Hotspot Analysis of Spatial Air Pollutants and Asthma Rate in New York State using Kernel Density Estimation

An important component of human health protection from poor air quality is identification hot spots in respect to poor air quality in a region. The present study examines the use of spatial analysis for identifying air pollution hotspots due to three air pollutants (PM2.5, SO2, and O3) in New York State, U.S.A. Higher concentrations zone were identified and the asthma discharge rate in those areas were determined for understanding the effect of exposure of high air pollutants to asthma discharge rate. In a preliminary investigation, kernel density estimation (KDE) technique was used for hotspot analysis of air pollution from annual average air pollutants concentrations. Results show that there are multiple hotspots for these three air pollutants and they are significantly correlated to the locations of asthma discharge rate in the study area. Air pollution hotspots and polluted sampling densities are clearly defined using the KDE approach based on point data of air pollutants. Furthermore, the risk prone areas are explored by this technique (KDE) and the hotspot areas are captured without requiring exhaustive sampling anywhere. Keywords: kernel density estimation (KDE); air pollution; asthma