Traffic noise is one of the main pollutants in urban and suburban areas. European authorities have driven several initiatives to study, prevent and reduce the effects of exposure of population to traffic. Recent technological advances have allowed the dynamic computation of noise levels by means of Wireless Acoustic Sensor Networks (WASN) such as that developed within the European LIFE DYNAMAP project. Those WASN should be capable of detecting and discarding non-desired sound sources from road traffic noise, denoted as anomalous noise events (ANE), in order to generate reliable noise level maps. Due to the local, occasional and diverse nature of ANE, some works have opted to artificially build ANE databases at the cost of misrepresentation. This work presents the production and analysis of a real-life environmental audio database in two urban and suburban areas specifically conceived for anomalous noise events’ collection. A total of 9 h 8 min of labelled audio data is obtained differentiating among road traffic noise, background city noise and ANE. After delimiting their boundaries manually, the acoustic salience of the ANE samples is automatically computed as a contextual signal-to-noise ratio (SNR). The analysis of the real-life environmental database shows high diversity of ANEs in terms of occurrences, durations and SNRs, as well as confirming both the expected differences between the urban and suburban soundscapes in terms of occurrences and SNRs, and the rare nature of ANE.