Abstract
Abstract. The Global Atmospheric Watch research station at Mace Head (Ireland) offers the possibility to sample some of the cleanest air masses being imported into Europe as well as some of the most polluted being exported out of Europe. We present a statistical cluster analysis of the physical characteristics of aerosol size distributions in air ranging from the cleanest to the most polluted for the year 2008. Data coverage achieved was 75% throughout the year. By applying the Hartigan-Wong k-Means method, 12 clusters were identified as systematically occurring. These 12 clusters could be further combined into 4 categories with similar characteristics, namely: coastal nucleation category (occurring 21.3 % of the time), open ocean nucleation category (occurring 32.6% of the time), background clean marine category (occurring 26.1% of the time) and anthropogenic category (occurring 20% of the time) aerosol size distributions. The coastal nucleation category is characterised by a clear and dominant nucleation mode at sizes less than 10 nm while the open ocean nucleation category is characterised by a dominant Aitken mode between 15 nm and 50 nm. The background clean marine aerosol exhibited a clear bimodality in the sub-micron size distribution, with although it should be noted that either the Aitken mode or the accumulation mode may dominate the number concentration. However, peculiar background clean marine size distributions with coarser accumulation modes are also observed during winter months. By contrast, the continentally-influenced size distributions are generally more monomodal (accumulation), albeit with traces of bimodality. The open ocean category occurs more often during May, June and July, corresponding with the North East (NE) Atlantic high biological period. Combined with the relatively high percentage frequency of occurrence (32.6%), this suggests that the marine biota is an important source of new nano aerosol particles in NE Atlantic Air.
Highlights
The parameters of the atmospheric aerosols are poorly characterized in global climate models
Our study shows similar results to the ones reported by Yoon et al (2007), and further discussions on the seasonality of Scanning Mobility Particle Sizer (SMPS) clusters associated with this type are provided
Aerosol size distributions sampled at Mace Head (Ireland) during the EUCAARI year (2008, 75 % data coverage) were analysed by the k-means clustering technique
Summary
The parameters of the atmospheric aerosols are poorly characterized in global climate models. Different states of the aerosol were determined by using a novel application of cluster analysis, which uses the degree of similarity and difference between individual observation to define the groups and to assign group memberships One advantage of this clustering method over providing an average of aerosol size distributions is that it does provide a specific number of size distributions which can be compared across different time periods (Beddows et al, 2009). Charron et al (2007) presented an examination of the source signature or origin signature represented by particle number size distribution and modal diameters measured at a rural receptor size in southern England while Beddows et al (2009) was able to reduce the complexity of the different rural, urban, and curbside atmospheric particle size data according to the temporal and spatial trends of the clusters. Whilst a number of intensive field studies have been focusing on average monthly datasets, clustering analysis on year long particle size distributions measurements are scarce (Engler et al, 2007; Kivekas et al, 2009; Venzac et al, 2009)
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