Modified Inverse Distance Weighting Interpolation for Particulate Matter Estimation and Mapping

Various studies are currently underway on PM (Particulate Matter) monitoring in view of the importance air quality public health management. Spatial interpolation has been used to estimate concentrations due that it can overcome shortcomings station-based and provide spatially continuous information. However, is affected by a combination several factors, only considers spatial relationship between stations limited ensuring accuracy. Additionally, relatively accurate results may be obtained case using external drifts, but methods have disadvantage they require additional data preprocessing. This study proposes modified IDW (Inverse Distance Weighting) allows more estimations based sole use measurements. The proposed method improves accuracy estimation weight correction according each known point. Use PM10 PM2.5 Seoul-Gyeonggi region South Korea led an improved compared with IDW, kriging, linear triangular interpolation. In particular, showed high conventional large error.