A look at aerosol formation using data mining techniques

[摘要] Atmospheric aerosol particle formation isfrequently observed throughout the atmosphere, but despitevarious attempts of explanation, the processes behind it remain unclear. In this study data miningtechniques were used to find the key parameters needed for atmospheric aerosol particle formationto 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 clusteringand classification methods. The aim of this approach was to gain new parameters independentof any subjective interpretation. This resulted in two key parameters, relative humidity andpreexisting aerosol particle surface (condensation sink), capable in explaining 88%of the nucleation events. The inclusion of any further parameters did not improve theresults notably. Using these two variables it was possible to derivea nucleation probabilityfunction. Interestingly, the two most important variables are related to mechanisms thatprevent the nucleation from starting andparticles from growing, while parameters relatedto initiation of particle formation seemed to be less important.Nucleation occurs only with low relative humidity and condensation sink values.One possibleexplanation for the effect of high water content is that it prevents biogenic hydrocarbonozonolysis reactions from producing sufficient amounts of low volatility compounds, which might beable to nucleate. Unfortunately the most important biogenic hydrocarbon compound emissions were notavailable for this study.Another effect of water vapour may be due to its linkage to cloudiness which may prevent theformation of nucleating and/or condensing vapours.A high number of preexisting particles will act as a sink for condensable vapours that otherwise wouldhave been able to form sufficient supersaturation and initiate the nucleation process.

[学科分类] 大气科学