Back%20Trajectory%20Techniques%20in%20Air%20Pollution

1
Back TrajectoryTechniques in Air Pollution
Farhan Akhtar Benton Whitesides Bo
Yan 11/19/2003 EAS 6792
2
Definition

• Trajectories the paths of infinitesimally small
  particles of air as they move through time and
  space.
• Such fluid particles, marked at a certain point
  in space at a given time, can be traced forward
  or backward in time along their trajectory.
• Backward (back) trajectories
• indicate the past path of a particle
• Forward trajectories
• indicate the future path of a particle

3
Example Back Trajectory
7-day Back trajectories from the ship (receptor)
have been calculated using the HYSPLIT 4 model
(HYbrid Single-Particle Lagrangian Integrated
trajectory).
receptor
4
Applications of Back Trajectories

• Synoptic meteorology
• Investigate air mass flow around mountains
  (Steinacker, 1984)
• Climatology
• Identify pathways of water vapor transport
  (DAbreton and Tyson, 1996) or desert dust
  (Chiapello et al., 1997)
• Environmental Sciences
• Establish source-receptor relationships of air
  pollutants (Stohl, 1996a)
• Law Enforcement
• Combine with pollen measurements to find possible
  locations of marijuana cultivation (Cabezudo et
  al.,1997)

5
Calculation of the Back Trajectory
X - the position vector during a time step dt
resulting from the wind v - mean wind
velocity vector (no consideration the turbulent
mixing in atmosphere)
6
Calculation of the Back Trajectory (contd)
If known x0 at t0
7
Error Sources in the Computation of Back
Trajectories

• Wind field errors
• In many cases, they are the largest single source
  of errors for back trajectory calculations. Wind
  field errors can be due to either analysis or
  forecast errors.
• Starting position errors and amplification of
  errors
• The starting positions of the trajectories are
  often not exactly known
• Difficult to select start positions due to the
  differences between the model topography and the
  real topography
• Back trajectory position errors can be strongly
  amplified in convergent flow.

8
Error sources for the computation of back
trajectories (cont)

• Truncation errors
• They come from the trajectory equation solution,
  which is approximated by a finite-difference
  scheme that neglects the higher order terms of
  Taylor series. In order to keep truncation errors
  negligible, a numerical scheme of high order
  using very short time steps is needed.
• Interpolation errors
• Due to the limit available wind data, wind speed
  must be estimated at the trajectory position. The
  interpolation errors will be caused during the
  process.
• Errors resulting from assumptions regarding the
  vertical wind
• Because there are no routine observation of
  vertical wing component w, Wind field of w can
  only gotten from meteorological model. So, it is
  less accurate than the horizontal wind fields.

9
Lagrangian Particle Dispersion Models (LPDM)

• V - mean wind vector obtained directly from
  meteorological model
• V - turbulent wind vector describing the
  turbulent diffusion of the tracer in the PBL.

10
Lagrangian box models

• Similar to LPDM, changes in the concentrations in
  the box caused by chemical reactions and
  deposition are calculated.
• No boundary conditions are required.
• Applicable only at higher levels of the
  atmosphere
• The most important boundary layer processes, such
  as the formation of nighttime reservoir layers or
  the rapid growth of the mixed layer depth in the
  morning, can be described with such models
  (Hertel et al., 1995),

11
Statistical analyses of trajectories

• Flow Climatologies
• Cluster analysis
• Residence time analysis and conditional
  probability
• Concentration fields
• Redistributed concentration field
• Inverse modeling

12
Accuracy

• Measure of the integral effect of all errors
• Determined by following the movement of conserved
  tracers
• Balloons
• Stay at a constant pressure height
• Do not measure vertical errors
• Material Tracers
• Conservative species are monitored.
• Compare results with Meteorological measurements
• Dynamical Tracers
• Attempt to model vertical movement in the
  atmosphere
• Potential temperature, isentropic potential
  vorticity

13
Examples Applications of Back-Trajectory
Techniques
Determination of Regional Sources of Winter Smoke
Pollution in New Zealand Tajectory analysis of
particulates in Big Bend national park
14
Determination of Regional Sources of Smoke
Pollution in Winter

• Night time burning of wood and coal in domestic
  fires created smoke pollution for the town of
  Christchurch, New Zealand.
• In the evening, temperature inversions trap
  pollution close to the surface.
• Burning created high concentrations of
  particulate matter from the ground to 10m.
• Used back-trajectory models to determine origin
  and pathways of polluted parcels.

15
PM10 and CO Concentrations

• Winter 1988-1999 averaged concentrations in
  Christchurch for a 24 hour period.
• Reveals Diurnal cycle of PM10 peaking over night.

16
Region of Interest

• City of Cristchurch New Zealand
• Plains to the North and West
• Hills to the South
• Water to the East

17
Complexities

• Terrain creates complexity in low level flow.
• On clear calm nights, radiative cooling of hill
  slopes causes cold air drainage into the region
  of interest.

18
Techniques

• Only enough data to use simple back-trajectory
  techniques.
• Lagrangian Kinematic Back-Trajectory Modeling
  techniques.
• Regional Atmospheric Modelling System (RAMS)
  based on averaged nocturnal wind fields typically
  associated with high pollution events in the city
  (1995-2000).

19
Nested Grid Model

• RAMS is a 3-D Nested Grid Model allowing focus on
  specific regions.
• No vertical grid nesting- focus on lowest km of
  atmosphere (damping applied to higher altitudes).

20
Techniques

• Models air flow of 4 Cases
• No initial wind
• Weak NW wind
• Strong SW wind
• Moderate NE wind
• Resolution (Spatial 500m) (Temporal 15 mins)
• Run times 3pm to 3am
• 2nd Order Turbulence Closure

21
Model Vs. Observations

• Model recreation of the horizontal wind field
  compares well to actual observations.
• Other methods of comparison included standard
  deviation root-mean square.
• Using these wind fields, back trajectories
  plotted for given endpoints.

22
Problems

• Ignored particle settling rates.
• Vertical velocities neglected (though realistic
  for night)
• No examination of concentration changes in
  parcels during transport.
• No consideration of sources of sinks during
  transport (chemical photochemical reactions).
• Synoptic events not considered

23
Back Trajectory Plots

• Trajectory plots show parcel path across grid
  space from surrounding regions.
• Urban area of Christchurch is represented by grid
  dots.

24
Results No Initial Wind

• Surface airflow dominated by local effects (cold
  air drainage from hills).
• Air originates in plains and moves towards the
  city, except for near the hills where cold air
  drainage occurs.

25
Results Strong SW Wind (10 m/s)

• Gradient wind -dominates transport,
  -turbulent mixing and -inhibits inversion
• No impact from cold air drainage.
• Air travels much farther.

26
Results Light NW Wind

• Similar to what happens with no initial wind.
• Terrain dominates transport (cold air drainage).
• Transport almost independent from wind.
• Parcels move from hills into city.
• (As expected from cold air drainage)

27
Results Moderate NE Wind

• Very different from other cases
• Air blowing on shore.
• Seabreeze orographic wind switch direction as
  drainage develops.
• Air re-circulates over city allowing evening
  pollution buildup.
• Hills less important.

28
3 Back Trajectories From NE Wind

• Note recirculation of parcels over the city with
  changing winds.
• Grey dots indicate endpoints of each trajectory.

29
Implications Conclusions

• Cold Air Drainage allows leakage of southern hill
  pollutants into city and northern valleys
  overnight.
• Drainage can be inhibited by stability.
• Burning during winter (problematic months) should
  be restricted.

30
Particulates in Big Bend National Park
31
Background

• Park has registered the poorest visibility in the
  western United States.
• Since 1988, fine particulate matter and optical
  data has been collected in the park
• The majority of the visibility degradation is due
  to sulfate particles.
• Large coal-fired power plants are located over
  the border into Mexico.
• Use a LPDM to determine the sources for these
  particulates

32
LPDM Inputs

• The depth of the transport zone is set at the
  lowest inversion layer which meets these
  criteria
• height is at least 300 m above the ground
• Potential temperature lapse rate of at least 5
  K/km
• Potential temperature is 2K greater at the top
  than at the bottom
• If no inversion exists, 3000m is assumed
• Horizontal winds are linearly interpolated from
  rawinsonde measurements
• Computed backward in 6h time steps for a maximum
  of 120h (5 days)

33
Accuracy and Errors

• Rainout and especially low inversion layers are
  not accounted for
• Trajectories are aggregated over long time
  periods to attempt to minimize errors

34
Results

• If over 80 of the trajectories calculated for a
  day came from one country, the day was assigned
  to that country.
• 935 days from 10 years were analyzed
• The model indicates that most particles (59)
  came from Mexico.

35
Results by season
Overall source attribution from 1989-1998
36
Results by season
Overall source attribution for fine sulfur from
1989-1998
37
Results by season
Overall source attribution for organic carbon
from 1989-1998
38
References
Gebhart, Kristi A., et al., Back-trajectory
analyses of fine particulate matter measured at
Big Bend National Park in the historical database
and the 1996 scoping study. The Science of the
Total Environment. Vol 276. Elsevier 2001.
pp.185-204. Stohl, A. Computation, Accuracy and
Applications of Trajectories- A Review and
Bibliography. Atmospheric Environment. Vol 32.
Pergamon 1998. pp. 947-966. Stohl, A., et. al.
A replacement for simple back trajectory
calculations in the interpretation of
atmospheric trace substance measurements.
Atmospheric Environment. Vol 36. Pergamon
2002. pp. 4635-4648. Sturman, A., P. Zawar-Reza.
Aplication of back-trajectory techniques to the
determination of urban clean air zones.
Atmospheric Environment. Vol 36. Pergamon
2002. pp. 3339-3350.