Street emission ceilings (SEC) project

Transcription

1 Street emission ceilings (SEC) project Objectives: to develop a method for determining the needed emission reductions in hot spots (i.e. streets) to reach certain AQ thresholds, on top of Europe-wide abatement measures. to be used by local authorities, to get overview of AQ near main road system, and to set SECs for individual streets. to be used in IAM for CAFE programme, to evaluate need for additional local measures,and as a part of the basis for cost calculations and optimisation.

2 Pollutant concentrations at street hot spots Sum of contributions from regional and urban scales + the street traffic s own contribution What does the hot-spots mean in terms of contribution to population exposure - in a city, or Europe-wide? - it is the high end of the exposure distribution - only few people exposed? How will existing and future policies (e.g. CAFE scenarios) affect the hot-spot contribution to population exposure (and to effects)? Will local measures be necessary in addition?

3 The SEC typology AUT / LHTEE Illustration of typology City typology defining f(pop) Urban background concentration Urban background concentrations Population Type C1a Type C1b Type C2a Type C2b Type C3a Type C3b Type C4a Type C4b Type C5a Type C5b Type C6a Type C6b Street typology defining g(emi). Street concentration. Street concentrations Type S1a Type S1b Type S2a Type S2b Type S3a Type S3b Type S4a Type S4b Brussels, 5 May 4 8 Street emission

4 Street types in the SEC typology Geometry/driving pattern Urban motorway (4 combinations) Geometry parameter % trucks Canyon width Driving pattern z =.1m 7%/15% - km/h Wind speed Fleet age Distance 2) 25m; m Urban non-canyon street (4 combinations) z =1m 7%/15% - 44km/h Coupled Coupled m; to EU to EU 4m region region Canyon (4 15m 5m H=15m 7%/15% 44km/h combinations) 4m 15m 1) In addition the age of the fleet and the average meteo wind speed has to be taken, dependent on the EU region. This needs to be defined later, consistent with the regions chosen in City-Delta. 2) The lower distance should not be combined with unrealistically high traffic intensities. Additional parametrics: Typical / unfavourable streets Annual average and high percentiles

5 Relationships between traffic flow and concentrations for SEC street types using the CAR model as example, Dutch fleet and meteo N2 annual mean (ug/m3) PM annual mean concentration - local contribution Traffic intensity (veh/day) Motorw ay 1 Motorw ay 2 Motorw ay 3 Motorw ay 4 Motorw ay 5 Urban non-canyon 1 Urban non-canyon 2 Urban non-canyon 3 Urban non-canyon 4 Canyon 1 Canyon 2 Canyon 3 (ug/m3) Traffic intensity (veh/day) Motorway 1 Motorway 2 Motorway 3 Motorway 4 Urban non-canyon 1 Urban non-canyon 2 Urban non-canyon 3 Urban non-canyon 4 Canyon 1 Canyon 2 Canyon 3 Canyon 4

6 Marylebone Road, London Analysis of continuous monitoring data at station pairs: - delta (street-ub) - delta ratios (e.g. dpm 2.5 /dno x ) for: -workday -weekend -summer -winter Delta, workingday, winter PM PM2.5 NO2 NOx/ Delta, weekend, winter PM PM2.5 NO2 NOx/ Delta, workingday, summer PM PM2.5 NO2 NOx/ Delta ratio relative to NOx PM PM2.5 NO Delta ratio relative to Nox PM PM2.5 NO Delta ratio relative to NOx PM PM2.5 NO Delta, weekend, summer PM PM2.5 NO2 NOx/ Delta ratio relative to NOx PM PM2.5 NO

7 Marylebone Rd London 6 5 Delta, workingday, winter PM PM2.5 NO2 NOx/ workdays, winter 4 3 Delta ratio relative to NOx PM PM2.5 NO

8 Marylebone Road, London.25 PM2.5/NOx PM/NOx NO2/NOx Delta ratios. Summer Winter Summe Winter Summer Winter - Marylebone Rd, London Frankfurter Allee, Berlin Frankfurther Allee, Berlin.6 Red: workdays.5 Summer PM 2.5 /NO x Winter PM /NO x NO 2 /NO x Summer Winter Summer Winter Blue: weekend days

9 Marylebone Road, London.25 PM2.5/NOx PM/NOx NO2/NOx Delta ratios. Summer Winter Summe Winter Summer Winter - Marylebone Rd, London Hornsgatan, Stockholm Hornsgatan, Stockholm,45 Red: workdays Blue: weekend days,4,35,3 Summer PM 2.5 /NO x Winter PM /NO x Summer Winter,36 NO 2 /NO x Summer Winter,25,251,249,,15,2,151,165,,98,78,5,3,23,4,44,

10 AUT / LHTEE Interpretation via street emission estimates Calculation of emissions for CO, NO x, using COPERT 3 methodology, taking into account: Traffic volume and speed Fleet composition (% of HDV) Road characteristics Classification using TRENDS model results. Sector Subsector Tech January Heavy Duty Vehicles Gasoline >3,5 t Conventional Heavy Duty Vehicles Diesel 3,5-7,5 t Conventional 1246 Heavy Duty Vehicles Diesel 3,5-7,5 t Euro I - 91/542/EEC Stage I 2882 Heavy Duty Vehicles Diesel 3,5-7,5 t Euro II - 91/542/EEC Stage II 4126 Heavy Duty Vehicles Diesel 3,5-7,5 t Euro III - Standards Heavy Duty Vehicles Diesel 7,5-16 t Conventional 1363 Heavy Duty Vehicles Diesel 7,5-16 t Euro I - 91/542/EEC Stage I 3166 Heavy Duty Vehicles Diesel 7,5-16 t Euro II - 91/542/EEC Stage II 4533 Heavy Duty Vehicles Diesel 7,5-16 t Euro III - Standards Buses - Coaches Urban Buses Conventional 6461 Buses - Coaches Urban Buses Euro I - 91/542/EEC Stage I 63 Buses - Coaches Urban Buses Euro II - 91/542/EEC Stage II 819 Buses - Coaches Urban Buses Euro III - Standards Buses - Coaches Urban Buses Euro IV - 5 Standards Buses - Coaches Urban Buses Euro V - 8 Standards Buses - Coaches Coaches Conventional 1615 Buses - Coaches Coaches Euro I - 91/542/EEC Stage I 158 Buses - Coaches Coaches Euro II - 91/542/EEC Stage II 5 Buses - Coaches Coaches Euro III - Standards Only hot emissions are assumed as the cold start effect is assumed to be negligible in specific street canyons. Brussels, 5 May 4

11 Marylebone road, London AUT / LHTEE PM 2.5 /NO x ratios for monthly and hourly data PM2.5/NOx.3 PM2.5/NOx JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Emission ratios ratios Emission ratios ratios Brussels, 5 May 4

12 Hornsgatan, Stockholm AUT / LHTEE PM 2.5 /NO x ratios for monthly and hourly data PM 2.5 /NO x.4.3 PM 2.5 /NO x JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC Emission ratios ratios Emission ratios ratios Brussels, 5 May 4

13 Testing of models, Frankfurter Allee,, 2 concentration (µg/m 3 ) NO hours concentration 3) (µg/m NO x hours - OSPM - SEP_SCAM SEP_SCAM OSPM monitoring background 5 PM SEP_SCAM OSPM monitoring background 1.2 CO 4 1. concentration (µg/m 3 ) 3 concentration (mg/m 3 ) hours SEP_SCAM OSPM monitoring background hours SEP_SCAM OSPM monitoring background

14 Contribution to CAFE Integrated assessment CAFE IA methodology: RAINS model + CITY-DELTA Alternative: EMEP + urban modelling (e.g. OFIS) Additional hot-spot contribution: SEC methodology EMEP + OFIS + SEC hot-spot to be applied at cities of the MERLIN project, and possibly CITY-DELTA cities

15 Short-term effort to provide input to the CAFE Thematic strategy: Select a small number of real or model streets Place them in cities in different European regions - different fleet characteristics - different meteo regimes Calculate hot-spot contributions OSPM/CAR/. - for baseline scenarios - for CAFE scenarios Add rural/urban background (from RAINS/CD or EMEP/OFIS) Estimate added population exposure from hot-spots - use street/traffic statistics from European cities