Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
Workshop on the preparation of air...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
Foreword Italian Regions are the I...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
Piedmont Region:
a complex territo...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Population:Population: 4.290.000...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Several subjects provide the sou...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
Regional Air Quality
Network • 74 ...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Air Quality ManagementAir Qualit...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Zoning for Air Quality Managemen...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
Following the EU Framework Directi...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Zone, why ???Zone, why ???
 The...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 it is clear that the collection ...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 So, 10 years ago, we have used o...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Regional Emission Inventory: yea...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 PiemontePiemonte : Zones and agg...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
CTM application: air quality asses...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
Air quality assessment modeling sy...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
METEOROLOGICAL DATA
MINERVE
SURFPR...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 FARM:FARM: (Flexible Air quality...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
Emission dataEmission data The Emi...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
Emission data treatmentEmission da...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
99 total observations
Observations...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Stations & fields used to define...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Evaluation of model performances...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Evaluation of model performances...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Evaluation of model performances...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 The Piemonte Region Air Quality ...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Piemonte 2005: PMPiemonte 2005: ...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Piemonte 2005: NOPiemonte 2005: ...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Piemonte 2005: OPiemonte 2005: O...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 …… the problem is:the problem is...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 The output fields produced by th...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 the aggregation at municipality ...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 MethodologyMethodology
Experienc...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Comparison between the three alg...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Functional approach for land cla...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Clustering resultsClustering res...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Multi-pollutant zoningMulti-poll...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Multi-pollutant zoningMulti-poll...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 The DifferenceThe Difference
199...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Air Quality PlanAir Quality Plan...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
Regional AQ system
Boundary
condit...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 MethodologyMethodology
1.1. Inve...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Piemonte AQ Plan: measures at 20...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Piemonte Case: Effects on emissi...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Piemonte Case: Effects on emissi...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Piemonte Case: Effects on emissi...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Piemonte Case: Effects on emissi...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Piemonte Case: Effects on concen...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Piemonte Case: Effects on concen...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Piemonte Case: Effects on concen...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Room for improvement …?
(RAINS –...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
 Lessons learnedLessons learned
…...
Workshop on the preparation of air quality
[Ing. Giorgio Arduino, Reg. Piemonte, Italy]
Thank YouThank You
ForFor
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The experience of piedmont in Air Quality

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INFRA 32329 Workshop on the preparation of air quality plans 23 April 2009 (Belgrade - Serbia)
The Experience of Piedmont
Giorgio Arduino

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  • GDP (Gross Domestic Product)
  • The Framework Directive and the first Daughter Directive introduce, for the first time in European air quality directives, the use of modelling in assessment and management of air quality. The Framework Directive refers in its preamble to “the use of other techniques of estimation of ambient air quality besides direct measurement”, defines (Article 2) that assessment “shall mean any method used to measure, calculate, predict or estimate the level of a pollutant…” and then states specifically (Article 6) that modelling techniques may be used. The first Daughter Directive expands this by introducing the use of supplementary assessment methods (Article 6(3)), which is discussed in more detail in Section 2.4 of this guidance report. It also indicates data quality objectives for models, in terms of accuracy (Annex VIII).
    It is clear that 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. Models improve the effectiveness of air quality management. Through models, the contributions to exceedences of limit values from various sources and source categories can be established.
    Another main advantage to be gained from using models in assessment and management of air quality is that it enhances the ability to map the spatial distribution of the pollutant concentrations. By using models suitable for the scale and application in question, all scales (from regional background to city quarters and streets), may be mapped. This opens the possibility to relax on the measurement requirements (possibility to reduce the number of stations), and thus produce a more cost-effective, and yet complete, air quality assessment.
  • Framework Directive DIR 1996/62/CE
    Article 5
    Preliminary assessment of ambient air quality
    Member States which do not have representative measurements of the levels of pollutants for all zones and agglomerations shall undertake series of representative measurements, surveys or assessments in order to have the data available in time for implementation of the legislation
    referred to in Article 4 (1).
    Article 6
    Assessment of ambient air quality
    1. Once limit values and alert thresholds have been set, ambient air quality shall be assessed throughout the territory of the Member States, in accordance with this Article.
    2. In accordance with the criteria referred to in Article 4 (3), and in respect of the relevant pollutants under Article 4 (3), measurement is mandatory in the following zones:
    — agglomerations as defined in Article 2 (10),
    — zones in which levels are between the limit values and the levels provided for in paragraph 3, and
    — other zones where levels exceed the limit values.
    The measures provided for may be supplemented by modelling techniques to provide an adequate level of information on ambient air quality.
  • Regime 1: Greater than the upper assessment threshold
    High quality measurement is mandatory. Data from measurement may be supplemented by information from other sources, including air quality modelling.
    Regime 2: Less than the upper assessment threshold but greater than the lower assessment threshold
    Measurement is mandatory, but fewer measurements may be needed, or less intensive methods may be used, provided that measurement data are supplemented by reliable information from other sources.
    Regime 3: Less than the lower assessment threshold
    a. In agglomerations, only for pollutants for which an alert threshold has been set**
    At least one measuring site is required per agglomeration, combined with modelling, objective estimation, indicative
    measurements.
    b. In non-agglomeration zones for all pollutants and in all types of zone for pollutants for which no alert threshold has been set
    Modelling, objective estimation, and indicative measurements alone are sufficient.
    * Data quality objectives are given in Annex VIII of the first Daughter Directive.
    ** In the first Daughter Directive this only applies to SO2 and NO2.
    *** Indicative measurements are measurements using simple methods, or carried out for a restricted time. They are less accurate than continuous high quality measurement but can be used to explore air quality as a check where pollution levels are relatively low, and to supplement high quality measurement in other areas.
  • 2.2 Zones and assessment regimes
    The new air quality directives oblige the Member States to divide their territories in zones.
    Zones are primarily units for air quality management, but the directives also specify assessment requirements per zone.
    These requirements depend on how far air quality levels are below a limit value.
    For each pollutant two thresholds are set in the Daughter Directives5: the upper assessment threshold (UAT) and the lower assessment threshold (LAT).
    The thresholds are lower than the limit value and are defined as percentages of the limit value.
    The assessment requirements in a zone depend on whether, in the preceding years, an assessment threshold is exceeded anywhere in the zone.
    In the first year of implementation of the Daughter Directive the assessment regime depends on the results of the Preliminary Assessment (Van Aalst, et al., 1998).
    If the UAT of a certain pollutant is exceeded, the most intensive assessment requirements apply for this pollutant; if LAT is exceeded, but UAT is not, slightly less intensive assessment requirements are prescribed; if the levels are everywhere below LAT the least intensive requirements apply.
    So, exceedence of the limit value does not determine the assessment requirements; it triggers air quality reporting and management actions.
    See Figure.
  • Chemical Transport Models (CTMs)
  • Gridded emissions are computed on hourly basis starting from different emission inventories (high resolution regional INEMAR inventory for Piemonte and Lombardia, national CORINAIR inventory for the remaining Italian regions and EMEP for foreign countries). Hourly emission rates of the desired species are estimated by a pre-processing system allowing flexible space disaggregation, time modulation and non-methanic hydrocarbon speciation of inventory data related to point, line and area sources.
  • Meteorological fields are reconstructed assimilating ARPA Piemonte meteorological network observations (including surface measurements and vertical soundings) within background fields obtained by ECMWF analyses.
  • The atmospheric pollutant concentration fields are finally obtained driving the chemical transport model FARM by means of boundary conditions provided by continental runs of the chemical transport model CHIMERE, from the INERIS Prev’Air service (http://prevair.ineris.fr) and Regione Piemonte air quality monitoring network observations.
  • the aggregation at municipality scale can be realized solving the so-called “change of support problem”, retrieving a value of a random field on an area starting from its values on points for every fixed time.
    A simple solution is to integrate over the area, that means to average the field values weighted by areas over the cells belonging to a certain municipality. Two alternatives for the aggregation are the average
    of the field values weighted by the building percentage for every cell (a point in the grid represent a cell) and the 90th percentile over the cell values in a municipality.
    The building percentage is an important indicator of the antropic activity which could generate more pollution in a municipality, whereas a wide country area could not contribute at all. Instead the 90th percentile is chosen as a measure of extreme cases in a municipality, in a precautionary perspective.
    or a mixture of the two
  • 2) and 3) are proposed because the building percentage is an important indicator of the anthropic activity which could generate more pollution in a municipality, whereas a wide country area could not contribute at all.
    Instead the 90th percentile (maximum) is chosen as a measure of extreme cases in a municipality, in a precautionary perspective.
  • Functional approach for land classification using data coming from AQA modelling system
    Pollutant time series can be considered as realizations of continuous processes that are recorded in discrete time.
    The conversion from discrete data to curves involves smooth-ing, using linear combinations of B-spline functions.
    Thus we have functional data that can be classified by clustering procedures.
    The non hierarchical algorithm PAM (Partioning Around Medoid) is used to cluster objects.
    The parameterization of functions using B-splines can replace the classical analysis by synthetic indicators (as average levels, standard deviations, quantiles) to respect the functional form of pollutant concentrations through time.
    Synthesizing features contained within time series in a little number of coefficients, we preserve in the “zoning” most information about pollutant concentration levels and time profiles.
    This approach is applied to functional data of the biggest critical atmospheric pollutants in Piemonte.
  • The experience of piedmont in Air Quality

    1. 1. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy] Workshop on the preparation of air quality plansWorkshop on the preparation of air quality plans organised in co-operation with theorganised in co-operation with the Ministry of Environment andMinistry of Environment and Spatial PlanningSpatial Planning Experiences in establishment ofExperiences in establishment of zones and agglomerationszones and agglomerations the Case of Piedmont regionthe Case of Piedmont region (Italy)(Italy)
    2. 2. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy] Foreword Italian Regions are the Institutions committed to perform air quality assessment required by EU directives Tasks: •Subdivide territory in zones defined depending on the risk level of exceeding air quality limits •Realise yearly air quality assessment elaborate air quality information to be transmitted to the European Commission •Periodically revise zones definition •Define mitigation actions and pollution reduction plans Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    3. 3. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy] Piedmont Region: a complex territory Mountains 43% Foothill 30% Lowlands 27%  Area:Area: 25.42625.426 Km²  Climate:Climate: Winters: cold, dry and banks of fog Summers: cool in the hills and quite hot in the plains  Temperature range during the year:Temperature range during the year: - 5°C / +30°C- 5°C / +30°C  HydrographyHydrography: more than 4000 km  Land coverLand cover: 52%52% agricultural, 40,2%40,2% forest and semi natural, 6,3%6,3% artificial, 1,5%1,5% water bodies-wetlands  Protected areasProtected areas: 22 national parks, 6767 regional parks, 8,3%8,3% of the total surface  Nature 2000 networkNature 2000 network: 123123 SCI, 5151 SPA, 15,67%15,67% of the total surface  Monitoring stationsMonitoring stations Air: 85 Water: 129 Meteorological: 322 Experiences in establishment of zones and agglomerations:Experiences in establishment of zones and agglomerations: PiedmontPiedmont
    4. 4. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Population:Population: 4.290.0004.290.000  Density:Density: 169 pop/Km²169 pop/Km²  88 ProvincesProvinces - 1.206- 1.206 MunicipalitiesMunicipalities  Chief Town:Chief Town: Turin ( 901.000)Turin ( 901.000)  AgglomerateAgglomerate: Turin + 11 ( 1.297.000): Turin + 11 ( 1.297.000)  Road net:Road net: 22.630 Km22.630 Km ( first in Italy !!! )( first in Italy !!! )  Vehicles:Vehicles: 3.481.7363.481.736 GDP 2006:GDP 2006: 119 Bil €119 Bil € (10% GDP Italy)(10% GDP Italy) Businesses:Businesses: 407.137407.137 Agriculture 18% Industries 28% Services 54% Piedmont Region: a complex territory Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    5. 5. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Several subjects provide the source information: Region, Provinces, Environmental Agency, Municipalities, Private organizations….  Environmental information creation process is transversal to the public bodies with specific competence PROVINCES Permitting procedures and local planning REGIONAL ENVIRONMENT PROTECTION AGENCY (ARPA) Technical control and monitoring REGION Planning and coordinating Environmental Information System Environmental information in Piedmont Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    6. 6. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy] Regional Air Quality Network • 74 public fixed stations74 public fixed stations • 6 public mobile stations6 public mobile stations • 11 private fixed stations11 private fixed stations In the fixed network there are: 65 nitrogen oxide analyzers (NOx) 47 carbon monoxide analyzers (CO) 54 PM10 samplers and analyzers 2 PM2.5 samplers 25 sulphur dioxide analyzers (SO2) 33 ozone analyzers (O3) 16 aromatic hydrocarbon analysers (BTX) Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    7. 7. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Air Quality ManagementAir Quality Management ……air quality models have an important place in air qualityair quality models have an important place in air quality management. They are essential tools in the development of actionmanagement. They are essential tools in the development of action plans for improving air quality, which is the ultimate goal of theplans for improving air quality, which is the ultimate goal of the Member States and local authorities in order to fulfil their obligationsMember States and local authorities in order to fulfil their obligations under the directives.under the directives. From: Guidance on Assessment under the EU Air Quality Directives, EEA 2002From: Guidance on Assessment under the EU Air Quality Directives, EEA 2002 Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    8. 8. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Zoning for Air Quality ManagementZoning for Air Quality Management Starting from the preliminary assessmentStarting from the preliminary assessment DIR 1996/62/CEDIR 1996/62/CE (art. 5)(art. 5) Member States which do not have representative measurements of theMember States which do not have representative measurements of the levels of pollutants for all zones and agglomerations shall undertakelevels of pollutants for all zones and agglomerations shall undertake series of representative measurements, surveys or assessments inseries of representative measurements, surveys or assessments in order to have the data available in time for implementation of theorder to have the data available in time for implementation of the legislation referred to in Article 4 (1).legislation referred to in Article 4 (1). Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    9. 9. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy] Following the EU Framework Directive (96/62/EC) and his Daughter Directives (1999/30/EC; 2000/69/EC; 2002/3/EC; 2004/107/EC) … and now New Air Quality Directive (2008/50/EC) Zones and assessmentZones and assessment regimesregimes From: Guidance on Assessment under the EU Air Quality Directives, EEA 2002From: Guidance on Assessment under the EU Air Quality Directives, EEA 2002 Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    10. 10. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Zone, why ???Zone, why ???  The new air quality directives oblige the Member States to divide theirThe new air quality directives oblige the Member States to divide their territories in zonesterritories in zones  Zones are primarily units for air quality managementZones are primarily units for air quality management Municipal Administrative BoundariesMunicipal Administrative Boundaries  but the directives also specify assessment requirements per Zonebut the directives also specify assessment requirements per Zone Homogeneous Data on Air PollutionHomogeneous Data on Air Pollution  These requirements depend on how far air quality levels are below a limitThese requirements depend on how far air quality levels are below a limit valuevalue Air Quality Data in All the TerritoryAir Quality Data in All the Territory Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    11. 11. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  it is clear that the collection of air quality data throughout the territory isit is clear that the collection of air quality data throughout the territory is the priority in order to properly zoning the entire regionthe priority in order to properly zoning the entire region  The Piedmont region in 1999 (year of implementation in Italy) did not haveThe Piedmont region in 1999 (year of implementation in Italy) did not have an adequate network of continuous monitoringan adequate network of continuous monitoring  The estimation methodology used in reference to the limits of long-termThe estimation methodology used in reference to the limits of long-term (annual average) for nitrogen dioxide and PM10 is based on the correlation(annual average) for nitrogen dioxide and PM10 is based on the correlation between the amount of pollutant emitted annually per unit area in a givenbetween the amount of pollutant emitted annually per unit area in a given municipality, and the concentrations found in the same town stations ofmunicipality, and the concentrations found in the same town stations of regional air quality monitoring networkregional air quality monitoring network  The simplifying assumptions underlying this approach is to consider that theThe simplifying assumptions underlying this approach is to consider that the average concentration of a pollutant in the territory of a municipality isaverage concentration of a pollutant in the territory of a municipality is substantially dependent on sources of emissions within the samesubstantially dependent on sources of emissions within the same municipalitymunicipality  It should be stressed that the methodology based on regional emissionsIt should be stressed that the methodology based on regional emissions inventory provides, at present, an estimate of the average concentration ofinventory provides, at present, an estimate of the average concentration of a pollutant in the territory of a municipalitya pollutant in the territory of a municipality Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    12. 12. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  So, 10 years ago, we have used one incorrect methodology forSo, 10 years ago, we have used one incorrect methodology for zoning an entire region, using only few monitoring data and emissionzoning an entire region, using only few monitoring data and emission data (not so bad) for every municipalities !data (not so bad) for every municipalities ! This is the correlation between emission NOThis is the correlation between emission NOxx [t/km[t/km22 ] and NO] and NO22 [[µµg/mg/m33 ]] Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    13. 13. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Regional Emission Inventory: yearly total emissionRegional Emission Inventory: yearly total emission NOx NMVOC PM10 Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    14. 14. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  PiemontePiemonte : Zones and agglomerations (after preliminary assessment): Zones and agglomerations (after preliminary assessment) Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    15. 15. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy] CTM application: air quality assessment & zoning According to the European Directive 96/62/EC and the ItalianAccording to the European Directive 96/62/EC and the Italian Legislation (D.L. 351/1999), the Regional administrations are in chargeLegislation (D.L. 351/1999), the Regional administrations are in charge to perform theto perform the air quality assessment (AQA)air quality assessment (AQA) in order to divide theirin order to divide their territories in homogeneous zones and assess air quality within them,territories in homogeneous zones and assess air quality within them, taking into account the different pollutants’ limit and threshold valuestaking into account the different pollutants’ limit and threshold values Since 2005, Piemonte authorities have charged the ARPA Piemonte toSince 2005, Piemonte authorities have charged the ARPA Piemonte to perform yearly AQA integrating the information provided by theperform yearly AQA integrating the information provided by the regional monitoring network with concentration fields supplied by aregional monitoring network with concentration fields supplied by a CTM modelling system.CTM modelling system. The modelling system has been built and optimised performing yearThe modelling system has been built and optimised performing year 2004 AQA and successively applied for year 2005, 2006 and 2007.2004 AQA and successively applied for year 2005, 2006 and 2007. The modelling system works on a computational domain covering theThe modelling system works on a computational domain covering the whole Piemonte Region with an horizontal resolution of 4 km and 12whole Piemonte Region with an horizontal resolution of 4 km and 12 vertical levels, spanning the lower 3500 metres of the atmosphere.vertical levels, spanning the lower 3500 metres of the atmosphere. Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    16. 16. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy] Air quality assessment modeling system architectureAir quality assessment modeling system architecture Pollutants: SOPollutants: SO22 NONOxx NONO22 CO PMCO PM1010 PMPM2.52.5 OO33 CC66 HH66 Simulation timeSimulation time: 1 year: 1 year Temporal resolutionTemporal resolution: 1 hour: 1 hour Meteorological fields reconstructed integrating analysed fields from the European Centre forMeteorological fields reconstructed integrating analysed fields from the European Centre for Medium Range Weather Forecast (ECMWF) with observations (radiosoundings and surfaceMedium Range Weather Forecast (ECMWF) with observations (radiosoundings and surface data provided by the regional meteorological network) by means of a mass-consistent modeldata provided by the regional meteorological network) by means of a mass-consistent model Boundary conditions obtained assimilating continental runs of the CTM CHIMERE and air qualityBoundary conditions obtained assimilating continental runs of the CTM CHIMERE and air quality monitoring observationsmonitoring observations Post-processing tools to compute all the indicators required by EU air quality legislation.Post-processing tools to compute all the indicators required by EU air quality legislation. 220 x 284 km2 ∆xy: 4 km Nx = 56 Ny= 72 Vertical levels: 12 (up to 3500m agl) Simulation length: 1 year Output fields time resolution: 1hour Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    17. 17. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy] METEOROLOGICAL DATA MINERVE SURFPRO EMISSION MANAGER FARM GEOGRAPHICAL DATA EMISSION DATA METEOROLOGICAL INPUT EMISSION INPUT IC/BC Modelling system main modules Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    18. 18. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  FARM:FARM: (Flexible Air quality Regional Model)(Flexible Air quality Regional Model)  3D Eulerian model, derived from STEM-II3D Eulerian model, derived from STEM-II (Carmichael et al.)(Carmichael et al.)  Diffuse sources & LPS with plume riseDiffuse sources & LPS with plume rise  Horizontal adv.-diff.: Blackman cubic polynomialsHorizontal adv.-diff.: Blackman cubic polynomials (Yamartino, 1993)(Yamartino, 1993)  Vertical adv.-diff.: hybrid semi-implicit Crank-Nicolson / fully implicitVertical adv.-diff.: hybrid semi-implicit Crank-Nicolson / fully implicit schemescheme (Yamartino et al., 1992)(Yamartino et al., 1992)  Actinic flux reduction effect from cloudsActinic flux reduction effect from clouds  SOx-NOx-NH3 simplified schemeSOx-NOx-NH3 simplified scheme (EMEP)(EMEP)  Photochemistry: SAPRC-90 chemical schemePhotochemistry: SAPRC-90 chemical scheme  PM: Models-3/CMAQ aero-3 modulePM: Models-3/CMAQ aero-3 module (Binkowski, 1999)(Binkowski, 1999); aero-0 simplified; aero-0 simplified bulk modulebulk module  One- or two-way nestingOne- or two-way nesting Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    19. 19. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy] Emission dataEmission data The Emission component is prepared from IREA (Regional Emission Inventory) by EMMA code (Arianet), to obtain hourly emission rates gridded on the regional domain and nearby regions. The emissions inside IREA are defined on a polygonal bases (details on municipal or provincial boundaries) and a specific module of EMMA is able to take into account the characteristics of land-use components inside each cell, so that emissions associated with individual human activities (production of energy, agriculture, farming, transport, waste treatment, etc ...) or natural (biogenic, soil dust, ecc. ) are distributed only into the cells of the domain intersected by each polygon emission and the appropriate land-use type. DTM 250 m CORINE LC 250 m Regional transport graph Urban area from CTR INEMAR Piemonte EMEP CORINAIR Italy Valle d'Aosta Regional Inventory INEMAR Lombardia Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    20. 20. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy] Emission data treatmentEmission data treatment Example:Example: A: distribution of conifers by CORINE Land CoverA: distribution of conifers by CORINE Land Cover B: spatialisation biogenic emissions from conifer grills on the domainB: spatialisation biogenic emissions from conifer grills on the domain A B Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    21. 21. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy] 99 total observations Observations: Wind, T, Q 30 grid points (0.5° lat lon resolution), every 6 hours ECMWF Analyses: (Cuneo Levaldigi e Milano Linate) 2 Radiosoundings: VV, DV, T, RH VV, DV, T, P, RH (hourly data) 94 surface stations: 3 WMO (Synop): VV, DV, T, P, RH, (every 3 hours)  Meteorological data Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    22. 22. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Stations & fields used to define initial and boundary conditionsStations & fields used to define initial and boundary conditions Chimere Continental run provided by Prev’Air • 0.5 ° space resolution, 8 vertical levels • Chemical mechanism: MELCHIOR + aerosol Air Quality measurements from Piemonte and nearby Italian Regions networks Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    23. 23. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Evaluation of model performances: PMEvaluation of model performances: PM1010 2005 – PM10 yearly averages 2005 – PM10 daily averages Station: Torino-Consolata Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    24. 24. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Evaluation of model performances: NOEvaluation of model performances: NO22 2005 – NO2 daily averages Station: Torino-Rebaudengo (roadside) 2005 – NO2 hourly averages Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    25. 25. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Evaluation of model performances: OEvaluation of model performances: O33 2005 – O3 max 8-hour average 2005 – O3 max 8-hour average Station: Novara-Verdi (urban – background)Station: Buttigliera d’Asti (rural – background) Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    26. 26. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  The Piemonte Region Air Quality Assessment modelling system has been evaluated comparingThe Piemonte Region Air Quality Assessment modelling system has been evaluated comparing modelled concentrations with measurements from stations located in different geographic, topographicmodelled concentrations with measurements from stations located in different geographic, topographic and land cover environment.and land cover environment.  O3 indicators shows satisfactory results, with good accuracy in reproducing measured levels, for bothO3 indicators shows satisfactory results, with good accuracy in reproducing measured levels, for both eight-hours and hourly averages.eight-hours and hourly averages.  NO2 concentration fields are satisfactorily reproduced, yearly averages and concentration statisticsNO2 concentration fields are satisfactorily reproduced, yearly averages and concentration statistics are compatible with measured values. The model accuracy remains within the requested limit for mostare compatible with measured values. The model accuracy remains within the requested limit for most monitoring sites. Some underestimation of peak concentration has been detected where modelmonitoring sites. Some underestimation of peak concentration has been detected where model resolution is insufficient and during adverse meteorological conditions (severe episodes).resolution is insufficient and during adverse meteorological conditions (severe episodes).  PM10 concentrations have been reconstructed with values within the requested accuracy for bothPM10 concentrations have been reconstructed with values within the requested accuracy for both daily and yearly averages at most station locations, even though a clear underestimation can bedaily and yearly averages at most station locations, even though a clear underestimation can be noticed for stations located outside the Torino metropolitan area.noticed for stations located outside the Torino metropolitan area. This shortcoming can be partly ascribed to a certain underestimation of emissions outside Torino (e.g.This shortcoming can be partly ascribed to a certain underestimation of emissions outside Torino (e.g. from wood burning) and to the difficulty to simulate PM accumulation phenomena within the Po valley.from wood burning) and to the difficulty to simulate PM accumulation phenomena within the Po valley.  Regione Piemonte implemented the modelling system as a permanent air quality assessment tool andRegione Piemonte implemented the modelling system as a permanent air quality assessment tool and ARPA Piemonte is now in charge to perform modelling applications on a yearly basis.ARPA Piemonte is now in charge to perform modelling applications on a yearly basis. Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    27. 27. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Piemonte 2005: PMPiemonte 2005: PM1010 - Zones and agglomerations- Zones and agglomerations Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    28. 28. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Piemonte 2005: NOPiemonte 2005: NO22 - Zones and agglomerations- Zones and agglomerations Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    29. 29. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Piemonte 2005: OPiemonte 2005: O33 - Zones and agglomerations- Zones and agglomerations Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    30. 30. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  …… the problem is:the problem is: Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont PM10 2005 yearly average The AQA modelling system provides data on a regular grid We need to aggregate data at municipality scale (“change of support problem”)
    31. 31. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  The output fields produced by the modeling system are superimposed (usingThe output fields produced by the modeling system are superimposed (using GIS GRASS) to vector thematic maps that describe the region:GIS GRASS) to vector thematic maps that describe the region:  in this way are identified for each administrative unit, the cells that fall within it,in this way are identified for each administrative unit, the cells that fall within it, and, on the basis of intersection polygon-cells, the breakdown of communaland, on the basis of intersection polygon-cells, the breakdown of communal cellscells Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont Note: the grid points belonging to the municipality of Alessandria However, very few municipalities inHowever, very few municipalities in Piedmont have more than 5 dataPiedmont have more than 5 data
    32. 32. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  the aggregation at municipality scale can be realized solving the so-calledthe aggregation at municipality scale can be realized solving the so-called “change of support problem”.“change of support problem”.  A simple solution is to integrate over the area, that means to average theA simple solution is to integrate over the area, that means to average the field values weighted by areas over the cells belonging to a certainfield values weighted by areas over the cells belonging to a certain municipality.municipality.  Two alternatives for the aggregation are the average of the field valuesTwo alternatives for the aggregation are the average of the field values weightedweighted by theby the building percentagebuilding percentage for every cell (a point in the gridfor every cell (a point in the grid represent a cell) and therepresent a cell) and the 90th percentile90th percentile over the cell values in aover the cell values in a municipality.municipality.  TheThe building percentagebuilding percentage is an important indicator of theis an important indicator of the antropicantropic activityactivity which could generate more pollution in a municipality, whereas awhich could generate more pollution in a municipality, whereas a wide country area could not contribute at all.wide country area could not contribute at all.  Instead theInstead the 90th percentile90th percentile is chosen as a measure ofis chosen as a measure of extreme casesextreme cases in a municipality, in a precautionary perspective.in a municipality, in a precautionary perspective. Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    33. 33. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  MethodologyMethodology Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont (1) Weighted block average (weight = municipality area percentage) 〈C i〉=∑ j=1 npi ijc j ij= Aij Ai (2) Weighted block average (weight = municipality built area percentage) 〈C i〉=∑ j=1 npi  ijc j e  ij= Eij Ei (3) Weighted block average (weight obtained using municipality area and build area percentage) 〈C i〉=1〈C1i〉2 〈C2i〉 con 〈C1i〉=∑ j=1 npi Iij1ijc j e 1ij= Aij Ai∣Iij=1 dove Iij=1 se Eij Aij ≥ , Iij=0 se Eij Aij  e con 〈C2i 〉=∑ j=1 npi 1− Iij2ijc j e 2ij= Aij Ai∣1−Iij=1 (4) 90th percentile or maximum over the cell valuea in a municipality
    34. 34. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Comparison between the three algorithms (examples of Biella, whereComparison between the three algorithms (examples of Biella, where we see major differences - with built concentrated in a restricted area)we see major differences - with built concentrated in a restricted area) and Torino (little difference)and Torino (little difference) Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    35. 35. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Functional approach for land classification using data coming from AQAFunctional approach for land classification using data coming from AQA modelling system - Cluster Analysismodelling system - Cluster Analysis  Pollutant time series can be considered as realizations of continuousPollutant time series can be considered as realizations of continuous processes that are recorded in discrete time. The conversion from discreteprocesses that are recorded in discrete time. The conversion from discrete data to curves involves smoothing, using linear combinations of B-splinedata to curves involves smoothing, using linear combinations of B-spline functions. Thus we have functional data that can be classified by clusteringfunctions. Thus we have functional data that can be classified by clustering procedures. The non hierarchical algorithm PAM (Partioning Around Medoid)procedures. The non hierarchical algorithm PAM (Partioning Around Medoid) is used to cluster objects. The parameterization of functions using B-splinesis used to cluster objects. The parameterization of functions using B-splines can replace the classical analysis by synthetic indicators (as average levels,can replace the classical analysis by synthetic indicators (as average levels, standard deviations, quantiles) to respect the functional form of pollutantstandard deviations, quantiles) to respect the functional form of pollutant concentrations through time. Synthesizing features contained within timeconcentrations through time. Synthesizing features contained within time series in a little number of coefficients, we preserve in the “zoning” mostseries in a little number of coefficients, we preserve in the “zoning” most information about pollutant concentration levels and time profiles.information about pollutant concentration levels and time profiles.  This approach is applied to functional data of the biggest criticalThis approach is applied to functional data of the biggest critical atmospheric pollutants in Piemonte.atmospheric pollutants in Piemonte. Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    36. 36. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Clustering resultsClustering results Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont NO2 (left, 4 cluster) and PM10 (right, 3 cluster) Data coming from simulations for AQA 2005
    37. 37. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Multi-pollutant zoningMulti-pollutant zoning To support decisors considering jointly differentTo support decisors considering jointly different pollutants, in order to get a multi-pollutantpollutants, in order to get a multi-pollutant zoning, we propose to summarize them in anzoning, we propose to summarize them in an air quality index (1) or, alternatively, in principalair quality index (1) or, alternatively, in principal components (2).components (2). (1)(1) We propose to aggregate over pollutants by theWe propose to aggregate over pollutants by the maximum function, in order to keep informationmaximum function, in order to keep information about critical cases, to obtain air quality indexabout critical cases, to obtain air quality index time series for all the municipalities.time series for all the municipalities. Considering these time series as functionalConsidering these time series as functional data we can cluster them and obtain groups ofdata we can cluster them and obtain groups of municipalities, through a functional clustermunicipalities, through a functional cluster analysis where PAM algorithm is embeddedanalysis where PAM algorithm is embedded Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    38. 38. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Multi-pollutant zoningMulti-pollutant zoning (1)(1) As alternative technique, we explore theAs alternative technique, we explore the Functional Principal Component AnalysisFunctional Principal Component Analysis (FPCA) in its multivariate version, since we(FPCA) in its multivariate version, since we consider different pollutants taking intoconsider different pollutants taking into account their interactions. Then we applyaccount their interactions. Then we apply the PAM algorithm to the scores of thethe PAM algorithm to the scores of the principal components, obtaining groups ofprincipal components, obtaining groups of municipalities. In this case the medoids aremunicipalities. In this case the medoids are scores where the temporal component isscores where the temporal component is integrated outintegrated out Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    39. 39. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  The DifferenceThe Difference 1999 2009
    40. 40. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Air Quality PlanAir Quality Plan ……only using quality models we can take good plan with reasonableonly using quality models we can take good plan with reasonable scenario.scenario. Italy:Italy: national, regional, provincial & municipal plansnational, regional, provincial & municipal plans  Regional decision maker: … LV will be respected ? … role of local measures ?  Develop coherent evaluations, taking into account:  local features (sources, topography & land-use, meteorology…)  broader context Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    41. 41. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy] Regional AQ system Boundary conditions Meteo modelEmission manager Dispersion & chemistry Impacts Reference Inventory Regional plan Emission scenario Atmospheric simulation system Costs Emissions Atmospheric dispersion Health & env. impacts Enargy / ind. / agric. Projections Emission control RAINS-Italy RAIL Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    42. 42. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  MethodologyMethodology 1.1. Inventories harmonization:Inventories harmonization: IREA (Regional Emission Inventory)IREA (Regional Emission Inventory) vs. RAINS-Italy, for baseline yearvs. RAINS-Italy, for baseline year 2.2. Projected emission scenario:Projected emission scenario: RAINS-Italy CLE, downscaled atRAINS-Italy CLE, downscaled at municipality level using IREAmunicipality level using IREA 3.3. Regional Plan emission scenarios:Regional Plan emission scenarios: translation (at municipalitytranslation (at municipality level) of local measureslevel) of local measures 4.4. Impacts on concentrations:Impacts on concentrations: simulation through regional 3Dsimulation through regional 3D atmospheric modelling systematmospheric modelling system Ongoing process, promoted by the Ministry of the Environment, with the progressive involvement of Regional GovernmentsOngoing process, promoted by the Ministry of the Environment, with the progressive involvement of Regional Governments Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    43. 43. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Piemonte AQ Plan: measures at 2010  Heating • energy efficiency (new & renovated) • boilers: efficiency & emission limits • ban of dirtier fuels (coal and distillate oil) • incentives for solar heating for sanitary water • district heating expansion  Transport • whole region: progressive ban of the most polluting vehicles • “Plan Zones”: restricted traffic zones in municipalities > 10000 inh. • adoption of DPF (diesel particles filters) Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    44. 44. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Piemonte Case: Effects on emissions Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    45. 45. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Piemonte Case: Effects on emissions  Variations for “Plan 2010” scenarios respect to “Base 2005” (all categories) Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    46. 46. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Piemonte Case: Effects on emissions Detail on individual measures – Heating “Plan 2010” vs. “Reference 2010” variations, by measure (local measure) Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    47. 47. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Piemonte Case: Effects on emissions Detail on individual measures – Mobility “Plan 2010” vs. “Reference 2010” variations, by type (example) Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    48. 48. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Piemonte Case: Effects on concentration Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    49. 49. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Piemonte Case: Effects on concentration  NO2 concentrations, yearly averages  “Plan-R 2010” vs. “Baseline 2005” (CLE + local measures) Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    50. 50. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Piemonte Case: Effects on concentration  PM10 concentrations, yearly averages  “Plan-R 2010” vs. “Baseline 2005” (CLE + local measures) Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    51. 51. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Room for improvement …? (RAINS – technical measures)(RAINS – technical measures) Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    52. 52. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy]  Lessons learnedLessons learned …… implementing integrated N policies: difficulties & suggestionsimplementing integrated N policies: difficulties & suggestions There is room for local, coordinated policiesThere is room for local, coordinated policies …… supported by regional- and urban-scale analysessupported by regional- and urban-scale analyses (spatial details, hotspots)(spatial details, hotspots) …… linked to broader contextlinked to broader context …… multiple models: need of consistent tools & data - harmonizationmultiple models: need of consistent tools & data - harmonization Long-term perspectiveLong-term perspective (4/5 years…)(4/5 years…) Lack of multidisciplinary connectionsLack of multidisciplinary connections (e.g. mobility, agriculture)(e.g. mobility, agriculture) especially on “quantitative approaches”especially on “quantitative approaches” …… Italian peculiarity ?Italian peculiarity ? Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont
    53. 53. Workshop on the preparation of air quality [Ing. Giorgio Arduino, Reg. Piemonte, Italy] Thank YouThank You ForFor Your AttentionYour Attention Experiences in establishment of zones and agglomerations: PiedmontExperiences in establishment of zones and agglomerations: Piedmont

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