Source apportionment HM

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A source apportionment study and model validation
for HMs and POPs air concentrations of MINNI
project C. Silibello1, G. Calori1, M. Costa1,
P. Radice1, M. Mircea2
1 ARIANET Srl, Via Gilino, 9, 20128, Milan,
Italy 2 ENEA, National Agency for New
Technologies, Energy and Sustainable Economic
Development, via Martiri di Monte Sole 4, 40129,
Bologna, Italy
13th TFMM annual meeting 17th19th April 2012 -
Grand Hotel Mgarr Gozo MALTA
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Outline

• Simulation setup
• Wind re-suspension from soil and seawater
• Comparison with experimental data
• Source apportionment foreign sources
  contribution and sector contribution
• Summary and future plans

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Simulation setup
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The MINNI ProjectAtmospheric Modelling System
Space,time, species info
Local data
Reference inventory
ECMWF fields
Meteorological Subsystem
Emission Subsystem
RAMS SURFPRO
Emission Manager
Reference Meteorological year
Reference Emission year
B.C. MSC-W Inorganic/Organic MSC-East POPs/HMs
Chemical- transport Subsystem
FARM
Transfer matrices
Concentration Deposition fields
RAINS
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Meteorology
Meteorology subsystem
ECMWF fields
Re-analysis
RAMS 1 2 grids, 4DDA
SYNOPs
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Emission subsystemNational emission inventory
for heavy metals year 2005
(ISPRA, 2009)
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Emission subsystemIntegration of inventories
Emissions of surrounding countries from EMEP
National emission inventory by province and
sector (NUTS3 and SNAP2/3) LPS (140)
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Emission subsystemExample Sea traffic
International (EMEP)
National
Total
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Boundary conditions EMEP Meteorological
Synthesizing Centre East (MSC-E)

• EMEP MSC-E air concentrations
• 50 kmx50km, 6 hours
• HMs
• Pb, Cd, Hg, As, Ni, Cr, Zn, Cu, Se
• POPs
• 4 indicator PAHs
• ?-HCH
• HCB
• 17 congeners of PCDD/Fs
• 5 congeners PCBs.

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Yearly average concentrations of As
EMEP 50km x 50km
MINNI 20km x 20km
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Wind re-suspension from soil and seawater
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Wind re-suspension from soil and seawater
Wind re-suspension of particles from soil and
with sea-salt is estimated using Vautard et al.
(2005) and Zhang et al. (2005). The production of
dust from soils is not taken into account if
precipitation during the last 48 hours exceeds
0.5 mm.
Emission factors of heavy metals for suspension
with sea-salt aerosol
From MODELLING OF HEAVY METALS ATMOSPHERIC
DISPERSION IN EUROPE by Oleg Travnikov and Ilia
Ilyin Meteorological Synthesizing Centre East
of EMEP
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As concentration in topsoil
Spatial distribution of heavy metal concentration
in soil has obtained using data available from
FOREGS web site. For Eastern Europe and Africa
default concentration values based on the
literature data were used (Table below).
Default concentrations of heavy metals in soil
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Yearly averaged concentration of As MINNI
All sources
Wind re-suspension from soil and seawater
The contribution from Aeolian resuspension is
about 1
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Comparison with experimental data
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Background monitoring sites
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As yearly averaged concentration All stations
Target value 6 ng m-3
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Ni yearly averaged concentrations All stations
Target value 20 ng m-3
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Cd yearly averaged concentrations All stations
Target value 5 ng m-3
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Pb yearly averaged concentrations All stations
Limit value 500 ng m-3
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BaP yearly averaged concentrations All stations
Target value 1 ng m-3
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Source apportionment
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Source apportionment

• Foreign sources
• A) Zeroing BCs ( Long-range contribution)
• Zeroing both BCs and emissions in surrounding
  countries
• For both cases
• Two months run of the AMS (winter January- and
  summer July-)
• Computation of the variation between reference
  and case run concentrations (?). The percentage
  contribution of the case run is computed as
  100? / Creference

• Sector contribution
• Emission scenario decrease of sector emissions
  (-20)
• Two months run of the AMS (winter January- and
  summer July-)
• Computation of the variation between reference
  and scenario averaged concentrations (?). The
  percentage contribution of a sector i is computed
  as ? i / ?i ? N

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Foreign sources contributionsNi and BaP
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Ni Long-range contribution (A)
Contribution
Variation ?i
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Ni Long-range contribution (A)
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Ni Surrounding countries emissions (B)
Contribution
Variation ?i
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BaP Long-range contribution (A)
Contribution
Variation ?i
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BaP Surrounding countries emissions (B)
Contribution
Variation ?i
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Major sectors contribution on concentrations

• Sector contribution
• combustion in energy production and
  transformation (Sector 1)
• non-industrial combustion, residential and
  commercial (Sector 2)
• combustion in manufacturing industry (Sector 3)
• industrial processes (Sector 4)
• road transport (Sector 7)
• other mobile sources (Sector 8)
• waste treatment and disposal (Sector 9).

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Pb Combustion in Residential, Combustion in
Industry and Production Processes
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Pb Non-industrial combustion, residential and
commercial (Sector 2)
Contribution
Variation ?i
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Pb Combustion in manufacturing industry (Sector 3)
Contribution
Variation ?i
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Pb Production processes (Sector 4)
Contribution
Variation ?i
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BaP Non-industrial combustion, residential and
commercial (Sector 2)
Contribution
Variation ?i
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Summary and future plans

• the atmospheric modelling system of the MINNI
  project is able to simulate realistic
  concentrations of heavy metals and BaP
• lower values of modelled concentrations suggest a
  significant underestimation in the emissions. A
  better knowledge in emission inventories may
  improve predictions
• more observations, for longer periods and
  covering the whole country, are necessary for a
  comprehensive validation of model results
• the contribution of Aeolian resuspension to heavy
  metals concentrations is low BaP
  concentrations are strongly influenced by
  national sources, over most of the Italian
  territory
• the effect of foreign emissions is higher near
  the Alpine border at the north, over the islands
  (Sardinia and Sicily) and in some rural areas in
  the central-southern part of the Italian
  peninsula, far from densely inhabited zone
• civil heating, particularly in the regions where
  wood burning devices are used, is the main
  contributor BaP concentrations. The
  contribution of the industrial sector isrelevant
  around major facilities, with the largest
  absolute contribution in Taranto, whose steel
  industries are the largest individual source of
  PAH in the country according to the national
  emission inventory. Road traffic contributes for
  a few percentage points, with highest absolute
  contributions in the Po Valley and near Rome and
  Naples metropolitan areas. The remaining sectors
  play an almost negligible role.
• simulations for other years, with higher spatial
  resolution, coupling of POPs partitioning to full
  chemical model (SAPRC99 and AERO3)

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Acknowledgements

• 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 of Environment, Territory
  and Sea.
• We wish to thank Ilia Ilyin, Marina Varygina and
  Alexey Vladimirovich Gusev (EMEP MSC-E) and Anna
  Carlin Benedictow and Michael Gauss (EMEP MSC-W)
  for providing EMEP models output.
• We also wish to thank Beatrice Bondanelli
  (Autonomous Province of Bolzano), Monica
  Angelucci (Environmental Agency of Umbria
  Region), Sandro Zampilloni (Lazio Region), Carla
  Contardi (Piemonte Region), Fulvio Stel
  (Environmental Agency of Region Friuli-Venezia
  Giulia), Giuseppe Onorati (Campania Region),
  Salvatore Patti (Environmental Agency of Veneto
  Region) for supplying monitoring data.

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Thank you!