The spatial variability of PM₂.₅ over Europe using satellite POLDER-3/PARASOL data
The paper presents the results of the monthly mean PM₂.₅ analysis in the period from 2005 to 2013 over the Europe based on the connection between daily fine particle concentrations (PM₂.₅) by surface in-situ measurements in AIRBASE network and column aerosol optical thickness (AOT) derived from POLD...
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Головна астрономічна обсерваторія НАН України
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| Цитувати: | The spatial variability of PM₂.₅ over Europe using satellite POLDER-3/PARASOL data / A. Bovchaliuk // Advances in Astronomy and Space Physics. — 2013. — Т. 3., вип. 2. — С. 102-108. — Бібліогр.: 27 назв. — англ. |
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Bovchaliuk, A. 2017-06-07T18:21:23Z 2017-06-07T18:21:23Z 2013 The spatial variability of PM₂.₅ over Europe using satellite POLDER-3/PARASOL data / A. Bovchaliuk // Advances in Astronomy and Space Physics. — 2013. — Т. 3., вип. 2. — С. 102-108. — Бібліогр.: 27 назв. — англ. 2227-1481 https://nasplib.isofts.kiev.ua/handle/123456789/119625 The paper presents the results of the monthly mean PM₂.₅ analysis in the period from 2005 to 2013 over the Europe based on the connection between daily fine particle concentrations (PM₂.₅) by surface in-situ measurements in AIRBASE network and column aerosol optical thickness (AOT) derived from POLDER-3/PARASOL satellite sensor. The regression function between PM₂.₅ and AOT was derived from measurements done over Europe in the period from April to October 2007. Considering 749 match-up data points over 20 fine particle monitoring sites, we found that the POLDER-3/PARASOL derived AOT at 865 nm is correlated with collocated PM₂.₅ measurements with a correlation coeficient 0.62 (RMS = 3.26). According to the obtained linear regression PM2.5 = 73.4 × AOT865 + 9.6, a signi cant o set caused an introduction of the threshold of 0.01 in monthly mean AOT for assessment of PM₂.₅ based on satellite data. Therefore, only PM₂.₅ values larger than 10.3 µg/m³ can be obtained using this method. According to results the monthly mean PM₂.₅ in the period from 2005 to 2013 over the Europe is usually characterised by values less than 12 µg/m³ (classified as "good" by Air Quality Categories, AQC), but values ranging from 12 to 18 µg/m³ (classified as "moderate") are found in the densely populated and industrial areas, such as the Netherlands, Belgium, the Ruhr and Danube area, Northern Italy, Poland, Romania and Eastern Ukraine. Additionally, the maximum values of PM₂.₅ over Eastern Europe are observed during forest, peat and agricultural wildfires in May 2006 (15-21 µg/m³), April 2009 (14-18 µg/m³) and August 2010 (35-55 µg/m³, classi-fied as "unhealthy for sensitive groups"). An extended set of aerosol parameters including particle size distribution, complex refractive index, as well as parameters characterising aerosol particle shape and vertical distribution will be analysed in the future work. This study was supported by Award No. UKG2-2969-KV-09 of the U.S. Civilian Research & Development Foundation (CRDF) and by the projects M/115-2012, and F41/106-2012 of Derzhinformnauka, and PICS 2013-2015 of CNRS and NASU, and the project 11BF051-01-12 of the Taras Shevchenko National University of Kyiv. The author thanks the ICARE Data and Services Center team for providing access to the POLDER-3 data and for general assistance and development support. The author acknowledges all network operators that submitted their data to the AIRBASE database. The author is grateful to G. Milinevsky, V. Danylevsky, V. Bovchaliuk, P. Goloub, O. Dubovik, F. Ducos, M. Sosonkin and anonymous referee for detailed comments and useful suggestions. en Головна астрономічна обсерваторія НАН України Advances in Astronomy and Space Physics The spatial variability of PM₂.₅ over Europe using satellite POLDER-3/PARASOL data Article published earlier |
| institution |
Digital Library of Periodicals of National Academy of Sciences of Ukraine |
| collection |
DSpace DC |
| title |
The spatial variability of PM₂.₅ over Europe using satellite POLDER-3/PARASOL data |
| spellingShingle |
The spatial variability of PM₂.₅ over Europe using satellite POLDER-3/PARASOL data Bovchaliuk, A. |
| title_short |
The spatial variability of PM₂.₅ over Europe using satellite POLDER-3/PARASOL data |
| title_full |
The spatial variability of PM₂.₅ over Europe using satellite POLDER-3/PARASOL data |
| title_fullStr |
The spatial variability of PM₂.₅ over Europe using satellite POLDER-3/PARASOL data |
| title_full_unstemmed |
The spatial variability of PM₂.₅ over Europe using satellite POLDER-3/PARASOL data |
| title_sort |
spatial variability of pm₂.₅ over europe using satellite polder-3/parasol data |
| author |
Bovchaliuk, A. |
| author_facet |
Bovchaliuk, A. |
| publishDate |
2013 |
| language |
English |
| container_title |
Advances in Astronomy and Space Physics |
| publisher |
Головна астрономічна обсерваторія НАН України |
| format |
Article |
| description |
The paper presents the results of the monthly mean PM₂.₅ analysis in the period from 2005 to 2013 over the Europe based on the connection between daily fine particle concentrations (PM₂.₅) by surface in-situ measurements in AIRBASE network and column aerosol optical thickness (AOT) derived from POLDER-3/PARASOL satellite sensor. The regression function between PM₂.₅ and AOT was derived from measurements done over
Europe in the period from April to October 2007. Considering 749 match-up data points over 20 fine particle monitoring sites, we found that the POLDER-3/PARASOL derived AOT at 865 nm is correlated with collocated PM₂.₅ measurements with a correlation coeficient 0.62 (RMS = 3.26). According to the obtained linear regression PM2.5 = 73.4 × AOT865 + 9.6, a signi cant o set caused an introduction of the threshold of 0.01 in monthly mean AOT for assessment of PM₂.₅ based on satellite data. Therefore, only PM₂.₅ values larger than 10.3 µg/m³ can be obtained using this method. According to results the monthly mean PM₂.₅ in the period from 2005 to 2013 over the Europe is usually characterised by values less than 12 µg/m³ (classified as "good" by Air Quality Categories, AQC), but values ranging from 12 to 18 µg/m³ (classified as "moderate") are found in the densely populated and industrial areas, such as the Netherlands, Belgium, the Ruhr and Danube area, Northern Italy, Poland, Romania and Eastern Ukraine. Additionally, the maximum values of PM₂.₅ over Eastern Europe are observed during forest, peat and agricultural wildfires in May 2006 (15-21 µg/m³), April 2009 (14-18 µg/m³) and August 2010 (35-55 µg/m³, classi-fied as "unhealthy for sensitive groups"). An extended set of aerosol parameters including particle size distribution, complex refractive index, as well as parameters characterising aerosol particle shape and vertical distribution will be analysed in the future work.
|
| issn |
2227-1481 |
| url |
https://nasplib.isofts.kiev.ua/handle/123456789/119625 |
| citation_txt |
The spatial variability of PM₂.₅ over Europe using satellite POLDER-3/PARASOL data / A. Bovchaliuk // Advances in Astronomy and Space Physics. — 2013. — Т. 3., вип. 2. — С. 102-108. — Бібліогр.: 27 назв. — англ. |
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AT bovchaliuka thespatialvariabilityofpm25overeuropeusingsatellitepolder3parasoldata AT bovchaliuka spatialvariabilityofpm25overeuropeusingsatellitepolder3parasoldata |
| first_indexed |
2025-11-25T15:45:25Z |
| last_indexed |
2025-11-25T15:45:25Z |
| _version_ |
1850517124802412544 |
| fulltext |
The spatial variability of PM2.5 over Europe
using satellite POLDER-3/PARASOL data
A.Bovchaliuk
∗
Advances in Astronomy and Space Physics, 3, 102-108 (2013)
© A.Bovchaliuk, 2013
Space Physics Laboratory, Astronomy and Space Physics Department,
Taras Shevchenko National University of Kyiv, Volodymyrska str. 64/13, 01601 Kyiv, Ukraine
The paper presents the results of the monthly mean PM2.5 analysis in the period from 2005 to 2013 over the
Europe based on the connection between daily �ne particle concentrations (PM2.5) by surface in-situ measure-
ments in AIRBASE network and column aerosol optical thickness (AOT) derived from POLDER-3/PARASOL
satellite sensor. The regression function between PM2.5 and AOT was derived from measurements done over
Europe in the period from April to October 2007. Considering 749 match-up data points over 20 �ne particle
monitoring sites, we found that the POLDER-3/PARASOL derived AOT at 865 nm is correlated with collocated
PM2.5 measurements with a correlation coe�cient 0.62 (RMS = 3.26). According to the obtained linear regression
PM2.5 = 73.4×AOT865 + 9.6, a signi�cant o�set caused an introduction of the threshold of 0.01 in monthly mean
AOT for assessment of PM2.5 based on satellite data. Therefore, only PM2.5 values larger than 10.3µg/m3 can be
obtained using this method. According to results the monthly mean PM2.5 in the period from 2005 to 2013 over the
Europe is usually characterised by values less than 12µg/m3 (classi�ed as �good� by Air Quality Categories, AQC),
but values ranging from 12 to 18µg/m3 (classi�ed as �moderate�) are found in the densely populated and industrial
areas, such as the Netherlands, Belgium, the Ruhr and Danube area, Northern Italy, Poland, Romania and Eastern
Ukraine. Additionally, the maximum values of PM2.5 over Eastern Europe are observed during forest, peat and
agricultural wild�res in May 2006 (15�21µg/m3), April 2009 (14�18µg/m3) and August 2010 (35�55µg/m3, classi-
�ed as �unhealthy for sensitive groups�). An extended set of aerosol parameters including particle size distribution,
complex refractive index, as well as parameters characterising aerosol particle shape and vertical distribution will
be analysed in the future work.
Key words: aerosols, PM2.5, atmosphere, AOT, pollution
introduction
Atmospheric aerosols are conventionally de�ned
as particles suspended in air having radius in the
range from 0.001µm to 100µm [7]. These particles
have a signi�cant negative e�ects on human health
[23], including lung cancer, asthmatic symptom, pul-
monary in�ammation and cardiopulmonary mortal-
ity. The solution of many practical problems in the
�eld of environmental and human health protection
is connected with needs for high quality information
about pollution level and the physicochemical prop-
erties of atmospheric aerosols.
The particulate matter (PM) mass, also known
as air pollution, is a generally accepted means to
quantify the amount of aerosols in the atmosphere
and is used as a standard to evaluate air quality
by United States Environmental Protection Agency1
(EPA). Fine fraction of particulate matter (PM2.5,
µg/m3) is the integrated mass of aerosols with di-
ameter up to 2.5µm that is generally resulted from
combustion, including motor vehicles, power plants,
forest wild�res, and agricultural burning. The EPA
has established that the 24-hour averaged PM2.5 con-
centration must be less than 35.4µg/m3 for healthy
conditions concerning the whole population. Most
of monitoring stations are located close to major ur-
ban regions leaving large areas without operational
observations. Furthermore, it is widely recognised
that it is problematic to measure the absolute level
of PM2.5 on a routine basis. In routine measure-
ment processes, heating of the air sample is neces-
sary, which partially increase volatilisation of semi-
volatile aerosol components. This in turn leads to
systematic measurement errors depending on mea-
surement technique and aerosol composition. The
limited spatial representativeness and di�erent sys-
tematic errors of national or regional air quality net-
works make it impossible to achieve an air quality
overview across Europe by surface in-situ measure-
ments only.
In addition to surface in-situ measurements of
PM2.5, the monitoring of aerosols and trace gases
from space has been widely used [16, 20, 26]. Pri-
mary aerosol quantity derived from spaceborne re-
mote sensors operated in the visual and IR wave-
∗bovchaliuk@gmail.com
1http://www.epa.gov
102
Advances in Astronomy and Space Physics A.Bovchaliuk
length bands is the aerosol optical thickness (AOT).
The relationship between column AOT derived from
satellite and PM2.5 surface in-situ measurements
has already been explored over the United States
[1, 27], Italy [8] and some populated and indus-
trial regions in Asia [18] using retrievals from the
MODIS radiometer (MODerate Imaging Spectrora-
diometer), and over France [15] based on data from
the POLDER-2 (Polarization and Directionality of
Earth's Re�ectances) satellite instrument.
Currently, the comparison studies between new
satellite radiometer POLDER-3 and PM2.5 surface
in-situ measurements over Europe have not been con-
ducted yet. In the present paper we use the relation
obtained for 2007, being the year when PM2.5 data
were available online. We present results on the spa-
tial distributions of monthly mean PM2.5 values es-
timations based on POLDER-3 data over Europe.
Last section gives an overview of special events and
PM2.5 characteristics in the period from 2005 to 2013
over investigated area.
surface in-situ airbase data
In this paper, the PM2.5 data from the AIR-
BASE database2 were used for determine the rela-
tionship between PM2.5 values and AOT retrieved
from POLDER-3. AIRBASE is a public database
system operated by the European Environmental
Agency (EEA). It provides air quality monitoring
data and associated information submitted by more
than 30 participating countries within Europe [9].
Measurement sites are classi�ed according to the
type of surroundings (urban, suburban, or rural) and
dominant local source (tra�c, industrial, or back-
ground). The reported precision of the measure-
ments is satisfactory (random errors typically less
than 15% for daily averages), and the absolute sys-
tematic uncertainty in these data is estimated to be
19%. The gravimetric methods based on the deter-
mination of the PM2.5 mass fraction of particulate
matter collected on a �lter under ambient conditions
was used to give typically 24-hour averages, while au-
tomatic instrumental methods TEOM (Tapered Ele-
ment Oscillating Microbalance) and Beta Absorption
provided hourly data [21]. In the Beta Absorption
and TEOM methods, the sampled air is heated be-
fore collecting the aerosols on a �lter to avoid hu-
midi�cation of the �lter. This procedure is known
to lead to loss of semi-volatile aerosol components.
The extent to which volatilisation occurs depends
on time and space dependent chemical composition
of the aerosols, and the measurement technique. To
correct for systematic errors, correction factors are
generally applied to the measured data, but these
di�er by 30% or more between countries [6]. Conse-
quently, systematic di�erences between territories of
measurements may be present in the data due to use
of di�erent methods. However, the data from AIR-
BASE were used in the form that submitted by the
countries. In the comparison of spatial distribution
of AOT and PM2.5, 17 rural and 3 suburban back-
ground stations have been analysed. The stations
were selected in Austria, Belgium, Cyprus, Czech
Republic, Finland, France, Germany, Italy, Latvia,
Netherlands, Slovenia, Spain, Sweden, Switzerland
and the United Kingdom to present di�erent under-
lying surfaces (need for satellite retrieval) and aerosol
loading. According to standard data from stations,
the 24-hour averaged PM2.5 values were used in anal-
ysis.
satellite polder-3/parasol data
A unique set of observations on the global aerosol
distribution has been acquired by the POLDER-
3 instrument that was installed aboard French mi-
crosatellite PARASOL in December 2004 and col-
lected data in the period from March 2005 to
September 2013. The instrument carried out multi-
spectral (443, 490, 565, 670, 763, 765, 865, 910 and
1020 nm), multi-directional (as many as 16 direc-
tions within the scope of 100◦ approximately along
the ground trace) measurements of intensity and lin-
ear polarization degree of the back-scattered solar
radiation [25]. The current standard aerosol inver-
sion strategy detailed in [10] is based on the look-up
tables approach, where the re�ected radiances are
simulated for 10 aerosol models with log-normal size
distributions of particles with e�ective radius from
0.075 to 0.225µm and a complex refractive index of
1.47�0.01i. This inversion can be used to character-
ize the �ne mode aerosols with particle size < 0.3µm
[2, 5, 11]. According to the cloud-screening algorithm
[4] the cloud-free pixels were processed only. The
surface contribution to the polarized re�ectance was
based on a priori values (as a function of observation
geometry and surface type) derived from statistical
analysis of POLDER-1 data [22]. The aerosol param-
eters were adjusted to give the best agreement be-
tween the measured and simulated multidirectional
polarized radiances at 490, 670 and 865 nm wave-
lengths.
The spectroradiometer POLDER-3 data were
processed and described at the project web-page3.
The spatial resolution of POLDER-3 instrument was
16 km× 18 km in the AOT. The aerosol characteris-
tics accuracy has been estimated over ocean [12, 13]
and land [5, 11], where correlation with AERONET
(AErosol RObotic NETwork) [14] data is equal to
0.77�0.95 depending on location of measurement and
aerosol type. For example, the correlation coe�-
cients for the POLDER-3 and AERONET AOT re-
trieval comparisons are equal: 0.78 for Moscow site,
2http://acm.eionet.europa.eu/databases/airbase/
3http://www.icare.univ-lille1.fr/parasol
103
Advances in Astronomy and Space Physics A.Bovchaliuk
0.76 � Minsk, 0.86 � Belsk, 0.81 � Moldova, 0.93 �
Kyiv and 0.63 for Sevastopol sites [2].
comparison between aot and pm2.5
The satellite overpass time for the investigated
territory was 10:00�11:30UT depending on the orbit
and geometry of measurements. The POLDER-3 de-
rived AOT values at 865 nm were selected from each
pixel (16 km× 18 km) covered the PM2.5 surface in-
situ stations. It should be noted that the amount
of data increased for the sites at lower latitudes and
larger number of sunshine days. For latitudes above
50◦N, data were not available in winter, because the
solar elevation is too low at these latitudes to allow
AOT retrieval. The underlying surface in the inves-
tigated territory varies highly in spring and autumn
due to variable vegetative cover. Moreover, the sur-
face impact on polarization is relatively greater when
the amount of aerosol in the atmosphere is small.
Fig. 1: Regression line between POLDER-3/PARASOL
derived AOT at 865 nm and PM2.5 measured at the sur-
face over 20 stations in Europe from April to October
2007.
For deriving the regression function PM2.5 ver-
sus AOT the 24-hour averaged PM2.5 values were
selected from 20 stations in Europe with more than
75% of valid measurements in the period from April
to October 2007. Than we excluded AOT zero val-
ues obtained by POLDER-3 (lack of phase angles,
glint or impossibility of retrievals) from analysis as
well. Taking into account the above requirements the
comparison was performed between POLDER-3 de-
rived AOT and PM2.5 values and presented in Fig. 1.
The overall match-up database corresponds to 749
comparison points. A signi�cant o�set 9.6µg/m3 in-
dicates that the satellite has a limited capacity for
monitoring small amounts of aerosols. The slope of
the regression contributes to 73.4µg/m3 per AOT
unit (RMS = 3.26). The correlation coe�cient is es-
timated as 0.62. The deviation could be explained
by the rough spatial resolution of the POLDER-3
instrument comparing to the local station. Besides,
the relationship between PM2.5 and AOT strongly
depends on vertical pro�le and aerosols type with
similar optical properties that will be evaluated in
the future study.
The comparison of relation between POLDER-3
AOT and PM2.5 with those previously established
using MODIS is complicated by the in�uence of sev-
eral factors, like using PM10 instead of PM2.5 [8, 18],
di�erent wavelengths and spatial resolutions for the
satellite AOT [27], di�erent time periods, and di�er-
ent sensitivity of the sensors to �ne particles [5]. For
example, the local study over Alabama [27] demon-
strates that the slope is equal to 71µg/m3 per AOT
unit using PM2.5 based on MODIS data that is in a
good agreement with the results presented here.
Since the PM2.5 values lie in the range from 3.2
to 33.8µg/m3, it can be argued that no speci�c
events occurred in the days of comparison. PM2.5
values larger than 35.4µg/m3 are not presented,
which characterise this match-up data by two �rst
categories according to the EPA Air Quality Cate-
gories (AQC) [27], i. e. below 12µg/m3 (classi�ed
as �good�) and between 12.1µg/m3 and 35.4µg/m3
(classi�ed as �moderate�). Besides, the AOT at
870 nm over Europe during 2003�2011 years was
characterized by values ranging from 0.002 to 0.2,
except the period of July�August 2010 with strong
forest and peat wild�res when the AOT typical val-
ues ranged from 0.3 to 0.5 [2].
spatial distributions
of monthly mean pm2.5
Based on analysis presented in previous section,
it is possible to estimate the spatial distributions of
monthly mean PM2.5 using POLDER-3/PARASOL
AOT data during 2005�2013 over Europe. Never-
theless, a signi�cant o�set 9.6µg/m3 indicates that
atmosphere with small amount of aerosols cannot be
represented on the maps. Thus, in order to decrease
the uncertainties in determining PM2.5 the threshold
of 0.01 was applied for monthly mean AOT values.
This threshold was chosen due to increasing uncer-
tainties in determining AOT when the amount of
aerosol in the atmosphere is small. According to lin-
ear regression (Fig. 1) only PM2.5 values larger than
10.3µg/m3 can be obtained using this method.
The monthly mean PM2.5 values for August
month through 2005�2013 except 2010 are presented
in Fig. 2. The territory is usually characterised by
PM2.5 values less 12µg/m3. In general, there are
some changes in distribution of aerosol pollution in
the same month from year to year due to regional
emissions, variable transboundary transfers and dif-
104
Advances in Astronomy and Space Physics A.Bovchaliuk
ferent quantity of sunshine days for averaging. In
addition, areas with moderate PM2.5 values (12�
18µg/m3) were found in the densely populated and
industrial regions of Europe. It should be noted
that analysis of aerosol pollution over these areas
was based on POLDER-3 data retrieved during the
period from April 2005 to September 2013.
According to [24] the MODIS instrument ob-
served emissions from agricultural �res in the Baltic
countries, Belarus, Ukraine and Russia in April and
May 2006. The PM2.5 shows the high values ranging
in 15�21µg/m3 in May 2006 over Belarus, North-
ern Ukraine and west of the European part of Rus-
sia seen in Fig. 3a, which was caused by biomass
burning particles appeared during this event. More-
over, values 18�21µg/m3 were observed over Fin-
land which can be explained by transportation of
these particles from wild�res that caused the most
severe air pollution episode over the recorded period
at research stations in Svalbard [19]. Furthermore,
the aerosol transboundary transportation from for-
est and brushwood �res in the European part of Rus-
sia in April 2009 produced increased PM2.5 values of
14�18µg/m3 over Ukraine, Romania, Moldova and
Eastern Belarus (Fig. 3b). As one can seen from
Fig. 3a and Fig. 3b the PM2.5 values in the range of
17�19µg/m3 were observed over Belgium, Nether-
lands, and Germany Ruhr area, that equally char-
acterizes these industrial area in the spring of 2006
and 2009.
The maximum PM2.5 values were revealed in
August 2010 (Fig. 3c) that corresponds to wild-
�res in the centre of the European part of Rus-
sia [17]. Monthly mean values are ranged from
35 to 55µg/m3 over Moscow, Nizhniy Novgorod,
Ryazan, Tula and Vladimir regions, and accord-
ing to the AQC criteria this period can be classi-
�ed as �unhealthy for sensitive groups�. Moreover,
the biomass burning aerosols transboundary trans-
portation to Ukraine [3], Belarus, Lithuania, Latvia
and Estonia was observed with PM2.5 values from
20 to 35µg/m3 (Fig. 3c). For comparison to the
presented events the monthly average PM2.5 val-
ues for April 2013 are given in Fig. 3d, which are
probably characterised by presence of anthropogenic
aerosols over all Europe, particularly over East Ger-
many (17�19µg/m3), Northern Italy (15�18µg/m3),
Central and Northern France (13�16µg/m3), Cen-
tral Ukraine and Moldova (12�15µg/m3). The short
time events (hours, days) were not presented in this
study due to monthly averaging data.
conclusions
The AOT values retrieved from POLDER-3 data
during 2005�2013 over Europe have been used
to characterize aerosol pollution near the surface.
POLDER-3 AOT retrieval algorithm over land is
based on the measurement of the linear polariza-
tion of the light backscattered to space. It should
be emphasised that standard algorithm is particu-
larly sensitive to �ne mode aerosols that polarize
the signal. The relationship between column aerosol
optical thickness derived from satellite POLDER-
3/PARASOL and observed PM2.5 by surface in-situ
measurements is not straightforward and depends on
the vertical distribution of the particles and their
optical and microphysical properties. The uncer-
tainties of both types of measurements should be
taken into consideration as well. In the case of
the satellite inversion algorithm the major in�u-
ence of the surface and the spatial resolution pro-
duce those uncertainties. However, the POLDER-
3/PARASOL derived AOT at 865 nm is fairly well
correlated with collocated daily PM2.5 measurements
(PM2.5 = 73.4×AOT865 + 9.6). The correlation co-
e�cient 0.62 and slope of the regression 73.4µg/m3
per AOT unit (RMS = 3.26) are derived based on
AIRBASE data from 20 stations in Europe consid-
ered in the present study. Consequently, a signi�cant
o�set caused an introduction of the threshold of 0.01
in monthly mean POLDER-3/PARASOL AOT for
assessment of PM2.5 based on satellite data.
With the aim to provide possible explanations
for the general agreement and di�erences between
aerosol properties retrieved from satellites and those
observed at surface in-situ stations, in future work we
will analyse an extended set of aerosol parameters in-
cluding particle size distribution, complex refractive
index, as well as parameters characterizing aerosol
particle shape and vertical distribution. It is planned
to use GEOS-Chem model for retrieving the distri-
bution of aerosol mass and AOT with a transport
time step of 15min to calculate PM2.5 with better
precision.
The spatial distributions of monthly mean PM2.5
using POLDER-3/PARASOL AOT data have been
�rstly estimated over Europe in 2005�2013. The Eu-
rope territory is usually characterised by PM2.5 up to
12µg/m3, which is lower than in industrial regions
of East Asia and India. The POLDER-3/PARASOL
measurements show the major aerosol source regions
in the Netherlands, Belgium, Germany, Northern
Italy, Eastern Poland and Great Britain, Romania,
Hungary, Moldova, Eastern Ukraine and Belarus, as
well as individual large cities and industrial valleys
(Moscow, London, Rhone, and Danube). The PM2.5
values are ranged from 12 to 18µg/m3 over these
industrial regions in the period from April 2005 to
September 2013. In addition, the maximum values of
PM2.5 (15�21µg/m
3) over Eastern Europe have been
observed during forest, peat and agricultural wild-
�res in May 2006 over Belarus, Finland and North-
ern Ukraine, in April 2009 � 14�18µg/m3 over Euro-
pean part of Russia, Ukraine, Romania, Moldova and
Eastern Belarus, and in August 2010 � 35�55µg/m3
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Advances in Astronomy and Space Physics A.Bovchaliuk
over Moscow, Nizhniy Novgorod, Ryazan, Tula and
Vladimir region in Russia. Aerosol amount during
August 2010 is classi�ed as �unhealthy for sensitive
groups� according to AQC criteria.
acknowledgement
This study was supported by Award No. UKG2-
2969-KV-09 of the U.S. Civilian Research & Devel-
opment Foundation (CRDF) and by the projects
M/115-2012, and F41/106-2012 of Derzhinform-
nauka, and PICS 2013-2015 of CNRS and NASU,
and the project 11BF051-01-12 of the Taras
Shevchenko National University of Kyiv. The author
thanks the ICARE Data and Services Center team
for providing access to the POLDER-3 data and for
general assistance and development support. The
author acknowledges all network operators that sub-
mitted their data to the AIRBASE database. The
author is grateful to G.Milinevsky, V.Danylevsky,
V.Bovchaliuk, P.Goloub, O.Dubovik, F.Ducos,
M. Sosonkin and anonymous referee for detailed com-
ments and useful suggestions.
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Fig. 2: Spatial distributions of monthly mean PM2.5 for August month through 2005�2013 except 2010. White:
missing data or ocean.
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Advances in Astronomy and Space Physics A.Bovchaliuk
Fig. 3: Spatial distributions of monthly mean PM2.5 for: a) May 2006; b) April 2009; c) August 2010; d) April
2013. White: missing data or ocean. Note di�erent scale for August 2010.
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