Fusion of air quality information: Evaluation of the enfuser-methdoology in finland and a case study in China

Abstract

We describe a modelling system (FMI-ENFUSER), which fuses environmental information for the assessment of urban air quality in a high resolution based on local sensor network, meteorological data and a collection of GIS-datasets. With this combination of techniques the hourly concentration of particle matter (PM2.5 and PM10) and NO2 can be accurately predicted in several selected urban test sites in Finland. We also show and discuss the first results from test sites in China and India. The methodology can be used in any region where a proper training dataset and GIS-information exists.