Fine Resolution Mapping Of Air Quality in Jersey City

Keywords: PM 2.5, PM 10, CO2, HCHO, TEMPERATURE AND HUMIDITY.
Abstract Type: Poster Abstract

Abstract

Criteria Pollutants including PM 2.5, PM 10, CO2, and HCHO are of great concern to the public due to their significant risk to human health. There are many methods that have been developed to estimate PM 2.5, PM 10, CO2, and HCHO at unobserved locations due to the sparse number of fixed monitoring stations. This study mapped four criteria pollutants using field data sampled at various locations in Jersey City. The sampling locations are selected using a stratified random sampling process to represent all neighborhoods in jersey city across major land use categories. During this process, PM 2.5, PM 10, CO2, and HCHO with the current temperature and humidity were measured by an M2000 2nd Generation Multi-Functional Air Quality Detector. Two interpolation techniques Inverse distance weighted (IDW) interpolation and the Kriging method were adopted to estimate the concentration of these criteria pollutants at the unsampled location. An interesting finding is that PM2.5, PM 10, CO2, and HCHO concentrations in micro-environments varied in urban areas. During this project, Kriging interpolation performs better compared to IDW for the estimation of particulate matters (PM 2.5 and PM 10), whereas IDW performed better to estimate CO2 and HCHO at a fine spatial scale. Both PM 2.5 and PM 10 are highly concentrated in central business districts such as journal square, new port, and near the Hoboken area. However, HCHO is highly concentrated in industrial districts and port areas. High CO2 concentration was found in the southern part of the city.