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.