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Environmental Monitoring and Assessment (2006) 117: 357–375 DOI: 10.1007/s10661-006-0994-8

c Springer 2006 

SPATIAL VARIABILITY AND MONITORING OF PB CONTAMINATION OF FARMING SOILS AFFECTED BY INDUSTRY BILAL CEMEK1 and RIDVAN KIZILKAYA2,∗ 1

Department of Agricultural Engineering, Faculty of Agriculture, Ondokuz Mayis University, 55139 Samsun, Turkey; 2 Department of Soil Science Faculty of Agriculture, Ondokuz Mayis University, 55139 Samsun, Turkey (∗ author for correspondence, e-mail: [email protected])

(Received 4 May 2005; accepted 1 July 2005)

Abstract. In this study, the relationship between some physico-chemical properties of soils and lead contamination in soil due to emission from industrial operations in Samsun province of Turkey was investigated. The extent of timely contamination was studied by comparing the obtained results with the results of the study conducted in the same region in 1998. An area of 225 km2 (15 km × 15 km), which was divided into 1000 × 1000 m grid squares (16 lines in the east and south directions), was selected within the industrial area. The total of 256 grid points was obtained and soil samples were collected from three depths (0–5, 5–15, and 15–30 cm) of each grid center in 2004. The total Pb concentrations of soil samples were determined as 65.84–527.04 μg g−1 at 0–5 cm in depth, 58.50 – 399.54 μg g−1 at 5–15 cm in depth, and 44.65–330.07 μg g−1 at 15–30 cm in depth. DTPA-extractable Pb concentrations of soils were found to be in the range of 1.52–9.03 μg g−1 , 0.54–7.09 μg g−1 , 0.19– 6.13 μg g−1 at 0–5, 5–15, and 15–30 cm depths, respectively. There were significant relationships between both total or DTPA-extractable Pb concentrations and selected physico-chemical properties of soil. According to enrichment factor (EF) values calculated from the total Pb concentrations, 11.3% of the study area (225 km2 ) was enriched with Pb in high level, but 77% of the area was in significant enrichment level with Pb. The average total and DTPA-extractable Pb concentrations increased as 11 and 13%, respectively in comparison with the results of 1998. Keywords: enrichment factor, Pb pollution, smelter, soil, spatial variability

1. Introduction The metal content in soil is a sum of metals originating from natural processes and human activity. It is estimated that the contribution of the metals from anthropogenic sources in soil is higher than the contribution from natural ones (Nriagu and Pacyna, 1988). Significant increases in soil metal content are found in areas of high industrial operation where accumulation may be several times higher than the average content in uncontaminated areas. In addition, areas distant from industrial centers also show increasing metal concentrations due to long-range atmospheric transport. This fact has been observed by numerous authors (Amundsen et al., 1992; Saur and Juste, 1994; Steinnes et al., 1997). Accumulation of heavy metals in arable soils is an important issue because of its potential transfer through crops to animals and humans (Adriano, 1986; Kabata-Pendias and Pendias, 1992).

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Of the heavy metals, lead (Pb) is considered a widespread contaminant (Oliver, 1997). Lead poisoning can be regarded as one of the most prevalent public health problems in the world (Nriagu, 1988). The toxicity of Pb to animals and humans is fairly well documented. A recent review by Oliver (1997) implicated Pb in reproductive failures and brain damage (encephalopathy) causing hyperactivity and efficiency in the fine motor function. Children are mostly vulnerable to Pb poisoning through soil and dust ingestion (Watt et al., 1993; Mellor and Bevan, 1999) especially in developing countries, where soil, dust ingestion and inhalation by children are common because of unpaved surroundings and roads. Pocock et al. (1994) reviewed the epidemiological evidence of the effect of Pb on children’s intelligence and concluded that there were some significant inverse relations between Pb concentration in blood and the intelligence quotients (IQ) of children over five years in some developed countries. From this respect Pb is an toxic element, not only because of its toxicity for human being but also because of the high potential for root uptake and accumulation in above ground plant parts (Adriano, 1986; Kabata-Pendias and Pendias, 1992; Davies, 1995; Oliver, 1997). Lead can be added to soils through atmospheric deposition, industrial wastes, soil parent materials (Oliver, 1997) and also by the application of Pb containing agrochemicals to soils. However, soils have high capacity to immobilize Pb by sorption to clays, pedogenic oxides and organic matter (Sauve et al., 2000). Soil physico-chemical properties such as texture, pH, and organic matter play a very important role in the availability of Pb in the soil (Basta and Tabatabai, 1992; Li and Shuman, 1996). The magnitude of the problem, depending upon chemical properties of Pb and environmental conditions, may be vary effects in a specific locations. As Li and Shuman (1996) and Riffaldi et al. (1976) noted soil organic matter and texture plays an important role in Pb concentrations in soil. Some physico-chemical properties, such as pH, CEC, lime and clay content, are important factors affecting accumulation of Pb in soil. In this study, Pb pollution (total and DTPA-extractable Pb concentrations) in soils around the industrial operations resulting from emission was determined by soil samples obtained from different soil depths and the relationship between Pb contamination and some soil physico-chemical properties was investigated. In addition, the change in Pb contamination depending upon time was determined by comparing the results obtained from the spatial distribution of Pb pollution with the results of study conducted by Kızılkaya (1998) in the same area.

2. Materials and Methods 2.1. S ITE

CHARACTERISTICS

The study area is 225 km2 , which is located in northern Turkey, at the coast of Black Sea, 41◦ 21 N latitude and 36◦ 15 W longitude (Figure 1) and surrounded by

SPATIAL VARIABILITY AND MONITORING OF

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Figure 1. Topografic map of study area showing the location of soil sampling points.

C¸ar¸samba Plain in the east and the south-east and by A¸saˇgıcinik, Tekkek¨oy Plains in the south direction. There are small scale industrial operations and small settlements located in the center of Samsun province, which is in 14 km west direction of the experimental field. Ye¸silırmak delta and coastal plains are in coastal area, where

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industrial operations are located in. Physiography increases towards interior. There are also plains at altitude of 900–1700 m in these areas, that are located in direction of the south and south-east. 2.2. C LIMATE The minimum and maximum temperatures in February, August are 6.6 ◦ C and 23 ◦ C, respectively. The mean temperature is 14.2 ◦ C. The mean annual rainfall is 670.4 mm and this region has semi-humid climate (R f = 47.21). Even though changes in wind-direction occur every month, wind usually flows from north and west directions the most (Anonymous, 2003). 2.3. C HARACTERISTICS

OF FACTORIES

Two industrial factories are located side by side in the north-west of the study area ¨ and the coast of the Black Sea. One of them is fertilizer factory (TUGSAS ¸ ) and the other is copper factory (KB˙I). The total area, including green areas, of fertilizer factory is 275 ha, whereas the copper factory is settled on area of 362 ha. The local industries consist of fertilizer and copper factories that cover 9 and 20 ha of areas, respectively. Phosphate stone, ammonium, sulphuric acid, phosphoric acid, ammonium sulphate, potassium chloride, and pyrite are used as raw materials in the fertilizer factory. The annual (average) amount of 80,000 tons pyrite ash and 350,000 tons phosphogyps are stored in the environment as solid wastes. Copper, silica sand, coke breeze, and SO2 are used as raw materials in the copper factory. The annual (average) amount of 150000 tons flotation waste is stored in the environment as solid waste. Chemical properties of solid wastes are presented in Table I. 2.4. SOIL

SAMPLING AND LABORATORY ANALYSES

The position of the factories, spatial distribution of agricultural soils, wind speed and direction are considered in the selection of the study area and the arrangement of grids for soil sampling. Soil samples were obtained in 2004 July. The change in Pb TABLE I ¨ Chemical properties of solid wastes of fertilizer (TUGSAS ¸ ) and copper (KB˙I) companies Company

Solid waste

Chemical composition

¨ TUGSAS ¸

Pyrite ash

58.63% Fe, 12.00% SiO2 , 0.05% Al2 O3 , 0.34% P2 O5 , 3.22% S, 1.2% Pb, 0.18% As. 32.90% CaO, 45.63% SO3 , 1.84% SiO2 , 0.83% P2 O5 , 0.16% Al2 O3 , 0.28% F, 0.02% Cl 29.1% SiO2 , 47% Fe, 3.3% Zn, 0.6% S, 0.12% Pb, 0.07% As

Phospho-gypsum KBI

Waste

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contamination by the time was determined by comparing the results obtained from this study with the results of a study conducted by Kızılkaya (1998) in the same area. An area measuring 15,000 × 15,000 m was selected within the industrial area, divided into 1000 × 1000 m grid squares (16 lines in the east and south directions). The total of 256 grid points were obtained and soil samples were collected at three depths (0–5, 5–15, and 15–30 cm) of each grid center in 1998 and 2004. After transporting the soil samples to the laboratory, they were prepared for analysis by drying under shade, removing crop roots and stones by hand, smashing and sieving in 2 mm sieve. The soil physico-chemical properties were determined based on (in parentheses) as: particle size distribution (Bouyucos, 1951), pH in soil-water suspension by pH meter (Rowell, 1996), organic matter using wet oxidation method with K2 Cr2 O7 (Walkey, 1946), lime content by volumetric calcimeter method (Martin and Reeve, 1965), and cation exchange capacity (CEC) by sodium saturation method (Chapman, 1965). Total Pb: the total Pb analyzed after digestion in hydrofluoric, nitric, sulphuric, and perchloric acids and Pb in solution was determined by Inductively Coupled Plasma (ICP) (Balraadjsing, 1974). Available Pb: soil samples were extracted with DTPA solution (0.005 M DTPA + 0.01 M CaCl2 + 0.1 M TEA) and Pb content was determined using ICP (Lindsay and Norwell, 1978). 2.5. ENRICHMENT

FACTOR

The enrichment factor value (EF) for Pb was calculated using the equation suggested by Sposito (1989) and Agbenin (2002) as: EF = (Pbsoil )/(Pbearthcrust ) where Pbsoil is the total concentration in the soil and Pbearthcrust is the average Pb concentration in earth crust, which is approximately 14 mg kg−1 (Sposito, 1989). Five contamination categories are recognized on the basis of the EF values (Sutherland, 2000). EF < 2 EF = 2–5 EF = 5–20 EF = 20–40 EF > 40

2.6. S TATISTICAL

Deficiency to minimal enrichment Moderate enrichment Significant enrichment Very high enrichment Extremely high enrichment

AND GEOSTATISTICAL ANALYSES

Data analyses for each sampling grids were performed in three steps: (i) normality tests were applied (Kolmogorov–Simirhov); (ii) distributions were described with

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descriptive statistics (arithmetic mean, standard deviation, standard error, arithmetic maximum and minimum mean, coefficient of variation (CV), and soil Pb contents in both years were compared with t-test; (iii) for each variables, range, nugget and sill variance values were determined using semivariograms. Variable maps were produced by kriging technique (Isaaks and Sarivastava, 1989). Normality tests were performed using SPSS 10.0. Geostatistical software (GS +5.1, 2001; Gamma Design Software) was used to construct semivariograms and spatial structure analysis for variables. The hypothesis and parities by Burgess and Webster (1980). Semivariance is defined as the half of estimated square difference between sample values in a given distance (lag) (Trangmar et al., 1985). Estimated semivariance at the lag h is λ(h) =

 1 N (h) [z(xi) − z(xi + h)]2 2

where z is the regionalized variables, z(xi) and z(xi +h) are measured sample values at xi and xi + h points, and N is the number of pairs separated with distances h (lag space). In both years, maximum lag distances were 1000 m and there were 10 lags for each semivariogram. Calculated semivariances include between 930 and 5014 pairs for each of lag distances class. Active lag distances were 14,390 m for years. Model selection for semivariograms was done on the basis of regression (r 2 ) and visual fitting according to GS +5.1 program. 2.7. C ORRELATION

ANALYSIS

Correlation analysis was done using SPSS 10.0. Soil samples were divided into three categories based on Pb concentration as “all data from total area”, “uncontaminated”, and “contaminated”. The relations between the numerical values of Pb concentration related to this category and physico-chemical properties of soils were determined and these relations were found to be significant (P < 0.05 and P < 0.01), respectively.

3. Results and Discussion 3.1. P HYSICO-CHEMICAL

PROPERTIES ,

Pb CONTENTS

IN SOILS

Some physico-chemical properties of 768 soil samples obtained from 256 sampling point at 0–5,5–15, and 15–30 cm depths in the total of 225 km2 experimental area are presented in Table II. Even though physico-chemical properties of soils have indicated a wide range distribution, samples have low content of calcium carbonate (40

– 2992 17933 1575 –

ha

1998

2632 17325 2543 –

–

ha

2004

0.00 11.7 77 11.3 0.00

%

0–5 cm

0.00 60.5 37.9 1.6 0.00

% – 13612 8528 360 –

ha

1998

– 11610 10192 698 –

ha

2004

0.00 51.6 45.3 3.1 0.00

%

5–15 cm

0.00 78.9 20.3 0.8 0.00

%

– 17752 4568 180 –

ha

1998

– 16875 5445 180 –

ha

2004

0.00 75 24.2 0.8 0.00

%

15–30 cm

TABLE IV Comparison as area and % of EF values of the study area soils in 1998 and 2004 years

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Figure 2. Spatial distribution of enrichment factor (EF) as to total Pb concentrations of soils in 1998 and 2004 years.

3.2. E NRICHMENT

FACTOR

The EF values calculated from the total Pb contents in 2004 are presented in Table III. The significant increase (mean % 11) in EF values was determined when compared to the values of Kızılkaya (1998). According to the categorized EF values by Sutherland (2000), Pb contamination was more prevalent at 0–5 cm depth (Figure 2) in both years and was named as “significant enrichment” level (Table III). On the other hand, Pb contamination at 0–5 cm depth in 1998 was “very high enrichment (20–40) level” 7% (1575 ha), this level increased to 11.3% (2542.5 ha) in 2004. Significant increase was similarly observed at 5–15 and 15–30 cm depths in 2004 compared to 1998 (Table IV). 3.3. G EOSTATISTICAL

ANALYSES

The experimental semivariograms were calculated using untransformed data, since the data exhibited sufficiently normal distributions. Directional semivariograms

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TABLE V Isotropic model parameters for best fitted semivariogram models of Pb and EF Year 1998

Total-Pb

DTPA-Pb

EF

2004

Total-Pb

DTPA-Pb

EF

Depth (cm)

Nugget Co

Sill Co + C

Range, km

r2

Model

0–5 5–15 15–30 0–5 5–15 15–30 0–5 5–15 15–30 0–5 5–15 15–30 0–5 5–15 15–30 0–5 5–15 15–30

10 10 10 1.42 0.55 0.001 0.1 0.1 0.01 10 10 10 0.01 0.01 0.001 0.1 0.1 0.01

21120 6130 4129 4.13 1.48 2.01 70.2 33.8 21 31120 8845 4542 7.03 3.81 2.01 201.1 43.54 22.11

25.76 17.49 19.34 14.39 14.39 22.39 16.79 18.92 19.25 23.24 18.66 19.58 19.85 20.2 19.61 29.45 18.02 18.65

0.981 0.971 0.963 0.794 0.802 0.960 0.981 0.971 0.963 0.982 0.970 0.964 0.930 0.975 0.965 0.982 0.970 0.964

Linear Linear Linear Linear Linear Linear Linear Linear Linear Linear Linear Linear Linear Linear Linear Linear Linear Linear

were calculated at the angles of 0◦ (N–S), 45◦ (NE–SW), 90◦ (E–W), and 135◦ (SE– NW) for each soil property. There was no distinct difference among the structures of the semivariograms in the four directions for any of the soil properties. Therefore, all distributions of the Pb measured were considered to be isotropic. This means that directional effects are not showed, and the semivariance is only a function of the separation distance between the pairs. The best-fitted semivariogram models and model parameters, such as nugget variance, sill variance, and range obtained for soil properties, are presented in Table V. Nugget variance that was expressed as the percent of total semivariance was used to define for spatial dependency of soil variables. If this rate was equal to or lower than 25%, variables were accepted as strongly dependent and if the rate was between 25 and 75%, variables were moderately dependent and if the rate was higher than 75%, variables were weakly dependent (Cambardella et al., 1994). When the slope of semivariogram was close to zero since the nugget effect was not considered,it was accepted that the variables were randomly (no spatial dependency) (Cambardella and Karlen, 1999). The linear model has a slope that is close to zero, total variance equals the nugget variance, and the variables are not spatially correlated (Isaaks and Sarivastava, 1989). In this study, Pb content and EF values had linear models (the slope is significantly different from zero) that were spatially correlated at all lag

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distances greater than the minimum grid spacing distances. The semivariograms for Pb content and EF did not exhibit a zero slope or close to zero slope at each depths in the both year. Both Pb and EF variables had a range and did not randomly distributed. The range values were greater than 16.79 km (Table V) for the above mentioned Pb content and EF. 3.4. TOLERABLE

LEVEL

While soil properties, such as clay content, organic matter and lime content, and pH (Dube et al., 2001; Xian and Shokohifard, 1989; Soldatini et al., 1976; Gerriste and Van Driel, 1984) have enormous role on the heavy metal contamination and storage into soils, tolerable level is generally accepted as 100 μg g−1 for Pb (Kloke, 1980). Lead content over from this value can not be stored in soils; as a result, Pb is transported to either groundwater or nutrient cycle. Therefore, it has environmental risk. The Pb pollution risk map (>100 μg Pb g−1 ) prepared by using the total Pb contents in 1998 and 2004 are presented in Figure 3.

Figure 3. Spatial distribution of tolareable Pb concentrations of soils in 1998 and 2004 years.

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The Pb pollution risk was high at the surface of 0–5 cm due to high Pb contamination. While 35% of the 225 km2 area at 0–5 cm in 1998 was under the risk, it increased to 38.3% in 2004. Significant increase was similarly determined at 5–15 and 15–30 cm depths for following years (Table VI). Our results showed that contamination due to emission was 9 and 11 km in south and east directions, respectively, in 1998, whereas 9 and 13 km for south east directions, in 2004. 3.5. THE

RELATIONSHIPS BETWEEN Pb CONCENTRATIONS AND SOIL PHYSICO - CHEMICAL PROPERTIES

The statistical relationship between the total Pb and DTPA-extractable Pb and between both Pb concentration and physico-chemical properties, such as texture, organic matter, pH, CEC, and calcium carbonate content, was determined (Tables VII and VIII). The high positive correlations (P < 0.01) between the total Pb and DTPAextractable Pb in contaminated and noncontaminated areas were remarkable. The increase in the total Pb resulted in increase in DTPA-extractable Pb. Similarly, the other studies showed very significant relations between the total and DTPAextractable Pb and stated that the DTPA-extractable metals meant available form of concentration (Lindsay ve Norvell, 1978). However, significant negative correlations (P < 0.01) were determined between the total Pb and soil pH. Soil pH has significant effect on the transformation of Pb from nonsoluble to available form and soil acidity (decreasing of pH) significantly increases the availability of Pb (Basta and Tabatabai, 1992; Baldwin and Shelton, 1999; Harter, 1983). Therefore, the negative relationship between the DTPA-extractable Pb and pH is expected or inevitable. The negative relationship between the total Pb and pH was also determined. This situation might be due to the fact that contaminants such as SOx , NOx , F compounds (Kızılkaya 1998) in addition to Pb emissions from factories causes the formation of the acidity in soils. Similarly, significant relations between Pb concentrations and soil properties, such as texture, organic matter, calcium carbonate content, and CEC were observed. Although our results are parallel to those found by workers, they are conducted with the others (Zimdahl and Foster 1976; Riffaldi et al., 1976; Gerriste and Van Driel, 1984; Yin et al., 2002; Kızılkaya et al., 2004).

4. Conclusion Pb pollution was presented by risk map and EF value was calculated from the total and available Pb in soil samples obtained from the study area within 6 years (from 1998 to 2004). The available Pb increased significantly depending upon the increase in the total Pb content. The significant increase of EF was determined depending upon the increase in Pb concentration. The results indicated that Pb enrichment was in the surface layer (0–5 cm) and the significant increase was determined at

% 65 35

Total Pb, μg g−1

≤ 100 >100 14625 7875

ha

1998

61.7 38.3

%

0–5 cm

13882 8618

ha

2004

81.3 18.8

% 18292.5 4230

ha

1998

77 23

%

5–15 cm

17325 5175

ha

2004

91 9

%

20475 2025

ha

1998

88.7 11.3

%

19957 2543

ha

2004

15–30 cm

TABLE VI Comparation as area and % of buffer capacites (>100 μg g−1 ) as to Pb values of the study area soils in 1998 and 2004 years

370 B. CEMEK AND R. KIZILKAYA

15–30

5–15

0.478∗∗ 0.406∗∗ 0.467∗∗ 0.645∗∗ 0.662∗∗ 0.657∗∗ 0.774∗∗ 0.810∗∗ 0.728∗∗

0.984∗∗ 0.989∗∗ 0.988∗∗ 0.984∗∗ 0.972∗∗ 0.982∗∗ 0.988∗∗ 0.979∗∗ 0.985∗∗

0–5

All data Contaminated Uncontaminated All data Contaminated Uncontaminated All data Contaminated Uncontaminated

Sand

Total Pb

Soil depth, cm 0.305∗∗ −0.218 0.037 −0.659∗∗ −0.105 −0.687∗∗ −0.685∗∗ −0.566 −0.550∗∗

Clay 0.640∗∗ −0.384∗ −0.490∗∗ −0.540∗∗ −0.378 −0.564∗∗ −0.507∗∗ −0.889∗∗ −0.543∗∗

Silt −0.908∗∗ −0.784∗∗ −0.695∗∗ −0.850∗∗ −0.756∗∗ −0.792∗∗ −0.805∗∗ −0.675∗ −0.822∗∗

Org. matter −0.678∗∗ −0.647∗∗ −0.595∗∗ −0.718∗∗ −0.742∗∗ −0.677∗∗ −0.701∗∗ 0.310 −0.688∗∗

pH

TABLE VII Relationships between soil physico-chemical properties and total-Pb content

−0.218∗∗ −0.215 −0.160∗ −0.113 −0.314 −0.112 −0.202∗ −0.510 −0.229∗∗

CEC

0.348∗∗ 0.009 0.255∗∗ 0.625∗∗ −0.816∗∗ 0.670∗∗ 0.564∗∗ −0.912∗∗ 0.716∗∗

CaCO3

SPATIAL VARIABILITY AND MONITORING OF

Pb CONTAMINATION 371

15–30

5–15

0.444∗∗ 0.314∗ 0.473∗∗ 0.603∗∗ 0.572∗∗ 0.620∗∗ 0.755∗∗ 0.709∗ 0.702∗∗

0.984∗∗ 0.989∗∗ 0.988∗∗ 0.984∗∗ 0.972∗∗ 0.982∗∗ 0.988∗∗ 0.979∗∗ 0.985∗∗

0–5

All data Contaminated Uncontaminated All data Contaminated Uncontaminated All data Contaminated Uncontaminated

Sand

Total Pb

Soil depth, cm 0.264∗∗ −0.211 −0.036 −0.620∗∗ −0.096 −0.660∗∗ −0.686∗∗ −0.648 −0.556∗∗

Clay −0.591∗∗ −0.330∗ −0.497∗∗ −0.502∗∗ −0.406 −0.522∗∗ −0.471∗∗ −0.943∗∗ −0.495∗∗

Silt −0.839∗∗ −0.662∗∗ −0.701∗∗ −0.828∗∗ −0.632∗∗ −0.776∗∗ −0.781∗∗ −0.754∗ −0.794∗∗

Org. matter −0.644∗∗ −0.758∗∗ −0.567∗∗ −0.685∗∗ −0.632∗∗ −0.647∗∗ −0.677∗∗ 0.229 −0.658∗∗

pH

TABLE VIII Relationships between soil physico-chemical properties and available-Pb concent

−0.222∗∗ −0.232 −0.133 −0.098 −0.287 0.074 −0.185∗ −0.492 −0.204∗∗

CEC

0.332∗∗ −0.086 0.259∗∗ 0.589∗∗ −0.669∗∗ 0.646∗∗ 0.532∗∗ −0.931∗∗ 0.682∗∗

CaCO3

372 B. CEMEK AND R. KIZILKAYA

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5–15 and 15–30 cm depths. The territories affected by the factory emissions were broadened in industrial settlements (Figures 2 and 3). The possible reasons of these conditions are following: 1. The continuation of industrial operations up to the date of soil sampling 2. The increase of the court actions between the farmers and industrial managers because of the decrease in crop yield due to the industrial contamination, paying the compensation to the farmers and the increase of height of chimnies of factories as a temporary solution, 3. The distribution of Pb in the environment due to muffler emissions on the roads and agricultural activities, the existence of no restrictions for no-lead benzene usage in the vehicles, 4. The application of agricultural chemicals, such as fertilizers and pesticides, causes in increase of the heavy metal concentrations. The usage of 145 tons DAP (diammonium phosphate) and 200 tons of CAN (calcium ammonnium nitrate) fertilizers between 1998 and 2004 and the existence of Pb in these fertilizers may cause contamination of soils. In addition, the significant Pb pollution was determined in soils around the in¨ dustrial settlement (TUGSAS ¸ and KBI) in Samsun. This contamination increased the mean total Pb and available Pb in the rate of 11% and 13%, respectively, within 8 years. Therefore, observing contamination levels in soils around industrial operations and similar ecosystems is very important for monitoring soil contamination status by soil samplings periodically. Also, the application of reclamation methods, such as the addition of adsorbent materials – clay and zeolit to soils, or phytoremediation, or bioremediation are required in the region or in similar ecosystems.

References Adriano, D. C.: 1986, Trace Elements in the Terrestrial Environment, Spinger-Verlag Inc., New York, USA, 533 pp. Agbenin, T. O.: 2002, ‘Lead in a nigerian savanna under long-term cultivation’, Sci. Total Environ. 286, 1–14. Almas, A., Singh, B. R. and Sueistrup, T. E.: 1995, ‘The impact of the nickel industry in Russia on concentrations of heavy metals in agricultural soils and grass in Sor-Varanger, Norway’, Norwegian J. Agr. Sci. 9, 61–74. Amundsen, C. E., Hanssen, J. E., Semb, A. and Steinnes, E.: 1992, ‘Long-range transport of trace elements to Sourthern Norway’, Atmos. Environ. 26A, 1309–1324. Anonymous: 2003, ‘Samsun Climatic Data (1974–2002)’, State Meteorological Services (DMI), Unpublish, Ankara, Turkey. Baldwin, K. R. and Shelton, J. E.: 1999, ‘Availability of heavy metals in compost-amended soil’, Bioresource Technol. 69, 1–14. Balraadjsing, B. D.: 1974, ‘The determination of total lead in soil’, Commun. Soil Sci. Plant Anal. 5, 25–37.

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