close

Вход

Забыли?

вход по аккаунту

?

s11356-017-0455-7

код для вставкиСкачать
Environ Sci Pollut Res
https://doi.org/10.1007/s11356-017-0455-7
RESEARCH ARTICLE
Signs for secondary buildup of heavy metals in soils
at the periphery of Athens International Airport, Greece
Ioannis Massas 1 & Dionisios Gasparatos 2 & Dafni Ioannou 1 & Dionisios Kalivas 1
Received: 11 July 2017 / Accepted: 9 October 2017
# Springer-Verlag GmbH Germany 2017
Abstract Emissions from civil airports are similar to those
observed in industrial and urban areas. While air pollution
and noise levels are regularly monitored and assessed, information on the status of heavy metals in soils close to airport
facilities is limited. In this study, we monitored and assessed
heavy metal distribution in soils close to Athens International
Airport (AIA) in Attica, Greece. Following a grid sampling
scenario, topsoil samples were collected from 86 sites at the
periphery of AIA and total and available forms of Cu, Zn, Fe,
Mn, Ni, Cr, Pb, and Ba concentrations were determined in
aqua regia and DTPA soil extracts, respectively. Median concentration values for both metal forms are not considered as
particularly high. However, 90th percentile concentration
values for some metals are high, indicating soil enrichment.
Evaluation of enrichment factor (EF) and availability ratio
Responsible editor: Zhihong Xu
Electronic supplementary material The online version of this article
(https://doi.org/10.1007/s11356-017-0455-7) contains supplementary
material, which is available to authorized users.
* Ioannis Massas
massas@aua.gr
Dionisios Gasparatos
gasparatos@agro.auth.gr
Dafni Ioannou
dioannou@aua.gr
Dionisios Kalivas
kalivas@aua.gr
1
Laboratory of Soil Science, Agricultural University of Athens, Iera
Odos 75, 11855 Athens, Greece
2
Laboratory of Soil Science, Aristotle University of Thessaloniki,
54124 Thessaloniki, Greece
(AR) values and EFs spatial distribution have led to consistent
conclusions of secondary and ongoing metal accumulation in
the soils of the studied area. Tessier sequential extraction procedure was applied to 10% of the soil samples and the results
showed high potential availability of Pb, Mn, Cu, and Ni,
further supporting the continuous metal accumulation in the
studied soils.
Keywords Soil . Heavy metals . Airport . Soil pollution
indices . Sequential extraction . Spatial analysis . DTPA
extractable metals
Introduction
Heavy metals occur naturally as chemical elements in the
earth’s crust and surface soils in varying concentrations
(Alloway and Ayres 1997; Chai et al. 2015). Total metal contents in soils are directly related to the nature of the parent
material they are derived from (Alloway 2013). Soils in urban
and rural areas may become contaminated by accumulation of
heavy metals through natural processes and/or human practices. Such metals accumulation in soils can be high enough to
pose risk to human health, plants, animals, and ecosystems
(Antoniadis et al. 2017; D'Amore et al. 2005). In terrestrial
ecosystems, many kinds of interactions between solids, liquids, gases and the biota take place (Giannakopoulou et al.
2012). These interactions can be affected by anthropogenic
factors such as agricultural practices, industrial activities,
and waste treatments. (Kabata-Pendias and Pendias 2001).
Increased heavy metal concentrations in soils have been
recorded for many industrial, urban, rural, and mixed land
uses areas (Shrinivasa Gowd et al. 2010; Bretzel and
Calderisi 2006; Massas et al. 2009; Koulourasis et al. 2009;
Lin et al. 2017). Considering that soils are not a renewable
Environ Sci Pollut Res
resource and that heavy metals do not biodegrade but accumulate in soils, it is necessary to monitor soil metal concentrations to prevent pollution situations and to propose remediation actions if necessary (Massas et al. 2013; Gasparatos
2013).
Airports are considered as potential sources of air pollution
and concerns are raised about the exposure of the population
living in the vicinity of large airports to combustion products
of jet fuels. Adverse health effects, particularly on respiratory
and nervous systems, due to increased noise levels, are
suspected for people working in airports or living in their
neighbor. Tesseraux (2004), reports the conclusion derived
from an air toxic monitoring program at the Chicago O’Hare
Airport, that the emissions of the airport have an impact on the
air quality of the adjacent communities, but that impact does
not result in levels higher than those in a typical urban environment. Iavicoli et al. (2014) support that it is not easy to
directly associate between airport-related air pollution and
health effects on workers and residents. However, other studies support that for 2005, 160 premature deaths in the USA
can be attributed to ambient particulate exposure from airport
emissions while for the same reason 110 deaths occur in UK
each year (Masiol and Harrison 2014, and references therein).
Jet engines are fueled with kerosene which is a complex
mixture of hydrocarbons (HCs). Airplane emissions contain
carbon dioxide (CO2), nitrous oxides (NOx), sulfur oxides
(SOx), hydrocarbons (HCs), volatile organic compounds
(VOCs), and particulate matter (PM10,2.5). In many airports,
classical pollutants like sulfur dioxide, nitrogen oxides, carbon
monoxide, and particles are recorded and monitored on a regular basis. Hudda et al. (2014), recorded four- to fivefold particle number concentrations to distance of about 8–10 km
downwind jet trajectories in Los Angeles International
Airport (LAX). Several studies report on the organic compounds found as combustion products of aircraft engines
(Tesseraux (2004) and references therein; Riley et al.
(2016)). Various methodological and analytical approaches
have been followed to systematically investigate the
composition of soot particles in civil jet engine exhaust but
results regarding metal concentrations are rather limited.
Large amounts of Fe, O, S, Mn and K impurities were
detected by Demirdjian et al. (2007) in soot particles emitted
by an aircraft gas turbine engine. Vander Wal et al. (2014)
investigated jet exhaust particles from different aircrafts and
found varying amounts of N, S, Na, Ca, Zn, Ba, Sn, Cr, and
Al. Recently, Abegglen et al. (2016), tested the exhaust of
three aircraft engines for non-volatile particulate matter and
the presence of metallic compounds therein. Depending on the
type of engine, the most abundant metals in the exhaust were
Cr, Fe, Mo, Na, Ca, and Al, while V, Ba, Co, Cu, Ni, Pb, Mg,
Mn, Si, Ti, and Zr were also detected. Kerosene, engine lubrication oil, and abrasion from engine-wearing components
were considered as the potential sources.
Particulate matter (PM10,2.5) is considered as the main source
of metals in the airports ambient environment. Nevertheless,
information on PM elemental analysis is extremely limited.
Airport emissions that are contributing significantly to increased PM concentrations are mainly derived from aircraft
engines and aircraft tire and break wear. Masiol and Harrison
(2014) who thoroughly reviewed current literature concluded
that an issue that needs to be addressed is the significant
amounts of particulate materials added to airport emissions
through tire, brake, asphalt wear, and the re-suspension of particles due to the turbulence created by aircrafts movements.
According to British Airports Authority (2006), at Gatwick
airport, tire and brake wear are dominant sources of PM10,
accounting about 60 and 12% of all aircraft related emissions,
respectively. The high levels of organic carbon, Ba, Zn, Mo,
Cu, and Sb that measured in airborne PM10 collected close to a
major European airport (El Prat, Barcelona) by Amato et al.
(2010) were possibly derived from aircraft tire detritus/smoke
in runway and from aircraft brake dust.
Apparently, much of the airborne PMs and the associated
metals from airport emissions may fall to the ground close to
the airport but only few studies report on the distribution of
heavy metals in soils in the vicinity of international airports
(Al-Khashman and Shawabkeh 2009; Ray et al. 2012;
Olowoyo et al. 2013; Rao et al. 2015).
The purposes of this study were (1) to determine (i) the
total concentration of Cr, Ni, Zn, Pb, Cu, Co, Mn, Ba, and
Fe and (ii) the available concentration of Ni, Zn, Pb, Cu, Fe
and Mn in soils close to the Athens International Airport; (2)
to assess the spatial distribution of metals at the periphery of
the airport; (3) to discuss on possible relations between metals
concentrations and soil properties; and (4) to evaluate the impact of airport emissions on metals loading in the soils.
Materials and methods
Study area
The study area and the sampling sites are presented in Fig. 1.
Athens International Airport BEl. Venizelos^ is located in
Mesogaia region, Eastern Attica, Greece, approximately
25 km northeast of Athens. The climate of the area is typical
subtropical Mediterranean with prolonged hot and dry summers succeeded by considerably mild and wet winters
(Kaitantzian et al. 2013). The mean annual precipitation is
approximately 400 mm while snowfall is rare. The drought
period usually begins in May and lasts until October. The
daily mean temperature ranges between 27 °C during the summer months and 11 °C during the winter months
(Papathanasiou et al. 2013a, b). Geologically, the study area
is part of the Attico-Cycladic Massif. It is generally flat with
low hills and consists of alluvial and diluvial deposits.
Environ Sci Pollut Res
Fig. 1 Studied area and sampling
sites
Athens International Airport (AIA) operates since
March 2001 and according to air traffic statistical data
of the year 2013 has been ranked as the 35th airport in
Europe. In 2016, the airport handled 189,137 aircraft
movements, 20.02 million passengers and 35,339,047
tons of cargo (Athens International Airport 2017). The
municipalities of Spata, Koropi, Artemis, and
Markopoulo are located nearby. The airport facilities and
infrastructure occupy an area of approximately 12 km2
surrounded by agricultural land. Most of this land is covered by olive trees and vineyards but vegetable and fruit
tree cultivations are also present.
According to the environmental bulletin published by
Athens International Airport (Environmental Bulletin,
Athens International Airport S.A. 2015), emissions of nitrogen oxides (NOx), hydrocarbons (HCs), and carbon monoxide (CO) from sources across the airport site, including aircraft
emissions during the Landing-Take-Off (LTO) cycle, emissions from aircraft handling, emissions from road traffic in
public areas and on the apron as well as emissions from other
sources (e.g., stationary) are estimated on a year basis
(Supplementary Material-SM1).
Since 1998, the airport administration has established and
operates an Air Quality Monitoring Network (AQMN) which
consists of five permanent monitoring stations installed in a
close distance from AIA (Glyka Nera, Koropi, Markopoulo,
Pallini and Spata) and one mobile station.
Ground level concentrations of the major pollutants: nitrogen oxides (NOX), ozone (O3), particulate matter (PM10 and
PM2.5), sulfur dioxide (SO2), carbon monoxide (CO) and
hydrocarbons (HCs) are monitored on a daily basis
(Supplementary Material-SM2) (Environmental Bulletin,
Athens International Airport S.A. 2015).
Sampling
In June 2014, topsoil samples (0–10 cm depth) were collected
from the region around AIA. In order to obtain a distribution
pattern of heavy metals concentrations in the soils of the area,
a grid-type sampling scheme (cell size 1000 × 1000 m or
500 × 500 m in some cases) was followed, oriented by the
presence of the airport. At every sampling site, three subsamples from 100 × 100 cm surface area were obtained and mixed
to make each of the 86 bulk soil samples.
Sample preparation and analysis
The soil samples were transferred to the laboratory in polyethylene bags, air-dried and sieved through a 2-mm sieve. The
mechanical composition of the samples was determined by the
Bouyoucos hydrometer method (Bouyoukos 1951) and the
organic matter content by the Walkley-Black procedure
(Nelson and Sommers 1982). Soil pH was determined in 1:1
v/w soil-water ratio slurries by the use of standard glass/
calomel electrodes. The CaCO3 equivalent percentage was
estimated by measuring the evolved CO2 following HCl dilution (Gasparatos et al. 2015).
To obtain Bpseudo-total^ metal concentrations, the soil
samples were digested with aqua regia (HNO3/HCl, 1:3)
(Gasparatos and Haidouti 2001). BPseudo-total^ expression
Environ Sci Pollut Res
accurately describes the metal concentrations determined in
aqua-regia extracts, because aqua-regia digestion does not
completely destroy silicates (Facchinelli et al. 2001).
However, in the text of this study, the term Btotal^ is used
for simplicity.
For aqua regia digestion, 1 g of finely ground soil sample
was weighed into a 250-ml digestion vessel and 15 ml of aqua
regia was added. The flask was placed on a hot plate at 140 °C
and digested for 16 h. Reflux funnels with water were used to
reduce evaporation. After digestion, the samples were filtered
through Whatman Grade 42 filter papers and brought to 25 ml
with distilled water.
Available metal fraction (water-soluble, easily
exchangeable, and some of the organic bound metals) was
extracted by DTPA (Lindsay and Norvell 1978) by using
0.005 M diethylene triamine pentaacetic acid (DTPA),
0.01 M CaCl2, and 0.1 M triethanolamine (TEA) solution.
Twenty milliliters of DTPA (pH = 7.3) solution was added
to soil samples (10 g) in a 125-ml Erlenmeyer flask, shaken
for 2 h in a reciprocal shaker at 25 °C, and then filtered
through Whatman Grade 42 filter papers.
Several studies have shown that DTPA is the most suitable
extractant for the determination of metal availability in soils
(Gasparatos et al. 2011; Khanmirzaei et al. 2013; Chatzistathis
et al. 2017). DTPA was originally developed for calcareous
soils (like the soils of this study) minimizing dissolution of
carbonates as well as mimicking rhizosphere effects in the
soil.
The sequential extraction scheme proposed by Tessier et al.
(1979) was used to examine the chemical fractions of Cu, Mn,
Zn, Ni and Pb in 9 samples (approximately 10% of the soil
samples) that were randomly selected. Each fraction was defined as described by Gasparatos et al. (2015):
Exchangeable (fraction 1—F1)
2.00 g of soil extracted with 16 ml of 1 M MgCl2 (pH 7.0) in
100 ml polyethylene centrifuge tubes for 1 h at room temperature with continuous agitation
Bound to carbonates or acid-soluble (fraction 2—F2)
Residue from exchangeable fraction, extracted with 16 ml 1 M
CH3COONa (pH 5) for 5 h at room temperature with continuous agitation.
Bound to iron and manganese oxides or reducible (fraction
3—F3)
Residue from acid-soluble fraction, extracted with 40 ml of
0.04 M NH2OH.HCl in 25% acetic acid (v/v) for 5 h at 96 ± 3
under intermittent agitation.
Bound to organic matter or oxidizable (fraction 4—F4)
Residue from reducible fraction, extracted with 6 ml of
0.02 M HNO3 and 10 ml of 30% H2O2 (pH 2 with ΗΝΟ3).
The mixture was heated to 85 ± 2 for 2 h with occasional
agitation. After cooling, 10 ml of 3.2 M CH3COONH4 in
20% (v/v) HNO3 was added and the sample diluted to 40 ml
and agitated continuously for 30 min at room temperature.
Residual (fraction 5—F5)
Residue from oxidizable fraction was extracted by aqua regia
digestion.
After each extraction, the suspension was subjected to centrifugation for 20 min at 4000 rpm. The supernatant was removed with a pipette; care was taken not to remove any of the
solid residues.
All metal concentrations were determined by atomic adsorption spectrophotometer Varian spectra A300. The calibration standards were prepared in the appropriate matrices that
were used for the soil samples. A control sample was analyzed
for every ten samples, and reproducibility was tested by
reanalyzing 30% of the samples. Analytical precision, estimated as relative standard deviation, ranged from 3 to 5% depending on the metal. To check the reliability of the followed aqua
regia procedure, the ERM-CC141 loam soil was used as reference material. The mean recoveries of Cr, Zn, Pb, Mn, Cu,
and Ni were 96, 104, 95, 105, 95, and 106%, respectively.
Soil pollution indices
Enrichment factor (EF)
Enrichment Factor (EF) for Pb, Cr, Ni, Mn, Zn, and Cu, in the
soils around the airport was calculated as:
E: F: ¼ ðMi =Fei Þ=ðMr =Fer Þ
Mi
Fei
Mr
Fer
total metal concentration of the ith sample.
total Fe concentration in the ith sample.
reference total metal concentration.
reference total Fe concentration.
As reference total metal concentrations, the respective median values reported by Kaitantzian et al. (2013) for the top
soils of agricultural land in the Mesogaia greater area and
particularly for the soils belonging to the municipalities of
Koropi and Markopoulo were used. Since AIA is located
within this area and the survey conducted by Kaitantzian
et al. (2013) reports on metal forms extracted by aqua regia,
the total metal concentrations determined by these authors can
reasonably be used as geochemical baseline values for the
Environ Sci Pollut Res
agricultural soils in the airport surroundings. Considering that
the abundance of Fe in soils is rarely affected by human activities, metal concentrations were normalized by including
total Fe concentration in the E.F. formula. Hence, any EF
value > 1 may be regarded as increased metal accumulation
in the soils close to airport infrastructures.
Availability ratio (AR)
software STATISTICA for Windows (StatSoft, Inc., USA,
1995, Version 10).
Spatial distributions of total metal concentrations and
of above median EF values in the soils of the tested area
were visualized on maps produced by the ArcMap ver.
10.4 software. The Geostatistical Analyst extension was
used to interpolate values between the sampling sites and
to create interpolated surfaces by the Inverse Distance
Weighted method. The interpolated studied area covered
a land of 59 km2 (including the airport).
The following formula was applied for the calculation of the
availability ratio (Massas et al. 2010):
Results and discussion
AR ¼ ðCia =Cit Þ 102
Soil properties
Cia
Cit
the available metal concentration in the ith sampling
site.
the total metal concentration in the ith sampling site.
Mobility factor (MF)
The mobility of heavy metals in soils can be estimated
according to their active forms as determined by the
Tessier sequential extraction procedure, by calculating
the Mobility Factor (MF) (Iwegbue 2013; Gasparatos
et al. 2015). The MF was computed for the studied metals
as the ratio of exchangeable (F1) and acid-soluble (F2)
fractions to the sum of all fractions, according to the following formula:
MF ¼
F1 þ F2
x 100
ð F1 þ F2 þ F3 þ F4 þ F5Þ
The soils of the studied area were developed mainly on alluvial deposits and their physicochemical key characteristics are
presented in Table 1.
The soils show light to medium texture as sand content
ranged from 28.0–85.4% and clay content ranged from 8.0
to 42.6%. The pH does not vary much and is slightly basic
(mean value = 7.95) suggesting sub alkaline conditions and
low metal mobility in the tested soils. Calcium carbonate
equivalent ranges from 2.7 to 54.4%, with an average value
of 19%. High percentages of carbonates in soils are usually
related to low bio-availability of heavy metals. Organic matter
content highly fluctuated between traces and 21.06%, but
most of the samples are poorly or moderately supplied with
organic matter. The obtained physicochemical characteristics
point to soils of adequate drainage that ensures sufficient soil
aeration and oxidizing conditions. Sand, clay, silt, organic
matter, calcium carbonate equivalent content, and pH values
are normally distributed, pointing to minimal site specific system disturbance.
Total and available metal concentrations
Statistical analysis and GIS
The descriptive statistical parameters, correlation analysis,
and cluster analysis were carried out by using the statistical
Table 1 Descriptive statistics of
selected physicochemical
properties of the studied soils
(N = 86)
Mean
Median
Min.
Max.
10th perc.
90th perc.
SD
CV%
The descriptive statistics of the total and available forms of
Cu, Zn, Fe, Mn, Ni, Cr, Pb, and Ba concentrations are presented in Table 2.
Sand (%)
Silt (%)
Clay (%)
52.6
52.8
28.0
85.4
40.0
63.4
9.6
18.2
22.7
23.5
2.6
34.8
14.0
30.6
6.5
28.6
24.7
24.3
8.0
42.6
15.5
32.9
6.7
27.0
Org. matter (%)
2.53
2.24
traces
21.06
1.01
3.47
2.38
94.12
CaCO3 eq. (%)
pH (1:1)
19.0
19.8
0.4
54.4
2.7
33.2
11.8
61.8
7.95
7.96
7.02
8.69
7.64
8.25
0.26
3.30
Environ Sci Pollut Res
Table 2 Descriptive statistics for
the total and available
concentrations of the studied
metals in the soils nearby El.
Venizelos airport (N = 86)
Cr
Zn
Ni
Pb
Total
Mean
79.8
95.2
92.1
(mg/kg)
79
Median
74.2
81
86.9
Min.
Max.
31
154.4
33.5
518
34.6
177.1
10th perc.
52.9
61.5
60.4
90th perc.
S.D.
108.8
24.4
130.5
56.6
133.1
28.7
31
84
59
58
N.D.b
C.V.%
Median Background Valuea
Available
Mean
Median
Min.
Max.
10th perc.
90th perc.
S.D.
C.V.%
a
Kaitantzian et al. (2013)
b
Not determined
Total metal concentrations are not considered as high and
showed values similar to those presented by Kaitantzian et al.
(2013) for the agricultural soils of the Mesogaia region. Yet,
Zn, Pb, and Ni median concentration values are higher than
the respective values reported by these authors (i.e., 58, 67,
and 69 mg kg−1). Since median total concentrations for Zn,
Pb, and Ni in the agricultural soils of the area are lower by up
to 20%, it is logical to support that secondary enrichment of
the soils nearby the airport emerged due to activities relating to
the AIA operation. High Ni total concentrations are commonly detected in Greek soils and attributed to the composition of
soils’ parent material (Salminen et al. 2005; Kanellopoulos
et al. 2015); nonetheless, some soil samples showed clear
indications of Ni accumulation. In a number of sampling sites,
the 90th percentile and maximum total concentration values
indicate serious Cu, Mn, and Cr buildup from sources other
than the parent material and soil formation processes.
As it is presented in Table 3, the observed great variation of
the total metal concentrations in soils close to civil airports is
most likely due to differences in the daily number of landings
and taking offs, the total time of airport operation, the parent
material of the soils and the protocols that applied for the
extraction of the metals.
In comparison to the results of our study, Rao et al. (2015)
reported considerably higher Zn and Cr concentrations in the
soils close to Shanghai international airport, similar Cu and Pb
concentrations and lower Ni concentration; Olowoyo et al.
Mn
Ba
Cu
Fe
562.7
442.5
27
(mg/g)
22.4
74.9
497
422.8
23.3
21.7
53.3
271.2
223
1491
72
1171
8
129.1
7.8
44.8
62.4
363
257.5
17.7
15.5
96.2
26.2
860
232.2
649.5
174.2
33.7
16.7
29.3
6.2
31
69
33
67
41
484
39
62
24
28
24.6
3.5
1.0
3.7
(mg/kg)
9.2
N.D.2
3.3
1.7
0.9
0.1
0.9
0.1
3.6
0.6
7.5
0.2
1.8
0.3
1.2
0.4
100.3
0.4
7.2
11.4
326
2.9
0.4
1.6
0.5
50
8.3
1.7
5.7
1.7
46
53.6
2.5
15.8
7.8
85
73.5
0.6
4.0
9.0
273
13.9
0.7
2.6
2.0
119
(2013) determined much higher total Cu, Mn, Cr, Pb, and Fe
concentrations in the soils nearby the Pretoria Wonderboom
airport (South Africa); Ray et al. (2012) found similar total
metal concentrations in the soils close to Delhi airport, while
the extracted forms of Cu, Zn, Cr and Pb from the soils in the
vicinity of Queen Alia airport in Jordan were lower (AlKhashman and Shawabkeh 2009).
The distribution of Cu, Zn, Mn, Ni, Pb, and Cr total concentrations in the soils around AIA is presented in Fig. 2a.
There is no clear unique pattern for the distribution of all
metals that can be detected. Spots of higher Pb and Cu concentrations are observed in the northern part of the studied
area. Ni shows a distribution pattern similar to that of Pb and
Cu, while for Zn a south to north accumulation in the soils
appears. Increased Cr and Mn concentrations observed in the
eastern part though for Cr a north to south distribution are also
apparent.
The available fraction of metals in soils is rarely determined in soil pollution studies and in the few relevant references found in the literature various extractants were used
leading to low data comparability. DTPA is a chelating agent
that is commonly used in soil fertility studies to illustrate the
potential availability of micro-nutrients for plant uptake
(Gasparatos et al. 2011). Thus, in order to provide information
on metals mobility and hence availability to the soil biota and
plants, the soil samples of the studied area were subjected to
DTPA extraction.
Environ Sci Pollut Res
Table 3
Mean total metal concentrations in soils close to international airports (mg/kg)
Location
Cu
Zn
Shanghai Airport (China)
25
186
Pretoria Wonderboom (South Africa)
98
88.9
1320
Delhi airport (India)
21
97
391
44.2
16.9
60.2
562.7
92.1
79.8
79
Queen Alia Airport (Jordan)
3
51.4
Athens International Airport (Greece)
27
95.2
Mn
Ni
Cr
Pb
44
157
81
820
98.1
91.3
Olowoyo et al. (2013)
127
37.5
4.38
Ray et al. (2012)
With the exception of few sampling sites, the availability of
most metals in the soils close to AIA is low to medium
pointing to low environmental risk (Table 2). Indeed, mean
and median available forms concentrations of Zn, Ni, Pb, Mn,
Fe, and Cu are generally low. For Zn, Mn, Fe, and Cu, the
large median to maximum concentration range resulted to
extreme CV% values pointing to recent site specific soil enrichment by these metals (Chai et al. 2015). However, the 90th
percentile concentration values for Zn, Fe, and Cu were lower
than those proposed by Kaur and Rani (2006) as threshold
concentration values for the available Zn, Fe, and Cu fraction
in soils determined by the DTPA extraction protocol, i.e., 10,
20, and 5 mg kg−1, respectively. Though the soils of the area
are calcareous, the recorded availability of Mn was high, suggesting that further investigation and data processing are needed for this metal.
Partitioning of metals in soil fractions
According to the Tessier fractionation scheme five chemical
fractions of Pb, Cu, Zn, Ni, and Mn were defined, reflecting
the chemical partitioning of these metals in the studied soils;
exchangeable (F1), acid-soluble (F2), reducible (F3), oxidizable (F4) and residual (F5). The percentage distribution pattern of the five fractions is presented in Fig. 3. For Cu, Ni, and
Zn, the residual fraction (F5) represents more than 50% of the
total metal concentration. Similar results for Cu, Ni, and Zn
association with the residual fraction are also reported by
Botsou et al. (2016) for roadside and off road soils in
Mesogaia region. The next more abundant fraction for the
three metals is the reducible, indicating a possible relation
between Cu, Ni and Zn and Fe-Mn oxides. The very low
concentration of Zn in the exchangeable fraction (F1) that is
in accordance to the very low available Zn median concentration (Table 2), point to low Zn solubility under alkaline soil
conditions. Lead and Mn were mainly associated with the
reducible fraction (F3). The dissolution of Fe-Mn oxides at
this stage of fractionation and the formation of inner sphere
sorption complexes of Pb2+ with Fe and Mn compounds
(Scheinost et al. 2001) might explain the high extraction of
Mn and Pb at this fractionation stage.
Ba
Fe mg /g
Reference
Rao et al. (2015)
443
0.05
Al-Khashman and Shawabkeh (2009)
22.4
This study
Though the organic matter content of the soils was low, the
tendency of Cu to participate in high stability Cu—organic
complexes is supported by the higher Cu percentage concentration in the oxidizable fraction (F4) compared to the other
metals.
Cluster analysis and correlations
Cluster analysis (C. A.) was performed on normalized data
providing dendrograms for total and available metal concentrations (Fig. 4). For total metal concentrations, two main
clusters were distinguished (Fig. 4a). The metals included in
the first main cluster are Cr, Ni, Ba, Mn, Fe, and Zn while the
second main cluster consists of Pb and Cu. Within the first
main cluster, two clear sub-clusters observed indicating a
strong relation between Cr and Ni and Mn and Ba,
respectively.
A weak connection of Fe with the second sub-cluster is
also noticed and a very weak association of Zn with the
metals of the first main cluster is apparent. Since the
smaller the linkage distance the stronger the relation between metals, it can be supported that the concentration in
soils of metals belonging to the following Cr-Ni, Ba-Mn,
and Pb-Cu groups most likely originated from the same
sources. The significant correlations between the clay
content and Cr, Ni, and Mn total concentrations (r values
0.34, 0.36, and 0.34, respectively, p < 0.05) indicate that
to some extent these metals derived from the soil’s parent
material. Recently, Lv et al. (2015) reported that parent
material influenced the origin of Cr, Ni and Mn in urban
soils of Donggang area in Eastern China.
Clay content of the soils showed a significant correlation to
the Fe total concentration (r = 0.60, p < 0.001) that strongly
supports the geogenic origin of Fe. The physicochemical characteristics of the studied soils did not correlate to Ba, Cu, Zn,
and Pb total concentrations, pointing to secondary soil enrichment by these metals probably due to aerial depositions.
Very weak relations emerged among the available
forms concentrations of the studied metals as indicated
by the relatively large linkage distance. Indeed, only Mn
and Ni available fractions are strongly related (Fig. 4b),
suggesting a common emission source for these metals.
Environ Sci Pollut Res
Fig. 2 Total concentrations and
Enrichment Factor values for Cu,
Zn, Mn Ni, Pb, and Cr in the soils
around the Athens International
Airport (a) interpolated maps of
the total concentrations (b)
sampling sites with EF values
higher than median and 90th
percentile value; Cu: median
EF = 1.10, 90th percentile = 1.62;
Zn: median EF = 1.62, 90th
percentile = 2.65; Mn: median
EF = 1.20, 90th percentile = 1.68;
Ni: median EF = 1.48, 90th
percentile = 2.16; Pb: median
EF = 1.18, 90th percentile = 2.15;
Cr: median EF = 1.03, 90th
percentile = 1.53
Furthermore, organic matter content was significantly correlated to Mn and Ni available forms concentrations (r
values 0.47 and 0.44, p < 0.001), leading to the conclusion that organic substances in the studied soils have an
effect on the availability of these metals. DTPA extracted
Fe negatively correlated to pH and carbonates content (r
values − 0.29 and − 0.30, p < 0.05) reflecting the low Fe
availability in calcareous soils.
Environ Sci Pollut Res
Fig. 3 Mean values of metal
fraction percentages F1:
exchangeable fraction, F2: acidsoluble fraction, F3: reducible
fraction, F4: oxidizable fraction,
F5: residual fraction (N = 9)
concentration of the metal and for total Fe concentration in
soil. Hence, the lithogenic factor effect on total concentration
of a metal is included in the process of data evaluation, leading
to more reliable conclusions.
According to the median EF values that ranged from 1 for
Cr to 1.5 for Ni, 50% of the examined land showed evidence
of minor to medium soil enrichment by Pb, Cu, Zn, Mn, and
Evaluation of soil pollution indices
Enrichment factor
The formula used in this study to calculate enrichment factor
(E.F.), provides for every sampling site and metal a pollution
index that is normalized for both median reference
Weighted pair-group average
1-Pearson r
Weighted pair-group average
1-Pearson r
1,1
b
a
1,0
0,9
Linkage Distance
Linkage Distance
0,8
0,7
0,6
0,5
0,4
Cr
Ni
Ba
Mn
Fe
Zn
Pb
Cu
0,3
Fe
Zn
Mn
Ni
Cu
Pb
Fig. 4 Hierarchical clustering results (dendrogram) of the heavy metal concentrations in the soils around the Athens International Airport: a Total. b
Available
Environ Sci Pollut Res
Ni. Moreover, EF values higher than the 90th percentile,
representing soils of nine sampling sites, ranged between 1.6
for Cu and 2.5 for Zn, thus portraying an alarming situation in
terms of soil pollution. Sampling sites with EF values higher
than the median (open circles) or the 90th percentile values
(dark circles) are presented in Fig. 2b. Such illustration of EFs
reflects soil enrichment by the studied metals and highlights
the spatial distribution of sampling sites around the airport
facilities that represent areas mostly exposed to metals accumulation. Zinc enrichment occurs in the soils north and south
of the airport while in the western and eastern areas the soils
were not seriously affected. Copper buildup was observed in
the soils north and south of the airport, while soils in eastern
areas also showed increased Cu load. Manganese, Ni, and Cr
were mainly accumulated in the soils north and east of the
airport and Pb mainly in the northern soils but spots of higher
enrichment were also apparent at east and south. It is evident
that high accumulation of all metals occurs in the areas north
to the airport while, with the exception of Zn, soils at the
eastern airport borders also appear to be considerably enriched
by the studied metals. The similar pattern of spatially increased metal concentrations provides strong indications that
emissions from a common source relate to the additional metal
loading in the soils of the area. Activities related to Athens
International Airport operation nominate as major contributors of metals to the neighboring soils. Theophanides and
Anastassopoulou (2009), studied NOx, VOC, O3, CO, SO2
and PM10 dispersion over a large area around AIA and concluded that increased concentrations of these pollutants occur
over cities northern to the airport; they also directly pointed to
the airport related activities as the main cause for the observed
atmospheric pollution.
Significant positive correlations between equivalent
CaCO3 concentration and Pb, Ni, Cr, and Mn EFs (r values
equal to 0.40, 0.57, 0.35 and 0.42, respectively; p < 0.05)
suggest strong association of soil enrichment by these metals
to carbonates content in the soils. On the contrary, total concentrations of Pb, Ni, Cr, and Mn do not significantly correlate
to carbonates content in the soils and hence the significant
association of carbonates to EFs can be regarded as an indication of relatively recent accumulation of these metals in the
studied soils. In addition, Pb and Ni EFs are significantly and
negatively correlated to clay content (r values equal to − 0.41
and − 0.22, respectively; p < 0.05) further supporting the
argument of the relatively recent soil enrichment by Pb and
Ni. Moreover, the distribution pattern of high EFs does not
always coincide with high total metal concentrations in soils
(Fig. 2b).
Availability ratio and mobility factor
Availability ratio (AR) is indexing the extent of metals availability in relation to the total concentration of metals in soils.
Considering that as the time from a pollution episode passes
the available fraction of a metal in soils is progressively transformed to less available forms (Dousis et al. 2013), AR values
can be used to discuss on recent accumulation of metals in
soils. In this study, median AR values for most metals are low
and varied between 1.04% for Ni and 7.67% for Cu. The low
available fraction of Pb, Ni, and Mn is highlighted by the fact
that for all sampling sites AR values were lower than 10%,
while Zn AR values were higher than 10% in only three sampling sites (Fig. 5). However, the high availability of Cu that
detected in many sites of the studied area indicates that apart
from the airport related activities, Cu aerial deposition in soils
may have been also derived from agricultural practices like the
application of Cu-based fungicides in the vineyards and the
olive tree plantations nearby AIA. The normalization of
metals available fraction for their total concentration in soils
as it was achieved by the calculation of AR values resulted to
stronger relations among the studied metals that were not noticeable for the available metal concentrations. In fact, significant positive correlations were observed between Ni and Pb,
Cu, Mn, and Zn ARs (r = 0.30, 0.44, 0.71 and 0.52; p < 0.05),
between Cu and Zn and Mn ARs (r = 0.31 and 0.27; p < 0.05)
and between Zn and Mn ARs (r = 0.47; p < 0.05). Though
these relations are not so strong for some pairs of AR values,
they suggest that the availability of the metals in the studied
soils is affected to some extent by the emissions of a common
source, most probably from activities related to AIA
operation.
As it is illustrated in Fig. 6, and according to the median
mobility factor (MF) values, the mobility of metals in the
studied soils follows the order Pb > Mn > Cu > Ni > Zn.
The median MF values for Pb and Mn are much higher
than 10 while for Cu and Ni are close to that value, indicating
high or very high mobility of these metals in the studied soils.
Though only 10% of soil samples subjected to sequential extraction, the high MF values for these metals along with the
respective median EF values that were > 1 suggest an altering
status of the studied metals in the soils nearby AIA when
compared to the reference soils. Mobility factor values do
not significantly correlate to soil properties, except MnMF
values that strongly and positively correlate to soil organic
matter (r = 0.92, p < 0.001), elucidating the affinity of Mn
to weakly bound to organic substances.
Assessment of metals loading in the soils close to AIA
in the context of metals loading in the soils of Attica
prefecture
Athens International Airport locates within the administrative
boundaries of Attica prefecture, an area that covers 3% of
Greece and where 40% of the country’s population is
established. Within Attica prefecture, Athens city and
Thriassio plain are located; Athens city is densely populated
Environ Sci Pollut Res
60
Fig. 5 Availability Ratio median,
minimum, maximum, 10th and
90th percentile and raw data
values for Pb, Cu, Ni, Zn, and Mn
for the soils around the Athens
International Airport
Availability Ratio (A.R.)
50
40
30
20
10
0
Pb
Maximum
90th
Median
Minimum
Cu
8.8
7.3
4.7
0.7
57.0
13.5
7.7
1.2
(i.e., 3.5 million people in 400 km2) and Thriassio plain is a
land of mixed industrial, agricultural and residential land uses
and probably one of the most polluted areas in Greece. Studies
that report on the existing metal status in the soils of Athens
city, Thriassio plain and in other Attica soils provide the necessary background information to discuss on the contribution
of AIA emissions to metals concentrations in the soils at the
periphery of Athens International Airport (Massas et al. 2010;
Kaitantzian et al. 2013; Massas et al. 2013; Argyraki and
Fig. 6 Mobility Factors for Cu,
Pb, Ni, Mn, and Zn (N = 9)
Ni
2.5
1.7
1.0
0.1
Zn
19.4
3.5
1.2
0.1
Mn
Median
10%-90%
Min-Max
Raw Data
10.6
3.5
1.5
0.1
Kelepertzis 2014; Kelepertzis and Argyraki 2015; Botsou
et al. 2016; Gasparatos et al. 2015). In addition, the similar
physicochemical properties of the top soils studied in these
reports as texture, pH, carbonates, and organic matter contents
create a reliable framework for data assessment.
Median total metal concentrations in soils of urban, industrial, and agricultural land use in Attica prefecture are listed in
Table 4. As it is expected, metal concentrations are higher in
urban and industrial soils than in the agricultural soils close to
45
40
35
30
25
20
15
10
5
0
Cu_MF
Mn_MF
Ni_MF
Pb_MF
Zn_MF
Median
25%-75%
Min-Max
Outliers
Environ Sci Pollut Res
Table 4
Literature data on median total metal concentrations in soils of Attica prefecture (in mg/kg except Fe in %)
Area
Fe
Athens central (n = 70)
1.7
Athens greater
(N = 238)
Mn
Pb
Zn
Cu
Ni
Cr
Co
311
101.3
145.6
42
77.8
84.3
22.6
2.4
554
45
98
39
102
141
Thriassio plain (n = 90)
1.6
320.8
111.8
154.6
37.8
81.1
Ba
Analytical method
Reference
–
HNO3 + HCl
Massas et al. (2010)
16
–
77.9
24
834.4
HNO3 + HCl + HCLO4 +
HF
HNO3 + HCl
Argyraki and Kelepertzis
(2014)
Massas et al. (2013)
Agricultural (n = 37)
2.5
484
67
58
24
69
84
31
–
HNO3 + HCl
Kaitantzian et al. (2013)
Highwaysa (n = 10)
–
–
44.8
81.6
30.8
247
–
–
–
HNO3 + HCl
Botsou et al. (2016)
AIA soils (n = 86)
2.2
497
74.9
81
23.3
86.9
74.2
–
422.8
HNO3 + HCl
This study
a
Mean values
AIA facilities. During the short period of AIA operation, the
soils of the studied area have received considerably lower
metals addition due to airport emissions than the soils of urban
and industrial areas (such as Athens and Thriassio plain) that
receive aerial depositions due to various anthropogenic activities for a very prolonged time. Yet, with the exception of soils
close to highways, Ni and Mn median total concentrations
tend to be higher in the soils at the periphery of AIA, indicating that the establishment and the operation of Athens
International Airport during the past 13 years has affected
the concentration of Ni and Mn in the soils of the area. Zinc,
Pb, and Ni median available forms concentration values for
the soils of this study were also lower than the respective
values reported for the soils of Athens city playgrounds and
for the soils of Thriassio plain (Table 5). However, Mn available concentrations are similar to those reported for the soils of
Athens playgrounds that are mainly enriched by fossil fuels
emissions (i.e., vehicular and central heating systems). On the
contrary, Cu available fraction is lower than in the soils of
Athens playgrounds and similar to that in soils of Thriassio
plain. But, the actual availability of Cu in the soils of the
present study as demonstrated by the AR median and 90th
percentile values, points to serious and ongoing secondary soil
enrichment by copper. Indeed, median AR value for Cu in the
soils close to AIA is up to 25–30% higher than the respective
values for the soils of central Athens and Thriassio plain
(Table 5). Aerial depositions due to AIA operation provide a
possible explanation for the increased availability of Mn and
Cu in the nearby soils. An additional source for the high Cu
availability might also be the application of Cu-based fungicides in the olive tree and vineyard plantations that are present
in the greater AIA area.
The availability of metals in soils is also assessed by the
mobility factor (MF) and the risk assessment code (RAC) that
formulated by Tessier and BCR sequential extraction
schemes. The formula for the calculation of MF is included
in the section 3.5 of this study while for the calculation of
RAC the first fraction (F1) of BCR procedure is divided by
the sum of all fractions and expressed as %. Considering that
the F1 of BCR incorporates both the exchangeable and acid
soluble metal forms, as the F1 and F2 fractions of Tessier’s
procedure, RAC and MF indices may be regarded as comparable. Only two reports, where the BCR (Botsou et al. 2016)
and Tessier (Gasparatos et al. 2015) sequential extraction
schemes were applied, discuss on metals fractionation in the
soils of Attica prefecture. Botsou et al. (2016), determined the
RAC index for Zn, Cu, Cd, Pb, and Ni for ten soil samples
collected nearby two major highways and found that the availability of the metals followed the order Zn > Pb > Cu > Ni.
Gasparatos et al. (2015) determined the MF index for the soils
of Thriassio plain (n = 50) and report that the availability of
metals followed the order Pb > Cu > Ni > Zn > Cr. According
to MF values, the potential availability of Pb, Cu, Zn, and Ni
in the soils of the present study is comparable to that reported
Table 5 Median Zn, Ni, Pb, Mn, and Cu available concentrations extracted by DTPA (mg/kg) and Availability Ratio (A.R.) values in the soils of
Athens playgrounds and Thriassio plain. Concentration range and 90th percentile value in parenthesis
Zn
Athens playground
soils (n = 70)
Available
A.R.
Thriassio plain soils
(n = 90)
Available
A.R.
Ni
Pb
Mn
Cu
Reference
Massas et al. (2010)
5.5 (1.2–62.8, 18.3) 1.1 (0.3–6.8, 2.0) 5.0 (1.2–19.7, 9.3) 7.5 (0.5–25.0, 15.9) 2.3 (0.7–6.0, 4.1)
3.7 (0.4–37.0, 7.9) 1.5 (0.4–7.7, 2.8) 4.8 (1.2–19.0, 10.1) 2.1 (0.1–16.0, 5.6) 5.4 (1.3–14.4, 10.1)
Massas et al. (2013)
5.6 (0.8–32.2, 16.5) 1.7 (0.5–3.7, 2.8) 6.9 (1.6–37.4, 12.6) 5.7 (0.7–24.3, 12.6) 2.1 (0.5–51.3, 6.1)
3.5 (1.1–12.0, 2.2) 2.3 (0.5–3.7, 3.0) 5.5 (2.3–34.4, 8.4) 3.5 (1.1–12.0, 6.0) 6.4 (1.8–19.6, 12.1)
Environ Sci Pollut Res
for the soils of Thriassio plain. Such resemblance of metals
availability supports an ongoing secondary enrichment of the
soils close to AIA.
Conclusions
Monitoring of particulate matter (PM2.5,10) emissions from
airports is a routine procedure but the PMs chemical composition is rarely determined. PMs are the main carriers of heavy
metals and depending on their size they are distributed at
various distances in the surroundings of the airports. To a great
extent, soils are the final receptors of these depositions. To
comprehend the effect of Athens International Airport on the
quality of the ambient environment after 13 years of operation,
we studied the concentration and distribution of Pb, Cu, Zn,
Ni, Cr, Ba, Mn and Fe in the soils around AIA. Despite the fact
that the median total and available metal concentrations were
generally low, the systematic approach of the raw data by
using soil pollution indices and the spatial distribution of the
above median enrichment factor values in the area, revealed
metals buildup, mainly at north and east of the airport. Though
indicative, due to the number of soil samples that subjected to
sequential extraction, the great similarity of mobility factor
values of the present study to the respective values for soils
of Attica prefecture that constantly receive metals depositions,
further supports the ongoing enrichment of the studied soils.
Considering that AIA infrastructures and operational activities
are the major metal emitting source in the area, it is logical to
accept that the dense airplane landing and taking off, the maintenance of the aircrafts and the traffic burden within and nearby the airport area may contribute to the observed site specific
increased metals loading. However, insights into chemical
composition of PMs emitted from AIA and periodic monitoring of heavy metal concentrations in the soils nearby AIA are
necessary to strengthen the results of the present study.
References
Abegglen M, Brem BT, Ellenrieder M, Durdina L, Rindlisbacher T, Wang
J, Lohmann U, Sierau B (2016) Chemical characterization of freshly
emitted particulate matter from aircraft exhaust using single particle
mass spectrometry. Atmos Environ 134:181–197
Al-Khashman OA, Shawabkeh RA (2009) Metal distribution in urban
soil around steel industry beside Queen Alia Airport, Jordan.
Environmental Geochem Hlth 31:717–726
Alloway BJ, Ayres DC (1997) Chemical principles of environmental
pollution. Blackie Academic and Professional, London
Alloway B (2013) Sources of heavy metals and metalloids in soils. In:
Alloway B (ed) Heavy metals in soils—trace metals and metalloids
in soils and their bioavailability. Springer, Dordrecht, pp 11–50
Amato F, Moreno T, Pandolfi M, Querol X, Alastuey A, Delgado A,
Pedrero M, Cots N (2010) Concentrations, sources and
geochemistry of airborne particulate matter at a major European
airport. J Environ Monit 12:854–862
Antoniadis V, Shaheen SM, Boersch J, Frohne T, Du Laing G, Rinklebe J
(2017) Bioavailability and risk assessment of potentially toxic elements
in garden edible vegetables and soils around a highly contaminated
former mining area in Germany. J Environ Manag 186:192–200
Argyraki A, Kelepertzis E (2014) Urban soil geochemistry in Athens,
Greece: the importance of local geology in controlling the distribution of potentially harmful trace elements. Sci Total Environ 482–
483:366–377
Athens International Airport (2017) http://www.aia.gr/company-andbusiness/the-company/facts-and-figures/
Bouyoukos GH (1951) A recalibration of the hydrometer method for
making mechanical analysis of soils. Agron J 43:434–438
Botsou F, Sungur A, Kelepertzis E, Soylak M (2016) Insights into the
chemical partitioning of trace metals in roadside and off-road agricultural soils along two major highways in Attica’s region, Greece.
Ecotox Environ Safe 132:101–110
Bretzel F, Calderisi M (2006) Metal contamination in urban soils of
coastal Tuscany (Italy). Environ Monit Assess 118:319–335
British Airports Authority (2006) Gatwick 2010 baseline emission inventory. Availableat:http://83.98.24.64/Documents/business_and_
community/Publications/2006/2010_basline_emissions_inventory.pdf
Chai Y, Guo J, Chai S, Cai J, Xue L, Zhang Q (2015) Source identification of eight heavy metals in grassland soils by multivariate analysis
from the Baicheng–Songyuan area, Jilin Province, Northeast China.
Chemosphere 134:67–75
Chatzistathis T, Papaioannou A, Gasparatos D, Molassiotis A (2017)
From which soil metal fractions Fe, Mn, Zn and Cu are taken up
by olive trees (Olea europaea L., cv. 'Chondrolia Chalkidikis') in
organic groves? J Environ Manag 203(Pt 1):489–499. https://doi.
org/10.1016/j.jenvman.2017.07.079
D'Amore JJ, Al-Abed SR, Scheckel KG, Ryan JA (2005) Methods for
speciation of metals in soils: a review. J Environ Qual 34:1707–1745
Demirdjian B, Ferry D, Suzanne J, Popovicheva OB, Persiantseva NM,
Shonija NK (2007) Heterogeneities in the microstructure and composition of aircraft engine combustor soot: impact on the water uptake. J Atmos Chem 56:83–103
Dousis P, Anastopoulos I, Gasparatos D, Ehaliotis C, Massas I (2013)
Effect of time and glucose-C on the fractionation of Zn and Cu in a
slightly acid soil. Commun Soil Sci Plan 44:722–732
Environmental Bulletin, Athens International Airport SA (2015) http://
www.aia.gr/company-and-business/the-company/CorporatePublications/enviroment
Facchinelli A, Sacchi E, Mallen L (2001) Multivariate statistical and GISbased approach to identify heavy metal sources in soils. Environ
Pollut 114:313–324
Gasparatos D, Haidouti C (2001) A comparison of wet oxidation methods
for determination of total phosphorus in soils. J Plant Nutr Soil Sc
164:435–439
Gasparatos D, Roussos PA, Christofilopoulou E, Haidouti C (2011)
Comparative effects of organic and conventional apple orchard management on soil chemical properties and plant mineral content under
Mediterranean climate conditions. J Soil Sci Plant Nut 11:105–117
Gasparatos D (2013) Sequestration of heavy metals from soil with Fe-Mn
concretions and nodules. Environ Chem Lett 11:1–9
Gasparatos D, Mavromati G, Kotsovilis P, Massas I (2015) Fractionation
of heavy metals and evaluation of the environmental risk for the
alkaline soils of the Thriassio plain: a residential, agricultural, and
industrial area in Greece. Environ Earth Sci 74:1099–1108
Giannakopoulou F, Gasparatos D, Haidouti C, Massas I (2012) Sorption
behavior of cesium in two Greek soils: effects of Cs initial concentration, clay mineralogy and particle size fraction. Soil Sediment
Contam 21:937–950
Environ Sci Pollut Res
Hudda N, Gould T, Hartin K, Larson TV, Fruin SA (2014) Emissions
from an international airport increase particle number concentrations
4-fold at 10 km downwind. Environ Sci Technol 48:6628–6635
Iavicoli I, Fontana L, Ancona C, Forastiere F (2014) Airport related air
pollution and health effects Inquinamento atmosferico prodotto
dagli aeroporti ed effetti sulla salute Airport related air pollution
and health effects Inquinamento atmosferico prodotto dagli
aeroporti ed effetti sulla salute. Epidemiol Prev 38:237–243
Iwegbue CMA (2013) Chemical fractionation and mobility of heavy
metals in the vicinity of asphalt plants in Delta State, Nigeria.
Environ Forensic 14:248–259
Kabata-Pendias A, Pendias H (2001) Trace elements in soils and plants,
3rd edn. CRC, Boca Raton
Kaitantzian A, Kelepertzis E, Kelepertsis A (2013) Evaluation of the sources
of contamination in the suburban area of Koropi–Markopoulo, Athens,
Greece. Bull Environ Contam Toxicol 91:23–28
Kanellopoulos C, Argyraki A, Mitropoulos P (2015) Geochemistry of
serpentine agricultural soil and associated groundwater chemistry
and vegetation in the area of Atalanti, Greece. J Geochem Explor
158:22–33
Kaur R, Rani R (2006) Spatial characterization and prioritization of heavy
metal contaminated soil-water sources in peri-urban areas of national
capital territory (NCT), Delhi. Environ Monit Assess 123:233–247
Kelepertzis E, Argyraki A (2015) Geochemical associations for evaluating the availability of potentially harmful elements in urban soils:
lessons learnt from Athens, Greece. Appl Geochem 59:63–73
Khanmirzaei A, Bazargan K, Amir Moezzi A, Richards BK, Shahbazi K
(2013) Single and sequential extraction of cadmium in some highly
calcareous soils of southwestern Iran. J Soil Sci Plant Nutr 13:153–164
Koulourasis M, Aloupi M, Angelidis MO (2009) Total metal concentrations in atmospheric precipitation from the Northern Aegean Sea.
Water Air Soil Poll 209:381–403
Lin Y, Han P, Huang Y, Yuan GL, Guo LX, Li J (2017) Source identification of potentially hazardous elements and their relationships with
soil properties in agricultural soil of the Pinggu district of Beijing,
China: multivariate statistical analysis and redundancy analysis. J
Geochem Explor 173:110–118
Lindsay WL, Norvell WA (1978) Development of a DTPA soil test for
zinc, iron, manganese and copper. Soil Sci Soc Am J 42:421–428
Lv J, Liu Y, Zhang Z, Zhou R, Zhu Y (2015) Distinguishing anthropogenic and natural sources of trace elements in soils undergoing recent 10-year rapid urbanization: a case of Donggang, eastern China.
Environ Sci Pollut Res 22:10539–10550
Masiol M, Harrison RM (2014) Aircraft engine exhaust emissions and
other airport-related contributions to ambient air pollution: a review.
Atmos Environ 95:409–455
Massas I, Ehaliotis C, Gerontidis S, Sarris E (2009) Elevated heavy metal
concentrations in top soils of an Aegean island town (Greece): total
and available forms, origin and distribution. Environ Monit Assess
151:105–116
Massas I, Ehaliotis C, Kalivas D, Panagopoulou G (2010) Concentrations and
availability indicators of soil heavy metals; the case of children’s playgrounds in the city of Athens (Greece). Water Air Soil Poll 212:51–63
Massas I, Kalivas D, Ehaliotis C, Gasparatos D (2013) Total and available
heavy metal concentrations in soils of the Thriassio plain (Greece)
and assessment of soil pollution indexes. Environ Monit Assess 185:
6751–6766
Nelson DW, Sommers LE (1982) Total carbon, organic carbon and organic matter. In: Page AL, Miller RH, Keeney DR (eds) Methods of
soil analysis, Chap. 29. Soil Science Society of America, Madison
Olowoyo JO, van Heerden E, Fischer J (2013) Trace metals concentrations in soil from different sites in Pretoria, South Africa. Sustain
Environ Res 23:93–99
Papathanasiou C, Makropoulos C, Mimikou M (2013a) The
Hydrological Observatory of Athens: a state-of-the-art network for
the assessment of the hydrometeorological regime of Attica, Proc.
13th International Conference on Environmental Science and
Technology, 5–7 September, Athens, Greece
Papathanasiou C, Massari C, Pagana V, Barbetta S, Brocca L, Moramarco
T, Makropoulos C, Mimikou M (2013b) Hydrological Study of
Rafina catchment, Technical report for Action B1: Catchment
Hydrological Modelling of the FLIRE Project (LIFE11 ENV GR 975)
Rao P, Zhu A, Yao W, Zhang W, Men Y, Ding G (2015) Sources and risk
assessment of metal contamination in soils at the international airport of Shanghai, China. Toxicol Environ Chem 96:1153–1161
Ray S, Khillare PS, Kim KH (2012) The effect of aircraft traffic emissions
on the soil surface contamination analysis around the international
airport in Delhi, India. Asian J Atmos Environ 6:118–126
Riley EA, Gould T, Hartin K, Fruin SA, Simpson CD, Yost MD, Larson T
(2016) Ultrafine particle size as a tracer for aircraft turbine emissions. Atmos Environ 139:20–29
Salminen R, Batista MJ, Bidovec M, Demetriades A, De Vivo B, De Vos
W, Duris M, Gilucis A, Gregorauskiene V, Halamic J, Heitzmann P,
Lima A, Jordan G, Klaver G, Klein P, Lis J, Locutura J, Marsina K,
Mazreku A, O’Connor PJ, Olsson SA, Ottesen RT, Petersell V, Plant
JA, Reeder S, Salpeteur I, Sandstrom H, Siewers U, Steenfelt A,
Tarvainen T (2005) Geochemical atlas of Europe. Part 1: background information, methodology and maps. Espoo Geological
Survey of Finland, p 526. http://weppi.gtk.fi/publ/foregsatlas/
Scheinost AC, Abend S, Pandya KI, Sparks DL (2001) Kinetic control of Cu
and Pb sorption by ferrihydrite. Environ Sci Technol 35:1090–1096
Shrinivasa Gowd S, Ramakrishna M, Govil PK (2010) Assessment of
heavy metal contamination in soils at Jajmau (Kanpur) and Unnao
industrial areas of the Ganga Plain, Uttar Pradesh, India. J Hazard
Mater 174:113–121
Tesseraux I (2004) Risk factors of jet fuel combustion products. Toxicol
Lett 149:295–300
Tessier A, Campbell PGC, Bisson M (1979) Sequential extraction procedure for the speciation of particulate trace metals. Anal Chem 51:
844–851
Theophanides M, Anastassopoulou J (2009) Air pollution simulation and
geographical information systems (GIS) applied to Athens
International Airport. J Environ Sci Heal A 44:758–766
Vander Wal RL, Bryg VM, Huang CH (2014) Aircraft engine particulate
matter: macro-micro-and nanostructure by HRTEM and chemistry
by XPS. Combust Flame 161:602–611
Документ
Категория
Без категории
Просмотров
5
Размер файла
1 275 Кб
Теги
017, s11356, 0455
1/--страниц
Пожаловаться на содержимое документа