Volume 16 – No

Volume 16 – No. 12b - 2007 pp. 1618 - 1691

Official Journal of:

MESAEP - Mediterranean Scientific Association of Environmental Protection e.V. IAES - International Academy of Environmental Safety SECOTOX- Society of Ecotoxicology and Environmental SafetySafety

FEB – Fresenius Environmental Bulletin founded jointly by F. Korte and F. Coulston

Production by PSP – Parlar Scientific Publications, Angerstr. 12, 85354 Freising, Ger- many in cooperation with Lehrstuhl für Chemisch-Technische Analyse und Lebensmitteltech- nologie, Technische Universität München, 85350 Freising - Weihenstephan, Germany Copyright © by PSP – Parlar Scientific Publications, Angerstr. 12, 85354 Freising, Ger- many. All rights are reserved, especially the right to translate into foreign language. No part of the journal may be reproduced in any form- through photocopying, microfilming or other processes- or converted to a machine language, especially for data processing equipment- without the written permission of the publisher. The rights of reproduction by lecture, radio and television transmission, magnetic sound recording or similar means are also reserved.

Printed in GERMANY – ISSN 1018-4619

1 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

FEB - EDITORIAL BOARD Environmental Toxicology: Prof. Dr. H. Greim Senatskomm. d. DFG z. Prüfung gesundheitsschädl. Chief Editor: Arbeitsstoffe Prof. Dr. H. Parlar TU München, 85350 Freising-Weihenstephan, Germany

Institut für Lebensmitteltechnologie und Analytische Chemie Prof. Dr. A. Kettrup TU München - 85350 Freising-Weihenstephan, Germany Institut für Lebensmitteltechnologie und Analytische e-mail: [email protected] Chemie TU München - 85350 Freising-Weihenstephan, Germany

Co-Editors: FEB - ADVISORY BOARD

Environmental Analytical Chemistry: Environmental Analytical Chemistry: K. Ballschmitter, D - K. Bester, D - K. Fischer, D - R. Dr. D. Kotzias Kallenborn, N Commission of the European Communities, D.C.G. Muir, CAN - R. Niessner, D - W. Vetter, D - P. Joint Research Centre, Ispra Establishment, Conte, I 21020 Ispra (Varese), Italy Environmental Proteomic and Biology:

D. Adelung, D - G.I. Kvesitadze, GEOR Environmental Proteomic and Biology: A. Reichlmayr-Lais, D - C. Steinberg, D - R. Viswanathan, D

Prof. Dr. A. Görg Environmental Chemistry: Fachgebiet Proteomik TU München - 85350 Freising-Weihenstephan, Germany J.P. Lay, D - J. Burhenne, D - S. Nitz, D - R. Kreuzig, D D. L. Swackhammer, U.S.A. - R. Zepp, U.S.A. – T. Alpay, TR Prof. Dr. A. Piccolo Università di Napoli “Frederico II”, Environmental Management: Dipto. Di Scienze Chimico-Agrarie O. Hutzinger, A - L.O. Ruzo, U.S.A - U. Schlottmann, D Via Università 100, 80055 Portici (Napoli), Italy Environmental Toxicology: Prof. Dr. G. Schüürmann UFZ-Umweltforschungszentrum, K.-W. Schramm, D - H. Frank, D - H. P. Hagenmeier, D Sektion Chemische Ökotoxikologie Leipzig-Halle GmbH, D. Schulz-Jander, U.S.A. - H.U. Wolf, D – M. McLachlan, S Permoserstr.15, 04318 Leipzig, Germany

Environmental Chemistry: Prof. Dr. M. Bahadir Managing Editor: Institut für Ökologische Chemie und Abfallanalytik TU Braunschweig Dr. G. Leupold Hagenring 30, 38106 Braunschweig, Germany Institut für Chemisch-Technische Analyse und Chem- ische Prof. Dr. M. Spiteller Lebensmitteltechnologie, TU München Institut für Umweltforschung Universität Dortmund 85350 Freising-Weihenstephan, Germany Otto-Hahn-Str. 6, 44221 Dortmund, Germany e-mail: [email protected]

Prof. Dr. Ivan Holoubek Editorial Chief-Officer:

RECETOX_TOCOEN Selma Parlar Kamenice 126/3, 62500 Brno, Czech Republic PSP- Parlar Scientific Publications

Angerstr.12, 85354 Freising, Germany e-mail: [email protected] - www.psp-parlar.de Environmental Management: Marketing Chief Manager: Dr. H. Schlesing Secretary General, EARTO, Max-Josef Kirchmaier Rue de Luxembourg,3, 1000 Brussels, Belgium MASELL-Agency for Marketing & Communication, Public- Relations Angerstr.12, 85354 Freising, Germany Prof. Dr. F. Vosniakos e-mail: [email protected] - www.masell.com T.E.I. of Thessaloniki, Applied Physics Lab. P.O. Box 14561, 54101 Thessaloniki, Greece

Dr. K.I. Nikolaou Organization of the Master Plan & Environmental Protection of Thessaloniki (OMPEPT) 54636 Thessaloniki, Greece Abstracted/ indexed in: Biology & Environmental Sciences, BIOSIS, C.A.B. International, Cambridge Scientific Abstracts, Chemical Abstracts, Current Awareness, Current Contents/ Agricul- ture, CSA Civil Engineering Abstracts, CSA Mechanical & Trans- portation Engineering, IBIDS database, Information Ventures, NISC,

2 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

Research Alert, Science Citation Index (SCI), SciSearch, Selected Water Resources Abstracts

1618 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

CONTENTS

ORIGINAL PAPERS

BETTER URBAN MICROCLIMATE VIA A PROPOSED CITY PLANNING TOOL. 1619 A CASE STUDY IN GREECE Lila Theodoridou-Sotiriou, Glykeria Kariotou, Eleftherios Panagiotopoulos and George Kariotis

DETERMINATION OF INORGANIC ELEMENT CONCENTRATIONS 1627 BETWEEN TWO Laccophilus SPECIES (DYTISCIDAE: COLEOPTERA) BY ENERGY DISPERSIVE X-RAY FLUORESCENCE (WDXRF) SPECTROMETRY Ömer Köksal Erman and Ali Gürol

EFFECTS OF LAND-USE REGIME ON SOIL ERODIBILITY 1636 INDICES AND SOIL PROPERTIES IN UNYE, TURKEY Murat Yilmaz, Ayhan Usta, Lokman Altun and Fahrettin Tilki

THE EFFECT OF pH ON ADSORPTION OF 1643 LINEAR ALKYL BENZENE SULPHONATE BY BENTONITE Hasan B. Sağlam, Kadir Esmer, Erdogan Tarcan and Sibel Zor

A MICROBIAL APPROACH IN SOILS FROM CONTAMINATED MINE AREAS: 1648 THE JALES MINE (PORTUGAL) CASE STUDY Susana Loureiro, António J. A. Nogueira and Amadeu M. V. M. Soares

IMMOBILIZATION OF Rhodococcus sp. DG FOR EFFICIENT DEGRADATION OF PHENOL 1655 Mona K. Gouda

PCDDs, PCDFs AND DL-PCBs IN SOME SELECTED 1662 ESTONIAN AND IMPORTED FOOD SAMPLES Ott Roots

SHORT COMMUNICATION

EFFECTS OF EXTERNAL POLYAMINES ON DNA UNDER THE HIGHEST COPPER 1667 TOXICITY IN Ulva lactuca L. AND GENOTOXICITY DETECTION BY RAPD-PCR ASSAY Inci Tuney, Dilek Unal and Atakan Sukatar

INDEX 1671

SUBJECT INDEX for Fresenius Environmental Bulletin 2007 1673

AUTHOR INDEX for Fresenius Environmental Bulletin 2007 1684

1619 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

BETTER URBAN MICROCLIMATE VIA A PROPOSED CITY PLANNING TOOL. A CASE STUDY IN GREECE

Lila Theodoridou-Sotiriou*, Glykeria Kariotou, Eleftherios Panagiotopoulos and George Kariotis

Technological Educational Institute of Serres, Department of Geoinformatics and Surveying, 62122 Serres, Greece

Presented at the 13th International Symposium on Environmental Pollution and its Impact on Life in the Mediterranean Region (MESAEP), Thessaloniki, Greece, 08 – 12 Oct. 2005

SUMMARY INTRODUCTION

In Greece, the minimum mandatory distance (D) of a The typical south European city suffers from: a) traffic building from the plot’s boundaries, relates only to the congestion, atmospheric pollution and noise, b) lack of open building’s maximum height (H), given as D = 3 + 0.10*H. public spaces and green spaces, c) high densities, degrada- This is the main institutional tool that shapes urban open tion of the urban environment, and d) insufficient arrange- spaces and, consequently, the urban microclimate in Greece. ments for adequate sunning. Numerous E.U. policies al- In this paper, we will illustrate a numerical model for city ready address the climatic change aiming to achieve sus- planning, named D (b) in an attempt to define mandatory tainable city planning. A bioclimatic approach to urban minimum distance between building structures on differ- planning can reduce adverse effects [1]. ent plots, taking into account the ground relief and climatic conditions of an area. The methodology we used to create Morphological features of the built environment that the model is based on bibliographical sources for biocli- have a special bearing on urban microclimate are: a) den- matic design. In particular, we were interested in identify- sity and building system, b) geometry of urban street can- ing data regarding the sun’s height angle (V sun), the height yons, c) structural materials of buildings, and d) open air of the building causing shading (Z building), the desired spaces. Several variations of these featurescan influence: shadow height (Z shadow), and the ground slope (ω). a) sunning and shading of the external surfaces of buildings, b) visibility of the celestial dome and, therefore, the Our model was a pilot one applied in the city planning lighting and cooling of buildings and open spaces, c) air of a sparsely built area (a separate unit) to be incorporated permeability of the urban tissue and, therefore, the airing in the master plan of Serres town in Northern Greece. Two and cooling of the city, d) reflectiveness and thermal capac- city planning scenarios were developed (one using the pres- ity of urban tissue and, therefore, the maximum values ently applied, and the other using the proposed tool), and the and variations of air and surface temperature and e) green results of the expected thermal islet, as given by the two content that, among others, influences air temperature [2]. scenarios, were evaluated in comparison. In areas with Mediterranean climate like Greece, sun- The results of this pilot program suggest that bioclimat- ning and solar ray protections are the key objectives for ic distance between building structures [D (b)] contributes bioclimatic design models [3]. Analytical elements for the to the utilization of passive energy saving systems. Thus, specification of the sun’s position are height and azimuth it could be institutionally utilized and, in combination with angles for every given moment in time. The use of the currently observed distances, could constitute a valuable “apparent observed path of the sun” constitutes an im- addition to the existing city planning tools in Greece. portant element for bioclimatic design [4]. Given particular geographical latitude and atmospheric conditions, the controlling factors of sunning are the geographical orientation and breadth of streets, the choice of width for building polygons, and the distance between building struc- KEYWORDS: Urban microclimate, building coefficient (BC), building heights, cylindrical diagrams of solar height and azimuth, bio- tures [5]. Distance between building structures determines climatic distance between buildings. the minimum width of building polygons as well as the minimum breadth of streets. An increase in the breadth of streets can occur for functional reasons [6]. Conversely, breadth can be decreased (creation of pedestrian ways) by

1619 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

imposing larger portions of plots as border space between buildings are calculated taking into account only the factor buildings [7]. of the position of the sun, the gain would be minimal, and Despite of the above mentioned, according to the Na- such calculation would result in the creation of a thinly knit tional Building Regulation (NBR) of Greece, the calcula- urban tissue. This would increase the energy cost of people tion of maximum height allowed for a building is a func- movement and transportation, and render built structures tion of the specific area’s building coefficient (B.C.) while vulnerable to winter winds [12]. distance from plot boundaries is given by the formula D = The criterion of sunning must be based on a critical 3+0.10*Η, where H stands for building height [8]. date different than December 21st, while the whole proce-

dure must take into account cloud cover statistical data,

and energy gain due to sunning conditions. MATERIALS AND METHODS The sunning of the façade of buildings is less im- Methodology portant, depending on the specific use of buildings. The selection of December 21st as the critical date of- Commercial establishments and offices have less signifi- fers the simplest definition criterion, since this date repre- cant sunning requirements. Buildings with ground-floor st sents the period with the smallest solar height angles of garage, require adequate sunning from the 1 floor above the year in the northern hemisphere. Consequently, if the the ground and upwards. In cases where the ground-floor amount of solar radiation (sunning) on a surface at noon on of buildings is designed and constructed above ground December 21st is high enough, we can naturally assume level in order to avoid excessive ground moisture, dif- sunning to be at satisfactory levels during all remaining ferent sunning re-quirements apply. If the vertical differ- months and for more hours every day. In that case, we could entiation of space uses is predefined or foreseen (e.g. st achieve energy savings between 11% and 16.5% of total commercial uses on the ground-floor, offices on the 1 nd yearly energy consumption of buildings (at a latitude al- floor, residential uses from the 2 floor upward), specif- most identical to that of Athens, 37ο 58’). Factors influ- ic sunning requirements of shading height (Zsh) can be encing the shading of a space by a particular built struc- adopted, and distances between built structures can be ture are: a) the height of the built structure, b) the sun’s calculated. position at any given time, c) the building’s function, d) Ground slope on the North–South axis, where the im- ground slope, and e) distance to the next building that is pact of solar radiation is controlled and measured, has a shaded [9]. positive or negative impact on the calculation of distance According to related legislation in force, for areas un- depending on whether the ground is sloping upwards or dergoing city planning interventions, the maximum Build- downwards. ing Coefficient (BC) is set at 0.80 for areas of permanent In Figure 1, the straight line ΑΒ indicates building (ob- housing (i.e. not summer or secondary use housing), with- stacle) of height Z, ΕΖ indicates the adjacent building of out excluding certain exceptions. We thereby arrive, indi- height Ζ1 (aiming at securing adequate sunning). ΑC in- rectly albeit clearly, to the specification of the maximum dicates the solar ray intersecting the ground, ΒC is the allowed height of a built structure (as per NBR). sloping ground, and Ζsh is desired shading height as deriv- Maximum heat gain at 40ο North Geographical Lati- ing from the factor of use. So is the horizontal distance for tude (NGL) occurs when the building’s longest axis is ori- unhindered sunning, whereas S1 is the horizontal distance entated in an East-West direction, and its largest façade is so as to achieve the intended shading height for a given per- directed ±25ο to the east or west of the South compass bear- pendicular angle in combination with ground slope. ing. According to GBR, sunning is considered to be ade- Applying the ratio of cosines we have: quate when the sun is located higher than 7.50ο over the horizon, and solar rays fall on the building’s façade sur- Sk Ζ ο = (1) face at an angle larger than 22.50 at a horizontal projec- sin(90 − V) sin(V + ω) tion. The intensity of solar radiation reaching the earth’s sur- Sk is the sloping distance of shading on the ground, ω is ground slope (positive or negative), Ζ is the height of face a) decreases as the angle of incidence on the atmos- the obstacle (building), V is the sun’s declination angle, phere becomes smaller, b) depends on the cosine of the and CD is the horizontal distance between solar ray-ground angle of incidence on a surface, and c) depends on the dura- point of intersection and the obstacle. tion of sunning, which, in turn, is related to the duration of daylight and the conditions of the atmosphere (cloud cover, For rectangle CDB: atmospheric pollution) [10]. Sο = Sk * cos(ω) (2) In high geographical latitudes, solar radiation reaching the ground is considerably smaller in mid-December sin (90 - V) Sο = * Ζ * cos ω (3) and the sun’s perpendicular angle is rather small [11]. If, sin(V + ω) aiming at complete sunning of buildings, distances between

1620 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

Sο is the horizontal distance between the shading point of intersection on the sloping ground and the obstacle (building).

1621 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

acclivity declivity S1 Ε S1 Α Α Ε 90-V 90-V Zsun Z 1 Zsun Z Z Z 1 H V+ω H So Zsh Zsh D C - ω Ζ Β Sk (ground) Sk (ground) V V-ω Β V +ω Ζ D C So

FIGURE 1 - Schematic rendering of bioclimatic distance.

The question raising is what is the extent of the build- cos (V) ing being shaded, given the sun’s angle and ground slope ⇒ S1 = * ( Ζ – Zsh ) * cos ω (6) when the adjacent building is situated at an horizontal dis- sin(V + ω) tance S1 from a building considered as a sunning obstacle, and has a height of Z1 [13] ? RESULTS AND DISCUSSION Applying equality of triangles, we have: Z Ζsh S1 A pilot application of the bioclimatic approach is pro- = ⇒ Ζsh = Ζ – Ζ * (4) vided here concerning a sparsely built area of the city of Sο Sο - S1 Sο Serres, an area that has been lately included in the city’s Ζsh is the shaded height of a building. urban master plan through a recently approved city planning study. Seeking to determine distance S1, for which a given ο building height and perpendicular solar angle results in The city of Serres is approximately located at 41 05’ shading to a desired height Ζsh against a building, we NGL, and an alternative application is provided, taking into arrive at the following formula: account the factors already mentioned. Concerning the sun’s movement (Table 1), we utilized the cylindrical diagram So ο S1 = ( Z – Zsh ) * (5) 40 NGL, with an azimuth clockwise one-way reference Z and graphical value interpolation, assuming that it approxi- mates data in our geographical area.

TABLE 1 - Movement of the sun.

JANUARY FEBRUARY MARCH APRIL MAY HOUR DECEMBER JUNE NOVEMBER OCTOBER SEPTEMBER AUGUST JULY S Η V Η V Η V Η V Η V Η V Η V 5.20 67,5 7.5 5.30 72 7.5 6.05 83 7.5 6.40 97 7.5 7.25 113 7.5 8 128 5 126 7.5 119 14 111 22 101.5 30 94 34.5 89.5 36 8.15 131 7.5 12 180 26.5 29.5 39 49 61 69 73 15.45 230 7.5 16 233 5 236 7.5 242 14 250 22 260 30 268 34.5 272 36 16.35 248 7.5 17.20 263 7.5 17.55 278.5 7.5 18.30 290 7.5 18.40 294 7.5

1622 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

Evaluating data of the area’s climate and, in particu- breadth of the required public-use area to be used for func- lar, those concerning cloud cover, it is assumed that ex- tional purposes (trunk-road feeder road, local road, pedes- ploitable solar energy must be calculated for a solar decli- trian way), functional distance can be increased or decreased nation angle at 12 noon for the period January 21st – No- with the introduction of an area defined as border space be- vember, i.e. 29.50ο: tween buildings. D (b) ≅ 0.90 *(Zbuilding − Zshading) *cos | ω | (7) Formula (7) illustrates the total distance between build- sin(29.50 + ω) ing structures. Distance D must be an expression of the distance between the building structure and the plot’s borders. From the ground relief, we calculate the mean ground The calculated distance S1 is, therefore, divided in two seg- slope on the N-S axis using the previous equation, and set- ments and the following formula is derived: ting the desired degree of shading (Ζsh = 0.00, 1.50, 3.00, 4.50, 6.00, 7.50 m), we derive the results shown in Tables 2 D (b) of plot ≅ 0.45*(Zbuilding − Zshading)*cos | ω| (8) and 3. sin(29.50 +ω) Therefore, the distance between houses can be deter- where ground slope ω is expressed in degrees with a mined by calculating whether they are situated within the positive sign for upward slopes, and a negative sign for same building polygon or in different ones. Calculating the downward ones).

TABLE 2 - Upward slope with N-S orientation.

cos(29.50)*(Ζbuilding-Ζshadow)*cos|ω| Max. Build- D(b)= Ground slope Ground slope sin(29.50+ω) B.C.. ing height (%) at angle ω (Ζ) Zshadow 0.00 1.50 3.00 4.50 6.00 7.50 (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) 0.80 10.50 0.00 0.00 18.56 15.91 13.26 10.60 7.95 5.30 10.50 4.00 2.29 17.33 14.86 12.38 9.90 7.43 4.95 10.50 8.00 4.57 16.26 13.94 11.61 9.29 6.97 4.65 10.50 12.00 6.84 15.31 13.12 10.94 8.75 6.56 4.37 10.50 16.00 9.09 14.47 12.40 10.33 8.27 6.20 4.13 0.80 13.50 0.00 0.00 23.86 21.21 18.56 15.91 13.26 10.60 13.50 4.00 2.29 22.29 19.81 17.33 14.86 12.38 9.90 13.50 8.00 4.57 20.91 18.58 16.26 13.94 11.61 9.29 13.50 12.00 6.84 19.69 17.50 15.31 13.12 10.94 8.75 13.50 16.00 9.09 18.60 16.53 14.47 12.40 10.33 8.27 0.80 15.00 0.00 0.00 26.51 23.86 21.21 18.56 15.91 13.26 15.00 4.00 2.29 24.76 22.29 19.81 17.33 14.86 12.38 15.00 8.00 4.57 23.23 20.91 18.58 16.26 13.94 11.61 15.00 12.00 6.84 21.87 19.69 17.50 15.31 13.12 10.94 15.00 16.00 9.09 20.67 18.60 16.53 14.47 12.40 10.33

TABLE 3 - Downward slope with N-S orientation.

cos(29.50)*(Ζbuilding-Ζshadow)*cos|ω| Max. Build- D(b)= Ground slope Ground slope sin(29.50+ω) B.C.. ing height (%) at angle ω (Ζ) Zshadow 0.00 1.50 3.00 4.50 6.00 7.50 (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) 0.80 10.50 -4.00 -2.29 19.97 17.12 14.26 11.41 8.56 5.71 10.50 -8.00 -4.57 21.62 18.53 15.44 12.35 9.26 6.18 10.50 -12.00 -6.84 23.55 20.19 16.82 13.46 10.09 6.73 10.50 -16.00 -9.09 25.88 22.18 18.48 14.79 11.09 7.39 0.80 13.50 -4.00 -2.29 25.68 22.82 19.97 17.12 14.26 11.41 13.50 -8.00 -4.57 27.79 24.70 21.62 18.53 15.44 12.35 13.50 -12.00 -6.84 30.28 26.92 23.55 20.19 16.82 13.46 13.50 -16.00 -9.09 33.27 29.57 25.88 22.18 18.48 14.79 0.80 15.00 -4.00 -2.29 28.53 25.68 22.82 19.97 17.12 14.26 15.00 -8.00 -4.57 30.88 27.79 24.70 21.62 18.53 15.44 15.00 -12.00 -6.84 33.65 30.28 26.92 23.55 20.19 16.82 15.00 -16.00 -9.09 36.97 33.27 29.57 25.88 22.18 18.48

1623 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

Applying the above formula and conforming to bio- for various road orientations (Fig. 2), adopting the maxi- climatic distance, both regarding the N-S axis orientation mum allowed BC = 0.80. Thus, we arrived at the city and an orientation ±30ο degrees (Fig. 2), we calculate the planning arrangement of a unit of the city of Serres, as minimum schematic arrangements of building polygons shown in Fig. 3.

FIGURE 2 - Built structure arrangements in various street orientations, in conformity with bioclimatic distance.

1624 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

FIGURE 3 - Schematic arrangement of buildings, in conformity with bioclimatic distance.

1625 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

The depiction of microclimatic changes, brought about ΔΤa-u (max) = 7.54 + 3.97 * ln (Height / Breadth). by the impact of human activity on the natural environ- Table 4 shows comparative data of the two application ment, will be underlined and brought forward through a scenarios, as well as the results of the thermal islet, expected quantitative comparison of the urban heat islet of (a), the by the application. Comparison of the two formulas is done currently applied distance between built structures as pre- with a given level (horizontal) ground, since the NBR for- scribed by the NBR in force (D = 3.00+0.10*Ζbuilding) mula does not provide for ground slope. The proposed bio- and (b), the proposed bioclimatic distance. The NBR-pre- climatic distance includes comparisons of shaded heights of scribed distance D is doubled in order to render the dis- 3.00 and 6.00 m. Columns (4), (7), (10) and (13) refer to tance between built structures and to allow comparison angle V created by the adoption of the corresponding for- with the proposed bioclimatic distance D(b). mula. They express the angle formed (H / B), and can be Based on empirical studies, and taking into account the compared with the solar height angle V in Table 1, to de- geometrical characteristics (height and breadth) of a “can- termine the date when the particular point is exposed to yon”, the difference of temperature between urban and rural solar rays. areas is expressed by the relationship:

TABLE 4 - Thermal islet differences (two scenarios).

- - -

ing ing ing d d d

Maximum sin(Vsun+ ω ) sin(Vsun+ ω ) sin(Vsun+ ω )

B.C.. building height V angle created angle V created angle V created angle V created angle V cos(Vsun)(Zbuil * cos(Vsun)(Zbuil * cos(Vsun)(Zbuil * Η) (3+0.10* * 2 Δ = ΠΥ) / υ )max=7.54+3.97ln( ΠΥ) / υ )max=7.54+3.97ln( ΠΥ) / υ )max=7.54+3.97ln( ΠΥ) / υ )max=7.54+3.97ln( = = - - - -

) =) (a ω| cos| * 0.00) ω| cos| * 3.00) ω| cos| * 6.00) (a ΔΤ (a ΔΤ ΔΤ (a ΔΤ D(b) D(b D(b) (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) 0.80 10.50 8.10 52.35 8.57 18.56 29.50 5.28 13.26 38.38 6.61 7.95 52.86 8.64 0.80 13.50 8.70 57.20 9.28 23.86 29.50 5.28 18.56 36.03 6.28 13.26 45.52 7.61 0.80 15.00 9.00 59.04 9.57 26.51 29.50 5.28 21.21 35.27 6.16 15.91 43.32 7.31 1.00 13.50 8.70 57.20 9.28 23.86 29.50 5.28 18.56 36.03 6.28 13.26 45.52 7.61 1.00 16.50 9.30 60.59 9.82 29.16 29.50 5.28 23.86 34.66 6.08 18.56 41.64 7.07 1.00 18.00 9.60 61.93 10.04 31.81 29.50 5.28 26.51 34.17 6.00 21.21 40.32 6.89 1.20 18.00 9.60 61.93 10.04 31.81 29.50 5.28 26.51 34.17 6.00 21.21 40.32 6.89 1.60 21.00 10.20 64.09 10.41 37.12 29.50 5.28 31.81 33.43 5.89 26.51 38.38 6.61 2.00 24.00 10.80 65.77 10.71 42.42 29.50 5.28 37.12 32.89 5.81 31.81 37.03 6.42 2.40 27.00 11.40 67.11 10.96 47.72 29.50 5.28 42.42 32.48 5.75 37.12 36.03 6.28 3.00 32.00 12.40 68.82 11.30 56.56 29.50 5.28 51.26 31.98 5.67 45.95 34.85 6.10

CONCLUDING REMARKS text of the city planning study, while related data converted into table form may constitute a control tool for the study. The shaping of residential and urban landscapes is a Finally, the use of bioclimatic distance D(b) with the step of the procedure of an energy wasting community, requisite corresponding specifications and commitments, where solving the individual problem seriously burdens the should constitute an innovative tool for a rapprochement of collective ecological problem, towards an ecologically ac- humans and nature, through the construction-acceptance of ceptable community characterized by low inputs. the rights of adjacent property owners and the society as a The bioclimatic distance formula can be utilized by city whole. planners and supervisors of city planning implementation, and by engineers or town planners when issuing new building permits. It is obvious that the generalized use of the ACKNOWLEDGEMENTS formula should result in an easy-to-follow calculation procedure, or a tabulation of related data for standardized use. We would like to express our gratitude to the Research This simplified formula type may be described as a build- Committee of the Technological Education Institute of ing condition in the Official Journal Issue, including the Serres for partial funding of this work.

1626 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

REFERENCES

[1] Herzog, T. (ed.) (1998) Solar Energy in Architecture and Ur- ban Planning. Prestel, München: London, N.Y., pp. 172-193.

[2] Wachberger, M. and Wachberger, H. (1983) Mit der Sonne bauen: Anwendung passiver Solarenergie. Callweg, Muenchen, pp. 80-92.

[3] Τzonos, P. (1985) Heliasmos (Sun Lighting). Thessaloniki, pp.19-42.

[4] Yannas, S. (1994) Solar Energy and Housing Design, vol.1: Principles, Objectives, Guidelines. Architectural Association Publication, London, pp.30-38.

[5] Stasinopoulos, Ν.T. (1999) Geometrikes morfes kai heliasmos (Geometrical shapes and Sun lighting). PhD thesis, National Technical University of Athens, Athens

[6] Szokolay, S. (1996) Solar Geometry. PLEA Note 1, Univer- sity of Queensland, p. 27.

[7] Yannas S. et al. (2001) Bioclimatic principles for urban design». In: Pelivallontikos sxediasmos poleon kai anoikton choron (Environmental Design for cities and urban spaces) Open University of Greece: Patra, pp. 175-234.

[8] Amourgis, S. and Kalogeras, Ν. (2001) Greek urban and architectural tradition and natural environment. In: Pelivallon- tikos sxediasmos poleon kai anoikton choron (Environmental Design for cities and urban spaces), Open University of Greece: Patra, pp. 190-218.

[9] Brown, G.Z. and DeKay, M. (2001) Sun, Wind, and Light: Architectural Design Strategies. John Wiley & Sons: N.Y, pp.230-256.

[10] Givoni, B. (1998) Climate Considerations in Building and Urban Design. Van Nostrand Reinhold, N.Y, pp. 103-146.

[11] Kartalis, Κ. (1999) Meteorology. In: Eisagogi sto phisiko kai anthropogenes perivallon, t. A’: phsiko perivallon (Introduc- tion to the natural and human made environment, v. Α': Natu- ral Environment). Open University of Greece: Patra, pp.249- 256.

[12] Goulding J.R., Lewis, J.O. and Steemers, T.C. (1996) Ener- geia stin Arxitektoniki (The European Passive Solar Hand- book), translated by E. Tsigkas, Athens, 1997, pp. 185-194.

[13] Εvangelinos, Ε . and Zaharopoulos, Η. (2001) Methodoi kai Received: January 13, 2006 sistimata energiakou sxediasmou ktirion (Methods and sys- Accepted: April 13, 2006 tems of energy wasting design). In: Bioklimatikos sxediasmos ktirion (Bioclimatic design of buildings), v. A’, Open Univer- sity of Greece, Patra, pp.21-153. CORRESPONDING AUTHOR

Lila Theodoridou-Sotiriou Technological Educational Institute of Serres Department of Geoinformatics and Surveying 62122 Serres GREECE

E-mail: [email protected]

1627 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

FEB/ Vol 16/ No 12b/ 2007 – pages 1619 – 1626

1628 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

DETERMINATION OF INORGANIC ELEMENT CONCENTRATIONS BETWEEN TWO Laccophilus SPECIES (DYTISCIDAE: COLEOPTERA) BY ENERGY DISPERSIVE X-RAY FLUORESCENCE (WDXRF) SPECTROMETRY

Ömer Köksal Erman1* and Ali Gürol2

1Department of Biology, Science and Art Faculty, Atatürk University, 25240 Erzurum, Turkey 2Department of Physics, Science and Art Faculty, Atatürk University, 25240 Erzurum, Turkey

SUMMARY INTRODUCTION

In this investigation, concentrations of 39 different in- The Dytiscidae is a moderate-sized family of aquatic organic elements in Laccophilus minutus and 30 elements beetles, and commonly called predaceous diving beetles. in L. hyalinus collected in different regions of four cities Both adults and larvae are aquatic and predaceous, feeding in Turkey were measured by energy dispersive X-ray fluo- not only on a wide range of invertebrates such as molluscs, rescence (WDXRF) spectrometry. Statistical significance annelids, and insect larvae, but also some vertebrates such was assigned at P <0.05. From our results, there are differ- as fish fry and small amphibians. The adults are excellent ences in the concentrations of some elements. The concen- swimmers, but are clumsy on land [1]. Adults and larvae of trations of K, Ca and Br were found to differ significantly Dytiscidae occur together and have adapted to almost all between L. hyalinus and L. minutus. In addition, Na, Mn aquatic habitats imaginable. Most dytiscids occur in shal- and Fe concentrations for L. hyalinus and Ge for L. minutus low waters to about 1 m in depth, because most have to rise were significantly different between males and females. to the surface periodically to renew their air supply [2]. Generally, densely vegetated waters have a more diverse As a result, there are statistically important differences in both compositions and amounts of the elements that are dytiscid fauna than barren ones [3]. stored in the body of these two Laccophilus species and The family is divided into 10 subfamilies of which 6 their sexes. The difference in compositions may result from are occurring in Palaearctic region. According to the World the metabolic activity in the sexes, and between the two Catalogue of Dytiscidae, there are about 3,892 species [4]. species. But it must be also considered that the differences Laccophilus hyalinus (De Geer, 1774) and Laccophilus of element content and composition of insect bodies depend minutus (Linnaeus, 1758) are very common in European on the element content of their habitats. From our results, countries and Turkey [5]. knowledge about the element composition of an area is Generally, L. hyalinus and L. minutus have similar mor- easily obtained by making an analysis of the elements of phological characters. But the hind coxa of L. hyalinus has the bodies of the insects, specifically dominant predators stridulatory file. The head has microreticulation reduced like Laccophilus species. In addition, we suggest that it is dorsally and large coarse meshes. The pronotum is weakly possible to refine the wastes which contain some heavy expanded, only posteriorly, with a medial length of only metals, by using water insects as well as Laccophilus spe- about 1/3rd longer than length at front angle. In L. minu- cies. We also hypothesize that Sn and Sr elements can have tus, the metacoxa is without a stridulatory file. The head a role in beetle metabolism, since the elements could be has microreticulation distinct dorsally, or coarse meshes are determined in these two species collected in most of the small and deeply impressed. The pronotum is strongly ex- habitats. But there is a need for biochemical studies to panded posteriorly, with a medial length about half as much find out what roles the elements play in the bodies. longer than at front angle [3, 6].

Inorganic elements participate in the formation of sev- KEYWORDS: Inorganic element analysis, insect, Laccophilus, eral enzymes by binding to specific proteins as prosthetic Dytiscidae, WDXRF analysis. group (cofactor), and, moreover, also in the formation of NADP and ATP, which have important roles in energy metabolism and redox reactions [7]. Elements have a role in

1629 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

the formation of important biomolecules, such as proteins, Increased accuracy is achieved using Matching Li- nucleic acids and lipids [8]. Element analyses of zooplank- brary and Perfect Scan analysis programs. In addition, the ton are important for investigating the uptake and transfer SQX corrects the effects of sample film (Mylar film). of substances along the trophic chain, in order to define the role of these organisms in biochemical pathways [9]. In this investigation, concentrations of inorganic elements in L. minutus and L. hyalinus collected in different X-Ray Fluorescence (XRF) is unique in elemental regions of four cities (Erzurum, Erzincan, Artvin, Rize) in analysis of inanimate matter. In qualitative analysis, it has Turkey, were sensitively measured by energy dispersive unbeaten selectivity for all elements between boron to ura- X-ray fluorescence (WDXRF) spectrometry. The aim of the nium, and also for transuranium elements and an extremely present study was to investigate differences of their con- wide dynamic range in quantitative analysis (ppm to 100%). tents in L. hyalinus and L. minutus, and to determine whether Although plasma emission spectrometry (DCP or ICP), there are differences in the element concentrations between atomic absorption spectrophotometry, and neutron activa- the two species and the sexes. tion analysis have lower and much lower detection limits, the wide dynamic range remains a unique feature of XRF. The detection limits, which are about ppm level without MATERIALS AND METHODS using any pre-concentration method, and the limits to the maximum accuracy and precisions that can be obtained, The samples were collected by means of a sieve, ladle determine the boundaries of XRF applications [10]. Be- and net having 0.5 mm pore diameter, from shallow areas cause of this, the advent of commercially available Wave- of the various running waters, springs, streams, brooks and length Dispersive X-ray fluorescence (WDXRF) measure- ponds. The beetles were killed with ethyl acetate or in 70% ments has provided an economical and powerful tool for alcohol solution, and then the clay and muddy substance on environmental, clinical, chemical, geological and industrial their surfaces was brushed off with a small paint brush in analysis. XRF is a non-destructive, fast, multi-element tech- the laboratory. nique for analysing the surface layer and determining mi- nor and trace elements as well as inorganic elements in thin The specimens collected from the same locality were and thick samples of all sizes and forms. Although X- ray separated as males and females. One sample for each sex spectrometry measurement is simple for a quantitative study, was obtained by using bodies of all males and females accurate quantitative measurements often depend on matrix collecting from the one habitat. Tables 1 and 2 show the correction procedures, which require a large number of localities and the numbers of the collected L. hyalinus and standards. One of the major problems posed by geologi- L. minutus specimens. cal materials is the sample preparation. Since the After collection, the adult beetles were washed three WDXRF technique was first used as an analytical tool, a o great deal of research has been done in mineralogical and times in triple-distilled water. After drying at 60 C in a biological materials by different workers. Many works microwave oven, the samples were ground with HNO3 and were reported in the literature by using WDXRF and H2O2 by using a SPEX grinder. The samples were then put EDXRF in the last years [11-16]. Queralt et al. [17] through a 400-mesh sieve to minimize the particle-size evaluated macro- and microelement contents of five me- effects (400 is the number of wires in the mesh per linear dicinal plants (Taraxacum officinale Weber, Eucalyptus inch). Then, the ground and sieved samples were sprayed globulus Labill, Plantago lanceolata L., Matricaria on Mylar film. The samples were analyzed by using a chamomilla L. and Mentha pi-perita L.) and their infusion Rigaku ZSX 100e WDXRF spectrometer. by the combined use of X-ray fluorescence (WDXRF and EDXRF, bulk raw plants) and inductively coupled plasma TABLE 1 - The localities and the (ICP-MS and ICP-AES, infusions) techniques. Tıraşoğlu numbers of Laccophilus hyalinus specimens. et al. [18] examined differences of trace elements in Bras- Number of Samples Localities sica plant species grown in the Black Sea area in Turkey. specimens Karabulut et al. [19] used the technique for analysing 1 Erzurum, Tortum Lake 13 males trace elements in three species of a leaf beetle (Chrysome- 2 Erzurum, Tortum Lake 17 females la). Dumlupınar et al. [20] investigated the change of 3 Erzurum, Şenkaya, Turnalı Village 1 female inorganic elements in Drosophila melanogaster and in 4 Erzurum, İspir, Toprakkale Village 1 male 5 Erzurum, İspir, Toprakkale Village 3 females pulvini of bean plants [21] at chilling temperatures. 6 Erzincan, Kemaliye, Kozlupınar Village 8 males Rigaku Incorporation has further improved its semi- 7 Erzincan, Kemaliye, Kozlupınar Village 6 males 8 Erzurum, İspir, Leylek Boğazı 1 female quantitative software package with the introduction of SQX. 9 Erzurum, İspir, Leylek Boğazı 1 male It is capable of automatically correcting all matrix effects, 10 Erzurum, İspir, Zeyrek Village 1 male including line overlaps. SQX can also correct secondary 11 Erzurum, İspir, Zeyrek Village 5 females excitation effects by photoelectrons (light and ultra-light 12 Erzurum, Olur, Beğendik Village 1 male elements), varying atmospheres, impurities and different 13 Artvin, Şavsat, Karagöl 5 females sample sizes. 14 Erzincan, Çayırlı, Harmantepe Village 2 males

1630 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

TABLE 2 - The localities and the only heavy elements characteristic X-rays, and a gas flow- numbers of Laccophilus minutus specimens. type proportional counter for wavelengths longer than Number of 0.154 nm, regulating a 50-ml PR10 gas flow, included 90% Samples Localities specimens Ar and 10% methane, continuously during the measure- 1 Erzincan, Cayırlı, Harmantepe Village 6 males ments (counting only light elements). Typical spectra taken Erzincan, Kemaliye, Sırakonak, Gözaydın 2 5 females from the control group’s sample are illustrated in Fig. 1 for Village Erzincan, Kemaliye, Sırakonak, Gözaydın L. hyalinus, and Fig. 2 for L. minutus. In each spectrum, one 3 5 males Village part illustrated is for heavy elements by using LiF crystal 4 Erzurum, Oltu, Güryaprak ,Village Lakes 13 females and Scand, and the other for individual light elements, 5 Erzurum, Oltu, Güryaprak ,Village Lakes 12 males from F to Ca, by using LiF, PET and Ge crystals and PC. 6 Rize, Çayeli-Pazar Way 2 females 7 Rize, Çayeli-Pazar Way 1 male These concentrations measured by wavelength dis- 8 Rize, Arhavi-Fındıklı Way, 2. km 3 males persive X-ray fluorescence (WDXRF) spectrometry were 9 Rize, Arhavi-Fındıklı Way, 2. km 6 females statistically analysed. Statistical significance was assigned 10 Erzincan, Ilıc, Tabanlı Village 10 males at P < 0.05. 11 Erzincan, Ilıc, Tabanlı Village 10 females 12 Artvin, Şavsat, Susuz Village 1 males 13 Artvin, Şavsat, Susuz Village 2 females 14 Erzurum, Oltu, Güryaprak Village 4 males RESULTS AND DISCUSSION 15 Erzurum, Oltu, Güryaprak Village 2 females 16 Rize, Çayeli 2 females The technique has recently been used for element 17 Rize, Çayeli 2 males analysis in some biological materials [22-25]. The errors in 18 Rize, Pazar-Ayder Way 4 females the results were estimated to be about 10%. Figures 1 and 19 Rize, Pazar-Ayder Way 4 males 2 show spectra of the inorganic element intensity obtained from L. hyalinus and L. minutus. The spectrometer has a 4 kW end window X-ray tube with Rh anode. The X-rays which diffracted from crystals In this study, we used in total 33 male and 32 female (LiF, PET, Ge) were detected using a scintillation counter specimens belonging to Laccophilus hyalinus, as well as (SC) for wavelengths shorter than 0.336 nm, thus counting 48 male and 46 female specimens of L. minutus, collected

100 70 65 10 0.7 0.25 0.15

6.5 2.0 1 β 60 50 P Kα 6.0 60 55 1.8 0.6 and Zn-L

5.5 α 80 0.20

50 1.6 Na-K 5.0 40 50 0.5 Mg-Kα 45 4.5 1.4 0.10

40 nd 60 4.0 0.15 -2

40 1.2 0.4 α 30

35 P-K 3.5

5 rd 1.0 -3

30 α 3.0 30 0.3

40 Ca-K 0.10 25 0.8 2.5 20 0.05 20 2.0 20 0.6 0.2

Intensity (kcps) 1.5 20 10 0.4 0.05

1.0 10 10 α 3 0.1

P-SK 0.2 0.5 5

0 0.0 0 0 0 0 0.0 0.0 0.00 0.00 112 114 90 92 94 96 134 136 138 140 108 110 112 114 138 140 142 144 106 108 110 112 140 142 144 146 148 42 44 46 48 52 54 56 58 88 90 92 94 Ca Kα Cl-Kα K-Kα S-Kα P Kα Si-Kα Al-Kα Mg-Kα Na-Kα F-Kα

Heavy Elements

α Compton α Rh K Rh

Rh K Rh Compton 1 β α α Rh K Rh

20 Fe-K Zn-K 1 α Intensity (kcps) α β 1 α 1 β -K β α 1 Sn-K Sr-K Rh K Rh α β Br α α

K Zn-K Sn-K α Ge-K Ba-K Fe-K Ni-K α Cu- α α Co-K MnK Cr-K Ti-K 0 20 40 60 80

2θ FIGURE 1 - A typical spectrum of Laccophilus hyalinus.

1631 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

100 2.5 1.4 0.5 0.25 0.10 60 35 P Kα 6 1.2 0.4 80 2.0 30 0.4 0.20 50

5 1 β 1.0 Mg-Kα 25

and Zn-L 0.3 40 4 α 60 1.5 0.3 0.15

0.8 Na-K

20 rd

-3 0.05 α 30 3

0.6 Ca-K 0.2 40 1.0 15 0.2 0.10 nd

20 -2 2 α 0.4

10 P-K Intensity (kcps) 20 0.5 0.1 0.1 0.05 10 α 3 1 0.2 5 P-SK

0 0.0 0.0 0 0 0 0.0 0.0 0.00 0.00 112 114 92 94 134 136 138 140 108 110 112 114 138 140 142 144 106 108 110 112 140 142 144 146 148 42 44 46 48 52 54 56 58 88 90 92 94 Ca Kα Cl-Kα K-Kα S-Kα P Kα Si-Kα Al-Kα Mg-Kα Na-Kα F-Kα Heavy Elements

Compton α Rh K Rh

α Compton 1 β Rh K Rh 20 K Rh

α Intensity (kcps) α 1 Zn-K β

α α α α Sr-K 1 -K α β α Rh K Rh 1 Br -K Sn-K K Nd-K Fe-K β

α Se Zn-K Cu- α α Fe-K Ni-K Cr-K MnK 0 20 40 60 80 2 θ

FIGURE 2 - A typical spectrum of Laccophilus minutus.

from four different cities and 18 different habitats in Tur- suggest that the differences can be a sign of some meta- key. Samples for each sex of each species were prepared bolic differences between both species which belong to the by using all males and females collected from the same same genus, and female and male specimens for any spe- habitat. We determined percent concentrations of 30 differ- cies. ent inorganic elements in L. hyalinus, and 39 elements in Laccophilus minutus by WDXRF analysis. Some elements (Na, Mg, Al, Cl, Cr, Mn, Sr, Sn, Ti, Co, Ge, Br, Rb, In, La, Sm, Cd, Eu, Se, Y, Nb, I, Nd, Pr, The contents and amounts of the elements of speci- Pm, Ba, Ga, Ce, Te, Zr) could not be determined in males mens collected from each habitat obviously varied in our and females of L. minutus collected in each habitat (Ta- measurements (Tables 3a, b, c and 4a, b). Both composi- bles 3a, b, c). Although Na, Mg, Al, Cl, Cr, Mn, Sr, and tions and amounts of the elements showed differences be- Sn could be determined in specimens collected in most of tween male and female specimens of each species (Tables the habitats, we could not determine them in some habi- 5 and 6). From these result, males of L. hyalinus had more tats for L. minutus. It has been known that Na, Mg, Al, Cl Mg, Al and Si than those of female. But females of this and Mn have important roles in living metabolism [27]. species kept more Na and Fe than those of males. Howev- Despite of the fact that Sr and Sn were found in beetles er, concentrations of Na, Mn and Fe were significantly living in most of the habitats, the roles of these two ele- according to the analysis of variance. We determined that ments in insect metabolism have not been known. The the amounts of Na, K, Ti, Cr, Fe, Br, Sr, Sn, La, and Nd results indicate that both play a role in beetle metabolism, in males of L. minutus were higher than those of female. and this hypothesis was supported by Sn found in each The females of L. minutus retained more Co, Zn and Sm. specimen and habitat of L. hyalinus. We obtained similar Analysis of variance showed that the concentration of Ge results for Sn and Sr in a beetle species (A. bipustulatus) in differed significantly between males and females of L. our previous study [28]. But there is a need for biochemi- minutus. Ge had been found in only one female. It has been cal studies to identify the roles of the elements in beetles. known that there are metabolic and hormonal differences between both female and male specimens [26]. There are In L. hyalinus, some elements (Na, Mg, Al, Cr, Mn, very tight relations between inorganic elements which have Sr, Sn, Ti, Co, Ge, Br, Rb, In, La, Sm, Cd, Eu, Se, Y, Nb, three important functions (osmotic, structural, and biochemi- I, Nd, Pr, Pm, Ba, Ga, Ce, Te, Zr) could not be deter- cal) and metabolism of living organisms. That is why we mined concerning specimens collected in all ten different

1632 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

TABLE 3a - The results of element analysis for Laccophilus minutus (% concentration).

Na Mg Al Si P S Cl K Ca Ti Cr Mn Fe Co 1 1.8752 1.8445 0.3720 2.5762 3.2898 7.2879 4.2382 23.1220 34.6400 0.6887 - 1.1818 16.2850 - 2 1.9313 - 0.5535 2.3401 12.1710 9.6177 8.7592 18.0160 41.6780 0.9557 - 1.3496 0.4933 0.2042 3 4.8749 3.2586 1.2400 5.5700 14.444 9.4854 8.6495 21.6990 28.5380 - - 0.2567 0.3839 - 4 0.6668 - 0.4769 2.3179 9.0175 8.8025 4.4262 19.8470 49.2900 0.8364 0.6088 2.4082 0.0910 - 5 - - 0.4386 1.2500 6.2349 14.7680 6.3851 36.6780 30.5960 - 0.1878 1.0361 0.0255 - 6 - 1.9856 0.7891 2.1981 12.5650 15.7610 3.9380 7.9684 25.4940 - 1.8990 0.3783 7.5596 - 7 1.2584 - 0.7308 2.4955 11.9350 8.1327 3.4612 8.5836 46.4360 - 0.9794 1.1906 11.2490 - 8 4.2945 1.5631 1.9399 7.4251 12.1170 11.0010 5.5098 14.2950 30.1780 5.0305 0.4354 3.0489 1.5060 0.0731 9 2.6645 - 0.7784 2.3305 9.7542 16.1200 5.9884 15.6420 35.5100 0.8253 0.1243 4.6406 0.4174 - 10 - - 0.3300 2.8669 14.7290 15.451 4.7689 9.4468 45.2350 0.2644 0.1436 2.5209 1.3087 - 11 - 1.6870 1.9569 7.6710 17.4700 7.3641 15.0220 6.6244 38.1000 0.8239 0.2558 0.2227 0.7281 - 12 - - - 1.1314 8.0670 9.4452 4.7491 29.6150 39.0130 0.5700 0.7140 3.0370 1.0780 - 13 0.2611 - 0.2476 0.8403 11.4210 8.4784 5.8531 34.8700 34.0530 - 0.5344 1.8495 0.6110 - 14 - - 2.4306 7.0503 12.0320 4.5783 - 27.5420 30.6250 - 6.1543 - 4.2810 - 15 - - 0.7063 3.2679 7.7985 19.6110 3.5579 14.3830 46.4450 - 1.0493 0.6171 0.5874 - 16 - - - 1.4198 7.9907 14.0620 2.3547 19.6800 39.4830 - 0.4709 - 6.2981 - 17 5.3581 - - 2.5247 15.4520 19.1220 2.5866 14.5230 35.6280 - 0.4389 - 0.7003 - 18 0.9832 3.0211 3.0958 8.0760 11.7330 12.6830 13.6920 19.6340 21.7830 - - 2.3837 0.3194 - 19 2.5842 - 1.0854 2.2620 7.0164 10.3670 13.7320 22.3490 34.8360 - 0.7683 2.5850 0.3679 -

TABLE 3b - The results of element analysis for Laccophilus minutus (% concentration). Ni Cu Zn Ge Br Rb Sr In Sn La Sm Cd Eu Se 1 1.0584 0.7000 0.7758 - - - 0.0638 ------2 0.9669 0.6306 0.0177 0.0936 0.0441 - 0.0678 0.1101 ------3 0.7761 0.3134 0.4082 - 0.0468 - 0.0355 0.0187 ------4 0.4135 0.2220 0.1063 - 0.0246 0.0036 0.2376 - 0.1355 0.0363 0.0318 - - - 5 0.7571 1.2428 0.2994 - 0.0641 - - - 0.0370 - - - - - 6 0.8144 0.8771 2.0949 - - - 0.0070 - 0.3485 - 15.3220 - - - 7 1.1528 1.0743 0.3425 - 0.1049 0.0424 - 0.1046 0.5149 0.1233 0.0883 - - - 8 0.3966 0.3127 0.6938 - - - - - 0.0170 0.0552 - 0.0466 0.0608 - 9 0.4628 0.5846 0.3124 - - - 0.0146 - 0.0236 - 0.0046 - - 0.0160 10 0.6711 0.4019 0.3762 - 0.3684 - 0.5352 - 0.1558 - - - 0.0004 - 11 0.7501 0.3184 0.5860 0.0455 0.0830 - 0.1245 0.0444 0.0278 - 0.0041 - - - 12 0.5198 1.2813 0.2551 - 0.1616 - 0.1287 - 0.0232 - 0.0458 - - - 13 0.4492 0.2889 0.1171 - 0.0503 - 0.0444 - 0.0013 - 0.0295 - - - 14 0.6182 0.3315 2.7396 - - - - - 1.1654 - - - 0.4435 - 15 0.5430 0.6987 0.2872 - 0.2393 - 0.0289 - 0.0520 - - - - 0.0999 16 0.8972 1.6882 4.6742 - - - - - 0.5777 - 0.0075 - - - 17 1.4677 0.9817 0.2533 - - - - - 0.6282 - 0.0922 - - - 18 0.6194 1.2349 0.6753 - 0.0662 ------19 0.3750 0.7562 0.1866 - 0.0644 - - - 0.1566 0.1398 - - - 0.0629

TABLE 3c - The results of element analysis for Laccophilus minutus (% concentration). Y Nb I Nd Pr Pm Ba Ga Ce Te Zr 1 ------2 ------3 ------4 ------5 ------6 ------7 ------8 ------9 0.0358 0.0209 3.7289 0.0002 ------10 - - - - 0.4237 0.0021 - - - - - 11 ------0.0905 - - - - 12 - 0.0208 - - - - - 0.0925 0.0514 - - 13 ------14 ------0.0086 - 15 - - - 0.0272 ------16 ------0.3957 - - - - 17 ------0.2422 18 ------19 - 0.0277 - 0.2766 ------

1633 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

TABLE 4a - The results of element analysis for Laccophilus hyalinus (% concentration). Na Mg Al Si P S Cl K Ca Ti Cr Mn Fe Co Ni 1 1.4527 2.2638 6.0094 5.3382 11.7430 6.4228 3.0253 12.4260 47.7400 1.2414 0.2136 0.9698 0.0894 0.1447 0.2694 2 1.6474 1.3054 0.6249 1.7456 7.7426 8.4593 6.4651 15.3920 51.2520 0.7994 0.0623 2.0326 0.7516 - 0.3589 3 - - - 1.4177 6.6832 16.5500 4.0928 21.3020 41.7000 0.8939 0.3966 1.2384 0.9226 0.0278 0.7114 4 1.7114 - - 2.0012 6.4743 21.5980 9.4564 17.5320 28.8150 0.7863 1.3783 1.4707 1.1386 - 1.2197 5 - - - 2.2620 6.8078 18.3630 5.7671 19.0880 38.9980 0.8705 0.1256 0.5189 0.7721 - 0.5822 6 0.7708 1.8576 1.0359 4.4555 8.8312 9.4649 3.7315 11.0270 51.3150 - 0.4913 3.2095 0.9079 0.2218 0.7519 7 6.8287 - 0.1081 0.7434 6.0489 3.3456 3.2632 6.1132 61.2500 - 1.0135 5.0581 3.3790 - 0.6936 8 0.7231 1.2337 - 1.6714 9.6065 17.8520 4.1341 10.6790 46.5010 0.8609 0.9178 0.9623 0.5207 0.1737 1.6405 9 1.5674 - 0.2186 1.6906 6.2587 17.4320 3.0248 17.2130 45.9720 0.5727 0.8629 2.1627 0.6305 0.1539 0.2816 10 - 1.1522 0.4406 1.8933 10.3550 16.1240 5.4323 22.0060 36.4830 1.5662 1.1381 - 0.4081 0.2809 0.7555 11 1.9127 1.2714 0.8919 4.0300 10.3100 14.2370 5.4328 17.8170 37.8860 0.9837 0.9879 1.3038 0.9028 0.4155 0.7330 12 0.8742 - 0.4168 2.2175 8.7311 10.5020 5.0120 21.1710 44.9830 0.2547 1.5690 1.0222 0.6851 - 0.6420 13 1.1495 - 0.2709 1.9605 11.7320 15.8030 3.7457 8.8710 48.5060 0.4667 1.1977 2.0849 0.9304 0.0796 1.0591 14 - 0.9748 0.4119 2.1980 8.3913 8.8930 6.3346 31.0730 34.4390 0.5704 0.9179 1.6615 0.6710 - 1.4751

TABLE 4b - The results of element analysis for Laccophilus hyalinus (% concentration). Cu Zn Ge Br Rb Sr In Sn La Eu Ba Ga Ce As V 1 0.2628 0.1657 - - - 0.0480 - 0.0208 - 0.0575 0.0529 - - 0.0428 - 2 0.4252 0.6754 - - 0.0021 0.1461 - 0.0093 - - 0.1034 - - - - 3 1.0380 2.8316 0.0524 0.0653 - - - 0.0277 0.0482 ------4 1.1782 0.7135 - 0.5127 - 0.0945 - 0.0467 - - 3.8719 - - - - 5 1.0451 0.4612 - 0.5001 - 0.0610 - 0.3083 - - 2.9650 - - - 0.5039 6 0.7000 0.4590 - 0.3847 - 0.0970 - 0.1121 - - 0.1763 - - - - 7 0.0947 1.0965 - 0.4057 - 0.0651 - 0.1722 - - - 0.0142 0.1821 0.1240 - 8 1.3180 0.2313 - 0.1226 - 0.1413 - 0.3542 - - 0.3501 0.0066 - - - 9 0.8036 0.4896 - 0.0649 - 0.0324 - 0.1666 0.0238 - 0.2932 - - 0.0848 - 10 1.0452 0.3714 0.1916 - 0.0647 - 0.0984 - - - 0.0192 - 0.1744 - 11 0.4066 0.2391 0.0571 0.1243 - 0.0235 - 0.0341 ------12 1.0521 0.4125 - 0.3013 - 0.0455 0.0341 0.0282 - - 0.0452 - - - - 13 0.7688 0.8046 - 0.4569 - 0.0847 - 0.0155 - - 0.0130 - - - - 14 0.7598 0.2328 - 0.0610 - 0.0209 - 0.3006 - - 0.0294 - - - 0.5848

TABLE 5 - Average results of SQX analysis for inorganic element concentrations at Laccophilus hyalinus.

Element Na Mg Al Si P S Cl K Ca Ti Cr Mn Fe Co Ni Male 0.9109 0.8930 1.2190 2.8278 8.6835 12.9195 5.1453 18.9211 41.3924 0.7130 0.9390 1.4995 0.6470 0.1140 0.7710 Female 1.7516 0.5440 0.2708 1.9758 8.4187 13.5157 4.7001 14.1803 46.5847 0.6960 0.6720 1.8856 1.1700 0.0995 0.8260 Element Cu Zn Ge Br Rb Sr In Sn La Eu Ba Ga Ce As V Male 0.8290 0.4060 - 0.2170 - 0.0576 0.0049 0.1100 0.0034 0.0082 0.6380 0.0027 - 0.0431 0.0835 Female 0.7280 0.9060 0.0156 0.2390 0.0003 0.0745 - 0.1320 0.0069 - 0.4900 0.0030 0.0260 0.0177 0.0720

TABLE 6 - Average results of SQX analysis for inorganic element concentrations at Laccophilus minutus.

Element Na Mg Al Si P S Cl K Ca Ti Cr Mn Fe Co Ni Male 3.3742 2.2221 1.0709 3.5152 10.5317 10.9639 6.0089 20.7853 35.5725 1.6384 1.2277 1.8571 3.7185 0.0731 0.7793 Female 1.3014 2.2312 1.0756 3.3846 11.1023 12.4999 7.0657 17.4072 36.8707 0.8603 0.7061 1.7312 1.9006 0.2042 0.6574 Element Cu Zn Ge Br Rb Sr In Sn La Sm Cd Eu Se Y Nb Male 0.7396 0.6331 - 0.1350 0.0424 0.1908 0.0617 0.3373 0.1061 0.0754 0.0466 0.1682 0.0629 - 0.0243 Female 0.7270 0.9857 0.0696 0.0846 0.0036 0.0750 0.0773 0.1666 0.0363 2.5666 - - 0.0580 0.0358 0.0209 Element Nd Pr Pm Ba Ga Ce Te Zr I Male 0.2766 0.4237 0.0021 - 0.0925 0.0514 0.0086 0.2422 - Female 0.0137 - - 0.2431 - - - - 3.7289

habitats (Tables 4a, b). It was interesting to notice that of all elements in a suitable sample. Therefore, when an some of the elements (Na, Mg, Al, Mn) could not be de- element was not recorded, it could be that 1) it is absent, or termined in specimens found in some habitats, similar to 2) the element is below the detection limits of the equip- those of L. minutus. ment. Here, we suppose that there are small amounts of Na, Mg, Al, Mn in specimens living in some habitats, because WDXRF technique gives very sensitive results in meas- some are main elements for all living organisms. But even uring macro and microelements. It has been reported that the small amounts of trace elements are enough for a func- the WDXRF machine can measure percent concentrations tioning ecosystem. On the other hand, we note that many

1634 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

elements found infrequently in bodies of the two beetle of the same species have different capabilities of element species are economically valuable (Ti, Ge, Rb, Sr, In, La, storage, dependent on differences in their metabolisms. Eu, Ga, Ce and V in L. hyalinus, Ti, Ge, Br, Rb, Sr, In, La, Average results of SQX analysis for inorganic element Sm, Eu, Se, Y, Nb, Nd, Pr, Pm, Ga, Ce, Te and Zr in L. concentrations are given in Tables 5 and 6, between female minutus). We can here draw two conclusions from these and male L. hyalinus and L. minutus. Analysis of variance findings: 1. There are some differences of element compo- for the inorganic element levels between male and female sition and content between the habitats in which the two of L. hyalinus and L. minutus is given in Tables 7 and 8. species live. The differences may reflect habitat preference According to our statistical analyses, only the concentra- of the two species. At the same time, they confirm that tions of Na, Mg and Fe among the 30 elements were dif- there are differences in metabolism between the two spe- ferent between male and female L. hyalinus specimens, and cies. 2. Rare and valuable elements are available in those Ge concentration among the 39 elements showed the only ecological areas. Unfortunately, we cannot know what their important difference between males and females of L. minu- reserves are in those places. But, we suppose that our re- tus. Fe participates in the structure of some respiratory en- sults give clues for economically-oriented search activities zymes in the mitochondria of livings, and acts as a cofac- of the valuable elements in mining. Erman et al. [28] sug- tor in the respiration system. From the data, it can be suggest that these elements are available in their aquatic habi- gested that male specimens have higher metabolic activity tats, and source of the elements is the soil. The elements than females. In our previous study, we determined that are taken by producers as well as algae and high plants males of A. bipustulatus have statistically more Cu than from soil, and they pass to bodies of herbivores. They pass females [28]. In this study, the same tendency was found from sub-levels of the food chain (herbivores, primary and for the two beetle species (Tables 5 and 6), but the results secondary predators) to bodies of dominant predators on the were not statistically significant. top level of the food chain (as well as Agabus), together with the other necessary elements and biomolecules. They With regard to the heavy metals Al, Cr and Co, are then stored in the beetles’ bodies. L. hyalinus and L. theirconcentrations in males of L. hyalinus were found minutus belong to the same family of beetles, and they are to be higher than those of females, whereas Zn concen- dominant predators at the top level of the food chain in trations were higher in females than males. their aquatic ecosystems. That is why we can make the In addition, Cr concentrations in males as well as Co same suggestion for the two species of beetles examined. and Zn in females were higher than those of their opposite Some elements (Eu, Ce for L. hyalinus and Cd, Eu, sexes in L. minutus, although the amount of storage was Pr, Pm, Ga, Ce, Te, Zr for L. minutus) were only determined not statistically important between the sexes. Erman et al. in male specimens living in the same localities, while other [28] reported that A. bipustulatus had the capability to elements (Ge, Rb, for L. hyalinus and Ge, Y, Ba, I for L. store some heavy metals (Al, Cr, Co), although the amount minutus ) were unique to the females (Tables 3a, b, c and of storage was not statistically important between the sexes. 4a, b) Our results indicate that female and male specimens Our latest findings are quite similar.

TABLE 7 - Variance analysis for minor and trace element concentrations between male and female of L. hyalinus. Element Na* Mg Al Si P S Cl K Ca Ti Cr Mn* Fe* Co Ni Significance 0.000* 0.281 0.490 0.142 0.284 0.457 0.531 0.083 0.078 0.593 0.734 0.026* 0.000* 0.634 0.699 Element Cu Zn Ge Br Rb Sr In Sn La Eu Ba Ga Ce As V Significance 0.225 0.272 0.448 0.650 0.638 0.744 0.638 0.824 0.830 0.638 0.892 0.195 - 0.367 0.513

TABLE 8 - Variance analysis for minor and trace element concentrations between male and female of L. minutus. Element Na Mg Al Si P S Cl K Ca Ti Cr Mn Fe Co Ni Significance 0.370 0.999 0.910 0.934 0.509 0.693 0.388 0.278 0.498 0.827 0.402 0.856 0.502 0.415 0.557 Element Cu Zn Ge* Br Rb Sr In Sn La Sm Cd Eu Se Y Nb Significance 0.245 0.965 0.008* 0.613 0.711 0.824 0.502 0.346 0.411 0.658 0.655 0.260 0.514 0.514 0.258 Element Nd Pr Pm Ba Ga Ce Te Zr I Significance 0.720 0.529 0.529 0.523 - - 0.284 0.655 0.655

TABLE 9 - Variance analysis for minor and trace element concentrations between L. minutus and L. hyalinus.

Element Na Mg Al Si P S Cl K* Ca* Ti Cr Mn Fe Co Ni Significance 0.159 0.882 0.794 0.474 0.274 0.407 0.454 0.004 * 0.012 * 0.634 0.870 0.114 0.611 0.184 0.251 Element Cu Zn Ge Br* Rb Sr In Sn La Sm Cd Eu Se Y Nb Significance 0.307 0.846 0.395 0.012 * 0.963 0.640 0.381 0.691 0.993 0.995 1.000 0.203 0.494 1.000 1.000 Element Nd Pr Pm Ba Ga Ce Te Zr I As V Significance 0.944 0.420 0.420 0.525 0.149 - 0.170 1.000 1.000 0.071 0.255

1635 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

Industrial pollution is one of the most serious problems We suggest that it is possible to refine the kind of in the world. The activities generate many wastes including wastes containing some heavy metals by using water insects some radioactive substances and heavy metals. Refining as well as Laccophilus species for investigation. But, more of the wastes is important for the ecosystem. We collected research should be done for this species concerning water these beetles from some natural habitats and noticed that heavy metal analyses and pollution. the water beetles can store some heavy metals, which are We suggest that Sn and Sr can have a role in beetle found in the habitats. So, we suggest here that it will be metabolism, since they could be determined in the speci- possible to refine the kind of wastes by using water insects mens of both species collected in most of the habitats. But as well as Laccophilus species, because the water beetles there is a need for biochemical studies to understand pre- can be easily multiplied in a simple natural or artificial cisely the roles of these elements. aquatic system. On the other hand, some elements (Ti, Co, Ge, Br, Sr,

Rb, Sn, In, La, Eu, Ga, Ce, As and V for L. hyalinus and ACKNOWLEDGEMENTS Ti, Co, Ge, Rb, Br, Sr, In, Sn, La, Sm, Cd, Eu, Se, Y, Nb, Nd, Pr, Pm, Ga, Ce, Te, and Zr for L.minutus), which the The authors want to express their sincere thanks to insects contain in their bodies (Tables 3a, b, c and 4a, b, c), Prof. Dr. Abdulhalik Karabulut, Prof. Dr. Gökhan Budak are rarely found and economically valuable. We collected (Erzurum, Turkey) for their help, to Assoc. Prof. Dr. Ö. L. hyalinus specimens from 9 different habitats and L. minu- Cevdet Bilgin (Erzurum, Turkey) for statistical analyses, tus specimens from 10 different habitats in 4 cities (Ta- and to Prof. Dr. Garth Foster (3 Eglinton Terrace, AYR bles 1 and 2). As we could just detect Rb, In, Eu, Ce, Ge, KA7 1JJ, Scotland, UK) for checking the manuscript for La, and V in one or two of these 9 habitats for L. hyalinus use of English. This study was supported by the research (Table 1), and Co, Ge, Rb, Cd, Y, Pr, Pm, Ba, Ga, Ce, Te, fund of Atatürk University (Project no: 2002-125). and Zr in one or two of the 10 habitats for L. minutus (Ta- ble 2), we suggest that it is easy to obtain knowledge about the element composition of an area by analysing the bodies of insects, especially that of dominant predators like REFERENCES Laccophilus species. However, differences of K, Ca, and Br concentrations [1] Booth, R. G., Cox, M. L. and Madge, R. B. (1990) II E Guides to Insects of Importance to Man. 3. Coleoptera. The were significant between L. minutus and L. hyalinus (Ta- University Press, Cambridge, p. 1-369. ble 9), according to the analysis of variance. It cannot be explained only by metabolic differences between the two [2] Spangler, P.J. (1981) Aquatic Biota of Tropical South Amer- species, as we collected our samples from different habi- ica, Part 1: Arthropoda. San Diego State University, San Di- ego, California, p. 1-323. tats (Tables 1 and 2). Therefore, the occurring differences of element concentrations might also be influenced by ele- [3] Nilsson, A.N. and Holmen, M. (1995) The Aquatic Adephaga ment composition of habitats in which the beetles live. Er- (Coleoptera) of Fennoscandia and Denmark. II. Dytiscidae. man et al. [28] reported that knowledge about the element Fauna Ent. Scand. 32. E. J. Brill, Leiden, p. 1-192. composition of an area can be easily obtained by research- [4] Nilsson, A. N. (2001) World Catalogue of Insects. Volume 3. ing the element content of the bodies of insects, especially Dytiscidae (Coleoptera) Apollo Books, Stenstrup, p. 1-395. of dominant predators like Agabus bipustulatus, and the data can be used for research in mining. The findings in [5] Nilsson, A. N. (2003) Family Dytiscidae. In: Löbl, I. and Smetana, A. (Eds.) Catalogue of Palaearctic Coleoptera, 35- this study confirm our earlier ones. 78. 1. Archostemata–Myxophaga–Adephaga, Apollo Books Stenstrup, p. 1-818.

CONCLUSIONS [6] Zaitzev, F. A. (1972) Fauna of the USSR Coleoptera: Am- phizoidae, Hygrobiidae, Haliplidae, Dytiscidae, Gyrinidae, Israel Progr. Sci. Transl., Jerusalem, p. 1-401. As a result, there are statistically important differences in both compositions and amounts of the elements stored in [7] Kadıoğlu, A. (2004) Bitki Fizyolojisi. 3. Baskı. Lokman Yayın, the bodies of both Laccophilus species and their sexes. The Trabzon, Türkiye, p. 1-452. (In Turkish). difference of metabolic activity may have caused these dif- [8] Jolivet, P., Petitpierre, E., Hasiao, T. H. (2003) Biology of ferences. But it must be considered that element content Chrysomelidae. Series Entomologicia., vol. 42. Dordrecht, and composition of insect bodies depends also on that of MA: Kluwer Academic Publishers, p. 1-606. their habitats. [9] Mages, M., Woelfl, S. and Tumpling, W. A. (2001) A meth- Knowledge about the element composition of an area od for trace element determination of single Daphnia speci- is easily obtained by researching the element content in mens using total reflection X-ray fluorescence spectrometry. the bodies of insects, especially those of dominant predators Spectrochim Acta B, 56: 2209-17. like Laccophilus species. The data can be used for research- [10] Van Grieken R. E. and Markowicz, A. A. (1993) Handbook ing in mining. of X-Ray Spectrometry, Marcel Dekker Inc., p. 1-76.

1636 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

[11] Christopher, J., Patel, M. B., Ahmed, S. and Basu, B. (2001) [24] Karabulut, A., Aslan, İ., Dumlupınar, R., Tıraşoğlu, E. and Determination of sulphur in trace levels in petroleum prod- Budak, G. (2005) Determination of trace elements in three ucts by wavelength dispersive x-ray fluorescence spectrosco- Chrysomela (Coleoptera, Chrysomelidae) species by EDXRF py. Fuel 80, 1975-1979. analyses. Journal of Quantitative Spectroscopy and Radiative Transfer, 94, 373-378. [12] Van Dalen, G. (1998) Determination of the Phosphorus and Sulphur Content in Edible Oils and Fats by Wavelength- [25] Büyükavcı, M., Gürol, A., Karabulut, A., Budak, G. and Dispersive X-Ray Fluorescence Spectrometry. X-Ray Spec- Karacan, M. (2005) The role of iron and zinc in chemothera- trometry, 27, 26-30. py-induced alopecia. Journal of Quantitative Spectroscopy and Radiative Transfer, 95 (2 ), 255-261. [13] Kierzek, J., Malozewska-Bucko, B., Bukowski, P., Parus, J. L., Ciurapinski, A., Zaras, S., Kunach, B. and Wiland, K. (1999) [26] Nation, J. L. (2002) Insect Physiology and Biochemistry. Assessment of coal and ash environmental impact with the Gainesville, Florida, CRC Press, p. 1-485. use of gamma- and X-ray spectrometry. Journal of Radioana- lytical and Nuclear Chemistry, 240, 39- 45. [27] Noyan, A. (1999) Yaşamda ve Hekimlikte Fizyoloji. Meteksan, Ankara, p. 1157. [14] Van Dalen, G. (1999) Determination of Iron on Cloths by Wavelength-Dispersive X-Ray Fluorescence Spectrometry. [28] Erman, Ö. K., Gürol, A. and Dumlupınar, R. (2006) Deter- X-Ray Spectrometry, 28, 149-156. mination of Inorganic Element Differences Between Male and Female of a Water Beetle Species, Agabus bipustulatus [15] Pouzar, M., Černohorský, T. and Krejčová, A. (2003) Determi- (Dytiscidae: Coleoptera) by WDXRF Analyses. Fresenius nation of metals in drinking, surface and waste water by XRF Environmental Bulletin, 15 (7): 697-703. spectrometry after preconcentration of the sample on the ion- exchange filter. Chemia Analityczna, 48, 55-64. [16] Massena Ferreira, E. de M., L'Amoura, R. J. A., Carmob, J. M. N., Mantovanoa, J. L. and De Carvalho, M. S. (2004) Determination of Hg from Cu concentrates by X-ray fluorescence through preconcentration on polyurethane foam. Micro- chemical Journal, 78, 1-5.

[17] Queralt, I., Ovejero, M., Carvalho, M. L., Marques, A. F. and Llabrés, J. M. (2005) Quantitative determination of essential and trace element content of medicinal plants and their infusions by XRF and ICP techniques. X-Ray Spectrometry, 34, 213-217.

[18] Tıraşoğlu, E., Çevik, U., Ertuğral, B., Apaydın, B., Baltaş, H., Ertuğrul, M. (2005) Determination of trace elements in cole (Brassica oleraceae var. acephale) at Trabzon region in Tur- key. Journal of Quantitative Spectroscopy and Radiative Trans- fer, 94 (2): 181-187.

[19] Karabulut, A., Aslan, İ., Dumlupınar, R., Tıraşoğlu, E. and Budak, G. (2005) Determination of trace elements in three Chrysomela (Coleoptera, Chrysomelidae) species by EDXRF analyses. Journal of Quantitative Spectroscopy and Radiative Transfer, 94 (3-4): 373-378.

[20] Dumlupınar, R., Demir, F., Şişman, T., Budak, G., Karabulut, Received: April 18, 2006 A., Erman, Ö. K., Baydaş, E. (2006) Trace element changes Revised: July 23, 2006; May 11, 2007 during hibernation of Drosophila melanogaster by WDXRF Accepted: May 25, 2007 analyses at chilling temperature. Journal of Quantitative Spec- troscopy and Radiative Transfer, 102 (3): 492-498.

[21] Dumlupınar R., Demir, F., Budak, G., Karabulut, A., Kadi, N., CORRESPONDING AUTHOR Karakurt, H. and Erdal, S. (2007) Determination of replace- ment of some inorganic elements in pulvinus of bean (Phaseolus vulgaris cv. Gina 2004) at chilling temperatures. Ö. Köksal Erman Journal of Quantitative Spectroscopy and Radiative Trans- Atatürk University fer 103 (2), 331-339. Science and Art Faculty Department of Biology [22] Aslan, A., Budak, G., Tıraşoğlu, E., Karabulut, A., Karagöz, Y., Apaydın, G., Ertuğral, B. and Çevik, U. (2004) Analysis 25240 Erzurum of Elements in some Lichens by Radioisotope X-Ray Fluo- TURKEY rescence Spectrometry. Fresenius Environmental Bulletin, 13 (8), 740-747. Fax: +90 442 236 09 48 [23] Aslan, A., Budak, G., Tıraşoğlu E. and Karabulut, A. (2006) e-mail: [email protected], Determination of elements in some lichens growing in Giresun [email protected] and Ordu province (Turkey) using energy dispersive X-ray fluorescence spectrometry. Journal of Quantitative Spectros- copy and Radiative Transfer, 97 (1), 10-19. FEB/ Vol 16/ No 12b/ 2007 – pages 1627 – 1635

1637 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

EFFECTS OF LAND-USE REGIME ON SOIL ERODIBILITY INDICES AND SOIL PROPERTIES IN UNYE, TURKEY

Murat Yilmaz1*, Ayhan Usta2, Lokman Altun3 and Fahrettin Tilki4

1Faculty of Forestry, Duzce University, 81620 Duzce, Turkey 2Eastern Black Sea Forestry Research Institute, 61300 Trabzon, Turkey 3Faculty of Forestry, Blacksea Technical University, 61080 Trabzon, Turkey 4Faculty of Forestry, Artvin Coruh University, 08000 Artvin, Turkey

SUMMARY

We evaluated the effects of land-use regime on soil ral forest ecosystems of the eastern Black Sea region are erodibility indices and several soil properties in forested, excessively devastated relative to other forested regions in deforested, and cultivated areas in the village of Unye, Tur- Turkey. This area of fairly high and steep mountains re- key. Twelve sample plots (spaced 150 m apart) with north- ceives significant precipitation and is intensively populated. ern aspects were established in each land-use regime, and The main causes of forest devastation in this region are samples were taken at soil depths of 0–20, 20–50, and 50– tillage practices and cultivation (tea or hazelnut) in lower 80 cm. Soil organic matter (SOM), soil reaction (pH), total elevation sub-regions (600–1200 m), and transhumance lime (CaCO3), texture (sand, silt, and clay), dispersion ratio (cultivation of grass and meadow vent, and provision of (DR), erosion ratio (ER), colloid-moisture equivalent ratio combustion material) in higher regions of forested areas (C-MER), structural stability index (SSI), field capacity (1200–1700 m). (FC), wilting point (WP), and available water capacity Soils in Turkey are increasingly susceptible to erosion (AWC) were analyzed. The average (of the three soil depths) owing to the conversion of forests to croplands. Land-use AWC, FC, and WP values were not affected by the site, al- regimes affect soil properties and soil susceptibility to ero- though site, soil depth, or both significantly affected other sion, and deforestation and subsequent tillage practices can analyzed soil variables. Deforestation and subsequent till- change the stability of soil aggregates and deteriorate soil age practices resulted in an almost 20% decrease in clay properties [1-5]. According to Knuti et al. [6], agricultural content, a 33% decrease in SOM, a 15% decrease in AWC, practices in forest areas damage soil quality and increase a 51% decrease in total CaCO a 24% decrease in SSI, a 3, soil erosion. Boyle [7] and Mroz et al. [8] stated that total 60% increase in DR, and a 98% increase in ER relative to tree harvesting may have several negative effects on forest undisturbed forest soil. At cultivated and forested sites, the soils, including nutrient removal in the harvested material, ER and DR increased with increasing soil depth. At de- increased erosion rates or percolation losses of nutrients, forested sites, ER and DR were lowest at 50–80 cm. SOM and soil compaction. Likens et al. [9] reported on extensive was the highest at 0–20 cm in the forested sites. Decreas- nutrient losses (particularly of NO -N and Ca) following ing SOM, clay content, and SSI, as well as increasing DR 3 deforestation. Conversion of forest and grassland into agri- and ER were outcomes of deforestation. These results in- cultural land is of considerable concern worldwide in the dicate that the conversion of forest into cropland deterio- context of environmental degradation and global climate rates some soil properties, especially SOM and SSI, and change [10, 11]. Deforestation also has important conse- alters the stability of soil aggregates, thus increasing the quences for water conservation [2]. susceptibility of deforested sites to erosion. The objectives of this study were to examine the effect of land-use regime on soil erodibility indices and other properties, and to evaluate the changes in soil properties result- KEYWORDS: Land use, soil erosion, soil properties, Turkey. ing from deforestation or cultivation in the village of Unye, Turkey.

INTRODUCTION MATERIALS AND METHODS

One of the most important issues in Turkish forestry is The study was conducted in the village of Unye, on the forest degradation and subsequent forest clearing. The natu- northeastern coast of Turkey (41°08′–41°05′ N, 37°09′–

1638 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

37°21′ E). The study area of about 260 ha extends in the termined by Duncan’s new multiple range test. Statistical east-west direction, of which 34.6% is deforested which analyses were performed using SPSS. has been clear-cut about 20 years ago and cultivated until now. An additional 30.7% has been under cultivation for many years, and the remainder of the study area is main- RESULTS AND DISCUSSION tained as forest. The elevation of the site ranges from 150 to 650 m above sea level. The landscape in the area faces ANOVA revealed significant differences among the north, with a slope ranging from 30 to 50%. The region is sites and soil depths, or both, for sand, silt, clay, DR, ER, characterized by a warm and humid Black Sea climate. C-MER, SSI, SOM, pH, and total CaCO3 (p<0.05) (Ta- Mean annual rainfall is approximately 1100 mm, and 60% of bles 1 and 2). FC and WP were not significantly affected which falls in autumn and winter months. The mean annual by site or soil depth. temperature is 13.4 °C [12]. The sand, silt, and clay contents averaged across the Fagus orientalis, Carpinus orientalis, and Quercus spp. three soil depths showed significant differences among sites, are the predominant tree species in the forested area. Fruits but there were no significant differences in sand, silt, and and vegetables (e.g., corn, potato, cabbage) and hazelnuts clay contents among soil depths at each site (Tables 1 and are common crops in the cultivated parts of the study area. 2). The average sand content was significantly higher at the As is common in this region, Fagus orientalis and Quer- deforested site than at the other two sites (67.6%, 73.3%, cus spp. were the predominant vegetation in the area prior and 67.1% for the cultivated, deforested, and forested lands, to deforestation; the vegetation was cleared approximately respectively). The average silt content (of all three depths) 20 years ago, and these sites have commonly been used for was highest in the forested soil, and the clay content was hazelnut cultivation. higher in the forested and cultivated sites (Table 1).

Soil sampling and analyses More clay accumulated at lower depths (20–80 cm) in the cultivated and forested sites. However, the soils at the Soils were examined from three different land-use re- deforested site had a higher sand content and lower clay gimes (forested, deforested, and cultivated). From each site, content (17.5 to 18.4%) at each depth (Table 2). This may 12 samples located 150 m apart were systematically col- be the result of translocation of finer particles to lower lected for detailed analysis. The samples were taken from depths (>80 cm), or the movement of finer particles to three soil depths, 0–20, 20–50, and 50–80 cm, at each site. other areas via erosion, thus leaving the coarser particles in Particle size distribution and soil organic carbon were the soils of the deforested site. This scenario is supported determined using disturbed soil samples passed through a by ER and DR results; the average ER and DR values 2-mm sieve using the Bouyoucos hydrometer method [13, were highest in the deforested site at 0–50 cm. ER and 14] and the modified Walkley-Black wet oxidation proce- DR increased with soil depth at the cultivated and forested dure, respectively. Soil organic matter (SOM) was calcu- sites, but were lowest in the 50–80 cm soil depth at the de- lated by multiplying soil organic carbon by 1.72 [15, 16]. forested site. When averaged over the three soil depths, DR and ER were highest at the deforested site (12.1% and Calcium carbonate content (CaCO3) and soil acidity (pH) were measured using the procedures outlined by Arp [16] 28.4%, respectively). Soil depth also significantly affected and Page et al. [17]. Dispersion ratio (DR) was determined DR and ER. Compared to the soil surface (0–20 cm) at the according to the methods described by Middleton [18]. cultivated and forested sites, the deeper soils had higher Total clay (TC) and total silt (TS) contents were determined DR and ER. The 50–80 cm deep soils at the deforested site from the particle size distribution using the hydrometer had the lowest DR and ER values, 10.1% and 25.0%, re- method [19]. The clay and silt fractions obtained by chemi- spectively (Table 2). cal dispersion were taken as TC and TS, while water-dis- According to Karagül [3], DR and susceptibility to persible clay and silt (WDCS) was obtained as above, ex- erosion were higher at lower soil depths. In our study, in- cept that no chemical dispersant was used. Colloid-mois- creases in clay content at 50–80 cm depths in the forest ture equivalent ratio (C-MER) and erosion ratio (ER) [20], and cultivated sites may have caused higher DR at the shal- field capacity (FC), wilting point (WP), available water ca- lower depths. Nkana and Tonye [4] found that soil sand pacity (AWC) [21], and structural stability index (SSI) [22] content was significantly affected by site, and cultivated were also determined. lands usually have higher sand content in the surface soils than forested sites. As in our study, Hajabbasi et al. [2] Statistical analyses found a higher clay content at lower soil depths (30–130 Analyses of variance (ANOVA) were performed to de- cm) in de-graded and cultivated sites; however, in contrast termine the effects of land-use regime and soil depth on the to our fin-dings, they indicated that clay content was higher chemical and physical properties of the soil. Arcsine trans- in the upper soils (0–30 cm) of a forested site. Some studies formation was performed on percentage data, but the means have reported higher clay content in cultivated sites [3, based on the original measurements are presented in the 23, 24], whereas Celik [5] found higher clay levels in a tables. Significant differences between variables were deforested site. In our study, clay content was higher in the

1639 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

cultivated and forest sites than in the deforested site, and Although site and soil depth did not significantly affect there was no significant difference between cultivated FC and WP, the deeper soils (20–50 and 50–80 cm) had a and forested sites. Decreases in clay content and increases lower WP (26.1% and 25.4%, respectively) relative to the in sand content during the last 25 years at the degraded site surface soil (0–20 cm; 30.1%) at the forested site (Table 2). in our study could increase the susceptibility of this site to However, WP at the cultivated and deforested sites was erosion. lowest in the surface soils (0–20 cm; 27.9% and 25.9%, respectively). Similar to our study, Korkanç [25] and Karagül [3] The average FC values (of the three soil depths) were found a lower DR in forested sites than in cultivated ones. 37.3%, 36.7%, and 35.9% for the cultivated, deforested, and When DR was lower than 10%, soil susceptibility to ero- forested sites, respectively. A higher FC was found at the sion was low [20, 26]. We found the average DR to be low- lower depths (20–50 and 50–80 cm) in the cultivated and er than 10% in the forested and cultivated sites, but higher forested sites, but FC was higher in the surface soils at the than 10% at all depths in the deforested site. Thus, suscep- deforested site, as with WP. tibility to erosion was higher at the deforested site than at the other two sites. High DR and low C-MER resulted in No significant difference was found between the sites high ER, as found by Korkanç [25]. High levels of SOM at in average AWC (8.26%, 7.20%, and 8.44% for the culti- the forested site resulted in low DR and lower susceptibility vated, deforested, and forested sites, respectively; Table 1). to erosion, as reported by Balcı [27] and Karagül [3]. Soil depth, however, did affect AWC; at the 50–80 cm

TABLE 1 - Effect of land-use regime on soil properties.

Soil property** Land-use regime Mean Standard Deviation F-ratio Significance Level Cultivated 67.6 b* 9.27 Sand (%) Deforested 73.3 a 9.64 4.85 0.010 Forested 67.1 b 8.90 Cultivated 9.5 b 2.97 Silt (%) Deforested 9.0 b 3.26 3.54 0.033 Forested 10.9 a 3.76 Cultivated 22.9 a 8.25 Clay (%) Deforested 17.7 b 8.34 3.36 0.038 Forested 22.0 a 10.4 Cultivated 9.35 b 4.13 DR (%) Deforested 12.1 a 5.52 6.02 0.003 Forested 7.55 b 6.38 Cultivated 16.5 b 7.55 ER (%) Deforested 28.4 a 17.2 10.51 0.000 Forested 14.3 b 15.2 Cultivated 0.60 a 0.14 C-MER Deforested 0.48 b 0.30 6.56 0.002 Forested 0.59 a 0.20 Cultivated 27.5 a 8.47 SSI (%) Deforested 22.3 b 7.46 7.64 0.001 Forested 29.2 a 7.06 Cultivated 37.3 a 9.96 FC (%) Deforested 36.7 a 12.17 0.15 0.861 Forested 35.9 a 6.54 Cultivated 28.98 a 9.74 WP (%) Deforested 29.55 a 11.47 0.40 0.672 Forested 27.43 a 7.23 Cultivated 8.26 a 3.15 AWC (%) Deforested 7.20 a 3.48 1.26 0.288 Forested 8.44 a 4.14 Cultivated 1.78 b 1.24 SOM (%) Deforested 2.08 b 0.88 6.40 0.002 Forested 3.09 a 2.27 Cultivated 6.72 a 0.71 pH Deforested 6.35 b 0.70 3.88 0.024 Forested 6.28 b 0.65 Cultivated 10.1 b 17.78 CaCO3 (%) Deforested 2.59 ab 5.30 2.87 0.041 Forested 5.26 a 14.31 DR: dispersion ratio, ER: erosion ratio, C-MER: colloid-moisture equivalent ratio, SSI: structural stability index, FC: field capacity, WP: wilting point, AWC: available water capacity, SOM: soil organic matter. *: Means in a row followed by the same letter are not significantly different at p<0.05. ** Values are the averages obtained from three depths (0–20, 20–50 and 50–80 cm).

1640 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

TABLE 2 - Effect of land-use regime and soil depth on soil properties.

Land-use Depth Soil Std. Sig. Soil Std. Sig. Mean F-ratio Mean F-ratio regime (cm) property Dev. Level property Dev. Level 0–20 69.7 a 10.23 26.4 a 8.41 Cultivated 20–50 67.0 a 8.98 28.7 a 7.73 50–80 66.4 a 9.04 27.6 a 9.92 0–20 73.3 a 8.91 22.0 a 6.56 Deforested 20–50 Sand (%) 72.3 a 8.94 1.34 0.24 SSI (%) 23.0 a 6.88 1.90 0.68 50–80 74.3 a 11.53 22.0 a 9.26 0–20 67.9 a 8.84 29.3 a 7.54 Forested 20–50 67.4 a 8.14 28.7 a 5.96 50–80 65.6 a 10.79 29.8 a 8.48 0–20 9.8 a 4.13 34.1 a 9.62 Cultivated 20–50 9.1 a 2.61 37.9 a 10.06 50–80 9.4 a 1.92 40.0 a 10.16 0–20 9.2 a 2.81 34.3 a 9.17 Deforested 20–50 Silt (%) 10.3 a 3.20 1.63 0.13 FC (%) 37.0 a 11.89 0.51 0.84 50–80 7.3 a 3.31 38.8 a 15.25 0–20 11.6 a 3.36 37.5 a 7.06 Forested 20–50 10.9 a 3.46 34.7 a 6.15 50–80 10.4 a 4.95 35.2 a 6.69 0–20 20.5 a 8.63 27.9 a 10.29 Cultivated 20–50 24.0 a 7.92 29.1 a 9.71 50–80 24.2 a 8.44 30.0 a 10.0 0–20 17.5 a 8.20 25.9 a 7.44 Deforested 20–50 Clay (%) 17.5 a 8.09 1.06 0.40 WP (%) 30.1 a 11.5 0.67 0.71 50–80 18.4 a 9.33 32.7 a 14.2 0–20 20.5 a 10.67 30.1 a 6.91 Forested 20–50 21.6 a 9.63 26.1 a 7.16 50–80 24.0 a 12.20 25.4 a 7.56 0–20 8.6 ab 2.18 6.1 a 2.61 Cultivated 20–50 9.4 ab 3.21 8.8 a 2.22 50–80 10.2 ab 6.38 10.0 a 3.52 0–20 13.2 a 5.93 8.5 a 4.83 Deforested 20–50 DR (%) 12.8 a 5.80 2.16 0.04 AWC (%) 7.0 a 1.95 1.97 0.58 50–80 10.1 ab 4.70 6.1 a 2.86 0–20 5.6 b 4.00 7.4 a 3.63 Forested 20–50 8.4 ab 7.45 8.5 a 4.26 50–80 9.2 ab 7.68 9.8 a 4.75 0–20 16.0 b 6.42 3.19 b 1.01 Cultivated 20–50 15.6 b 5.91 1.20 e 0.61 50–80 18.0 ab 10.43 0.92 bcd 0.49 0–20 29.9 a 18.48 2.72 bcd 0.64 Deforested 20–50 ER (%) 30.4 a 16.79 2.70 0.01 SOM (%) 1.86 de 0.91 9.45 0.00 50–80 25.0 ab 17.41 1.66 de 0.76 0–20 12.8 b 12.31 4.48 a 2.91 Forested 20–50 15.2 b 18.08 2.82 bc 1.37 50–80 15.4 b 16.96 1.52 e 0.40 0–20 0.58 abc 0.13 6.55 a 0.49 Cultivated 20–50 0.63 ab 0.14 6.75 a 0.80 50–80 0.60 abc 0.16 6.90 a 0.84 0–20 0.50 bc 0.13 6.31 a 0.70 Deforested 20–50 C-MER (%) 0.47 bc 0.14 2.15 0.04 pH 6.32 a 0.71 1.16 0.33 50–80 0.48 bc 0.15 6.45 a 0.77 0–20 0.52 abc 0.19 6.22 a 0.69 Forested 20–50 0.61 abc 0.18 6.33 a 0.62 50–80 0.58 abc 0.13 6.34 a 0.74 0–20 7.0 a 11.6 Cultivated 20–50 10.9 a 20.1 50–80 12.5 a 21.2 0–20 3.6 a 7.8 Deforested 20–50 CaCO3 (%) 2.3 a 4.2 0.86 0.55 50–80 1.8 a 3.2 0–20 3.4 a 10.2 Forested 20–50 6.7 a 17.1 50–80 6.0 a 16.7 DR: dispersion ratio, ER: erosion ratio, C-MER: colloid-moisture equivalent ratio, SSI: structural stability index, FC: field capacity, WP: wilting point, AWC: available water capacity, SOM: soil organic matter. *: Means in a column with the same letter are not significantly different at p<0.05.

1641 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

depth, the cultivated and forested sites had significantly high particularly important. Tillage practices and cultivation AWCs. Relative to the surface soils (0–20 cm; 8.5%) at the caused organic matter content to decrease. Patrick and deforested site, the deeper soils (20–50 and 50–80 cm) were Smith [36] reported that total tree harvesting results in up characterized by lower AWC (7.0% and 6.1% respectively). to three times greater nutrient removal, including nitrogen However, AWC was lowest in the surface soils of the cul- removal, compared to conventional logging. In addition to tivated and forested sites (Table 2). Although there were no losses from biomass removal, when little vegetation is pre- significant differences among sites in our study, AWC was sent to take up nutrients at deforested sites, nutrients can higher in the forested area, as found by Karagul [3]. The be lost by increased soil nutrient mobilization and leach- high SOM content in the forest soil may have increased ing [37]. The presence of macroaggregates is usually and the soil AWC, as noted in previous studies [28-30]. positively associated with SOM concentration [38]. Clear- ly, as explained earlier, cultivation breaks up soil aggregates The average C-MER was lowest in the deforested site and exposes previously inaccessible organic matter to mi- (0.48%; Table 1). The C-MER values indicated a difference crobial attack and accelerated decomposition and mineral- between land use regimes (Table 2), and deforested sites ization of SOM [39]. had the lowest C-MER for all three soil depths. According to Özhan [16], soils with C-MER values lower than 1.5% The conversion of forest and pastureland into cropland are susceptible to erosion. In this study, all sites had C-MER deteriorates soil properties, reduces SOM, and changes the values below this threshold, indicating soil susceptibility to distribution and stability of soil aggregates [36, 37]. Rela- erosion. tive to SOM in forest and pasture soils, SOM in cultivated soils was reduced by 44% and 48% in the 0–10 cm layer, SSI was significantly affected by site, but not by soil and by 48% and 50% in the 10–20 cm layer over 12 years, depth (Tables 1 and 2). The deforested site had the lowest respectively [5]. Hajabbasi et al. [2] reported similar find- average SSI across the three depths (22.3%), and average ings, noting that deforestation and subsequent tillage prac- SSI was found to be 27.5% and 29.2% for the cultivated tices resulted in a nearly 50% decrease in SOM at a soil and forested sites, respectively. A high soil SSI reduces depth of 0–20 cm over 20 years in the central Zagrous susceptibility to erosion [22]. Doğan and Güçer [31] and Mountains of Iran. Aşkın [32] found that soils with an SSI lower than 40% were more susceptible to erosion.

CONCLUSIONS CaCO3 was significantly affected by site and soil depth. The average CaCO3 across the three depths was highest at the cultivated site (10.1%) and lowest at the deforested site Each year, hundreds of hectares of land in Turkey are deforested and converted to cropland. We found that some (2.59%). High CaCO3 can increase aggregate size in soil and reduce erosion. soil properties have been drastically modified by changes in land-use in the village of Unye. Deforestation and sub- Soil pH was significantly affected by site, and the aver- sequent tillage practices changed the distribution and stabil- age pH across the three soil depths was highest at the culti- ity of soil aggregates, deteriorated soil properties, and de- vated site (6.72). Although not significantly affected by soil creased SOM content, SSI, and clay content. Cultivation depth, pH increased in the lower depths at all three sites. caused organic matter content to decrease, and reductions The forest at 0–20 cm had the lowest pH (6.22). In a culti- in SOM at deforested sites resulted in high DR and ER and vated site, after forest removal, pH usually does not change, low SSI. Thus, deforestation and cultivation increased soil and SOM decreases over time [33]. At our cultivated sites, susceptibility to erosion in this region. Because cultivation pH was not too low because of liming practices. following deforestation is a common practice in the region, there is a need for a comprehensive soil conservation pro- SOM was significantly affected by both site and soil gram to prevent soil erosion problems in susceptible areas. depth. The average organic matter content across the three soil depths at the forested site was significantly higher than at the other two sites (3.09%, 2.08%, and 1.78% for the for- REFERENCES ested, deforested, and cultivated sites, respectively). In most studies, SOM was found to be high in forest soil [15, 34, [1] Kalay, H.Z. and Karagül, R. (1992). Ecological degradation, 35], due to vegetation cover and humus. In our study, the forest destruction, flood and soil erosion in the East Black surface soil (0–20 cm) at all sites had the greatest amount Sea region. Ecology Journal 2: 23–27 (in Turkish). of organic matter. The forest site at 0–20 and 20–50 cm had [2] Hajabbasi, M.A., Lalalian, A. and Karimzadeh, R. (1997). higher amounts of SOM (4.48% and 2.82%, respectively) Deforestation effects on soil physical and chemical proper- relative to the same depths at the deforested and cultivated ties, Lordegan, Iran. Plant Soil 190: 301–308. sites (Table 2). At soil depths of 50–80 cm, SOM content was lowest at the cultivated site. Cultivation was associated [3] Karagül, R. (1999). Investigations on soil erodibility and some properties of soils under different land use types in with significant changes in total nitrogen, and the losses of Sogutludere Creek Watershed near Trabzon. Turkish J. nitrogen from deforested and cultivated sites appear to be Agric. For. 23: 53–68 (in Turkish).

1642 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

[4] Nkana, J.C.V. and Tonye, J. (2003). Assessment of certain [20] Özhan, S. (2004). Watershed management. Istanbul Univer- soil properties related to different land use systems in Kaya sity Faculty of Forestry, publication no: 482. Istanbul, Turkey Watershed of the humid forest zone of Cameroon. Land Deg- (in Turkish). radation & Development. 14: 57–67. [21] Karaöz, M.Ö. (1989). Methods of analysis for some soil [5] Celik, I. (2005). Land-use effects on organic matter and chemical properties (pH, carbonate, salinity, organic matter, to- physical properties of soil in a Southern Mediterranean high- tal nitrogen, available phosphorus). Istanbul University Faculty land of Turkey. Soil Tillage & Research. Res. 83: 270–277. of Forestry, Series B 39: 64–82 (in Turkish).

[6] Knuti, L.L., Williams, D.L. and Hides, J.C. (1979). Profitable [22] Leo, W.M. (1963). A rapid method for estimating structural Soil Management. Prentice Hall, Englewood Cliffs, Prentice stability of soils. Soil Science. 96: 342–346 Hall, Inc., NJ. [23] Türüdü, Ö.A. (1981). Comparative investigation of soil phys- [7] Boyle, J.R. (1975). Whole tree harvesting impact on site ical and chemical properties of a Picea forest, a beech forest, quality. In Proc. TAPPI Annu. Meet. NY 24–26 February, pp. a grass field and a cornfield in the Hamsikoy region of Trab- 29–32. Technical Association of Pulp and Paper Industries, At- zon. Karadeniz Technical University Faculty of Forestry lanta, GA. Publications, no: 13, Trabzon, Turkey (in Turkish).

[8] Mroz G.D, Jurgensen M.F. and Frederick D.J. (1985) Soil [24] Erol, A. (2004). Effect of hydro-physical soil properties on nutrient changes following whole tree harvesting on tree- soil formation factors in Kose Creek Watershed in northern hardwood sites. Soil Science Society of America Gumushane. PhD thesis. Istanbul University Graduate School Journal 49: 1552–1557. of Natural & Applied Sciences, Istanbul, Turkey (in Turkish).

[9] Likens G.E., Bormann F.H., Johnson N.M., Fisher D.W. and [25] Korkanç S.Y. (2003). Land use problems and recommended Pierce R.S. (1970) Effects of forest cutting and herbicide solutions in the vicinity of Bartın (A case study of Iskalan treatment on nutrient budgets in the Hubbard Brook water- Creek Watershed). PhD thesis, Istanbul University Graduate shed-ecosystem. Ecological Monographs. 40(1): 23–47. School of Natural & Applied Sciences, Istanbul, Turkey (in Turkish). [10] Wali, M.K., Evrendılek, F., West, T., Watts, S., Pant, D., Gıbbs, H. and McClead, B. (1999). Assessing terrestrial ecosystem sustainability: usefulness of regional carbon and ni- [26] Balci, A.N. (1996). Soil conservation. Istanbul University trogen models. Natural Resources. 35: 20–33. Faculty of Forestry, publication no: 3947–439. Istanbul, Tur- key (in Turkish). [11] Mahtab, F.U. and Karim, Z. (1992). Population and agricultural land use: towards a sustainable food production system [27] Balci, A.N. (1973). Effect of parent material and aspect fac- in Bangladesh. Ambio 2: 50–55. tors on soil properties related to erodibility. Istanbul Univer- sity Faculty of Forestry, publication no. 195, Istanbul, Turkey (in Turkish). [12] Anonymous (1999). Turkish state meteorological service, Ankara, Turkey. [28] Kantarci, M.D. (2000). Soil science. Istanbul University Fac- [13] Bouyoucos, G.J. (1962). Hydrometer method improved for ulty of Forestry publication no. 3444/387, Istanbul, Turkey making particle size analyses of soils. Agronomy Journal. 54: (in Turkish). 464–465. [29] Heiskanen, J., and Makitalo, K. (2002). Soil water retention [14] Gülçur, F. (1974). Physical and chemical soil analysis meth- characteristics of Scots pine and Norway spruce forest sites ods. Istanbul University Faculty of Forestry Publications, no: in Finnish Lapland. Forest Ecology &Management 162: 137– 201, Istanbul, Turkey (in Turkish). 152.

[15] Nelson, D.W. and Sommers, L.E. (1982). Total carbon, or- [30] Allen, A. and Chapman, D. (2001). Impacts of aforestation ganic carbon, and organic matter. In: Page, A.L. (ed.), Meth- on groundwater resources and quality. Hydrogeology Journal ods of Soil Analysis. Part 2. Chemical and Microbiological 9: 390–400. Properties, second ed. Agronomy Monographs, 9. ASA-SSA, Madison, WI, pp. 539–579. [31] Doğan, O. and Güçer, C. (1976). Description of soil erosion and calculation of soil losses using the Universal equation. [16] Arp, P.A. (1999). Soils for Plant Growth, Field and Laborato- Soil and Water Resources National Information Centre. ry Manual. Faculty of Forestry and Environmental Manage- Technical publication no. 24, Ankara, Turkey (in Turkish). ment, University of New Brunswick, Canada. [32] Aşkın, T. (1997). An investigation determining the structural [17] Page, A.L., Miller, R.H. and Keeney, D.R. (1982). Methods of stability and erodibility of Ordu soils. Masters Thesis. On- Soil Analysis. Part 2. Chemical and Microbiological Properties, dokuz Mayıs University Institute of Natural and Applied Sci- second ed. Agronomy Monographs 9. ASA-SSA, Madison, ences, Department of Soil Science. Samsun,Turkey (in Turk- WI. ish).

[18] Middleton H.E. (1930). Properties of soils which influence [33] Jaiyeoba, I.A. (2003). Changes in soil properties due to con- soil erosion. United States Department of Agriculture. Tech- tinuous cultivation in Nigerian Semiarid Savannah. Soil Till- nical Bulletin. No. 178. age & Research 70: 91–98.

[19] Gee G.W. and Bauder J.W. (1986). Particle-size analysis. In [34] Abbasi, M.K. and Rasool, G. (2005). Effects of different Methods of Soil Analysis, Part 1, Klute A. (ed.). American land-use types on soil quality in the hilly area of Rawalakot Society of Agronomy and Soil Science Society of America: Azad Jammu and Kashmir. Acta Agriculturae Scandinavica Madison, WI, pp. 91–100. Section B Soil Plant Science 55 (3): 221–228.

1643 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

[35] Neufeld, H., Resck, D. and Ayarza, M. (2002). Texture and land use effects on soil organic matter in Cerrado Oxisols, Central Brazil. Geoderma 107: 151–164.

[36] Patrick, J.H. and Smith D.W. (1975). Forest management and nutrient cycling in eastern hardwoods. USDA For. Serv. Res. Pap. ME-4. Northeast For. Exp. Stat. Broomal, PA.

[37] Ross, S.M. (1993). Organic matter in tropical soils: current conditions, concerns and prospects for conservation. Progress in Physical Geography 17: 265–305.

[38] Singh, S. and Singh, J.S. (1996). Water-stable aggregates and associated organic matter in forest, savanna, and cropland soils of a seasonally dry tropical region. India Biological Fer- tility Soils 22: 76–82.

[39] Boix Fayos, C., Calvo Cases, A., Imeson, A.C. and Soriano Soto, M.D. (2001). Influence of soil properties on the aggre- gation of some Mediterranean soils and the use of aggregate size and stability as land degradation indicators. Catena 44: 47–67.

Received: January 17, 2007 Revised: March 13, 2007; May 07, 2007 Accepted: May 25, 2007

CORRESPONDING AUTHOR

Murat Yilmaz Faculty of Forestry Duzce University 81620 Duzce TURKEY

Phone: +90 0380 5421137-3207 Fax: +90 0380 5421136 E-mail: [email protected]

FEB/ Vol 16/ No 12b/ 2007 – pages 1636 - 1642

1644 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

THE EFFECT OF pH ON ADSORPTION OF LINEAR ALKYL BENZENE SULPHONATE BY BENTONITE

Hasan B. Sağlam1, Kadir Esmer2, Erdogan Tarcan2 and Sibel Zor1*

1Kocaeli University, Faculty of Science and Arts, Department of Chemistry, 41300 Kocaeli, Turkey 2Kocaeli University, Faculty of Science and Arts, Department of Physics, 41300 Kocaeli, Turkey

SUMMARY

In the present study, the effect of pH on the adsorption Clay minerals are widespread materials in the environ- of linear alkylbenzene sulphonate (LABS) by bentonite clay ment, and many organic pollutants are often deposited or was investigated. Anionic surfactant solutions with initial adsorbed on clay surfaces. Recently, a growing interest has pH values of 3, 6, 8 and 12 were used. The LABS concen- developed in photoinduced processes of organic adsorbates tration was determined by UV spectrophotometry, and on clay surfaces, perturbation of adsorbate adsorption and Fourier Transform-IR was used for clay-LABS interaction. emission spectra, charge-transfer complexes and photo in- The spectroscopic results indicated that LABS adsorbed on duced electron transfer [10]. Particularly, the use of IR-spec- bentonite. The adsorption isotherms were formed. The ad- tra for the analysis of adsorbed or intercalated molecules sorption of LABS on bentonite was found to correspond by clays is well-known. The mode of adsorption of mo- with the Freundlich adsorption isotherm, and k and n con- lecular species on surfaces can be known by studying the stants were determined from Freundlich’s linear equation. changes in IR-spectra brought about by sorption [11-13]. Moreover, the conductivity of suspensions with different Bentonite (montmorillonite) clays are transformed to concentrations of LABS and pH values was determined, platelets of µm-size (colloidal) made of two tetrahedral (T) and conductivity of aqueous phase was increased at pHs 3 sheets of SiO units linked by an octahedral (O) sheet of and 12. From the obtained results, the highest LABS ad- 4 Al(O, OH) units, forming T-O-T layers separated by an sorption onto bentonite was determined at low pHs and 6 interlayer space of various thicknesses. Adsorption in clay concentrations. minerals occurs through Van der Waals forces, hydrogen bonding, electro-static bonding and coordinate reactions. While organic cations are adsorbed by the clay surface, or- KEYWORDS: surfactants, adsorption, bentonite, kinetics. ganic anions mainly adhere to the edges of the clay surface. In the literature, there are many examples of studies on the adsorption of different organic compounds by clay. Especially significant is the interaction between the clay INTRODUCTION matrix and anionic as well as cationic surfactants and different organics and polymers [14-18]. Surfactants are especially used in many technological processes, such as those used in the detergent industry, Natural clay minerals have a drawback in the sense paint technology and water treatment. Due to the rapid de- that they contain inorganic cations which, in aqueous me- velopment in technology, industrial, agricultural and do- dium, are strongly hydrated. Thus, they are good adsorbents mestic wastes are discharged into several receiving sys- of ionic or polar compounds, but not of non-ionic or hydro- tems, but generally, this discharge is directed to water phobic organic compounds [16-18]. sources such as rivers, lakes and seas. Surfactants cause Bentonite, due to its excess negative charge resulting serious pollution problems in rivers, lakes and seas. There- from its crystalline structure, tends to draw the positive fore, removal of surfactants from industrial waste water cations in the environment in order to neutralize itself, when plays an important role. Different adsorbents are used for processed with organic compounds. As these cations are the removal from aqueous solutions of surfactants, such bonded with weak Van der Waals forces, they can change as silica, mineral oxides, activated carbons and natural and places with other cations. This causes these kinds of min- synthetic fibers [1-4]. The adsorption of surfactants on minerals to gain electrical conductivity relative to the movement eral oxides is also an important process in the study of de- of charge within the solution environment. tergency, mineral flotation, dispersion/flocculation, particle growth in suspension, oil enhanced recovery, drilling There are various factors that strongly influence sur- fluids and various other processes [5-9]. factant adsorption at the solid/liquid interface, such as the

1645 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

nature of the aqueous phase, its pH value and the electro- the intensity of the 1110 cm-1 band. By means of the LABS lyte content. Changes in the pH of the solution usually interaction of bentonite, carbonate band at 1385 cm-1, the cause remarkable changes in the adsorption of anionic sur- sharp vibration mode, shifted to 1400 cm-1 and its intensity factants onto solid surfaces. As the pH of the solution is decreased. The wide and intense structural υ (O–H) hy- decreased, the solid surface becomes more positive or less droxyl group frequencies of bentonite at 3400–3690 cm-1 negative, due to the adsorption of protons from the solu- were separated into two components as a sharp band in the tion onto the charged sites [19]. high frequency region (Fig. 2). Due to the screening effect of hydroxyl groups, the sharp and intensive υ (C–H) stretch- In this study, at first, the adsorption by bentonite of ing vibrations of LABS in the range 2854 – 2925 cm-1 different concentrations of anionic surfactant LABS is in- (Fig.1 ) witnessed a weak band by decreasing its intensity vestigated by spectroscopic methods. Secondly, the con- in the clay-LABS complex (Fig. 2). These results were ductivity of the solution at different concentration levels of LABS and pHs is determined. Also Freundlich adsorption found to be similar to the study on adsorption of anionic and cationic surfactants by different clay minerals [22]. isotherm constants are determined from the Freundlich linear equation. At the end of all these interactions, LABS molecules were adsorbed especially via benzene sulphonate in its structure from broken ends onto clay surfaces. Adsorbed MATERIALS AND METHODS molecules could be bound on clay surfaces via Si–OH groups with hydrogen bonding and exchangeable cations. The bentonite samples were obtained from the Enez Besides, they could also bind by a coordination bonding regions of Anatolia (Turkey). The size fraction <2 µm was due to electron pairs, which are not common sulphur atoms then separated by sedimentation according to Stoke’s Law. in the sulphonate group of their organic molecular struc- The chemical analysis was carried out by Güngör et al. [17], ture. using a Perkin Elmer 3030 Model atomic absorption spectrophotometer. The sample had the chemical composition Effect of pH on conductivity (%): SiO2 62.80; Al2O3 19.00; Fe2O3 2.20; CaO 4.60; MgO The changes in conductivity values of the aqueous 1.80; Na2O 1.00; K2O 0.76; TiO2 0.45 and H2O 7.39 [15, phase containing LABS at different pHs are shown in Fig. 3. 16]. The peptization process was done by mixing 4 wt% The lowest conductivity was observed at pH 6, and the NaHCO3 and clay sample with 35% humidity [18]. highest at pH 12. By increased concentrations at pHs 3, 6 The bentonite was activated at 165 0C in a drying oven and 12, the conductivity values did not change very much. for 24 hours. Clay samples of 0.2 g were processed with At pH 8, conductivity increased with an increase in LABS 200 ml of solutions containing LABS at different concen- concentration. A significant dependence on LABS concentrations of 15, 30 45 and 60 ppm, and initial pH values of 3, tration was not observed in the alteration of aqueous phase 6, 8 and 12 were used. The pH values were adjusted with conductivity. The conductivities at pH 3 and 12 are higher an Orion 720 pH-meter, using HCl (Merck) and NaOH than those at pHs 6 and 8 (Fig. 3). (Merck). The experiments were done at room temperature. In the case of no dissolution of bentonite, the conduc- The adsorption equilibrium for LABS was managed tivity of the aqueous phase is determined by the activity of ions (H+, OH-, or pH) which react with the clay surface. For within 360 min, stirring the solutions at constant speed. + After 360 min, the amount of LABS was measured spec- clay minerals, the conductivity-determining ions are H , OH-, and complex ions formed by bonding with H+ and trophotometrically (1601 PC UV-visible SHIMADZU) at - 224 nm. At the same time, conductivity of LABS solutions OH [20]. containing clay was measured with a conductometer. At low pHs, the reaction might be: The FTIR spectra (400-4000 cm-1) were recorded on SiOH + H+ → SiOH+2 0.1% concentration KBr discs using a Shimadzu 8201/ At high pHs, the reaction is: 86601 PC spectrophotometer. Spectra outputs were record- - - ed either in absorbance or transmittance mode as a function SiOH + OH → SiO + H2O of the wave number. The adsorption of LABS onto the adsorbent surface is primarily influenced by the surface charge on the adsorbent, which, in turn, is influenced by solution pH. Hydro- RESULTS AND DISCUSSION gen ion concentration was high at pH 3. The solid surface becomes more positive, due to the adsorption of a part of Spectroscopic Results pro-tons from the aqueous phases. Thus, the adsorption of The IR spectra of natural LABS and LABS-treated sur-factants onto the clay surface is increased. The con- bentonite are illustrated in Figs. 1 and 2, respectively. In- ductivity at pH 12, because of high hydroxide ion concen- teracted by the vibration mode of LABS molecules between tration, was increased. At high pH levels, it can be said the 1130–1174 cm-1 gap, υ (Si-O) stretching mode of clays that OH- ions added to the solution cannot bond to the observed in the range of 1044–1110 cm-1 have decreased

1646 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

anionic type-clay surface as fast as protons, and thus play a significant

1647 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

97.5 %T

95.0

92.5

90.0 %Transmittance

87.5

85.0

82.5 80.0

77.5

75.0

72.5

70.0

67.5

65.0

62.5

4400.0 4000.0 3600.0 3400.0 2800.0 2400.0 2000.0 1800.0 1600.0 1400.0 1200.0 1000.0 800.0 600.0 400.0 Wavenumber/cm-1 FIGURE 1 - FTIR spectrum of natural LABS (Linear Alkyl Benzene Sulphonate).

96.0 %T 94.0

92.0 %Transmittance

90.0

88.0

86.0

84.0

82.0

80.0

78.0

76.0

74.0

72.0

70.0

4400.0 4000.0 3600.0 3400.0 2800.0 2400.0 2000.0 1800.0 1600.0 1400.0 1200.0 1000.0 800.0 600.0 400.0 Wavenumber/cm-1 FIGURE 2 - FTIR spectrum of natural bentonite and LABS-bentonite (a) LABS-clay b) natural bentonite).

1648 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

linear adsorption isotherms (n is the slope showing the varia- 1200 tion of adsorption with concentration, and k is the intercept, showing the adsorption capacity from solution of unit con- 1000 centration). Linear variety of Freundlich adsorption iso- pH=3 therms at different pH values are given in Fig. 4 for LABS. 800 pH=6 The Freundlich constants for LABS are given in Table 1. pH=8 The highest k and n values have been obtained at pH 3, pH=12 600 and the lowest at pH 12.

400 Conductivity(uS) TABLE 1 - Freundlich isotherm constants, k and n, obtained at different pH values for LABS. 200 pH k n 3 1.53 0.87 0 10 20 30 40 50 60 6 1.50 0.77 Concentration (ppm) 8 0.57 0.63 12 0.14 0.47

FIGURE 3 - The changes in conductivity values of The adsorbed LABS amount was 48.8 % at pH 3, and clay suspension containing LABS at different pH values. with low concentrations (15 ppm) this value is 30 % at pH 12. By increase in concentrations, no excessive change has been observed in the amount of LABS adsorbed. This, too, points out that clay has a definite saturation capacity [21]. 1.6 pH=3 LABS In addition, the adsorbed surfactant molecules at high con- 1.5 pH=6 LABS centrations tend to form a bilayer of the surfactant, as a pH=8 LABS result of tail-tail interaction of the hydrocarbon chains of the 1.4 pH=12 LABS surfactant. In this case, the polar groups tend to face the 1.3 liquid side [21, 22]. Apart from this, it is also claimed that, at high concentrations, the pulse forces among the surfac- 1.2 tant molecules adsorbed in interface of the solid-solution are logCa (mg/g) logCa 1.1 more effective [21-24]. The LABS adsorption is increasing by a decrease in solution pH. This increase could be ex- 1.0 plained as the clay surface has become more positive as 0.9 result of proton adsorption onto negative charged regions 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 of clay’s surface. So it could be thought that the adsorption logCe (ppm) has been generated due to the effects of electrostatic interaction between positively charged clay surface and anionic

FIGURE 4 - Freundlich adsorption isotherm surfactant molecules [22]. This result also has been sup- of LABS on bentonite at different pH values. ported by the values of the Freundlich isotherm coefficients k and n, which are high at pH 3 (Table 1). role in increasing the conductivity of the solution (Fig. 3). At pH 12, the amount of LABS adsorbed has de- At this pH, adsorption of the surfactant was decreased decreased. This is directly related with the clay’s surface pending on the adsorbent’s surface charge. This decrease charge, which is of anionic character. It is thought that, is probably due to the increase of the repulsion between generating a more negative clay surface by orientation of polar portions of surfactants adsorbed on the surface. OH- ions towards positive regions of clay surface at pH 12, the adsorption of LABS molecules onto the surface, show- Adsorption Measurements ing an anionic surfactant feature, has been reduced. At pH The relation between the surfactant (LABS) adsorbed 12, there is a force of repulsion between adsorbent and ad- by bentonite surfactant and equilibrium concentration in sorbed molecules [21-24]. solution is given by the Freundlich adsorption isotherm:

log Ca = log k + 1/n log Ce CONCLUSIONS

In this equation, Ca (mg/g) is the amount of the surfac- In this study, bentonite clay was selected as a local, tant adsorbed per gram of bentonite, Ce (ppm) is the equi- cheap and readily available adsorbent for the removal of librium of the surfactant concentration in solution. LABS from aqueous solutions. The interaction of LABS- clay was determined by means of FTIR. The adsorption of Constants k and n, peculiar to adsorbent and adsorbate, LABS by bentonite was found to fit with Freundlich ad- were determined from the intercept and slopes of Freundlich sorption isotherm. The conductivity of aqueous phase was

1649 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

increased at pH 12, but also the adsorption of LABS was [14] Akyuz, S., Akyuz, T., Davies J. E. D., Esmer, K. and Ozel, E. decreased. At lower pHs and concentrations, the amount (1995) Fourier-transform Raman and Fourier transform IR spectroscopic investigation of pyrazine and bentonite from of adsorbed surfactant was increased. Anatolia. J.of Raman Spectroscop, 26(8-9): 883- 888.

At the end of adsorption studies, it can be said that [15] Esmer K., Yagci L., Saygin N. and Gungor N. (1998) FTIR bentonite may be used suitably for adsorption of LABS. spectroscopic investigation of molecules of some gases being adsorbed by bentonites. J. Scientific-Industrial Research, 57(6):330-334.

ACKNOWLEDGMENTS [16] Esmer, K. (1998) Electrical conductivity of modified bentonites and FTIR spectroscopic investigations of some aromatic molecules adsorbed by bentonites. Materials Letters 34(3-6): This study was supported by the Research Fund of the 398-404. Kocaeli University (Project No 1999 /27). [17] Gungor, N. (2000) Effect of the adsorption of surfactants on the rheology of Na- bentonite slurries. J. Applied Polymer Science 75(1): 107-110. REFERENCES [18] Alemdar, A., Atici, O. and Gungor N. (2000) The influence [1] Mohamed, M.M. (1996) Adsorption properties of ionic sur- of cationic surfactants on rheological properties of bentonite- factants on molybdenum-modified silica gels. Colloid Surf. water systems. Materials Letters 43(1-2): 57- 61. A: Phsicochem. Eng. Aspects 108: 39-48. [19] Pavan, P.C., Crepaldi, E.L., Games De Gilmer, A. and [2] Leyva –Ramos, R. (1989) Effect of temperature and pH on Valim, J.B. (1999) Adsorption of sodium dodecylsulfate on a hydrotalcite-like compound. Effect of temperature, pH and the adsorption of an anionic detergent on activated carbon. J. ionic strength. Colloids and Surfaces 154(3): 399-410. Chem. Tedchnol. Biotechnol. 33A: 231- 240. [20] Tahir, S.S. and Rauf, R. (2006) Removal of a cationic dye [3] Iqbal, M.J. and Ashiq, M.N. (2007) Adsorption of dyes from from aqueous solutions by adsorption onto bentonite clay. aqueous solutions on activated carcoal. J. Hazardous Mater. Chemosphere 63: 1842-1848. B139: 57-66. [21] Zor, S. (2004) Investigation of the adsorption of anionic sur- [4] Valentim, I.B. and Joekes, I. (2006) Adsorption of dodecyl- factants at different pH values by means of active carbon and sulfate on chrysotile. Colloids and Surfaces A: Physicochem. kinetics of adsorption. J. Serb.Chem.Soc. 69(1): 25-32. Eng. Aspects 290: 106-111. [22] Saleh, M.M. (2006) On the removal cationic surfactants from [5] Novich, B.E. and King, T.A. (1985) A predictive model for dilute streams by granular charcoal. Water Research 40 (5): the alkylamine quartz flotation system. Langmuir 1(6): 701- 1052-1060. 708. [23] Esmer, K. and Tarcan, E. (2001) The adsorption of anionic [6] Wilson, D.J. and Carter, K.N. (1983) Electrical aspects of ad- and cationic surfactants by the different clay minerals:FTIR sorbing colloid flotation17. Quasi-chemical method for ad- spectroscopic study. Spectroscopy Letters 34 (4): 443-451. sorption of mixed surfactants. Seperation Scence and Tech- nology 18(7): 657-681. [24] Bremmell, K.E., Jameson, G.J. and Biggs, S. (1999) Adsorp- tion of ionic surfactants in particulate systems: flotation, sta- [7] Vanjara, A.K. and Dixit, S.G. (1996) Adsorption of cationic bility and interaction forces. Colloids and Surfaces 146 (1-3): surfactants on rutile. Adsorption Science & Technology 75-87. 13(5): 397-407.

[8] Kaya, Y, Vergili, I, Gonder, Z.B. and Barlas, H. (2006) In- vestigation of organic matter removal from waters with adsorption polymers. Fresenius Environmental Bulletin 15(5): 437-440. Received: February 06, 2007 Revised: March 28, 2007 [9] Zor, S., Yazici, B. and Erbil, M. (2006) Removal of lin- Accepted: June 04, 2007 earalkylbenzene sulphonate (LAS) from aqueous solutions by electrocoagulation. Bulletin of Electrochemistry 22(6): 241- 248, 2006. CORRESPONDING AUTHOR [10] Mao, Y. and Thomas, J.K. (1993) Photoinduced electron- transfer and subsequent chemical-reactions of adsorbed thi- Sibel Zor anthrene on clay surfaces. J. Org. Chem. 58 (24): 6641-6649. Kocaeli University [11] Theng, B.K.G. (1974) The chemistry of clay-organic reac- Faculty of Science and Arts tions. Wiley & Sons: New York. Department of Chemistry 41300 Kocaeli [12] Sheppard, N. (1959) Infrared spectra of adsorbed molecules. TURKEY Spectrochim Acta, 14(1): 249-260.

nd E-mail: [email protected] [13] Grim, R.E. (1968) Clay minerology. 2 Ed. Mc Graw-Hill Book Company, 79.

1650 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

FEB/ Vol 16/ No 12b/ 2007 – pages 1643 - 1647 A MICROBIAL APPROACH IN SOILS FROM CONTAMINATED MINE AREAS: THE JALES MINE (PORTUGAL) CASE STUDY

* Susana Loureiro , António J. A. Nogueira and Amadeu M. V. M. Soares

Department of Biology & CESAM-Centre for Environmental and Marine Studies, University of Aveiro, 3810-193 Aveiro, Portugal.

SUMMARY

Microorganisms play a crucial role in decomposition Some authors [2-4] have suggested that biological or processes and nutrient cycling and, therefore, in soil biochemical properties that have been demonstrated to be quality. Soil enzymes have shown sensitivity to contami- useful for the detection of soil quality changes are related nants, such as heavy metals, due to their interaction with to nutrient cycles. Soil enzymatic activity can be used as a the specific reaction sites, thereby reducing the formation sensitive index addressing heavy metals contamination. Ni- of the reaction products. In this study, several enzymatic trification or respiration are usually recommended as tox- bioassays were applied (dehydrogenase, acid phosphatase, icity endpoints in specific guidelines, but other endpoints, arylsulfatase, urease and ß-glucosidase) to soils with differ- e.g. soil enzymatic activities, have also the advantages of ent heavy metal contents, from the abandoned Jales mine having rapid and cost-effective assays [5]. Metals are able (Portugal), before, during and after a rehabilitation to reduce enzyme activity by: 1) interacting with the en- process (years 2002, 2003 and 2004, respectively). Addi- zyme-substrate complex, 2) denaturing the protein by the tionally, the mineralization of N and the microbial bio- interaction with its active sites or 3) by simply affecting mass of C and N were measured. the microbial cells that produce the enzymes [6-8]. Not all metal species can induce similar effects, so metal spe- The results obtained in this study indicated that dehy- ciation in the solid or liquid phases, and consequently their drogenase, arylsulfatase and N-mineralization activities dem- bioavailability, will be of great importance on producing onstrated that there had been a recovery in soil microbial effects in soil enzymatic processes [9]. numbers, but provided no information on the influence of contaminants in soils. Microbial biomass C and N also presented an increase from 2002 to 2004, and soil organic The use of single enzyme bioassays has been criticized matter and pH influenced the enzymatic activities, mainly by several authors [2, 3, 10, 11], because each enzyme ca- dehydrogenase, acid phosphatase and arylsulfatase. talyses a specific reaction, using a specific substrate. There- fore, measuring different enzyme activities is advisable in An increase of microbial activities was observed in soil quality studies. 2003, with several soil enzymes showing recoveries in their activities. Therefore, nutrient cycles have probably bene- This study is integrated in a larger work carried out in fited from this, improving soil quality. Jales mine, where ecotoxicological approaches evaluated soil toxicity and contamination in two soils of this area [12- 14]. Over 3 years, four enzymatic activities, important in KEYWORDS: different nutrient cycles in soil and decomposition process- heavy metals, soil enzyme, microbial biomass, soil contamination. es (arylsulfatase, urease, acid phosphatase and ß-glucosidase) were determined. Nitrogen mineralization was also determined and the soil dehydrogenase activity was meas- INTRODUCTION ured because it is considered to be an endocellular enzyme, playing an integral part in microbial metabolism and, there- Soil quality is intimately related to both physicochemi- fore, an indicator of physiologically active organisms. Such cal soil properties and soil biological functions, and their an activity is also involved in the oxidation of organic mat- evaluation will help to characterize the fertility and produc- ter [15-17]. tivity of soils. Recently, some attention has been also directed to soil habitat function, and the assessment of fac- Two hypotheses were raised in this study: 1) are single tors that influence toxicity towards microorganisms and all enzymatic activities able to mirror soil contamination? 2) processes that they mediate need to be taken into consid- are soil enzymes able to detect slight contamination changes/ eration [1]. status during short-term periods?

1651 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

MATERIAL AND METHODS The water-soluble metal content from soil elutriates is given in Loureiro et al. [13]. Study area The vicinities of the mine spoil enclose agriculture and The study was carried out in the abandoned Jales mine pasture fields with vegetation composed by Alnus glutinosa vicinities (near Vila Pouca de Aguiar) in the northeast of (L.) Gaertn., Carpinus betulus L., Castanea sativa Miller, Portugal. During 1993, the mine was abandoned and from Frangula alnus Miller, Fraxinus angustifolia Vahl, Malus September 2002 to late 2003 the mine spoil was rehabili- domestica Bork, Pinus pinaster Aiton, Pinus sylvestris L., tated by an environmental concessionary hired by the Por- Quercus pyrenaica Willd., Quercus robur L., and Salix tuguese government, and acting independently from this atrocinerea Brot.. study. In this process, the mine spoil was impermeabilized using geosynthetic layers to prevent the spreading of spoil Soil sampling and soil analysis particles. This procedure prevented silt-sand-clay materials contaminated with As, Cd, Pb, Zn and Cu to flow over the In this study, the sampling was made by a composite surrounding area of the mine spoil, and with a consequent sampling procedure due to possible high heterogeneity of input of contamination. soil properties within a sampling area. In each selected area, 10 soil samples of the top 0-10 cm TABLE 1 (Ø 20 cm) were collected randomly, stored in open plastic Physico-chemical properties, biological characteristics and metal bags and then transported to the laboratory. In the lab, the content in JNC and JC soils from Mina de Jales (Portugal) in 2002. litter layer was removed and the soils sieved on a <2-mm mesh, and physico-chemical analyses were then conducted. Soil samples were pooled and stored in closed plastic bags at 4 ºC until enzymatic analysis was completed. As recommended, soil enzymatic activities were processed without freezing, drying out or waterlogged during storage [18]. Soil pHs were determined in a KCl (1M) solution [19], and soil moisture was measured by the difference in weight be-fore and after drying the soil, at 105 ºC, in an oven, overnight. The organic matter content was determined by the loss- ignition method, after the determination of soil moisture content, from loss in weight after 5 h at 540 ºC (adapted from [20]). Microbial biomass of C and N were measured, as based in a standardized protocol ISO 14240-2 [21], and the total N was determined by a Kjeldahl’s digestion. Heavy metal content was only analysed in the soil samples collected in 2002 because, as the spoil was being impermeabilized, no more metal input was expected. Also, the heavy metal content was similar to the values found by other authors some years before [22]. Nitrogen content and microbial biomass of C and N were evaluated in 2002 and 2004. Heavy metal analysis was performed by Inductively Coupled Plasma Optical Emission Spectroscopy (ICPOES, Perkin Elmer 4300 DV). Soil digestion was made in HCl

and HNO3 (3:1). Two distinct areas were chosen due to their different heavy metal content. The fields nearby the mine spoil Enzymatic Activities are used for agricultural purposes, but the sampling area In this study, we measured the enzymatic activities in (±400m2) chosen has not been used for the past years for the two soils at different stages of rehabilitation: in Febru- agricultural nor pastoral purposes. Cambisoil collected from ary 2002 (no rehabilitation), February 2003 (during rehabil- this area (N 41º 27’ 53.9’’; W 07º 34’ 50.6’’), hereafter itation) and February 2004 (after rehabilitation), and dis- identified as JC soil, has high heavy metal concentrations cuss the effects of contamination and rehabilitation on soil (Table 1). This area was harvested every summer. The other quality. selected sampling area (±800m2) was located 3 km from the mine spoil and was mainly used for cow and horse Dehydrogenase (DHA) (EC 1.1.1.49) activity was de- pasture (N 41º 28’ 36.1’’; W 07º 34’ 14.0’’). The cambisoil termined by the suspension of soil samples in a triphenyl- collected from this area, hereafter identified as JNC soil, tetrazolium chloride (TTC) solution and incubated for 24 h has lower heavy metal contents when compared to the JC at 40 °C. The triphenyl formazan (µg TPF / g.dm / h) pro- soil (Table 1), with the exception of aluminium content. duced was extracted with acetone and measured photomet-

1652 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

rically at 546 nm. This methodology is similar to the ISO statistical package [29]. To compare the differences in their draft that is being developed by ISO [23], and was based enzymatic activity between soils and sampling time, a two- on the methods of Schinner et al. [24]. To determine acid way ANOVA was performed. When significant differences phosphatase (EC 3.1.3.2) activity, soil samples were sus- were found, following the analysis of variance, a post-hoc pended in a buffered p-nitrophenyl phosphate solution (pH= multiple comparison Tukey test was used to assess differ- 5) and incubated for 2 h at 35 °C. The p-nitrophenol pro- ences between soils and sampling times. The Dunn’s test duced (µg pNP / g.dm / h) was coloured and measured pho- was applied when there was a positive result (p≤0.05) after tometrically at 405 nm in a microplate reader [24-26]. Aryl- a Kruskal-Wallis one-way analysis of variance on ranks sulfatase (EC 3.1.6.1) activity was determined by incubating (when data had not a normal distribution). soil samples in a buffered potassium-p-nitrophenylsulfate To evaluate the weight of abiotic environmental proper- solution (pH=5.8) at 37 ºC, for 1 h. The accumulation of ties on the ecosystems biotic fraction, multivariate analy- p-nitrophenol (µg pNP / g.dm / h) was measured as in the sis has been used in ecology, but this type of analysis is not phosphatase protocol, based on Schinner et al. [24]. The widely used in ecotoxicology [30]. In this study, Redundan- method for ß-glucosidase (EC 3.2.1.21) activity determi- cy Analysis (RDA) was performed with CANOCO [31], nation was adapted from methodologies of Tabatabai [26], using enzymatic activities as species and organic matter where soil samples were incubated in a buffered p-nitro- content, pH and soil moisture content as environmental phenyl-ß-D-glucoside solution (pH=6). The measurement of properties. Enzymatic data were transformed with the in- p-nitrophenol (µg pNP / g.dm / h) was done as previously ternal function ln (x + 1) to standardize and normalize all explained. Urease (EC 3.5.1.5) activity was determined the data. The Monte Carlo Permutation method was used following the protocol previously described by Schinner et to assess marginal effects associated with environmental al. [24], and Kandeler and Gerber [27], where soil samples factors. were suspended in a borate buffer (pH=10) and urea solu- + tions incubated for 2 h at 37 ºC. The release of NH4 (µg N / g.dm / 2 h) was measured in a microplate reader at RESULTS 690 nm. For the N-mineralization determination, soil samples were incubated in water at 40 ºC, and 1 week later + + Changes in pH values and organic matter content in NH4 was extracted with potassium chloride. NH4 was JNC and JC soils throughout the sampling periods, and measured as in the urease methodology [24]. also summer and autumn months in 2003, are presented in All measurements were performed in 5 sub-replicates Fig. 1. There was an increase in soil pH from 2002 to 2004 plus 3 controls. and, on the other hand, a decrease in soil organic matter in the same period. JC soil pH also suffered some fluctuations Statistical analysis within the year of 2003, with its higher value in November Soil enzyme activities were compared by one-way 2003. analysis of variance ANOVA [28], using the SigmaStat

FIGURE 1- pH values and organic matter content (%) of JNC and JC soils collected from Jales Mine (Portugal) recorded during all sampling period (from February 2002 till 2004).

1653 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

FIGURE 2- Enzymatic activities (average ± standard error) of JNC and JC soils collected from Jales Mine (Portugal) before, during and after the rehabilitation process (February 2002, February 2003 and February 2004).

Soil enzymes showed different patterns of activity be- F1,24=21.162, p≤0.05). Before rehabilitation (2002), the fore, during and after the mine’s rehabilitation (Fig. 2). two soils had similar activities, but during the first year of Additionally, microbial biomass of N increased from 2002 rehabilitation (2003) JNC soil showed a higher increase in to 2004 from 40 to 84 mg/Kg in JNC soil, and was activity, which turned out to be significantly different from maintained in JC soil (84.4 to 91.40 mg/Kg) in the same the activity in JC soil (two-way ANOVA, F2,24= 27.513, period. Microbial biomass of C showed a significant in- p≤0.05). crease in JNC soil from 96.90 to 361.50 mg/Kg, and also During this 3-years’ period both soils showed a de- maintained its values in JC soil (792.20 mg/Kg in 2002 and crease in their ß-glucosidase activity (two-way ANOVA, 637.03 mg/Kg in 2004). Microbial biomass C and N in- F2,17=18.913, p≤0.05). JNC soil decreased almost two- creased significantly four and two times, respectively, in fold and JC soil 4 times from 2002 till 2004. This led to a 2004 in JNC soil. significant difference between both soils only within 2003 During the same period, the DHA activity increased and 2004 samplings (two-way ANOVA, F1,17=14.507, p≤ significantly two-fold in the JNC soil and 1.5 times in the 0.05). JC soil in 2004, when compared to 2002 (two-way ANOVA,

1654 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

During the three sampling years, there were no signif- ciated with the enzymes, and the remaining 72.2% is ex- icant differences in the acid phosphatase activity be- plained by the interaction between enzymes and environ- tween the JNC and the JC soils (two-way ANOVA, F1,24= mental factors). The 2nd axis explains 6.6% of the variabil- 4.168, p>0.05). Both soils showed a significant decrease ity (1.4% is associated with the enzymes, and the remaining in their phosphatase activity in February 2004, when com- 5.2% is explained by the interaction between enzymes and pared to the two previous years (two-way ANOVA F2,24= environmental factors). The eigenvalues for the 1st and 2nd 31.106, p<0.05; Tukey test, p≤0.05). axis were 0.194 and 0.014, respectively (Fig. 3). In the JNC soil, the arylsulfatase activity increased From the triplot of Fig. 3, it can be observed that the significantly in 2004, reaching mean values 2.5 times higher 1st axis explains the distribution of the sampling years, than those from 2002 (one-way ANOVA, F2,12= 16.419, placing the year 2002 in an opposite part of the triplot p≤0.05; Tukey test, p≤0.05). The JC soil also showed a sig- when compared to the year 2004. This distribution occurs nificant increase, but by 1.3 times, when compared to 2002 along a gradient defined by urease and N-mineralization (one-way ANOVA, F2,12=9.105, p<0.05; Tukey test, p≤ (associated with 2004), and ß-glucosidase (associated with 0.05). 2002). Although with similar N-mineralization rates, both soils It can also be observed that both axes separate clearly showed markedly greater rates in 2004 when compared to the two soils. The 2nd axis separates also the enzymes that 2002 and 2003 (two-way ANOVA, F2,16=49.392, p≤0.05). showed recovery (increase in theiractivities) along the 3 The increased rate was three times higher than that before years (arylsulfatase, urease, DHA and N-minaralization) rehabilitation (February 2002). from the ones that showed even a decrease in their activity in 2004, when compared to 2002 (ß-glucosidase and acid- The urease activity did not show significant differences phosphatase). between soils in 2004 (two-way ANOVA F2,18= 0.503, p>0.05). This activity increased significantly in 2004 in the JNC soil, reaching twice the value obtained before the DISCUSSION beginning of mine rehabilitation (Kruskal-Wallis one-way analysis of variance on ranks, H=6,838, DF= 2, p≤0.05). In both soils, the rehabilitation process induced an in- Urease activity of JC soil showed a different behaviour, crease in soil enzymatic activities, with the exception of ß- decreasing in 2003, when compared to 2002, but recovering glucosidase and acid phosphatase. again to similar values in February 2004 (Kruskal-Wallis one-way analysis of variance on ranks, H=8,938, DF= 2, JNC soil denoted higher enzymatic activities and also p≤0.05). an increase in the microbial biomass C and N in 2004, showing a recovery of microbial biomass, during and at

the end of the rehabilitation process. Changes in the acid phosphatase activity were related to changes of pH (decreasing with the increase of pH values), and directly related with SOM contents, which was also reported by several authors [32, 33]. The major reason for this decrease of acid phosphatase with the increase of pH might be the fact that this enzyme is more predominant in acid soils, whereas alkaline phosphatase is predominant in more alkaline soils. So, as pH increases from 2002 till 2003 and maintained in 2004 (comparing only between the February months), the acid phosphatase activity decreases as the alkaline phosphatase increases. These authors also reported that arylsulfatase presented the opposite trend with pH values, increasing with the increase of pH. DHA and arylsulfatase activities and N-mineralization rate showed a better and positive response to the mine spoil rehabilitation process, while urease behaved differently; acid phosphatase and ß-glucosidase produced a decrease in their activity afterwards. DHA is related to active micro- FIGURE 3 - Redundancy Analysis (RDA): triplot of enzymatic organisms and has been used as an indicator of soil quality activities and environmental variables ( centroid for soil type; [15, 16]; it generally increases with the increase of soil pH. centroid for sampling year; - - - enzymatic activity; ______envi- ronmental parameters) of JNC and JC soils in February 2002, 2003 The increase of the mineralization process will improve the and 2004. transformation of organic forms to mineral forms, which is of extreme importance to plants. Consequently, their in- The RDA analysis showed that 91.6% of the variabil- crease is a good indication for soil quality improvement. st 2- ity of our data is explained by the 1 axis (19.4% is asso- Also SO4 is essential for plants and also immobilized by

1655 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

edaphic organisms; its production is promoted by aryl- The study of enzymatic activities in soil is a useful sulfatase activity which also presented an increase in both tool to check how nutrients are involved in the recycling soils from the mine area [34]. of soils and how contamination or other stressors are affecting soil quality. Nevertheless, this assessment should be From 2002 until 2004, there was an increase in the done as part of an integrative test battery, to fulfil the mi- microbial biomass C in JNC soil that might be responsible crobial gaps that usually exist in the ERA, but can not for the decrease/ degradation of the organic matter content probably be used by their own as “a single enzymatic in both soils collected from the mine. But it also induced battery”. the decrease in ß-glucosidase activity that was unexpected and contradictory to what was found in several studies where this enzyme was always positively and highly related ACKNOWLEDGEMENTS to the microbial biomass C content [4, 32, 35]. The increase in urease activity and N-mineralization The authors would like to thank Fundação para a Ciên- rate was also related to the increase of the microbial bio- cia e Tecnologia, for providing a PhD grant to Susana mass N, which doubled its value in February 2004, when Loureiro. The authors would also like to thank Prof. compared to 2003, in JNC soil. When decomposition pro- Philippe Ross for revising the manuscript. cesses are taking place in soil, the C/N ratio will decrease with time because carbon biomass is lost as CO2, while N is re-used by microorganisms [34]. The decrease in the N REFERENCES bio-mass will reach a point when the microbial activity will also decrease, due to organic carbon loss. In good [1] Stuczynski, T.I., McCarty, G.W., and Siebielec, G. (2003) quality soils, this loss will take short periods to recover, Response of soil microbiological activities to cadmium, lead and zinc salt amendments. J. Environ. Qual. 32, 1346-1355. depending only on the time that the organic material needs to be degraded [34, 36, 37]. [2] Nannipieri, P., Kandeler, E., and Ruggiero, P. (2002) En- zyme activities and microbiological and biochemical pro- The high concentration of Fe found in JC soil elutri- cesses in soil.In R.G. Burns and R.P. Dick (Ed-s.) Enzymes ates [13] can act as an inhibitor of enzymes, diminishing in the Environment: Activity, Ecology and Applications, their activities, but also can make complexes with other Marcel Dekker, Inc., New York, Marcel Dekker, Inc., 1-33. 2- ions like SO4 and other heavy metal complexes, reduc- [3] Cepeda, C.T., Leirós, M.C., Seoane, S., and Sotres, F.G. (2000) ing the heavy metal toxicity [9]. Aluminium concentration Limitations of soil enzymes as indicators of soil pollution. in JNC soil elutriates can also play an important role in Soil Biol. Biochem. 32, 1867-1875. this soil toxicity to microorganisms and soil quality [13]. [4] Ajwa, H.A., Dell, C.J., and Rice, C.W. (1999) Changes in In this study, pH value and microbial biomass C and enzyme activities and microbial biomass of tallgrass prairie N were the parameters that seemed to influence the most soil as related to burning and nitrogen fertilization. Soil Biol. Biochem. 31, 769-777. the recovery of soil enzymes along time. Heavy metal speciation varies with slight pH changes and, therefore, [5] Carbonell, G., Pablos, M.V., García, P., Ramos, C., Sánchez, changes in pH in both soils might be one of the responsi- P., Fernández, C., and Tarazona, J.V. (2000) Rapid and cost- ble factors for differences in enzymatic activities. The in- effective multiparameter toxicity tests for soil microorganisms. The Science of the total Environment. 247, 143-150. creases of microbial biomass C and N are probably related to the significant increase of soil enzymatic activity in [6] Vig, K., Megharaj, M., Sethunathan, N., and Naidu, R. (2003) JNC soil. Bioavailability and toxicity of cadmium to miccroorganisms and their activities in soil: a review. Advances in Environ- mental Research. 8, 121-135.

CONCLUSIONS [7] Guettes, R., Dott, W., and Eisentraeger, A. (2002) Determina- tion of Urease activity in soils by carbon dioxide release for In this study, DHA activity, an indication for living Ecotoxicological Evaluation of contaminated soils. Ecotoxicol- ogy. 11, 357-364. cells` presence in soils, showed a good recovery after the rehabilitation of the mine spill. This is usually considered [8] Madejón, E., Burgos, P., López, R., and Cabrera, F. (2001) to be a marker of soil quality. Additionally, arylsulfatase Soilenzymatic response to addition of heavy metals with or- activity and N mineralization rate showed a good upturn ganic residues. Biol. Fertil. Soils. 34, 144-150. in 2004, improving N and S cycles that are crucial for plants. [9] Allen, H.E. (2002) Bioavailability of Metals in Terrestrial Eco- With a different trend, enzymatic activities related to the systems: Importance of Partitioning for Bioavailability to In- C and P cycles showed regression in 2004. With these re- vertebrates, Microbes, and Plants. In: Lee, C. (Ed.) Metal and sults we can state that a range of enzymes must be analysed the Environment Series, SETAC, New York, SETAC, 158. to have a complete profile of microbial behaviour in soils. [10] Cepeda, C.T., Leirós, M.C., Sotres, F.G., and Seoane, S. (1998) Otherwise, wrong assumptions can be taken as premises. Towards a biochemical quality index for soils: an expression In this study, it was observed that some soil enzymes re- relating several biological and biochemical properties. Biol. sponded to changes due to the mine rehabilitation. Fertil. Soils. 26, 100-106.

1656 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

[11] Leirós, M.C., Cepeda, C.T., Fernández, F.G., and Sotres, F.G. [27] Kandeler, E. and Gerber, H. (1988) Short-term assay of soil (1999) Defining the validity of a biochemical index of soil urease activity using colorimetric determination of ammoni- quality. Biol. Fertil.Soils. 30, 140-146. um. Biol. Fertil. Soils. 6, 68-72.

[12] Loureiro, S., Soares, A.M.V.M., and Nogueira, A.J.A. (2005) [28] Zar, J.H. (1996) Biostatistical Analysis (Ed-s.), Prentice-Hall Terrestrial avoidance behaviour tests as screening tool to as- International, Inc., NJ, USA, Prentice-Hall International, Inc., sess soil contamination. Environ. Pollut. 138, 121-131. [29] SPSS, SigmaStat for Windows (version 2.03), S. Science, [13] Loureiro, S., Ferreira, A.L.G., Soares, A.M.V.M., and Editor. 1995: IL. Nogueira, A.J.A. (2005) Evaluation of the Toxicity of Two Soils from Jales mine (Portugal) Using Aquatic Bioassays. [30] Van den Brink, P.J., Van den Brink, N.W., and Ter Braak, Chemosphere. 61(2), 168-177. C.J.F. (2003) Multivariate analysis of ecotoxicological data using ordination: demonstrations of utility on the bases of [14] Loureiro, S., Santos, C., Pinto, G., Costa, A., Monteiro, M., various examples. Australian Journal of Ecotoxicology. 9, Nogueira, A.J.A., and Soares, A.M.V.M. (2006) Toxicity As- 141-156. sessment of Two Soils from Jales Mine (Portugal) Using Plants: Growth and Biochemical Parameters. Arch. Environ. [31] Ter Braak, C.J.F. and Smilauer, P. (2002) CANOCO Refer- Contam. Toxicol. 50, 182–190. ence manual and CanoDraw for Windows User's guide: Software for Canonical Community Ordination (version 4.5). [15] Rossel, D. and Tarradellas, J. (1991) Dehydrogenase activity In: Power, M. (Ed.), Ithaca, USA. of soil microflora: significance in ecotoxicological tests. En- vironmental Toxicology and Water Quality: An International [32] Mullen, M.D., Melhorm, C.G., Tyler, D.D., and Duck, B.N. Journal. 6, 17-33. (1998) Biological and biochemical soil properties in no-till corn with different cover crops. Journal of Soil and Water [16] Rossel, D., Tarradellas, J., Bitton, G., and Morel, J.-L. (1996) Conservation. 53(3), 219-224. Use of enzymes in soil ecotoxicology: a case of dehydrogenase and hydrolytic enzymes. Soil Ecotoxicology, Lewis Pub- [33] Ekenler, M. and Tabatabai, M.A. (2003) Responses of phos- lishers, Lewis Publishers, 179-206. phatases and arylsulfatase in soils to liming and tillage systems. J. Plant Nutr. Soil Sci. 166, 281-290. [17] Römbke, J., Bauer, C., and Marschner, A. (1996) Hazard assessment of chemicals in soil. Proposed ecotoxicological test [34] Varennes, A. (2003) Productividade dos Solos e Ambiente. strategy. Environ. Sci. Pollut. Res. 3(2), 78-82. In: Varennes, A. (Ed.) Escolar Editora. Lisboa, Escolar Ed- itora, 490. [18] ISO, Soil quality- Sampling- Part 6: Guidance on the collection, handling and storage of soil for the assessment of aero- [35] Turner, B.L., Hopkins, D.W., Haygarth, P.M., and Ostle, N. bic microbial processes in the laboratory. 1993, ISO- The In- (2002) b-Glucosidase activity in pasture soils. Applied Soil ternational Organization for Standardization: Genève. p. 4. Ecology. 20, 157-162.

[19] 1ISO, Soil quality- Determination of pH. 1994, ISO- The In- [36] Stevenson, F.J. and Cole, M.A. (Eds.) (1999) Cycles of Soil. ternational Organization for Standardization: Genève. p. 5. John Wiley & Sons, Inc., New York, John Wiley & Sons, Inc., 427. [20] Storer, D.A. (1984) A simple high sample volume ashing procedure for determination of soil organic matter. Commun. [37] Knoepp, J.D., Coleman, D.C., Crossley Jr., D.A., and Clark, in Soil Sci. Plant Anal. 15(7), 759-772. J.S. (2000) Biological indices of soil quality: an ecosystem case study of their use. Forest Ecology and Management. [21] ISO, Soil quality -- Determination of soil microbial biomass 138, 357-368. – Part 2: Fumigation-extraction method. 1997, ISO- The In- ternational Organization for Standardization: Genève. p. 12.

[22] Santos Oliveira, J.M. and Ávila, P.F. (1995) Avaliação do impacto químico ambiental provocado por uma exploração mineira. Um caso de estudo na Mina de Jales. Estudos, Notas e Trabalhos, I. G. M. 37, 25-50. Received: March 19, 2007 Revised: May 18, 2007 [23] ISO, Soil Quality- determination of dehydrogenase activity in Accepted: June 14, 2007 soils-Part 1: Method with TTC. Draft (Enquiry stage), ISO- The International Organization for Standardization: Genève. p. 5.

[24] Schinner, F., Ohlinger, R., Kandeler, E., and Margesin, R. CORRESPONDING AUTHOR (1996) Methods in Soil Biology. Springer- Verlag, Berlin, Springer- Verlag, 426. Susana Loureiro [25] Dick, R.P., Breakwell, D.P., and Turco, R.F. (1996) Soil En- Department of Biology & CESAM zymes activity and biodiversity measurements as integrative University of Aveiro microbiological indicators. In: Doran, J.W. and Jones, A.J. 3810-193 Aveiro (Eds.) Methods for assessing soil quality, Soil Science Socie- ty of America, Inc., Madison, Wisconsin, Soil Science Socie- PORTUGAL ty of America, Inc., 247-272. Phone: +351 234 370779 [26] Tabatabai, M.A. (1994) Soil Enzymes. In: Weaver, R.W., Fax: +351 234 372587 Angle, J.S. and Bottomley, P.S. (Eds.) Methods of soil Analysis, Part 2. Microbiological and biochemical Properties, Soil E-mail: [email protected] Science Society of America, Madison, Soil Science Society of America, 775-833. FEB/ Vol 16/ No 12b/ 2007 – pages 1648 - 1654

1657 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

IMMOBILIZATION OF Rhodococcus sp. DG FOR EFFICIENT DEGRADATION OF PHENOL

Mona K. Gouda*

Botany Department, Faculty of Science, Alexandria University, Alexandria, Egypt

SUMMARY

Phenol is a common environmental pollutant resulting some other forms, which may be harmful [7, 8]. Biodegra- from different industries. Rhodococcus sp. DG was isolated dation has been studied as an alternative technology, due from diesel contaminated soil and used to degrade phenol to the low cost of this method, as well as the possibility of in liquid mineral medium. The addition of 0.5 g L-1 peptone complete mineralization of the compound [9, 10]. Various as nitrogen source enhanced the degradation of phenol, aerobic and anaerobic phenol degrading microorganisms while supplementation of the medium with glucose at 0.6 g have been isolated and characterized [11, 12]. Many meso- L-1 delayed the degradation. The results show that the deg- philic microorganisms including Pseudomonas sp., Strep- radation rate was increased with increasing phenol concen- tomyces sp., Acinetobacter sp. and Alcaligenes sp. have tration up to 750 mg L-1 and then decreased due to the toxic been reported to degrade phenol [13]. The genus Rhodococ- effect of the phenol on bacterial growth. Immobilization of cus is a very diverse group of bacteria that possesses the the cells in calcium alginate beads could protect the cells ability to degrade a large number of organic compounds, from phenol toxicity and increased the degradation ability including some of the most difficult compounds with re- of the cells. The immobilized cells degraded about 70% of gard to recalcitrance and toxicity [14]. Various ways have 1000 mg L-1 phenol in comparison with only 31% by the been proposed to overcome substrate inhibition to treat free cells after 72 h and about 98% degradation was achieved medium-to-high-level phenol. These include adapting the with immobilized cells after 120 h. The immobilized cells cells to higher levels of phenol [15], adding yeast extract to can be reused for ten cycles with average degradation rate enhance degradation rate [16], and immobilization of the of 31.3 mg L-1h-1. The test organism was also able to de- cells [17]. Cell immobilization appears to be a more prom- grade cresol and catechol at different rates. ising technique. There has been an increasing interest in the immobilization of microorganisms used in biodegradation of persistent pollutant in recent years [18-20], due to high cell density and increased resistance to the toxic effect of KEYWORDS: the pollutant. Immobilized cells also have advantages over Rhodococcus; phenol; degradation; immobilization; alginate. free cells due to the possibility for reuse for a long period of time.

The aim of this study is to evaluate the ability of free INTRODUCTION and immobilized cells of Rhodococcus sp. DG, which was isolated from diesel contaminated soil, to degrade phenol Phenol is a common industrial chemical that is used in in liquid medium. the manufacture of resins, plastics, fibers, adhesives, iron, steel, leather, rubber and pharmaceutical and as major pollutants in wastewater of oil refineries and petrochemical MATERIALS AND METHODS plants [1-5]. It also found in disinfectants, cleaners and motor vehicle emissions. Natural phenolic compounds and their Bacterial strain and culture conditions derivatives are present everywhere in the environment. The bacterial strain used in this study was isolated These compounds enter the environment as intermediates from diesel contaminated soil (Cottbus, Germany) and during the biodegradation of natural polymers containing kindly provided by Prof. Dr. Spyra. The strain was identi- aromatics rings, such as lignins and tannins [6]. Phenol is fied as Rhodococcus sp. DG using 16S rRNA methodolo- responsible for serious damage to the flora, aquatic life, gy and had the accession number DQ084326. M-9 miner- animals as well as human beings in many ways [5]. Physi- al salt medium was used. The medium contained (g L-1): cal and chemical methods for phenol removal are costly Na2HPO4, 6; KH2PO4, 3; NaCl, 10; NH4Cl, 1, the pH was and cannot remove phenol completely or convert it into adjusted to 7 before sterilization at 121°C for 20 min. After

1658 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

sterilization 2 ml of sterile 0.5M MgSO4. 7H2O4 and 10 ml medium with phenol as the sole carbon source. On the other of 0.01M CaCl2 were added to the medium. Stock phenol hand, 10 ml of cells-agar mixture was poured in 10 cm sterile solution was prepared and sterilized by membrane filtra- Petri-dish and left to harden, and then cut into cubes, washed tion then added to the sterilized medium to give a final phe- with sterile water and added to the medium. In all experi- nol concentration of 500 mg L-1 mineral medium. Cultiva- ment gel materials without cells were used as control. tion was carried out in 250 ml conical flasks, containing 50 ml of the medium and inoculated with 1 ml (optical den- Scanning Electron Microscope (SEM) -1 sity 1.5 equivalents to 1 mg ml dry weight) of 24h seed The alginate beads were halved and dehydrated by culture. The cultures were incubated on a rotary-shaker at soaking in ethanol/water mixtures of progressively increas- 120 rpm and 30ºC for the requested time. To test the effect ing concentrations starting with 30% and ending with abso- of phenol concentration, different volumes of the stock phe- lute alcohol. The beads were then dried in a Critical Point- nol solution were added to the sterilized mineral medium to Drier Smadri-PVT-3B apparatus. After drying, the samples -1 give phenol concentration between 125 -1000 mg L . were coated with gold and examined by the scanning electron microscope (Jeol JSM-3500), at the Faculty of Science, Biomass determination Alexandria University, Alexandria, Egypt. The bacterial growth was determined by measuring the optical density (O.D.) at 660 nm using Jenway UV-visible light spectrophotometer. The dry biomass was estimated by RESULTS centrifugation of 10 ml culture and the supernatants were discarded. The precipitated was washed twice with distilled Figure 1 shows the growth of Rhodococcus sp. DG and water and dried overnight at 80ºC. Cooling in a desiccator phenol concentration after different incubation periods un- and weighed. The calibration curves were done by plotting der shaked conditions at 120 rpm and 30 ºC. The initial phe- the dry weight against the optical density. nol concentration was 500 mg L-1. The lag-phase was observed at the beginning of the experiment. The growth in- Phenol determination creased with incubation time and reached it maximum after The phenol concentration in the supernatant was de- 60 h, then remains more or less in stationary phase. The termined quantitatively by a colorimetric method using 4- degradation of the phenol was increased with growth in- aminoantipyrine [21]. During reuse of the immobilized cells, creasing and reached the maximum value in the stationary the residual phenol was measured at 270 nm. phase.

The residual phenol in both methods was calculated from phenol standard curve prepared and measured as the 600 1

-1 ) -1 samples (mg L ). The degradation rate was then calculated ) 0,8 by dividing the amount of degraded phenol by the time 660 required for degradation. 400 0,6

phenol Effect of phosphate concentration 0,4 O.D This experiment was conducted using different phos- 200 0,2 Residual Residual phenol (mg L

phate concentrations, while the ratios between the two phos- (O.D. Optical density phate salts remain constant to keep the buffer capacity of -1 0 0 the medium. The following concentrations (g : g L ) of 0 24 48 72 96 120 144 Na2HPO4 : KH2PO4; 1 : 0.5; 2 : 1; 3 : 1.5; 4 : 2; 5 : 2.5; 6 : 3 Time (h) and 7 : 3.5 were used. FIGURE 1 - Effect of incubation time on growth and phenol degradation by free cells of Rhodococcus sp. DG Immobilization of bacterial cells Cell immobilization was done using different gel The effect of different nitrogen sources on phenol bio- materials (Na-alginate, Agar-Agar and K-carrageenan). degradation by the tested organism was evaluated. The Rhodococcus sp. DG was grown in mineral medium using ammonium chloride in the mineral medium was replaced 1% glucose as carbon source for 48 h. The culture was cen- with different nitrogen sources on equal nitrogen basis. trifuged under sterile conditions and the cells were taken The results obtained in Fig. 2 shows that nitrogen source in 0.9% saline solution at a concentration of 1.5 O.D. The could affect the biodegradation of phenol by Rhodococcus cells were mixed with 3% of the Na-alginate or K-carra- sp. DG. The highest degradation (95 and 93%) was ob- geenan, while Agar-Agar was prepared at 2%. In case of served after 72 h in presence of peptone and yeast extract alginate, 10 ml of the mixture was added drop-wise through respectively, followed by sodium nitrate and ammonium sterile syringe to a sterile 0.2 M CaCl2 solution, while the salts. The lowest degradation (25%) was obtained in pres- K-carrageenan-cells mixture was dropped in KCl solution. ence of urea as nitrogen source. The growth in presence of The beads were left to harden for 4h at 4ºC, then washed urea was also very low. Peptone was selected as the best several times with sterile water and added to 50 ml M-9 nitrogen source. In order to reduce the cost of the medium,

1659 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

different peptone concentrations were tested and the data L-1 had no effect on phenol degradation, while increasing revealed that 0.5 g L-1 gave the maximum phenol degra- glucose concentration up to 1 g L-1 decrease the degrada- dation rate (data not shown). tion rate. The cells completely degrade the phenol in absence of glucose in 144 h, whereas in presence of more -1 than 0.6 g L glucose, the time required was 168 h (Data 600 not shown). )

1 500 - 24h The inhibition of free cells of Rhodococcus sp. DG at

mgl 400 72h ( high concentration of phenol could be overcome by im- 300 mobilized cells. Different gel materials (sodium alginate, 200 Agar-Agar and K-carrageenan) have been used to immo- 100 bilize Rhodococcus sp. DG but it was well known that the phenol Residual 0 presence of high phosphate concentration in the mineral medium decrease the stability of the alginate beads. So the Urea Peptone phosphate concentration must be optimized to improve the Yeast extract Sodium nitrate Casamino acid beads stability and prevent its dissolution. Firstly, the effect Potassium nitrate Casein hydrolysate AmmoniumAmmonium chloride sulphate Nitrogen sources of phosphate concentration on phenol degradation by free cells of Rhodococcus sp. DG was tested. The results ob- FIGURE 2 - Effect of different nitrogen sources on tained proved that the use of low phosphate concentration phenol degradation by free cells of Rhodococcus sp. DG in the medium had no great effect on the phenol biodegradation by the tested organism. Therefore, phosphate The effect of phenol concentration on the degradation (Na2HPO4 : KH2PO4) at concentration of 1 : 0.5 was used rate by Rhodococcus sp. DG was tested in liquid medium in the following experiments. with phenol as the sole carbon source. Figure 3 show that The biodegradation of the phenol by immobilized cells the increase in phenol concentration increased the degra- in different gel materials was presented in Table 1. The re- dation rate until 750 mg L-1, and then decreased. The or- sults show that cells immobilized in alginate degrade phe- ganism could degrade the phenol completely after 72 h at nol at higher rate than cells immobilized in Agar-Agar or concentrations 125 and after 96 h at concentration 250 K-carrageenan. After 72 h, about 70% of the phenol was and 500 mg L-1. The degradation rate was found to be 1.7, degraded by alginate immobilized cells, in comparison with 2.6, 5.2, 5.4 and 4.4 mg L-1h-1 with initial concentration of -1 only 31% by the free cells (Fig. 3). After 120 h, about 98, 125, 250, 500, 750 and 1000 mg L respectively. It was -1 94 and 92% of 1000 mg L was degraded using sodium also observed that the lag phase increased with increasing alginate, Agar-Agar and K-carrageenan immobilized cells the initial phenol concentration and the organism reached respectively. It was also observed that high concentration its maximum growth after 24-72 h at phenol concentration of free cells (cell leakage) was observed in Agar-Agar and (125-750 mg L-1), while, it was reached after 144 h at K-carrageenan immobilized cells. Figure 4 shows SEM mi- phenol concentration 1000 mg L-1 (data not shown). crophotographs of the alginate beads. It can be observed that the cells propagated inside the beads in presence of 1000 mg -1 1200 L phenol and at the same time the morphology of the cells

125 mg L-1 was affected by the presence of the phenol. 1000 250 mg L-1 ) -1 500 mg L-1 Alginate concentrations affect the strength of the formed 800 750 mg L-1 beads and therefore reduce the cell leakage, which could 1000 mg L-1 be affect phenol degradation. Therefore, the effect of dif- 600 ferent alginate concentrations on phenol degradation was

400 tested. Fig. 5 show that there are no great differences between 1, 2 and 3% alginate on phenol degradation, but high Residual phenol Residual (mg L 200 cell leakage was observed at 1% (data not shown). Increas-

0 0 20 40 60 80 100 120 140 160 TABLE 1 - Phenol degradation by entrapped cells of Rhodococcus sp. DG in different gel materials. Time (h)

Gel materials Sodium Agar-Agar K-carrageenan FIGURE 3 - Degradation of different phenol (3%) alginate concentrations by free cells of Rhodococcus sp. DG. -1 a Time (h) Residual phenol (mg L ) In order to test the effect of simple metabolized carbon 24 825.2 846.4 868.5 source on phenol degradation, glucose at concentration 48 532.5 650.3 642.0 ranged from 0.1 – 1 g L-1 was supplemented to the medi- 72 298.7 419.9 433.9 -1 96 98.6 134.7 163.7 um with initial phenol concentration 750 mg L . The 120 23.4 62.1 76.0 results revealed that glucose concentration at 0.1 – 0.4 g a Initial phenol concentration = 1000 mg L-1

1660 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

tive effect on phenol degradation. It was also found that about 93% of the phenol was degraded in presence of 6 mg biomass in comparison with only 72% with 2 mg biomass after 72 h incubation. On the other hand, increasing the biomass concentration in case of free cells increased the phenol degradation with a maximum value 72% in presence of 10 mg biomass in comparison with 31% in presence of 2 mg biomass.

1000 )

-1 Free cells Immobilized cells 800

600

400

200 Residual phenol (mg L 0 1 2 3 4 5 Biomass concentration (ml 100 ml -1 medium)

FIGURE 6 - Degradation of phenol by free and immobilized cells of Rhodococcus sp. DG at different biomass concentration after 72 h incubation at 120 rpm and 30 ºC. The added volume of seed culture corresponding to 2, 4, 6, 8 and 10 mg dry weight.

Another advantage of immobilized cells is the ability of repeated use to reduce the down stream processing. The results presented in Table 2 show that immobilized cells of FIGURE 4 - SEM of Rhodococcus sp. DG immobilized in alginate Rhodococcus sp. DG could be reused ten times without beads. (a) at zero time, (b) after 48 and (c) 72 h incubation. losing its ability to degrade phenol. It was also observed that the ability of the cells to degrade phenol was increased by increasing the number of reuse. Maximum degradation rate 1200 -1 -1 1% (41.7 mg L h ) was obtained after six cycles with initial -1 1000 2% phenol concentration 1000 mg L , increasing the phenol 3% -1 800 concentration to 1500 mg L decreased the degradation 5% rate to 31.3 mg L-1h-1. After the ten times reuse, free cells 600 were observed in the medium due the partial dissolution of 400 the beads.

200

Residual phenol (mgResidual L-1) TABLE 2 - Reuse of alginate immobilized 0 Rhodococcus sp. DG for phenol degradation. 0 24 48 72 96 120 Cycle Initial phenol Timeb Phenol degradation Time (h) number concentration (h) rate (mgL-1) (mg L-1h-1) FIGURE 5 - Effect of sodium alginate concentra- 1 500 48 10.4 tions on phenol degradation by Rhodococcus sp. DG 2 500 24 20.8 3 750 24 31.3 4 750 24 31.3 ing the alginate concentration to 5%, reduced phenol deg- 5 750 24 31.3 radation. Alginate concentration at 2% was used in the sub- 6 1000 24 41.7 7 1000 24 41.7 sequent experiments. 8 1000 24 41.7 At 1000 mg L-1 initial phenol concentration, the effect 9 1500 48 31.3 10 1500 48 31.3 of biomass concentrations on phenol degradation by free Total 9250 312 31.3a and immobilized cells was investigated. In this experiment, b Time required for complete degradation of phenol the flasks were inoculated with 1, 2, 3, 4 and 5 ml seed cul- a Average degradation rate ture in form of free or alginate immobilized cells. Figure 6 show that increasing cell loading in immobilized cells great- The efficiency of Rhodococcus sp. DG immobilized ly increased phenol degradation up to 6 mg dry weight (3 ml cells to degrade phenol, cresol and catechol as shown by seed culture) and any further increase in biomass had nega- UV-visible Spectrophotometric analysis was presented in

1661 © by PSP Volume 16 – No 12b. 2007 Fresenius Environmental Bulletin

TABLE 3 - Degradation of different phenolic compounds by Rhodococcus sp. DG as measured by UV-visible spectrophotometer.

Before degradation After degradation Compound Wavelength Absorbance value Wavelength Absorbance value (nm) (nm) Phenol 268.4 3.47 433.4 0.08 251.9 3.56 257.9 2.00 216.8 3.80 215.9 3.77 213.5 3.79 212.6 3.78 Cresol 270.0 3.13 267.6 3.49 213.0 3.66 255.9 3.55 209.4 3.66 215.4 3.87 198.9 3.66 196.2 3.61 196.2 3.48 193.8 3.48 193.8 3.33 Catechol 268.8 3.52 253.5 2.59 226.5 3.65 205.8 3.98 214.2 3.90 201.3 3.96 201.6 3.77 198.9 3.92 198.6 3.73 196.2 3.78 196.2 3.65 193.8 3.69 193.8 3.55

Table 3. The results revealed the ability of the tested or- the unsuitability of urea for the growth of the tested organ- ganism to degrade different phenolic compounds at differ- ism. ent rates. It was found that the free cells of Rhodococcus sp. DG All experiments were done three times and the stand- was highly affected by initial phenol concentration. The ard deviation was between 3 and 20. results show that the higher is the concentration of the phenol, the more time it takes to be completely consumed. Maximum phenol degradation rate was obtained when DISCUSSION AND CONCLUSION 750 mg L-1 phenol was added to the medium. Increasing the phenol concentration above 750 mg L-1 required more This work aimed to study the ability of free and immo- incubation time and consequently reduced the degradation bilized cells of Rhodococcus sp. DG to degrade phenol. rate, this may be due to the inhibition of the growth with Firstly, the cultivation conditions of the free cells were op- high phenol concentration. timized, and then immobilized cells were used. The results In the present study, it was also observed that increas- obtained in this study revealed that maximum phenol deg- ing the phenol concentration increased the lag phase time. radation was obtained in the stationary growth phase after This result is in agreement with that reported by Kumar et 96 h. It was also observed that growth of the tested organ- al. [26] and Hill and Robinson [27] who observed a lag ism show a period of lag phase for 12 h. Kobayashi et -1 phase of as long as one week during degradation of 700 mg al. [22] reported complete degradation of 100 mg L by a L-1 using P. putida. On the other hand, Adav et al. [28] novel microorganism after 120 h and a lag phase of 50 h. isolated Acintobacter strain which were able to degrade From the tested nitrogen sources, peptone and yeast 500 mg L-1 phenol completely with no lag phase and with a extract gave the maximum degradation rate (6.6 and 6.5 mg lag time of 10-15 h when phenol concentration was in- L-1h-1). This may be due to the fact that the complex nitro- creased to 800-1000 mg L-1. gen sources improve the growth of the tested organism, In this work, the addition of glucose at a concentration which reduces the phenol toxicity. These results are in of more than 0.4 g L-1 delayed the degradation of phenol. agreement with that obtained by Lob and Tar [23] who This may because the organism utilized the simple carbon reported that the addition of yeast extract improve the phe- source first and then the phenol. The same explanation was nol degradation rate by Pseudomonas putida. On the other reported by Dursun and Tepe [29]. Lob and Tar [23] also hand, Khleifat [24] showed that yeast extract and casein reported that the degradation rate of phenol decreased with caused a repression in the phenol degradation by 3.3 and increasing glucose concentration and dropped below the 1.6 fold respectively. The degradation rate obtained in the degradation rate achieved in the absence of glucose. They present study showed that Rhodococcus sp. DG is better attributed that to the catabolite repression by glucose. Inhi- than Rhodococcus erythropolis M1, which degrade phenol bition of phenolic compound with glucose was also reported at a rate of 4.5 mg L-1h-1 [25]. In the present study, the use by other researchers [30,31]. of urea as nitrogen source gave the poorest growth, which cannot tolerate the phenol toxicity, and accordingly the Cell immobilization is a useful technique that would degradation rate was only 1.7 mg L-1h-1. This could be due allow for recycling of the biocatalyst and may have other

beneficial effects such as increasing the resistance of the REFERENCES entrapped cells to the toxicity of xenobiotic compounds [32]. The present study indicated that immobilized cells of [1] Watanabe, K., Hino, S. and Takahashi, N. (1996). Responses Rhodococcus sp. DG resulted in a better performance than of activated sludge to an increase in phenol loading. J. Ferment. Bioeng. 82: 522-524. free cells in the removal of phenol. Immobilized cells of the tested organism removed phenol by about 2.5 fold more [2] Annadurai, G., Babu, R.S., Mahesh, K.P. and Murugesan, T. than free cells and reduced the time required for degrada- (2000).Adsorption and biodegradation of phenol by chitosan tion. White and Thomas [33] showed that the immobilized immobilized Pseudomonas putida (NCIM 2174). Bioprocess cells of P. aeruginosa C12B were able to degrade sodium Eng. 2: 493–501. dodecyl sulfate three fold more than that of the free cells. Dursun and Tepe [29] reported that immobilized cells could [3] Bandhyopadhyay, K., Das, D., Bhattacharyya, P. and Maiti, B.R. (2001).Reaction engineering studies on biodegradation tolerate higher level of phenol concentration than free cells. of phenol by Pseudomonas putida MTCC 1194 immobilised In this study, alginate concentrations affected the phe- on calcium alginate. Biochem. Eng. J. 8: 179–186 nol degradation by the immobilized cells of Rhodococcus [4] Sheeja, R.Y. and Murugesan, T. (2002). Mass transfer studies sp. DG. It was found that lower alginate concentration de- on the biodegradation of phenols in up flow packed bed reac- creased the strength of the beads resulting in higher cell tors. J. Hazard. Mater. B 89: 287–301. leakage. On the other hand, high alginate concentrations induce the mass transfer limitation and affect the oxygen [5] Prpich, G.P. and Daugulis, A.J. (2005). Enhanced biodegra- diffusion, which reduce the degradation ability by immo- dation of phenol by a microbial consortium in a solid–liquid two phase partitioning bioreactor. Biodegradation 16: 329– bilized cells [34]. The results obtained in this work revealed 339. that increasing the biomass concentrations in immobilized cells above 6 mg dry weight decreased the phenol degra- [6] Van Schie, P.M. and Young, L.Y. (1998). Isolation and char- dation, which may be due to depletion of oxygen inside the acterization of phenol-degrading denitrifying bacteria. Appl. beads. Gosmann and Rehm [34] also reported that increas- Environ. Microbiol. 64: 2432-2438. ing biomass concentration in the gel affects oxygen uptake [7] Kobayashi, H. and Rittman, B.E. (1982).Microbial removal by the immobilized microbes. Mukerjee-Dhar et al. [32] ob- of hazardous organic compound. Environ. Sci. Technol. 19: served that the optimum immobilized cell biomass concen- 470A–481A. tration for the degradation of Kaneclor was 8 mg ml-1 and increasing the biomass concentration any further resulted [8] Vindo, A.V. and Reddy, G.V. (2003). Dynamic behaviour of in a decrease in the degradation. Dobreva et al. [35] reported a fluidised bed bioreactor treating waste water, Indian Chem. that high initial biomass concentration probably retarded Eng. A 45: 20–27. cell growth in the gel beads. [9] Lisa, D.S. and Andrew, J.D. (1997). Biodegradation of phe- The present study concluded that alginate immobi- nol at high initial concentrations in two phase partitioning lized cells is a good candidate for phenol degradation and batch and fed batch bioreactors. Biotechnol. Bioeng. 50: 156–162. can be reused for ten cycle with average degradation rate -1 -1 of 31.3 mg L h . It was reported that the immobilized cells [10] Balan, S.M., Annadurai, G., Sheeja, R.Y., Srinivasamoorthy, of Acinetobacter sp. could be reused five times for phenol V.R. and Murugesan, T. (1999).Modelling of phenol degra- removal [36]. Mukerjee-Dhar et al. [32] reported that algi- dation system using artificial neural networks. Bioprocess nate immobilized cells of Rhodococcus opacus strain Eng. 21:129–134. TSP203 could be used only once to degrade 100 µg ml-1 [11] Ryoo, D., Shim, H., Canada, K., Barberi, P. and Wood, T.K. of polychlorinated biphenyl. It was also observed that (2000). Aerobic degradation of tetrachloroethylene by tolu- Rhodococcus sp. DG could degrade other phenolic com- ene-o-monooxygenase of Pseudomonas stutzeri OX1. Natl. pound than phenol. Biotechnol. 18: 775–778.

[12] Chen, W.M., Chang, J.S., Wu, C.H. and Chang, S.C. (2004). Characterization of phenol and trichloroethane degradation by the rhizobium Ralstonia taiwanensis. Res. Microbiol. 155: ACKNOWLEDGMENTS 672–680.

The author gratefully acknowledge Prof. W. Spyra, [13] Indu, C. and Shashidhar, S. (2004). Microbial degradation of Technische Universitaet Cottbus, Germany, for providing phenol by a species of Alcaligenes isolated from a tropical Rhodococcus sp. DG, Dr. med. Habil. W. Baer and Dr. T Ju- soil. Soil Science 3: 47-51. retzek, Carl-Thiem-Klinikum, Cottbus, Germany, for help- [14] Larkin, M. J., Kulakov, L.A. and Allen, C.C.R. (2005). Bio- ing in the molecular identification of Rhodococcus sp. DG. degradation and Rhodococcus – masters of catabolic versa- tility. Current Opinion Biotechnol. 16: 282-290.

[15] Masque, C., Nolla, M., Bordons, A. (1987). Selection and adaptation of phenol-degrading strain of Pseudomonas. Bio- technol. Lett. 9: 655-60.

[16] Armenante, P., Fava, F., Kafkewitz, D. (1995). Effect of yeast [31] Satsangee, R. and Ghosh, P. (1990). Anaerobic degradation of extract on phenol degradation in pure and mixed cultures. Bio- phenol using an acclimated mixed culture. Appl. Microbiol. technol. Bioeng. 17: 1211-1. Biotechnol. 34: 127-130.

[17] Chung, T.S., Loh, K.C. and Goh, S.K. (1998). Development [32] Mukerjee-Dhar, G., Shimura, M. and Kimbara, K. (1998). of cellulose acetate membranes for bacteria immobilization to Degradation of polychlorinated biphenyl by cells of Rhodococ- remove phenol. J. Appl. Polym. Sci. 68:1677–1688. cus opacus TSP203 immobilized in alginate and in solution. Enzyme Microb. Technol. 23: 34-41. [18] Mardocco, A., Kue, C. and Jenkins, R. (1999). Continuous degradation of phenol at low concentration using immobilized [33] White, G.F. and Thomas, O.R.T. (1990). Immobilization of Pseudomonas putida. Enzyme Microb. Technol. 25: 530-536. surfactant degrading bacteria Pseudomonas C12B in poly- acrylamide gel beads: Effect of immobilization on primary and ultimate biodegradation SDS, and redistribution of bacte- [19] Godjevargova, T., Ivanova, D., Aleksieva, Z. and Dimova, N. ria within beads during use. Enzyme Microb. Technol. 12: (2003). Biodegradation of toxic organic components from in- 697-705. dustrial phenol production waste waters by free and immobilized Trichosporon cutaneum R57. Process Biochem. 38: [34] Gosmann, B. and Rhem, H.J. (1986). Oxygen uptake of mi- 915-920. croorganisms entrapped in Ca-alginate. Appl. Microbiol. Bio- technol. 23: 163-169. [20] Pazarlioglu, N. and Telefoncu, A. (2005). Biodegradation of phenol by Pseudomonas putida immobilized on activated [35] Dobreva, E., Ivanova, V., Tonkova, A. and Radulova, E. pumice particles. Process Biochem. 40: 1807-1814. (1996). Influence of the immobilization conditions on the efficiency of α- amylase production by Bacillus licheniformis. [21] Greenberg, A.E., Clesceri, L.S., Eaton, A.D. (1992). Phenols, Process Biochem. 31: 229-234. In: Standard Methods for the Examination of water and wastewater. (Greenberg, AE, Clesceri LS, Eaton AD, eds). [36] Abd-El-Haleem, D., Beshay, U., Abdelhamid, A.O., Moawad, American Public Health Assoc. Pub. Office. Washington H. and Zaki, S. (2003). Effects of mixed nitrogen sources on D.C. pp. 5-33. biodegradation of phenol by immobilized Acinetobacter sp. strain W-17. African J. Biotechnol. 2: 8-12. [22] Kobayashi, F., Daidai, M., Suzuki, N. and Nakamura, Y. (2007). Degradation of phenol in seawater using a novel microorganism isolated from the intestine of Aplysia kurodai. International Biodeterioration & Biodegradation, doi:10.1016/j.ibiod.2006.12.002.

[23] Lob, K.C. and Tar, P.P. (2000). Effect of additional carbon sources on biodegradation of phenol. Bull. Environ. Contam. Toxicol. 64: 756-763.

[24] Khleifat, K.M. (2006). Biodegradation of phenol by Ewingella americana: Effect of carbon starvation and some growth conditions. Process Biochem. 41: 2010-2016.

[25] Goswami, M., Shivaraman, N. and Singh, R.P. (2005). Micro- bial metabolism of 2-chlorophenol, phenol and p-cresol by Rhodococcus erythropolis M1 in coculture with Pseudomo- nas fluorescens P1. Microbiol. Res. 160: 101-109. Received: May 29, 2007 Revised: July 21, 2007 [26] Kumar, A., Kumar, S. and Kumar, S. (2005). Biodegrada- Accepted: September 21, 2007 tion kinetics of phenol and catechol using Pseudomonas putida MTCC 1194. Biochem. Eng. J. 22: 151-159.

CORRESPONDING AUTHOR [27] Hill, G.A. and Robinson, C.W. (1975). Substrate inhibition kinetics: Phenol degradation by Pseudomonas putida. Bio- technol. Bioeng. 17: 1599-1615. Mona K. Gouda Botany Department [28] Adav, S.S., Chen, M-Y., Lee, D-J., Ren, N-Q. (2007). Deg- Faculty of Science radation of phenol by Acinetobacter strain isolated from aer- Alexandria University obic granules. Chemosphere 67: 1566-1572. 21511 Moharram Bey, Alexandria EGYPT [29] Dursun, A.Y. and Tepe, O. (2005). Internal mass transfer effect on biodegradation of phenol by Ca-alginate immobilized Ralstonia eutropha. J. Hazardous Mat. B126: 105-111. Phone: +2034977048 Fax: +2033911794 [30] Papanastasiou, A.C. (1982). Kinetics of biodegradation of E-mail: [email protected] 2,4- Dichlorophenoxyacetate in the presence of glucose. Bio- technol. Bioeng. 24: 2001-2011. FEB/ Vol 16/ No 12b/ 2007 – pages 1655 – 1661

PCDDs, PCDFs AND DL-PCBs IN SOME SELECTED ESTONIAN AND IMPORTED FOOD SAMPLES

Ott Roots¹ ²*

¹Estonian Environmental Research Centre, Marja 4D, 10 617 Tallinn, Estonia ²Estonian Marine Institute, University of Tartu, Mäealuse 10a, 12618 Tallinn, Estonia

SUMMARY Na- tional authorities have the responsibility and obligation to- The main source of human exposure to polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs) and dioxin-like polychlorinated biphenyls ensure that toxic chemicals, such as pesticides, heavy met- (DL-PCBs) is food. The contamination of food by poten- als, environmental contaminants and natural occurring tox- tially hazardous substances is a worldwide public health ins, are not present in food at levels that may adversely concern. Environmentally hazardous substances are acutely affect the health of consumers. A hazardous substance is an toxic, persistent and bioaccumulative (i.e. they become con- element or a compound, which through its toxicity, stabil- centrated in the food chains to reach toxic levels). For this ity or bioaccumulation, poses or may pose a threat to hu- reason, emission quantities do not have to be very great be- man health and impairs or may impair other living organ- fore the initial effects of accumulations can be seen. The ob- isms or ecosystems. The amount of chemicals on the mar- jective of this article is to harmonise and integrate the activ- ket is enormous and even at this moment it is extremely ities of the New European Union (EU) Member State - difficult to get an overview of their actual quantity. It is Estonia in the field of chemical food safety with those of assumed that as many as ten million chemicals are known the Old Member States. This study reports polychlorinated to researchers, whereby several hundred thousand of them dibenzo-p-dioxins, polychlorinated dibenzofurans and DL- are in everyday use. We can get an impression of how com- PCBs in Estonian food: milk, butter, pork and imported plicated it really is to have a control over such a multitude fish oil, for the first time. All studied pork, butter, milk and of chemicals. At the same time it is evident that we are not imported fish oil samples had WHO-PCDD/F-TEQ and also able to manage without using chemicals in the modern socie- combined WHO-PCDD/F-PCB-TEQ upper bound values ty of today [1, 3]. A mission of the world in the immediate below the maximum limits set in Council Regulation (EC) future is to reduce the emission quantities of hazardous con- No 2375/2001 and Council Regulation (EC) No199/2006. taminants that are discarded into the surrounding environment as well as their concentration in the air, water, ground

and food alike and at the same time bring down the con- KEYWORDS: Estonia, Baltic Sea, polychlorinated dibenzo-p- tent of toxicants in our surrounding environment to the level dioxins, polychlorinated dibenzofurans , DL-PCB, Estonian food, harmless to human health [7]. The health significance of hu- meat, butter, milk, imported fish oil. man exposure to dioxins (polychlorinated dibenzo-p- dioxins, PCDDs), furans (polychlorinated dibenzofurans, PCDFs) and dioxin-like polychlorinated biphenyls (DL- INTRODUCTION PCBs) has been the subject of extensive discussion [1, 7]. Several persistent organic pollutants, like dioxins and fu- The main reason for analysing toxic compounds origi- rans, have never been used as chemicals and for that rea- nating from our surroundings (including food) is the need to son it is no wonder that they have been „discovered rela- determine how dangerous they are to people and to their tively late“ in the nature. Only a few people are aware of the living environment [1-6]. Persistent organic pollutants (po- fact that the group of dioxins for one comprises 75 “dif- lychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated ferent chemicals” (isomers) and the number of known fu- dibenzofurans (PCDFs) and “dioxin-like PCBs” (DL-PCBs) rans amounts to 135. 17 of the compounds are toxic and one are a group of toxic persistent chemicals whose effect on compound is yielding to the genesis of cancer. The num- human health and on the environment include dermal tox- ber of the isomers of polychlorinated biphenyls is by one icity, immunotoxicity, reproductive effects and teratogen- item less than that of the dioxins/furans, notably 209, of icity, endocrine disrupting effects and carcinogenicity. which 12 are dioxin-like toxic isomers. Environmental pollution with persistent organic pollutants will bring along a

series of human health disorders, including allergy and in- (PCB 80, 101, 105, 118, 138, 153, 156, 157, 170, 180, fertility, wield carcinogenic effect and may appear as the 194, and 209), and 4 ¹³C-labelled co-planar (co-PCB) con- cause of untimely death. The aim of this study is to de- geners (PCB 77, 81, 126, and 169) were used as internal termine the contents of dioxins, in food products, practi- standards for PCBs and DL-PCBs. cally for the first time in the milk, butter, meat of different PCDD/PCDFs and PCBs were analysed by high reso- regions in Estonia and imported fish oil. lution gas chromatography-high resolution mass spectrome-

try (Hewlett-Packard 6890-VG 70-250SE) using selective

ion recording (resolution 10,000). Both PCDD/PCDF and MATERIALS AND METHODS PCB congeners were separated on a DB-Dioxin capillary column (J&W Scientific: 60 m, 0.25 mm, 0.15 µm). The When collecting food product samples, European Un- method is accreditated (Testing laboratory T077 by FINAS; ion legislation was followed: Commission recommendation http://www.finas.fi). Limits of quantification (LOQ) for 2004/705/EC, on the monitoring of background levels of PCDD/ PCDFs, DL-PCBs, and other PCBs varied between dioxins and dioxin-like PCBs in foodstuffs; Commission 0.0007 and 0.63, 0.0007 and 0.13, and 0.035 and 13 pg/g directive 2002/69/EC, laying down the sampling methods fresh weight (fw), respectively, depending on each individ- and methods of analysis for the official control of dioxins ual congener and on the individual food stuff [8-10]. Re- and the determination of dioxin-like PCBs in foodstuffs. sults were calculated as upper bound, medium bound and Leaving aside fish, dioxins in Estonian food products have lower bound values per gram fresh and lipid weight. previously only been detected in two butter samples taken in 2002-2003, during research arranged by the Institute for Health and Consumer Protection located in Italy [2]. Eight RESULTS AND DISCUSSION countries (Cyprus, Czech Republic, Estonia, Lithuania, Po- land, Romania, Slovenia and Slovakia) sent two butter sam- In 2006 the dioxin content of dairy products (milk and ples each between December 2002 and March 2003 to the butter), meat, imported fish oil had been examined. A total Joint Research Centre of the European Union (EU) in Italy of 11 samples were analysed. For milk and dairy products, for analysis. The butter samples had been bought in ordinary three samples of raw milk and two samples of butter were stores. All eight countries butter samples persistent organic taken, which were collected directly from either a place of pollutant levels were below the European Union (EU) production, from a corresponding farm or dairy industry. In maximum tolerances and EU action levels for PCDD/F [2]. the case of meat, pork samples collected from three slaugh- The chemical analysis of samples ordered from the ac- ter houses were analysed. Imported fish oil products (in credited laboratory in Finland (National Public Health Insti- capsule form) from the Russian company “BioKontur” and tute, Department of Environmental Health, Laboratory of the Norwegian company “Peter Möller” were analysed. Chemistry, Neulaniementie 4, FI-70 210 Kuopio, Finland). Thanks to the assistance of the Ministry of Agriculture The determination of PCDD/PCDFs, DL-PCBs, and other it has been possible for the moment to study persistent or- PCBs was done according to standard operation procedure ganic pollutants in the Estonian food. The dioxin content in the laboratory of Chemistry in the National Public Health in fish has been fairly exhaustively studied in Estonia [11- Institute (KTL) (SOP called “Determination of PCDD/ 16]. All studied Baltic Sea wild fish herring, sprat, perch, PCDFs, PCBs, DL-PCBs, and other POPs in tissue samples, eel, pikeperch, flounder and aquaculture rainbow trout, KEM MO3”). The method is in part described in a previ- eel samples had WHO-PCDD/F-TEQ and also combined ously published paper [8-10]. WHO- PCDD/F-PCB-TEQ upperbound values below the Analytes were extracted in a 33 mL stainless steel ex- maximum limits set in Council Regulation (EC) No 2375/ traction cells from freeze dried sample with an ASE 300 2001 and Council Regulation (EC) No199/2006. Accelerated Solvent Extractor (Dionex Sunnyvale, Cali- Milk and butter. It may be useful to use butter as an fornia). Extraction solvent was 50% acetone-hexane using indicator matrix for contamination of persistent organic 3x5 min extraction cycles, 120°temperature, 1500 psi pres- pollutants. Compounds analysed in the two butter samples sure and 80% flush volume. Solvent was evaporated and collected in 2006 are almost below the PCDD/F detection fat % was determined gravimetrically. Fat was decomposed limits. Exceeding the decision limit in sample 1 are five with ASE from the sample in a 100 mL stainless steel clean- PCDF compounds and in sample 2 only one PCDF com- up extraction cells filled with sulphuric acid impregnated pound - 2,3,4,7,8-PeCDF. Therefore, there the upper and silica gel. Hexane was the clean-up extraction solvent using lower bound for the results differs significantly (Table 1). 5x1 min extraction cycles, 40°C temperature, 1500 psi pres- Based upon concentration, the dominant PCDD/F com- sure and 100% flush volume. After the fat removal sample pounds in sample are 1,2,3,4,7,8-HxCDF (30%) and was fractionated and further purified on carbon and acti- 2,3,4,7,8-PeCDF (28%), however, based on toxicity vated alumina columns as described earlier [8-10]. 2,3,4,7,8-PeCDF (69%) is dominant. Thus, based on both Internal ¹³C PCDD/PCDF standards (altogether 16 stan- concentration and toxicity PCDD/F compound PCDF is dards) were used to quantitate the concentrations of PCDDs/ dominant in both butter samples (Table 1). In all three of PCDFs. ¹²C PCB 30 and 12 ¹³C-labelled PCB congeners the 2006 milk samples, four PCDF compounds - 2,3,4,7,8-

PeCDF and three HxCDF exceed the detection limit. In Pork. In the three analysed pork samples, most of the addition to these, sample 2 includes one PCDD (OCDD) and PCDD/F compounds are below the detection limit. In ex- in sample 3 - 1,2,3,7,8-PeCDF and two PCDD (1,2,3,6,7,8- cess of the decision limit in samples 1 and 2 are one HxCDD and 2,3,7,8-TCDD). The difference between the PCDD (OCDD) and four PCDF compounds (2,3,7,8-TCDF, upper and lower limit results is nearly three fold (Table 2). 1,2,3,4,7,8-HxCDF, 1,2,3,4,6,7,8-HpCDF and OCDF), but Dominant in the analysed milk samples, based on both in sample 3 only one PCDD/F compound - OCDD. With toxicity as well as concentration is 2,3,4,7,8-PeCDF (re- this result, the difference between the upper and lower spectively 67% and 34%), while based on concentration bound based on concentration is nearly double, while based are the following three HxCDF compounds (respectively on toxicity it is several times higher (Table 3). Based on 15%, 14% and 14%). Thus, based on both concentration concentration, the PCDD/F compound dominant in sample 2 and toxicity, PCDF content is higher in milk than that of is OCDF (38%), but in the two remaining samples it is PCDD (Table 2). Based on toxicity, the relative im- OCDD (88% and 100%). Based on toxicity, the only com- portance of PCDD/F increases, however, the content of pound higher than the detection limit in sample 3 is OCDD, di-oxin-like PCB compounds is still higher (65% and while in the two remaining samples it was 1,2,3,4,7,8- 35%). In the case of milk, the large difference between HxCDF (68% and 49%) and 2,3,7,8-TCDF (23% and 44%). samples should be noted: based on toxicity the difference Based on toxicity, the dominant PCDD/F compound was between the highest (sample 3) and lowest (sample 2) val- PCDF (nearly 70%; Table 3). Based on concentration (Ta- ues in terms of PCDD/F is 3 times, and in the case of ble 3), DL-PCBs are overwhelmingly dominant in pork dioxin-like PCBs 14 times. In butter and milk samples, the samples (totaling an average of 99%), however, based on combined content of PCDD/F as well as that of sum of toxicity the relative importance of PCDD/F is higher than dioxins (PCDD/ Fs+DL-PCBs) is significantly lower that of DL-PCB compounds (respectively 83% and 17%). than the established limits (respectively 3.0 and 6.0 pg In all pork samples the summary content of PCDD/F as WHO-TEQ/g fat). Results in terms of PCDD/F – 0.2 to well as combined dioxins (PCDD/Fs+DL-PCBs) is lower 0.3 (in one milk sample 0.8) pg I-TEQ/g fat is comparable than the established limits (respectively 1.0 and 1.5 pg to data from other European states (as a rule between 0.3 - WHO-TEQ/g fat). Our results, as far as PCDD/F is con- 2.1 pg I-TEQ/g fat). The same applies for DL-PCB com- cerned (0.15 to 0.29 pg I-TEQ/g fat), are also comparable pounds – our results for butter and the two milk samples with the data from other European countries (as a rule below was 0.2 to 0.4, with the European average being 0.2 - 0.4 pg I-TEQ/g fat). The dioxin content of pork (based on 1.8 WHO-TEQ/g for fat. The DL-PCB content was higher in one milk sample 3 – 2.17 WHO-TEQ/g fat [4-6].

TABLE 1 - Content of PCDD/F and dioxin-like PCB compounds in 2006 in Estonian butter samples [17].

Compound/unit 1 2 pg/g for fat PCDD/F Lower bound 0.457 0.095 Medium bound 0.945 0.989 Upper bound 1.433 1.882 DL-PCB Lower bound 1489 1137 Medium bound 1499 1155 Upper bound 1508 1174 pg WHO- TEQ /g for fat PCDD/F Lower bound 0.093 0.048 Medium bound 0.176 0.176 Upper bound 0.260 0.304 DL-PCB Lower bound 0.445 0.390 Medium bound 0.446 0.391 Upper bound 0.447 0.392

TABLE 2 - Content of PCDD/F and dioxin-like PCB compounds in 2006 milk samples [17].

Compound/unit 1 2 3 pg/g for fat PCDD/F Lower bound 0.573 0.765 1.952 Medium bound 1.302 1.348 2.643 Upper bound 2.030 1.931 3.333 DL-PCB Lower bound 954 386 3877 Medium bound 958 392 3879 Upper bound 962 399 3882 pg WHO-TEQ/ g for fat PCDD/F Lower bound 0.135 0.084 0.615 Medium bound 0.258 0.175 0.706 Upper bound 0.381 0.267 0.797

DL-PCB Lower bound 0.356 0.158 2.167 Medium bound 0.356 0.159 2.167 Upper bound 0.357 0.159 2.167 TABLE 3 - Content of PCDD/F and dioxin-like PCB compounds in 2006 pork samples [17].

Compound/unit 1 2 3 pg/g for fat PCDD/F Lower bound 1.046 0.492 1.810 Medium bound 1.504 0.878 2.613 Upper bound 1.962 1.264 3.415 DL-PCB Lower bound 203 299 174 Medium bound 214 308 187 Upper bound 224 317 199 pg WHO-TEQ/ g for fat PCDD/F Lower bound 0.008 0.018 0.000 Medium bound 0.116 0.097 0.176 Upper bound 0.225 0.176 0.352 DL-PCB Lower bound 0.042 0.063 0.024 Medium bound 0.045 0.066 0.031 Upper bound 0.049 0.068 0.038

TABLE 4 - Content of PCDD/F and dioxin-like PCB compounds in 2006 fish oil samples [17].

Compound/unit 1 2 3 pg/g for fat PCDD/F Lower bound 2.605 9.548 8.550 Medium bound 2.974 9.696 8.736 Upper bound 3.342 9.843 8.922 DL-PCB Lower bound 124 10753 12689 Medium bound 172 10753 12689 Upper bound 220 10753 12689 pg WHO-TEQ/ g for fat PCDD/F Lower bound 0.007 2.079 1.798 Medium bound 0.119 2.091 1.804 Upper bound 0.230 2.103 1.810 DL-PCB Lower bound 0.121 4.022 4.077 Medium bound 0.126 4.022 4.077 Upper bound 0.131 4.022 4.077

fat) is, as a rule, lower than that of beef or poultry. There- (43%) and CB-126 (62%) are dominant. Of the PCDD/F fore, the continued analysis of dioxins in pork, in addition compounds, PCDD is in excess in both concentration to other meat products, is critical. and toxicity in sample 1, while in samples 2 and 3 PCDF is in excess (Table 4). In the case of DL-PCBs, mono- Imported fish oil. Dioxin content is determined by ortho PCB concentration is significantly higher than three fish oil samples, whereas sample 1 (Norway, Peter non-orto PCB in all samples. As opposed to toxicity, non- Möller) is clearly distinguished from samples 2 and 3 (Rus- orto PCB is in excess. In both concentration as well as sia, “BioKontur”). In sample 1, two PCDD (1,2,3,4,6,7,8- toxicity PCDD/F content, as a rule, is lower than DL-PCB HpCDD, OCDD) and three PCDF compounds (2,3,7,8- content. Only in sample 1, based on the upper bound and TCDF, 1,2,3,4,6,7,8-HpCDF and OCDF) were over the de- average data, is the PCDD/F content higher than the diox- tection limit. Based on concentration OCDD (77%) is dom- in-like PCB content (Table 4). The dioxin content in sam- inant, while based on toxicity 2,3,7,8-TCDF (59%) is dom- ples 1 and 3 of fish oil were lower than the established inant. DL-PCB compounds CB-77, CB-81, CB-114 and limits for PCDD/F and combined content of dioxins CB-118 are below the detection limit. Based on concen- (PCDD/Fs+DL-PCBs)(respectively 2.0 and 10.0 pg WHO- tration, CB-156 (40%) was dominant in fish oil sample 1, TEQ/g fat). In sample 2, the summary dioxin content was and based on toxicity CB-126 (65%) was dominant. Differ- below the established limits, although PCDD/F content ences in the upper and lower bound results are critical (upper limit 2.103 pg WHO-TEQ/g fat) was above the (nearly 30 times) in the case of PCDD/F toxicity (Table 4). norm. In samples 2 and 3, one PCDD and two PCDF compounds are below the detection limit. All DL-PCB compounds exceed the de-tection limit in both samples. CONCLUSION Therefore, the difference between the upper and lower bound is practically non-existent (Table 4). Based on con- This study reports PCDD/Fs and DL-PCBs in Estonian centration 2,3,7,8-TCDF (50%) and CB-118 (64%) are food: milk, butter, pork and imported fish oil, for the first dominant, while based on toxicity 2,3,4,7,8-PeCDF time. In the case of milk and butter, the content of dioxins

is, as a rule, 10 times lower than the limit. An exception was [6] Weiss, J., Päpke, O. and Bergman, A. (2005). PCDDs, PCDFs one milk sample, whose content of dioxins was significantly and related conta-minants in butter originating from 39 countries world wide. AMBIO. 34, No. 8: 589-597. higher than the average of the other samples – PCDD/F was nearly double, DL-PCB compounds were eight times [7] Fiedler, H. (2007). National PCDD/PCDF release inventories higher. It can be concluded that the DL-PCB compounds under the Stockholm Convention on Persistent Organic Pol- are not a problem in Estonian milk and butter, but, it is nec- lutants. Chemosphere, 67:S96-S108. essary to continue analysing them. The content of dioxins [8] Kiviranta, H., Ovaskainen, M-L. and Vartiainen, T. (2004). in pork is comparable with the results from the rest of the Market basket study on dietary intake of PCDD/Fs, PCBs, and countries in Europe, and on average is five times lower PBDEs in Finland. Environment International, 30:923-932. than the established limit. The content of dioxins in pork is generally lower than in other meat products, therefore in [9] Isosaari, P., Hallikainen, A., Kiviranta, H., Vuorinen, P.J., Parmanne, R., Koistinen, J. and Vartiainen, T. (2006). Poly- 2007 attention should be focused on beef and poultry analy- chlorinated dibenzo-p-dioxins, dibenzofurans, biphenyls, naph- sis. The content of dioxins in fish oil (Omega-3; sample 1) thalenes and polybrominated diphenyl ethers in the edible fish originating in Norway is lower, by nearly an order of mag- caught from the Baltic Sea and lakes in Finland. Environmental nitude, than the established limit. Fish oil originating from Pollution, 141: 213-225. Russia (“BioKontur”, samples 2 and 3) have a combined [10] Parmanne, R., Hallikainen, A., Isosaari, P., Kiviranta, H., content of dioxins two times lower than the established Koistinen, J., Laine, O., Rantakokko, P., Vuorinen, P.J. and limits, although PCDD/F content in sample 3 (1.81 pg Vartianen, T. (2006). The dependence of organohalogen com- WHO-TEQ/g fat) is near the corresponding established pounds concentrations on herring age and size in the Bothnian Sea, northern Baltic. Marine Pollution Bulletin, 52: 149-161. limit and sample 2 (2.10 pg WHO-TEQ/g fat) actually ex- ceeds the established limit. It can be concluded that it will [11] Roots, O., Lahne, R., Simm, M. and Schramm, K-W. (2003). continue to be necessary in the future to control the share Dioxins in the Baltic herring and sprat in Estonian coastal of dioxin in imported products. waters. Organohalogen Compounds, 62: 201-203. [12] Roots, O., Schramm, K.-W., Simm, M., Henkelmann, B. and Lankov, A. (2006). Polychlorinated dibenzo-p-dioxins and dibenzofurans in Baltic herring and sprat in the north-eastern ACKNOWLEDGEMENT part of the Baltic Sea. Proceedings of the Estonian Academy of Sciences, Biology, Ecology, 55: 51 - 60.

This project was financially supported by the Ministry [13] Roots, O. and Zitko, V. (2004). Chlorinated dibenzo-p-dioxins of Agriculture of Estonia and by the Chemical Food Safety and dibenzofu-rans in the Baltic herring and sprat of Estonian Network for the enlarging Europe - SAFEFOODNET Pro- coastal waters. Environmental Science & Pollution Research, 11:186-193. ject. Sixth Framework Programme. Priority 5. Food Quality and Safety (Contract No. 513988). [14] Roots, O. and Zitko, V. (2006). The effect of age on the concentration of polychlorinated dibenzo-p-dioxins, dibenzofurans and dioxin-like polychlori-nated biphenyls in the Baltic herring and sprat. Fresenius Environmental Bulletin, 15:207-219.

REFERENCES [15] Pandelova, M., Henkelmann, B., Roots, O., Simm, M., Benfenati, E. and Schramm, K.-W. (2006). Levels of [1] Dioxins (2004). Methodologies and principles for setting tol- PCDD/F in Baltic fish in different age groups, Organohalo- erable intake levels for dioxins, furans and dioxin-like PCBs. gen Compounds, 68:1932 – 1934. EFSA Scientific Colloquium Summary Report, Brussels, Bel- gium, 1-130. [16] Simm, M., Roots, O., Kotta, J., Lankov, A., Henkelmann, B., Shen, H. and Schramm, K-W. (2006). PCDD/Fs in sprat (Sprattus sprattus (L.) from the Gulf of Finland, the Baltic [2] Malisch, R. and Dilara, P. (2004). PCDD/Fs and PCBs butter Sea. Chemosphere, 65, issue 9:1570-1575. samples from new European Union member states and candidate countries. Organohalogen Compounds, 66:2080-2084. [17] Roots, O. and Simm, M.(2006). Dioksiini seire toidus 2006. aastal (in Estonian). (http://www.agri.ee/index.php/14298). [3] Roots, O. (2006). Persistent Organic Pollutants in our Envi- ronment. Ministry of the Environment and Estonian Envi- ronmental Research Centre, Tallinn, Paar, 27p.

[4] Santillo, D., Fernandes, A., Stringer, R., Johnston, P., Rose, M. and White, S. (2001). Concentrations of PCDDs, PCDFs and PCBs in samples of butter from 24 countries. Organochlorine compounds, 51:275 – 278. Received: June 28, 2007 [5] Weiss, J., Päpke, O. and Bergman, A. (2001). PCDDs, PCDFs Accepted: September 19, 2007 and related conta-minants in butter originating from 39 countries world wide. Organochlorine compounds, 51:271 –274.

CORRESPONDING AUTHOR Phone:+372-611-2964 Ott Roots Fax:+372-611-2901 Estonian Environmental Research Centre E-mail: [email protected] Marja 4D 10 617 Tallinn FEB/ Vol 16/ No 12b/ 2007 – pages 1662 – 1666 ESTONIA EFFECTS OF EXTERNAL POLYAMINES ON DNA UNDER THE HIGHEST COPPER TOXICITY IN Ulva lactuca L. AND GENOTOXICITY DETECTION BY RAPD-PCR ASSAY

Inci Tuney*, Dilek Unal and Atakan Sukatar

Ege University, Faculty of Science, Department of Biology, Hydrobiology Section, 35100 Bornova, Izmir, Turkey

SUMMARY mobile of the heavy metals in surface environments [4]. Copper is bound, or adsorbed, to organic materials, and to Copper is essential to living organisms, but at elevated clay and mineral surfaces. Because of its high water solu- concentrations, copper may become toxic for living sys- bility, excessive amounts of copper sulfate should be kept tems. During this research the effects of copper were evalu- out of lakes, streams and ponds. Water can be contaminated ated at molecular levels in a marine green algae Ulva lactu- by inappropriate cleaning of application equipment, or dis- ca. In addition, the protection role of polyamines against posal of waste associated with this material. DNA mutations and strand breaks against the copper treatment searched by RAPD-PCR analysis. The main changes observed in the RADP profiles have been resulted both in Although copper is essential for living systems, because appearance or disappearance of different bands and varia- of its role in electron transport system, respiration, growth, tion of their intensity. etc., many studies have also reported that copper induces

toxicity [5]. For instance, the binding of copper to DNA

bases unwinds the double helix [6] and DNA damage can

be generated. Also in another study it was shown that the KEY WORDS: Polyamines, RAPD, copper, Ulva lactuca. binding of copper to DNA is necessary for the generation of double- strand breaks, 8- hydrodeoxyguanosine and intrastrand crosslinks in Fenton reactions [7]. Plant cells can be protected against the oxidative dam- INTRODUCTION age by a broad spectrum of radical-scavenger systems including antioxidant enzymes and a number of biologically A number of metals are essential micronutrients for active substances that may prevent the free radical induced marine algae but at elevated concentrations, including cop- cellular damage [8]. To date, polyamines (PA) have been per, they may become toxic by enhancing the production reported as efficient antioxidants in many experimental of reactive oxygen species (ROS) [1]. Higher levels of ROS systems and various kind of environmental stresses [9]. In may cause oxidative damage manifested as protein oxida- addition, the biological activity of PAs is attributed to the tion and inactivation, lipid peroxidation, membrane dam- cationic nature of these molecules. Interactions of PAs with age, DNA damage, increased mutational rates, metabolic the phosphate groups of DNA, with anionic components of perturbation and death, cumulatively depicted as oxidative phospholipids and with cell wall components, such as pec- stress [2, 3]. tic polysaccarides, have been reported. Furthermore, PA Copper sulfate is washed down to lower soil levels by protects DNA damage by neutralizing charge and confor- water percolating through the ground, bound to soil com- mational changes of DNA [10]. However, the PA role in the ponents and changed into different metabolites, or break- protection systems still remains unclear. down products. Copper is considered to be among the more

The understanding of the biochemical and physiologi- tion rate under copper stress in Ulva lactuca. To test the cal mechanisms that make plants tolerant or sensitive to above hypothesis, we employed molecular techniques and heavy metals is very important for the application of the from our findings it seems that copper stress indeed causes cited plant-based technologies. Furthermore, over the past damages to DNA and the damages caused to DNA could be decade, several molecular techniques have been developed conveniently and rapidly assessed by RAPD-PCR tech- to provide information on diversity, genotoxicology, genetic nique. relationships etc. One of the methods that used for these aims is RAPD-PCR (Random Amplified Polymorphic MATERIALS AND METHODS DNA-Polymerase Chain Reaction). The RAPD procedures were first developed in 1990 [11, 12] using PCR to amplify Material anonymous segments of nuclear DNA with identical pri- Ulva lactuca samples were collected from Izmir Bay mers which are 10 bp length. Genetic variation and diver- and kept in ice during transportation to the laboratory. After gence within and between the taxa of interest are assessed cleaning with sterile distilled water the thallus was divided by the presence or absence of each product. RAPD poly- into 5 pieces. morphisms can occur due to base substitutions at the primer binding site sor to indels in the regions between the The test solutions were prepared just before the ex- sites. The RAPD primers are commercially available and periment. Samples were incubated for two hours in solu- do not require prior knowledge of the target DNA se- tions of CuSO4 (30 mM) and compared with control sam- quence. RAPD markers have been used for species identi- ples soaked in sea water medium. In a separate trial, thalli fication, analysis of population structure, analysis of genetic were treated with CuSO4 30 mM and polyamines putres- impacts of environmental stress and analysis of genetic cine, spermidine and spermine (1 mM) for 2h., respec- diversity. tively (Figure 1). The light density measured by luxmeter and reported as 210 lux at 20 ºC. The main purpose of this research is to investigate whether the protective role of polyamines on DNA muta-

FIGURE 1

1) Ulva lactuca thallus in sea water medium with CuSO4,, 2) Ulva lactuca thallus in sea water medium with CuSO4 and putrescine, 3) Ulva lactuca thallus in sea water medium with CuSO4 and spermidine, 4) Ulva lactuca thallus in sea water medium with CuSO4 and spermine.

Isolation of DNA Amplification of genomic DNA was performed in 50 µl After incubation DNA isolated from Ulva lactuca reaction mixture containing 18.5 Mili Q water, 1.75 µl of samples by CTAB method [13]. 10 x Taq polymerase buffer, 1.2 µl of MgCl2, 1.5 µl of dNTPs, 0.6 µl of primer and 0.6 µl of Taq DNA polymerase RAPD-PCR before adding DNA.

RAPD-PCR was performed by 10 different RAPD ance of some bands may correlate with level of photo- primers (Table 1) after checking the DNAs by agarose gel products in DNA template and DNA structural changes electrophoresis. PCR bands were checked again by agarose such as deletions, insertions or breaks after copper treat- gel electrophoresis after PCR analysis. The PCR analysis ment as genotoxic agent. performed three times as control. As seen in Figure 2a and 2b there are band differences, and variations among band patterns between U. lac- TABLE 1 RAPD primers used for PCR amplification. tuca DNAs treated by sea water medium, sea water medium with CuSO4 and polyamines or without. Primer number 1, Primer 1 5’-TGC GCC CTT C-3’ 2, 4, 8, 9 and 10 amplified the U. lactuca DNAs by PCR Primer 2 5’-GGT GAC GCA G-3’ amplification. Primer 3 5’-TCC GCT CTG G-3’ Primer 4 5’-CCT TGA CGC A-3’ We got only one band after amplifying the untreated Primer 5 5’-GTA GAC CCG T-3’ sample with Primer number 1 (Figure 2a, lane 1) also we Primer 6 5’-GTC CAC ACG G-3’ had the same band with CuSO4 and spermidine treated Primer 7 5’-TGC GCC CTT C-3’ sample but we had two bands with CuSO and spermine Primer 8 5’-GGG TAA CGC C-3’ 4 Primer 9 5’-TCG TCA CCC C-3’ treated sample (Figure 2a, lane 3). There are no bands with Primer 10 5’-GTT TCG CTC C-3’ CuSO4 treated and CuSO4 and putrescine treated samples Amplification done in ABI Prisim 9700 Thermal Cy- amplified by primer number one. cler with 5 cycles; denaturation at 94oC for 1 minute, annealing at 40 oC for 30 seconds and extension at 72 oC for 1 minute, 40 cycles; denaturation at 94oC for 45 seconds, annealing at 60 oC for 1 minute and extension at 72 oC for 45 seconds, final extension at 72 oC for 11 minutes. The amplified product kept in 4oC until gel electrophoresis. 9 µl of each PCR product was electrophoresed on 1.2% agarose gel in TAE buffer (40 mM Tris acetate, 1 mM EDTA, pH 8.0) at 80 V for 1 hour. The gel was stained with ethidium bromide and photographed.

RESULTS AND DISCUSSION

In the case of ROS generated by transition metals, most of the studies about the influence of polyamines on DNA damage have been based on the effect that produces on DNA strand breakage. Pedreňo et al. [14] found that at higher metal concentrations spermine stimulated DNA damage by increasing the formation of single and double FIGURE 2a - DNAs amplified by Primer 1:1-5, Primer 2: 6-10, strand breaks and even causing the disappearance of the Primer 3: 11-15, Primer 4; 16-20, Primer 5: 21-25, Primer 6: 26-30. supercoiled, open circular and linear forms of the ΦX174

DNA. Similarly, Mozdzan et al. [15] showed that spermidine and spermine did not protect DNA and spermine even +2 enhanced the DNA degradation by Cu -H2O2 oxidizing system. On the other hand, spermidine and spermine were +2 excellent protected to DNA from Cu -H2O2-ascorbic acid +2 and Fe - H2O2-ascorbic acid-induced damage [15]. In the present study, the effects of polyamines on the protection of DNA strand breaks by CuSO4 treatment searched by RAPD primers. PCR products checked by agarose gel electrophoresis and photographed (Figure 2a, 2b). There are band differences between samples which are treated with different solutions; sea water medium, sea water medium with CuSO4 and polyamines or without. The main changes observed in the RAPD profiles have been resulted both in appearance or disappearance of different bands and variation of their intensity. The differ- entiation in band intensity and appearance or disappear-

sure. We had nearly the same results by amplification with primer number 9. The put and spd treated samples gave the clearest bands after untreated sample.

On the basis of the results, it is evident that CuSO4 treatment affects the template activity of DNA and this effect may be due to the structural damage caused to DNA. It is conceivable; polyamines, especially put and spd, have some roles on protecting DNA base alternations against copper. Obviously, sensitivity of the RAPD assay depends on the mutation levels and it needs further investigations. Also it has shown that these six RAPD primers could be used for detecting DNA damage on green algae U. lactuca by RAPD-PCR assay. We assume that this study may be a help for the further searches on protective roles of polyamines on DNA strand breaks against genotoxic agents.

REFERENCES

[1] Andrade, S., Contreras, L., Moffett, J.W. and Correa, A.J. (2006) Kinetics of the copper accumulation in Lessonia ni- grescens (Phaeophyceae) under conditions of the environmen- FIGURE 2b - DNAs amplified by Primer 7:1-5, tal oxidative stress. Aquatic toxicology 78: 398-401. Primer 8: 6-10, Primer 9: 11-15, Primer 10; 16-20. [2] Yu, B.P. (1994) Cellular defenses against damage from reactive oxygen species. Phgysiol. Rev. 74: 139-162. Amplification by Primer number two we had three bands with untreated sample’s DNA (Figure 2a, Lane 6). [3] Kohen, R. and Nyska, A. (2002) Oxidation of biological sys- By the other DNAs we get same 2 bands but the intensity tems: oxidative stress phenomena, antioxidants, redox reactions, and methods for their quantification. Toxicol Pathol 30: of the bands is different (Figure 2a, Lane 7-10). 620-650.

Amplification by Primer number 4 we had five band [4] Hartley, D. and Kidd, H. (983) The agrochemicals handbook. patterns only with untreated sample (Figure 2a, Lane 16). Royal Society of Chemistry, Nottingham, England The other samples did not give any bands (Figure 2a, [5] Atienzar, F.A., Cordi, B., Donkin, M.E., Evenden, A.J., Jha, Lane 17-20). A.N. and Depledge, M.H. (2000) Comparasion of ultraviolet- induced genotoxicity detected by random amplified poly- The eighth primer gave amplification only with un- morphic DNA with chlorophyll fluorescence and growth in a treated sample (Figure 2b, Lane 6). Primer 10 gave the same marine macroalgae, Palmaria palmata. Aquatic Toxicology results with primer eight but the number of the band patterns 50: 1-12. is different. [6] Eichhorn, GL. and Shin, Y.A. (1968) Interaction of metal After amplification by primer nine, the untreated sam- ions with polynucleotides and related compounds: XII The reactive effect of various metal ions on DANN helicity. J. ple gave 2 bright, 2 unclear bands (Figure 2b, Lane 11). The Am. Chem. Soc. 90: 7323-7328. other samples gave the same band patterns but the intensity of the band brightness is different (Figure 2b, Lane 12-15). [7] Llyod, D.D. and Phillips, D.H. (1990) Oxidative DNA damage mediated by copper (II), iron (II) an nikel (II) Fenton re- It is evident from the electrophoretic pattern of DNA actions: Evidence for site-specific mechanisms in the for- fragments amplified by RAPD that DNA of untreated sam- mation of the double-strand breaks, 8-hydrodeoxyguanosine ple showed different numbers of distinct bands whereas the and putative intrastrand cross-links. - Mutat. Res. 424: 23-36. samples exposure to CuSO4 and CuSO4 with polyamines [8] Kuthanová A., Gemperlová L., Zelenková S., Eder J., showed loss of various fragments. There was complete Macháčková I., Opatrný Z., Cvikrová M. (2004) Cytogical disappearance of all the high molecular weight fragments. changes and alterations in polyamine contents induced by cadmium in tobacco BY-2 cells. Plant Physiology and Bio- The intensity of the low molecular weight of fragments chemistry 42: 149-156. was less than untreated ones. The fragments amplified by primer 1 there are intensity differences among low molecu- [9] Lovaas, E. and Olsen, J.E. (1998) No induction of polyamines and radical scavenging antioxidants in Nicotiana tabacum ex- lar weight fragments. The intensity of CuSO4 treated frag- posed to iron excess, as incestigated by the DPPH assay and ment and the spm treated fragments are the same. Besides, differential spectroscopy. J. Plant Physiol. 153: 401-408. the intensity of untreated sample’s band pattern and spd and put treated sample’s fragments are same. According [10] Kakkar, R.J. and Sawhney, V.K. (2000) Polyamine research in plants-a changing perspective. Physiologia Plantarum 116: to these results we assume that the polyamines put and spd 281-292. could have role on protecting DNA against CuSO4 expo-

[11] Welsh, J. and McClelland, M. (1990) Fingerprinting genomes D using PCR with arbitrary primers. Nucleic Acids Res. 18, 7213-7218. degradation 1655 DL-PCB 1662 [12] Williams, J.G.K., Kubelik, A.R., Livak, K.J., Rafalski, J.A. Dytiscidae 1627 and Tingey, S.V. (1990) DNA polymorphisms amplified by arbitrary primers are useful as genetic markers. Nucleic Acids Res. 18, 6531-6535. E Estonia 1662 [13] Doyle, J.J. and Doyle, J.L. (1987) A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phyto- Estonian food 1662 chemistry Bulletin 19: 11-15. [14] Pedreňo, E., López-Contreras, A.J., Cremades, A. and H Peňafiel, R. (2005) Protecting or promoting effects of sperm- heavy metals 1648 ine on DNA strand breakage induced by iron or copper ions as a function of metal concentration. Journal of Inorganic Biochemistry 99: 2074-2080. I immobilization 1655 [15] Mozdzan, M., Szemraj, J., Rzysz, J., Stolarek, R.A. and Nowak, D. (2006) Anti-oxidant activity of spermine and sper- imported fish oil 1662 midine re-evaluated with oxidizing systems involving iron and inorganic element analysis 1627 copper ions. The International Journal of Biochemistry & insect 1627 Cell Biology 38: 69-8. K kinetics 1643

Received: May 18, 2007 Accepted: September 20, 2007 L Laccophilus 1627 land use 1636 CORRESPONDING AUTHOR Inci Tuney M Ege University meat 1662 Faculty of Science microbial biomass 1648 Department of Biology milk 1662 Hydrobiology Section 35100 Bornova-Izmir P TURKEY phenol 1655 polyamines 1667 E-mail: [email protected] polychlorinated dibenzofurans 1662

FEB/ Vol 16/ No 12b/ 2007 – pages 1667 - 1670 polychlorinated dibenzo-p-dioxins 1662 SUBJECT INDEX

A R adsorption 1643 RAPD 1667 alginate 1655 Rhodococcus 1655

S B Baltic Sea 1662 soil contamination 1648 bentonite 1643 soil enzyme 1648 bioclimatic distance between buildings 1619 soil erosion 1636 building coefficient (BC) 1619 soil properties 1636 building heights 1619 surfactants 1643

butter 1662 T

Turkey 1636 C

copper 1667 U cylindrical diagrams of solar height 1619 cylindrical diagrams of azimuth 1619 Ulva lactuca 1667 urban microclimate 1619

W WDXRF analysis 1627 subject-index

AUTHOR INDEX

Altun, Lokman 1636

E Esmer, Kadir 1643

G Gouda, Mona K. 1655 Gürol, Ali 1627

K Kariotis, George 1619 Kariotou, Glykeria 1619 Köksal Erman, Ömer 1627

L Loureiro, Susana 1648

N Nogueira, António J. A. 1648

P Panagiotopoulos, Eleftherios 1619

R Roots, Ott 1662

S Sağlam, Hasan B. 1643 Soares, Amadeu M.V.M. 1648 Sukatar, Atakan 1667

T Tarcan, Erdogan 1643 Theodoridou-Sotiriou, Lila 1619 Tilki, Fahrettin 1636 Tuney, Inci 1667

U Unal, Dilek 1667 Usta, Ayhan 1636

Y Yilmaz, Murat 1636

Z Zor, Sibel 1643 author-index

SUBJECT INDEX for Fresenius Environmental Bulletin 2007

A alginate 1655 Achillea 601 alkaline lipase 1503 acidic soil 1076 alkaline protease 1523 Actinobacillus sp. 726 Allium cepa 817 actinomycin D 917 Amberlite IR-120 720 activated carbon 235 amino acid 310 activity staining 1503 ammonium removal 168 Adriatic Sea 1242 ammonium 24 Adriatic 1457 anaerobic digestion 154 adsorbent 99 anaerobic digestion 162 adsorption 11 anaerobic treatment 1201 adsorption 235 anchovy 608 adsorption 731 anomalies` determination 561 adsorption 764 ANOVA 660 adsorption 887 anthracite 1468 adsorption 998 antifeedant 601 adsorption 1137 antimicrobial activity 428 adsorption 1377 antioxidant enzymes 922 adsorption 1551 antioxidant 839 adsorption 1583 apparent activation energy 928 adsorption 1643 Aqaba Gulf 1131 adsorption constants 500 aquaculture 784 adsorption-desorption 1363 aquaculture 1005 adsorption equilibrium 856 aquifer 517 adsorption kinetics 720 arsenic 421 adsorption kinetics 856 arsenic 861 adults 601 Artemia salina 1100 advanced oxidation processes 1216 Artemisia 601 Aegean Sea 776 artificial neural networks 1474 Aegean Sea 1012 artificial saliva 408 aerobic treatment 1451 As 896 aerosol size distributions 1160 Ascidiacea 1012 Aesculus 601 Aspergillus oryzae 1020 atmosphere 1238 Ag/TiO2 1147 agar plate screening 1309 atomic absorption spectrometry (AAS) 8 atomic absorption spectrometry 118 Ag-BiVO4 242 Agean region 1220 atomic absorption spectrometry (AAS) 145 agriculture 443 atomic absorption spectrometry 1274 agriculture 590 atrazine 379 agriculture 645 atrazine 1061 air pollution 660 automatic extraction 272 air pollution 861 automatic weather station 948 air purification 310 autopolymerizing 408 air quality monitoring network 364 azide 176 air quality 508 airborne particulate 543 B Alcian blue 817 Bacillus subtilis 1435 algae trapping 1087 background model 710 algal bloom 798 backpropagation 1474 algal bloom 1087 bacterial bioluminescence assay 1457 algal dynamics 798 Bahia Magdalena 1331 algal extract 428 Baltic herring 1126

Baltic Sea 1126 Buxus 601 Baltic Sea 1662 barley 917 C batch method 118 C.I. Acid red 14 1152 battery industry waste 99 Ca determination 216 battery of microbiotests 109 cabbage aphid 19 bean 548 cadmium biosorption 1600 bentonite 8 cadmium chloride 1100 bentonite 1137 cadmium 256 bentonite 1643 cadmium 295 benzene 330 cadmium 839 Berlin Teltowkanal 1248 cadmium 1227 bilirubin oxidase 1389 calcareous soils 1113 bioaccumulation 1571 calcinations 1137 bioclimatic distance between buildings 1619 calibration 1556 biodegradable liquid 1563 canonical correlation analysis (CCA) 82 biodegradation 489 Carassius carasius 904 biodegradation 632 carbohydrates 299 biodegradation 726 carboxylatozinc(II) complexes 851 biodegradation 1532 carrot 792 biodiversity 1030 Cascade correlation 1474 biogas plants 804 CAT 922 biogenic NMVOC emissions 465 Çatalagzi 182 bio-heat 735 catalase 1435 bioindicators 145 cattle manure 1227 biological acidation precipitation 1424 Cd determination 216 biological decolorisation 1309 central Italy 973 biological sludge 34 CFD 1517 biological treatment 393 change detection 1325 biological treatment 1532 characteristics 1588 biological treatment 1608 chemical composition 561 biomarkers 330 chemical factors 82 biomass 1023 chemical industry 1248 biomass 735 chemical oxygen demand 154 birds 63 chemical oxygen demand (COD) 162 biscuit wastewater 1201 chemistry 91 bisphenol A 1043 chernozem soil 295 bisphenol C 690 chilling stress 548 bituminous coal 235 Chlorella kessleri 826 black gram husk 1600 Chlorella vulgaris 621 black liquor 1424 Chlorella vulgaris 1492 Black Sea 1556 2-chlorophenol 617 Black Sea Region 1359 chlorophenols 1492 blackwater 1608 chlorophyll-a 1429 blow 272 chlorpyrifos 50 BOD decay rate 76 chlorpyrifos-methyl 50 BOD5 385 chlorpyrifos-methyl 764 Bonferroni adjusted two step cluster 261 chromium(VI) 1571 borate 928 Cicer arietinum 1600 Bosphorus 1429 citrus crops 50 bottom-up control 82 clam culture 1331 bran 122 clays 887 brucite 29 clean environments 1160 building coefficient (BC) 1619 cleanrooms parameters 1176 building heights 1619 clinoptilolite 168 bulk deposition 91 cluster analysis 561 Bursa 1227 cluster 364 butter 1662 Co determination 216

coal mining wastes 998 DEM 272 coal-fired power plant 182 denture base 408 coastal lagoon 1442 design flood 1300 coastal zone management 1030 desorption 1061 COD 821 diatoms 555 COD 1056 Dicentrarchus labrax 495 COD removal 393 differentiate effect 1468 COD removal 1216 digestion procedure 216 COD removal rates 1578 digestion 145 Colitea 601 dioxin-like PCBs 1126 co-metabolism 1563 direct communication 948 complexing capacity 372 Direct Red 80 821 composting 1069 dissolved organic ligands 372 concentrations of cations 261 dissolved oxygen 1093 condition factor 1355 dissolved oxygen 1544 conservation 1335 distribution 1351 constructed wetland 934 DL-PCB 1662 constructed wetland 1082 DMBA 596 contamination 256 DNA 299 contamination control 1160 Donghu Lake 856 control matrix 1176 DPD2794 1369 control software 948 dried sugar beet pulp 576 conventional farming 1195 drinking water supply 1087 co-oxidation 71 Drosophila melanogaster 991 copper 372 duckweed 38 copper 1355 Düzce-Turkey 145 copper 1667 dye degradation 1563 copper ions 29 Dytiscidae 1627 coprecipitation 745 core sediments 776 E

CORINE. 1325 EC50 621 corn 1113 EC50 826 correlation 57 eco-chemical status 1412 correlation 1351 ecohydrology 1030 corrosion behavior 613 edible mushroom 1359 co-substrate 1593 EDTA 832 cotton wastewater 1593 EDXRF 359 coupled ZrO2/ZnO 1152 effective diffusivity 500 CPs 1345 effects 1509 Cu determination 216 electrochemical laboratory 1238 cyanobacterial species composition 82 electrocoagulation 1056 β-cyclodextrin 1043 electro-Fenton 1216 cylindrical diagrams of azimuth 1619 electrostatic interaction 1363 cylindrical diagrams of solar height 1619 elemental analysis 359 elemental analysis 508 D El-Mex Bay 710 Daphnia magna 537 Emiliania huxleyi 832 DataFit® 674 empirical model 674 dechlorination 745 endocrine disruption 495 decolorization 242 Engraulis encrasichalus 608 decolorization 821 enhancement 690 decolorization 1389 enrichment factor 710 decrease 601 environmental analysis 880 defoliation 770 environmental conservation 940 degradation 379 environmental impact 1207 degradation 1020 environmental implications 261 degradation 1152 environmental parameters 1176 degradation 1655 environmental planning 1331

environmental pollutants 44 fractal analysis of AMCs 1176 environmental pollution 397 fractionation 421 enzymes 632 frequency analysis 1300 enzymes 1532 frequency domain 76 Ephestia kuehniella 1395 freshwater fish 1005 epilithic 555 fulvic acid (FA) 701 epipelic 555 fumigant toxicity 1498 epiphytic 555 fungicide 817 essential oil 1395 fungicides 880 essential oil 1498 Fusarium spec. 1503 Estonia 1126 Estonia 1662 G Estonian food 1662 gallium 1288 17β-estradiol 495 GAP 206 estuarine systems 1030 GAP region 272 EU water framework directive 1451 gas chromatography 1401 EU-bordering states 443 gas-chromatography 223 eutrophic freshwater 613 gauging station 272 eutrophic lake water 934 GC-MS 973 eutrophication 1023 Gediz river basin 477 eutrophication 1087 generative stages 1232 ever-green 1023 genetic algorithms 278 Evros River 776 genotoxicity 1319 exo-polysaccharide (EPS) 140 genotoxicity 1369 exposure 330 geographic information system 1325 extracellular polymeric substances (EPS) 299 glutathione 1435 extraction 118 glutathione pool 435 extraction 299 glycocalyx 817 gonad 1355 F goodness-of-fit tests 1300 farmyard manure 1295 GPx 922 Fe (III)-hydroxyl complexes 1043 GR 922 Fe determination 216 grapes 223 feeding 1100 gray water 1608 fertilization 295 Greece 1108 filter media 1468 Greek forests 465 Finland 1126 green waste 1069 fir 91 grey relationship analysis (GRA) 1345 fish industry 1588 grey theory 1345 fish-farm 784 groundwater 517 fixed-dome biogas reactor 804 groundwater quality 206 flame AAS 11 growth 851 flood 1220 growth bioassay 826 flood 1300 growth inhibition 869 floodplain 109 growth inhibition tests 621 fluent 1517 growth rate 38 fluorescence detection 543 growth rate 826 fluoride 278 gyttja 701 fluoride 928 fly ash 532 H foam fractionation 1503 Harran Plain 206 forest 91 HCB 745 forest condition 770 heart rate 1401 forest ecosystem values 963 heat island effect 639 forest health 770 heavy metal 14 forest management 963 heavy metal 38 fossil fuels 1207 heavy metal 235 fractal analysis of aerosols 1176 heavy metal 285

heavy metal 861 INAA 1279 heavy metal 904 inclusion complex 1043 heavy metal accumulation 19 indigo carmine 1389 heavy metal availability 1113 indium 1288 heavy metal pollution 1279 industrial waste minimization 99 heavy metal resistance 140 inorganic element 548 heavy metals 3 inorganic element analysis 1627 heavy metals 34 insect 1627 heavy metals 182 insecticidal activity 1395 heavy metals 352 insecticides 223 heavy metals 397 insecticides 252 heavy metals 710 integrated vertical flow constructed wetland 934 heavy metals 1005 integrated vertical flow 1082 heavy metals 1069 inverse calculation model 76 heavy metals 1076 invert sugar 459 heavy metals 1295 ion exchange 720 heavy metals 1359 ionic strength 764 heavy metals 1412 iron speciation 832 heavy metals 1451 irrigation water quality 590 heavy metals 1648 irrigation 206 Helicobacter pylori 749 irrigation 875 hematological parameters 596 irrigation 1485 hen manure 804 İskenderun Bay 756 herbicide 537 isoamyl acetate 118 herbicide pollution 973 isotherm 1583 Hindered settling 674 Istanbul 1517 HMF 459 Izmit Bay 910 Holothuria tubulosa 290 honey 459 J HPLC 543 Juniperus nana 216 HPLC-UV 973 Juniperus oxycedrus ssp. Oxycedrus 216 HRT 1593 Hubei province 1207 K humic acid (HA) 701 K determination 216 humic substances 1061 Kalman learning rule 1474 Hungary 660 kinetics 71 Hydra attenuate 1100 kinetics 1049 hydration 1137 kinetics 1643 hydraulic calibration 278 Kırıkkale 57 hydraulic loading rate 1082 Kızılırmak River 14 hydraulic retention time 1201 Klebsiella oxytoca 489 hydrocarbons 776 Korbevačka River 1412 hydrochemical analysis 1464 Kovada Lake 904 hydrodechlorination 745 Kupa River drainage basin 561 hydrotalcite-like compound 928 hydroxyl radicals 1492 L L. decemlineata 601 I Laccophilus 1627 IC50 869 Lactobacillus spp. 608 ICP-MS 1279 Lake Dianchi 82 imazapyr 1137 lakes 421 immersion experiment 613 land use 1325 immobilization 29 land use 1636 immobilization 1020 land uses 645 immobilization 1655 landfill leachate 1216 imported fish oil 1662 landfill leachate 1451 in situ chemical oxidation 617 landscape architectural applications 193 in situ documentation 980 landscape values 193

Langmuir 1551 Mert stream 1556 larvae 601 metal bioaccumulation 851 Lasioderma serricorne 1395 metal ion 133 LC50 value 472 metal ions 415 leachate 168 metal ions 1377 lead 38 metal ions removal 99 lead 256 metal pollutants 176 lead 1227 metals 826 lead 1351 metals 910 lead 1551 metamorphosis 991 Lemna minor 38 methacrylic acid 408 Lemna minor 379 methyl methacrylate 408 Lemna minor 524 methyl orange 247 Li determination 216 methylene blue (MB) 242 life cycle assessment 1207 methylene blue 1583 life-history 537 metsulfuron-methyl 1363 lignin 887 Mexico 1331 lignite power plants 508 Mg determination 216 lignite 701 Mg-Fe composite oxides 745 linear programming 963 MgFe2O4 745 lipid peroxidation 435 microalgae 1492 littoral zone 1087 microbial biomass 1648 liver 1355 microbial community structure 1578 livestock feed 1227 microclimatic improvement 639 longitudinal dispersion coefficient 76 Micrococcus sp 1571 long-term monitoring 770 microcystin-RR 1435 low-cost adsorbent 1049 micronuclei 472 Luffa cylindrical 1020 micronutrients 1578 Lycopersicum esculentum L. 133 microwave-assisted extraction 127 microwave-curing 408 M milk 1662 macro-algae 428 mineral composition 561 macro-invertebrate abundance 1030 mineral content 459 macroinvertebrate assemblages 645 mineral water 252 magnesium removal 720 mining activities 1076 magnesium–aluminum oxide 928 minor elements 1359 maize 851 mite allergen activities 310 malathion 472 mitotic activity 917 manganese 415 mixing layer 697 mapping 57 MLSS 393 Marches region 973 Mn determination 216 marine sediment 1279 modeling 617 marine sediments 1523 modeling 1049 Marmara Sea 910 modification 1377 mass spectrometry 223 modified 8 material flow analysis 1207 monitoring systems 443 MATLAB® 674 monitoring 508 measurement 1160 monitoring 1160 meat 1662 montmorillonite 11 mechanisms 29 morphology 19 meiofauna 784 mosses 145 membrane fouling 654 moss-monitoring 182 membrane reactor 812 moving window 304 Menemen Plain 1485 multiresidue method 223 mercaptans 44 municipal solid waste 1069 mercury 176 municipal wastewater 1593 mercury 1442 mushrooms 397 mercury vapour 1238 Myrothecium sp. 1389

N organic solvent stability 1523 Na determination 216 organochlorine compounds 1126 Na2C2O4 1424 organochlorine pesticides 122 Na-clinoptilolite 24 organochlorine pesticides 576 nanoparticles 320 organochlorine pesticides 1131 nanotechnology 320 organochlorine 252 Na-P 24 organo-mineral complexes 1061 Natura 2000 1335 Origanum onites L. 1401 natural plants 193 Origanum 1232 natural plants identification 193 Orthrias angorae 472 Neomenia carinata 1242 osculum 980 nervous system drugs 524 ovary 1407 neural network 304 oviposition deterrency 1498 neural network 798 oxidative damage 839 Ni determination 216 oxidative stress 435 niacin 393 oxidative stress 1435 nickel 1551 ozonation 617 Nigde 352 ozone 821 nitrogen 532 nitrogen 1232 P nitropolycyclic aromatic hydrocarbons 543 PAH 776 NMVOC emissions 1108 Pandorina morum 621 nonstationary 304 Pandorina morum 869 nonylphenol (NP) 227 paper mill sludge 1049 Northeastern Mediterranean 756 parameter estimation 1300 Northern Adriatic 784 paraquat 621 Northern Adriatic Sea 980 participation 940 North-West Turkey 182 particulate matter 508 nuclear energy 998 particulate matter 697 numerical approach 674 passive cooling techniques 639 nutrient accumulation 1023 pattern recognition 1335 nutrient removal 1023 Pb 896 nutrient removal 1082 Pb determination 216 nutrients 756 PCA 364 nutrients 1429 PCA 1186 PCB congeners 792 O PCHC values 1248 occupational exposure 1238 peaches 223 octylphenl (OP) 227 peat 1551 oil spill 1517 Péczely’s large-scale weather situations 660 oily wastewater 1532 pentachlorophenol (PCP) 856 olive blackwater 1020 performance 19 olive mill wastewater 887 peripheral erythrocyte 472 OLR 1593 permethrin 1407 oocyte 1407 peroxidase activity 917 open dump 1069 persistent organic pollutants 1126 operational parameter 1152 pesticide 63 operational parameters 654 pesticide 443 optimization 654 pesticides 731 orange G dye 1049 pesticides 880 Oreochromis niloticus 1355 pH 764 organic acids 764 pH 798 organic compounds 320 pharmaceuticals 524 organic enrichment 1012 pharmaceuticals 1509 organic farming 1195 Phaseolus vulgaris 548 organic loading 1201 phenol 489 organic matter 34 phenol 726 organic matter 290 phenol 812

phenol 887 population structure 1012 phenol 991 precipitation 477 phenol 1655 preconcentration 8 phosphoric acid 34 Press release 452 phosphorus release 934 probability distribution 1300 phosphorus removal 934 probiotic 608 photocatalysis 812 propanil 537 photocatalysis 1345 proteins 299 photocatalyst 403 prove of log-normal aerosol distribution 1176 photocatalyst 1147 Pseudokirchneriella subcapitata 621 photocatalyst 1152 Pseudokirchneriella subcapitata 869 photocatalytic 242 Pseudomonas spp. 140 photocatalytic activity 626 photocatalytic activity 1152 Q photocatalytic decoloration 247 QUAL2E 1556 photocatalytic treatment 310 quinoline 632 photodegradation 524 photodegradation 690 R photodegradation 1043 radial basis function 304 photosynthesis 1492 radioisotopes 998 Phragmites australis 14 rainbow trout 922 physical factors 82 rainbow trout 1005 physico-chemical characterization 1588 rainfall duration equations 1220 phyto-extraction 1113 rainfall frequency equations 1220 phytoplankton dynamics 756 rainfall intensity equations 1220 phytoremediation 1464 RAPD 1667 phytostabilization 1076 Raphidocelis subcapitata 826 phytotoxicity 524 Raxil 817 pine 91 real-time communication data link 948 Pinus pinea 1335 real-time PCR 749 pirimicarb 403 recA 1369 planktonic 555 rectorite 247 plankton-net material 1442 refinery 1056 plant 1232 regression 57 plant distribution 1186 remediation 320 plant ecology 1186 remote sensing 1325 plant extracts 601 remote station 948 plant nutrient elements 285 removal rate 1468 plant parts 1274 renewable energy 804 PM 352 renewable energy sources 735 PM10 57 residual monomer 408 pollution 14 residue 63 pollution 57 residue 252 pollution 352 resins 731 pollution 645 respiratory uptake 861 pollution 904 resuspension 421 pollution 1351 retention time 674 polyamines 1667 reuse 875 polychlorinated biphenyls 576 reuse 1485 polychlorinated dibenzofurans 1126 reuse guidelines 590 polychlorinated dibenzofurans 1662 reuse standards 590 polychlorinated dibenzo-p-dioxins 1126 revegetation 1295 polychlorinated dibenzo-p-dioxins 1662 Rhodococcus 1655 polycyclic aromatic hydrocarbons 127 risk assessment 1288 polycyclic aromatic hydrocarbons 543 river Bilina 1248 polyphenols 154 river Elbe 1248 polyphenols 162 river flow routing 1474 population behavior 304 river habitat modification 645

river Lippe 1248 silica 403 river Main 1248 silver 1147 river Mulde 1248 simulation 1517 river Rhein 1248 simulation 1556 river water 1412 SiO2 1147 road pollution 133 Sirius F3B 821 root growth 917 Sitophilus granaries 1395 round ceramsite 1468 Skadar Lake 3 sludge 299 S SO2 352 safety 256 soil 63 Sahara dust 861 soil 109 salinity 206 soil 133 salinity 517 soil 532 Salmonella mutagenicity test 1319 soil 792 sand filtration 875 soil 1232 Sander lucioperca 904 soil 1274 sawdust 1583 soil colloids 764 Scutellaria orientalis ssp. Pectinata 216 soil contamination 1648 Scutellaria orientalis ssp. Pinnatifida 216 soil degradation 285 sea cucumber 290 soil enzyme activities 1186 sea surface microlayer 372 soil enzyme activities 1195 sea water 910 soil enzyme 1648 sediment 3 soil erosion 1636 sediment 109 soil particle-size fractions 1195 sediment 1412 soil-plant transfer 792 sediment 1544 soil properties 1636 sediment oxygen demand 1544 Solanum nigrum 896 sediment quality 784 solar light 247 sediment quality 1030 solar system 403 sedimentation 1451 Solenogastres 1242 sediments 421 solvents 1108 sediments 910 sorption isotherms 1600 sediments 1131 sorption 1061 sediment/water interaction 1544 SOS chromotest 1319 selenium 14 SOS chromotest 1369 selenium 1351 SOS response 1369 SEM 731 spatial presentation 261 semiarid climate 1076 speciation 256 semiconductor industry 1288 species 193 semi-conductors 44 spectrometry 548 semi-empirical model 720 spider mite 1498 sensitivity analysis 798 sponge contraction 980 sensitivity of species 109 spray drift 50 separation 415 stabilization pond 385 sepiolite 887 stabilization ponds 875 sepiolite 1377 stabilization ponds 1093 ® septage 385 Stam Novel Flo 480 537 sequencing batch reactor 1608 standard statistic 1160 serum 839 statistical distribution function 1220 sewage sludge 127 sterile filling 1160 sewage treatment plant 127 sterile filling 1176 Shannon index 364 stock assessment 1012 ship wastewaters 1608 Strait of Malacca 1279 shrimp waste 256 stratification 1093 siamese fighting fish 176 stream sediments 561 SIG 517 stream-flow 477 silanol-terminated poly(dimethyl)siloxane 626 Streptomyces 1523

stress 922 titanium oxide 44 structural parameter 1345 top-down control 82 Suberites domuncula 980 total particulate matter 352 submerged membrane bioreactor (SMBR) 154 total protein content 917 submerged membrane bioreactor (SMBR) 162 town waste 285 submerged membrane bioreactor (SMBR) 654 toxicity 537 subtropical region 1082 toxicity 601 sugar beet refinery 576 toxicity 839 sulphur 1113 toxicity 896 sulphur mine tailings 1295 toxicity 1457 sunflower 1274 toxicity endpoints 1100 sunflower oil 122 toxicity levels 1274 superoxide dismutase 1435 trace element 1274 supported liquid membrane 685 trace element 1288 supported liquid membranes 415 trace elements 8 surface modification 626 trace elements 1005 surface morphology 731 trace metal 459 surface water genotoxicity 1319 trace metals 145 surface-active substances 372 tracer 278 surfactants 1643 transformation products 1509 susceptibility 330 transport 415 suspended particulate matter (SPM) 856 treated wastewater 1485 sustainability 784 treatment 320 synthetic organoselenium compounds 596 treatment 385 synthetic pyrethroids 1407 trend analysis 477 Szeged 660 Trifolium incarnatum 896 1-[3-(trimethoxysilyl)propyl]urea 1377 T trioctyl amine 118 tailings 1076 trioctyl phosphine oxide 8 tailings amendment 1295 trioctyl phosphine oxide 118 Talmadge-Fitch 674 Troia 63 Tanacetum 601 tumor necrosis 435 tanker accident 1517 Turkey 206 tannery wastewater 1571 Turkey 477 tebuconazole 817 Turkey 904 technology evaluation 735 Turkey 1359 temperature 1093 Turkey 1636 temperate climate 1093 Typha angustifolia 14 teratogenic effect 991 Tetranychus cinnabarinus 1498 U textile dye 685 UASB reactor 1201 textile dye 1309 UASB 1593 textile wastewater 1578 Uluabat Lake 940 textile wastewater 393 Ulva lactuca 1667 Thermaikos Gulf 1012 umuC test 1369 Thioflavin T 685 uptake 928 Thioridazine 524 uranium 998 throughfall 91 urban areas 639 Thymbra spicata L. 1401 urban environment 57 time domain 76 urban lakes 227 time lagged daily flows 1474 urban microclimate 1619 tin oxide 44 urban pollution 697 TiO2 247 urban wastewater 385 TiO2 626 urban wastewater 749 TiO2 812 urease activity 532 TiO2 semiconductor 310 ureC gene 749 tissues 839 UV light 690 titanium dioxide (TiO2) 320 UV light irradiation 242

UV shielding 626 white rot fungi 1309 white rot fungi 1424 V white rot fungi 1563 vacuum sewage systems 1608 white rot fungus 632 variably charged soil 1363 white sugar 576 vegetable oil 1056 wild-type cereals 359 vegetable oils 685 wine distillery wastewater (WDW) 154 vegetation classification 1335 wine distillery wastewater (WDW) 162 vegetative stages 1232 winter 57 ventilation frequency 1401 vertical flow constructed wetlands 1468 X vertical profiles 697 Xiphophorus helleri 1407 vicinity 1248 village development 940 Y vitellogenin 495 Yaqui Valley 517 volatile fatty acids (VFAs) 154 yields 1295 volatile fatty acids (VFAs) 162 volatile organic components 500 Z voltammetry 372 Zea mays L. 1295 zeolite 1147 W zeolite 4A 500 wastewater 8 zeolites 1468 wastewater 24 zero-valent iron (ZVI) 320 wastewater 127 zeta potential 1377 wastewater 1056 zinc oxide 44 wastewater 1093 zirconium 869 wastewater reuse 590 Zn 896 wastewater reuse 639 Zn(II) 851 wastewaters 1588 Zn determination 216 wastewater sludge 532 zooplankton 1442 wastewater treatment 71 zooplankton 1464 wastewater treatment 875 ZSM-5 1492 wastewater treatment 1509 wastewater treatment 1600 wastewater treatments 821 water 63 water 1023 water 1131 water analysis 880 water autopurification 1464 water bodies contamination 50 water quality 517 water quality 1030 water quality 1087 water quality 1485 water quality 1544 water quality monitoring net-work 272 water samples 11 water supply networks 278 water treatment 99 water vapour 500 WDXRF analysis 1627 WDXRF technique 548 weather classification 660 weight 601 well water 973 wet air oxidation 71 wheat grain 122

AUTHOR INDEX for Fresenius Environmental Bulletin 2007

A Atamanalp, Muhammed 922 Abbate, Cristina 764 Ates, Burhan 596 Abdallah, Maha A.M. 710 Audigiuer, Martine 1137 Abidin Sulaiman, Zainal 1279 Avanus, Kozet 1227 Abreu, Sizenando 1442 Ay, Özcan 1355 Acar, Reşat 1220 Aydın, Özkan 720 Adams, Tawakalitu M.O. 256 Azbar, Nuri 1309 Adeniyi, Adeleke A. 256 Azeiteiro, Ulisses M. 1442 Afyon, Ahmet 1359 Ai, Zhihui 1345 B Akay, M. Emin 57 Badr, Nadia B.E. 710 Akin, Senol 1005 Bagiorgas, Haralambos S. 639 Akkaya Aslan, S. Tulin 940 Bagiorgas, Haralambos S. 948 Akkoyunlu, Atilla 1201 Baglieri, Andrea 764 Akosman, Cevdet 500 Bakan, Gülfem 1544 Aksu, Abdullah 910 Bakan, Gülfem 1556 Aktaç, Tülin 817 Bakar, Elvan 817 Alawi, Mahmoud A. 403 Balík, Jiří 792 Alawi, Mahmoud A. 408 Balkıs, Neslihan 1429 Alawi, Mahmoud A. 1131 Balkıs, Nuray 910 Alawi, Mahmoud A. 1147 Baloutsos, George 91 Alkan, Mahir 1377 Baltaş, Hasan 359 Alkan, Ufuk 532 Bartoš, Tomáš 1369 Al-Majali, Ibrahim 489 Bartzokas, Aristides 660 Al-Masri, Mohamad Ghiath 1131 Başaran, Saime 193 Alpertunga, Buket 880 Başkaya, H. Savaş 532 Altun, Lokman 1636 Başkent, E. Zeki 963 Alyan, Sofyan 176 Batel, Renato 980 Alzahrany, Awad A. 1279 Bayir, Abdulkadir 922 Ametisti, Mirco 973 Bayram, Adem 1069 Amin, Wala 408 Bazzi, Lahcen 1588 Anaç, Süer 477 Bendou, Abdelaziz 1588 Αngelidis, Μichael Ο. 776 Beneduce, Luciano 749 Antolić, Boris 1242 Berger, Ralf G. 1503 Antoniadou, Chryssanthi 1012 Bergheim, Werner 1248 Apaydin, Gökhan 1005 Bester, Kai 1509 Apaydin, Halit 272 Beyatli, Yavuz 140 Apostolopoulos, Charis A. 639 Beyatli, Yavuz 608 Arici, C. Franziska 940 Bhatnagar, Amit 99 Arici, Ismet 940 Bhatnagar, Amit 1049 Arnaldos, Raquel 1076 Bihari, Nevenka 1457 Arslan, Oktay 1232 Bilgin-Sokmen, Bahar 839 Arslan-Alaton, Idil 590 Bin Saion, Elias 1279 Ashraf, Waqar 685 Blagojevic, Srdjan 3 Askin Bak, Osman 1517 Blagojevic, Srdjan 295 Aşkın, Hakan 991 Blaise, Christian 1100 Aslan, Irfan 1395 Blazina, Maria 784 Aslan, Sukru 1485 Bogner, Danijela 784 Aslim, Belma 140 Bolkent, Sehnaz 839 Assimakopoulos, Margarita N. 639 Bolzacchini, Ezio 697 Assimakopoulos, Margarita N. 948 Boon Siong, Wee 1279 Asvesta, Argiro 508 Bostan, Hidayet 548

Bourletsikas, Athanassios 91 Čupr, Pavel 1369 Bourletsikas, Athanassios 770 Cvejanov, Jelena 122 Brümmer, Franz 980 Cvetković, Olga 1412 Bukhari, Alaadin 685 Cvitković, Ivan 1242 Bulut, V. Numan 1069 Burgess, Jo E. 154 D Burgess, Jo E. 162 D’Emilio, Mariagrazia 364 Dane, Feruzan 817 C Darbi, Ashref 415 Cadirci, Bilge Hilal 428 Demir, Faruk 548 Caggiano, Rosa 364 Demir, İbrahim 1201 Çaglar, Özcan 1395 Demirbaş, Özkan 1377 Çalmaşur, Önder 1395 Demirezen Yilmaz, Dilek 14 Camcı Çetin, Sema 1186 Demirezen Yilmaz, Dilek 1351 Can, Sevilay 1517 Deng, Deming 247 Canella, Maddalena 973 Deng, Huanhuan 299 Cao, Gang 613 Deng, Lin 1043 Capri, Ettore 50 Deng, Lin 1207 Cardelli, Roberto 1195 Deng, Nansheng 690 Carrillo, Manuel 495 Deng, Nangsheng 1043 Carter, Joy 133 Deng, Nansheng 1207 Castro, Paula M.L. 896 Despalatović, Marija 1242 Cebovic, Tatyana 435 Di Leo, Senatro 364 Çelik, Aysun 1186 Diamantopoulou, Maria J. 1474 Celik, Fahri 1517 Dikbaş, Fatih 1300 Cengiz, Mehtap 922 Dincer, Ali Rıza 1274 Cengiz, Mustafa 922 Doğan, Mehmet 1377 Cerit, Harun 1227 Doğan, Serap 1232 Cetin, A. Kadri 555 Dokianakis, Spyros N. 1608 Çevik, Uğur 359 Dönmez, Gönül 1571 Çevik, Uğur 1005 Đorđević, Ljiljana 1412 Chakir, Achraf 1137 dos Prazeres, Janaina N. 1503 Chang, Jie 1023 Doulia, Danae 731 Chang, Jie 1082 Drillia, Panagiota 127 Che, Yu-ling 1578 Drobniewska, Agata 109 Chebli, Bouchra 1588 Duarte Mendes, Cristiana 537 Chen, Hong-Wen 543 Duarte, Armando C. 1442 Chen, Hong-Wen 1288 Duborija, Aleksandar 3 Chen, Jian-Feng 29 Dumlupinar, Rahmi 548 Chen, Shuiping 227 Dural, Adil 235 Cheng, Kang 247 Đurišić-Mladenović, Nataša 122 Cheng, Shui-ping 654 Cheng, Shui-ping 934 E Cheng, Shui-ping 1468 Economou, Anastasios 91 Cheng, Zhenhua 1216 Economou, Anastassios 770 Chintiroglou, Chariton 1012 Edyvean, Robert G.J. 1600 Chu, Jinyu 242 Ekosse, Georges-Ivo E. 261 Cicik, Bedii 1355 El Hourch, Abderrahim 1137

Čík, Gabriel 1492 El Kacemi, Kacem 1137 Çimen Türeli, Funda 701 Elhassadi, Abdulmonem 415 Çimrin, K. Mesut 1113 Elias, Md Suhaimi 1279 Coelho, João P. 1442 Erdem, Cahit 1355 Conesa, Héctor M. 1076 Erler, Fedai 1498 Cortés-Jiménez, Juan Manuel 517 Ertuğral, Birol 359 Ćosović , Božena 372 Ertuğral, Birol 1005 Cristalli, Gloria 973 Ertürk, Ömer 601 Cüce, Hüseyin 1544 Esmer, Kadir 1643 Cui, Longzhe 812 Evagelopoulos, Vasilis 508

Eyvaz, Murat 1201 Gürdegin, Bahadır 472 Gurel, Melike 590 F Gürol, Ali 1627 Fafanđel, Maja 1457 Györyová, Katarína 851

Fan, Yuehua 76 Faz, Ángel 1076 H Ferrero, Luca 697 Habibi, Mohammad H. 44 Ferrini, Barbara 697 Halilova, Hanım 701 Fiocco, Daniela 749 Hamer, Bojan 980 Flegrová, Zuzana 1369 Hameş-Kocabaş, E. Esin 1523 Fouche, Paul S. 261 Hasan, Lina A. 403 Fountoulakis, Michalis 127 Hasar, Halil 34 Fountoulakis, Michalis S. 1608 Hashimoto, Tadanori 310 Frančišković-Bilinski, Stanislav 561 Hassan, Nouri 415 Francoletti, Enrica 973 Has-Schön, Elizabeta 826 Fresco, Paula M.F.C. 869 Hatzianestis, Ioannis 776 Fu, Dongmei 71 Hazirbulan, Servet 887 Fu, Guiping 227 He, Feng 227 Furusawa, Takeshi 626 He, Feng 654 He, Feng 856 G He, Feng 934 Gagné, Francois 1100 He, Feng 1468 Gan, Fuxing 247 Heinisch, Emanuel 1248 Gan, Fuxing 613 Hizarci, Leyla 832 Gan, Jay 1363 Holoubek, Ivan 1369 Garas, Stylianos 508 Hong-ying, Hu 393 Garatuza-Payán, Jaime 517 Hormatatllah, Abderahim 1588 García, Gregorio 1076 Horvatić, Janja 826 García-Hernández, José Luis 517 Hou, Guoxiang 304 Gašparović, Blaženka 372 Hou, Guoxiang 798 Ge, Liyun 299 Hu, Hong-ying 1578

Ge, Ying 1023 Huang, Chin-Pao 617 Ge, Ying 1082 Huang, Wen-min 82 Genç, Hasan 359 Hui, Wang 393 Genç, Osman 1401 Gennari, Mara 50 I Gennari, Mara 764 İbar, Hilmi 8 Georgiadis, Theodoros 1335 İbar, Hilmi 118 Georgiou, Pantazis E. 1474 İli, Pınar 1401 Gerbl-Rieger, Susanne 443 Ince, Mahir 145 Giardiná, Dario 973 Ince, Mahir 182 Gioda, Adriana 861 Iqbal, Muhammad 1600 Gok, Yetkin 596 Irmak, Seyyid 285 Gonçalves, Ana M.M. 621 İşgören-Emiroğlu, Dilek 290 Gonçalves, Fernando 537 Isik, Oya 832 Gonçalves, Fernando 621 Iskender, Gulen 590 Görür, Gazi 19 Gouda, Mona K. 1655 J Gritzalis, Konstantinos C. 645 Jaklin, Andrej 980 Grubelić, Ivana 1242 Jalili, Abderahim 1588 Gržetić, Ivan 1412 Javorská, Hana 792 Güçlü, Kubilay 998 Jeon, Byong-Hun 99 Gül, Süleyman 472 Jeon, Byong-Hun 1049 Gulluoglu, Said M. 206 Jiang, Li 613 Gülsoy, Nagihan 1407 Jiang, Ming 617 Günay, Deniz 290 Jimenez-Velez, Braulio D. 861 Gündoğdu, Ali 1069 Jin, Yee-Chung 320 Guo, Yu-feng 1578 Jones, Paul 133

K Kuleyin, Ayşe 168 Kaichouh, Ghizlan 1137 Kulikova, Natalia A. 1061 Kalavrouziotis, Ioannis K. 133 Kurşun, Ozen 1227 Kalavrouziotis, Ioannis K. 639 Kwokal, Željko 1238 Kalebaşi Aktaş, Yıldız 8 Kyriakopoulos, Grigorios 731 Kalebaşi Aktaş, Yıldız 11 Kalebaşi Aktaş, Yıldız 118 L Kalender, Mehmet 500 Labbaci, Lidia 1195 Kaliszová, Regina 792 Lagunas-Vázquez, Magdalena 1331 Kalmış, Erbil 1309 Lazzati, Zelda 697 Kalogerakis, Antonis 735 Lee, Giehyeon 1049 Kalyoncu, Fatih 1309 Lee, Sang Suh 517 Kamber, Ufuk 472 Levi-Minzi, Renato 1195 Kameda, Tomohito 928 Li, Ai-min 379 Kamiya, Kanichi 310 Li, Changsheng 242 Kampioti, Adamantia 127 Li, Dun-Hai 1435 Kaneco, Satoshi 310 Li, Dun-hai 82 Kanellopoulos, Theodore D. 776 Li, Er 76 Kaping, Daniel 1509 Li, Fanxiu 1345 Kaplan, Mustafa 1295 Li, Fengting 1152 Kapsimalis, Vasilios 776 Li, Gen-bao 82 Kapur, Burçak 1113 Li, Haifeng 690 Karaca, Ayten 1186 Li, Hongbin 304 Karami, Bahador 44 Li, Hongbin 798 Karaouzas, Ioannis 645 Li, Huaming 242 Karaytug, Sahire 1355 Li, Jianfen 1583 Kariotis, George 1619 Li, Jin 856 Kariotou, Glykeria 1619 Li, Shi-Peng 1023 Kasap, Yaşar 285 Liang, Wei 227 Kaska, Yakup 1401 Liang, Wei 393 Katsumata, Hideyuki 310 Liang, Wei 654 Kaya, Orhan 1395 Liang, Wei 1468 Kaya, Taylan Özgür 472 Liang, Wei 1578 Kaya, Zafer 193 Liang, Xinmiao 71 Kaykioglu, Gul 1274 Liapis, Konstadinos S. 223 Kaynar, Pinar 608 Lin, Feng 24 Kaza, Michał 524 Linke, Diana 1503 Keleş, Sedat 963 Liu, Li-Jun 856 Kettrup, Antonius 1248 Liu, Renhua 71 Khleifat, Khaled M. 489 Liu, Wenbin 745 Khleifat, Khaled M. 726 Liu, Wenxia 745 Kim, Seong-Heon 99 Liu, Xing-mei 1363 Kir, İsmail 904 Liu, Yan 299 Kirmikil, Muge 940 Liu, Yanxiang 1043 Kızılcıklı, İrfan 998 Liu, Yong-ding 82 Kocak-Enturk, Emel 804 Liu, Yongding 798 Koçberber Kılıç, Nur 1571 Liu, Yong-Ding 1435 Köksal Erman, Ömer 1627 Liu, Youxun 1389 Komorsky-Lovrić, Šebojka 1238 Lo Porto, Claudia 697 Konofaos, Nikolaos 948 Lolas, Petros 1030 Konuk, Muhsin 1359 Loureiro, Susana 1648 Kornaros, Michalis 1608 Lovrić, Milivoj 1238 Κotonia, Chrissi Α. 223 Lu, Jinwei 1087 Kotzias, Dimitrios 330 Lu, Shou-Ci 29 Kouloumpis, Victor 735 Lu, Xiaohua 812 Kráľová, Katarína 851 Lu, Xiaohua 1345 Krestenitis, Yannis 1012 Luminari, Maria C. 973 Kukul, Yasemin S. 477 Lyberatos, Gerasimos 127

Lyberatos, Gerasimos 1608 Nimtz, Manfred 1503 Nishikawa, Naomi 310 M Niu, Xiao-Yin 1023 Ma, Luming 299 Niu, Xiao-Yin 1082 Ma, Xiaodong 745 Nogueira, António J. A. 1648 Mahramanlioglu, Mehmet 998 Nur, Gökhan 472 Makra, László 660 Nuri Ergun, Osman 168 Malagrino, Giovanni 1331 Mao, Xuhui 613 O Mao, Yibing 1424 Öbek, Erdal 34 Marques, Ana P.G.C. 896 Oduguwa, Oluseyi O. 256 Martins, Ana S.B. 869 Ohta, Kiyohisa 310 Masarovičová, Elena 851 Okedeyi, Olumuyiwa O. 256 Massa, Salvatore 749 Okuwaki, Akitsugu 928 Masuyama, Kazuaki 310 Oliveira, Joana B. 621 Matthopoulos, Demetrios P. 639 Önen, Hüseyin 1186 Matthopoulos, Demetrios P. 948 Opedal, Elisabeth H. 1451 Meghea, Aurelia 1160 Ören, Muhammet 145 Meghea, Aurelia 1176 Ören, Muhammet 182 Mei, Ping 1345 Orhon, Derin 590 Melamane, Xolisa L. 154 Orman, Sule 1295 Melamane, Xolisa L. 162 Ortega-Rubio, Alfredo 1331 Meli, Salvatore Marco 50 Orun, Ibrahim 596 Merdun, Hasan 272 Otludil, Birol 1319 Messina, Cristina 764 Oturan, Mehmet Ali 1137 Metaxa, Irene 385 Oturan, Nihal 1137 Metaxa, Irene 875 Ovez, Suleyman 590 Metaxa, Irene 1093 Øygard, Joar Karsten 1451 Michopoulos, Panagiotis 91 Ozbayrak, Eda 1556 Michopoulos, Panagiotis 770 Özcan, Hasan 63 Mihalakakou, Giouli 639 Ozdemir, Ilknur 596 Mihalakakou, Giouli 948 Ozdemir, Osman N. 278 Mika, János 660 Özel, Mustafa Zafer 1401 Minocha, A. K. 99 Özen, Fazıl 1232 Minocha, A. K. 1049 Özhan, Gül 880 Miyahara, Motoya 928 Özmen, Ismail 922 Mizoguchi, Tadaaki 928 Özmetin, Cengiz 720 Montazerozohori, Morteza 44 Öztepe, Çetin 1020 Mor, Firdevs 1227 Ozturk, Fazli 272 Moraes, Jorge M. 477 Öztürk, Murat 832 Mucci, Nicolina 330 Ozturk, Mustafa 804 Müller, Werner E.G. 980 Özyurt, Mustafa 1020 Murillo-Amador, Bernardo 517 Mutlu, Cengiz 1005 P Pacheco, Mário 495 N Pakou, Constantina 127 Nabi, Ari Q. 749 Panagiotopoulos, Eleftherios 1619 Najdek, Mirjana 784 Panagiotou, Magdalini 1012 Nałęcz-Jawecki, Grzegorz 109 Pang, Wenqin 24 Nałęcz-Jawecki, Grzegorz 524 Pantazis, Panagiotis 1030 Namli, Hilmi 1377 Papadaki, Ekaterini 421 Narr, Jaspreet 320 Papadopoulos, Aristotelis 385 Nas, S. Serkan 1069 Papadopoulos, Aristotelis 875 Nègre, Michèle 764 Papadopoulos, Aristotelis 1093 Neofitou, Christos 1030 Papadopoulos, Frantzis 385 Neofitou, Nikos 1030 Papadopoulos, Frantzis 875 Nie, Qiyang 247 Papadopoulos, Frantzis 1093 Nikolaidis, Vassilios 1335 Papagianopoulou, Areti 1093

Papamichail, Dimitris M. 1474 Sakar, Mahmut K. 216 Paparelli, Giovanna 973 Salghi, Rachid 1588 Pardal, Miguel A. 1442 Sangiorgi, Giorgia 697 Parissopoulos, George 385 Santos, Maria Ana 495 Parissopoulos, George 875 Sapci Zengin, Zehra 1593 Parissopoulos, George 1093 Sari, Mustafa 1325 Park, Ju-Myon 1049 Sarıbaş, Metin 193 Parlar, Harun 443 Sato, Masahide 626 Pastore, Glaucia M. 1503 Saviozzi, Alessandro 1195 Patentalaki, Argiro 948 Sawicki, Józef 109 Pato, Pedro 1442 Sawicki, Józef 524 Pavičić-Hamer, Dijana 980 Sayin, Selin 832 Pavlić, Želimira 826 Schaff, Peter 443 Pavlíková, Daniela 792 Schaff, Peter 1160 Pereira, Joana Luísa 537 Schaff, Peter 1176 Pereira, Maria E. 1442 Selamoglu, Zeliha 596 Pereira, Mário J. 621 Şenocak, Serkan 1220 Pereira, Mário J. 869 Şenol, Erdinç 910 Perez Sirvent, Carmen 1137 Seren, Gulay 1274 Peréz, Ulda 861 Šeršeň, František 1492 Perfler, Reinhard 1082 Shao, Lei 29 Perminova, Irina V. 1061 Shawabkeh, Reyad 489 Perrone, Maria Grazia 697 Shen, Yin-wu 82 Peršić, Vesna 826 Shi, Xiaoyan 1583 Petraccone, Stefania 697 Siddiquey, Iqbal Ahmed 626 Picó, Yolanda 973 Sidiropoulos, Christos 465 Plavšić, Marta 372 Sidiropoulos, Christos 1108 Polat, Sevim 756 Simiqueli, Ana P. 1503 Popovic, Mira 435 Simm, Mart 1126 Priesolová, Soňa 1492 Sirkecioğlu, A. Necdet 922 Proto, Monica 364 Škarek, Michal 1369 Psilovikos, Aris 1030 Skoulikidis, Nikolaos 645 Škrbić, Biljana 122 Q Škrbić, Biljana 576 Quinn, Brian 1100 Soares, Amadeu M.V.M. 1648 Song, Lirong 798 R Song, Lirong 304 Ragosta, Maria 364 Song, Yu-dong 1578 Rangel, António O.S.S. 896 Sönmez, Namık Kemal 1325 Rasheed, Mohammed 1131 Sözüdoğru Ok, Sonay 701 Ratushnyak, Anna A. 1464 Spano, Giuseppe 749 Recknagel, Friedrich 304 Spanou, Sofia 1335 Ren, Dajun 632 Srinivasan, Asha 1532 Riffaldi, Riccardo 1195 Stamatelatou, Katerina 127 Roots, Ott 1126 Stanisavljevic, Miodrag 3 Roots, Ott 1662 Stasinos, Konstantinos 1030 Rosa, Zenaida 861 Steimer, Michael 443 Rúriková, Darina 851 Stjepanović, Barbara 826 Stock, Hans-Dieter 1509 S Strong, James P. 162

Saad, Massoud A.H. 710 Sukatar, Atakan 428 Sabaz, Mehmet 193 Sukatar, Atakan 1667 Sabudak, Temine 1274 Sulhi Gundogdu, Kemal 940 Sacan, Ozlem 839 Sümeghy, Zoltán 660 Saeed, Asma 1600 Sumorok, Beata 109 Saf, Betül 1300 Sun, Hongwen 745 Sung, Menghau 617 Sağlam, Hasan B. 1643 Sagratini, Gianni 973 Sürücü, Abdülkadir 285

Sutcu, Hale 235 Uyar, Güray 145 Sutcu, Hale 1551 Uyar, Güray 182 Suzuki, Noboru 626 Uysal, Handan 991 Suzuki, Tohru 310 Uysal, Yağmur 38 Uzel, Atac 1523 T Tanaka, Keiichi 403 V Tanaka, Keiichi 1147 Vardar, Filiz 917

Tandlich, Roman 154 Varnavas, Soterios P. 133 Tandlich, Roman 162 Verep, Bülent 1005 Taner, Fadime 38 Viraraghavan, Thiruvenkatachari 320 Tanik, Aysegul 590 Viraraghavan, Thiruvenkatachari 415 Tarawneh, Khaled 489 Viraraghavan, Thiruvenkatachari 1532 Tarcan, Erdogan 1643 Vittori, Sauro 973 Tekin-Özan, Selda 904 Volpini, Rosaria 973 Teles, Mariana 495 Voulala, Maria 91 Terzi, Valeria 749 Voulala, Maria 770 Tezcan Un, Umran 1056 Voutsa, Dimitra 421 Theodoridou-Sotiriou, Lila 1619 Tilki, Fahrettin 1636 W Τiniakou, Αrgyro 1335 Wang, Guanghui 690 Titretir, Serap 216 Wang, Hongjun 1087 Tlustoš, Pavel 792 Wang, Hongwu 299 Tolan, Veysel 1319 Wang, Hongxun 632 Topaç, F. Olcay 532 Wang, Hongxun 1389 Topuz, Emine 1498 Wang, Hongxun 1563 Travizi, Ana 784 Wang, Hui 1578 Triantafyllou, Athanasios G. 508 Wang, Weidong 1087 Troyo-Diéguez, Enrique 517 Wang, Xue-Dong 379 Trushin, Maxim V. 1464 Wang, Yifei 24 Tsilingiridis, George 1108 Wang, Zheng 1152 Tsilingiridis, George 465 Weißsieker, Horst 1160 Tsoutsos, Theocharis 735 Weißsieker, Horst 1176 Tunali, Sevim 839 Wenzel, Sabine 1248 Tuney, Inci 428 Wood, Ab. Khalik. H. 1279 Tuney, Inci 1667 Wu, Chundu 242 Turan, Metin 1113 Wu, Feng 1043 Turan, Pınar 1377 Wu, Guiping 812 Turgut, Cafer 252 Wu, Hangjun 1389 Turgut, Günfer 1401 Wu, Wen-Xiu 29 Turgut, Sebahat 1401 Wu, Zhenbin 227 Turgut, Zuhal 821 Wu, Zhen-bin 654 Turhan, Kadir 397 Wu, Zhen-Bin 856 Turhan, Kadir 459 Wu, Zhen-bin 934 Turhan, Kadir 821 Wu, Zhen-bing 1468 Turhan, Yasemin 1377 Turkdogan Aydinol, F. Ilter 1593 X Xiao, Bo 1583 U Xiao, En-rong 654 Uçaner, Erkan 278 Xie, Ling-Ling 856 Uchida, Miho 928 Xie, Zheng-miao 1363 Uğurlu, Mehmet 887 Xing, Wei 82 Unal, Dilek 428 Xu, Hui 242 Unal, Dilek 1667 Xu, Jian-ming 1363 Ünal, Meral 917 Xu, Qing 71 Ünal, Mesude 1186 Xu, Qing-Shan 1023 Uslu, Ufuk 601 Xu, Qing-Shan 1082 Usta, Ayhan 1636 Xu, Youyi 812

Xue, Xingya 71 Zhang, Xiang-ling 1468 Zhang, Xiaohong 1082 Y Zhang, Xiaoyu 632 Yağiz, Dursun 1359 Zhang, Xiaoyu 1389 Yalcin, Mustafa G. 352 Zhang, Xiaoyu 1424 Yaman, Barbaros 193 Zhang, Xiaoyu 1563 Yamazaki, Eiji 310 Zhang, Xu 1043 Yan, Keliang 632 Zhang, Zheng 227 Yan, Keliang 1389 Zhang, Zhixiang 1207 Yan, Keliang 1563 Zhang, Zhongman 1424 Yan, Yongsheng 242 Zheng, Minghui 745 Yanardag, Refiye 839 Zheng, Xiong 1424 Yang, Cui-Yun 1435 Zhou, Pei-Jiang 856 Yang, Shao 379 Zhou, Xinping 1583 Yang, Xiaoyan 1583 Zhu, Chi 379 Yaşar, Mutlu 1300 Zhu, You-feng 1363 Yaslioglu, Erkan 940 Ziani, Fatima 1588 Yeşilırmak, Ercan 477 Ziogas, Vasilios N. 223 Yesilnacar, Irfan M. 206 Zitko, Vladimir 1126

Yetilmezsoy, Kaan 674 Zor, Sibel 1643 Yetilmezsoy, Kaan 804 Zoras, Stamatis 508 Yıldırım, İsmet 63 Zorn, Holger 1503 Yildirim, Vesile 555 Žuljević, Ante 1242 Yildirim, Yilmaz 182 Yıldız, Osman 57 Yılmaz, Gülden 817 Yilmaz, Huseyin 1517 Yilmaz, Ismet 596 Yilmaz, Murat 1636 Yin, Chengqing 1087 Yin, Yanli 1563 Yolasiğmaz, H. Ahmet 963 Yoshioka, Toshiaki 928 Yu, Changxing 1207 Yu, Rong 690 Yuan, Songhu 1345 Yu-dong, Song 393 Yue, Chun-Lei 1023 Yu-feng, Guo 393 Yüksel Tatar, Şule 34 Yüksel, Ebubekir 1201 Yu-ling, Che 393 Yumurtacı, Ayşen 917 Yuvali Celik, Gokcen 140

Z Zafar, Saeed I. 1600 Zahn, Rudolf K. 980 Zarkovic, Branka 295 Zdragas, Antonis 385 Zdragas, Antonis 875 Zhang, Ai-Qing 379 Zhang, Daobin 1216 Zhang, Feifang 71 Zhang, Hui 617 Zhang, Hui 1216 Zhang, Sheng 934 Zhang, Sheng 1468

1695