28.10. Statistical studies of atmospheric nanoparticles and their precursors

Public examination of a doctoral dissertation in the field of computational engineering

Doctoral candidate: M.Sc. Santtu Mikkonen 

Date and venue: 28.10.2011, at 12 noon, L21, Snellmania, Kuopio campus


Aerosols affect our everyday life in many ways. Understanding the processes controlling the formation and growth of the aerosol particles is essential in order to estimate their effect on the global climate, air quality and human health. A large number of measurements on the composition of the atmosphere have been made, and are made all the time, but large amounts of the collected data still requires further analysis. Appropriate methods are needed for the analysis of large datasets, and statistical methodology offers the tools for finding the properties of the data. In this work we studied the usability of several different statistical methods for extensive measurement data. We applied the tried and tested methodologies for the studies included in this thesis, namely discriminant analysis for new particle formation (NPF) event classification, mixed models for parameterizing the number concentration of aerosol particles and nonlinear regression for constructing proximity measure for sulphuric acid concentration. 

The main conclusions of the work presented in this thesis are: 1) New particle formation is frequent phenomenon in semi polluted and polluted areas such as San Pietro Capofiume, Italy, Melpitz and Hohenpeissenberg, Germany, and conditions favouring new particle formation can be characterized with measured atmospheric variables, 2) The concentration of 50 nm sized particles can be predicted with in-situ meteorological and gas phase parameters by using a multivariate mixed effects model. 3) New particle formation was found to be important source of Cloud Condensation Nuclei (CCN): probability of a NPF event was found to be a significant predictor for the number concentration of CCN-sized particles. 4) Decreasing sulphur dioxide concentration was found to decrease the sulphuric acid concentration in the atmosphere. We were able to introduce a universal proximity measure for sulphuric acid concentration. CCN concentration was found to increase when sulphur dioxide concentration was decreased. 

The work presented in this thesis increases our understanding of the formation and growth processes of new particles. The trace gases and meteorological variables that participate directly in the processes or indicate the conditions needed for the processes to take place are specified. The study also gives tools for the global atmospheric models to get more precise results without the need for increased computational resources. 

The doctoral dissertation of Santtu Mikkonen entitled “Statistical studies of atmospheric nanoparticles and their precursors” will be examined at the Faculty of Science and Forestry. The opponent in the public examination is Docent Miikka Dal Maso from the University of Helsinki and the custos is Professor Ari Laaksonen of the University of Eastern Finland.

Photo available for download at http://www.uef.fi/vaitoskuvat

Contact: Santtu Mikkonen, santtu.mikkonen@uef.fi, tel. +358 040 355 2319

Publishing year: 2011

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