calcFno2(input,
tau = 60,
plot = TRUE,
user.fno2,
main = "",
xlab = "year",
...)nox
andno2 (roadside NOX and NO2 concentrations),
backnox, backno2 and backo3 (hourly
background concentrations of each pollutant). In TRUE and
will plot the trend in f-NO2 as a monthly time series.user.no2 will be
applied to the whole time series and is useful for testing "what if"
questions.calcFno2 works best when the roadside signal
is strong i.e. when roadside concentrations are in clear excess of
background concentrations. When there is little difference between
roadside and background concentrations it is difficult for the method
to distinguish between the NO2 from direct emissions and that formed
through the reaction with NO and O3. Similarly, during summertime
conditions when concentrations are generally lower, it can be
difficult to estimate the level of primary NO2. A safer approach would
be to calculate f-NO2 during "winter" condtions. See
selectByDate for information on selecting specific
time periods.
Sometimes it can be useful to filter by wind direction (and maybe wind
speed) to ensure that the conditions where the contribution from the
road is prominent are selected. The polarPlot function
can be useful for filtering the data in this way.linearRelation for details of how to estimate the
primary NO2 fraction.
In the absence of roadside O3 measurements, it is rather more
problematic to calculate the fraction of primary NO2. Carslaw and
Beevers (2005c) developed an approach based on
linearRelation the analysis of roadside
and background measurements. The increment in roadside NO2
concentrations is primarily determined by direct emissions of NO2 and
the availability of One to react with NO to form NO2. The method aims
to quantify the amount of NO2 formed through these two processes by
seeking the optimum level of primary NO2 that gives the least error.
Test data is provided at linearRelation if you have roadside ozone measurements.## Users should see the full openair manual for examples of how
## to use this function.Run the code above in your browser using DataLab