An new emission model for re-suspension of particles along roads

Transcription

1 An new emission model or re-suspension o particles along roads Gunnar Omstedt *, Björn Bringelt and Christer Johansson ** * Swedish Meteorological and Hydrological Institute ** ITM Air Pollution Laboratory,Stockholm University introduction description o the model measurements results sensitivity analysis conclusions Introduction HORNSGATAN SVEAVÄGEN MADRID ESSINGELEDEN PESCARA NORRLANDSG MADRID PRAHA PRAHA PRAHA PRAHA VA LHA LLAVÄGEN LISBOA BRATISLAVA MADRID E4 SOLLENTUNA MADRID BERLIN ROSLAGSVÄGEN MADRID MADRID BERLIN PRAHA ZÜRICH BERLIN DARMSTADT LO NDO N PRAHA MÏNCHEN MÏNCHEN MÏNCHEN BREMEN ZÜRICH MÏNCHEN MÏNCHEN LO NDO N CHARLEROI GLASGOW HELSINKI LO NDO N LO NDO N LO NDO N UG/M Measurements rom 19 countries in Europe (including more than 7 measurement sites) o PM1 halter as 9-percentiles(AirBase CAFE-PM,23)

2 Measured concentrations o PM1 at Hornsgatan presented as running monthly average. Red line is street level and blue line is roo level measurements. Model evaluations are done or the year Model description e tot = e direct + e re suspension Processes Emissionsactor(mg/vkm) Exhaust pipe 2 Tyre and brake wear 1 Road wear 1 Re-suspension (dry conditions) 1-1 Winter e re suspension = q * d * e w int er, PM ( dust) re re suspension re summer Summer e * e, ( dust) = q PM q is the source strength or re-suspension which is related to the moister amount o the dust on the street surace d is the amount o dust on the street e re ( dust) is a reerence emission actor, PM

3 Model description e ( C ( C C PM1 PM1 re street roo, PM1 = e, NOx NOx NOx street Croo ) ) the tracer method e(dust) mg/km - mätdata Jan 2-Mar 1-May 3-Jun 29-Aug 28-Oct 27-Dec Model description- basic assumptions d is the dust depot (relative units) d( d) dt = So d Si d Sources Sanding/salting Traic related road wear Sinks Re-suspension Run-o with precipitation g (mm) is the moister amount on the surace d( g) dt = So g Si g Sources Precipitation Sinks Run-o Evaporation

4 Model description- the q parameter g (mm) is the moister amount on the surace g = min( 1., g + rr) * gred rr is hourly precipitation gred is hourly reduction actor or g due to evaporation gred = exp( k * E p ) E p is evaporation; k empirical actor ound to be k=.75 obtained by solving the budget equation: dg E p ( m = g ) dt g m where g is maximum moisture amount and (m) is evaporation rate when g=gm. m E p Model description- the q parameter E p R = 36*( n ρc ra + e γ γ L(1 + ) ra γ p ) R n is net radiation, r a aeodynamic resistance e the saturated vapour pressure deicit q = 1.93* g q is the source strength or re-suspension

5 Model description- the d parameter, sources a) sanding/salting i we have no data on sanding/salting then we assume that sanding/ salting occurs during days with slippery conditions anskid = anskid +1/ nanskid anskid is the accumulated number o days with sanding/salting during the current winter season b) action by studded tyres tyre = tyre + k t * a dubb studded tyres tyre is the ratio o accumulated depot o material, released by riction between studded tyres and pavement, to the highest depot at the end o the winter season a dubb is the share o studded tyres k t is an empirical actor Jan 1-Apr 3-Jun 28-Sep 27-Dec 9 Model description- the d parameter, sinks a) re-suspension = 1 decay* susp q susp is the relative hourly decay o the dust depot due to re-suspension decay is an empirical parameter b) run-o r i i = max(( g + rr)* E p rr < 2 rr [ 2,1] r is the hourly dust depot decay actor due to run-o r = 1. r = 1.5*( r 2) /( r 2) i rr > 1 r =.95 For every hour anskid and tyre are reduced due to re-suspension and run-o anskid = anskid * r * tyre = tyre * r * susp 1.,) susp r is the hourly water runo max

6 Model description- the d parameter d = resuspα * tyre + resuspβ * anskid resuspα is the share o tyre and road particles in the total road dust depot resuspβ is corresponding share or sand/salt particles d relative units a Model description tyre d anskid.2 q relative units 1-Jan 31-Jan 1-Mar 31-Mar 3-Apr index or rain b 12 1-Jan 31-Jan 1-Mar 31-Mar 3-Apr 3-May e resuspension ( mg/km) 8 4 c 1-Jan 31-Jan 1-Mar 31-Mar 3-Apr 3-May

7 Hornsgatan,, Stockholm 4 v/d Figur 5. Hornsgatan monitoring station North (N) and South (S). The houses are o similar height, 24 m, total street width is 24 m. Uphill slope westward is 2.3% (Gidhagen et al.,24). Measurements o PM1 are only done on the north side ( NOx Hornsgatan year 2 NOx model- OSPM averagex=155.3 averagey=132.5 r= NOx street -NOx roo Comparison o measured and modelled concentrations o NOx

8 PM1 Hornsgatan year 2 PM1 street -PM1 roo Hornsgatan 2 daily mean measurments model average measurments=24.9 average model=24. r=.77 1-Jan 1-Mar 3-Apr 29-Jun 28-Aug 27-Oct 26-Dec Comparison o measured and modelled concentrations o PM PM1 Hornsgatan year PM1 model measuredbackground model yearly mean percentile percentile PM1 measured-background As the last igure but sorted in size

9 PM 2.5 Hornsgatan year 2 PM2.5 street -PM2.5 roo Hornsgatan 2 daily mean measurments model average measurments=5.4 average model=5.5 r=.72 1-Jan 1-Mar 3-Apr 29-Jun 28-Aug 27-Oct 26-Dec Comparison o measured and modelled concentrations o PM Vallstanäs,, E4:an norr om Stockholm 52 3 v/d E2 E1 Monitoring campain 23 mars-maj W

10 NOx Vallstanäs 4 Vallstanäs 23 measurments model NOx model wind direction SSW-NNW average x=72.9 average y=64.4 r=.76 NOx E NOx E1 -NOx background 2-Mar 27-Mar 3-Apr 1-Apr 17-Apr 24-Apr 1-May 8-May 15-May Comparison o measured and modelled concentrations o NOx PM1 Vallstanäs PM1 E1 -PM1 background PM1 model wind direction SSW-NNW average x=22.9 average y=22.2 r= PM1 E1 -PM1 background 2-Mar 27-Mar 3-Apr 1-Apr 17-Apr 24-Apr 1-May 8-May 15-May Comparison o measured and modelled concentrations o PM

11 Source-receptor modelling Traic-related sources PM1 Model PM1 µg/m Mar 2-Mar 3-Mar 9-Apr 19-Apr 29-Apr 9-May 19-May 29-May Date 23 Figure 1. Comparison between the PMF source-receptor model apportionment o PM1 concentrations or the sum o the our traic-related sources and the PM1 concentrations estimated by the SMHI PM1 model. Erik Swietlicki et al., no q or d unctions no summer sub model measurments - NOx no d unction no summer sub model no summer sub model measurments - PM1 complete model Sensitivity analysis PM NOx Jan 31-Jan 1-Mar 31-Mar3-Apr3-May29-Jun 29-Jul28-Aug27-Sep27-Oct26-Nov26-Dec

12 Conclutions A new model or calculation o emissions rom re-suspended particles (PM1 and PM2.5) in traic environments is presented. The model is compared with measurements, both rom a narrow street canyon in Stockholm (Hornsgatan) and or an open highway, with good results. The model is able to account or the main eatures in the PM1 variability, especially the peak inpm1 concentrations in late winter and early spring that is commonly experienced in the Nordic countries where studded tires are used. More tests on other streets and roads need to be done Indata Meteorologiska data: vind, temp, ukt, nederbörd, globalstrålning, moln Bakgrundshalter: bakgrundshalter av PM1 Traik data: ordonsmängd, andel tunga ordon, hastighet Geometrisk data: gatans/vägens riktning, bredd, byggnadshöjder antal körält Vägdata: vägbanans uktighet, sandning/saltning, snöröjning, dubbdäcksandelar, renhållning, egenskaper hos vägbeläggning Inormation som ota saknas!

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