Transcript Slide 1

Non-linear effects in modelling PM10 and PM2,5
contributions from anthropogenic sources
Clemens Mensink, Felix Deutsch,
Jean Vankerkom and Liliane Janssen
VITO
Centre for Integrated Environmental Studies
Mol, Belgium
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Contents
1. Introduction
2. Methodology
• EUROS model
• Extension to PM modelling
3. Results & discussion
• Emission scenarios for 2010
• Sector contributions
• Non-linear effects
4. Conclusions
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Introduction
• In Belgium and Europe we are faced with episodes
of high PM concentrations (2003: 10 episodes with
PM10 > 100 µg/m³)
• These are associated with adverse health effects
(Pope et al., 1995; Dockery et al., 1993)
• We want to study why and how these episodes
occur, using numerical models
• What are the possible abatement strategies ?
(policy support)
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Methodology
• EUROS model, originally developed for ozone at
RIVM and implemented in Belgium in 2001 as an
operational tool for policy support (BelEUROS)
• 2004/2005: extension for PM modelling
 Domain: Europe (shifted pole coordinates)
 Resolution: horizontal: 6015 km; vertical: 4 layers
 Meteorology: ECMWF (T, rH, ws+wd, CC, PR),
ALADIN (mixing height)
 Emissions: EMEP/CORINAIR for Europe + detailed
national emission inventories
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PM10 modelled
for 2002
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wet
upper layer
wet
deposition
fumigation
reservoir layer
mixing layer
vertical
diffusion
dry
deposition
surface layer
time
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Methodology
Implementation of two new modules in the
ozone-version of BelEUROS
• gas phase mechanism: CB-IV (ozone) -> CACM (PM)
(Caltech Atmospheric Chemistry Mechanism)
122 components, 361 reactions
contains ozone-chemistry AND describes the formation of
presursors for secondary organic aerosols in a mechanistic way
• aerosol module: MADRID 2
(Model of Aerosol Dynamics, Reaction, Ionization, and
Dissolution)
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Chemical-Aerosol-Module CACM/MADRID 2
emissions prim. inorg. aerosols, NH3
emissions prim. org. aerosols
emissions
SO2, NOx
emissions
NMVOS
emissions
NMVOC
anorganic
compounds
organic
hydrophilic
compounds
organic
hydrophobic
compounds
INORG.
EQUIL.
lumped (5c.)
inorg. distr., LWC, H+

org. distr., new
LWC/H+
CHEMICAL
MECHANISM
ORGANIC
HYDROPHIL.
Lumped (5c.)
ORGANIC
HYDROPHOB.
liquid
phase
mechanism
heterogenic
phase
mechanism
EQUILIBRIUM
MODULE
iterations till
LWC = const.
total distrib.
inorg. + org.
Inorg. + Organ.
composition; size
distribution
Nucleation
Condensation
PARTICLE
FORMATION
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Industry
Traffic
Agriculture
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Biogenic
vegetation: isoprenes
and terpenes
NOT: mineral dust from outside
the domain
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Biogenic
NOT: forest fires
NOT: sea salt
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6-hourly reanalysed meteorological fields (ECMWF)
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Mixing height for the domain (ALADIN)
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Model output
 mass and 7 chemical compounds
for 2 size bins (PM10-2,5, PM2,5):
 primary inorganic compounds
 primary organic compounds
 elementary carbon
 sulphate SO42- (primary and secondary)
 ammonium NH4+, nitrate NO3- and SOA
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Measured & modelled PM10 - URBAN station
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Measured & modelled PM10 - URBAN station
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Results & Discussion
• Emission scenarios for 2010
• Base year 2002 (EMEP)
• CAFE 2010 CLE scenario (IIASA)
• Setting all emissions in Flanders to zero
• Sector contributions
• Setting all emissions in sector to zero
• Non-linear effects
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Belgian emissions for 2002
EUROS-sector
1 combustion
NH3
NMVOC
NOx
SO2
PM2.5
PM10-2.5
95
2035
47428
52131
1381
2570
360
5134
22175
22947
4770
1884
0
14944
0
0
108
1308
3439
37846
66085
74406
15154
15630
0
72146
0
0
0
0
1370
96814
164286
8491
11054
2219
7 agriculture
73737
1082
25
26
1533
6389
Total
79000
230000
300000
158000
34000
30000
2 residential
3 refineries
4 industry
5 solvent use
6 traffic
Belgian emissions (in Mg) for the year 2002
according to EMEP, Expert emissions
W-05emis02-V5 (2005-03-10)
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Results & Discussion
2002
CLE 2010
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Results & Discussion
2002
2010
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Results & Discussion
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Concentration change 2002-2010
max. change [%]
Location
Flanders
Wallonia
Brussels
Belgium
PM10
-21,9
-26,4
-12,8
-26,4
PM2.5
-20,7
-24,0
-16,5
-24,0
min. change [%]
PM10
-4,8
-9,2
-11,9
-4,8
PM2.5
-8,0
-12,5
-15,1
-8,0
avg. change [%]
PM10
-11,6
-12,8
-12,3
-12,3
PM2.5
-14,8
-14,9
-15,8
-14,9
Relative difference of PM10- and PM2,5-concentrations
between 2002 and 2010 in the Belgian regions.
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Sector contributions in 2010
Contribution of sectors 2010 PM10
non-anthrop. Fl.
combustion
domestic
ind./ref./solvent
traffic
agriculture
Contribution of sectors 2010 PM2.5
non-anthrop. Fl.
combustion
domestic
ind./ref./solvent
traffic
agriculture
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Sector contributions
Anthropogenic contributions from
sectors in Flanders
PM10 (%)
2002
0.7
PM2.5 (%)
2002
1.1
Residential
2.4
3.7
1.4
2.4
Refineries & industry & solvent use
0.9
1.2
0.8
1.2
Traffic
4.0
5.9
3.7
5.6
Agriculture
7.5
0.5
7.6
1.0
15.5
12.4
13.8
10.7
Combustion
Total
PM10 (%)
2010
0.3
PM2.5 (%)
2010
0.5
Relative contributions [%] of the anthropogenic sources per sector
to PM10- and PM2.5-concentrations obtained by setting all
anthropogenic emissions in one sector in Flanders to zero.
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Reductions for zero emissions
Location
Flanders
Wallonia
Brussels
Belgium
max. reduction [%]
min. reduction [%]
avg. reduct. [%]
PM10
-22.3
-18.0
-19.8
-22.3
PM10
-2.4
-1.0
-11.0
-1.0
PM10
-15.2
-2.6
-15.4
-8.2
PM2.5
-25.3
-15.8
-20.6
-25.3
PM2.5
-1.5
-1.1
-12.1
-1.1
PM2.5
-11.9
-2.6
-16.7
-6.7
Reductions [%] in PM10- and PM2,5-concentrations
obtained by setting all anthropogenic emissions in
Flanders to zero in 2010.
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Results & Discussion
• Reduction in PM10 obtained when setting all
emissions in Flanders to zero: 15,2%
• Sum of the reductions in PM10 obtained when
setting all emissions in individual sectors to
zero: 13,8%
• Did we miss something (1,4%) ???
• No! non-linear effects (or synergies)
account for approximately 10% of the
reductions !!!
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Results & Discussion
EUROS-sector
1 combustion
NH3
NMVOC
NOx
SO2
PM2.5
PM10-2.5
95
2035
47428
52131
1381
2570
360
5134
22175
22947
4770
1884
0
14944
0
0
108
1308
3439
37846
66085
74406
15154
15630
0
72146
0
0
0
0
1370
96814
164286
8491
11054
2219
7 agriculture
73737
1082
25
26
1533
6389
Total
79000
230000
300000
158000
34000
30000
2 residential
3 refineries
4 industry
5 solvent use
6 traffic
Belgian emissions (in Mg) for the year 2002
according to EMEP, Expert emissions
W-05emis02-V5 (2005-03-10)
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Discussion: non-linear effects
• Emissions from various sectors are effectively necessary for
the formation of the secondary compound (e.g. formation of
ammonium-nitrate through emission contributions from the
sectors traffic (NOx) and agriculture (NH3))
• During the formation of secondary aerosols (nitrate, sulphate,
ammonium and SOA) a small reduction in a gaseous
compound (e.g. SO2) does not necessarily lead to the same
amount of reduction of the secondary compound (e.g. SO4)
• Non-uniform spatial distribution of the emissions and
concentrations may locally lead to enhanced formation of
secondary aerosols
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Assumptions & caveats
• The emission factor used to estimate the emissions for the
sector “agriculture” is very uncertain (and currently in
revision).
• Diffusive emission sources (e.g. fugitive emissions stemming
from handling and storing activities) are not taken into
account, although recently they are gaining more importance
in abatement strategies with the aim to comply with the limit
values for particulate matter (EU directive 1999/30/EU)
• The CLE scenario was still in discussion in the context of
CAFE and can therefore not be considered as the definite
choice.
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Conclusions
• EUROS has been extended with CACM & MADRID 2
to model mass and chemical composition (7 compounds)
of PM2,5 and PM10-2,5
• Contributions from anthropogenic sources in Flanders are
found to be responsible for 17,1% of the annual averaged
PM10 concentrations in Flanders in 2002. In 2010 this
contribution drops to 15,2%.
• Non-linear effects can not be neglected and were found to
be in the order of 10%.
• The results demonstrate the severe limitations with
respect to impact of national policy measures for relatively
small countries such as Belgium
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Acknowledgement
• We would like to thank the Flemish Environmental
Administration for financially supporting this study
• We would like to thank the Flemish Environmental
Agency and the Interregional Cell for the Environment
in Brussels for supplying the air quality data
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