A polynomial approximation of the traffic contributions for kriging-based interpolation of urban air quality model

Abstract The European directives for ambient air quality require to assess areas where air pollutant concentrations exceed a regulatory threshold. As the spatial distribution of the pollutant is not exactly known, deterministic atmospheric dispersion models are commonly used to supplement the observational network. To reduce the computational time, the simulations are made on irregular grids, especially in urban areas where the grid is refined close to the roads. An interpolation method is then necessary to map the dispersion model at any location. We propose a new geostatistical approach based on kriging with external drift to distinguish the information along and across the roads. An exponential function is introduced to describe the decrease of the concentrations across the roads. Its series expansion is used to build a set of polynomial auxiliary predictors with unknown coefficients. This framework leads to a drift that is more generic and flexible in the kriging system.