3) Use interpolation techniques to create spatial fields using ambient speciation data.
4) Use interpolation techniques to create spatial fields using ambient speciation data and gridded
model outputs to gradient adjust the species concentrations.
In general, we recommend using spatial interpolation techniques to estimate species
concentrations at FRM sites that do not have speciation data (numbers 3 and 4 above). But in
some cases, interpolating data from nearby sites may not be appropriate, may not be feasible, or
simply may not be necessary. For the CAIR analysis, a relatively simple interpolation technique
was used to estimate species concentrations at all FRM sites in the country. The analysis used a
Voronoi Neighbor Averaging (VNA) technique. Other interpolations have been done using
Kriging and other more complicated methodologies. States are encouraged to explore
techniques that are most appropriate for their area and situation. EPA’s MATS software
contains routines to interpolate data and model output using the VNA technique.
38References to STN monitors in this document always refer to the overall speciation
network which includes both trends sites and SLAMS sites.
39There are ~1100 FRM measurement sites and ~200-250 urban speciation sites (trends
For areas which contain one or more speciation sites, and where FRM sites exhibit very
little spatial gradients, it may be appropriate to assume that the speciation site is representative of
the entire area. Areas which exhibit strong spatial gradients in PM2.5 concentrations should
strongly consider using more sophisticated techniques to estimate species concentrations.
Combining ambient data with model output concentrations (number 4 above) may help adjust
concentrations in areas with strong gradients, but limited speciation data. This technique has
great promise but has not been used extensively for PM2.5 analyses. The technique is further
limited by uncertainties in the representativeness of the model outputs and emissions inventories.
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