Several types of trajectory plot are available. trajPlot by
default will plot each lat/lon location showing the origin of
each trajectory, if no pollutant is supplied.If a pollutant is given, by merging the trajectory data with
concentration data (see example below), the trajectories are
colour-coded by the concentration of pollutant. With a long
time series there can be lots of overplotting making it difficult
to gauge the overall concentration pattern. In these cases setting
alpha to a low value e.g. 0.1 can help.
The user can aslo show points instead of lines by plot.type
= "p".
Note that trajPlot will plot only the full length
trajectories. This should be remembered when selecting only part
of a year to plot.
An alternative way of showing the trajectories is to bin the
points into latitude/longitude intervals For these purposes
trajLevel should be used. There are several trajectory
statistics that can be plotted as gridded surfaces. First,
statistic can be set to frequency to show the
number of back trajectory points in a grid square. Grid squares
are by default at 1 degree intervals, controlled by lat.inc
and lon.inc. Such plots are useful for showing the
frequency of air mass locations. Note that it is also possible to
set method = "hexbin" for plotting frequencies (not
concentrations), which will produce a plot by hexagonal binning.
If statistic = "difference" the trajectories associated
with a concentration greater than percentile are compared
with the the full set of trajectories to understand the
differences in freqeuncies of the origin of air masses of the
highest concentration trajectories compared with the trajectories
on average. The comparsion is made by comparing the percentage
change in gridded frequencies. For example, such a plot could show
that the top 10% of concentrations of PM10 tend to orginate from
air-mass origins to the east.
If statistic = "pscf" then the Potential Source
Contribution Function is plotted. The PSCF calculates the
probability that a source is located at latitude $i$ and
longitude $j$ (Pekney et al., 2006).The basis of PSCF is that
if a source is located at (i,j), an air parcel back trajectory
passing through that location indicates that material from the
source can be collected and transported along the trajectory to
the receptor site. PSCF solves $$PSCF = m_{ij}/n_{ij}$$ where
$n_{ij}$ is the number of times that the trajectories passed
through the cell (i,j) and $m_{ij}$ is the number of times
that a source concentration was high when the trajectories passed
through the cell (i,j). The criterion for de-termining
$m_{ij}$ is controlled by percentile, which by default
is 90. Note also that cells with few data have a weighting factor
applied to reduce their effect.
A limitation of the PSCF method is that grid cells can have the
same PSCF value when sample concentrations are either only
slightly higher or much higher than the criterion. As a result, it
can be difficult to distinguish moderate sources from strong
ones. Seibert et al. (1994) computed concentration fields to
identify source areas of pollutants. The Concentration Weighted
Trajectory (CWT) approach considers the concentration of a species
together with its residence time in a grid cell. The CWT approach
has been shown to yield similar results to the PSCF approach. The
openair manual has more details and examples of these approaches.
A further useful refinement is to smooth the resulting surface,
which is possible by setting smooth = TRUE.