Cluster analysis of particulate matter (PM10) and black carbon (BC) concentrations

The monitoring of air-pollution constituents like particulate matter (PM10) and black carbon (BC) can provide information about air quality and the dynamics of emissions. Air quality depends on natural and anthropogenic sources of emissions as well as the weather conditions. For a one-year period the diurnal concentrations of PM10 and BC in the Port of Koper were analysed by clustering days into similar groups according to the similarity of the BC and PM10 hourly derived day-profiles without any prior assumptions about working and non-working days, weather conditions or hot and cold seasons. The analysis was performed by using k-means clustering with the squared Euclidean distance as the similarity measure. The analysis showed that 10 clusters in the BC case produced 3 clusters with just one member day and 7 clusters that encompasses more than one day with similar BC profiles. Similar results were found in the PM10 case, where one cluster has a single-member day, while 7 clusters contain several member days. The clustering analysis revealed that the clusters with less pronounced bimodal patterns and low hourly and average daily concentrations for both types of measurements include the most days in the one-year analysis. A typical day profile of the BC measurements includes a bimodal pattern with morning and evening peaks, while the PM10 measurements reveal a less pronounced bimodality. There are also clusters with single-peak day-profiles. The BC data in such cases exhibit morning peaks, while the PM10 data consist of noon or afternoon single peaks. Single pronounced peaks can be explained by appropriate cluster wind speed profiles. The analysis also revealed some special day-profiles. The BC cluster with a high midnight peak at 30/04/2010 and the PM10 cluster with the highest observed concentration of PM10 at 01/05/2010 (208.0 μg m−3) coincide with 1 May, which is a national holiday in Slovenia and has very strong tradition of bonfire parties. The clustering of the diurnal concentration showed that various different day-profiles are presented in a cold period, while this is not the case for the hot season. Additional analysis of ship traffic and rain fall data showed that there is no statistically significant difference between the ship gross (bruto) registered tonnage (BRT) values in the case of BC and PM10 clusters, but that there is statistically significant differences between the rain fall in the BC and PM10 clusters. The wind-rose for clusters which included most days in the sampling period indicating that emitted PM10 and BC from Port of Koper were manly transported in the west direction over the sea and in the east direction, where there is in no populated area. Presented analysis showed that both BC and PM10 concentrations were driven by rain intensity and wind speed.

► The BC/PM10 data analysis was performed using k-means clustering.
► Ten-BC and eight-PM10 different typical day-profiles occurred during the one-year.
► The clusters with low daily concentrations include the most days.
► Various different clusters are present in a cold period, but not in the hot season.
► BC pattern reveal a more-pronounced bimodality than PM10 pattern.