Ecology/6. Ecologic monitoring


Postgraduate student Rodriges Zalipynis R.A.

Donetsk National Technical University, Ukraine

Risks of air pollution by aerosols over the territory of Europe


Abstract. For the first time, using satellite Earth remote sensing data, the maps of air pollution risks by aerosols over the territory of Europe with spatial resolution of 1.0º×1.0º (approximately 110 km × 72 km for the 48º latitude) were created. The presented risk calculation technique is simple yet delivers extensive understanding of air pollution character. It is shown that the highest levels of air pollution by aerosols in Europe are observed over the north of Italy. The stripe is identified over which the highest risk levels of air pollution by aerosols are found over the rest of Europe.

 Keywords: Earth remote sensing data, atmospheric air, aerosol optical thickness, time series, maps of risk, Europe


Introduction. Today, air pollution data come mainly from the network of ground-based stations the majority of which are located in large cities. The stations deliver point measurements of pollutant concentrations on the height of up to 10 meters over the sea level. In several countries, including Ukraine, aerosols are not measured at all (except of suspended dust). Chemical reactions, air transport of pollutants in the atmosphere and other factors lead to low reliability of the results of numerical modeling in the areas without air quality control stations. It is impossible to obtain a complete and consistent picture of air pollution over the whole territory of Europe using scattered data from ground-based stations.

Satellite Earth remote sensing data provide atmospheric pollutant concentrations with high spatial and temporal resolution. Today, these data are not widely used for solving practical tasks of ecologic monitoring due to extremely high complexity of accessing to them, their visualization and analysis.

Modern ecologic monitoring complex provides new opportunities not available before for solving urgent tasks of environmental protection [1]. The instruments it provides made possible to create maps of air pollution risks by aerosols over the whole territory of Europe using satellite Earth remote sensing data.

High resolution maps of air pollution risks allow to answer many important questions in the domain of ecologic safety. For example, what countries have the highest level of air pollution and what is the relative level of air pollution between different regions inside a country.

Related work. Due to NASA initiatives for providing free of charge remote sensing data, for instance [2], active research is carried out of aerosol optical thickness (AOT) all over the Earth. AOT trend analysis is carried out, including for the atmosphere of Europe [3], aerosol concentrations obtained from satellite radiometers and ground stations are compared [4]. The most extensive ground-based AOT data comes from AERONET network [5]. Satellite Earth remote sensing data are also used for studying aerosol pollution episodes over the territory of Europe during eruption of volcanos [6]. Clarifications of links between AOT and climate variability over the territory of Europe [7] as well as contributions of anthropogenic and natural factors to the AOT level [8] are carried out.

The goal of the research carried out in this paper is to derive the typical picture of air pollution by aerosols over the whole territory of Europe instead of climatological mean or study of individual pollution episodes. The approach proposed below allows to considerably reduce the influence on the resulting risk map of aerosol concentration values not typical for the air over the territory under investigation.

Satellite Earth remote sensing data. Daily AOT values in air column were taken from MODIS radiometer of Terra satellite product available on regular latitude-longitude grid (1.0°×1.0°, about 110 km × 72 km for the 48º latitude) during 01.03.2000 – 05.10.2012. AOT values are unitless and are between -0.05..5 [2]. For each 1.0°×1.0° cell the maximal AOT value was taken among pixels of scenes of level 2 with spatial resolution of 10 km × 10 km that fall into that cell. The maximal values were chosen due to the interest mainly to the pollution of anthropogenic character as well as assumption that maximal AOT values may be observed primarily over cities and areas of impact of industrial enterprises.

For the first time AOT time series were obtained for each grid cell [1]. Time series are directly available from within R analysis environment [9].

Risk calculation method. In this paper, the air pollution risk is defined as the probability of observing a pollutant concentration in a given interval over the territory under investigation. The risk is calculated for each grid cell.

For each grid cell the number of days, S(i), was calculated with AOT concentrations in intervals [0.2 × i]..[0.2 × i + 0.2], were i=0..24 as well as the number of days T for which AOT measurements are not missing due to clouds or other reasons (AOT between -0.05..5).

The risk of pollution for a grid cell is equal to R(i)=S(i) / T.

After experimental study of the typical concentration of AOT over Europe, it was found that step 0.2 allows capturing the majority of features of AOT pollution distribution over Europe. Risk categories were also experimentally selected in order to keep acceptable the number of categories (table 1).


Table 1. – Risk categories of air pollution by aerosols over the territory of Europe


Risk category


Very low








Very high




Results and discussion. Six risks maps have the layout according to the presented earlier categories left to right and top to bottom (fig. 1). Thus, the topmost left map corresponds to the very low risk category (0.0..0.2) while the downmost right map corresponds to the catastrophic risk category (1.0..5.0).

The created maps span the territory of Europe approximately from London (England) on the west to Baku (Azerbaijan) on the east and from Stockholm (Norway) on the north to Tyrant (Greece) on the south. To better perceive the geographical context of the research, the political map of Europe spanning approximately the area under investigation is given on fig. 2.

The region on the north of Italy between 44–46 latitude and 7–13 longitude is cut from all maps except the first two (very low and low risk levels). Big cities located in that region include Turin, Milan, Genoa, Parma, Bologna and Padua. The region was cut due to its extremely high risk values what leads to low detail level of the color bar for the rest part of Europe.

Very low AOT risk levels are typical for Sweden and Norway. On the remaining maps, risks of aerosol pollution for these countries are one of the lowest witnessing about relatively clean (from aerosols) air over these countries. Low risk levels can be also attributed to the atmosphere over the south of France. Grid cells with cities Kiev (Ukraine) and Moscow (Russian Federation) are also noticeable as well as the north of Italy witnessing about low level aerosol content being non-typical in the atmosphere over that grid cells.

Low AOT risk levels reach the highest values both over sea and land. High risk levels are observed in the atmosphere over all seas (Black, Azov, the North Sea, the Balearic, Tyrrhenian, Adriatic). Over land the highest risk levels are observed over the center of the Western Europe (Poland, Germany, Czech Republic, Austria). Although risk levels over seas and land are relatively the same, the observed values over the former may be caused by natural while over the latter by anthropogenic factors. This may take place since the same land area with high risk levels for the low risk category is susceptible also to high risk levels of more severe risk categories as can be seen from the corresponding maps.

Figure 1. – Maps of air pollution risks by aerosols over the territory of Europe


The distinguishable area in the Western Europe has the highest risk levels for moderate, high and very high risk categories. It is shaped as a stripe with northern end consisting of Poland and Germany. It stretches to the south-east through the territories of Slovakia, Hungary, Serbia, Bulgaria and the south of Romania.


Figure 2. – The political map of Europe corresponding to the area for which air pollution risks by aerosols are shown on figure 1


Probably, the maps of moderate, high and very high risk categories are the most representative for identification of industrial regions. These regions include the north of Italy and the characteristic stripe as was noted earlier. Kiev and Moscow cities are still noticeable, however other cities, for example, Paris, Warsaw and Prague have higher risk levels.

Catastrophic AOT risk levels are noticeable over Russian Federation and North and Baltic seas. In the latter case, the territory can be divided on European and Southern (the Republic of Kalmykia, Astrakhan, Atyrau, West Kazakhstan regions) parts of Russian Federation. Probably these risk levels for Russian Federation may be caused primarily by natural disasters, for example, wildfires.

Conclusions and further work. In Europe, the most polluted air by aerosols is over the north of Italy. The air pollution risks by aerosols of high category for that region are 1.6 times higher the risks for the rest of Europe. Big cities located in that region include Turin, Milan, Genoa, Parma, Bologna and Padua.

After the north of Italy, the highest air pollution risks by aerosols in Europe are shaped as a stripe with northern end consisting of Poland and Germany. It stretches to the south-east through the territories of Slovakia, Hungary, Serbia, Bulgaria and the south of Romania. The lowest air pollution risks by aerosols are for Sweden, Norway and southern France.

Further work may be directed to the rating of the European countries according to their risk levels of air pollution by aerosols. The rate of a country can be calculated by aggregating risk levels of grid cells that fall into the administrative boundary of a country. Data with higher spatial resolution may be used, for example, Aura satellite (OMI radiometer). This will allow to carry out a more detail analysis of air pollution inside a separate country. Using data from a climate reanalysis will allow to determine the dependence of aerosol concentration in a grid cell from wind speed and direction. In some cases industrial enterprises can be identified that have the greatest contribution to the aerosol pollution of nearby territories.

Acknowledgements. This work was supported by Award No. UKM1-2973-DO-09 of the U.S. Civilian Research & Development Foundation (CRDF).  Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of CRDF.

Paper availability. Electronic copy of this paper with colored maps is also freely available at



1.       Rodriges Zalipynis, R.A. Representing Earth remote sensing data as time series / R.A. Rodriges Zalipynis // Donetsk National Technical University. Series: System analysis and information technology in environmental and social sciences, №2, 2012.

2.       MODIS Atmosphere [Electronic resource] – Access method: (24.01.2013)

3.       Koukouli, M.E. Signs of a negative trend in the MODIS aerosol optical depth over the Southern Balkans / M.E. Koukouli, S. Kazadzis, V. Amiridis, C. Ichoku, D.S. Balis, A.F. Bais // Atmos. Environ., № 44, 2010, P. 1219–1228.

4.       Yoon, J. Analysis of linear long term trend of aerosol optical thickness derived from SeaWiFS using BAER over Europe and South China / J. Yoon, W. von Hoyningen-Huene, M. Vountas, J.P. Burrows // Atmos. Chem. Phys., № 11, 2011, P. 12149–12167.

5.       Aerosol Robotic Network (AERONET) Homepage [Electronic resource] – Access method: (24.01.2013)

6.       Ansmann, A. The 16 April 2010 major volcanic ash plume over central Europe: EARLINET lidar and AERONET photometer observations at Leipzig and Munich, Germany / A. Ansmann, M. Tesche, S. Gross, V. Freudenthaler, P. Seifert, A. Hiebsch, J. Schmidt, U. Wandinger, I. Mattis, D. Müller, M. Wiegner // Geophys. Res. Lett., № 37, L13810, 2010.

7.       Chiacchio, M. Decadal variability of aerosol optical depth in Europe and its relationship to the temporal shift of the North Atlantic Oscillation in the realm of dimming and brightening / M. Chiacchio, T. Ewen, M. Wild, M. Chin, T. Diehl // J. Geophys. Res., № 116, D02108, 2011.

8.       Streets, D. G. Anthropogenic and natural contributions to regional trends in aerosol optical depth, 1980–2006 / D.G. Streets, F. Yan, M. Chin, T. Diehl, N. Mahowald, M. Schultz, M. Wild, Y. Wu, C. Yu // J. Geophys. Res., № 114, D00d18, 2009.

9.       R: A language and environment for statistical computing [Electronic resource] – Access method: (24.01.2013)