The place of ukraine in Europe according to the level of air pollution using earth remote sensing data

Problem statement. Nitrogen dioxide (NO2) is a very toxic gas and is one of the major air pollutants in Europe [1]. Aerosols and, especially particulate matter (PM2.5, PM10), are considered to be the primary causes of lung diseases [2]. Carbon monoxide (CO) reduces oxygen delivery to the heart and brain [3] while carbon dioxide (CO2) is one of the main greenhouse gases. It is important for a country to comply with international agreements restricting pollutant emissions, for example, Kyoto protocol [4]. The locations of air pollution hot-spots largely influence budget allocation decisions. Today, air pollution data come mainly from irregularly spaced network of ground-based stations [5]. Many EU countries as well as Ukraine have large areas without air quality control stations [6]. It is impossible to obtain a complete picture of typical air pollution pattern over the whole Europe using only these data. Satellite Earth remote sensing delivers consistent measurements of atmospheric pollutant concentrations for the whole Europe with high spatial and temporal resolution. Satellite data and new technologies [7] provide a unique chance to consistently compare Ukraine with EU countries.

Task formulation. The research goal is to estimate the relative level of air pollution in Ukraine to other EU countries and identify regions in Europe having highest levels of air pollution. To reach the goal, maps of air pollution risks are built using the method presented below. Maps possess inherent ability to clearly compare regions while new risk assessment method considers a temporal component.
Satellite Earth remote sensing data. Daily values in air column were taken from several radiometers of Terra, Aura and Aqua satellites on regular latitude-longitude grids (table 1, approximate spatial resolution in kilometers is given for 48º latitude). AOT is unitless between -0.05..5, NO2 and CO are in DU (Dobson Units, 1 DU = 2.69 × 1016 molecules/cm2), СO2 is in ppm.

Table 1 – Satellite Earth remote sensing data




Time interval

Nitrogen dioxide (NO2)


27,5×18 km

01.10.2004  20.06.2012

Aerosol optical thickness, AOT


110×72 km


Carbon monoxide (CO)


110×72 km


Carbon dioxide (СO2)


220×144 km


Air pollution risk assessment 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 as R(a, b)=S(a, b) / T, where S(a, b) is the number of observations with a pollutant concentration between a..b while T is the total number of days for which pollutant measurements are not missing due to clouds or other reasons. Both

S(a, b) and T are calculated using the whole available time interval (table 1).
Pollution categories were experimentally selected. For NO2 the interval between  0.0..0.2 DU is considered to be low pollution level, 0.2..0.4 DU – moderate (fig. 1), 0.4..0.6 DU – high, 0.6..0.8 DU – very high, over 0.8 DU – catastrophic. For AOT: 0.0..0.2 – very low, 0.2..0.4 – low, 0.4..0.6 – moderate (fig. 2a), 0.6..0.8 – high, 0.8..1.0 – very high, 1.0..5.0 – catastrophic. For CO: less 100 DU – low, 100..150 DU – moderate (fig. 2b), over 150 DU – high.

Risk (map of Europe)

Risk (map of Ukraine)


Fig. 1. Risk of moderate level of air pollution by nitrogen dioxide (NO2)






Fig. 2. Risk of moderate level of air pollution by (a) aerosols and (b) carbon monoxide (CO)

∆ ppm

Fig. 3. The map of mean differences of СO2 trends

Conclusions. The presented risk calculation technique is simple yet delivers extensive understanding of air pollution character. Due to good mixing, monthly mean concentration of CO2 over Ukraine, US, China, Western Europe and North Pole can be considered the same. Electronic copy of this paper with colored maps is also freely available http_wikience_donntu_edu_ua/rodriges.
Results. The highest levels of air pollution by nitrogen dioxide in Europe are observed over Germany, Belgium, Netherlands and southern part of the North Sea as well as over large cities. The highest levels of air pollution by aerosols in Europe are observed over the north of Italy (cut from the map to prevent dimming of its remaining part). The stripe is identified over which the highest risk levels of air pollution by aerosols are found over the rest of Europe.
For each cell of global regular latitude-longitude grid 2,0°×2,5° time series of CO2 concentrations are built [7]. From monthly mean values for each time series trends were extracted using STL method [8] and mean difference ∆ppm was calculated as follows. Let v = <v1, v2, …, v98> and w = <w1, w2, …, w98> – extracted trends from arbitrary and fixed cell correspondingly during the computation. The 98 is the number of months since January, 2004 till February, 2012. Mean difference ∆ppm for trend v equals (vi – wi)/98, where i= 1, 2,…, 98. By adding to ∆ppm the minimum among all obtained mean differences, the map on fig. 3 is obtained. Only 16 colors were used to increase the contrast.

1. European Environment Agency, Air quality in Europe – 2012 report, EEA Report No 4/2012.
2. Ozone and particulates most serious air quality problems in Europe – European Environment Agency [Electronic resource]
3.Carbon Monoxide [Electronic resource]
4.Kyoto Protocol Documents [Electronic resource]
5.AirBase database [Electronic resource]
6. Environmental Monitoring System in Ukraine, Air Pollution Observations [Electronic resource]
7. Rodriges Zalipynis, R.A. Representing Earth remote sensing data as time series / Sc. Works of Donetsk National Technical University, Series Information analysis and information technology in environment and society, №1(2) – 2(3), 2012. – 212 pp. – P. 135 – 145.
8. Cleveland, R. Seasonal-trend decomposition procedure based on LOESS / R. Cleveland, W. Cleveland, J.E. McRee // Journal of Official Statistics, № 6, 1990. – P. 3 – 73.


The place of ukraine in europe according to the level of air pollution using earth remote sensing data [Електронний ресурс]  / [Rodriges Zalipynis R.A.] // Режим доступу:

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