EXPERIMENTAL AND MODELLING STUDIES OF ULTRAFINE PARTICLE CONCENTRATIONS IN URBAN STREET AND BACKGROUND ENVIRONMENT

Transcription

1 EXPERIMENTAL AND MODELLING STUDIES OF ULTRAFINE PARTICLE CONCENTRATIONS IN URBAN STREET AND BACKGROUND ENVIRONMENT M. KETZEL 1,2,#, P. WÅHLIN 1, R. BERKOWICZ 1 and F. PALMGREN 1 1 National Environmental Research Institute, Roskilde, Denmark 2 Division of Nuclear Physics, Physics Dept., Lund University, Lund, Sweden # Corresponding author. mke@dmu.dk (M.Ketzel) Summary The presentation has two main parts focussing on a) results from ambient particle measurements and b) application of different air pollution models to estimate the particle concentration at kerbside and in the urban background. Measurements We reported previously on long term measurements of particle size distribution (size range 1-7nm) and PM1 at street and urban background location in Copenhagen (Ketzel et al., 23a). These measurements enable us to estimate vehicle emission factors. In addition we present here seasonal variations and correlation with meteorological parameters (e.g. temperature, wind speed, rain events) (Palmgren et al., 23). We show that we are able to fit the size distributions averaged separately for each hour of the week with 3 lognormal modes. The variation of these 3 modes together with CO and NOx measurements gives the basis for a factor analysis. As one possible solution we obtain 3 factors resembling the following profiles: Factor 1: Mode 1+2; NOx Factor 2: Mode 1+3; NOx Factor 3: - NOx; CO An interesting aspect is that the Factor 3 explains all the variation in CO (tracer for gasoline vehicles) but does not contain any ultrafine particles. That means that we can interpret our field measurements without gasoline particle emissions and only two different types of 'diesel factors'. We also report first results of a short term measuring campaign (6 weeks) conducted simultaneously at an urban background station in Copenhagen and two rural background locations ca. 3 km west and 6 km northeast of Copenhagen (Ketzel et al., 23b). These measurements allow for estimating the contribution from the city to the elevation of particle number concentration and PM1. Modelling In this study we are applying these emission factors together with a street pollution model OSPM (Berkowicz, 2b) to predict time series of particle number and NOx at street level. We show that an assumed temperature dependence of the particle emissions can improve the model results. The time scales for particle dynamic processes (e.g. coagulation, deposition, dilution) are estimated for urban street and background environment and discussed in their relevance for influencing the particle size distribution. In agreement with the literature (Pohjola et al., 23; Vignati et al., 1999) we conclude that coagulation is too slow to alter the size distribution in the exhaust plume and dilution is the dominating process. A similar conclusion can be drawn for the street scale. In a more confined environment as e.g. a road tunnel the removal processes coagulation and deposition might play a important role (Gidhagen et al., 23). First model results for the urban scale using a simple plume approach for the pollutant dispersion(berkowicz, 2a) in connection with the aerosol model AERO3 (Vignati, 1999) show that 1) the coagulation and deposition account for ca. 2% loss of particles in the urban background compared to street level and 2) the size dependent removal lead to a slight increase in max - diameter of the particle size distriution.

2 REFERENCES Berkowicz, R. (2a): A simple model for urban background pollution. Environmental Monitoring and Assessment 65, Berkowicz, R. (2b): OSPM - A parameterised street pollution model. Environmental Monitoring and Assessment 65, Gidhagen, L., Johansson, C., Ström, J., Kristensson, A., Swietlicki, E., Pirjola, L., and Hansson, H.-C. (23): Model simulation of ultrafine particles inside a road tunnel. Atmospheric Environment 37, Ketzel, M., Wåhlin, P., Berkowicz, R., and Palmgren, F. (23a): Particle and trace gas emission factors under urban driving conditions in Copenhagen based on street and roof-level observations. Atmospheric Environment 37, Ketzel, M., Wåhlin, P., Kristensson, A., Swietlicki, E., Berkowicz, R., Nielsen, O. J., and Palmgren, F. (23b): Particle size distribution and particle mass measuremnts at urban, near-city and rural levl in the Copenhagen area and Southern Sweden. Atmos.Chem.Phys.Discuss.(submitted for publication). Palmgren, F., Wåhlin, P., Berkowicz, R., Ketzel, M., Illerup, J. B., Nielsen, M., Winther, M., Glasius, M., and Jensen, B. (23): Aerosols in Danish Air (AIDA), Mid-term report National Environmental Research Institute, Roskilde, Denmark. NERI Technical Report No. 45. Pohjola, M., Pirjola, L., Kukkonen, J., and Kulmala, M. (23): Modelling of the influence of aerosol processes for the dispersion of vehicular exhaust plumes in street environment. Atmospheric Environment 37, Vignati, E. (1999): Modelling Interactions between Aerosols and Gaseous Compounds in the Polluted Marine Atmosphere. PhD Thesis. Risø National Laboratory, Denmark, Report: Risø-R-1163(EN). Vignati, E., Berkowicz, R., Palmgren, F., Lyck, E., and Hummelshoj, P. (1999): Transformation of size distributions of emitted particles in streets. The Science of The Total Environment 235,

3 Experimental and Modelling Studies of Ultrafine Particle Concentrations in Urban Street and Background Environment 7th ETH Conference 23 Matthias Ketzel, Peter Wåhlin, Ruwim Berkowicz and Finn Palmgren National Environmental Research Institute, Roskilde, Denmark Funding: Danish EPA Outline of the presentation Objective Particle measurements in Copenhagen (follow up of last years presentation) Dispersion modelling time scale analysis kerbside modelling urban scale modelling

4 Objective ambient measurements of nanoparticles real world particle emission factors + size distribution separated for vehicle classes (gasoline/diesel; LD/HD) analyse dependence on meteorological parameters include particles in our dispersion models forecast of pollution levels scenario calculations... Measuring station at Jagtvej, Copenhagen 26 veh./day; 6-8% HDV Danish diesel: 5 ppms; gasoline 6-7 ppm S Pair of stations: kerbside -- urban background HCØ (background) particles trace gas meteorology DMPS 1-7nm CO wind direction (UCPC > 3nm) NO wind speed PM1 - Teom NOx temperature O3 RH global radiation Jagtvej (street canyon) particles trace gas div DMPS 1-7nm CO traffic counts PM1 - Teom NO rain PM1 - filter packs NOx

5 Average weekly profile of size distribution, Difference Street - background periode 15-5 to ca. 12 weeks of data (1h averages) constant mode diameter during day diesel gasoline night time shift to smaller sizes diesel taxi + oxicat. nucleation?!?? Dp in nm Ratio CO/NOx (ppb/ppb) RatioCO/NOx working days Saturdays Sundays dn/dlog Dp (cm-3) time ( hour of the week ) Ketzel et al. 23 Atmos. Env. 37, 2735 Fitting of the particle size distribution with 3 log-normal modes Day: 5 ;Hour: 7 Measured Sum Fit Mode1: 63.6 nm, GSD= 1.97 Mode2: 23.9 nm, GSD= 1.57 Mode3: 11.7 nm, GSD= Day: 5 ;Hour: 22 Measured Sum Fit Mode1: 63.6 nm Mode2: 23.9 nm Mode3: 11.7 nm Day: 6 ;Hour: 4 Measured Sum Fit Mode1: 63.6 nm, GSD= 1.97 Mode2: 23.9 nm, GSD= 1.57 Mode3: 11.7 nm, GSD=

6 Factor Analysis Average weekly variation of NOx CO Strength of Mode 1-3 (all corrected for background!) Possible Solution: Factor 1: Mode 1+2; NOx Factor 2: Mode 1+3; NOx Factor 3: - NOx; CO (dn/dlogd)/[no x ] (cm -3 /ppb) Source Profiles Factor 1 (normal diesel) Factor 2 (modern diesel; Taxi) Dp in nm Sum Fit Mode1: 63.6 nm, GSD= 1.97 Mode2: 23.9 nm, GSD= 1.57 Mode3: 11.7 nm, GSD= 1.42 Sum Fit Mode1: 63.6 nm, GSD= 1.97 Mode2: 23.9 nm, GSD= 1.57 Mode3: 11.7 nm, GSD= 1.42 Temperature variations - particle number kerbside (Jagtvej) lower particle / NOx ratio at lower temperatures ToN / NOx [pt/cm 3 /ppb] y = x R 2 = Temp [ o C] (dn/dlogd)/[no x ] (cm -3 /ppb) night traffic low temp. C < t < 5 C 5 C < t < 1 C 1 C < t < 15 C 15 C < t < 2 C 2 C < t by P.Wåhlin Ratios between particle number concentration (versus size) d (nm) and the NOx concentration at HCAB (street station).

7 Conclusions - ambient measurements: fleet emission factors could be estimated (last years talk) 3 - modal structure of the size distribution possible factor solution: 2 factors (NOx + particles) 1 factor (NOx + CO, no particles) temperature dependence Modelling of ambient ultrafine particles Which particle transformation processes are relevant at the different scales?

8 Time scales for several processes Time scale in s 1.E+6 1.E+5 1.E+4 1.E+3 1.E+2 1.E+1 1.E+ 1.E-1 background kerbside road tunnel Coagulation monodisperse Coagulation polydisperse Dilution Deposition 1.E-2 exhaust plume 1.E-3 1.E+3 1.E+4 1.E+5 1.E+6 1.E+7 1.E+8 1.E+9 Gidhagen et al. poster here Concentration in #/cm3 Gidhagen et al % loss for Dp < 1nm - 41% loss for Dp 1-29nm Vignati et al Pohjola et al. 23 : -no effect of coag. Modelling the dilution at kebside Operational Street Pollution Model (OSPM); Berkowicz et al Roof level wind Background pollution Recirculating air Leeward side Direct plume Windward side C = F(wind direction, wind speed, vehicle speed...) * Q [pt/km/s]

9 25 OSPM and emission factors from inverse modelling Modelling at kebside for NOx and total particle number inert particles (no particle dynamics) NOx_Str_Imod cnox_str_obs_2 background subtracted 2 15 NOx_Str_Imod Linear (NOx_Str_Imod) modelled R 2 =.72 1: ToN_mod Linear (ToN_mod) ToN_mod ToNdiff_obs 7 R 2 =.64 measured 1:1 y =.68 R class=-7 9 class=-2 8 class=2 class=7 7 class=12 class=17 6 class=23 Linear (class=12) 5 Linear (class=17) Linear (class=7) 4 Temperaturedependent Emissions R 2 =.64 y =.736x R 2 =.686 y =.6197x R 2 =.6998 y =.5311x R 2 =.62 3 class=-7 1 class=-2 2 class=2 class=7 1 8 class=12 class= class=23 12 Linear (class=12) -1 6 Linear (class=17) Linear (class=7) R 2 =.67 y =.6721x y = y =.661x.6615x R 2 2 = R 2 = E(T) = E(15C)*[ (T-15C)] E()/E(15) ~ 15%

10 Measurements at urban, near-city and rural level Note on... Background X X Lille Valby X dn/dlogdp [#/cm 3 ] HCOE Vavihill JGTV_21 HCOE_21 HCOE_22 LVBY_22 VVHL_ Diameter [nm] Modelling of the urban background plume model for vertical dispersion background from measurements emission factor + size distrib. from kerbside measurements sectional model for particle dynamics including processes modelled: background emission vertical dilution deposition coagulation dn/dlogdp [cm -3 ] 1E+4 8E+3 6E+3 4E+3 shift of max. due to size dependent removal 2% removal LVBY near-city no removal processes Deposition not Coag Coag. + Deposition 2E+3 E Dp [nm]

11 Conclusions - modelling: street level coagulation is too slow to alter the size distribution dilution is the dominant process at street level OSPM (without particle dynamics) can be used also for particles temperature dependent e-factors increase correlation observed vs. modelled results urban scale coagulation and deposition account for ca. 2% loss of particles size dependent removal leads to a slight increase in max - diameter