Abstract

In this paper, we investigate similarities of greenhouse gas (GHG) emissions in Europe, which are available as interval time series. The GHG time series are available as intervals to reflect uncertainty in the estimation phase. Therefore, a spatio-temporal hierarchical clustering algorithm for Interval Time Series (ITS) data is proposed. The spatial dimension is considered in the clustering process to instrument for possible relevant information such as atmospheric conditions and regional factors affecting the amount of emissions. A comparison with different temporal distances for clustering GHG emissions is discussed in light of the peculiar features of this type of ITS data.