*2.5. Inverse Distance Weighted (IDW) Spatial Interpolation*

Many spatial interpolation methods, such as kriging (universal or ordinary) and inverse distance weighted (IDW) spatial interpolation, have been used in different studies [45,46]. IDW geospatial interpolation is a type of deterministic method for multivariate interpolation with a known scattered set of points. IDW assigns values to unknown points according to the weighted average of the values of the known points and is more suitable

for regional interpolation [47]. In this study, we used IDW spatial interpolation technique to interpolate spatial distribution of PM2.5, PM10, SO2, NO2, CO, O3, AQI, and PM2.5/PM10 ratio in NWC. Equation (3) describes the interpolation analysis.

$$Zp = \frac{\sum\_{i}^{n} = 1 \frac{zi}{dip}}{\sum\_{i}^{n} = 1 \frac{1}{dip}}\tag{3}$$

where *Zp* refers to the value of unknown point, *Zi* is the value observed at the point of I; I represents the nearest neighborhood of interpolated point produced; p is the weighting absolute value, and p is equal to inverse distance weight, respectively.
