Air quality forecasting in Europe using statistical persistence

Abstract

In this paper we augment the methodology of Chiera et al., [2010] to produce a multi-indicator model to predict pollution levels at measuring stations located in 36 European nations, based on observed persistent behaviour in air quality. An attractive feature of the adapted usage of the CFZG model is that it can be applied to multiple pollutant signals including all of the primary European pollutants such as Nitrous Oxides, Particulate Matter, Volatile Organic Compounds and Ozone. Unlike the single-indicator CFZG model, which used measuring stations from two locations only, we use measuring stations for pollutant signals which are geographically disparate, located in both rural and urban sites across 36 countries, all of which are registered with the European Environmental Agency. We present examples of typical nitrous oxide and ozone levels across selected sites and forecasting results for our chosen case study — rural Bosnia-Herzegovina — and compare the forecast against a control test that uses a random signal.