In this paper we report the results of the detailed monitoring and analysis of combustion emissions from fast moving diesel trains. A new highly efficient monitoring methodology is proposed based on the measurements of the total number concentration (TNC) of combustion aerosols at a fixed point (on a bridge overpassing the railway) inside the violently mixing zone created by a fast moving train. Applicability conditions for the proposed methodology are presented, discussed and linked to the formation of the stable and uniform mixing zone. In particular, it is demonstrated that if such a mixing zone is formed, the monitoring results are highly consistent, repeatable (with typically negligible statistical errors and dispersion), stable with respect to the external atmospheric turbulence and result in an unusual pattern of the aerosol evolution with two or three distinct TNC maximums. It is also shown that the stability and uniformity of the created mixing zone (as well as the repeatability of the monitoring results) increase with increasing length of the train (with an estimated critical train length of ~10 carriages, at the speed of ~150km/h). The analysis of the obtained evolutionary dependencies of aerosol TNC suggests that the major possible mechanisms responsible for the formation of the distinct concentration maximums are condensation (the second maximum) and thermal fragmentation of solid nanoparticle aggregates (third maximum). The obtained results and the new methodology will be important for monitoring and analysis of combustion emissions from fast moving trains, and for the determination of the impact of rail networks on the atmospheric environment and human exposure to combustion emissions.

We demonstrate new powerful methods of statistical analysis of atmospheric aerosols on the example of urban background aerosol in the Brisbane area, Australia. It is shown that even in the absence of notable features on the size distribution, it is still possible to identify distinct particles modes and analyze their mutual interactions and transformations. The obtained unique anti‐symmetric correlation patterns between particle modes may serve as fingerprints of particular evolutionary processes in the background aerosols. The obtained results suggest that thermal fragmentation of nano‐particles may be one of the major physical mechanisms shaping urban background aerosols. In particular, based on the fragmentation theorem, we demonstrate possible existence of substantially different time scales for fragmentation of atmospheric aerosols. The proposed approaches and obtained results may also be important for the analysis of different types of atmospheric aerosols on local, regional and global scales.