Transcript Atmospheric chemistry: Overview and future challenges

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)
Develop and implement at ECMWF a new validated, comprehensive and
operational global data assimilation/forecasting system for atmospheric
composition and dynamics.
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.
GEMS Global System
Data input (Assimilation, Satellite, Real-time)
optical
properties
oxidants
Coordination
oxidants
green house gasses
GEMS
Global
System
Global
Aerosols
Global
Greenhouse
Gasses
boundary
conditions
Regional
Regional
Air
Quality (RAQ
Air
Quality
modelling)
System Integration
Global
GlobalReactive
ReacGasses(UVtive Gasses
forecast)
Products, User Service
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.
Operational deliverables
• Current and forecasted 3-dim. global distributions of atmospheric
key compounds (horizontal resolution 50 km):
– greenhouse gases (CO2, CH4, N2O and SF6),
– reactive gases (O3, NO3, SO2, 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
Individual
20 Institutes
V.-H. Peuch (co.), A. Dufour
METEO-FR (Météo-France, Centre National de Recherches Météorologiques)
A. Manning
METO-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. Langmann
MPI-M (Max-Planck Institut für Meteorologie)
H. Eskes
KNMI (Koninklijk Nederlands Meteorologisch Instituut)
J. Kukkonen, M. Sofiev
FMI (Finnish Meteorological Institute)
A. Gross, J.H Sørensen
DMI (Danmarks Meteorologiske Institut)
M. Beekmann
SA- UPMC (Université Pierre et Marie Curie Service d’Aéronomie)
C. Zerefos, D. Melas
NKUA (Laboratory of Climatology and Atmospheric Environment, University of Athens)
M. Deserti, E. Minguzzi
ARPA-SM (ARPA Emilia Romagna, Servizio IdroMeteorologico)
F. Tampieri, A. Buzzi
ISAC (Institute of Atmospheric Sciences and Climate Consiglio Nazionale delle Ricerche)
L. Tarrason, L.-A. Breivik
DNMI (Det Norske Meteorologisk Institutt)
H. Elbern, H. Jakobs
FRIUUK (Rheinisches Institut für Umweltforschung, Universität Köln)
L. Rouil
INERIS (Institut National de l’Environnement Industriel et des Risques)
J.Keder, J.Santroch
CHMI (Czech Hydrometeorological Institute)
F.McGovern B.Kelly
EPAI (Irish Environmental Protection Agency)
W.Mill
PIEP (Polish Institute of Environmental Protection)
D.Briggs
ICSTM (Imperial College of Science, Technology and Medicine, London)
Models Within RAQ Sub-Project
Contribution 
Models and Partners 
Target species
Data assimilation
NRT Forecast
E/P*
Re-analyses
simul. E / P *
MOCAGE
METEO-FR
Ozone and precursors (RACM);
aerosol components (ORISAM);
ENVISAT; MOPITT;
OMI; IASI; surface data
P and E
E
BOLCHEM
CNR-ISAC
Ozone and precursors (CB-IV or
SAPRC90).
Surface and profile
data.
P, then E
P, case studies
EURAD
FRIUUK
Ozone and precursors (RACM);
aerosol components (MADE).
SCIAMACHY; MOPITT;
surface data.
P, then E
_____
CHIMERE
CNRS and
SA_UPMC
Ozone and precursors (EMEP or
SAPRC90); aerosol components
(ORISAM).
SCIAMACHY; Surface
and profile data.
P
P
SILAM
FMI
Chemically inert aerosols of arbitrary
size spectrum
_____
P
P, year 2000
MATCH
FMI
Ozone and precursors (EMEP);
aerosol components (MONO32).
_____
P
P, year 2000
CAC
DMI
Ozone and precursors (RACM) and
sulphur/DMS; aerosol components.
_____
P
P, case studies
MM5-UAMV
NKUA
Ozone and precursors (CB-IV).
_____
P
P, case studies
EMEP
met.no
Ozone and precursors (EMEP);
aerosol components (MM32).
MERIS and MODIS for
PM information
P
P, 2005
REMO
MPI-M
Ozone and precursors (RADM2).
_____
_____
P
UMAQ-UKCA
UKMO
Ozone 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 NOX, and
VOC chemistry shall also be included.
Reaction
HOXNO
and
high VOCs
Reaction
CycleCycle
of HOofX and
onlyx,VOC
– methane
x, NO
CH
Hydrocarbons
4
H2O2, CO
H2 O2
HCHO, RCHO
products
hν
CH
RO
3O
22
O3
hν +H2O
HO
O3
HO2
HNO3
RNO3
H2 O2
Hydrocarbons
HCHO
NO
NO2
Nighttime chem.
NO3
RONO2
RO+NO2
CH
ROOH
3OOH
RO3NO2
RO2NO2
hν
O(3P)
CO
Hydrocarbons
O3
Oxidation Steps of Hydrocarbons
NO3 O2
HO2
R’─R
HO
ROOH
hν
HO
C12H26
NO3+O2
NO2
HO
O2 RO NO3 NO
3
RH
R·
RO2
RO·
H2 O
NO2 NO2
O3
R’CHO
R’─R
O
NO
R’CHO
HO2
RO3
RO2
HO2
HO
R(ONO2)
O
O
O2
HNO3
CH3Cl
R’O2
NO3
hν+O2
HO
C2Cl4
RO + R’O+ O2
R(-H)O+R’OH+O2
ROOR’+O2
ROOH+R’O2
Green: only alkene path
Red: also other end products
but these react further
to the given end product
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 RO2+ R’O2, RO2 + HO2, RO2 +NO2 ,RO2 + NO reactions
and their products are very limited and complex.
– E.g. system with only 10 RO2 (no NOX) results in approximately 165
reactions.
• ozonolysis of alkenes are important in urban polluted area.
Example:
O3 + H2 C
O
O
CH2 →
O
→HCHO + H2COO *
primary ozonide
H2COO 37%
CO+H2O 38%
CO2+H2 13%
Criegee biradical
The rate and product yields of the stable Criegee biradical with NO, NO2
and H2O 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
O
O
O
trans-butenedial
O
O
O
4-oxo-2-pentanal
3-hexene-2,5-dione
(Atmospheric oxidation products from aromatics)
O
O
4-hexadienedials
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
studied by more than one lab. but with over all uncertainties greater than 30%
iso-propyl-benzene
o- m- p-ethyl-toluene
tert-butyl-benzene
indan
indene
– 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
NO2
NO2
NO2
flouranthene
1-: 2-nitronaphthalene
2-methyl-1-nitron-aphthalene
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)
O
O
phenanthrene (fac. of 2)
dibenzo-p-dioxin(fac. of 1.5)
dibenzofuran (30%)
anthracene: one of the most abundant and important PAH in the atmosphere
Rate highly uncertain:
anthracene
range (18 to 289) × 10-12 cm3 molecule-1
HO +PAH
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:
3-methyl-phenanthrene
pyrene
benzo[a]flouorene
NO3 + 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).
OH
OH
Only studies: NO3 +
&
phenol
OH
&
o-: m-: p-cresol
NO2
m-nitro-phenol
• O3 + aromatics: have gaps but these reactions are not
highly important in atmospheric chemistry.
• O(3P) + 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
NO3 with HO
□ (line c): addition reactions
Δ (lines a & b): abstraction reacs
Correlation of the rates for
NO3 with O(3P)
Correlation of Peroxy ─ Peroxy Radical Reactions
Function fit depend on number of carbons
and the alkyl-alkoxy substitution
Function fit depend on the rates from the
reactants peroxy-self-reaction rates
Lumped Atmospheric Chemical Mechanisms
Mech.
Abbreviation
Developed
in
Number of
Species
Reactions
47
114
ADOM-11
USA
CB-IV
USA
27
63
RADM2
USA
63
158
SAPRC-90
IVL
USA
Europe
60
715
155
1640
EMEP
RACM
Europe
USA
79
77
141
237
SAPRC-99
Master MCH.
USA
Europe
74
2400
211
7100
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: NO2, NO and O3.
Chamber Experiment EC-237
•
•
•
•
•
Photolysis
NOX
Ethene
Propene
tert-2-butene
•
•
•
•
n-butene
2, 3-dimethylbutene
toulene
m-xylene
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 O3, NOX,
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.
O3
─
i
s
o
p
l
e
t
s
local
noon
Ref. Gross and Stockwell, JAC, 2004
O3 and HO
Scatter plots
O3
HO
O3
HO
Without
Emissions
3 days sim.
Local Noon
Δ: urban
□: rural
×: neither urban
nor rural
Ref. Gross and Stockwell, JAC, 2004
HO2 and RO2
HO2
RO2
HO2
RO2
Scatter plots
Without
Emissions
3 days sim.
Local Noon
Δ: urban
□: rural
×: neither urban
nor rural
Ref. Gross and Stockwell, JAC, 2004
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)
Isoprene
Monoterpene
Other VOCs
≈ 500
≈ 130
≈ 650
ethylene
isoprene
2-methyl-3-buten-2-ol
many tissues
methanol
chloroplasts
monoterpenes
cell walls
resin ducts or glands
100s of VOC
flowers
cell membranes
C6-acetaldehydes
C6-alcohols
leaves, stems, roots
formaldehyde
formic acid
acetaldehyde
acetic acid
ethanol
acetone
(Fall, 1999)
Some Biogenic Emitted Hydrocarbons
isoprene
terpinolene
α-pinene
α-phellandrene
β-pinene
limonene
β-phellandrene
myrcene
α-terpinene
ocimene
γ-terpinene
camphene
Δ3-carene
p-cymene
Some Oxygen-Containing Organics Biogenic Sources
O
O
formaldehyde
O
acetaldehyde
acetone
butanone
n-hexanal
O
O
3-methyl-5-hepten-2-one
OH
O
3-hexenal
O
2-hexenal
thujone
methanol
O
OH
ethanol
OH
n-hexanol
OH
HO
2-methyl-3-buten-2-ol
OH
OH
3-hexenol
camphor
linalool
OH
O
formic acid
O
O
O
acetic acid
3-henenyl-acetate
1, 8-cineol
EUPHORE Chamber Experiment and Simulation without BVOCs (called base mix)
Ref. Ruppert, 1999
EUPHORE Chamber Experiment and Simulation: base mix + 90 ppbV α-pinene
Ref. Ruppert, 1999
EUPHORE Chamber Experiment and Simulation: base mix + isoprene
Sim. with RACM
Sim. with modified RACM
ozone
toluene
ethene
isoprene
NO2
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
HS
CH3SO2OH
CS2
CH3S(O)OOH
COS
CH3SCH2OOH
SO2
CH3S(O)2OOH
H2SO4 [SULF]
CH3OS(O)2OH
CH3SCH3 [DMS]
CH3OS(O)2OCH2
CH3S(O)CH3 [DMSO]
CH3S(O)2CH3OOH
CH3S(O)2CH3 [DMSO2]
HOCH2S(O)2OH
CH3SSCH3 [DMDS]
HOCH2S(O)2CH2OH
CH3SH
CH3SO2ONO
CH3SOH [MSEA]
CH3SO2ONO2
CH3S(O)OH [MSIA]
CH3S(O)2OH [MSA]
It is not an easy task to make a DMS gas-phase mechanism?
The ELCID gas-phase mch.
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).
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.
DMS mch. for Atm Modelling
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):
dCi/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
Influence of DMS on acc. mode particles in the clean MBL
DMS emission in pptV/min
DMS % cont. Nnss
AIS
AIW CGS CGW EUMELI3
26.8
13.3
18.3
2.95
12.9
9.72
12.9
2.33
9.44
5.24
7.07
1.21
5.08
DMS % cont. Ntot
upper limit
17.8
DMS % cont. Ntot
lower limit
10.0
Ref. Gross and Baklanov, IJEP, 2004, 22, 51
AIS/W: Amsterdam Island Summer/Winter
CGS/W: Cape Grim Summer/Winter
EUMELI3: oceanografic cuise south and east of the Canary Islands
• DMS % cont. Nnss: DMS contribution in % to accumulation mode nss. aerosols.
• DMS % cont. Ntot upper (lower) limit: the upper (lower) limit of DMS contribution
in % to the sea salt plus the non sea salt accumulation mode aerosols.
Mechanism Comparison
Koga and Tanaka
Hertel et al.
Capaldo and Pandis
JRC ISPRA mch.
ELCID mch.
Number of Sulphur
Species
Reacs.
33
40
36
58
37
71
32
38
21
34
Ref.
JAC, 1992, 17, 201
Atm. Env. 1994, 38, 2431
JGR. 1997, 102, 23251
Privat comm., 2002
ELCID proj., 2004
Mechanism adjustments:
• The mechanisms is adjusted such that similar rate constants for the
DMS loss, and SO2 and H2SO4 formation are used.
• Rest of the mechanisms are not changed.
Concentration of DMSOX (pptV)
, 2004
, 1995
, 2002
, 1992
Contour levels from 50 to 850 pptV, increment interval 50 pptV
Ref. Gross and Baklanov, ITM, 2004
, 1997
DMS emis. = 0.36 ppt/min: ELCID: ──
JRC ISPRA: ──,
Cap&Pan: ──
Hertel et al.: ── ,
Kog&Tan: ──
Concentration of inorganic sulphur (pptV)
, 2004
, 2002
max.
117.5
pptV
, 1995
max.
153.2
pptV
max.
133.6
pptV
, 1992
max.
117.5
pptV
Contour levels from 10 to 165 pptV, increment interval 15 pptV
Ref. Gross and Baklanov, ITM, 2004
, 1997
max.
137.3
pptV
DMS emis. = 0.36 ppt/min: ELCID: ──
JRC ISPRA: ──,
Cap&Pan: ──
Hertel et al.: ── ,
Kog&Tan: ──
Particle number concentration (cm-3), Accumulation mode
, 2004
, 2002
max.
118.5
pptV
, 1994
max.
118.5
pptV
Contour levels from 10 to 120 cm-3, increment interval 10 cm-3
Ref. Gross and Baklanov, ITM, 2004
max.
117.7
pptV
, 1997
max.
104.4
pptV
, 1992
max.
105.0
pptV
DMS emis. = 0.36 ppt/min: ELCID: ──
JRC ISPRA: ──,
Cap&Pan: ──
Hertel et al.: ── ,
Kog&Tan: ──
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 DMSOX, 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 + O2 → DMSO + HO2
(the dominant channel)
2. DMSOH + O2 → DMS(OH)(OO) (occur, minor channel)
3. DMSOH + O2 → CH3SOH + CH3O2
(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 NOX 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).
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.
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).
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.