Nano-particle aerosols are one of the major types of air pollutants in the urban indoor and outdoor environments. Therefore, determination of mechanisms of formation, dispersion, evolution, and transformation of combustion aerosols near the major source of this type of air pollution - busy roads and road networks - is one of the most essential and urgent goals. This Thesis addresses this particular direction of research by filling in gaps in the existing physical understanding of aerosol behaviour and evolution. The applicability of the Gaussian plume model to combustion aerosols near busy roads is discussed and used for the numerical analysis of aerosol dispersion. New methods of determination of emission factors from the average fleet on a road and from different types of vehicles are developed. Strong and fast evolution processes in combustion aerosols near busy roads are discovered experimentally, interpreted, modelled, and statistically analysed. A new major mechanism of aerosol evolution based on the intensive thermal fragmentation of nano-particles is proposed, discussed and modelled. A comprehensive interpretation of mutual transformations of particle modes, a strong maximum of the total number concentration at an optimal distance from the road, increase of the proportion of small nano-particles far from the road is suggested. Modelling of the new mechanism is developed on the basis of the theory of turbulent diffusion, kinetic equations, and theory of stochastic evaporation/degradation processes. Several new powerful statistical methods of analysis are developed for comprehensive data analysis in the presence of strong turbulent mixing and stochastic fluctuations of environmental factors and parameters. These methods are based upon the moving average approach, multi-variate and canonical correlation analyses. As a result, an important new physical insight into the relationships/interactions between particle modes, atmospheric parameters and traffic conditions is presented. In particular, a new definition of particle modes as groups of particles with similar diameters, characterised by strong mutual correlations, is introduced. Likely sources of different particle modes near a busy road are identified and investigated. Strong anti-correlations between some of the particle modes are discovered and interpreted using the derived fragmentation theorem. The results obtained in this thesis will be important for accurate prediction of aerosol pollution levels in the outdoor and indoor environments, for the reliable determination of human exposure and impact of transport emissions on the environment on local and possibly global scales. This work will also be important for the development of reliable and scientifically-based national and international standards for nano-particle emissions.