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10th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes Sissi (Malia), Crete, Greece 17-20 October, 2005

Model based yearly air quality evaluation on Piemonte region

Camillo Silibello1, Giuseppe Calori1, Giorgio Arduino2, Carla Contardi2 and Franca Sordi2

1 ARIANET s.r.l., Milano, Italy

2 Regione Piemonte – Direzione Tutela e Risanamento Ambientale, Torino, Italy

The Framework Directive (1996/62/EC) and the first Daughter Directive (1999/30/EC) introduce, for the first time in European air quality directives, the combined use of monitoring data, emission inventories and modelling techniques in assessment and management of air quality.

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100% measurementMeasurement, no interpretationMeasurement+interpretationMeasurement+interpolationMeasurement+model fitted to measurementData assimilationModel validated by measurement in the same zoneModel validated elsewhereUnvalidated model100% modelling

Assessment under EU Air Quality Directives

Combining models with measurement

…there is an almost continuous spectrum of combination of measurements and otherassessment methods (mathematical techniques and models)From: Guidance on Assessment under the EU Air Quality Directives, EEA 2002

modelling

measurement

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Measurement+interpolation

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Combining models with measurementExample: NO2 yearly averages

Model validation using measurement in the same zone

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MAIN GOALTo give an example of air quality assessment over PiemonteRegion using an atmospheric modelling system validated by measurements in the same zone.

CONTENTS

• Piemonte Region Air Quality Assessment methods;

• The Italian national-scale MINNI Project;

• Air Quality Assessment for 1999 (Downscaling of MINNI data);

• Related works:• Air Quality Management

(two examples);• Air Quality Assessment for 2004

(highlights);• Smaller scale study;

• Conclusions

10th International Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes Sissi (Malia), Crete, Greece 17-20 October, 2005

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Piemonte Region Air Quality Assessment methods

Piemonte Region Air Quality Assessment methods

Emission inventory (INEMAR)

EMISSIVE INPUT FORDISPERSION MODELS

EMISSION MANAGER

METEOROLOGICAL FIELD

3D WIND ANDTEMPERATURE

TURBULENCEPARAMETERS

MINERVE

SURFPRO

IC and BC

POLLUTANT CONCENTRATION FIELDS

3D EULERIANPHOTOCHEMICAL

MODEL

FARM

METEOROLOGICAL ANDGEOGRAPHICAL DATA SETS

EMISSIVE INPUT FORDISPERSION MODELS

EMISSION MANAGER

METEOROLOGICAL FIELD

3D WIND ANDTEMPERATURE

TURBULENCEPARAMETERS

MINERVE

SURFPRO

3D WIND ANDTEMPERATURE

TURBULENCEPARAMETERS

3D WIND ANDTEMPERATURE

TURBULENCEPARAMETERS

MINERVE

SURFPRO

IC and BCIC and BC

POLLUTANT CONCENTRATION FIELDS

3D EULERIANPHOTOCHEMICAL

MODEL

FARM

3D EULERIANPHOTOCHEMICAL

MODEL

FARM

METEOROLOGICAL ANDGEOGRAPHICAL DATA SETS

Atmospheric Modelling System

68 stations28 O3 stations

Air Monitoring Network

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FARM (Flexible Air quality Regional Model)

3D Eulerian model, derived from STEM-II (Carmichael et al.)

• Diffuse sources & LPS with plume rise• Horizontal adv.-diff.: Blackman cubic polynomials (Yamartino, 1993) • Vertical adv.-diff.: hybrid semi-implicit Crank-Nicolson / fully implicit scheme

(Yamartino et al., 1992)

• Actinic flux reduction effect from clouds

• SOx-NOx-NH3 simplified scheme (EMEP)• Photochemistry: SAPRC-90 chemical scheme • PM: Models-3/CMAQ aero-3 module (Binkowski, 1999); aero-0 simplified bulk

module

• One- or two-way nesting

The Italian national-scale MINNI Project

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National-scale MINNI Project

GOALDevelopment of an Integrated Assessment Modelling System, supporting the international negotiation concerning the air pollution and the development of environmental policies at national level.

AMS ItaliaDealing with the air pollution dynamics (transport and dispersion) and multiphase chemical transformations, able to quantify concentrations and deposition flux of air pollutants (SOx, NOx, NH3, PM and O3), with a spatial resolution of 20 x 20 km2

RAINS ItaliaInheriting the valuable features of RAINS-Europe model, but fed by the coefficients of the Atmospheric Transfer Matrix (ATM) calculated with the AMS-Italia at a higher spatial resolution.

MINNI ProjectMeteorological sub-systemECMWF fields

Re-analysis

SYNOPs

RAMS1 | 2 grids, 4DDAHARMO-10

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MINNI ProjectEmission sub-system

0%

20%

40%

60%

80%

100%

CH4 CO CO2 NMCOV N2O NH3 NOx SOx

NATUREAGRICULTURE

WASTE TREATMENT & DISP.OTHER MOBILE SOURCESROAD TRANSPORT

SOLVENT AND OTHER PRODUCT USEEXTR. AND DISTRIB. OF FOSSIL FUELS

PRODUCTION PROCESSESCOMBUSTION IN MANUFACT. INDUSTRYNON-INDUSTRIAL COMBUSTION

COMBUSTION IN ENERGY

Model input(hourly, gridded,

speciated)

“Input emissions”

(NUTS2, RAINS sectors)

Ref. inventory

(NUTS3, SNAP3)

TU & sector partition

Grid disaggregation

Thematiclayers

0

0.2

0.4

0.6

0.8

1

1.2

1 3 5 7 9 11 13 15 17 19 21 23

hour

00.20.40.60.8

11.21.41.61.8

1 2 3 4 5 6 7 8 9 10 11 12

month

Modulation profiles

(yearly, weekly, daily)

Time modulation

Speciationprofiles

0 5 10 15 20 25

A-PINENEACETALDEHYDEACETALDEHYDE

ACETIC ACIDACETONE

ACETYLENEACID

ALCOHOLSALDEHYDES

ALKANESALKENES

ALKIYNESAMIDESAMINES

ANHYDRIDESANILINESARENES

B-PINENEBENZENE

CARBOXYL ESTERSESTERSETHANE

ETHYL ACETATEETHYL ALCOHOL

ETHYLAMINEETHYLBENZENE

ETHYLENEFORMALDEHYDE

PROPRIONALDEHYDEFORMIC ACID

GLYCOLSGLYOXAL

HEPTENEHEXENEHEXYNE

ISOPRENEKETONES

METHYL ALCOHOLN-BUTANE

OLEFINSOTHERS

PARAFFINESPENTYNEPHENOLSPROPANE

PROPYLENESTYRENE

TERPENESTOLUENE

UNIDENTIFIED

NMVOC, PM speciation

MINNI ProjectChemical-transport sub-system

NO2 concentrations on 1 October 1999 hr. 1920 km resolution

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Air Quality Assessment for 1999 (Downscaling of MINNI data)

Downscaling of MINNI national data

The basic idea is to use emissions, meteorology and pollutant (primary and secondary) concentrations hourly fields produced within the MINNI project to perform nested simulations over the Piemonte region for the year 1999.

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From: K.D. van den Hout, Air Quality Assessment Requirements Under The New EU Air Quality Directives

from 15 m to30 km

from 1 hr to1 year

Temporal and spatial aspects of limit values under EU Air Quality Directives

FARM has been applied to whole 1999, on hourly base, over Piemonte region with:a spatial resolution of 4 km (56x72x12) cells;simplified aerosol module (aero0).

State-of-the-art models (as FARM) require so much calculation time that a high spatial resolution and a full coverage of calendar year is impossible!

INEMARLombardia

APAT 2000

INEMARPiemonte

EMEP

EMISSION SUB-SYSTEMIntegration of local inventories

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Gridded area sources Point sources

EMISSION SUB-SYSTEMSpatial disaggregation (NOx)

MINNI – ITALY (20 KM) PIEMONTE (4 KM)

SPATIAL RESOLUTION EFFECTSOzone at ground

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MINNI – ITALY (20 KM) PIEMONTE (4 KM)

SPATIAL RESOLUTION EFFECTSNitrogen dioxide at ground

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90

O3

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calc

. (ug

/m3 )

SO2

Assessment under EU Air Quality Directives

Model validation by measurement in the same zone (yearly averages)

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NOx SO2

Yearly average: limit 30 μg m-3 Yearly average: limit 20 μg m-3

Assessment of the Limit Values for the protection of ecosystems

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Yearly average: limit 40 μg m-3

Assessment of the Limit Values for the protection of human health (NO2)

200 μg m-3 not to be exceeded more than18 times a calendar year (hourly base)

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Yearly average: limit 40 μg m-350 μg m-3 not to be exceeded more than

35 times a calendar year (daily base)

Assessment of the Limit Values for the protection of human health (PM10)

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120 μg m-3 not to be exceeded more than 25 times a calendar year (maximum daily 8-hour mean)

Assessment of the Limit Values for the protection of human health (O3)

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Air Quality Management

…air quality models have an important place in air quality management. They are essential tools in the development of action plans for improving air quality, which is the ultimate goal of the Member States and local authorities in order to fulfil their obligations under the directives.

From: Guidance on Assessment under the EU Air Quality Directives, EEA 2002

Impact of year 2008 vehicles fleet

Fleet projectionExample: COPERT classes of gasoline cars > 1400 cc

E URO IVE URO III

E URO IIE URO I

ECE 04E CE 03E CE 02

E CE 00 -0 1P RE ECE

0%

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1 00%

20 03 2 008

2003 2008

[t/year]

Variation of NOx emissions

Variation of NO2yearly avg.

concentrations

-6

-5.5

-5

-4.5

-4

-3.5

-3

-2.5

-2

-1.5

-1

-0.5

ug/m3

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Impact of future buildings heating sector

Example:decrease of PM10 emissions

Decrement of PM10 avg. concentrations in cold

season

Changes of:• fuels• boilers• buildings• district heatingover 10 years

[t/year]

-14.8%-1.8%-4.2%Winter totals

-8.2%-0.9%-2.2%Yearly totals

-73%-21%-39%Macrosector 2

SO2PM10NOx

Changes in regional emissions

Air Quality Assessment update at 2004

Most significant changes from 1999 assessment:use of local meteorological data;nesting on CHIMERE continental-scale model.

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wind ground stations temperature ground stations

radiosoundings

synop stations

METEOROLOGICAL NETWORKGround level stations

AIR QUALITY MONITORING NETWORKPM10 stations (with almost 90% of valid data)

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PM10 Yearly average (2004)

Model

Yearly average: limit 40 μg m-3

Data assimilationSuccessive correction scheme (ADAS)

Smaller scale study(500 m resolution)

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11249 51IvreaIvrea

LocalLocalDomainDomain

Province Domain

2 km resolution 500 m resolution

1999Measured values: 2000

Ivrea monitoring site

SPATIAL RESOLUTION EFFECTSIvrea, NO2 yearly average

CONCLUSIONS

• Piemonte Region has implemented the Framework directive and daughter legislations using measurements (regional air quality network), emission inventories (INEMAR) and modelling techniques;

• the Air Quality Assessment for 1999 (downscaling of MINNI data) shows exeedances for ozone in large portions of the regional basin and for NOxand PM10 within Turin urban area;

• The use of the modelling system has permitted to estimate the impact of future emission scenarios (Air Quality Management);

• The Air Quality Assessment for 2004 year is terminated and 2005 is in progress;

• Simulation results claim for the use of a more complete aerosol module (aero3) and a better representation of PM10 phenomenology

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Acknowledgements

This work has been supported by Regione Piemonte (Direzione Tutela e Risanamento Ambientale).

Thanks also to:• A.R.P.A. Piemonte people (Roberta De Maria, Monica Clemente, Cinzia

Cascone, Federica Motta, Stefano Bande, Massimo Muraro, Maria Elena Picollo, Francesco Lollobrigida) for their relevant contribution to the development of the Regional Air Quality Assessment and Management system;

• Gianluigi Truffo for his contribution to the preparation of the regional emission inventory

• ENEA for providing MINNI data used in this work (contact person: Dr. Gabriele Zanini: zanini@bologna.enea.it);

• EMEP for providing data (emission, concentrations) used in this work .

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