108 Revista Română de Materiale / Romanian Journal of Materials 2016, 46 (1),108 -114

IN MEMORIAM Prof. Dr. Ing. PETRU BALTĂ

DETERMINAREA CONCENTRATIEI DE METALE GRELE ÎN SOLURILE

DIN APROPIEREA ZGUREI DE GUNOI DETERMINING THE CONCENTRATION OF HEAVY METALS

IN THE SOILS NEAR SLAG LANDFILLS

DANIELA LAURA BURUIANA1∗ , ŞTEFAN BALTĂ1, CĂTĂLINA ITICESCU1, LUCIAN P. GEORGESCU1, DĂNUŢ LEFTER1, INA I. HUMENIUC2

1UNIVERSITATEA DUNĂREA DE JOS DIN GALAŢI - 55 Domnească Str.,800008, Galaţi, Romania, 2SC TopoScad SRL, Lieşti, 807180, Galaţi, Romania

The paper presents the study of crops in rural areas along the Siret River basin near the industrial area of Galati, affected by heavy metal pollution

The city of Galaţi is situated in the geographic center of the largest hydrographic basin in Europe being in the same time, together with Brăila city one of the most important industrial area in Romania. The present research in are on multicriterial monitoring points complex with prognosis using Kriging method. Interpolation methods estimate the values in unsampled locations. The mapping and spatial analysis often requires converting the field measurements into continuous space.

Articolul prezintă studiul culturilor în zonele rurale

de-a lungul bazinului râului Siret aproape de zona industrială a oraşului Galaţi, afectate de poluarea cu metale grele.

Orasul Galaţi este situat în centrul geografic al celui mai mare bazin hidrografic din Europa, fiind în acelaşi timp, împreună cu oraşul Brăila unul dintre cele mai importante zone industriale din România. Prezenta cercetare se bazează pe punctele de monitorizare complex multicriterial cu prognoza cu ajutorul metodei Kriging. Metode de interpolare estimează valorile în locaţiile dintre punctele de monitorizare. Cartografia şi analiza spaţială necesită adesea convertirea domeniul măsurătorile în spaţiul continuu.

Keywords: kriging, pollution, soil, vegetation 1. Introduction

Galaţi is an industrial area, situated in the South - East of the largest hydrographic basin in Europe therefore it is highly sensitive to all types of pollution. Galati has an important steel and iron industry and different historic industrial activities.

The object of this paper is, using XRF technique to determine the level of a number of heavy metals (As, Cd, Co, Hg, Mn, Zn, Pb, Cr and Cu) in the vicinity of the city (S-V area). The second part of this paper presents a method called kriging that is a prediction method to determine soil pollution for less accessible areas. In the scientific world the XRF method has been utilized by “Metode atomice şi nucleare aplicate în studiul metalelor grele poluante” [1] and from local area Antoaneta Ene, Alina Boşneagă, L. Georgescu “Determination of heavy metals in soils using XRF technique” [2].

Authors like Mindaugas Raulinaitis, Gytautas Ignatavičius, Stanislovas Sinkevičius, Vytautas Oškinis in “Assessment of heavy metal

contamination and spatial distribution in surface and subsurface sediment layers in the northern part of Lake Babrukas”[3], X.J. Wang in his article “Kriging and heavy metal pollution assessment in wastewater irrigated agricultural soil of Beijing's eastern farming regions”[4], Ilaria Guagliardi, Domenico Cicchella, Rosanna De Rosa in “A Geostatistical Approach to Assess Concentration and Spatial Distribution of Heavy Metals in Urban Soils”[5], Vaidotas Valskysa, Gytautas Ignatavičiusa, Marina Valentukevičienėb in “The Analysis of Sediments Contamination with Heavy Metals after Hydro-mechanical Treatment in the Southern Part of Lake Babrukas”[6] utilized the kriging method as a characterization of the spatial variation of heavy metals in soil.

The retention of heavy metals in soil depends on the pH of that soil and of the interstitial water but also on the concentration of solution in metals. The dispersion of elements in the environment are subject to physical and chemical barriers [7]. The adsorption barriers are formed in soils rich in

∗ Autor corespondent/Corresponding author, E-mail: dana.negoita@gmail.com

D. L. Buruiană, Ş. Baltă, C. Iticescu, L.P. Georgescu, D. Lefter, I.I. Humeniuc / Determinarea concentraţiei de metale grele 109 în solurile din apropierea zgurei de gunoi

adsorbents such as secondary clay minerals, colloidal suspensions or alluvial deposits, due to the power of attracting and retaining various cations, an area favored by the Siret Valley. The capacity of vegetation and organisms to assimilate or redistribute, within the geochemical cycle, a number of chemicals released by soil weathering processes is a field of great importance in terms of environmental protection and human health [8]. Papacostea P. (1976) estimated that the microelements in the soil can be grouped into five groups; and the first three: soluble in water, exchangeable adsorbed are in balance and are the most important in ensuring microelements for plants during the growing season [9].

Similar studies about studying the pollution of heavy metals in soil have been made in Bacau city, Rovinari area, Rosia Montana area with different results. If in Bacau city the soil pollution show no concern, in Rovinari area the concentration of Cu, Cd and Zn were very high and in Rosia Montana area the concentration of Zn are high with some values above the intervention limit, values above the intervention limit are noted for Cd, Pb and Cu. This paper has two purposes: the first one is to determine the extent of the heavy metal pollution in soil, in an area known for pollution do to proximity to industrial activities and the second is demonstrating how the kriging method works and to allow us to see a bigger picture of the soil pollution than just the analyses of our sample points. Determining the heavy metal pollution of this soil is important do to the fact that the area is near a village and a major water source. Using the data from the studies carried out all over the country we could gain a better understanding about the soil pollution in Romania and what measures should be taken for a safe environment. 2. Materials and method

The X-ray fluorescence spectrometry is an analytical technique non-destructive qualitative and quantitative used to determine the chemical composition of the samples. For metal analysis, the XRF analyzer emits X-rays to irradiate primary purpose of the test sample. During interaction with the samples, X-ray emission tube products may be subject to be spreading (dominant process) or subjected to absorption of the sample atoms in a process known as the photoelectric effect (absorption coefficient) [10].

The NITON XLT 792 tool analyzes the X-ray emission lines characteristic of the inner layers of atoms: K, L, and occasionally layer M. X-ray emission lines characteristic to layer K are the stronger lines on an item, and therefore are the preferred analytical lines. K lines are always accompanied by L and M lines of the same element. The energies of the L and M lines are much smaller than K lines and the process can

usually be neglected for those items for which the K lines are useful analytically.

X ray fluorescence spectrometry is a well-established analytical technique widely used in industrial and research applications for elemental composition analysis. A relatively recent development has been the availability of portable instrumentation, which can be used for both the direct in situ non-destructive analysis of samples, and also is readily transportable to field sites for use in a ‘mobile laboratory’ style of operation [11]. The overall efficiency of the fluorescence process is referred to as the excitation efficiency and it is proportional to the product between the absorption coefficient and fluorescence yield. Our XRF analyzers provide lab-quality soil/sediment chemistry in seconds (As, Cd, Co, Hg, Mn, Zn, Pb, Cr and Cu) [12].

The samples were collected in plastic bags and stored at 4°C. Each sample weighing approximately 350-400 grams. After collecting, the samples were weighted and dried at 150°C temperature until a constant weight was achieved. The dry sample are initially ground with a mortar and pestle and passed through a sieving system of 60µ dimension, if there were oversize the procedure which was repeated until the sample passes though sieves. A portion of sample of finely ground sample was then placed in a sample analysis cup for analysis. The sample cup was be one-half to three-quarters full as per instructions. The sample cup was covered with a Mylar film for analysis. For each sample concentration and uncertainty for As, Cd, Co, Hg, Mn, Zn, Pb, Cr, and Cu was recorded [13,14].

For the XRF testing of the encapsulated soil samples, we used a NITON XTl 793 X-ray spectrometer with an Rh tube. Thus, the used analyzer, NITON XTl 793 XRF, allowed us to simultaneously analyze these 9 elements (heavy metals). 3. Kriging method

Due to the rise in demand for spatial data

the interpolation methods were created to describe and model spatial patterns. The most common methods are: Kriging, IDW, Thiessen polygons and TIN. One of the more frequent use of the interpolation method is to transform the data from the field (sampling points) into a continuous form such as maps. We implement an interpolation method to predict the values in an unsampled location and to assess the uncertainty of the predicted values as an alternative to a detailed survey. There are more than one method but for this paper we used the ordinary kriging method (Caridad-Cancela et al., 2005) [15].

Kriging method works best in a convex area (an area where, in addition to two points, will also contains the segment that unites them).

110 D. L. Buruiană, Ş. Baltă, C. Iticescu, L.P. Georgescu, D. Lefter, I.I. Humeniuc / Determining the concentration of heavy metals in the soils near slag landfills

Fig. 1 - Distribution of the 47 sampling points/ Distribuţia 47 puncte prelevate.

Usually, the results of a kriging interpolation are expected value (kriging average) and dispersion (kriging variant), estimated in the desired point in the region.

The applied interpolation method is ordinary kriging and for all variables (heavy metals concentrations) recording an asymmetry of the data sets, we used the method of normalization through logarithms or power transformation. Thus, the creation of a prediction area for the values of the heavy metal concentration was achieved on three sectors, Figure 1. (The distribution of the 47 sampling points).

4. Results and discussions To start we decided the area that we would

analyze taking in consideration several facts like proximity to a pollute area, proximity to an industrial area, possibility of contaminating a water supply. Are analyzed area is located near a major county road, a railroad line and nearby an industrial area. After deciding on the area a team of two people went in to the field with the necessary equipment (a GPA South 82S for collecting the coordinates of the sampling points and equipment for collecting samples of soil in the

Fig. 2 - Distribution of heavy metals in the analyzed soil As / Distribuţia de metale grele din solul analizat As

D. L. Buruiană, Ş. Baltă, C. Iticescu, L.P. Georgescu, D. Lefter, I.I. Humeniuc / Determinarea concentraţiei de metale grele 111 în solurile din apropierea zgurei de gunoi

Fig. 3 - Distribution of heavy metals in the analyzed soil Cd / Distribuţia de metale grele din solul analizat Cd.

Fig. 4 - Distribution of heavy metals in the analyzed soil Co / Distribuţia de metale grele din solul analizat Co.

Fig. 5 - Distribution of heavy metals in the analyzed soil Hg / Distribuţia de metale grele din solul analizat Hg.

112 D. L. Buruiană, Ş. Baltă, C. Iticescu, L.P. Georgescu, D. Lefter, I.I. Humeniuc / Determining the concentration of heavy metals in the soils near slag landfills

Fig. 6 - Distribution of heavy metals in the analyzed soil Mn / Distribuţia de metale grele din solul analizat Mn.

Fig. 7 - Distribution of heavy metals in the analyzed soil Zn / Distribuţia de metale grele din solul analizat Zn.

Fig. 8 - Distribution of heavy metals in the analyzed soil Pb / Distribuţia de metale grele din solul analizat Pb.

D. L. Buruiană, Ş. Baltă, C. Iticescu, L.P. Georgescu, D. Lefter, I.I. Humeniuc / Determinarea concentraţiei de metale grele 113 în solurile din apropierea zgurei de gunoi

specific points) to collect the 47 sample points. In the field the area that was to be analyzed was surveyed and the sample points were taken as equally distanced as possible so that the kriging method used would be more accurate.

The analysis of the soil samples taken from the sampling points emphasized the presence of heavy metals in soils in concentrations specific to the industrial activities which had previously been carried out, respectively Pb and Zn, in concentrations which exceed in most cases the normal values, being, however, situated below the alarm threshold [(200 mg/kg) Pb and (700 mg/kg) Zn] for industrial use [17].

The results of spatial interpolation through the application of kriging model were concretized in a series of 9 maps regarding the identification of heavy metals in the analyzed areas (As, Cd, Co, Hg, Mn, Zn, Pb, Cr and Cu), Figure 2-10.

Correlation of distribution maps with other types of maps (road transport network, the network

of transport by rail, industrial areas map active and/or inactive etc.) for comparative analyzes and identify potential sources of pollution we came to the following conclusions: road traffic is the main active source of pollution for Mn, Cu, Zn and rail traffic has been identified as an important source of Cu.

From the geostatistical analysis it can be concluded that diminishing pollution is an important factor of dispersal for the heavy metal.

The main sources of pollution of the area surveyed are nearby industry but also agriculture and road traffic should be monitored continuously in order to find the best possible techniques for minimizing and reducing the amount of pollutants released into the atmosphere.

Increased levels of atmospheric pollutants by precipitation and soil pollution cause indirectly a cumulative effect to the existing level. In the analyzed area of Sendreni, because the Nord-East winds are most common, the dispersion of powder in suspense

Fig. 9 - Distribution of heavy metals in the analyzed soil Cr / Distribuţia de metale grele din solul analizat Cr.

Fig. 10 - Distribution of heavy metals in the analyzed soil Cu / Distribuţia de metale grele din solul analizat Cu.

114 D. L. Buruiană, Ş. Baltă, C. Iticescu, L.P. Georgescu, D. Lefter, I.I. Humeniuc / Determining the concentration of heavy metals in the soils near slag landfills

is accentuate by the slag dump nearby and also by intense road traffic. Experimental determinations have watched the degree of contamination of the soil. All metal concentrations were below the maximum allowable limit.

Landfill in the area of the steel plant is located near the urban area Sendreni along with a 50 years old fuel transshipment station which favors vegetation pollution with particulate matter carried away by the wind. This dust covers the surfaces of leaves often forming a crust with devastating effects due to high alkalinity which prevents foliar perspiration and respiration, disturbs the process of photosynthesis.

In the study of the effect of pollution on vegetation in the area analyzed, it is not easy to generalize a phenomenon linked to heavy metal pollution; the diversity, particular atmospheric chemistry, the possible combinations with various new polluting compounds - often unknown, the many transformations they undergo once released into the environment, the final state in which they get to interact with the vegetation, the manner in which species respond by structural and metabolic changes, are only some of the issues drawing the attention of researchers in agriculture [7,18]. Also a monitoring of heavy metal concentration in soil is especially important in securing a healthy environment for the people living near the analyzed area. 5. Conclusions

The negative influence of pollutants on

vegetation in the area analyzed was highlighted by the damage to the ecological balances. Even if the pollutants involved are different chemically, the place of the two points investigated in the paper, the presence of Siret Meadow lanes and atmospheric circulation driven along them, thermal inversions, rainfall, appreciable calm percentage contribute to the stability of the core with the highest concentrations above the vegetation along the area concerned. That is why the greatest impact of pollutants and vegetation occurs in areas bordering these waste ponds. The investigations were focused on observations of vegetation that serves pastures.

From the comparative analysis with the values determined in other studies realized in other parts of the country it shows that the maximum values obtained in this area are lower than most of the other areas analyzed for which we found information in the specialty literature. Using the data from the studies carried out and improved with data base obtained from synthesis of studies carried out in the country of the concentrations of heavy metals in the soil, it may be possible to make comparative analyzes relating to specified concentrations of heavy metals in the soil, on the basis of the soil use categories.

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