History and Perspective of Air Quality in Milan and the Po Valley: Scientific and Management Challenges

History and Perspective of Air Quality in Milan and the Po Valley: Scientific and Management Challenges

History and perspective of air quality in Milan and the Po Valley: scientific and management challenges Guido Lanzani [email protected] Head of Air Quality Unit – Environmental Monitoring Area ARPA Lombardia Sandro Finardi [email protected] ARIANET Gian Luca Gurrieri [email protected] Head of Air Quality, Climate, Environ. sustainability Unit Lombardia Region 10 th International Conference on Air Quality: Science and application Milano March 15°, 2016 Milano and Lombardia: Where and how many Lombardia • Inhabitants: 9,9 milion Region • Population density: 419inab/km2 Milan • Inhabitants: 3,6 milion conurbation • Population density: 3.141inab/km2 – Po Valley: closed by mountains exceeding 2500 m a.s.l. on three sides – Meteorological conditions often adverse to air pollution dispersion History and perspective of air quality in Milan and the Po Valley – Important regional background (old and secondary). 2 Guido Lanzani – Sandro Finardi - Gian Luca Gurrieri Milano March 15 °, 2016 Meteorological conditions often adverse to air pollution dispersion Lack in wind Lack in wind comparisonFrequent 20 years very stable annualcomparison averagethermal wind 20 conditions years annual average wind Milano - Linate December 2015 Monthly mean temperature and humidity at 12:00 GMT Frequent very stable thermal conditions MI-Linate December 2015 Monthly mean temperature and History and perspective of air quality humidity at 12:00 GMT in Milan and the Po Valley 3 Guido Lanzani – Sandro Finardi - Gian Luca Gurrieri Milano March 15 °, 2016 Meteorological conditions often adverse to air pollution dispersion Lack in wind comparison 20 years annual average wind Frequent very stable thermal conditions MI-Linate December 2015 Monthly mean temperature and History and perspective of air quality humidity at 12:00 GMT in Milan and the Po Valley 4 Guido Lanzani – Sandro Finardi - Gian Luca Gurrieri Milano March 15 °, 2016 Air Quality Concentrations are decreasing but: • Widespread exceedances of PM10 daily limit (50 ug/m3) (80-100 every year) • NO2 annual limit exceedances, especially in traffic stations (annual mean in city from 39 to 62 µg/m3) • B(a)P standard non achieved where wood burning is more diffuse ( outside downtown) • Widespread exceedances of both health and vegetation Ozone protection standards (above) 5 Annual mean PM2.5 2013 Po Valley from 2015 EEA Air Quality Report Po Valley In Po Valley PM2.5 concentrations are often above 25 ug/m3 and don’t show important differences among type of stations 6 A (quite) common winter day PM10 daily concentration ≈ 500 km Limito (great Ponti (rural Milan): bck): 126 µg/m3 Venice: 123 µg/m3 158 µg/m3 Pavia: Mantova: 131 Torino: 156 µg/m3 µg/m3 132 µg/m3 Air quality data sharing PM10 daily concentrations are very similar in the whole Po Valley, platform /thanks to ARPA Emilia Romagna Piemonte, Liguria, Trentino,7 also in suburban and rural background stations Veneto, Friuli Venezia Giulia 93.2 percentile of O3 maximum daily 8-hours mean in 2013 Po Valley from 2015 EEA Air Quality Report In Po Valley frequent and widespread exceedances of health and Vegetation protection standards are registered 8 Milan PM composition Urban background station annual average PM10 PM2.5 from AIRUSE LIFE+ project 9 Milan PM composition Urban background station annual average PM10 PM2.5 from AIRUSE LIFE+ project – The scale of secondary PM is the whole basin – Local actions are not very effective – It is necessary to limit precursors emissions 10 – Often difficult to be modelled Lombardia Region Emission Inventory 2012 Sector NOx NH 3 PM10 CO 2eq 97% Energy production and refineries 6.2% 1.5% 18% from Residental combustion 10% 0.2% 45% 24% wood Industrial combustion 15% 0.5% 4.3% 12% Production processes 2.2% 4.9% 5.6% Extracton and distribution of fuels 2.7% Solven use 0.1% 4.0% 3.0% Road Transport 52% 1.1% 25% 23% Other mobile sources 11% 0.00% 3.0% 1.9% Waste treatment and disposal 2.9% 0.5% 0.4% 4.5% Agriculture 0.7% 98% 6.7% 11% Other sources and sinks 0.1% 5.9% -6.0% Fonte: INEMAR - ARPA Lombardia(2015), INEMAR, Inventario Emissioni in Atmosfera: emissioni in Regione Lombardia nell'anno 2012 – dati finali. ARPA Lombardia Settore Monitoraggi Ambientali. 11 Primary PM10 emissions by fuel (tons/year) 45% 14% 13% 22% 22% 21% 12 Emissions comparison Comparison SO2 NOx CO NH3 PM10 PM2.5 CO2 eq Lombardia - per capita -78% -29% -32% 35% -29% -21% -9% UE27 average Lombardia - per GDP -82% -42% -45% 11% -42% -35% -25% UE27 average Sources EU-27 Emissions http://www.ceip.at/webdab-emission-database/officially-reported-emission-data/ GHG EU-27 emissions http://www.eea.europa.eu/data-and-maps/data/data-viewers/greenhouse-gases-viewer GDP EU-27 http://epp.eurostat.ec.europa.eu/portal/page/portal/statistics/search_database http://epp.eurostat.ec.europa.eu/tgm/table.do?tab=table&language=en&pcode=tps0000 EU-27 population 1&tableSelection=1&footnotes=yes&labeling=labels&plugin=1 13 Air Quality modelling in Po Valley and Lombardia Region • Many different air quality modelling studies have been dedicated / included Po Valley: – Among those performed in the last decade : Thunis et al., Atm. Env., 2007; Vautard et al., Atm. Env., 2007; Angelino et al., Env. Model. Assess., 2008; Carnevale et al., Env. Model. Assess., 2008; Silibello et al., Env. Model. Soft., 2008; de Meij et al., Atm. Env., 2009; Lonati et al., Atmos. Res. 2010; Pernigotti et al., Atm. Env., 2012; Mircea et al., Atm. Env., 2014; Finardi et al., Urb. Climate, 2014; Mircea et al., AAQM, 2016 – Model intercomparisons focused on or including Po Valley (CityDelta, POMI, EuroDelta,…) – EU and national projects including Po Valley (GEMS/MACC, MEGAPOLI, CityZen, MINNI...) 14 Air Quality modelling in Po Valley and Lombardia Region – PM often underestimated , in particular during winter, despite FromFrom Pernigotti Pernigotti et et al., al., 2012 2012 broad spectrum of models and different emission inventories. – Possible reasons – meteorological modelling: – Overestimation of wind speed and atmospheric dispersion, – Poor performance of surface/boundary layer turbulence parametrizations in From Lonati et al., 2010 low wind conditions, – air quality modelling: – coarse resolution – inadequate treatment of the formation of secondary organic and inorganic aerosol, – emission inventories: 15 underestimated some activity sectors Air Quality modelling in Po Valley and Lombardia Region – PM often underestimated , in particular during winter, despite From Pernigotti et al., 2012 broad spectrum of models and different emission inventories. – Possible reasons – meteorological modelling: – Overestimation of wind speed and atmospheric dispersion, – Poor performance of surface/boundary layer turbulence parametrizations in From Lonati et al., 2010 low wind conditions, – air quality modelling: – coarse resolution – inadequate treatment of the formation of secondary organic and inorganic aerosol, – emission inventories: 16 underestimated some activity sectors Local inventory, high res. and diagnostic meteorology improve results for PM2.5 and PM components 20 km PM10PM104 km PM10 • Increasing resolution:20 km from 20 PM104 km PM10 to 4 km grid size 2013 2014 Fract. Bias PM10 -0,09 -0,02 MINNI PROJECT Mircea et al (AAQR, in press) Impact of Grid Resolution on Fract. Bias PM2.5 0,11 0,17 Aerosol Predictions: A Case Study over Italy • Grid size 4 km • Diagnostic meteorology reduced wind overestimation • Local bottom-up high resolution inventory From: C. Colombi, E. Peroni et al EAC2015 17 Local inventory, high res. and diagnostic meteorology improve results for PM2.5 and PM components 20 km PM10PM104 km PM10 • Increasing resolution: from 20 to 4 km grid size MINNI PROJECT Mircea et al (AAQR, in press) Impact of Grid Resolution on Aerosol Predictions: A Case Study over Italy • Grid size 4 km • Diagnostic meteorology reduced wind overestimation • Local bottom-up high resolution inventory From: C. Colombi, E. Peroni et al EAC2015 18 Models are a key instrument in supporting policy development and enforcement Examples – Scenario studies supporting Air quality plan – Ammonia / NOx emissions reduction influence over the Po Valley: • Not obious considering what is the limiting factor • Agriculture Stakeholders produced autonomous evaluations PM2.5 Scenario -25.0% NH 3 From Angelino E. et al., Ammonia and Nitrogen emissions reduction influence on air quality over the Po Valley 19 Air Quality Conference 2014 PRIA: Regional plan of actions on air quality • Big LEZ: limitations up to euro 3 diesel cars TRANSPORT AND • Area C in Milan centre MOBILITY • Bikes and car sharing 40 measures • 2 new underground lines • Highway speed limits reduction (under study) • Promotion of energy efficiency and rational STATIONARY use of energy SOURCES • Wood combustion rules and limitations 37 measures • Industrial plants and waste treatment: BAT and limitations to resettle of new plants AGRICULTURAL AND BREEDING • Anaerobic digestion of manure and direct SECTOR injection in the field 14 measures 20 examples Conclusions • Despite the improvements, in Lombardia and Po Valley air quality is still poor, above all for PM and ozone • Orographic and meteorological condition play a crucial role although emissions are not higher than in other developed areas • Secondary PM is prevalent on primary one; to obtain improvements it is necessary to act both on primary and precursors pollutant emissions on the whole Po Valley (500 km long) • Traffic, wood burning, agriculture and industry all must be considered in policies against air pollution • In the past PM was often underestimated by air quality and scenario studies in Po Valley • Air quality modelling shows important improvements and it is an important tools in evaluating the results of policies • Air quality plan define a path for improvement even if actions are necessary at all the levels: local, regional, national, European 21 Thank You for Your attention.

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