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Street wetness

Street wetness. Michael Norman 2010-11-16. Todays topic. Street wetness Variation during the year Variation between streets Dry up rate EF Influenced by street wetness Seasonal variation Variation between streets. Street surface wetness sensor. L3. L2. Two electrodes

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Street wetness

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  1. Street wetness Michael Norman 2010-11-16

  2. Todaystopic • Street wetness • Variation during the year • Variation betweenstreets • Dry up rate • EF • Influenced by streetwetness • Seasonal variation • Variation betweenstreets

  3. Street surface wetness sensor L3 L2 • Two electrodes • Connected to two metal pins in the street • Gives a voltsignal when water on the street surface • 3 sensors at every station • Cheap L1

  4. Measuring stations Sveavägen, north-south Norrlandsgatan, north-south Hornsgatan, east-west Folkungagatan, east-west Torkel Knutssong., rooflevel, urban background

  5. Street wetness, seasonal variation

  6. Differencebetweenstreets • The streets are not alwaysdry/wetat the same time • Variesdue to • Direction (solar radiation) • Trafficdensity • Snow cover

  7. Example Dec 2008

  8. Example Nov 2010 North-South

  9. Example Nov 2010 East-West Folkungag

  10. Dry up rate, example Apr 2010 Norrlandsgatan Sveavägen Hornsgatan Folkungagatan Fast, but not at the same time

  11. Dry up rate • Street dry up within an hour • PM10 levelsincreaseequally fast

  12. Emission factor, PM10 • -EF=((PM10(street)-PM10(urban background))/(NOx(street)-NOX(urban background))*0.75 • EF NOx ~0.75 g/veh km • Seasonal variation • Somedifferencebetween the streets

  13. PM10 monthly average divided into dry and wet streets Drystreet Wetstreet Large difference during periods with high PM10 concentrations All days exceeding the 50 µg/m3 had dry street surface

  14. EF as function of streetwetness • Norrlandsgatan & Hornsgatan • Data from 2006 of PM10, NOx, streetwetnesstogether with PM10 and NOx from urban background • Count number of hours with wetstreet for everyday • Compare with the EF for that day

  15. Norrlandsgatan

  16. Hornsgatan

  17. Hornsgatan Mar-Apr Jan-Feb May-Jun Jul-Aug Nov-Dec Sep-Oct

  18. Norrlandsg Mar-Apr Jan-Feb May-Jun Jul-Aug Nov-Dec Sep-Oct

  19. What EF to use in model? • Different EF for different streets • Largelydependence on streetwetness, • Varies with • Street • Season • Not linear • Parameterize the streetwetness • Based on meteorological and traffic data

  20. Factorsinfluensing the streetwetness • Precipitation • Amount of snow • Both snow on the street as well as melting snow on next to the street • Relative humidity • High humidity causes wet street surface • Solar radiation • Street dries upp faster during days with sun, large difference during the year • Wind speed • Wind causes the street to dry up faster • Road salt, • Salt bind moisture to the street • Dustbinding, • Keeps the street wet for longer periods • Traffic amount

  21. Conclusions • Street wetness • Variesduring the year • Variesbetweenstreets • Dry up rate is fast • EF • Influenced by streetwetness • Seasonal variation • Variation betweenstreets

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