Contributo delle polveri sahariane al
PM10 sull’ Italia: approccio modellistico
ed approccio statistico.
1Pederzoli
A., 2Mircea M., 3Finardi S.
1 JRC Ispra
2 ENEA Bologna
3. ARIANET Srl
ENEA MEETING, 24th March 2011
APPROCCIO MODELLISTICO: SKIRON + FARM
State of the art (March 2011):
MAIN STEPS:
1. SCELTA DEGLI SCENARI E DELL’EPISODIO
2. AGGIUNTA DI SKIRON-DUST ALLE BCs di FARM 20x 20km2
3. RUNS DI FARM
4. CONFRONTO TRA I RISULTATI DELLE SIMULAZIONI a 20 x 20 km2
5. CONFRONTO CON LE MISURE SUL DOMINIO 20 X 20 km2
6. STATISTICAL EVALUATION
1. SCELTA DEGLI SCENARI E DELL’EPISODIO
NDC (“No Dust Case”)
Concentrations from the EMEP model are used as LBCs in FARM. EMEP concentrations are
interpolated from 50 x 50 km2 to 20 x 20 km2 and re-projected onto the four sides of the FARM
domain.
DC (“Dust Case”)
Hourly SKIRON fields are interpolated to 20 x 20 km2 and re-projected onto the four sides of the
FARM grid. Size-resolved dust concentrations by SKIRON are then added to the LBCs used in the
previous case (NDC).
DC1.3 (“Dust*1.3 Case”)
SKIRON dust concentrations are multiplied by a factor 1.3. According to Kallos et al. (2007) the model
underestimates low dust concentrations by approximately 30%. The same study suggests to multiply
SKIRON dust fields by a factor 1.3 in order to reduce the bias of the model. The same procedure used
in the DC is then applied and new LBCs are created.
DUST EVENT: 26-29 JULY 2005 (Meloni et al. 2007, Gariazzo et al., 2007, Griffin et al., 2007)
2. ADDING SKIRON DUST TO FARM 20x 20km2 RESOLUTION BCs
AEROSOL SPECIES IN FARM
SIZE DISTRIBUTION IN SKIRON
AITKEN
ACCUMULATION
COARSE
ASO4
Sulphate mass
X
X
ANH4
Ammonium mass
X
X
ANO3
Nitrate mass
X
X
AORGA
Anthropogenic secondary organic mass
X
X
AORGPA
Primary organic mass
X
X
AORGB
Secondary biogenic organic mass
X
X
AEC
Elemental carbon mass
X
X
A25
unspecified anthropogenic mass
X
X
ACORS
Unspecified anthropogenic mass
X
ASEAS
Marine mass
X
ASOIL
Soil-derived mass
X
AH2)
Water mass
X
X
X
NUM
Number of particles
X
X
X
SRF
Surface area
X
X
X
PMC1 A25J
PMC2 ASOIL
CLASS
NAME
CATEG
ORY
RADIUS
1
PMC1
CLAY
< 1 um
2
PMC2
SMALL
SILT
1 um 10 um
3
PMC3
LARGE
SILT
10 um 25 um
4
PMC4
SAND
> 25 um
Contribution from the last two classes (PMC3 and PMC4) was not considered (no addition was
performed) as particles of large silt and sand, due to their large dimensions, are rapidly
removed from the atmosphere (dry deposition processes).
2. ADDING SKIRON DUST TO FARM 20x 20km2 RESOLUTION BCs
LATERAL BOUNDARY BONDITIONS (LBC) IN FARM
Daily Lateral Boundary Conditions (LBC) as a function of altitude for the crustal component (c_ASOIL) on day 29th July 2005.
• DC and DC1.3 show higher concentrations (up to
50 mgm-3) along both South and West boundaries,
which reflect the intrusion of dust from SW.
• The vertical dust layer extends from surface up to
3.5 km.
• An isolated hot spot, approximately between 1
and 3 km high, is also visible, indicating a residual
dust layer due to a previous episode (23rd - 25th
July).
120-hours air mass backward trajectories ending over S.Antioco,
Monrupino and Febbio on July the 29th at 2300 UTC at both 1500 m
(red) and 2500 m (blue). Starting time: 25th March 2005 at 0000
UTC.
3. RUNS DI FARM
27th July: DC–NDC between 5 and 10 mgm-3 over Central and Southern Italy and over the islands (Sicily and Southern
Sardinia). The difference is not significant over the Po Valley.
28thJuly: a similar amount of dust is predicted over the islands, Southern Italy and partially over the Central Italy. DC-NDC is
between 2 mgm-3and 8 mgm-3 over the Po Valley.
29th July: The contribution of dust becomes significant almost everywhere, ranging between 5 and 15 ugm-3 across Northern
Italy and Sardinia. DDC1.3 - NDC is in the same range as DC-NDC for all days.
4. CONFRONTO CON LE MISURE
Comparison to ground measurements
Modelled hourly surface PM10 concentrations
extracted in single grid cells and compared to ground
measurements from rural background monitoring
stations across Italy.
Analysis of the vertical dust distribution
Modeled volume vertical profiles are compared to Lidar
measurements at Tor Vergata site (41.83° N, 12.65° E)
(Gobbi et al., 2004). The volume of total suspended aerosols
is computed by using model derived relationships between
backscatter coefficients and aerosol volume (Barnaba and
Gobbi, 2001).
5. STATISTICAL EVALUATION
The introduction of dust onto the boundaries reduces the FB for the same episode from 1.3 to approximately 0.85.
The NMB for NDC varies from approximately -70% to -90%, reduced to the range -40% - -80% in DC and DC1.3.
The averaged NMB for all stations is -77%, -65%,-59% for NDC, DC and DC1.3 respectively.
CONCLUSIONS
Differences in PM10 surface concentrations between both DC and DC1.3 scenarios and the default
case NDC are approximately between 5 and 15 mg m-3.
The correction (30%) introduced in DC1.3 and suggested by Kallos et al. (2007) for reducing SKIRON
underestimation of dust concentration over Greece is not suitable over Italy: differences in PM10
concentrations between DC1.3 and NDC are in the same ranges as DC-NDC for all days. A new
correction factor needs to be introduced for the Italian contest.
The analysis of the vertical dust distribution shows that the dust contribution at surface is low
compared to the one at high altitudes: most of dust particles remains above 2000 m and does not
reach the ground. This suggests a process of sedimentation and deposition of aerosol particles too
slow with respect to the transport process inside the model. Further investigations need to be
carried out in the future in order to verify this hypothesis.
The comparison with ground measurements reveals that the addition of dust improves FARM
aerosol mass concentration predictions: the underestimation of PM10 concentration is reduced from
approximately 77% to 59%.
The use of these new LBCs also improves the performance of FARM compared to the results
achieved by Gariazzo et al. (2007) which makes use of climatology fields: the fractional bias is
reduced from 1.3 to 0.8.
APPROCCIO STATISTICO: METODO DI ESCUDERO
State of the art (March 2011):
MAIN STEPS:
1. Identification of dust episodes in 2003-2005
2. Estimates of dust contribution (mg m-3) to PM10 concentrations
3. Calculation of the reduction in the number of exceedances of 50 mg m-3
Quantification of Saharan dust contribution to PM10 concentrations over Italy during
2003 - 2005
A. Pederzoli, M. Mircea, S. Finardi, A. di Sarra, G. Zanini, Atmospheric Environment 44
(2010) 4181-4190.
1. Identification of dust episodes
SOURCES:
1. Monitoring network measurements
2. Satellite retrievals
3. Mesurements of optical
properties
Trieste Monrupino
Year 2005
700
500
400
300
200
16/10/2005
11/09/2005
0
07/08/2005
100
03/07/2005
PM10 concentration (mg m-3)
600
Hours
Rural background stations
4. Air mass backward trajectory
analysis
5. Numerical dust models (SKIRON)
1. Identification of dust episodes
Number of dust events (%)
2003-2005
Fontechiari
S.Antioco
Gherardi
La Mandria
Ispra
Passo Giovi
Lampedusa
50
45
40
(%)
35
30
25
20
15
10
5
0
Jan
Feb
March
April
May
Jun
Jul
Aug
Months
SOURCES:
Air mass backward trajectory analysis (HYSPLIT)
Satellite retrievals (i.e. MODIS)
Ground measurements of optical properties and PM10 concentrations
Modelled data
Sept
Oct
% Events
Nov
Dec
 M 
 i 
  iNT1   100


 i 
 i 1 
2. Stima del contributo alla concentrazione di
PM10
Escudero M., Querol X., Avila A., Cuevas E. (2007). Origin of the
exceedances of the European daily PM limit value in the regional
background areas of Spain. Atmos. Environ. 41, 730–744.
Per stazioni remote-rurali
(no anthropogenic
contribution):
C ij DUST  C ij TOT  RB ij
i=rural site
j=dust day
RB ij  X thmoving
percentile  30th
Calculated over the month
excluding j-days
2. Stima del contributo alla concentrazione di PM10
Example of methodology application for a daily episode
i
29th July 2005
j
Trieste Monrupino
RB
i
j
C ij TOT
C ij DUST
30th daily moving percentile calculated over all days of July 2005
apart the dust day (29th) = 20 mg m-3
Average of PM10 concentration = 59 mgm-3
Dust contribution for 29th July 2005 = 59-20 - = 39 mg m-3
Average monthly contribution for July 2005 = 1.4 mg m-3
2. Stima del contributo alla concentrazione di PM10
Natural contribution to PM10 concentration
2005
32
Lazio-Fontechiari
Sardinia-S.Antioco
Emilia Romagna-Gherardi
Piemonte-La Mandria
Lombardy-Ispra
Liguria-Passo Giovi
Natural contribution to PM10 concentration
-3
(mgm )
.
28
24
20
16
12
8
4
0
Jan
Feb
March
April
May
Jun
Jul
Months
Aug
Sept
Oct
Nov
Dec
3. Riduzione del numero di eccedenze (> 50 mg m-3)
REDUCTION (%) 
N T  N T  RB
 100
NT
Conclusioni
• Le intrusioni Sahariane sono maggiormente concentrate in primavera
(40%-45%) ed estate (35%-55%).
•
In inverno ed autunno i siti nel Nord Italia hanno registrato un
numero significativo di eventi (tra il 7% e il 10% in Gennaio e
Febbraio) .
•
Il numero maggiore di intrusioni è stato registrato sull’isola di
Lampedusa in estate (57% del totale).
• il contributo mensile delle polveri sahariane alle concentrazioni di
PM10 varia tra 1 mg m-3 e 10 mg m-3 nel 2005 e tra 1 mg m-3 e 8 mg m-3
nel 2003; nel 2004 è < 5 mgm-3 per tutti i siti.
• La riduzione (%) nel numero di eccedenze del limite giornaliero varia
da stazione a stazione: tra il 20% e il 50% nel in 2005 e tra il 5% e
25% nel 2003 e 2004.
AKNOWLEDGEMENTS
This work is part of the MINNI (Integrated National Model in support to the
International Negotiation on Air Pollution) project, funded by the Italian
Ministry for Environment, Territory and Sea and carried out by ENEA.
This work was supported and coordinated by ENEA and ARIANET Srl.
Special thanks to:
Professor G. Kallos and the Atmospheric Modeling and Weather Forecasting
Group at the University of Athens.
The Environmental Protection Agency of Friuli Venezia Giulia for providing
PM10 measurements at Trieste Monrupino.
Dr. Gian Paolo Gobbi, of the Institute of Atmospheric Sciences and Climate of
Rome for the Lidar measurements at Tor Vergata. The authors finally gratefully
aknowledge the Air Resources Laboratory (ARL) for the provision of the
HYSPLIT model.