CONTRIBUCIÓN DE FUENTES A PM X URBANO. Xavier Querol, IDAEA-CSIC

Transcription

1 CONTRIBUCIÓN DE FUENTES A PM X URBANO Xavier Querol, IDAEA-CSIC

2 THE AIRUSE PROJECT AIMS Characterizing similarities & differences in PM sources & contributions across S-EU (5 cities) Once the main sources of PM1 and PM2.5 are identified, the strategic goal of the AIRUSE project is to develop, test and propose specific and non specific measures to abate urban ambient air PM in S.-EU, to meet AQ standards & to approach WHO guidelines. Specific PM mitigation measures Street washing & dust suppressants for road dust and deposited African dust Biomass burning Industrial emissions (channelled and fugitive) Strategies from other European countries (LEZ, eco-efficient vehicles, labelling, shipping, biomass burning )

3 AIRUSE MANAGING STRUCTURE Coordinating Beneficiary Project Manager Spain Associated Beneficiaries Leader B5 D5 Spain Leader B8 UK Leader B3 D2 Greece Leader B2 Italy Leader B4 Portugal Milan Italy

4 AIRUSE STRUCTURE: ACTIONS & TASKS ACTION A. Preparatory actions A.1 Authorities and stakeholders consultation ACTION B. Implementation actions B7. Developing & testing cost-effective PM measures & strategies B8. Applicability of selected measures from N to S Europe B1. Documentation of the current status B2. Harmonization and implementation of source apportionment using receptor modelling & determination of the impact of: B3. Natural sources B4. Biomass burning B5. Industrial sources B6. Traffic related sources Intensive additional work on inventories, emission chemical profiles, emission factors ACTION C. Implementation actions C1. Effectiveness of the project actions C2. Assessment of the socio-economic impact

5 Mg Mg B1: AQ TRENDS SPAIN µg/m SO Traffic Urban backgraound Industrial 3, µg/m 3 6 NO Traffic Urban backgraound Industrial , µg/m 3 12 NO 1 x Traffic Urban backgraound Industrial 8, µg/m 3 3, 2,5 2, 1,5 1, Regional Background (EMEP),5 Mean Sav, Nie, Peñ Bar, CdC, Viz, Cam, Tor, Zar, E SO 2 National Emissions 1.E+6 SO 2 (Mg) µg/m 3 6, 5, 4, 3, 2, Regional Background (EMEP) µg/m 3 1, 1, Media CdC, Viz,Tor, Sav, Nie Bar, Cam, Zar, Peñ Media CdC, Viz,Tor, Sav, Nie Bar, Cam, Zar, Peñ,, E Regional Background Urban Background Traffic Industrial Regional Background PM2.5 speciation 7, 6, 5, 4, 3, 2, 5E+5 NO x NO x (Mg) NO x National Emissions 8.E+5 6.E+5 4.E+5 2.E+5.E+ Industrial processes with combustion Power generation and transformation Other transport and mobile machinery A Coruña Vigo O Sabiñao Gijón Avilés Oviedo Peñausende Niembro Pamplona Bilbao Campisábalos Valladolid Madrid Cabo de Creus Zaragoza Montseny Barcelona El Torms Valencia L Hospitalet P. Mallorca 4E+5 3E+5 2E+5 1E+5 E+ Industrial processes with combustion Power generation and transformation Other transport and mobile machinery Road transport Barcarrota Zarra Sevilla Córdoba Granada Viznar Alicante Murcia Santa Cruz Las Palmas Querol et al., 214. Science of Total Environment

6 Time average map of SO 2 Column amount (PBL) (Dobson Units) NASA SO 2 OMI level 3. Plotted using the Giovanni online data system, developed and maintained by the NASA GES DISC

7 NASA NO 2 OMI level 3 Plotted using the Giovanni online data system, developed and maintained by the NASA GES DISC Mean annual tropospheric NO 2 column (clear, -3% cloud) (1 14 molec/cm 2 )

8 Mg Mg B1: AQ TRENDS SPAIN PM PM2.5 µg/m µg/m Traffic Urban background Industrial Mean µg/m µg/m Regional Background Regional Background 4 (EMEP) 5 (EMEP) Media Bar, CdC, Viz,Tor, Zar, Nie Cam, Sav, Peñ 2 Media Bar, CdC,Viz, Tor Cam, Sav, Nie, Zar, Peñ 3.5E E PM1 National PM1 Emissions (Mg) 3.E+4 2.5E+4 PM2.5 National PM2.5 Emissions (Mg) E+4 2.E+4 1.5E+4 1.E+4 5.E+3.E+ Industrial processes with combustion Agriculture and farming Other transport and mobile machinery Road transport Non industrial combustion E+4 1.5E+4 1.E+4 5.E+3.E+ Querol et al., 214. Science of Total Environment Industrial processes with combustion Other transport and mobile machinery Road transport Non industrial combustion

9 PM1 (µg/m 3 ) PM1 (µg/m 3 ) PM1 (µg/m 3 ) PM1 (µg/m 3 3 ) ) PM1 (µg/m 3 ) 3 ) 8 6 Annual Annual average mean PM1 PM1 Florence FI-AGGarea ANNUAL PM1 AVERAGES FI-AGG Annual Annual mean mean PM1 PM1 ATH-AGG ATH-AGG ATH-AGG ATH-GAA WHO -34% Annual mean PM1 POR-MA Florence_Bassi Florence_Bassi Florence_Gramsci Florence_Gramsci Florence_Boboli Florence_Boboli Florence_Mosse Florence_Mosse Signa Calenzano Signa boccaccio Calenzano giovanni 12 Scandicci Campi B. Calenzano boccaccio Sesto Calenzano giovanni Mean Campi Annual B. limit value Empoli Greve Incisa Montelupo Pontassieve Sesto Mean Annual Limit Value 1 POR-MA 2 WHO 1-32% Annual 25mean 26 PM1 27 MLN-AGG % MLN-AGG Agia Paraskevi Aristotelous Goudi Thrakomakedones Lykovrusi Marousi Piraeus Mean Annual limit limit value value WHO Francisco Sá Carneiro Sobreiras - Lordelo de Ouro Av Espinho 1 Anta - Espinho Augusto Gomes - Matosinhos D. Manuel II - Vermoim Gaia - Avintes VN Telha - Maia Custóias - Matosinhos Leça do Balio - Matosinhos Meco - Perafita Sra. Da Hora - Matosinhos Ermesinde - Valongo Mean Annual limit value 8-46% -45% 2 Annual mean PM1 BCN-MA WHO -32% Cantù Como centro Merate Busto Arsizio - Accam Gallarate San Lorenzo Meda Monza Macchiavelli Monza Parco Milano Senato Mean Annual limit value Cantù Como centro Merate Busto Arsizio - Accam Gallarate San Lorenzo Meda Monza Macchiavelli BCN-MA -32% València, WHO 4-5 febrero % Barcelona (c/ Lluís Solé Sabarís) Barcelona (Eixample) Barcelona (Gràcia - Sant Gervasi) i -49%

10 PORTO FLORENCE B2. HARMONIZED 213 PM1 & PM2.5 SOURCE APPORTIONMENT BARCELONA MILAN ATHENS UB UB PORTO FLORENCE TR UB MILAN ATHENS ATHENS SUB TR FLORENCE 147 PM1 samples 1116 PM2.5 samples

11 B2. HARMONIZATION & OBTENTION OF 213 PM1 & PM2.5 SOURCE APPORTIONMENT BCN-UB FI-UB MLN-UB ATH-SUB 1% 2% 2% 11% 4% 34% 14% 4% 23% 7% 31% 6% 1% 45% 2% 2% 61% 37% 31% Primary: 35% Secondary: Primary: 35% 65% Secondary: 65% Primary: 19% Secondary: Primary: 3% 81% Secondary: 7% 37% Primary: 32% Secondary: Primary: 32% 68% Secondary: 68% Primary: 18% Primary: Secondary: 18% 82% Secondary: 82% POR-TR ATH-TR 3% 11% 5% 22% 16% 27% 4% 37% Secondary organics Secondary inorganics Primary OM + EC Primary: Mineral dust Primary: Sea salt 46% Primary: 62% Secondary: 38% 29% Primary: 34% Secondary: 66% PM2.5

12 PM1 (annual mean) 1. Road Traffic is the main source contributing to PM1: 23-38% 1.1. Vehicle exhaust + traffic related NO 3 - are the main causes: 2-29% 1.2. Non-exhaust vehicle emissions are also relevant: 8-11% 2. Regional OC and/or SO 4 2- dominated pollution: 2-26% (POR-TR 1%) 3. Local dust : 9-19% 4. Biomass burning very relevant in POR & FI (14-16%), less in ATH (12%), negligible in BCN 5. Industry BCN 11%, 4-5%, ATH <1% 6. Non traffic-no % (2% POR) 7. Shipping 4-5% in coastal sites 8. African dust ATH-SUB 14%, 1-5% 9. Sea salt POR 13%, 4-8% 1. Anthropogenic dust (Local dust + Non exhaust) reaches 19-27% PM1 (days of exceedance) 24-45% 3-34% 18-29% BCN-ATH 11-3%, 2-6% POR & ATH-SUB 13-27%, 1-4% POR,FI (25-3%),ATH-TR11%, <1 BCN,ATH-SUB BCN 17%, <1-3% BCN, FI 7-9%, 1-2% POR,ATH-SUB, 22% ATH-TR 3-5% in coastal sites 1%, ATH-SUB 25-52%, ATH-TR 5% ATH-SUB 7%, 1-3% 11-33% PM2.5 (annual mean) 1. Road Traffic is the main source contributing to PM2.5: 22-39% 1.1. Vehicle exhaust + traffic related NO 3 - are the main causes: 11-34% 1.2. Non-exhaust vehicle emissions are also relevant: 5-9% (BCN&FI 1-2%) 2. Regional OC and/or SO 4 2- dominated pollution: 19-37% (POR 13%) 3. Local dust: POR 16%, 2-6% 4. Biomass burning very relevant in MLN, FI & POR (18-21%), less in ATH (11-19%), negligible in BCN 5. Industry 5-12%, ATH <1% 6. Non traffic-no 3-3-8% (POR 1%) 7. Shipping 5-7% in coastal sites 8. African dust: ATH 2-6%, <1% 9. Sea salt POR 5%, <1-3%, 1. Anthropogenic dust (Local dust + Non exhaust) reaches 1-21%, BCN 7%, FI 4% PM2.5 (days of PM1 exceedance) 28-42% (ATH-SUB 9%) 31-4% (ATH 11-19%) 1-9% BCN-MLN-ATH 11-24%, 2-6% POR 22%, 1-2%, ATH-TR <1% POR, FI <2%, MLN (26-33%), ATH-TR 16% BCN 18%, <1-3% BCN, FI, ATH & MLN 6-9% (1-3% POR ) 3-1% in coastal sites ATH-SUB 45%, ATH-TR 4%, 1% <1%-2% POR 15, 3-9%

13 B2. HARMONIZATION & OBTENTION OF 213 PM1 & PM2.5 SOURCE APPORTIONMENT ng/m PM2.5 Levoglucosan BCN-UB BCN-TRAFFPOR-TRAFF FI-UB MIL-UB ATH-SUB ATH-TRAFF PM2.5 K ng/m BCN-UB BCN-TRAFFPOR-TRAFF FI-UB MIL-UB ATH-SUB ATH-TRAFF

14 B4: BIOMASS BURNING PROFILES BIOFUELS AND APPLIANCES Biomass fuels: Based on forest inventories and information provided by the AIRUSE partners, wood species widely used as biofuels in residential combustion in Southern European Holm oak (Quercus ilex rotundifolia) (Fagus sylvatica) Black poplar (Populus nigra) Cork oak (Quercus suber ) Pine (Pinus pinaster) European beech Portuguese oak (Quercus faginea) (Quercus pyrenaica) Olive (Olea europea) Golden wattle Eucalypt (Acacia longifolia) (Eucalyptus globulus) Pyrenean oak agro-fuels Briquettes 4 types of pellets Olive pit Shell of pine nuts Almond shell

15 BB4: IOMASS BURNING PROFILES BIOFUELS AND APPLIANCES Biomass burning appliances Traditional brick fireplace Traditional cast iron wood stove Eco-labelled chimney-type wood stove Pellet stove

16 mg MJ -1 (dry basis) mg MJ -1 (dry basis) B4: PM EMISSION FACTORS x3 x12 x ENplus quality seal x5 x6 8 6 Fireplace Traditional woodstove Eco-labelled woodstove Pellet stove 4 2 Pellet - type I Pellet - type II Pellet - type III Pellet - type IV Olive Pit Shell of Pine Nuts Almond Shell 1 kg de biomasa corresponde aproximadamente a 18 MJ 5 mg MJ -1 in Denmark & Switzerland 35 mg MJ -1 wood fuels & 25 mg MJ -1 for pellets in Austria 27 mg MJ -1 in Germany

17 Standards need to be established in the EU for elemental composition of commercial wood pellets and chips to avoid the inclusion of extraneous materials. Only Germany has standards containing extensive trace element limits. B4: PM1 MASS FRACTIONS OF TRACE ELEMENTS (wt%) Pb Zn type I type II type III type IV Olive pit Shell of pine nuts Almond shell 1.81 type I type II type III type IV Olive pit Shell of pine nuts Almond shell Fe As type I type II 1.7 type III type IV.12 Olive pit.248 Shell of pine nuts bdl Almond shell type I type II.3 type III.22 type IV.1 bdl bdl Olive pit Shell of pine nuts Almond shell

18 B4: RECOMMENDATIONS ON BIOMASS BURNING Traditional residential combustion appliances, such as fireplaces and woodstoves, should be replaced by certified equipment rather than installing flue gas depollution technologies Emission requirements for the eco-labelling or certification of small-scale combustion appliances must be mandatory in all countries The market of firewood sales should be regulated; chemically treated material should not be allowed in any quality class of pellets; all pellets sold at the market must have quality certification. Also transport and storage should be regulated to control moisture

19 latitude B7: ROAD DUST LOADING IN EU 5 Road dust Loading mg/m rd longitude

20 B7: REMEDIATION MEASURES Preventive Reduce number of vehicles Reduce traffic speed Reduce HDV Reduce wear Mitigation Street washing (and sweeping) Calcium Magnesium Acetate (CMA) MgCl 2 Polymers CaCl 2 Porous asphalt.

21 B7: AIRUSE TESTS Road dust At typical urban road: Street cleaning CMA MgCl 2 At industrial paved road: Street cleaning CMA At unpaved road: Water flushing CMA Soil dust At urban park we tested nano-polymer

22 B7: URBAN ROAD (BARCELONA): STREET CLEANING PM1 (µg m -3 ) no-stc days StC days 9 Cleaning site µg m PM1 (µg m -3 ) no-stc days StC days Reference sites µg m -3 Local time Local time Reduction: 4-5 µg m -3 (7-1%)

23 B:7 URBAN ROAD (BARCELONA) Water flushing: 1L H 2 O/m 2 Dust suppressant: 2 g/m 2 of a solution 25%CMA or 2% MgCl 2 Dust Track, TEOM and GRIMM; High volume samplers PM1 (daily) High volume samplers PM2.5 (every third day). PM chemical characterization (ions, elements, OC and EC); Streaker for PM2.5 and PM2.5-1; Black Carbon (MAAP and mini-aeth); NOx, O 3 and SO 2 and meteo.

24 B7: URBAN ROAD (BARCELONA): CMA and MgCl 2

25 Emission factor Deposition > Emission B7: EFFECT OF PRECIPITATION/WASHING Deposition = Emission ddl dt Dep f ( DL) Time Time for emission recovery

26 Dust loadings (g m -2 ) DL (g m -2 ) B7: EFFECT OF PRECIPITATION/WASHING,8-2 Dust loadings (g ).8, ,6.6.6,5.5,4.4.4, ,2.2.1 Dust loadings DL=3.56E E-3 e -.87*t,1.1 R 2 =.99 Utrecht., t (hours after rain) t (hours after rain) Barcelona Utrecht t (hours after rain) Barcelona In 8 hours, 5% of dust is re-plenished In 24 hours, 99% of dust is re-plenished In 24 hours, 5% of dust is re-plenished In 72 hours, 99% of dust is re-plenished

27 B7: RECOMMENDATIONS ON ROAD DUST ABATEMENT Source Location Dust loading Road dust Soil dust Urban paved road Industrial paved road Industrial unpaved road 3-6 mg/m mg/m 2 infinite Public park infinite Measure Dosage PM1 Notes on reduction measurement 7-1% on Street 1 washing L/m 2 a daily mean kerbside CMA 15-2 g/m 2 Negligible kerbside MgCl g/m 2 Negligible kerbside Street washing CMA Street washing CMA Nanopolymer 27 L/m g/m 2 18% on a daily mean 8% on a daily mean >9% up kerbside kerbside 3.5 L/m 2 to 1 h downwind 1 Not g/m 2 observed downwind 3 L/m µg/m 3 Inside the park

28 REPORTS PRODUCED (OR TO BE PRODUCED) Action B8 Street cleaning Dust suppressants Low emission zones Electric, hybrid and gas vehicles Diesel car/fuel taxation Vehicle Eco-efficiency NOx reduction technologies applied to traffic Biomass burning abatement in Northern Europe Shipping abatement measures Interference and synergy of air quality and climate

29 ACKNOWLEDGEMENTS LIFE+ AIRUSE Spain MAGRAMA, GenCat, Barcelona and Madrid City Councils Italy ARPA-Lombardia, Regione Lombardia, Regional Government of Tuscany, ARPA Toscana Portugal Porto City Council, North Regional Coord. & DeveloP. Comm. (CCDR-N) Greece Ministry of Environment, Energy and Climate Change Spain M. Brritte Larka, A. Orio, M. Pallares, I. Hernández, A. Cristobal, E. Aulí Portugal C. Figueiredo (CCDR-N); J. Monjardino (CENSE, Universidade Nova de Lisboa) Italy F. Forni (Regione Toscana), Greece M. Lazaridis y Athina Progiou (Proyecto ACEPT AIR) GRACIAS POR SU ATENCIÓN!!! xavier.querol@idaea.csic.es