UFP  PARTICLE NUMBER (ToN)

Slides:



Advertisements
Similar presentations
9 th INTERNATIONAL CFD CONFERENCE September Institute of Power Technology MOSCOW, Russia.
Advertisements

 If it is assumed that  w is made up of a contribution from the mean wind and a contribution from the traffic, then it can be suggested that Introduction.
Ian Longley Physics Department, UMIST, Manchester, U.K. Fine scale temporal variation in ultrafine particle concentrations in a busy street canyon with.
Fine-Scale Variations in Aerosol Transport within a Street Canyon – a Pilot Field Study I.D. Longley, M.W. Gallagher, M. Flynn, J.R. Dorsey, P.I. Williams.
Earth Science 17.1A Atmosphere Characteristics
Update on PM 2.5 – The Scope of the Problem and Overview of Sources Matthew M. Russell, PhD ENVIRON International Corporation Los Angeles, California April.
Gaseous And Particulate Dispersion In Street Canyons
PARTICLE EMISSIONS FROM TYRE AND BRAKE WEAR ON-GOING LITERATURE REVIEW Sustainable Transport Unit Institute for Energy and Transport Joint Research Centre.
OpenFOAM for Air Quality Ernst Meijer and Ivo Kalkman First Dutch OpenFOAM Seminar Delft, 4 november 2010.
Particle Number Size Distributions at an Urban Site in southern Sweden: Estimates of the Contribution of Urban Particle Sources Erik Swietlicki 1, Andreas.
Aerosols By Elizabeth Dahl (2005) Edited by Ted Dibble (2008)
Large-eddy simulation of flow and pollutant dispersion in urban street canyons under different thermal stratifications W. C. Cheng and Chun-Ho Liu * Department.
Low emission zones in Dutch cities Approach and experiences Paul Poppink.
Ge/Ay133 How do small dust grains grow in protoplanetary disks?
VII. How might current analysis methods be enhanced or combined to obtain more information about the nature of OC, EC, and other carbon fractions in filter.
Ultrafine Particles and Climate Change Peter J. Adams HDGC Seminar November 5, 2003.
Laminar and Turbulent Flow
Typically have a higher organic content than coarse particles Also contain soluble inorganics: NH 4 +, NO 3 -, SO 4 2- A bimodal peak is often observed.
Modelling Pollution Dispersion in Urban Areas Silvana Di Sabatino Universita’ di Lecce, Dipartimento Scienza dei Materiali, Via Arnesano, Lecce (I)
F AST R ESPONSE M EASUREMENTS FOR THE D ISPERSION OF N ANOPARTICLES IN V EHICLE W AKE AND S TREET C ANYON 89 TH AMS M EETING, P HOENIX, J ANUARY.
ULTRAFINE PM IN NEAR GROUND LAYER OF URBAN ATMOSPHERE, PRAGUE 2002/2003 JAN HOVORKA, LUBOMÍR BETUŠ ; Institute.
M+P – consulting engineers Müller-BBM group Acoustics Noise and vibration control Air quality Air Quality alongside motorways Air Quality alongside.
Senate department of urban development Unit IX D: air pollution and noise control, M. Lutz 1 Berlin’s Air Quality Strategy: measures and expected effects.
Air quality and health impact assessment AQ information at the regional scale, urban background scale and street scale past, present and future air quality.
WORKSHOP ON VEHICLE EXHAUST PARTICULATE EMISSION MEASUREMENT METHODOLOGY San Diego, 21 Oct 2002 Zissis Samaras Lab of Applied Thermodynamics Aristotle.
Nanoparticles from Road Vehicle Exhaust. An Artifact or a Reality? Background Current emission standards for motor vehicles are mass based. Properties.
School of something FACULTY OF OTHER 1 Lecture 2: Aerosol sources and sinks Ken Carslaw.
Windy Cities
Effects of different surface types and human activities.
Results from the SMEAR III urban measurement station
Vehicle generated nanoparticles are not an artifact! D. B. Kittelson, W.F. Watts, and J.P. Johnson Center for Diesel Research University of Minnesota 8th.
Properties of Particulate Matter Physical, Chemical and Optical Properties Size Range of Particulate Matter Mass Distribution of PM vs. Size: PM10, PM2.5.
Transport & Deposition of Air Pollutants David Gay Coordinator National Atmospheric Deposition Program University of Illinois, Champaign, IL ,
WRF Volcano modelling studies, NCAS Leeds Ralph Burton, Stephen Mobbs, Alan Gadian, Barbara Brooks.
Meteorology & Air Pollution Dr. Wesam Al Madhoun.
4. Atmospheric chemical transport models 4.1 Introduction 4.2 Box model 4.3 Three dimensional atmospheric chemical transport model.
1 Ultrafine Particles and Freeways Yifang Zhu, Ph.D. Assistant Professor Department of Environmental Engineering Texas A&M University –Kingsville
DEPARTMENT OF MUNICIPAL HYGIENE AND OCCUPATIONAL HEALTH LECTURE ON ENVIRONMENTAL SANITATION FOR 4TH YEAR TOPIC: PROBLEMS OF AIR POLLUTION RESIDENTIAL.
Influence of the Asian Dust to the Air Quality in US During the spring season, the desert regions in Mongolia and China, especially Gobi desert in Northwest.
Statistical and optimized results concerning the mobile measurements of fine and coarse emission factors by the Sniffer-system Jari Härkönen Senior Researcher.
Institute of Epidemiology Epidemiological Evidence for Health Effects of Nanoparticles H.-Erich Wichmann GSF – Institute of Epidemiology LMU – University.
Office of Research and Development National Exposure Research Laboratory, Atmospheric Modeling and Analysis Division Office of Research and Development.
Urban Heat Island and Pollution
Shaping the Future Emissions Formation and Control.
PNWIS Cross-border Air and Waste Solutions The effect of vegetative buffers on wind and dispersion of particulate matter around poultry barns Andreas.
Jorma Keskinen Tampere University of Technology (TUT) Occurrence and fate of traffic generated nanoparticles in (urban) atmosphere.
NATS 101 Lecture 1 Atmospheric Composition. 100 km a  6500 km C = 2  a  x 10 4 km Ratio: Height/ Length is 100/(4.084 x 10 4 )  2.45 x
TUG Roadside Measurements of Particulate Matter (PM) size distribution P.J. Sturm, S. Hausberger Graz University of Technology: Michael Bacher, Bernhard.
Atmospheric Lifetime and the Range of PM2.5 Transport Background and Rationale Atmospheric Residence Time and Spatial Scales Residence Time Dependence.
Properties of Particulate Matter
Jeng K. Rongchai FETE Conference 21 July 2011.
Urban Microclimates I can define and apply the concept of an urban heat island I can identify reasons for an issues stemming from urban air pollution I.
Exposure to air pollution in the transport microenvironment: how important is short-term exposure to high concentrations, and what are the determinants.
Sibley School of Mechanical and Aerospace Engineering
Reynolds Number (Re) Viscosity: resistance of a liquid to change of form. Inertia: resistance of an object (body) to a change in its state of motion.
Dispersion of Air Pollution and Penetration into the Local Environment
Section 1: What Cause Air Pollution?
Ian D. Longley, M.W. Gallagher
Clarkson UNIVERSITY defy convention
Urban Microclimates Temperature Wind Pollution
Increasing Canopy Cover in Urban Areas
COMPUTATIONAL MODELING OF PARTICLE TRANSPORT IN TURBULENT AIRFLOW
MODULE II: SIMULATIONS
Aerosol Drug Therapy Copyright © 2013, 2009, 2003, 1999, 1995, 1990, 1982, 1977, 1973, 1969 by Mosby, an imprint of Elsevier Inc.
I. What? ~ II. Why? ~ III. How? Modelling volcanic plumes with WRF
M. Samaali, M. Sassi, V. Bouchet
Meteorology & Air Pollution Dr. Wesam Al Madhoun
EURODELTA III RCG-Model
On-going developments of SinG: particles
Low emission zones in Dutch cities
Presentation transcript:

UFP  PARTICLE NUMBER (ToN) Emissions, Dynamics and Dispersion of Ultrafine Particles in Polluted Air (extract from doctoral thesis by Lars Gidhagen) traffic exhaust particles microenvironments: a) car tunnel b) street canyon c) close to a highway urban scale UFP  PARTICLE NUMBER (ToN)   SO2 -pinene 1. How many particles are emitted by each vehicle? 2. What processes will affect the ambient air concentrations? 3. What processes are of importance for particle number concentrations on the urban scale? Introduction (WHO)

Diesel soot particles low density (decreasing with size) Vehicle emissions Diesel soot particles low density (decreasing with size) (Van Gulijk et al., 2004 ) tailpipe Inital dilution/particle formation zone (dilution ratio ~ 5 - 50) soot particles (agglomerates): 40-300 nm Nanoparticles: < 50 nm Subgrid (emission factor) Simulated in aerosol model nanoparticles contribute to > 90% of particle number most of them are liquid (possibly solid core) low concentrations of soot => more nanoparticles low ambient temperature => more nanoparticles

lung deposition number surface area mass number surface area mass Urban aerosol nanoparticles < 50 nm ultrafine mode 3 - 100 nm fine mode 0.1 - 2.5 m coarse mode 2.5 - 10 m number surface area mass lung deposition number surface area mass (Kittelson, 2004

Brownian motion makes nanoparticles collide with…. Removal processes Brownian motion makes nanoparticles collide with…. particle 100-200 nm Intermodal coagulation Intramodal coagulation …. other particles: Coagulation quasi-laminar layer turbulent diffusion …. surfaces: Dry deposition Effective reduction of nanoparticles if concentrations of larger particles are high Effective reduction of nanoparticles if the turbulent transport towards the surface is fast

==> 30 % removal of total particle number concentrations 97% Car tunnel (PAPER I) 36 000 veh/day ToN: up to 1 300 000 cm-3 Remaining particles at tunnel exit (rush hour conditions) 23% 59% 84% 97% ==> 30 % removal of total particle number concentrations

2 ms-1 Fraction removed due to coagulation and dry deposition Street canyon (PAPER II) coag + dep: 27% only coag: 15% Fraction removed due to coagulation and dry deposition ToN removal as compared to inert particles from source A 2 ms-1 B A C 35 500 veh/day ToN: up to 210 000 cm-3 coag + dep: 5% only coag: 6% A B Most of the removal occurs close to the vehicles Deposition is enhanced by vehicle movements (insensitive to wind speed) coag + dep: 7% only coag: 7% C coag + dep: 27% only coag: 15% Coagulation is only important during low wind speed conditions

slow but continuously working coagulation Highway (PAPER III) 52 300 veh/day ToN: up to 70 000 cm-3 Limited removal over the road, almost no removal for the dispersion ~ 100 m downwind intense deposition (~10%) slow but continuously working coagulation (<1%) wind

Coagulation unimportant for average ToN concentrations Urban scale (PAPER IV) Roof level (25 m) Evaluation of simulated particle number concentrations against measurements 120 000 Removal in % due to coagulation (compared to only dilution) 2.5-3 1.5-2 1-1.5 Average particle number (ToN) concentrations April 17-27, 2002 >15000 background ~ 3000 # cm-3 Removal in % due to dry deposition (compared to only dilution) 20-25 >15 10-15 5-10 15-20 The results show that particle number can be simulated in urban models, in a similar way to particle mass or gaseous pollutants Tower (100 m) Coagulation unimportant for average ToN concentrations Dry deposition important on the urban scale

! ! ! Principal results    Outlook Vehicle ToN emission factors for urban modeling  Particle number / urban scale: - Dry deposition important - Coagulation of little importantance  Particle number can be simulated over large cities  Outlook ! Verify size distribution on urban scale Verify model in larger / “warmer” city ! Extend model to national scale !

Finis