AIR POLLUTION MODELLING

1
VEHICLE TYPE SPECIFICATIONS
Indication of Environmental Impacts of the traffic
TRAVEL DEMANDS
VEHICLE ENERGY, EMISSIONS MODEL Submodels for
estimation of fuel use and pollutant generation
rates for specified vehicle types under the given
traffic conditions
TRAFFIC MODEL Simulation, estimation of levels of
traffic flow, travel times, delays and congestion
in study area, over nominated time period
POLLUTANT DISPERSION MODEL Simulation, estimation
of area-wide pollutant levels
METEOROLOGICAL CONDITIONS
NETWORK CONFIGURATION
TOPOGRAPHY AND BUILT ENVIRONMENT DATA
2
AIR POLLUTION MODELLING

• Single and multiple box models, with and without
  chemical reactions
• Dispersion (diffusion) models for single and
  multiple point sources
• Receptor models

3
(No Transcript)
4
(No Transcript)
5
SOURCE ORIENTED vs RECEPTOR ORIENTED MODELS

• Source oriented given source characteristics and
  meteorological data, estimate pollutant
  concentrations at receptor site(s)
• Receptor oriented given measured pollutant
  concentration at receptor site, estimate the
  contributions of different sources, source
  apportionment

6
Figure 6.1 de Nevers

• Simple box model of a rectangular city

7
SIMPLE BOX MODEL OF A CITY
8
Figure 6.10 de Nevers

• UAM scheme

9
MULTIPLE BOX MODEL OF A CITYTHE URBAN
AIRSHED MODEL - UAM

• Mass balances (including generation and
  consumption terms) written for many boxes of
  typically 2-5 km square and 102 meters high.
• Each box is considered to be well mixed.
• Boxes can have mass fluxes to/from all adjacent
  boxes.
• Inputs are time variant emission and wind
  patterns as well as solar flux (for ozone
  photochemistry)
• Outputs are time variant concentrations of
  pollutant in each box.

10
Figure 4-A Wark Warner

• Development of mass balance equation with
  diffusion and advection components

11

• ci concentration of pollutant i,
• a function of space (x,y,z) and time (t)
• u,v,w horizontal and vertical wind speed
  components
• KX, KY horizontal turbulent diffusion
  coefficients
• KV vertical turbulent exchange coefficients
• Ri net rate of production of pollutant i by
  chemical reactions
• Si emission rate of pollutant i
• Di net rate of change of pollutant i due to
  surface uptake processes
• Wi net rate of change of pollutant i due to
  wet deposition

12
Figure 6.3 de Nevers

• Gaussian plume

13
(No Transcript)
14
GAUSSIAN (NORMAL) DISTRIBUTION
15
DOUBLE GAUSSIAN DISTRIBUTION
16
Figure 4-1 Wark Warner

• Gaussian or normal distribution function

17
2-D STEADY DISPERSION MODEL

• Solution for windspeed of u m/s and continuous
  release of Q g/s of pollutant at x y 0
  (stack location) and z H (the effective
  stack height)
• H h ??h
• h physical stack height, ?
• ?h plume rise due to buoyancy

18
Figure 6.7 de Nevers

• Horizontal dispersion coefficient

19
Figure 6.8 de Nevers

• Vertical dispersion coefficient

20
DISPERSION MODELLING

• The dispersion calculations for a single point
  source under a particular meteorology can be
  repeated for
• multiple sources with additive effects
• different meteorologies that might be expected at
  different times of the day or year
• The Industrial Source Complex (ISC) model
  incorporates the basic dispersion equations and
  makes it possible to incorporate available
  meteorological datasets

21
LINE SOURCES - Infinite line source

• Can be handled in principle as one dimensional
  dispersion from a point source.
• For wind perpendicular to line source
• q emission per unit time per unit distance

22
Oblique wind and finite line source

• For wind at an angle of with the line source,
  the strength is effectively increased by a
  factor of (sin ?)-1
• For a finite line source we must consider the end
  effects, the resulting concentration will be less
  than that for an infinite line source under the
  same conditions.
• Examples 4-9 and 4-10 (Wark, Warner Davis)
  demonstrate the application of the infinite line
  source case to CO concentrations near a highway.

23
COMPLICATIONS

• For ? lt 45, the (sin ?)-1 correction becomes
  increasingly inaccurate.
• The dispersion due to vehicle induced turbulence
  and thermal buoyancy due to heat release from
  the vehicles are important factors
• The P-G-T dispersion coefficients were originally
  observed in flat grass terrain, most highways of
  interest have some roughness effects associated
  with them (bridge, below grade. above grade etc.)

24
CALINE

• series of models developed to provide better
  estimations of motor vehicle pollutant
  concentrations near highways and arteries.
• Main features
• - Finite line segment approach
• - Mixing zone concept to incorporate traffic
  induced dispersion
• - New dispersion data near highways,
  adjustments for averaging time and surface
  roughness included for P-G-T coefficients

25
(No Transcript)
26
(No Transcript)
27
(No Transcript)
28
DISPERSION MODELLINGMOTOR VEHICLE EMISSIONS

• Line source in open terrain, CALINE and similar
  models.
• Line source in urban environment, CAR, OMG
• Intersections, CAL3QHC and similar
• Urban street canyons and more complex geometry,
  finite element modelling

29
(No Transcript)
30
(No Transcript)
31
(No Transcript)
32
(No Transcript)
33
(No Transcript)
34
(No Transcript)
35
(No Transcript)
36
(No Transcript)
37
(No Transcript)
38
(No Transcript)