheric Chemical Mechanisms Mech. Abbreviation Developed in Number of Species Reactions ADOM-11USA47114 CB-IVUSA2763 RADM2USA63158 SAPRC-90USA60155 IVLEurope7151640 EMEPEurope79141 RACMUSA77237 SAPRC-99USA74211 Master MCH.Europe24007100
Chamber Experiment EC-237 Photolysis NO X Ethene Propene tert-2-butene n-butene 2, 3-dimethylbutene toulene m-xylene RACM and RADM2 are tested against 21 Chamber Experiments included: 9 organic species. Used chamber: Statewide Air Pollution Research Center. Key species tested in the chamber: NO 2, NO and O 3.
RACM better than RADM2 Ref. Stockwell et al., JGR, 1997
RACM better than RADM2 Ref. Stockwell et al., JGR, 1997
Problems With These Chamber Experiments 50% or more of the total HO comes from the chamber walls (depend on the chamber). Chamber walls can serve as sources or sinks for O 3, NO X, aldehydes and ketones. Photolysis maybe uncertain. Chamber experiments are conducted at much higher species concentrations than in the atmosphere (i.e. have a lot of radical reactions which do not occur in the real atmosphere). If e.g. EUPHORE chamber data were used these problems would be smaller.
O 3 ─ i s o p l e t s local noon Ref. Gross and Stockwell, JAC, 2004
O 3 and HO Scatter plots Without Emissions 3 days sim. Local Noon O3O3 O3O3 HO Ref. Gross and Stockwell, JAC, 2004 Δ: urban □: rural × : neither urban nor rural
HO 2 and RO 2 Scatter plots Without Emissions 3 days sim. Local Noon HO 2 RO 2 Ref. Gross and Stockwell, JAC, 2004 Δ: urban □: rural × : neither urban nor rural
Mechanism Comparison, Summary Compared to each other the mechanisms showed clear trends: O3: EMEP > RACM > RADM2 HO and HO2: RACM > EMEP and RACM > RADM2 RO2:EMEP > RACM and RADM2 > RACM The mechanism comparison showed little differences between the three mechanisms, equally good. However, all these mechanisms are based on the same guessed rates and reactions, i.e. the same amount of uncertainty. However, few of the simulated scenarios gave very large simulated differences between the mechanisms. This showed that only one “typical” scenario (which often has been considered to be sufficient) is not enough in order to make a proper mechanism comparison.
Biogenic Chemistry –Several hundreds different BVOC have been identified. Most well known are ethene, isoprene and the monoterpenes. –Isoprene is the major single emitted BVOC. –The BVOC emission depend highly on vegetation type. –BVOC emissions also contain oxygen-containing organics Estimated global Annual BVOC Emission (Tg/year) IsopreneMonoterpeneOther VOCs ≈ 500≈ 130≈ 650
Some Oxygen-Containing Organics Biogenic Sources 3-methyl-5-hepten-2-one 3-hexenal 2-hexenal thujone methanol ethanol n-hexanol 3-hexenol camphor linalool HO formaldehyde acetaldehyde acetone butanone n-hexanal O OH OO O O O O O O O O O 2-methyl-3-buten-2-ol formic acid acetic acid 3-henenyl-acetate 1, 8-cineol
Ref. Ruppert, 1999 EUPHORE Chamber Experiment and Simulation without BVOCs (called base mix)
Ref. Ruppert, 1999 EUPHORE Chamber Experiment and Simulation: base mix + 90 ppbV α-pinene
EUPHORE Chamber Experiment and Simulation: base mix + isoprene Sim. with RACM Sim. with modified RACM ozone toluene ethene isoprene NO 2 NO Ref. Ruppert, 1999
Biogenic Study, Summary The BVOC emission inventory are calculated from land-use data. The BVOCs emissions from plants are usually only given for isoprene and monoterpenes. However in Kesselmeier and Staudt (Atm. Env., 33, 23, 1999) are BVOCs from other compounds than isoprene and monoterpene presented. How shall the split of the emissions of monoterpenes into specific species (α-pinene, β-pinene, limonene etc.) be performed? This is not clear. BVOC emission inventories have uncertainties of factors ≈ 2.5-9. How good are the land-use data bases to describe the current BVOC? –How good are seasonal changes of vegetation described? –How good are human changes of vegetation described? The understanding of biogenic chemistry is very incomplete. Today only one lumped mch. treat other biogenic emitted species than isoprene. RACM also treat –API: α-pinene and other cyclic terpenes with more than one double bound, –LIM: d-limonene and other cyclic diene-terpenes. Commonly used lumped mechanisms (CBM-IV, RADM2, EMEP and RACM) do not describe the chemistry of isoprene very good.
DMS (DiMethyl Sulphide) Chemistry Identified Atmospheric Sulphur Compounds HSCH 3 SO 2 OH CS 2 CH 3 S(O)OOH COSCH 3 SCH 2 OOH SO 2 CH3S(O) 2 OOH H 2 SO 4 [SULF] CH 3 OS(O) 2 OH CH 3 SCH 3 [DMS] CH 3 OS(O) 2 OCH 2 CH 3 S(O)CH 3 [DMSO] CH 3 S(O) 2 CH 3 OOH CH 3 S(O) 2 CH 3 [DMSO 2 ] HOCH 2 S(O) 2 OH CH 3 SSCH 3 [DMDS] HOCH 2 S(O) 2 CH 2 OH CH 3 SHCH 3 SO 2 ONO CH 3 SOH [MSEA] CH 3 SO 2 ONO 2 CH 3 S(O)OH [MSIA] CH 3 S(O) 2 OH [MSA] It is not an easy task to make a DMS gas-phase mechanism?
A gas-phase DMS mch. was developed during the EU-project period. This DMS mch. included 30 sulphur species and 72 reactions (49 guessed & 23 experimental rates). Based on clean MBL scenarios the DMS ELCID mch. was reduced to 21 sulphur species and 34 reactions (22 guessed & 12 experimental rates). DMS mch. for Atm Modelling The ELCID gas-phase mch. The ELCID mch. was further reduced by lumping to 15 sulphur species and 20 reactions. This mechanism was used for 3D modelling in the ELCID project.
The Atmospheric Box-model In the box the following processes are solved for species i (which can be either a liquid or gas phases species): dC i /dt = + chemical production – chemical loss + emission – dry deposition – wet deposition + entrainment from the free troposphere to the boundary layer + aerosol model + CCN model + cloud model Ref. Gross and Baklanov, IJEP, 2004, 22, 52
Clean MBL Scenarios Simulated in the Study Meteorological Conditions: Ground Albedo 0.10 Pressure (mbar) 1013.25 Relative Humidity 90 % Cloud Frequency 1 d -1 Precipitation Frequency 0.1 d -1 Temperature (K) 288.25 Initial Aerosol Distribuitions: Nuclei Mode: Number conc.133 cm -3 log(σ) 0.657 Geo. Mean Dia. 0.8×10 -6 cm Accumulation mode: Number conc. 66.6 cm -3 log(σ) 0.21 Geo. Mean Dia..266×10 - 4 cm Initial Gas-Phase Conc.: H 2 2 ppmV CH 4 1.7 ppmV CO 0.14 ppmV H 2 O 3 % N 2 78% O 2 20 % NO 2 400 pptV H 2 O 2 1 pptV HO 2 0 pptV CH 3 O 2 0 pptV HNO 3 150 pptV O 3 40 ppbV HCHO 10 pptV VOC 5.5 ppbC SO 2 2 pptV DMS 100 pptV MSA 1 pptV Emission of SO 2 in pptV/min: 0.014 Emission of DMS in pptV/min: 0.00, 0.06, 0.12, 0.24, 0.36, 0.48, and 0.60
Emissions of DMS is varied from 0.0 (blue) to 0.6 (purple) pptV/min Emis. of SO 2 = 0.014 pptV/min for all the simulations DMSO X in pptV Inorganic Sulphur in pptV Ref. Gross and Baklanov, IJEP, 2004, 22, 51
Solid line: accumulation mode Dashed line: nuclei mode Particle number conc. in cm -3 Geometic mean diameter in cm Ref. Gross and Baklanov, IJEP, 2004, 22, 51
Influence of DMS on acc. mode particles in the clean MBL DMS emission in pptV/min AISAIWCGSCGWEUMELI3 DMS % cont. N nss 26.813.318.32.9512.9 DMS % cont. N tot upper limit17.89.7212.92.339.44 DMS % cont. N tot lower limit10.05.247.071.215.08 AIS/W: Amsterdam Island Summer/Winter CGS/W: Cape Grim Summer/Winter EUMELI3: oceanografic cuise south and east of the Canary Islands DMS % cont. N nss : DMS contribution in % to accumulation mode nss. aerosols. DMS % cont. N tot upper (lower) limit: the upper (lower) limit of DMS contribution in % to the sea salt plus the non sea salt accumulation mode aerosols. Ref. Gross and Baklanov, IJEP, 2004, 22, 51
Mechanism Comparison Number of Sulphur SpeciesReacs.Ref. Koga and Tanaka 33 40JAC, 1992, 17, 201 Hertel et al. 36 58Atm. Env. 1994, 38, 2431 Capaldo and Pandis 37 71JGR. 1997, 102, 23251 JRC ISPRA mch. 32 38Privat comm., 2002 ELCID mch. 21 34ELCID proj., 2004 Mechanism adjustments: The mechanisms is adjusted such that similar rate constants for the DMS loss, and SO 2 and H 2 SO 4 formation are used. Rest of the mechanisms are not changed.
Concentration of DMSO X (pptV) Contour levels from 50 to 850 pptV, increment interval 50 pptV DMS emis. = 0.36 ppt/min: ELCID: ── JRC ISPRA: ──, Cap&Pan: ── Hertel et al.: ──, Kog&Tan: ──, 2004, 1992, 1997, 2002, 1995 Ref. Gross and Baklanov, ITM, 2004
Particle number concentration (cm -3 ), Accumulation mode Contour levels from 10 to 120 cm -3, increment interval 10 cm -3 DMS emis. = 0.36 ppt/min: ELCID: ── JRC ISPRA: ──, Cap&Pan: ── Hertel et al.: ──, Kog&Tan: ── max. 105.0 pptV max. 117.7 pptV max. 104.4 pptV max. 118.5 pptV max. 118.5 pptV, 2004, 2002, 1994, 1992, 1997 Ref. Gross and Baklanov, ITM, 2004
DMS Study, Summary DMS important to include in atm. modelling if aerosols and large ocean areas are included in the model domain, since DMS can roughly contribute from 13─27% (summer period) and 3─13% (winter period) of the formation of non sea salt aerosols. from 10─18% (summer period) and 1─10% of the total aerosol formation. Too simplified DMS chemistry [DMS(g)+HO(g)->SO2(g)->H2SO4(l)] create too many new accumulation mode particles (Gross and Baklanov, ITM, 2004). The DMS mechanism comparison showed that all five mechanism gave all most the same amount of inorganic DMSO X, sulphur, aerosols, equally good. However, all these DMS mechanisms are based on the same guessed rates and reactions, i.e. the same amount of uncertainty.
DMS Summary, Resent Results A resent ab initio/DFT study (Gross, Barnes et al., JPC A, 2004, 108, 8659) shows: 1.DMSOH + O 2 → DMSO + HO 2 (the dominant channel) 2.DMSOH + O 2 → DMS(OH)(OO) (occur, minor channel) 3.DMSOH + O 2 → CH 3 SOH + CH 3 O 2 (does not occur) However, in DMS mechanisms channels 1 and 2 are often considered to be equal important, and channel 3 is included. Simulations of DMS chamber experiments (which were performed at different temperatures and NO X concentrations) indicate that we still not fully understand the chemistry of the additional DMS+HO channel. Important chemical mechanisms are missing. (Gross and Barnes, unpublished results).
Conclusions More detailed mechanisms of aromatics and peroxide reactions are needed. The isoprene chemistry should been updated in the lumped mechanisms. If heterogeneous chemistry also is included in the ACTM many parameters used to described the mass transport of gas-phase species to aerosols and these species aerosol physics are still uncertain/unknown. The DMS chemistry is still highly uncertain both with respect to rate constant determination and the product mechanism. Furthermore, the emission of DMS is poorly known. Better description of biogenic emissions is needed before it is meaningful to increase the chemistry of BVOC with more species than isoprene and monoterpene. (personal opinion). Has described the most important chemistry need for regional scale Atmospheric Chemistry Transport Modelling (ACTM), and has described where atmospheric chemistry still has large uncertainties.
Collaborators Atmospheric Science: Senior Scientist Alexander A. Baklanov, Danish Meteorology Institute, Denmark. Senior Scientist Jens H. Sørensen, Danish Meteorology Institute, Denmark. Senior Scientist Alix Rasmussen, Danish Meteorology Institute, Denmark. Research Scientist Alexander Mahura, Danish Meteorology Institute, Denmark. Atmospheric Chemistry: Research Prof. William R. Stockwell, Desert Research Institute, Reno, Nevada, USA. Associate Prof. I. Barnes, University of Wuppertal, Germany. Ph.D. Stud. Marianne Sloth, University of Copenhagen, Denmark and Danish Meteorological Institute, Denmark. Theoretical and Physical Chemistry: Prof. Kurt V. Mikkelsen, University of Copenhagen, Denmark. Asistant Prof. Balakrishan Naduvalath, State University of Nevada, Las Vegas, USA. Ph.D. Stud. Nuria Gonzales Garcia, Universitat Autonoma de Barcelone, Spain. Research Assistant Hanne Falsig, University of Copenhagen, Denmark.