# What principles do we consider when selecting an air pollution monitor location?

I'm working on a project aiming at finding some potential point as a new air pollutant monitor site for a city to measure $SO_2$, $NO_2$, $PM_{2.5}$, etc.
After modeling the surface concentration of the area, here is my select standard:

1. The violation situation

Finding the area which exceed the local air quality standard most in the modeling area.

2. The representation area

Each modeling grid concentration is a time-series dataframe. Compute the
spatial correlation coefficient (r) between one grid with surroundings area,
we can get each grid's represent area assuming there is a cut-off coefficient $r_c$.

For example, 3 grid i, j, k in the city.
$r_(ij) > r_c$ → $grid_i$ can represent the temporal variation of $grid_j$
$r_(ik) < r_c$ → $grid_i$ can't represent the temporal variation of $grid_k$

3. Population density

Considering the environmental exposure healthy risks, I add the pop-ind data for each concentration grid

### Here is my question

• Are these principle enough for a monitoring site?
• How to combine the results from the analysis based on multi-air pollutant data?
( In practice, one monitoring site often measure various air pollutants simultaneously, but my method is based on a specific type of air pollutant owing to the different emission source & chemical reactivity)

• Combining each site, We can get a monitoring network, how to estimate the network's strengths and weaknesses?