A look at aerosol formation using data mining techniques

Atmospheric aerosol particle formation is frequently observed throughout the atmosphere, but despite various attempts of explanation, the processes behind it remain unclear. In this study data mining techniques were used to find the key parameters needed for atmospheric aerosol particle formation to occur. A dataset of 8 years of 80 variables collected at the boreal forest station ( SMEAR II) in Southern Finland was used, incorporating variables such as radiation, humidity, SO2, ozone and present aerosol surface area. This data was analyzed using clustering and classification methods. The aim of this approach was to gain new parameters independent of any subjective interpretation. This resulted in two key parameters, relative humidity and preexisting aerosol particle surface ( condensation sink), capable in explaining 88% of the nucleation events. The inclusion of any further parameters did not improve the results notably. Using these two variables it was possible to derive a nucleation probability function. Interestingly, the two most important variables are related to mechanisms that prevent the nucleation from starting and particles from growing, while parameters related to initiation of particle formation seemed to be less important. Nucleation occurs only with low relative humidity and condensation sink values. One possible explanation for the effect of high water content is that it prevents biogenic hydrocarbon ozonolysis reactions from producing sufficient amounts of low volatility compounds, which might be able to nucleate. Unfortunately the most important biogenic hydrocarbon compound emissions were not available for this study. Another effect of water vapour may be due to its linkage to cloudiness which may prevent the formation of nucleating and/or condensing vapours. A high number of preexisting particles will act as a sink for condensable vapours that otherwise would have been able to form sufficient supersaturation and initiate the nucleation process.