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Risks, challenges and mitigation actions in the APICE partners’ area: between the scientific findings and new governance models - Genoa M.C. Bove, P. Brotto,F. Cassola, E. Cuccia, D. Massabò, A. Mazzino, P. Prati Department of Physics – University of Genoa. - PowerPoint PPT Presentation
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Risks, challenges and mitigation actions in the APICE partners’ area: between the scientific findings and new governance models - Genoa
M.C. Bove, P. Brotto,F. Cassola, E. Cuccia, D. Massabò, A. Mazzino, P. Prati
Department of Physics – University of Genoa
Final conference – Venice, 8th November 2012
APICE scientific issues: the case of Genoa
Main goal: to provide Authorities and Stakeholders with a
reliable tool to study and forecast air quality: a “Chemical
Transport Model, CTM”
Methodology (shared with all the Partners):
1) “picture” of air quality (i.e. PM2.5) with a 1-year
monitoring campaign Source Apportionment (SA).
2) CTM assessment with updated emission data
3) Check of CTM vs. real-world measured data
4) Comparison of SA by CTM and monitoring campaign
2
Site1:C.So Firenze
Site2: Multedo
Site3: Bolzaneto
PORT
Monitoring campaign
Intensive campaign (May-Oct 2011)
after prevailing meteo conditons analysis
• The PM2.5 level is almost the same in the three sites
Main PM2.5 sources: at “regional” scale
PM2.5 levelsMass Concentration
y = 1.07x
R2 = 0.5
y = 0.98x
R2 = 0.7
0
5
10
15
20
25
30
35
0 5 10 15 20 25 30 35
C.so Firenze (mg/m3)
Mu
lte
do
an
d B
olz
an
eto
(m
g/m
3 )
Multedo
Bolzaneto
• The correlation between PM2.5 time series is stronger for the sites much closer to the port
F
M
B
PM2.5 average apportionment: Corso Firenze Corso Firenze
7±2%
23±3%
8±3%
14±5%49±5%
Oil combustion Soil Nitrates Traffic Sulphates
Corso Firenze
0%
20%
40%
60%
80%
100%
Al
Si K
Ca Ti V
Mn
Fe Ni
Cu
Zn
Pb
OC
EC
NO
3-
SO
4--
Na
NH
4+
Sulphates
Traffic
Oil combustion
Soil
Nitrates
(14 ± 5) %
Multedo
50±3%
5±3%
17±3%
8±2%
7±2%
12±4%
Oil combustion Soil Nitrates Traffic Sulphates Zn Mn
Multedo
0%
20%
40%
60%
80%
100%
Al
Si K
Ca Ti V
Mn
Fe Ni
Cu
Zn
Pb
OC
EC
NO
3-
SO
4--
Na
+
NH
4+
zn mn
Traffic
Sulphates
Soil
Nitrates
Oil combustion
PM2.5 average apportionment: Multedo
(12 ± 4) %
Bolzaneto
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Al
Si K
Ca Ti V
Mn
Fe Ni
Cu
Zn
Pb
OC
EC
NO
3-
SO
4--
Na
NH
4+
Traffic
Local
Sulphates
Fe Mn
Nitrates
Soil
Oil combustion
Bolzaneto
21±3%
5±2% 9±3%6±3%
8±2%
5±2%
46±3%
Oil combustion Soil Nitrates Traffic Sulphates Local source Fe Mn
PM2.5 average apportionment: Bolzaneto
(9 ± 3) %
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
Oilcombustion
Soil Nitrates Traffi c Sulphates Localsource
Fe Mn Zn Mn
Conc
entr
ation
(ng/
m3 ) bolzaneto
multedo
corso fi
PM2.5 apportionment at a glance
Basically: ship emissions
Oil combustion
0
500
1000
1500
2000
2500
3000
June 2011 July 2011 August 2011 September 2011
Ave
rag
e P
M2.
5 (n
g/m
3 )
Bolzaneto
Corso Firenze
Multedo
Temporal behaviour of ship emissions
Many ferries to the
Islands
Meteorological preprocessor: WRF
3-domain configuration (10 km + 3.3 + 1.1 km)
Simulations driven by NCEP GFS fields (0.5°)
24-hr-long simulations, hourly outputs, year 2011
10
11
Chemical transport model: CAMx
• Maritime sector (harbour activities)
• Road transport
• Industry
• Non-industrial combustion plants
• Other sources (including natural emissions)
Outer domain covering Western and Central Europe (10 km resolution)
2-way nesting procedure
Inner domain – focus on local area
47x47 grid points
1.1 km resolution
PM source apportionment approaches:
Zero-out
CAMx PSAT routine
City area
Harbor area
Pollutants:
NOx, SOx, CO, PM….
Emission data
Large-scale anthropogenic emission data provided by AUTH (TNO data processed through the MOSESS code)
Natural emissions obtained processing WRF outputs with the NEMO code (developed by AUTH)
Updated (2010) harbour emission data calculated by Techne Srl (provider of Province of Genoa) according to CORINAIR Guidebook 2011 (no disaggregation for different harbour activities contribution available)
Local gridded emission data provided by Liguria Region (reference year 2008):
• 1 km spatial resolution• hourly temporal resolution• SNAP sectors disaggregation
12
Model validation – comparison with observed data (PM2.5)
13
Model validation – comparison with observed data (Sulfates)
14
Model validation – comparison with observed data (NOx)
15
16
CTM source apportionment results (zero-out)
PM2.5 NOx
Contribution restricted to the area around the harbour (expecially for PM2.5)
Contribution of harbour activities (%)
Summer 2011
17
CTM source apportionment results (zero-out)
PM2.5 NOx
Contribution of road transport (%)
Summer 2011
Contribution to concentrations over the whole city
18
SourcesSA by measured data
(PMF)SA by CTM
(CAMx with PSAT)
Maritime (13 ± 5) % coast (9 ± 3) % inland
9% coast 5% inland
Industrial(30 ± 10) % 20%
Road Traffic (40 ± 15) % 45%
Residential combustion Not resolved 5 %
Others (crustal, sea, etc. ) (15 ± 5) % 20%
SA of PM2.5: June- August 2011 - Intercomparison
± ???
19
Harbor activities contribution to PM2.5 concentrations CTM vs Receptor models
CTM Receptor Models
Cso Firenze
11 % (14 ± 5) %
Multedo 9 % (12 ± 4) %
Bolzaneto 4 % (9 ± 3) %
20
-20 %
+2 %
Future scenario analysis: PM2.5 Scenario 1 – 2020 without mitigation actions
21
- 35 %
- 5 %
Future scenario analysis: PM2.5 Scenario 2 – 2020 with S % reduction in fuels
22
- 40 %
- 5 %
Future scenario analysis: PM2.5 Scenario 3 – 2020 with S % reduction in fuels and
cold ironing of container and ferries terminal
23
Summary
A quite complete picture of PM2.5 levels and sources for the year 2011 has been obtained thanks to a considerable experimental effort
A CTM model has been implemented and put in operation: validation vs. measured data pretty good
Source apportionment by real-world data + receptor model (PMF) and CTM (WRF+CAMx) in fair agreement
Future scenarios according to stakeholders inputs and APICE methodology completed (reference year 2020)
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