Work package 05
Start: October 2006
Reporting period: January 2007 – June 2007
Authors: Matthias Beekmann, CNRS
Work package objectives:
Modelling of test cases to estimate ambient air concentrations under “low anthropogenic”
conditions and assessment of policy instruments applied by the EU and CLRTAP.
Presentation of modeling results
1. Emissions
Biogenic and natural emission inventories developed in other work packages during NatAir project
were implemented and tested into CHIMERE chemistry-transport model. The following natural and
biogenic sources were implemented:









Natural and semi-natural vegetation (NMVOC)
NO from soils (natural and agricultural) (NO)
Wind blown dust (PM)
Biomass burning and forest fires (NOx, PM, CO, NMVOC)
Primary biological aerosol particles (PM)
Sea salt (PM)
Wild animals (CH4, NH3)
Anoxic soil processes (wetlands) (CH4)
Geological seepages (CH4)
In the following, we show annual totals of anthropogenic and biogenic/natural emissions for various
compounds and source types used in CHIMERE simulations. All maps are given with the same
colour scale in order to facilitate cross comparison.
1.1.
Non Methane Volatile Organic Compounds (NMVOC)
Figure 1.1. Annual emissions of Non Methane Volatile Organic Compounds (NMVOC) for year 2000. Maps units read
millions of grams (Mg). On the left, athropogenic emissions derived from EMEP expert emissions; on the right,
summed Biogenic VOC (BVOC = isoprene, monoterpenes, sesquiterpenes and other VOCs) and biomass burning
NMVOC emissions calculated within NatAir project. All emissions are remapped on the 0.5°x0.5° grid of CHIMERE
model used for simulations. Total emission over domain is shown inset in millions of tons (Tg=106 Mg).
In Figure 1.1 we show annual anthropogenic and biogenic emissions of NMVOC for year 2000.
Anthropogenic sources are taken from EMEP expert emissions, while biogenic sources are summed
hourly emissions of isoprene, monoterpenes, sesquiterpenes and other VOCs calculated within
NatAir project. The total annual flux of VOC over the domain is the same order of magnitude for
anthropogenic and biogenic sources. However, there is great variability in the local share of
NMVOC emissions from anthropogenic/biogenic sources. In large metropolitan areas of London,
Paris, Benelux, Western Germany and Northern Italy anthropogenic sources clearly contribute most
to NMVOC burden. Anthropogenic hot spots are also clearly visible over large cities such as
Madrid, Barcelona, Rome, Naples, Warsaw, Budapest, Bucharest and Athens. On the other hand, in
Portugal, Spain, Southern Italy, Greece, Balkans and Scandinavia biogenic sources contribute more
than anthropogenic sources.
Figure 1.2. Comparison of isoprene (left panels) and terpenes (right) emissions from NatAir (top panels) and derived
from Simpson et al. (1999) (bottom) for year 2000. Note that colour scale and units are different with respect to Figure
1.1. Total annual emissions in Tg is shown inset.
In Figure 1.2 we compare BVOC emissions calculated within NatAir with previous widely-used
estimate by Simpson et al. (1999). Country annual totals given in the latter, are implemented into
CHIMERE as gridded emissions as described by Derognat et al. (2003). We shall refer to “NatAir”
and “D03” emissions respectively for the first and the latter inventory. NatAir is more detailed than
the D03 model in several respects: (1) use of plant species distributions on a regional level instead
of general distributions on national level, (2) revised emission factors and biomass densities
including their seasonal variability, (3) introduction of a canopy model to adjust for light extinction
and the leaf temperature variations inside the canopy. For further detailed information please refer
to the part of the report dedicated to results of emissions work package.
Isoprene emissions in NatAir are reduced at about half of D03 emissions, while terpenes
(monoterpenes plus sesquiterpenes) emissions are the same magnitude in both inventories. NatAir
emissions are generally lower than D03 in Central and Eastern Europe and Scandinavia, while are
higher over Iberian Peninsula. The latter emerges as the largest European BVOC hot-spot in NatAir.
NatAir emissions display finer structures in their spatial distribution, for example over France and
the Balkans, as a result of the detailed species distributions used in calculations. Note that over
Ukraine and Russia emissions couldn’t be calculated in D03 because of lack of input data.
Figure 1.3. Speciated NatAir BVOC emissions for year 2000. Isoprene (top-left), monoterpenes (top-right),
sesquiterpenes (bottom-left) and other VOCs (bottom-right) annual total summed over domain is shown inset in Tg.
Speciated NatAir BVOC emissions for year 2000 are shown in Figure 1.3. In terms of total
NMVOC flux monoterpenes and other VOCs are the most important sources. These emissions have
been implemented into CHIMERE model as follows:
1. Isoprene as isoprene
2. Sum of Monoterpenes and Sesquiterpenes as α-pinene
3. Other VOC splitted as follows:
o 64% methanol
o 2% formaldehyde
o 11% ethanol
o 11 % acetaldehyde
o 12% acetone
BVOC emissions in CHIMERE model contribute to gas phase chemistry through their oxidation
that yield to ozone production and to aerosol phase through formation of secondary organic aerosol
(SOA) from oxidation of terpenes.
Figure 1.4. Biomass burning emissions calculated within NatAir for year 2000.
The contribution to total NMVOC emissions from biomass burning is shown in Figure 1.4. Biomass
burning makes a significant contribution only over Iberian Peninsula for this particular year, where
it can represent up to 5% of NMVOC emissions at some locations. NMVOC biomass burning
emissions are splitted into CHIMERE following emission factors given in Table 1 of Andreae and
Merlet (2001) with these fractions:
 1.2% isoprene
 1.5 % terpenes
 13.8% methanol
 15.2% formaldehyde
 0.8% ethanol
 6.0% acetaldehyde
 14.1% acetone
 6.6% ethane
 6.0% n-butane
 7.7% ethylene
 7.6% propene
 19.6% xylenes
1.2.
Nitrogen oxides (NOx)
Figure 1.5. Nitrogen oxides annual emissions for year 2000. Anthropogenic emissions (left) form EMEP expert data
and biogenic NO from soils and biomass burning (right) calculated within NatAir. Annual totals over domain in Tg
shown inset.
In Figure 1.5 we show NOx emissions for year 2000 from anthropogenic (EMEP) and biogenic
(NatAir) sources. NatAir daily NO emissions from soils were calculated only for those countries for
which enough input data to the model were available (see dedicated section for details). On an
annual/continental basis biogenic sources of NOx are insignificant compares to anthropogenic
sources, being only 2% of the latter. But they can have a significant role in rural areas where
anthropogenic emissions are low. For example, in some areas of Spain and France biogenic NO
from soils may contribute up to 20% of total NOx emissions. In Portugal biomass burning may also
contribute up to 20% locally.
1.3.
Particulate Matter (PM)
Figure 1.6. Annual primary emissions of PM10 from EMEP anthropogenic (left) and natural/biogenic sources (right)
calculated within NatAir. NatAir sources include: wind blown dust, primary biological aerosol particles (PBAP),
biomass burning, and sea salt. Annual total for natural/biogenic emissions is calculated considering only emissions over
the continent (thus excluding sea salt).
In Figure 1.6 we show primary PM10 emissions from anthropogenic (EMEP expert data) and
natural/biogenic sources calculated within NatAir for year 2000. NatAir natural/biogenic sources
include: wind blown dust, primary biological aerosol particles (PBAP), biomass burning, and sea
salt. Natural/biogenic emissions sum up to about 30% of anthropogenic total emissions over the
continent. Sea salt is emitted in huge fluxes, but only a small fraction of emitted particles reaches
the coast and penetrate into the continent (as we shall see in the following). The fraction of PM2.5
for each kind of source is estimated as follows:
 Anthropogenic PM10 : 65% PM<2.5 µg/m3
 Wind blown dust PM10 : 0% PM<2.5 µg/m3
 PBAP PM10 : 15% PM<2.5 µg/m3
 Biomass Burning PM10 : 45% PM<2.5 µg/m3
 Sea Salt PM10 : 8% PM<2.5 µg/m3
An important impact of natural/biogenic primary emissions on PM10 is expected along coastal
zones because of sea salt emissions, and in many rural areas where wind blown dust clearly
overwhelm anthropogenic PM10 emissions.
Figure 1.7. Separated natural and biogenic PM10 sources calculated within NatAir for year 2000. Total emissions for
wind blown dust (top-left), biomass burning (top-right), PBAP (bottom-left) and sea salt (bottom-right) are shown inset.
In Figure 1.7 the contribution of each source type calculated within NatAir is shown. Over the
continent dust emissions clearly dominates, while near costal areas sea salt emissions are expected
to play a major role. Biomass burning again make a sensible contribution only in Portugal and
Spain, while PBAP is expected to play a minor role in PM10 formation.
1.4.
Methane (CH4)
Figure 1.8. Annual natural/biogenic sources of methane calculated within NatAir for year 2000. Separated contribution
from each type of source is shown in Figure 1.9.
Methane emissions included in CHIMERE model are only of natural/biogenic origin as calculated
within NatAir project. The summed total emissions from all kind of sources is shown in Figure 1.8,
while the contribution from every single source type is given in Figure 1.9. Wetlands are the most
important source with particularly elevated emissions in Northern Europe, followed by geological
seepages that near the emission source (e.g. Black Sea) can reach very high emission fluxes.
Humans and pets methane emissions are as expected concentrated in large urbanized areas, while
wild animals emissions are more homogeneously distributed over the continent.
Figure 1.9. Methane 2000 annual emissions calculated within NatAir. From top-left to bottom-right the following
source were considered: anoxic processes in wetlands, biomass burning, geological seepages, humans, pets and wild
animals.
1.5.
Ammonia (NH3)
Figure 1.10. Annual ammonia emissions from anthropogenic (EMEP) and biogenic (NatAir) sources for year 2000.
Biogenic NH3 emissions calculated within NatAir include: humans, pets and wild animals.
In Figure 1.10 anthropogenic and biogenic annual emissions of ammonia are shown. Anthropogenic
emissions are EMEP expert emissions, while biogenic sources are calculated within NatAir and
include humans, pets and wild animals. Biogenic ammonia sources sum up only to 2% of
anthropogenic sources and are not expected to have a major impact on NH3 concentrations and
PM10 formation.
1.6.
Carbon monoxide (CO)
Figure 1.11. Anthropogenic and biogenic carbon monoxide sources for year 2000. The only biogenic CO source
calculated in NatAir is biomass burning.
In Figure 1.11 carbon monoxide emissions for year 2000 are shown. Anthropogenic (EMEP expert
data) largely dominates over NatAir biogenic sources (biomass burning) even at a local scale.
2. CHIMERE chemistry-transport model
In the following chapters, we show results on the impact of NatAir natural and biogenic emissions
on ozone and PM10 using CHIMERE chemistry-transport model. We first give a brief description
of the model.
The model used in this study is the eulerian regional chemistry-transport model named CHIMERE
(Schmidt et al., 2001) in its version V200606A (see http://euler.lmd.polytechnique.fr/chimere/),
modified here to include the detailed NatAir biogenic VOC emissions for an extended European
area. The model has been applied to simulate and analyze pollution episodes at continental (Vautard
et al., 2005; Hodzic et al., 2006) and regional scale (Monteiro et al., 2007; Coll et al., 2005;
Derognat et al., 2003), for long-term ozone trends analysis (Vautard et al., 2006), and for
diagnostics or inverse modelling of emissions (Vautard et al., 2003; Deguillaume et al., 2007;
Konovalov et al., 2006). The model has also been used for experimental (Blond and Vautard, 2004)
and operational forecast of pollutant levels over Western Europe (Honoré et al., 2007;
http://www.prevair.org). It is designed to simulate both the gaseous and the aerosol phase
(Bessagnet et al., 2004), but here we will focus on the gas phase only. The model is setup on a
0.5°×0.5° horizontal grid covering all Europe ([35°-70°N; 15°W-35°E]) and 8 hybrid-sigma vertical
layers extending to 500 hPa.
Meteorological input is provided by PSU/NCAR MM5 model (Dudhia, 1993) run at 48×48 km2
horizontal resolution and 33 vertical sigma layers extending up to 100 hPa. The model is forced by
ECMWF ERA-40 reanalysis taken at 1.125°×1.125° using the grid nudging (grid FDDA) option
implemented within MM5.
Anthropogenic emissions are derived from EMEP annual totals scaled to hourly emissions applying
temporal profiles provided by IER (Friedrich, 1997), as described in Schmidt et al. (2001). VOC
emissions are aggregated into 11 model classes following the mass and reactivity weighting
procedure proposed by Middleton et al. (1990). Biogenic emissions are described in the following
subsection.
The gas-phase chemical mechanism MELCHIOR (Latuatti, 1997) includes about 80 species and
more than 300 reactions. Isoprene oxidation is derived from the work of Paulson and Seinfeld
(1992). α-pinene is chosen as a representative for terpenes and its oxidation pathway is based on
that included in the RACM mechanism (Stockwell et al., 1997).
Chemical boundary conditions for long-lived species are provided by a monthly mean global
climatology from LMDz-INCA model (Hauglustaine et al., 2004). The numerical method for the
temporal solution of the stiff system of partial differential equations is adapted from the secondorder TWOSTEP algorithm originally proposed by Verwer (1994).
3. Impact of natural/biogenic emissions on summer daily ozone maximum
The simulations performed to assess the impact of natural and biogenic sources calculated within
NatAir on summer ozone levels are reported in Table 3.1.
Table 3.1. List of simulations performed to study the impact of NatAir natural/biogenic emissions on summer ozone
levels. Notes: a biogenic emissions derived from Simpson et al. (1999) and implemented into CHIMERE model by
Derognat et al. (2003).
Simulation ID
CTRL
ALL2
ALL1
BNO2
OVC2
BB2
CH42
AON2
Description
All BIOGENIC emissions switched OFF
CTRL + Isoprene and Terpenes emissions from NatAir
CTRL + Isoprene and Terpenes emissions from D03a
CTRL + soil NO emissions
CTRL + NatAir Other VOC emissions
CTRL + NatAir Biomass burning emissions
CTLR + NatAir methane emissions
CTRL + All NatAir natural/biogenic emissions
Figure 3.1 (left panel) shows average summer (JJA) 2000 daily ozone maxima in the first model
layer for the CTRL run (no biogenic emissions). Elevated ozone values are simulated in the
Mediterranean basin as a result of large anthropogenic precursor emissions in coastal areas,
abundant solar radiation and small deposition rates. The Po Valley in Northern Italy appears by far
as the most polluted region in Europe, with average daily ozone maxima up to 70 ppbv (54-66 ppbv
in the rest of Italy). The average ozone maximum over land reaches 47 ppbv (42 and 53 ppbv north
and south of 47.5°N respectively), with a north-west to south-east gradient in qualitative agreement
with previous data from rural monitoring sites (Scheel et al., 1997).
BVOC emissions from the NatAir inventory (ALL2 simulation) increase daily ozone maxima over
land by 3.1 ppbv on the average (respectively 1.2 and 3.9 ppbv north and south of 47.5°N) (Figure
3.1, right). The general pattern of ozone change is well correlated with ozone itself (r2~0.7), because
both quantities reflect the gradient of photochemical activity from north to south. Change in ozone
due to BVOCs peaks up to 20 ppbv at several locations in the Mediterranean area (Strait of
Gibraltar, Aegean sea). At the country level, Portugal is the most impacted country. In general,
large changes are predicted throughout the Mediterranean Sea (average ~5 ppbv). It is interesting to
notice that some of the most impacted areas are metropolitan regions of Porto (10-15 ppbv), Po
Valley (5-10 ppbv), Marseille (5-8 ppbv), and Paris (4-6 ppbv). Also remarkably, in Spain, although
the large BVOC emissions, ozone change is relatively small (2-4 ppbv) but larger along the
populated coasts (4-10 ppbv) and Madrid (4-6 ppbv). These observations point out the importance
of NOx emissions, abundant in metropolitan areas and scarce in rural regions, as necessary catalyst
for efficient ozone production from BVOC oxidation.
Over land, the average share of ozone production from BVOCs is about 60% from isoprene and
40% from terpenes, over sea it is 50% and 50% (not shown). Ozone destruction in northern Europe
is due to ozonolysis of terpenes.
Figura 3.1. Impact of isoprene and terpenes emissions on summer average daily ozone maximum for year 2000. On the
left, surface ozone calculated in reference simulations that includes only anthropogenic emissions (CTRL, see Table
3.1). On the right, surface ozone change calculated as the difference with a simulation that includes NatAir isoprene and
terpenes emissions (ALL2-CTRL).
The differences in the predicted impact on ozone between the NatAir and D03 inventories are
evaluated in Figure 3.2 for summer 2001. The differences are largely consistent with the differences
in emissions themselves. With respect to NatAir, D03 BVOC emissions have less impact on ozone
in the Mediterranean and more in Northern Europe (average over land ozone change of, 1.7 and 3.6
ppbv north and south of 47.5°N respectively, 3.3 ppbv for the whole domain). For example, the
effect of BVOC in Germany is 2-4 ppbv with NatAir and 3-5 ppbv with D03 emissions. In Portugal
the change in ozone is 5-15 ppbv with NatAir and only 2-6 ppbv with D03 emissions.
In Figure 3.3, the interannual variability of the BVOC impact on ozone is displayed, for summers
(JJA) 1997, 2000, 2001, and 2003. The general pattern already described for the year 2000, with a
negative gradient from south to north, is similar for all years. The year 1997 (average impact inland
2.2 ppbv) is similar to 2001, while 2000 (impact 2.1 ppbv), a relatively cold year, displays the
lowest impact because of reduced biogenic emissions and lower photochemical activity. Summer of
2003 (impact 2.8 ppbv) was characterized by several heat-waves (Vautard et al., 2005, and
references therein) and persisting high ozone levels. Prolonged hot periods enhanced BVOC
emissions increasing their impact on ozone by 2-3 ppbv with respect to other years at some
locations. The impact of BVOC in France is nearly doubled. In Portugal and Po Valley the areas
with impact above 6 ppb are greatly extended. Impact on ozone over the Mediterranean Sea is also
significantly increased for summer 2003.
Figure 3.2. Difference of average effect of biogenic VOC emissions on summer 2001 surface ozone (daily maximum)
calculated using NatAir inventory and D03 inventory (derived from Simpson et al. (1999)). (a) Average daily ozone
maximum simulated with CHIMERE in summer (JJA) 2001 without BVOC emissions (CTRL run, see Table 1). (b)
Ozone change including NatAir BVOC emissions (difference of ALL2-CTRL runs), (c) ozone change including D03
BVOC emissions (ALL1-CTRL).
Figure 3.3. Interannual variability of BVOC impact on summer (JJA) daily ozone maximum. Maps show ozone change
using NatAir BVOC emissions (difference of ALL2-CTRL runs) for the years 1997, 2000, 2001 and 2003.
In Figure 3.4 the impact of soil NO emission on average daily ozone maximum is shown. Adding
NatAir biogenic NO emissions to the reference simulation (CTRL) the model predicts a maximum
change of +1 ppbv at some rural areas in France and Spain. Near London and over the Netherlands,
ozone change is negative, because there the chemical regime is NOx-saturated.
The additional NO source from soils has a slightly larger effect on ozone maximum when included
together with biogenic isoprene and terpenes emissions. The maximum impact on ozone is again
about +1 ppbv, but larger continental areas are interested.
Figure 3.4. Impact of NatAir biogenic soil NO emissions on average daily ozone maximum in summer 2000. Left,
effect of soil NO emissions on ozone with respect to CTRL simulation. Right, combined effect on ozone of NatAir
isoprene, terpenes and soil NO emissions.
In Figure 3.5 we show the impact of biogenic OVOC (other VOC, i.e. other than isoprene and
terpenes) emissions on average daily ozone maximum (summer 2000). The additional VOC source
produces about 1 additional ppbv of ozone in Spain, Marseille, Italy, Germany, South Poland,
Czech and Slovak Republics, Slovenia and Greece. Over Po Valley the effect may reach 2 ppbv.
Similarly to terpenes, the prevailing effect on ozone over Scandinavia is consumption through
ozonolysis.
Figure 3.5. Impact of NatAir biogenic OVOC (Other VOC, i.e. other than isoprene and terpenes) emissions on average
daily ozone maximum in summer 2000. Left, effect of biogenic OVOC emissions with respect to CTRL simulation.
Right, combined effect on ozone of NatAir isoprene, terpenes and OVOC emissions.
In Figure 3.6 the impact of NatAir biomass burning and natural/biogenic methane emissions on
average daily ozone maximum is shown (summer 2000). These two sources have a minor role in
average continental scale ozone production. Biomass burning might reach a local effect of less than
1 ppbv near the source.
Figure 3.6. Impact of NatAir biomass burning (left) and natural/biogenic methane (right) emissions on average daily
ozone maximum in summer 2000.
In Figure 3.7 we show total impact of natural/biogenic emissions on ozone levels. Each row
correspond to a different scenario. In the first row, summer 2000 reference simulation (CTRL) and
ozone change due to NatAir natural/biogenic emissions are shown (figures already displayed
before). In the second row, we show CTRL run and impact of natural/biogenic sources on ozone in
summer of 2003 (the one characterized by heat-waves). In the third row, we show results for a 2010
anthropogenic emission scenario using 2000 meteorology.
In Table 3.2 the average ozone change over continental areas is calculated for the three scenarios.
Average ozone change north of and south of 47.5°N is also shown.
Remarkably, in summer 2003, which can be considered a proxy for future summers under climate
change, the average effect of natural/biogenic emissions increases of more than 50% on average,
with peaks of 100% for example in France.
Figure 3.7. Impact of all NatAir natural/biogenic emissions on average daily ozone maximum in summer for different
scenarios. Top panels: reference simulation (CTRL, on the left) and ozone change (right) due to all NatAir
natural/biogenic emissions in summer 2000. Middle panels: same as top panels, but for summer 2003. Bottom panels:
same as top panels, but using 2010 EMEP expert anthropogenic emissions.
Table 3.2. Impact of NatAir natural/biogenic emissions on average daily maximum of surface ozone for different
scenarios. Values are in ppbv calculated as the difference of a reference run without natural/biogenic emissions and a
run with all natural/biogenic emissions included. Only grid cells over the continent are considered in calculations.
Units: ppbv
All continent
Continent<47.5°N
Continent>47.5°N
2000
2.9
4.6
1.7
2003
4.0
6.3
2.2
2010
2.8
4.4
1.6
4. Impact of natural/biogenic emission on PM10 daily mean
The simulations performed to assess the impact of natural and biogenic sources calculated within
NatAir on summer PM10 levels are reported in Table 4.1.
Table 4.1. List of simulations performed to study the impact of NatAir natural/biogenic emissions on summer PM10
levels.
Simulation ID
Description
CTRL
ALL2
BB2
SDST2
ISAL
NH32
PBAP
AAA2
All BIOGENIC emissions switched OFF
CTRL + Isoprene and Terpenes emissions from NatAir
CTRL + NatAir Biomass burning emissions
CTLR + NatAir dust emissions
CTRL + NatAir Sea Salt emissions
CTRL + NatAir ammonia emissions
CTRL + NatAir PBAP emissions
CTRL + All NatAir natural/biogenic emissions
Figure 4.1. Impact of natural and biogenic emissions on average daily PM10 surface concentrations in summer 2000
simulated with CHIMERE model and NatAir emissions. Top-left: summer (JJA) average PM10 daily mean simulated in
reference run (CTRL, see Table 4.1). Top-right: Average PM10 change including all natural/biogenic sources calculated
within NatAir project. Other panels: impact on PM10 of single sources. From top-left to bottom-right: (1) Secondary
Organic Aerosols (SOA) from the oxidation of biogenic terpenes, (2) biomass burning, (3) wind blown dust, (4) sea
salt, (5) ammonia, and (6) Primary Biological Aerosol Particles (PBAP).
TBC
TBC
Figure 4.2. Impact of all NatAir natural/biogenic emissions on average daily PM10 in summer for different scenarios.
Top panels: reference simulation (CTRL, on the left) and ozone change (right) due to all NatAir natural/biogenic
emissions in summer 2000. Middle panels: same as top panels, but for summer 2003. Bottom panels: same as top
panels, but using 2010 EMEP expert anthropogenic emissions.
Table 4.2. Impact of NatAir natural/biogenic emissions on average daily mean of surface PM10 for different scenarios.
Values are in µg/m3 calculated as the difference of a reference run without natural/biogenic emissions and a run with all
natural/biogenic emissions included. Only grid cells over the continent are considered in calculations.
Units: ppbv
All continent
Continent<47.5°N
Continent>47.5°N
2000
2.8
3.4
2.3
2003
TBC
TBC
TBC
2010
2.9
3.6
2.3
SUMMARY OF IMPACT ON OZONE AND PM10 OF NATURAL/BIOGENIC EMISSIONS
Source
Average Maximu Average Maximu Average Maximu
impact
m impact impact
m impact impact
m impact
on
on
on
on
on
on
surface
surface
surface
surface
surface
surface
O3
O3
PM10
PM10
trace gas trace gas
species
species
Natural and semi- 2.5 ppbv
natural
vegetation
(NMVOC)
15 ppbv 1 µg/m3
(Porto,
Portugal)
NO from soils
1 ppbv
(Spain,
France)
Wind
(PM)
blown
0.25
ppbv
dust
Biomass burning and 0.02
forest fires (NOx, ppbv
PM, CO, VOC)
Primary
aerosol
(PM)
biological
particles
Sea salt (PM)
9 µg/m3
(SouthWest
Spain)
0.1
µg/m3
2 µg/m3
(East
Spain)
0.1
µg/m3
0.2
µg/m3
(Po
Valley,
Balkans)
1 µg/m3
5 µg/m3
(Denmar
k), 3-4
µg/m3
(Atlantic
coasts,
South
Spain)
1 ppbv
(Portugal
)
Humans, Pets and
Wild animals (NH3)
0.01
µg/m3
0.3
0.06
3
µg/m
ppbv
(London) (NH3)
0.5 ppbv
(Major
metropol
itan
areas)
(NH3)
Humans, Pets and
Wild animals
and
Anoxic soil
processes (wetlands)
and
Geological seepages
(CH4)
0.007
ppbv
0.02
ppbv
(Romani
a)
6.4 ppbv 90 ppbv
(CH4)
(Black
Sea)
(CH4)
Combined emissions
2.9 ppbv
15 ppbv 2.8
(Porto,
µg/m3
Portugal)
10 µg/m3
(Spain)
5. Comparison with observations
In the following tables comparison with AirBase observations at rural/background sites are
compared with Chimere timeseries for year 2000.
Table 5.1. Statistical indices and excedances O3 simulations (daily maximum, threshold=90 ppbv, number of
stations=369)
Simulation
ID
AirBase
CTRL
ALL2
ALL1
AON2
Mean
Conc.
(ppbv)
50.3
45.8
48.0
TBC
49.2
N.
Excedances
(>90 ppbv)
659
9
62
TBC
121
RMS (ppbv)
Bias (ppbv)
Correlation
10.8
9.7
TBC
9.4
-4.5
-2.3
TBC
-1.2
0.776
0.789
TBC
0.791
Table 5.2. Statistical indices and excedances PM10 simulations (daily mean, threshold=50 µg/m3, number of
stations=63)
Simulation
ID
AirBase
CTRL
ALL2
SDST2
Mean
Conc.
(µg/m3)
20.2
11.1
11.8
11.2
N.
Excedances
(>50 µg/m3)
118
0
0
0
RMS (µg/m3)
Bias (µg/m3)
Correlation
11.7
11.1
11.6
-9.1
-8.3
-9.0
0.590
0.627
0.589
ISAL1
AAA2
-
14.6
14.0
0
0
10.1
10.2
-5.7
-6.2
0.505
0.490
Timeseries: heat-wave 2003 O3, particular cases PM10
Figure 5.1. Timeseries of hourly surface ozone at four AirBase stations in the Mediterranean region during July-August
2003. Observations are displayed with black dots, Chimere CTRL simulation in blue and Chimere ALL2 simulation
(CTRL+NatAir BVOCs) in red.
In Figure 5.1 we show a clear example of how biogenic emissions can contribute to severe ozone
events during heat-waves. Inclusion of BVOC emissions in necessary for the model to reproduce
the extreme hourly ozone values observed at AirBase sites. In one single case (in Spain) BVOCs are
responsible for the production of 100 µg/m3 (50 ppbv).
In Figure 5.2 we show maps of mean model bias of simulated PM10 with respect to AirBase
observations. Looking at the reference run (top-left) we note that the model is generally biased low,
particularly over the Iberian Peninsula and Benelux region. In the former region, the bias can reach
-40 µg/m3 at some location. In top-right panel, we note that most of the PM10 excedances have
place at those locations where the model is greatly biased low. In following panels, we show that
inclusion of various natural/biogenic PM10 sources reduce model bias, but the comparison is still
poor and bias still elevated. This explains why the model is not really able to reproduce observed
PM10 excendances even when accounting for additional natural/biogenic emissions (see Table 5.2).
Figure 5.2. Comparison of Chimere PM10 daily mean values with observations at AirBase sites for summer 2000. Topleft: mean model bias in reference simulation (CTRL). Top-right: number of PM10 daily excedances (>50 µg/m3)
observed at AirBase sites. Middle-left: mean model bias in ALL2 (CTRL+BVOCs) simulation. Middle-right: mean
model bias in SDST2 (CTRL+dust) simulation. Bottom-left: mean model bias in ISAL1 (CTRL+sea salt) simulation.
Bottom-right: mean model bias in AAA2 (CTRL+all natural/biogenic sources) simulation.