Wind-sensitive Interpolation of Urban Air Pollution Forecasts

Abstract

People living in urban areas are exposed to outdoor air pollution. Air contamination is linked to numerous premature and pre-native deaths each year. Urban air pollution is estimated to cost approximately 2% of GDP in developed countries and 5% in developing countries. Some works reckon that vehicle emissions produce over 90% of air pollution in cities in these countries. This paper presents some results in predicting and interpolating real-time urban air pollution forecasts for the city of Valencia in Spain. Although many cities provide air quality data, in many cases, this information is presented with significant delays (three hours for the city of Valencia) and it is limited to the area where the measurement stations are located. We compare several regression models able to predict the levels of four different pollutants (NO, NO2, SO2, O3) in six different locations of the city. Wind strength and direction is a key feature in the propagation of pollutants around the city, in this sense we study different techniques to incorporate this factor in the regression models. Finally, we also analyse how to interpolate forecasts all around the city. Here, we propose an interpolation method that takes wind direction into account. We compare this proposal with respect to well-known interpolation methods. By using these contamination estimates, we are able to generate a real-time pollution map of the city of Valencia.