ec4macs workshop, paris, 8-9 march 2012 gabriele zanini, luisella ciancarella...

EC4MACS workshop, Paris, 8-9 March 2012EC4MACS workshop, Paris, 8-9 March 2012

Gabriele Zanini, Luisella Ciancarella

[email protected]

Technical Unit: Models, Methods and Technologies for the Environmental Assessment , Bologna, Italy.

Modelling the PM10 and NO2 concentrations in

Italy. The role of the national integrated assessment model MINNI in support of the

request of time extensions


National Integrated Model supporting International Negotiation on atmospheric pollution

Project Leader: Gabriele ZaniniWorkgroup: ENEA (UTVALAMB-AIR, UTTAMB-ATM, UTMEA-TER), Arianet srl

http://www.minni.org/

The MINNI Project

RAIL

ATM


RAMS, LAPS

Emission Manager

SURFPROMeteo

Turbolence Parameters

FARM

Emissions

ECMWF Fields Local DataEmission Inventories

(EMEP, ISPRA and GAINS)

Spatial and temporal info

Concentrations and Depositions

Atmospheric Transfer Matrices

EMEP IC e BC Fields

METEOSubsystem

EMISSIONSubsystem

CHEMICAL TRANSPORTSubsystem GAINS

MODEL CHAIN


METEOROLOGY:1999, 2005:20km res. RAMS (nudging)4km res. LAPS (diagnostic)2003, 2007:RAMS (nudging) at 20km and 4km res.

EMISSIONS:EMEP + National Inventory (ISPRA) (top-down approach)+ Regional Inventories (GAINS methodology)

IC/BC:EMEP concentration fields

AIR QUALITY:20km and 4 km res. FARMOne-way nested

MODEL SIMULATIONS


• 3D meteorological fields

• 3D concentration fields for the main pollutants

• Years: 1999, 2005, 2003, 2007

• Temporal resolution: 1 hour

• Spatial resolution: 20 km , 4 km

• Vertical grid:• 12 levels (up to 4 km) 1999• 16 levels (up to 10 km) 2005,

2003, 20070 500000 1000000 1500000

4000000

4500000

5000000

5500000

MINNI AVAILABLE OUTPUTS


The project aims to provide decision makers with a scientific support instrument for developing and assessing the effectiveness of air quality policies at international, national and regional scale.

• Studies and analysis of the atmospheric processes

• Processing and assessing alternative emission scenarios - present and or future

• Environmental and health impact scenario

• Meteorological and chemical database for Air Quality studies, intercomparisons, boundary and initial conditions for downscaling

MINNI OBJECTIVES


• Both inventories, national and local, follow the EMEP-CORINAIR Methodology and the SNAP (Selective Nomenclature for Air Pollution) classification scheme in 11 main classes

• Harmonization efforts between national and local emission inventories are in progress

• The recent Italian decree n. 155/2010, implementing the European Directive 2008/50/CE, confirms that air pollution prevention, improvement and preservation management is assigned to the Italian administrative Regions but in a coherent national frame

• Regions are in charge to elaborate Air Quality Plans in order to meet established environmental target

EMISSION INVENTORIES


THE ROLE OF GAINS_ITALY

Non Energy Activity Level Scenario

Energy Activity Level

GAINSItaly

Control Strategy(Emission Control

Technologies)

Emission Scenarios Deposition Maps Concentration Maps Health and Environmental

Impact Indicators

GAINS-ITALY RESOLUTION => 20 ITALIAN ADMINISTRATIVE REGIONS (NUTS2)


RAIL

ATM

GAINSGAINS IS AN EMISSION MODEL AND NOT AN EMISSION INVENTORY. IS AN EMISSION MODEL AND NOT AN EMISSION INVENTORY.

DUE TO ITS TECHNOLOGICAL SETTING, EMISSIONS DO NOT FOLLOW DUE TO ITS TECHNOLOGICAL SETTING, EMISSIONS DO NOT FOLLOW

SNAP CLASSIFICATION (SOFTWARE RAIL MATCHES THE TWO SNAP CLASSIFICATION (SOFTWARE RAIL MATCHES THE TWO

CLASSIFICATION SCHEMES) CLASSIFICATION SCHEMES)

EMISSION PROJECTIONS ARE BASED ON A REFERENCE YEAR WHICH EMISSION PROJECTIONS ARE BASED ON A REFERENCE YEAR WHICH

HAS TO BE SIMILAR BETWEEN STATE AND REGIONSHAS TO BE SIMILAR BETWEEN STATE AND REGIONS

GAINSGAINS NEEDS A FIRST CALIBRATION FOR THE REFERENCE YEAR TO NEEDS A FIRST CALIBRATION FOR THE REFERENCE YEAR TO

REPRODUCE NATIONAL EMISSION INVENTORY (FIRST STEP) AND REPRODUCE NATIONAL EMISSION INVENTORY (FIRST STEP) AND

REGIONAL EMISSION INVENTORIES (SECOND STEP)REGIONAL EMISSION INVENTORIES (SECOND STEP)

HARMONIZATIONHARMONIZATION

EMISSIONS IN GAINS-ITALY


MINNI AND REGIONAL 2003-2007 AIR QUALITY PLANS

MINNI supported the assessment of the first “generation” of Italian Regional Air Quality Management Plans (AQMPs) in 2003-2007 years (D’Elia et al. “Technical and Non-Technical Measures for air pollution emission reduction:The integrated assessment of the regional Air Quality ManagementPlans through the Italian national model”, Atmospheric Environment 43 (2009), 6182–6189)

The assessment included both technical and non technical measures and was carried out with the RAINS-Italy model comparing the Current LEgislation (CLE) scenario and an alternative scenario containing all the measures adopted by Regional administrations to pursue compliance with air quality standards

The target year, 2010, was set and the efficacy of all AQMPs measures was assessed in terms of SO2, NOx and PM10 emissions avoided and PM10 concentration reductions together with the improvements of the health impact indicator, the Life Expectancy Reduction (LER), defined as months lost attributable to PM2.5 concentrations


1 = Urban Waste incineration with heat recovery; 2 = Biogas recovery in agricultural and in farming sectors; 3 = District heating Plant with waste and biomass; 4 = Photovoltaic; 5 = Wind; 6 = Hydroelectric; 7 = Geothermic Well; 8 = High efficiency domestic boilers; 9 = Energy efficiency in building;10 = Residential heating accountability;11 = Heat pumps;

12 = Solar heating systems;13 = Regulation of some fuel use;14 = Incentives for shift to natural gas in domestic boilers;15 = Efficiency improvements in fireplaces and stoves;16 = Low emission zones;17 = Road traffic restriction;18 = Pollution charge;19 = Car sharing;20 = Motorway speed limits;21 = Bike sharing;22 = Incentives for new cars;

23 = Incentives for new diesel heavy duty;24 = Opening new rail lines;25 = Opening new underground lines;26 = Cycle paths;27 = Sea motorway;28 = Bus investment (new buses, service extension, frequency increase);29 = Antiparticulate filter;30 = Incentives for biofuel public transport;31 = New methane service stations;32 = Incentive for hydrogen cars;33 = Rationalising load transport in urban area;

0

1

2

3

4

5

6

7

8

9

10

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33

Measures

n°r

egio

ns

0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

Contribution (%) by measure to PM10 emission savings

Energy, Domestic and Road Transport regional measure adoption frequency



Emission Scenarios in support to PM10 time extension

-70% -60% -50% -40% -30% -20% -10% 0% 10% 20%

Piemonte

Valle d'Aosta

Lombardia

Trentino Alto Adige

Veneto

Friuli Venezia Giulia

Liguria

Emilila Romagna

Toscana

Umbria

Marche

Lazio

Abruzzo

Molise

Campania

Puglia

Basilicata

Calabria

Sicilia

Sardegna

Italia

PM10

NH3

NOx

SO2

Regional emission trends between 2011 and 2005with measures adopted in 2003-2007 Regional Air Quality Management Plans


Emission Reduction Tests

In order to achieve the compliance with the PM10 limit values in

all national territory some further emission reduction hypothesis have been tested.In particular the abatements regard primary PM10 emissions and

some precursors emissions in 2011 year.The resulting concentrations were simulated with MINNI model.

-50% -40% -30% -20% -10% 0%

test1

test2

test3

test4

test5

PM10

NH3

NOxReduction hypotheses


2011 Scenarios

-50% -40% -30% -20% -10% 0%

test1

test2

test3

test4

test5

PM10

NH3

NOx

PM10 annual mean concentrations in a subset of regional background (red-circled) and traffic stations Emission reductions

Annual Limit Value: 40 µg/m3

Annual Limit Value statistically estimated to comply also with daily limit value in 2011: 33-35 µg/m3

0

10

20

30

40

50

60

70

80

[ug/

m3]

2005 2011 piani QA 2011 test1 2011 test2 2011 test3 2011 test4 2011 test5


2011 Scenarios

-50% -40% -30% -20% -10% 0%

test1

test2

test3

test4

test5

PM10

NH3

NOx

PM10 annual mean concentrations in a subset of regional background stations Emission reductions

Annual Limit Value: 40 µg/m3

Annual Limit Value statistically estimated to comply also with one day limit value in 2011: 33-35 µg/m3

0

10

20

30

40

50

60

70

[ug/

m3]

2005 2011 piani QA 2011 test1 2011 test2 2011 test3 2011 test4 2011 test5


Form 3A: Quantitative source apportionment

REGIONSREGIONS

Form 2: Description of the exceedance of the limit value

Form 5A: Details of measures implementedbefore the original date of compliance

Form 4B: Baseline level for extended deadline for compliance

Form 3B: Reflection on the failure to deliver compliance by the original deadline

Form 4A: Baseline level for original deadline for compliance

MINNIMINNI

MINNI support to NO2 time extension notifications


NO2 Regional Source Apportionment

a. Emission variation (-20%)b. Model run at national scale with 20 km spatial resolution, for 1 winter

and 1 summer period c. Calculation of mean concentrations with reference to base run

This for:• Each Region separately (“regional” runs)

… variation i

• All Regions jointly (“control” run)

… variation N

• The percentage contribution of each Region i is estimated as i / N

Base run: 2008 national emission inventory at activity level (Institute for Environmental Protection and Research- ISPRA)


1

2

5

1 0

2 0

3 0

4 0

5 0

6 0

7 0

8 0

9 0

[ % ]

Northern ItalyNorthern Italy



1

2

5

1 0

2 0

3 0

4 0

5 0

6 0

7 0

8 0

9 0

[ % ]

Sistema MINNI


Central Italy and SardiniaCentral Italy and Sardinia


1

2

5

1 0

2 0

3 0

4 0

5 0

6 0

7 0

8 0

9 0

[ % ]

Sistema MINNI


Southern ItalySouthern Italy


1

2

5

1 0

2 0

3 0

4 0

5 0

6 0

7 0

8 0

9 0

[ % ]

NO2 Transboundary Source Apportionment


NO2 Sectorial Source Apportionment

a. Emission variation (-20%)b. Model run at national scale with 4 km spatial resolution, for 1 winter and

1 summer period c. Calculation of mean concentrations variation with reference to base

run

This for:• Each Sector separately (“sectorial” runs)

… variation i

• All Sectors jointly (“control” run)

… variation N

• The percentage contribution of each Sector i is estimated as i / N


NO2 Sectorial Source Apportionment

Cluster of activities:

• Road transport (SNAP group 07)• Residential (SNAP group 02)• Sea traffic and inland navigation (SNAP sub-groups 8.3 + 8.4)• Other transports (SNAP sub-groups 8.x)• Energy and industrial combustion, waste disposal

(SNAP groups 01, 03, 04, 09)


NO2 annual mean

0 . 1

1

2

5

1 0

2 0

3 0

4 0

5 0

6 0

7 0

8 0

[ u g / m 3 ]

Northern Italy


NOx total emissions: sectorial share

Northern Italy


NO2 – Sectorial source apportionment

Road transport (07)

contribution %

Variation i

0.020.050.10.20.50.7511.522.533.544.555.566.577.58

[ug/m 3]

0 . 1

1

2

5

1 0

2 0

3 0

4 0

5 0

6 0

7 0

8 0

9 0

[ % ]

Northern Italy


contribution %

Variation i

0.020.050.10.20.50.7511.522.533.544.555.566.577.58

[ug/m 3]

0 . 1

1

2

5

1 0

2 0

3 0

4 0

5 0

6 0

7 0

8 0

9 0

[ % ]

NO2 – Sectorial source apportionment

Residential (02)

Northern Italy


Sistema MINNI

NO2 – Source apportionment settoriale – Nord Italia

Trasporti marittimi e navigazione interna (8.3 + 8.4)

contribution %

Variation i

0.020.050.10.20.50.7511.522.533.544.555.566.577.58

[ug/m 3]

0 . 1

1

2

5

1 0

2 0

3 0

4 0

5 0

6 0

7 0

8 0

9 0

[ % ]


Sistema MINNI

NO2 – Source apportionment settoriale – Nord Italia

Other mobile emissions (8.x)

contribution %

Variation i

0.020.050.10.20.50.7511.522.533.544.555.566.577.58

[ug/m 3]

0 . 1

1

2

5

1 0

2 0

3 0

4 0

5 0

6 0

7 0

8 0

9 0

[ % ]


Form 4A: Baseline level for original deadline for compliance

Which NOWhich NO22 annual average concentrations annual average concentrations are expectedare expected in in 2010? And in 2015? 2010? And in 2015?

2005

2015

[ u g / m 3 ]

0

4

8

1 2

1 6

2 0

2 4

2 8

3 2

3 6

4 0

4 4

4 8

5 2

2010

2020

Form 4B: Baseline level for extended deadline for compliance

20x20 km2 resolution


NONO22 annual average concentrations annual average concentrations with bottom-up emissions (GAINS_Italy)with bottom-up emissions (GAINS_Italy)


2015: 2015: NO2 annual average concentrations NO2 annual average concentrations

(4km x 4km)(20km x 20km)


NONO22 annual average concentrations annual average concentrations with bottom-up emissions (GAINS_Italy)with bottom-up emissions (GAINS_Italy)

Percentage relative variation in 2015 NO2 annual mean concentration Percentage relative variation in 2015 NO2 annual mean concentration Compared to 2005Compared to 2005


2015 NO2 exceedences of the annual average concentrations at monitoring stations (current measures)


2015 NO2 exceedences of the annual average concentrations at monitoring stations with additional measures

ec4macs workshop, paris, 8-9 march 2012 gabriele zanini, luisella ciancarella...

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