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In last decade space-density of monitoring stations increased, in to addition also air pollution modeling made big progress. Using diversity of big data can lead to better knowledge about air pollution at continental scale. The focus of presented study is the data-driven approach using non-negative matrix factorization to provide new insights and to study the characteristic space-time particulate-matter patterns across Europe. We analyzed the PM10 concentrations obtained from 1097 monitoring stations (AirBase data) and the Monitoring Atmospheric Composition and Climate (MACC) modeled fields for a period of 3 years. We distinguished five characteristic patterns obtained from the AirBase data and five patterns from the MACC data. A comparison between the AirBase and MACC data shows a good spatial overlap for the east Europe, central Europe and the Mediterranean patterns. However, it should be noted that an analysis of the MACC data revealed two additional marine patterns: the Celtic and the North Seas. The Po Valley and Balkan patterns were very clearly identified when analyzing the AirBase data. In order to better understand the influence of the synoptic situation on the particulate-matter concentrations the synoptic meteorological situations were additionally analyzed. The cold season, low wind and very stable conditions, which can last for several days, is the most common situation linked to high concentrations of anthropogenic air pollution with particulate matter. In contrast, for the Mediterranean pattern the most common situation (high factor loadings) is observed during the summer period. This pattern also exhibits a clearer annual cycle. A closer look at the sea-salt patterns (Celtic and North Seas) shows low time-series correlations between these two factors. Nevertheless, the physical mechanism is the same: a steep gradient between the cyclone and the anti-cyclone that causes high winds and, consequently, higher sea-salt production.

In this work, we characterise the performance of a Sharp optical aerosol sensor model GP2Y1010AU0F. The sensor was exposed to different environments: to a clean room, to a controlled atmosphere with known aerosol size distribution and to the ambient atmosphere on a busy city street. During the exposure, the output waveforms of the sensor pulses were digitised, saved and a following offline analysis enabled us to study the behaviour of the sensor pulse-by-pulse. A linear response of the sensor on number concentration of the monosized dispersed PSL particles was shown together with an almost linear dependence on particle diameters in the 0.4 to 4 micrometer range. The gathered data about the sensor were used to predict its response to an ambient atmosphere, which was observed simultaneously with a calibrated optical particle counter.

In the presented study a comprehensive statistical analysis of the chemical composition of atmospheric particulate matter was carried out. The data were collected from April 2003 to August 2008 with a 7-day time resolution in the Northern Adriatic Port of Koper and analyzed by the Proton Induced X-ray method (PIXE). The Positive Matrix Factorization (PMF) analysis of fifteen chemical elements identified six source factors, three natural-regional sources and three local-anthropogenic sources. Heavy machinery, industry and iron ore factor were marked as anthropogenic sources. Heavy machinery source was represented by the elements V, Ni and Cu. The elements Fe and Mn are attributed to the Iron ore source and were explained by the proximity of the bulk-cargo warehouse and the intense handling of iron ore in Port of Koper. The heavy industry source represented by Pb and Zn was the only anthropogenic factor, which shows clear seasonal pattern. In contrast to the local-anthropogenic source factors, natural and regional source factors show significant negative trend. The reduction of the crustal elements Ca, Ti and Sr, joined in a soil source, and sulfur-biomass source, represented by elements K and S, have been attributed to more intense precipitation and to the negative trend of the North Atlantic Oscillation (NAO) index. The negative trend of the Cl and Br elements was in line with the negative trend of the wind speed above the sea surface and the significant sea-wave height.

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.