Water, sediment and soil physicochemical interactions in freshwater, brackish and saline systems

The physicochemical interactions between water, sediment and soil deeply influence the formation and development of the ecosystem. In this research, different freshwater, brackish and saline subaqueous environments of Northern Italy were chosen as study area to investigate the physicochemical processes which occur at the interface between water and sediments, as well as the effects of soil submergence on ecosystem development. In the freshwater system of the Reno river basin, the main purpose was to define the heavy metals hazard in water and sediments of natural and artificial water courses. Heavy metals partitioning and speciation allowed to assess the environmental risk linked to the critical action of dredging canal sediments, for the maintenance of the hydraulic safety of plain lands. In addition, some bioremediation techniques were experimented for protecting sediments from heavy metals contamination, and for giving an answer to the problem of sediments management. In the brackish system of S. Vitale park, the development of hydromorphic and subaqueous soils was investigated. The study of soil profiles highlighted the presence of a soil continuum among pedons subjected to different saturation degrees. This investigation allowed to the identification of both morphological and physicochemical indicators, which characterize the formation of subaqueous soils and describe the soil hydromorphism in transitional soil systems. In the saline system of Grado lagoon, an ecosystem approach was used to define the role of water oscillation in soil characterization and plants colonization. This study highlighted the close relationship and the mutual influence of soil submergence and aeration, tide oscillation and vegetation cover, on the soil development. In view of climate change, this study contribute to understand and suppose how soil and landscape could evolve. However, a complete evaluation of hydromorphic soil functionality will be achieved only involving physiological and biochemical expertise in these kind of studies.

Application of innovative methods of source apportionment in air contamination assessment

In this work, new tools in atmospheric pollutant sampling and analysis were applied in order to go deeper in source apportionment study. The project was developed mainly by the study of atmospheric emission sources in a suburban area influenced by a municipal solid waste incinerator (MSWI), a medium-sized coastal tourist town and a motorway. Two main research lines were followed. For what concerns the first line, the potentiality of the use of PM samplers coupled with a wind select sensor was assessed. Results showed that they may be a valid support in source apportionment studies. However, meteorological and territorial conditions could strongly affect the results. Moreover, new markers were investigated, particularly focusing on the processes of biomass burning. OC revealed a good biomass combustion process indicator, as well as all determined organic compounds. Among metals, lead and aluminium are well related to the biomass combustion. Surprisingly PM was not enriched of potassium during bonfire event. The second research line consists on the application of Positive Matrix factorization (PMF), a new statistical tool in data analysis. This new technique was applied to datasets which refer to different time resolution data. PMF application to atmospheric deposition fluxes identified six main sources affecting the area. The incinerator’s relative contribution seemed to be negligible. PMF analysis was then applied to PM2.5 collected with samplers coupled with a wind select sensor. The higher number of determined environmental indicators allowed to obtain more detailed results on the sources affecting the area. Vehicular traffic revealed the source of greatest concern for the study area. Also in this case, incinerator’s relative contribution seemed to be negligible. Finally, the application of PMF analysis to hourly aerosol data demonstrated that the higher the temporal resolution of the data was, the more the source profiles were close to the real one.