  A set of indicators derived from the analysis of complex networks have been
introduced to identify singularities on a time series. To that end, the
Visibility Graphs (VG) from three different signals related to photochemical
smog (O3, NO2 concentration and temperature) have been computed. From the
resulting complex network, the centrality parameters have been obtained and
compared among them. Besides, they have been contrasted to two others that
arise from a multifractal point of view, that have been widely used for
singularity detection in many fields: the Holder and singularity exponents
(specially the first one of them). The outcomes show that the complex network
indicators give equivalent results to those already tested, even exhibiting
some advantages such as the unambiguity and the more selective results. This
suggest a favorable position as supplementary sources of information when
detecting singularities in several environmental variables, such as pollutant
concentration or temperature.
