Spatial distribution and source identification of trace elementsin topsoil from heavily industrialized region, Aliaga, Turkey

Melik Kara & Yetkin Dumanoğlu & Hasan Altıok &

Tolga Elbir & Mustafa Odabası & Abdurrahman Bayram

Received: 22 January 2014 /Accepted: 14 May 2014 /Published online: 24 May 2014# Springer International Publishing Switzerland 2014

Abstract Topsoil samples (n=40) were collected froma heavily industrialized region in Turkey. The regionincludes several scrap processing iron–steel plants withelectric arc furnaces (EAFs), a petroleum refinery, apetrochemical complex, steel rolling mills, a naturalgas-fired power plant, ship-breaking yards and verydense transportation activities. The region has under-gone a rapid transition from an agricultural region to aheavily industrialized region in the last three decades.Collected soil samples were analyzed for 48 trace ele-ments using inductively coupled plasma-mass spec-trometry (ICP-MS). The elemental distribution patternin the region indicated that Nemrut area with denseiron–steel production activities was a hotspot for ele-mental pollution. In addition to crustal elements, con-centrations of anthropogenic trace elements (i.e., Fe, Zn,Pb, Mn, Cu, Cd, Cr and Mo) were very high in the areainfluencing many parts of the region. Elemental compo-sitions of fugitive sources polluting the soil (i.e., pavedand unpaved roads, slag piles, EAFs filter dust piles andcoal piles) were also determined. The methods (enrich-ment factors [EFs] and the index of geoaccumulation[Igeo]) used for determination of pollution status of soilshowed that Cr, Ag, Zn, As and Pb were the strongly

contaminating elements for the region. Principal com-ponent analysis (PCA) clearly indicated that anthropo-genic sources (steel production, refinery and petrochem-ical processes and traffic) were important sources in thisregion.

Keywords Trace elements . Topsoil . Pollutionassessment .GIS .Fugitivesources . Iron–steel emissions

Introduction

In industrial and urban areas, several pollutants areemitted from different sources such as industrial plants,vehicle emissions, residential heating, fugitive sourcesand natural activities (Guo et al. 2012; Anatolaki andTsitouridou 2007; Azimi et al. 2005; Salvador et al.2004). Soil is a crucial component of the ecosystem,and in industrial and urban areas it receives largeamounts of trace elements from several sources.Therefore, accumulated pollutants in surface soils canbe transported to different environmental components,such as deep soil, water, plants and dust particles. Whileelemental contamination of soils is caused mainly byatmospheric deposition, soil also affects the air qualitysince enriched trace elemental contents in atmosphericparticulate matter originate from resuspension of pollut-ed soils (Ashbaugh et al. 2003).

Assessment of the trace elemental contents in soiland their origin are primary objectives for maintainingand improving soil quality in many regions. Therefore,to establish reliable policies for a sustainable soil quality

Environ Monit Assess (2014) 186:6017–6038DOI 10.1007/s10661-014-3837-z

M. Kara (*)Center for Air Resources Engineering and Science,Clarkson University, Potsdam, NY 13699-5708, USAe-mail: melik.kara@deu.edu.tr

M. Kara :Y. Dumanoğlu :H. Altıok : T. Elbir :M. Odabası :A. BayramDepartment of Environmental Engineering, Dokuz EylulUniversity, Tinaztepe Campus, Izmir 35160, Turkey

for a region, it is necessary to have a good knowledge ofsoil pollution. Soil pollution is often determined bycomparing elemental concentrations with the relatedenvironmental guidelines (CCME 2007; VROM 2000)and by using potential ecological risk index with respectto relevant background levels (Luo et al. 2012). Severalstatistical methods have also been widely used to deter-mine the degree of the pollution in the soil. (Dragovicet al. 2008; Wei and Yang 2010; Li et al. 2014).Multivariate analyses (principal component analysis[PCA] and cluster analysis [CA]) for identification ofpossible sources (Zhao et al. 2007; Chen et al. 2008; Liand Feng 2012) and geostatistical analysis (spatial map-ping based on GIS) for determining of possible hotspotsof trace elements (Zhao et al. 2014; Yesilonis et al. 2008;Guo et al. 2012; Yuan et al. 2014) have also been usedfor industrial and urban soils.

Soil pollution has become a severe problem in manyparts of the world due to human activities (Facchinelliet al. 2001; Solgi et al. 2012; Zhang 2006; Davis et al.2009). Following rapid social and economic develop-ment over the past several decades, soil trace elementalpollution in urban, industrial, agricultural and miningareas has also become serious and widespread in someregions of Turkey. Recently, studies were carried out onsoils affected by human activities (i.e., industrial andmining) in different regions of Turkey (Odabasi et al.2010; Canbay et al. 2010; Gemici et al. 2009; Koz et al.2012; Kumru and Bakac 2003; Yatkin and Bayram2011; Yaylalı-Abanuz 2011). Results have indicated thattrace element concentrations in soil reached up to highlevels in some heavily industrialized regions (i.e.,Iskenderun, Gebze). Aliaga region is also one of theheavily industrialized regions in Turkey. The regionhas undergone a rapid transition from an agriculturalregion to a heavily industrial region, and has formed acomplete industrial structure arising from iron–steelproduction from scrap, petroleum refining, petrochemi-cal plants, electric power generation and other industries(i.e., fertilizer plants, steel rolling mills). The establish-ment of industrial activities without proper planning andsubsequent population increase have resulted in impor-tant impacts on the local ecosystem and posed a poten-tial threat to human health.

The objectives of this study were (1) to determine theconcentrations of trace elements in soils of a heavilyindustrialized region (Aliaga, Turkey) and characterizetheir spatial distribution using a GIS (GeographicInformation System)-based interpolation method, and

(2) to identify the possible sources of trace elements insoils. Samples from fugitive dust sources (paved andunpaved roads, slag and coal piles, and stack dust fromscrap processing iron–steel plants with electric arc fur-naces [EAFs]) were also characterized to determine theireffect on soil pollution.

Materials and methods

Study area and sampling sites

Located in ∼50 km north of Izmir, Turkey, the Aliagaregion contains several significant pollutant sources in-cluding scrap processing iron–steel plants with EAFs, alarge petroleum refinery, a petrochemical complex, sev-eral steel rolling mills, a natural gas-fired power plant, afertilizer plant, scrap storage and classification sites,large slag and scrap piles, a very dense transportationactivity of ferrous scrap trucks, heavy road and railtraffic, ship-breaking yards and busy ports used forproduct and raw material shipping. The Aliaga town,with a population of ∼60,000, several villages and agri-cultural areas, are also located in the region. The regionlocated on the coast of Aegean Sea is mainly classifiedwithin the local climate of the Mediterranean Sea char-acterized by hot, dry summers and cool, wet winters andspring. The annual rainfall reaches to 688 mm whilehighest monthly rainfall is 131 mm during December(TSMS 2013). The prevailing wind directions are north-west for summer and southeast for winter. Locations ofthe sampling sites, industrial activities and settlements inthe study area and wind rose for the region are illustratedin Fig. 1.

Sample collection and analysis

The topsoil samples (upper 5 cm layer) were collectedfrom industrial (n=7), Nemrut area (n=13) and non-industrial (rural or residential) (n=20) sites in July2009 (in dry period) in the study area. Also, fugitivedust samples were collected from paved roads (n=13),unpaved roads (n=8), slag piles (n=4), EAF filter dust(n=3), coal dust (n=1), PM10 and PM2.5 (n=3) from thestack gas of EAFs after fabric filters in the Nemrutindustrial area (Fig. 1).

The soil samples were collected as composites of at theleast 10 points in each sampling site and the plant roots,leaves and stones were initially removed. Approximately

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Fig. 1 General view of the study area

Environ Monit Assess (2014) 186:6017–6038 6019

500-g samples were placed into polyethylene bags andtransported to laboratory within a portable icebox. At thelaboratory, the samples were passed through a plasticsieve (1 mm mesh size) after being homogenized manu-ally. Soil samples for each site (∼0.5 g) were weighedusing a microbalance (GEC Avery, capable of weighing100 μg) and they were digested using a HNO3 (65 %,Merck, Suprapur®) and HCl (30 %, Merck, Suprapur®)mixture with a microwave digestion system (MARS 5,CEM Corp.). Digested samples were diluted to 100 mLwith deionized water (18.2 MΩ/cm) and filteredthrough a 0.45 μm PTFE filter (Millipore) beforeanalysis. The same procedures were applied for thefugitive dust samples after they were sieved through a75-μm mesh sieve (i.e., the fine size fraction classifiedby EPA Method AP-42).

PM10 and PM2.5 samples from the stack gas of EAFswere collected using a sampling train for PM10 andPM2.5 fractions (Model PF 20357, PF 20358, PF20359; Zambelli Inc.) according to EPA Method 201/201A. The sampling was carried out with a flow rate of14.27 l/min determined according to stack gas proper-ties and 4 mm nozzle size was used to obtain anisokinetic sampling. Teflon filters (PTFE) (47 mm,2.0–μm pore size; Whatman) conditioned at 103 °Cfor 1 h followed by 1 h in a desiccator were weighedbefore and after sample collection using a microbalance(Mettler-Toledo; capable of weighing 1 μg). The filterswere digested and prepared using the same proceduresutilized for other samples.

Analysis of trace elements (Ag, Al, As, B, Ba, Be, Bi,Ca, Cd, Ce, Co, Cr, Cu, Dy, Er, Eu, Fe, Ga, Gd, Hg, Ho,K, La, Li, Lu, Mg, Mn, Mo, Na, Nd, Ni, P, Pb, Pr, Rb,Sb, Se, Sm, Sn, Sr, Tb, Th, Tl, U, V, Y, Yb and Zn) werecarried out using inductively coupled plasma-massspectrometry (ICP-MS) (Agilent 7700x, with HMI).Quality control/quality assurance procedures wereapplied during the sample preparation and analysis.Aliquots of reference material sandy loam soil(CRM030-50) from RTC (RT Corp.) were digestedand analyzed along with the samples to determinerecovery efficiencies of the extraction procedure.The recovery of elements was in the range of 80–110 %of the certified elemental concentrations. The continuingcheck verification standard solution was used to checkthe validity of calibration curve during the analysis. Thelimit of detection (LOD) values for all elements wasdefined as the average plus three standard deviations ofthe blank sample amounts.

Physical and chemical properties of soil

In the study area, the most common soil group (67.5 %)is non-calcareous brown soils which are non-calcareoussoils over non-calcareous rock or massive limestone.They are followed by colluvial soils (11.5 %), brownforest soils (7.7 %), rendzina soils (5.4 %), alluvial soils(5.2 %), red brown Mediterranean soils (1.3 %), non-calcareous brown forest soils (1.2 %) and saline–alka-line soils (0.2 %) (Eroglu and Bozyigit 2013).

The pH of all soils was measured potentiometricallyin a 1:2.5 soil–water suspension using a pH meter(WTW pH 720) instrument. The mean pH value was7.8 while soil samples according to pH ranges weredetermined as slight acid for 2 %, neutral for 20 %,slightly alkaline for 42 %, moderately alkaline for23 %, strongly alkaline for 5 % and very strong alkalinefor 8 %. On the other hand, soil moisture content wasdetermined by weighting sub-samples of soils beforeand after drying at 103 °C in an oven for 24 h, and theorganic matter content was determined by loss on igni-tion in a muffle furnace at 600 °C for 4 h. While theaverage water content of soil was 3.1±1.8 % (with min.0.8 % and max. 9.1 %), average organic matter contentwas 8.5±5.2 % (with min. 2.9 % and max. 30.7 %) andaverage clay content was 36.8±11.9 % (with min.13.6 % and max. 61.3 %).

Statistical analysis

The statistical methods were applied to process theanalytical data to determine its distribution and correla-tion among the parameters. The IBM SPSS Statisticsversion 21 software was used for statistical analyses ofelemental concentrations in the soil samples. Basic sta-tistical parameters such as mean, median, standard de-viation, skewness and kurtosis were computed alongwith multivariate statistical techniques (PCA and CA).The PCA was carried out using Varimax rotation andKaiser Normalization and the CA was applied to thestandardized matrix of samples, using hierarchical clus-tering method. While PCA is used to describe possiblesources, CA organizes a set of variables into two ormore mutually exclusive unknown groups/clustersbased on combination of internal variables. In addition,an interpolation method (the inverse distance weighted[IDW]) was employed using GIS mapping software(ArcGIS 10) to determine the concentration levels oftrace elements in unsampled sites.

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Contamination assessment methods

The enrichment factor (EF) for trace elements in soil iswidely used as an index to identify their origins (crustalor anthropogenic) and to evaluate the degree of anthro-pogenic influences. It is calculated by Eq. 1:

EFTE ¼ CTE=CRð Þsample

CTE=CRð Þbackground; ð1Þ

where (CTE/CR)sample is the ratio of the concentration ofthe trace elements (TE) to that of reference element (R)in the soil sample, and (CTE/CR)background is the sameratio in the background soil. In this study, EF values forsurface soil samples were calculated using local back-ground soil to represent the regional geochemistry. Alwas selected as the reference element since it is one ofthe major components of the local soil. However, dif-ferent crustal elements (i.e., Ti, Sr, Fe, Mn and Na) havebeen used as the reference in the previous studies(Srinivasa Gowd et al. 2010; Iqbal and Shah 2011).Different classifications of EFs have been used to assessthe degree of anthropogenic input to soil (Acosta et al.2009; Gerdol et al. 2000; Varrica et al. 2000; Yuan et al.2014). Five categories were used in the present study;deficiency to minimal enrichment (EF<2), moderateenrichment (2<EF≤5), severe enrichment (5<EF≤20),very high enrichment (20<EF≤40) and extremely highenrichment (40<EF) (Iqbal and Shah 2011; Li and Feng2012; Yongming et al. 2006).

The contamination levels of trace elements in in-dustrial, urban and rural soils are evaluated by usingthe index of geoaccumulation (Igeo) introduced byMuller (1969). Igeo is used to determine trace elemen-tal contamination in soils by comparing the currentand pre-industrial concentrations of the elements. Thebackground or earth’s crust soil concentrations areused for calculation of Igeo because it is not alwayseasy to reach pre-industrial concentrations. It is com-puted using Eq. 2:

Igeo ¼ log2CTE

1:5BTE

� �; ð2Þ

where CTE denotes the measured concentrations ofthe trace elements in the examined soil and BTE

denotes the concentration of the element in the earth’scrust (Taylor and McLennan 1995). The constant 1.5allows analyzing the lithogenic variations of the con-tent of a given substance in the environment and to

detect very small anthropogenic influences (Muller 1969).The Igeo is classified as: uncontamined (Igeo≤0), un-contaminated to moderately contaminated (0<Igeo≤1),moderately contaminated (1<Igeo≤2), moderately tostrongly contaminated (2<Igeo≤3), strongly contaminat-ed (3<Igeo≤4), strongly to extremely contaminated(4<Igeo≤5) and extremely contaminated (5<Igeo)(Cheng et al. 2014; Iqbal and Shah 2011; Loskaet al. 2004).

To further assess the contamination levels of traceelements, the PI and the integrated pollution index(IPI) of elements were calculated using the followingequations:

PITE ¼ CTE=TTE ð3Þ

IPIN ¼ IPI2avg þ PI2max

� �=2

h i1=2; ð4Þ

where CTE is the concentration of a trace element insampled soil and TTE is the corresponding target con-centration of Dutch soil guidelines (VROM 2000),which are based on extensive studies on human andecotoxicology effects of soil contamination. In Eq. 4,IPIavg is the average value of all PITE, and PImax is themaximum value (Nemerow 1991). The IPIN is classifiedas: safe (IPIN≤0.7), precaution (0.7<IPIN≤1), slight pol-lution (1<IPIN≤2), moderate pollution (2<IPIN≤3) andheavy pollution (IPIN≥3) (Luo et al. 2012).

Results and discussions

The concentrations and spatial distributions of traceelements in the topsoil

The mean (and standard deviation) elemental concen-trations of non-industrial, industrial and Nemrut areasites are given in Table 1 along with overall median,kurtosis and skewness statistics. The Nemrut area waspresented and evaluated separately since it containsmany activities related to iron–steel production fromscrap.

Elemental composition indicated that the soil sam-ples from both industrial and non-industrial sites weredominated by crustal elements such as Ca, Fe, Al, Mgand K and the sea salt element, Na which is typical forAegean region. These elements were followed by thetrace elements (Zn, Mn, Pb) emitted by iron–steel pro-duction from scrap. This finding was consistent with

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Table 1 Elemental concentrations in industrial, Nemrut area, and non-industrial sites, and distributional statistics

Mean ± standard deviation (mg/kg dw) Overall

Industrial Nemrut area Residential/rural All regions Median Kurtosis Skewness(n=7) (n=13) (n=20) (n=40)

Caa 49.2±28.8 62.8±30.9 24.8±15.3 41.1±28.8 35.6 0.20 0.97

Fea 23.6±7.4 50.9±17.3 15.9±5.3 27.9±18.7 20.1 0.66 1.28

Ala 15.3±2.9 15.8±5.5 16.2±5.4 15.9±4.9 15.2 0.21 0.47

Mga 7.9±4.9 13.9±9.8 7.1±8.1 9.3±8.6 5.9 5.98 2.39

Zn 311±221 6,065±4,854 151±167 1,957±3,754 219 4.19 2.26

K 3,715±1,210 3,150±1,423 4,251±1,681 3,813±1,564 3,584 −0.54 0.44

Mn 731±284 3,148±1,704 612±221 1,397±1,486 672 4.18 2.05

Na 788±266 2,113±1,141 938±688 1,261±966 799 0.49 1.31

Pb 128±157 1,309±963 37.1±36.1 437±776 63.1 3.24 2.07

P 764±416 690±273 731±290 726±306 613 1.74 1.37

Ba 261±91.7 346±90.4 201±42.5 257±93.5 213 −0.23 0.89

Cu 54.6±52.6 237±118 24.3±15.8 94.1±117 28.5 0.54 1.40

Cr 30.6±19.1 232±146 20.8±15.5 86.2±125 24 4.60 2.14

Sr 136±78.2 115±35.8 82.7±53.6 103±57.7 86.4 3.36 1.66

Ga 50.4±18 77.9±32.5 40±8.78 53.5±25.9 41.3 4.35 1.98

Ni 50.2±23.7 71.9±36.6 18.5±8.21 40.8±32.9 30.2 2.64 1.58

V 63.8±46.3 41.4±20.6 26.8±7.53 38.6±27.1 32.5 10.75 3.07

Sn 2.77±2.27 32.5±16.5 2.81±3.11 11.7±16.5 2.71 0.79 1.49

Ce 42.8±10.3 28.1±10.7 38.3±10.9 36.1±11.8 35.6 0.26 0.21

B 5.3±1.99 25.5±17.8 5.12±4.04 11.3±13.7 5.68 4.31 2.22

As 31.7±18.5 25.5±14.7 16.9±29 22.4±23.8 17.7 12.97 3.18

Cd 0.88±0.85 23.5±21.3 0.38±0.59 7.42±15.5 0.45 8.19 2.77

Rb 16.8±4.38 18±10.8 20.7±7.96 19.1±8.38 17.9 0.12 0.57

Co 13.9±6.5 16.7±7.41 9.75±2.82 12.7±6.05 12 4.90 1.96

La 22.3±7.6 13.7±4.96 18.3±4.89 17.7±6.19 17.2 3.43 1.04

Nd 17.8±3.53 12.9±4.4 16±3.99 15.4±4.34 15.8 0.53 0.06

Th 11±4.94 9±4.56 9.38±3.55 9.6±4.11 8.92 −0.69 0.49

Y 10.9±1.41 8.24±2.01 10.5±2.67 9.89±2.49 9.87 2.17 0.76

Mo 2.31±1.44 8.02±4.78 1.07±1.44 3.57±4.21 1.33 1.32 1.56

Li 3.79±1.12 7.36±3.9 6.4±2 6.17±2.84 5.73 1.06 1.01

Sb 1.69±2.56 5.3±3.25 0.57±0.55 2.21±2.94 0.6 0.90 1.50

Ag 0.21±0.18 3.84±3.24 0.18±0.17 1.28±2.42 0.16 5.35 2.41

Pr 4.51±0.87 3.2±1.12 4.01±0.99 3.87±1.1 4 0.56 0.01

Bi 0.37±0.18 2.5±1.96 0.24±0.09 0.94±1.47 0.33 5.49 2.42

Sm 3.23±0.59 2.34±0.72 2.92±0.7 2.8±0.75 2.86 0.72 0.10

U 2.27±0.91 2.11±0.91 1.6±0.85 1.89±0.9 1.49 0.00 1.04

Gd 2.77±0.44 2.04±0.6 2.55±0.59 2.44±0.62 2.49 1.05 0.13

Dy 1.99±0.28 1.51±0.39 1.89±0.44 1.8±0.43 1.8 1.68 0.41

Se 1.12±0.18 1.16±0.43 1.01±0.23 1.08±0.3 1.03 6.10 1.78

Be 1.26±0.45 1.13±0.59 0.87±0.23 1.03±0.43 0.97 3.08 1.60

Er 1.04±0.15 0.79±0.2 1.01±0.26 0.95±0.25 0.95 2.02 0.69

Yb 0.9±0.14 0.69±0.17 0.9±0.25 0.84±0.23 0.84 2.53 0.95

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previous studies around this region (Yatkin and Bayram2011; Cetin et al. 2007). The mean concentrations of Zn,Mn, Pb were 6,065, 3,148, 1,309 mg/kg dw in Nemrutarea; 311, 731, 128 mg/kg dw in industrial sites and 151,612, 37.1 mg/kg dw in non-industrial sites, respectively.On the other hand, the mean concentrations of Ni, V, Asand Co that are anthropogenic elements associated withoil refining and combustion were measured as 71.9,41.4, 25.5, 16.7 mg/kg dw in Nemrut area; 50.2, 63.8,31.7, 13.9 mg/kg dw in industrial sites; and 18.5, 26.8,16.9, 9.8 mg/kg dw in non-industrial sites, respectively.B concentrations were also highest in Nemrut area, 25.5,5.3 and 5.1 mg/kg dw in Nemrut area, industrial sitesand non-industrial sites, respectively. This may be dueto the groundwater use in the cooling towers of severalplants having geothermal interferences in the study area(Senguler et al. 2000; Ozkan et al. 2011). Some anthro-pogenic elements in non-industrial sites and, generally,the rare earth element concentrations were lower than1 mg/kg dw.

The skewness values were calculated for each ele-ment (Table 1). The skewness is an indicator used indistribution analysis as a sign of asymmetry and devia-tion from a normal distribution. In nature, if an elementis not influenced by anthropogenic sources, it follows anormal distribution in an area (Zhao et al. 2010). Theelements Al, Ba, Ca, Gd, K, Rb and rare earth elementswere normally distributed in the topsoil of the studyarea, so they are thought to be affected mainly by thesoil parent materials. Ag, As, B, Bi, Cd, Cr, Mg,Mn, Pb,V and Zn (skewness >2) exhibited a right-skewed dis-tribution (most values are concentrated on left of themean, with extreme values to the right) with moreoutliers, which might be attributed to the anthropogenic

inputs and different rock types that may cause a largevariation in concentrations of some crustal elementssuch as Mg. On the other hand, other anthropogenicelements like Be, Co, Cu, Ga, Mo, Ni, Sb, Se, Sn, Srand Tl showed asymmetric distribution patterns withskewness values >1.5.

In the study area, the spatial distribution patterns ofsoil elemental concentrations varied greatly among sam-pling sites. The highest concentrations for almost alltrace elements were measured in Nemrut area and in-dustrial sites due to anthropogenic sources (Table 1).The mean concentrations of trace elements in theNemrut area were up to 61, 40, 35, 22, 12, 11, ten, ten,nine and eight times higher than those in non-industrialsites for Cd, Zn, Pb, Ag, Sn, Cr, Cu, Bi, Sb and Mo,respectively since iron–steel production from scrapemits significant amounts of these elements, both fromstack emissions and fugitive sources such as large slagand scrap piles. On the other hand, crustal elements(such as P, Ba, Sr) and rare earth elements (Nd, Pr,Sm, Dy, Er) levels did not show significant differencesamong the sampling sites. The spatial distributions ofselected elemental concentrations were mapped by IDWmethod and depicted in Figs. 2 and 3. The Fe, Zn, Cdand Cr distribution trends were generally similar, al-though their concentrations were different, indicatingthat these elements emitted from the same sources.However, the distribution of Fe was wider because it iscrustal as well as anthropogenic (due to steel plantemissions) in this area. The spatial distribution of Cuand Ga were slightly different from the distribution ofZn, Cd and Cr. Although the highest Cu and Ga con-centrations were found in iron–steel production areasimilar to other elements related to iron–steel production,

Table 1 (continued)

Mean ± standard deviation (mg/kg dw) Overall

Industrial Nemrut area Residential/rural All regions Median Kurtosis Skewness(n=7) (n=13) (n=20) (n=40)

Hg 0.16±0.29 0.58±0.44 0.15±0.27 0.43±0.41 0.25 0.94 1.29

Eu 0.53±0.1 0.41±0.14 0.43±0.1 0.45±0.12 0.45 0.11 0.04

Tl 0.57±0.29 0.34±0.11 0.29±0.12 0.36±0.19 0.3 3.69 1.98

Ho 0.38±0.05 0.29±0.08 0.37±0.09 0.35±0.09 0.35 1.87 0.54

Tb 0.37±0.07 0.25±0.08 0.34±0.09 0.32±0.09 0.31 0.61 0.37

Lu 0.15±0.02 0.11±0.03 0.15±0.05 0.14±0.04 0.14 2.69 1.09

a In g/kg dw

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Fig. 2 Spatial distribution of trace elements (Fe, Ag, Zn, Cd, Cr, Co) in soils around the Aliaga region

6024 Environ Monit Assess (2014) 186:6017–6038

Fig. 3 Spatial distribution of trace elements (Cu, Ga, V, Ni, K, Rb) in soils around the Aliaga region

Environ Monit Assess (2014) 186:6017–6038 6025

their concentrations were also high in the vicinity of shipbreaking yards and in the peninsula. Copper recycling byremoving the plastic insulation from copper wire andelectronic wastes are performed on the scraps from shipbreaking. This procedure is conducted by uncontrolledburning of the plastic coating in open areas. Therefore,substantial amounts of Cu are emitted from this recyclingprocess and salvage activities. As shown in Figs. 2 and 3,V hotspots were mainly in the petrochemical and refineryarea in peninsula because it is a marker for fuel-oilcombustion (Kim and Hopke 2004). Co and Ni showeda similar pattern and associated with the distribution of Vin the peninsula, since they were also emitted from oilcombustion, petrochemical complex and refinery. On theother hand, Co and Ni are also associated with iron–steelindustries using ferrous scrap (Ismail et al. 2013; Lineet al. 1997; Temple and Linzon 1976; U.S. GeologicalSurvey 2013). Therefore, the highest concentrations forNi and Co were measured in Nemrut area (iron–steelproduction area). K and Rb had completely differentspatial distribution patterns from the marker elements ofdominating sources (i.e., Cd, Zn, Pb, Ag, Sn, Cr, Cu, Bi,Sb for iron–steel production; V, Ni and Co for oil com-bustion, petroleum refining and petrochemical industry).Concentrations of K and Rb were lower in the Nemrutarea and industrial site. K has a crustal origin and is alsoemitted from wood combustion from residential heatingalong with Rb.

Present mean elemental levels in the industrial andnon-industrial soils were also compared with those re-ported form other regions around the world and uppercontinental crust (UCC) in Table 2. Concentrations ofsome crustal elements (Al, K, Mg, Na, Sr and Ba) werelower than those in UCCs and some rural regions. Caand Fe concentrations were considerably higher thanUCCs. This indicated that crustal element concentra-tions depend on the soil/rock formations; hence crustalelemental concentrations vary with regard to geologicalorigin. As compared to a previous study in the sameindustrial region (Yatkin and Bayram 2011), the con-centrations of Co, Cr, Mg, Ni, Sr and V were similarhowever levels of Cd, Cu, Fe, Mn, Pb and Zn wereconsiderably higher. Increase in the elemental concen-trations related to the iron–steel production might beattributed to their accumulation in the soil and increas-ing activities of these plants recently. Although the meanconcentrations of As, Cd, Cu, Mn, Pb and Zn measuredin industrial sites of the present study were higher thanmost of the reported levels in the Table 2, Cr, Cu and Ni

levels were lower than those reported from industrialarea in Ghaziabad, India (Chabukdhara and Nema2013). Mean concentrations of several elements fornon-industrial sites in this region were comparable tothose reported from other urban and rural sites.

The elemental concentrations of fugitive sources

In the study region, especially in Nemrut area, signifi-cant pollutant sources for soils are the fugitive sources(i.e., paved and unpaved roads, slag piles, EAFs filterdust piles and coal piles) and regular emissions fromstacks of the iron–steel plants. The uncontrolled partic-ulate matter emissions are emitted from roads by resus-pension due to moving vehicles, from the piles due toloading and dumping activities, and due to wind entrain-ment from the slag storage areas and coal screeningareas. These particulate matter emissions are thenaccumulated in local soil by dry and wet deposition.Therefore, samples were collected from these sourcesand they were characterized in terms of their ele-mental composition. Table 3 shows the elementalcompositions of the samples collected from fugitiveand regular sources.

Paved and unpaved roads

Dust from paved and unpaved roads is one of the majorsources of particulate matter in Nemrut area due to verydense transportation activity of ferrous scrap trucks. Themajor arterial roads (Canakkale-Izmir and Foca roads)passed through the study area. The mean hourly vehiclecounts were 125, 39 and 25 in Foca road and 496, 161and 134 in Canakkale-Izmir road for passenger cars,light duty trucks and heavy duty trucks, respectively.The elemental composition of paved road dust wasdominated by crustal elements such as Fe, Ca, Mg andAl. In addition, Zn and Pb were abundant in paved roaddust. These results were consistent with the other studies(Han et al. 2009; Lin et al. 2008). The elemental com-position of unpaved road dust was similar to the pavedroads, since the emissions from iron–steel production isthe dominant source in the area. On the other hand, theconcentrations in main roads (Canakkale-Izmir andFoca roads) were lower as compared to those in pavedroads. As compared to the elemental concentrations ofsoil samples in Nemrut area, the crustal element levels(Ca, Al andMg) were similar. However, Fe, Zn, Mn and

6026 Environ Monit Assess (2014) 186:6017–6038

Tab

le2

Com

parisonof

elem

entalconcentratio

ns(m

g/kg)with

theprevious

studiesaround

theworld

As

Ba

Cd

Co

Cr

Cu

Fe

KMg

Mn

Mo

Ni

PPb

SrV

Zn

Reference

Aliaga,Izm

irIndustrial(including

Nem

rutarea)

28312

1416

152

164

40,036

3,376

11,524

2,181

5.7

63720

836

123

503,763

ThisStudy

Aliağa,Izm

irNon-industrial

16201

0.4

9.7

2124

15,896

4,250

7,112

612

1.1

18731

3783

27150

ThisStudy

Aliaga,Izm

irIndustrial

512

2.3

23163

4527,800

18,300

14,300

864

6285

190

781,092

YatkinandBayram

(2011)

Kanpur,India

Industrial

295

2,652

4238

105

54159

SrinivasaGow

detal.(2010)

HongKong

Industrial

181.3

2687

62Chenetal.(1997)

Ghaziabad,India

Industrial

1.1

807

295

25,457

809

279

225

373

ChabukdharaandNem

a(2013)

Weinan,China

Industrial

8.5

542

1196

20538

2546

7771

Liand

Feng(2012)

Annaba,Algeria

Industrial

0.4

3139

24,270

355

5368

Maasetal.(2010)

Murcia,Spain

Urban

531

9.2

229.3

28,202

208

1419

27Acostaetal.(2009)

Xuzhou,China

Urban

0.6

7334

459

334

37198

169

Wang(2013)

Lishuicity,C

hina

Urban

8.8

0.5

6.4

3536

1463

43192

Luetal.(2010)

CentralCatalonia,

Spain

Urban

227

0.3

2520

21,754

463

2420

7450

72Tum

eetal.(2011)

China

Urban

110.4

7638

2727

74Cheng

etal.(2014)

MexicoCity,M

exico

Urban

135

9349

116

447

Rodríguez-Salazar

etal.(2011)

Hangzhoucity,C

hina

Rural/Urban

6.3

0.3

9.3

6237

415

2046

116

T.Chenetal.(2008)

NoviS

ad,S

erbia

Rural/Urban

1.7

3.6

2226

29110

SkrbicandDurisic-M

ladenovic

(2010)

Korea

Rural

1.9

0.4

1322

14132

Koetal.(2010)

Belgrade,Serbia

Rural

1.4

468.6

953

320

4222

Dragovicetal.(2008)

Luxem

bourg

Rural

58232

0.8

24124

3294,000

12,000

4,000

1,364

2070

44116

338

224

Horckmansetal.(2005)

Faridpur,B

angladesh

Rural

6.9

0.1

3812

20,372

3,841

282

24353

8.5

103

Rahman

andNaidu

(2010)

Islamabad,P

akistan

Rural

1.9

1823

148,371

1,124

2,988

424

3384

34Iqbaland

Shah

(2011)

Granada,S

pain

Rural

7.9

944

2020

1737

Díezetal.(2009)

Upper

Contin

ental

Crust

Background

1.5

550

0.1

1035

2535,000

28,000

13,300

600

1.5

20700

20350

6071

Taylor

andMcL

ennan(1995)

Environ Monit Assess (2014) 186:6017–6038 6027

Table 3 The elemental composition of the samples collected from fugitive and regular sources (mg/kg dw)

Fugitive sources The stack gas of EAFs

Paved roads Unpaved road Slag piles Filter dust Coal piles PM10 PM2.5

Fea 218±62.4 158±67.7 152±98.8 217±11.7 23.6 231±36.5 203±43.9

Caa 79.9±14.1 76.7±25.6 106±35.2 20.1±1 10 5.145±2.9 1.63±0.85

Mga 14.7±3.9 22.9±18.9 45.1±28.6 8.3±0.29 1.5 5.053±0.73 4.49±0.65

Ala 16.6±3.5 17.3±3.5 20.5±5.7 3.6±0.04 9.2 2.225±0.88 1.82±1.14

Zna 16.9±10.3 18.5±10.7 18.5±10.8 164±2.1 1.3 234±59.4 241±20.3

Mn 9,313±2,825 8,222±3,177 9,886±6,219 13,743±639 953 16,994±2,445 12,920±2,084

Pb 3,872±2,009 4,010±2,271 3,596±1,742 21,297±996 260 22,067±2,982 34,561±4,510

Na 1,809±718 3,219±1,663 3,518±4,507 15,115±625 533 23,169±3,457 25,179±4,004

K 1,950±664 1,934±499 1,987±969 11,468±610 1,045 16,219±2,956 19,658±4,544

Cr 948±293 788±233 1,138±931 1,851±126 53.5 1,943±153 1,736±190

P 904±91.2 872±214 875±298 837±26.5 756 771±204 1,010±234

Ba 684±125 614±143 724±292 454±18 347 628±148 834±169

Cu 774±180 605±257 556±316 2,216±70.6 75.5 2,839±358 3,068±527

Sr 205±29.2 221±15.5 245±19.5 72±2.82 246 54.8±9.31 47.9±6.14

Ni 247±75.5 169±64.3 147±85.2 180±9.22 30.4 204±38.9 251±62.7

B 117±44.5 122±37.2 140±80.1 377±1.43 15.6 348±78.1 315±11.4

Ga 121±21.7 113±22.2 129±47.2 109±0.76 67.1 190±41.9 236±35.4

V 115±27.3 120±49.4 124±59.2 53.1±4.76 21 41±6.93 36.2±5.08

Sn 74.5±31.3 66.5±30 69.4±40.9 516±10.4 3.37 679±44.5 787±107

Cd 66.8±33.9 65.8±41.5 57.5±33.3 733±34.7 3.78 928±190 949±198

Rb 21.5±7.59 19.4±6.05 28.2±24.6 62±0.59 5.71 83±15.9 108±24.6

Mo 43±17.8 27.9±11.9 24.1±14.3 33.5±2.2 2.41 43.1±9.26 60.5±10.4

As 33.8±3.93 31.1±10.1 23.3±10.7 48.7±1.81 7.66 62.3±5.25 74.5±2.25

Ce 24.6±2.84 26±4.38 22.4±7.64 4.83±0.07 20.8 5.22±0.86 4.1±0.48

Ag 17.4±8.86 18.2±10.1 18.8±12.4 173±4.98 1.32 216±45.2 293±57

Co 28.6±7.73 21.7±8.88 16.1±8.3 17.7±0.7 8.88 17.2±1.88 17.1±1.59

Li 12.7±3.3 14.3±2.59 13±2.84 36.9±1.39 8.11 44.9±5.82 39.4±1.73

La 12.6±1.54 12.7±2.41 11.5±4.3 2.1±0.03 10.5 1.17±0.31 0.9±0.01

Nd 10.6±1.01 10.8±2.14 10.9±2.45 2.03±0.08 8.7 1.26±0.17 0.85±0.07

Y 6.96±0.77 7.92±1.96 6.83±2.06 0.95±0.03 10 0.3±0.07 0.22±0.03

Bi 9.94±4.81 7.5±4.61 6.31±2.88 78±17.2 0.51 69.8±8.8 92.5±8.77

Th 5.45±1.35 4.87±1.6 4.53±3.02 0.26±0.02 3.05 0.14±0.03 0.07±0.02

Sb 4.79±2.21 4.79±2.6 3.95±1.71 29.3±0.84 0.25 38.7±4.56 46.6±6.97

Pr 2.7±0.31 2.79±0.57 2.91±0.81 0.47±0.04 2.26 0.29±0.02 0.19±0.01

Se 1.45±0.6 1.49±0.72 1.74±0.75 7.09±0.31 0.68 14±0.43 19.2±1.12

Sm 1.79±0.24 1.89±0.45 1.71±0.59 0.23±0.05 1.8 0.02±0.04 0.01±0.01

U 1.81±0.28 2±0.57 1.7±0.25 0.32±0.01 1.36 0.26±0.07 0.18±0.02

Gd 1.49±0.22 1.63±0.4 1.34±0.51 0.16±0.01 1.73 0.03±0.02 ND

Dy 1.23±0.14 1.39±0.33 1.14±0.35 0.16±0.02 1.56 ND ND

Be 0.69±0.15 0.79±0.27 0.76±0.43 0.12±0.01 1.42 0.05±0.02 0.03±0.01

Er 0.62±0.08 0.73±0.21 0.56±0.19 0.06±0.02 0.85 ND ND

Hg 0.58±0.23 0.58±0.32 0.53±0.39 2.1±0.34 0.42 7.08±2.58 9±3.1

Yb 0.56±0.07 0.67±0.18 0.53±0.17 0.06±0.01 0.66 ND ND

6028 Environ Monit Assess (2014) 186:6017–6038

Pb concentrations were up to five times higher than thesoil samples.

Slag piles

During iron–steel production slag is created as a solidwaste. Its elemental concentrations were higher than thetypical concentrations in Aliaga soil. Therefore, slagposes an environmental risk to human and natural lifethat come into contact with this substance. The area ofthe slag piles were 0.46 km2 in the Nemrut area. Theelemental composition of slag dust was dominated bycrustal elements such as Fe, Ca, Mg and Al. Highconcentrations of Zn and Pb were also observed in theslag dust samples. The element percentages of slag(<75 μm) were 15 % for Fe, 10 % for Ca, 4.5 % forMg, 2.1 % for Al, 1.8 % for Zn, 1.0 % for Mn and 0.4 %for Pb.

Coal piles

The coal screening and packaging plants in the Nemrutarea are one of the significant fugitive dust sources.Open coal processing area covered 0.24 km2 in thestudy area. The elemental concentrations were obvious-ly lower than other dust samples. Elemental composi-tion shows the abundance of Fe, Ca, Al, Mg, Zn, K, Mnand Na in the coal dust (<75 μm). Comparison of theprofiles in the present study with those reported previ-ously (Kong et al. 2011) showed similarities.

EAFs filter dusts

Isokinetic for PM10 and PM2.5 sampling was carriedout at the stack gas of EAFs after fabric filters. Filterdust samples (<75 μm) were also collected from the

plants. The results indicated that PM and filter dustsamples contained substantial amounts of Fe, Zn, Mn,K, Mg, Ca, Al, Pb, Cd, Cr, Cu and Sn. The followingmean percentage contributions were determined: 24 %,23 %, 16 % for Zn; 20 %, 23 %, 22 % for Fe; 2.5 %,2.3 %, 1.5 % for Na; 3.5 %, 2.2 %, 2.1 % for Pb; 1.3 %,1.7 %, 1.4 % for Mn; 2 %, 1.6 %, 1.2 % for K, 0.2 %,0.5 %, 2 % for Ca, 0.5 %, 0.5 %, 0.8 % for Mg in PM2.5,PM10 and filter dust, respectively. The percentage ofcrustal elements was higher in coarse fraction. In addi-tion, percentage of Cu, Al, Cr, Cd, P and Sn were rangedbetween 0.1 % and 0.3 %. The percentage contributionsof these elements in the present study were consistentwith the reported elemental composition of EAF dust inprevious studies (Yatkin and Bayram 2008; Sofilić et al.2004; Patil et al. 2013).

Assessment of pollution state and sources

Three approaches (EF, Igeo and IPI) were used for deter-mination of pollution status of soil samples, and thepossible sources were identified by PCA and CA inthe Aliaga region.

The EFs calculated relative to the background site forindustrial (including Nemrut area) and non-industrialsites are shown in Fig. 4a and b. As an indicator ofanthropogenic input in industrial sites, EFs indicatedmoderate enrichment for Ni, Fe, Na and Sb, and severeenrichment for Mn, B, Hg, Cr, Cu, Bi and Mo. Since theiron–steel plants with EAFs contributed significantly tothe soil pollution, Sn (EF=32.8) and Zn (EF=37.4) inindustrial sites (including Nemrut area) were highlyenriched compared to the non-industrial sites (EFZn=1.8, EFSn=5.1). However, Ag, Pb and Cdwere extreme-ly enriched in industrial sites with EFs of 42.6, 47.1 and121.4, respectively, whereas they were 3.9, 2.5 and 4.2

Table 3 (continued)

Fugitive sources The stack gas of EAFs

Paved roads Unpaved road Slag piles Filter dust Coal piles PM10 PM2.5

Eu 0.3±0.04 0.32±0.05 0.29±0.12 0.05±0.02 0.32 ND ND

Tl 0.44±0.11 0.43±0.15 0.25±0.11 1.87±0.1 0.74 2.97±0.29 3.61±0.27

Ho 0.21±0.03 0.25±0.07 0.19±0.07 0.01±0.01 0.27 ND ND

Tb 0.19±0.03 0.22±0.06 0.17±0.08 0.01±0.01 0.23 ND ND

Lu 0.06±0.01 0.08±0.03 0.06±0.03 ND 0.05 ND ND

a In g/kg dw

Environ Monit Assess (2014) 186:6017–6038 6029

for non-industrial sites. EFs for many trace elementsindicated no enrichment for non-industrial sites.

The non-industrial sites appeared to be uncontami-nated with negative Igeo values for the all trace elements.The mean Igeo values for Cd, Ag, Zn, As, Pb, Sb, Bi, Hg,Cu, Ga, Mo, Cr, Ni, Mn and Sn in the industrial sites(including Nemrut area) were in the range of 0.25–4.78.While Igeo values revealed strong to extreme contami-nation by Cr, they indicated strong contamination forAg, Zn, As, Pb in the industrial sites. Figure 5 presentsthe boxplots of the Igeo values for the trace elements inthe industrial sites. In Horozgedigi village located in

Nemrut area, the Igeo values for Cd, Ag, Pb, Zn and Sbwere found to be 7.96, 6.28, 6.39, 6.58 and 4.51, re-spectively showing extreme contamination.

The assessment of the EFs and Igeo values for theindustrial sites (including Nemrut area) indicated thatCd, Pb, Ag, Zn, Sn, Bi. Hg and Mo originated fromanthropogenic sources and they might pose a seriousrisk for soil environment in the industrial sites.

The PI values were calculated for As, Ba, Be, Cd, Co,Cr, Cu, Hg, Mo, Ni, Pb, Sb, Se, Tl, Vand Zn accordingto target concentrations given by Dutch soil guidelines,and then IPIN values were determined for the study sites.

0.1

1

10

100

Li

K

Ce

Tb

La

Sm

Nd

Gd

Eu

Pr

Dy

Rb Y

Ho

Er

Yb

Lu P

Se

Th

As

Co

Ba

Be

Mg

Ga V Tl

U

Ca

Sr

Ni

Fe

Na

Sb

Mn B

Hg

Cr

Cu

Bi

Mo

Sn

Zn

Ag

Pb

Cd

EFs

(a)

0.1

1

10

100

Sb

Li

Ni

K La

Eu

Ce

Tb

Sm

Nd

Pr

V

Gd

Se

Co

Dy

Fe

Cr

Ba Y

Ga

Ho

Rb

Th

Er P

Ca

Yb

Mn

Lu

Be

As

Zn B

Cu

Bi

Tl

U

Mg

Pb

Na

Sr

Ag

Mo

Cd

Hg

Sn

EFs

(b)

Fig. 4 Enrichment factors of elements in industrial (a), non-industrial (b) sites. The error bars represent 1 standard deviation

-2

0

2

4

6

8

10

Cd Ag Zn As Pb Sb Bi Hg Cu Ga Mo Cr Ni Mn Sn

Igeo

Val

ue

Fig. 5 Boxplots of the Igeo values for trace elements in the industrial sites

6030 Environ Monit Assess (2014) 186:6017–6038

The spatial distribution of IPIN values in surface soils inAliaga region is presented in Fig. 6. The results indicatedthat heavily industrialized Nemrut area and ship break-ing sites appeared to be the highest contaminated siteswith IPI values higher than 3. The elemental concentra-tions in these sites were significantly influenced byindustrial and fugitive emission sources such as iron–steel production and ship breaking yards. Figure 6 alsoshows that except two sites, other sites in the studyregion appeared to be slightly polluted with IPIN valueshigher than 1. This indicates that trace elemental pollu-tion has distributed to the entire region and soils havebeen significantly influenced by the elements derivedfrom anthropogenic activities. Cd, Cu, Pb and Zn whichare among themarker elements for iron–steel productionfrom scrap significantly contributed to IPIN values in afew sites. The PI values of Cd, Cu, Pb, and Zn rangedbetween 0.3 and 86.4, 0.4 and 11.6, 0.4 and 25.1, and 0.4and 74.4 for industrial sites (including Nemrut area) and0.1 and 3.6, 0.2 and 2.4, 0.2 and 1.6, and 0.2 and 5.5 fornon-industrial sites, respectively. The mean value of PIwas the highest for Zn, followed by Cd, Pb, Cu, Ba, Se,Hg, Co, Mo and Ni. In Horozgedigi, Turkelli, Gencelli

villages, IPIN values indicated heavy pollution with38.9, 4.0 and 3.5, respectively, while IPIN showed mod-erate pollution with 2.2 and 2.0 for Bozkoy and Aliagatown. This can pose a serious health risk for the peopleliving in these settlements.

To determine the relationships among trace elementsand to identify the possible sources in soil samples, PCAwith Varimax rotation was applied to the data obtainedfrom industrial and non-industrial sites in the region.The results of the PCA are shown in Tables 4 and 5 forindustrial (including Nemrut area) and non-industrialsites, respectively. For industrial sites, the analysis re-sulted in six factors accounting for 85.7 % of the cumu-lative variance. The first factor (PC1), that accounts for42.8 % of the variance, exhibited high loadings of Sn,Cr, Zn, Cu, Pb, Ag, Mn, Cd, Fe, Sb, Ga and Mo. Thisfactor could be interpreted as iron–steel production andsalvage activities in ship breaking yards since Sn Cr, Zn,Pb, Ag, Mn, Cd and Mo are marker elements for iron–steel production from scrap (Sofilić et al. 2004), whileCu, Sb and Ga are emitted as a result of recycling ofelectronic wastes (U.S. Geological Survey 2013).Anthropogenic elements like Hg and Ba were also

Fig. 6 The spatial distribution ofthe IPIs in surface soils in Aliagaregion

Environ Monit Assess (2014) 186:6017–6038 6031

associated with this factor. This finding was also inagreement with the pollution status of soil. The secondfactor (PC2) accounted for 12.19 % of the variance andassociated mainly with Mo and Ni. The primary uses ofNi and Mo are in the production of alloys includingstainless steel (ATSDR 2005). Ni is also emitted fromfuel-oil combustion. Therefore this factor also presentsindustrial activities. The third factor (PC3) showed highloadings with Se, Al, Mg and Sb. This factor could beassociated with emissions related to traffic and road dust(Stortini et al. 2009; Beuck et al. 2011). The fourthfactor (PC4) accounted for 7 % of the variance, and it

was associated with crustal elements like Ba, Sr and P(Srimuruganandam and Shiva Nagendra 2012). Thefifth (PC5) and sixth (PC6) factors were loaded withCo, Ni, V and As. Hence, these factors represent oilcombustion in refinery and petrochemical complexes(Karanasiou et al. 2009; Mansha et al. 2012). On theother hand, for the non-industrial sites, factors extractedfrom PCA were consistent with those for industrialsites since the anthropogenic sources affected the en-tire region. The extracted seven components accountedfor 91.4 % of the cumulative variance for the non-industrial sites. The first factor (PC1) that accounts for

Table 4 Factor analysis on ele-mental composition of industrialsoil samplesa,b

aExtraction method: principalcomponent analysis; rotationmethod: Varimax with KaisernormalizationbFactor loadings >0.400 werereported

PC1 PC2 PC3 PC4 PC5 PC6

Sn 0.962

Cr 0.916

Zn 0.909

Cu 0.909

Pb 0.900

Ag 0.896

Mn 0.880

Cd 0.876

Fe 0.849

B 0.822

Sb 0.810 0.407

Ga 0.806

Mo 0.771 0.500

Hg 0.704

Ba 0.686 0.423

Gd −0.646 −0.575Na 0.638

Ca 0.799

K −0.791Rb −0.697Se 0.856

Al 0.836

Mg 0.475 0.762

Sr 0.800

P 0.671

Co 0.906

Li 0.558 0.665

Ni 0.453 0.466

As 0.752

V 0.750

% of Variance 42.76 12.19 11.53 7.00 6.80 5.41

6032 Environ Monit Assess (2014) 186:6017–6038

23.7 % of the variance is associated with crustalelements (Sr, Mg, Ca, Na and Fe) and some anthro-pogenic elements (Ni, Mo and Hg). Therefore, this factorcould be explained as polluted soil, since anthropogenicinterferences (such as residual oil combustion) could beseen for the source. The second factor (PC2) accountedfor 20.2 % of the variance, associated with Fe, Zn, Cd,Cu, Pb, Cr, Sb, Ag, Co and Mn. Hence, this factorrepresents iron–steel production from scrap. Third(PC3) and sixth factors (PC6) are associated with iron–steel production, similar to PC2. The fourth factor (PC4)showed high loadings with Se, Al, Ba, Gd and Ga. This

factor might be explained as traffic and road dust. Thefifth factor (PC5) accounted for 10.4 % of the variance,associated with Ni, V, Co and Se which are the markerelements for fuel-oil combustion. The last factor withhigh loading of P may be related to fertilizer use inagricultural areas and emissions of the fertilizer plant inthe area.

The results of CA for 40 sampling sites using theirtrace elemental concentrations were illustrated with adendrogram in Fig. 7. Four groups were defined by thedendrogram in the study area. Mean concentrations forsome elements of each cluster and the number of the

Table 5 Factor analysis onelemental composition ofnon-industrial soil samplesa,b

aExtraction method: principalcomponent analysis; rotationmethod: Varimax with KaisernormalizationbFactor loadings >0.400 werereported

PC1 PC2 PC3 PC4 PC5 PC6 PC7

Sr 0.963

As 0.956

Mg 0.950

Hg 0.922

Mo 0.918

Ca 0.818

Na 0.715 0.543

Ni 0.610 0.594

Fe 0.519 0.493 0.513

Zn 0.974

Cd 0.974

Cu 0.923

Pb 0.857 0.410

Cr 0.830 0.442

B 0.890

Sn 0.846

Sb 0.482 0.733

Li 0.717

Ag 0.611 0.693

Ga 0.965

Ba 0.965

Se 0.668 0.579

Gd 0.650 0.522

Al −0.496 0.526 −0.410V 0.798

Co 0.407 0.672 0.426

K −0.766Mn 0.545 0.699

Rb −0.494 −0.579P 0.884

% of Variance 23.71 20.17 12.71 11.41 10.43 7.69 5.31

Environ Monit Assess (2014) 186:6017–6038 6033

sampling sites included in each cluster are given inTable 6. Groups 1 and 2 included mostly the samplescollected from non-industrial sites. In these groups,there were relatively low concentrations of anthropo-genic elements, and high concentrations of K, Al, P, Ce,

La, Pr, Rb, Sm and Th. Group 3 contained the highestconcentrations of Cd, Cr, Cu, Fe, Mn, Mo, Ni, Pb, Snand Zn among all the groups. The pollution level wasthe heaviest. All soils in Group 3 were located inNemrut area and this group reflected the influence of

Fig. 7 Dendrogram obtained by cluster analysis for trace element contents in soil samples

6034 Environ Monit Assess (2014) 186:6017–6038

iron–steel production from scrap. The last group wasslightly different from Group 3. Group 4 has also highconcentrations for anthropogenic elements and high pol-lution level although concentrationswere lower than thosein Group 3. It included some residential sites within theNemrut area as well as the industrial Nemrut area sites.

Conclusions

The surface soil samples were collected from industrialand non-industrial sites in July 2009 in the study area.

Fugitive dust samples were also collected from pavedroads, unpaved roads, slag piles, EAF filter dust, coaldust, PM10 and PM2.5 from the stack gas of EAFs.The results of the study indicated the impact ofanthropogenic sources on the levels of trace elementsin region’s soil. The soil was extremely contaminateddue to industrial activities, especially by iron–steelproduction and other associated activities in theNemrut area. Elemental composition indicated thatsoil samples were dominated by crustal elements.These elements were followed by Zn, Mn, Pb, emittedby iron–steel production from scrap. Concentrations ofCd, Zn, Pb, Ag, Sn, Cr, Cu, Bi, Sb and Mo in industrialsites were also high, consistent with those reported inprevious studies.

Fugitive sources like paved and unpaved roads, slagpiles, EAFs filter dust piles and coal piles were alsosignificant pollution sources for soils in the area. Theelemental composition measured in soil samples wassimilar to the composition of fugitive sources. Fe, Mn,Zn and Pb were the dominant elements for both soil andfugitive sources samples. The mean elemental compo-sition for iron–steel production emissions were 24 %,22 %, 2.8 %, 1.5 %, 0.3 %, 0.2 %, 0.2 % and 0.1 % forZn, Fe, Pb, Mn, Cu, Al, Cr and Cd, respectively.

EF and Igeo values were also calculated for traceelements. The highest EF values were calculatedfor Ag, Pb, Cd, Mn, B, Hg, Cr, Cu, Bi and Mo.Igeo values revealed strong to extreme contaminationby Cr. Moreover, Igeo values for Ag, Zn, As and Pbindicated strong contamination in industrial sites. Theassessment of the EFs and Igeo values for the indus-trial sites indicated that Cd, Pb, Ag, Zn, Sn, Bi. Hgand Mo originated from anthropogenic sources andthey may pose a serious risk for soil environment inthe industrial sites. According to IPIN values, heavilyindustrialized Nemrut area and ship breaking sitesappeared to be the highest contaminated sites. ThePCA results also indicated that anthropogenic sources(steel production, refinery and petrochemical processes,and traffic and road dust) were important sources inthis region.

Acknowledgments This study was funded by the “Assessmentof current status of Aliaga industrial region for air pollution”project conducted by Dokuz Eylul University and supported bythe Turkish Ministry of Environment and Urbanism and by theindustries located in Aliaga region. We also thank the Scientificand Technological Research Council of Turkey (TUBITAK) forscholarship support for the first author.

Table 6 Comparison of means of elemental concentrations(mg/kg dw) among clusters, and number of sites included ineach cluster

Group 1 Group 2 Group 3 Group 4

Mean of trace elements

Fe 18,370 16,162 65,694 42,439

Zn 194 218.38 7,855 4,597

Mn 649 631 4,503 2,278

K 4,176 4,473 2,397 3,023

Pb 50.4 61.9 1,650 1,044

P 770 820 516 628

Cr 24.9 19.6 353 157

Cu 31.8 27.8 326 182

Ni 26.5 26.4 101 56.9

Ga 44.6 41.3 82.9 70.6

V 39.4 27.1 56.2 42.1

Sn 2.39 3.80 41.5 24.9

B 4.35 6.64 40.2 16.6

Cd 0.57 0.49 28.4 18.7

As 14.4 16.8 21.0 44.5

Co 10.8 11.0 16.8 16.1

Rb 20.4 19.6 13.4 18.7

Mo 1.28 1.02 12.7 6.15

La 20.5 18.5 8.99 15.4

Sb 0.52 0.88 7.51 4.52

Y 10.8 10.3 6.16 9.37

Ag 0.15 0.24 5.12 2.87

Th 10.6 9.71 4.83 9.65

Bi 0.28 0.27 3.24 1.93

Number of sites included in each cluster

Non-industrial sites 12 7 0 1

Industrial sites 3 3 0 2

Nemrut Area 2 0 4 6

Environ Monit Assess (2014) 186:6017–6038 6035

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