Monitor Direct. Monitor Direct grid creation uses air pollution monitoring data to estimate air

pollution levels for each grid cell in the selected Grid Definition. This may be done using one of

two interpolation procedures – Closest Monitor, or Voronoi Neighbor Averaging (VNA). With

closest monitor, BenMAP simply uses the data of the monitor closest to each grid cell's centroid.

With VNA, BenMAP first identifies the set of monitors that most closely “surround” each grid

cell, and then calculates an inverse-distance weighted average of the data from these neighboring

monitors.

Monitor and Model Relative. Monitor and Model Relative grid creation allows you to

combine information from both monitor and modeling data files. BenMAP uses the modeling data

to scale the monitoring data, to compensate for incomplete monitoring data coverage, and the

inability of monitor data to predict future conditions. Like the Monitor Direct approach, you

choose an interpolation method (Closest Monitor or VNA), but a scaling approach is also chosen,

either temporal, spatial, or both. This approach is described in more detail in the Air Quality Grid

Creation chapter, as well as in the appendix on Air Pollution Exposure Estimation Algorithms.

Monitor Rollback. Monitor Rollback grid creation allows you to reduce, or roll back, monitor

data using three methods: percentage rollback, incremental rollback, and rollback to a standard.

Percentage rollback reduces all monitor observations by the same percentage. Incremental

rollback reduces all observations by the same increment. Rollback to a standard reduces monitor

observations so that they just meet a specified standard. After the monitor data is rolled back, it

may be directly interpolated (as in Monitor Direct grid creation) or combined with modeling data

(as in Monitor and Model Relative grid creation). This approach is described in more detail in

the Air Quality Grid Creation chapter, as well as in the appendix on Monitor Rollback Algorithms.

 

 

 

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